Data Mining

Data Mining

Quality in Manufacturing Data

Best Practices Approach To The Manufacturing Industry

Data Mining: Quality in Manufacturing Data was written by Ken Collier KPMG Consulting and Gerhard Held SAS Consultants Curt Marjaniemi Don Sautter KPMG Consulting and Mohan Namboodiri SAS Technical Reviewers Knowledge Management Solutions Group KPMG Consulting and Development Group Business Solutions Division, Knowledge SAS

October 2000

Table of Contents
List of Exhibits. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . ii 1. Manufacturing in a Rapidly Changing Market. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 2. The Role of Quality . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 3. Enterprise Quality and Data Mining . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 4. Case Study 1: Printing Process Out of Control . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6 5. Case Study 2: Failures in Hard Disk Drives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 6. Summary . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 7. References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 8. Companion Document. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 9. Recommended Reading . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Credits . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

Case Sampling i

List of Exhibits
Figure 1. Quality Data Warehouse . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 Figure 2. Three-level Quality Strategy. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Figure 3. P-chart for the Proportion of Banding . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Figure 4. Pareto Diagram of Press Type . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7 Figure 5. Data Mining Flow for Band Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 8 Figure 6. Data Replacement Node . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 9 Figure 7. Variable Selection Node . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Figure 8. Lift Chart for Banding Models . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10 Figure 9. Tree for Banding Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11 Figure 10. Data Mining Flow for Hard Drive Failure Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Figure 11. Lift Curves for the Best Neural Net, Decision Tree, and Regression Model . . . . . . . . . . . . . . . . 16

Table 1. Potential Causes for Bands in the Printing Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

October 2000

1. Manufacturing in a Rapidly Changing Market
The manufacturing industry has become more and more complex and has grown to include a variety of sub-sectors. Some of the sub-sectors in the manufacturing industry are the following: ??? ??? ??? ??? ??? ??? exploitation of mineral resources (coal, oil, gas) high technology equipment such as computers consumer-oriented mass production such as food processing highly specialized capital goods production such as turbines process-oriented production such as chemicals discrete consumables such as cars.

Although these sub-sectors are very diverse internally, they all have in common production, research, and development facilities, which often can be large. Most if not all of them also face very similar production issues such as new product development, quality management, capacity planning and tracking, preventive maintenance of production facilities, health, safety, and environmental protection, inventory optimization, and supply chain management. The marketplace for manufacturing companies has changed drastically over the past 10 to 15 years. Production has become more complex. Most companies face increased competition both at home and abroad. Mergers and acquisitions create a series of opportunities and threats through economies of scale, integration, and globalization of operations. For example, in the engineering industry, the value of all cross-border business leaped from US$43 billion in 1997 to $78 billion in 1998, while many companies merged: Daimler/Chrysler, Ford/Volvo (both automotive), Honeywell/Allied Signal (automation systems/power generation), Veba/Viag, and Alsthom/ABB (power generation) to name just a few.1 In addition, manufacturing efficiency, quality control, and faster time-to-market influence competitive advantage. Manufacturing industries have reacted with increased investment in information technology to streamline production processes and to assemble data about their customers. These investments include spending on company staff as well as software. In some companies, such as ABB (mechanical and electronic engineering) and Cummins Engine (diesel engines), up to one-third of their development engineers are software engineers. Enterprise resource planning (ERP) systems from companies such as SAP and Baan have been installed as a standard to run the everyday business; however, such systems provide little help in adjusting to changes in customer demand. Often going hand in hand with the drive for economies of scale is the move to restructure companies into smaller and more efficient sub-units with a large service component capable of reacting more quickly to ever-increasing customer expectations. Information delivery systems have been or are being introduced to track customer loyalty and market trends as early as possible.2 Meanwhile the e-commerce revolution has already reached manufacturing. For example, volume car manufacturers such as General Motors and Ford are planning to coordinate their relationships with suppliers through online systems.3 On the production side, processes have been automated to the finest detail, and production is surveyed by measurement systems that collect a huge amount of data. Usually these data are only collected to signal if something has gone out of control so that operators are informed immediately to stop production and identify the potential root cause of the failure.


Marsh 1999


SAS, Inform 23, 1998 Tait, Kehoe, and Burt 1999


Data Mining 1

October 2000

This best practices paper discusses quality-related aspects of the enterprise and explains some of the ways in which information technology can help solve quality problems in manufacturing data. These solutions are set in the context of developing quality efforts over time. The quality issue is discussed as one requiring management attention and an enterprisewide solution approach. This paper focuses on the contribution that modern analytical techniques such as data mining can make to this approach and is substantiated with two case studies, one of a comparatively simple printing process and another from a more complex hard disk drive production process.

2. The Role of Quality
The interest in quality as a business topic was inspired by the success of Japanese production techniques in the 1960s and 1970s and in later years in other East Asian countries. Notable contributors such as W. Edwards Deming, Kaoru Ishikawa, and Joe Juran helped along the Quality Movement.4 Inspection of crucial quality characteristics of manufactured goods became a widespread practice. Given mass production and the lack of automated measurement systems, inspections were initially done through acceptance sampling, that is, the inspection of a random sample from which conclusions were drawn about the underlying production lot or batch. With the introduction of automatic measuring devices, this early phase of quality measurement led to continuous quality control online (during the production process). Widespread use of statistical process control (SPC) systems became standard, and control charts could be found everywhere on factory floors. When errors in production exceeded control limits, the root causes of failures were identified. The next step was to identify factors for problems in production through experiments designed offline. Often, production had to be stopped to run these experiments, so great care was taken to minimize the number of experimental settings (or runs) to restrict the cost of out-time. The heavy emphasis on statistical quality control is often referred to as the first generation quality initiative. The first generation quality initiative is still in current practice but only as a baseline in the manufacturing industry. As Lori Silverman has noted, ???The basic tools of quality are no longer sufficient to achieve the performance levels that todays organizations are seeking to maintain market leadership and competitive advantage.???5 Measuring quality continuously is a requirement, but the drawback is that SPC/experimental design only concentrates on individual processes. In modern production settings, manufacturing consists of numerous interrelated steps. For example, semiconductor manufacturing involves treating wafers of silicon in more than 100 steps. Typically, 100,000 of these are produced per day, which means a gigantic amount of process data is produced by manufacturing execution systems. Other sources of data cover other aspects of quality. SPC systems calculate quality-related metadata6 such as statistics of subgroup samples or capability indices from process data. Laboratory information management systems (LIMS) include research and testing data, while ERP systems might add data about material resource planning or non-production-related data. Modern quality implementation is therefore no longer restricted to controlling individual processes but has moved into a second generation, which considers the quality management of the whole enterprise. In this second generation, quality has become a top management issue. From an IT perspective, the quality initiative is now required to build up quality data warehouses,7 which cover the whole production process including other quality-related data in an analysis-ready form. A quality data warehouse links supplier data, process data, data from other manufacturing plants, and human resource data to address questions such


Deming 1986


Silverman 1999


Metadata are descriptive data or other information about data entities, such as field names and types, and are typically stored in data dictionaries and data warehouses.


SAS, ???The Quality Data Warehouse,??? 1999

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as comparing quality across products, manufacturing lines, or plants, linking warranty problems to internal process data, or predicting product quality before the product reaches the customer (Figure 1).

Figure 1. Quality Data Warehouse

Quality solutions that take into consideration the entire enterprise need to enable decision makers at various levels of the organization to make effective decisions that impact the quality of a process or product. For example, the introduction of an enterprise quality system at Gerber Products, the baby food company, has enabled floor operators to know exactly when to adjust the process and, just as importantly, when to leave the process alone.8 At the same time, plant managers can track quality performance through a process flow reporting feature and identify immediately a root cause failure in the production upstream, while corporate management will receive standardized reports about key quality metrics on a regular basis.9


SAS, SAS Communications, 1999


SAS, SAS Communications, 1999

3. Enterprise Quality and Data Mining
Data warehouses populated with historical quality data serve to address questions of a more predictive nature, such as when a particular machine component is likely to break, and what combination of causes tend to lead to a malfunction in the production process. Questions of this nature require analytical modelling and/or data mining, which is a third generation of quality initiatives. Data mining is defined as the process of selecting, exploring, and modelling potentially large amounts of data to uncover previously unknown patterns for business advantage.10 In contrast, more traditional decision support techniques like online analytical processing (OLAP) usually provide descriptive answers to complex queries and assume some explicit knowledge about the factors causing the quality problem.


SAS, ???From Data Mining to Business Advantage: Data Mining, The SEMMA Methodology and SAS Software,??? 1998 Data Mining 3

October 2000

Analytical modelling can range from descriptive modelling using statistical analysis or OLAP to predictive modelling using advanced regression techniques and data mining methods. While data mining can generate high returns, it requires a substantial investment. Effective data mining requires well-defined objectives, high quality data in a form ready to be mined, and generally some amount of data pre-processing and manipulation. This technology is not a fully automated process. Data mining assumes a combination of knowledge about the business/production processes and the advanced analytical skills required to ask the right questions and interpret the validity of the answers. Typically data mining is done as a team effort to assemble the necessary skills. A feedback loop to deploy data mining results into the production system ensures that a return on investment can be realized together with some clues on how to repeat this exercise for the next problem to be addressed. Thus, a three-level quality strategy can be employed in which each level serves as a precursor to the next, and each new level generates increased knowledge about the production process and additional return of investment (Figure 2).

Figure 2. Three-Level Quality Strategy

Fortunately, manufacturing data lends itself well to advanced analytics and data mining. There is an abundance of data that are usually of high quality because their acquisition is automated. What is required is to establish a habit of storing historic data for mining analysis. In the first generation of quality management, the quality control approach, data are typically only used for online SPC and then discarded or else archived but never analyzed. In the second generation of quality management, the enterprise quality solution approach, data are also generated about research, suppliers, customers, and complaints. Such data are vital if the production data are to be enriched and exploited intelligently.

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Decision support or data mining has been used successfully to streamline processes in manufacturing. The following are a few examples: ??? Honda Motor Company in the United States is using Weibull analyses to predict at what age or mileage various components of cars are likely to fail. The resulting information allows engineers to plan maintenance schedules and design cars that will last longer. This careful analysis and the feedback of its findings into production have enabled Honda to achieve some of the highest resale values for cars in the United States.11 ??? A major South African power generating station experienced problems with tube failures in a re-heater. Tube failures are very costly; the material costs to replace the damaged tubes, the labor cost to perform the scope of work, the cost of lost production, and the external costs required to replace the lost production all add up. The company sought a method that would enable it to predict the potential tube failures to plan maintenance. Data mining and multidimensional visualization techniques showed that the problem was due to a high local wear rate of a certain tube. Further investigation revealed that the inlet header disturbed the airflow, which caused the high local wear rate. A different setting of the inlet header reduced the wear significantly. Increasing the tube life by just one year delivers an estimated return on investment of 480 percent, an estimate that considers only the tube itself. Taking into account the damage and costs incurred for the re-heater and the wider effects for the entire plant, the return on investment is considerably greater. ??? Data mining is used in semiconductor manufacturing to predict the likelihood that a microprocessor die will fail after packaging. It is often more cost-effective to discard defective die packages than to rework them. By pre-classifying each die with a probability of failure, the manufacturer can discard those with high probabilities very early in the assembly cycle. This analytics-based selection process eliminates unnecessary manufacturing costs and increases the percentage of good parts exiting the assembly/test process. ??? Computer hard disks are produced at mass quantities (100,000 parts per day) with a current failure rate of 1 percent. With a cost of $25 for each failure, even an improvement of 0.25 percent in the failure rate results in cost savings of $2,281,250 per year.12 Case Study 2 covers the details of this example. There are many more examples where data mining has proven to be extremely useful for process control applications, maintenance interval prediction, and production and research process optimization. These examples include reducing inventory by 50 percent without any loss in service levels, optimizing filling operations in the food industry, optimizing yield in car engine testing, predicting peak loads in telecommunication networks, forecasting utility demand (water, gas, electricity), reducing energy consumption at power stations, and identifying fault patterns in gas drilling. Data mining is also widely employed in sales and marketing operations, for example, to calculate the profitability of customers or to find out which customers are most likely to leave for the competition. Forrester Research reported in a recent study of Fortune 1000 companies comparing current (1999) and planned (2001) usage of data mining that while marketing, customer service, and sales will remain as the major business application areas for data mining, process improvement applications will experience the highest relative increase from 2 percent in 1999 to 22 percent of all data mining application areas in 2001 (multiple responses accepted).13


SAS, SAS Communications, 1999


Collier 1999


Forrester Research Inc. 1999 Data Mining 5

October 2000

4. Case Study 1: Printing Process Out of Control

Evans and Fisher 1994

This case study was one of the earliest published examples on the use of data mining techniques to address a process-related problem. Bob Evans and Doug Fisher14 discussed the problem of ???banding??? in rotogravure printing occurring at R.R. Donnelly, America??™s largest printer of catalogues, retail brochures, consumer and trade magazines, directories, and books. Rotogravure printing involves rotating a chrome-plated, engraved, copper cylinder in a bath of ink and pressing a continuous supply of paper against the inked image with a rubber roller. Sometimes a series of grooves ??“ called a band ??“ appears in the cylinder during printing and ruins the finished product. Once a band is discovered, the printing press needs to be shut down, and the band needs to be removed by polishing the copper cylinder and re-plating the chrome finish. This process causes considerable downtime, delaying time-critical printing processes, which wastes time, money, and resources. Banding became a considerable cost factor at R.R. Donnelly, and a task force was appointed to address the problem. In brainstorming sessions, the task force discussed a number of possible reasons for banding to avoid the problem in the first place, but the task force came up with a large list of factors, which could have potentially contributed to this problem. There were 37 factors being selected, some of which are listed in Table 1.

Table 1. Potential Causes for Bands in the Printing Process


These data are publicly available at machine-learning-databases/

The task force studied conditions under which bands occurred and the settings of the potential causes (inputs) at that time. For control purposes, a number of settings were also recorded when the printing process was in control (no bands). For organizational reasons, the task force was not in a position to assemble a lot of data, and data were recorded when it was convenient, not in a controlled environment setting. In total, the data consisted of 541 records with 255 in 1990, 223 in 1991, 37 in 1992, and 16 in 1993. Bands occurred in 227 cases (about 42 percent). There were no bands in 312 cases (57.7 percent), and there were missing values for band in two cases.15

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The task force tried to analyze the data through a series of graphs but failed. In this re-analysis of the data, a P-chart (proportion of defectives) was applied to the target variable BAND/NO BAND (Figure 3). The chart was restricted to data points from April 1990 to November 1991, and data were summarized by month to have an acceptable number of points per month to calculate the proportion of defectives.

Figure 3. P-chart for the Proportion of Banding

At first sight, the printing process seems to be in control. The chart shows the proportion of defectives to be in the admissible range (Figure 3, shown in blue). However, because the data were not generated in a controlled experiment, the mean proportion of bands is artificially high (mean proportion for banding .395), and the admissible range covers the whole data range from 0 to 1 or no band to 100 percent banding. Figure 4 also shows a slightly upward trend of bands occurring, so the printing problem gets worse over the time frame considered. One way to identify potential causes is with Pareto diagrams. Figure 4 shows a Pareto diagram of press types (four different types were used) against banding problems in percent. The first two printing machines with highest occurrence of banding already accounted for 80 percent of all banding problems, a clear indication that press type is an important influential factor for bands.

Figure 4. Pareto Diagram of Press Type Data Mining 7

October 2000

The value of Pareto charts is limited when numerous potential factors need to be considered. Moreover, Pareto charts are not suited to explore potential interactions between factors. In fact, the task force at R.R. Donnelly also did discover the impact of press type early on; however, although this factor was taken into account, the banding problem continued to exist at a lower rate. Clearly, control charts and Pareto diagrams (first generation of quality implementation) were not adequate to explain the banding problem fully. Evans and Fisher therefore decided to use specific data mining methods (a decision tree algorithm) available at that time. These data were re-analyzed using SAS??™ data mining solution Enterprise Miner.?„?16 Enterprise Miner implements data mining analysis as a process. Data mining tasks are represented as icons, which can be dragged and dropped onto a workspace, arranged as nodes in sequence, and connected to form process flow diagrams. Data mining tasks are grouped according to an underlying data mining methodology called SEMMA, which stands for Sample, Explore, Modify, Model, and Assess.17 Figure 5 shows a data mining flow using Enterprise Miner for the Donnelly banding data in the Diagram Workspace (the right side region of the graphical user interface). The Input node reads the data and automatically assembles a number of statistical metadata. These are descriptive statistics about each variable such as the role of the variable in the modelling process (input, target, identification, or a few other choices), and the variable??™s measurement level (nominal, binary, ordinal, or interval).


For more details about Enterprise Miner, see the ???Companion Document??? section.


SAS, ???From Data Mining to Business Advantage: Data Mining, The SEMMA Methodology and SAS Software,??? 1998

Figure 5. Data Mining Flow for Band Data

The Data Replacement node is one of the icons for data modification. As the name indicates, it allows replacing invalid data through user-selected values or the imputation of missing values using a wide range of imputation methods. Figure 6 displays an opened Data Replacement node with the Class Variables tab selected. As it appears, there were a number of inconsistencies (mainly between upper and lower case letters) in the original data, which blurred the analysis. A user-specified replacement value eliminates this problem with the data. Also there were a number of missing values in the original data (up to 12 percent for a given variable). A typical strategy would be either to disregard cases with missing values for analysis or replace missing values with a representative value, such as the mean or the mode (the most frequent value). Instead, a strategy to impute missing values through tree imputation was chosen. Tree imputation uses all available information except the one from the imputed variable (all
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October 2000

information from user-selected variables) from this specific record as input to calculate the value of the imputed variable with a tree algorithm. This approach ensures that a maximum of information is used for imputation and the imputation itself is done in a very flexible way.

Figure 6. Data Replacement Node

Partitioning of the data is the next task in the data mining flow. Partitioning provides mutually exclusive data for training, that is, calculating the model for explanation of bands and subsequent assessment (comparison) of the models. As a result, assessment of the models is done on data independent of those used for model generation. From data partitioning, the flow divides into a branch pointing to a Tree node and another branch that points into a Variable Selection node first and then into a Regression and a Neural Network model (see Figure 5). Variable selection is a very useful tool with a large number of model inputs. It assists analysts by dropping those variables that are unrelated to the target and retaining those that are useful for predicting the target (bands) based on a linear framework. The remaining significant variables are then passed to one of the modelling nodes such as the Regression or Neural Network nodes for more detailed evaluation. Figure 7 shows results from the Variable Selection node. A number of variables are rejected because of their low relationship with the target. In this process, the Variable Selection node always tries to reduce the number of levels of each class variable to groups to test if that strengthens relationships with the target. If that is the case, then the original variable is rejected, and the grouped variable is selected instead. Assuming for the moment that modelling has been completed, assessing all of the models would reveal which model explains banding most effectively. For example, double clicking on the Assessment node enables the analyst to select each of the three models and display a lift chart (Figure 8). For each model, records of the validation data are scored with the result (the formula) from the model, ordered from highest to lowest score, and then separated into deciles. In its first decile, the tree model classified 95.5 percent records correctly as bands. The baseline (Figure 8 in dark blue) shows the average of bands in the assessment data
Data Mining 9

October 2000

(about 36 percent). The larger the distance between a model and the baseline, the better the model explains the data. As is apparent from the lift chart, the tree model outperforms the regression and neural network models.

Figure 7. Variable Selection Node

10 Data Mining

Figure 8. Lift Chart for Banding Models

October 2000

Given its performance, it makes sense to take a closer look at the tree model results (Figure 9). A tree (also called a decision tree) is so called because the predictive model for banding can be represented in a tree-like structure. A decision tree is read from top down starting in the root node. Each internal node represents a split based on the values of one of the inputs with the goal of maximizing the relationship with the target. Consequently, nodes get purer (more or fewer bands depending on the split) the further down the tree. As is apparent, the percentage of solvent explains the most variation for bands. Whereas bands for the whole training data occur in 46.1 percent of cases, bands always result when the solvent percent is less than 31.35. Where the solvent percentage is equal to or greater than 31.35, press type is the next most important classifier. As noted earlier with the Pareto diagram (Figure 4), the press type Woodhoe 70 would generate the most bands, but the analysis has shown that this relationship would only be of interest for solvent values larger than 31.35 percent. The terminal levels of a tree are the ???leaves.??? For the branch Woodhoe 70, the humidity 31.35 and press type is Woodhoe 70 and humidity

Data Communications

Transmission medium – the physical path between transmitter and receiver in a data transmission system.

2 Categories
o Guided transmission media – are those media with some form of conductor that provides a conduit in which electromagnetic signals arte contained.
o Unguided transmission media – are wireless system. Unguided signals are emitted and then radiate through air or a vacuum.

Metallic Transmission Lines – a transmission line is a metallic conductor system use to transfer electrical energy from one point to another using electrical current flow.

Transverse Electromagnetic Waves
2 kinds of waves
o Longitudinal ??“ the displacement (amplitude) is in the direction of propagation.
E.g. surface waves, sound waves.
o Transverse ??“the direction or displacement is perpendicular to the direction of propagation.
E.g. Electromagnetic waves

Characteristics of Electromagnetic Waves
3 primary characteristics
o Wave velocity ??“ Waves travel at different speeds depending on the type of wave and the characteristics of the propagation medium.
o Frequency ??“ the oscillations of an electromagnetic wave are periodic and repetitive.
o Wavelength ??“ the distance of one cycle occurring in space.

Transmission Lines Classifications
2. classifications
o Balanced transmission lines – both conductors in a balanced line carry signal currents.
o Unbalanced transmission lines ??“ one wire is at ground potential, whereas the other wire is at signal potential.

Metallic Transmission Line Types
??? Parallel-conductor transmission lines ??“ comprised of two or more metallic conductors separated by a nonconductive insulating material called a dielectric.
o Open-wire transmission lines ??“these two-wire parallel conductors, closely spaced and separated by air..
o Twin-lead ??“ essentially the same as open-wire transmission line except that the spacers between the two conductors are replaced with a continuous solid dielectric ensuring the uniform spacing along the entire cable.
o Twisted-pair transmission lines ??“ is formed by twisting two insulated conductors around each other.
.2 Basics types specified by EIA/TIA 568 Commercial Building Telecommunications Cabling Standard
? Unshielded twisted-pair (UTP) ??“an UTP cable consists of two copper wires where each wire is separately encapsulated in PVC (polyvinyl chloride) insulation.
? Shielded twisted-pair (STP) – is a parallel two-wire transmission line consisting of two copper conductors separated by a solid dielectric material.
o Plenum cable ??“ metal rectangular-shaped air ducts were traditionally placed in the plenum to control airflow in the building.

??? Coaxial (concentric) transmission lines ??“ consists of center conductor surrounded by a dielectric material (insulation), then a concentric (uniform distance from the center) shielding, and finally a rubber environmental protection outer jacket.
2 types of coaxial cable connectors
? BNC connectors ??“ are sometimes referred to bayonet mount, as they can be easily twisted on or off.
? N-type connectors ??“ are threaded and must be screwed on and off.

Metallic Transmission Line Equivalent Circuit ??“ the characteristics of a transmission line are determined by its electrical properties like wire conductivity, insulator dielectric constant and its physical properties like wire diameter and conductor spacing.

??? Characteristics Impedance ??“ for maximum power transfer from the source to load, a transmission line must be terminated in a purely resistive load equal to the characteristic impedance of the transmission line.
Using Ohm??™s law, the characteristic impedance is simply the ratio of the source voltage to the line current (Io), given by
Zo = Eo / Io , where Zo is the characteristic impedance in ohms, Eo is source voltage in volts and Io is transmission line current in amps.

? Characteristic impedance of a two wire parallel transmission line with an air dielectric can be determined from its physical dimensions Zo = 276 log D/r where D is distance between the centers of the two conductors and R is the radius of the conductors.
? Characteristic impedance of a coaxial cable can also be determined from its physical dimensions: where, D is inside diameter

Of the conductor and is relative dielectric constant of the insulating material.

Wave Propagation on Metallic Transmission Line Types ??“ EM waves travel at speed of light through vacuum and nearly the same through air, but they travel considerably slowly in metallic transmission lines, where the conductor is generally copper and the dielectric materials vary with cable type.

? Velocity factor??“ the ratio of the actual velocity of propagation of an electromagnetic wave through a given medium to the velocity of propagation through a vacuum.
? Dielectric constant ??“ is simply the relative permittivity of a material.
? Coupling losses – it occurs whenever a connection is made to or from a transmission line or when two sections of transmission line are connected together.
? Corona ??“ a luminous discharge that occurs between the two conductors of a transmission line.

Data Collection Paper

Data Collection Paper
March 25, 2012

Team B intends to conduct research to evaluate a possible correlation between wage earner salaries and production levels. Team B??™s hypothesis indicates the higher an individual??™s salary, the higher level of production he or she will produce. For purposes of this research, Team B intends to gather information and knowledge through observation, data collection, and literature reviews. Theoretical framework, generalization of hypothesis, scientific research, analysis, and interpretation will be used throughout the project as well. The purpose of this research will enable researchers to substantiate the hypothesis and answer research questions. With completed research, managerial decisions can be made based on the findings pertaining to the research question.
The research problem or question identified for this project is ???does an employee??™s wage affect productivity??? This research question is important because employers can apply the research information to make managerial decisions for hiring, terminations, rates of pay, and a host of other job related functions.
Problem Definition
The question of ???does an employee??™s wage affect productivity??? is defined as the problem statement for this project. Variables such as gender, education, annual wage, and occupation may contribute to a substantiated hypothesis and provide an answer to the research question addressed within this paper.
The theoretical framework for the dependent and independent variables included in this paper is detailed in the diagram below.

The independent variable of the research being conducted in this project is wage earnings. The dependent variable in this research is productivity, which is the main subject of interest for this project. Other independent variables that may affect Team B??™s hypothesis are occupation, education, and gender.
The dependent variable (wage earnings) can be affected by the independent variable of productivity because the amount of education an employee has, the more effective he or she may be therefore increasing production. The independent variable of occupations may affect the dependent variable in this research because the occupation may be demanding. A less demanding job may require much less production effort than a demanding occupation.
The dependent variable of gender can affect the independent variable in this research because a male may do more work in a given occupation than a female, such as lifting heavy objects. The dependent variable of annual wage in dollars may affect the dependent variable in this research because an employee??™s wages, specifically if the wages are lower could affect the amount of productivity.
Research Hypothesis and Possible Outcomes
Team B??™s research hypothesis is that companies whose employee wage earnings are
higher will have higher productivity levels. Team B has devised three possible outcomes that will most likely result from the research project. One possible outcome is an employee who earns a higher wage will be more productive than an employee who earns a lower wage. This is a possibility because employees that make higher wages are typically happier and produce at higher levels. The second possible outcome of this research could be that employees who make lower wages will not feel motivated to work at high productivity levels. The third possible outcome is that workers making higher wages might feel as though they have achieved a level of satisfaction in life and therefore are not as motivated to be productive. High wages can make a worker feel like their goal was achieved resulting in less drive and production.
Operational Definitions
Numerous factors are used as variables within this research project. Below is a list of the variables used and their operational definitions:
Wage: Wage is defined as the amount of American Dollars earned annually by one employee. The operational definition is the amount of money an employee can earn based on education or occupation.
Occupation: Occupation is the type of work that an individual does. The operational definition is the amount of wages an employee receives depends on the type of occupation an employee is in.
Education: Education is the years of school that an individual has completed. The operational definition is an employee??™s annual wage in dollars greatly depends on the amount of education an employee has received in a given occupation.
Male/Female: Indicates the gender of the individual. The operational definition is a female annual wage in dollars is possibly less than that of a male in the same occupation. An employee??™s wage earnings and ability to work in certain occupations may be dependent upon the individual??™s gender.
Age: Age is defined as how old a person is in years. The Operational Definition is an employee??™s age affects the annual wage in dollars an employee can receive.
Identifying Variables
Level of Measurement, and Measurement Scale
The independent variable included in this research is wage earnings. The dependent variables in this research are occupation, gender, education, and annual wage in dollars. The level of measurement for the independent variable of wage earnings is 0-5. This is measured using a ratio scale. By using a ratio scale, the amount of wages an employee earns can easily be measured by administering surveys or collecting data that answer questions, such as do you make above or below $20,000 a year The measurement scale that will be used to measure the dependent variables, occupation, and education is the nominal scale. The level of measurement will be from 0-5 where employees in certain occupations and educational levels are grouped into categories using numbers. An example could be employees with no formal education would be grouped as a zero, and all employees with one year of formal education would be coded as a one and so on. The level of measurement for the dependent variable annual wage in dollars will be from 0-5 using the nominal scale where employees will be grouped according to their annual wage.
The remaining steps of the research process that will be followed are steps six through eleven. Step six of the research process will enable the research project to become more informative on the problem definition and allow the hypothesis to be substantiated. Step seven of the research process will help contribute important data, analysis, and interpretation of research issues. Steps eight through eleven of the research process will help contribute to the writing, report presentation, and managerial decision making with use of the research found regarding the projects problem definition.
Review of Literature
In addition to the data and documentation already discussed, Team B has also performed additional research for the purposes of their research project. Four peer-reviewed articles are included for the purpose of literature review. Below is a brief synopsis for each article as well as how each article applies to the current research project.
The Workforce Composition and Firm Productivity article (Workforce Composition and Firm Productivity: Evidence from Taiwan,? 2010) produces evidence under a limited study that smaller companies outperform larger companies. According to the study, the increase in performance is related to the middle-aged employees who have secondary education experience. These individuals are more productive than other employees who are under 30 or over 55. The study shows evidence that the middle-aged workers with secondary education experience receive higher wage compensation than other groups of workers. Other factors of significance of wage compensations are economic incentives and market competition. The article relates to the purpose of this research paper in the possible correlation of wage earner salaries and production levels.
The ???What Determines Productivity??? article (What Determines Productivity, 2011) discusses several factors of productivity within any given firm including macroeconomics, industrial organization, labor, and trade. The research delves deeply into the differences in productivity levels between businesses and production practices. It also compares the effects of outer influences, such as competition and technology and its effects on productivity. The article briefly touches on a few elements related to this research paper, specifically education level and gender as found on page 340. Although age was not mentioned as a factor, the article did make mention of experience and industry tenure that can be related to the age factor of the research project.
The article ???Why have the dynamics of labor productivity changed??? (Why Have the Dynamics of Labor Productivity Changed, 2010) states that the world of economic labor productivity has changed as a result of supplies, and a reduction in the demands of the working environments. These changes have developed stronger more affordable materials, and advancing technology reduces the need for laborers. The reduction of laborers has positively changed firms and large corporations but has a negative impact on individuals seeking work and his or her salary. Exporting has become overwhelmed with advanced productivity from competitive companies from an international point-of-view as well as domestically. As e-commerce advances, it demonstrates how predictable online selling and buying have become, thus reducing the number of workforce personnel needed. This strength is building tremendously for businesses reducing the need for paid laborers. This article provides an additional variable to Team B??™s research that was not previously considered.
The article ???Wage Productivity Linkages in Indian Industries??? (Wage-Productivity Linkages in Indian Industries, 2012) discusses the standardization of Indian industries. The article indicates that the cost of living in India is rising rapidly and that measures must be taken to reduce the problem. The research conducted for this article links wage earning to production. Researchers believe that a link between wages and productivity may help India slow the rising of cost of living for workers in rural, urban, and aggregate industries. The article suggests that increases in wages based on productivity instead of inflationary measures may help slow the issues of an increasing cost of living. Information contained within this piece of literature provides data sampling showing the correlation between wage and productivity.
Sampling Design
The population used for data collection purposes for this project came from 100 employees of various genders and occupations within the chosen organization. The sample size is appropriate for this research project because it encompasses all departments within the company, including management. It also encompasses varied amounts of the dependent variables being included within the research project. Therefore, enough data collection has been collected to provide the type of feedback needed to help form a hypothesis.
The reliability of the research should be precise to the type of measuring that will be conducted. However, because there is a category in occupation called ???other??? it may produce results that may not indicate which occupations have higher or lower productivity. Team B should consider another interview to try to place these employees into an occupation that is already in the population or create a new category that specifically describes their occupation. The ???other??? category also has the highest percent frequency so the outcome may be somewhat skewed.
Validity within the research should also be accurate and provide desired results. The only source of bias that can be foreseen is the possibly gender category. Some people may take the information found within this project the wrong way and assume the findings are indicating that men or women are more productive. This is not the case. The gender category is being used to help produce as many results as possible to get an accurate measure.
Data Collection
The data collected for this research project has been formatted into tabular and graphical formats for easy reference. Below are displays that compare data regarding occupation, gender, and annual wage.

Occupation | Frequency | Relative Frequency | Percent Frequency |
Management | 13 | 0.13 | 13% |
Construction | 6 | 0.06 | 6% |
Service | 21 | 0.21 | 21% |
Clerical | 21 | 0.21 | 21% |
Professional | 17 | 0.17 | 17% |
Other | 22 | 0.22 | 22% |
Total | 100 | 1.00 | 100% |




Male Or Female | Frequency | Relative Frequency | Percent Frequency |
Male | 53 | 0.53 | 53% |
Female | 47 | 0.47 | 47% |
Total | 100 | 1.00 | 100% |



Annual Wage in Dollars | Frequency | Relative Frequency | Percent Frequency |
10,000 – 30,000 | 59 | 0.59 | 59% |
30,000 – 50,000 | 28 | 0.28 | 28% |
50,000 – 70,000 | 6 | 0.06 | 6% |
70,000 – 90,000 | 4 | 0.04 | 4% |
90,000 – 110,000 | 3 | 0.03 | 3% |
Total | 100 | 1.00 | 100% |

Primary Data Collection Methods
Some primary data collection methods that will be used to collect important data include Internet, internal and external researchers, Directory of Corporations, The Business Periodicals Index and Trade Publications.

Ethical Concerns
There are many possible ethical concerns regarding wages and wage earners. When considering ethical concerns for this research, several issues come to the forefront. For example, some individuals may think that age and experience help one to develop ethical standards. Can it be said that a person of an older age and knowledge base should get increased wages versus a person who graduated from college with honors and references stating how valuable and resourceful they were Minimum wage is another topic that is considered an ethical concern. Some may think the minimum wage is a fair wage based on today??™s cost of living; however, others may disagree, and say it is not enough. Some country??™s allow sweatshops where children and adults work for wages well below the minimum wage. They can do this because they are living in a country that is poverty stricken and people will work for anything to survive, is this ethical in regard to wages and wage earners, most would think not.
Team B is nearing the end of their research project regarding wage and productivity. In the near future additional information will be included in their findings. The team intends to provide additional data analysis using descriptive statistics. Central tendency, dispersion, and skew for the data collected will be evaluated and graphics provided to assist the team in evaluating their hypothesis.

Liu, J., Tsou, M., & Wang, P. (2010). Workforce Composition and Firm Productivity: Evidence from Taiwan. Economic Inquiry, 48(4), 1032-1047. Retrieved from EBSCO HOST
Manonmani, M. M. (2012). Wage- Productivity Linkages in Indian Industries. Indian Journal Of Industrial Relations, 47(3), 450-458.
Syverson, C. (2011). What Determines Productivity. Journal Of Economic Literature, 49(2), 326-365.
Uma Sekaran. (2003). Introduction to Research. Retrieved from Uma Sekaran, RES 341 website
Van Zandweghe, W. (2010). Why Have the Dynamics of Labor Productivity Changed. Federal Reserve Bank Of Kansas City Economic Review, 95(3), 5-30.

Data Analysis


Second and Foreign Language Data
Whenever a language is learnt, the main objective is to communicate; nevertheless, the enquiry for some researchers is how do we actually do it, and as a result of this, researches are done in order to answer whether the utterances are being produced in a proper manner, or if not to see what kind of problem can be found in between.
On the one hand, several steps are needed in order to do a research, implying hours of work for eliciting samples, which make the data collection one of the most important steps, since with it, researches are able to prove what they are looking for. On the other hand, the data collection may have a higher number of variables that can lead the study to different mistakes or even worse, to a complete failure because of the amount of data collected.
Let us not forget that the first thing researchers have to do to both making a research and collecting the data, is to investigate about the issue they want to study by reading the literature related to the it, analyzing some data, as well as previous studies concerning their topic in order to have different ideas and even more, to come up with an hypothesis, which can vary according to the findings in the data, to support their research.
Moreover, when making a second language acquisition research, the main actors in the study are people, so their learning process is different, since diversity is involved. This means different minds, experiences and even the environment play a fundamental role when it comes to communication: therefore, not only a linguistic factor is involved, but also a psychological one.
One of the examples from the text that draw my attention was the use of plurals that made me think the following: If the collection of data for plurals taken from the text would have been done to two or three groups from different cultures, probably the results had not been the same, so how was the research truly done Was one of these factors left aside
In addition, there is another problem in data analysis which deals with unique creations (interlanguages) from the learners; the learner cannot be placed into one developmental category, because their utterances may vary and it is likely to take a standardized test into account; however, these kind of data I think may be tricky, because learners answer randomly and with this, the data collected might be unreal; Unless, the test has open answers, in that case they can be placed into one category easily, since what is really working is the messages the brain sends in order to be written and moreover, interlanguage can be seen.
Finally, it does not matter what kind of study researches have in mind concerning SLA, but the crucial goal of our study which is to discover the system underlying a second language, for turning into better researches and what is more, into better teachers as well.
Alejandra Garrido.


Data Analysis

What is Business Research

???Research??™ has been defined in a number of ways, depending upon peculiar interests and demands of the researcher, his professional training and skills and, of course, the nature of the problem being examined or analysed. In this sense, there is no one standard definition of research (same is true of the dictionaries defining research). Similarly, there is no one way of doing research. Research can be done in numerous ways, from chronological to descriptive to analytical, from qualitative to quantitative, from explanatory to predictive, from exploratory to evaluative (cost – benefit analysis) to instrumental and action-oriented, to theoretical to applied research. There is a whole variety of research possible.

In a similar vein, the term ???methodology??™ has been defined in various ways, indeed ???normatively??™ and ???structurally??™. Normatively, it has been defined in the sense of theory of knowledge (epistemology) or philosophy of science. The dominant theory, of course, is ???logical positivism??™, a philosophical tradition that holds that all ???facts??™ are derived from ???experience??™, defined minimally in terms of senses, and that all knowledge is based on experience. Judgments of ???values??™ cannot be accepted as knowledge.

The main argument of the empiricists as a whole remained, as always, their emphasis on experience, empirical experience. That is, an experience brought forth by facts which could be ???observed??™ and ???verified??™. In operational terms today, it means identification of the problem (research problem), formulation of hypotheses (the relation of ???independent??™ variables to one or more ???dependent??™ variable/s), collection and analysis of data to test the variables in a measurable relation, rejection or validation of hypotheses suggesting a relationship (ideally ???causal??™, that is, ???cause and effect relationship??™), and generalization of the findings or conclusions into a ???theory??™, ???model??™, ???system??™, or an ???approach??™. This process of inquiry that tests against reality in a disciplined manner, with each step in the process quite explicit and integral, is described as the ???scientific??™ method, or, more specifically, the ???empirical method??™ (after the empiricists).


Data are facts, figures, enumerations and other materials, past and present, serving as basis for study and analysis; they are raw material for analysis; provide basis for testing hypothesis, developing scales and tables

Data help researchers draw inferences on specific issues/ problems

Quality of Findings depend on relevance, adequacy and reliability of data

Types of Data (not in Statistical sense)

1. Personal data (individual as a source)

? Demographic and Socio-economic characteristics
? Behaviour variables
? Attitude, behaviour, opinions
? Awareness, preferences, knowledge
? Practices, intensions

2. Organizational data (organizational sources)
? Archives
? Manuscript library
? Museums
? 3 Territorial data
? Economic structure, occupation pattern


Secondary data

? How to Scrutinize
? Published & unpublished
? Methods where used
A. Meta analysis
B. Historical method
C. Content analysis
D. Informetrics
E. Use studies

Primary Data

A. Records and relics
B. Observation
C. Experimentation
D. Simulation
E. Ask people orally
F. Ask people in writing
G. Panel study
H. Projective techniques
I. Sociometry
J. Case study
??? Interview / Depth interview / schedule
??? Mail Survey / questionnaire
??? Mechanical devices

How to collect data

I. Use existing data
Already collected by someone else for different / general purpose (paper method) i.e,

Secondary data

? Published or unpublished
? Retrospective panel study
? Letters
? Unpublished biographic / autobiographics
? Library statistics
? Raw data like invoices / log data for expenditure & use of data bases
? Published directories for (i) study funding for research activities (ii) statistics about publishing industry
? Published reports of UN, world bank, IMF, WHO, ILO etc.

Use Secondary data
? As supplementary data
? For reference purpose
? As bench marks (for comparison)
? Rarely as sole / main source


? Quick
? Cheap
? Wide coverage (space and time)
? Broad database leading to generalizations
? Cross check Primary data


? Suitability
? Up-to ??“ dateness
? Accuracy
? Availability and accessibility

Scrutinize Secondary data for

1. Reliability
? Who collected (possible bias)
? From what sources
? Which methods
? What time
? What accuracy

2. Suitability
? Definition of terms
? Units of measurements
? Objective, scope and nature of survey
3. Adequacy
? Level of accuracy
? Narrower or wider than present study
? Completeness in terms of methodology and sampling design

Types of Secondary data

1. published (literature0
2. Unpublished

– Diaries
– Letters
– Unpublished biographic

A Meta analysis

– Analysis of several analyses

– A way of extracting meaningful (statistical) information / data from lots of small studies (trials).

B. Historical Method
– Systematic and objective location, evaluation and synthesis of evidence order to establish facts and draw conclusions about past events
– Deals with the evidence of man??™s past acts and thoughts
– Attempts to test the truthfulness of the report of observations made


1. Remains or relics
– Skeletons, fossils, weapons, tools, utensils, buildings, pictures, furniture, coins, etc.

2. Items that have direct physical relationship with the event being reconstructed, i.e. written and oral testimony
– annuals, archive catalog, chronicle
– deeds, legend, manuscript, memoir, register etc
– museums

C. Content analysis ( a quantitative method)
– Both for collection and analysis of data
– Developed in USA for communication research
– Useful for historical research


??? A quantitative analysis of contents of written documents, i.e a multipurpose research method meant specially for investigating a broad spectrum of problems in which the contents of communication serve as a basis of inference

??? Transforms verbal, non quantitative document into quantitative data

??? Systematic and quantitative description of manifest contents of communication


??? Basic design of logical proof to test hypothesis with three basic principles:-

– Replication ??“Repeated Several times

– Randomization ??“ protects extraneous factors of chance

– Local Control ??“ Deliberate wide variability to measure and eliminate error

??? Helps finding causal relationship between variables

??? Employs a set of control and experimental groups

??? Administration treatment / stimuli
??? Controlled observation of change / deviation in variables (Adequate control is the essence => reduce bias increases reliability


??? Lab experiments
??? Field experiments ??“ A real life situation

Simulate the condition

Simulation (& observe)

??? Cheaper and suited to systems with interrelated and interdependent components


??? Man simulation (role / game playing)
??? Computer simulation
??? Man-computer simulation
??? Used in war strategies, behavioral, political economics and business problems


??? Earliest use involved work counts and usage rates of words (i) throw light on authenticity of a source document (ii) drawing inference about inner emotional states (e.g. anxiety)

??? Personality traits from logical and cognitive characteristics of verbal communication

??? Aspects of culture and cultural change probe hypothesis pertaining to the contents of material e.g themes of most contemporary best ??“selling novels are based primarily upon sex or violence???

??? Identify activities characterized as sex or violence

??? Quantitatively analyses the themes (content)

??? Test the hypothesis

??? Hypothesis testing is facilitated when a comparison is sought in
a study between or among elements of various documents role of mass media in moulding public opinion

??? Stand of newspapers on current issues

??? Philosophy of saints, leaders, authors etc

??? Themes and values of novels and short stories

??? Socio-cultural life in ancient times

??? Measuring behaviour variables like need, values, attitudes, authoritarianism, creativity, etc through analysis of both available materials and deliberately created materials of protective type

??? Propaganda technique (marketing)

??? Literary style, concepts or beliefs of writers

Darwin vs Creationism

Darwin reads the Bible
Darwinism has been butting heads with creationism for decades. Darwinism is a theory on the way the world would began through mass evolution, whereas creationism argues that some form of God or deity created the universe as though just waving a magical wand. The main difference between the two arguments is where each gathers their evidence. Darwinism is based on logical theories and hard science while creationism bases its logic on faith and beliefs of the unknown. Creationism is an invalid argument that should not stand in the way of evolutionism.
Darwinism follows scientific principles through logical theories. Charles Darwin (left) creditor of Darwinism; explains how a gross amount of time and a process called natural selection is responsible for modern day evolution. In the beginning of the world two atoms would collide creating the universe as it is today through millions of years of experimentation and species growth, coupled with the concept of natural selection a selection that chooses a random species and instills a new trait into that particular species genetics. For example, an animal growing wings would pass that trait to the next offspring while the others in the pack that did not grow wings would eventually die (allaboutscience). The strong survive because they can adopt. Another example of natural selection is monkeys, which are the most similar mammal to humans, evolving into the human species. The concept is natural selection but the process is survival of the fittest; the strongest have progressed through
millennia and have brought us to today where humans are the rulers of the world and control virtually every aspect of life. This will continue until Mother Nature randomly selects a new species to rival humans and best human kind and thus the circle of life continues. Right shows Charles Darwin depicted as a monkey reflected by ideas about monkeys and evolution.
Creationism is based on practices in theology. Theology is the study of God and branches into ties of creationism (Shol). Creationists believe that a God created the almighty universe within a moment. There is not really any further explanation as to when or where this God came from other than existing in a reality outside our own reality. Left depicts man and God. But people who follow creationism are firm in their own believe of a supernatural creator that created the alpha and can cause the omega. In contrast to natural selection creationists do not believe in a randomly created world where humans consequently ended up as the superior race; instead they have faith in an unseen orchestrated path for all of humankind. God has created every detail from the smallest cell to the grand Milky Way; he has illustrated all life and has a purpose for everything in his sandbox (God and science) One basis for believers of creationism might be from neglect of any purpose in life driving oneself to seek a reason for living and in return settling for a God and a form of higher reason through that God??™s gift of life. In this sense Creationism differs from Charles Darwin??™s theory of Darwinism adding the element of purpose in our life??™s instead of pure random coincidence.
Why is the debate so monumental and what should we believe Questions focused on the origin of the first atoms or origins of God blur the lines in the debate.

The whole debate could even crumble to nothing from these fundamental philosophical questions. The real reason why the debate is so constantly fought over is because it essentially touches everyone on the planet. People stand on either sides of the fence living their lives for a God, a divine higher purpose or living their lives completely free of an overseeing conscious. People live on a hope that their actions affect the overall scheme of life. However to keep consistency throughout the world the more logical ???creation story??? should be implemented.
Disregarding the origin of God and atoms how can faith in a supernatural power beyond our reality stand in argument against random creation through natural selection in our physical world The reality behind this situation is that Darwinism deals with physical truth and science while creationism positions itself outside this truth into a senseless guess. Believing in an unknown only prolongs evolution. If people believe that there is some form of higher power than they are only living a life in the shadows. Truth should be known so generations that follow us do not waste their time preaching and debating over a theory that can never be proven. People want something to believe in. That is why religion is not going anywhere.
Creationism cannot be taken seriously and implementation in the world is just throwing fire on this endless debate. By removing this theory people can start to live with their eyes open to life instead of consciously tied to a whim of a higher power. Darwinism shows us how natural selection has crafted the world we live in today, it shows us how life with a mass amount of time can create extraordinary beings created through continuous evolution and explains how life is randomly planned through the principle of survival of the fittest. Contrasting
Darwinism is Creationism the perspective of a God creating the universe, governing all living things at any given moment and existing in a realm of life beyond our physical reality (God and science). Our life is not monitored by an unseen eye but instead by a steadfast of random, constantly changing factors of natural selection. Life is not about any higher purpose; life is driven by our own reasons to live. Life is meant to be truthful and allowing creationism into anyway of life is restricting not only to our generation but to our species overall. Creationism is invalid and should be removed from Darwinism??™s path.

Darwin – Greatest Idea

Is Darwin??™s Idea of Natural Selection the Greatest Idea Ever

In Daniel Dennet??™s book Darwin??™s Dangerous Idea: Evolution and Meanings of Life, Dennet argues that the Darwinian processes are the single best idea ever had. While this statement is undoubtedly controversial, much truth surrounds it. Many may argue for the ideas brought to life by Isaac Newton and Albert Einstein. However, none of these two geniuses??™ concepts have proven to be so straightforward yet profound. Charles Darwin??™s ideas of natural selection are the greatest concept because these ideas have brought together so much complexity into stunning simplicity. Darwin??™s theories have unified social science and natural science by showing how purpose and design can rise from purposelessness.
In order to fully appreciate the Darwinian processes, one must fully understand the theory of natural selection. The idea of natural selection is often misconceived as a process in which an organism changes its physical characteristics in response to its surroundings. However this is not entirely true. In order to make this idea clearer, I will first use the example of bacteria, one of the smallest living organisms on the planet with an extremely exciting and quick (compared to greater organisms) evolution.
The bacterium Staphylococcus aureus lives on the skin of all of us. It is relatively harmless and even helps to prevent harmful bacteria from hurting us. Several years ago, though, a mutation in the normal S. aureus genome in just one bacterium occurred in which it made it no longer susceptible to the antibiotic Methicillin that is supposed to destroy it. Because this one bacterium with the mutation was not killed and was allowed to grow and divide and others around it were killed (because they did not have the mutation), this organism with the mutation became dominant and could now spread to other areas and other people. This organism is now known as Methicillin Resistant Staphylococcus aureus, or MRSA. One important thing to note is that the mutation did not occur because it had to happen. It occurred spontaneously and was only allowed to become dominant because it was able to survive and pass on this mutation, while others without the mutation were killed by the antibiotic. This is natural selection.
Now let us apply this idea to greater living organisms, such as animals. Each one has a very different DNA composition that makes it different from the next. And they are that way because their parents and their parents (and so on) all had very different DNA compositions from everyone else that combined and made an entirely new set of genes. These dissimilarities allow different animals to be more adapt to surviving in their environment than others. For example polar bears are distinguished from other bears because they have white fur. Thousands of years ago, bears living in the Arctic did not have entirely white fur. Suppose some had brown fur and others had white fur. The white fur would conceal the bear from its prey in the snowy Arctic, while the brown fur would not. Those bears with white fur then would be more likely to survive to reproductive age and be able to produce more offspring than those with brown fur. Therefore eventually white fur will become dominant.
So what Is this really such a great idea that it can be called the best idea anyone ever had The suggestion seems so simple yet not one of the many geniuses before Darwin was able to outline it. It must be noted that before Darwin, most people believed that every living organism was made by God with purpose and design. For Darwin to set this central idea to the side and think differently about the evolution of life without prior knowledge of genetics was an accomplishment in itself. Even today this idea would be a triumph. For many people still do not believe in the idea of natural selection and still hold true to the belief that God created all creatures with rationale and intention.
Most importantly, however, Darwin??™s processes of natural selection explain the reason why every living organism is the way that it is. Natural selection can account for animals??™ fur color and texture, humans??™ skin color, songs of birds, necks of giraffes, the rise of resistance in infectious diseases, and so much more. Natural selection may even be able to elucidate the history of a particular organism based on its genotypic and phenotypic characteristics.
Darwin??™s ideas of natural selection are the greatest idea anyone ever had. His ideas have brought together many different complex aspects of science into one simple scheme. In short, the Darwinian processes explain the reason why every living creature is the way that it is, and no other idea can claim that.


Geografski odsjek PMF-a

Seminarski rad iz turisticke geografije

Razvoj turizma u gradu Daruvaru

Turisticko geografski polozaj grada Daruvara

Prema regionalizaciji Republike Hrvatske, Daruvar pripada sredisnjoj makroregiji. Daruvar se nalazi u njenom istocnom dijelu Lonjsko??“ilovskoj zavali. Kako uzi prostor Daruvara ne predstavlja posebnu prirodnu regiju, nema ni svog uzeg regionalnog imena. Granice tog prostora prolaze; na sjeveru naistocnijim obroncima Bilogore, na istoku zapadnim obroncima Papuka i Psunja na zapadu rijekom Ilovom i na jugu potokom Bijela.
Daruvar se nalazi na 45? 35??™ sjeverne geografske sirine i 17? 20??™ istocne geografske duzine na jugozapadnom dijelu prostrane panonske nizine, dok njegova nadmorska visina iznosi 155 -171 m. lezi u kotlinskom prosirenju rijeke Toplice, pritoka lijevog pritoka Ilove, na prijelazu planinskog prostora Papuka i valovitog poilovlja.
Najjacu koncentraciju funkcija od vecih naselja regije ima Bjelovar, a Daruvar kao drugi grad zupanije ima direktnu utjecajnu zonu na svoj blizi prostor te je jedan od subreginalnih centara.
Daruvar se prostire na povrsini 64 km? i danas broji 9811 st. a s okolnim naseljima 13243. to su Daruvarski vinogradi, Doljani, Donji Daruvar, Gornji Majur, Ljudevit selo, Markovac i Vrbovac. Postanak naselja uvijetovali su termalni izvori uz rijeku Toplicu i padine gorskog masiva Papuk.
Urbana povijest Daruvara je duga i uskoro ce biti dvije tisuce godina od osnutka prvog lokaliteta poznatog kao organizirana urbana cijelina. Najstarije poznato naselje, smjesteno pored ljekovitih geotermalnih izvora na prostoru daruvarske kotline datira iz 4 st. prije Krista. Arheologija na ovom podrucju svojim nalazima (kamene sjekire) govori da je kraj bio naseljen i ranije, u kameno doba. Prvi poznati stanovnici daruvarskog podrucja bili su Jasi (Iassioi ili Iassi) sto znaci ??? toplicani ??? ili ??? Iscijelitelji ???, mjesavina ilirskih i keltskih plemena.
Dolaskom Rimljana nastaje rimsko naselje ??“ Res publica Iasorum i postaje ne samo znacajni administrativno, politicki, kulturni i zdravstveni centar vec je imao i znacajnu stratesku ulogu na prometnom pravcu Siscia ??“ Mursa. Arheoloski izvori potvrduju da je anticki grad Aquae Balissae (???vrlo jaka vrela???) u vrijeme rimske vlasti imao status municipija, samouprave zajednice Iassa. Nalazi ukazuju da je u Aquae Balissae postojao forum ukrasen carskim konjanickim broncanim kipovima u statuama, Jupiterov hram, termalni kompleks sa Silvanovim hramom i amfiteatrom. Najpoznatiji arheoloski nalaz iz Daruvara je carski mrezasti diatretni pehar za vino koji je danas izlozen u Kunsthistorisches Museum u Becu. Ovo rimsko naselje stradalo je vec u prvoj fazi seobe naroda kada su daruvarskim podrucjem prosli mnogi narodi koji su iza sebe ostavili pustos i za vise stoljeca zaustavili daljnji kulturni razvoj. Propascu Rimskog Carstva pocinje citav niz migracijskih procesa koji daju snazan pecat socio ??“ ekonomskim odnosima u daruvarskom kraju.
Slaveni, zajedno s Avarima stizu u ove krajeve na prijelazu iz 6. u 7. stoljece. Slaveni stvaraju svoju zajednicu ??“ knezevinu Panonsku Hrvatsku. Od 11. st. ovo je podrucje pripadalo srednjovjekovnoj Zagrebackoj biskupiji i Krizevackoj zupaniji. U Daruvarskoj kotlini, na brezuljku Stari Slavik iznad geotermalnih izvora plemici Nelipici od Dobre Kuce podizu svoju utvrdu Kamengrad (Kuwar). Do 12 st. prostor istocnog Poilovlja cinio je zupu Svetacje. U 12 st. to se podrucje raspalo na tri manje zupe: Topolicu, Pakrac, i Svetacje, koja podjela traje sve do 15 otkada su uvedeni kotari , te ove zupe postaju kotari. U ovoj podjeli prostor danasnjeg Daruvara pripadao je zupi Toplica, odnosno kotaru Toplica do 15 st.
Nakon poraza hrvatsko ??“ ugarske vojske na Mohac polju 1526. godine, daruvarskom kraju pocinju se priblizavati Turci. Pred Turcima se narod seli u sigurnije krajeve a kraj izmedu Ilove i Papuka ostao je napusten. Turci su ovim prostorom vladali od 1543. ??“ 1687. godine i oslobodenu tijekom tog vremana unistena sva kulturna i materijalna dobra iz prethodnih stoljeca. Odrzao se jedino naziv Podborje koje je bilo sjediste istoimene nahije ( opcine ). Turci su koristili termalne izvore i nazivali ih Ilidza. Nakon odlaska Turaka 1687. godine devastirano podborsko podrucje uslo je u novo razdoblje koje je trajalo do kraja 19 st. u kojem su ova podrucja dobila svoje nove stanovnike. U to vrijeme vojne vlasti, preko svojih oficira Ceha, dovode ceske obitelji na zemlju oslobodenu od poreza. Kao sumski radnici dolaze i njemacki doseljenici. Zemljiste na kojem je danas Daruvar kupio je od Marije Terezije plemic Antun Jankovic koji od 1771 do 1777. po nacrtima beckih arhitekata gradi u Daruvaru barokni dvorac, a koji sa svojim parkom postaje centralni motiv jezgre danasnjeg grada. Izgradnjom prvih gradskih kupki 1772. Godine Antun Jankovic je zacrtao jednu od osnovnih funkcija grada Daruvara, a to je termalno lijeciliste. Na termalnim izvorima uz stocarstvo stanovnici ovih prostora poceli su uzgajati pcele, saditi duhan i gajiti dudov svilac. Zbog toga je Antun Jankovic dobio pohvalu Marije Terezije, a 1765.godine dobio potvrdu nasljednog plemstva i pridjevak ???de Daruvar??? (daruvarski), zbog zdrala u svom grbu, po cemu se Podborje i postupno pocelo nazivati Daruvar (daru ??“ zdral, var ??“ grad).
Daruvar je krajem 19 st bio vec poznato ljecilisno srediste u kojeg su dolazili ne samo seljaci iz okolnih sela veci mnogi potencijalni bolesnici ali i turisti.
Grof Julije Jankovic prodao je vlastelinstvo Daruvar grofici Magdaleni Lechner i kupalisno lijeciliste mijenja vlasnika.U to vrijeme grofica Lechner obnavlja stare i gradi nove kupalisne zgrade, daje izvrsiti kemijsku analizu vode i mineralnog blata, te uz medicinsko osoblje organizirano vodi koristenje tople vode i blata u svrhu lijecenja na tada suvremeni nacin. To vrijeme se moze oznaciti kao pocetak zdravstvenog turizma ovoga kraja.

Swot analiza

Povoljan geografski polozaj , dobre prometnice sa zapada iz Ilovske zavale, kao i sa sjevera omogucile su sirenje grada u dolini rijeke Toplice i uz termalne izvore, a time je naselje postalo gravitacijsko srediste manjih naselja iz okolice, a izgradnjom cestovnih i zeljeznickih komunikacija i prostor za razvoj turizma, industrije, trgovine i obrta.
Osobitost polozaja Daruvara u makroprostoru je u gotovo podjednakoj udaljenosti od Save i Drave (50 km),odnosno od Zagreba ( 130 km) i Osijeka (140 km) cime je Daruvar u sredistu medurjecja Save i Drave. Grad se nalazi na prostoru najpovoljnijeg prijelaza iz Podravine u Posavinu, odnosno sredisnjih dijelova Panonske nizine preko sredista Dinarskih planina na Srednji Jadran, pa je time na transverzalnoj cestovnoj prometnici izmedu Save i Drave. Laka pristupacnost sa zapada iz podrucja Ilove veze Daruvar cestom s Bjelovarom (53 km), Garesnicom (30km), Kutinom (50km) i Pakracom (21km). Suvremene ceste i most na Dravi kod Barcza potencirali su ulogu medunarodnog turistickog tranzitnog mjesta u smjeru Srednjeg Jadrana, posebno iz Madarske, Ceske i Slovacke.

Od turistickih i zdravstvenih ustanova ???Daruvarske toplice??? drze primat u ovom kraju, a tradicija je jos od rimskog doba ??“ ljeciliste Aquae Balissae, speijalizirane za medicinsku rehabilitaciju i nositelji razvoja zdravstvenog turizma i ugostiteljske ponude. Osnovni prirodno ljekoviti faktori su termalna voda i mineralno blato (peloid). Danas ljeciliste raspolaze sa 294 postelje u ljecilisnom hotelu ???Termal??? B kategorije i 23 postelje u novo adaptiranoj depadansi ???Arcadia??? ( simbol kupalista i grada) u sklopu koje se nalazi i restoran ???Terasa??? (ocijenjen i uvrsten medu 100 najboljih restorana u Hrvatskoj), smjesteno u sjeveroistocnom dijelu grada u visestoljetnom parku prepunom egzoticnih vrsta drveca (uglavnom mediteranske), a smjestajne kapacitete popunjava i hotel ???Balise??? s 39 postelja u samom centru grada. U parku se nalazi i Centralno blatno kupaliste izgradeno 1909. godine u maurskom stilu. Od kulturnih i povijesnih atrakcija tu su jos i barokni dvorac grofa Jankovica smjesten u parku u kojem se nalazi stoljetno drvece (Gynko Biloba). Od povijesnih gradevina u samom centru se takoder nalazi Crkva Presvetog Trojstva izgradena 1764.g., dok 6 km sjeverozapadno od Daruvara nalazi se Dvorac Dios (poseban je po neuobicajenim arhitektonskim rjesenjima i zasticen je spomenik kulture, izgraden 1904. g.) koji nije otvoren za javnost nego sluzi salezijancima za obavljanje bogosluzja, ali je omiljeno izletiste i zanimljiva tocka na biciklistickoj stazi .
U gradu se nalazi i sportski ribnjak ???Jezero??? u kojem se odrzavaju brojna sportska natjecanja u ribolovu i pripremanju fisa. Osim ribolova tu je i lovni turizam koji postaje zaseban sastavni dio turisticke ponude ovoga kraja, a u tom smislu Daruvarske toplice su u svom programu za prezentiranje lovnog sadrzaja opremile, osim pratecih zahtjeva lovaca, prihvatiliste za lovacke pse i hladnjace za prihvat i cuvanje odstrela divljaci. U okviru razvijanja lovne tendencije toplice vrlo blisko suraduju sa lovackim drustvima u svrhu osmisljavanja kompletnih lovnih programa.
Jedna od najzapazenijih turistickih kota je Petrov vrh udaljen 9 km od sredista grada. Ovdje se nalazi planinarski dom ???Petrov vrh??? u vlasnistvu Planinarskog saveza, visoko kategoriziran jer nudi ugostiteljske usluge i pruza mogucnost smjestaja za 40 osoba u jednokrevetnim i dvokrevetnim sobama. Uz planinarski dom tu se nalazi i skijaska staza sa vucnicom i instaliranim osvjetljenjem za nocno skijanje. U sklopu doma djeluje skijaska skola koja za zimskih mjeseci privlaci mnogobrojne obitelji na zimski odmor. Od planinarskog doma moguci su izleti prema Dulovcu i razvalinama Stupcanice na 380m nadmorske visine ( tri i pol sata hoda ), Crnom vrhu na 863 m nadmorske visine ( cetiri sata ), Zvecevu na 450 m nadmorske visine (osam sati hoda).
Cesta do planinarskog doma prolazi kroz Daruvarsko vinogorjegdje je uzgoj vinove loze zapoceo prije dvije tisuce godina, pa do danasnjih dana, proizvodnjom visoko kvalitetnih vina. Mikroklimatski uvjeti na ogranicenim lokalitetima posebno pogoduju osobinama daruvarskih vina. Posebice se istice Sauvignon za koji daruvarsko vinogorje predstavlja idealno mjesto uzgoja, te koji svojim bogatstvom arome podsjeca na miris livada. To je uvjetovalo nastanak vinske turisticke ceste, koja pocinje u Daruvaru, a nastavlja se Vinogradskom cestom kroz naselje Daruvarski Vinogradi prema Petrovom vrhu. Uz samu vinsku cestu postoje vec nadaleko poznate turisticke atrakcije medu kojima su najreprezentativnije Rimska suma (Park suma), te Zidovsko groblje za koje je Minisatrsvo kulture, Uprava za zastitu kulturne bastine, Konzervatorski odjel u Zagrebu donijelo Rjesenje o preventivnoj zastiti. Prvi punkt trase je izletiste Vranjevina sa izvorom ???Sveta voda??? koje je 15. lipnja 2000. godine proglaseno sumom s posebnom namjenom za odmor i rekreaciju. Prostorni plan Bjelovarsko ??“ bilogorske zupanije respektira ovaj proctor i cijeli potez od Vranjevine do Petrovog vrha valorizira kao prirodni krajolik kao nastavak podrucja Parka prirode ??“ Papuk.
U Daruvaru vec niz godina djeluje ???Aeroklub Zdral??? koji svojim panoramskim letovima i aeromitinzima cini turisticku ponudu Daruvara jos bogatijom (registrirana zracna luka za sportske letjelice i avione), a kasacko sportsko rekreativni turizam razvija se na novouredenom hipodromu. Inicijativom Konjickog kluba ???Daruvar??? 1996. Registrirana su drzavana natjecanja pod nazivom ???Kasacke utrke Daruvar???, u kasackim disciplinama sa stazom B kategorije. Drzavno natjecanje ali i galopska utrka rekreativnih konja izrazito je primamljiva mnogim posjetiteljima.
Daruvarska pivovara izgradena je 1840 godine, proizvodi ???Starocesko pivo??? po izvornoj ceskoj recepturi. Njeni pogoni se mogu razgledavati a turisti koji to zele mogu pivo i degustirati.
Turisticka zajednica grada Daruvara sustavno se brine o ocuvanju identiteta ovog kraja kroz tradicionalno organiziranje raznih manifestacija i priredbi od kojih najvecu pozornost privlace ???Zetvene svecanosti??? ??“ Dozinky. To je jedna od najvecih manifestacija hrvatskih Ceha, a odrzavaju se svake druge godine uz sudjelovanje svih ceskih beseda u Hrvatskoj (???Ceske besede??? su amaterska drustva organizirana kao udruge gradana u kojima Cesi njeguju svoj jezik i kulturu). Od znacajnih priredbi koje se odrzavaju svake godine vazno je spomenuti tradicionalno ???Daruvarsko martinje???, ??? Vincekovo???, ???Vinodar??? ??“ izlozba vina koja se odrzava u podrumu dvorca grofa Jankovica, te ???Darfest??? ??“ festival pjevaca amatera.
Osobitosti danasnje turisticke potraznje jesu naglasena ekoloska svijest, zanimanje za dozivljavanjem tipicnog, lokalnog ugodaja i posebnosti mjesta, te privlacnosti i raznolikosti rekreacijskih, zabavnih te sportskih sadrzaja pa je zbog toga odmor na seoskom gospodarstvu sve cesci oblik nacina provodenja slobodnog vremena. Tako i ergela kasaca ???Pehovac??? , seljacko domacinstvo sa ergelom jahacih konja koje se nalazi u Daruvarskom Brestovcu, u zaseoku Pehovac, udaljenom od sredista Daruvara svega 5 km, ima sve veci znacaj. Smjestena je na 9 jutara livada a ima i dva vlastita izvora pitke vode koja sluze kao napajalista. Na samom gospodarstvu je uredena suvremena jahaca staza duljine 550 m koja sluzi za treniranje ali je isto tako pogodna za turisticku voznju u dvosjedu. U neposrednoj blizini ergele nalazi se adaptirana star seoska kuca autohtonog zdanja sa svim obiljezjima koji se mogu pronaci samo u daruvarskom kraju, a mjesavina je multinacionalnih specificnosti ovog kraja a raspolaze sa 10 lezaja. Na ergeli se nudi skola jahanja, skola za vozaca kasaca te rekreativno jahanje.

| | | | | |
| | |ATRAKCIJE | | |
| | | | | |
|rijeka Toplica |Ribolov na rijeci Toplici i|Ostaci iz antickog doba |Zetvene svecanosti |Ceski gastronomski |
| |sportskom ribnjaku | |???Dozinki??? i ceski folklor |specijaliteti |
| | | | | |
|Gusto posumljene |Rekreacijsko jahanje na |Crkva Presvetog Trojstva |???Vinodar???, martinje |Posjet Daruvarkoj pivovari |
|sume Papuka |ergeli konja Pehovac | | |i Vinariji i kusanje |
| | | | |proizvoda |
| | | | | |
|Izvori termalne |Lov u sumama Papuka |Dvorac grofa Jankovica |???Darfest???, natjecanje |Aeromitinzi, panoramski |
|vode | | |amatera |letovi |
| | | | | |
|vinogradi |Brdski biciklizam, |Stoljetno drvece Gynko |Konjicke i kasacke utrke na|Voznja fijakerom ???Bukac??? |
| |planinarenje |Biloba |hipodromu | |
| | | | | |
|Klima- blage |Skola skijanja na Petrovom |Zidovsko groblje |Natjecanje u ribolovu |Fisijade na ribnjaku |
|zime, suha ljeta |vrhu | | |???Toplica??? |
| | | | | |
|Park – suma |Trim staze u parkovima |Stoljetni perivoji i |Nogometni turniri |Daruvarske mazoretkinje |
| | |parkovi | | |


Godisnja insolacija krece se oko 1853 sata, sto je manje od ostalih panonskih gradova zbog kotlinskog smjestaja, termalnih izvora i blizine sumskog prostora istocno od grada, uzrokujuci tako cesce jesenske i zimske magle, a sto samo po sebi utjece negativno na dolazak, zadrzavanje i raspolozenje turista.
Slijedeci nedostatak za bolji razvoj turizma je relativno losa prometna povezanost. Transferzalni cestovni pravac sjever ??“ jug, te regionalni pravac koji se proteze kroz Daruvar u smjeru istok ??“ zapad, znatno ga cine ???daljim??? nego sto on to jest. Sto se tice zeljeznickog prometa stvar je jos gora. Naime, zeljeznicka pruga koja povezuje Daruvar s Viroviticom na sjeveru te Banovom Jarugom na jugozapadu je uskotracna pa tako nema mogucnosti dolaska putnickih i brzih vlakova.
Daruvar svoje povijesne tragove biljezi vec preko dvije tisuce godina, a nedostatak gradskoga muzeja onemogucuje predstavljanje grada siroj javnosti.
Nedostatak strucnih kadrova te ogranicenost kapitala jedni su od kljucnih prepreka brzeg napretka. Na to se nadovezuje nedostatk krevetne mreze te seoska gazdinstva, koja sluzbeno nemaju registriranih postelja.
Jedan od prioriteta je i Planinarski dom ???Petrov vrh??? koji iziskuje bolju opremljenost soba za smjestaj izletnika te adekvatno tome i ugostiteljski trakt. Tako i skijaska staza s vucnicom ne odgovaraju zahtijevima sireg trzista, a takoder i losa makadamska cesta kojom ne mogu prolaziti autobusi.
Sto se tice promocije, Turisticka zajednica grada koristi se klasicnim propagandnim sredstvima (prospekti) sto predstavlja zastarjelu metodu komuniciranja sa trzistem a tome je razlog nedostatak video ??“ filmova, televizijskih spotova, mapa i turistickih vodica sa svim programima turisticke ponude, te izrada nove, suvremenije brosure.

Da bi se odstranila stihija i sprijecila masovnost vazno je sto prije izraditi strateski marketinski plan razvitka turizma zupanije. Tim planom trebalo bi odrediti nosioce razvitka turizma i rajonizirati ponudu prema prednostima nekog dijela zupanije.
U registriranim smjestajnim objektima u zupaniji ima 900 postelja i to u hotelima, motelima i domovima. U njih turisti dolaze uglavnom radi zdravstveno ??“ lijecilisnog turizma., rekreativno ??“ sportskog, lovnog i ribolovnog turizma. Kada se uzima bilo koji podatak za analizu razvijenosti turizma u Daruvaru i okolici (brojnost ponude, kvaliteta ugostiteljske ponude, putnicke agencije) dolazi se do zakljucka da je turizam nerazvijena oblast iako su mogucnosti i potencijali veliki. Zbog toga se razvitku turizma ovog kraja treba pristupiti znalacki i s puno strpljenja. S obzirom na nedostatak strucnih kadrova , i ogranicenost kapitala, sustav treba razvijati kroz pokazne objekte i sadrzaje izvedene na jednom podrucju i primjenjive na drugom, slicnom porucju. Tako gledajuci postoji mogucnost dvaju modela revitalizacije turizma na daruvarskom podrucju.

Prvi model je ???Daruvarski model??? koji pretpostavlja da na daruvarskom podrucju treba iskoristiti tradiciju i unapredivati zdravstvo ??“ ljecilisni turizam, sportsko ??“ rekreacijski turizam, lov i ribolov, te poticati novi razvoj u obliku vinske ponude, skijanje, izletnicke ture, kulturne dogadaje i dr.
Drugi model je ???Bilogorsko ??“ moslavacki??? model koji podrazumijeva postojanje niza seoskih domacinstava i obiteljskih vinarija, koji bi uz manja ulaganja i strucnu edukaciju mogli ponuditi smjestaj te niz aktivnosti (ucestvovanje u poslovima gazdinstva, tecaj rucnog rada, branje voca i sl.) ali i drugih (biciklisticke, pjesacke i jahacke ture).

Obzirom na malobrojnost sadrzaja, tek promjena dvaju modela moze dati nekoliko dana zanimljivog boravka turista u ovom podrucju. Sire gledano, tesko da ce se danasnji turist odluciti za daljnji ili ponovljeni boravak u ovim krajevima. Uloga lokalne jedinice samouprave vazna je na nacin da se Daruvar kao turisticko mjesto planira i ureduje tako da se naglasi i sacuva orginalnost i tradicija ali i ispune kriteriji modernog zivota.

Za komuniciranje sa trzistem u svrhu propagande i promicanja turizma Daruvara vazno je razmotriti i mogucnost uvrstavanja u strucne casopise te prezentiranja turisticke ponude na sjmovima, burzama, izlozbama, znanstvenim skupovima o zdravstvu, ciljanim simpozijima te prisustvovanju sastancima u cilju prosirivanja direktnih poslovnih kontakata po oblicima ponude ali i odrzavanja tradicionalnih prigoda te osmisljavanja vlastitog identiteta u promoviranju gastro ponude te instaliranja novih obrazovnih kadrova u Turisticku zajednicu grada u smislu implementacije odjela odnosa s javnoscu usmjerenog prema trzistu. Svrha ustrojstva ovakvog odjela je stvaranje povoljnog misljenja tj. stava o Daruvaru kao visokopozicioniranoj destinaciji kontinentalnog turizma, poticanje javnosti da misli, vjeruje i reagira drugacije nego sto je do tada. Odjel odnosa s javnoscu bi imao za cilj odrzavati dobre i stalne veze s masovnim medijima, organizaciju i vodenje konferencija za novinare, sponzoriranje razlicitih priredbi, organiziranje priredbi, izlozbi, sajamskih nastupa te komuniciranje sa inozemnim trzistem, a sve u ostvarivanju osnovnog cilja turisticke zajednice i grada Daruvara u smislu promoviranja vlastitog stila ??“ imagea ove destinacije.

Aqua park koji bi trebao biti otvoren do ljeta, ima priliku biti jedan od glavnih nosioca turizma u gradu, zupaniji i regiji.. Uz olimpijski bazen, koji je uvelike nedostajao kompleksu daruvarskih toplica, instalirati ce se sportski tereni i wellness centar. Ovaj projekt bi trebao rijesiti potrebu za ostalim sadrzajima koji su u sadasnjoj srtukturi ponude nedovoljno zastupljeni a to su kvalitetna ugostiteljska ponuda i povecanje krevetne mreze. U okviru popunjavanja smjestajnih kapaciteta i njihove iskoristenosti prvenstveno se misli na veci obim koristenja usluga vec obradenih struktura, s tim da se ne remeti kvaliteta u pruzanju usluga ??“ prilagodavanje programa turisticke ponude novim programima. Mogucnost produzenja trajanja boravka postoji u diferencijaciji cijena i iznalazenju klijentele vece platezne moci, a ocjenjuje se na temelju popunjenosti smjestajnih kapaciteta, prodanih aranzmana i prosirenja ponude novim programima te kvalitetom usluga. Poboljsanje kvalitete usluga je faktor koji dominira kada se govori o politici proizvoda. U tu svrhu trebalo bi u buducnosti jasnije profilirati uslugu, znaci specijalizirati se i uvesti inovacije koje vode vecoj kvaliteti i uspijesnijem pruzanju usluga.
Daruvarsko vinogorje svoju turisticku afirmaciju treba dozivjeti registriranjem gospodarskih domacinstava i klijeti sa smjestajnim kapacitetima te promoviranjem domace zdrave hrane ??“ sira, kobasica, slanine i sunke te degustaciju vina, te uredenjem okolisa izletnickih punktova na vinskoj cesti te obnova vidikovca ???Piramide??? nekdasnjeg simbola planinara i ljubitelja prirode.
Aeroklub ???Zdral??? takoder pruza mogucnost prosirenja koristenja avio letova u razlicite svrhe (avio taxi) , ali u ovisnosti sa financijskom potporom.
Ovom analizom vidimo da su potencijali razvoja turizma veliki, narocito za razvoj seoskog. Da bi se takva gosopodarstva mogla odrzati, potrebno je sve ponude daruvarskog kraja komercijalizirati te da bi se postigla sto veca razina izvrsnosti vazno je I to da se ukljuci drzava sa svojim sredstvima za poticanje malog I srednjeg poduzetnistva. S obzirom da u ovom podrucju vlada opca nezaposlenost, u promicanju malih seoskih domacinstava treba sto prije revitalizirati selo, poticati primarnu seosku proizvodnju I preradu poljoprivrednih proizvoda, zastitu I razvoj karakteristika ruralnih podrucja a narocito njihovih vrednota I identiteta. Isto tako vodeci brigu o izvedivosti modela seoskih gospodarstava u svrhu turisticke ponude trebalo bi usrajati na razvoju seljaka kao poduzetnika.
Izgradnjom magistralne ceste koja je u planu, a koja bi prolazila zapadno od grada, Zagreb bi se ???priblizio??? Daruvaru, ali i ostali dijelovi sredisnje Hrvatske.

Promocija je, uz proizvod, drugi najvazniji element marketinga mix-a jer ako se turisticka ponuda adekvatno ne promovira i na taj nacin pravovremeno ne obavijesti o njezinoj prisutnosti na trzistu, turisticka potraznja ostat ce neiskoristena.
Poboljsanje kvalitete usluga je faktor koji dominira kada se govori o politici proizvoda. U tu svrhu trebalo bi u buducnosti jasnije profilirati uslugu, znaci specijalizirati se i uvesti inovacije koje vode vecoj kvaliteti i uspijesnijem pruzanju usluga, u suprotnom rezultati nece biti zadovoljavajuci za turizam i gospodarstvo grada opcenito.
Konkretna opasnost za razvoj turizma grada mogla bi biti neisplativost aqua parka. Ta opasnost je opravdana jer se slican aqua park planira otvoriti u blizini,u sjevernom dijelu Bosne I Hercegovine (Banja Luka ??“ bolji prometni polozaj ).

Grad Daruvar sa svojom stoljetnom tradicijom ljecilisnog turizma i prirodnim znamenitostima, skladno spojenim s modernim turistickim kapacitetima, nezaobilazno je mjesto na turistickij karti Hrvatske. Danas, prepoznatljiva je teznja Daruvara za napredan, suvremen pristup orijentaciji razvoja kontinentalnog turizma, stoga je u planiranju razvoja novoj trzisnoj orijentaciji i okretanju prema pojedincu, usmjeren na koncept razvoja turizma, ekologije i infrastructure.
Prirodni potencijali zajedno sa organizacijsko ??“ materijalnim postavkama turisticke ponude, uvjetuju Daruvar posebnim atraktivnim mjestom u kontinentalnom dijelu Hrvatske, koji puni procvat tek treba dozivjeti. To nadalje znaci, da je u novoj strategiji unapredenja turistickog razvoja daruvarskog kraja utkan uravnotezen razvoj ekonomskih, ekoloskih i infrastrukturnih cinitelja temeljenih na aktivnostima malih racionalnih programa ambijentalne i autohtone vrijednosti, na programima inovacija, revitalizacije, selekcije i korekcije postojecih kapaciteta i resursa. Takvim projektima na najbolji se nacin moze trajno i sveobuhvatno afirmirati vrijednost turizma i daruvarskog kraja u cjelini.
Gradu Daruvaru je novi selektivno – kvalitetni turisticki koncept danas nuznost, obzirom na visestruke komparativne prednosti iz kojih proizlazi potreba i mogucnost za valoriziranjem pojedinih selektivnih oblika. Naravno, pri tome nisu dovoljne samo individualne inicijative nego sire zajednicke aktivnosti i akcije drustvane zajednice kojoj mora biti cilj da prezentirane turisticke oblike priblizi visokim standardima i u tom pruzi odgovarajucu pomoc kako u interpretaciji tako i u jedinstvenoj organiziranosti u nastupu revitalizacije daruvarskog turizma.
U uspjesnoj realizaciji selektivno ??“ kvalitetnog koncepta moguce je i jedino, odgovorno pristupiti stvaranjem turisticke atmosfere, turistickog ambijenta i entuzijazma, educiranjem domaceg receptivnog stanovnistva, mladu populaciju, turisticke djelatnike pa i same turiste, te prenositi sadrzajne turisticke mogucnosti i istinu o Daruvaru kao domacinu.

1.Caplar A.: Osnove
2.Cetinski, V.:Stratesko upravljanje razvojem turizma I organizacijska dinamika, FTHM, Opatija, 2005.
3. Enciklopedija likovnih umjetnosti, JLZ, 1966, staklo
4. Gjurin M.: Planinarsko ??“ turisticki vodic, Tiskara Daruvar, 1997.
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6. Hrvatski lovacki savez, www.hrvatski-
7. Magas, D.: Turisticka destinacija, Hotelijerski fakultet Opatija, Opatija, 1997.
8. Monografija grada Daruvara, Biblioteka Monografije, Turistkomerc, Zagreb, 1998.
9. Mrnjavac, E.: Promet u turizmu, FTHM, Opatija, 2002.
10.Narodne novine br. 30
11.Pavicic, I.: Sportsko-ribolovni turizam kao temelj razvoja kontinentalnog turizma,
12.Poljak Z.: Hrvatske planine, Planinarsko ??“ turisticki vodic, br. 4, 2005.
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14.Senecic, J., Vukovic, B.: Marketing u turizmu, Skolska knjiga, Zagreb, 1993.
15.Senecic, J.: Promocija u turizmu, Mikrorad, Zagreb, 1998.
16.Sluzbene stranice grada Daruvara,
17.Statisticke informacije 2005., Drzavni zavod za statistiku Republike Hrvatske, Zagreb, 2005.
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1. Pucko otvoreno uciliste: Pucka knjiznica Daruvar
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3. Internet

Darren Siwes Artistic Intentions

Question 1-Practice
Refer to the resources supplied.
Discuss the artist??™s intentions and how they approach their artmaking.
(500 words)
Darren Siwes is an Australian Artist who uses photography as his medium to express ideas such as not belonging and the feeling of dislocation. Siwes expresses these ideas through various photographical techniques, such as the colours and amount of light he uses, multiple exposures and through the landscapes he deliberately chooses.

Siwes use of colour is fairly limited in the majority of his shots. The lack of colour adds a sense of drama and suspense that couldnt have been felt if Siwes used a wide variety of colour in his work. The main source of colour in his works comes from streetlights or lamps in houses which cast a dim, yellowish shade over the work. This is seen in his work, One Night at Mount Lofty, where the only colour is shown through the lamps captured in this photograph. Quite often Siwes keeps his artwork black and white adding to this dramatic effect and therefore almost heightening the sense of dislocation, giving off a very serious, sombre atmosphere. He creates this lack of colour by using black and white film or colour film with a low ISO level, allowing for less light within his photographs and, hence, less colour. This whole art making process helps Siwes to present his intentions to the audience.

In nearly all of his works Siwes uses multiple exposures (generally a double exposure) where one photo is taken and then another on top of it. This process may be done numerous times and doesnt only have to be done digitally. An example of this may be seen in his work, Trained Man where a semi-transparent figure is seen in front of the railway platform. To my knowledge, Siwes doesnt digitally edit his photographs. The double exposure was simply done on his film camera. Siwes has evidentially set up his camera on a tripod, taken a photo of a landscape with a figure standing in it (commonly, the photographs featured himself and occasionally his wife) using a self timer, then taken a photo of that same landscape without the figure with possibly a longer exposure time, leaving the figure with a lack of substance, giving the audience a sense of melancholy, thus adding to Siwes original intentions of expressing the feeling of dislocation.

Finally, Siwes carefully selects the landscapes he uses to reflect the era of British colonisation in Australia. This is the time period that Siwes has a special link with because of his Dutch/Aboriginal background. His careful choosing of landscapes may be viewed in his work, Pre Sense, which is actually a photograph taken in the United Kingdom, however, the photograph still aims to represent this period of time. Siwes aims to challenge the audience about this period of time which is why it is important he carefully chooses these landscapes to fit this era. Through the landscapes he tries to communicate the dislocation that the British people would have felt at the time when they were taking over a land owned by Aboriginal people. His choosing of landscapes is especially crucial to his art marking process as without it, much meaning would be lost

In conclusion, Siwes is an artist who relies greatly on his art making process to communicate the messages he focuses on in his artworks. This is evident in all of his works which strongly depict an illusion of dislocation through the various processes he goes through.

Word Count: 566

Dark Knight Gothic Theme

Gotham City: Jokers Wild
Twentieth century versions of the Gothicism have many characteristics of emptiness, threatening settings and dangerous creatures to a city, as exemplified in numerous films. The Dark Knight is a movie directed and co-written by Christopher Nolan. The character of Batman is a dark and empowering figure. He does not wear the colourful apparel of Superman and lacks the light-hearted sarcasm of Spiderman. Out of all of the original superheroes of the past, Batman is the only one that obtains all the right imagery, atmosphere, and settings to be believed as true Goth. The movie is a dark and Gothic tale, with the title and Heath Ledger??™s terrifying role as the Joker alluding to that. Batman is once again forced to save the city of Gotham from the malicious Joker. The battle for Gotham City??™s soul has been jeopardized by the Joker and his plan to destroy Batman. The Joker? evokes terror in the city through the depiction of physical and psychological violence. With his clown like make up, green hair and intimidating laugh, he obtains the ideal image of a gothic villain.
The Jokers demonstrates his controlling nature in the opening scene of the movie, as he instructs the bank robbers individually, to kill the last person before loading the truck. The robbers all believed that they were given specific instructions by the Joker, but consequently they had entered a death trap. The joker has no remorse or repentance for his actions as he kills anyone who interferes with his money. An example is when the Joker is thought to be killed, and is thrown on top of the pool table. He attacks the man who had put out a reward for his body, and holds a knife to his face and states:
Want to know how I got these scars My father was a drinker and a fiend. And one night, he goes off crazier than usual.? Mommy? gets the kitchen knife to defend herself. He doesn??™t like that. Not one bit. So, me watching, he takes the knife to her, laughing while he does it. He turns to me, and he says, Why so serious Comes at me with the knife, why so serious? Sticks? the blade in my mouth, Lets put a smile on that face, and, why so serious(Scene 12)
The Joker explores his nightmares and wants people to feel his suffering. Slicing the man face shows a direct relation to past pain. Torturing and killing is an escape route for the Joker as he tries to come to terms with himself. His abusive father and memories of his childhood can be a large determinant for his actions.
The Dark Knight film depicts an ideal gothic villain through the Joker. He had killed many innocent people and put many other lives at risk. The physical and psychological violence of the Joker contributes to the gothic traits that he exhibits. Someone should ask the Joker, Why So Serious
1. Do you believe that peoples past can harm their future
2. Why do you think the Joker gave Batman a choice to save Harvey Dent or Rachel Does the Joker enjoy seeing people suffer