A New Heuristic Statistical Methodology for Optimizing Queuing Networks Using Discreet Event Simulation

Most of the real queuing systems include special properties and constraints, which can not be analyzed directly by using the results of solved classical queuing models. Lack of Markov chains features, unexponential patterns and service constraints, are the mentioned conditions. This paper represents an applied general algorithm for analysis and optimizing the queuing systems. The algorithm stages are described through a real case study. It is consisted of an almost completed non-Markov system with limited number of customers and capacities as well as lots of common exception of real queuing networks. Simulation is used for optimizing this system. So introduced stages over the following article include primary modeling, determining queuing system kinds, index defining, statistical analysis and goodness of fit test, validation of model and optimizing methods of system with simulation.

e-Collaborative Learning Circles

In this paper, we introduce an e-collaborative learning circles methodology which utilizes the information and communication technologies (ICTs) in e-educational processes. In e-collaborative learning circles methodology, the teachers and students announce their research projects on various mailing lists and discussion boards using available ICTs. The teachers & moderators and students who are already members of the e-forums, discuss the project proposals in their classrooms sent out by the potential global partner schools and return the requested feed back to the proposing school(s) about their level of the participation and contribution in the research. In general, an e-collaborative learning circle project is implemented with a small and diverse group (usually 8-10 participants) from around the world. The students meet regularly over a period of weeks/months through the ICTs during the ecollaborative learning process. When the project is completed, a project product (e-book / DVD) is prepared and sent to the circle members. In this research, when taking into account the interests and motivation of the participating students with the facilitating role of the teacher(s), the students in each circle do research to obtain new data and information, thus enabling them to have the opportunity to meet both different cultures and international understandings across the globe. However, while the participants communicate along with the members in the circle they also practice and develop their communication language skills. Finally, teachers and students find the possibility to develop their skills in using the ICTs as well.

Real-time Laser Monitoring based on Pipe Detective Operation

The pipe inspection operation is the difficult detective performance. Almost applications are mainly relies on a manual recognition of defective areas that have carried out detection by an engineer. Therefore, an automation process task becomes a necessary in order to avoid the cost incurred in such a manual process. An automated monitoring method to obtain a complete picture of the sewer condition is proposed in this work. The focus of the research is the automated identification and classification of discontinuities in the internal surface of the pipe. The methodology consists of several processing stages including image segmentation into the potential defect regions and geometrical characteristic features. Automatic recognition and classification of pipe defects are carried out by means of using an artificial neural network technique (ANN) based on Radial Basic Function (RBF). Experiments in a realistic environment have been conducted and results are presented.

Evaluating the Innovation Ability of Manufacturing Resources

Due to today-s turbulent environment, manufacturing resources, particularly in assembly, must be reconfigured frequently. These reconfigurations are caused by various, partly cyclic, influencing factors. Hence, it is important to evaluate the innovation ability - the capability of resources to implement innovations quickly and efficiently without large expense - of manufacturing resources. For this purpose, a new methodology is presented in this article. Within the methodology, design structure matrices and graph theory are used. The results of the methodology include different indices to evaluate the innovation ability of the manufacturing resources. Due to the cyclicity of the influencing factors, the methodology can be used to synchronize the realization of adaptations.

Combining Bagging and Additive Regression

Bagging and boosting are among the most popular re-sampling ensemble methods that generate and combine a diversity of regression models using the same learning algorithm as base-learner. Boosting algorithms are considered stronger than bagging on noise-free data. However, there are strong empirical indications that bagging is much more robust than boosting in noisy settings. For this reason, in this work we built an ensemble using an averaging methodology of bagging and boosting ensembles with 10 sub-learners in each one. We performed a comparison with simple bagging and boosting ensembles with 25 sub-learners on standard benchmark datasets and the proposed ensemble gave better accuracy.

Stock Market Integration Measurement: Investigation of Malaysia and Singapore Stock Markets

This paper tests the level of market integration between Malaysia and Singapore stock markets with the world market. Kalman Filter (KF) methodology is used on the International Capital Asset Pricing Model (ICAPM) and the pricing errors estimated within the framework of ICAPM are used as a measure of market integration or segmentation. The advantage of the KF technique is that it allows for time-varying coefficients in estimating ICAPM and hence able to capture the varying degree of market integration. Empirical results show clear evidence of varying degree of market integration for both case of Malaysia and Singapore. Furthermore, the results show that the changes in the level of market integration are found to coincide with certain economic events that have taken placed. The findings certainly provide evidence on the practicability of the KF technique to estimate stock markets integration. In the comparison between Malaysia and Singapore stock market, the result shows that the trends of the market integration indices for Malaysia and Singapore look similar through time but the magnitude is notably different with the Malaysia stock market showing greater degree of market integration. Finally, significant evidence of varying degree of market integration shows the inappropriate use of OLS in estimating the level of market integration.

Fractal Dimension: An Index to Quantify Parameters in Genetic Algorithms

Genetic Algorithms (GAs) are direct searching methods which require little information from design space. This characteristic beside robustness of these algorithms makes them to be very popular in recent decades. On the other hand, while this method is employed, there is no guarantee to achieve optimum results. This obliged designer to run such algorithms more than one time to achieve more reliable results. There are many attempts to modify the algorithms to make them more efficient. In this paper, by application of fractal dimension (particularly, Box Counting Method), the complexity of design space are established for determination of mutation and crossover probabilities (Pm and Pc). This methodology is followed by a numerical example for more clarification. It is concluded that this modification will improve efficiency of GAs and make them to bring about more reliable results especially for design space with higher fractal dimensions.

Identification of Factors Influencing Company's Competitiveness

Fast development of technologies, economic globalization and many other external circumstances stimulate company’s competitiveness. One of the major trends in today’s business is the shift to the exploitation of the Internet and electronic environment for entrepreneurial needs. Latest researches confirm that e-environment provides a range of possibilities and opportunities for companies, especially for micro-, small- and medium-sized companies, which have limited resources. The usage of e-tools raises the effectiveness and the profitability of an organization, as well as its competitiveness. In the electronic market, as in the classic one, there are factors, such as globalization, development of new technology, price sensitive consumers, Internet, new distribution and communication channels that influence entrepreneurship. As a result of eenvironment development, e-commerce and e-marketing grow as well. Objective of the paper: To describe and identify factors influencing company’s competitiveness in e-environment. Research methodology: The authors employ well-established quantitative and qualitative methods of research: grouping, analysis, statistics method, factor analysis in SPSS 20 environment, etc. The theoretical and methodological background of the research is formed by using scientific researches and publications, such as that from mass media and professional literature; statistical information from legal institutions as well as information collected by the authors during the surveying process. Research result: The authors detected and classified factors influencing competitiveness in e-environment.  In this paper, the authors presented their findings based on theoretical, scientific, and field research. Authors have conducted a research on e-environment utilization among Latvian enterprises. 

Compact Binary Tree Representation of Logic Function with Enhanced Throughput

An effective approach for realizing the binary tree structure, representing a combinational logic functionality with enhanced throughput, is discussed in this paper. The optimization in maximum operating frequency was achieved through delay minimization, which in turn was possible by means of reducing the depth of the binary network. The proposed synthesis methodology has been validated by experimentation with FPGA as the target technology. Though our proposal is technology independent, yet the heuristic enables better optimization in throughput even after technology mapping for such Boolean functionality; whose reduced CNF form is associated with a lesser literal cost than its reduced DNF form at the Boolean equation level. For cases otherwise, our method converges to similar results as that of [12]. The practical results obtained for a variety of case studies demonstrate an improvement in the maximum throughput rate for Spartan IIE (XC2S50E-7FT256) and Spartan 3 (XC3S50-4PQ144) FPGA logic families by 10.49% and 13.68% respectively. With respect to the LUTs and IOBUFs required for physical implementation of the requisite non-regenerative logic functionality, the proposed method enabled savings to the tune of 44.35% and 44.67% respectively, over the existing efficient method available in literature [12].

Distributed Case Based Reasoning for Intelligent Tutoring System: An Agent Based Student Modeling Paradigm

Online learning with Intelligent Tutoring System (ITS) is becoming very popular where the system models the student-s learning behavior and presents to the student the learning material (content, questions-answers, assignments) accordingly. In today-s distributed computing environment, the tutoring system can take advantage of networking to utilize the model for a student for students from other similar groups. In the present paper we present a methodology where using Case Based Reasoning (CBR), ITS provides student modeling for online learning in a distributed environment with the help of agents. The paper describes the approach, the architecture, and the agent characteristics for such system. This concept can be deployed to develop ITS where the tutor can author and the students can learn locally whereas the ITS can model the students- learning globally in a distributed environment. The advantage of such an approach is that both the learning material (domain knowledge) and student model can be globally distributed thus enhancing the efficiency of ITS with reducing the bandwidth requirement and complexity of the system.

Hazard Identification and Sensitivity of Potential Resource of Emergency Water Supply

The paper presents the case study of hazard identification and sensitivity of potential resource of emergency water supply as part of the application of methodology classifying the resources of drinking water for emergency supply of population. The case study has been carried out on a selected resource of emergency water supply in one region of the Czech Republic. The hazard identification and sensitivity of potential resource of emergency water supply is based on a unique procedure and developed general registers of selected types of hazards and sensitivities. The registers have been developed with the help of the “Fault Tree Analysis” method in combination with the “What if method”. The identified hazards for the assessed resource include hailstorms and torrential rains, drought, soil erosion, accidents of farm machinery, and agricultural production. The developed registers of hazards and vulnerabilities and a semi-quantitative assessment of hazards for individual parts of hydrological structure and technological elements of presented drilled wells are the basis for a semi-quantitative risk assessment of potential resource of emergency supply of population and the subsequent classification of such resource within the system of crisis planning.

Deployment of Service Quality Characteristics

This work discusses an innovative methodology for deployment of service quality characteristics. Four groups of organizational features that may influence the quality of services are identified: human resource, technology, planning, and organizational relationships. A House of Service Quality (HOSQ) matrix is built to extract the desired improvement in the service quality characteristics and to translate them into a hierarchy of important organizational features. The Mean Square Error (MSE) criterion enables the pinpointing of the few essential service quality characteristics to be improved as well as selection of the vital organizational features. The method was implemented in an engineering supply enterprise and provides useful information on its vital service dimensions.

A Study of Computational Organizational Narrative Generation for Decision Support

Narratives are invaluable assets of human lives. Due to the distinct features of narratives, they are useful for supporting human reasoning processes. However, many useful narratives become residuals in organizations or human minds nowadays. Researchers have contributed effort to investigate and improve narrative generation processes. This paper attempts to contemplate essential components in narratives and explore a computational approach to acquire and extract knowledge to generate narratives. The methodology and significant benefit for decision support are presented.

A Model Predictive Control and Time Series Forecasting Framework for Supply Chain Management

Model Predictive Control has been previously applied to supply chain problems with promising results; however hitherto proposed systems possessed no information on future demand. A forecasting methodology will surely promote the efficiency of control actions by providing insight on the future. A complete supply chain management framework that is based on Model Predictive Control (MPC) and Time Series Forecasting will be presented in this paper. The proposed framework will be tested on industrial data in order to assess the efficiency of the method and the impact of forecast accuracy on overall control performance of the supply chain. To this end, forecasting methodologies with different characteristics will be implemented on test data to generate forecasts that will serve as input to the Model Predictive Control module.

Accurate Control of a Pneumatic System using an Innovative Fuzzy Gain-Scheduling Pattern

Due to their high power-to-weight ratio and low cost, pneumatic actuators are attractive for robotics and automation applications; however, achieving fast and accurate control of their position have been known as a complex control problem. A methodology for obtaining high position accuracy with a linear pneumatic actuator is presented. During experimentation with a number of PID classical control approaches over many operations of the pneumatic system, the need for frequent manual re-tuning of the controller could not be eliminated. The reason for this problem is thermal and energy losses inside the cylinder body due to the complex friction forces developed by the piston displacements. Although PD controllers performed very well over short periods, it was necessary in our research project to introduce some form of automatic gain-scheduling to achieve good long-term performance. We chose a fuzzy logic system to do this, which proved to be an easily designed and robust approach. Since the PD approach showed very good behaviour in terms of position accuracy and settling time, it was incorporated into a modified form of the 1st order Tagaki- Sugeno fuzzy method to build an overall controller. This fuzzy gainscheduler uses an input variable which automatically changes the PD gain values of the controller according to the frequency of repeated system operations. Performance of the new controller was significantly improved and the need for manual re-tuning was eliminated without a decrease in performance. The performance of the controller operating with the above method is going to be tested through a high-speed web network (GRID) for research purposes.

Inverse Problem Methodology for the Measurement of the Electromagnetic Parameters Using MLP Neural Network

This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Design of Gravity Dam by Genetic Algorithms

The design of a gravity dam is performed through an interactive process involving a preliminary layout of the structure followed by a stability and stress analysis. This study presents a method to define the optimal top width of gravity dam with genetic algorithm. To solve the optimization task (minimize the cost of the dam), an optimization routine based on genetic algorithms (GAs) was implemented into an Excel spreadsheet. It was found to perform well and GA parameters were optimized in a parametric study. Using the parameters found in the parametric study, the top width of gravity dam optimization was performed and compared to a gradient-based optimization method (classic method). The accuracy of the results was within close proximity. In optimum dam cross section, the ratio of is dam base to dam height is almost equal to 0.85, and ratio of dam top width to dam height is almost equal to 0.13. The computerized methodology may provide the help for computation of the optimal top width for a wide range of height of a gravity dam.

Kinematic Optimal Design on a New Robotic Platform for Stair Climbing

Stair climbing is one of critical issues for field robots to widen applicable areas. This paper presents optimal design on kinematic parameters of a new robotic platform for stair climbing. The robotic platform climbs various stairs by body flip locomotion with caterpillar type main platform. Kinematic parameters such as platform length, platform height, and caterpillar rotation speed are optimized to maximize stair climbing stability. Three types of stairs are used to simulate typical user conditions. The optimal design process is conducted based on Taguchi methodology, and resulting parameters with optimized objective function are presented. In near future, a prototype is assembled for real environment testing.

Migration and Unemployment Duration: The Case of the OECD Countries

This paper examines whether or not immigration has a positive influence on the duration of unemployment, in a macroeconomic perspective. We analyse also whether the degree of labor market integration can influence migration. The integration of immigrants into the labor market is a recurrence theme in the work on the economic consequences of immigration. However, to our knowledge, no researchers have studied the impact of immigration on unemployment duration, and vice versa. With two methodology of research (panel estimations (OLS and 2SLS) and panel cointegration techniques), we show that migration seems to influence positively the short-term unemployment and negatively long-term unemployment, for 14 OECD destination countries. In addition, immigration seems to be conditioned by the structural and institutional characteristics of the labour market.

Application of Multi-objective Optimization Packages in Design of an Evaporator Coil

A novel methodology has been used to design an evaporator coil of a refrigerant. The methodology used is through a complete Computer Aided Design /Computer Aided Engineering approach, by means of a Computational Fluid Dynamic/Finite Element Analysis model which is executed many times for the thermal-fluid exploration of several designs' configuration by an commercial optimizer. Hence the design is carried out automatically by parallel computations, with an optimization package taking the decisions rather than the design engineer. The engineer instead takes decision regarding the physical settings and initializing of the computational models to employ, the number and the extension of the geometrical parameters of the coil fins and the optimization tools to be employed. The final design of the coil geometry found to be better than the initial design.