Capacity Optimization for Local and Cooperative Spectrum Sensing in Cognitive Radio Networks

The dynamic spectrum allocation solutions such as cognitive radio networks have been proposed as a key technology to exploit the frequency segments that are spectrally underutilized. Cognitive radio users work as secondary users who need to constantly and rapidly sense the presence of primary users or licensees to utilize their frequency bands if they are inactive. Short sensing cycles should be run by the secondary users to achieve higher throughput rates as well as to provide low level of interference to the primary users by immediately vacating their channels once they have been detected. In this paper, the throughput-sensing time relationship in local and cooperative spectrum sensing has been investigated under two distinct scenarios, namely, constant primary user protection (CPUP) and constant secondary user spectrum usability (CSUSU) scenarios. The simulation results show that the design of sensing slot duration is very critical and depends on the number of cooperating users under CPUP scenario whereas under CSUSU, cooperating more users has no effect if the sensing time used exceeds 5% of the total frame duration.

The Influencing Factors and the Approach to Enhance the Standard of E-Commerce for Small and Medium Enterprises in Bangkok

The objectives of this research paper were to study the influencing factors that contributed to the success of electronic commerce (e-commerce) and to study the approach to enhance the standard of e-commerce for small and medium enterprises (SME). The research paper focused the study on only sole proprietorship SMEs in Bangkok, Thailand. The factors contributed to the success of SME included business management, learning in the organization, business collaboration, and the quality of website. A quantitative and qualitative mixed research methodology was used. In terms of quantitative method, a questionnaire was used to collect data from 251 sole proprietorships. The System Equation Model (SEM) was utilized as the tool for data analysis. In terms of qualitative method, an in-depth interview, a dialogue with experts in the field of ecommerce for SMEs, and content analysis were used. By using the adjusted causal relationship structure model, it was revealed that the factors affecting the success of e-commerce for SMEs were found to be congruent with the empirical data. The hypothesis testing indicated that business management influenced the learning in the organization, the learning in the organization influenced business collaboration and the quality of the website, and these factors, in turn, influenced the success of SMEs. Moreover, the approach to enhance the standard of SMEs revealed that the majority of respondents wanted to enhance the standard of SMEs to a high level in the category of safety of e-commerce system, basic structure of e-commerce, development of staff potentials, assistance of budget and tax reduction, and law improvement regarding the e-commerce respectively.

Social Media and Counseling: Opportunities, Risks and Ethical Considerations

The purpose of this article is to briefly review the opportunities that social media present to counselors and psychologists. Particular attention was given to understanding some of the more important common risks inherent in social media and the potential ethical dilemmas which may arise for counselors and psychologists who embrace them in their practice. Key considerations of issues pertinent to an online presence such as multiple relationships, visibility and privacy, maintaining ethical principles and professional boundaries are being discussed.

A Sociocybernetics Data Analysis Using Causality in Tourism Networks

The aim of this paper is to propose a mathematical model to determine invariant sets, set covering, orbits and, in particular, attractors in the set of tourism variables. Analysis was carried out based on a pre-designed algorithm and applying our interpretation of chaos theory developed in the context of General Systems Theory. This article sets out the causal relationships associated with tourist flows in order to enable the formulation of appropriate strategies. Our results can be applied to numerous cases. For example, in the analysis of tourist flows, these findings can be used to determine whether the behaviour of certain groups affects that of other groups and to analyse tourist behaviour in terms of the most relevant variables. Unlike statistical analyses that merely provide information on current data, our method uses orbit analysis to forecast, if attractors are found, the behaviour of tourist variables in the immediate future.

Prediction of Optimum Cutting Parameters to obtain Desired Surface in Finish Pass end Milling of Aluminium Alloy with Carbide Tool using Artificial Neural Network

End milling process is one of the common metal cutting operations used for machining parts in manufacturing industry. It is usually performed at the final stage in manufacturing a product and surface roughness of the produced job plays an important role. In general, the surface roughness affects wear resistance, ductility, tensile, fatigue strength, etc., for machined parts and cannot be neglected in design. In the present work an experimental investigation of end milling of aluminium alloy with carbide tool is carried out and the effect of different cutting parameters on the response are studied with three-dimensional surface plots. An artificial neural network (ANN) is used to establish the relationship between the surface roughness and the input cutting parameters (i.e., spindle speed, feed, and depth of cut). The Matlab ANN toolbox works on feed forward back propagation algorithm is used for modeling purpose. 3-12-1 network structure having minimum average prediction error found as best network architecture for predicting surface roughness value. The network predicts surface roughness for unseen data and found that the result/prediction is better. For desired surface finish of the component to be produced there are many different combination of cutting parameters are available. The optimum cutting parameter for obtaining desired surface finish, to maximize tool life is predicted. The methodology is demonstrated, number of problems are solved and algorithm is coded in Matlab®.

Work Motivation, Work Stress, and Job Satisfaction in between Taiwan and China - An Empitical Study

This study investigates the relationships between Work Motivation, Work Stress, and Job Satisfaction toward cross-strait employees. The target subjects are three manufacturing firms in Mainland China and Taiwan. Out of 450 distributed surveys, 352 valid surveys were obtained with the response rate of 78.22%.The findings have addressed three main pull factors toward cross-strait employees in choosing jobs, which are (1) high level of firm stability, (2) good firm image, and (3) good employee benefits. In addition, various employee attributes exert different impacts on Work Motivation, Work Stress, and Job Satisfaction. The comparison between expected and actual perceived Job Satisfaction toward cross-strait employees shows that “salary" ranks highest regarding expected Job Satisfaction whereas “co-worker relationship" ranks highest regarding actual perceived Job Satisfaction, which implies actual perceived Job Satisfaction do not match employee expectations. Therefore, this research further concludes that there exists differences between employees- expected and actual perceived Job Satisfaction.

Detection of Linkages Between Extreme Flow Measures and Climate Indices

Large scale climate signals and their teleconnections can influence hydro-meteorological variables on a local scale. Several extreme flow and timing measures, including high flow and low flow measures, from 62 hydrometric stations in Canada are investigated to detect possible linkages with several large scale climate indices. The streamflow data used in this study are derived from the Canadian Reference Hydrometric Basin Network and are characterized by relatively pristine and stable land-use conditions with a minimum of 40 years of record. A composite analysis approach was used to identify linkages between extreme flow and timing measures and climate indices. The approach involves determining the 10 highest and 10 lowest values of various climate indices from the data record. Extreme flow and timing measures for each station were examined for the years associated with the 10 largest values and the years associated with the 10 smallest values. In each case, a re-sampling approach was applied to determine if the 10 values of extreme flow measures differed significantly from the series mean. Results indicate that several stations are impacted by the large scale climate indices considered in this study. The results allow the determination of any relationship between stations that exhibit a statistically significant trend and stations for which the extreme measures exhibit a linkage with the climate indices.

Climate Change and the Problem of Malaria in Armenia

The data presented in this work show that in Armenia a rise of air temperature is expected in the season, and annual terms. As a result of the noted increase in temperature, a significant growth of vulnerability of the territory of Armenia in relation to malaria is expected. Zoning by the risk of renewed malaria transmission has been performed.

Health Risk Assessment for Sewer Workers using Bayesian Belief Networks

The sanitary sewerage connection rate becomes an important indicator of advanced cities. Following the construction of sanitary sewerages, the maintenance and management systems are required for keeping pipelines and facilities functioning well. These maintenance tasks often require sewer workers to enter the manholes and the pipelines, which are confined spaces short of natural ventilation and full of hazardous substances. Working in sewers could be easily exposed to a risk of adverse health effects. This paper proposes the use of Bayesian belief networks (BBN) as a higher level of noncarcinogenic health risk assessment of sewer workers. On the basis of the epidemiological studies, the actual hospital attendance records and expert experiences, the BBN is capable of capturing the probabilistic relationships between the hazardous substances in sewers and their adverse health effects, and accordingly inferring the morbidity and mortality of the adverse health effects. The provision of the morbidity and mortality rates of the related diseases is more informative and can alleviate the drawbacks of conventional methods.

Application of Fuzzy Logic Approach for an Aircraft Model with and without Winglet

The measurement of aerodynamic forces and moments acting on an aircraft model is important for the development of wind tunnel measurement technology to predict the performance of the full scale vehicle. The potentials of an aircraft model with and without winglet and aerodynamic characteristics with NACA wing No. 65-3- 218 have been studied using subsonic wind tunnel of 1 m × 1 m rectangular test section and 2.5 m long of Aerodynamics Laboratory Faculty of Engineering (University Putra Malaysia). Focusing on analyzing the aerodynamic characteristics of the aircraft model, two main issues are studied in this paper. First, a six component wind tunnel external balance is used for measuring lift, drag and pitching moment. Secondly, Tests are conducted on the aircraft model with and without winglet of two configurations at Reynolds numbers 1.7×105, 2.1×105, and 2.5×105 for different angle of attacks. Fuzzy logic approach is found as efficient for the representation, manipulation and utilization of aerodynamic characteristics. Therefore, the primary purpose of this work was to investigate the relationship between lift and drag coefficients, with free-stream velocities and angle of attacks, and to illustrate how fuzzy logic might play an important role in study of lift aerodynamic characteristics of an aircraft model with the addition of certain winglet configurations. Results of the developed fuzzy logic were compared with the experimental results. For lift coefficient analysis, the mean of actual and predicted values were 0.62 and 0.60 respectively. The coreelation between actual and predicted values (from FLS model) of lift coefficient in different angle of attack was found as 0.99. The mean relative error of actual and predicted valus was found as 5.18% for the velocity of 26.36 m/s which was found to be less than the acceptable limits (10%). The goodness of fit of prediction value was 0.95 which was close to 1.0.

Coordination on Agrifood Supply Chain

Coordinated supply chain represents major challenges for the different actors involved in it, because each agent responds to individual interests. The paper presents a framework with the reviewed literature regarding the system's decision structure and nature of demand. Later, it characterizes an agri food supply chain in the Central Region of Colombia, it responds to a decentralized distribution system and a stochastic demand. Finally, the paper recommends coordinating the chain based on shared information, and mechanisms for each agent, as VMI (vendor-managed inventory) strategy for farmer-buyer relationship, information system for farmers and contracts for transportation service providers.

Impact of Computer-Mediated Communication on Virtual Teams- Performance: An Empirical Study

In a complex project environment, project teams face multi-dimensional communication problems that can ultimately lead to project breakdown. Team Performance varies in Face-to-Face (FTF) environment versus groups working remotely in a computermediated communication (CMC) environment. A brief review of the Input_Process_Output model suggested by James E. Driskell, Paul H. Radtke and Eduardo Salas in “Virtual Teams: Effects of Technological Mediation on Team Performance (2003)", has been done to develop the basis of this research. This model theoretically analyzes the effects of technological mediation on team processes, such as, cohesiveness, status and authority relations, counternormative behavior and communication. An empirical study described in this paper has been undertaken to test the “cohesiveness" of diverse project teams in a multi-national organization. This study uses both quantitative and qualitative techniques for data gathering and analysis. These techniques include interviews, questionnaires for data collection and graphical data representation for analyzing the collected data. Computer-mediated technology may impact team performance because of difference in cohesiveness among teams and this difference may be moderated by factors, such as, the type of communication environment, the type of task and the temporal context of the team. Based on the reviewed model, sets of hypotheses are devised and tested. This research, reports on a study that compared team cohesiveness among virtual teams using CMC and non-CMC communication mediums. The findings suggest that CMC can help virtual teams increase team cohesiveness among their members, making CMC an effective medium for increasing productivity and team performance.

The Stone in the Identity of the Landscape

The stone is a constituent part of the geological structure of the Territory, introducing himself as a subject that has always interconnected human and environment in the development of a discourse of meanings and symbols that reflect elements realized in different cultures and experiences. This action meant that the first settlements and their areas of influence gained importance in the field of humanization and spatial organization of the territory, not only for the appropriation that its inhabitants did, but mainly because the community regardless of their economic or social condition, used it as living space and cultural integration. These factors become decisive in the characterization of the landscape area in the northwest of Portugal, because the stone is a material that appears not only in the natural landscape, but is also a strong element in humanized landscape, becoming this relation the main characterization of the study area.

Topological Queries on Graph-structured XML Data: Models and Implementations

In many applications, data is in graph structure, which can be naturally represented as graph-structured XML. Existing queries defined on tree-structured and graph-structured XML data mainly focus on subgraph matching, which can not cover all the requirements of querying on graph. In this paper, a new kind of queries, topological query on graph-structured XML is presented. This kind of queries consider not only the structure of subgraph but also the topological relationship between subgraphs. With existing subgraph query processing algorithms, efficient algorithms for topological query processing are designed. Experimental results show the efficiency of implementation algorithms.

The Building Thermal Performance and Carbon Sequestration Evaluation for Psophocarpus tetrogonobulus on Biofaçade Wall in the Tropical Environment

Plants are commonly known for its positive correlation in reducing temperature. Since it can benefit buildings by modifying the microclimate, it-s also believed capable of reducing the internal temperature. Various experiments have been done in Universiti Sains Malaysia, Penang to investigate the comparison in thermal benefits between two rooms, one being a typical control room (exposed wall) and the other a biofacade room (plant shaded wall). The investigations were conducted during non-rainy season for approximately a month. Climbing plant Psophocarpus tetrogonobulus from legume species was selected as insulation for the biofacade wall. Conclusions were made on whether the biofacade can be used to tackle the energy efficiency, based on the parameters taken into consideration.

ANN based Multi Classifier System for Prediction of High Energy Shower Primary Energy and Core Location

Cosmic showers, during the transit through space, produce sub - products as a result of interactions with the intergalactic or interstellar medium which after entering earth generate secondary particles called Extensive Air Shower (EAS). Detection and analysis of High Energy Particle Showers involve a plethora of theoretical and experimental works with a host of constraints resulting in inaccuracies in measurements. Therefore, there exist a necessity to develop a readily available system based on soft-computational approaches which can be used for EAS analysis. This is due to the fact that soft computational tools such as Artificial Neural Network (ANN)s can be trained as classifiers to adapt and learn the surrounding variations. But single classifiers fail to reach optimality of decision making in many situations for which Multiple Classifier System (MCS) are preferred to enhance the ability of the system to make decisions adjusting to finer variations. This work describes the formation of an MCS using Multi Layer Perceptron (MLP), Recurrent Neural Network (RNN) and Probabilistic Neural Network (PNN) with data inputs from correlation mapping Self Organizing Map (SOM) blocks and the output optimized by another SOM. The results show that the setup can be adopted for real time practical applications for prediction of primary energy and location of EAS from density values captured using detectors in a circular grid.

Experimental Investigation of the Maximum Axial Force in the Folding Process of Aluminum Square Columns

In this paper, a semi empirical formula is presented based on the experimental results to predict the first pick (maximum force) value in the instantaneous folding force- axial distance diagram of a square column. To achieve this purpose, the maximum value of the folding force was assumed to be a function of the average folding force. Using the experimental results, the maximum value of the force necessary to initiate the first fold in a square column was obtained with respect to the geometrical quantities and material properties. Finally, the results obtained from the semi empirical relation in this paper, were compared to the experimental results which showed a good correlation.

The Weight of Corporate Social Responsibility Indicators in Measurement Procedure

The Corporate Social Responsibility (CSR) performance has garnered significant interest during the last two decades as numerous methodologies are proposed by Social Responsible Investment (SRI) indexes. The weight of each indicator is a crucial component of the CSR measurement procedures. Based on a previous study, the appropriate weight of each proposed indicator for the Greek telecommunication sector is specified using the rank reciprocal weighting. The Kendall-s Coefficient of Concordance and Spearman Correlation Coefficient non-parametric tests are adopted to determine the level of consensus among the experts concerning the importance rank of indicators. The results show that there is no consensus regarding the rank of indicators in most of stakeholders- domains. The equal weight for all indicators could be proposed as a solution for the lack of consensus among the experts. The study recommends three different equations concerning the adopted weight approach.

Thermal Analysis of the Current Path from Circuit Breakers Using Finite Element Method

This paper describes a three-dimensional thermal model of the current path included in the low voltage power circuit breakers. The model can be used to analyse the thermal behaviour of the current path during both steady-state and transient conditions. The current path lengthwise temperature distribution and timecurrent characteristic of the terminal connections of the power circuit breaker have been obtained. The influence of the electric current and voltage drop on main electric contact of the circuit breaker has been investigated. To validate the three-dimensional thermal model, some experimental tests have been done. There is a good correlation between experimental and simulation results.