Optimum energy consumption in wireless sensitive networks plays an important role on network management. In the proposed model of this paper, first all the nods send the energy, station distance and density parameters to their fuzzy modules. According to each nod & apos; s fuzzy module outputs, a timer is activated for all nodes, which start reverse-counting from obtained value from fuzzy module. Timer of better nod comes to zero sooner and two best nods are selected in each zone (with the distance of r). One of them is introduced as superior cluster head and the other nods are connected to the closest cluster head. In addition, the cluster head not introduced as superior cluster head first collects data from neighbor & apos; s nods and then sends it to the superior cluster head after classifying data as package. The performance of the proposed model of this paper is compared with other methods and the preliminary results indicate that the proposed algorithm has increased first nod death time compared with other methods in the literature.

The 20th century was the age of an industry-based as well as knowledge-based economy. In a knowledge-based economy, knowledge plays an essential role to produce wealth compared with other tangible and physical assets. The purpose of this research is to identify and rank different aspects of knowledge management based on the Hicks model using the fuzzy TOPSIS technique for one of the most prestigious universities in Iran. The proposed model considers four main criteria of knowledge including creation, distribution, storage, and application along with 17 sub-criteria. The Chi-square correlation test indicates a positive and meaningful correlation between four mentioned criteria and knowledge management implementation. Using the fuzzy TOPSIS technique, the results also indicate that “Need for new and updated information and knowledge” was selected as the most important sub-criterion and “Sharing or distribution of knowledge” was selected as the most important main criterion on Hicks model.

Automation in service delivery has increased the consumers’ expectation with regard to service quality and subsequently the perception of the same. Technology-driven services redefined quality dimensions and their subsequent impact on the behavioural outcomes of the consumers with specific reference to attitudinal loyalty and propensity to switch. Customer Relationship Management (CRM) has further reinforced the operational aspects of a service provider by integrating the behavioural perspectives with technology. This paper attempts to explore the nomological link between automated service quality and its behavioural consequences with specific reference to consumers’ attitudinal loyalty and their intention to switch or defect from their present service provider. The study further takes into consideration the moderating effects of the performance of the dimensions and attributes of customer relationship management by introducing a novel approach to CRM performance indexing. The cross-sectional study was carried out with the customers of State Bank of India at Asansol, Durgapur, Bolpur and Santiniketan in West Bengal, India. The study used structural equation modeling (SEM) to assess and validate the nomological relationship between the variables.

With the ever-increasing demands for high surface finish and complex shape geometries, conventional metal removal methods are now being replaced by non-traditional machining (NTM) processes. These NTM processes use energy in its direct form to remove materials in the form of atoms or molecules to obtain the required accuracy and burr-free machined surface. In order to exploit the optimal capabilities of the NTM processes, it is often required to determine the best possible combinations of their controllable parameters. Different non-conventional optimization techniques have been used for dealing with these process optimization problems because of their inherent advantages and capabilities for arriving at the almost global optimal solutions. This paper reviews the applications of different non-conventional optimization techniques for parametric optimization of NTM processes. It is observed that electrical discharge machining processes have been optimized most number of times, followed by wire electrical discharge machining processes. In most of the cases, the past researchers have preferred to maximize material removal rate. Genetic algorithm has been found to be the most popular non-conventional optimization technique.

Most recent studies are based on benchmarking analysis allowing the measure of company efficiency relatively to a reference performance. Benchmarking is a helpful tool to analyze and promote efficiency in insurance companies. The fast development of X-efficiency notion makes traditional performance measures (ROA, ROE, etc.) obsolete. Indeed, various methods have been used, various input-output measures have been proposed and various research fields have been explored in insurance company investigation. So, after reviewing most known efficiency concepts and their definitions, this section explores the literature review of two principal points of discussion: the first point is focused on the different used techniques to measure efficiency, including the developed approaches to define inputs, outputs and their prices. The second point represents an overview of efficiency investigations in insurance industry.

Safety is a relative quantity that is a function of the situation in which it is measured. This research has been conducted in a well established pharmaceutical company in Bangladesh practicing GMP (Good Manufacturing Practice), which has a tablet manufacturing facility. Tablet manufacturing comprises a number of manufacturing activities and machineries. Each of these activities, requiring amalgamated interaction of man, machine, equipment and environment has the potential of producing unforeseen hazards. Therefore, analysis of risk to assure worker safety is not only necessary here, it is also important to use an appropriate tool that can incorporate all the risk- producing parameters. The research work conducted here using a very effective tool named Failure Mode and Effect Analysis (FMEA), consisted of observing the works at different sections, breaking them down into sequential steps, noting the surrounding variables of each task, and using these data to perform risk analysis to find out the most hazardous works for the workers.

This research study focuses the existence of “weak form efficiency” in the Karachi stock exchange of Pakistan. Daily stock returns are used to check the “weak form efficiency’ in KSE covering a time period of 15 years ranges from July, 1997 to April, 2012. Kolmogrov-Smirnov (K-S) test, runs test, Unit root test Augumented Dickey Fuller test, Phillips Perron test are run to check the hypothesis. It is revealed that the KSE is not distributed normally and patterns are there in the prices so, the technical analyst can get the benefit in short run through predicting the future prices. This means that there exists some opportunity for the traders and investors to predict the upcoming stock prices of the securities, which are trading in the KSE and can earn high return and outperform the market. However, in long run scenario (in monthly data) the results are vice versa and Karachi stock exchange is a weak form efficient market.

Capital structure plays an important role on market growth investigation. In this paper, we investigate the relationship between capital structure as dependent variable and seven independent variables including tax rate, firms & apos; growth rate, fixed assets, firms & apos; size, operating risk, profitability and industry type. The proposed study of this paper uses the financial information of 107 selected companies from 18 different industries listed on Tehran Stock Exchange over the period of 2004-2011 covering 40% of total number of companies listed in this stock exchange. We use ordinary least square technique to study the relationships. The results of the survey indicate that the there is a positive relationship between tax rate and firm & apos; s growth rate, and capital structure. The result of the survey also indicates there is a negative relationship between firm & apos; s profitability and capital structure. However, there is no evidence to believe that there was any relationship between fixed assets and capital structure. We have also concluded that there was a negative relationship between firm & apos; s profitability and capital structure but the results of our survey did not indicate that there was any difference between the mean of profitability in various sectors.

This research investigates the relationship between auditor’s opinion and stock return in the companies listed at Tehran stock exchange market. In this study, all required data are collected from aware shareholders and provide a sampling of 130 questionnaires, the data collected over the period 2010-2011 using test methods such as computer software, data analysis and statistical methods to answer research questions. According to research result through questionnaires and tests, there is a significant relationship between stock returns and the auditor & apos; s opinion, in fact, for aware shareholders of the company the auditor’s opinion has a special message. This message is based on the results of study hypothesis in comparison with previous research with regard to changes in the questionnaire and provides assumptions that are more detailed. The first finding is that unqualified audit report has a positive impact on stock returns of companies with a medium to low degree. Adverse audit report has a negative impact on stock returns of companies with medium to high degree. Disclaimer of audit report has a negative impact on stock returns of companies with medium to high degree. Finally, qualifying paragraphs, which modified the items of income statement items have more impact in comparison with qualifying paragraphs which modified the Balance Sheet items.

For many years, investors used some basic financial ratios to measure the relative performance of various active industries based on two-digit ISIC classification. However, direct implementation of basic financial figures may not be practical in today & apos; s business environment since investors face with different criteria. The proposed model of this paper uses Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to compare 37 various industries based on different financial figures. We gather the necessary data over the period of 2009-2010 from Tehran Stock Exchange and investigate the data in two stages. In the first stage, we perform fundamental analysis to select the most appropriate firms and the in the second stage, we use TOPSIS to rank selected firms based on different criteria. The results of the study confirm that information and communication technology, which is one of the biggest firms in this exchange is considered as the best option (relative ranking 0.88 in two years) followed by some Cement industry (with relative ranking of 0.26 in 2009 and 0.19 in 2010) and oil refinery units (with relative ranking of 0.23 in 2009 and 0.19 in 2010). The figure also shows that other firms maintain low ratios varied from 0.23 to 0.01. The lowest industry ranking belongs to marine industry.