Clustering is a critical data analysis and it is a popular data mining technique. This paper presents a rapid Ant based clustering-genetic algorithm (RAC-GA) with local search to solve clustering problem. GA and local search are used as a global and local search to obtain better results. The proposed algorithm is evaluated by testing on some of the well-known real-world datasets, and the results are compared with other popular heuristics in clustering, such as GA, SA, TS, ACO and RAC. The results show strong improvement both in quality solution and process time area, especially in process time which is much less than previous algorithms

During the past few years, there have been growing interests in using email for delivering various types of messages such as social, financial, etc. There are also people who use email messages to promote products and services or even to do criminal activities called Spam email. These unwanted messages are sent to different target population for different purposes and there is a growing interest to develop methods to filter such email messages. This paper presents a method to filter Spam email messages based on the keyword pattern. In this article, a multi-agent filter trade based on the Bayes rule, which has benefit of using the users’ interest, keywords and investigation the message content according to its topic, has been used. Then Nested Neural Network has been used to detect the spam messages. To check the authenticity of this proposed method, we test it for a couple of email messages, so that it could determine spams and hams from each other, effectively. The result shows the superiority of this method over the previous ones including filters with Multi-Layer Perceptron that detect spams.

The Ad hoc network is one of the multistep-based self-organizing networks, which are dynamically changing and are taken more into account as the ways of connecting the terminals through the development of wireless communication terminals. We are faced with numerous challenges in designing a wireless network such as the dynamic topology, common and limited bandwidth, and the limited energy. The nodes are moving according to the continuous changes in the topology and the source-to-destination paths are completely broken. Therefore, the repeated route discovery enhances the delay and overload of routing. Thus, it is essential to consider the link stability while designing the path in order to choose the routing protocol. Providing the multiple paths may lead to the better performance than a path. The transmission energy control in the wireless Ad hoc networks is the option for the level of transmission energy in order to transmit each node packet in this system. Therefore, transmission energy control affects the wireless medium interface. Because of choosing the appropriate protocol, the routing operation can be improved and the energy consumption can be controlled properly as well as enhancing the durability and longevity of network. The main objective of this study is to enhance the network longevity. The proposed algorithm in this research considers the combination of 2 parameters including the rate of node energy and number of steps in Fuzzy System applied on AOMDV Protocol, which is a Multipath Routing Protocol. The results of simulation also indicate the improved performance of proposed algorithm (AOMDV-F) compared to AODV and AOMDV Protocols in NS2 simulator.

The complexity of large-scale projects has led to numerous risks in their life cycle. This paper presents a new risk evaluation approach in order to rank the high risks in large-scale projects and improve the performance of these projects. It is based on the fuzzy set theory that is an effective tool to handle uncertainty. It is also based on an extended VIKOR method that is one of the well-known multiple criteria decision-making (MCDM) methods. The proposed decision-making approach integrates knowledge and experience acquired from professional experts, since they perform the risk identification and also the subjective judgments of the performance rating for high risks in terms of conflicting criteria, including probability, impact, quickness of reaction toward risk, event measure quantity and event capability criteria. The most notable difference of the proposed VIKOR method with its traditional version is just the use of fuzzy decision-matrix data to calculate the ranking index without the need to ask the experts. Finally, the proposed approach is illustrated with a real-case study in an Iranian power plant project, and the associated results are compared with two well-known decision-making methods under a fuzzy environment.

In construction cost management system, normally earned value management (EVM) is applied as an efficient control approach in both status detection and estimation at completion (EAC) cost forecasting. The traditional approaches in EAC predictions normally extend the current situation of a project to the future by employing pervious performance factor. The proposed approach of this paper considers both qualitative and quantitative factors affecting the EAC prediction. The proposed approach of this research not only estimates the completion of the project, but also it can generate accurate forecast for the entire future periods using a fuzzy neural network model. The model is also implemented for a real-world case study and yields encouraging preliminary results.

This paper studies the problem of single machine stochastic scheduling with random processing times, deterministic due dates and an independent setup time. The jobs are also deteriorated based on the position, which their processes are done. The objective function is to find a schedule of jobs, which minimizes the expected value of maximum lateness. A branch and bound scheme is presented to solve the problem analytically and a simulated annealing meta-heuristic (SA) is also provided for solving the problem in larger scales. Computational experiments demonstrate that the proposed SA is capable of finding near optimal solutions with very low gap.

This paper investigates the persistence of earnings components and pricing test of abnormal changes in cash for selected firms listed on Tehran Stock Exchange (TSE). The proposed study gathers the necessary data from 166 firms over the period 2004-2012 from firms whose shares were actively traded on TSE market. The study uses Panel data and with the implementation of linear regression technique examines four hypotheses. The results indicate that abnormal negative changes in cash are more persistence than positive abnormal changes. In addition, both positive and negative abnormal changes are more persistence than accruals. Market also has a good perception on abnormal positive and negative changes in cash.

This study examines the relationship between the working capital management and profitability for a real-world case study in Iran over the period 2004-2012. There are three components associated with working capital including account payable period, inventory turnover period and receivable account period. The study uses cash conversion cycle to investigate the impacts of working capital management on profitability, simultaneously. We use Pearson correlation ratios as well as regression techniques to study different hypotheses. The result indicates an inverse relationship between variables of working capital and profitability. It means if account receipt, cash conversion cycle and period of debt payment increase, the profitability of this company will decrease so managers can create more value that is positive for shareholders by decreasing period of debt payment, period of inventory turnover and period of demand collection.

Developing a national brand is one of the most important issues for development of a brand. In this study, we present factor analysis to detect the most important factors in building a national brand. The proposed study uses factor analysis to extract the most influencing factors and the sample size has been chosen from two major auto makers in Iran called Iran Khodro and Saipa. The questionnaire was designed in Likert scale and distributed among 235 experts. Cronbach alpha is calculated as 84%, which is well above the minimum desirable limit of 0.70. The implementation of factor analysis provides six factors including “cultural image of customers”, “exciting characteristics”, “competitive pricing strategies”, “perception image” and “previous perceptions”.

University of applied science and technology has been designed to create a platform for multilateral activities such as industrial, military and academic in developing countries to promote science and scientific research applications. These universities are responsible to promote practical training in quantitative and qualitative indicators and they provide appropriate infrastructure to implement theoretical graduates to solve practical problems to build necessary infrastructure to transfer modern technology into developing countries. During the past few years, there have been tremendous development on these units but some of them have not been efficient. In this paper, we present an empirical study to measure the relative efficiencies of various units of applied science and technology universities using data envelopment analysis. The proposed model of this paper uses two inputs including human resources as well as total assets and two outputs including the number of graduate students as well as operating profit. The results of the study have indicated that some of the units are inefficient and need to be merged with other units to increase the relative efficiency of these universities.