Genetic algorithm (GA) based feature selection method is an evolving search heuristic, used to provide solutions to optimization problems. Feature selection is an important aspect that improves classification accuracy. The main objective of this work is to utilize GA for feature selection by integrating it with a bank of multi-class Support Vector Machine (SVM) for identification of the effective feature set. The proposed GA based approach finds its application in epileptic seizure detection. EEG dataset containing artefacts and noise were removed by employing constrained Independent Component Analysis (cICA) and Stationary Wavelet Transform (SWT). The features of the input data are constructed in the form of feature vector by FastICA technique. The fitness calculation for the selection of individuals in the GA is calculated by a Linear Discriminant Analysis (LDA) classifier. The multi-class Support Vector Machine (SVM) (one-against-all) classifier is used for the validation of the selected features. The samples are taken from 948 patients and the classes are divided as normal, seizure, and seizure-free using artificial neural networks. Experimental results demonstrate that the GA - multi-SVM feature selection technique can achieve higher accuracies as compared to the case without feature selection.

Wireless Sensor Network (WSN) consists of spatially distributed and dedicated sovereign sensor nodes with confined resources to politely monitor physical and environmental conditions. In recent years, there has been a rising interest in WSN. One of the major confrontations in WSN is developing an energy-efficient routing protocol to enhance the network longevity. With that concern, this work contributes in providing a novel approach called DAO-LEACH (Data Aggregation based Optimal- LEACH) by which the energy efficient routing in WSN is attained based on effective data ensemble and optimal clustering. Aggregating the data sent by cluster members comprehend in draining network load and amending the bandwidth. In order to minimize the energy dissipation of sensor nodes and optimize the resource utilization, cluster head is elected for each cluster. Moreover, the energy efficient route in WSN is obtained by combining the nodes having maximum residual energy. Experimental results have shown that the proposed approach furnishes efficient route for data transmission among the sensor nodes in an adept manner, thereby prolonging the network lifetime.

The prodigious growth of internet as an environment for learning has led to the development of enormous sites to offer knowledge to the novices in an efficient manner. However, evaluating the quality of those sites is a substantial task. With that concern, this paper attempts to evaluate the quality measures for enhancing the site design and contents of an e-learning framework, as it relates to information retrieval over the internet. Moreover, the proposal explores two main processes. Firstly, evaluating a website quality with the defined high-level quality metrics such as accuracy, feasibility, utility and propriety using Website Quality Assessment Model (WQAM) and secondly, developing an e-learning framework with improved quality. Specifically, the quality metrics are analyzed with the feedback compliance obtained through a Questionnaire Sample (QS). By which, the area of the website that requires improvement can be identified and then, a new e-learning framework has been developed with the incorporation of those enhancements.

Rapid improvement of electronic documents in World Wide Web has made overload to the users in accessing the information. Therefore, abstracting the primary content from numerous documents related to same topic is highly essential. Summarization of multiple documents helps in valuable decision-making in less time. This paper proposed a framework named Adept Multi-Document Summarization (AMDS) for efficient summarization of document, which achieves the aforementioned requirement. Here, the documents are preprocessed initially to remove the information that is less important. Summary of each preprocessed document is obtained through the sentence extraction process. Single document summarization is carried out based on graph model. A ranking method named Ingenious Ranking (IR) is proposed to rank and order the extracted single document summaries. It ranks the sentences in the generated summaries of each document and incorporates the individual summaries to generate a concise summary. Empirical results presented in this paper demonstrate the efficiency of the proposed AMDS framework.

Regression testing is a re-testing technique to test the changes, which is taken in the modified or enhanced application to ensure that the changes do not impairment the accessible behavior of the application. Modifications in the applications mainly focus on three types namely binding, process and interfaces. In order to accomplish the regression testing for a modified portion of an application, test cases are selected from a test suite. Selection, generation and prioritization of the test cases are more important and also it is a tough process in regression testing. In this article, we proposed a technique to automatically generate the test cases for testing the changes of various versions of BPEL (Business Process Execution Language) dataset. We construct a hierarchical test tree (HTT) for both the new and old versions composite services that are modified for an application and also for the unmodified. The changes are tracked by analyzing the control flow of both trees constructed above using the BPEL dataset. Test Case Prioritization Algorithm (TCPA), which uses multiple criteria are used to prioritize the tests cases. We analyzed the performance of the proposed technique and the experimental results showed that our method performs well than the earlier techniques.

Neural networks are a computational paradigm model of the human brain that has become popular in recent years. We have tried to address the problem of Glioma by creating a more accurate classifier which can act as an expert assistant to medical practitioners. Brain stem gliomas are now recognized as a heterogenous group of tumors. In this paper, proposed a prediction of Glioma in MR images using weight optimized neural network. Magnetic Resonance (MR) images are affected by rician noise which limits the accuracy of any quantitative measurements from the data. A recently proposed filter for rician noise removal is analyzed and adapted to reduce this noise in MR images. This parametric filter, named Non-Local Means (NLM), is highly dependent on setting its parameters. Experimental results reveal the efficacy of the adduced methodology as compared to the related work.

Abstract. Focusing on high-quality construction, and improving seismic performance of under-construction buildings on one hand, and rapid elimination of housing shortages and/or other spaces and buildings required in the country on the other hand, clarify application of the modern technologies instead of inefficient and traditional systems. Hence, the main aim of this study is to reorganize, prioritize, and determine the status of full construction systems using industrial production methods.\nIn this study, each of the technologies has been evaluated from two main structural and architectural perspectives. In order to obtain the predefined objective, the main element of the research has been studied within the three criteria of quality, economy and speed. It is hoped that every technology will find its special\nposition in the building industry in terms of capability of construction and operation.\nWith due observance to the above mentioned subjects, and in accordance with the results of the present study, common construction methods in the country have not met demands of mass housing construction. Among industrial construction systems, although Light Steel Frame (LSF) has obtained higher status than others have, however, it needs to be modified in order to improve its performance and obtaining better ranking among other technologies.

Water Quality Indices (WQIs) provide a simplified representation of monitoring data by aggregating several water quality parameters. Horton (1965) developed the first WQI, and since then at least 40 indices have been composed. Fuzzy Clustering (FC) is applied here in order to derive an efficient and flexible WQI. FC is a new approach based on fuzzy logic methodology in which the classification of information is determined by a fuzzy relationship, such as a Max-Min function. After selecting a fuzzy similarity relation, the approach is as follow: a fuzzy similarity matrix is established, the selected fuzzy relationship stabilizes it, a dynamic clustering chart is developed and, given a suitable threshold, the appropriate classification is determined. \nIn this work, the selected classification is related to a reach of the water body and is used to identify zones for water quality management. Therefore a general methodology for FC analysis is developed and illustrated with a case study of water quality evaluation for the Karoon River, the largest river in Iran. Many industrial and municipal point sources and agricultural non-point sources of pollution line the Karoon and have caused a high degree of degradation in the river. Hence, in this paper eleven indicators are analyzed to account for a range of water quality impacts. A significant issue in FC is selection of a suitable distance equation to determine the similarity matrix. In this work this problem is addressed by using four well-known equations: the Wang Peizhuang, Cosine, Single linkage, Tajrishy, Canbera Metric, City Block Metrics, and Minkowski Metrics functions. The results of applications of each of these functions are compared and a suitable method for the Karoon River is identified. Based on these results, water quality zoned maps are prepared.\nUnderstanding large and complex data sets and revealing underlying relations and phenomena, and visualizing major tendencies are too difficult. Making sense of data is an ongoing task of researchers and professionals in almost every practical endeavor. The age of information technology, characterized by a vast array of data, has enormously amplified this quest and made it even more challenging. Data collection anytime and everywhere has become the reality of our lives.

It was to determine some metal concentrations in some tissues of Capoeta trutta collected from four various sites (S1, S2, S3, S4) of the Keban Dam Lake, Turkey. The highest heavy metal level in all tissues was Fe except that in muscle, while Ni was the lowest except that in muscle. The lowest heavy metal levels were observed in all tissues of fish from site S4 for (P<0.05). There were statistically differences among fish from four sites for Fe, Mn, Pb and Ni in all the tissues (P<0.05), but no difference in Ni in muscle (P>0.05). Generally, the fish from S1, S2 and S3 showed the highest heavy metal levels than from S4. The highest levels of Fe (1064.67±487.06 mg kg-1dw) and Pb (18.27±1.25 mg kg-1dw) were obtained in liver tissues of fish caught from S2 and S3 (P<0.05), respectively. The highest levels of Mn (143.42±14.14 mg kg-1dw) and Ni (11.32±1.4 mg kg-1dw) were obtained in gills of fish caught from S2 (P<0.05), while Hg (30.42±11.04 mg kg-1dw) was in kidney of fish caught from S3. In conclusion, Capoeta trutta caught from Keban Dam Lake based on the higher levels of Pb and Hg, might be unsafe for human consumption.

Urdu is a lingua franca in Pakistan. It is our national language. It is associated with education and being educated in our country. In addition, it is the language of media in Pakistan. These and other factors seem to have brought about a change in the linguistic behavior of educated people speaking regional languages as their mother tongues. The study tries to bring to light this linguistic change through a questionnaire based survey. According to the findings of the study Urdu seems to have become the language of family communication among the educated native speakers of Saraiki and Punjabi in Bahawalpur. The survey was conducted in Bahawalpur among married people working at different state-run institutes. 90% of the respondents in the survey speak Saraiki and Punajbi as their mother tongues. 57% of the respondents speak Urdu with their spouses. 78% of the respondents speak Urdu with their children. 94% of the respondents think that they prefer to speak Urdu at home with their children because it is the medium of instruction of education in Pakistan. The study rounds off by discussing various social and linguistic implications of this change in the linguistic behavior of the people of the Southern Punjab.

This research work is devoted to general equilibria in abstract spaces, through the agency of the ideal points, fixed points of multifunctions, Isac’s cones, Choquet boundaries and applied mathematics for academic and industrialists engaged in eco - efficiency

Corn is one of important crop produces in Iran. Plant density and nitrogen levels have high effect on yield of this corp. In this research, the effect of plant density and nitrogen levels on single-cross704 corn physiological indices, were evaluated. A field experiment was carried out of Miyandoab agricultural research station 2012. Treatments were arranged in a factorial split experiment based on RCBD with four replications. The SC704 as the main plot and the plant densities (24, 19, 15.6 and 13.6 cm row distance) and nitrogen levels (200, 300, 400 and 500 kg.ha-1) were randomized in sub- plots. The results shows that, increasing of nitrogen fertile from 200 to 300 Kg.ha-1, leaf area index and crop growth rate were increased. But increasing of this fertile from 200 to 400 and 500 Kg. ha-1 has more effect on increasing of these indices. Between physiological indices, the relative growth rate has less affect from increasing of nitrogen fertile and has decreasing trend in growth season. From this research, by increasing of plant density, the leaf area index and crop growth rate were increased. The increasing of leaf area index causes to increasing of light adsorption and so increasing of plant photosynthesis capacity and crop yielding.\nThe major increasing of crop growthing was because of increasing of crop density and so leaf area index. Because of importance of leaf area index, crop growth rate and relative growth rate in increasing of grain yield, we concluded that the major increasing of grain yield because of crop density increasing, are depend on improving of physiological indices.

The future management of air traffic allows aircrafts choosing their own velocities,\naltitudes and directions. In aviation industry, this possibility is known as “free flight”.\nOne of the important issues in free flight method is conflict resolution. In successful\nfree flight, conflicts while maintaining satisfactory efficiency must be avoided. In this\npaper, we proposed a multi agent based conflict detection and resolution approach in\nfree flight method. We selected aircrafts and ground flight path controllers as agents\nthroughout the airspace, respectively called “AA” and “FPCA”. This type of agent\nselection provides a proper balance between distributed and centralized authority in\norder to solve air traffic conflicts and this is one of the merits of the system. FPCA\nAgents by negotiation with each other, map the situation of the airspace (in their vision\ndomain) to a directed graph. After some conversion on mapped graph, agents color the\ncorresponding graph using Particle Swarm Optimization (PSO) algorithm. There are\nmany benefits to using such a system include delay reduction, passenger comfort, safety\nand speed increase, travel time reduction and less fuel consumption. The proposed\nsystem not only proposed for free flight method but also can be use as a tool beside the\ncurrent air traffic management system without completely replaces it. The proposed\nmethod is implemented and tested by using different common test cases. The\nexperimental results show high efficiency of the system.