Survey on Multi Agent Energy Efficient Clustering Algorithms in Wireless Sensor Networks

In the last few years, there are many applications for Wireless Sensor Networks (WSNs). One of the main drawbacks of these networks is the limited battery power of sensor nodes. There are many cases to reduce energy consumption in WSNs. One of them is clustering. Sensor nodes partitioned into the clusters so that one is chosen as Cluster Head (CH). Clustering and selection of the proper node as CH is very significant in reducing energy consumption and increasing network lifetime. In this paper, we have surveyed a multi agent clustering algorithms and compared on various parameters like cluster size, cluster count, clusters equality, parameters used in CHs selection, algorithm complexity, types of algorithm used in clustering, nodes location awareness, inter-cluster and intra-cluster topologies, nodes homogeneity and MAC layer communications

Localisation and Pre-calculation for Anti-missile Defence Shield System

One of the most important problems in anti-missile systems is localisation ambulatory missiles’ defence sites along with fixed missiles’ defence sites in best positions to destroy enemy’s missiles. For localisation, there are lots of constraints and consumptions, which should be considered to making predictions in missiles behaviours. An optimum algorithm for localisation of the missiles’ defence sites is provided. Predictions of attackers’ missiles behaviors for assisting real-time defending operations in the defender sites is also provided. One simulator for finding the best places to locate ambulatory missiles’ defence sites presented. This simulator considers fixed and ambulatory missiles’ defence sites along with their parameters to provide best solutions by relying on modified genetic algorithm.

An imperialist competitive algorithm for the winner determination problem in combinatorial auction

Winner Determination problem (WDP) in combinatorial auction is an NP-complete problem. The NP-complete problems are often solved by using heuristic methods and approximation algorithms. This paper presents an imperialist competitive algorithm (ICA) for solving winner determination problem. Combinatorial auction (CA) is an auction that auctioneer considers many goods for sale and the bidder bids on the bundle of items. In this type of auction, the goal is finding winning bids that maximize the auctioneer’s income under the constraint that each item can be allocated to at most one bidder. To demonstrate, the postulated algorithm is applied over various benchmark problems. The ICA offers competitive results and finds good-quality solution in compare to genetic algorithm (GA), Memetic algorithm (MA), Nash equilibrium search approach (NESA) and Tabu search

Nanoparticles of SBA-15 synthesized from corn silica as an effective delivery system for valproic acid

AbstractThe aim of this work is to study the behavior of SBA-15 synthesized using amorphous silica extracted from different parts of the corn plant, as drug carriers. The synthesized nano-silica and mesoporous SBA-15 were characterized by x-ray diffraction (XRD), thermogravimetric analysis (TGA), x-ray fluorescence (XRF), scanning electron microscopy (SEM), transition electron microscopy (TEM), Fourier transform infrared (FT-IR), and N2 isotherms. SEM and TEM images showed that SBA-15 is formed by spongy agglomerated nanoparticles revealing the growth of hexagonal shaped domains. The synthesized SBA-15 was modified with cetyltrimethylammonium bromide (CTAB), to increase the carriers' capacity. The SBA-15 and modified SBA-15 show hexagonal order with decreasing pore size from 7.5 nm to 5.5 nm after modification, and surface area from 488 m2/g to 127.75 m2/g in modified SBA-15. Finally, SBA-15 and modified SBA-15 were used as a carrier for valproic acid. The release studies were carried out at λ max = 205 nm by UV-Vis. The results indicated that the release of the drug increased with increasing pH and time. As the drug moves, the digestive tract increases from the stomach to the intestine, and a pH of 6.8 resembling the best results as compared with pH 1.2

W_SR: A QoS Based Ranking Approach for Cloud Computing Service

Cloud computing is a kind of computing model that promise accessing to information resources in request time and subscription basis. In this environment, there are different type of user’s application with different requirements. In addition, there are different cloud Service providers which present spate services with various qualitative traits. Therefore determining the best cloud computing service for users with specific applications is a serious problem. Service ranking system compares the different services based on quality of services (QoS), in order to select the most appropriate service. In this paper, we propose a W_SR (Weight Service Rank) approach for cloud service ranking that uses from QoS features. Comprehensive experiments are conducted employing real-world QoS dataset, including more than 2500 web services over the world. The experimental results show that execution time of our approach is less than other approaches and it is more flexible and scalable than the others with increase in services or users

An ensemble feature selection method to detect web spam

Feature selection is an important issue in data mining, and it is used to reduce dimensions of features set. Web spam detection is one of research fields of data mining. With regard to increasing available information in virtual space and the need of users to search, the role of search engines and used algorithms are important in terms of ranking. Web spam is an illegal method to increase mendacious rank of internet pages by deceiving the algorithms of search engines, so it is essential to use an efficient method. Up to now, many methods have been proposed to face with web spam. An ensemble feature selection method has been proposed in this paper to detect web spam. Content features of standard dataset of WEBSPAM-UK2007 are used for evaluation. Bayes network classifier is used along with 70-30% training-testing spilt of dataset. The presented results show that Area Under the ROC Curve (AUC) of this method is higher than the other methods reported in this paper. Moreover, the best values of evaluation metrics in our proposed method are optimal in comparison to the other methods reported in this paper. In addition, it improves classification metrics in comparison to basic feature selection methods