Volume 11, Number 2

In this paper different classification methods are compared using base and meta(Combination of Multiple Classifier for training) level classifiers, for the fruitful diagnosis of Lower Back Pain. The Lower Back Pain becomes chronic with age, so needs to be correctly diagnose with symptoms in the early age. Five independent classifiers were implemented at base level and meta level. At meta level, five combinations of different classifiers were implemented, using voting technique. According to the scores, the overall classification using Naïve Bayes and Multilayer Perceptron got the maximum efficiency 83.87%. The purpose of this paper is to diagnose healthy individuals efficiently. To carry out study the Lower Back Pain Symptoms Dataset is used from very famous platform for predictive modeling, Kaggle. The experiments were carried out in WEKA (Waikato Environment for Knowledge Analysis), suite of machine learning software¹.

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Distributed structure of programming and computing has evolved in all facets of development and spawned a new era of distributed computing. In these structures, the isolated processing nodes have been networked to form a powerful processing and communication device. Now, they need an integrated infrastructure for communication that is capable of providing and developing strong and secure mobility features. The mobile agent technology is becoming a promising solution for widely distributed systems like the Internet. Mobile agent based infrastructure is capable of forming migratory environment efficiently using the network resources. The mobile agent is software code capable of moving closer to the required resource in contrast to systems that incorporate the mobility of non-executable code only. It is also required for various agent-oriented languages to support architectural heterogeneity and less or no dependency on the previous system once an agent is transmitted to another system in the network. This paper reviews the architectural components that exist and required for agent-based systems. It also reviews various software components of universal mobile agent system and explores some aspects of migration and intercommunication of agent-oriented approaches.

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With the continuous advancement in technology, web technologies have reached to a new height. Enterprise applications are meant to be the basic need of today’s world which aims to produce results that are highly reliable, portable and adaptable. With these enormous features, they needed the storage mechanism which could handle and store the data effectively. The storage system thus required was a database management system but again technical knowledge was required to make things work appropriately.  However, this approach was the traditional one which requires data to be stored in tabular format whereas Object oriented architecture has taken the programming language to a whole new technical phase for which the traditional RDBMS will not efficiently accomplish the expected job. To fulfill this gap in the literature, Object Relational Mapping is emerged as a solution to provide which provide comparative technical features effortlessly. These characteristics simplify and make the mapping of objects in object-oriented programming languages more flexible, efficient and easy to use.Therefore, we propose in this paper that Object relational Modeling (ORM) relates each object of object oriented languages to corresponding rows in the table.

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The rapid and revolutionary advancement in technology has increased the demand for advanced ubiquitous mobile applications in our daily lives. Home automation system uses collective smart technology to elevate sphere of security and human living standards. Wireless Smart home systems have been prototyped by researchers to realize different applications in vast contexts. In this paper we propose a keyless smart home security system which uses Bluetooth as a communication protocol to automate door locks based on a security code and predefined user credentials. The system combines Android phone as a signal sender to dispatch the input signal from an end users side, Bluetooth communication module as signal receiver, ARDUINO microcontroller as CPU and servo motor and light emitting diodes as an output. The system integrates two modules: one of which is Arduino microcontroller which is responsible for authentication and verification of security code and allows servo motor to process the output according to the received input. The second is android Application which provides an interface to the user to set credentials and security code which is then transmitted to the Arduino microcontroller via Bluetooth technology. Since Arduino and Android are open source, hence implementation rate of the proposed system is inexpensive and feasible.

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The Shipboard Training in the selected Maritime Institution uses a distributed documentation partially manual process in monitoring the performance of the cadets that most likely causes the delay and inconsistency of reports. Their Department uses any Social Media Website in assessing/validating the reports on the performance of the cadets. The Department of Shipboard Training receives a summary of the report through  Social Media Website.

Technology nowadays is overwhelming that resulted to change faster from a stand-alone system to a web based technology which is capable of supporting almost all of the computerized transactions using an open source mobile applet and Content Management Systems. Most of the organizations have embraced technology and have developed exceptional online programs that provide easy access and massive communication. These maritime schools entirely take after the IMO model courses as proclaimed by the 1978 tradition on Standards of Training, Certification and Watch keeping for seafarers (STCW), as altered in 1995, and are the main ones permitted by our legislature to lead and regulate baccalaureate courses with 3-year scholastics in addition to 1 year managed shipboard apprenticeship for deck and engine cadets.

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Capacitated Vehicle Routing Problem (CVRP) is anoptimization task where customers are assigned to vehicles aiming that combined travel distances of all the vehicles as minimum as possible while serving customers. A popular way among various methods of CVRP is solving it in two phases: grouping or clustering customers into feasible routes of individual vehicles and then finding their optimal routes. Sweep is well studied clustering algorithm for grouping customers and different traveling salesman problem (TSP) solving methods are commonly used to generate optimal routes of individual vehicles. This study investigates effective CVRP solving method based on recently developed adaptive Sweep and prominent Swarm Intelligence (SI) based TSP optimization methods. The adaptive Sweep cluster is a heuristic based adaptive method to select appropriate cluster formation starting angle of Sweep. Three prominent SI based TSP optimization methods are investigated which are Ant Colony Optimization, Producer-Scrounger Method and Velocity Tentative Particle Swarm Optimization (VTPSO). Genetic Algorithm is also considered since it is the pioneer and well-known population based method. The experimental results on two suites of benchmark CVRPs identified the effectiveness of adaptive Sweep plus SI methods in solving CVRP. Finally, adaptive Sweep plus the VTPSO is found better than other tested methods in this study as well as several other prominent existing methods.

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Matching mug shot photos to forensic sketches drawn according to verbal descriptions of eyewitnesses is a decisive point for criminal investigations. However, the incapability of a witness to precisely describe the appearance of a suspect and his/her reliance on a subjective aspect of the description often lead to imprecise and inadequate sketches. This necessitates the development of robust automated matching methods such that least dependency exists on the quality of original sketches. The focus of the paper is on enhancing the preprocessing phase, before the matching phase is applied, by generating a population of sketches out of each initial sketch via applying geometrical changes in facial areas. The population is then optimized using Genetic Algorithms (GA) by adopting the Structural SIMilarity (SSIM) index as the fitness function. The matching is finally applied to the best sketch produced by GA by employing the Local Feature-based Discriminant Analysis (LFDA) framework. The efficiency of the proposed hybrid approach in achieving correct matchings is evaluated against 88 sketch/photo pairs provided by the Michigan State Police Department and Forensic Art Essentials, and 100 sketch/black-and-white photo pairs from FERET database. The experimental results indicate that our proposed approach obtains fairly better results relative to the LFDA framework. Furthermore, we notice a significant improvement in the retrieval rate if sketch/photo pairs are first cropped to central facial areas before a matching technique is applied.

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