Journal of Computer Sciences and Applications

Comparison of Kernel Selection for Support Vector Machines Using Diabetes Dataset

by Tapas Ranjan Baitharu, Subhendu Ku. Pani and Sunil kumar Dhal

Conference Paper

One of the major problems in the study of Support vector machine (SVM) is kernel selection, that’s based necessarily on the problem of deciding a kernel function for a particular task and dataset. By contradiction to other machine learning algorithms, SVM focuses on maximizing the generalisation ability, which depends on the empirical risk and the complexity of the machine. We were focused on SVM trained using linear, polynomial, puk and Radial Basic Function (RBF) kernels. A preliminary study has been made between SVM using the best choice of kernel. Results had revealed that SVM trained using Linear Kernel is the best choice for dealing with Diabetes dataset.

Journal of Computer Sciences and Applications. 2015, 3(6), 181-184. DOI: 10.12691/jcsa-3-6-14
Pub. Date: January 04, 2016

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Big Data Processing: Big Challenges and Opportunities

by Neelamani Samal and Nilamadhab Mishra

Conference Paper

With the rapid growth of emerging applications like social network, semantic web, sensor networks and LBS (Location Based Service) applications, a variety of data to be processed continues to witness a quick increase. Effective management and processing of large-scale data poses an interesting but critical challenge. Recently, big data has attracted a lot of attention from academia, industry as well as government. This paper introduces several big data processing techniques from system and application aspects. First, from the view of cloud data management and big data processing mechanisms, we present the key issues of big data processing, including definition of big data, big data management platform, big data service models, distributed file system, data storage, data virtualization platform and distributed applications. Following the Map Reduce parallel processing framework, we introduce some MapReduce optimization strategies reported in the literature. Finally, we discuss the open issues and challenges, and deeply explore the research directions in the future on big data processing in cloud computing environments.

Journal of Computer Sciences and Applications. 2015, 3(6), 177-180. DOI: 10.12691/jcsa-3-6-13
Pub. Date: December 31, 2015

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17623 Views5618 Downloads1 Citations

Ground Water Prediction Using Bacterial Foraging Optimization Technique

by Dixit Prasanna Kumar and Sahoo Archana

Conference Paper

Ground water in the water located beneath the earth’s surface in soil pore spaces and in the patterns of rock formations. The ways to determine the level of ground water is called ground water prediction. The ground water level is the important factors which affect the development of national economy and society. It is needed to predict ground water because in recent times too much water is pumped out from under ground . In the State of Odisha (India), more than 85% of geographical area falls under consolidation formations with low groundwater development status. In places like Puri, Bhubaneswar ground water can be found at around 200ft down but in case of rocky areas like Keonjhar, western Odisha such as Koraput, Titlagarh etc., it is very hard to reach the ground water level which is very deep down the earth surface. Another problem is the authorities from water resource development use to dig unnecessary pot holes in search of ground water without having any information about the availability of water. These pot holes create problems for the local people. It leads to wastage of both time and money of government. So this paper proposes a method through this we can overcome the above problem. In this paper the availability of ground water was predicted by using some prediction techniques like linear regression, multi-linear regression. Regression analysis can be used to model the relationship between one or more independent or predictor variables and a dependent or response variable (which is continuous-valued). In other words, a regression model is a mathematical model that predicts a continuous response variable. And also we are introducing the prediction of ground water by using a nature inspired Bacterial Foraging Optimization (BFO). This technique is proposed by K.M. Passino in 2002 to handle complex problems of the real world . Bacterial Foraging Optimization Algorithm (BFO) is inspired by the foraging and chemotactic phenomenon of bacteria. Bacterial Foraging Optimization (BFO) algorithm is a new class of biologically stochastic global search technique based on the foraging behaviour of E. coli bacteria. This method is used for locating, handling, and ingesting the food. During foraging, a bacterium can exhibit two different actions: tumbling or swimming which can be simulated for predicting the ground level water.

Journal of Computer Sciences and Applications. 2015, 3(6), 172-176. DOI: 10.12691/jcsa-3-6-12
Pub. Date: December 31, 2015

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11863 Views4231 Downloads

A Review on Mobile Agent Technology and Its Perspectives

by Rajesh Kumar, S Niranjanr1 and Yashpal Singh

Conference Paper

No doubt, the usages of mobile agent and mobile phone technologies are rapidly increased. The mobile agent has a promising room in the industry area. Unfortunately, this technology faces some security problems from mobile agents and hosts sides. Two of the fundamental issues in designing protocols for message passing between mobile agents (MAs) are tracking the migration of the target agent and forwarding messages to it. Even with an ideal fault-free network-transport mechanism, messages can be dropped during MA migration. Therefore, in order to provide reliable message delivery, protocols need to overcome message loss caused by asynchronous operations of agent migration and message forwarding. As mobile devices and third generation mobile networks have become a reality, location based services are thought to be a major growing area. Mobile devices are given context sensitiveness so that they can be aware of the users/services surrounding physical environment and state. In this paper we propose message forwarding approaches, namely push and pull, are explored to design adaptive and reliable message delivery protocols.Also location aware services scheme by using an agency, which helps in discovering the required services for the mobile users. The agency consists of five agents: Manager Agent (MA), Route Monitoring Agent (RMA), Local Service Management Agent (LSMA), Global Service Management Agent (GSMA) and Area Monitoring Agent (AMA).

Journal of Computer Sciences and Applications. 2015, 3(6), 166-171. DOI: 10.12691/jcsa-3-6-11
Pub. Date: December 31, 2015

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Emergence of Big Data on Cloud Computing (An Insight to Current and Future)

by Amar Nath Singh and Rakesh Kumar Rath

Conference Paper

In Database the prime objective of database is to arrange the data in a well designed manner so that the data should be stored and retrieved effectively as and when required. But in traditional database like DBMS the major fault was scalability. So in this database management systems (DBMS) the following problems are arise always such as, 1. Update intensive application workloads, and 2. Decision support systems for descriptive and deep analytics. These are a critical part of the cloud infrastructure and play an important role in ensuring the smooth transition of applications from the traditional enterprise infrastructures to next generation cloud infrastructures. So these scalability natures of the data base cause a lot of problem for data integration when the amounts of data were huge. This paper presents an organized picture of the challenges faced by application developers and DBMS designers in developing and deploying internet scale applications. We have designed this paper on the basis of the following aspects, such as: (i) For supporting update heavy applications, and (ii) For ad-hoc analytics and decision support. Here we also focus on providing an in-depth analysis of systems for supporting update intensive web-applications which are mostly now a day’s used in the companies and provide a survey of the state-of-the art in this domain. We have tried to crystallize the design aspect of choices made by considering some large scale database management systems, analyze the application demands and access patterns, and enumerate the desiderata for a cloud-bound DBMS.

Journal of Computer Sciences and Applications. 2015, 3(6), 162-165. DOI: 10.12691/jcsa-3-6-10
Pub. Date: December 31, 2015

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Effective Clustering Algorithm of Wireless sensor network through clustered Mobile agents

by Kamla Deep, S Niranjanr and Yashpal Singh

Conference Paper

In wireless sensor networks, the mobile agent technology is used in data transmission from one cluster to another cluster. The Optimization of mobile agent in the routing within the clustering algorithm for wireless sensor networks to further reduce the amount of data transfer. the main objectives of wireless sensor network design is to improve the energy efficiency & effective utilization of sensor nodes to prolong the lifespan of a wireless network .This paper presents an effective clustering algorithm, which is an extension to the LEACH routing algorithm., this algorithm fully utilizes the location information of network nodes in routing to reduce the routing cost. Through a clustering approach of intelligent mobile agents, it is possible to reduce the cost of time for each individual agent, here the problem of Multiple Clustering of Mobile Agents (MCCMA) where the decision is to cluster mobile agents such that a group of similar intelligent mobile agents will visit a group of similar sensor nodes are compare with location based clustering algorithm of wsn. both of Simulation results indicate that these algorithm & approach of mobile agent & wireless sensor network Nodes can have balance nodes' energy consumption and prolong the network's life span. It also has good extensibility & stability

Journal of Computer Sciences and Applications. 2015, 3(6), 154-161. DOI: 10.12691/jcsa-3-6-9
Pub. Date: December 31, 2015

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28306 Views7981 Downloads1 Likes

JADE: A Platform for Running Mobile Agents in Java

by S Sonia, S Niranjanr and Yashpal Singh

Conference Paper

Mobile agents are programs that can be dispatched from one computer and delivered to a remote computer for execution. Arriving at the remote computer, they present their credentials and obtain access to local services and data. This paper gives an overview of what the mobile agents are, what they should do and how they can be implemented in Java. It seems to be the best available language for making mobile agents roaming through the Internet for the time being. We describe our Java-based mobile agent platform to create mobile agent called JADE(Java Agent Development Environment) and present its programming interface. JADE can then be considered an agent middle-ware that implements an Agent Platform and a development framework. It also presents the JADE software describing its intended uses, hardware /software requirement as well as being a walkthrough of JADE internal architecture.

Journal of Computer Sciences and Applications. 2015, 3(6), 147-153. DOI: 10.12691/jcsa-3-6-8
Pub. Date: December 31, 2015

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4708 Views2705 Downloads1 Likes

A New Approach toward Locating ERP Components on Cloud Computing Architecture

by Jharana Paikaray, Smaranika Mohapatra and Santosh Kumar Rath

Conference Paper

Nowadays, Cloud Computing [1] is an emerging phenomenon, which is subject of discussion in many Enterprises. Therefore, numerous studies have been done in this context and some well-known IT solution providers such as IBM and Oracle have provided a particular cloud architecture which can be deployed in cloud environments. On the other hand, modern Enterprises looking for standard structures and they use standard best practice LANSA ERP Frameworks and A McKinsey 7S Model-Based Framework for ERP [7]. So, using these best practice frameworks and ERP systems in cloud architecture can lead to more popularity of cloud environments and increase reliability of organizational users. The purpose of this paper is to provide a new approach toward locating a suitable ERP system in management layer of cloud computing architecture with the aim of integrate and standardize cloud environments and improving cloud architecture. This architecture is finally compared with other architecture in a form of statistical graphs.

Journal of Computer Sciences and Applications. 2015, 3(6), 143-146. DOI: 10.12691/jcsa-3-6-7
Pub. Date: December 30, 2015

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13763 Views3534 Downloads1 Likes

Future Trends in Cloud Computing and Big Data

by Smaranika Mohapatra, Jharana Paikaray and Neelamani Samal

Conference Paper

In recent years, accompanied by lower prices of information and communications technology (ICT) equipment and networks, various items of data gleaned from the real world have come to be accumulated in cloud data centers. There are increasing hopes that analysis of this massive amount of data will provide insight that is valuable to both businesses and society. Since tens of terabytes (TBs) or tens of petabytes (PBs) of data, big data, should be handled to make full use of it, there needs to be a new type of technology different from ordinary ICT. It revolves around different areas of analytics and Big Data. Through a detailed survey, we identify possible gaps in technology and provide recommendations for the research community on future directions on Cloud-supported Big Data computing and analytics solutions.

Journal of Computer Sciences and Applications. 2015, 3(6), 137-142. DOI: 10.12691/jcsa-3-6-6
Pub. Date: December 30, 2015

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Performance Evaluation of Big Data by Applying Ant Colony Optimization Techniques

by Prasad Suman Sourav, Mohanty Anita and Mishra Sambit Kumar

Conference Paper

Big data is a collection of huge amount of data. As the world is changing rapidly, many new technologies, devices such as smart phones, social networking sites have been evolved due to which the amount of data produced day by day is increasing rapidly. It has become a problem for many companies to process such a huge amount of data using traditional computing techniques. The collection of each and every data of a company(homogeneous or heterogeneous data) is called big data. Research is being carried out to find an appropriate algorithm to find an optimal solution when the size of the database increases. Most of the data we are handling today are of unstructured type like the data in social sites, research engines, blogs etc. The challenges we face with big data today is not only to store or link but also to retrieve, update and analyze them too. Now this big data is needed to be processed on some platform. This platform on which big data is operated is known as cloud computing. Anyone may process big data on cloud computing without the need of any specific software. Cloud computing can expand and shrink as per the need of storage. Cloud computing mainly provides resources as and when needed. As big data is also a kind of resource so it is also available through cloud computing. In this paper, ant colony optimization technique may be applied to evaluate the performance while processing queries in big data.

Journal of Computer Sciences and Applications. 2015, 3(6), 134-136. DOI: 10.12691/jcsa-3-6-5
Pub. Date: December 30, 2015

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10723 Views3301 Downloads8 Likes

Performance Evaluation of Complex Data Sets with Heterogeneity Using Particle Swarm Optimization

by Mishra Jyoti Prakash and Mishra Sambit Kumar

Conference Paper

Traditional query processing applications may not be adequate with large or complex data sets with heterogeneity. Challenges to this context may include analysis, capture, search, sharing, storage, transfer, visualization, and information privacy. Cloud computing refers to the practice of transitioning computer services such as computation or data storage to multiple redundant offsite locations available on the internet, that allows application software to be operated using internet enabled devices. Cloud computing usually focuses on maximizing the effectiveness of the shared resources. Cloud resources are generally not only shared by multiple users but are dynamically reallocated as per demand. The present cloud services realize improved execution efficiency by aggregating application execution environments. Now a day it is in the phase of expanding from application aggregation and sharing data aggregation and utilization. In this paper, the query evaluation strategies have been proposed by considering partially correlated data in heterogeneous databases of concern. The main idea behind this strategy is to retrieve the data from heterogeneous databases linked with the declarative query I interface implementing data access methods and optimization mechanisms. The indexing and query processing strategies may be applied to the integrated components of the database systems with heterogeneity. As a result, it may be convenient and useful to analyze and evaluate the data using efficient functional evaluations implemented inside the database systems. Usually the index structures are generated to coordinate the result analysis without duplicating the query evaluation result. It is also aimed to provide an end-to-end solution for scalable access to big data integration, where end users may formulate queries based on a familiar conceptualization of the domain. It has also been proposed to process the distributed query in the heterogeneous environment to evaluate scalable solution for executing queries in the cloud.

Journal of Computer Sciences and Applications. 2015, 3(6), 130-133. DOI: 10.12691/jcsa-3-6-4
Pub. Date: December 30, 2015

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13899 Views4024 Downloads4 Likes

Significance of Processing Queries and Implementation of Cipher in Remote Location

by Mishra Suchismita, Mishra Bibhuti Bhusan and Mishra Sambit Kumar

Conference Paper

Confidentiality, Integrity and Availability are the three key attributes in preserving the essence of the data being used in remote exchanges between users & servers. Always there is need of maintaining a balance between the access and the protection of the system dealing with data. The encryption concept also proved as a powerful tool helps in enhancing the integrity of the remote data. The database server, clients and high speed Internet services are very much essential for processing data as well as optimizing queries in remote locations. Therefore security measures must be taken care, while processing private queries. It has been observed that cloud computing plays a vital role of preserving queries while processing and maintaining the privacy of data. In this paper, it is primarily focused regarding the security measures of data while processing queries in remote locations where the position of database server is not known and implementation of cipher in data transfer.

Journal of Computer Sciences and Applications. 2015, 3(6), 127-129. DOI: 10.12691/jcsa-3-6-3
Pub. Date: December 30, 2015

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8440 Views2220 Downloads

Graph Theory in an Object Oriented Approach

by Dixit Prasanna Kumar, Sahoo Archana and Badajena Tushar Kumar

Conference Paper

Many real world situations can be describe by means of a diagram consisting of set of points connected by lines. Graph theory has many applications in different field. This paper show how various elements involved in graph theory including graph representations using computer system such as object oriented concept.

Journal of Computer Sciences and Applications. 2015, 3(6), 123-126. DOI: 10.12691/jcsa-3-6-2
Pub. Date: December 30, 2015

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12300 Views2916 Downloads

Forcasting the Impact of Surface Mining on Surroundingusing Cloud Computing

by Amar Nath Singh, Medini Srinivas and Bikash Narayan Naik

Conference Paper

Mining is an important process by using which we are extracting the most of the valuable product from the core of the earth. It is the process which deals with many steps of extraction. Here we have taken the cases of Danbad and Jharia, which now a day’s found in the state of Jharkhand. The mining projects vary according to the type of metals or materials to be extracted from the earth. The majority of proposed mining projects involve the extraction of ore deposits such as copper, nickel, cobalt, gold, silver, lead, zinc, molybdenum, and platinum [2]. The environmental impacts of large-scale mining projects involving these metal ores are the subject of this Guidebook. The Guidebook does not discuss the mining of ores that are extracted using strip mining methods, including aluminum (bauxite), phosphate, and uranium [4]. The Guidebook also does not discuss mining involving extraction of coal or aggregates, such as sand, gravel, and limestone.

Journal of Computer Sciences and Applications. 2015, 3(6), 118-122. DOI: 10.12691/jcsa-3-6-1
Pub. Date: December 30, 2015

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10671 Views3200 Downloads1 Citations

Volume 3, Issue 6