International Journal of Computer and Applications

In this paper, a novel text clustering method, improved krill herd algorithm with a hybrid function, called MMKHA, is proposed as an efficient clustering way to obtain promising and precise results in this domain. Krill herd is a new swarm-based optimization algorithm that imitates the behavior of a group of live krill. The potential of this algorithm is high because it performs better than other optimization methods; it balances the process of exploration and exploitation by complementing the strength of local nearby searching and global wide-range searching. Text clustering is the process of grouping significant amounts of text documents into coherent clusters in which documents in the same cluster are relevant. For the purpose of the experiments, six versions are thoroughly investigated to determine the best version for solving the text clustering. Eight benchmark text datasets are used for the evaluation process available at the Laboratory of Computational Intelligence (LABIC). Seven evaluation measures are utilized to validate the proposed algorithms, namely, ASDC, accuracy, precision, recall, F-measure, purity, and entropy. The proposed algorithms are compared with the other successful algorithms published in the literature. The results proved that the proposed improved krill herd algorithm with hybrid function achieved almost all the best results for all datasets in comparison with the other comparative algorithms.

Hybrid clustering analysis using improved krill herd algorithm

Financial fraud detection applying data mining techniques: A comprehensive review from 2009 to 2019

We believe that sharing data among multiple users is perhaps one of the most engaging features that motivates cloud storage. A unique problem introduced during the process of public auditing for shared data in the cloud is how to preserve identity privacy from the TPA, because the identities of signers on shared data may indicate that a particular user in the group or a special block in shared data is a higher valuable target than others. Abstract—With cloud storage services, it is common place for data to be not only stored in the cloud, but also shared across multiple users. However, public auditing for such shared data — while preserving identity privacy— remains to be an open challenge. In this paper, we propose the first privacy-preserving mechanism that allows public auditing on shared data stored in the cloud. In particular, we exploit ring signatures to compute the verification information needed to audit the integrity of shared data. With our mechanism, the identity of the signer on each block in shared data is kept private from a third party auditor (TPA), who is still able to publicly verify the integrity of shared data without retrieving the entire file. Our experimental results demonstrate the effectiveness and efficiency of our proposed mechanism when auditing shared data. mechanism for cloud data, so that during public auditing, the content of private data belonging to a personal user is not disclosed to the third party auditor.

/pdf/oruta-privacy-preserving-public-auditing-for-shared-data-in-2sg8k05207.pdf

Oruta: Privacy- Preserving Public Auditing for Shared Data in the Cloud

Context: Quality assurance effort, especially testing effort, is often a major cost factor during software development, which sometimes consumes more than 50% of the overall development effort. Consequently, one major goal is often to reduce testing effort. Objective: The main goal of the systematic mapping study is the identification of existing approaches that are able to reduce testing effort. Therefore, an overview should be presented both for researchers and practitioners in order to identify, on the one hand, future research directions and, on the other hand, potential for improvements in practical environments. Method: Two researchers performed a systematic mapping study, focusing on four databases with an initial result set of 4020 articles. Results: In total, we selected and categorized 144 articles. Five different areas were identified that exploit different ways to reduce testing effort: approaches that predict defect-prone parts or defect content, automation, test input reduction approaches, quality assurance techniques applied before testing, and test strategy approaches. Conclusion: The results reflect an increased interest in this topic in recent years. A lot of different approaches have been developed, refined, and evaluated in different environments. The highest attention was found with respect to automation and prediction approaches. In addition, some input reduction approaches were found. However, in terms of combining early quality assurance activities with testing to reduce test effort, only a small number of approaches were found. Due to the continuous challenge of reducing test effort, future research in this area is expected.

http://romisatriawahono.net/lecture/rm/survey/software%20engineering/Software%20Testing/Elberzhager%20-%20Reducing%20test%20effort%20-%202012.pdf

Reducing test effort: A systematic mapping study on existing approaches

Specific crime in the banking system is credit card fraud. Credit card usage has been increased due to the rapid growth of E-commerce techniques. Credit card fraud also increased at the same time. Prevention is better than detection. So the existing system prevented the credit card fraud by identifying fraud in the application of the Credit card. Due to the limitation of the existing system, this paper proposed new algorithm along with the existing algorithm. Scalability issues, extreme imbalanced class and time constraints are the limitation of existing systems. Those limitations are overcome by hybrid support vector machine (HSVM) along with communal and spike detection for credit card application fraud detection. HSVM is the most used method for the pattern recognition and classification.

Prevention of credit card fraud detection based on HSVM

Cloud computing is a model for conveying data innovation benefits in which assets are recovered from the web through online devices and applications, instead of an immediate association with a server. Clients can set up and boot the required assets and they need to pay just for the required assets. Subsequently, later on giving a component to a productive asset administration and the task will be a vital target of Cloud computing. Load balancing is one of the major concerns in cloud computing, and the main purpose of it is to satisfy the requirements of users by distributing the load evenly among all servers in the cloud to maximize the utilization of resources, to increase throughput, provide good response time and to reduce energy consumption. To optimize resource allocation and ensure the quality of service, this article proposes a novel approach for load-balancing based on the enhanced ant colony optimization.

A Novel Approach of Load Balancing and Task Scheduling Using Ant Colony Optimization Algorithm

Background/Objectives: In this paper, we propose the speech recognition of tamil words from dump mute persons with NAM sensor. Methods/Statistical analysis : The NAM sensor collects the speech signal of the tamil words frequently used in day-to-day life. These frequently used words are classified using fuzzy logic, based on syllables and the words are recognized. Findings: Until now, the NAM speech recognition was implemented only for vowels. From the 50 sample of speech sound, we attained 85% of accuracy in recognition. Application/Improvements: System helps in recognizing the tamil words from dump mute persons.

Fuzzy Logic based NAM Speech Recognition for Tamil Syllables

Cloud computing is a combination of several key technologies that have evolved and matured over the years. Cloud computing has a potential for cost savings to the enterprises but the security risk are also enormous. Cloud computing weakness include list of issues such as the security and privacy of business data being hosted in remote 3rd party data centers, being lock-in to a platform, reliability/performance concerns, and the fears of making the wrong decision before the industry begins to mature. We show Successful implementation of cloud computing in an enterprise requires proper planning and understanding of emerging risks, threats and possible countermeasures. This paper show how we secure the cloud security, privacy and reliability when a third party is processing sensitive data. In this paper, we have discussed security risks and concerns in cloud computing and enlightened steps that an enterprise can take to reduce security risks and protect their resources.

/pdf/survey-on-security-issues-and-solutions-in-cloud-computing-14bsw4forr.pdf

Survey on Security Issues and Solutions in Cloud Computing

Electrical Impedance scanning (EIS) is a new technique in which moderate variations in capacitance values are reflected by the cells of various type of normal membrane. The malignant membrane, in contrast, in EIS demonstrates significant capacitance relaxation phenomena concomitant with α dispersion in the low audio frequency range. The author has endeavored to establish the above stated phenomena. In his experimental setup, the lipoprotein constituent of the membrane was dissolved in acetone solvent and the interaction of the dissolved lipoprotein in the presence of electrical stimuli in the lower audio frequency range at room temperature of about 25oC was studied. The capacitance relaxation phenomena concomitant with α dispersion in the malignant membrane for subjects below and above 50 years has been simulated in MATLAB 6.5. The model incorporates a modified homeostat comprising of a homeostat and transduction phase in the feedback path and it represents the interaction of the lipoprotein in a malignant membrane associated with α dispersion mediated through capacitance relaxation phenomena. Results from the output of the model are in close conformity with the capacitance relaxation phenomena, which suggest an adjunctive detection modality in the differentiation of membrane malignancy that is equivocal on Ultrasonography.

/pdf/modeling-of-capacitance-relaxation-phenomenain-a-malignant-3hc67oldv3.pdf

G. Gunasekaran

Papers

Prevention of credit card fraud detection based on HSVM

A Novel Approach of Load Balancing and Task Scheduling Using Ant Colony Optimization Algorithm

Fuzzy Logic based NAM Speech Recognition for Tamil Syllables

Survey on Security Issues and Solutions in Cloud Computing

Modeling Of Capacitance Relaxation PhenomenaIn A Malignant Membrane