Data Mining - Concepts and Techniques.

Data Mining Practical Machine Learning Tools and Techniques

This sales letter may not influence you to be smarter, but the book that we offer will evoke you to be smarter. Yeah, at least you'll know more than others who don't. This is what called as the quality life improvisation. Why should this research methods in social relations? It's because this is your favourite theme to read. If you like this theme about, why don't you read the book to enrich your discussion?

Research methods in social relations

Technical foundations introduction software reliability and system reliability the operational profile software reliability modelling survey model evaluation and recalibration techniques practices and experiences best current practice of SRE software reliability measurement experience measurement-based analysis of software reliability software fault and failure classification techniques trend analysis in validation and maintenance software reliability and field data analysis software reliability process assessment emerging techniques software reliability prediction metrics software reliability and testing fault-tolerant SRE software reliability using fault trees software reliability process simulation neural networks and software reliability. Appendices: software reliability tools software failure data set repository.

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Handbook of software reliability engineering

Will Tracz, our esteemed editor and Used-Program salesman, has written an entertaining, non-technical book dealing with the practice (and lack of) of software reuse. Its a collection of essays, mostly rehashed (reused?) and updated from various columns and papers published over the years.. Its a short (a bit over 200 pages) easy reading and enjoyable book (I read most of it in one sitting). Some of the essays discuss what was printed in the past and a discussion of the current status of the points.

Safeware: System Safety and Computers

“Generalization of convolutional network to domain adaptation network for classification of disaster images on twitter”

Many empirical studies have been performed to evaluate software testing methods in past decades. However, we are still not able to generalize the results as most studies are not complete and differ significantly from one another. To contribute to the existing knowledge base of software testing methods, we performed an empirical study to evaluate 3 testing methods: (1) code reading by stepwise abstraction, (2) functional testing using equivalence partitioning and boundary value analysis, and (3) structural testing using 100% branch, multiple-condition, loop, and relational-operator coverage using a well-defined and standard schema. A controlled experiment is performed with 18 subjects who applied the 3 defect detection techniques to 3 C programs in a fractional factorial experimental design to observe failures and isolate faults. The experimental results show that (1) the techniques are equally effective in terms of observing failures and finding faults, (2) the effectiveness of the techniques depends on the nature of the program, (3) all the testing techniques are equally efficient in case of failure observation, (4) the techniques are different in their efficiency in terms of fault isolation where code reading performed better than that of structural and functional testing, and (5) with respect to the fault types, all the techniques were equally effective in observing failures and isolating faults except in case of cosmetic faults where functional testing performed better than the other 2 techniques The effectiveness and efficiency of testing techniques were significantly influenced by the type of program. The results presented in this paper contribute to an empirical knowledge base of testing methods and may be helpful for the software engineers to decide the appropriate techniques in improving the software testing process.

A replicated empirical study to evaluate software testing methods

Medical sciences currently rely on the imaging technology and post processing of these medical images in order to diagnose the diseases. The acquisition of such images may get affected by inherent noise which can lead to false perception of the diagnostic image. To perceive these images correctly the effective image enhancement techniques are the foremost requirement to improve the quality and level of perception. In this paper we apply various image enhancement techniques on CT images. Resultant images are inspected visually by radiologists for performance evaluation. Median filter removes noise and smoothen CT images effectively and outperforms other Filtering techniques. While as adaptive histogram equalization enhances the contrast and outperforms other contrast enhancement techniques.

Contrast enhancement and smoothing of CT images for diagnosis

Purpose




The purpose of this paper is to propose a model to map the on-premise computing system of the university with cloud computing for achieving an effective and reliable university e-governance (e-gov) system.




Design/methodology/approach




The proposed model incorporates the university’s internal e-gov system with cloud computing in order to achieve better reliability, accessibility and availability of e-gov services while keeping the recurring expenditure low. This model has been implemented (and tested on a university e-gov system) in the University of Kashmir (UOK); case study of this implementation has been chosen as the research methodology to discuss and demonstrate the proposed model.




Findings




According to the results based on practical implementation, the proposed model is ideal for e-governed systems as it provided adequate cost savings and high availability (HA) with operational ease, apart from continuing to have the necessary security in place to maintain confidential information such as student details, grades, etc.




Practical implications




The implication of this study is to achieve HA and to reduce the cost from using external clouds, mapping internal IT servers of the university with the external cloud computing services.




Originality/value




Because no established mapping model for universities has been provided for effective, low-cost, highly available university e-gov system, the proposed mapping model through this paper closes this gap and provides guidelines to implement a hybrid-mapped e-gov model for universities while keeping the recurring expenditure on cloud computing minimal. The paper provides the perceptions of its adoption at UOK for achieving high reliability, accessibility and uptime of its e-gov applications while keeping the recurring expenditure on cloud computing minimal.

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Mapping cloud computing in university e-governance system

As earliest the software defects uncovered and fixed in STLC, the lesser the amount required to fix it. With the advent of cloud computing a lot of new opportunities for business opens, especially in the field of software testing & maintenance. The cloud testing methodology is the set of techniques, tools and process to be followed while undergoing tests for cloud service. A new methodology is proposed to test the cloud which is known as SUPerB methodology, deals with cloud security, user acceptance, performance and business requirements. Successful implementation of SUPerB methodology for cloud testing might establish a strong foundation for an organization to lead in the market. Software vulnerabilities give rise to the cyber-crime and related risk associated with it just due to lapses in security policies, which increases the security breaches in the business. Efficiency of a system can be measured in terms of performance testing. While selecting a test tool, users must keep certain characteristics of cloud testing tool in consideration, like platform compatibility, available support, flexibility and service cost. It might be possible that an organization has to deal with a number of challenges while adopting cloud computing services.

S. M. K. Quadri

Papers

“Generalization of convolutional network to domain adaptation network for classification of disaster images on twitter”

A replicated empirical study to evaluate software testing methods

Contrast enhancement and smoothing of CT images for diagnosis

Mapping cloud computing in university e-governance system

Software Testing Approach for Cloud Applications (STACA) – Methodology, Techniques & Tools