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

Understanding and mitigating security issues in Sun NFS

Data Retrieval is still a pervasive challenge faced in applications that need to query across multiple autonomous and heterogeneous data sources. There is decent amount of standardization as far as World-Wide Web is concerned, while google is universal access tool to search and determine source of the information user requires there is still no such tool that can be implemented at enterprise level where there are multitude of data sources and organization users are still facing difficulty in accessing data available on the intranet of the organization and not on the WWW, in order to access such data users within the organizations need to know a lot including location, access techniques etc while still data consistency & redundancy is beyond the scope of common organization user/s. This paper introduces GENERIC SEARCH PRINCPLE: Solution making use of Knowledge base where in users of the organization irrespective of their technical ability, data source knowledge and location can search heterogeneous data sources including legacy data sources of organization and retrieve information, also taking into consideration user attributes like his/her location, work profile, designation etc so as to make search more relevant and results more precise.

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Generic Search Optimization for Heterogeneous Data Sources

The aim of the paper is to empirically evaluate the quantitative Availability metric derived from the dependencies among the individual measurable components of an information system. The Availability metric is twofold, based on the operating program and the network delay metric of the information system (for the local bound component composition the availability metric is purely based on the software/operating program, for the remote bound component composition the metric incorporates the delay metric of the network). The metric is used for measuring Availability of an information system from the security perspective, the measurements may be done at the system-design level or for a developed system the metric is applied to the individual working components (software/program code. The system to be evaluated is a network based video monitoring system EES and all the measurements are done using the source code of the system. The steps mentioned in the availability evaluation algorithm are followed in the evaluation process of the system and the final output of the algorithm is the availability score IAV(SyS) for the EES system. The score gives an indication of security of the system with the current design.

Component based metric for evaluating availability of an information system: an empirical evaluation

Software cost estimation is the forecast of development effort and time needed to develop a software project. Estimating software cost is endlessly proving to be a difficult problem and thus catches the attention of many researchers. Recently, the usage of meta-heuristic techniques for software cost estimation is increasingly growing. In this paper, we are proposing a technique consisting of functional link artificial neural network model and particle swarm optimisation algorithm as its training algorithm. Functional link artificial neural network is a high order feedforward artificial neural network consisting of an input layer and an output layer. It reduces the computational complexity and has got the fast learning ability. Particle swarm optimisation does optimisation by iteratively improving a candidate solution. The proposed model has been evaluated on promising datasets using magnitude of relative error and its median as a measure of performance index to simply weigh the obtained quality of estimation.

An improved particle swarm optimisation-based functional link artificial neural network model for software cost estimation

Software cost estimation is forecasting the amount of developmental effort and time needed, while developing any software system. A good volume of software cost prediction models ranging from the very old algorithmic models to expert judgement to non-algorithmic models have been proposed so far. Each of these models has their advantage and disadvantage in estimating the development effort. Recently, the usage of meta-heuristic techniques for software cost estimations is increasingly growing. So in this paper, we are proposing an approach, which consists of functional link ANN and artificial bee colony algorithm as its training algorithm for delivering most accurate software cost estimation. FLANN reduces the computational complexity in multilayer neural network, and does not has any hidden layer, and thus has got fast learning ability. In our model, we are using MRE, MMRE and MdMRE as a measure of performance index to simply weigh the obtained quality of estimation. After an extensive evaluation of results, it showed that training a FLANN with ABC for the problem of software cost prediction yields a highly improved set of results. Besides this, the proposed model involves less computation during its training because of zero hidden layers and thus is structurally simple.

S. M. K. Quadri

Papers

Understanding and mitigating security issues in Sun NFS

Generic Search Optimization for Heterogeneous Data Sources

Component based metric for evaluating availability of an information system: an empirical evaluation

An improved particle swarm optimisation-based functional link artificial neural network model for software cost estimation

Artificial Bee Colony-Trained Functional Link Artificial Neural Network Model for Software Cost Estimation