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

Data warehousing systems enable enterprise managers to acquire and integrate information from heterogeneous sources and to query very large databases efficiently. Building a data warehouse requires adopting design and implementation techniques completely different from those underlying information systems (1). Issue of information integration is vital part of any data warehouse and the design challenge increases by the variety of heterogeneous data sources present in the system. These data sources have varying conceptual models, semantic heterogeneity which seems to be an unavoidable burden in data integration. In this paper we discuss designing of a Data Warehouse for heterogeneous data sources using University Examination Systemas an example. This paper also discusses various challenges that were faced by the team in implementation of the same.

Integrating information from heterogeneous data sources: university of kashmir case study

It has been established and accepted that mental disorders pose one of the most prominent health challenges worldwide. Information retrieval from mental health data which may be explicit in electronic health records and clinical notes or may be implicit in social media postings has vast potential to detect, distinguish and diagnose the status of mental health of individuals and aid in managing this problem. This paper summarizes some recent studies that apply the state of art Artificial Intelligence (AI) techniques to mental health data. The paper summarizes that newly emerging AI technologies hold a decent promise and can be leveraged to predict, assist in the diagnosis and management of mental disorders. The role of AI in this area becomes particularly important in a scenario where there is a worldwide dearth of qualified professionals who can deal with mental health disorders, where the cost of these services is high and the people suffering from these problems often refrain from availing these services due to social stigma associated with it.

Emerging Role of Intelligent Techniques for Effective Detection and Prediction of Mental Disorders

the field of security metric and security evaluation is multifaceted and multidimensional in nature, which needs great care and systematic approach to evaluate. The security evaluation is a continuous process that should be carried out throughout the different software development stages and also in the operational phases. In practice the secure software development is based upon the guidelines and rules for secure design and coding. Even if the secure software development process and guidelines are to be followed, the resultant level of security remains unknown to the development team. A security evaluation framework that can be applied at the early system development stages,the derived metrics that act as indicators of security level of the system and point out the most critical component of the system , in order to provide the basis for the system developers to take the design decisions regarding security is the foremost requirement of secure software development. In this study we haveproposed the extended security evaluation framework which strikes at the architectural and design phase of the software lifecycle, along with the empirical evaluation on a running system. In The proposed framework the mathematical modeling to derive the security metrics has been adopted. The empirical evaluation is carried out on a Finger Print Attendance Automation system (FASS) developed for the department of computer science UoK.

Security Metric Framework for the Software Architecture and Design Level An Empirical Evaluation

scJVAE: A novel method for integrative analysis of multimodal single-cell data

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. Data Retrieval is still a pervasive challenge faced in applications that need to query across multiple autonomous and heterogeneous data sources. Data integration & extraction is crucial in every enterprises that own a multitude of data sources, where data sets are being produced independently by various departments of the organization, for better cooperation among various departments within the organization, data retrieval technique that cuts across heterogeneous data sources and is independent of size and access techniques required to access data sources as well as does not require user to have any sort of knowledge that includes location, query language etc, is need of hour. 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 The basic standard of data integration is to combine (integrate) designated information sources from a particular domain, in a way that a whole new data Source is generated. The end user, when querying for data, has the impression of interacting with one single system, which presents him a combined logical view of the data available. The first efforts to address information integration issues in enterprises where based principally on data warehousing methods, however proposed architecture, provides the user with a combined view of all data, on which queries can be posed. This particular schema is not intended to store any data; it is purely a logical schema. 20th century resulted in accumulation of two things-wires and data, while both brought enormous success to organization in specific and information technology in general, 21st century is all about management. Industry realized need to get rid of wires and integrate/manage/transform data present everywhere around us. Fiber & Wi-Fi is replacement to wires; however data integration/management is still challenge at large because of varying underlying structure, format, operatingsystem etc. proposed method of data transformation at application level without having to modifying underlying structure of data storage. Once the data has become machine readable in an Information System many issues related to its security arise. Although the information systems provide users greater access than ever to vast information resources, however they are equally subject to threats that jeopardize the privacy and confidentiality of sensitive information, the integrity of data, and the availability of critical information system resources. Protecting information and the resources that process and maintain information is critical to the continuity of operations. Security of information resources must include controls and safeguards to offset possible threats as well as controls to ensure timeliness, availability, integrity, confidentiality, etc. Information technology (IT) security encompasses the total infrastructure for maintenance and delivery of information, including physical computer hardware, supporting equipment, communication systems, and logical processes defined by software, procedures etc. Data security is proposed using encryption and University Registration System is taken as case study in understanding the system. For the access control of the system, the built in Database Control features are used however the user operations are monitored and controlled by introducing the process of encryption. We propose a model for system security involving the available database security features and the encryption technique. The model is designed specifically for preventing un-authorized modification of the data by its users which enjoy different levels of authorizations.

S. M. K. Quadri

Papers

Integrating information from heterogeneous data sources: university of kashmir case study

Emerging Role of Intelligent Techniques for Effective Detection and Prediction of Mental Disorders

Security Metric Framework for the Software Architecture and Design Level An Empirical Evaluation

scJVAE: A novel method for integrative analysis of multimodal single-cell data

Adaptation System for Data Retrieval and Information Translation from Semantically Heterogeneous, Autonomous Data Sources