Analytical study and computational modeling of statistical methods for data mining

Today, there is tremendous increase of the information available on electronic form. Day by day it is increasing massively. There are enough opportunities for research to retrieve knowledge from the data available in this information. Data mining and app

A Study Regarding the Re-treatment of the Balance Sheet and of the Profit and Loss Account under Circumstances of Inflation and Hyper-inflation Approached According to the Conception of International Financial Reporting Standards

Inflation constantly has been seen as a controversial economic phenomenon that has generated numberless chronic lacks of balance in economy. In a hyper-inflationist economy the report without inflation re-treatment of the balance sheet and the profit and loss account is no more relevant for those who use accounting data, and the 90s’ Romania certainly faced such a hyper-inflationist economy. As the evaluation basis in accountancy is historic cost, and, due to the fact that under circumstances of high inflation, historic cost suffers a series of changes that distort reality, several accounting methods are employed. Theses accounting methods under circumstances of inflation may rely on conversion, evaluation or other mixed methods that consist in re-treating the financial reports of the companies at opening and closing these financial reports. As under the present circumstances a too rapid economic growth is envisaged for Romania that might determine the increase of inflation, the re-treatment of the balance sheet and of the results account could be a necessity in the future.inflation, balance sheet, profit, loss, re-treatment, evaluation, index, adjustment, price, hyper-inflation

The Development of Data Mining

Abstract Mining is the current hot spots, the most promising research areas has broad one, through data mining research status, algorithms and applications of analysis to explore data mining problems and trends, which is the development of data mining has certain reference value

Software Engineering Methods for the Internet of Things: A Comparative Review

Accessing different physical objects at any time from anywhere through wireless network heavily impacts the living style of societies worldwide nowadays. Thus, the Internet of Things has now become a hot emerging paradigm in computing environments. Issues like interoperability, software reusability, and platform independence of those physical objects are considered the main current challenges. This raises the need for appropriate software engineering approaches to develop effective and efficient IoT applications software. This paper studies the state of the art of design and development methodologies for IoT software. The aim is to study how proposed approaches have been solved issues of interoperability, reusability, and independence of the platform. A comparative study is presented for the different software engineering methods used for the Internet of Things. Finally, the key research gaps and open issues are highlighted as future directions

A Case Study of Data Analysis Process and Tools for a Consulting Company

It is crucial from any Consulting company's point of view to perceive some degree of data analysis in the environment of business intelligence. This research examines the different processes and tools in data analysis, and builds a specific and effective process and tool with cost-benefit analysis for Florilla Consulting, which can be beneficial to similar consulting companies operating in data analysis field. Based on a large sample of qualitative data we demonstrate the benefits and importance of using data analysis processes and tools in business intelligence as a strategic necessity and show how this system can be implemented in various business case scenarios. Finally we propose a business model of data analysis to be tested by future research

Data quality assurance for strategic decision making in Abu Dhabi's public organisations

“A thesis submitted to the University of Bedfordshire, in partial fulfilment of the requirements for the degree of Master of Philosophy”.Data quality is an important aspect of an organisation’s strategies for supporting decision makers in reaching the best decisions possible and consequently attaining the organisation’s objectives. In the case of public organisations, decisions ultimately concern the public and hence further diligence is required to make sure that these decisions do, for instance, preserve economic resources, maintain public health, and provide national security. The decision making process requires a wealth of information in order to achieve efficient results. Public organisations typically acquire great amounts of data generated by public services. However, the vast amount of data stored in public organisations’ databases may be one of the main reasons for inefficient decisions made by public organisations. Processing vast amounts of data and extracting accurate information are not easy tasks. Although technology helps in this respect, for example, the use of decision support systems, it is not sufficient for improving decisions to a significant level of assurance. The research proposed using data mining to improve results obtained by decision support systems. However, more considerations are needed than the mere technological aspects. The research argues that a complete data quality framework is needed in order to improve data quality and consequently the decision making process in public organisations. A series of surveys conducted in seven public organisations in Abu Dhabi Emirate of the United Arab Emirates contributed to the design of a data quality framework. The framework comprises elements found necessary to attain the quality of data reaching decision makers. The framework comprises seven elements ranging from technical to human-based found important to attain data quality in public organisations taking Abu Dhabi public organisations as the case. The interaction and integration of these elements contributes to the quality of data reaching decision makers and hence to the efficiency of decisions made by public organisations. The framework suggests that public organisations may need to adopt a methodological basis to support the decision making process. This includes more training courses and supportive bodies of the organisational units, such as decision support centres, information security and strategic management. The framework also underscores the importance of acknowledging human and cultural factors involved in the decision making process. Such factors have implications for how training and raising awareness are implemented to lead to effective methods of system development

CORPORATE SOCIAL RESPONSIBILITY IN ROMANIA

The purpose of this paper is to identify the main opportunities and limitations of corporate social responsibility (CSR). The survey was defined with the aim to involve the highest possible number of relevant CSR topics and give the issue a more wholesome perspective. It provides a basis for further comprehension and deeper analyses of specific CSR areas. The conditions determining the success of CSR in Romania have been defined in the paper on the basis of the previously cumulative knowledge as well as the results of various researches. This paper provides knowledge which may be useful in the programs promoting CSR.Corporate social responsibility, Supportive policies, Romania

Decision Support Systems

Decision support systems (DSS) have evolved over the past four decades from theoretical concepts into real world computerized applications. DSS architecture contains three key components: knowledge base, computerized model, and user interface. DSS simulate cognitive decision-making functions of humans based on artificial intelligence methodologies (including expert systems, data mining, machine learning, connectionism, logistical reasoning, etc.) in order to perform decision support functions. The applications of DSS cover many domains, ranging from aviation monitoring, transportation safety, clinical diagnosis, weather forecast, business management to internet search strategy. By combining knowledge bases with inference rules, DSS are able to provide suggestions to end users to improve decisions and outcomes. This book is written as a textbook so that it can be used in formal courses examining decision support systems. It may be used by both undergraduate and graduate students from diverse computer-related fields. It will also be of value to established professionals as a text for self-study or for reference