The scientific basis for prediction research

Copyright @ 2012 ACMIn recent years there has been a huge growth in using statistical and machine learning methods to find useful prediction systems for software engineers. Of particular interest is predicting project effort and duration and defect behaviour. Unfortunately though results are often promising no single technique dominates and there are clearly complex interactions between technique, training methods and the problem domain. Since we lack deep theory our research is of necessity experimental. Minimally, as scientists, we need reproducible studies. We also need comparable studies. I will show through a meta-analysis of many primary studies that we are not presently in that situation and so the scientific basis for our collective research remains in doubt. By way of remedy I will argue that we need to address these issues of reporting protocols and expertise plus ensure blind analysis is routine

Predicting Fraud in Mobile Phone Usage Using Artificial Neural Networks

Mobile phone usage involves the use of wireless communication devices that can be carried anywhere, as they require no physical connection to any external wires to work. However, mobile technology is not without its own problems. Fraud is prevalent in both fixed and mobile networks of all technologies. Frauds have plagued the telecommunication industries, financial institutions and other organizations for a long time. The aim of this research work and research publication is to apply 3 different neural network models (Fuzzy, Radial Basis and the Feedforward) to the prediction of fraud in real-life data of phone usage and also analyze and evaluate their performances with respect to their predicting capability. From the analysis and model predictability experiment carried out in this scientific research work, it was discovered that the fuzzy network model had the minimum error generated in its fraud predicting capability. Thus, its performance in terms of the error generated in this fraud prediction experiment showed that its NMSE (Normalized mean squared error) for the fraud predicted was 1.98264609. The mean absolute error (M AE = 15.00987244) for its fraud prediction was also the least; this showed that the fuzzy model fraud predictability was much better than the other two models

International organisation of ocean programs: Making a virtue of necessity

When faced with the needs of climate prediction, a sharp contrast is revealed between existing networks for the observation of the atmosphere and for the ocean. Even the largest and longest-serving ocean data networks were created for their value to a specific user (usually with a defence, fishing or other maritime purpose) and the major compilations of historical data have needed extensive scientific input to reconcile the differences and deficiencies of the various sources. Vast amounts of such data remain inaccessible or unusable. Observations for research purposes have been generally short lived and funded on the basis of single initiatives. Even major programs such as FGGE, TOGA and WOCE have been driven by the dedicated interest of a surprisingly small number of individuals, and have been funded from a wide variety of temporary allocations. Recognising the global scale of ocean observations needed for climate research, international cooperation and coordination is an unavoidable necessity, resulting in the creation of such bodies as the Committee for Climatic Changes and the Ocean (CCCO), with the tasks of: (1) defining the scientific elements of research and ocean observation which meet the needs of climate prediction and amelioration; (2) translating these elements into terms of programs, projects or requirements that can be understood and participated in by individual nations and marine agencies; and (3) the sponsorship of specialist groups to facilitate the definition of research programs, the implementation of cooperative international activity and the dissemination of results

Transformation of entrepreneurial leadership in the 21st century: prospects for the future

The 21st century imposed many challenges on mankind, among them there is a very important problem of entrepreneurial leadership transformation. Entrepreneurship gradual modification under the pressure of factors of innovation, informatization of the environment and the need for socialization of the relations between businessmen and society has led to the need of new understanding of leadership positions. The purpose of this scientific research is to substantiate the style of entrepreneurial leadership, which will become dominant in the 21st century. Analyzing and systematizing the scientific works of many modern scholars by the methods of theoretical synthesis, analysis and synthesis, we have solved the problems of entrepreneurial leadership transformation. The use of the historical and logical method has revealed the relationship between the entrepreneurial leadership development and entrepreneurial types. The study found that the global business environment requires new leaders, whose key competences will meet the needs of society, educational space, ethical requirements, etc. Studying the similarities and differences of various leadership styles has become the basis for the allocation of a new style – the leadership of conscious influence, the main characteristics of which are given in this research. In order to achieve the goals, set by the leader-entrepreneur, it is proposed to systematize the leadership opportunities on tactical and strategic, the factors of influence on their realization in the future are generalized. By the method of scientific and theoretical prediction the portrait of an entrepreneur in a global perspective has been formed. Prospects for further research in this area are the development of a methodology for evaluating the effectiveness of business leaders' actions and systematization of ways to increase their effectiveness in the future

United States Weather Research Program (USWRP)

After more than a decade of development by a broad cross-section of the U.S. atmospheric research community involved in planning for the National STORM Program, the Subcommittee on Atmospheric Research (SAR) of the Committee on Earth and Environmental Science (CEES) led the development of a strategic plan to realize the objectives of STORM so as to improve our nation's capability to provide accurate short-term forecasts of weather. This strategic plan will guide the planning and implementation of what is now called the United States Weather Research Program (USWRP). The USWRP is charged with achieving operational atmospheric prediction based on mesoscale observations and model results and establishing the scientific and technological basis for global atmospheric mesoscale prediction by the year 2000. The key scientific questions that are addressed under USWRP are discussed

Model of operational search prediction of intentional homicide by criminal police

The purpose of the article is to determine the model of operational search prediction of intentional homicide by criminal police of Ukraine. Subject of research: The subject of research is a model of operational search prediction of intentional homicides by criminal police of Ukraine. Methodology: The methodological basis for the article is general and special methods and techniques of scientific knowledge, in particular: normative and dogmatic method, epistemological method, monographic method, comparative and legal method, modeling method, method of grouping, logical and legal method, method of generalization. Research results: The characteristic of the method of prediction and its use by the bodies of criminal police is given. Practical consequences: The features of the process of construction of operational search model of a situation are considered. International experience of regulating the issue under consideration is studied. Value / originality: Based on the examination of international experience, it is proposed to apply appropriate measures to combat intentional homicide in the activities of the National Police of Ukraine

Seventh U.S.-Japan Earthquake Prediction Research Seminar: Use of Real-Time Earthquake Information for Hazard Warning

For the seventh time since 1964, a seminar on earthquake prediction has been convened under the U.S.-Japan Cooperation in Science Program. The purpose of the seminar was to provide an opportunity for researchers from the two countries to share recent progress and future plans in the continuing effort to develop the scientific basis for predicting earthquakes and practical means for implementing prediction technology as it emerges. Thirty-six contributors, 15 from Japan and 21 from the U.S., met in Morro Bay, California, September 12-14. The following day they traveled to nearby sections of the San Andreas fault, including the site of the Parkfield prediction experiment. The conveners of the seminar were Hiroo Kanamori, Seismological Laboratory, Caltech, for the U.S., and Takeshi Mikumo, Disaster Prevention Research Institute, Kyoto University, for Japan. Funding for the participants came from the U.S. National Science Foundation and the Japan Society for the Promotion of Science, supplemented by other agencies in both countries