In bringing together this book, the editors have kept two goals in mind. Firstly, the goal of educating the reader by giving an insight into the wealth of computing and mathematical techniques now being used to build decision support systems. Secondly, of aiming to stimulate the imagination by including an eclectic mix of contributions from a wide range of business areas to demonstrate that there is no field in which modern decision support techniques cannot usefully be applied. The quintessence of decision support systems is that they are designed to assist people in establishing the best course of action in a given situation but not to automate or tell them prescriptively how to achieve a goal.

Decision-aiding software, the underpinning of computer-aided judicial analysis, can facilitate the prediction of how cases are likely to be decided, prescribe decisions that should be reached in such cases, and help administrate more efficiently the court process. It can do so, says Nagel, by listing past cases on each row of a spreadsheet matrix, by listing predictive criteria in the columns, and in general by showing for each factual element the estimated probability of winning a case. The software aggregates the information available and deduces likely outcomes. But it can also prescribe judicial decisions by listing alternatives in the rows, the goals to be achieved in the columns, and by showing relations between alternatives in the cells. By similar means decision-aiding software can also help perform administrative tasks, such as rationally assigning judges or other personnel to cases, and by sequencing cases to reduce the time consumed by each case. In Part I, Nagel provides an overview of computer-aided analysis and the role of decision-aiding software in the legal process. In the second part he deals with judicial prediction from prior cases and from present facts; and in the third part he emphasizes the prescribing role of judges, particularly in deciding the rules that ought to be applied in civil and criminal procedures. Nagel also covers computer-aided mediation and provides a new perspective on judicial decisions. Then, in Part IV, he treats at length the process of judicial administration and how to improve its efficiency. Of particular interest to court personnel will be the benefits to be derived from reducing delays and in the docketing and sequencing of cases.

Computer Aided Geometric Design covers the proceedings of the First International Conference on Computer Aided Geometric Design, held at the University of Utah on March 18-21, 1974. This book is composed of 15 chapters and starts with reviews of the properties of surface patch equation and the use of computers in geometrical design. The next chapters deal with the principles of smooth interpolation over triangles and without twist constraints, as well as the graphical representation of surfaces over triangles and rectangles. These topics are followed by discussions of the B-spline curves and surfaces; mathematical and practical possibilities of UNISURF; nonlinear splines; and some piecewise polynomial alternatives to splines under tension. Other chapters explore the smooth parametric surfaces, the space curve as a folded edge, and the interactive computer graphics application of the parametric bi-cubic surface to engineering design problems. The final chapters look into the three-dimensional human-machine communication and a class of local interpolating splines. This book will prove useful to design engineers.

Computer-aided diagnosis (CAD) in medicine is the result of a large amount of effort expended in the interface of medicine and computer science. As some CAD systems in medicine try to emulate the diagnostic decision-making process of medical experts, they can be considered as expert systems in medicine.

This text focuses on how decision analysis can be used to support the managerial decision process. It supports professors and students in the classroom with extensive case studies and problem sets, and with Arborist software and documentation.

For MIS specialists and non-specialists alike, this text is a comprehensive, readable, understandable guide to the concepts and applications of decision support systems.

The 4th International Conference on Economic Management and Big Data Applications was successfully held in Tianjin, China from October 27th to 29th, 2023. This conference served as a platform for researchers, scholars, and industry professionals to exchange knowledge and insights in the field of economic management and the application of big data. The conference held great significance in advancing the understanding and application of economic management and big data. By bringing together experts from around the globe, the conference facilitated the exchange of innovative ideas and research findings, contributing to the development of these fields. The topics covered during the conference showcased the latest advancements and trends in enterprise economic statistics, information evaluation, blockchain technology, industrial structure optimization, information retrieval, data regression analysis, intelligent Internet of Things platforms, and data encryption. The discussions and presentations during the conference allowed participants to explore new methodologies, strategies, and technologies that can enhance economic management practices and leverage the potential of big data. The conference provided a platform for scholars and practitioners to share their experiences, insights, and best practices, fostering collaboration and networking opportunities. Furthermore, the proceedings were published, ensuring the dissemination of valuable research findings to a wider audience. The collective knowledge and research presented at the conference will contribute to the academic community, industry professionals, and policymakers, enabling them to make informed decisions and develop effective strategies in the fields of economic management and big data applications. Overall, the 4th International Conference on Economic Management and Big Data Applications played a pivotal role in promoting knowledge exchange, fostering innovation, and shaping the future of economic management by harnessing the power of big data.