The Development of the Generalization Algorithm Based on the Rough Set Theory

This paper considers the problem of concept generalization in decision-making systems where such features of real-world databases as large size, incompleteness and inconsistence of the stored information are taken into account. The methods of the rough set theory (like lower and upper approximations, positive regions and reducts) are used for the solving of this problem. The new discretization algorithm of the continuous attributes is proposed. It essentially increases an overall performance of generalization algorithms and can be applied to processing of real value attributes in large data tables. Also the search algorithm of the significant attributes combined with a stage of discretization is developed. It allows avoiding splitting of continuous domains of insignificant attributes into intervals

A high-performance data structure for mobile information systems

Mobile information systems can now be provided on small form-factor computers. Dictionary-based data compression extends the capabilities of systems with limited processing and memory to enable data intensive applications to be supported in such environments. The nature of judicial sentencing decisions requires that a support system provides accurate and up-to-date data and is compatible with the professional working experience of a judge. The difficulties caused by mobility and the data dependence of the decision-making process are addressed by an Internet-based architecture for collecting and distributing system data.We describe an approach to dictionary-based data compression and the structure of an information system that makes use of this technology

A taxonomy of supply chain innovations

In this paper, a taxonomy of supply chain and logistics innovations was developed and presented. The taxonomy was based on an extensive literature survey of both theoretical research and case studies. The primary goals are to provide guidelines for choosing the most appropriate innovations for a company, and help companies in positioning themselves in the supply of chain innovations landscape. To this end, the three dimensions of supply chain innovations, namely the goals, supply chain attributes, and innovation attributes were identified and classified. The taxonomy allows for the efficient representation of critical supply chain innovations information, and serves the mentioned goals, which are fundamental to companies in a multitude of industries

Is Individual Environmental Consciousness One of the Determinants in Transport Mode Choice?

This paper models a transport negative impact on environment as one of attributes of the transport mode. By this modeling, we are able to examine whether individual environmental consciousness has a significant effect on his/her choice of transport mode. A survey data from Saito and Onohara Area in Northern Osaka of Japan is used to estimate the model specified by Heteroscedastic Extreme Value (HEV). Both of the estimated and simulated results imply that individual environmental consciousness does influence his/her decision on transport mode choice. Furthermore, the likelihood ratio tests suggest that both the utility and scale parameters are not equal across sub-samples of university commuters, research-facility commuters, and residents. The details of the comparison across sub-samples suggest that we may learn more from subdividing a whole sample into several sub-samples if we could select them based on their characteristics.Environmental consciousness; Transport mode choice; Stated choice experiment; Heteroscedastic Extreme Value (HEV) model; Value of time saving (VOTS)

Structural Interactions in Spatial Panels

Until recently, much effort has been devoted to the estimation of panel data regression models without adequate attention being paid to the drivers of diffusion and interaction across cross section and spatial units. We discuss some new methodologies in this emerging area and demonstrate their use in measurement and inferences on cross section and spatial interactions. Specifically, we highlight the important dis?tinction between spatial dependence driven by unobserved common factors and those based on a spatial weights matrix. We argue that, purely factor driven models of spatial dependence may be somewhat inadequate because of their connection with the exchangeability as?sumption. Limitations and potential enhancements of the existing methods are discussed, and several directions for new research are highlighted.Cross Sectional and Spatial Dependence, Spatial Weights Matrix, Interactions and Diffusion, Monetary Policy Committee, Generalised Method of Moments.

PCG: A prototype incremental compilation facility for the SAGA environment, appendix F

A programming environment supports the activity of developing and maintaining software. New environments provide language-oriented tools such as syntax-directed editors, whose usefulness is enhanced because they embody language-specific knowledge. When syntactic and semantic analysis occur early in the cycle of program production, that is, during editing, the use of a standard compiler is inefficient, for it must re-analyze the program before generating code. Likewise, it is inefficient to recompile an entire file, when the editor can determine that only portions of it need updating. The pcg, or Pascal code generation, facility described here generates code directly from the syntax trees produced by the SAGA syntax directed Pascal editor. By preserving the intermediate code used in the previous compilation, it can limit recompilation to the routines actually modified by editing

Architecture value mapping: using fuzzy cognitive maps as a reasoning mechanism for multi-criteria conceptual design evaluation

The conceptual design phase is the most critical phase in the systems engineering life cycle. The design concept chosen during this phase determines the structure and behavior of the system, and consequently, its ability to fulfill its intended function. A good conceptual design is the first step in the development of a successful artifact. However, decision-making during conceptual design is inherently challenging and often unreliable. The conceptual design phase is marked by an ambiguous and imprecise set of requirements, and ill-defined system boundaries. A lack of usable data for design evaluation makes the problem worse. In order to assess a system accurately, it is necessary to capture the relationships between its physical attributes and the stakeholders\u27 value objectives. This research presents a novel conceptual architecture evaluation approach that utilizes attribute-value networks, designated as \u27Architecture Value Maps\u27, to replicate the decision makers\u27 cogitative processes. Ambiguity in the system\u27s overall objectives is reduced hierarchically to reveal a network of criteria that range from the abstract value measures to the design-specific performance measures. A symbolic representation scheme, the 2-Tuple Linguistic Representation is used to integrate different types of information into a common computational format, and Fuzzy Cognitive Maps are utilized as the reasoning engine to quantitatively evaluate potential design concepts. A Linguistic Ordered Weighted Average aggregation operator is used to rank the final alternatives based on the decision makers\u27 risk preferences. The proposed methodology provides systems architects with the capability to exploit the interrelationships between a system\u27s design attributes and the value that stakeholders associate with these attributes, in order to design robust, flexible, and affordable systems --Abstract, page iii