Search

Word sense disambiguation (WSD) is the process of automatically identifying which the appropriate meaning of a word given in its sentence. WSD is a promising research area in computational linguistics, especially in wide range of advanced applications, such as medical and social sciences. This research employs the concept (WSD) to determine the inherent meaning of voter intentions regarding possible political candidates. Where candidates can be examined and their true assets and competencies in three major areas of eligibility, education, and experience inputs can be deciphered. Data envelope analysis (DEA) is used to determine underlying word instances for elected and successful outputs. The results demonstrate the validity of using (DEA) as a tool for (WSD). The results also indicate that the survey administered by the website which is developed for the purpose of this research, and used in this study, is a promising tool for predicting successful presidential candidates. We further validated our research findings by employing a qualitative comparative analysis approach to define the fuzzy relationships found in our data. [ABSTRACT FROM AUTHOR]

Parts backorder reduction has become increasingly important in supply chain management. When it is difficult or time consuming to acquire parts, the operational availability of a system is reduced. This study describes a technique that helps planners proactively identify potential problem spare parts to better manage spare parts acquisition in military weapon systems. The paper reports on the results of fuzzy induced linguistic ordered weighted averaging for group decision support evaluation of backorder risk triggers to ensure that equipment is available and fully operational when needed. Risk factors were identified, the impact importance and probability metric performance ratings were determined via induced linguistic ordered weighted averaging, and a risk mitigation strategy was used to identify and predict supply chain backorder risk triggers (SCBORT). L-Project is an illustrative example that utilizes Petri nets and Pareto charts to present the evaluation hierarchy of supply chain risk. Cluster analysis is utilized to determine that there are five triggers of engineering, obsolescence, demand, NSN unique sustainment, and cataloging in light of the five SCBORT probability performance metric dimensions of quality, cost, lead time, service level, and information availability. There are also four aggregated SCBORT impact clusters of market sensitiveness, process integration, information drivers, and flexibility. Supply chain risk is presented as a probability/impact matrix. [ABSTRACT FROM AUTHOR]

In this paper, we investigate the impact of team size on the software development effort. Using field data of over 200 software projects from various industries, we empirically test the impact of team size and other variables—such as software size in function points, ICASE tool and programming language type—on software development effort. Our results indicate that software size in function points significantly impacts the software development effort. The two-way interactions between function points and use of ICASE tool, and function points and language type are significant as well. Additionally, the interactions between team size and programming language type, and team size and use of ICASE tool were all significant. [ABSTRACT FROM AUTHOR]

Efforts to eliminate unnecessary scheduling and inventory problems faced by the coal industry today initiated the development of a generalized, nonlinear programming model. Although no accepted methodology for developing such a model for this purpose currently exists, one was created and successfully tested. Production and transportation cost estimates were obtained from independent coal mines in Illinois, Virginia, and Pennsylvania, and based on these estimates, a hypothetical model was developed and tested using genetic search for nonlinear optimization. The results of our tests indicate that the model has potential for decision support in coal mines. [ABSTRACT FROM AUTHOR]