Pure lazy functional languages are a promising programming paradigm for harvesting massive parallelism, as their abstraction features and lack of side effects support the development of modular programs without unneed...
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the proceedings contain 12 papers. the topics discussed include: can we verify an elephant?;pain, possibilities, and prescriptions industry trends in advancedfunctional verification;the SBSE approach to automated opt...
ISBN:
(纸本)9783642192364
the proceedings contain 12 papers. the topics discussed include: can we verify an elephant?;pain, possibilities, and prescriptions industry trends in advancedfunctional verification;the SBSE approach to automated optimization of verification and testing;reduction of interrupt handler executions for model checking embedded software;diagnosability of pushdown systems;functional test generation with distribution constraints;an explanation-based constraint debugger;evaluating workloads using multi-comparative functional coverage;reasoning about finite-state switched systems;dataflow analysis for properties of aspect systems;bisimulation minimizations for Boolean equation systems;synthesizing solutions to the leader election problem using model checking and genetic programming;stacking-based context-sensitive points-to analysis for java;and an interpolating decision procedure for transitive relations with uninterpreted functions.
this paper presents a new task, learning logical structures of paragraphs in legal articles, which is studied in research on Legal Engineering (Katayama, 2007). the goals of this task are recognizing logical parts of ...
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the utilization of robots as an educational medium in teaching and learning has in recent times become prominent. this paper presents a framework identifying the necessary constructs that establishes a sustainable mod...
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the utilization of robots as an educational medium in teaching and learning has in recent times become prominent. this paper presents a framework identifying the necessary constructs that establishes a sustainable model for using test arenas in educational robotics as an educational tool. Several successful implementation of this framework is demonstrated, covering projects and research activities ranging from advanced level software engineering courses to higher research degree. Areas of the project includes, search and rescue, intelligent navigation, search and detection and computer-aided learning (CAL) to design and build competitive dancing and soccer playing robots.
In this paper, we focus on hierarchical multiobjective linear programming problems with random variable coefficients where multiple decision makers in a hierarchical organization have their own multiple objective line...
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In this paper, we focus on hierarchical multiobjective linear programming problems with random variable coefficients where multiple decision makers in a hierarchical organization have their own multiple objective linear functions together with common linear constraints. In order to deal with multiple objective linear functions and linear constraints involving random variable coefficients, P-Pareto optimality concept is defined in cumulative distribution function space. After each decision maker specifies his/her own decision power and reference probabilistic values, the corresponding candidate of a satisfactory solution is obtained from among P-Pareto optimal solution set on the basis of linear programming. Interactive processes are demonstrated by means of an illustrative numerical example.
A new fuzzy rule mining method based on Generalized Genetic Network programming(Generalized GNP) has been proposed to extract important time related association rules from sequential numerical database. the fuzzy set ...
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A new fuzzy rule mining method based on Generalized Genetic Network programming(Generalized GNP) has been proposed to extract important time related association rules from sequential numerical database. the fuzzy set theory is applied to the data handling of continuous data in this paper. A new classification method based on extracted rules is also proposed to predict the future traffic density of each road in road networks. Experiments on traffic density prediction are carried out using the proposed methods and the results show that the proposed methods are available to find a variety of rules from the large database effectively and efficiently and improve the classification accuracy.
In this paper we consider a multiobjective two-level integer programming problem in which there is not cordination between the decision maker at the upper level and the decision maker at the lower level. the decision ...
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In this paper we consider a multiobjective two-level integer programming problem in which there is not cordination between the decision maker at the upper level and the decision maker at the lower level. the decision maker at the upper level has an objective function and the decision maker at the lower level has multiple objective functions. the decision maker at the upper level must take account of multiple rational responses of the decision maker at the lower level in the problem. We examine two kinds of situations based on anticipation of the decision maker at the upper level;an optimistic anticipation and a pessimistic anticipation. Mathematical programming problems for obtaining the Stackelberg solutions based on two kinds of anticipation are formulated and three kinds of computational methods for obtaining the Stackelberg solutions are proposed. We carry out numerical experiments in order to demonstrate feasibility and effectiveness of the proposed methods.
the authors have developed a programming training system based on the ARCS learning model, and have applied the system in an actual programming course. the ARCS model is known as a learning model aiming at stimulating...
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the authors have developed a programming training system based on the ARCS learning model, and have applied the system in an actual programming course. the ARCS model is known as a learning model aiming at stimulating and sustaining the learner's motivation to learn. In this training system, learners create programs similarly to solving a puzzle game. In such a learning support system, it is important that the learner can view one's learning progress objectively. Furthermore, if the learning progress could be compared withthose of other learners, competition will occur to stimulate the learner's motivation. In this paper, the features to realize the real-time monitoring of each the learner's progress are proposed, and implemented in the puzzle-based programming training system CAPTAIN currently under development. the proposed features allows the learner to view one's own progress ranking compared to the whole class, and also enables the teacher to monitor each individual learner, in order to quickly spot and support learners having difficulty.
When a large-scaled disaster occurs, it is expected that plural lifelines get damaged at the same time. this causes big damage to our everyday lives, so we urgently need a plan to recover from the disaster. However, s...
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When a large-scaled disaster occurs, it is expected that plural lifelines get damaged at the same time. this causes big damage to our everyday lives, so we urgently need a plan to recover from the disaster. However, since lifeline networks have mutual relationships in terms of their functions, so it is difficult to promptly make a proper disaster restoration schedule. Withthis background, in this study, we aim to efficiently make a disaster restoration schedule with genetic algorithm taking account of the functional constraints among lifeline networks.
Today, it is said that many people have got lifestylerelated diseases and the metabolic syndrome. therefore, the health care has been becoming an important issue in our lives. So, in this study, we focus on recommendi...
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Today, it is said that many people have got lifestylerelated diseases and the metabolic syndrome. therefore, the health care has been becoming an important issue in our lives. So, in this study, we focus on recommending proper cooking recipes as a part of health care. We propose a method to recommend healthy cooking recipes to such people by selecting some candidates of recipes with restricted calorie intake considering the user's schedule and by applying linear programming to the candidates withthe constraints of carbohydrate, fat, protein, salt, increasing the amount of vegetable intake. In addition, we also show flexible recommendation methods considering various cases where user's schedule has changed and a user did not have the recommended foods, etc.
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