When a child abuse situation arises, the responsible agencies and entities in charge of response should be capable of providing a fast and personalized solution for the good of the child. This need leads the authors t...When a child abuse situation arises, the responsible agencies and entities in charge of response should be capable of providing a fast and personalized solution for the good of the child. This need leads the authors to consider the formation of dynamic virtual organizations tailored to each particular abuse case. In the authors＇ approach the partner selection of these collaborative networks is done through a software tool that combines two technologies from the field of artificial intelligence, specifically multi-agent systems and expert systems. In addition, these partners come from the breeding environment constituted by all the agencies or individuals, either in a region or locality, which have the potential of response.展开更多
The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifie...The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifiers are built based on these three different approaches. Second, the three different classifiers utilize the same product metrics as predictor variables to identify the fault-prone components. Third, the predicting results are compared on two aspects, how good prediction capabilities these models are, and how the models support understanding a process represented by the data.展开更多
Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE a...Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.展开更多
Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches foc...Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches focus on specific application fields. This paper accommodates for this lacuna and provides some general modeling principles and strategies. At last, the actual new modeling method Hierarchical Object Oriented Petri net (HOONet) which has been proved to be an effective modeling methodology, is used to illustrate the modeling strategies.展开更多
According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has...According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has developed a set of software applications, the software in chemical products quality inspection and analysis of the means of management is an innovation. The software functions, can automatically process data, judge the product grade, quality analysis, objective and fair, convenient, fast, accurate, stable, practical, and easy to popularize.展开更多
Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-...Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-propagation reliability model(CBPRM)with low complexity for the complex software system reliability evaluation is presented in this paper.The proposed model is based on the artificial neural networks and the component reliability sensitivity analyses.These analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation.CBPRM has a linear increasing complexity and outperforms the state-based and the path-based reliability models.Another advantage of CBPRM over others is its robustness.CBPRM depends on the component reliabilities and the correlative sensitivities,which are independent from the software system structure.Based on the theory analysis and experiment results,it shows that the complexity of CBPRM is evidently lower than the contrast models and the reliability evaluating accuracy is acceptable when the software system structure is complex.展开更多
Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that...Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions.Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area.展开更多
文摘When a child abuse situation arises, the responsible agencies and entities in charge of response should be capable of providing a fast and personalized solution for the good of the child. This need leads the authors to consider the formation of dynamic virtual organizations tailored to each particular abuse case. In the authors＇ approach the partner selection of these collaborative networks is done through a software tool that combines two technologies from the field of artificial intelligence, specifically multi-agent systems and expert systems. In addition, these partners come from the breeding environment constituted by all the agencies or individuals, either in a region or locality, which have the potential of response.
文摘The contribution of this paper is comparing three popular machine learning methods for software fault prediction. They are classification tree, neural network and case-based reasoning. First, three different classifiers are built based on these three different approaches. Second, the three different classifiers utilize the same product metrics as predictor variables to identify the fault-prone components. Third, the predicting results are compared on two aspects, how good prediction capabilities these models are, and how the models support understanding a process represented by the data.
文摘Model driven generative domain engineering (MDGDE) is a domain engineering method aiming to develop optimized, reusable architectures, components and aspects for application engineering. Agents are regarded in MDGDE as special objects having more autonomy, and taking more initiative. Design of the agent involves three levels of activities: logical analysis and design, physical analysis, physical design. This classification corresponds to domain analysis and design, application analysis, and application design. Agent is an important analysis and design tool for MDGDE because it facilitates development of complex distributed system—the mobile robot. According to MDGDE, we designed a distributed communication middleware and a set of event-driven agents, which enables the robot to initiate actions adaptively to the dynamical changes in the environment. This paper describes our approach as well as its motivations and our practice.
文摘Although the modeling technologies for open robot controllers have been discussed widely, not much literature is devoted to the actual general modeling principles and strategies. The reason is that many researches focus on specific application fields. This paper accommodates for this lacuna and provides some general modeling principles and strategies. At last, the actual new modeling method Hierarchical Object Oriented Petri net (HOONet) which has been proved to be an effective modeling methodology, is used to illustrate the modeling strategies.
文摘According to the regulations of the People＇s Republic of China national standard as the basis, on the part of chemical industry product quality inspection and analysis of the implementation of computer management has developed a set of software applications, the software in chemical products quality inspection and analysis of the means of management is an innovation. The software functions, can automatically process data, judge the product grade, quality analysis, objective and fair, convenient, fast, accurate, stable, practical, and easy to popularize.
基金Supported by the National Natural Science Foundation of China(No.60973118,60873075)
文摘Since most of the available component-based software reliability models consume high computational cost and suffer from the evaluating complexity for the software system with complex structures,a component-based back-propagation reliability model(CBPRM)with low complexity for the complex software system reliability evaluation is presented in this paper.The proposed model is based on the artificial neural networks and the component reliability sensitivity analyses.These analyses are performed dynamically and assigned to the neurons to optimize the reliability evaluation.CBPRM has a linear increasing complexity and outperforms the state-based and the path-based reliability models.Another advantage of CBPRM over others is its robustness.CBPRM depends on the component reliabilities and the correlative sensitivities,which are independent from the software system structure.Based on the theory analysis and experiment results,it shows that the complexity of CBPRM is evidently lower than the contrast models and the reliability evaluating accuracy is acceptable when the software system structure is complex.
文摘Machine intelligence is increasingly entering roles that were until recently dominated by human intelligence. As humans now depend upon machines to perform various tasks and operations, there appears to be a risk that humans are losing the necessary skills associated with producing competitively advantageous decisions.Therefore, this research explores the emerging area of human versus machine decision-making. An illustrative engineering case involving a joint machine and human decision-making system is presented to demonstrate how the outcome was not satisfactorily managed for all the parties involved. This is accompanied by a novel framework and research agenda to highlight areas of concern for engineering managers. We offer that the speed at which new human-machine interactions are being encountered by engineering managers suggests that an urgent need exists to develop a robust body of knowledge to provide sound guidance to situations where human and machine decisions conflict. Human-machine systems are becoming pervasive yet this research has revealed that current technological approaches are not adequate. The engineering insights and multi-criteria decision-making tool from this research significantly advance our understanding of this important area.
