基于PTIDES执行策略的调度算法

分析现有PTIDES执行策略调度算法,综合考虑事件的截止期和执行时间,改进传统最小空闲时间优先算法,将空闲时间作为事件调度优先权,提出零空闲时间优先PTIDES调度算法——ZSFPTIDES。实例分析表明,ZSFPTIDES调度算法能避免事件在处理过程中因得不到及时处理而夭折的现象,减小事件的抢占切换率,优化分布实时嵌入式系统的调度性能。     

DipGame: A challenging negotiation testbed

There is a chronic lack of shared application domains to test advanced research models and agent negotiation architectures in Multiagent Systems. In this paper we introduce a friendly testbed for that purpose. The testbed is based on The Diplomacy Game where negotiation and the relationships between players play an essential role. The testbed profits from the existence of a large community of human players that know the game and can easily provide data for experiments. We explain the infrastructure in the paper and make it freely available to the AI community.     

Saving time or innovating practice: Investigating perceptions and uses of Learning Management Systems

Learning Management Systems (LMS) are web-based systems that allow instructors and/or students to share materials, submit and return assignments, and communicate online. In this study, we explored the uses and perceived benefits of using a LMS to support traditional classroom teaching as reported by instructors and students at a large American Midwestern university. We examined two years of survey data focusing on specific uses of the LMS that emphasized either efficient communication or interactive teaching and learning practices. We matched aggregate user log data with corresponding survey items to see if system use was consistent with patterns seen in the survey results. Findings suggest that instructors and students value tools and activities for efficient communication more than interactive tools for innovating existing practices. However, survey item analysis reveals that instructors and students also highly value the teaching and learning tools within the LMS.     

A Visualization Based Approach for Digital Signature Authentication

We propose a visualization based approach for digital signature authentication. Using our method, the speed and pressure aspects of a digital signature process can be clearly and intuitively conveyed to the user for digital signature authentication. Our design takes into account both the expressiveness and aesthetics of the derived visual patterns. With the visual aid provided by our method, digital signatures can be authenticated with better accuracy than using existing methods—even novices can examine the authenticity of a digital signature in most situations using our method. To validate the effectiveness of our method, we conducted a comprehensive user study which confirms positively the advantages of our approach. Our method can be employed as a new security enhancement measure for a range of business and legal applications in reality which involve digital signature authorization and authentication.     

Acceptance of agile methodologies: A critical review and conceptual framework

It is widely believed that systems development methodologies (SDMs) can help improve the software development process. Nevertheless, their deployment often encounters resistance from systems developers. Agile methodologies, the latest batch of SDMs that are most suitable in dealing with volatile business requirements, are likely to face the same challenge as they require developers to drastically change their work habits and acquire new skills. This paper addresses what can be done to overcome the challenge to agile methodologies acceptance. We provide a critical review of the extant literature on the acceptance of traditional SDMs and agile methodologies, and develop a conceptual framework for agile methodologies acceptance based on a knowledge management perspective. This framework can provide guidance for future research into acceptance of agile methodologies, and has implications for practitioners concerned with the effective deployment of agile methodologies.     

Dynamic changes in the use of online advice in response to task success or failure

A range of responsible gambling systems have been developed, but they are not necessarily used by consumers. This requires an understanding of factors (e.g. risk and loss) influencing response to advice. Therefore, an experiment examined the use of decisional support in response to induced success or failure. A total of 21 university students played computer Blackjack at two levels of risk, and were informed as to whether the odds were in their favour (‘card count’), and were given online advice as to card selection (Basic). Winning streaks led to overconfidence, as indicated by larger mean bets, more Basic errors, and a failure to adjust wagering upon cessation of the winning streak. Participants were more cautious in response to losses, betting less, and were more likely to comply with advice. Participants attended and complied with advice earlier at low risk, but at high risk noticed advice later and did not comply. Induced emotional states (e.g. winning or losing) are important as they influence the likelihood that people will listen to online advice. Designers of Behaviour Change Support Systems should consider methods of contingently implementing advice.     

Using Visualization to Explore Original and Anonymized LBSN Data

We present GSUVis, a visualization tool designed to provide better understanding of location‐based social network (LBSN) data. LBSN data is one of the most important sources of information for transportation, marketing, health, and public safety. LBSN data consumers are interested in accessing and analysing data that is as complete and as accurate as possible. However, LBSN data contains sensitive information about individuals. Consequently, data anonymization is of critical importance if this data is to be made available to consumers. However, anonymization commonly reduces the utility of information available. Working with privacy experts, we designed GSUVis a visual analytic tool to help experts better understand the effects of anonymization techniques on LBSN data utility. One of GSUVis's primary goals is to make it possible for people to use LBSN data, without requiring them to gain deep knowledge about data anonymization. To inform the design of GSUVis, we interviewed privacy experts, and collected their tasks and system requirements. Based on this understanding, we designed and implemented GSUVis. It applies two anonymization algorithms for social and location trajectory data to a real‐world LBSN dataset and visualizes the data both before and after anonymization. Through feedback from domain experts, we reflect on the effectiveness of GSUVis and the impact of anonymization using visualization.     

A new expert system for learning management systems evaluation based on neutrosophic sets

There has been a sudden increase in the usage of Learning Management Systems applications to support learner's learning process in higher education. Many studies in learning management system evaluation are implemented under complete information, while the real environment has uncertainty aspects. As these systems were described by development organizations with uncertainty terms such as vague, imprecise, ambiguity and inconsistent, that is why traditional evaluation methods may not be effective. This paper suggests neutrosophic logic as a better option to simulate human thinking than fuzzy logic because unlike fuzzy logic, it is able to handle indeterminacy of information which expresses the percentage of unknown parameters. As previous studies suggested neutrosophic decision maker and neutrosophic expert systems as future work in ecommerce and e‐learning applications, this paper presents neutrosphic expert system for learning management systems evaluation. Information for building and validating the neutrosophic expert system is collected from five experts using surveys, and then analysis is done by using Fuzzytech 5.54d software. Finally, the comparison between fuzzy expert system and neutrosophic expert system results show that the neutrosophic logic is capable of representing uncertainty in human thinking for evaluating Learning Management Systems.     

Metamodeling of Smart Environments: from design to implementation

A smart environment is a physical environment enriched with sensing, actuation, communication and computation capabilities aiming at acquiring and exploiting knowledge about the environment so as to adapt itself to its inhabitants’ preferences and requirements. In this domain, there is the need of tools supporting the design and analysis of applications. In this paper, the Smart Environment Metamodel (SEM) framework is proposed. The framework allows to model applications by exploiting concepts specific to the smart environment domain. SEM approaches the modeling from two different points of view, namely the functional and data perspectives. The application of the framework is supported by a set of general guidelines to drive the analysis, the design and the implementation of smart environments. The effectiveness of the framework is shown by applying it to the modeling of a real smart office scenario that has been developed, deployed and analyzed.