基于模糊认知图的情感Agent模型研究

人工情感是人工心理的一个主要研究内容。从研究人工情感出发,提出一种基于模糊认知图的情感Agent建模的方法。模糊认知图模型通过在传统认知图模型中引入模糊测度来量化概念间因果关系的影响程度。Agent的知识由内部组元的状态以及组元之间的关系权值进行描述,用简单数值运算代替了复杂的符号逻辑来实现Agent的智能推理和决策。通过实验表明,该模型设计简单、易于扩展、适用性好。     

B model: A browsing behavior model based on High-Level Petri Nets to generate behavioral patterns for e-learning

As Internet use has proliferated, e-learning systems have become increasingly popular. Many researchers have taken a great deal of effort to promote high quality e-learning environments, such as adaptive learning environments, personalized/adaptive guidance mechanisms, and so on. These researches need to collect large amounts of behavioral patterns for the verification and/or experimentation. However, collecting sufficient behavioral patterns usually takes a great deal of time and effort. To solve this problem, this paper proposes a browsing behavior model (B² model) based on High-Level Petri Nets (HLPNs) to model and generate students’ behavioral patterns. The adopted HLPN contains (1) Colored Petri Nets (CPNs), in which colored tokens can be used to identify and separate student, learning content and assessment, and (2) Timed Petri Nets (TPNs), in which time variable can be used to represent the time at which a student reads learning content. Besides, to validate the viability of the B² model, this paper implements a B² modeling tool to generate behavioral patterns. The generated behavioral patterns are compared with actual behavioral patterns collected from elementary school students. The results confirm that the generated behavioral patterns are analogous to actual behavioral patterns.     

Role of personality in computer based learning

With the rapid growth of technology enhanced learning, new mediums for learning have emerged. One of these mediums is computer based learning where the main concern is how to design a computer based learning system which takes into consideration the learners' differences. Personality is considered as one of the most critical sources of individual differences. This study investigates how personality differences within learners can affect computer based learning, through a comprehensive review of the literature. The highlighted results from the obtained nineteen studies are: (a) the most referred to personality model in computer based learning is MBTI; (b) personality traits affect how learners prefer learning content and learning approach like collecting information, communicating with instructor and peer, study behavior, acting and performing; (c) a new model of personality variables should be considered in computer based learning by taking all interested researchers and practitioners into accounts; and (d) the traditional questionnaire approach which is still the pre-dominant method to identify the learner's personality; and this needs to be changed with new potential of big data and learning analytics. Furthermore, this study presents a new implicit approach using learning analytics instead of questionnaire-based approach to identify the learner's personality.     

Evaluating intertwined effects in e-learning programs: A novel hybrid MCDM model based on factor analysis and DEMATEL

Internet evolution has affected all industrial and commercial activity and accelerated e-learning growth. Due to cost, time, or flexibility for designer courses and learners, e-learning has been adopted by corporations as an alternative training method. E-learning effectiveness evaluation is vital, and evaluation criteria are diverse. A large effort has been made regarding e-learning effectiveness evaluation; however, a generalized quantitative evaluation model, which considers both the interaffected relation between criteria and the fuzziness of subjective perception concurrently, is lacking. In this paper, the proposed new novel hybrid MCDM model addresses the independent relations of evaluation criteria with the aid of factor analysis and the dependent relations of evaluation criteria with the aid of DEMATEL. The AHP and the fuzzy integral methods are used for synthetic utility in accordance with subjective perception environment. Empirical experimental results show the proposed model is capable of producing effective evaluation of e-learning programs with adequate criteria that fit with respondent’s perception patterns, especially when the evaluation criteria are numerous and intertwined.     

Research and trends in the field of e-learning from 2001 to 2005: A content analysis of cognitive studies in selected journals

This paper provided a content analysis of studies in the field of cognition in e-learning that were published in five Social Sciences Citation Index (SSCI) journals (i.e. Computers and Education, British Journal of Educational Technology, Innovations in Education and Teaching International, Educational Technology Research & Development, and Journal of Computer Assisted Learning) from 2001 to 2005. Among the 1027 articles published in these journals from 2001 to 2005, 444 articles were identified as being related to the topic of cognition in e-learning. These articles were cross analyzed by published years, journal, research topic, and citation count. Furthermore, 16 highly-cited articles across different topics were chosen for further analysis according to their research settings, participants, research design types, and research methods. It was found from the analysis of the 444 articles that “Instructional Approaches,” “Learning Environment,” and “Metacognition” were the three most popular research topics, but the analysis of the citation counts suggested that the studies related to “Instructional Approaches,” “Information Processing” and “Motivation” might have a greater impact on subsequent research. Although the use of questionnaires might still be the main method of gathering research data in e-learning cognitive studies, a clear trend was observed that more and more studies were utilizing learners’ log files or online messages as data sources for analysis. The results of the analysis provided insights for educators and researchers into research trends and patterns of cognition in e-learning.     

Identifying affect elements based on a conceptual model of affect: A case study on a smartphone

The concept of affect has been considered as a requisite for the success of a product in the market. However, ‘affect’ is an ill-defined concept. This study developed a new conceptual model to explain the fundamental concept of affect. Based on this model, a systematic procedure of affect element identification was proposed using a literature review, a focus group interview, an internet survey and statistical analyses. Affect elements of smartphones were classified into two parts: appearance and applications. The results of this study are expected to help developers understand the nature of affect. The systematic approach proposed in the study can be applied with minor modifications to identify affect elements of other smart products.Relevance to industryThis study proposed a conceptual model of affect and identified affect elements of smartphones. The list of affect elements will be helpful for developing and evaluating smartphones including diverse types of smart products.     

A mathematical model to calculate real cost/performance in software distributed shared memory on computing environments

One of the important factors in high-performance computing (HPC) is the cost/performance ratio. Calculation of cost/performance ratio is the main criterion for the separation of hardware computing systems (supercomputers) from software computing systems (Cluster, Grid, Peer-to-Peer). There are various economic methods to calculate hardware cost. In addition, there are numerous methods in software engineering to calculate the cost of developing and programming the scientific and engineering software. The computing power in the aforementioned systems is basically calculated with programs like LINPACK and HPCL. The inter-process communication is considered as a variable in calculating the cost of executing the scientific programs, whose nature and amount depends on the program execution itself. As there is a high dependency of effective variables in cost calculation of inter-process communications during the program execution, it should be used for calculating the cost of any application. This paper complements the existing methods by presenting a more comprehensive and accurate method to calculate the real cost of distributed shared memory (DSM) mechanisms used by HPC Systems. Therefore, a systematic method has been used to achieve a whole equation for DSM costing, determine the effective factors of the cost, and propose a method based on costing economic methods. Effective parameters are classified into two groups, namely DSM-inhere dependent and application-specific dependent parameters. Each parameter is presented and discussed, and the correlation between them specifies the system’s weight on DSM real cost according to which the cost is modeled and validated analytically.     

Personality and its effects on learning performance: Design guidelines for an adaptive e-learning system based on a user model

An increasingly widespread interest in developing fully adaptable e-learning systems (e.g., intelligent tutoring systems) has led to the development of a wide range of adaptive processes and techniques. In particular, advances in these systems are based on optimization for each user's learning style and characteristics, to enable a personalized learning experience. Current techniques are aimed at using a learner's personality traits and its effect on learning preferences to improve both the initial learning experience and the information retained (e.g., top-down or bottom-up learning organization). This study empirically tested the relationship between a learner's personality traits, analyzed the effects of these traits on learning preferences, and suggested design guidelines for adaptive learning systems. Two controlled experiments were carried out in a computer-based learning session. Our first experiment showed a significant difference in the learning performance of participants who were identified as introverts vs. those who were identified as being extroverts, according to the MBTI scale. As the distinction between extroverted personality types vs. introverted personality types showed the strongest correlation in terms of different learning styles, we used this criteria in our second experiment to determine whether design guidelines for appropriate content organization could reinforce the aforementioned correlation between personality type and learning experience.     

A new time invariant fuzzy time series forecasting method based on particle swarm optimization

In the analysis of time invariant fuzzy time series, fuzzy logic group relationships tables have been generally preferred for determination of fuzzy logic relationships. The reason of this is that it is not need to perform complex matrix operations when these tables are used. On the other hand, when fuzzy logic group relationships tables are exploited, membership values of fuzzy sets are ignored. Thus, in defiance of fuzzy set theory, fuzzy sets’ elements with the highest membership value are only considered. This situation causes information loss and decrease in the explanation power of the model. To deal with these problems, a novel time invariant fuzzy time series forecasting approach is proposed in this study. In the proposed method, membership values in the fuzzy relationship matrix are computed by using particle swarm optimization technique. The method suggested in this study is the first method proposed in the literature in which particle swarm optimization algorithm is used to determine fuzzy relations. In addition, in order to increase forecasting accuracy and make the proposed approach more systematic, the fuzzy c-means clustering method is used for fuzzification of time series in the proposed method. The proposed method is applied to well-known time series to show the forecasting performance of the method. These time series are also analyzed by using some other forecasting methods available in the literature. Then, the results obtained from the proposed method are compared to those produced by the other methods. It is observed that the proposed method gives the most accurate forecasts.     

From laser-scanned data to feature human model: a system based on fuzzy logic concept

This paper describes the development of a prototype system using fuzzy logic concept for constructing a feature human model, which is to be stored in a 3D digital human model database. In our approach, the feature human model is constructed by unorganized cloud points obtained from 3D laser scanners. Firstly, noisy points are removed, and the orientation of the human model is adjusted; secondly, a feature based mesh generation algorithm is applied on the cloud points to construct the mesh surface of a human model; lastly, semantic features of the human model are extracted from the mesh surface. Compared with earlier approach, our method strongly preserves the topology of a human model; more details can be constructed; and both the robustness and the efficiency of the algorithm are improved. At the end of the paper, in order to demonstrate the functionality of feature human models, potential applications are given.     

A genetic fuzzy system to model pedestrian walking path in a built environment

A study on the pedestrian’s steering behaviour through a built environment in normal circumstances is presented in this paper. The study focuses on the relationship between the environment and the pedestrian’s walking trajectory. Owing to the ambiguity and vagueness of the relationship between the pedestrians and the surrounding environment, a genetic fuzzy system is proposed for modelling and simulation of the pedestrian’s walking trajectory confronting the environmental stimuli. We apply the genetic algorithm to search for the optimum membership function parameters of the fuzzy model. The proposed system receives the pedestrian’s perceived stimuli from the environment as the inputs, and provides the angular change of direction in each step as the output. The environmental stimuli are quantified using the Helbing social force model. Attractive and repulsive forces within the environment represent various environmental stimuli that influence the pedestrian’s walking trajectory at each point of the space. To evaluate the effectiveness of the proposed model, three experiments are conducted. The first experimental results are validated against real walking trajectories of participants within a corridor. The second and third experimental results are validated against simulated walking trajectories collected from the AnyLogic® software. Analysis and statistical measurement of the results indicate that the genetic fuzzy system with optimised membership functions produces more accurate and stable prediction of heterogeneous pedestrians’ walking trajectories than those from the original fuzzy model.     

A fuzzy regression model based on distances and random variables with crisp input and fuzzy output data: a case study in biomass production

Least-squares technique is well-known and widely used to determine the coefficients of a explanatory model from observations based on a concept of distance. Traditionally, the observations consist of pairs of numeric values. However, in many real-life problems, the independent or explanatory variable can be observed precisely (for instance, the time) and the dependent or response variable is usually described by approximate values, such as “about £300pounds300” or “approximately $500”, instead of exact values, due to sources of uncertainty that may affect the response. In this paper, we present a new technique to obtain fuzzy regression models that consider triangular fuzzy numbers in the response variable. The procedure solves linear and non-linear problems and is easy to compute in practice and may be applied in different contexts. The usefulness of the proposed method is illustrated using simulated and real-life examples.     

A cloud‐based responsive replenishment system in a franchise business model using a fuzzy logic approach

In today's volatile markets, increasingly unpredictable customer demand is exerting great challenges to responsive replenishment. The complexity of responsive replenishment is higher when the business is global in which demand in both domestic and overseas markets has to be catered for. The emergence of cloud computing has eased the difficulties as it allows nearly real‐time access to a universal platform for information sharing between franchisors and franchisees, creating huge opportunities for understanding global market needs for responsive replenishment. Considering the existence of uncertainties due to the fluctuating demands, fuzzy logic is useful in providing decision support for replenishment in uncertain environments. This paper presents a cloud‐based responsive replenishment system to manage operation data of a franchise business using cloud computing, and for analysis using fuzzy logic in order to provide franchisors with the required inventory levels. To the best of our knowledge, this is the first study that applies cloud computing and artificial intelligence techniques in franchising. A pilot run of the system is conducted in an education company, which is considered to be a good representation of an industry operating with a franchise model. The results show that the system allows franchisors to formulate effective responsive replenishment strategies.     

A communication model based on the 2-tuple fuzzy linguistic representation for a distributed intelligent agent system on Internet

 Internet users are assisted by means of distributed intelligent agents in the information gathering process to find the fittest information to their needs. In this paper we present a distributed intelligent agent model where the communication of the evaluation of the retrieved information among the agents is carried out by using linguistic operators based on the 2-tuple fuzzy linguistic representation as a way to endow the retrieval process with a higher flexibility, uniformity and precision. The 2-tuple fuzzy linguistic representation model allows to make processes of computing with words without loss of information.     

基于认知模型的室内移动服务机器人人机耦合协同作业机制

针对老年人和残疾人这类特殊用户群体与服务机器人构成的人机智能系统,提出了基于ACT-R(理性思维的适应性控制)认知架构模型的室内移动服务机器人人机耦合协同作业机制.基于ACT-R认知架构对人机一体化室内移动服务机器人人机协同作业系统进行了总体设计,利用简单自然的人机效应通道,设计了基于ACT-R认知架构的人机耦合界面;通过人-机-环境空间感知耦合,提出并建立了室内移动服务机器人人机一体化协同决策作业机制.最后在室内环境下进行移动服务机器人人机协同作业实验,系统安全高效地完成了作业任务,验证了该机制的有效性.     

micrOMEGAs 2.0: A program to calculate the relic density of dark matter in a generic model

micrOMEGAs 2.0 is a code which calculates the relic density of a stable massive particle in an arbitrary model. The underlying assumption is that there is a conservation law like R-parity in supersymmetry which guarantees the stability of the lightest odd particle. The new physics model must be incorporated in the notation of CalcHEP, a package for the automatic generation of squared matrix elements. Once this is done, all annihilation and coannihilation channels are included automatically in any model. Cross-sections at v=0, relevant for indirect detection of dark matter, are also computed automatically. The package includes three sample models: the minimal supersymmetric standard model (MSSM), the MSSM with complex phases and the NMSSM. Extension to other models, including non-supersymmetric models, is described.

Program summary

Title of program:micrOMEGAs2.0Catalogue identifier:ADQR_v2_0Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADQR_v2_0Program obtainable from: CPC Program Library, Queen's University of Belfast, N. IrelandComputers for which the program is designed and others on which it has been tested:PC, Alpha, Mac, SunOperating systems under which the program has been tested:UNIX (Linux, OSF1, SunOS, Darwin, Cygwin)Programming language used:C and FortranMemory required to execute with typical data:17 MB depending on the number of processes requiredNo. of processors used:1Has the code been vectorized or parallelized:noNo. of lines in distributed program, including test data, etc.:91 778No. of bytes in distributed program, including test data, etc.:1 306 726Distribution format:tar.gzExternal routines/libraries used:noCatalogue identifier of previous version:ADQR_v1_3Journal reference of previous version:Comput. Phys. Comm. 174 (2006) 577Does the new version supersede the previous version:yesNature of physical problem:Calculation of the relic density of the lightest stable particle in a generic new model of particle physics.Method of solution: In numerically solving the evolution equation for the density of dark matter, relativistic formulae for the thermal average are used. All tree-level processes for annihilation and coannihilation of new particles in the model are included. The cross-sections for all processes are calculated exactly with CalcHEP after definition of a model file. Higher-order QCD corrections to Higgs couplings to quark pairs are included.Reasons for the new version:There are many models of new physics that propose a candidate for dark matter besides the much studied minimal supersymmetric standard model. This new version not only incorporates extensions of the MSSM, such as the MSSM with complex phases, or the NMSSM which contains an extra singlet superfield but also gives the possibility for the user to incorporate easily a new model. For this the user only needs to redefine appropriately a new model file.Summary of revisions:

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Possibility to include in the package any particle physics model with a discrete symmetry that guarantees the stability of the cold dark matter candidate (LOP) and to compute the relic density of CDM.

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Compute automatically the cross-sections for annihilation of the LOP at small velocities into SM final states and provide the energy spectra for final states.

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For the MSSM with input parameters defined at the GUT scale, the interface with any of the spectrum calculator codes reads an input file in the SUSY Les Houches Accord format (SLHA).

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Implementation of the MSSM with complex parameters (CPV-MSSM) with an interface to CPsuperH to calculate the spectrum.

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Routine to calculate the electric dipole moment of the electron in the CPV-MSSM.

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In the NMSSM, new interface compatible with NMHDECAY2.1.

Typical running time:0.2 secUnusual features of the program:Depending on the parameters of the model, the program generates additional new code, compiles it and loads it dynamically.     

A dialog switching strategy for information retrieval in noisy environments based on a confidence score

This paper presents a dialog switching strategy for information retrieval in human–robot dialog in order to cope with different intensities of background noise. The strategy dynamically switches between a more open and a closed dialog scheme based on a continuously adapted confidence score evaluating resulting numbers of cases of recognition and non-recognition of user speech, which are dependent on the level of background noise. Thereby, more natural and more robust dialog components are balanced, respectively. Experimental results are presented, illustrating the effectiveness of the approach.     

A fuzzy model to control the temperature in the cooling of metal molds with a spray robot

In a die-casting operation, the die spray is the key to quality and productivity, but the die-spray operation depends on parameter settings such as the spray volume and the operator's experience, even when a robot sprayer is used. The purpose of this study was to establish an intelligent system to control the surface temperature of a die with a water-based mist spray. A fuzzy model was applied to determine the optimum mist spray volume. The results generated show a good match with the actual measurements of the rate of the temperature drop versus the spray-mist volume. After the fuzzy analysis, the spray parameters calculated were used to control an actual die temperature experiment conducted on a heated plate model. The fuzzy model constructed by using fundamental experiments allowed the die spray operation to maintain a predetermined spray volume. This work was presented in part at the Fourth International Symposium on Artificial Life and Robotics, Oita, Japan, January 19–22, 1999