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Systems, Man and Cybernetics, Part A: Systems and Humans, IEEE Transactions on

Issue 5 • Date Sept. 2011

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Displaying Results 1 - 23 of 23
  • Table of contents

    Publication Year: 2011 , Page(s): C1 - 825
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans publication information

    Publication Year: 2011 , Page(s): C2
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  • Special Issue on Social Media Analytics: Understanding the Pulse of the Society

    Publication Year: 2011 , Page(s): 826 - 827
    Cited by:  Papers (1)
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  • Mining Evolutionary Topic Patterns in Community Question Answering Systems

    Publication Year: 2011 , Page(s): 828 - 833
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (898 KB) |  | HTML iconHTML  

    Community Question Answering (CQA) is becoming a popular Web 2.0 application. By analyzing evolutionary topic patterns from CQA applications, one can gain insights into user interests and user responses to external events. This paper proposes a novel evolutionary topic pattern mining approach. This approach consists of three components: 1) extraction of the topics being discussed through a temporal analysis; 2) discovery of topic evolutions and construction of evolutionary graphs of extracted topics; and 3) life cycle modeling of the extracted topics. We show empirically the effectiveness of our approach using two real-world data sets. View full abstract»

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  • Query-Guided Event Detection From News and Blog Streams

    Publication Year: 2011 , Page(s): 834 - 839
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (344 KB) |  | HTML iconHTML  

    With the advent of Web 2.0, searching and publishing became two major forms of online activities for web users. When an event happens, web users would search for the latest information about the event as well as publish blog posts to discuss the event. Both the queries from users and the blog posts published give strong indications of the real-world events of users' concern. In this paper, we propose to study query-guided event detection from two parallel document streams (i.e., news and blog). Our goal is to group user queries, news articles, and blog posts into events to which they are related. The evolution of an event is reflected by the changes in both the query keywords and news/blogs content during the event happening period. We propose a two-stage real-time event detection framework consisting of event fragment detection and event detection. The proposed framework integrates queries, news articles, and blog posts through the notion of query profile. In our experiments, we evaluate the proposed framework using real-world data collected from Technorati and Google News. View full abstract»

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  • Exploiting the Social Tagging Network for Web Clustering

    Publication Year: 2011 , Page(s): 840 - 852
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1133 KB) |  | HTML iconHTML  

    Social tagging is a major characteristic of Web 2.0. A social tagging system can be modeled with a tripartite network of users, resources, and tags. In this paper, we investigate how to enhance Web clustering by leveraging the tripartite network of social tagging systems. We propose a clustering method called “Tripartite Clustering” which clusters the three types of nodes (resources, users, and tags) simultaneously by only utilizing the links in the social tagging network. We also investigate two other approaches to exploit social tagging for clustering with K-means and Link K-means. All the clustering methods are experimented on a real-world social tagging data set sampled from del.icio.us. The clustering results are evaluated against a human-maintained Web directory. The experimental results show that the social tagging network is a very useful information source for document clustering. All social-annotation-based clustering methods can significantly improve the performance of content-based clustering. Compared to social-annotation-based K-means and Link K-means, Tripartite Clustering achieves equivalent or better performance and produces more useful information. View full abstract»

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  • Determining Content Power Users in a Blog Network: An Approach and Its Applications

    Publication Year: 2011 , Page(s): 853 - 862
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (972 KB) |  | HTML iconHTML  

    In a blog network, there are special users who induce other users to actively utilize blogs. Identifying such influential users is important when establishing business policy and business models for the blog network. This paper defines the users whose contents exhibit significant influence over other users as content power users (CPUs) and proposes a method of identifying them. We analyze the performance of the proposed method by applying it to an actual blog network and comparing its results with those of preexisting methods for determining power users. The experimental results demonstrate that the definition of CPUs is adequate to address the dynamic nature of the blogosphere and the main concerns of the blog industry. We also discuss the business models based on CPUs that could be used to stimulate user activities in a blog network. View full abstract»

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  • Design of an Airborne Three-Dimensional Separation Assistance Display

    Publication Year: 2011 , Page(s): 863 - 875
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (881 KB) |  | HTML iconHTML  

    In the context of the Next Generation Air Transportation System and Single European Sky ATM Research future airspace programs, this paper describes a concept for an airborne separation assurance display that is designed to aid pilots in their task of self-separation, by visualizing the possibilities for conflict resolution that the airspace provides. This paper is part of an ongoing research toward an ecological design of a separation assistance interface that can present all the relevant properties of the spatiotemporal separation problem. A work-domain analysis is described from which several perspective projections of traffic properties and travel constraints are derived. A display concept is proposed that presents heading and altitude action possibilities in a flight-path angle-track angle action space. Key issues in the current design are discussed, with recommendations for future work. View full abstract»

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  • Metazoa Ludens: Mixed-Reality Interaction and Play for Small Pets and Humans

    Publication Year: 2011 , Page(s): 876 - 891
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1084 KB) |  | HTML iconHTML  

    Although animals and pets are so important for families and society, in modern urban lifestyles, we can only spend little time with our animal friends. Interactive media should be aimed to enhance not only human-to-human communication but also human-to-animal communication. Thus, we promote a new type of interspecies media interaction which allows human users to interact and play with their small pet friends (in this case, hamsters) remotely via the Internet through a mixed-reality-based game system “Metazoa Ludens.” We used a two-pronged approach to scientifically examine the system. First, and most importantly, the body condition score study was conducted to evaluate the positive effects to the hamsters. Second, the method of Duncan was used to assess the strength of preference of the hamsters toward Metazoa Ludens. Lastly, the effectiveness of this remote interaction with respect to the human users as an interactive gaming system with their pets/friends (hamster) was examined based on Csikszentmihalyi's Flow theory. Results of both studies inform of positive remote interaction between human users and their pet friends using our research system. This research is not only just aimed at providing specific experimental results on the implemented research system but is also aimed as a wider lesson for human-to-animal interactive media. Therefore, as an addition, we present a detailed framework suited in general for human-to-animal interaction systems inferred from the lessons learned. View full abstract»

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  • Fuzzy Segmentation for the Exploratory Analysis of Multidimensional Signals: Example From a Study on Driver Overtaking Behavior

    Publication Year: 2011 , Page(s): 892 - 904
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1064 KB) |  | HTML iconHTML  

    This paper explains the key role played by windowing in the preliminary analysis of multifactor and multivariate (MFMV) databases. The explanation is based on the general case of a database featuring quantitative or qualitative measurement variables and a hyperparallelepipedic structure in which the directions correspond to the factors. In order to maintain the MFMV aspects of this data structure, the windowing approach as described in this paper does not reduce the information as much as most of the basic non-windowing summarizing procedures using the standard statistical indicators. First, the data in each cell of the hyperparallelepiped are transformed into membership values that can be averaged over factors, such as time or individuals. Then, these membership values may be potentially investigated into with several graphic techniques; for this paper, multiple correspondence analysis (MCA) was chosen. The presentation fall into two parts. First, a didactic example based on a simulated data set describes the approach in comparison with more traditional approaches, and then a real data set, with multidimensional signals recorded for 34 subjects in 15 experimental overtaking situations, is used to demonstrate the power of the “space windowing/MCA” pair on a large real database. Next, the discussion section weighs out the pros and the cons of using space windowing to perform a preliminary analysis of a large MFMV database in studies of human component systems. View full abstract»

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  • A Loosely Coupled Integration Environment for Collaborative Applications

    Publication Year: 2011 , Page(s): 905 - 916
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (881 KB) |  | HTML iconHTML  

    In the computer-supported cooperative work domain, researchers have always wondered about which principles and models to adopt for the development of collaborative applications capable to really meet users' needs. However, these requirements are often unpredictable and depend on several task- or environment-related factors. Integrated collaborative environments are rarely open, extensible, and reconfigurable enough so as to meet these requirements. This paper presents an environment, called loosely coupled environment for integrating collaborative applications (LEICA), allowing the integration of existing collaborative applications. LEICA adopts a loosely coupled integration approach which is based on Web Services technology, an Event Notification System, and the definition of Collaboration Policies to control the interactions between integrated applications. LEICA allows different functionalities of existing applications to be dynamically combined and controlled, enhancing its flexibility. Through a case study, we show how LEICA was successfully used to integrate three collaborative applications: a Co-browsing tool, an instant messaging tool, and a Voice over Internet Protocol Conference Controller. View full abstract»

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  • One-Shot Decision Theory

    Publication Year: 2011 , Page(s): 917 - 926
    Cited by:  Papers (5)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (341 KB) |  | HTML iconHTML  

    This paper focuses on one-shot (one-time) decision problems, which concern the situations where a decision is experienced only once. Such one-shot decision problems are commonly encountered in business, economics, and social systems. The one-shot decision process comprises two steps. In the first step, a decision maker identifies which state of nature should be taken into account for each alternative among all available states of nature. These identified states of nature are called focus points. Twelve types of focus points are proposed according to a decision maker's attitudes about the possibility of a state of nature and satisfaction resulted by its occurrence. In the second step, a decision maker evaluates the alternatives based on focus points where the consequences provided by all alternatives are compared with each other to obtain the best alternative. The relationships between different focus points are analyzed. An example, which is a newsvendor problem of a new product with a short life cycle, is used to illustrate the one-shot decision. The results of analysis show that the proposed decision models can provide useful insights into understanding different behaviors of decision makers and help the decision maker in finding out the best solution according to his/her attitude about possibility and satisfaction. View full abstract»

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  • Fuzzy Nonlinear Models for New Product Development Using Four-Phase Quality Function Deployment Processes

    Publication Year: 2011 , Page(s): 927 - 945
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (620 KB) |  | HTML iconHTML  

    Quality function deployment (QFD) frameworks are useful tools for constructing a new product development (NPD) plan that enables the clear itemization of customer needs and the systematic evaluation of each solution to maximize customer satisfaction. A complete QFD process includes four sequential phases in which four important decision outcomes are determined for NPD, namely, the fulfillment levels of design requirements (DRs), part characteristics, process parameters, and production requirements. Unlike prior studies which have focused only on determining DRs, this paper extends Chen and Ko's models to consider the close link between the four phases in NPD using the means-end chain concept to build up a series of fuzzy nonlinear programming models for determining the fulfillment levels of each decision outcome for customer satisfaction. In addition, this paper incorporates risk analysis, which is treated as the constraint in the models, into the QFD process. To deal with the vague nature of product development processes, fuzzy sets are applied for both QFD and risk analysis. A numerical example is used to demonstrate the applicability of the proposed model. View full abstract»

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  • A Multi-Agent Memetic System for Human-Based Knowledge Selection

    Publication Year: 2011 , Page(s): 946 - 960
    Cited by:  Papers (3)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (832 KB) |  | HTML iconHTML  

    In these last decades, both industrial and academic organizations have used extensively different learning methods to improve humans' capabilities and, as consequence, their overall performance and competitiveness in the new economy context. However, the rapid change in modern knowledge due to exponential growth of information sources is complicating learners' activity. At the same time, new technologies offer, if used in a right way, a range of possibilities for the efficient design of learning scenarios. For that reason, novel approaches are necessary to obtain suitable learning solutions which are able to generate efficient, personalized, and flexible learning experiences. From this point of view, computational intelligence methodologies can be exploited to provide efficient and intelligent tools to be able to analyze learner's needs and preferences and, consequently, personalize its knowledge acquirement. This paper reports an attempt to achieve these results by exploiting an ontological representation of learning environment and an adaptive memetic approach, integrated into a cooperative multi-agent framework. In particular, a collection of agents analyzes learner preferences and generate high-quality learning presentations by executing, in a parallel way, different cooperating optimization strategies. This cooperation is performed by jointly exploiting data mining via fuzzy decision trees, together with a decision-making framework exploiting fuzzy methodologies. View full abstract»

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  • A Systematic Approach to Model Checking Human–Automation Interaction Using Task Analytic Models

    Publication Year: 2011 , Page(s): 961 - 976
    Cited by:  Papers (9)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (958 KB) |  | HTML iconHTML  

    Formal methods are typically used in the analysis of complex system components that can be described as “automated” (digital circuits, devices, protocols, and software). Human-automation interaction has been linked to system failure, where problems stem from human operators interacting with an automated system via its controls and information displays. As part of the process of designing and analyzing human-automation interaction, human factors engineers use task analytic models to capture the descriptive and normative human operator behavior. In order to support the integration of task analyses into the formal verification of larger system models, we have developed the enhanced operator function model (EOFM) as an Extensible Markup Language-based, platform- and analysis-independent language for describing task analytic models. We present the formal syntax and semantics of the EOFM and an automated process for translating an instantiated EOFM into the model checking language Symbolic Analysis Laboratory. We present an evaluation of the scalability of the translation algorithm. We then present an automobile cruise control example to illustrate how an instantiated EOFM can be integrated into a larger system model that includes environmental features and the human operator's mission. The system model is verified using model checking in order to analyze a potentially hazardous situation related to the human-automation interaction. View full abstract»

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  • Pattern- and Network-Based Classification Techniques for Multichannel Medical Data Signals to Improve Brain Diagnosis

    Publication Year: 2011 , Page(s): 977 - 988
    Cited by:  Papers (6)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (561 KB) |  | HTML iconHTML  

    There is an urgent need for a quick screening process that could help neurologists diagnose and determine whether a patient is epileptic versus simply demonstrating symptoms linked to epilepsy but actually stemming from a different illness. An inaccurate diagnosis could have fatal consequences, particularly in operating rooms and intensive care units. Electroencephalogram (EEG) has been traditionally used, as a gold standard, to diagnose patients by evaluating those brain functions that might correspond to epilepsy and other brain disorders. This research therefore focuses on developing new classification techniques for multichannel EEG recordings. Two time-series classification techniques, namely, Support Feature Machine (SFM) and Network-Based Support Vector Machine (SVM) (NSVM), are proposed in this paper to predict from EEG readings whether a person is epileptic or nonepileptic. The SFM approach is an optimization model that maximizes classification accuracy by selecting a group of electrodes (features) that has strong class separability based on time-series similarity measures and correctly classifies EEG samples in the training phase. The NSVM approach integrates a new network-based model for multidimensional time-series data with traditional SVMs to exploit both the spatial and temporal characteristics of EEG data. The proposed techniques are tested on two EEG data sets acquired from ten and five patients, respectively. Compared with other commonly used classification techniques such as SVM and decision trees, the proposed SFM and NSVM techniques provide very promising and practical results and require much less time and memory resources than traditional techniques. This study is a necessary application of data mining to advance the diagnosis and treatment of human epilepsy. View full abstract»

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  • Metric Optimization-Based Design of Systems Subject to Hostile Disruptions

    Publication Year: 2011 , Page(s): 989 - 1000
    Cited by:  Papers (4)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (944 KB) |  | HTML iconHTML  

    In many applications, engineering systems are required to operate acceptably well in hostile environments. In the past, survivability engineering has addressed this requirement using heuristic rule-based design approaches followed by analysis to determine if survivability constraints have been satisfied. The treatment of survivability as a constraint rather than an independent design objective hinders the ability of system engineers to trade off survivability with other design objectives, such as cost and performance. Herein, the survivability problem is posed in terms of maximizing expected performance and minimizing the risk of unacceptable performance. Design metrics that allow optimal selection of systems on the basis of these survivability dimensions are presented. The metrics are part of a systematic approach to system engineering in which survivability concerns are quantified and individual systems and entire classes of systems can be compared objectively. These metrics are a necessary step toward an integrated design process wherein tradeoffs between all design objectives can be identified. This methodology is demonstrated on the design of a notional electric warship integrated engineering plant (IEP) that is subject to hostile disruptions posed by antiship missiles. By use of this method, the performance of the IEP is shown to be improved. View full abstract»

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  • Face Recognition With an Improved Interval Type-2 Fuzzy Logic Sugeno Integral and Modular Neural Networks

    Publication Year: 2011 , Page(s): 1001 - 1012
    Cited by:  Papers (18)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (855 KB) |  | HTML iconHTML  

    In this paper, a modification of the Sugeno integral with interval type-2 fuzzy logic is proposed. The modification includes changing the original equations of the Sugeno Measures and the Sugeno integral that were initially proposed for type-1 fuzzy logic. The proposed modification enables calculation of the interval type-2 Sugeno integral for combining multiple source of information with a higher degree of uncertainty than with the traditional type-1 Sugeno integral. The advantages of the interval type-2 Sugeno integral are illustrated by reporting improved recognition rates in benchmark face databases. This new concept could also be a useful tool in other areas of applications. Also, the improvement provided by the type-2 integral is verified to be statistically significant in the recognition results for complex face databases (like the FERET database) when compared with the type-1 Sugeno integral. The proposed Sugeno integral is used to combine the modules' outputs of a modular neural network for face recognition. Simulation results show that the interval type-2 Sugeno integral is able to improve the recognition rate for the benchmark face databases. Recognition results are better or comparable to results produced by alternative approaches present in the literature reported for the same benchmark problems. View full abstract»

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  • OInduced: An Efficient Algorithm for Mining Induced Patterns From Rooted Ordered Trees

    Publication Year: 2011 , Page(s): 1013 - 1025
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1040 KB) |  | HTML iconHTML  

    Frequent tree patterns have many practical applications in different domains, such as Extensible Markup Language mining, Web usage analysis, etc. In this paper, we present OInduced , which is a novel and efficient algorithm for finding frequent ordered induced tree patterns. OInduced uses a breadth-first candidate generation method and improves it by means of an indexing scheme. We also introduce frequency counting using tree encoding. For this purpose, we present two novel tree encodings, namely, m-coding and cm-coding, and show how they can restrict nodes of input trees and compute frequencies of generated candidates. We perform extensive experiments on both real and synthetic data sets to show the efficiency and scalability of OInduced. View full abstract»

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  • A Component-Based Approach for the Development of Automated Systems

    Publication Year: 2011 , Page(s): 1026 - 1031
    Cited by:  Papers (1)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (240 KB) |  | HTML iconHTML  

    This paper addresses a component-based approach using the Event-B method to develop automated systems. These systems are composed of two parts: the control part (controller) and the operative part (controlled component). The first is a software component which controls the operative part that models the physical device and its environment. We propose in this paper the use of the formal Event-B method to develop automated systems applying a codesign technique, where the two components are developed separately, and then, a composition is defined with the Event-B method to prove the automated system correctness. First of all, we define a specification for the composition of these two components in the Event-B method. Second, we give refinement semantics for a component-based system before proposing a method to verify the refinement of a whole system from that of its components. View full abstract»

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  • Macrodynamics Analysis of Migration Behaviors in Large-Scale Mobile Agent Systems for the Future Internet

    Publication Year: 2011 , Page(s): 1032 - 1036
    Cited by:  Papers (2)
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (319 KB) |  | HTML iconHTML  

    Network services in the future Internet are required to be highly available, ubiquitous, self-managing, and adaptable to dynamic environments. A promising way to implement such network services is combining mobile agent approaches with ecosystem-inspired evolutionary approaches. However, this perspective is still far from being practically implemented. An important reason is a lack of fundamental theory on macrodynamics of mobile agents in the new paradigm. This paper considers a type of large-scale mobile agent system and discusses the macrodynamics mainly affected by mobile agents' migration behaviors in the systems. The study benefits not only the design of composite services emerged from mobile agents in a type of ecosystem-inspired network architecture but also the future deployment of an Internet-scale system that holds myriads of mobile agents, hosts, and migratory behaviors of mobile agents. View full abstract»

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  • IEEE Systems, Man, and Cybernetics Society Information

    Publication Year: 2011 , Page(s): C3
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  • IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans Information for authors

    Publication Year: 2011 , Page(s): C4
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Aims & Scope

The fields of systems engineering and human machine systems: systems engineering includes efforts that involve issue formulation, issue analysis and modeling, and decision making and issue interpretation at any of the lifecycle phases associated with the definition, development, and implementation of large systems.

 

This Transactions ceased production in 2012. The current retitled publication is IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Witold Pedrycz
University of Alberta