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In this article the author cites the five papers presented in the "Institute of Electrical and Electronics Engineers (IEEE) First International Conference on Biometrics: Theory, Applications, and Systems," or BTAS 07, held in Washington, D.C. on September 27-29, 2009. It states that the papers received positive reviews and were revised for the special section of "IEEE Transactions on Systems, Man, and Cybernetics-Part A." Among these papers were authored by Elaine Newton and P. Jonathan Phillips, and Andreas Humm and colleagues from the University of Fribourg in Switzerland.

Nonverbal vocal interaction (NVVI) is an input modality by means of which users control the computer by producing sounds other than speech. Previous research in this field has focused mainly on studying isolated instances of NVVI (such as mouse cursor control in computer games) and their performance. This paper presents a study with 36 elderly users in which basic NVVI vocal gestures (commands) were ranked by their perceived fatigue, satisfaction, and efficiency. The results of this study inspired a set of NVVI gesture design guidelines that are also presented in this paper. [ABSTRACT FROM PUBLISHER]

There is increasing need for agencies to coordinate their interdependent risk assessment, risk management, and risk communication activities in compliance with risk program guidelines. In particular, there is a challenge to measure risk program compliance and maturity to guidelines such as the U.S. Office of Management and Budget (OMB) memorandum “Updated Principles for Risk Analysis” among others. This paper demonstrates a systemic approach to evaluate large-scale risk program maturity with utilization of business process modeling and self-assessment methods. This approach will be helpful to agencies implementing risk guidelines such as those of the OMB, the U.S. Government Accountability Office, the U.S. Department of Homeland Security, the U.S. Department of Defense, and others. This paper will be of interest to risk managers, agencies, and risk and safety analysts engaged in the conception, implementation, and evaluation of risk and safety programs. [ABSTRACT FROM PUBLISHER]

This paper presents a novel concept of modeling biological systems by means of preserving the natural rules governing the system's dynamics, i.e., their intrinsic fractal (recurrent) structure. The purpose of this paper is to illustrate the capability of recurrent ladder networks to capture the intrinsic recurrent anatomy of neural networks and to provide a dynamic model which shows typical neuronal phenomena, such as the phase constancy. As an illustrating example, the simplified model for a neural network consisting of motor neurons is used in simulation of a recurrent ladder network. Starting from a generalized approach, it is shown that, in the steady state, the result converges to a constant-phase behavior. The outcome of this paper indicates that the proposed model is a suitable tool for specific neural models in various neuroscience applications, being able to capture their fractal structure and the corresponding fractal dynamic behavior. A link to the dynamics of EEG activity is suggested. By studying specific neural populations by means of the ladder network model presented in this paper, one might be able to understand the changes observed in the EEG with normal aging or with neurodegenerative disorders. [ABSTRACT FROM PUBLISHER]

Team working is becoming increasingly important in modern organizations due to its beneficial outcomes. A team's performance levels are determined by complex interactions between the attributes of its individual members, the communication and dynamics between members, the working environment, and the team's work tasks. As organizations evolve, so too does the nature of team working. During the past two decades, product development in engineering organizations has increasingly been undertaken by multidisciplinary integrated product teams. Such increasing complexity means that the nature of research methods for studying teams must also evolve. Accordingly, this paper proposes an agent-based modeling approach for simulating team working within an engineering environment, informed by research conducted in two engineering organizations. The model includes a number of variables at an individual level (competency, motivation, availability, response rate), team level (communication, shared mental models, trust), and task level (difficulty, workflow), which jointly determine team performance (quality, time to complete the task, time spent working on the task). In addition to describing the model's development, the paper also reports the results of various simulation runs that were conducted in response to realistic team working scenarios, together with its validation. Finally, the paper discusses the model's practical applications as a tool for facilitating organizational decision making with respect to optimizing team working. [ABSTRACT FROM PUBLISHER]

An ensemble empirical mode decomposition (EEMD)-based approach was developed to extract steady-state visual evoked potentials (SSVEPs) for wireless handling of a small robot car. Three visual stimuli, flickering at 13, 14, and 15 Hz, were displayed on a liquid crystal display monitor to induce user's SSVEPs. The induced SSVEPs were used to control three movement functions (forward, left, and right) of the small robot car. Users gazed at one chosen visual stimulus at one time, and the induced SSVEP was recognized to activate the desired movement function. In this paper, all subjects were requested to handle the small robot car to complete an S-shaped course four times. The proposed system utilized only one electroencephalography (EEG) channel placed at the Oz position. The acquired EEG signals were first segmented into 1-s epochs, and each epoch was then decomposed by EEMD into a series of oscillation components, denoted as intrinsic oscillatory functions (IOFs), representing multiscale features of the recorded signal. The SSVEP-related IOFs were then recognized using a matched filter detector (MFD), including a matched filter demodulator and an amplitude detector. The visual stimulus, which contributed maximum power to the MFD, was recognized as the gazed target. In this paper, all subjects could actuate the small robot car using the proposed EEMD-based brain computer interface system to complete an S-shaped course four times; the mean execution time, number of valid detections, and command transfer interval over the 11 subjects were 84.5 s, 51.13 commands, and 1.65 s/command, respectively. [ABSTRACT FROM PUBLISHER]

Managing human resources and skills for information technology (IT) presents a challenging task for executives, more so when new ITs are involved. Lack of familiarity with the technology, the learning curve associated with its incorporation, and the relative paucity of skilled personnel serve to alter the strategies for management of human resources and skills. This paper presents a system dynamics approach for examining alternative strategies for skill management and supporting decisions during the implementation of service-oriented architecture (SOA) in an organization. For projects involving SOA, the initial planning and implementation of the underlying architecture entail higher costs and slower delivery of initial SOA applications. The use of appropriate IT human resource management strategies for SOA projects is critical for successful SOA implementation. The complexity associated with the fluctuating demand for IT skills, coupled with the need for highly skilled senior architects and professional developers in SOA projects, as well as inevitable delays in skill acquisition, makes this a challenging task. This paper examines the impact of alternative staffing strategies under various environmental conditions and provides guidance for staffing decisions. Using a design science methodology, it employs system dynamics as a vehicle for allowing human resource managers to examine the impact of alternative staffing strategies under a variety of environmental conditions. [ABSTRACT FROM PUBLISHER]

This paper presents new warranty cost models subject to two types of warranty periods (warranty and postwarranty periods), minimal repairs, and various types of warranty policies including free repair/replacement warranty and prorata warranty for k-out-of-n systems. Two-dimensional warranty is applied to investigate the warranty cost using repair times and failure times. We obtain the long-run expected cost functions per unit time with respect to both the warranty and postwarranty periods by considering the aspects of both the manufacturer and the customer. This paper considers a periodic preventive maintenance (PM) policy with both corrective maintenance and PM and also determines three decision variables including warranty period, repair time limit, and periodical maintenance cycles, which minimize the long-run expected cost. Numerical examples are discussed to demonstrate the applicability of the methodologies, and results including the three optimum decision-variable solution and their corresponding long-run expected cost per unit are derived. [ABSTRACT FROM PUBLISHER]

Role assignment is a critical task in role-based collaboration. It has three steps, i.e., agent evaluation, group role assignment, and role transfer, where group role assignment is a time-consuming process. This paper clarifies the group role assignment problem (GRAP), describes a general assignment problem (GAP), converts a GRAP to a GAP, proposes an efficient algorithm based on the Kuhn–Munkres (K-M) algorithm, conducts numerical experiments, and analyzes the solutions' performances. The results show that the proposed algorithm significantly improves the algorithm based on exhaustive search. The major contributions of this paper include formally defining the GRAPs, giving a general efficient solution for them, and expanding the application scope of the K-M algorithm. This paper offers an efficient enough solution based on the K-M algorithm that outperforms significantly the exhaustive search approach. [ABSTRACT FROM PUBLISHER]

To address the need for evaluation techniques for complex business processes, also known as workflows, this paper proposes an approach based on generalized stochastic Petri nets (GSPNs). We review ten related approaches published in the last fifteen years and compare them to our approach using a wide range of criteria. On the basis of this evaluation, we observe that the newly proposed approach provides results that are at least as good as those from the most accepted alternatives and holds a number of additional advantages, such as modeling simplicity, improved precision, and model reuse for qualitative analyses. The overall approach is formally defined in this paper, along with the definition of several performance metrics. Part of these metrics can be computed analytically, while the remainder can be obtained by simulating the GSPN. Furthermore, a tool has been developed to translate automatically business process execution language processes into GSPNs. Finally, we present a case study in which we applied the proposed approach, colored Petri net tools, and an industrial tool to obtain performance insights into a realistic workflow. The results were highly similar, demonstrating the feasibility and the accuracy of our approach. [ABSTRACT FROM PUBLISHER]

The blood vessel structure of the sclera is unique to each person, and it can be remotely obtained nonintrusively in the visible wavelengths. Therefore, it is well suited for human identification (ID). In this paper, we propose a new concept for human ID: sclera recognition. This is a challenging research problem because images of sclera vessel patterns are often defocused and/or saturated and, most importantly, the vessel structure in the sclera is multilayered and has complex nonlinear deformations. This paper has several contributions. First, we proposed the new approach for human ID: sclera recognition. Second, we developed a new method for sclera segmentation which works for both color and grayscale images. Third, we designed a Gabor wavelet-based sclera pattern enhancement method to emphasize and binarize the sclera vessel patterns. Finally, we proposed a line-descriptor-based feature extraction, registration, and matching method that is illumination, scale, orientation, and deformation invariant and can mitigate the multilayered deformation effects and tolerate segmentation error. The experimental results show that sclera recognition is a promising new biometrics for positive human ID. [ABSTRACT FROM PUBLISHER]

In human–machine collaboration, automated machines may assist operators in a variety of ways. However, chaotic assistance may lead to negative consequences, which makes the achievement of effective coordination of the different types of assistance all the more important. This paper discusses the classification of assistance on a cognitive basis and a method of coordinating assistance. Cognitive assistance is viewed as a 2-D problem, consisting of when to provide assistance (a control problem) and what assistance to provide (an interface problem). This paper further proposes dynamically controlling cognitive engagement levels to meet the demands of maintaining performance. Cognitive engagement control determines the appropriate moment to provide the proper level of cognitive assistance. To validate the above approach, a driving assistance experiment was conducted on a driving simulator. In the experiment, an intelligent assistance system monitored the real-time driving performance of human drivers, e.g., time headway and lateral deviation. Because of the importance of visual attention in driving performance, the system monitored the cognitive engagement status of drivers by measuring their eye movements with an eye tracker. Through five sessions of car-following driving tests, the coordinated cognitive assistance (named adaptive assistance) was compared with four other types of cognitive assistance: no aid, soft aid , soft intervention, and hard intervention. The experimental results confirmed that coordinated cognitive assistance is the most effective approach to provide assistance in both primary and secondary tasks. It also appears to be more enjoyable and less intrusive when compared with other individual types of cognitive assistance. [ABSTRACT FROM PUBLISHER]

The end-of-life (EOL) disassembly sequencing problem (DSP) has become increasingly important in the process of handling EOL products. This paper proposes a solution procedure for the “EOL DSP”; the procedure is based on a novel soft-computing algorithm that utilizes modified “simplified swarm optimization,” and the procedure combines the precedence preservative operator, feasible solution generator, self-adaptive parameter control, and repetitive pairwise exchange procedures. By taking into consideration the non-deterministic polynomial time (NP)-complete nature of the problem, the proposed algorithm efficiently seeks the optimal disassembly sequence with a novel approach; this approach involves reducing the initial solution space and using a combination of soft-computing algorithms for achieving higher computational efficiency and solution quality. The results presented in this paper show that the proposed algorithm outperforms the existing algorithms in terms of solution quality achieved in a limited computation time. [ABSTRACT FROM PUBLISHER]

In new widespread peer-to-peer (P2P) systems, peers are exposed to great risk due to frequent trading with unfamiliar peers. Therefore, trust and reputation mechanisms become important issues. For computational efficiency, this paper focuses on localized information trust/reputation mechanisms. Previous studies have not paid much attention to the overall distribution of peer interactions. Based on the scale-free feature of real-world networks, we introduce a power-law distribution of the number of neighbors in P2P trust and reputation systems. To rigorously distinguish the effects of the overall considerations introduced herein, we compare the model proposed in this paper with models in previous studies under the same set of parameters. Simulation results show that the proposed model can discern a small difference between real quality of service (QoS) and other peers' feedback while distinguishing the malicious peers, even when the exaggeration coefficient is high. When one or a group of peers change their QoS, the model exhibits a quick reaction to this change. This response is demonstrated by a rapid decrease in reliability when the QoS change is downward and a slow increase when the change is upward. A slow reaction to the upward QoS change may exclude those peers who frequently change their QoS and encourage consistent reliable service providers. [ABSTRACT FROM PUBLISHER]

Effect-based weapon–target pairing assigns weapons to targets for the given desired effects on such targets. The most obvious and natural effects on targets are represented by the percentages of damage of these targets. In this paper, we focus on the generation of input for effect-based weapon–target pairing optimization. One way to generate such input is based on the Joint Munition Effectiveness Manual (JMEM). JMEM allows the evaluation of the weapons. It is a database that contains many tables, and each table contains many different data fields. Because of the sheer size of JMEM, the optimization of weapon–target pairing based on JMEM is currently focused mainly on one target at a time. In other words, the optimization of weapon–target pairing for many targets and weapons is not directly supported by JMEM, although all the necessary data is there. In this paper, we derive an input based on the given JMEM and desired effect(s), which should be useful in the follow-on effect-based weapon–target pairing optimization that is not limited to a single weapon or target. In particular, effect-based weapon–target pairing will rely on the scanning of the attack guidance table that we derive from JMEM to determine a preferred set of weapon combinations for engaging a given set of targets. [ABSTRACT FROM PUBLISHER]

Job deterioration and learning co-exist in many realistic scheduling situations. This paper introduces a general scheduling model that considers the effects of position-dependent learning and time-dependent deterioration simultaneously. In the proposed model, the actual processing time of a job depends not only on the total processing time of the jobs already processed but also on its scheduled position. This paper focuses on the single-machine scheduling problems with the objectives of minimizing the makespan, total completion time, total weighted completion time, discounted total weighted completion time, and maximum lateness based on the proposed model, respectively. It shows that they are polynomially solvable and optimal under certain conditions. Additionally, it presents some approximation algorithms based on the optimal schedules for the corresponding single-machine scheduling problems and analyzes their worst case error bound. [ABSTRACT FROM PUBLISHER]

This paper presents a class of Petri nets, process nets with channels (PNCs) that can model some types of concurrent systems in two aspects: process and interaction. Its significance lies in offering efficient analysis and verification methods for these systems. PNCs belong to the class of extended free choice nets. This paper establishes the conditions to examine their liveness, reversibility, and reachability based on their structural characteristics. Siphons, traps, and a state equation are used to describe these conditions such that analysis techniques based on reachability graphs and siphon enumeration are avoided. A polynomial-time algorithm is presented for the liveness analysis, and an effective method is also given to decide the reachability. A real-world example is used to illustrate the application of PNCs. [ABSTRACT FROM PUBLISHER]

In this correspondence paper, the wavelet transform, which is an important tool in signal and image processing, has been generalized by coalescing wavelet transform and fractional random transform. The new transform, i.e., fractional random wavelet transform (FrRnWT) inherits the excellent mathematical properties of wavelet transform and fractional random transform. Possible applications of the proposed transform are in biometrics, image compression, image transmission, transient signal processing, etc. In this correspondence paper, biometrics is chosen as the primary application; and hence, a new technique is proposed for securing fingerprints during communication and transmission over insecure channel. [ABSTRACT FROM PUBLISHER]

This paper focuses on the decidability status of various forms of behavioral correctness criteria for resource-constrained workflow (RCWF) nets (Petri net models of RCWF systems). These behavioral correctness criteria, usually called soundness criteria, are natural extensions of similar correctness criteria for workflow nets (Petri net models of workflow systems). While all forms of soundness are known to be decidable for workflow nets, only soundness for RCWF nets with just one resource type is known to be decidable. In this paper, we show that if we limit the number of cases, then soundness for RCWF nets with arbitrarily many resource types is decidable. Moreover, we show that some “intermediate” forms of soundness, as well as a restrictive form of structural soundness for RCWF nets, are decidable too. The proof technique is based on instantiation nets as a general tool for dealing with arbitrarily many cases and arbitrarily large resources in workflow nets and RCWF nets. It is also shown why this technique cannot be extended to the most general form of soundness. [ABSTRACT FROM PUBLISHER]

Text summarization techniques have been found to be effective with regard to helping users find relevant information faster. The effectiveness and efficiency of a user's performance in an information-seeking task can greatly be improved if he/she needs to only look at a summary that includes the relevant information presented in his/her preferred manner. On the other hand, if the main idea is misrepresented and/or omitted altogether from a summary, it may take users more time to solve a target problem or, even worse, lead users to make incorrect decisions. There is an important need to design a personalized text summarization system that takes into account both what a user is currently interested in and how a user perceives information. The latter factor is referred to as a user's cognitive styles. Although there are some existing approaches that have employed a user's interests to help in the design of a personalized text summarization system, there has been inadequate focus on exploring cognitive styles. This paper aims at studying the impact of a user's cognitive styles when assessing multidocument summaries. In particular, we choose two dimensions of a user's cognitive style—the analytic/wholist and verbal/imagery dimensions—and study their impacts on how a user assesses a summary that was generated from a set of documents. In particular, the type of a document set refers to whether the set's content is loosely or closely related. We use a document set type to explore if there are any differences in the users' assessments of summaries that were generated from sets of different types. The results of this paper show that different users have different assessments with regard to information coverage and the way that information is presented in both loosely and closely related document sets. In addition, we found that the coherency ratings that were given to summaries from the two types of document sets were significantly different between the analytic and wholist groups. This result leads us to investigate the impact of a user's cognitive styles and the following two factors that directly relate to the coherence of a summary: 1) graph entropy and 2) the percentage of stand-alone concepts. We found that these two factors and a user's cognitive styles affect a user's ratings on the coherency of a summary. [ABSTRACT FROM PUBLISHER]

Networked multiagent systems are very popular in large-scale application environments. In networked multiagent systems, the interaction structures can be shaped into the form of networks where each agent occupies a position that is determined by such agent's relations with others. To avoid collisions between agents, the decision of each agent's strategies should match its own interaction position, so that the strategies available to all agents are in line with their interaction structures. Therefore, this paper presents a novel decision-making model for networked multiagent strategies based on their interaction structures, where the set of strategies for an agent is conditionally decided by other agents within its dependence interaction substructure. With the presented model, the resulting strategies available to all agents can minimize the collisions of multiagents regarding their interaction structures, and the model can produce the same resulting strategies for the isomorphic interaction structures. Furthermore, this paper uses a multiagent citation network as a case study to demonstrate the effectiveness of the presented decision-making model. [ABSTRACT FROM PUBLISHER]

This paper considers the reliability analysis of multistate systems (MSSs) subject to propagated failure with global effect (PFGE) and failure isolation effect. The PFGE can be caused by an imperfect fault coverage despite the presence of fault-tolerant mechanism or by a destructive effect of failures that originate from some system components on other components. The failure isolation effect is caused by functional dependence among system components, where the failure of some component can prevent the propagation of failures that originate from other components within the same system. Existing approaches for simultaneously addressing PFGE and failure isolation are limited to binary-state systems in which the system and its components exhibit two and only two states: operation or failure. In practice, however, many systems are MSS in which the system and/or its components may exhibit multiple performance levels corresponding to different states ranging from perfect operation to complete failure. In this paper, a separable and combinatorial methodology is proposed for evaluating the reliability of MSS subject to both PFGE and the failure isolation effect. The proposed method has no limitation on the type of time-to-failure distributions for the system components and is applicable to MSS with any arbitrary system structure. Application and advantages of the proposed method are illustrated through a detailed analysis of an example of a multistate memory system. [ABSTRACT FROM PUBLISHER]

In group decision making, consensus models are decision aid tools and help experts modify their individual opinions to reach a closer agreement. Based on the concept of minimum-cost consensus, this paper proposes a novel framework to achieve minimum-cost consensus under aggregation operators. Analytical results indicate that the proposed framework reduces to the consensus model of Ben-Arieh when the selected aggregation operator is the ordered weighted averaging (OWA) operator with weight vector (1/2, \ldots, 0, \ldots, 1/2)^T. Furthermore, this paper closely examines the minimum-cost consensus models with a linear cost function under the common aggregation operators (e.g., the weighted averaging operator and the OWA operator). Linear-programming-based approaches are also developed to solve these models. The results of this paper significantly contribute to efforts to develop the consensus model of Ben-Arieh [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

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. [ABSTRACT FROM PUBLISHER]

All online sharing systems gather data that reflects users' collective behavior and their shared activities. This data can be used to extract different kinds of relationships which can be grouped into layers and which are basic components of the multidimensional social network (MSN) proposed in the paper. The layers are created on the basis of two types of relations between humans, i.e., direct and object-based ones which, respectively, correspond to either social or semantic links between individuals. For better understanding of the complexity of the social network structure, layers and their profiles were identified and studied on two, spanned in time, snapshots of the `Flickr' population. Additionally, for each layer, a separate strength measure was proposed. The experiments on the `Flickr' photo sharing system revealed that the relationships between users result either from semantic links between objects they operate on or from social connections of these users. Moreover, the density of the social network increases in time. The second part of this paper is devoted to building a social recommender system that supports the creation of new relations between users in a multimedia sharing system. Its main goal is to generate personalized suggestions that are continuously adapted to users' needs depending on the personal weights assigned to each layer in the MSN. The conducted experiments confirmed the usefulness of the proposed model. [ABSTRACT FROM AUTHOR]

This paper focuses on the role of user modeling and semantically enhanced representations for personalization. This paper presents a generic Ontology-based User Modeling framework (OntobUMf), its components, and its associated user modeling processes. This framework models the behavior of the users and classifies its users according to their behavior. The user ontology is the backbone of OntobUMf and has been designed according to the Information Management System Learning Information Package (IMS LIP). The user ontology includes a Behavior concept that extends IMS LIP specification and defines characteristics of the users interacting with the system. Concrete examples of how OntobUMf is used in the context of a Knowledge Management (KM) System are provided. This paper discusses some of the implications of ontology-based user modeling for semantically enhanced KM and, in particular, for personal KM. The results of this research may contribute to the development of other frameworks for modeling user behavior, other semantically enhanced user modeling frameworks, or other semantically enhanced information systems. [ABSTRACT FROM AUTHOR]

Fit represents a central concept for organizational design, but extant research maintains a static focus on fit, a focus that is incommensurate with the fundamentally dynamic nature of organizations and their environments. Most key organizational environments are inherently dynamic; hence, the corresponding organizational designs required for fit are necessarily dynamic too. The problem is, the dynamics of fit are not addressed well by extant theory in organization and management sciences. Alternatively, organizations can be viewed as systems of purposeful design, and designing organizations to maintain fit and respond to dynamic environments over time may be informed well by theory and practice in engineering fields where such design is well established. In this paper, we abstract to the level of airplane design, and we utilize the dynamical language and integrated system of concepts, definitions, and interrelationships from the engineering field Aerodynamics to extend organization and management sciences and address the problem of organizational design in a dynamic context. We begin with a focused summary of the literature regarding the nature of organizational fitness. We then outline a conceptual model adapted to organizational design from Aerodynamics, and we summarize the key aerodynamics concepts stability and maneuverability to inform our conceptualization in terms of both airplane and organization design. This paper enables us to articulate a set of propositions and measures that form a basis for empirical testing. This paper also reveals important, dynamic organizational design tradeoffs and implications, and it shows how such conceptualization can elucidate new insights via comparison with and extension to extant theory. [ABSTRACT FROM PUBLISHER]

This paper compares the performance of several boosting and bagging techniques in the context of learning from imbalanced and noisy binary-class data. Noise and class imbalance are two well-established data characteristics encountered in a wide range of data mining and machine learning initiatives. The learning algorithms studied in this paper, which include SMOTEBoost, RUSBoost, Exactly Balanced Bagging, and Roughly Balanced Bagging, combine boosting or bagging with data sampling to make them more effective when data are imbalanced. These techniques are evaluated in a comprehensive suite of experiments, for which nearly four million classification models were trained. All classifiers are assessed using seven different performance metrics, providing a complete perspective on the performance of these techniques, and results are tested for statistical significance via analysis-of-variance modeling. The experiments show that the bagging techniques generally outperform boosting, and hence in noisy data environments, bagging is the preferred method for handling class imbalance. [ABSTRACT FROM PUBLISHER]

The retina still poses many structural and computational questions. Structurally, for example, it is not yet clear how many distinct horizontal cell (HC) types the primate retina contains and what the exact patterns of connections between photoreceptors (PRs) and HCs consist of. Computationally, it is not yet clear, for instance, what functions are present and how they are being implemented. This paper proposes a model (a linear recurrent neural network defined by 31 parameters) of the outer retina and an optimization methodology that hopes to shed some light on these questions. This paper shows that a simplified model of the outer retina can implement several low-level visual functions involving the modulation of noise, brightness, contrast, saturation, and even color. The results demonstrate that contrast control functions can be implemented with a minimum of two HC types and that spectral specificity between PRs and HCs is a common and important feature. It is also shown that several different spectrally specific patterns can emerge in order to implement the same function. One interesting microcircuit that naturally emerged from our experiments involves nonblurry denoising via interchromatic gap junctions and compensatory resaturation via HC circuits, a strategy that we hypothesize to exist in some biological retinae. [ABSTRACT FROM PUBLISHER]

Evaluating multistate flow network reliability and reducing system cost are important tasks when planning and designing systems. Existing methods are based on (d, c)-minimal paths ((d, c)-MP), which are vectors, such that d units of flow transmit between two specified nodes with a total cost that does not exceed c. However, these methods only work for directed networks. This correspondence paper finds all (d, c)-MPs before calculating network reliability under budget constraints using a novel method. The proposed algorithm is easier to understand and implement and is superior to existing algorithms. This correspondence paper analyzes and proves the correctness of the proposed algorithm, using two examples to demonstrate how to generate, verify, and implement all (d, c)-MPs to solve multistate flow network reliabilities under budget constraints using the proposed algorithm. [ABSTRACT FROM AUTHOR]

This paper proposes a new Petri net class, namely, Ratio-enforced weighted Augmented Marked Graphs (RAMGs), and solves ratio control and liveness-enforcing supervision problems for automated manufacturing systems. RAMGs can ensure the required product ratios as demanded by production planners. Since the deadlock of such a system can be attributed to improper acquisition of finite shared resources, a supervisor is introduced such that they are properly allocated. This paper proves that ratio and supervisory controllers for an RAMG can be separately designed. Their design methods are presented. Examples are given to illustrate them. [ABSTRACT FROM AUTHOR]

This paper presents an extension of the assumption-based truth maintenance system (ATMS), called “credibilistic ATMS,” which has the capability to cope with uncertain justifications and assumptions. Such justifications and assumptions are represented and dealt with in the framework of credibility theory. Important concepts in ATMS such as environments, labels, logical consequences, and consistency are redefined by the use of credibility measure. Based on these concepts, the label-updating procedure of the classical ATMS is extended, allowing effective computation of the membership function of any node within the network and that of its supporting environment. In addition, the contradictory environments can be captured with respect to their inconsistency degrees. This paper is compared to the most relevant existing research (i.e., ATMS using necessity as the truth value and ATMS using possibility as the truth value), demonstrating the significant improvements made. This paper also presents an illustrative application of credibilistic ATMS in supporting automated construction of domain models. [ABSTRACT FROM PUBLISHER]

Reliable people counting and human detection is an important problem in visual surveillance. In recent years, the field has seen many advances, but the solutions have restrictions: people must be moving, the background must be simple, and the image resolution must be high. This paper aims to develop an effective method for estimating the number of people and locate each individual in a low resolution image with complicated scenes. The contribution of this paper is threefold. First, postprocessing steps are performed on background subtraction results to estimate the number of people in a complicated scene, which includes people who are moving only slightly. Second, an Expectation Maximization (EM)-based method has been developed to locate individuals in a low resolution scene. In this method, a new cluster model is used to represent each person in the scene. The method does not require a very accurate foreground contour. Third, the number of people is used as a priori for locating individuals based on feature points. Hence, the methods for estimating the number of people and for locating individuals are connected. The developed methods have been validated based on a 4-hour video, with the number of people in the scene ranging from 36 to 222. The best result for estimating the number of people has an average error of 10% over 51 test cases. Based on the estimated number of people, some results of the EM-based method have also been shown. [ABSTRACT FROM PUBLISHER]

Distributed virtual machines can help to build scalable, manageable, and efficient grid infrastructures. The work proposed in this paper focuses on employing virtual machines for grid computing. In order to efficiently run grid applications, virtual machine resource information should be provided. This paper first discusses the system architecture of virtual machine pools and the process of information retrieval from virtual machines. Based on the characterization of the system model, this paper presents the work on how to retrieve resource information from Xen/VMware virtual machines via VMware Common Information Model Software Development Kit and lightweight Java agents. The resource information is integrated into a grid information service. The work is implemented in a test bed with Xen/VMware virtual machines and the Globus Toolkit. With a performance evaluation and discussion on a real test bed, it is declared that the design and implementation of information services for virtual-machine-based grid systems are feasible, efficient, and scalable. [ABSTRACT FROM PUBLISHER]

This paper introduces a new general methodology for the modeling and reliability evaluation of small isolated power systems, which include wind turbines, photovoltaics, and diesel generators, based on fluid stochastic Petri nets (FSPNs). The proposed methodology presents two major novelties in FSPN modeling, namely: 1) the introduction of a new kind of Petri net arc, called the database arc, which makes possible the direct import of real data in the simulation process; and 2) the selection of constant time intervals in FSPN modeling, instead of assuming continuous dynamics defined by the change of fluid level over time. Moreover, in order to construct the overall system model, this paper proposes a general framework for modular representation of the system under study following a number of well-defined steps. The obtained model is fully parameterized and compared to classical simulation methods, it provides to its user the additional advantage of graphical representation of system's components and attributes. Four scenarios, which describe power system's performance under different conditions, were implemented. For each one of the developed scenarios, nine reliability and performance indexes have been calculated and compared. [ABSTRACT FROM PUBLISHER]

In this paper, warranty cost models are presented based on the quasi-renewal processes and exponential distribution. Cost analyses are conducted for various systems under the basic assumption that a repair service is imperfect. We develop warranty cost models, reliability, and other measures for several systems, including multicomponent systems. This paper focuses on warranty cost analysis, including repairable products with a given warranty period considering conditional probabilities and renewal theory. The exponential distribution is used to analyze and obtain the warranty cost. Numerical examples are discussed to demonstrate the applicability of the methodology derived in this paper. [ABSTRACT FROM PUBLISHER]

This paper presents a new multimodal grammar generation system (MGGS) that allows defining a multimodal grammar in a very easy and intuitive way, overcoming the difficulties arising from the textual description of grammar production rules. The novelty of the proposed approach relies in adopting a “by example” paradigm to define a multimodal grammar. This paradigm consists in providing concrete examples of multimodal sentences, and enabling a grammar inference algorithm to automatically generate the grammar rules to parse those sentences. The main contribution of this approach is that it is general enough to be applicable for whatever modalities and in whichever domains. Moreover, the use of the grammar inference algorithm for automating the grammar writing and updating processes, reduces costs of the grammar development and maintenance. In the first part of this paper, we present the MGGS, describing in detail the methodology we have implemented in this system. More specifically, the multimodal attribute grammar and the grammar inference algorithm are illustrated. The second part describes the experiment aimed at observing participants while interacting with the system in order to provide some real data about the usability of the system. Results of this experiment showed that the proposed system facilitates the grammar definition and updating, and it is more suitable also for nonexpert people as it does not require the learning of the grammar notation. [ABSTRACT FROM PUBLISHER]

Reference models are an important aid for business process modeling and design. Their aim is to capture domain knowledge and assist in the design of enterprise-specific business processes. The application of reference models for process design requires guidance in reusing these models and flexibility in adapting them to specific enterprises. One popular modeling language for specifying reference models is event-driven process chain (EPC), which has been extended to express configurable reference models, i.e., configurable EPC (C–EPC). These models provide explicit reuse guidance but allow a limited level of flexibility following a reuse by configuration approach. To increase the level of adaptability of reference models, in this paper, we propose to utilize the application-based domain modeling (ADOM) approach to specify and apply reference models by using EPC. ADOM supports the enforcement of reference model constraints while allowing high levels of flexibility, adaptability, and variability in the business processes of particular enterprises. This paper presents the syntax and semantics of the proposed approach, called ADOM–EPC, and its specialization and configuration capabilities. ADOM–EPC is evaluated by comparing it to C–EPC, a leading approach for reference modeling and reuse, in terms of expressiveness and comprehensibility. Although the expressiveness of ADOM–EPC, i.e., its set of specified reuse operations, exceeds that of C–EPC, the understandability of the two types of reference models is similar. [ABSTRACT FROM PUBLISHER]

Large organizations usually have difficulties in dealing with the exponential growth of information. Therefore, there is a high demand for innovative solutions to deal with such growth and to integrate such information. This paper proposes a new approach, called Emergent Ontologies (EOs), toward the generation of a single organizational ontology through which it becomes possible to browse all information of an organization. This proposal considers that, typically, an organization's information is distributed in peers, and that in each peer, this information could be represented through a different ontology. As each peer of an organization needs to exchange information, peer-to-peer mappings are created to bridge these ontologies. Based on these mappings, this paper proposes a set of heuristics, which are used to generate the EO. These heuristics have been incorporated into the OntoEmerge system, a prototype developed to facilitate the creation of an initial organization ontology. In order to evaluate such a system and the heuristics behind it, some experiments have been performed. A quantitative and qualitative analysis of these experiments is also presented in this paper. This approach presents encouraging results, and this fact can be considered as a starting point for the creation of organizational ontologies. [ABSTRACT FROM AUTHOR]

We define a digital ecosystem (DES) as the dynamic and synergetic complex of digital communities consisting of interconnected, interrelated, and interdependent digital species situated in a digital environment that interact as a functional unit and are linked together through actions, information, and transaction flows. The design of DESs requires the integration of a number of different and complementary technologies, including agent-based and self-organizing systems, ontologies, swarm intelligence, ambient intelligence, data mining, genetic algorithms, etc. The integration of multiple technologies and the resulting synergetic effects contribute to the creation of highly complex, dynamic, and powerful systems. The application of DESs within different domains has the power to transform these domains by giving them a more intelligent and a more dynamic nature. In this paper, we illustrate how a DES design methodology can be used to systematically create a Digital Health Ecosystem (DHES). We address the key steps associated with the DES design and focus specifically on the use of the electronic health records within the DHES. The design methodology framework illustrated in this paper serves as a navigating tool during the design of DHESs. [ABSTRACT FROM AUTHOR]

This paper proposes modeling the rapidly evolving energy systems as cyber-based physical systems. It introduces a novel cyber-based dynamical model whose mathematical description depends on the cyber technologies supporting the physical system. This paper discusses how such a model can be used to ensure full observability through a cooperative information exchange among its components; this is achieved without requiring local observability of the system components. This paper also shows how this cyber--physical model is used to develop interactive protocols between the controllers embedded within the system layers and the network operator. Our approach leads to a synergistic framework for model-based sensing and control of future energy systems. The newly introduced cyber--physical model has network structure-preserving properties that are key to effective distributed decision making. The aggregate load modeling that we develop using data mining techniques and novel sensing technologies facilitates operations of complex electric power systems. [ABSTRACT FROM AUTHOR]

The concept of synchronization is of fundamental importance in multimedia systems and applications. The focus of this paper is on olfaction-enhanced multimedia, which concerns itself with associating computer-generated smell with other media. However, the lingering nature of smell, as opposed to the transitory nature of other media objects that multimedia applications are accustomed to, such as video and audio, means that specific attention needs to be given when synchronizing other media content with olfactory data. Consequently, this paper presents the results of an experimental study carried out to explore and investigate the temporal boundaries within which olfactory-data output in an olfaction-enhanced multimedia application can be successfully synchronized with other media objects from an end-user perspective. Results show the presence of two main synchronization regions, and that olfaction ahead of audiovisual content is more tolerable than olfaction behind content. [ABSTRACT FROM AUTHOR]

This paper proposes a technique for frequency-partitioned spectrum estimation (FPSE), which is used in the National Taiwan University Wireless Health Advanced Monitoring Bio-Diagnosis System for electrocardiogram analysis. A process for analyzing the RR interval (which is a time series formed by the heat-beat duration that represents heart-rate variations) in conjunction with the fuzzy clustering technique is proposed for arrhythmia recognition. FPSE helps reduce data transmission errors and allows the computational load to be moved to a remote server; however, it suffers from waveform deterioration during reconstruction of the signal power spectrum. To compensate for this problem, this paper proposes a modified FPSE approach that imposes an additional boundary constraint to ensure that the estimated spectrum is smooth. The simulation results show that the proposed algorithm is more effective at recovering the original frequency information and achieves a globally asymptotic trend. The proposed arrhythmia recognition procedure was applied to the Massachusetts Institute of Technology-Boston's Beth Israel Hospital (MIT-BIH) database (developed by MIT and Boston's Beth Israel Deaconess Medical Center), which demonstrated that it is both very convenient and efficient. [ABSTRACT FROM AUTHOR]

Research in the areas of 3-D face recognition and 3-D facial expression analysis has intensified in recent years. However, most research has been focused on 3-D static data analysis. In this paper, we investigate the facial analysis problem using dynamic 3-D face model sequences. One of the major obstacles for analyzing such data is the lack of correspondences of features due to the variable number of vertices across individual models or 3-D model sequences. In this paper, we present an effective approach for establishing vertex correspondences using a tracking-model-based approach for vertex registration, coarse-to-fine model adaptation, and vertex motion trajectory (called vertex flow) estimation. We propose to establish correspondences across frame models based on a 2-D intermediary, which is generated using conformal mapping and a generic model adaptation algorithm. Based on our newly created 3-D dynamic face database, we also propose to use a spatiotemporal hidden Markov model (ST-HMM) that incorporates 3-D surface feature characterization to learn the spatial and temporal information of faces. The advantage of using 3-D dynamic data for face recognition has been evaluated by comparing our approach to three conventional approaches: 2-D-video-based temporal HMM model, conventional 2-D-texture-based approach (e.g., Gabor-wavelet-based approach), and static 3-D-model-based approaches. To further evaluate the usefulness of vertex flow and the adapted model, we have also applied a spatial-temporal face model descriptor for facial expression classification based on dynamic 3-D model sequences. [ABSTRACT FROM AUTHOR]

This paper presents a novel segmentation algorithm to segment a body posture into different body parts using the technique of deformable triangulation. To analyze each posture more accurately, they are segmented into triangular meshes, where a spanning tree can be found from the meshes using a depth-first search scheme. Then, we can decompose the tree into different subsegments, where each subsegment can be considered as a limb. Then, two hybrid methods (i.e., the skeleton-based and modeldriven methods) are proposed for segmenting the posture into different body parts according to its occlusion conditions. To analyze occlusion conditions, a novel clustering scheme is proposed to cluster the training samples into a set of key postures. Then, a model space can be used to classify and segment each posture. If the input posture belongs to the nonocclusion category, the skeleton-based method is used to divide it into different body parts that can be refined using a set of Gaussian mixture models (GMMs). For the occlusion case, we propose a model-driven technique to select a good reference model for guiding the process of body part segmentation. However, if two postures' contours are similar, there will be some ambiguity that can lead to failure during the model selection process. Thus, this paper proposes a tree structure that uses a tracking technique so that the best model can be selected not only from the current frame but also from its previous frame. Then, a suitable GMM-based segmentation scheme can be used to finely segment a body posture into the different body parts. The experimental results show that the proposed method for body part segmentation is robust, accurate, and powerful. [ABSTRACT FROM AUTHOR]

Extending technical education to students abroad requires the systematic development of virtual laboratories (VLs) that provide interaction with real and specialized equipment. This paper proposes a generic and modular model for VLs for robotics over the Internet. The model is defined by using Unified Modeling Language (UML) to depict its software structure and also Petri nets to describe its dynamic behavior. A development methodology uses themodel as a reference framework. This proposed methodology, based on experiment specifications, customizes the framework in UML and formally translates its dynamic description, depicted by statecharts, into the Petri net formalism. Petri nets are used to analyze, control, and validate the VL dynamic design as a stable and event-synchronized telerobotic system. UML and Petri net charts obtained from themethodology supply a complete guideline for the developer to implement VLs for robotics. Themodel and its methodology are used to develop a remote VL for mobile robotics. This paper attempts to bridge the gap between ad hoc and formal implementation of VLs. [ABSTRACT FROM AUTHOR]

One of the most important issues in road safety management is the lack of reliable methods for predicting the likelihood of accidents. Road safety assessment systems have been developed; however, these systems only employ historical or retrospective analyses, and the human factor element is weak or missing. Effective safety management requires both holistic and prospective viewpoints, with human factors having an intrinsic role. The main goal of this paper is to contribute toward that need through the application of Bayesian belief networks and road traffic simulation for validating the safety requirements of prospective road designs. The theoretical platform of the method is the concepts of human performance and mental workload and how these affect accident likelihood. This paper presents a novel method and a tool that integrates these two mature technologies, for assessing the safety performance of road designs before they are developed. A case study is included that illustrates the application of the method and tool. [ABSTRACT FROM AUTHOR]