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Deadlock Prevention Based on Structure Reuse of Petri Net Supervisors for Flexible Manufacturing Systems
Deadlocks are an undesirable situation in automated flexible manufacturing systems (FMS). Their occurrences often deteriorate the utilization of resources and may lead to catastrophic results. Finding an optimal supervisor is NP-hard. A computationally efficient method often ends up with a suboptimal one. This paper develops a deadlock prevention method that makes a good tradeoff between optimality and computational tractability for a class of Petri nets, which can model many FMS. The theory of regions guides our efforts toward the development of near-optimal solutions for deadlock prevention. Given a plant net, a minimal initial marking is first decided by structural analysis, and an optimal live controlled system is computed. Then, a set of inequality constraints is derived with respect to the markings of monitors and the places in the model such that no siphon can be insufficiently marked. A method is proposed to identify the redundancy condition for constraints. For a new initial marking of the plant net, a deadlock-free controlled system can be obtained by regulating the markings of the monitors such that the inequality constraints are satisfied, without changing the structure of the controlled system. The near-optimal performance of a controlled net system via the proposed method is shown through several examples.
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Advanced Input Generating Algorithm for Effect-Based Weapon–Target Pairing Optimization
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.
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IEEE Transactions on Systems, Man, and Cybernetics—Part A: Systems and Humans publication information
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A Method to Compute Strict Minimal Siphons in a Class of Petri Nets Based on Loop Resource Subsets
Strict minimal siphons (SMS) play an important role in the development of deadlock control policies for flexible manufacturing systems (FMS). For a class of Petri nets called Systems of Simple Sequential Processes with Resources (S3PR), the resource circuit-based method is an effective way to compute SMS. In this paper, a more effective one to compute SMS is proposed. First, the concepts of loop resource subsets and their characteristic resource subnets are proposed. Next, sufficient and necessary conditions for loop resource subsets to generate SMS are established. Finally, an algorithm is given to find all the SMS based on loop resource subsets. Since the number of loop resource subsets is much less than that of resource circuits and their combinations, the computational efficiency of the SMS enumeration task is significantly improved by the proposed method. An FMS example is used to illustrate the application of the proposed method, and computational time comparisons are provided on several S3PRs to show its superior efficiency.
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How Autonomy Impacts Performance and Satisfaction: Results From a Study With Spinal Cord Injured Subjects Using an Assistive Robot
We report a small dual cohort pilot study with traumatic spinal cord injured (SCI) subjects designed to investigate the utility of a wheelchair-mounted robotic arm for these subjects. The UCF-MANUS, a vision-based 6DOF assistive robotic arm, has been designed to aid individuals with upper limb extremities to complete tasks of daily living that they would otherwise be unable to complete themselves. Pick-and-place IADL tasks were designed and ten (10) users post-SCI were selected under IRB guidelines to be trained and tested with the system for 1 to 2 h weekly over a period of three weeks. During this time, they controlled the robot either through a manual or an autonomous (supervised) mode of operation. Baseline characteristics (pre-study), quantitative performance metrics (during study), and psychometrics (post-study) were obtained and statistically analyzed to test a set of hypotheses related to performance and satisfaction with the two control modes. At the end of the study, both the autonomous and the manual mode had comparable task completion times while user effort required for operating the robot in autonomous mode was significantly less than that for the manual mode. However, the autonomous mode failed to commensurately raise the user's level of satisfaction. Over the three-week study, the manual mode users showed a pronounced learning effect in terms of reducing mean task completion time and number of commands while the auto mode users showed improvement in terms of reduction of variability. Based on qualitative feedback and quantitative results, possible directions for system design are presented to concurrently achieve better performance and satisfaction outcomes.
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IEEE Systems, Man, and Cybernetics Society Information
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Design and Realization of a Framework for Human–System Interaction in Smart Homes
The current smart home is a ubiquitous computing environment consisting of multiple autonomous spaces, and its advantage is that a service interacting with home users can be set with different configurations in space, hardware, software, and quality. As well as being smart technologically speaking, a smart home should also never forget to retain the “home nature” when it is serving its users. In this paper, we first analyze the relationship among services, spaces, and users, and then we propose a framework as well as a corresponding algorithm to model their interaction relationship. Later, we also realize the human-system interaction framework to implement a smart home system and develop “pervasive applications” to demonstrate how to utilize our framework to fulfill the human-centric interaction requirement of a smart home. Finally, our preliminary evaluations show that our proposed work can enhance the performance of the human-system interaction in a smart home environment.
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User Experience Modeling and Simulation for Product Ecosystem Design Based on Fuzzy Reasoning Petri Nets
Product ecosystem design entails complex user experience (UX) that involves interactions among multiple users, products, and the ambience. This paper aims to capture causal relationships between UX and design elements and in turn to provide decision support to product ecosystem analysis. A fuzzy reasoning Petri net is developed to deal with the uncertainty, complexity, and dynamics associated with UX modeling. Reasoning of diverse constructs of UX is embedded in the fuzzy production rules that are derived from self-report UX data based on rough set mining. A fuzzy reasoning algorithm is implemented to perform parallel inference by multicriteria rules and to simulate most likely UX under different ambient factors. A case study of subway station UX design demonstrates the potential of product ecosystem FRPN formulation.
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A Logical Approach to Real Options Identification With Application to UAV Systems
Complex systems are subject to uncertainties that may lead to suboptimal performance or even catastrophic failure if unmanaged. Uncertainties may be managed through real options that provide a decision maker with the right, but not the obligation, to exercise actions in the future. While real options analysis has traditionally been used to quantify the value of such flexibility, this paper is motivated by the need for a structured approach to identify where real options are or can be embedded for uncertainty management. We introduce a logical model-based approach to identification of real option mechanisms and types, where the mechanism is the enabler of the option, while the type refers to the flexibility provided by the option. First, we extend the classical design structure matrix and the more general multiple-domain matrix (MDM), commonly used in modeling and analyzing interdependencies in complex socio-technical systems, to the more expressive Logical-MDM that supports the representation of flexibility. Second, we show that, in addition to flexibility, two new properties, namely, optionability and realizability, are relevant to the identification of real options. We use the Logical-MDM to estimate flexibility, optionability, and realizability metrics. Finally, we introduce the Real Options Identification (ROI) method based on these metrics, where the identified options are valued using standard real options valuation methods to support decision making under uncertainty. The expressivity of the logic combined with the structure of the dependency model allows the effective representation and identification of mechanisms and types of real options across multiple domains and lifecycle phases of a system. We demonstrate this approach through a series of unmanned air vehicle scenarios.
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Optimization of the Disassembly Sequencing Problem on the Basis of Self-Adaptive Simplified Swarm Optimization
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.
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Customer-Driven Content Recommendation Over a Network of Customers
As the Web evolves into an ecological platform of information, people, and technologies, its usage paradigm has gradually shifted so that the importance of its participative role is observed. Users contribute by uploading multimedia content, writing wiki pages, and posting blog articles. As the effect of user participation (the word-of-mouth effect) in the Internet becomes a factor influencing firms' success, firms search for ways to utilize blogs, social networks, and other Internet resources. To actively make use of the online word-of-mouth effect, firms must structure preference-based customer networks so that local interaction happens among closely related customers and effective propagation of ideas or diffusion of products can be achieved. In this paper, we propose a recommendation technique utilizing the fast diffusion and information sharing capability of a large customer network. The proposed method [described as the customer-driven recommender system (CRS)] follows the collaborative filtering (CF) principle but performs distributed and local searches for similar neighbors over a customer network in order to generate a recommendation list. In order to validate the effectiveness and efficiency of the proposed method, we build customer networks for the recommendation of digital content and tangible products from two real data sets and compare the proposed method against the traditional system based on CF. Experimental results show that the local search mechanism of the CRS is computationally more efficient than but equally as accurate as the global search mechanism of the traditional recommender system.
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IEEE Foundation
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Managing Complex Mechatronics R&D: A Systems Design Approach
To compress research and development (R&D) cycle times of high-tech mechatronic products with conformance performance metrics, managing R&D projects to allow engineers from electrical, mechanical, and manufacturing disciplines receive real-time design feedback and assessment are essential. In this paper, we propose a systems design procedure to integrate mechanical design, structure prototyping, and servo evaluation through careful comprehension of the servo-mechanical-prototype production cycle commonly employed in mechatronic industries. Our approach focuses on the Modal Parametric Identification of key feedback parameters for fast exchange of design specifications and information. This enables efficient conduct of product design evaluations, and supports schedule compression of the R&D project life cycle in the highly competitive consumer electronics industry. Using the commercial hard disk drive as a case example, we demonstrate how our approach allow inter-disciplinary specifications to be communicated among engineers from different backgrounds to speed up the R&D process for the next generation of intelligent manufacturing. This provides the management of technology team with powerful decision-making tools for project strategy formulation, and improvements in project outcome are potentially massive because of the low costs of change.
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Table of Contents
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Quantifying the Impact of Information and Organizational Structures via Distributed Auction Algorithm: Point-to-Point Communication Structure
This paper presents how information and organizational structures with point-to-point communication structure impact team coordination in a distributed task-asset allocation problem. A key distinguishing characteristic of this problem is that each decision maker knows only a part of the weight matrix and/or controls a subset of the assets. Here, we extend the distributed algorithm developed for blackboard communication structure in another part of this work to the point-to-point communication structure. Our results indicate that edge organizations with horizontal and vertical information structures exhibit shorter delays than those with block diagonal and checkerboard information structures. We also showed how our findings can be applied effectively to mission planning of the Navy's maritime operations center.
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Single-Machine Scheduling With Job-Position-Dependent Learning and Time-Dependent Deterioration
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.
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Mining User Movement Behavior Patterns in a Mobile Service Environment
Mobile service systems offer users useful information ubiquitously via mobile devices. Based on changeable user movement behavior patterns (UMBPs), mobile service systems have the capability of effectively mining a special request from abundant data. In this paper, UMBPs are studied in terms of the problem of mining matching mobile access patterns based on joining the following four kinds of characteristics, U, L, T, and S, where U is the mobile user, L is the movement location, T is the dwell time in the timestamp, and S is the service request. By introducing standard graph-matching algorithms along with the primitives of a database management system, which comprises grouping, sorting, and joining, these joint operations are defined. Moreover, by mining the associated structure via maximum weight bipartite graph matching, a prediction mechanism, based on the model of UMBPs, is utilized to find strong relationships among U , L, T , and S. In addition, a PC-based experimental evaluation under various simulation conditions, using synthetically generated data, is introduced. Finally, performance studies are conducted to show that, in terms of execution efficiency and scalability, the proposed procedures produced excellent performance results.
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Process Nets With Channels
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.
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A Pattern-Recognition-Based Algorithm and Case Study for Clustering and Selecting Business Services
Positioned as the backbone of service asset management console, a service registry has to enable real-time and offline service selection in an effective manner. This paper presents an analytic algorithm that is used to guide the architectural design of service exploration in a service registry. Service assets are proposed to be framed into a well-established categorical structure based on pattern recognition algorithm. This design aims to provide systematic methodology and enablement architecture for analyzing, clustering, and adapting heterogeneous services for dynamic application integration. The exploitation of pattern recognition algorithm maps a large amount of services into a manageable feature space, which consists of attributes that are related to static description and dynamic features, such as historical QoS and service-level agreement. The proposed architecture and associated service exploration methodology have been integrated into an industry strength service-oriented architecture solution design platform. We also present a case study using the developed platform to illustrate the proposed algorithm for business service clustering and selection.
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Decidability Results for Soundness Criteria of Resource-Constrained Workflow Nets
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.
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