<![CDATA[ IEEE Transactions on Systems, Man, and Cybernetics: Systems - new TOC ]]>
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TOC Alert for Publication# 6221021 2017December 07<![CDATA[Table of contents]]>4712C13101460<![CDATA[IEEE Transactions on Systems, Man, and Cybernetics publication information]]>4712C2C2180<![CDATA[A Robust Reorder-Time/Order-Quantity Policy Under Invisible Stock Loss]]>${r}$ , ${Q}$ ), (${s}$ , ${S}$ ), and (${R}$ , ${S}$ ) policies: 1) if there exist invisible stock loss and inaccurate inventory record, the inventory system will be trapped into the zero-service state (i.e., the inventory level becomes less than or equal to zero with probability one) in finite time under the classical policies and 2) if the probability distribution of inventory record error is known exactly, the RTQ policy prevents the inventory system from being trapped into the zero-service state and maintains a high service level, even if we do not make any audit of its physical inventory level.]]>4712310231161228<![CDATA[Semiautomatic System Domain Data Analysis: A Smart Grid Feasibility Case Study]]>4712311731272303<![CDATA[Robust Iris Segmentation Method Based on a New Active Contour Force With a Noncircular Normalization]]>4712312831412309<![CDATA[Physical Activity Recognition From Smartphone Accelerometer Data for User Context Awareness Sensing]]>4712314231491583<![CDATA[An Inventory Routing Policy Under Replenishment Lead Time]]>${N}$ retailers) is modeled mathematically. To solve the problem, first a simple case (i.e., one vendor and two retailers) is analyzed to obtain the theoretical optimal policy. By proving the ${K}$ -convexity of the objective function, we confirm that the structure of the optimal replenishment and routing policy is of switching curve type. In this policy, the state space, which is composed of the inventory positions of the two retailers, is divided into several domains; and for inventory positions in each domain, there exists an optimal order-up-to level. This structure reveals, for managerial insight, that when lead-time is considered, the current routing decision is not independent of the previous one. Second, since the optimal policy is difficult to realize in practice, a myopic policy that is easier to implement is proposed and numerical experiments are conducted to examine the near-optimal performance of the myopic policy. Finally, the myopic policy is extended to a realistic-size IRP with replenishment lead-time (i.e., the IRP for the case of one vendor and multiple retailers) and a numerical example is provided to indicate the feasibilit-
of the policy.]]>4712315031641878<![CDATA[Undergraduate Students’ Engagement With Systems Thinking: Results of a Survey Study]]>4712316531762063<![CDATA[Availability Modeling of Generalized $k$ -Out-of- $n$ :G Warm Standby Systems With PEPA]]>${k}$ -out-of-${n}$ :G warm standby repairable systems with many nonidentical components is tedious and error-prone, requiring specification of the generator matrix of a high dimensional Markov chain. Using the performance evaluation process algebra (PEPA) as an intermediary, this paper gives a new modeling approach for availability evaluation of such systems with ${r}$ repair facilities. The components of the system are classified into ${n}$ different groups that consist of statistically identical components following exponential time-to-failure and repair time distributions. A library of PEPA components and their actions are defined for system component groups, repair facilities, repair queue, and system dynamics. To capture the dependency of system states on components, a signaling mechanism is realized by actions with suitably high rates. A compilation tool is provided to automatically generate the PEPA model from a brief specification of the system, using the library components. This provides input for the PEPA analysis tool and is amenable to availability analysis. Examples are used to illustrate the proposed modeling method. Modeling with PEPA provides an efficient way to deal with availability evaluation of systems considered with many groups of repairable components.]]>471231773188620<![CDATA[Optimal Shipping Strategy and Return Service Charge Under No-Reason Return Policy in Online Retailing]]>4712318932061086<![CDATA[Location Anonymization With Considering Errors and Existence Probability]]>${k}$ -anonymity, have been proposed to tackle this issue. Existing studies for ${k}$ -anonymity usually anonymize each user’s location so that the anonymized area contains ${k}$ or more users. Existing studies, however, do not consider location errors and the probability that each user actually exists at the anonymized area. As a result, a specific user might be identified by untrusted third parties. We propose novel privacy and utility metrics that can treat the location and an efficient algorithm to anonymize the information associated with users’ locations. This is the first work that anonymizes location while considering location errors and the probability that each user is actually present at the anonymized area. By means of simulations, we have proven that our proposed method can reduce the risk of the user’s attributes being identified while maintaining the utility of the anonymized data.]]>4712320732181852<![CDATA[Context Ontology-Based Reasoning Service for Multimedia Conferencing Process Intelligence]]>4712321932322393<![CDATA[A New Local Rule for Convergence of ICLA to a Compatible Point]]>4712323332443068<![CDATA[A Systematic Analysis of Transform Coefficients and Block Decomposition for Texture Enhancement With Orthogonal Polynomials Model]]>4712324532551765<![CDATA[A Multiobjective Path-Planning Algorithm With Time Windows for Asset Routing in a Dynamic Weather-Impacted Environment]]>4712325632711396<![CDATA[Bi-TOPSIS: A New Multicriteria Decision Making Method for Interrelated Criteria With Bipolar Measurement]]>4712327232831431<![CDATA[Using New Version of Extended $t$ -Norms and $s$ -Norms for Aggregating Interval Linguistic Labels]]>$boldsymbol {t}$ -norms and $boldsymbol {s}$ -norms. We discuss the properties of these operational laws, such as commutative law, associative law, and distribution law. Different kinds of extended $boldsymbol {t}$ -norms and $boldsymbol {s}$ -norms, such as the extended algebraic, extended Einstein, extended Hamacher, and extended Frank $boldsymbol {t}$ -norms and $boldsymbol {s}$ -norms, have been investigated to produce different operational laws. As an application of such operational laws, we propose some extended $boldsymbol {t}$ -norms and $boldsymbol {s}$ -norms based interval linguistic weighted power average operators. We also study some basic properties of such aggregation functions. The cross-entropy of interval linguistic information is proposed and applied to obtain the weights of attributes. An approach to multiple attributes decision making with interval linguistic information is proposed. Finally, two cases of practical decision issues are illustrated to show the application of the proposed method.]]>4712328432981090<![CDATA[Measuring Uncertainty of Probabilistic Rough Set Model From Its Three Regions]]>471232993309775<![CDATA[Optimal Distribution of Nonperiodic Full and Incremental Backups]]>471233103320966<![CDATA[Representing Belief Functions as Random Variables]]>$ {n=32}$ , a Möbius inversion that takes 1057 years to accomplish using nonoptimized set operations or 15.8 years via the best existing FMT algorithm will take only one second via the random-variable based FMT. In addition, the new FMT forgoes the need to maintain and lookup any graphical structures and allows the application of FMT to any list of subsets, rather than the power set.]]>471233213330607<![CDATA[Sufficient and Necessary Conditions on Finite-Time Tracking]]>471233313339712<![CDATA[Active Compressive Sensing via Pyroelectric Infrared Sensor for Human Situation Recognition]]>4712334033501993<![CDATA[Agent Cooperation Mechanism for Decentralized Manufacturing Scheduling]]>4712335133622288<![CDATA[Can Dynamic Knowledge-Sharing Activities Be Mirrored From the Static Online Social Network in Yahoo! Answers and How to Improve Its Quality of Service?]]>4712336333761327<![CDATA[The Partial-Value Association Discovery Algorithm to Learn Multilayer Structural System Models From System Data]]>4712337733851313<![CDATA[Multidimensional Hebbian Learning With Temporal Coding in Neocognitron Visual Recognition]]>4712338633968139<![CDATA[FBMTP: An Automated Fault and Behavioral Anomaly Detection and Isolation Tool for PLC-Controlled Manufacturing Systems]]>4712339734173430<![CDATA[Solving the Group Multirole Assignment Problem by Improving the ILOG Approach]]>4712341834241255<![CDATA[Determining Truth Degrees of Input Places in Fuzzy Petri Nets]]>471234253431782<![CDATA[Introducing IEEE Collabratec]]>4712341234122171<![CDATA[IEEE Systems, Man, and Cybernetics Society Information]]>4712C3C3108<![CDATA[IEEE Transactions on Human-Machine Systems information for authors]]>4712C4C486