A multi-functional platform for implementing intelligent and ubiquitous functions of smart substations under SCADA

For more efficient and economical management of substations under SCADA (Supervisory Control and Data Acquisition) systems, the concept of a smart substation has been introduced using intelligent and ubiquitous IT (Information Technology) techniques. A multi-functional platform needs to perform more intelligent and ubiquitous functions of smart substation effectively. In this paper, we propose a multi-functional platform to implement smart substations effectively. A prototype hardware, functions and communication interfaces on an embedded platform are introduced. Also, we suggest operating system architecture for smart substations.     

Fundamental calculus on generalized stochastically bounded bursty traffic for communication networks

Since many applications and networks do not require or provide deterministic service guarantees, stochastic service guarantee analysis is becoming increasingly important and has attracted a lot of research attention in recent years. For this, several stochastic versions of deterministic traffic models have been proposed in the literature. Unlike previous stochastic models that are based on the traffic amount property of an input process, we present another stochastic model, generalized Stochastically Bounded Burstiness (gSBB), which is based on the virtual backlog property of the input process. We show the advantages of this approach. We study the superposition of gSBB traffic, and set up the input–output relation. Under various service disciplines, we characterize the output process for each source and investigate probabilistic upper bound on delay. Finally, we introduce a stochastic ordering monotonicity property of gSBB. With this property, we show that many well-known traffic models can be readily represented using the proposed gSBB model. These results set up the basis for a network calculus for gSBB traffic.     

Inductive semimodules and the vector modules over them

The notion of an inductive semimodule over an ordered *-semiring is introduced and some related properties are investigated. Inductive semimodules are extensions of several important algebraic structures such as Kleene modules, Kleene algebras and inductive *-semirings. We prove that an inductive semimodule over an ordered *-semiring K is a Kleene module if and only if K is a Kleene algebra. Moreover, we establish that the vector module of an inductive semimodule over an ordered Conway semiring is again an inductive semimodule over the matrix semiring. Consequently, in an inductive semimodule over an ordered Conway semiring, least solutions to linear inequation systems can be denoted by linear expressions, avoiding the least fixed point operator. In addition, we also introduce a related notion called weak inductive semimodules, and propose several open problems on them.

Human tracking and silhouette extraction for human–robot interaction systems

In this study, we propose a new integrated computer vision system designed to track multiple human beings and extract their silhouette with a pan-tilt stereo camera, so that it can assist in gesture and gait recognition in the field of Human–Robot Interaction (HRI). The proposed system consists of three modules: detection, tracking and silhouette extraction. These modules are robust to camera movements, and they work interactively in near real-time. Detection was performed by camera ego-motion compensation and disparity segmentation. For tracking, we present an efficient mean shift-based tracking method in which the tracking objects are characterized as disparity weighted color histograms. The silhouette was obtained by two-step segmentation. A trimap was estimated in advance and then effectively incorporated into the graph-cut framework for fine segmentation. The proposed system was evaluated with respect to ground truth data, and it was shown to detect and track multiple people very well and also produce high-quality silhouettes.

Understanding design activities through computer simulation

In this paper, a new experimental approach – computer simulation – is introduced for understanding design activities and for validating design theories. Following the generic framework of computer simulation, three main components in simulating design activities are introduced: mathematical model, simulation model, and statistical analysis. The mathematical model consists of the design governing equation and Environment-Based Design (EBD), based on which three routes are introduced to look for new design solutions: (1) formulating the design problem differently at the beginning of a design process may get quite different solutions, in which creative design could emerge; (2) extending designer’s knowledge and experience can help generate more candidate solutions, and so increasing the probability of generating a good concept; (3) changing the sequence of design problem decomposition may change product requirements, and thus change the generated design concepts. By viewing mesh generation algorithms as design agents, a computer simulation environment is used to study design activities. Statistical analysis is conducted to validate quantitatively the three routes to new design solutions. The results show that computer simulation is an effective approach to studying design activities.     

DEVS-Based modeling of VoIP spam callers’ behavior for SPIT level calculation

At the present time the VoIP (Voice over Internet Protocol) service is generally accepted as an alternative for people seeking cheaper means to make a phone call. Users of VoIP service may fall anywhere along a spectrum between types at two extremes: one of which is an ordinary caller who doesn’t use the telephone for commercial purposes, while the other is a person who generates spam calls for commercial purposes. The focus of this paper concerns modeling of spam callers’ behavior to calculate the SPIT (Spam over Internet Telephony) level for management of the quality of service. From the perspective of a VoIP service provider’s view, spam callers are also a type of customer and sometimes they are valuable for increasing revenue. However, if a service provider does not manage spam calls, it can harm their business, because ordinary users might not receive phone calls using the phone numbers of the VoIP service. Thus, there is a trade-off between revenues and usability in managing spam calls in the VoIP service. This work presents a model of spam caller’s behavior using the DEVS (Discrete Event System Specification) formalism. The DEVS formalism is applicable as a model of behavior, by defining the state and state transition of the target of the model. In our model, we use six main parameters to define the states and state transitions. Each state is represented by a number which indicates the SPIT level of a caller. If the value is 1.0 then the caller is more similar to a spam caller. Based on the model definition, we constructed a SPIT level Calculation UI (User Interface) that is used to manage spam calls to improve VoIP service quality.     

Semplore: A scalable IR approach to search the Web of Data

The Web of Data keeps growing rapidly. However, the full exploitation of this large amount of structured data faces numerous challenges like usability, scalability, imprecise information needs and data change. We present Semplore, an IR-based system that aims at addressing these issues. Semplore supports intuitive faceted search and complex queries both on text and structured data. It combines imprecise keyword search and precise structured query in a unified ranking scheme. Scalable query processing is supported by leveraging inverted indexes traditionally used in IR systems. This is combined with a novel block-based index structure to support efficient index update when data changes. The experimental results show that Semplore is an efficient and effective system for searching the Web of Data and can be used as a basic infrastructure for Web-scale Semantic Web search engines.     

Adaptive fuzzy IMM algorithm for uncertain target tracking

In real system application, the interacting multiple model (IMM)-based uncertain target tracking system operates with the following problems: it requires less computing resources as well as a robust performance with respect to the maneuvering such as a sub-model mismatched case, and further, it requires an easy design procedure related to its structures and parameters. To solve these problems, an adaptive fuzzy IMM (AFIMM) algorithm, which is based on well-defined basis sub-models and well-adjusted mode transition probabilities (MTPs), is proposed. The basis sub-models are defined by the detailed analysis in terms of kinematic models as well as the maneuvering property and the MTPs are adjusted by the fuzzy adaptor as well as the fuzzy decision maker. To verify the performance of the proposed algorithm, an airborne target tracking is performed. Simulation results show that the AFIMM effectively solves the problems experienced in the uncertain target tracking system online. Keywords: Adaptive fuzzy IMM, basis sub-models, mode transition probabilities, uncertain target.