State Transition Matrix (STM) is a table-based modeling language that has been frequently used in industry for specifying behaviors of systems. Functional correctness of a STM design (i.e., a design developed with STM) could often be expressed as invariant properties. In this paper, we first present a formalization of the static and dynamic aspects of STM designs. Consequentially, based on this formalization, we investigate a symbolic encoding approach, through which a STM design could be bounded model checked w.r.t. invariant properties by using Satisfiability Modulo Theories (SMT) solving technique. We have built a prototype implementation of the proposed encoding and the state-of-the-art SMT solver - Yices, is used in our experiments to evaluate the effectiveness of our approach. Two attempts for accelerating SMT solving are also reported.

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For the Internet, system developers often have to estimate the QoS by simulation techniques or mathematical analysis. Probabilistic model checking can evaluate performance, dependability and stability of information processing systems with random behaviors. We apply a hybrid analysis approach onto real-time distributed systems. In the hybrid analysis approach, we perform stepwise analysis using probabilistic models of target systems in different abstract levels. First, we create a probabilistic model with detailed behavior of the system (called detailed model), and apply simulation on the detailed model. Next, based on the simulation results, we create a probabilistic model in an abstract level (called simplified model). Then, we verify qualitative properties using the probabilistic model checking techniques. This prevents from state-explosion. We evaluate the validity of our approach by comparing to simulation results of NS-2 using a case study of a video data streaming system. The experiments show that the result of the proposed approach is very close to that of NS-2 simulation. The result encourages the approach is useful for the performance analysis on various domain.

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Probabilistic model checking is an emerging technology for analyzing systems which exhibit stochastic behaviors. The verification of a larger system using probabilistic model checking faces the same state explosion problem as ordinary model checking. Probabilistic symmetry reduction is a technique to tackle this problem. In this paper, we study probabilistic symmetry reduction for a system with a ring buffer which can describe various applications. A key of probabilistic symmetry reduction is identifying symmetry of states with respect to the structure of the target system. We introduce two functions; Shift_δ and Reverseto clarify such symmetry. Using these functions, we also present pseudo code to construct a quotient model. Then, we show two practical case studies; the one-dimensional Ising model and the Automatic Identification System (AIS). Behaviors of them were verified, but suffered from the state explosion problem. Through the case studies, we show that probabilistic symmetry reduction takes advantage of reducing the size of state space.

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This paper presents a strategy together with tool support for the translation of state machines from equational theories into rewrite theories, aiming at automatically generating rewrite theory specifications. Duplicate effort can be saved on specifying state machines both in equational theories and rewrite theories, when we incorporate the theorem proving facilities of CafeOBJ with the model checking facilities of Maude. Experimental results show that efficiencies of the generated specifications by the proposed strategy are significantly improved, compared with those that are generated by three other existing translation strategies.

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The number of Web applications handling online transaction is increasing, but verification of the correctness of Web application development has been done manually. This paper proposes a method for modeling, verifying and testing Web applications. In our method, a Web application is modeled using two finite-state automata, i.e., a page automaton which specifies Web page transitions, and an internal state automaton which specifies internal state transitions of the Web application. General properties for checking the Web application design are presented in LTL formulae and they are verified using the model checker Spin. Test cases examining the behavior of the Web application are also generated by utilizing the counterexamples obtained as the result of model checking. We applied our method to an example Web application to confirm its effectiveness.

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Network on Chip (NoC) is proposed as a new intra-chip communication infrastructure. In current NoC design, one related problem is mapping IP cores onto NoC architectures. In this paper, we propose a performance-aware hybrid algorithm (PHA) for mesh-based NoC to optimize performance indexes such as latency, energy consumption and maximal link bandwidth. The PHA is a hybrid algorithm, which integrates the advantages of Greedy Algorithm, Genetic Algorithm and Simulated Annealing Algorithm. In the PHA, there are three features. First, it generates a fine initial population efficiently in a greedy swap way. Second, effective global parallel search is implemented by genetic operations such as crossover and mutation, which are implemented with adaptive probabilities according to the diversity of population. Third, probabilistic acceptance of a worse solution using simulated annealing method greatly improves the performance of local search. Compared with several previous mapping algorithms such as MOGA and TGA, simulation results show that our algorithm enhances the performance by 30.7%, 23.1% and 25.2% in energy consumption, latency and maximal link bandwidth respectively. Moreover, simulation results demonstrate that our PHA approach has the highest convergence speed among the three algorithms. These results show that our proposed mapping algorithm is more effective and efficient.

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In the face of constant malicious attacks to network-connected software systems, software vulnerabilities need to be discovered early in the development phase. In this paper, we present AspFuzz, a state-aware protocol fuzzer based on the specifications of application-layer protocols. AspFuzz automatically generates anomalous messages that exploit possible vulnerabilities. The key observation behind AspFuzz is that most attack messages violate the strict specifications of application-layer protocols. For example, they do not conform to the rigid format or syntax required of each message. In addition, some attack messages ignore the protocol states and have incorrect orders of messages. AspFuzz automatically generates a large number of anomalous messages that deliberately violate the specifications of application-layer protocols. To demonstrate the effectiveness of AspFuzz, we conducted experiments with POP3 and HTTP servers. With AspFuzz, we can discover 20 reported and 1 previously unknown vulnerabilities for POP3 servers and 25 reported vulnerabilities for HTTP servers. Two vulnerabilities among these can be discovered by the state-awareness of AspFuzz. It can also find a SIP state-related vulnerability.

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Packet loss and delay are the major network impairments for transporting real-time voice over IP networks. In the proposed system, multiple descriptions of the speech are used to take advantage of the packet path diversity. A new objective method is presented for predicting the perceived quality of multi-stream voice transmission. Also proposed is a multi-stream playout buffer algorithm, together with an adaptive parameter adjustment scheme, that maximizes the perceived speech quality via delay-loss trading. Experimental results showed that, compared to FEC-protected single-path transmission, the proposed multi-stream transmission scheme achieves significant reductions in delay and packet loss rates as well as improved speech quality.

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Energy conservation is an important issue in mobile ad hoc networks (MANET), where the terminals are always supplied with limited energy. A new routing protocol is presented according to the study on the influence of low-energy nodes in ad hoc networks. The novel routing protocol (energy sensing routing protocol, ESRP) is based on the energy sensing strategy. Multiple strategy routing and substitute routing are both adopted in this paper. Referring to the level of the residual energy and the situation of energy consumption, different routes are chosen for packets transmission. The local maintenance is adopted, which can reduce packets retransmission effectively when the link breaks. We focus on the network lifetime most in all performances. The evaluation is done in comparison with other routing protocols on NS2 platform, and the simulation results show that this routing protocol can prolong the network lifetime and balance energy consumption effectively.

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In the present paper, we propose an object tracking method called scenario-type hypothesis object tracking. In the proposed method, an indoor monitoring region is divided into multiple closed micro-cells using sensor nodes that can detect objects and their moving directions. Sensor information is accumulated in a tracking server through wireless multihop networks, and object tracking is performed at the tracking server. In order to estimate the trajectory of objects from sensor information, we introduce a novel concept of the virtual world, which consists of virtual micro-cells and virtual objects. Virtual objects are generated, transferred, and deleted in virtual micro-cells according to sensor information. In order to handle specific movements of objects in micro-cells, such as slowdown of passing objects in a narrow passageway, we also consider the generation of virtual objects according to interactions among virtual objects. In addition, virtual objects are generated when the tracking server estimates loss of sensor information in order to decrease the number of object tracking failures. Through simulations, we confirm that the ratio of successful tracking is improved by up to 29% by considering interactions among virtual objects. Furthermore, the tracking performance is improved up to 6% by considering loss of sensor information.

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In this paper, a soft-error-tolerant BILBO (Built-In Logic Block Observer) FF (flip-flop) is presented. The proposed FF works as a soft-error-tolerant FF in system operations and as a BILBO FF in manufacturing testing. The construction of the proposed FF is based on that of an existing soft-error-tolerant FF, namely a BISER (Built-In Soft Error Resilience) FF. The proposed FF contains a reconfigurable C-element with XNOR calculation capability, which works as a C-element for soft-error-tolerance during system operations and as an XNOR gate employed in linear feedback shift registers (LFSRs) during manufacturing testing. The evaluation results shown in this paper indicate that the area of the proposed FF is 8.5% smaller than that of a simple combination of the existing BISER and BILBO FFs. In addition, the sum of CLK-Q delay and D-CLK setup times on system operations for the proposed FF is 19.7% shorter than that for the combination.

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Navigation systems providing route-guidance and traffic information are one of the most widely used driver-support systems these days. Most navigation systems are based on the map paradigm which plots the driving route in an abstracted version of a two-dimensional electronic map. Recently, a new navigation paradigm was introduced that is based on the augmented reality (AR) paradigm which displays the driving route by superimposing virtual objects on the real scene. These two paradigms have their own innate characteristics from the point of human cognition, and so complement each other rather than compete with each other. Regardless of the paradigm, the role of any navigation system is to support the driver in achieving his driving goals. The objective of this work is to investigate how these map and AR navigation paradigms impact the achievement of the driving goals: productivity and safety. We performed comparative experiments using a driving simulator and computers with 38 subjects. For the effects on productivity, driver's performance on three levels (control level, tactical level, and strategic level) of driving tasks was measured for each map and AR navigation condition. For the effects on safety, driver's situation awareness of safety-related events on the road was measured. To find how these navigation paradigms impose visual cognitive workload on driver, we tracked driver's eye movements. As a special factor of driving performance, route decision making at the complex decision points such as junction, overpass, and underpass was investigated additionally. Participant's subjective workload was assessed using the Driving Activity Load Index (DALI). Results indicated that there was little difference between the two navigation paradigms on driving performance. AR navigation attracted driver's visual attention more frequently than map navigation and then reduces awareness of and proper action for the safety-related events. AR navigation was faster and better to support route decision making at the complex decision points. According to the subjective workload assessment, AR navigation was visually and temporally more demanding.

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Automatic recognition of finger gestures can be used for promotion of life quality. For example, a senior citizen can control the home appliance, call for help in emergency, or even communicate with others through simple finger gestures. Here, we focus on one-stroke finger gesture, which are intuitive to be remembered and performed. In this paper, we proposed and evaluated an accelerometer-based method for detecting the predefined one-stroke finger gestures from the data collected using a MEMS 3D accelerometer worn on the index finger. As alternative to the optoelectronic, sonic and ultrasonic approaches, the accelerometer-based method is featured as self-contained, cost-effective, and can be used in noisy or private space. A compact wireless sensing mote integrated with the accelerometer, called MagicRing, is developed to be worn on the finger for real data collection. A general definition on one-stroke gesture is given out, and 12 kinds of one-stroke finger gestures are selected from human daily activities. A set of features is extracted among the candidate feature set including both traditional features like standard deviation, energy, entropy, and frequency of acceleration and a new type of feature called relative feature. Both subject-independent and subject-dependent experiment methods were evaluated on three kinds of representative classifiers. In the subject-independent experiment among 20 subjects, the decision tree classifier shows the best performance recognizing the finger gestures with an average accuracy rate for 86.92%. In the subject-dependent experiment, the nearest neighbor classifier got the highest accuracy rate for 97.55%.

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In this paper, we propose a spatially adaptive gradient-projection algorithm for the H.264 video coding standard to remove coding artifacts using local statistics. A hybrid method combining a new weighted constrained least squares (WCLS) approach and the projection onto convex sets (POCS) approach is introduced, where weighting components are determined on the basis of the human visual system (HVS) and projection set is defined by the difference between adjacent pixels and the quantization index (QI). A new visual function is defined to determine the weighting matrices controlling the degree of global smoothness, and a projection set is used to obtain a solution satisfying local smoothing constraints, so that the coding artifacts such as blocking and ringing artifacts can be simultaneously removed. The experimental results show the capability and efficiency of the proposed algorithm.

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In this article, we present a new image-stabilization technology for still images based on blind deconvolution and introduce it to a consumer digital still camera. This technology consists of three features: (1) double-exposure-based PSF detection, (2) efficient image deblurring filter, and (3) edge-based ringing reduction. Without deteriorating the deblurring performance, the new technology allows us to reduce processing time and ringing artifacts, both of which are common problems in image deconvolution.

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A novel method is proposed to estimate the 3D relative positions of an articulated body from point correspondences in an uncalibrated monocular image sequence. It is based on a camera perspective model. Unlike previous approaches, our proposed method does not require camera parameters or a manual specification of the 3D pose at the first frame, nor does it require the assumption that at least one predefined segment in every frame is parallel to the image plane. Our work assumes a simpler assumption, for example, the actor stands vertically parallel to the image plane and not all of his/her joints lie on a plane parallel to the image plane in the first frame. Input into our algorithm consists of a topological skeleton model and 2D position data on the joints of a human actor. By geometric constraint of body parts in the skeleton model, 3D relative coordinates of the model are obtained. This reconstruction from 2D to 3D is an ill-posed problem due to non-uniqueness of solutions. Therefore, we introduced a technique based on the concept of multiple hypothesis tracking (MHT) with a motion-smoothness function between consecutive frames to automatically find the optimal solution for this ill-posed problem. Since reconstruction configurations are obtained from our closed-form equation, our technique is very efficient. Very accurate results were attained for both synthesized and real-world image sequences. We also compared our technique with both scaled-orthographic and existing perspective approaches. Our proposed method outperformed other approaches, especially in scenes with strong perspective effects and difficult poses.

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This paper introduces an interactive expression editing system that allows users to design facial expressions easily. Currently, popular example-based methods construct face models based on the examples of target face. The shortcoming of these methods is that they cannot create expressions for novel faces: target faces not previously recorded in the database. We propose a solution to overcome this limitation. We present an interactive facial-geometric-feature animation system for generating expressions of novel faces. Our system is easy to use. By click-dragging control points on the target face, on the computer screen display, unique expressions are generated automatically. To guarantee natural animation results, our animation model employs prior knowledge based on various individuals' expressions. One model prior is learned from motion vector fields to guarantee effective facial motions. Another, different, model prior is learned from facial shape space to ensure the result has a real facial shape. Interactive animation problem is formulated in a maximum a posterior (MAP) framework to search for optimal results by combining the priors with user-defined constraints. We give an extension of the Motion Propagation (MP) algorithm to infer facial motions for novel target faces from a subset of the control points. Experimental results on different facial animations demonstrate the effectiveness of the proposed method. Moreover, one application of our system is exhibited in this paper, where users create expressions for facial sketches interactively.

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A Modified Hierarchical 3D-Torus (MH3DT) network is a 3D-torus network consisting of multiple basic modules, in which each basic module itself is a 3D-torus network. Inter-node communication performance has been evaluated using dimension-order routing and 2 virtual channels (VCs) under uniform traffic patterns but not under non-uniform traffic patterns. In this paper, we evaluate the inter-node communication performance of MH3DT under five non-uniform traffic patterns and compare it with other networks. We found that under non-uniform traffic patterns, the MH3DT yields high throughput and low latency, providing better inter-node communication performance compared to H3DT, TESH, mesh, and torus networks. Also, we found that non-uniform traffic patterns have higher throughput than uniform traffic in the MH3DT network.

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Autonomous objects represent active database objects which can be distributed over the Internet. This paper proposes a robust authentication scheme for the remote autonomous object based on AES (Advanced Encryption Standard) symmetric cryptosystem. Compared with related schemes, the proposed scheme not only resists various security attacks but also provides computation and communication efficiency.

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