Flexibility, adaptation and distribution have been regarded as major challenges of modern interorganizational workflow. To address these issues, this paper proposes an interorganizational workflow execution framework based on process agents and ECA rules. In our framework, an interorganizational workflow is modeled as a multiagent system with a process agent for each organization. The whole execution is divided into two parts: the intra-execution, which means execution within a same organization, and the inter-execution, which represents interaction between organizations. For intra-execution, we use the method of transforming the graph-based local workflow into block-based workflow to design general ECA rules. ECA rules are used to control internal state transitions and process agents are used to control external state transitions of tasks in the local workflows. Inter-execution is realized by process agent interaction protocols. The proposed approach can provide flexible execution of interorganizational workflow with distributed organizational autonomy and adaptation. A case study of offshore software development is illustrated for the proposed approach.

This paper proposes a new method for realizing the web page recommendation system by sharing users' web browse history on an anonymous P2P network. Our scheme creates a user profile, a summary of the user's web browse trends, by analyzing the contents of the web pages browsed. The scheme then provides a P2P network to exchange web browse histories so as to create mutual web page recommendations. The novelty of our method lies in its P2P network formulation; it is formulated in a way so that users having similar user profiles are automatically connected, yet their user profiles are protected from being disclosed to other users. The proposed method intentionally distributes bogus user profiles on the P2P network, while not harming the efficiency of the web browse history sharing process.

In this paper, we extend our framework of speculative computation in multi-agent systems by introducing default constraints. In research on multi-agent systems, handling incomplete information due to communication failure or due to other agents' delay in communication is a very important issue. For a solution to this problem, we previously proposed speculative computation based on abduction in the context of master-slave multi-agent systems and gave a procedure in abductive logic programming. In our previous proposal, a master agent prepares a default value for a yes/no question in advance, and it performs speculative computation using the default without waiting for a reply to the question. This computation is effective unless the contradictory reply to the default is returned. In this paper, we formalize speculative constraint processing, and propose a correct operational model for such computation so that we can handle not only yes/no questions, but also more general types of questions.

Recommender System (RS) predicts user's ratings towards items, and then recommends highly-predicted items to user. In recent years, RS has been playing more and more important role in the agent research field. There have been a great deal of researches trying to apply agent technology to RS. Collaborative Filtering, one of the most widely used approach to predict user's ratings in Recommender System, predicts a user's rating towards an item by aggregating ratings given by users who have similar preference to that user. In existing approaches, user similarity is often computed on the whole set of items. However, because the number of items is often very large and so is the diversity among items, users who have similar preference in one category may have totally different judgement on items of another kind. In order to deal with this problem, we propose a method to cluster items, so that inside a cluster, similarity between users does not change significantly from item to item. After the item clustering phase, when predicting rating of a user towards an item, we only aggregate ratings of users who have similarity preference to that user inside the cluster of that item. Experiments evaluating our approach are carried out on the real dataset taken from MovieLens, a movies recommendation web site. Experiment results suggest that our approach can improve prediction accuracy compared to existing approaches.

Web services (WS, hereafter) paradigm has attained such a relevance in both the academic and the industry world that the vision of the Internet has evolved from being considered as a mere repository of data to become the underlying infrastructure on which organizations' strategic business operations are being deployed [1]. Security is a key aspect if WS are to be generally accepted and adopted. In fact, over the past years, the most important consortiums of the Internet, like IETF, W3C or OASIS, have produced a huge number of WS-based security standards. Despite this spectacular growth, a development process that facilitates the systematic integration of security into all subprocesses of WS-based software development life-cycle does not exist. Eventually, this process should guide WS-based software developers in the specification of WS-based security requirements, the design of WS-based security architectures, and the deployment of the most suitable WS security standards. In this article, we will briefly present a process of this type, named PWSSec (Process for Web Services Security), and the artifacts used during the elicitation activity, which belongs to the subprocess WSSecReq aimed at producing a WS-based security requirement specification.

Due to the continuous growth of wireless communication technology and mobile equipment, the history management of moving object is important in a wide range of location-based applications. To process queries for history data, trajectories, we generally use trajectory-preserving index schemes based on the trajectory preservation property. This property means that a leaf node only contains segments belonging to a particular trajectory, regardless of the spatiotemporal locality of segments. The sacrifice of spatiotemporal locality, however, causes the index to increase the dead space of MBBs of non-leaf nodes and the overlap between the MBBs of nodes. Therefore, an index scheme for trajectories shows good performance with trajectory-based queries, but not with coordinate-based queries, such as range queries. We propose new index schemes that improve the performance of range queries without reducing performance with trajectory based queries.

High power dissipation can occur when the response to a test vector is captured by flip-flops in scan testing, resulting in excessive IR drop, which may cause significant capture-induced yield loss in the DSM era. This paper addresses this serious problem with a novel test generation method, featuring a unique algorithm that deterministically generates test cubes not only for fault detection but also for capture power reduction. Compared with previous methods that passively conduct X-filling for unspecified bits in test cubes generated only for fault detection, the new method achieves more capture power reduction with less test set inflation. Experimental results show its effectiveness.

This paper describes a technique for controlling the degree of expressivity of a desired emotional expression and/or speaking style of synthesized speech in an HMM-based speech synthesis framework. With this technique, multiple emotional expressions and speaking styles of speech are modeled in a single model by using a multiple-regression hidden semi-Markov model (MRHSMM). A set of control parameters, called the style vector, is defined, and each speech synthesis unit is modeled by using the MRHSMM, in which mean parameters of the state output and duration distributions are expressed by multiple-regression of the style vector. In the synthesis stage, the mean parameters of the synthesis units are modified by transforming an arbitrarily given style vector that corresponds to a point in a low-dimensional space, called style space, each of whose coordinates represents a certain specific speaking style or emotion of speech. The results of subjective evaluation tests show that style and its intensity can be controlled by changing the style vector.

DTW-based text-dependent speaker verification technology is an effective scheme for protecting personal information in personal electronic products from others. To enhance the performance of a DTW-based system, an impostor database covering all possible passwords is generally required for the matching scores normalization. However, it becomes impossible in our practical application scenario since users are not restricted in their choice of password. We propose a method to generate pseudo-impostor data by employing an acoustic codebook. Based on the pseudo-impostor data, two normalization algorithms are developed. Besides, a template compression approach based on the codebook is introduced. Some modifications to the conventional DTW global constraints are also made for the compressed template. Combining the normalization and template compression methods, we obtain more than 66% and 35% relative reduction in storage and EER, respectively. We expect that other DTW-based tasks may also benefit from our methods.

Steganographic methods usually produce distortions in cover images due to the process of embedding secret bits. These distortions are hard to remove, and thus the cover image cannot be recovered. Although the distortions are always small, they cannot be allowed for some sensitive applications. In this paper, we propose a reversible embedding scheme for VQ-compressed images, which allows the original cover image to be completely recovered after the extraction of the secret bits. The embedded payload in the proposed method comprises the secret bits plus the restoration information. In order to reduce the size of payload, we utilized the spatial correlations in the image as the restoration information and then compressed the correlations by a lossless compression method. In addition, an alternative pairing method for codewords was proposed to improve the stegoed image quality and control the embedding capacity. Experimental results showed that the proposed method has the benefit of high efficiency of the steganographic process, high image quality, and adaptive embedding capacity compared with other schemes.

3D video, which consists of a sequence of mesh models, can reproduce dynamic scenes containing 3D information. To summarize 3D video, a key frame extraction method is developed using rate-distortion (R-D) trade-off. For this purpose, an effective feature vector is extracted for each frame. Shot detection is performed using the feature vectors as a preprocessing followed by key frame extraction. Simple but reasonable definitions of rate and distortion are presented. Based on an assumption of linearity, an R-D curve is generated in each shot, where the locations of the key frames are optimized. Finally, R-D trade-off can be achieved by optimizing a cost function using a Lagrange multiplier, where the number of key frames is optimized in each shot. Therefore, our system will automatically determine the best locations and the number of key frames in the sense of R-D trade-off. Our experimental results show the extracted key frames are compact and faithful to the original 3D video.

This paper presents a lifting wavelet coding technique with permutation and coefficient modification processes for coding the structured geometry data of 3-D polygonal mesh model. One promising method for coding 3-D geometry data is based on the structure processing of a 3-D model on a triangle lattice plane, while maintaining connectivity. In the structuring process, each vertex may be assigned to several nodes on the triangular lattice plane. One of the nodes to which a vertex is assigned is selected as a representative node and the others are called expanded nodes. Only the geometry data of the vertices at the representative nodes are required for reconstructing the 3-D model. In this paper we apply a lifting wavelet transform with a permutation process for an expanded node at an even location in each decomposition step and the neighboring representative node. This scheme arranges more representative nodes into the lower frequency band. Also many representative nodes separated from the connective expanded nodes are made to adjoin each other in lower frequency bands, and the correlation between the representative nodes will be reduced by the following decomposition process. A process is added to use the modified coefficients obtained from the coefficients of the adjacent representative nodes instead of the original coefficients in the permutation process. This has the effect of restraining increases in the decomposed coefficients with larger magnitude. Some experiments in which the proposed scheme was applied to structured geometry data of a 3-D model with complex connectivity show that the proposed scheme gives better coding performance and the reconstructed models are more faithful to the original in comparison with the usual schemes.

In this letter, we propose PQ-MAC: a priority-based medium access control (MAC) protocol for providing quality of service (QoS) in wireless sensor networks (WSNs) which minimizes the energy consumption with traffic-based sleep-wakeup scheduling and supports QoS using differentiating channel access policy, packet scheduling, and queue management. The PQ-MAC utilizes the advantages of time division multiple access (TDMA) and slotted carrier-sense multiple access (CSMA). The proposed protocol is an energy-efficient, priority-based, and QoS compatible MAC protocol. It consists of multi-level queue management, sleep-wakeup scheduling, and an ordered contention period (CP) scheme. It also guarantees time-bounded delivery of QoS packets. Performance evaluation is conducted between PQ-MAC and S-MAC with respect to three performance metrics: energy consumption, throughput, and average latency. The simulation results show that the performance of PQ-MAC is better than that of S-MAC.

DHT based p2p systems appear to provide scalable storage services with idle resource from many unreliable clients. If a DHT is used in storage intensive applications where data loss must be minimized, quick replication is especially important to replace lost redundancy on other nodes in reaction to failures. To achieve this easily, a simple replication method directly uses a consistent set, such as a leaf set and a successor list. However, this set is tightly coupled to the current state of nodes and the traffic needed to support this replication can be high and bursty under churn. This paper explores efficient replication methods that only glimpse a consistent set to select a new replica. Replicas are loosely coupled to a consistent set and we can eliminate the compulsory replication under churn. Because of a complication of the new replication methods, the careful data management is needed under churn for the correct and efficient data lookup. Results from a simulation study suggest that our methods can reduce network traffic enormously for high data durability.

A simple and efficient semi-supervised classification method is presented. An unsupervised spectral mapping method is extended to a semi-supervised situation with multiplicative modulation of similarities between data. Our proposed algorithm is derived by linearization of this nonlinear semi-supervised mapping method. Experiments using the proposed method for some public benchmark data and color image data reveal that our method outperforms a supervised algorithm using the linear discriminant analysis and a previous semi-supervised classification method.

In this paper, we propose a statistical approach to improve the performance of spectral quantization of speech coders. The proposed techniques compensate for the distortion in a decoded line spectrum pair (LSP) vector based on a statistical mapping function between a decoded LSP vector and its corresponding original LSP vector. We first develop two codebook-based probabilistic matching (CBPM) methods by investigating the distribution of LSP vectors. In addition, we propose an iterative procedure for the two CBPMs. Next, the proposed techniques are applied to the predictive vector quantizer (PVQ) used for the IS-641 speech coder. The experimental results show that the proposed techniques reduce average spectral distortion by around 0.064 dB and the percentage of outliers compared with the PVQ without any compensation, resulting in transparent quality of spectral quantization. Finally, the comparison of speech quality using the perceptual evaluation of speech quality (PESQ) measure is performed and it is shown that the IS-641 speech coder employing the proposed techniques has better decoded speech quality than the standard IS-641 speech coder.

A new type of sound source segregation method using robot-mounted microphones, which are free from strict head related transfer function (HRTF) estimation, has been proposed and successfully applied to three simultaneous speech recognition systems. The proposed segregation method is executed with sound intensity differences that are due to the particular arrangement of the four directivity microphones and the existence of a robot head acting as a sound barrier. The proposed method consists of three-layered signal processing: two-line SAFIA (binary masking based on the narrow band sound intensity comparison), two-line spectral subtraction and their integration. We performed 20 K vocabulary continuous speech recognition test in the presence of three speakers' simultaneous talk, and achieved more than 70% word error reduction compared with the case without any segregation processing.

We consider the blind recovery problem such that images embedded with side information are given, and we want to obtain the side information under some prescribed constraints. In this case, the system equation becomes y=Ax+b where in addition to the unknown A and x, b also is an unknown quantity and but clearly not a noise component. We assume that several images with the same embedding side information are given, and the image processing to b is described as the perturbation of A. We formulate the optimization function to obtain A, b and x, under the constraint of some finite brightness levels i.e. finite alphabets.

This paper proposes a new binary motion estimation algorithm that improves the motion vector accuracy by using a hybrid distortion measure. Unlike conventional binary motion estimation algorithms, the proposed algorithm considers the sum of absolute difference (SAD) as well as the sum of bit-wise difference (SBD) as a block-matching criterion. In order to reduce the computational complexity and remove additional memory accesses, a new scheme is used for SAD calculation. This scheme uses 8-bit data of the lowest layer already moved into the local buffer to calculate the SAD of other higher binary layer. Experimental results show that the proposed algorithm finds more accurate motion vectors and removes the blockishness of the reconstructed video effectively. We applied this algorithm to existing video encoder and obtained noticeable visual quality enhancement.

We present a linear-time algorithm for treating collision response of articulated rigid bodies in physically based modeling. By utilizing the topology of articulated rigid bodies and the property of linear equations, our method can solve in linear time the system of linear equations that is crucial for treating collision response.