Microcalcification detection is an important part of early breast cancer detection. In this paper, we propose a microcalcification detection algorithm using adaptive contrast enhancement in a mammography CAD (computer-aided diagnosis) system. The proposed microcalcification detection algorithm includes two parts. One is adaptive contrast enhancement in which the enhancement filtering parameters are determined based on noise characteristics of the mammogram. The other is a multi-stage microcalcification detection. The results show that the proposed microcalcification detection algorithm is much more robust against fluctuating noisy environments.

A novel concurrent core test approach is proposed to reduce the test cost of SOC. Prior to test, the test sets corresponding to cores under test (CUT) are merged by using the proposed merging algorithm to obtain a minimum merged test set. During test, the proposed scan tree architecture is employed to support the concurrent core test using the merged test set. The approach achieves concurrent core test with one scan input and low hardware overhead. Moreover, the approach does not need any additional test generation, and it can be used in conjunction with general compression/decompression techniques to further reduce test cost. Experimental results for ISCAS 89 benchmarks have proven the efficiency of the proposed approach.

This paper proposes novel methods to provide intelligence for characters in fighting action games by using neural networks. First, how a character learns basic game rules and matches against randomly acting opponents is considered. Since each action takes more than one time unit in general fighting action games, the results of a character's action are exposed not immediately but several time units later. We evaluate the fitness of a decision by using the relative score change caused by the decision. Whenever the scores of fighting characters are changed, the decision causing the score change is identified, and then the neural network is trained by using the score difference and the previous input and output values which induced the decision. Second, how to cope more properly with opponents that act with predefined action patterns is addressed. The opponents' past actions are utilized to find out the optimal counter-actions for the patterns. Lastly, a method in order to learn moving actions is proposed. To evaluate the performance of the proposed algorithm, we implement a simple fighting action game. Then the proposed intelligent character (IC) fights with the opponent characters (OCs) which act randomly or with predefined action patterns. The results show that the IC understands the game rules and finds out the optimal counter-actions for the opponents' action patterns by itself.

In this letter, we suggest two new efficient hardware structures of correlators for packet and frame synchronization of MB-OFDM UWB. In the proposed structure 1, we suggest a hierarchical structure composed of 8 and 16 tap sub-correlators instead of ordinary 128 tap correlators. In the proposed structure 2, we suggest a structure which uses quantized coefficients and simplified multipliers. Results of simulations indicates that the hardware complexities of proposed structures are reduced to about 54% and 31% with minor performance loss, compared with a conventional method.

Scaling of CMOS Integrated Circuit is becoming difficult, due mainly to rapid increase in power dissipation. How will the semiconductor technology and industry develop? This paper discusses challenges and opportunities in system LSI from three levels of perspectives: transistor level (physics), IC level (electronics), and business level (economics).

The Hilbert transformation together with empirical mode decomposition (EMD) produces Hilbert spectrum (HS) which is a fine-resolution time-frequency representation of any nonlinear and non-stationary signal. The EMD decomposes the mixture signal into some oscillatory components each one is called intrinsic mode function (IMF). Some modification of the conventional EMD is proposed here. The instantaneous frequency of every real valued IMF component is computed with Hilbert transformation. The HS is constructed by arranging the instantaneous frequency spectra of IMF components. The HS of the mixture signal is decomposed into subspaces corresponding to the component sources. The decomposition is performed by applying independent component analysis (ICA) and Kulback-Leibler divergence based K-means clustering on the selected number of bases derived from HS of the mixture. The time domain source signals are assembled by applying some post processing on the subspaces. We have produced experimental results using the proposed separation technique.

This letter studies the effect of node mobility on application-level QoS of audio-video multipath streams in wireless ad hoc networks. The audio-video streams are transmitted with the MultiPath streaming scheme with Media Synchronization control (MPMS), which was previously proposed by the authors. We perform computer simulation with a grid topology network of IEEE 802.11b including two mobile nodes. The simulation results show that MPMS is effective in achieving high application-level QoS in mobile networks as well.

Lossless video coding is required in the fields of archiving and editing digital cinema or digital broadcasting contents. This paper combines a discrete wavelet transform and adaptive inter/intra-frame prediction in the wavelet transform domain to create multiresolution lossless video coding. Based on the image statistics of the wavelet transform domains in successive frames, inter/intra frame adaptive prediction is applied to the appropriate wavelet transform domain. This adaptation offers superior compression performance. A progressive transmission scheme is also proposed for effective resolution scalability. Experiments on test sequences confirm the effectiveness of the proposed algorithm.

H.264 video coding standard has a significant performance better than the other standards are the adoption of variable block sizes, multiple reference frames, and the consideration of rate distortion optimization within the codec. However, these features incur a considerable complexity in the encoder for motion estimation. As for the multiple reference frames motion estimation, the increased computation is in proportion to the number of searched reference frames. In this paper, a fast multiple frame reference frames selection method is proposed for H.264 video coding. The proposed algorithm can efficiently determine the best reference frame from the allowed five reference frames. As determine the number of reference frames to search the motion using the correlation of the different block between the block of current frame and that of previous frame, this scheme can efficiently reduce the computational cost while keeping the similar quality and bit-rate. Simulation results show that the speed of the proposed method is faster than that of the original scheme adapted in JVT reference software JM95 while keeping the similar video quality and bit-rate.

Because fault-based attacks on cryptosystems have been proven effective, fault diagnosis and tolerance in cryptography have started a new surge of research and development activity in the field of applied cryptography. Without magnitude comparisons, the Montgomery multiplication algorithm is very attractive and popular for Elliptic Curve Cryptosystems. This paper will design a Montgomery multiplier array with a bit-parallel architecture in GF(2m) with concurrent error detection capability to protect it against fault-based attacks. The robust Montgomery multiplier array with concurrent error detection requires only about 0.2% extra space overhead (if m=512 is as an example) and requires four extra clock cycles compared to the original Montgomery multiplier array without concurrent error detection.

The computational grid provides a promising platform for the deployment of various high-performance computing applications. Problem in implementing computational grid environments is how to effectively use various resources in the system, such as CPU cycle, memory, communication network, and data storage. There are many effective heuristic algorithms for scheduling in the computational grid, however most scheduling strategies have no theoretical guarantee at all. In this paper, a cost-based online scheduling algorithm is presented for job assignment in the grid environment with theoretical guarantee. Firstly, a scheduling framework is described, where the grid environment is characterized, and the online job model is defined. Secondly, the cost-based online scheduling algorithm is presented where costs of resources are exponential functions of their loads, and the performance of this algorithm is theoretically analyzed against the performance of the optimal offline algorithm. Finally, we implement the algorithm in the grid simulation environment, and compare the performance of the presented algorithm with the other three algorithms, and experimental results indicate that the cost-based online scheduling algorithm can outperform the other three online algorithms.

Grid computing technologies enable large-scale aggregation and sharing of resources via wide-area networks. Grid technologies include elements such as security, job description, information gathering, scheduling, and resource dispatching, among others. In this paper, we address information gathering and focus on providing a domain-based model for network information measurement using Network Weather Service (NWS) on Grid computing environments.

iPat/OMP is an interactive parallelization assistance tool for OpenMP. In the present paper, we describe the design concept of iPat/OMP, the parallelization sequence achieved by the tool and its current implementation status. In addition, we present an evaluation of the performance of the implemented functionalities. The experimental results show that iPat/OMP can detect parallelism and create an appropriate OpenMP directive for several for-loops.

Mobile applications require software reconfiguration to improve resource usage and availability. We propose a power-aware reconfiguration scheme that (1) moves energy-demanding applications to proxy servers, and (2) adjusts the fidelity of mobile applications as resources diminish. We formulate a cooperative reconfiguration plan which determines when, where, and which components should be deployed and have their fidelity controlled, so as to minimize the power consumption of mobile devices and to utilize the system resources of servers efficiently. We then construct a graph-theoretic model of the cost of migrating components to one proxy server or to a cluster of servers. In this model, changes to the residual energy of mobile devices, available server resources, and the wireless network bandwidth can all accelerate or decelerate the migration and fidelity control of applications. We suggest an approximation algorithm that achieves a near-optimal solution in terms of energy consumption. Our proposal will support mobile applications which require large amount of computation and need to maintain their services for an extended time such as video conferencing, multimedia e-mail, and real-time navigation. Simulation-based experiments verify that our scheme is an efficient way to extend the battery life of mobile devices and to improve the response time of mobile applications.

This paper describes a numerical design procedure of element values of RC polyphase filters with equal minima in stopband and equal ripple in passband. Determination of element values of RC polyphase filters with equal-ripple characteristic have not been solved to the best knowledge of the authors. There found a paper tackling with the problem; however, it can only give sub-optimal solutions via numerical calculation [3]. We propose a numerical element value design procedure for RC polyphase filters with equi-ripple gain in both stopband and passband by using the coefficient matching method. Some design examples are given.

In parallelizing compilers on distributed memory systems, distributions of irregular sized array blocks are provided for load balancing and irregular problems. The irregular data redistribution is different from the regular block-cyclic redistribution. This paper is devoted to scheduling message for irregular data redistribution that attempt to obtain suboptimal solutions while satisfying the minimal communication costs condition and the minimal step condition. Based on the list scheduling, an efficient algorithm is developed and its experimental results are compared with previous algorithms. The improved list algorithm provides more chance for conflict messages in its relocation phase, since it allocates conflict messages through methods used in a divide-and-conquer algorithm and a relocation algorithm proposed previously. The method of selecting the smallest relocation cost guarantees that the improved list algorithm is more efficient than the other two in average.

Grid computing presents a new trend to distributed and Internet computing to coordinate large scale resources sharing and problem solving in dynamic, multi-institutional virtual organizations. Due to the diverse failures and error conditions in the grid environments, developing, deploying, and executing applications over the grid is a challenge, thus dependability is a key factor for grid computing. This paper presents a dependable grid computing framework, called DRIC, to provide an adaptive failure detection service and a policy-based failure handling mechanism. The failure detection service in DRIC is adaptive to users' QoS requirements and system conditions, and the failure-handling mechanism can be set optimized based on decision-making method by a policy engine. The performance evaluation results show that this framework is scalable, high efficiency and low overhead.

Recent improvements in the performance of end-computers and networks have made it feasible to construct a grid system over the Internet. A grid environment consists of many computers, each having a set of components and a distinct performance. These computers are shared among many users and managed in a distributed manner. Thus, it is important to focus on a situation in which the computers are used unevenly due to decentralized management by different task schedulers. In this study, which is a preliminary investigation of the performance of task allocation schemes employed in a decentralized environment, the average execution time of a long-lived task is analytically derived using the M/G/1-PS queue. Furthermore, assuming a more realistic condition, we evaluate the performance of some task allocation schemes adopted in the analysis, and clarify which scheme is applicable to a realistic grid environment.

This paper proposes a set of novel distributed algorithms on m-D mesh overlay configurations for short delay and low resource consumption application layer multicast. In contrast to previous approaches, our application layer multicast adopts two-layer tree architecture and the novelty and contribution are: (1) cluster formation algorithm assigns the closest group members into the same cluster that greatly decreases the multicast delay and resource consumption caused by the message transmission among the members with long distances; (2) optimal core selection algorithm seeks the cluster member who has the minimum sum of static delay distances to other cluster members as the optimal cores (i.e. cluster cores) that guarantees the short multicast delay; (3) weighted shortest path tree generation algorithm constructs a shortest path tree rooted at the optimal core for each cluster. The shortest path tree utilizes the minimum sum of links that are on the shortest paths among the cluster members; and (4) distributed multicast routing algorithm directs the multicast messages to be efficiently distributed along the two-layer multicast architecture in parallel without a global control. The extended simulation results indicate that the application layer multicast constructed by our algorithms is efficient in terms of short multicast delay and low network resource consumption as compared with other well-known existing multicast solutions.

The concept of grid computing emerged with the appearance of high-speed network. Effective grid worker (i.e., computing resource) selection mechanism is important to achieve reliable grid computing system since each worker participate in grid computing is heterogeneous. In this paper, we suggest a credible worker selection mechanism that maximizes grid computing performance by allocating appropriate tasks to each grid worker. Diverse workers can be used efficiently by grid applications through the ranking process of worker's credibility. Initially, the rank of each grid worker's credibility is decided considering static information only such as CPU speed, RAM size, storage capacity and network bandwidth. And then, the rank is refined by using dynamic information such as failure rate, turn around time provided after the task is completed, and correctness of the return value. In the experiments, we find that the proposed mechanism provides improved grid computing performance with high credibility.