This paper proposes several novel hierarchical interconnection networks based on the (3, 3)-graphs, namely folded (3, 3)-networks, root-folded (3, 3)-networks, recursively expanded (3, 3)-networks, and flooded (3, 3)-networks. Just as the hypercubes, CCC, Peterson-based networks, and Heawood-based networks, these hierarchical networks have the following nice properties: regular topology, high scalability, and small diameters. Due to these important properties, these hierarchical networks seem to have the potential as alternatives for the future interconnection structures of multicomputer systems, especially massively parallel processors (MPPs). Furthermore, this paper will present the routing and broadcasting algorithms for these proposed networks to demonstrate that these algorithms are as elegant as the algorithms for hypercubes, CCC, and Petersen- or Heawood-based networks.

The alignment of biological sequences is a crucial tool in molecular biology and genome analysis. A wide variety of approaches has been proposed for multiple sequence alignment problem; however, some of them need prerequisites to help find the best alignment or some of them may suffer from the drawbacks of complexity and memory requirement so they can be only applied to cases with a limited number of sequences. In this paper, we view the multiple sequence alignment problem as an optimization problem and propose a heuristic-based genetic algorithm (GA) approach to solve it. The heuristic/GA hybrid yields better results than other well-known packages do. Experimental results are presented to illustrate the feasibility of the proposed approach.

By using distributed database systems, many advantages can be obtained such as database management cost, efficiency, and high integrity of systems through allocating fragments to many distributed sites with horizontal/vertical fragmentation of global database schema. To minimize costs, distributed algorithms must be applied so that database fragments are allocated to optimal sites. It is useful to replicate fragments, such as allocating many copies in many sites including load balancing. But there are too many possible combinations of each site and fragment, making it impossible to find a solution in real time, i.e., it is an NP-complete problem. This paper proposes near optimal heuristic algorithms for minimizing cost by defining a cost model based on read and update queries that are requested in many sites. Various factors are applied to the proposed algorithms for sizing efficient network resources that compute database transactions as remote query or update requests for consistency in replicated database systems. For network load balancing, incoming network traffic table is defined in each site. A request transaction from unallocated sites to allocated sites can be accessed properly at any other replicated sites by using the network traffic table. Finally, some experimental results verified the proposed algorithms by comparing actual cases of database allocation.

Many techniques have been proposed for segmenting feature point trajectories tracked through a video sequence into independent motions, but objects in the scene are usually assumed to undergo general 3-D motions. As a result, the segmentation accuracy considerably deteriorates in realistic video sequences in which object motions are nearly degenerate. In this paper, we propose a multi-stage unsupervised learning scheme first assuming degenerate motions and then assuming general 3-D motions and show by simulated and real video experiments that the segmentation accuracy significantly improves without compromising the accuracy for general 3-D motions.

In this paper, the optimal assignment problem which assigns cells in PCS (Personal Communication Service) to switches on ATM (Asynchronous Transfer Mode) network is investigated. The cost considered in this paper has two components: one is the cost of handoff that involves two switches, and the other is the cost of cabling. This problem assumes that each cell in PCS can be assigned to two switches in ATM network. This problem is modelled as dual-homing cell assignment problem, which is a complex integral linear programming (ILP) problem. Since finding an optimal solution of this problem is NP-hard, a hybrid method which combines several heuristics and a stochastic search method (based on a simulated annealing(SA) approach) is proposed to solve this problem. The solution method consists of three phases: Primary Assignment Decision Phase (PADP), Secondary Assignment Decision Phase (SADP) and Refinement Phase (RP). The PADP and SADP are used to find good initial assignment, then domain-dependent heuristics are encoded into perturbations of SA in Refinement Phase to improve the result. Simulation results show that the proposed hybrid method is robust for this problem.

A new scheme for watermarking based on vector quantization (VQ) over a binary symmetric channel is proposed. By optimizing VQ indices with genetic algorithm, simulation results not only demonstrate effective transmission of watermarked image, but also reveal the robustness of the extracted watermark.

An adaptive filtering algorithm based on the sliding window criterion is known to be very attractive for violent changing environments. In this paper, a new sliding window linearly constrained recursive least squares (SW-LC-RLS) algorithm based on the modified minimum mean squared error (MMSE) structure is devised for the RAKE receiver in direct sequence spread spectrum code-division multiple access (DS-SS CDMA) system over multipath fading channels, where the channel estimation scheme is accomplished at the output of adaptive filter. The proposed SW-LC-RLS algorithm has the advantage of having faster convergence property and tracking ability, and can be applied to the environments, where the narrowband interference is joined suddenly to the system, to achieve desired performance. Via computer simulation, we show that the performance, in terms of mean square errors (MSE), signal to interference plus noise ratio (SINR) and bit error rate (BER), is superior to the conventional LC-RLS and orthogonal decomposition-based LMS algorithms based on the MMSE structure.

In this paper we apply a parallel adaptive solution algorithm to simulate nanoscale double-gate metal-oxide-semiconductor field effect transistors (MOSFETs) on a personal computer (PC)-based Linux cluster with the message passing interface (MPI) libraries. Based on a posteriori error estimation, the triangular mesh generation, the adaptive finite volume method, the monotone iterative method, and the parallel domain decomposition algorithm, a set of two-dimensional quantum correction hydrodynamic (HD) equations is solved numerically on our constructed cluster system. This parallel adaptive simulation methodology with 1-irregular mesh was successfully developed and applied to deep-submicron semiconductor device simulation in our recent work. A 10 nm n-type double-gate MOSFET is simulated with the developed parallel adaptive simulator. In terms of physical quantities and refined adaptive mesh, simulation results demonstrate very good accuracy and computational efficiency. Benchmark results, such as load-balancing, speedup, and parallel efficiency are achieved and exhibit excellent parallel performance. On a 16 nodes PC-based Linux cluster, the maximum difference among CPUs is less than 6%. A 12.8 times speedup and 80% parallel efficiency are simultaneously attained with respect to different simulation cases.

The goal of source localization in the brain is to estimate a set of parameters for representing source characteristics; one of such parameters is the source number. We here propose a method combining the Powell algorithm with the information criterion method for determining the optimal dipole number. The potential errors can be calculated by the Powell algorithm with the concentric 4-sphere head model and 32 electrodes, then the number of dipoles is determined by the information criterion method with the potential errors mentioned above. This method has the advantages of a high identification accuracy of dipole number and a small number of EEG data because in this method: (1) only one EEG topography is used in the computation, (2) 32 electrodes are used to obtain the EEG data, (3) the optimal dipole number can be obtained by this method. In order to prove our method to be efficient, precise and robust to noise, 10% white noise is introduced to test this method theoretically. Some investigations are presented here to show our method is an advanced approach for determining the optimal dipole number.

Recently, Muramatsu proposed source coding algorithms that use the randomness of a past sequence. The technique of his source coding algorithms is one method of constructing codes from the technique of random coding. By using his technique, we propose a channel coding algorithm with random numbers which can be observed by both the encoder and the decoder where the random numbers are independent of the messages to be transmitted. Then the proposed coding algorithm can transmit messages over a discrete memoryless channel up to the channel capacity with an arbitrarily small decoding error rate and arbitrarily small bits of random numbers per message transmission asymptotically.

In this paper, we propose a new technique to generate virtual views of three-dimensional (3D) models. The technique is implemented into our facial pose transformation system, which takes only one frontal image and transforms it into virtual views. In our system, to overcome the complex of 3D geometric model, Image Based Rendering based algorithm and mesh-based methods are applied. We also introduce our new Invertible Meshwarp Algorithm, which is developed based on Two-pass Meshwarp Algorithm. Firstly, in the system, for any given person, we take a frontal face image to compose a frontal mesh for it. The standard mesh set of a specific person is created for several face sides; front, half left, half right, left and right side. The other meshes are then automatically generated based on the standard mesh set and the frontal mesh. Continually, we use Invertible Meshwarp Algorithm, which improvably solves the overlap or inversion of neighbor vertices of those created meshes. This step will finalize the generation of different views or the virtual looks of the frontal face image. We then evaluate our transformation system performance by comparing the normalized distance between several feature points in the real and transformed face images. The system is built based on C/C++ language and our result shows that the average error in the feature location is about 7% of the distance from the center of both eyes to the center of a mouth between the actual and transformed face images.

Sampling is important for many applications in research areas such as graphics, vision, and image processing. In this paper, we present a novel stratified sampling algorithm (SSA) for the coiled tubing surface with a given probability density function. The algorithm is developed from the inverse function of the integration for the areas of the coiled tubing surface. We exploit a Hierarchical Allocation Strategy (HAS) to preserve sample stratification when generating any desirable sample numbers. This permits us to reduce variances when applying our algorithm to Monte Carlo Direct Lighting for realistic image generation. We accelerate the sampling process using a segmentation technique in the integration domain. Our algorithm thus runs 324 orders of magnitude faster when using faster SSA algorithm where the order of the magnitude is proportional to the sample numbers. Finally, we employ a parabolic interpolation technique to decrease the average errors occurred for using the segmentation technique. This permits us to produce nearly constant average errors, independent of the sample numbers. The proposed algorithm is novel, efficient in computing and feasible for realistic image generation using Monte Carlo method.

Internet traffic engineering is much important for Internet Service Providers (ISPs) today, since it can be used to fully utilize already deployed network resources. For ISPs, the requirements for traffic engineering should be simple, easy to configure, cost-effective and efficient. Based on these considerations, we propose an algorithm called Web First Adaptive Traffic Engineering (WFATE). Since World Wide Web (WWW) services dominate most of the total Internet traffic and WWW flows are not long-lived, we only apply load balancing to WWW traffic in the algorithm. It can be shown that the number of coexistent WWW flows at an ingress node is almost certainly below a bound, and thus a forward-per-flow mechanism without keeping track of the state of each flow is feasible. This mechanism can balance traffic load at fine granularity and therefore get better performance. Through simulations and performance comparison, it is shown that WFATE is quite efficient, which can improve the network throughput averagely by 26% under the "dense source" traffic pattern and 9% under the "sparse source" traffic pattern.

We analyze the Lagarias-Odlyzko low-density attack precisely, and show that this low-density attack can be applied to the Chor-Rivest and the Okamoto-Tanaka-Uchiyama cryptosystemes, which are considered to be secure against the low-density attack. According to our analysis, these schemes turn out to be no longer secure against the low-density attack.

In this paper, a simple blind algorithm for a beamforming antenna is proposed. This algorithm exploits the property of cyclostationary signals whose cyclic autocorrelation function depends on delay as well as frequency. The cost function is the mean square error between the delay product of the beamformer output and a complex exponential. Exploiting the delay greatly reduces the possibility of capturing undesired signals. Through analysis of the minima of the non-quadratic cost function, conditions to extract a single signal are derived. Application of this algorithm to code-division multiple-access systems is considered, and it is shown through simulation that the desired signal can be extracted by appropriately choosing the delay as well as the frequency.

In the CNN problem, a "scene" appears on the two-dimensional plane, at different positions sequentially, and a "camera crew" has to shoot the scene whenever it appears. If a scene appears at some position, the camera crew does not have to move to the position exactly, but has only to move to a point that lies in the same horizontal or vertical line with the scene. Namely it is enough to move either to the same row or to the same column. The goal is to minimize the total moving distance of the camera crew. This problem has been quite popular in the last decade but it is still open whether or not there is a competitive algorithm, i.e., an algorithm with competitive ratio bounded by a constant. In this paper we study this problem under a natural restriction that the server can move only along the X-axis and the Y-axis. It is shown that there exists a competitive algorithm for this restricted version, namely there is an online algorithm for this "axis-bound CNN" with competitive ratio 9.0.

Learning behaviors of hierarchically structured stochastic automata operating in a general nonstationary multiteacher environment are considered. It is shown that convergence with probability 1 to the optimal path is ensured by a new learning algorithm which is an extended form of the relative reward strength algorithm. Several computer simulation results confirm the effectiveness of the proposed algorithm.

A variety of real-time multicast applications such as video conferences, remote lectures, and video-on-demand have become in commonplace with the expansion of broadband Internet services. Due to nontrivial problems in the IP multicast technology, the peer-to-peer multicast technology (P2P-multicast) has emerged as a practical implementation, although its network resource utilization is less efficient. A multihome network has the potential of alleviating this inefficiency by providing flexibility in communication path selections for each host with multiple gateways to the Internet. This paper has first formulated the P2P-multicast routing problem in the multihome network, and has proved the NP-completeness of its decision problem. Then, a two-stage heuristic algorithm called P2PMM_router has been presented for this P2P Multicast Multihome-network routing problem. The first stage constructs an initial multicast routing tree from an optimum spanning tree by Prim algorithm, through satisfying the constraints. The second stage improves the tree by repeating partial modifications and constraint satisfactions. The extensive simulation results using random network instances support the effectiveness of our P2PMM_router.

The issues of comparing the similarity or dissimilarity (distance) between structures have been studied. Especially, several distances between trees and their efficient algorithms have been proposed. However, all of the tree distances are defined based on mapping between vertices only, and they are helpless to compare the tree structures whose vertices and edges hold information. In this paper, we will propose a mapping between rooted and unordered trees based on vertex translation and edge translation, and then define a distance based on proposed mapping, and develop an efficient algorithm for computing proposed distance. Proposed distance can be used to compare the similarity or distance between two natural language sentences.

In this letter, we propose a packet scheduling algorithm to support both real-time voice and video traffic for wireless multimedia data service in orthogonal frequency division multiple access (OFDMA) system. Our design objective is to maximize the number of real-time service users that can be supported in the system subject to QoS requirement of packet loss rate (PLR). Both time slots and subcarriers are taken into account as the basic resource allocation unit in OFDMA/FDD system. The simulation results show that our proposed algorithm can dramatically increase the number of users satisfying the underlying QoS requirement for the real-time service, as compared to the existing algorithm.