This paper presents an approach for improving proximity and diversity in multiobjective evolutionary algorithms (MOEAs). The idea is to discover new nondominated solutions in the promising area of search space. It can be achieved by applying mutation only to the most converged and the least crowded individuals. In other words, the proximity and diversity can be improved because new nondominated solutions are found in the vicinity of the individuals highly converged and less crowded. Empirical results on multiobjective knapsack problems (MKPs) demonstrate that the proposed approach discovers a set of nondominated solutions much closer to the global Pareto front while maintaining a better distribution of the solutions.

Simple power analysis (SPA) can be employed in examining the power consumption trace of elliptic curve scalar multiplication to retrieve the computational sequence. However, SPA cannot distinguish point addition from point subtraction. The attacker still requires an exhaustive search to recover the private key when it is recoded in NAF or recoded by the 2-bit sliding window method. The average Hamming weight of an n-bit NAF recoded scalar is n/3, and an exhaustive search among the 2n/3 candidates is required. This paper shows that in a left-to-right NAF recoded or a left-to-right 2-bit sliding window manipulated scalar the relative position of nonzero bits will reveal their values. Our analysis skill reduces the number of candidates of the scalar from the naive search of 2n/3 to 22n/9 and 20.19n respectively for the cases of NAF and sliding window method.

In this paper, we propose a genetic algorithm (GA) based equalization approach for direct sequence ultra-wideband (DS-UWB) wireless communication systems, where the GA is combined with a RAKE receiver to combat the inter-symbol interference (ISI) due to the frequency selective nature of UWB channels for high data rate transmission. The proposed GA based equalizer outperforms significantly the RAKE and the RAKE-minimum mean square error (MMSE) receivers according to results obtained from intensive simulation work. The RAKE-GA receiver also provides bit-error-rate (BER) performance very close to that of the optimal RAKE-maximum likelihood detection (MLD) approach, while offering a much lower computational complexity.

The IEEE 802.11 MAC standard for wireless ad hoc networks adopts Binary Exponential Back-off (BEB) mechanism to resolve bandwidth contention between stations. BEB mechanism controls the bandwidth allocation for each station by choosing a back-off value from one to CW according to the uniform random distribution, where CW is the contention window size. However, in asymmetric multi-hop networks, some stations are disadvantaged in opportunity of access to the shared channel and may suffer severe throughput degradation when the traffic load is large. Then, the network performance is degraded in terms of throughput and fairness. In this paper, we propose a new cross-layer scheme aiming to solve the per-flow unfairness problem and achieve good throughput performance in IEEE 802.11 multi-hop ad hoc networks. Our cross-layer scheme collects useful information from the physical, MAC and link layers of own station. This information is used to determine the optimal Contention Window (CW) size for per-station fairness. We also use this information to adjust CW size for each flow in the station in order to achieve per-flow fairness. Performance of our cross-layer scheme is examined on various asymmetric multi-hop network topologies by using Network Simulator (NS-2).

This paper proposes a new pattern matching architecture with multi-character processing for deep packet inspection. The proposed pattern matching architecture detects the start point of pattern matching from multi-character input using input text alignment. By eliminating duplicate hardware components using process element tree, hardware cost is greatly reduced in the proposed pattern matching architecture.

Recently, the importance of data sharing structures in autonomous distributed networks has been increasing. A wireless sensor network is used for managing distributed data. This type of distributed network requires effective information exchanging methods for data sharing. To reduce the traffic of broadcasted messages, reduction of the amount of redundant information is indispensable. In order to reduce packet loss in mobile ad-hoc networks, QoS-sensitive routing algorithm have been frequently discussed. The topology of a wireless network is likely to change frequently according to the movement of mobile nodes, radio disturbance, or fading due to the continuous changes in the environment. Therefore, a packet routing algorithm should guarantee QoS by using some quality indicators of the wireless network. In this paper, a novel information exchanging algorithm developed using a hash function and a Boolean operation is proposed. This algorithm achieves efficient information exchanges by reducing the overhead of broadcasting messages, and it can guarantee QoS in a wireless network environment. It can be applied to a routing algorithm in a mobile ad-hoc network. In the proposed routing algorithm, a routing table is constructed by using the received signal strength indicator (RSSI), and the neighborhood information is periodically broadcasted depending on this table. The proposed hash-based routing entry management by using an extended MAC address can eliminate the overhead of message flooding. An analysis of the collision of hash values contributes to the determination of the length of the hash values, which is minimally required. Based on the verification of a mathematical theory, an optimum hash function for determining the length of hash values can be given. Simulations are carried out to evaluate the effectiveness of the proposed algorithm and to validate the theory in a general wireless network routing algorithm.

A reaction cut is a set of chemical reactions whose deletion blocks the operation of given reactions or the production of given chemical compounds. In this paper, we study two problems ReactionCut and MD-ReactionCut for calculating the minimum reaction cut of a metabolic network under a Boolean model. These problems are based on the flux balance model and the minimal damage model respectively. We show that ReactionCut and MD-ReactionCut are NP-hard even if the maximum outdegree of reaction nodes (Kout) is one. We also present O(1.822n), O(1.959n) and o(2n) time algorithms for MD-ReactionCut with Kout=2, 3, k respectively where n is the number of reaction nodes and k is a constant. The same algorithms also work for ReactionCut if there is no directed cycle. Furthermore, we present a 2O((log n)) time algorithm, which is faster than O((1+ε)n) for any positive constant ε, for the planar case of MD-ReactionCut under a reasonable constraint utilizing Lipton and Tarjan's separator algorithm.

An assume-guarantee verification method has been recognized as a promising approach to verify component-based software by model checking. This method is not only fitted to component-based software but also has a potential to solve the state space explosion problem in model checking. The method allows us to decompose a verification target into components so that we can model check each of them separately. In this method, assumptions are seen as the environments needed for the components to satisfy a property and for the rest of the system to be satisfied. The number of states of the assumptions should be minimized because the computational cost of model checking is influenced by that number. Thus, we propose a method for generating minimal assumptions for the assume-guarantee verification of component-based software. The key idea of this method is finding the minimal assumptions in the search spaces of the candidate assumptions. The minimal assumptions generated by the proposed method can be used to recheck the whole system at much lower computational cost. We have implemented a tool for generating the minimal assumptions. Experimental results are also presented and discussed.

This paper presents a high-speed, low-complexity VLSI architecture based on the modified Euclidean (ME) algorithm for Reed-Solomon decoders. The low-complexity feature of the proposed architecture is obtained by reformulating the error locator and error evaluator polynomials to remove redundant information in the ME algorithm proposed by Truong. This increases the hardware utilization of the processing elements used to solve the key equation and reduces hardware by 30.4%. The proposed architecture retains the high-speed feature of Truong's ME algorithm with a reduced latency, achieved by changing the initial settings of the design. Analytical results show that the proposed architecture has the smallest critical path delay, latency, and area-time complexity in comparison with similar studies. An example RS(255,239) decoder design, implemented using the TSMC 0.18 µm process, can reach a throughput rate of 3 Gbps at an operating frequency of 375 MHz and with a total gate count of 27,271.

In this paper, we studied the use of common-mode noise reduction technique for in-vehicle electronic equipment in an actual instrument design. We have improved the circuit model of the common-mode noise that flows to the wire harness to add the effect of a bypass capacitor located near the LSI. We analyzed the improved circuit model using a circuit simulator and verified the effectiveness of the noise reduction condition derived from the circuit model. It was also confirmed that offsetting the impedance mismatch in the PCB section requires to make a circuit constant larger than that necessary for doing the impedance mismatch in the LSI section. An evaluation circuit board comprising an automotive microcomputer was prototyped to experiment on the common-mode noise reduction effect of the board. The experimental results showed the noise reduction effect of the board. The experimental results also revealed that the degree of impedance mismatch in the LSI section can be estimated by using a PCB having a known impedance. We further inquired into the optimization of impedance parameters, which is difficult for actual products at present. To satisfy the noise reduction condition composed of numerous parameters, we proposed a design method using an optimization algorithm and an electromagnetic field simulator, and confirmed its effectiveness.

In this paper, a novel CMA (constant modulus algorithm) algorithm employing fast convolution in the DFT (discrete Fourier transform) domain is proposed. We propose a non-linear adaptation algorithm that minimizes CMA cost function in the DFT domain. The proposed algorithm is completely new one as compared to the recently introduced similar DFT domain CMA algorithm in that, the original CMA cost function has not been changed to develop DFT domain algorithm, resulting improved convergence properties. Using the proposed approach, we can reduce the number of multiplications to O(Nlog2 N), whereas the conventional CMA has the computation order of O(N2). Simulation results show that the proposed algorithm provides a comparable performance to the conventional CMA.

This letter presents the globally optimal data replication in the distributed networks. We propose a distributed approach based on the metropolis-hastings algorithm to achieve the globally optimal data replication without requiring any global information. Experimental results show that the proposed approach works well and the error can be held below 0.6% easily.

We develop a novel construction method for n-dimensional Hilbert space-filling curves. The construction method includes four steps: block allocation, Gray permutation, coordinate transformation and recursive construction. We use the tensor product theory to formulate the method. An n-dimensional Hilbert space-filling curve of 2r elements on each dimension is specified as a permutation which rearranges 2rn data elements stored in the row major order as in C language or the column major order as in FORTRAN language to the order of traversing an n-dimensional Hilbert space-filling curve. The tensor product formulation of n-dimensional Hilbert space-filling curves uses stride permutation, reverse permutation, and Gray permutation. We present both recursive and iterative tensor product formulas of n-dimensional Hilbert space-filling curves. The tensor product formulas are directly translated into computer programs which can be used in various applications. The process of program generation is explained in the paper.

This paper discusses the issues involved in the design of a complete information retrieval system for DataSpace based on user relevance probabilistic schemes. First, Information Hidden Model (IHM) is constructed taking into account the users' perception of similarity between documents. The system accumulates feedback from the users and employs it to construct user oriented clusters. IHM allows integrating uncertainty over multiple, interdependent classifications and collectively determines the most likely global assignment. Second, Three different learning strategies are proposed, namely query-related UHH, UHB and UHS (User Hidden Habit, User Hidden Background, and User Hidden keyword Semantics) to closely represent the user mind. Finally, the probability ranking principle shows that optimum retrieval quality can be achieved under certain assumptions. An optimization algorithm to improve the effectiveness of the probabilistic process is developed. We first predict the data sources where the query results could be found. Therefor, compared with existing approaches, our precision of retrieval is better and do not depend on the size and the DataSpace heterogeneity.

Polar Fourier Descriptor(PFD) and Spherical Fourier Descriptor(SFD) are rotation invariant feature descriptors for two dimensional(2D) and three dimensional(3D) image retrieval and pattern recognition tasks. They are demonstrated to show superiorities compared with other methods on describing rotation invariant features of 2D and 3D images. However in order to increase the computation speed, fast computation method is needed especially for machine vision applications like realtime systems, limited computing environments and large image databases. This paper presents fast computation method for PFD and SFD that are deduced based on mathematical properties of trigonometric functions and associated Legendre polynomials. Proposed fast PFD and SFD are 8 and 16 times faster than direct calculation that significantly boost computation process. Furthermore, the proposed methods are also compact for memory requirements for storing PFD and SFD basis in lookup tables. The experimental results on both synthetic and real data are given to illustrate the efficiency of the proposed method.

Social bookmarking services have recently made it possible for us to register and share our own bookmarks on the web and are attracting attention. The services let us get structured data: (URL, Username, Timestamp, Tag Set). And these data represent user interest in web pages. The number of bookmarks is a barometer of web page value. Some web pages have many bookmarks, but most of those bookmarks may have been posted far in the past. Therefore, even if a web page has many bookmarks, their value is not guaranteed. If most of the bookmarks are very old, the page may be obsolete. In this paper, by focusing on the timestamp sequence of social bookmarkings on web pages, we model their activation levels representing current values. Further, we improve our previously proposed ranking method for web search by introducing the activation level concept. Finally, through experiments, we show effectiveness of the proposed ranking method.

In this paper, a Stochastic Collocation Algorithm combined with Sparse Grid technique (SSCA) is proposed to deal with the periodic steady-state analysis for nonlinear systems with process variations. Compared to the existing approaches, SSCA has several considerable merits. Firstly, compared with the moment-matching parameterized model order reduction (PMOR) which equally treats the circuit response on process variables and frequency parameter by Taylor approximation, SSCA employs Homogeneous Chaos to capture the impact of process variations with exponential convergence rate and adopts Fourier series or Wavelet Bases to model the steady-state behavior in time domain. Secondly, contrary to Stochastic Galerkin Algorithm (SGA), which is efficient for stochastic linear system analysis, the complexity of SSCA is much smaller than that of SGA for nonlinear case. Thirdly, different from Efficient Collocation Method, the heuristic approach which may result in "Rank deficient problem" and "Runge phenomenon," Sparse Grid technique is developed to select the collocation points needed in SSCA in order to reduce the complexity while guaranteing the approximation accuracy. Furthermore, though SSCA is proposed for the stochastic nonlinear steady-state analysis, it can be applied to any other kind of nonlinear system simulation with process variations, such as transient analysis, etc.

Previously, we have proposed an access point (AP) allocation algorithm in indoor environments for the Wireless Internet-access Mesh NETwork (WIMNET) using one gateway (GW) to the Internet. WIMNET consists of multiple APs that are connected wirelessly mainly by the Wireless Distribution System (WDS), to expand the coverage area inexpensively and flexibly. In this paper, we present two extensions of this algorithm to enhance the applicability to the large-scale WIMNET. One is the multiple GW extension of the algorithm to increase the communication bandwidth with multiple GWs, where all the rooms in the network field are first partitioned into a set of disjoint GW clusters and then, our previous allocation algorithm is applied to each GW cluster sequentially. The APs in a GW cluster share the same GW. The other is the dependability extension to assure the network function by maintaining the connectivity and the host coverage, even if one link/AP fault occurs, where redundant APs are added to the AP allocation by our previous algorithm. The effectiveness of our proposal in terms of the number of APs and the throughput is verified through simulations using the WIMNET simulator.

There is evidence in favor of a relationship between the presence of 1/f noise and computational universality in cellular automata. To confirm the relationship, we search for two-dimensional cellular automata with a 1/f power spectrum by means of genetic algorithms. The power spectrum is calculated from the evolution of the state of the cell, starting from a random initial configuration. The fitness is estimated by the power spectrum with consideration of the spectral similarity to the 1/f spectrum. The result shows that the rule with the highest fitness over the most runs exhibits a 1/f type spectrum and its transition function and behavior are quite similar to those of the Game of Life, which is known to be a computationally universal cellular automaton. These results support the relationship between the presence of 1/f noise and computational universality.

Deploying and managing content objects efficiently is critical for building a scalable and transparent content delivery system. This paper investigates the advanced incremental deploying problem of which the objects are delivered in a successive manner. Recently, the researchers show that the minimum-cost content deployment can be obtained by reducing the problem to the well-known network flow problem. In this paper, the maximum flow algorithm for a single graph is extended to the incremental growing graph. Based on this extension, an efficient incremental content deployment algorithm is developed in this work.