In this paper, we present our investigation of Latent Semantic Indexing (LSI) on the local query regions for solving the computation restrictions of the LSI on the global information space. Through the experiments with different SVD dimensionality on the local query regions, the results show that low-dimensional LSI can achieve much better precision than VSM and similar precision to global LSI. Such small SVD factors indicate that there is an almost linear surface in the local query regions. The largest or the two largest singular vectors have the ability to capture such a linear surface and benefit the particular query. In spite of the fact that Local LSI analysis needs to perform the Singular Value Decomposition (SVD) computation for each query, the surprisingly small requirements of the SVD dimension resolve the computation restrictions of LSI for large scale IR tasks. Moreover, on the condition that several relevant sample documents are available, application of low dimensional LSI for these documents can obtain comparable precision with the Local RF in a different manner.

A framework is described for a peer-to-peer information exchange system, and a collaborative information retrieval (IR) scheme for the system is proposed. The aims of the system include smooth knowledge and information management to activate organizations or communities. Conventional server-centric systems are weak because they create information-providing bottlenecks. Accordingly, the proposed framework targets the collaborative inter-working of personal repositories that accumulate per-user information, and accept and service requests. Issues concerning the framework are addressed. One issue is the retrieval of information from another's personal repository; the retrieval criteria of a system are tightly personalized for its user. The system is assumed to employ a vector space model with a concept-base as its IR mechanism. The vector space on one system is very different from that on another system. Another issue is the automated control of the information-providing criteria. This paper presents solutions to the first problem. To achieve IR that provides satisfactory results to a user requiring information from another's personal repository, we need vector space equalization to compensate for the differences in the vector spaces of the personal repositories. The paper presents a vector space equalization scheme, the automated relevance feedback scheme, that compensates the differences in the vector spaces of the personal repositories. We implement the scheme as a system and evaluate its performance using documents on the Internet.

We show that the necessary and sufficient condition for the existence of a balanced bowtie decomposition of the complete multigraph λKn is n 5 and λ(n-1) 0 (mod 12). Decomposition algorithms are also given.

An element consist of a slot and a post is designed for canceling the reflection in a rectangular waveguide by the method of moments. For reducing the computation time in practical design of the element with a wide range of coupling strength for an array, only the axial uniform currents on the post surface are considered. This approximation is valid when the post for reflection-canceling is far enough from the slot. The post location is determined by this simple analysis for both transverse and longitudinal slots with typical coupling strength. Measured results using 4 GHz-band standard waveguides reveal that the assumption of uniform line currents on the post surface is acceptable. The design is further extended to demonstrate its applicability to a practical array design by considering a wide range of coupling strength.

In this paper, we consider the problem of estimating the time-varying directions-of-arrival (DOAs) of coherent narrowband cyclostationary signals impinging on a uniform linear array (ULA). By exploiting the cyclostationarity of most communication signals, we investigate a new computationally efficient subspace-based direction estimation method without eigendecomposition and spatial smoothing (SS) processes. The proposed method uses the inherently temporal property of incident signals and a subarray scheme to decorrelate the signal coherency and to suppress the noise and interfering signals, while the null subspace is obtained from the resulting cyclic correlation matrix through a linear operation. Then an on-line implementation of this method is presented for tracking the DOAs of slowly moving coherent signals. The proposed algorithm is computationally simple and has a good tracking performance. The effectiveness of the proposed method is verified through numerical examples.

The case postpositions usually have more than one semantic role in Korean. The adverbial postpositions among various postpositions especially make the development of Korean-based machine translation system difficult, because they have more semantic roles than others. In this paper, we describe a new method for resolving semantic ambiguities of adverbial postpositions using decision tree induction. The lack of training examples in decision tree induction is overcome by clustering words into classes using a kind of greedy algorithm. The cross validation results show that the presented method achieves 76.5% of accuracy on the average, which is 20.3% improvement over the baseline method.

A compact high-temperature superconducting (HTS) bandpass filter (BPF) using coplanar waveguide (CPW) meander-line parallel-circuited resonators is proposed for microwave receiver applications. The design theory is presented based on a conventional filter theory with J-inverters. Also, analytical and numerical studies of the meander-line resonator are carried out in terms of equivalent circuit values, the resonant frequency, and the unloaded Q. Two- and four-stage 0.05 dB ripple Chebyshev BPFs at 2 GHz with relative bandwidth 60 MHz are fabricated with the metalorganic deposition (MOD)-derived YBCO films on LaAlO3 substrates and their performance are demonstrated. The measured frequency characteristics and the unloaded quality factors agree well with the theoretical and numerical results and the validity of the design theory is confirmed.

A mobile station (MS) positioning method using signal strength is an algorithm to estimate the geographical position of a target MS based on measured strength of signals transmitted to/from the MS from/to multiple base stations (BSs) at known geographical positions. This paper proposes a novel MS positioning method using signal strength in cellular systems. The primary sources of position location error for positioning methods using signal strength are multipath fading and shadowing. Although signal strength averaging can help to reduce the effect of multipath fading, the effect of shadowing still remains. In order to eliminate the error caused by shadowing, the proposed method applies a statistical approach and a minimum mean squared error (MMSE) criterion to determine a position estimate. The performance of the proposed method is compared to that of a maximum likelihood (ML) positioning method and a cell-site positioning method. The performance is obtained by computer simulations and field experiments. A computer simulation result shows that the proposed method can determine position estimates in higher probability than the ML method. Also, it is shown that the proposed method provides higher accuracy than the ML method and the cell-site method.

In recent years, sliding electric contacts came to be often used under very severe conditions such as high temperature, extremely low temperature, high vacuum, etc. Conventionally, solid lubricants having excellent properties in lubricating performance are generally used compositely with a metal of high electric conductivity, because of their high electrical resistivity. In the present study, we proved that more excellent sliding electrical contacts can be produced with a design made by controlling the distribution on contact surface of a solid lubricant having excellent lubricating performance and of a metal with high electric conductivity through expansion of Greenwood's theory.

In provisioning packet data service on wireless cellular networks, a scheme of altering connection status between mobile and base stations appeared with an effort to utilize resource during idle periods. A critical issue in such scheme of sojourn and transition on the connection states is to determine a maximum time to sojourn at each state. An excessive sojourn time leads to resource invasion by inactive stations, while a high cost of re-establishing connection components is imposed by an insufficient sojourn. Thus, the maximum sojourn times must be optimized in consideration of the two conflicting arguments. In this paper, we consider a generic scheme of connection status transitions and formulate a decision problem to determine maximum sojourn times by introducing a loss function which reflects the cost of connection re-establishment as well as the loss induced by inefficient resource usage. From the decision problem, we derive an optimal value for maximum sojourn time, identified as Bayes rule, by observing the delay time of last packet to have posterior information about the length of upcoming idle period. From the analytical results, we show the Bayes sojourn time is trivial under a constraint on loss coefficients when packet arrivals follow a Poisson process.

In testing the possible biological effects of electromagnetic exposure from cellular telephones in small animals such as mice, it is essential to realize a highly localized head exposure as close as possible to that due to cellular telephones in humans. In this study, a 1.5GHz exposure setup was developed which has a highly localized specific absorption rate (SAR) of 2W/kg in the mouse brain and a low whole-body averaged SAR of 0.27W/kg. The low whole-body averaged SAR was realized by using a flexible magnetic sheet attachment on the mouse holder. Its validity has been carefully examined by both numerical simulation with an anatomically based mouse model and experimental simulation with a solid mouse phantom. Good agreement was obtained between the numerical and experimental results, which confirmed the effectiveness of the magnetic sheet attachment to the mouse holder.

A dual greedy polyhedron is defined by a system of linear inequalities, where the right-hand sides are given by a submodular function and the coefficients matrix is given by the incidence vectors of antichains of a rooted forest. Faigle and Kern introduced this concept and showed that a dual greedy algorithm works for the linear program over dual greedy polyhedra. In this paper, we show that a dual greedy polyhedron is the isomorphic image of an ordinary submodular polyhedron under the Mobius function of the underlying rooted forest. This observation enables us to reduce linear optimization problems over dual greedy polyhedra to those over ordinary submodular polyhedra. We show a new max-min theorem for intersection of two dual greedy polyhedra as well.

The authors proposed a switching beam slot array antenna with a 4-way Butler matrix. All are integrated in one substrate with post-wall waveguide techniques. The planar Butler matrix is realized by using short slot directional couplers (cross coupler). Experiments in 26GHz band confirmed the key operation of this antenna; almost identical four beams are switched to cover the total of horizontal 90-degree sector with equal angular spacing.

One of the difficulties in routing problem is in wirability which is to guarantee a physical connection of a given topological route. Wirability often fails since the width of a wire is relatively large compared with the size of modules. As a possible solution, this paper proposes an incremental wiring algorithm which generates wires net-by-net without overlapping other pre-placed circuit elements. The idea is to divide a wire into a series of rectangles and handles them as modules with additional constraints to keep the shape of the wire. The algorithm was implemented and experimented on a small instance to show its promising performance.

Reconfigurable architectures have been focused for its potential on achieving high performance by reconfiguring special purpose circuits for a target application and its flexibility due to its ability of reconfiguring. We have set our sights on use of a reconfigurable architecture as a general-purpose computer by extending the advantageous properties of the architecture. To achieve the goal, a generalized execution model for reconfigurable architecture is required, so we have proposed an Ideal PARallel Structure (I-PARS) execution model. In the I-PARS execution model, any programs based on its model has no restriction depending on hardware structures based on a specific reconfigurable processor, which makes it easier to develop software. Further, we have proposed a PARS architecture which executes programs based on the I-PARS execution model effectively. The PARS architecture has a large reconfigurable part for highly parallel execution, which utilizes parallelism described on the I-PARS execution model. For effective utilization of the reconfigurable part in the PARS architecture, it has an ability to reconfigure and execute operations simultaneously in one cycle. Further, the PARS architecture supports branch operations to introduce control flow in an execution on the architecture, which makes it possible to skip an execution which does not produce a valid result. In this paper, we introduce the detailed structure of an implemented prototype processor based on the PARS architecture. In the implementation, 420,377 CMOS transistors were used, which was only 3.8% of the number of transistors used in the UltraSPARC-III in logic circuits. Additionally, we evaluated the performance of the prototype processor by using some benchmark programs. From the evaluation results, we found that the prototype processor could achieve nearly the same performance and be implemented with extremely the less number of transistors compared with UltraSPARC-III 750MHz.

GPS receivers are susceptible to jamming by interference. This paper proposes a recurrent neural network (RNN) predictor for new application in GPS anti-jamming systems. Five types of narrowband jammers, i. e. AR process, continuous wave interference (CWI), multi-tone CWI, swept CWI, and pulsed CWI, are considered in order to emulate realistic conditions. As the observation noise of received signals is highly non-Gaussian, an RNN estimator with a nonlinear structure is employed to accurately predict the narrowband signals based on a real-time learning method. The node decoupled extended Kalman filter (NDEKF) algorithm is adopted to achieve better performance in terms of convergence rate and quality of solution while requiring less computation time and memory. We analyze the computational complexity and memory requirements of the NDEKF approach and compare them to the global extended Kalman filter (GEKF) training paradigm. Simulation results show that our proposed scheme achieves a superior performance to conventional linear/nonlinear predictors in terms of SNR improvement and mean squared prediction error (MSPE) while providing inherent protection against a broad class of interference environments.

Existing routing protocols for mobile ad hoc networks assume that all nodes have the same transmission range. In other words, the mobile ad hoc network has symmetric links, which means that two neighboring nodes A and B are within the transmission range of one another. However, since nodes consume battery power independently according to their computing and communication load, there exist asymmetric links, which means that node A is within node B's transmission range, but not vice versa. In this paper, two approaches are presented to support routing in the existence of asymmetric links: GAHA (GPS-based Hop-by-hop Acknowledgment) and GAPA (GPS-based Passive Acknowledgment) schemes. Both GAHA and GAPA can be applied to any routing protocols by utilizing GPS (Global Positioning System) location information. Simulation results reveal that both GAHA and GAPA protocols cope well in the presence of asymmetric wireless links and nodes' mobility.

In the last three decades of the 20th Century, research in speech recognition has been intensively carried out worldwide, spurred on by advances in signal processing, algorithms, architectures, and hardware. Recognition systems have been developed for a wide variety of applications, ranging from small vocabulary keyword recognition over dial-up telephone lines, to medium size vocabulary voice interactive command and control systems for business automation, to large vocabulary speech dictation, spontaneous speech understanding, and limited-domain speech translation. Although we have witnessed many new technological promises, we have also encountered a number of practical limitations that hinder a widespread deployment of applications and services. On one hand, fast progress was observed in statistical speech and language modeling. On the other hand only spotty successes have been reported in applying knowledge sources in acoustics, speech and language science to improving speech recognition performance and robustness to adverse conditions. In this paper we review some key advances in several areas of speech recognition. A bottom-up detection framework is also proposed to facilitate worldwide research collaboration for incorporating technology advances in both statistical modeling and knowledge integration into going beyond the current speech recognition limitations and benefiting the society in the 21st century.

In this paper we consider blind source separation (BSS) problem of signals which are spatially uncorrelated of order four, but temporally correlated of order four (for instance speech or biomedical signals). For such type of signals we propose a new sufficient condition for separation using fourth order statistics, stating that the separation is possible, if the source signals have distinct normalized cumulant functions (depending on time delay). Using this condition we show that the BSS problem can be converted to a symmetric eigenvalue problem of a generalized cumulant matrix Z(4)(b) depending on L-dimensional parameter b, if this matrix has distinct eigenvalues. We prove that the set of parameters b which produce Z(4)(b) with distinct eigenvalues form an open subset of RL, whose complement has a measure zero. We propose a new separating algorithm which uses Jacobi's method for joint diagonalization of cumulant matrices depending on time delay. We empasize the following two features of this algorithm: 1) The optimal number of matrices for joint diago- nalization is 100-150 (established experimentally), which for large dimensional problems is much smaller than those of JADE; 2) It works well even if the signals from the above class are, additionally, white (of order two) with zero kurtosis (as shown by an example).

This paper presents a method of temporal decomposition (TD) for line spectral frequency (LSF) parameters, called "Modified Restricted Temporal Decomposition" (MRTD), and its application to low rate speech coding. The LSF parameters have not been used for TD due to the stability problems in the linear predictive coding (LPC) model. To overcome this deficiency, a refinement process is applied to the event vectors in the proposed TD method to preserve their LSF ordering property. Meanwhile, the restricted second order TD model, where only two adjacent event functions can overlap and all event functions at any time sum up to one, is utilized to reduce the computational cost of TD. In addition, based on the geometric interpretation of TD the MRTD method enforces a new property on the event functions, named the "well-shapedness" property, to model the temporal structure of speech more effectively. This paper also proposes a method for speech coding at rates around 1.2 kbps based on STRAIGHT, a high quality speech analysis-synthesis method, using MRTD. In this speech coding method, MRTD based vector quantization is used for encoding spectral information of speech. Subjective test results indicate that the speech quality of the proposed speech coding method is close to that of the 4.8 kbps FS-1016 CELP coder.