From lessons learned in medical data mining projects we show that integration of advanced computation techniques and human inspection is indispensable in medical data mining. We proposed an integrated approach that merges data mining and text mining methods plus visualization support for expert evaluation. We also appropriately developed temporal abstraction and text mining methods to exploit the collected data. Furthermore, our visual discovery system D2MS allowed to actively and effectively working with physicians. Significant findings in hepatitis study were obtained by the integrated approach.

We design M(≥3)-phase spreading sequences of Markov chains optimal in terms of bit error probabilities in asynchronous SSMA (spread spectrum multiple access) communication systems. To this end, we obtain the distributions of the normalized MAI (multiple access interference) for such systems and find a necessary and sufficient condition that the distributions become independent of the phase shifts.

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.

This paper presents an investigation of radio-wave propagation characteristics in the 5 GHz band in a residential two-story house. We investigated the 3-D angular spectra of incident waves when a transmitter and a receiver were situated on the first and second floors, respectively. First of all, correlation in the measured "home environment" containing furniture such as beds, a sofa and tables was determined to confirm a quasi-static environment. Then, 3-D angular spectra measurements were performed by using an eight-element Yagi-Uda antenna as a receiving antenna. Furthermore, the 4-by-4 MIMO channel capacity at each elevation angle was estimated by using elevation angular spectra and the propagation characteristics between the first and second floors were evaluated. The results indicated that the channel capacity in the elevation direction was strongly influenced by the direction of the transmitting antenna.

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.

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 speech enhancement method is proposed that can be implemented efficiently due to its use of wavelet packet transform. The proposed method uses a modified spectral subtraction with noise estimation by a least-squares line method and with an overweighting gain per subband with nonlinear structure, where the overweighting gain is used for suppressing the residue of musical noise and the subband is used for applying the weighted values according to the change of signals. The enhanced speech by our method has the following properties: 1) the speech intelligibility can be assured reliably; 2) the musical noise can be reduced efficiently. Various assessments confirmed that the performance of the proposed method was better than that of the compared methods in various noise-level conditions. Especially, the proposed method showed good results even at low SNR.

Digital hearing aid users often complain of difficulty in understanding speech in the presence of background noise. To improve speech perception in a noisy environment, various speech enhancement algorithms have been applied in digital hearing aids. In this study, a speech enhancement algorithm using modified spectral subtraction and companding is proposed for digital hearing aids. We adjusted the biases of the estimated noise spectrum, based on a subtraction factor, to decrease the residual noise. Companding was applied to the channel of the formant frequency based on the speech presence indicator to enhance the formant. Noise suppression was achieved while retaining weak speech components and avoiding the residual noise phenomena. Objective and subjective evaluation under various environmental conditions confirmed the improvement due to the proposed algorithm. We tested segmental SNR and Log Likelihood Ratio (LLR), which have higher correlation with subjective measures. Segmental SNR has the highest and LLR the lowest correlation of the methods tested. In addition, we confirmed by spectrogram that the proposed method significantly reduced the residual noise and enhanced the formants. A mean opinion score that represented the global perception score was tested; this produced the highest quality speech using the proposed method. The results show that the proposed speech enhancement algorithm is beneficial for hearing aid users in noisy environments.

In this paper, a novel speech enhancement algorithm based on the MAP estimation is proposed. The proposed speech enhancer adaptively changes the speech spectral density used in the MAP estimation according to the sum of the observed power spectra. In a speech segment, the speech spectral density approaches to Rayleigh distribution to keep the quality of the enhanced speech. While in a non-speech segment, it approaches to an exponential distribution to reduce noise effectively. Furthermore, when the noise is super-Gaussian, we modify the width of Gaussian so that the Gaussian model with the modified width approximates the distribution of the super-Gaussian noise. This technique is effective in suppressing residual noise well. From computer experiments, we confirm the effectiveness of the proposed method.

This paper presents a novel feature extraction algorithm based on particle swarms for processing hyperspectral imagery data. Particle swarm optimization, originally developed for global optimization over continuous spaces, is extended to deal with the problem of feature extraction. A formulation utilizing two swarms of particles was developed to optimize simultaneously a desired performance criterion and the number of selected features. Candidate feature sets were evaluated on a regression problem. Artificial neural networks were trained to construct linear and nonlinear models of chemical concentration of glucose in soybean crops. Experimental results utilizing real-world hyperspectral datasets demonstrate the viability of the method. The particle swarms-based approach presented superior performance in comparison with conventional feature extraction methods, on both linear and nonlinear models.

The present paper describes a quality enhancement of speech corrupted by additive background noise in a single channel system. The proposed approach is based on the introduction of perceptual criteria using a frequency-weighting filter in a subtractive-type enhancement process. This newly developed algorithm allows for an automatic adaptation in the time and frequency of the enhancement system and finds a suitable noise estimate according to the frequency of the corrupted speech. Experimental results show that the proposed approach can efficiently remove additive noise related to various types of noise corruption.

Acoustic field analysis results of surface acoustic wave dispersive delay lines using inclined chirp IDTs on a Y-Z LiNbO3 substrate are described. The calculated results are compared with optical measurements. The angular spectrum of the plane wave method is applied to calculation of the acoustic fields considering the anisotropy of the SAW velocity by using the polynomial approximation. Acoustic field propagating along the Z-axis of the substrate, which is the main beam excited by the inclined chirp IDT, shows asymmetric distribution between the +Z and -Z directions. Furthermore the SAW beam propagating in a slanted direction with an angle of +18 from the Z axis to the X-axis is observed. It is described that the SAW beam propagating in a slanted direction is the first side lobe excited by the inclined chirp IDT. The acoustic field shows asymmetric distribution along the X-axis because of the asymmetric structure of the inclined chirp IDT. Finally, acoustic field of a two-IDT connected structure which consists of the same IDTs electrically connected in series is presented. The acoustic field of the two-IDT connected structure is calculated to be superposed onto the calculated result of the acoustic field exited by one IDT on the calculated result shifted along the X-axis. Two SAW beams excited by IDTs are observed. The distributions of the SAW beams are not in parallel. The calculated results show good agreement with the optical measurement results.

This paper presents a design method for AND-OR-EXOR three-level networks, where a single two-input exclusive-OR (EXOR) gate is used. The network realizes an EXOR of two sum-of-products expressions (EX-SOPs). The problem is to minimize the total number of products in the two sum-of-products expressions (SOPs). We introduce the notion of µ-equivalence of logic functions to develop exact minimization algorithms for EX-SOPs with up to five variables. We minimized all the NP-representative functions for up to five variables and showed that five-variable functions require 9 or fewer products in minimum EX-SOPs. For n-variable functions, minimum EX-SOPs require at most 9·2n-5 (n ≤ 6) products. This upper bound is smaller than 2n-1, which is the upper bound for SOPs. We also found that, for five-variable functions, on the average, minimum EX-SOPs require about 40% fewer literals than minimum SOPs.

This paper proposes an event-based transition system called A-LTS. An A-LTS is a simple system consisting of two agents, a basic program and a monitor. The monitor observes the behavior of the basic program and if the behavior matches some pre-defined pattern, then the monitor interrupts the execution of the basic program and possibly triggers the execution of another specific program. An A-LTS models a common feature found in recent software technologies such as Aspect-Oriented Programming (AOP), history-based access control and active database. We investigate the expressive power of A-LTS and show that it is strictly stronger than finite state machines and strictly weaker than pushdown automata (PDA). This implies that the model checking problem for A-LTS is decidable. It is also shown that the expressive power of A-LTS, linear context-free grammar and deterministic PDA are mutually incomparable. We also discuss the relationship between A-LTS and pointcut/advice in AOP.

This paper investigates the dynamic spectrum management problem for digital subscriber lines. Two new distributed dynamic spectrum management algorithms, which improve upon the existing iterative water-filling algorithm, are proposed. Unlike the iterative water-filling algorithm, in which crosstalk interference is reduced by using adaptive power backoff, the new algorithms employ full power and mitigate crosstalk interference by shifting one user's spectrum away from the other's. Simulation results show that the new algorithms achieve significant performance gains over the iterative water-filling algorithm in mixed central office/remote terminal (CO/RT) deployment asymmetric digital subscriber line (ADSL) and upstream very-high bit-rate digital subscriber line (VDSL).

Time-of-Flight Mass Spectroscopy (TOF-MS) with superconducting detectors has two advantages over MS with conventional ion detectors. First, it is coverage for a very wide range of molecule weight over 1,000,000. Secondly, kinetic energies of accelerated molecules can be measured at impact events one by one. These unique features enable an ultimate detection efficiency of 100% for intact ions and a fragmentation analysis that is critical for top-down proteomics. Superconducting MS is expected to play a role in, for example, the detection of antigen-antibody complexes, which are important for medical diagnosis. In this paper, how superconductivity contributes to MS is described.

Digital watermarking is a technique that aims at hiding a message signal in a multimedia signal for copyright claim, authentication, device control, or broadcast monitoring, etc. In this paper, we focus on embedding watermarks into still images, where the watermarks themselves can be binary sequences or grayscale images. We propose to scramble the watermark bits with pseudo-noise (PN) or orthogonal codes before they are embedded into an image. We also try to incorporate error correction coding (ECC) into the watermarking scheme, anticipating reduction of the watermark bit error rate (WBER). Due to the similarity between the PN/orthogonal-coded watermarking and the spread spectrum communication, it is natural that, following similar derivations regarding data BER in digital communications, we derive certain explicit quantitative relationships regarding the tradeoff between the WBER, the watermark capacity (i.e. the number of watermark bits) and the distortion suffered by the original image, which is measured in terms of the embedded image's signal-to-noise ratio (abbreviated as ISNR). These quantitative relationships are compactly summarized into a so-called tradeoff triangle, which constitutes the major contribution of this paper. For the embedding of grayscale watermarks, an unequal error protection (UEP) scheme is proposed to provide different degrees of robustness for watermark bits of different degrees of significance. In this UEP scheme, optimal strength factors for embedding different watermark bits are sought so that the mean squared error suffered by the extracted watermark, which is by itself a grayscale image, is minimized while a specified ISNR is maintained.

A highly accurate measurement method of parameters of MZ-type LN optical intensity modulators is presented. In this method, a CW optical signal is input to an optical terminal and small CW RF signal is applied to an electrode of the modulator. Then sideband levels of an output optical signal at different bias points are measured by using optical spectrum analyzer. By using 1st order sideband levels which are measured at two different bias conditions, and using a compensation method to measured levels, we can obtain accurate chirp parameter even when very small power of RF signal is applied to the modulator. In this method, the chirp parameter can be obtained in good accuracy when the input RF voltage is only 3% of the halfwave voltage.

A major step in the numerical solution of electromagnetic scattering problems involves the computation of the convolution based reaction integrals. In this paper a procedure based on the analytical Fourier transform is introduced which allows us to calculate the convolution-based reaction integrals in the spectral domain without evaluating any convolution products directly. A numerical evaluation of the computational cost is presented to show the efficiency of the method when handling electrically large problems.

The extended version of spectral domain approach (ESDA) is applied to evaluate the scattering characteristics of discontinuities in coaxial line. Discontinuities may be in inner and/or outer conductor of coaxial line. This method secures the high accuracy by considering the singularities of fields near the conductor edge properly. The computational labor of the new method is far lighter than that of FEM, so that novel method is suitable for the time consuming iterative computation such as fitting procedure in material evaluation or optimization of antenna design.