In this paper, a spectral domain method named the SDF (Spectral Density Fitting) method for intra-die spatial correlation function extraction is presented. Based on theoretical analysis of random field, the spectral density, as the spectral domain counterpart of correlation function, is employed to estimate the parameters of the correlation function effectively in the spectral domain. Compared with the existing extraction algorithm in the original spatial domain, the SDF method can obtain the same quality of results in the spectral domain. In actual measurement process, the unavoidable measurement error with arbitrary frequency components would greatly confound the extraction results. A filtering technique is further developed to diminish the high frequency components of the measurement error and recover the data from noise contamination for parameter estimation. Experimental results have shown that the SDF method is practical and stable.

A critical problem after a natural/manmade disaster is to provide immediate post-disaster communication links between the disaster victims and some overlay networks. This paper proposes a novel scheme that uses the surviving Mobile handSets (MS) as sensing nodes to form an auto-configured Hierarchical Cognitive Radio Network (H-CRN). The implementation of this H-CRN is explained through detailed problem scenario statement and step-by-step implementation of automatic identification of emergency situation by the MS nodes. An overview of the cross-layer framework used by the MS nodes is also presented. This novel scheme is tested through some hypothesis along with probability calculations for successful identification of emergency situation, formation of ad hoc group and Emergency Beacon Message (EBM) transmission.

This Letter proposes an optimal gain filter for the perceptual acoustic echo suppressor. We designed an optimally-modified log-spectral amplitude estimation algorithm for the gain filter in order to achieve robust suppression of echo and noise. A new parameter including information about interferences (echo and noise) of single-talk duration is statistically analyzed, and then the speech absence probability and the a posteriori SNR are judiciously estimated to determine the optimal solution. The experiments show that the proposed gain filter attains a significantly improved reduction of echo and noise with less speech distortion.

The key issue in cognitive radio is to design a reliable spectrum sensing method that is able to detect the signal in the target channel as well as to recognize its type. In this paper, focusing on classifying different orthogonal frequency-division multiplexing (OFDM) signals, we propose a two-step detection and identification approach based on the analysis of the cyclic autocorrelation function. The key parameters to separate different OFDM signals are the subcarrier spacing and symbol duration. A symmetric peak detection method is adopted in the first step, while a pulse detection method is used to determine the symbol duration. Simulations validate the proposed method.

Two adaptive energy detectors are proposed for cognitive radio systems to detect the primary users. Unlike the conventional energy detector (CED) where a decision is made after receiving all samples, our detectors make a decision with the sequential arrival of samples. Hence, the sample size of the proposed detectors is adaptive. Simulation results show that for a desired performance, the average sample size of the proposed detectors is much less than that of the CED. Therefore, they are more agile than the CED.

To mitigate the asynchronous ICI (Inter-Cell Interference), SCM (Spatial Covariance Matrix) of the asynchronous ICI plus background noise should be accurately estimated for MIMO-OFDMA (Multiple-input Multiple-output-Orthogonal Frequency Division Multiple Access) system. Generally, it is assumed that the SCM of the asynchronous ICI plus background noise is estimated by using training symbols. However, it is difficult to measure the interference statistics for a long time and considering that training symbols are not appropriate for OFDMA system such as LTE (3GPP Long Term Evolution). Therefore, noise reduction method is required to improve the estimation accuracy. Although the conventional time-domain low-pass type weighting method can be effective for noise reduction, it causes significant estimation error due to the spectral leakage in practical OFDM system. Therefore, we propose a time-domain sinc type weighing method which can not only reduce noise effectively minimizing estimation error caused by the spectral leakage but also can be implemented using frequency-domain weighted moving average filter easily. We also consider the iterative CFR (Channel Frequency Response) and SCM estimation method which can effectively reduce the estimation error of both CFR and SCM, and improve the performance for LTE system. By using computer simulation, we show that the proposed method can provide up to 2.5 dB SIR (Signal to Interference Ratio) gain compared with the conventional method, and verify that the proposed method is attractive and suitable for implementation with stable operation.

In spectrum-sharing systems where the secondary user (SU) opportunistically accesses the primary user (PU)'s licensed channel, the SU should satisfy both the transmit power constraint of the SU transmitter and the received power constraint at the PU receiver. This letter studies the ergodic capacity of spectrum-sharing systems in fading channels. The ergodic capacity expression along with the optimal power allocation scheme is derived considering both the average transmit and received power constraints. The capacity function in terms of the two power constraints is found to be divided into transmit power limited region, received power limited region and dual limited region. Numerical results in Rayleigh fading channels are presented to verify our analysis.

Microarray technology has been applied to various biological and medical research fields. A preliminary step to extract any information from a microarray data set is to identify differentially expressed genes between microarray data. The identification of the differentially expressed genes and their commonly associated GO terms allows us to find stimulation-dependent or disease-related genes and biological events, etc. However, the identification of these deregulated GO terms by general approaches including gene set enrichment analysis (GSEA) does not necessarily provide us with overrepresented GO terms in specific data among a microarray data set (i.e., data-specific GO terms). In this paper, we propose a statistical method to correctly identify the data-specific GO terms, and estimate its availability by simulation using an actual microarray data set.

Biologically-inspired approaches are one of the most promising approaches to realize highly-adaptive distributed systems. Biological systems inherently have self-* properties, such as self-stabilization, self-adaptation, self-configuration, self-optimization and self-healing. Thus, the application of biological systems into distributed systems has attracted a lot of attention recently. In this paper, we present one successful result of bio-inspired approach: we propose distributed algorithms for resource replication inspired by the single species population model. Resource replication is a crucial technique for improving system performance of distributed applications with shared resources. In systems using resource replication, generally, a larger number of replicas lead to shorter time to reach a replica of a requested resource but consume more storage of the hosts. Therefore, it is indispensable to adjust the number of replicas appropriately for the resource sharing application. This paper considers the problem for controlling the densities of replicas adaptively in dynamic networks and proposes two bio-inspired distributed algorithms for the problem. In the first algorithm, we try to control the replica density for a single resource. However, in a system where multiple resources coexist, the algorithm needs high network cost and the exact knowledge at each node about all resources in the network. In the second algorithm, the densities of all resources are controlled by the single algorithm without high network cost and the exact knowledge about all resources. This paper shows by simulations that these two algorithms realize self-adaptation of the replica density in dynamic networks.

This paper compares the expressive power of five language-based access control models. We show that the expressive powers are incomparable between any pair of history-based access control, regular stack inspection and shallow history automata. Based on these results, we introduce an extension of HBAC, of which expressive power exceeds that of regular stack inspection.

In the OTS/CafeOBJ method, software specifications are described in CafeOBJ executable formal specification language, and verification is done by giving scripts to the CafeOBJ system. The script is called a proof score. In this study, we propose a test case generator from an OTS/CafeOBJ specification together with a proof score. Our test case generator gives test cases by analyzing the proof score. The test cases are used to test whether an implementation satisfies the specification and the property verified by the proof score. Since a proof score involves important information for verifying a property, the generated test cases are also expected to be suitable to test the property.

This paper proposes spread-spectrum clock modulation algorithms for EMI reduction in digitally-controlled DC-DC converters. In switching regulators using PWM, switching noise and harmonic noise concentrated in a narrow spectrum around the switching frequency can cause severe EMI. Spread-spectrum clock modulation can be used to minimize EMI. In conventional switching regulators using analog control it is very difficult to realize complex spread-spectrum clocking, however this paper shows that it is relatively easy to implement spread-spectrum EMI-reduction using digital control. The proposed algorithm was verified using a power converter simulator (SCAT).

A prototype of a three-axis electro-optic (EO) probe is developed that has the linearity of approximately 0.5 dB in the specific absorption rate (SAR) range of 0.01 to 100 W/kg and the directivities are eight-shaped with cross-axis sensitivity isolation of greater than 30 dB. It is confirmed that electric fields and SAR distributions can be measured using a three-axis EO probe.

This letter proposes a high precision ranging scheme based on the time of arrival estimation technique for the IEEE 802.15.4a chirp spread spectrum system. The proposed scheme consists of a linear channel impulse response estimation process with the zero forcing or minimum mean square error technique and the multipath delay estimation process with matrix pencil algorithm. The performance of the proposed scheme is compared with that of a well known MUSIC algorithm in terms of computational complexity and ranging precision. Simulation results demonstrate that the proposed scheme outperforms the MUSIC algorithm even though it has comparatively lower computational complexity.

Slit-Mura defect is a notorious yield flaw of color filters. In this study, an innovative non-contact in-line optical inspection method is developed to detect low contrast slit Mura through quantitative measurements by a spectrometer. Using the features of either thickness or chromaticity profiles across a slit Mura, a thickness difference from 21 nm to 41 nm of color filters can be differentiated accurately. Thus, the quality of color filters can be accessed in-line during the manufacturing process TFT-LCDs.

Two discrete-time Wirtinger-type inequalities relating the power of a finite-length signal to that of its circularly-convolved version are developed. The usual boundary conditions that accompany the existing Wirtinger-type inequalities are relaxed in the proposed inequalities and the equalizing sinusoidal signal is free to have an arbitrary phase angle. A measure of this sinusoidal signal's power, when corrupted with additive noise, is proposed. The application of the proposed measure, calculated as a ratio, in the evaluation of the power of a sinusoid of arbitrary phase with the angular frequency π/N, where N is the signal length, is thoroughly studied and analyzed under additive noise of arbitrary statistical characteristic. The ratio can be used to gauge the power of sinusoids of frequency π/N with a small amount of computation by referring to a ratio-versus-SNR curve and using it to make an estimation of the noise-corrupted sinusoid's SNR. The case of additive white noise is also analyzed. A sample permutation scheme followed by sign modulation is proposed for enlarging the class of target sinusoids to those with frequencies M π/N, where M and N are mutually prime positive integers. Tandem application of the proposed scheme and ratio offers a simple method to gauge the power of sinusoids buried in noise. The generalization of the inequalities to convolution kernels of higher orders as well as the simplification of the proposed inequalities have also been studied.

High-Tc superconducting quantum interference device (SQUID) is an ultra-sensitive magnetic sensor. After the discovery of the high-Tc superconducting materials, the performance of the high-Tc SQUID has been improved and stabilized. One strong candidate for application is a detection system of magnetic foreign matters in industrial products. There is a possibility that ultra-small metallic foreign matter has been accidentally mixed with industrial products such as lithium ion batteries. If this happens, the manufacturer of the product suffers a great loss recalling products. The outer dimension of metallic particles less than 100 micron cannot be detected using X-ray imaging, which is commonly used for the inspection. Therefore a highly sensitive system for small foreign matters is required. We developed detection systems based on high-Tc SQUID for industrial products. We could successfully detect small iron particles of less than 50 micron on a belt conveyer. These detection levels were hard to be achieved using conventional X-ray detection or other methods.

With the rapid progress of electronic and information technology, an expectation for the realization of body area network (BAN) by means of ultra wide band (UWB) techniques has risen. Although the signal from a single UWB device is very low, the energy absorption may increase significantly when many UWB devices are simultaneously adorned to a human body. An analysis method is therefore required from the point of view of biological safety evaluation. In this study, two approaches, one is in the time domain and the other is in the frequency domain, are proposed for the specific energy absorption (SA) and the specific absorption rate (SAR) calculation. It is shown that the two approaches have the same accuracy but the time-domain approach is more straightforward in the numerical analysis. By using the time-domain approach, SA and SAR calculation results are given for multiple UWB pulse exposure to an anatomical human body model under the Federal Communications Commission (FCC) UWB limit.

We propose a new filter method for feature selection for SELDI-TOF mass spectrum datasets. In the method, a new relevance index was defined to represent the goodness of a feature by considering the distribution of samples based on the counts. The relevance index can be used to obtain the feature sets for classification. Our method can be applied to mass spectrum datasets with extremely high dimensions and process the clinical datasets with practical sizes in acceptable calculation time since it is based on simple counting of samples. The new method was applied to the three public mass spectrum datasets and showed better or comparable results than conventional filter methods.

The body area network (BAN) has attracted attention because of its potential for high-grade wireless communication technology and its safety and high durability. Also, human area transmission of a BAN propagating at an ultra-wide band (UWB) has been demonstrated recently. When considering the efficiency of electromagnetic (EM) propagation inside the human body for BAN and hyperthermia treatment using RF, it is important to determine the mechanism of EM dissipation in the human body. A body heating system for hyperthermia must deposit EM energy deep inside the body. Also, it is important that the EM field generated by the implant system is sufficiently strong. In this study, the specific absorption rate (SAR) distribution is simulated using an EM simulator to consider the biological transmission mechanism and its effects. To utilize the EM field distribution using an implant system for hyperthermia treatment, the SAR distribution inside the human body is simulated. As a result, the SAR distribution is concentrated on the surface of human tissue, the muscle-bolus interface, the pancreas, the stomach, the spleen and the regions around bones. It can also be concentrated in bone marrow and cartilage. From these results, the appropriate location for the implant system is revealed on the basis of the current distribution and differences in the wave impedance of interfacing tissues. The possibility of accurate data transmission and suitable treatment planning is confirmed.