In this paper, performances of two different virtual multiple-input multiple-output (MIMO) transmission schemes — spatial multiplexing (SM) and space-time block coding (STBC) — in a correlated wireless sensor network are analyzed. By utilizing a complex Wishart distribution, we investigate the statistical properties of a correlated virtual MIMO channel between the sensors and data collector that is used in the performance analysis of each MIMO transmission mode. Distributed sensors then transmit their data cooperatively to the data collector by choosing a proper transmission mode adaptively based on the channel conditions and spatial correlation among the sensors. Furthermore, after analyzing the energy efficiencies of SM and STBC, we propose a new energy efficient mode switching rule between SM and STBC. Finally, by analytically deriving the required transmit energy of the proposed adaptive transmission scheme, the manner in which the spatial correlation influences the energy consumption is shown. This suggests a cooperating node scheduling protocol that makes energy consumption less sensitive to the variation of the spatial correlation.

Fused Blocked Pattern Matching is a kind of approximate matching based on Blocked Pattern Matching, and can be used in identification of fused peptides in tumor genomes. In this paper, we propose a new algorithm for fused blocked pattern matching. We give a comparison between Julio's solution and ours, which shows our algorithm is more efficient.

In this paper, a robust cyclic ADC architecture with β-encoder is proposed and circuit scheme using switched-capacitor (SC) circuit is introduced. Different from the conventional binary ADC, the redundancy of proposed cyclic ADC outputs β-expansion code and has an advantage of error correction. This feature makes ADC robust against the offset of comparator capacitor mismatch and finite DC gain of amplifier in multiplying-DAC (MDAC). Because the power penalty of high-gain wideband amplifier and the required accuracy of circuit elements for high resolution ADC can be relaxed, the proposed architecture is suitable for deep submicron CMOS technologies beyond 90 nm. We also propose a β-value estimation algorithm to realize high accuracy ADC based on β-expansion. The simulation results show the effectiveness of proposed architecture and robustness of β-encoder.

Computer-aided detection (CADe) and diagnosis (CAD) has been a rapidly growing, active area of research in medical imaging. Machine leaning (ML) plays an essential role in CAD, because objects such as lesions and organs may not be represented accurately by a simple equation; thus, medical pattern recognition essentially require “learning from examples.” One of the most popular uses of ML is the classification of objects such as lesion candidates into certain classes (e.g., abnormal or normal, and lesions or non-lesions) based on input features (e.g., contrast and area) obtained from segmented lesion candidates. The task of ML is to determine “optimal” boundaries for separating classes in the multi-dimensional feature space which is formed by the input features. ML algorithms for classification include linear discriminant analysis (LDA), quadratic discriminant analysis (QDA), multilayer perceptrons, and support vector machines (SVM). Recently, pixel/voxel-based ML (PML) emerged in medical image processing/analysis, which uses pixel/voxel values in images directly, instead of features calculated from segmented lesions, as input information; thus, feature calculation or segmentation is not required. In this paper, ML techniques used in CAD schemes for detection and diagnosis of lung nodules in thoracic CT and for detection of polyps in CT colonography (CTC) are surveyed and reviewed.

We propose a novel acceleration scheme for Monte Carlo based statistical static timing analysis (MC-SSTA). MC-SSTA, which repeatedly executes ordinary STA using a set of randomly generated gate delay samples, is widely accepted as an accuracy reference. A large number of random samples, however, should be processed to obtain accurate delay distributions, and software implementation of MC-SSTA, therefore, takes an impractically long processing time. In our approach, a generalized hardware module, the STA processing element (STA-PE), is used for the delay evaluation of a logic gate, and netlist-specific information is delivered in the form of instructions from an SRAM. Multiple STA-PEs can be implemented for parallel processing, while a larger netlist can be handled if only a larger SRAM area is available. The proposed scheme is successfully implemented on Altera's Arria II GX EP2AGX125EF35C4 device in which 26 STA-PEs and a 624-port Mersenne Twister-based random number generator run in parallel at a 116 MHz clock rate. A speedup of far more than10 is achieved compared to conventional methods including GPU implementation.

The quadtree-based variable block sized prediction makes the biggest contribution for dramatically improved coding efficiency in the new video coding standard named HEVC. However, this technique takes about 75–80% computational complexity of an HEVC encoder. This paper brings forward an adaptive scheme that exploits temporal, spatial and transform-domain features to speed up the original quadtree-based prediction, targeting at high resolution videos. Before encoding starts, analysis on utilization ratio of each coding depth is performed to skip rarely adopted coding depths at frame level. Then, texture complexity (TC) measurement is applied to filter out none-contributable coding blocks for each largest coding unit (LCU). In this step, a dynamic threshold setting approach is proposed to make filtering adaptable to videos and coding parameters. Thirdly, during encoding process, sum of absolute quantized residual coefficient (SAQC) is used as criterion to prune useless coding blocks for both LCUs and 3232 blocks. By using proposed scheme, motion estimation is performed for prediction blocks within a narrowed range. Experiments show that proposed scheme outperforms existing works and speeds up original HEVC by a factor of up to 61.89% and by an average of 33.65% for 4kx2k video sequences. Meanwhile, the peak signal-to-noise ratio (PSNR) degradation and bit increment are trivial.

We describe 25-Gb/s error-free transmission over multi-mode fiber (MMF) by using a transmitter based on a 1.3-µm lens-integrated surface-emitting laser (LISEL) and a CMOS laser-diode driver (LDD). It demonstrates 25-Gb/s error-free transmission over 30-m MMF under the overfilled-launch condition and over 150-m MMF with a power penalty less than 1.0 dB under the underfilled-launch condition.

Time domain synchronous orthogonal frequency division multiplexing (TDS-OFDM) has higher spectral efficiency than the standard cyclic prefix OFDM (CP-OFDM) OFDM by replacing the random CP with the known training sequence (TS), which could be also used for synchronization and channel estimation. However, TDS-OFDM requires suffers from performance loss over fading channels due to the iterative interference cancellation has to be used to remove the mutual interferences between the TS and the useful data. To solve this problem, the novel TS based OFDM transmission scheme, referred to as the unified time-frequency OFDM (UTF-OFDM), is proposed in which the time-domain TS and the frequency-domain pilots are carefully designed to naturally avoid the interference from the TS to the data without any reconstruction. The proposed UTF-OFDM based flexible frame structure supports effective channel estimation and reliable channel equalization, while imposing a significantly lower complexity than the TDS-OFDM system at the cost of a slightly reduced spectral efficiency. Simulation results demonstrate that the proposed UTF-OFDM substantially outperforms the existing TDS-OFDM, in terms of the system's achievable bit error rate.

This letter proposes an analog active noise control (ANC) circuit with an all-pass filter (APF). To improve performance of the previously reported analog ANC circuit, we inserted an APF to the circuit in order to fit phases of a noise and an electrical signal in the circuit. As a result, we confirmed improvement of the noise canceling effect of the analog ANC circuit.

This paper describes the analysis and design of low-noise analog circuits for a new architecture readout LSI, Qpix. In contrast to conventional readout LSIs using TOT method, Qpix measures deposited charge directly as well as time information. A preamplifier with a two-stage op amp and current-copy output buffers is proposed to realize these functions. This preamplifier is configured to implement a charge sensitive amplifier (CSA) and a trans-impedance amplifier (TIA). Design issues related to CSA are analyzed, which includes gain requirement of the op amp, stability and compensation of the two-stage cascode op amp, noise performance estimation, requirement for the resolution of the ADC and time response. The offset calibration method in the TIA to improve the charge detecting sensitivity is also presented. Also, some design principles for these analog circuits are presented. In order to verify the theoretical analysis, a 400-pixel high speed readout LSI: Qpix v.1 has been designed and fabricated in 180 nm CMOS process. Calculations and SPICE simulations show that the total output noise is about 0.31 mV (rms) at the output of the CSA and the offset voltage is less than 4 mV at the output of the TIA. These are attractive performances for experimental particle detector using Qpix v.1 chip as its readout LSI.

Parametric images can help investigate disease mechanisms and vital functions. To estimate parametric images, it is necessary to obtain the tissue time activity curves (tTACs), which express temporal changes of tracer activity in human tissue. In general, the tTACs are calculated from each voxel's value of the time sequential PET images estimated from dynamic PET data. Recently, spatio-temporal PET reconstruction methods have been proposed in order to take into account the temporal correlation within each tTAC. Such spatio-temporal algorithms are generally quite computationally intensive. On the other hand, typical algorithms such as the preconditioned conjugate gradient (PCG) method still does not provide good accuracy in estimation. To overcome these problems, we propose a new spatio-temporal reconstruction method based on the dynamic row-action maximum-likelihood algorithm (DRAMA). As the original algorithm does, the proposed method takes into account the noise propagation, but it achieves much faster convergence. Performance of the method is evaluated with digital phantom simulations and it is shown that the proposed method requires only a few reconstruction processes, thereby remarkably reducing the computational cost required to estimate the tTACs. The results also show that the tTACs and parametric images from the proposed method have better accuracy.

Our purpose in this study is to develop a scheme to segment the rectus abdominis muscle region in X-ray CT images. We propose a new muscle recognition method based on the shape model. In this method, three steps are included in the segmentation process. The first is to generate a shape model for representing the rectus abdominis muscle. The second is to recognize anatomical feature points corresponding to the origin and insertion of the muscle, and the third is to segment the rectus abdominis muscles using the shape model. We generated the shape model from 20 CT cases and tested the model to recognize the muscle in 10 other CT cases. The average value of the Jaccard similarity coefficient (JSC) between the manually and automatically segmented regions was 0.843. The results suggest the validity of the model-based segmentation for the rectus abdominis muscle.

During the production of speech signals, the vowel onset point is an important event containing important information for many speech processing tasks, such as consonant-vowel unit recognition and speech end-points detection. In order to realize accurate automatic detection of vowel onset points, this paper proposes a reliable method using the energy characteristics of homomorphic filtered spectral peaks. The homomorphic filtering helps to separate the slowly varying vocal tract system characteristics from the rapidly fluctuating excitation characteristics in the cepstral domain. The distinct vocal tract shape related to vowels is obtained and the peaks in the estimated vocal tract spectrum provide accurate and stable information for VOP detection. Performance of the proposed method is compared with the existing method which uses the combination of evidence from the excitation source, spectral peaks, and modulation spectrum energies. The detection rate with different time resolutions, together with the missing rate and spurious rate, are used for comprehensive evaluation of the performance on continuous speech taken from the TIMIT database. The detection accuracy of the proposed method is 74.14% for ±10 ms resolution and it increases to 96.33% for ±40 ms resolution with 3.67% missing error and 4.14% spurious error, much better than the results obtained by the combined approach at each specified time resolution, especially the higher resolutions of ±10±30 ms. In the cases of speech corrupted by white noise, pink noise and f-16 noise, the proposed method also shows significant improvement in the performance compared with the existing method.

Objective: The virtual slides are high-magnification whole digital images of histopathological tissue sections. The existing virtual slide system, which is optimized for scanning flat and smooth plane slides such as histopathological paraffin-embedded tissue sections, but is unsuitable for scanning irregular plane slides such as cytological smear slides. This study aims to develop a virtual slide system suitable for cytopathology slide scanning and to evaluate the effectiveness of multi-focus image fusion (MF) in cytopathological diagnosis. Study Design: We developed a multi-layer virtual slide scanning system with MF technology. Tumors for this study were collected from 21 patients diagnosed with primary breast cancer. After surgical extraction, smear slide for cytopathological diagnosis were manufactured by the conventional stamp method, fine needle aspiration method (FNA), and tissue washing method. The stamp slides were fixed in 95% ethanol. FNA and tissue washing samples were fixed in CytoRich RED Preservative Fluid, a liquid-based cytopathology (LBC). These slides were stained with Papanicolaou stain, and scanned by virtual slide system. To evaluate the suitability of MF technology in cytopathological diagnosis, we compared single focus (SF) virtual slide with MF virtual slide. Cytopathological evaluation was carried out by 5 pathologists and cytotechnologists. Results: The virtual slide system with MF provided better results than the conventional SF virtual slide system with regard to viewing inside cell clusters and image file size. Liquid-based cytology was more suitable than the stamp method for virtual slides with MF. Conclusion: The virtual slide system with MF is a useful technique for the digitization in cytopathology, and this technology could be applied to tele-cytology and e-learning by virtual slide system.

Broadcast encryption scheme with personalized messages (BEPM) is a new primitive that allows a broadcaster to encrypt both a common message and individual messages. BEPM is necessary in applications where individual messages include information related to user's privacy. Recently, Fujii et al. suggested a BEPM that is extended from a public key broadcast encryption (PKBE) scheme by Boneh, Gentry, and Waters. In this paper, we point out that 1) Conditional Access System using Fujii et al.'s BEPM should be revised in a way that decryption algorithm takes as input public key as well, and 2) performance analysis of Fujii et al.'s BEPM should be done depending on whether the public key is transmitted along with ciphertext or stored into user's device. Finally, we propose a new BEPM that is transmission-efficient, while preserving O(1) user storage cost. Our construction is based on a PKBE scheme suggested by Park, Kim, Sung, and Lee, which is also considered as being one of the best PKBE schemes.

For the problem of Indoor Home Scene Classification, this paper proposes the BOW Model of Local Feature Information Gain. The experimental results show that not only the performance is improved but also the computation is reduced. Consequently this method out performs the state-of-the-art approach.

We propose a novel propagation measurement scheme for terrestrial TV signal indoor reception based on a virtual array technique. The system proposed in this paper carries out two-branch recording of target signals and the reference signal. By using the signal phase reference in the reference signal, we clarify the spatial propagation characteristics obtained from the two-dimensional virtual array outputs. Outdoor measurements were performed first to investigate the validity of the proposed measurement system. The results confirm its effectiveness in accurately determining the direction-of-arrival (DOA). We then investigated the propagation characteristics in an indoor environment. The angular spectrum obtained showed clear wave propagation structure. Thus, our proposed system is promising as a very accurate measurement tool for indoor propagation analysis.

We present a new approach for sparse Cholesky factorization on a heterogeneous platform with a graphics processing unit (GPU). The sparse Cholesky factorization is one of the core algorithms of numerous computing applications. We tuned the supernode data structure and used a parallelization method for GPU tasks to increase GPU utilization. Results show that our approach substantially reduces computational time.

We present an optimization algorithm for the design of multilayer antireflection (AR) coatings for organic photovoltaic (OPV) cells. When a set of available materials for the AR films is given, the proposed method allows for searching the globally optimized AR structure that maximizes the short-circuit current density (JSC) under simulated solar light illumination (AM 1.5). By applying this method to an OPV solar cell with a configuration of Al/P3HT:PCBM/MoO3/ITO, we demonstrated that JSC can increase by 7.5% with a 6-layer AR coating, consisting of MgF2, ZnS, and Al2O3. A notable feature of this method is that it can find not only the optimal solution, which maximizes JSC , but also the quasi-optimal solutions, which increase JSC to nearly maximum levels. We showed that the quasi-optimal solution may have higher robustness against deviations in film thicknesses, from their designated values. This method indicates the importance of practically useful, non-optimal solutions for designing AR coatings. The present method allows for extending the user's choices and facilitates the realization of a practical design for an AR coating.

We present a small-area second-order all-digital time-to-digital converter (TDC) with two frequency shift oscillators (FSOs) comprising inverter chains and dynamic flipflops featuring low jitter. The proposed FSOs can maintain their phase states through continuous oscillation, unlike conventional gated ring oscillators (GROs) that are affected by transistor leakage. Our proposed FSOTDC is more robust and is eligible for all-digital TDC architectures in recent leaky processes. Low-jitter dynamic flipflops are adopted as a quantization noise propagator (QNP). A frequency mismatch occurring between the two FSOs can be canceled out using a least mean squares (LMS) filter so that second-order noise shaping is possible. In a standard 65-nm CMOS process, an SNDR of 61 dB is achievable at an input bandwidth of 500 kHz and a sampling rate of 16 MHz, where the respective area and power are 700 µm2 and 281 µW.