Faced with social problems such as rapidly aging society, the solutions have been expected in sports medicine. Humans became widely distributed on the earth from their birth by acquiring abilities to walk in an upright position and to adapt themselves to various natural environments. However, seeking a ‘comfortable environment’ in modern civilization has deteriorated these genetic characteristics of humans, and the consumption of resources and energy to acquire such a ‘comfortable environment’ has induced global warming-associated natural disasters and the destruction of social order. To halt this vicious cycle, we may reactivate the genetic characteristics in humans by doing exercise. To do this, we have developed a health promotion program for middle aged and older people, Jukunen Taiikudaigaku Program, in cooperation with the Japanese government, developed high-intensity interval walking training (IWT), and examined the physical and mental effects on 5,400 people for these 10 years. We found that IWT for 4 months increased physical fitness by 10-20%, decreased the indices of life-style related diseases by 10-20%. Since a prescription of IWT can be conducted by using an IT network system called e-Health Promotion System, the participants in the program were able to receive the prescription even if they lived remote from trainers, enabling them to perform IWT at their favored places and times, and also at low cost. Moreover, we found some single nucleotide polymorphisms closely related to inter-individual differences in the responses to IWT. Further, the system enables us to assess the inactivation/activation of genes for inflammatory responses which has been suggested to be involved in life-style related diseases. Also, the system enables us to search foods to promote health when they are consumed during exercise training. Thus, the system would have strong potential to promote health of middle-aged and older people in advanced aging society.

A reduction in the intensity deviation of a nine-channel optical frequency comb block (OFCB) is demonstrated, by adopting an asymmetric differential drive method for an InP-based dual drive Mach-Zehnder modulator. The generation of a tailored OFCB with an intensity deviation of less than 0.8dB is confirmed by using the modulator.

In this paper, we clarify the relationship between an initial (final) state in a tail-biting error-trellis and the obtained syndromes. We show that a final state is dependent on the first M syndromes as well, where M is the memory length of the parity-check matrix. Next, we calculate the probability of an initial (final) state conditioned by the syndromes. We also apply this method to concrete examples. It is shown that the initial (final) state in a tail-biting error-trellis is well estimated using these conditional probabilities.

Tracking capsule endoscope location is one of the promising applications offered by implant body area networks (BANs). When tracking the capsule endoscope location, i.e., continuously localize it, it is effective to take the weighted sum of its past locations to its present location, in other words, to low-pass filter its past locations. Furthermore, creating an exact mathematical model of location transition will improve tracking performance. Therefore, in this paper, we investigate two tracking methods with received signal strength indicator (RSSI)-based localization in order to solve the capsule endoscope location tracking problem. One of the two tracking methods is finite impulse response (FIR) filter-based tracking, which tracks the capsule endoscope location by averaging its past locations. The other one is particle filter-based tracking in order to deal with a nonlinear transition model on the capsule endoscope. However, the particle filter requires that the particle weight is calculated according to its condition (namely, its likelihood value), while the transition model on capsule endoscope location has some model parameters which cannot be estimated from the received wireless signal. Therefore, for the purpose of applying the particle filter to capsule endoscope tracking, this paper makes some modifications in the resampling step of the particle filter algorithm. Our computer simulation results demonstrate that the two tracking methods can improve the performance as compared with the conventional maximum likelihood (ML) localization. Furthermore, we confirm that the particle filter-based tracking outperforms the conventional FIR filter-based tracking by taking the realistic capsule endoscope transition model into consideration.

Attenuated and delayed versions of the pulse signal overlap in multipath propagation. Previous algorithms can resolve them only if signal sampling is ideal, but fail to resolve two counterparts with non-ideal sampling. In this paper, we propose a novel method which can resolve the general types of non-ideally sampled pulse signals in the time domain via Taylor Series Expansion (TSE) and estimate multipath signals' precise time delays and amplitudes. In combination with the CLEAN algorithm, the overlapped pulse signal parameters are estimated one by one through an iteration method. Simulation results verify the effectiveness of the proposed method.

We propose an improved design of a neuron circuit, using coupled SQUIDs gates, for a superconducting neural network. An activation function with step-like input vs. output characteristics is desirable for a neuron circuit to solve a combinatorial optimization problem. The proposed neuron circuit is composed of two coupled SQUIDs gates with a cascade connection, in order to obtain such characteristics. The designed neuron circuit is fabricated by a 2.5kA/cm2 Nb/AlOx/Nb process. The operation of a fabricated neuron circuit is experimentally demonstrated. Network performance of a neural network using proposed neuron circuits is also estimated by numerical dynamic simulations.

By the motivation to discover patterns in massive structured data in the form of graphs and trees, we study a special case of the k-subtree enumeration problem with a tree of n nodes as an input graph, which is originally introduced by (Ferreira, Grossi, and Rizzi, ESA'11, 275-286, 2011) for general graphs. Based on reverse search technique (Avis and Fukuda, Discrete Appl. Math., vol.65, pp.21-46, 1996), we present the first constant delay enumeration algorithm that lists all k-subtrees of an input rooted tree in O(1) worst-case time per subtree. This result improves on the straightforward application of Ferreira et al.'s algorithm with O(k) amortized time per subtree when an input is restricted to tree. Finally, we discuss an application of our algorithm to a modification of the graph motif problem for trees.

In recent VLSIs, small-delay defects, which are hard to detect by traditional delay fault testing, can bring about serious issues such as short lifetime. To detect small-delay defects, on-chip delay measurement which measures the delay time of paths in the circuit under test (CUT) was proposed. However, this approach incurs high test cost because it uses scan design, which brings about long test application time due to scan shift operation. Our solution is a test application time reduction method for testing using the on-chip path delay measurement. The testing with on-chip path delay measurement does not require capture operations, unlike the conventional delay testing. Specifically, FFs keep the transition pattern of the test pattern pair sensitizing a path under measurement (PUM) (denoted as p) even after the measurement of p. The proposed method uses this characteristic. The proposed method reduces scan shift time and test data volume using test pattern merging. Evaluation results on ISCAS89 benchmark circuits indicate that the proposed method reduces the test application time by 6.89∼62.67% and test data volume by 46.39∼74.86%.

In this paper, we propose a novel confidence measure to improve the performance of spoken term detection (STD). The proposed confidence measure is based on the context consistency between a hypothesized word and its context in a word lattice. The main contribution of this paper is to compute the context consistency by considering the uncertainty in the results of speech recognition and the effect of topic. To measure the uncertainty of the context, we employ the word occurrence probability, which is obtained through combining the overlapping hypotheses in a word posterior lattice. To handle the effect of topic, we propose a method of topic adaptation. The adaptation method firstly classifies the spoken document according to the topics and then computes the context consistency of the hypothesized word with the topic-specific measure of semantic similarity. Additionally, we apply the topic-specific measure of semantic similarity by two means, and they are performed respectively with the information of the top-1 topic and the mixture of all topics according to topic classification. The experiments conducted on the Hub-4NE Mandarin database show that both the occurrence probability of context word and the topic adaptation are effective for the confidence measure of STD. The proposed confidence measure performs better compared with the one ignoring the uncertainty of the context or the one using a non-topic method.

For battery based real-time embedded systems, high performance to meet their real-time constraints and energy efficiency to extend battery life are both essential. Real-Time Dynamic Voltage Scaling (RT-DVS) has been a key technique to satisfy both requirements. This paper presents EccEDF (Enhanced ccEDF), an efficient algorithm based on ccEDF. ccEDF is one of the most simple but efficient RT-DVS algorithms. Its simple structure enables it to be easily and intuitively coupled with a real-time operating system without incurring any significant cost. ccEDF, however, overlooks an important factor in calculating the available slacks for reducing the operating frequency. It calculates the saved utilization simply by dividing the slack by the period without considering the time needed to run the task. If the elapsed time is considered, the maximum utilization saved by the slack on completion of the task can be found. The proposed EccEDF can precisely calculate the maximum unused utilization with consideration of the elapsed time while keeping the structural simplicity of ccEDF. Further, we analytically establish the feasibility of EccEDF using the fluid scheduling model. Our simulation results show that the proposed algorithm outperforms ccEDF in all simulations. A simulation shows that EccEDF consumes 27% less energy than ccEDF.

In this paper, we design an efficient P2P based mobile social network to facilitate contents search over mobile ad hoc networks. Social relation is established by considering both the locations and interests of mobile nodes. Mobile nodes with common interests and nearby locations are recommended as friends and are connected directly in a mobile social network. Contents search is handled by using social relationships of the mobile social network rather than those of the whole network. Since each mobile node manages only neighboring nodes that have common interests, network management overhead is reduced. Results of experiments have shown that our proposed method outperforms existing methods.

This letter presents three methods for producing 8-QAM+ sequences. The first method transforms a ternary complementary sequence set (CSS) with even number of sub-sequences into an 8-QAM+ periodic CSS with both of the period and the number of sub-sequences unaltered. The second method results in an 8-QAM+ aperiodic CSS with confining neither the period nor the number of sub-sequences. The third method produces 8-QAM+ periodic sequences having ideal autocorrelation property on the real part of the autocorrelation function. The proposed sequences can be potentially applied to suppression of multiple access interference or synchronization in a communication system.

In this paper, we present an average-case efficient algorithm to resolve the problem of determining whether two Boolean functions in trace representation are identical. Firstly, we introduce a necessary and sufficient condition for null Boolean functions in trace representation, which can be viewed as a generalization of the well-known additive Hilbert-90 theorem. Based on this condition, we propose an algorithmic method with preprocessing to address the original problem. The worst-case complexity of the algorithm is still exponential; its average-case performance, however, can be improved. We prove that the expected complexity of the refined procedure is O(n), if the coefficients of input functions are chosen i.i.d. according to the uniform distribution over F2n; therefore, it performs well in practice.

Biometric identification has recently attracted attention because of its convenience: it does not require a user ID nor a smart card. However, both the identification error rate and response time increase as the number of enrollees increases. In this paper, we combine a score level fusion scheme and a metric space indexing scheme to improve the accuracy and response time in biometric identification, using only scores as information sources. We firstly propose a score level indexing and fusion framework which can be constructed from the following three schemes: (I) a pseudo-score based indexing scheme, (II) a multi-biometric search scheme, and (III) a score level fusion scheme which handles missing scores. A multi-biometric search scheme can be newly obtained by applying a pseudo-score based indexing scheme to multi-biometric identification. We secondly propose the NBS (Naive Bayes search) scheme as a multi-biometric search scheme and discuss its optimality with respect to the retrieval error rate. We evaluated our proposal using the datasets of multiple fingerprints and face scores from multiple matchers. The results showed that our proposal significantly improved the accuracy of the unimodal biometrics while reducing the average number of score computations in both the datasets.

In order to analyze an impact of threshold voltage (Vth) fluctuation induced by random telegraph noise (RTN) on LSI circuit design, we measured a 40-nm 6-Tr-SRAM TEG which enables to evaluate individual bit-line current. RTN phenomenon was successfully measured and we also identified that the transfer MOSFET in an SRAM bit-cell was the most sensitive MOSFET. The proposed word line boosting technique, which applies slightly extra stress to the transfer MOSFET, improves about 30% of detecting probability of fail-bit cells caused by RTN.

The estimation of the power spectral density (PSD) of noise is crucial for retrieving speech in noisy environments. In this study, we propose a novel method for estimating the non-white noise PSD from noisy speech on the basis of a generalized gamma distribution and the minimum mean square error (MMSE) approach. Because of the highly non-stationary nature of speech, deriving its actual spectral probability density function (PDF) using conventional modeling techniques is difficult. On the other hand, spectral components of noise are more stationary than those of speech and can be represented more accurately by a generalized gamma PDF. The generalized gamma PDF can be adapted to optimally match the actual distribution of the noise spectral amplitudes observed at each frequency bin utilizing two real-time updated parameters, which are calculated in each frame based on the moment matching method. The MMSE noise PSD estimator is derived on the basis of the generalized gamma PDF and Gaussian PDF models for noise and speech spectral amplitudes, respectively. Combined with an improved Weiner filter, the proposed noise PSD estimate method exhibits the best performance compared with the minimum statistics, weighted noise estimation, and MMSE-based noise PSD estimation methods in terms of both subjective and objective measures.

This paper presents an analysis of radiation-induced clock-perturbation in phase-locked loop (PLL). Due to a trade-off between cost, performance, and reliability, radiation hardened PLL design need robust strategy. Thus, evaluation of radiation vulnerability is important to choose the robust strategy. The conventional evaluation-method is however based on brute-force analysis — SPICE simulation and experiment. The presented analysis result eliminates the brute-force analysis in evaluation of the radiation vulnerability. A set of equations enables to predict the radiation-induced clock-perturbation at the every sub-circuits. From a demonstration, the most vulnerable nodes have been found, which are validated using a PLL fabricated with 0.18µm CMOS process.

Hardware Trojan (HT) has emerged as an impending security threat to hardware systems. However, conventional functional tests fail to detect HT since Trojans are triggered by rare events. Most of the existing side-channel based HT detection techniques just simply compare and analyze circuit's parameters and offer no signal calibration or error correction properties, so they suffer from the challenge and interference of large process variations (PV) and noises in modern nanotechnology which can completely mask Trojan's contribution to the circuit. This paper presents a novel HT detection method based on subspace technique which can detect tiny HT characteristics under large PV and noises. First, we formulate the HT detection problem as a weak signal detection problem, and then we model it as a feature extraction model. After that, we propose a novel subspace HT detection technique based on time domain constrained estimator. It is proved that we can distinguish the weak HT from variations and noises through particular subspace projections and reconstructed clean signal analysis. The reconstructed clean signal of the proposed algorithm can also be used for accurate parameter estimation of circuits, e.g. power estimation. The proposed technique is a general method for related HT detection schemes to eliminate noises and PV. Both simulations on benchmarks and hardware implementation validations on FPGA boards show the effectiveness and high sensitivity of the new HT detection technique.

Gait-based owner authentication using accelerometers has recently been extensively studied owing to the development of wearable electronic devices. An actual gait signal is always subject to change due to many factors including variation of sensor attachment. In this research, we tackle to the practical sensor-orientation inconsistency, for which signal sequences are captured at different sensor orientations. We present an iterative signal matching algorithm based on phase-registration technique to simultaneously estimate relative sensor-orientation and register the 3D acceleration signals. The iterative framework is initialized by using 1D orientation-invariant resultant signals which are computed from 3D signals. As a result, the matching algorithm is robust to any initial sensor-orientation. This matching algorithm is used to match a probe and a gallery signals in the proposed owner authentication method. Experiments using actual gait signals under various conditions such as different days, sensors, weights being carried, and sensor orientations show that our authentication method achieves positive results.

Traditionally, in computer systems, file I/O has been a big performance bottleneck for I/O intensive applications. The recent advent of non-volatile byte-addressable memory (NVM) technologies such as STT-MRAM and PCM, provides a chance to store persistent data with a high performance close to DRAM's. However, as the location of the persistent storage device gets closer to the CPU, the system software layers overheads for accessing the data such as file system layer including virtual file system layer and device driver are no longer negligible. In this paper, we propose a light-weight user-level persistent storage, called UStore, which is physically allocated on the NVM and is mapped directly into the virtual address space of an application. UStore makes it possible for the application to fast access the persistent data without the system software overheads and extra data copy between the user space and kernel space. We show how UStore is easily applied to existing applications with little elaboration and evaluate its performance enhancement through several benchmark tests.