In this paper, we propose a method to estimate the most resource-consuming disease from electronic claim data based on Labeled Latent Dirichlet Allocation (Labeled LDA). The proposed method models each electronic claim from its medical procedures as a mixture of resource-consuming diseases. Thus, the most resource-consuming disease can be automatically estimated by applying Labeled LDA to the electronic claim data. Although our method is composed of a simple scheme, this is the first trial for realizing estimation of the most resource-consuming disease.

The the depth-of-field limitation of our eyes causes out-of-focus blur in the retinal images. The blur dynamically changes whenever we change our gaze and accordingly the scene point we are looking at changes its depth. This paper proposes an image display that reproduces retinal out-of-focus blur by using a stereoscopic display and eye trackers. Its purpose is to provide the viewer with more realistic visual experiences than conventional (stereoscopic) displays. Unlike previous similar systems that track only one of the viewer's eyes to estimate the gaze depth, the proposed system tracks both eyes individually using two eye trackers and estimates the gaze depth from the convergence angle calculated by triangulation. This provides several advantages over existing schemes, such as being able to deal with scenes having multiple depths. We describe detailed implementations of the proposed system and show the results of an experiment conducted to examine its effectiveness. In the experiment, creating a scene having two depths using two LCD displays together with a half mirror, we examined how difficult it is for viewers to distinguish between the real scene and its virtual reproduction created by the proposed display system. The results of the experiment show the effectiveness of the proposed approach.

Many methods have been proposed for measuring the structural similarity between two protein folds. However, it is difficult to select one best method from them for the classification task, as each method has its own strength and weakness. Intuitively, combining multiple methods is one solution to get the optimal classification results. In this paper, by generalizing the concept of the large margin nearest neighbor (LMNN), a method for combining multiple distance metrics from different types of protein structure comparison methods for protein fold classification task is proposed. While LMNN is limited to Mahalanobis-based distance metric learning from a set of feature vectors of training data, the proposed method learns an optimal combination of metrics from a set of distance metrics by minimizing the distances between intra-class data and enlarging the distances of different classes' data. The main advantage of the proposed method is the capability in finding an optimal weight coefficient for combination of many metrics, possibly including poor metrics, avoiding the difficulties in selecting which metrics to be included for the combination. The effectiveness of the proposed method is demonstrated on classification experiments using two public protein datasets, namely, Ding Dubchak dataset and ENZYMES dataset.

In this letter, a new method is presented to suppress fractional pseudocodewords by eliminating small instantons of irregular low-density parity-check (LDPC) codes under the linear programming (LP) decoding over the binary symmetric channel (BSC). By appending several new rows found by the integer linear programming formulation to the original parity-check matrix, the optimal distribution spectrum of BSC-instantons in the modified code is obtained. Simulation results show that the proposed method can improve the fractional distance of parity-check matrices and considerably enhance the error-correcting performance of irregular LDPC codes under the LP decoding at the cost of a slightly loss of the original code rate.

In this paper, an analytical threshold voltage model of the strained gate-all-around MOSFET fabricated on the Si1-xGex virtual substrate is presented by solving the two-dimensional Poisson equation. The impact of key parameters such as the strain, channel length, gate oxide thickness and radius of the silicon cylinder on the threshold voltage has been investigated. It has been demonstrated that the threshold voltage decreases as the strain in the channel increases. The threshold voltage roll-off becomes severe when increasing the Ge content in the Si1-xGex virtual substrate. The model is found to tally well with the device simulator.

This paper presents a novel MEMD interval thresholding denoising, where relevant modes are selected by the similarity measure between the probability density functions of the input and that of each mode. Simulation and measured EEG data processing results show that the proposed scheme achieves better performance than other traditional denoisings.

In modern communication systems, it is a critical and challenging issue for existing carrier tracking techniques to achieve near-ideal carrier synchronization without the help of pilot signals in the case of symbol rate sampling and low signal-to-noise ratio (SNR). To overcome this issue, this paper proposes an effective carrier frequency and phase offset tracking scheme which has a robust confluent synchronization architecture whose main components are a digital frequency-locked loop (FLL), a digital phase-locked loop (PLL), a modified symbol hard decision block and some sampling rate conversion blocks. As received signals are sampled at symbol baud rate, this carrier tracking scheme is still able to obtain precise estimated values of carrier synchronization parameters under the condition of very low SNRs. The performance of the proposed carrier synchronization scheme is also evaluated by using Monte-Carlo method. Simulation results confirm the feasibility of this carrier tracking scheme and demonstrate that it ensures that both the rate-3/4 irregular low-density parity-code (LDPC) coded system and the military voice transmission system utilizing the direct sequence spread spectrum (DSSS) technique achieve satisfactory bit-error rate (BER) performance at correspondingly low SNRs.

In previous papers by the authors, a new scheme for diagnosis of stochastic discrete event systems, called sequence profiling (SP), is proposed. From given event logs, N-gram models that approximate the behavior of the target system are extracted. N-gram models are used for discovering discrepancy between observed event logs and the behavior of the system in the normal situation. However, when the target system is a distributed system consisting of several subsystems, event sequences from subsystems may be interleaved, and SP cannot separate the faulty event sequence from the interleaved sequence. In this paper, we introduce wildcard characters into event patterns. This contributes to removing the effect by subsystems which may not be related to faults.

Bag of Visual Words (BoVW) is an effective framework for image retrieval. Query expansion (QE) further boosts retrieval performance by refining a query with relevant visual words found from the geometric consistency check between the query image and highly ranked retrieved images obtained from the first round of retrieval. Since QE checks the pairwise consistency between query and highly ranked images, its performance may deteriorate when there are slight degradations in the query image. We propose Query Bootstrapping as a variant of QE to circumvent this problem by using the consistency of highly ranked images instead of pairwise consistency. In so doing, we regard frequently co-occurring visual words in highly ranked images as relevant visual words. Frequent itemset mining (FIM) is used to find such visual words efficiently. However, the FIM-based approach requires sensitive parameters to be fine-tuned, namely, support (min/max-support) and the number of top ranked images (top-k). Here, we propose an adaptive support algorithm that adaptively determines both the minimum support and maximum support by referring to the first round's retrieval list. Selecting relevant images by using a geometric consistency check further boosts retrieval performance by reducing outlier images from a mining process. An important parameter for the LO-RANSAC algorithm that is used for the geometric consistency check, namely, inlier threshold, is automatically determined by our algorithm. We further introduce tf-fi-idf on top of tf-idf in order to take into account the frequency of inliers (fi) in the retrieved images. We evaluated the performance of QB in terms of mean average precision (mAP) on three benchmark datasets and found that it gave significant performance boosts of 5.37%, 9.65%, and 8.52% over that of state-of-the-art QE on Oxford 5k, Oxford 105k, and Paris 6k, respectively.

A novel circularly and linearly polarized loop antenna is presented. A simple loop configuration, twisted like a cross shape, has achieved radiating wide beam circular polarization simultaneously with linear polarization in two close bands. This cross configuration brings good circular polarization to a loop antenna because it uses the transmission line mode of a folded dipole antenna. For these reasons, the antenna is named the Cross Spiral Antenna (CSA). In this paper, a basic structure and the principle of the CSA radiating circular polarization with one port feeding is explained. The prototype CSA, which is tuned to around 1.57GHz and 1.6GHz, is tested for verifying the effectiveness of the suggested antenna configuration.

Recently, Ku et al. proposed a sector-based graphical password scheme, RiS, with dynamically adjustable resistance to login-recording attacks. However, since most users are more familiar with textual passwords than graphical passwords, we propose a secure and efficient textual-graphical password scheme, T-RiS, which is a variant of RiS. The T-RiS user can efficiently complete the login process in an environment under low threat of login-recording attacks and securely complete the login process in an environment under high threat of login-recording attacks. T-RiS can be used in environments where the users are more familiar with passwords based on texts than passwords based on icons/images and the number of login sessions the adversary can record is usually less than five.

This paper presents a low complexity metric for joint maximum-likelihood detection (MLD) in overloaded multiple-input multiple-output (MIMO)-orthogonal frequency division multiplexing (OFDM) systems. In overloaded MIMO systems, a nonlinear detection scheme such as MLD combined with error correction coding achieves better performance than is possible with a single signal stream with higher order modulation. However, MLD incurs high computation complexity because of the multiplications in the selection of candidate signal points. Thus, a Manhattan metric has been used to reduce the complexity. Nevertheless, it is not accurate and causes performance degradation in overloaded MIMO systems. Thus, this paper proposes a new metric whose calculations involve only summations and bit shifts. New numerical results obtained through computer simulation show that the proposed metric improves bit error rate (BER) performance by more than 0.2dB at the BER of 10-4 in comparison with a Manhattan metric.

A frequency-domain (FD) uniform asymptotic solution (FD-UAS) which is useful for engineering applications is newly derived for the two-dimensional scattered magnetic field by a coated conducting cylinder covered with a thin lossy medium. The FD-UAS is uniform in the sense that it remains valid within the transition region adjacent to the shadow boundary, and it smoothly connects a geometric optical ray (GO) solution and a geometrical theory of diffraction (GTD) solution exterior to the transition region, respectively. We assume that the thickness of a coating medium is thin as compared with one wavelength of a cylindrical wave radiated from a magnetic line source. This uniform asymptotic solution is represented by a combination of scattered field component solutions, namely, the GO solution composed of a direct GO (DGO) and a reflected GO, the extended uniform GTD (extended UTD) solution made up of a DGO and a pseudo surface diffracted ray (pseudo SD), the modified UTD solution representing SD series, and the GTD solution for a lowest order SD. The FD-UAS is valid for a source point and/or an observation point located either near the coating surface or in the far-zone. The effectiveness and usefulness of the FD-UAS presented here are confirmed by comparing with both the exact solution and the conventional UTD shadow region solution.

The Lyapunov stability theory-based adaptive filter (LST-AF) is a robust filtering algorithm which the tracking error quickly converges to zero asymptotically. Recently, the software module of the LST-AF algorithm is effectively used in engineering applications such as tracking, prediction, noise cancellation and system identification problems. Therefore, hardware implementation becomes necessary in many cases where real time procedure is needed. In this paper, an implementation of the LST-AF algorithm on Field Programmable Gate Arrays (FPGA) is realized for the first time to our knowledge. The proposed hardware implementation on FPGA is performed for two main benchmark problems; i) tracking of an artificial signal and a Henon chaotic signal, ii) estimation of filter parameters using a system identification model. Experimental results are comparatively presented to test accuracy, performance and logic occupation. The results show that our proposed hardware implementation not only conserves the capabilities of software versions of the LST-AF algorithm but also achieves a better performance than them.

Cold boot attack is a side channel attack that recovers data from memory, which persists for a short period after power is lost. In the course of this attack, the memory gradually degrades over time and only a corrupted version of the data may be available to the attacker. Recently, great efforts have been made to reconstruct the original data from a corrupted version of AES key schedules, based on the assumption that all bits in the charged states tend to decay to the ground states while no bit in the ground state ever inverts. However, in practice, there is a small number of bits flipping in the opposite direction, called reverse flipping errors. In this paper, motivated by the latest work that formulates the relations of AES key bits as a Boolean Satisfiability problem, we move one step further by taking the reverse flipping errors into consideration and employing off-the-shelf SAT and MaxSAT solvers to accomplish the recovery of AES-128 key schedules from decayed memory images. Experimental results show that, in the presence of reverse flipping errors, the MaxSAT approach enables reliable recovery of key schedules with significantly less time, compared with the SAT approach that relies on brute force search to find out the target errors. Moreover, in order to further enhance the efficiency of key recovery, we simplify the original problem by removing variables and formulas that have relatively weak relations to the whole key schedule. Experimental results demonstrate that the improved MaxSAT approach reduces the scale of the problem and recover AES key schedules more efficiently when the decay factor is relatively large.

The phenomenon of stochastic resonance (SR) in a mono-threshold-system-based detector (MTD) with additive background noise and multiplicative external noise is investigated. On the basis of maximum a posteriori probability (MAP) criterion, we deal with the binary signal transmission in four scenarios. The performance of the MTD is characterized by the probability of error detection, and the effects of system threshold and noise intensity on detectability are discussed in this paper. Similar to prior studies that focus on additive noises, along with increases in noise intensity, we also observe a non-monotone phenomenon in the multiplicative ways. However, unlike the case with the additive noise, optimal multiplicative noises all tend toward infinity for fixed additive noise intensities. The results of our model are potentially useful for the design of a sensor network and can help one to understand the biological mechanism of synaptic transmission.

This study explored the question of how to minimize older drivers' accidents and to identify at-risk drivers by analyzing their driving performance. Previous traffic research reported that there were two factors involved in risky driving, namely driving risk perception and risky driving attitude. We investigated these two factors as indicators of an at-risk driver by using large-scale test data from license renewal tests that are obligatory for Japanese drivers who are 70 years of age or older. The tests include a driving simulator test, an on-road test, and a cognitive screening test. By using these assessments and predictions made with renewal driving tests, we were able to indicate the possibility of identifying at-risk drivers.

A tri-band Multiple-input-multiple-output (MIMO) antenna system for LTE 700, LTE2500 and GSM 1800/1900 mobile handset application is presented. The whole system consists of four identical 3-D IFAs (inverted F antenna) folded on FR4 cuboids. Without any special designed decoupling structures, the measured isolation among antenna elements is higher than 20dB in the low and upper bands, even in the middle band, the isolation is higher than 13.7dB. Reflection coefficient, correlation coefficient, gain and radiation pattern are also presented. Acceptable agreement between the antenna models with and without plastic housing, battery and LCD screen demonstrate that the proposed antenna is a competitive candidate for mobile handsets.

This paper proposes a practical throughput upper bound that considers physical layer techniques using adaptive modulation and coding (AMC) for orthogonal frequency division multiplexing (OFDM) multiple-input multiple-output (MIMO) multiplexing. The proposed upper bound is computed from the modulation and coding scheme (MCS) that provides the maximum throughput considering the required block error rate (BLER) at the respective received signal-to-noise power ratios as a constraint. Then, based on the practical throughput upper bound, we present the causes of impairment for selecting the best MCS based on the computed mutual information for OFDM MIMO multiplexing. More specifically, through the evaluations, we investigate the effect of MCS selection error on an increasing maximum Doppler frequency due to the round trip delay time and the effect of channel estimation error of maximum likelihood detection associated with reference signal based channel estimation.

A threshold secret sharing scheme can realize reliable delivery of important content using redundant routes through a network. Furthermore, multicast delivery of threshold secret shared content can achieve efficient resource utilization thanks to the application of multicast and network coding techniques to multiple pieces of the content. Nevertheless, a tradeoff exists between reliability and efficiency if multicast content delivery uses network coding. This paper proposes a flexible multicast delivery scheme for threshold secret shared content that can control the tradeoff between reliability and efficiency. The proposed scheme classifies all the pieces obtained from the original content into multiple groups, and each group is subjected to network coding independently. An optimization procedure is proposed for the multicast delivery scheme, which involves two different heuristic delivery route computation methods applicable to large-scale networks. Evaluation results show that the optimized multicast delivery scheme adopting an appropriate grouping method and classifying the pieces into a suitable number of groups can minimize the required link bandwidth while satisfying a specified content loss probability requirement.