We outline a number of high temperature superconducting Josephson junction-based devices including superconducting quantum interference devices (SQUIDs) developed for a wide range of applications including geophysical exploration, magnetic anomaly detection, terahertz (THz) imaging and microwave communications. All these devices are based on our patented technology for fabricating YBCO step-edge junction on MgO substrates. A key feature to the successful application of devices based on this technology is good stability, long term reliability, low noise and inherent flexibility of locating junctions anywhere on a substrate.

By using electric-field-induced optical second-harmonic generation (EFISHG) measurement, we investigated interfacial carrier behavior in organic solar cells (OSCs) with a blocking layer of bathocuproine (BCP). Results evidently showed that the Maxwell-Wagner type excess charges accumulate on both pentacene/C60 and C60/BCP interfaces. Also, the measurement under short-circuit and open-circuit conditions clearly showed the different photo-induced carrier behaviors in the OSCs devices. Our work proved that the dielectric nature of OSCs dominates the operation of our OSCs and the EFISHG technique is very effective to characterize the dielectric performance of the OSCs.

This paper presents a basic investigation of the power imbalance problem with regard to maximum ratio combining (MRC) array antennas for digital TV broadcast reception. First, the relationship between the decrease in the diversity gain and reduction in the received power was investigated using two-element and four-element dipole array antennas by means of a Monte Carlo simulation. The relationship between the decrease in the diversity gain and the number of branches imposed to reduce the received power was also investigated. Then, a simple method of predicting the reduction in the diversity gain under imbalanced power conditions is given using the simulation results. The objective is to determine a criterion associated with the gain reduction that allows us to achieve the required system performance. Finally, the proposed method is confirmed by analysis using a model representing a typical portable digital broadcasting TV set held with both hands that simulates the power imbalance condition.

We investigated oxidation time dependence of graphene oxide employing modified Hummer method by dynamic light scattering. Oxidation reaction proceeded rapidly within about 24 hours, and was saturated. It is suggested that graphene oxides were not able to freely fragment. This implies that the oxidation reactions occur at the limited sites.

Magnetospinography (MSG) is one of the most promising techniques to detect the nerve activity of spinal cords thanks to its noninvasiveness and high spatial/temporal resolutions. Multichannel superconducting quantum interference device (SQUID) MSG measurement systems optimized for supine subjects have been developed previously and employed in clinical applications in hospitals. Magnetic source analyses of MSG data based on spatial filter techniques reveal the transition of reconstructed current distributions adjacent to the spinal cord. The propagation of the neural signals was noninvasively visualized. The MSG measurements provide significant diagnostic information such as irregularities in the transitions of the reconstructed current distribution and/or considerable decreases in the current intensity at the lesion. Such functional imaging of the spinal cord in addition to conventional neurologic examinations and morphological imaging will be fairly effective in presurgical lesion localizations of the spinal cord.

Face perception and recognition have attracted more attention recently in multidisciplinary fields such as engineering, psychology, neuroscience, etc. with the advances in physical/physiological measurement and data analysis technologies. In this paper, our main interest is building computational models of human face recognition based on psychological experiments. We specially focus on modeling human face recognition characteristics of average face in the dimension of distinctiveness. Psychological experiments were carried out to measure distinctiveness of face images and their results are explained by computer analysis results of the images. Two psychological experiments, 1) Classical experiment of distinctiveness rating and, 2) Novel experiment of recognition of an average face were performed. In the later experiment, we examined on how the average face of two face images was recognized by a human in a similarity test respect to the original images which were utilized for the calculation of the average face. To explain results of the psychological experiments, eigenface spaces were constructed based on Principal Component Analysis (PCA). Significant correlation was found between human and PCA based computer recognition results. Emulation of human recognition of faces is one of the expected applications of this research.

In precoded TDD MIMO systems, precoding is done based on the downlink CSI, which can be predicted according to the outdated uplink CSI. This letter proposes a double-scale channel prediction scheme where frame-scale Kalman filters and pilot-symbol-scale AR predictors jointly predict the needed downlink CSI.

Compensation for the nonlinear systems represented by polynomials involves polynomial inverse. In this paper, a new algorithm is proposed that gives the baseband polynomial inverse with a limited order. The algorithm employs orthogonal basis that is predetermined from the distribution of input signal and finds the coefficients of the inverse polynomial to minimize the mean square error. Compared with the well established p-th order inverse method, the proposed method can suppress the distortions better including higher order distortions. It is also extended to obtain memory polynomial inverse through a feedback-configured structure. Both numerical simulations and experimental results demonstrate that the proposed algorithm can provide good performance for compensating the nonlinear systems represented by baseband polynomials.

We propose a novel network traffic matrix decomposition method named Stable Principal Component Pursuit with Frequency-Domain Regularization (SPCP-FDR), which improves the Stable Principal Component Pursuit (SPCP) method by using a frequency-domain noise regularization function. An experiment demonstrates the feasibility of this new decomposition method.

This paper presents an approach for cross-pose face recognition by virtual view generation using an appearance clustering based local view transition model. Previously, the traditional global pattern based view transition model (VTM) method was extended to its local version called LVTM, which learns the linear transformation of pixel values between frontal and non-frontal image pairs from training images using partial image in a small region for each location, instead of transforming the entire image pattern. In this paper, we show that the accuracy of the appearance transition model and the recognition rate can be further improved by better exploiting the inherent linear relationship between frontal-nonfrontal face image patch pairs. This is achieved based on the observation that variations in appearance caused by pose are closely related to the corresponding 3D structure and intuitively frontal-nonfrontal patch pairs from more similar local 3D face structures should have a stronger linear relationship. Thus for each specific location, instead of learning a common transformation as in the LVTM, the corresponding local patches are first clustered based on an appearance similarity distance metric and then the transition models are learned separately for each cluster. In the testing stage, each local patch for the input non-frontal probe image is transformed using the learned local view transition model corresponding to the most visually similar cluster. The experimental results on a real-world face dataset demonstrated the superiority of the proposed method in terms of recognition rate.

In this paper, an energy- and traffic-balance-aware mapping algorithm from IP cores to nodes in a network is proposed for application-specific Network-on-Chip(NoC). The multi-objective optimization model is set up by considering the NoC architecture, and addressed by the proposed mapping algorithm that decomposes mapping optimization into a number of scalar subproblems simultaneously. In order to show performance of the proposed algorithm, the application specific benchmark is applied in the simulation. The experimental results demonstrate that the algorithm has advantages in energy consumption and traffic balance over other algorithms.

In recent years, technologies and markets related to data centers have been rapidly changing and growing. Data centers are playing an important role in ICT infrastructure deployment and promise to become common platforms for almost all social infrastructures. Even though research has focused on networking technologies, various technologies are needed to develop high-performance, cost-efficient, and flexible large-scale data centers. To understand those technologies better, this paper surveys recent research and development efforts and results in accordance with a data center network taxonomy that the authors defined.

Process variation causes significant fluctuations in the timing performance of analog circuits, which causes a fraction of circuits to fail specifications. By testing the delay-performance, we can recognize the failed circuits during production testing. In this paper, we have proposed a low overhead and process tolerant delay evaluation circuit for built-in self test (BIST) function for analog differential circuits. This circuit contains a delay generation cell, an input differential signal generation cell, a delay matching cell, a sample-hold circuit, and a comparator. This circuit was implemented with 0.18 µm CMOS process. Simulation results over process variation, devices mismatch and layout parasitics, but without silicon measurement, show that the accuracy in delay detection is within 5 ps. A case study was done over a feed-forward equalizer (FFE). A typical use of this circuit is testing the delay of various FIR (Finite Impulse Response) filters.

We humans are easily able to instantaneously detect the regions in a visual scene that are most likely to contain something of interest. Exploiting this pre-selection mechanism called visual attention for image and video processing systems would make them more sophisticated and therefore more useful. This paper briefly describes various computational models of human visual attention and their development, as well as related psychophysical findings. In particular, our objective is to carefully distinguish several types of studies related to human visual attention and saliency as a measure of attentiveness, and to provide a taxonomy from several viewpoints such as the main objective, the use of additional cues and mathematical principles. This survey finally discusses possible future directions for research into human visual attention and saliency computation.

We show an improved throughput scaling law for an ultra-wide band (UWB) ad hoc network by using a modified hierarchical cooperation (HC) strategy; the n wireless nodes are assumed to be randomly sited. In a dense network of unit area, our result indicates that the derived throughput scaling depends on the path-loss exponent α for certain operating regimes due to the power-limited characteristics. It also turns out that the use of HC is helpful in improving the throughput scaling of our UWB network in some conditions. More specifically, assuming that the bandwidth scales faster than nα+1(log n)α/2, it is shown that the HC protocol outperforms nearest multi-hop routing for 2 < α < 3 while using nearest multi-hop routing leads to higher throughput for α ≥ 3.

In this letter, unlike the previous work in [2], the optimal power allocation in a non-orthogonal, amplify-and-forward (AF) relay-assisted transmission is investigated in the uplink. Here, the inter-user-interference among the signals from MTs and relays exists due to non-zero interference suppression factor (ISF), i.e., finite spreading factor. In this letter, we show that the optimal solution to achieve a 'max-min fairness' among mobile terminals can be alternatively obtained by solving its inverse problem. The impact of various ISFs as well as the Jain's fairness is investigated in comparison with the equal power allocation.

Magnetoencephalography (MEG) measures very weak neuromagnetic signals using SQUID sensors. Standard MEG analyses include averaged waveforms, isofield maps and equivalent current dipoles. Beamforming MEG analyses provide us with frequency-dependent spatiotemporal information about the cerebral oscillatory changes related to not only somatosensory processing but also language processing. Language dominance is able to be evaluated using laterality of power attenuation in the low γ band in the frontal area. Neuromagnetic signals of the unilateral upper movements are able to be decoded using a support vector machine.

We address the global asymptotic stability of FAST TCP, especially considering cross traffics, time-varying network feedback delay, and queuing delay dynamics at link. Exploiting the inherent dynamic property of FAST TCP, we construct two sequences that represent the lower and upper bound variations of the congestion window in time. By showing that the sequences converge to the equilibrium point of the congestion window, we establish that FAST TCP in itself is globally asymptotically stable without any specific conditions on the tuning parameter α or the update gain γ.

An automotive operating system is a typical safety-critical software and therefore requires extensive analysis w.r.t its effect on system safety. Our earlier work [1] reported a systematic model checking approach for checking the safety properties of the OSEK/VDX-based operating system Trampoline. This article reports further performance improvement using embeddedC constructs for efficient verification of the Trampoline model developed in the earlier work. Experiments show that the use of embeddedC constructs greatly reduces verification costs.

We examine the relationship between 116 VHF sensor events recorded by the VHF sensor on the Maido-1 satellite and lightning strokes detected by the World Wide Lightning Location Network (WWLLN) to show that most of the VHF sensor events were caused by lightning discharges. For each VHF sensor event, the WWLLN events within 1400 km from the subsatellite point and within 1 sec, 30 sec, and 300 sec of the VHF sensor trigger time are analyzed. We find that the coincidence rates in the North and South American continents, and in Southeast/East Asia and the Australian continent are greater than 0.90. Those in the African and European continents, and in the Pacific and Atlantic Oceans are less than 0.61. These high enough coincidence rates indicate that the VHF sensor events were emitted from lightning, although the coincidence rates in the other regions are quite low because of the low detection efficiency of the WWLLN in the regions. We also focus on 6 coincident events measured by both the VHF sensor and the WWLLN. The incidence angles of the EM waves for the VHF sensor are estimated from the group delay characteristics of the recorded EM waveforms. Compared with the WWLLN lightning locations, the two incidence angles are temporally and spatially coincident. These results indicate that a large fraction of the VHF sensor events are emitted by lightning discharges.