Magnetic particle imaging (MPI), in which the nonlinear interaction between internally administered magnetic nanoparticles (MNPs) and electromagnetic waves irradiated from outside of the body is utilized, has attracted attention for its potential to achieve early diagnosis of diseases such as cancer. In MPI, the local magnetic field distribution is scanned, and the magnetization signal from MNPs within a selected region is detected. However, the signal sensitivity and image resolution are degraded by interference from magnetization signals generated by MNPs outside of the selected region, mainly because of imperfections (limited gradients) in the local magnetic field distribution. Here, we propose new methods based on correlation information between the observed signal and the system function–defined as the interaction between the magnetic field distribution and the magnetizing properties of MNPs. We performed numerical analyses and found that, although the images were somewhat blurred, image artifacts could be significantly reduced and accurate images could be reconstructed without the inverse-matrix operation used in conventional image reconstruction methods.

Superconducting integrated circuits should be operated at low temperature below a half of their critical temperatures. Thermal heat from a bias resistor could rise the temperature in Josephson junctions, and would reduce their critical currents. In this study, we estimate the temperature in a Josephson junction heated by a bias resistor at the bath temperature of 4.2 K, and introduce a parameter β that connects the thermal heat from a bias resistor and the temperature elevation of a Josephson junction. By using β, the temperature in the Josephson junction can be estimated as functions of the current through the resistor.

A generation effect of higher harmonics for an externally applied signal in a photoconductive (PC) terahertz (THz)-wave emitter has been found. This effect is applicable to accurately measuring for frequencies of THz waves. This paper describes reasons why higher harmonics are generated in a PC device. The dependence of the photoconductance on the applied voltage in the PC device consists of a flat range and a negative slant range, and one sharply bending point is then formed at the boundary between the flat and slant ranges. When the PC device is irradiated by two laser beams with slightly different optical frequencies, the photoconductance is strongly modulated at the optical beat frequency in the THz region by photomixing the two laser beams. As a result, three bending points are formed in the average photoconductance (introduced as the average of the temporal photoconductance varying at the THz frequency). The slants comprised of the three bending points are different from each other. When the variation range of the applied voltage driven by the signal input on the biased voltage covers the voltage of one of the bending points, the photoconductance (or the average photoconductance in optical beating) varies along the different two slopes, the resultant temporal photocurrent is largely distorted, and then the harmonics of the signal input are generated in the photocurrent. The following features are clarified: (1) the harmonics of the signal input are generated by appropriately adjusting the bias voltage and the amplitude of the signal input, regardless of the presence/absence of optical beating; (2) the efficiency of the harmonic generation is about 10-4 -10-5; and (3) the harmonics over 35th order with almost flat amplitudes (-3.8 dB/octave) are generated.

In this paper, a novel microstrip hairpin-line bandpass filter which employs a modified Minkowski fractal shape is proposed. Although conventional hairpin-line filters are popular for RF front ends, they suffer from undesired spurious responses located at the second harmonic, which causes asymmetry in the upper skirt band. By proper design, the second harmonic of fractal filters can be significantly suppressed through the use of fractal shape. To validate this novel geometry, the proposed filters are fabricated and measured. Simulated results are in good agreement with measured results.

This paper presents an efficient algorithm to generate all (unordered) rooted trees with exactly n vertices including exactly k leaves. There are known results on efficient enumerations of some classes of graphs embedded on a plane, for instance, biconnected and triconnected triangulations [3],[6], and floorplans [4]. On the other hand, it is difficult to enumerate a class of graphs without a fixed embedding. The paper is on enumeration of rooted trees without a fixed embedding. We already proposed an algorithm to generate all “ordered” trees with n vertices including k leaves [11], while the algorithm cannot seem to efficiently generate all (unordered) rooted trees with n vertices including k leaves. We design a simple tree structure among such trees, then by traversing the tree structure we generate all such trees in constant time per tree in the worst case. By repeatedly applying the algorithm for each k=1,2, ...,n-1, we can also generate all rooted trees with exactly n vertices.

While the Secure Socket Layer or Transport Layer Security (SSL/TLS) is assumed to provide secure communications over the Internet, many web applications utilize basic or digest authentication of Hyper Text Transport Protocol (HTTP) over SSL/TLS. Namely, in the scheme, there are two different authentication schemes in a session. Since they are separated by a layer, these are not convenient for a web application. Moreover, the scheme may also cause problems in establishing secure communication. Then we provide a scheme of authentication binding between SSL/TLS and HTTP without modifying SSL/TLS protocols and its implementation, and we show the effectiveness of our proposed scheme.

We propose a new method, called Subclass-oriented Dimensionality Reduction with Pairwise Constraints (SODRPaC), for dimensionality reduction. In a high dimensional space, it is common that a group of data points with one class may scatter in several different groups. Current linear semi-supervised dimensionality reduction methods would fail to achieve fair performances, as they assume two data points linked by a must-link constraint are close each other, while they are likely to be located in different groups. Inspired by the above observation, we classify the must-link constraint into two categories, which are the inter-subclass must-link constraint and the intra-subclass must-link constraint, respectively. We carefully generate cannot-link constraints by using must-link constraints, and then propose a new discriminant criterion by employing the cannot-link constraints and the compactness of shared nearest neighbors. The manifold regularization is also incorporated in our dimensionality reduction framework. Extensive experiments on both synthetic and practical data sets illustrate the effectiveness of our method.

A new approach to speech feature estimation under noise circumstances is proposed in this paper. It is used in noise-robust continuous speech recognition (CSR). As the noise robust techniques in isolated word speech recognition, the running spectrum analysis (RSA), the running spectrum filtering (RSF) and the dynamic range adjustment (DRA) methods have been developed. Among them, only RSA has been applied to a CSR system. This paper proposes an extended DRA for a noise-robust CSR system. In the stage of speech recognition, a continuous speech waveform is automatically assigned to a block defined by a short time length. The extended DRA is applied to these estimated blocks. The average recognition rate of the proposed method has been improved under several different noise conditions. As a result, the recognition rates are improved up to 15% in various noises with 10 dB SNR.

When a graph can be decomposed into components of well-connected subgraphs, it is possible to speed up random walks by taking advantage of topology of the graph. In this paper, a modified Metropolis random walk scheme is introduced and conditions are given when it performs better than the original Metropolis algorithm.

In the task of face recognition, a challenging issue is the one sample problem, namely, there is only one training sample per person. Principal component analysis (PCA) seeks a low-dimensional representation that maximizes the global scatter of the training samples, and thus is suitable for one sample problem. However, standard PCA is sensitive to the outliers and emphasizes more on the relatively distant sample pairs, which implies that the close samples belonging to different classes tend to be merged together. In this paper, we propose two-stage block-based whitened PCA (TS-BWPCA) to address this problem. For a specific probe image, in the first stage, we seek the K-Nearest Neighbors (K-NNs) in the whitened PCA space and thus exclude most of samples which are distant to the probe. In the second stage, we maximize the “local” scatter by performing whitened PCA on the K nearest samples, which could explore the most discriminative information for similar classes. Moreover, block-based scheme is incorporated to address the small sample problem. This two-stage process is actually a coarse-to-fine scheme that can maximize both global and local scatter, and thus overcomes the aforementioned shortcomings of PCA. Experimental results on FERET face database show that our proposed algorithm is better than several representative approaches.

Large-scale adoption of electronic healthcare applications requires semantic interoperability. The new proposals propose an advanced (multi-level) DBMS architecture for repository services for health records of patients. These also require query interfaces at multiple levels and at the level of semi-skilled users. In this regard, a high-level user interface for querying the new form of standardized Electronic Health Records system has been examined in this study. It proposes a step-by-step graphical query interface to allow semi-skilled users to write queries. Its aim is to decrease user effort and communication ambiguities, and increase user friendliness.

This work examines energy trajectory and voice quality measurements, in addition to conventional formant and duration properties, to classify tense and lax vowels in English. Tense and lax vowels are produced with differing articulatory configurations which can be identified by measuring acoustic cues such as energy peak location, energy convexity, open quotient and spectral tilt. An analysis of variance (ANOVA) is conducted, and dialect effects are observed. An overall 85.2% classification rate is obtained using the proposed features on the TIMIT database, resulting in improvement over using only conventional acoustic features. Adding the proposed features to widely used cepstral features also results in improved classification.

The general method for estimating phrase translation probabilities consists of sequential processes: word alignment, phrase pair extraction, and phrase translation probability calculation. However, during this sequential process, errors may propagate from the word alignment step through the translation probability calculation step. In this paper, we propose a new method for estimating phrase translation probabilities that reduce the effects of error propagation. By considering the semantic recoverability of phrase retranslation, our method identifies incorrect phrase pairs that have propagated from alignment errors. Furthermore, we define retranslation similarity which represents the semantic recoverability of phrase retranslation, and use this when computing translation probabilities. Experimental results show that the proposed phrase translation estimation method effectively prevents a PBSMT system from selecting incorrect phrase pairs, and consistently improves the translation quality in various language pairs.

Intermittent Periodic Transmission (IPT forwarding) has been proposed as an efficient packet relay method for wireless backhaul. In IPT forwarding, a source node sends packets to a destination node with a certain time interval (IPT duration) so that signal interference between relay nodes that send packets simultaneously are reduced and frequency reuse is realized which brings about an improvement of system throughput. However, optimum IPT duration setting for each node is a difficult problem which is not solved adequately yet. In this paper, we propose a new IPT duration setting protocol which employs some training packets to search for the optimum IPT duration for each node. A simulation and experiment show that the proposed method is not only very effective but also practical for wireless backhaul.

Recent developments of electronic devices containing Josephson junctions (JJ) with high-Tc superconductors (HTS) are reported. In particular, the fabrication process and the properties of superconducting quantum interference devices (SQUIDs) with a multilayer structure and ramp-edge-type JJs are described. The JJs were fabricated by recrystallization of an artificially deposited Cu-poor precursory layer. The formation mechanism of the junction barrier is discussed. We have fabricated various types of gradiometers and magnetometers. They have been actually utilized for several application systems, such as a non-destructive evaluation (NDE) system for deep-lying defects in a metallic plate and a reel-to-reel testing system for striated HTS-coated conductors.

We present sampling theorems that reconstruct consistent signals from noisy underdetermined measurements. The consistency criterion requires that the reconstructed signal yields the same measurements as the original one. The main issue in underdetermined cases is a choice of a complementary subspace L in the reconstruction space of the intersection between the reconstruction space and the orthogonal complement of the sampling space because signals are reconstructed in L. Conventional theorems determine L without taking noise in measurements into account. Hence, the present paper proposes to choose L such that variance of reconstructed signals due to noise is minimized. We first arbitrarily fix L and compute the minimum variance under the condition that the average of the reconstructed signals agrees with the noiseless reconstruction. The derived expression clearly shows that the minimum variance depends on L and leads us to a condition for L to further minimize the minimum value of the variance. This condition indicates that we can choose such an L if and only if L includes a subspace determined by the noise covariance matrix. Computer simulations show that the standard deviation for the proposed sampling theorem is improved by 8.72% over that for the conventional theorem.

In this paper, we investigate two improved turbo receivers for the Long Term Evolution (LTE) uplink in the presence of transmitter (Tx) in-phase and quadrature-phase imbalance (IQI) with parameters known at eNodeB. For multiuser multiple-input multiple-output (MU-MIMO) single-carrier frequency division multiple access (SC-FDMA) systems, we derive a optimal joint linear minimum mean square error (MMSE) turbo multiuser detector (MUD) based on the mirror symmetry clusters. For the single use SC-FDMA system with Tx IQI, we derive an optimal widely linear MMSE (WLMMSE) turbo equalizer. Both receivers are implemented in the discrete frequency domain and only slightly increase the computational complexity compared to the conventional turbo receivers. Monte Carlo simulations show that the proposed receivers significantly outperform the conventional turbo receivers. The simulation results are then confirmed by the extrinsic information transfer (EXIT) chart analysis.

In this letter, we introduce a novel patch sampling strategy for the task of image classification, which is fundamentally different from current patch sampling strategies. A top-down guidance learned from training images is used to guide patch sampling towards informative regions. Experiment results show that this approach achieved noticeable improvement over baseline patch sampling strategies for the classification of both object categories and scene categories.

This paper considers the power allocation (PA) problem for three-node decode-and-forward (DF) relay communication systems, where the aggregate transmit power constraint is imposed on the source and the relay and the optimization target is to maximize the system's instantaneous information rate. Since the relay is equipped with multiple antennas, the receiver and transmitter beamforming strategies are generally adopted. In this paper, we start by proposing a closed-form solution for the frequency-flat (FF) fading environment, then give a bisection algorithm with low complexity to obtain an optimal solution for the frequency-selective (FS) fading scenario. Finally, simulations validate the proposed methods.

Software Defined Radio (SDR) techniques are expected to be among the key technologies of heterogeneous cognitive radio networks for realizing efficient and convenient wireless communications by providing multiple radio services to users and decreasing development costs. In this paper, in order to evaluate the feasibility of SDR modems, we study the amount of computing throughput of a recent wireless system and determine a suitable modem architecture. Firstly, the functions for which SDR techniques provide significant benefits are clarified. Secondly, the computing throughputs are measured under the assumption that a dynamically reconfigurable processor, FlexSwordTM, is employed. Finally, based on a consideration of timing charts, we propose the architecture of an SDR-based modem with FlexSword. The possibility of implementing several wireless systems is also considered.