The research of detecting co-saliency over multiple images is just beginning. The existing methods multiply the saliency on single image by the correspondence over multiple images to estimate co-saliency. They have difficulty in highlighting the co-salient object that is not salient on single image. It is caused by two problems. (1) The correspondence computation lacks precision. (2) The co-saliency multiplication formulation does not fully consider the effect of correspondence for co-saliency. In this paper, we propose a novel co-saliency detection scheme linearly combining foreground correspondence and single-view saliency. The progressive graph matching based foreground correspondence method is proposed to improve the precision of correspondence computation. Then the foreground correspondence is linearly combined with single-view saliency to compute co-saliency. According to the linear combination formulation, high correspondence could bring about high co-saliency, even when single-view saliency is low. Experiments show that our method outperforms previous state-of-the-art co-saliency methods.

Function speculation design with error recovery mechanisms is quite promising due to its high performance and low area overhead. Previous work has focused on two-stage function speculation and thus lacks a systematic way to address the challenge of the multistage function speculation approach. This paper proposes a multistage function speculation with adaptive predictors and applies it in a novel adder. We deduced the analytical performance and area models for the design and validated them in our experiments. Based on those models, a general methodology is presented to guide design optimization. Both analytical proofs and experimental results on the fabricated chips show that the proposed adder's delay and area have a logarithmic and linear relationship with its bit number, respectively. Compared with the DesignWare IP, the proposed adder provides the same performance with 6-17% area reduction under different bit lengths.

Secure authentication of low cost Radio Frequency Identification (RFID) tag with limited resources is a big challenge, especially when we simultaneously consider anonymity, un-traceability, and forward secrecy. The popularity of Internet of Things (IoT) further amplifies this challenge, as we should authenticate these mobile tags in the partial-distributed-server environments. In this paper, we propose an RFID authentication scheme in the partial-distributed-server environments. The proposed scheme owns excellent performance in terms of computational complexity and scalability as well as security properties.

A novel ROI-based reversible data hiding scheme is proposed for medical images, which is able to hide electronic patient record (EPR) and protect the region of interest (ROI) with tamper localization and recovery. The proposed scheme combines prediction error expansion with the sorting technique for embedding EPR into ROI, and the recovery information is embedded into the region of non-interest (RONI) using histogram shifting (HS) method which hardly leads to the overflow and underflow problems. The experimental results show that the proposed scheme not only can embed a large amount of information with low distortion, but also can localize and recover the tampered area inside ROI.

Many wireless communication systems use a relay station for cooperative diversity or cell coverage extension. In this letter, an efficient partial single relay selection scheme is proposed for wireless communications. The conventional schemes such as the best harmonic mean and the threshold-based relay selection should know channel state informaion (CSI), or noise variance at all stations in advance. But the proposed scheme does not require any priori information. It uses a characteristic of the repeated signal pattern at candidates of the relay station. Simulation results show that the performance of proposed scheme is very close to the best harmonic mean relay selection scheme as one of the optimal relay selection schemes.

Users of wireless mobile devices need Internet access not only when they stay at home or office, but also when they travel. It may be desirable for such users to select a "longcut route" from their current location to his/her destination that has longer travel time than the shortest route, but provides a better mobile wireless environment. In this paper, we formulate the above situation as the optimization problem of “optimal longcut route selection”, which requires us to find the best route concerning the wireless environment subject to a travel time constraint. For this new problem, we show NP-hardness, propose two pseudo-polynomial time algorithms, and experimental evaluation of the algorithms.

In this letter, we propose a new no-reference blur estimation method in the frequency domain. It is based on computing the cumulative distribution function (CDF) of the Fourier transform spectrum of the blurred image and analyzing the relationship between its shape and the blur strength. From the analysis, we propose and evaluate six curve-shaped analytic metrics for estimating blur strength. Also, we employ an SVM-based learning scheme to improve the accuracy and robustness of the proposed metrics. In our experiments on Gaussian blurred images, one of the six metrics outperformed the others and the standard deviation values between 0 and 6 could be estimated with an estimation error of 0.31 on average.

In this paper, two receive beamforming techniques (Method 1 and Method 2) are proposed for a mobile station (MS) with multiple antenna arrays in an OFDM-based millimeter-wave (mm-wave) cellular communication system. Since the MS in mm-wave cellular communication requires fast processing due to its frequent movement and rotation, a receive beamforming technique with reduced computation complexity and processing time is proposed in Method 2. Of particular interest, estimation techniques for 2-dimensional (2D) direction-of-arrivals (DoAs) corresponding to each cell ID are proposed for uniform circular arrays (UCAs) and uniform rectangular arrays (URAs). Also, a cell selection technique for MSs with multiple antenna arrays is described that use the candidate cell IDs and parameters estimated for all antenna arrays to provide combining gain in addition to array gain in multipath channels. The proposed beamforming techniques are evaluated by computer simulation using a simple model of amm-wave cellular communication system with 3-dimensional spatial channel model (3D SCM).

Detecting traffic anomalies is an indispensable component of overall security architecture. As Internet and traffic data with more sophisticated attacks grow exponentially, preserving security with signature-based traffic analyzers or analyzers that do not support massive traffic are not sufficient. In this paper, we propose a novel method based on combined sketch technique and S-transform analysis for detecting anomalies in massive traffic streams. The method does not require any prior knowledge such as attack patterns and models representing normal traffic behavior. To detect anomalies, we summarize the entropy of traffic data over time and maintain the summarized data in sketches. The entropy fluctuation of the traffic data aggregated to the same bucket is observed by S-transform to detect spectral changes referred to as anomalies in this work. We evaluated the performance of the method with real-world backbone traffic collected at the United States and Japan transit link in terms of both accuracy and false positive rates. We also explored the method parameters' influence on detection performance. Furthermore, we compared the performance of our method to S-transform-based and Wavelet-based methods. The results demonstrated that our method was capable of detecting anomalies and overcame both methods. We also found that our method was not sensitive to its parameter settings.

In retinal blood vessel extraction through background removal, the vessels in a fundus image which appear in a higher illumination variance area are often missing after the background is removed. This is because the intensity values of the vessel and the background are nearly the same. Thus, the estimated background should be robust to changes of the illumination intensity. This paper proposes retinal blood vessel extraction using background estimation. The estimated background is calculated by using a weight surface fitting method with a high degree polynomial. Bright pixels are defined as unwanted data and are set as zero in a weight matrix. To fit a retinal surface with a higher degree polynomial, fundus images are reduced in size by different scaling parameters in order to reduce the processing time and complexity in calculation. The estimated background is then removed from the original image. The candidate vessel pixels are extracted from the image by using the local threshold values. To identify the true vessel region, the candidate vessel pixels are dilated from the candidate. After that, the active contour without edge method is applied. The experimental results show that the efficiency of the proposed method is higher than the conventional low-pass filter and the conventional surface fitting method. Moreover, rescaling an image down using the scaling parameter at 0.25 before background estimation provides as good a result as a non-rescaled image does. The correlation value between the non-rescaled image and the rescaled image is 0.99. The results of the proposed method in the sensitivity, the specificity, the accuracy, the area under the receiver operating characteristic (ROC) curve (AUC) and the processing time per image are 0.7994, 0.9717, 0.9543, 0.9676 and 1.8320 seconds for the DRIVE database respectively.

Recently, a next-generation heterodyne mixer detector---a hot electron bolometer (HEB) mixer employing a superconducting microbridge---has gradually opened up terahertz-band astronomy. The surrounding state-of-the-art technologies including fabrication processes, 4 K cryostats, cryogenic low-noise amplifiers, local oscillator sources, micromachining techniques, and spectrometers, as well as the HEB mixers, have played a valuable role in the development of super-low-noise heterodyne spectroscopy systems for the terahertz band. The current developmental status of terahertz-band HEB mixer receivers and their applications for spectroscopy and astronomy with ground-based, airborne, and satellite telescopes are presented.

We report the fabrication of magnetic metallic contaminant detectors using multiple high-Tc SQUIDs (superconducting quantum interference devices) for a lithium-ion battery cathode sheet. Finding ultra-small metallic foreign matter is an important issue for a manufacturer because metallic contaminants carry the risk of an internal short. When contamination occurs, the manufacturer of the product suffers a great loss from recalling the tainted product. Hence, a detection method of small contaminants is required. Preventing such accidents is also an important issue for manufacturers of industrial products. Given the lower detection limit for practical X-ray usage is in the order of 1 mm, a detection system using a SQUID is a more powerful tool for sensitive inspections. We design and set up an eight-channel roll-to-roll high-Tc dc-SQUID inspection system for a lithium ion battery cathode sheet. We report the evaluation results that the detection of a small $arphi $18,-$mu $m steel particle on a lithium-ion battery cathode sheet was successfully done.

In this letter, we present a method for automatic mura detection for display film using the efficient decision of cut-off frequency with DCT and mask filtering with wavelet transform. First, the background image including reflected light is estimated using DCT with adaptive cut-off frequency, and DWT is applied to background-removed images for generating mura mask. Then, a mura mask is generated by separating low-frequency noise in the approximation coefficients. Lastly, mura is detected by applying mura mask filtering to the detail coefficients. According to the comparison by Semu index, the results from the proposed method are superior to those from the existing methods. This indicates that the proposed method is high in reliability.

In this paper, we present new methods for learning the individual patterns of a card user's transaction amount and the region in which he or she uses the card, for a given period, and for determining whether the specified transaction is allowable in accordance with these learned user transaction patterns. Then, we classify legitimate transactions and fraudulent transactions by setting thresholds based on the learned individual patterns.

Since the birth of astrophysics, astronomers have been using free-space optics to analyze light falling on Earth. In the future however, thanks to the advances in photonics and nanoscience/nanotechnology, much of the manipulation of light might be carried out using not optics but confined waveguides, or circuits, on a chip. This new generation of instruments will be not only extremely compact, but also powerful in performance because the integration enables a greater degree of multiplexing. The benefit is especially profound for space- or air-borne observatories, where size, weight, and mechanical reliability are of top priority. Recently, several groups around the world are trying to integrate ultra-wideband (UWB), low-resolution spectrometers for millimeter-submillimeter waves onto microchips, using superconducting microelectronics. The scope of this Paper is to provide a general introduction and a review of the state-of-the-art of this rapidly advancing field.

As semiconductor devices scale into deep sub-micron regime, the reliability issue due to radiation-induced soft errors increases in on-chip memory systems. Neutron-induced soft errors transiently upset adjacent information of multiple cells in these systems. Although single error correction and double error detection (SEC--DED) codes have been employed to protect on-chip memories from soft errors, they are not sufficient against multiple cell upsets (MCUs). SEC--DED and double adjacent error correction (SEC--DED--DAEC) codes have recently been proposed to address this problem. However, these codes do not the resolve mis-correction of double non-adjacent errors because syndromes for double non-adjacent errors are equal to that of double adjacent errors. The occurrence of this mis-correction in region of critical memory section such as operating systems may lead to system malfunction. To eliminate mis-correction, the syndrome spaces for double adjacent and double non-adjacent errors are not shared using the matrix with reversed colexicographic order. The proposed codes are implemented using hardware description language and synthesized using 32 nm technology library. The results show that there is no mis-correction in the proposed codes. In addition, the performance enhancement of the decoder is approximately 51.9% compared to double error correction codes for on-chip memories. The proposed SEC--DED--DAEC codes is suitable for protecting on-chip memory applications from MCUs-type soft errors.

This paper develops the double generating function method for the discrete-time linear quadratic optimal control problem. This method can give generators for optimal solutions only in terms of pre-computed coefficients and boundary conditions, which is useful for the on-line repetitive computation for different boundary conditions. Moreover, since each generator contains inverse terms, the invertibility analysis is also performed to conclude that the terms in the generators constructed by double generating functions with opposite time directions are invertible under some mild conditions, while the terms with the same time directions will become singular when the time goes infinity which may cause instability in numerical computations. Examples demonstrate the effectiveness of the developed method.

Superconducting tunnel junction (STJ) array detectors can exhibit excellent performance with respect to energy resolution, detection efficiency, and counting rate in the soft X-ray energy range, by which those excellent properties STJ array detectors are well suited for detecting X-rays at synchrotron radiation facilities. However, in order to achieve a high throughput analysis for trace impurity elements such as dopants in structural or functional materials, the sensitive area of STJ array detectors should be further enlarged up to more than 10 times larger by increasing the pixel number in array detectors. In this work, for a large STJ-pixel number of up to 1000 within a 10,mm- square compact chip, we have introduced three-dimensional (3D) structure by embedding a wiring layer in a SiO$_{2}$ isolation layer underneath a base electrode layer of STJs. The 3D structure is necessary for close-packed STJ arrangement, avoiding overlay of lead wiring, which is common in conventional two-dimensional layout. The fabricated STJ showed excellent current-voltage characteristics having low subgap currents less than 2,nA, which are the same as those of conventional STJs. An STJ pixel has an energy resolution of 31,eV (FWHM) for C-K$alpha $ (277,eV).

During the investment process for enhancing the level of IT security, organizations typically rely on two kinds of security countermeasures, i.e., proactive security countermeasures (PSCs) and reactive security countermeasures (RSCs). The PSCs are known to prevent security incidents before their occurrence, while the RSCs identify security incidents and recover the damaged hardware and software during or after their occurrence. Some researchers studied the effect of the integration of PSCs and RSCs, and showed that the integration can control unwanted incidents better than a single type of security countermeasure. However, the studies were made mostly in a qualitative manner, not in a quantitative manner. In this paper, we focus on deriving a quantitative model that analyzes the influence of different conditions on the efficiency of the integrated security countermeasures. Using the proposed model, we analyze for the first time how vulnerability and the potential exploits resulting from such vulnerability can affect the efficiency of the integrated security countermeasures; furthermore, we analytically verify that as the efficiency of PSCs increases, the burden of RSCs decreases, and vice versa. Also, we describe how to select possibly optimal configurations of the integrated security countermeasures.

In this letter, we give a trace representation of binary Jacobi sequences with period pq over an extension field of the odd prime field Fr. Our method is based on the use of a pqth root of unity over the extension field, and the representation of the Jacobi sequences by corresponding indicator functions and quadratic characters of two primes p and q.