A readout technique using single-flux-quantum (SFQ) circuits enables superconducting single photon detectors (SSPDs) to operate at further high-speed, where a mutually-coupled dc-to-SFQ (MC-dc/SFQ) converter is used as an interface between SSPDs and SFQ circuits. In this work, we investigated pulse response of the MC-dc/SFQ converter. We employed on-chip pulse generators to evaluate pulse response of the MC-dc/SFQ converter for various pulses. The MC-dc/SFQ converter correctly operated for the pulse current with the amplitude of 52,$mu$A and the width of 179,ps. In addition, we examined influence of the pulse amplitude and width to operation of the MC-dc/SFQ converter by numerical simulation. The simulation results indicated that the MC-dc/SFQ converter had wide operation margins for pulse current with amplitudes of 30--60,$mu$A irrespective of the pulse widths.

Recently, Gan and Luo have proposed a direction-of-arrival estimation method for uncorrelated and coherent signals in the presence of multipath propagation [3]. In their method, uncorrelated and coherent signals are distinguished by rotational invariance techniques and the property of the moduli of eigenvalues. However, due to the limitation of finite number of sensors, the pseudo-inverse matrix derived in this method is an approximate one. When the number of sensors is small, the approximation error is large, which adversely affects the property of the moduli of eigenvalues. Consequently, the method in [3] performs poorly in identifying uncorrelated signals under such circumstance. Moreover, in cases of small number of snapshots and low signal to noise ratio, the performance of their method is poor as well. Therefore, in this letter we first study the approximation in [3] and then propose an improved method that performs better in distinguishing between uncorrelated signals and coherent signals and in the aforementioned two cases. The simulation results demonstrate the effectiveness and efficiency of the proposed method.

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.

Based on the work by Helleseth [1], for an odd prime p and an even integer n=2m, the cross-correlation values between two decimated m-sequences by the decimation factors 2 and 4pn/2-2 are derived. Their cross-correlation function is at most 4-valued, that is, $igg {rac{-1 pm p^{n/2}}{2}, rac{-1 + 3p^{n/2}}{2}, rac{-1 + 5p^{n/2}}{2} igg }$. From this result, for pm ≠ 2 mod 3, a new sequence family with family size 4N and the maximum correlation magnitude upper bounded by $rac{-1 + 5p^{n/2}}{2} simeq rac{5}{sqrt{2}}sqrt{N}$ is constructed, where $N = rac{p^n-1}{2}$ is the period of sequences in the family.

The minimum biclique cover problem is known to be NP-hard for general bipartite graphs. It can be solved in polynomial time for C4-free bipartite graphs, bipartite distance hereditary graphs and bipartite domino-free graphs. In this paper, we define the modified Galois lattice Gm(B) for a bipartite graph B and introduce the redundant parameter R(B). We show that R(B)=0 if and only if B is domino-free. Furthermore, for an input graph such that R(B)=1, we show that the minimum biclique cover problem can be solved in polynomial time.

In this paper, we propose a framework for the real-time estimation of a multidimensional QoE of Multi-View Video and Audio (MVV-A) IP transmission. The framework utilizes linear multiple regression analysis with application-level and transport-level QoS parameters which can be measured in real time. In order to cope with a variety of MVV-A usage-situations, we introduce the concept of usage-situation type for grouping usage-situations with similar features to apply a representative regression line. We deal with two contents, two camera arrangements, and two user interfaces for viewpoint change as representative examples of the usage-situations. We assess multidimensional QoE of MVV-A with various types of average load, playout buffering time, and delay in the network. We then conduct the multiple regression analysis for the multidimensional QoE values represented by a psychological scale. From the comparison of measured values and estimated ones, we notice that real-time estimation of QoE is feasible in MVV-A IP transmission.

This letter deals with the carrier frequency offsets (CFO) estimation problem for orthogonal frequency division multiple access (OFDMA) uplink systems. Combined with centro-symmetric (CS) trimmed autocorrelation matrix and weighting subspace projection, the proposed estimator has better estimate performance than MVDR, MUSIC, CS-MUSIC, and ESPRIT estimators, especially in relatively less of OFDMA blocks and low SNR situations. Simulation results are presented to verify the efficiency of the proposed estimator.

FOX is a family of block ciphers published in 2004 and is famous for its provable security to cryptanalysis. In this paper, we present multiple 4-round impossible differentials and several new results of impossible differential attacks on 5,6,7-round FOX64 and 5-round FOX128 with the multiple differentials and the new early abort technique which shall reduce the data complexity and the time complexity respectively. In terms of the data complexity and the time complexity, our results are better than any of the previously known attacks.

Optical coherence tomography using a tunable single-mode laser is investigated to clarify the effects of long coherence length and step-wise frequency changes.

Recently, hue-preserving color image enhancement methods have been proposed by several researchers. However, the theoretical comparison of the performance of their methods has not been conducted yet. In this paper, we propose a hue-preserving saturation maximization method, and show a relationship of the saturation of enhanced colors by related methods. We also demonstrate the correctness of the relationship experimentally.

A narrowband interference (NBI) estimation and mitigation method based on compressive sensing (CS) for communication systems with repeated training sequences is investigated in this letter. The proposed CS-based differential measuring method is performed through the differential operation on the inter-block-interference-free regions of the received adjacent training sequences. The sparse NBI signal can be accurately recovered from a time-domain measurement vector of small size under the CS framework, without requiring channel information or dedicated resources. Theoretical analysis and simulation results show that the proposed method is robust to NBI under multi-path fading channels.

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.

We are developing a fast Fourier transform (FFT) processor using high-speed and low-power single-flux-quantum (SFQ) circuits. Our main concern is the development of an SFQ butterfly processing circuit, which is the core processing circuit in the FFT processor. In our previous study, we have confirmed the complete operation of an integer-type butterfly processing circuit using the AIST 2.5 kA/cm$^{2}$ Nb standard process at the frequency of 25 GHz. In this study, we have designed an integer-type butterfly processing circuit using the AIST 10,kA/cm$^{2}$,Nb advanced process and confirmed its high-speed operation at the maximum frequency of 50,GHz.

This paper discusses the decidability of node query preservation problems for tree transducers. We assume a transformation given by a deterministic linear top-down data tree transducer (abbreviated as DLTV) and an n-ary query based on runs of a tree automaton. We say that a DLTV Tr strongly preserves a query Q if there is a query Q' such that for every tree t, the answer set of Q' for Tr(t) is equal to the answer set of Q for t. We also say that Tr weakly preserves Q if there is a query Q' such that for every t, the answer set of Q' for Tr(t) includes the answer set of Q for t. We show that the weak preservation problem is coNP-complete and the strong preservation problem is in 2-EXPTIME. We also show that the problems are decidable when a given transducer is a functional extended linear top-down data tree transducer with regular look-ahead, which is a more expressive transducer than DLTV.

In the big data era, messaging systems are required to process large volumes of message traffic with high scalability and availability. However, conventional systems have two issues regarding availability. The first issue is that failover processing itself has a risk of failure. The second issue is to find a trade-off between consistency and availability. We propose a resilient messaging system based on a distributed in-memory key-value store (KVS). Its servers are interconnected with each other and messages are distributed to multiple servers in normal processing state. This architecture can continue messaging services wherever in the messaging system server/process failures occur without using failover processing. Furthermore, we propose two methods for improved resilience: the round-robin method with a slowdown KVS exclusion and the two logical KVS counter-rotating rings to provide short-term-availability in the messaging system. Evaluation results demonstrate that the proposed system can continue service without failover processing. Compared with the conventional method, our proposed distribution method reduced 92% of error responses to clients caused by server failures.

In this letter, we propose a novel Uniformity-Approximated Histogram Equalization (UAHE) algorithm to enhance the image as well as to preserve the image features. First, the UAHE algorithm generates the image histogram and computes the average value of all bins as the histogram threshold. In order to approximate the uniform histogram, the bins of image histograms greater than the above threshold are clipped, and the subtracted counts are averaged and uniformly assigned to the remaining bins lower than the threshold. The approximated uniform histogram is then applied to generate the intensity transformation function for image contrast enhancement. Experimental results show that our algorithm achieves the maximum entropy as well as the feature similarity values for image contrast enhancement.

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.

Robust yet efficient techniques for detecting and tracking targets in infrared (IR) images are a significant component of automatic target recognition (ATR) systems. In our previous works, we have proposed infrared target detection and tracking systems based on sparse representation method. The proposed infrared target detection and tracking algorithms are based on sparse representation and Bayesian probabilistic techniques, respectively. In this paper, we adopt Naïve Bayes Nearest Neighbor (NBNN) that is an extremely simple, efficient algorithm that requires no training phase. State-of-the-art image classification techniques need a comprehensive learning and training step (e.g., using Boosting, SVM, etc.) In contrast, non-parametric Nearest Neighbor based image classifiers need no training time and they also have other more advantageous properties. Results of tracking in infrared sequences demonstrated that our algorithm is robust to illumination changes, and the tracking algorithm is found to be suitable for real-time tracking of a moving target in infrared sequences and its performance was quite good.

This paper proposes a novel scheme for sequential orthogonal frequency division multiplexing channel estimation on the receiver side.The scheme comprises two methods: one improves estimation accuracy and the other reduces computational complexity. Based on a state-space model, the first method appropriately considers frequency correlation in an approach that derives a narrow-band channel gain for multiple pilot subcarriers; such consideration of frequency correlation leads to an averaging effect in the frequency domain. The second method is based on the first one and forces the observation matrix into a sparse bidiagonal matrix in order to decrease the number of mathematical processes. The proposed scheme is verified by numerical analysis.

Least squares error (LSE) method adopted recursively can be used to track the frequency and amplitude of signals in steady states and kinds of non-steady ones in power system. Taylor expansion is used to give another version of this recursive LSE method. Aided by variable-windowed short-time discrete Fourier transform, recursive LSEs with and without Taylor expansion converge faster than the original ones in the circumstance of off-nominal input singles. Different versions of recursive LSE were analyzed under various states, such as signals of off-nominal frequency with harmonics, signals with step changes, signals modulated by a sine signal, signals with decaying DC offset and additive Gaussian white noise. Sampling rate and data window size are two main factors influencing the performance of method recursive LSE in transient states. Recursive LSE is sensitive to step changes of signals, but it is in-sensitive to signals' modulation and singles with decaying DC offset and noise.