Multi-slot information extraction, also known as frame extraction, is a task that identify several related entities simultaneously. Most researches on this task are concerned with applying IE patterns (rules) to extract related entities from unstructured documents. An important obstacle for the success in this task is unknowing where text portions containing interested information are. This problem is more complicated when involving languages with sentence boundary ambiguity, e.g. the Thai language. Applying IE rules to all reasonable text portions can degrade the effect of this obstacle, but it raises another problem that is incorrect (unwanted) extractions. This paper aims to present a method for removing these incorrect extractions. In the method, extractions are represented as intuitionistic fuzzy sets, and a similarity measure for IFSs is used to calculate distance between IFS of an unclassified extraction and that of each already-classified extraction. The concept of k nearest neighbor is adopted to design whether the unclassified extraction is correct or not. From the experiment on various domains, the proposed technique improves extraction precision while satisfactorily preserving recall.

The step size is a parameter of fundamental importance in learning algorithms, particularly for the natural policy gradient (NPG) methods. We derive an upper bound for the step size in an incremental NPG estimation, and propose an adaptive step size to implement the derived upper bound. The proposed adaptive step size guarantees that an updated parameter does not overshoot the target, which is achieved by weighting the learning samples according to their relative importances. We also provide tight upper and lower bounds for the step size, though they are not suitable for the incremental learning. We confirm the usefulness of the proposed step size using the classical benchmarks. To the best of our knowledge, this is the first adaptive step size method for NPG estimation.

A free-viewpoint application has been developed that yields an immersive user experience. One of the simple free-viewpoint approaches called “billboard methods” is suitable for displaying a synthesized 3D view in a mobile device, but it suffers from the limitation that a billboard should be positioned in only one position in the world. This fact gives users an unacceptable impression in the case where an object being shot is situated at multiple points. To solve this problem, we propose optimal deformation of the billboard. The deformation is designed as a mapping of grid points in the input billboard silhouette to produce an optimal silhouette from an accurate voxel model of the object. We formulate and solve this procedure as a nonlinear optimization problem based on a grid-point constraint and some a priori information. Our results show that the proposed method generates a synthesized virtual image having a natural appearance and better objective score in terms of the silhouette and structural similarity.

The-state-of-the-art neural quality estimation (QE) of machine translation model consists of two sub-networks that are tuned separately, a bidirectional recurrent neural network (RNN) encoder-decoder trained for neural machine translation, called the predictor, and an RNN trained for sentence-level QE tasks, called the estimator. We propose to combine the two sub-networks into a whole neural network, called the unified neural network. When training, the bidirectional RNN encoder-decoder are initialized and pre-trained with the bilingual parallel corpus, and then, the networks are trained jointly to minimize the mean absolute error over the QE training samples. Compared with the predictor and estimator approach, the use of a unified neural network helps to train the parameters of the neural networks that are more suitable for the QE task. Experimental results on the benchmark data set of the WMT17 sentence-level QE shared task show that the proposed unified neural network approach consistently outperforms the predictor and estimator approach and significantly outperforms the other baseline QE approaches.

When the automated driving cars are in widespread usage, traffic will coexist with prioritized vehicles (e.g., ambulances, fire trucks, police vehicles) and automated driving cars. Automated driving cars are expected to be safer and lower stress than manual driving vehicles because of passengers paying less attention to driving. However, there are many challenges for automated driving cars to get along with surrounding transport participants. In particular, when an ambulance is driving into an intersection with the red traffic signal, the automated driving car is required to deal with a situation differently from normal traffic situations. In order to continue safe driving, it is necessary to recognize the approach of the ambulance at an earlier time. Possible means of recognizing ambulances include siren sound, rotating red lights and vehicle to vehicle communication. Based on actual traffic data, the authors created a mathematical model of deceleration for giving way and consider the status of suitable behavior by automated driving cars. The authors calculate the detection distance required to take suitable action. The results indicate that there are advantages in vehicle to vehicle communication in detecting ambulances by automated driving cars.

Motorcycles are driven in a road widely but must be driven carefully because they are easily damaged by obstacles, bumps or potholes in the road. Thus, motorcycle trajectories are valuable for detecting road abnormalities. The trajectories are usually obtained from GPS (Global Positioning System). However, errors often occur in GPS positioning. In this research, we will present a detection idea of the GPS error based on behavior estimation of riders. Moreover, we will propose a novel behavior estimation method.

A term is a connected acyclic graph (unrooted unordered tree) pattern with structured variables, which are ordered lists of one or more distinct vertices. A variable of a term has a variable label and can be replaced with an arbitrary tree by hyperedge replacement according to the variable label. The dimension of a term is the maximum number of vertices in the variables of it. A term is said to be linear if each variable label in it occurs exactly once. Let T be a tree and t a linear term. In this paper, we study the graph pattern matching problem (GPMP) for T and t, which decides whether or not T is obtained from t by replacing variables in t with some trees. First we show that GPMP for T and t is NP-complete if the dimension of t is greater than or equal to 4. Next we give a polynomial time algorithm for solving GPMP for a tree of bounded degree and a linear term of bounded dimension. Finally we show that GPMP for a tree of arbitrary degree and a linear term of dimension 2 is solvable in polynomial time.

The energy of a threshold circuit C is defined to be the maximum number of gates outputting ones for an input assignment, where the maximum is taken over all the input assignments. In this paper, we study computational power of threshold circuits of energy at most two. We present several results showing that the computational power of threshold circuits of energy one and the counterpart of energy two are remarkably different. In particular, we give an explicit function which requires an exponential size for threshold circuits of energy one, but is computable by a threshold circuit of size just two and energy two. We also consider MOD functions and Generalized Inner Product functions, and show that these functions also require exponential size for threshold circuits of energy one, but are computable by threshold circuits of substantially less size and energy two.

The concept of threshold public key encryption (TPKE) with the special property called key re-splittability (re-splittable TPKE, for short) was introduced by Hanaoka et al. (CT-RSA 2012), and used as one of the building blocks for constructing their proxy re-encryption scheme. In a re-splittable TPKE scheme, a secret key can be split into a set of secret key shares not only once, but also multiple times, and the security of the TPKE scheme is guaranteed as long as the number of corrupted secret key shares under the same splitting is smaller than the threshold. In this paper, we show several new constructions of a re-splittable TPKE scheme by extending the previous (ordinary) TPKE schemes. All of our proposed schemes are based on discrete logarithm (DL)-type assumptions. Therefore, our results suggest that key re-splittability is a very natural property for DL-type TPKE schemes.

Multisignatures are digital signatures for a group consisting of multiple signers where each signer signs common documents via interaction with its co-signers and the data size of the resultant signatures for the group is independent of the number of signers. In this work, we propose a multisignature scheme, whose security can be tightly reduced to the CDH problem in bilinear groups, in the strongest security model where nothing more is required than that each signer has a public key, i.e., the plain public key model. Loosely speaking, our main idea for a tight reduction is to utilize a three-round interaction in a full-domain hash construction. Namely, we surmise that a full-domain hash construction with three-round interaction will become tightly secure under the CDH problem. In addition, we show that the existing scheme by Zhou et al. (ISC 2011) can be improved to a construction with a tight security reduction as an application of our proof framework.

Card-based cryptographic protocols provide secure multi-party computations using a deck of physical cards. The most important primitive of those protocols is the shuffling operation, and most of the existing protocols rely on uniform cyclic shuffles (such as the random cut and random bisection cut) in which each possible outcome is equally likely and all possible outcomes constitute a cyclic subgroup. However, a couple of protocols with non-uniform and/or non-cyclic shuffles were proposed by Koch, Walzer, and Härtel at Asiacrypt 2015. Compared to the previous protocols, their protocols require fewer cards to securely produce a hidden AND value, although to implement of such unconventional shuffles appearing in their protocols remains an open problem. This paper introduces “pile-shifting scramble,” which can be a secure implementation of those shuffles. To implement such unconventional shuffles, we utilize physical cases that can store piles of cards, such as boxes and envelopes. Therefore, humans are able to perform the shuffles using these everyday objects. Furthermore, we show that a certain class of non-uniform and/or non-cyclic shuffles having two possible outcomes can be implemented by the pile-shifting scramble. This also implies that we can improve upon the known COPY protocol using three card cases so that the number of cases required can be reduced to two.

Kreyvium is a NLFSR-based stream cipher which is oriented to homomorphic-ciphertext compression. This is a variant of Trivium with 128-bit security. Designers have evaluated the security of Kreyvium and concluded that the resistance of Kreyvium to the conditional differential cryptanalysis is at least the resistance of Trivium, and even better. However, we consider that this attack is effective for reduced Kreyvium due to the structure of it. This paper shows the conditional differential cryptanalysis for Kreyvium, and we propose distinguishing and key recovery attacks. We show how to arrange differences and conditions to obtain good higher-order conditional differential characteristics. We use two types of higher-order conditional differential characteristics to find a distinguisher, e.g. the bias of higher-order conditional differential characteristics of a keystream and the probabilistic bias of them. In the first one, we obtain the distinguisher on Kreyvium with 730 rounds from 20-th order characteristics. In the second one, we obtain the distinguisher on Kreyvium with 899 rounds from 25-th order conditional differential characteristics. Moreover, we show the key recovery attack on Kreyvium with 736 rounds from 20-th order characteristics. We experimentally confirm all our attacks. The second distinguisher shows that we can obtain the distinguisher on Kreyvium with more rounds than the distinguisher on Trivium. Therefore, Kreyvium has a smaller security margin than Trivium for the conditional differential cryptanalysis.

Image quality assessment (IQA) is an inherent problem in the field of image processing. Recently, deep learning-based image quality assessment has attracted increased attention, owing to its high prediction accuracy. In this paper, we propose a fully-blind and fast image quality predictor (FFIQP) using convolutional neural networks including two strategies. First, we propose a distortion clustering strategy based on the distribution function of intermediate-layer results in the convolutional neural network (CNN) to make IQA fully blind. Second, by analyzing the relationship between image saliency information and CNN prediction error, we utilize a pre-saliency map to skip the non-salient patches for IQA acceleration. Experimental results verify that our method can achieve the high accuracy (0.978) with subjective quality scores, outperforming existing IQA methods. Moreover, the proposed method is highly computationally appealing, achieving flexible complexity performance by assigning different thresholds in the saliency map.

Electrical contacts are separated at constant speed and break arcs are generated in nitrogen or air in a 200V-450VDC/10A resistive circuit. The break arcs are extinguished by magnetic blow-out. Arc duration for the silver and copper contact pairs is investigated for each supply voltage. Following results are shown. The arc duration for Cu contacts in nitrogen is the shortest. For Cu contacts, the arc dwell time in air was considerably longer than that of nitrogen. For Ag contacts, the arc duration in nitrogen was almost the same as that in air.

In small-aperture high frequency surface wave radar, the main-lobe clutter all can be seen as a more severe space spread clutter under the influence of the smaller array aperture. It compromises the detection performance of moving vessels, especially when the target is submerged in the clutter. To tackle this issue, an improved spread clutter estimated canceller, combining spread clutter estimated canceller, adaptive selection strategy of the optimal training samples and rotating spatial beam method, is presented to suppress main-lobe clutter in both angle domain and range domain. According to the experimental results, the proposed algorithm is shown to have far superior clutter suppression performance based on the real data.

The output feedback consensus problem of nonlinear multi-agent systems under a directed network with a time varying communication delay is studied. In order to deal with this problem, the dynamic output feedback controller with an additional low gain parameter that compensates for the effect of nonlinearity and a communication delay is proposed. Also, it is shown that under some assumptions, the proposed controller can always solve the output feedback consensus problem even in the presence of an arbitrarily large communication delay.

High-performance Network Over Coax, or HINOC for short, is a broadband access technology that can achieve bidirectional transmission for high-speed Internet service through a coaxial medium. In HINOC access networks, buffer management scheme can improve the fairness of buffer usage among different output ports and the overall loss performance. To provide different services to multiple priority classes while reducing the overall packet loss rate and ensuring fairness among the output ports, this study proposes a QoS optimization method for access networks. A backpressure-based queue threshold control scheme is used to minimize the weighted average packet loss rate among multiple priorities. A theoretical analysis is performed to examine the performance of the proposed scheme, and optimal system parameters are provided. Software simulation shows that the proposed method can improve the average packet loss rate by about 20% to 40% compared with existing buffer management schemes. Besides, FPGA evaluation reveals that the proposed method can be implemented in practical hardware and performs well in access networks.

We consider a device-to-device (D2D) underlaid cellular network where D2D communications are allowed to share the same radio spectrum with cellular uplink communications for improving spectral efficiency. However, to protect the cellular uplink communications, the interference level received at a base station (BS) from the D2D communications needs to be carefully maintained below a certain threshold, and thus the BS coordinates the transmit power of the D2D links. In this paper, we investigate on-off power control for the D2D links, which is known as a simple but effective technique due to its low signaling overhead. We first investigate the optimal on-off power control algorithm to maximize the sum-rate of the D2D links, while satisfying the interference constraint imposed by the BS. The computational complexity of the optimal algorithm drastically increases with D2D link number. Thus, we also propose an on-off power control algorithm to significantly reduce the computational complexity, compared to the optimal on-off power control algorithm. Extensive simulations validate that the proposed algorithm significantly reduces the computational complexity with a marginal sum-rate offset from the optimal algorithm.

For general multiple-input multiple-output (MIMO) interference networks, determining the feasibility conditions of interference alignment (IA) to achieve the maximum degree of freedom (DoF), is tantamount to accessing the maximum spatial resource of MIMO systems. In this paper, from the view of antenna configuration, we first explore the IA feasibility in the K-user MIMO interference channel (IC), G-cell MIMO interference broadcast channel (IBC) and interference multiple access channel (IMAC). We first give the concept of the equalized antenna, and all antenna configurations are divided into two categories, equalized antennas and non-equalized ones. The feasibility conditions of IA system with equalized antennas are derived, and the feasible and infeasible regions are provided. Furthermore, we study the correlations among IC, IBC and IMAC. Interestingly, the G-cell MIMO IBC and IMAC are two special ICs, and a systemic work on IA feasibility for these three interference channels is provided.

The micro-mechanism of molten pool and metal droplet sputtering are significant to the material erosion caused by breaking or making arcs especially for high-power switching devices. In this paper, based on Navier-Stokes equations for incompressible viscous fluid and potential equation for electric field, a 2D axially symmetric simplified hydrodynamic model was built to describe the formation of the molten metal droplet sputtering and molten pool under arc spot near electrode region. The melting process was considered by the relationship between melting metal volumetric percentage and temperature, a free surface of liquid metal deformation was solved by coupling moving mesh and the automatic re-meshing. The simulated metal droplet sputtering and molten pool behaviors are presented by the temperature and velocity distribution sequences. The influence mechanism of pressure distribution and heat flux on the formation of molten pool and metal droplet sputtering has been analyzed according to the temperature distribution and sputtering angles. Based on the simulation results, we can distinguish two different models of the molten metal droplet sputtering process: edge ejection and center ejection. Moreover, a new explanation is proposed based on calculated results with arc spot pressure distribution in the form of both unimodal and bimodal. It shows that the arc spot pressure distribution plays an important role in the metal droplet ejected from molten pool, the angle of the molten jet drop can be decreased along with the increment of the arc spot pressure.