We consider space time block coded-continuous phase modulation (STBC-CPM), which has the advantages of both STBC and CPM at the same time. A weak point of STBC-CPM is that the normalized spectral efficiency (NSE) is limited by the orthogonality of the STBC and CPM parameters. The purpose of this study is to improve the NSE of STBC-CPM. The NSE depends on the transmission rate (TR), the bit error rate (BER) and the occupied bandwidth (OBW). First, to improve the TR, we adapt quasi orthogonal-STBC (QO-STBC) for four transmit antennas and quasi-group orthogonal Toeplitz code (Q-GOTC) for eight transmit antennas, at the expense of the orthogonality. Second, to evaluate the BER, we derive a BER approximation of STBC-CPM with non-orthogonal STBC (NO-STBC). The theoretical analysis and simulation results show that the NSE can be improved by using QO-STBC and Q-GOTC. Third, the OBW depends on CPM parameters, therefore, the tradeoff between the NSE and the CPM parameters is considered. A computer simulation provides a candidate set of CPM parameters which have better NSE. Finally, the adaptation of non-orthogonal STBC to STBC-CPM can be viewed as a generalization of the study by Silvester et al., because orthogonal STBC can be thought of as a special case of non-orthogonal STBC. Also, the adaptation of Q-GOTC to CPM can be viewed as a generalization of our previous letter, because linear modulation scheme can be thought of as a special case of non-linear modulation.

The main purpose of Codemark is to distribute digital contents using offline media. Due to the main purpose of Codemark, Codemark cannot be used on digital images. It has high robustness on only printed images. This paper presents a new color code called Robust Index Code (RIC for short), which has high robustness on JPEG Compression and Resize targeting digital images. RIC embeds a remote database index to digital images so that users can reach to any digital contents. Experimental results, using our implemented RIC encoder and decoder, have shown high robustness on JPEG Comp. and Resize of the proposed codemark. The embedded database indexes can be extracted 100% on compressed images to 30%. In conclusion, it is able to store all the type of digital products by embedding indexes into digital images to access database, which means it makes a Superdistribution system with digital images realized. Therefore RIC has the potential for new Internet image services, since all the images encoded by RIC are possible to access original products anywhere.

MICKEY-family ciphers are lightweight cryptographic primitives and include a register R determined by two related maximal-period linear transformations. Provided that primitivity is efficiently decided in finite fields, it is shown by quantitative analysis that potential parameters for R can be found in probabilistic polynomial time.

We discuss Nash equilibria in combinatorial auctions with item bidding. Specifically, we give a characterization for the existence of a Nash equilibrium in a combinatorial auction with item bidding when valuations by n bidders satisfy symmetric and subadditive properties. By this characterization, we can obtain an algorithm for deciding whether a Nash equilibrium exists in such a combinatorial auction.

Saliency detection for videos has been paid great attention and extensively studied in recent years. However, various visual scene with complicated motions leads to noticeable background noise and non-uniformly highlighting the foreground objects. In this paper, we proposed a video saliency detection model using spatio-temporal cues. In spatial domain, the location of foreground region is utilized as spatial cue to constrain the accumulation of contrast for background regions. In temporal domain, the spatial distribution of motion-similar regions is adopted as temporal cue to further suppress the background noise. Moreover, a backward matching based temporal prediction method is developed to adjust the temporal saliency according to its corresponding prediction from the previous frame, thus enforcing the consistency along time axis. The performance evaluation on several popular benchmark data sets validates that our approach outperforms existing state-of-the-arts.

High Efficiency Video Coding (HEVC) has a better coding efficiency comparing with H.264/AVC. However, performance enhancement results in increased computational complexity which is mainly brought by the quadtree based coding tree unit (CTU). In this paper, an early termination algorithm based on AdaBoost classifier for coding unit (CU) is proposed to accelerate the process of searching the best partition for CTU. Experiment results indicate that our method can save 39% computational complexity on average at the cost of increasing Bjontegaard-Delta rate (BD-rate) by 0.18.

Association rule mining discovers relationships among variables in a data set, representing them as rules. These are expected to often have predictive abilities, that is, to be able to predict future events, but commonly used rule interestingness measures, such as support and confidence, do not directly assess their predictive power. This paper proposes a cross-validation -based metric that quantifies the predictive power of such rules for characterizing software defects. The results of evaluation this metric experimentally using four open-source data sets (Mylyn, NetBeans, Apache Ant and jEdit) show that it can improve rule prioritization performance over conventional metrics (support, confidence and odds ratio) by 72.8% for Mylyn, 15.0% for NetBeans, 10.5% for Apache Ant and 0 for jEdit in terms of SumNormPre(100) precision criterion. This suggests that the proposed metric can provide better rule prioritization performance than conventional metrics and can at least provide similar performance even in the worst case.

Electronic payment protocols provide secure service for electronic commerce transactions and protect private information from malicious entities in a network. Formal methods have been introduced to verify the security of electronic payment protocols; however, these methods concentrate on the accountability and fairness of the protocols, without considering the impact caused by timeliness. To make up for this deficiency, we present a formal method to analyze the security properties of electronic payment protocols, namely, accountability, fairness and timeliness. We add a concise time expression to an existing logical reasoning method to represent the event time and extend the time characteristics of the logical inference rules. Then, the Netbill protocol is analyzed with our formal method, and we find that the fairness of the protocol is not satisfied due to the timeliness problem. The results illustrate that our formal method can analyze the key properties of electronic payment protocols. Furthermore, it can be used to verify the time properties of other security protocols.

Review rating prediction is an important problem in machine learning and data mining areas and has attracted much attention in recent years. Most existing methods for review rating prediction on Location-Based Social Networks only capture the semantics of texts, but ignore user information (social links, geolocations, etc.), which makes them less personalized and brings down the prediction accuracy. For example, a user's visit to a venue may be influenced by their friends' suggestions or the travel distance to the venue. To address this problem, we develop a review rating prediction framework named TSG by utilizing users' review Text, Social links and the Geolocation information with machine learning techniques. Experimental results demonstrate the effectiveness of the framework.

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.

Optical interconnect is a promising candidate for network on chip. As the key element in the network on chip, the routers greatly affect the performance of the whole system. In this letter, we proposed a new router architecture, Waffle, based on compact 2×2 hybrid photonic-plasmonic switching elements. Also, an optimized architecture, Waffle-XY, was designed for the network employed XY routing algorithm. Both Waffle and Waffle-XY are strictly non-blocking architectures and can be employed in the popular mesh-like networks. Theoretical analysis illustrated that Waffle and Waffle-XY possessed a better performance compared with several representative routers.

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.

We consider combinatorial online prediction problems and propose a new construction method of efficient algorithms for the problems. One of the previous approaches to the problem is to apply online prediction method, in which two external procedures the projection and the metarounding are assumed to be implemented. In this work, we generalize the projection to multiple projections. As an application of our framework, we show an algorithm for an online job scheduling problem with a single machine with precedence constraints.

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.

In this study, we address a problem pertaining to the induced matching enumeration. An edge set M is an induced matching of a graph G=(V,E). The enumeration of matchings has been widely studied in literature; however, there few studies on induced matching. A straightforward algorithm takes O(Δ2) time for each solution that is coming from the time to generate a subproblem, where Δ is the maximum degree in an input graph. To generate a subproblem, an algorithm picks up an edge e and generates two graphs, the one is obtained by removing e from G, the other is obtained by removing e, adjacent edge to e, and edges adjacent to adjacent edge of e. Since this operation needs O(Δ2) time, a straightforward algorithm enumerates all induced matchings in O(Δ2) time per solution. We investigated local structures that enable us to generate subproblems within a short time and proved that the time complexity will be O(1) if the input graph is C4-free. A graph is C4-free if and only if none of its subgraphs have a cycle of length four.

Given an axis-aligned rectangle R and a set P of n points in the proper inside of R we wish to partition R into a set S of n+1 rectangles so that each point in P is on the common boundary between two rectangles in S. We call such a partition of R a feasible floorplan of R with respect to P. Intuitively, P is the locations of columns and a feasible floorplan is a floorplan in which no column is in the proper inside of a room, i.e., columns are allowed to be placed only on the partition walls between rooms. In this paper we give an efficient algorithm to enumerate all feasible floorplans of R with respect to P. The algorithm is based on the reverse search method, and enumerates all feasible floorplans in O(|SP|) time using O(n) space, where SP is the set of the feasible floorplans of R with respect to P, while the known algorithms need either O(n|SP|) time and O(n) space or O(log n|SP|) time and O(n3) space.

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.

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.