Left-weight sequences (LW-sequences for short) are in common currency for encoding binary trees. In [16], Wu et al. proposed an algorithm associated with tree rotations for listing all binary trees in diverse representations including LW-sequences. In particular, such a list of LW-sequences is generated in Gray-code order. In this paper, based on this ordering, we present efficient ranking and unranking algorithms. For binary trees with n internal nodes, the time complexity and the space requirement in each of our ranking and unranking algorithms are O(n2) and O(n), respectively.

In this paper, a convolution theorem which is analogous to the theorem for Fourier transform is shown among a certain type of polynomials. We establish a fast method of the multiplication in a special class of quotient rings of multivariate polynomials over q-element finite field GF(q). The polynomial which we treat is one of expressing forms of the multiple-valued logic function from the product of the semigroups in GF(q) to GF(q). Our results can be applied to the speedup of both software and hardware concerning multiple-valued Boolean logic.

In the 3-slope ski-rental problem, the player is asked to determine a strategy, that is, (i) whether to buy a ski wear and then a ski set separately, or to buy them at once for a discount price, and (ii) when to buy these goods. If the player has not got any thing, he/she can rent it for some price. The objective is to minimize the total cost, under the assumption that the player does not know how many times he/she goes skiing in the future. We reveal that even with a large discount for buying at once available, there is some price setting for which to buy the goods separately is a more reasonable choice. We also show that the performance of the optimal strategy may become arbitrarily worse, when a large discount is offered.

A visible watermarking technique to provide copyright protection for portrait images is proposed in this paper. The proposal is focused on real-world applications where a portrait image is printed and illegitimately used for commercial purposes. It is well known that this is one of the most difficult challenges to prove ownership through current watermark techniques. We propose an original approach which avoids the deficiencies of typical watermarking methods in practical scenarios by introducing a smart process to automatically detect the most suitable region of the portrait image, where the visible watermark goes unnoticed to the naked eye of a viewer and is robust enough to remain visible when printed. The position of the watermark is determined by performing an analysis of the portrait image characteristics taking into account several conditions of their spatial information together with human visual system properties. Once the location is set, the watermark embedding process is performed adaptively by creating a contrast effect between the watermark and its background. Several experiments are performed to illustrate the proper functioning of the proposed watermark algorithm on portrait images with different characteristics, including dimensions, backgrounds, illumination and texture, with the conclusion that it can be applied in many practical situations.

Controlling the peak-to-mean envelope power ratio (PMEPR) of orthogonal frequency-division multiplexed (OFDM) transmissions is a significant obstacle in many low-cost applications of OFDM. An coding approach proposed by H.R. Sadjadpour presents non-square M-QAM symbols as a combination of QPSK and BPSK signals when M=22n+1, and then uses QPSK and BPSK Golay (or Golay-like) sequences with a constant PMEPR to generate M-QAM sequences. This paper proposes a new scheme in which M-QAM sequences are generated by QPSK and BPSK sequences with variable PMEPRs. In other words, this new scheme is a general case of the existing approach. As a result, the code rate of the new sequence is significantly improved, while the upper bound of its PMEPR remains at a comparative level.

A method for increasing alignment tolerance in simple multiple-stream transmission is described. Its use of π-shifted antenna directivity phase enables it to cancel interference even when antenna placement deviations occur. The interference cancellation by using π-shifted directivities provides higher alignment tolerance than that with conventional fixed weight methods. It also provides smaller channel gain variation than can be obtained using fixed weights even when antenna displacement occurs. An objective function is described that is determined by the alignment tolerance. The function is defined to maximize the alignment tolerance. The method's validity is confirmed by an experimental analysis of two-stream transmission in which the alignment tolerance of the proposed method is compared to that of conventional fixed weight methods.

This study focuses on modeling the storytelling performance of the participants in a group conversation. Storytelling performance is one of the fundamental communication techniques for providing information and entertainment effectively to a listener. We present a multimodal analysis of the storytelling performance in a group conversation, as evaluated by external observers. A new multimodal data corpus is collected through this group storytelling task, which includes the participants' performance scores. We extract multimodal (verbal and nonverbal) features regarding storytellers and listeners from a manual description of spoken dialog and from various nonverbal patterns, including each participant's speaking turn, utterance prosody, head gesture, hand gesture, and head direction. We also extract multimodal co-occurrence features, such as head gestures, and interaction features, such as storyteller utterance overlapped with listener's backchannel. In the experiment, we modeled the relationship between the performance indices and the multimodal features using machine-learning techniques. Experimental results show that the highest accuracy (R2) is 0.299 for the total storytelling performance (sum of indices scores) obtained with a combination of verbal and nonverbal features in a regression task.

This paper newly proposes and theoretically analyzes the performance of multi-hop free-space optical (FSO) systems employing optical amplify-and-forward (OAF) relaying technique and wavelength division multiplexing (WDM). The proposed system can provide a low cost, low latency, high flexibility, and large bandwidth access network for multiple users in areas where installation of optical fiber is unfavorable. In WDM/FSO systems, WDM channels suffer from the interchannel crosstalk while FSO channels can be severely affected by the atmospheric turbulence. These impairments together with the accumulation of background and amplifying noises over multiple relays significantly degrade the overall system performance. To deal with this problem, the use of the M-ary pulse position modulation (M-PPM) together with the OAF relaying technique is advocated as a powerful remedy to mitigate the effects of atmospheric turbulence. For the performance analysis, we use a realistic model of Gaussian pulse propagation to investigate major atmospheric effects, including signal turbulence and pulse broadening. We qualitatively discuss the impact of various system parameters, including the required average transmitted powers per information bit corresponding to specific values of bit error rate (BER), transmission distance, number of relays, and turbulence strength. Our numerical results are also thoroughly validated by Monte-Carlo (M-C) simulations.

Because the perceptual compressive sensing framework can achieve a much better performance than the legacy compressive sensing framework, it is very promising for the compressive sensing based image compression system. In this paper, we propose an innovative adaptive perceptual block compressive sensing scheme. Firstly, a new block-based statistical metric which can more appropriately measure each block's sparsity and perceptual sensibility is devised. Then, the approximated theoretical minimum measurement number for each block is derived from the new block-based metric and used as weight for adaptive measurements allocation. The obtained experimental results show that our scheme can significantly enhance both objective and subjective performance of a perceptual compressive sensing framework.

This paper presents a method for registering retinal images. Retinal image registration is crucial for the diagnoses and treatments of various eye conditions and diseases such as myopia and diabetic retinopathy. Retinal image registration is challenging because the images have non-uniform contrasts and intensity distributions, as well as having large homogeneous non-vascular regions. This paper provides a new retinal image registration method by effectively combining expectation maximization principal component analysis based mutual information (EMPCA-MI) with salient features. Experimental results show that our method is more efficient and robust than the conventional EMPCA-MI method.

We present circuit implementations for computing exponentials and logarithms suitable for rapid single-flux-quantum (RSFQ) logic. We propose hardware algorithms based on the sequential table-lookup (STL) method using the radix-2 signed-digit representation that achieve high-throughput, digit-serial calculations. The circuits are implemented by processing elements formed in systolic-array-like, regularly-aligned pipeline structures. The processing elements are composed of adders, shifters, and readouts of precomputed constants. The iterative calculations are fully overlapped, and throughputs approach the maximum throughput of serial processing. The circuit size for calculating significand parts is estimated to be approximately 5-10 times larger than that of a bit-serial floating-point adder or multiplier.

Recent studies have obtained superior performance in image recognition tasks by using, as an image representation, the fully connected layer activations of Convolutional Neural Networks (CNN) trained with various kinds of images. However, the CNN representation is not very suitable for fine-grained image recognition tasks involving food image recognition. For improving performance of the CNN representation in food image recognition, we propose a novel image representation that is comprised of the covariances of convolutional layer feature maps. In the experiment on the ETHZ Food-101 dataset, our method achieved 58.65% averaged accuracy, which outperforms the previous methods such as the Bag-of-Visual-Words Histogram, the Improved Fisher Vector, and CNN-SVM.

This paper considers an optimal stabilization problem of quantitative discrete event systems (DESs) under the influence of disturbances. We model a DES by a deterministic weighted automaton. The control cost is concerned with the sum of the weights along the generated trajectories reaching the target state. The region of weak attraction is the set of states of the system such that all trajectories starting from them can be controlled to reach a specified set of target states and stay there indefinitely. An optimal stabilizing controller is a controller that drives the states in this region to the set of target states with minimum control cost and keeps them there. We consider two control objectives: to minimize the worst-case control cost (1) subject to all enabled trajectories and (2) subject to the enabled trajectories starting by controllable events. Moreover, we consider the disturbances which are uncontrollable events that rarely occur in the real system but may degrade the control performance when they occur. We propose a linearithmic time algorithm for the synthesis of an optimal stabilizing controller which is robust to disturbances.

It is known that, using just a deck of cards, an arbitrary number of parties with private inputs can securely compute the output of any function of their inputs. In 2009, Mizuki and Sone constructed a six-card COPY protocol, a four-card XOR protocol, and a six-card AND protocol, based on a commonly used encoding scheme in which each input bit is encoded using two cards. However, up until now, there are no known results to construct a set of COPY, XOR, and AND protocols based on a two-card-per-bit encoding scheme, which all can be implemented using only four cards. In this paper, we show that it is possible to construct four-card COPY, XOR, and AND protocols using polarizing plates as cards and a corresponding two-card-per-bit encoding scheme. Our protocols use a minimum number of cards in the setting of two-card-per-bit encoding schemes since four cards are always required to encode the inputs. Moreover, we show that it is possible to construct two-card COPY, two-card XOR, and three-card AND protocols based on a one-card-per-bit encoding scheme using a common reference polarizer which is a polarizing material accessible to all parties.

User-based and item-based collaborative filtering (CF) are two of the most important and popular techniques in recommender systems. Although they are widely used, there are still some limitations, such as not being well adapted to the sparsity of data sets, failure to consider the hierarchical structure of the items, and changes in users' interests when calculating the similarity of items. To overcome these shortcomings, we propose an evolutionary approach based on hierarchical structure for dynamic recommendation system named Hierarchical Temporal Collaborative Filtering (HTCF). The main contribution of the paper is displayed in the following two aspects. One is the exploration of hierarchical structure between items to improve similarity, and the other is the improvement of the prediction accuracy by utilizing a time weight function. A unique feature of our method is that it selects neighbors mainly based on hierarchical structure between items, which is more reliable than co-rated items utilized in traditional CF. To the best of our knowledge, there is little previous work on researching CF algorithm by combining object implicit or latent object-structure relations. The experimental results show that our method outperforms several current recommendation algorithms on recommendation accuracy (in terms of MAE).

In this paper, we investigate a preference-aware multicast mechanism in active array aided LTE (Long Term Evolution) networks. An active antenna system can direct vertical beams in different horizontal and vertical directions, so the amount of energy delivered is more concentrated on the target users. The active array provides each multicast group with an individual beam with specific downtilt delivering shared video to all users in the group. For the multicast system, the objective of our proposed resource allocation scheme is to maximize the total throughput, subject to the constraints of power, subcarrier and antenna downtilt, as well as horizontal angles and the vertical half power bandwidth. To solve the problem, individual beams are steered for multicast groups. Furthermore, a novel subcarrier assignment scheme is proposed to enhance the spectrum resource utilization, and the optimal power allocation is obtained by virtue of Lagrangian method. Simulation results demonstrate the throughput and the spectral efficiency enhancement of our proposed scheme over other conditional schemes.

This paper presents a novel data compression method for testing integrated circuits within the selective dictionary coding framework. Due to the inverse value of dictionary indices made use of for the compatibility analysis with the heuristic algorithm utilized to solve the maximum clique problem, the method can obtain a higher compression ratio than existing ones.

The classification of warheads and decoys is a core technology in the defense of the ballistic missile. Usually, a high range resolution is favorable for the development of the classification algorithm, which requires a high sampling rate in fast time, and thus leads to a heavy computation burden for data processing. In this paper, a novel method based on compressed sensing (CS) is presented to improve the range resolution of the target with low computational complexity. First, a tool for electromagnetic calculation, such as CST Microwave Studio, is used to simulate the frequency response of the electromagnetic scattering of the target. Second, the range-resolved signal of the target is acquired by further processing. Third, a greedy algorithm is applied to this signal. By the iterative search of the maximum value from the signal rather than the calculation of the inner product for raw echo, the scattering coefficients of the target can be reconstructed efficiently. A series of experimental results demonstrates the effectiveness of our method.

As technology nodes continue to shrink, the impact of radiation-induced soft error on processor reliability increases. Estimation of processor reliability and identification of vulnerable flip-flops requires accurate soft error rate (SER) analysis techniques. This paper presents a proposal for a soft error propagation analysis technique. We specifically examine single event upset (SEU) occurring at a flip-flop in sequential circuits. When SEUs propagate in sequential circuits, the faults can be masked temporally and logically. Conventional soft error propagation analysis techniques do not consider error convergent timing on re-convergent paths. The proposed technique can analyze soft error propagation while considering error-convergent timing on a re-convergent path by combinational analysis of temporal and logical effects. The proposed technique also considers the case in which the temporal masking is disabled with an enable signal of the erroneous flip-flop negated. Experimental results show that the proposed technique improves inaccuracy by 70.5%, on average, compared with conventional techniques using ITC 99 and ISCAS 89 benchmark circuits when the enable probability is 1/3, while the runtime overhead is only 1.7% on average.

Some diffusive and recurrence properties of Lorentz Lattice Gas Cellular Automata (LLGCA) have been expensively studied in terms of the densities of some of the left/right static/flipping mirrors/rotators. In this paper, for any combination S of these well known scatters, we study the computational complexity of the following problem which we call PERIODICITY on the S-model: given a finite configuration that distributes only those scatters in S, whether a particle visits the starting position periodically or not. Previously, the flipping mirror model and the occupied flipping rotator model have been shown unbounded, i.e. the process is always diffusive [17]. On the other hand, PERIODICITY is shown PSPACE-complete in the unoccupied flipping rotator model [21]. In this paper, we show that PERIODICITY is PSPACE-compete in any S-model that is neither occupied, unbounded, nor static. Particularly, we prove that PERIODICITY in any unoccupied and bounded model containing flipping mirror is PSPACE-complete.