An (≤n,≤ω)-one-time secure broadcast encryption scheme (BES) allows a sender to choose any subset of receivers so that only the designated users can decrypt a ciphertext. In this paper, we first show an efficient construction of an (≤n,≤ω)-one-time secure BES with general ciphertext sizes. Specifically, we propose a generic construction of an (≤n,≤ω)-one-time secure BES from key predistribution systems (KPSs) when its ciphertext size is equal to integer multiple of the plaintext size, and our construction includes all known constructions. However, there are many possible combinations of the KPSs to realize the BES in our construction methodology, and therefore, we show that which combination is the best one in the sense that secret-key size can be minimized. Our (optimized) construction provides a flexible parameter setup (i.e. we can adjust the secret-key sizes) by setting arbitrary ciphertext sizes based on restrictions on channels such as channel capacity and channel bandwidth.

Operating swarm robots has the virtues of improved performance, fault tolerance, distributed sensing, and so on. The problem is, high overall system costs are the main barrier in managing a system of foraging swarm robots. Moreover, its control algorithm should be scalable and reliable as the foraging (search) spaces become wider. This paper analyzes a nature-inspired cooperative method to reduce the operating costs of the foraging swarm robots through simulation experiments. The aim of this research is to improve efficiency of mechanisms for reducing the cost by developing a new algorithm for the synergistic cooperation of the group. In this paper, we set the evaluation index of energy efficiency considering that the mission success rate as well as energy saving is important. The value is calculated as the number of successful operations against the total consumption of energy in order to also guarantee optimized for the work processing power than the one simple goal of energy savings. The method employs a behavioral model of a honey bee swarm to improve the energy efficiency in collecting crops or minerals. Experiments demonstrate the effectiveness of the approach. The experiment is set a number of strategies to combine the techniques to the proposed and conventional methods. Considering variables such as the area of search space and the size of a swarm, the efficiency comparison test is performed. As the result, the proposed method showed the enhanced energy efficiency of the average 76.9% as compared to the conventional simple model that means reduction of the recharging cost more than 40%.

Through-silicon vias (TSV) allow the stacking of dies into multilayer structures, and solve connection problems between neighboring tiers for three-dimensional (3D) integrated circuit (IC) technology. Several studies have investigated the placement and routing in 3D ICs, but not much has focused on circuit partitioning for 3D stacking. However, with the scaling trend of CMOS technology, the influence of the area of I/O pads, power/ground (P/G) pads, and TSVs should not be neglected in 3D partitioning technology. In this paper, we propose an iterative layer-aware partitioning algorithm called EX-iLap, which takes into account the area of I/O pads, P/G pads, and TSVs for area balancing and minimization of inter-tier interconnections in a 3D structure. Minimizing the quantity of TSVs reduces the total silicon die area, which is the main source of recurring costs during fabrication. Furthermore, estimations of the number of TSVs and the total area are somewhat imprecise if P/G TSVs are not taken into account. Therefore, we calculate the power consumption of each cell and estimate the number of P/G TSVs at each layer. Experimental results show that, after considering the power of interconnections and pads, our algorithm can reduce area-overhead by ~39% and area standard deviation by ~69%, while increasing the quantity of TSVs by only 12%, as compared to the algorithm without considering the power of interconnections and pads.

A cover free family (CFF) is a useful mathematical tool for cryptographic schemes where any pre-defined number of sets in the family do not cover another set in the family. The common disadvantage of CFF-based schemes is the requirement for a significantly large amount of data such as public keys and ciphertexts. This paper proposes a simple method to reduce the size of ciphertexts in CFF-based broadcast encryption schemes by removing redundant elements from sets in the family, and then analyzes the size of cihpertexts. As a result, in a typical distribution case, the average amount of ciphertexts is reduced to 83 percents (from 691Kbits to 576Kbits).

Synthetic aperture radar (SAR) imagery is significantly deteriorated by the random phase noises which are generated by the frequency jitter of the transmit signal and atmospheric turbulence. In this paper, we recast the SAR imaging problem via the phase-corrupted data as for a special case of quadratic compressed sensing (QCS). Although the quadratic measurement model has potential to mitigate the effects of the phase noises, it also leads to a nonconvex and quartic optimization problem. In order to overcome these challenges and increase reconstruction robustness to the phase noises, we proposed a QCS-based SAR imaging algorithm by greedy local search to exploit the spatial sparsity of scatterers. Our proposed imaging algorithm can not only avoid the process of precise random phase noise estimation but also acquire a sparse representation of the SAR target with high accuracy from the phase-corrupted data. Experiments are conducted by the synthetic scene and the moving and stationary target recognition Sandia laboratories implementation of cylinders (MSTAR SLICY) target. Simulation results are provided to demonstrate the effectiveness and robustness of our proposed SAR imaging algorithm.

Since 2008, three different classes of Boolean functions with optimal algebraic immunity have been proposed by Carlet and Feng [2], Wang et al.[8] and Chen et al.[3]. We call them C-F functions, W-P-K-X functions and C-T-Q functions for short. In this paper, we propose three affine equivalent classes of Boolean functions containing C-F functions, W-P-K-X functions and C-T-Q functions as a subclass, respectively. Based on the affine equivalence relation, we construct more classes of Boolean functions with optimal algebraic immunity. Moreover, we deduce a new lower bound on the nonlinearity of C-F functions, which is better than all the known ones.

A novel scheme to implement a filter bank multicarrier/offset quadrature amplitude modulation (FBMC/OQAM) transmission system is proposed. This is achieved by replacing the existing polyphase filter banks based on FFT/IFFT with fast filter bank (FFB) in order to utilize its good properties such as cascaded structure and high frequency selectivity with a comparable complexity as FFT/IFFT. Although this topic is not addressed in the literature, the impulse response of the prototype filter for each stage within FFB can still be obtained by using an optimization technique, which is used to minimize the distortion caused by intersymbol and interchannel interferences (ISI and ICI) of the proposed FBMC/OQAM transmission system, subject to allowable ripples in the passband and stopband. As a result, the relationship between two-path prototype filters in each subfilter should be modified with a general form accordingly. Simulations show that the number of multiplications required by the proposed scheme is smaller than that needed by the polyphase filter banks solution based on FFT/IFFT. Furthermore, the suitability of the design of prototype filters and the validation can be also supported by the results.

For detecting the image copies of a given original image generated by arbitrary rotation, the existing image copy detection methods can not simultaneously achieve desirable performances in the aspects of both accuracy and efficiency. To address this challenge, a novel effective and efficient image copy detection method is proposed based on two global features extracted from rotation invariant partitions. Firstly, candidate images are preprocessed by an averaging operation to suppress noise. Secondly, the rotation invariant partitions of the preprocessed images are constructed based on pixel intensity orders. Thirdly, two global features are extracted from these partitions by utilizing image gradient magnitudes and orientations, respectively. Finally, the extracted features of images are compared to implement copy detection. Promising experimental results demonstrate our proposed method can effectively and efficiently resist rotations with arbitrary degrees. Furthermore, the performances of the proposed method are also desirable for resisting other typical copy attacks, such as flipping, rescaling, illumination and contrast change, as well as Gaussian noising.

Modern optimizing compilers tend to be conservative and often fail to vectorize programs that would have benefited from it. In this paper, we propose a way to predict the relevant command-line options of the compiler so that it chooses the most profitable vectorization strategy. Machine learning has proven to be a relevant approach for this matter: fed with features that describe the software to the compiler, a machine learning device is trained to predict an appropriate optimization strategy. The related work relies on the control and data flow graphs as software features. In this article, we consider tensor contraction programs, useful in various scientific simulations, especially chemistry. Depending on how they access the memory, different tensor contraction kernels may yield very different performance figures. However, they exhibit identical control and data flow graphs, making them completely out of reach of the related work. In this paper, we propose an original set of software features that capture the important properties of the tensor contraction kernels. Considering the Intel Merom processor architecture with the Intel Compiler, we model the problem as a classification problem and we solve it using a support vector machine. Our technique predicts the best suited vectorization options of the compiler with a cross-validation accuracy of 93.4%, leading to up to a 3-times speedup compared to the default behavior of the Intel Compiler. This article ends with an original qualitative discussion on the performance of software metrics by means of visualization. All our measurements are made available for the sake of reproducibility.

In this paper, the system identification problem from the high-dimensional input and output is considered. If the relationship between the features extracted from the data is represented as a linear time-invariant dynamical system, the input-output manifold learning method has shown to be a powerful tool for solving such a system identification problem. However, in the previous study, the system is assumed to be initially relaxed because the transfer function model is used for system representation. This assumption may not hold in several tasks. To handle the initially non-relaxed system, we propose the alternative approach of the input-output manifold learning with state space model for the system representation. The effectiveness of our proposed method is confirmed by experiments with synthetic data and motion capture data of human-human conversation.

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.

Network virtualization (NV) provides a promising solution to overcome the resistance of the current Internet in aspects of architecture change, and virtual network embedding (VNE) has been recognized as a core component in NV. In this paper, the current advances in exploring model, methods and technologies for embedding the virtual network into the substrate network, are summarized. Furthermore, the future research trends are drawn. The main distinctive aspects of this survey with early ones include that it is mainly contributed to simplify the VNE problem on large networks, and that more recent publications in this field are introduced. In addition, the suggestions to the future investigation will concern some new terms of the VNE optimization.

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.

In the development of intrabody communication systems, it is important to understand the effects of user's posture on the communication channels. In this study, dynamic measurements of intrabody communication channels were made and their dependences on the grounding conditions were investigated. Furthermore, the physical mechanism of the dynamic communication channels was discussed based on electrostatic simulations. According to the measured and the simulated results, the variations in the signal transmission characteristics depend not only on the distance between the Tx and the Rx but also on the shadowing by body parts.

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.

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.

Stability-featured dynamic multi-path routing (SDMR) based on the existing Traffic engineering eXplicit Control Protocol (TeXCP) is proposed and evaluated for traffic engineering in terrestrial networks. SDMR abandons the sophisticated stability maintenance mechanisms of TeXCP, whose load balancing scheme is also modified in the proposed mechanism. SDMR is proved to be able to converge to a unique equilibria state, which has been corroborated by the simulations.