This paper proposes an efficient broadcast scheme based on traffic density measurement to mitigate broadcast storms in Vehicular Ad Hoc Networks (VANETs). In a VANET, the number of vehicles that rebroadcasts a message is closely related with the collision ratio of the message, so a well-designed broadcast scheme should consider traffic density when rebroadcasting a message. The proposed scheme introduces a traffic density measurement scheme and broadcast scheme for VANET. It is based on the slotted p-persistence scheme, but the rebroadcast procedure is enhanced and the rebroadcast probability p is controlled dynamically according to the estimated traffic density. Simulation results demonstrate that the proposed scheme outperforms existing schemes in terms of the end-to-end delay and collision ratio.

In wireless sensor networks, unbalanced energy consumption and transmission collisions are two inherent problems and can significantly reduce network lifetime. This letter proposes an unequal clustering and TDMA-like scheduling mechanism (UCTSM) based on a gradient sinking model in wireless sensor networks. It integrates unequal clustering and TDMA-like transmission scheduling to balance the energy consumption among cluster heads and reduce transmission collisions. Simulation results show that UCTSM balances the energy consumption among the cluster heads, saves nodes' energy and so improves the network lifetime.

Histopathology is a microscopic anatomical study of body tissues and widely used as a cancer diagnosing method. Generally, pathologists examine the structural deviation of cellular and sub-cellular components to diagnose the malignancy of body tissues. These judgments may often subjective to pathologists' skills and personal experiences. However, computational diagnosis tools may circumvent these limitations and improve the reliability of the diagnosis decisions. This paper proposes a prostate image classification method by extracting textural behavior using multifractal analysis. Fractal geometry is used to describe the complexity of self-similar structures as a non-integer exponent called fractal dimension. Natural complex structures (or images) are not self-similar, thus a single exponent (the fractal dimension) may not be adequate to describe the complexity of such structures. Multifractal analysis technique has been introduced to describe the complexity as a spectrum of fractal dimensions. Based on multifractal computation of digital imaging, we obtain two textural feature descriptors; i) local irregularity: α and ii) global regularity: f(α). We exploit these multifractal feature descriptors with a texton dictionary based classification model to discriminate cancer/non-cancer tissues of histopathology images of H&E stained prostate biopsy specimens. Moreover, we examine other three feature descriptors; Gabor filter bank, LM filter bank and Haralick features to benchmark the performance of the proposed method. Experiment results indicated that the performance of the proposed multifractal feature descriptor outperforms the other feature descriptors by achieving over 94% of correct classification accuracy.

Scan-based side channel attack on hardware implementations of cryptographic algorithms has shown its great security threat. Unlike existing scan-based attacks, in our work we observed that instead of the secret-related-registers, some non-secret registers also carry the potential of being misused to help a hacker to retrieve secret keys. In this paper, we first present a scan-based side channel attack method on AES by making use of the round counter registers, which are not paid attention to in previous works, to show the potential security threat in designs with scan chains. And then we discussed the issues of secure DFT requirements and proposed a secure scan scheme to preserve all the advantages and simplicities of traditional scan test, while significantly improve the security with ignorable design overhead, for crypto hardware implementations.

Multicore processor architectures have become ubiquitous in today's computing platforms, especially in parallel computing installations, with their power and cost advantages. While the technology trend continues towards having hundreds of cores on a chip in the foreseeable future, an urgent question posed to system designers as well as application users is whether applications can receive sufficient support on today's operating systems for them to scale to many cores. To this end, people need to understand the strengths and weaknesses on their support on scalability and to identify major bottlenecks limiting the scalability, if any. As open-source operating systems are of particular interests in the research and industry communities, in this paper we choose three operating systems (Linux, Solaris and FreeBSD) to systematically evaluate and compare their scalability by using a set of highly-focused microbenchmarks for broad and detailed understanding their scalability on an AMD 32-core system. We use system profiling tools and analyze kernel source codes to find out the root cause of each observed scalability bottleneck. Our results reveal that there is no single operating system among the three standing out on all system aspects, though some system(s) can prevail on some of the system aspects. For example, Linux outperforms Solaris and FreeBSD significantly for file-descriptor- and process-intensive operations. For applications with intensive sockets creation and deletion operations, Solaris leads FreeBSD, which scales better than Linux. With the help of performance tools and source code instrumentation and analysis, we find that synchronization primitives protecting shared data structures in the kernels are the major bottleneck limiting system scalability.

In this letter, for offloading traffic to Wireless Local Area Network (WLAN) with transport layer mobility where WLAN service is intermittently available, we propose a novel scheme to freeze and melt the timeout handling procedure of SCTP. Simulation results show that the proposed scheme significantly improves the performance in terms of file transfer completion time.

The shift bound is a good lower bound of the minimum distance for cyclic codes, Reed-Muller codes and geometric Goppa codes. It is necessary to construct the maximum value of the independent set. However, its computational complexity is very large. In this paper, we consider cyclic codes defined by their defining set, and a new method to calculate the lower bound of the minimum distance using the discrete Fourier transform (DFT) is shown. The computational complexity of this method is compared with the shift bound's one. Moreover construction of independent set is shown.

The single carrier block transmission (SCBT) system has become one of the most popular modulation systems because of its low peak to average power ratio (PAPR). This work proposes precoding design on the transmitter side to retain low PAPR, improve performance, and reduce computational complexity on the receiver side. The system is designed according to the following procedure. First, upper-triangular dirty paper coding (UDPC) is utilized to pre-cancel the interference among multiple streams and provide a one-tap time-domain equalizer for the SCBT system. Next, to solve the problem of the high PAPR of the UDPC precoding system, Tomlinson-Harashima precoding (THP) is developed. Finally, since the UDPC-THP system is degraded by the deep fading channels, the dynamic channel on/off assignment by the maximum capacity algorithm (MCA) and minimum BER algorithm (MBA) is proposed to enhance the bit error rate (BER) performance. Simulation results reveal that the proposed precoding transceiver can provide excellent BER and low PAPR performances for the SCBT system over a multipath fading channel.

In time-varying frequency selective channels, to obtain high-rate joint time-frequency diversity, linear dispersion coded orthogonal frequency division multiplexing (LDC-OFDM), has recently been proposed. Compared with OFDM systems, single-carrier systems may retain the advantages of lower PAPR and lower sensitivity to carrier frequency offset (CFO) effects, which motivates this paper to investigate how to achieve joint frequency and time diversity for high-rate single-carrier block transmission systems. Two systems are proposed: linear dispersion coded cyclic-prefix single-carrier modulation (LDC-CP-SCM) and linear dispersion coded zero-padded single-carrier modulation (LDC-ZP-SCM) across either multiple CP-SCM or ZP-SCM blocks, respectively. LDC-SCM may use a layered two-stage LDC decoding with lower complexity. This paper analyzes the diversity properties of LDC-CP-SCM, and provides a sufficient condition for LDC-CP-SCM to maximize all available joint frequency and time diversity gain and coding gain. This paper shows that LDC-ZP-SCM may be effectively equipped with low-complexity minimum mean-squared error (MMSE) equalizers. A lower complexity scheme, linear transformation coded SCM (LTC-SCM), is also proposed with good diversity performance.

Histogram modification based image enhancement algorithms have been extensively used in 2-D image applications. In this letter, we apply a histogram modification framework to stereoscopic image enhancement. The proposed algorithm estimates the histogram of a stereo image pair without explicitly computing the pixel-wise disparity. Then, the histogram in the occluded regions is estimated and used to determine the target histogram of the stereo image. Experimental results demonstrate the effectiveness of the proposed algorithm.

In this paper, we propose a normalization method dividing the gradient vector by the sum of the diagonal and two adjoining elements of the matrix expressing the correlation between the components of the discrete Fourier transform (DFT) of the reference signal used for the identification of unknown system. The proposed method can thereby improve the estimation speed of coefficients of adaptive filter.

Secret sharing schemes have been proposed to protect content by dividing it into many pieces securely and distributing them over different locations. Secret sharing schemes can also be used for the secure delivery of content. The original content cannot be reconstructed by the attacker if the attacker cannot eavesdrop on all the pieces delivered from multiple content servers. This paper aims to obtain secure delivery routes for the pieces, which minimizes the probability that all the pieces can be stolen on the links composing the delivery routes. Although such a route optimization problem can be formulated using an ILP (Integer Linear Programming) model, optimum route computation based on the ILP model requires large amounts of computational resources. Thus, this paper proposes a lightweight route computation method for obtaining suboptimum delivery routes that achieve a sufficiently small probability of all the pieces being stolen. The proposed method computes the delivery routes successively by using the conventional shortest route algorithm repeatedly. The distance of the links accommodating the routes that have already been calculated is adjusted iteratively and utilized for calculation of the new shortest route. The results of a performance evaluation clarify that sufficiently optimum routes can be computed instantly even in practical large-scale networks by the proposed method, which adjusts the link distance strictly based on the risk level at the considered link.

Conventional entropy measure is derived from full-band (range from 0 Hz to 4 kHz); however, it can not clearly describe the spectrum variability during voice-activity. Here we propose a novel concept of adaptive long-term sub-band entropy ( ALT-SubEnpy ) measure and combine it with a multi-thresholding scheme for voice activity detection. In detail, the ALT-SubEnpy measure developed with four part parameters of sub-entropy which uses different long-term spectral window length at each part. Consequently, the proposed ALT-SubEnpy -based algorithm recursively updates the four adaptive thresholds on each part. The proposed ALT-SubEnpy-based VAD method is shown to be an effective method while working at variable noise-level condition.

This paper describes a new method for semi-supervised discriminative language modeling, which is designed to improve the robustness of a discriminative language model (LM) obtained from manually transcribed (labeled) data. The discriminative LM is implemented as a log-linear model, which employs a set of linguistic features derived from word or phoneme sequences. The proposed semi-supervised discriminative modeling is formulated as a multi-objective optimization programming problem (MOP), which consists of two objective functions defined on both labeled lattices and automatic speech recognition (ASR) lattices as unlabeled data. The objectives are coherently designed based on the expected risks that reflect information about word errors for the training data. The model is trained in a discriminative manner and acquired as a solution to the MOP problem. In transcribing Japanese broadcast programs, the proposed method reduced relatively a word error rate by 6.3% compared with that achieved by a conventional trigram LM.

This paper introduces novel high-speed and low-power boosted level converters for use in dual-supply systems. The proposed level converters adopt a voltage boosting at the gate of pull-down transistors to improve driving speed and reduce contention problem. Comparison results in a 0.13-µm CMOS process indicated that the proposed level converters provided up to 70% delay reduction with up to 57% power-delay product (PDP) reduction as compared to conventional level converters.

This paper proposes Burst Error Resilient coding (BRC) technology in mobile broadcasting network. The proposed method utilizes Scalable Video Coding (SVC) and Forward Error Correction (FEC) to overcome service outage due to burst loss in mobile network. The performance evaluation is performed by comparing PSNR of SVC and the proposed method under MBSFN simulation channel. The simulation result shows PSNR of SVC equal error protection (EEP), unequal error protection (UEP) and proposed BRC using Raptor FEC code.

This paper introduces balanced switching schemes to compensate linear and quadratic gradient errors, in the unary current source array of a current-steering digital-to-analog converter (DAC). A novel algorithm is proposed to avoid the accumulation of gradient errors, yielding much less integral nonlinearities (INLs) than conventional switching schemes. Switching scheme examples with different number of current cells are also exhibited in this paper, including symmetric arrays and non-symmetric arrays in round and square outlines. (a) For symmetric arrays where each cell is divided into two parallel concentric ones, the simulated INL of the proposed round/square switching scheme is less than 25%/40% of conventional switching schemes, respectively. Such improvement is achieved by the cancelation of linear errors and the reduction of accumulated quadratic errors to near the absolute lower bound, using the proposed balanced algorithm. (b) For non-symmetric arrays, i.e. arrays where cells are not divided into parallel ones, linear errors cannot be canceled, and the accumulated INL varies with different quadratic error distribution centers. In this case, the proposed algorithm strictly controls the accumulation of quadratic gradient errors, and different from the algorithm in symmetric arrays, linear errors are also strictly controlled in two orthogonal directions simultaneously. Therefore, the INLs of the proposed non-symmetric switching schemes are less than 64% of conventional switching schemes.

Scalable video coding with different modulation and coding schemes (MCSs) applied to different video layers is very appropriate for wireless multicast services because it can provide different video quality to different users according to their channel conditions, and a promising solution to handle packet losses induced by fading wireless channels is the use of layered hybrid FEC/ARQ scheme according to light-weight feedback messages from users about how many packets they have received. It is important to choose an appropriate MCS for each layer, decide how many parity packets in one layer should be transmitted, and determine the resources allocated to multiple video sessions to apply scalable video coding to wireless multicast streaming. We prove that such resource allocation problem is NP-hard and propose an approximate optimal algorithm with a polynomial run time. The algorithm can get the optimal transmission configuration to maximize the expected utility for all users where the utility can be a generic non-negative, non-decreasing function of the received rate. The results from simulations revealed that our algorithm offer significant improvements to video quality over a nave algorithm, an optimal algorithm without feedback from users, and an algorithm with feedback from designated users, especially in scenarios with multiple video sessions and limited radio resources.

In the framework of the modernization plan of COMPASS system, the existing COMPASS signals should be transmitted along with the modernized signals to maintain backward compatibility. In this paper, an efficient multiplexing scheme based on the optimal aligning method for combining COMPASS Phase II B3 and Phase III B3 signals is proposed, which offers significantly higher efficiency than Interplex and Generalized Majority Voting (GMV) multiplexing methods. The proposed scheme can provide potential opportunities for COMPASS system and other global navigation satellite systems (GNSS) modernization and construction plans.

This paper precisely characterizes secret sharing schemes based on arbitrary linear codes by using the relative dimension/length profile (RDLP) and the relative generalized Hamming weight (RGHW). We first describe the equivocation Δm of the secret vector =[s1,...,sl] given m shares in terms of the RDLP of linear codes. We also characterize two thresholds t1 and t2 in the secret sharing schemes by the RGHW of linear codes. One shows that any set of at most t1 shares leaks no information about , and the other shows that any set of at least t2 shares uniquely determines . It is clarified that both characterizations for t1 and t2 are better than Chen et al.'s ones derived by the regular minimum Hamming weight. Moreover, this paper characterizes the strong security in secret sharing schemes based on linear codes, by generalizing the definition of strongly-secure threshold ramp schemes. We define a secret sharing scheme achieving the α-strong security as the one such that the mutual information between any r elements of (s1,...,sl) and any α-r+1 shares is always zero. Then, it is clarified that secret sharing schemes based on linear codes can always achieve the α-strong security where the value α is precisely characterized by the RGHW.