This paper proposes a low power artificial bandwidth extension (ABE) technique that reduces computational complexity by introducing a fast codebook mapping method. We also introduce a weighted classified codebook mapping method for constructing the spectral envelope of the wideband speech signal. Classified codebooks are used to reduce spectrum mapping errors caused by characteristic difference among voiced, unvoiced and onset sound. The weighted distortion measure is also used to handle the spectral sensibility. The performance of the proposed ABE system is evaluated by a spectral distortion (SD), a perceptual evaluation of speech quality (PESQ), informal listening tests and weighted million operations per second (WMOPS) calculations. With the use of fast codebook mapping, the WMOPS complexity of the codebook mapping module is reduced by 45.17%.

We propose a novel saliency detection model based on Bayes' theorem. The model integrates the two parts of Bayes' equation to measure saliency, each part of which was considered separately in the previous models. The proposed model measures saliency by computing local kernel density estimation of features in the center-surround region and global kernel density estimation of features at each pixel across the whole image. Under the proposed model, a saliency detection method is presented that extracts DCT (Discrete Cosine Transform) magnitude of local region around each pixel as the feature. Experiments show that the proposed model not only performs competitively on psychological patterns and better than the current state-of-the-art models on human visual fixation data, but also is robust against signal uncertainty.

A combination of single-carrier frequency-division mult-iple-access (SC-FDMA) and relay transmission is effective for performance improvement in uplink transmission. In SC-FDMA, a mapping strategy of user's spectrum has an enormous impact on system performance. In the relay communication, the optimum mapping strategy may differentiate from that in direct communication because of the independently distributed channels among nodes. In this letter, how each link should be considered in subcarrier mapping is studied and the impact of mapping strategies on the average bit error rate (BER) performance of single-user SC-FDMA relay communications will be given.

We propose a high-speed and low-complexity architecture for the very large-scale integration (VLSI) implementation of the maximum a posteriori probability (MAP) algorithm suited to the double binary turbo decoder. For this purpose, equation manipulations on the conventional Linear-Log-MAP algorithm and architectural optimization are proposed. It is shown by synthesized simulations that the proposed architecture improves speed, area and power compared with the state-of-the-art Linear-Log-MAP architecture. It is also observed that the proposed architecture shows good overall performance in terms of error correction capability as well as decoder hardware's speed, complexity and throughput.

The approximately synchronized code-division multiple-access (CDMA) communication system, using the QAM sequences with zero correlation zone (ZCZ) as its spreading sequences, not only can remove the multiple access interference (MAI) and multi-path interference (MPI) synchronously, but also has a higher transmission data rate than the one using traditional ZCZ sequences with the same sequence length. Based on Gray mapping and the known binary ZCZ sequences, in this letter, six families of 16-QAM sequences with ZCZ are presented. When the binary ZCZ sequences employed by this letter arrive at the theoretical bound on the binary ZCZ sequences, and their family size is a multiple of 4 or 2, two of the resultant six 16-QAM sequence sets satisfy the bound referred to above as well.

High Dynamic Range (HDR) images have been widely applied in daily applications. However, HDR image is a special format, which needs to be pre-processed known as tone mapping operators for display. Since the visual quality of HDR images is very sensitive to luminance value variations, conventional watermarking methods for low dynamic range (LDR) images are not suitable and may even cause catastrophic visible distortion. Currently, few methods for HDR image watermarking are proposed. In this paper, two watermarking schemes targeting HDR images are proposed, which are based on µ-Law and bilateral filtering, respectively. Both of the subjective and objective qualities of watermarked images are greatly improved by the two methods. What's more, these proposed methods also show higher robustness against tone mapping operations.

In 2010, Guo and Zhang proposed a group key agreement protocol based on the chaotic hash function. This letter points out that Guo-Zhang's protocol is still vulnerable to off-line password guessing attacks, stolen-verifier attacks and reflection attacks.

This paper presents novel hybrid push-pull protocols for peer-to-peer video streaming. Our approaches intend to reap the best of push- and pull-based schemes by adaptively switching back and forth between the two modes according to video chunk distributions. The efficacy of the proposed protocols is validated through an evaluation study that demonstrates substantial performance gains.

In this correspondence, a new method to extend the number of quaternary low correlation zone (LCZ) sequence sets is presented. Based on the inverse Gray mapping and a binary sequence with ideal two-level auto-correlation function, numbers of quaternary LCZ sequence sets can be generated by choosing different parameters. There is at most one sequence cyclically equivalent in different LCZ sequence sets. The parameters of LCZ sequence sets are flexible.

Because of its simple structure, many reports on the logistic map have been presented. To implement this map on computers, finite precision is usually used, and therefore rounding is required. There are five major methods to implement rounding, but, to date, no study of rounding applied to the logistic map has been reported. In the present paper, we present experimental results showing that the properties of sequences generated by the logistic map are heavily dependent on the rounding method used and give a theoretical analysis of each method. Then, we describe why using the map with a floor function for rounding generates long aperiodic subsequences.

In this paper, a new construction method of quaternary sequences of even period 2N having the ideal autocorrelation and balance properties is proposed. These quaternary sequences are constructed by applying the inverse Gray mapping to binary sequences of odd period N with the ideal autocorrelation. Autocorrelation distribution of the proposed quaternary sequences is derived. These sequences can be used to construct quaternary sequence families of even period 2N. Family size and the maximum absolute value of correlation spectrum of the proposed quaternary sequence families are also derived.

Post-silicon debugging is getting even more critical to shorten the time-to-market than ever, as many more bugs escape pre-silicon verification according to the increasing design scale and complexity. Post-silicon debugging is generally harder than pre-silicon debugging due to the limited observability and controllability of internal signal values. Conventionally, simulation of corresponding low-level designs such as RTL or gate-level has been used to get observability and controllability, which is inefficient for contemporary large designs. In this paper, we introduce a post-silicon debugging approach using simulation of high-level designs, instead of low-level designs. To realize such a debugging approach, we propose an I/O sequence mapping method that converts I/O sequences of chip executions to those of the corresponding high-level design. First, we provide a formal definition of I/O sequence mapping and relevant notions. Then, based on the definition, we propose an I/O sequence mapping method by executing FSMs representing the interface specifications of the target design. Also, we propose an implementation of the proposed method to get further efficiency. We demonstrate that the proposed method can be effectively applied to several practical design examples with various interfaces.

This paper provides conceptual and experimental analysis of a new approach in the study of kanji, our “Learner's Visualization (LV) Approach”. In a previous study we found that the LV Approach assists beginning learners in significantly updating their personal kanji deconstruction visualization. Additionally, in another study our findings provided evidence that beginning learners also receive a significant impact in the ability to acquire vocabulary. In this study, our research problem examines how beginning and intermediate students use visualization to cognitively deconstruct (divide) kanji in different ways, and how this affects their learning progress. We analyze the cognitive differences in how kanji learners explore and deconstruct novel kanji while using the LV Approach and how these differences affect their learning process while using the LV Approach. During the learning experience, our LILES System (Learner's Introspective Latent Envisionment System), based on the LV Approach, guides learners to choose from a set of possible “kanji deconstruction layouts” (layouts showing different ways in which a given kanji can be divided). The system then assists learners in updating their “kanji deconstruction level” (the average number of parts they visualize within kanji according to their current abilities). Statistical analysis based on achieved performance was conducted. The analysis of our results proves that there are cognitive differences: beginners deconstruct kanji into more parts (“blocks”) than intermediate learners do, and while both improve their kanji deconstruction scores, there is a more significant change in “kanji deconstruction level” in beginners. However, it was also found that intermediate learners benefit more in “kanji retention score” compared with beginners. Suggestions for further research are provided.

We propose a new stereo image retargeting method based on the framework of shift-map image editing. Retargeting is the process of changing the image size according to the target display while preserving as much of the richness of the image as possible, and is often applied to monocular images and videos. Retargeting stereo images poses a new challenge because pixel correspondences between the stereo pair should be preserved to keep the scene's structure. The main contribution of this paper is integrating a stereo correspondence constraint into the retargeting process. Among several retargeting methods, we adopt shift-map image editing because this framework can be extended naturally to stereo images, as we show in this paper. We confirmed the effectiveness of our method through experiments.

In the case of Barreto-Naehrig pairing-friendly curves of embedding degree 12 of order r, recent efficient Ate pairings such as R-ate, optimal, and Xate pairings achieve Miller loop lengths of(1/4) ⌊log2 r⌋. On the other hand, the twisted Ate pairing requires (3/4) ⌊log2 r⌋ loop iterations, and thus is usually slower than the recent efficient Ate pairings. This paper proposes an improved twisted Ate pairing using Frobenius maps and a small scalar multiplication. The proposed idea splits the Miller's algorithm calculation into several independent parts, for which multi-pairing techniques apply efficiently. The maximum number of loop iterations in Miller's algorithm for the proposed twisted Ate pairing is equal to the (1/4) ⌊log2 r ⌋ attained by the most efficient Ate pairings.

In this paper, we define a discretized chaotic map as a digital realization of a one-dimensional chaos map. As a concrete example, we consider a family of pseudochaotic sequences with maximum length, referred to as maximum length pseudochaotic sequences, obtained from a class of discretized piecewise linear map. A theoretical framework for designing maximum length pseudochaotic sequences of the discretized chaotic maps is obtained. These discretized piecewise linear chaotic maps can be used in the design of binary sequences with constant autocorrelation values for several time delays.

Network on Chip (NoC) is proposed as a new intra-chip communication infrastructure. In current NoC design, one related problem is mapping IP cores onto NoC architectures. In this paper, we propose a performance-aware hybrid algorithm (PHA) for mesh-based NoC to optimize performance indexes such as latency, energy consumption and maximal link bandwidth. The PHA is a hybrid algorithm, which integrates the advantages of Greedy Algorithm, Genetic Algorithm and Simulated Annealing Algorithm. In the PHA, there are three features. First, it generates a fine initial population efficiently in a greedy swap way. Second, effective global parallel search is implemented by genetic operations such as crossover and mutation, which are implemented with adaptive probabilities according to the diversity of population. Third, probabilistic acceptance of a worse solution using simulated annealing method greatly improves the performance of local search. Compared with several previous mapping algorithms such as MOGA and TGA, simulation results show that our algorithm enhances the performance by 30.7%, 23.1% and 25.2% in energy consumption, latency and maximal link bandwidth respectively. Moreover, simulation results demonstrate that our PHA approach has the highest convergence speed among the three algorithms. These results show that our proposed mapping algorithm is more effective and efficient.

Navigation systems providing route-guidance and traffic information are one of the most widely used driver-support systems these days. Most navigation systems are based on the map paradigm which plots the driving route in an abstracted version of a two-dimensional electronic map. Recently, a new navigation paradigm was introduced that is based on the augmented reality (AR) paradigm which displays the driving route by superimposing virtual objects on the real scene. These two paradigms have their own innate characteristics from the point of human cognition, and so complement each other rather than compete with each other. Regardless of the paradigm, the role of any navigation system is to support the driver in achieving his driving goals. The objective of this work is to investigate how these map and AR navigation paradigms impact the achievement of the driving goals: productivity and safety. We performed comparative experiments using a driving simulator and computers with 38 subjects. For the effects on productivity, driver's performance on three levels (control level, tactical level, and strategic level) of driving tasks was measured for each map and AR navigation condition. For the effects on safety, driver's situation awareness of safety-related events on the road was measured. To find how these navigation paradigms impose visual cognitive workload on driver, we tracked driver's eye movements. As a special factor of driving performance, route decision making at the complex decision points such as junction, overpass, and underpass was investigated additionally. Participant's subjective workload was assessed using the Driving Activity Load Index (DALI). Results indicated that there was little difference between the two navigation paradigms on driving performance. AR navigation attracted driver's visual attention more frequently than map navigation and then reduces awareness of and proper action for the safety-related events. AR navigation was faster and better to support route decision making at the complex decision points. According to the subjective workload assessment, AR navigation was visually and temporally more demanding.

On uniformly convex real Banach spaces, a fixed point theorem in weak topology for successively recurrent system of fuzzy-set-valued nonlinear mapping equations and its application to ring nonlinear network systems are theoretically discussed in detail. An arbitrarily-level likelihood signal estimation is then established.

This paper introduces a practical color filter array (CFA) interpolation technique. Among the many technologies proposed in this field, the inter-color methods that exploit correlation between color planes generally outperform the intra-color approaches. We have found that the filtering direction, e.g., horizontal or vertical, is among the most decisive factors for the performance of the CFA interpolation. However, most of the state-of-the-art technologies are not flexible enough in determining the filtering direction. For example, filtering only in the upper direction is not usually supported. In this context, we propose an inter-color CFA interpolation using a local map called unified geometry map (UGM). In this method, the filtering direction is determined based on the similarity of the local map data. Thus, it provides more choices of the filtering directions, which enhances the probability of finding the most appropriate direction. It is confirmed through simulations that the proposal outperforms the state-of-the-art algorithms in terms of objective quality measures. In addition, the proposed scheme is as inexpensive as the conventional methods with regard to resource consumption.