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As the latest generation of video coding standards, versatile video coding (VVC) introduces several new coding tools in transform coding to concentrate the energy of residual blocks. In this work, we propose a regular multiplier (RM) based hardware architecture for 2D transform that can process different transform sizes and types using a unified architecture. This architecture consists of a 1D row transform, a transpose memory, and a 1D column transform, allowing for processing 16 coefficients per cycle. For the 1D row/column transform, the unified calculation structure consists of 512 regular multipliers supporting various transform sizes and types. For the transpose memory, we design an SRAM-based diagonal storage approach, along with a FIFO for storing the block information. Compared with the state-of-the-art MCM-based design, the proposed RM-based design shows a 30.9% reduction in area while can operate at a higher frequency. [ABSTRACT FROM AUTHOR]

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• A fast coding method is proposed for HEVC inter-frame. • First, the characteristics of HEVC inter-frame coding are analyzed. • Then, an Inter-Frame Feature Transfer-LSTM (IFFT-LSTM) model is designed to accelerate CTU partition decision. • Finally, an algorithm flowchart for fast HEVC inter-frame coding is formulated. • The proposed method can reduce HEVC inter-frame coding complexity significantly with acceptable subjective video quality. High Efficiency Video Coding (HEVC) is the most commonly used video coding standard. However, its high coding complexity is a heavy burden for real-time video applications. But, coding tools designed based on traditional coding frameworks have reached limits. Furthermore, existing low-complexity video coding methods have not thoroughly analyzed the characteristics of compressed video, making it impossible to develop targeted models to reduce coding complexity. Therefore, in this research, a fast HEVC inter-frame coding technique is proposed. Firstly, we perform a characteristics analysis of HEVC inter-frame coding to explore the correlation between video frames. Secondly, we develop an Inter-Frame Feature Transfer-Long Short-Term Memory (IFFT-LSTM) model to obtain the optimal coding tree unit (CTU) partition structure. Thirdly, we embed the IFFT-LSTM model into the HEVC test platform. The experimental results show that suggested method can effectively reduce the HEVC inter-frame coding complexity with a small amount of rate-distortion (RD) performance loss while maintaining acceptable subjective video quality. [ABSTRACT FROM AUTHOR]

• Conditionally and directly skip all non-first pre-coding. • In I picture, for a CU with top-left location (x, y), if both x and y are multiples of 64, then each non-first pre-coding is skipped. • In I picture, for a CU with top-left location (x, y), if at least one of x and y is not multiples of 64 and a set of conditions is satisfied by a non-first pre-coding, then the non-first pre-coding is skipped. • In non-I picture, for CUs at any location, if a set of conditions is satisfied by a non-first pre-coding, then the non-first pre-coding is skipped. • Direct Non-First Pre-coding Skip (DNFPS) significantly reduce the coding complexity with negligible impact on coding efficiency. The third generation of Audio Video Coding Standard (AVS3) adopts sophisticated block partitioning structure with a multi-type tree, which includes Quad-Tree (QT), Binary-Tree (BT), and Extend Quad-Tree (EQT). During multi-type tree recursive block partitioning and pre-coding process of encoding, each Coding Unit (CU) of each Size at each Location (CUeSeL) of the picture is repeatedly pre-coded many times when visiting each branch of each tree. Although there are early termination mechanism, the number of visits for each CUeSeL is still very high and up to more than fifty. This process brings very high coding complexity. In order to reduce the coding complexity of AVS3, this paper proposes a method named Direct Non-First Pre-coding Skip (DNFPS) for a CUeSeL to directly and completely skip all non-first pre-coding under specific conditions. The conditions include, but are not limited to, those related to the first pre-coding. The contributions of the paper are as follows. In I pictures, for a CUeSeL with top-left location (x, y), if both x and y are multiples of 64 or if a set of conditions related to first pre-coding is satisfied, then each non-first pre-coding is skipped, and the coding result of the first pre-coding is reused for each non-first pre-coding skipped. In non-I pictures, each non-first pre-coding is skipped, and the coding result of the first pre-coding is reused for each non-first pre-coding skipped, provided a set of conditions related to first pre-coding is satisfied. The experimental results demonstrate that DNFPS has a negligible impact on coding efficiency under All Intra (AI) configurations, and coding runtime is reduced by 16 %. [ABSTRACT FROM AUTHOR]

Small image acquisition devices like digital single lens reflex (DSLR) cameras most commonly use Joint Photographic Expects Group (JPEG) coding standard for lossy compression. Although JPEG is a simple coding standard, its compression efficiency is very low as compared to any typical state-of-the-art image coding standards like set partitioning in hierarchical trees (SPIHT). In this paper, a novel state-table-based SPIHT (STS) algorithm and its field programmable gate array (FPGA) implementation is proposed. The STS uses two small state-tables and two extremely small lists. The STS not only provides better compression efficiency than the state-of-the-art JPEG 2000 at high bit rates but also requires very small memory to hold the state-tables and lists in comparison to SPIHT. On average STS requires 0.86% of the memory needed by SPIHT when evaluated for image sizes ranging from 4 Mpixels to 40 Mpixels. The implementation results show that STS consumes very less FPGA area in comparison to SPIHT-based architectures. The dynamic power dissipation of STS is also less than that of JPEG-like compression standards. This makes our proposed algorithm a better candidate for compression in low-power, low-memory digital image acquisition devices. [ABSTRACT FROM AUTHOR]

Highlights • Analysis of implemented food, energy, water nexus thinking in EU policies. • Inductive development of a FEW nexus specific coding system. • Differences in liability of nexus considerations among policy sectors. • Agricultural and energy sectors resume role as originators. • Water sector policies are driven by impacts of other sectors. Abstract In recent years there has been a major, policy-driven increase in research on the food-energy-water- (FEW-) nexus. Although the concept has played a significant role in much of the political sustainability debate since its emergence in 2011, it is increasingly criticized for its conceptual character and lack of practicability. To address the question of the concept's application in the political practice of the European Union, an analysis of currently existing EU policies has been conducted with specific focus on implemented nexus thinking. To limit the scope of the study, policy documents were chosen from the major political frameworks within the directly nexus-relevant policy sectors agricultural, energy and water policy, most notably – but not exclusively – the Common Agricultural Policy (CAP), the EU Energy Strategy, and the Water Framework Directive (WFD), as well as documents which address the integration among those. The study included a total of 50 policy documents. An inductive research approach was chosen to derive a FEW nexus specific coding system for the computer-assisted, semi-quantitative and qualitative analysis of the documents. The results reflect the fact that, in the past, policy design has mostly been framed within sectoral mandates, e.g., for water, agriculture or energy. Cross-sectoral effects especially among all three nexus resources have only recently been accounted for and predominantly exist in the form of non-formalized statements of intent. The establishment of cross-sectoral thinking is most advanced between the sectors of agricultural and water policy, mainly driven by their respective and historically grown roles within the nexus system. [ABSTRACT FROM AUTHOR]

Many researchers have commonly pointed out that the characteristics of crew communications is one of the most important factors affecting the operation safety of complicated process control systems. From this concern, a couple of speech-act coding schemes were developed from the point of view of ‘what was done by crew members?’ In this study, a novel speech-act coding scheme was developed, which allows us to see the contents crew communication from a different angle – ‘what was the communication intention of crew members?’ To this end, the communication contents uttered by MCR operators who were faced with various kinds of simulated off-normal conditions were collected from the full-scope simulator of domestic NPPs. Then, the novel speech-act coding scheme was developed by involving additional yardsticks (such as Means, Acceptance criteria , and Constraints ), which are useful for elucidating the nature of communications from a task description perspective. As a result, the novel speech-act coding scheme was proposed, which consists of 45 behavioral task categories and the associated definitions. Although the novel speech-act coding scheme proposed in this study is still a preliminary version, this would be a good starting point to enhance the quality of crew communications through visualizing their communication intentions. [ABSTRACT FROM AUTHOR]

Image data, text, video, and audio data all require compression for storage issues and real-time access via computer networks. Audio data cannot use compression technique for generic data. The use of algorithms leads to poor sound quality, small compression ratios and algorithms are not designed for real-time access. Lossless audio compression has achieved observation as a research topic and business field of the importance of the need to store data with excellent condition and larger storage charges. This article will discuss and analyze the various lossless and standardized audio coding algorithms that concern about LPC definitely due to its reputation and resistance to compression that is audio. However, another expectation plans are likewise broke down for relative materials. Comprehension of LPC improvements, for example, LSP deterioration procedures is additionally examined in this paper. [ABSTRACT FROM AUTHOR]

In high efficiency video coding (HEVC) standard, residuals are partitioned into variable-size transform units, and integer cosine transforms (ICTs) of order-4, 8, 16, and 32 are adopted to optimize the coding performance. Order-64 ICT is not used due to its high complexity and limited gain in general coding applications. This paper proposes a set of low-complexity ICTs (LCICTs), from order-8 to order-64, which have fully factorizable structures. LCICTs achieve similar coding performance as the state-of-art methods on HEVC Test Model 13 while requiring lower complexity, e.g., 71% fewer multiplications than the partially factorizable ICTs in the order-64 case. Moreover, we find that order-64 ICTs achieve around 1% average bitrate reduction at high quantization parameters. [ABSTRACT FROM AUTHOR]

As modern video coding standards are not designed to code panoramic videos, the pixels on the sphere need to be sampled onto a rectangle, and this process is called mapping. The mapping schemes generally include two steps: sampling points on sphere and arranging points into one compression-friendly rectangular frame. Traditional mapping schemes including equirectangular and cubic mapping have high sampling density on some sampling areas, which result in wasted pixels. In this letter, we propose a novel octagonal mapping scheme, which can decrease the oversampling areas and arrange points into an octagon. The octagon can be reshaped and rearranged into a rectangle before encoding. Experimental results demonstrate that the proposed mapping scheme saves more bitrates, compared to the existing mapping schemes. [ABSTRACT FROM AUTHOR]

This paper focuses on applying a new sign bit hiding method to improve the video coding efficiency. Sign bits account for a large proportion of the encoded stream conforming to the latest high efficiency video coding (HEVC) standard; hence, its hiding technique is of great significance. In this paper, an extra sign bit hiding algorithm is proposed. The parity of the sum of the first and last nonzero coefficients in a coefficient group is used to predict the sign bit, and one more bit could be hidden at the coefficient group level based on state-of-the-art algorithms. The proposed algorithm could recover transform coefficients with minor adjustment on multiple sign bit hiding technique in HEVC. Evaluation results on standard test sequences demonstrate -0.06% BD-rate gain compared to well-known multiple sign bit hiding method. Besides, either the quality loss or complexity increase is negligible with the proposed algorithm, which is applicable in real-time processing. [ABSTRACT FROM AUTHOR]

Depth data has a widespread use since the popularity of high resolution 3D sensors. In multi-view sequences, depth information is used to supplement the color data of each view. This article proposes a joint encoding of multiple depth maps with a unique representation. Color and depth images of each view are segmented independently and combined in an optimal Rate-Distortion fashion. The resulting partitions are projected to a reference view where a coherent hierarchy for the multiple views is built. A Rate-Distortion optimization is applied to obtain the final segmentation choosing nodes of the hierarchy. The consistent segmentation is used to robustly encode depth maps of multiple views obtaining competitive results with HEVC coding standards. [ABSTRACT FROM AUTHOR]

Data compression is a well-studied (and well-solved) problem in the setup of long coding blocks. But important emerging applications need to compress data to memory words of small fixed widths. This new setup is the subject of this paper. In the problem we consider, we have two sources with known discrete distributions, and we wish to find codes that maximize the success probability that the two source outputs are represented in $L$ bits or less. A good practical use for this problem is a table with two-field entries that is stored in a memory of a fixed width $L$ . Such tables of very large sizes are common in network switches/routers and in data-intensive machine-learning applications. After defining the problem formally, we solve it optimally with an efficient code-design algorithm. We also solve the problem in the more constrained case where a single code is used in both fields (to save space for storing code dictionaries). For both code-design problems we find decompositions that yield efficient dynamic-programming algorithms. With the help of an empirical study we show the success probabilities of the optimal codes for different distributions and memory widths. In particular, this paper demonstrates the superiority of the new codes over existing compression algorithms. [ABSTRACT FROM AUTHOR]

Intuition tells us that code that is difficult to review is likely complicated and faulty. Many organizations will create a coding standard to encourage higher quality software development. Coding standards are not always followed, and even when they are, complicated code continues to be written. Human nature demonstrates that people do not put effort into activities that they believe to be unproductive. It is also true that people have limited capacity for remembering and following directions, so extra requirements from a coding standard may even inhibit creativity. Because of human behavior, this paper recommends that organizations have two layers of a coding standard. The first layer should be easy to remember items. The second layer should be the long-established coding standard an organization wishes to comply with. [ABSTRACT FROM AUTHOR]

Zhao, Liu, & Deng (2013) reviewed 22 inter-coder reliability indices, and found that each makes unrealistic assumption(s) about coder behavior, leading to paradoxes and abnormalities. Krippendorff's α makes more of such assumptions, consequently produces more paradoxes and abnormalities than any other index. Professor Krippendorff (2013) countered that “most of the authors' discoveries are the artifacts of being led astray by strange, almost conspiratorial uses of language.” The commentary reiterated Krippendorff's long-standing position that Krippendorff's α is the standard reliability measure, and is the only index qualified to serve the function (Hayes & Krippendorff, 2007; Krippendorff, 2004b, 2016). This paper continues this dialogue. We offer a review of literature to show that the scientific community, including Krippendorff, has defined intercoder reliability as intercoder agreement, and Krippendorff's α, like all its main competitors, was designed and declared to measure intercoder agreement. Now that evidences are mounting that α, like Scott's π and Cohen's κ, does not accurately measure intercoder agreement, Krippendorff chose to redefine intercoder reliability and, furthermore, redefine information, variation, sensitivity, and specificity. By redefining reliability, we argue, Prof. Krippendorff has redefined the function of Krippendorff's α, thereby disqualified α as an indicator of intercoder agreement. The search for a better index of intercoder agreement aka intercoder reliability should continue. We, however, also note a spiral of inertia in science communication in general, and reliability research in particular. The powerful spiral, we argue, should not forever keep up the appearances for α, π or κ. [ABSTRACT FROM AUTHOR]

Determining the best partitioning structure of a coding tree unit is one of the most time-consuming operations in High Efficiency Video Coding (HEVC) encoding. Specifically, it is the evaluation of the quadtree hierarchy using the rate-distortion (RD) optimization that has the most significant impact on the encoding time, especially in the cases of high definition (HD) and ultra HD videos. In order to expedite the encoding for low-delay applications, this paper proposes a coding unit (CU) size selection and encoding algorithm for inter prediction in the HEVC. To this end, it describes: 1) two CU classification models based on Inter $N\times N$ mode motion features and RD cost thresholds to predict the CU split decision; 2) an online training scheme for dynamic content adaptation; 3) a motion vector reuse mechanism to expedite the motion estimation process; and 4) finally introduces a computational complexity to coding efficiency tradeoff process to enable flexible control of the algorithm. The experimental results reveal that the proposed algorithm achieves a consistent average encoding time performance ranging from 55%–58% and 57%–61% with average Bjøntegaard delta bit rate increases of 1.93%–2.26% and 2.14%–2.33% compared with the HEVC 16.0 reference software for the low delay P and low delay B configurations, respectively, across a wide range of content types and bit rates. [ABSTRACT FROM PUBLISHER]

In this paper, we address the problem of tracking the time varying/frequency selective fading channels with different fading rates in a decode-and-forward physical layer network coding (PLNC) structure. Since, in a PLNC system multi users send their information to the relay, simultaneously, the relay needs to estimate the uplink multi-channels, simultaneously, to be able to extract the network coded signal from superimposed signals. Different fading rates of channels due to different velocities of mobile users in a PLNC system make the channel tracking problem more complex. Providing an algorithm to simultaneous track multi-channels in such a system is the main object of this paper. To this end, a time domain channel tracking algorithm based on sum-product rules is derived, where, both frequency and time selectivity characteristics of the channels are taken into account. In order to stabilize against the frequency selectivity property of the channels, orthogonal frequency division multiplexing is also considered in this system. High accuracy, no phase ambiguity, and stability in fast fading conditions are some advantages of the proposed approach. The performance of the algorithm in the existence of channel coding has been also considered and compared with the non-coded channel system. [ABSTRACT FROM AUTHOR]

The second generation of the audio video coding standard (AVS2), which has been issued as IEEE 1857.4, doubles the coding efficiency of AVS1 and H.264/AVC. However, the advanced techniques in AVS2 also dramatically increase the computational complexity. The research on a commercial encoder for AVS2 is still at an early stage. In this paper, we propose the first fast intra-encoding platform for AVS2, which we term iAVS2. The platform uses numerous speedup methods, including code optimization, single-instruction multiple-data acceleration, and fast algorithms for almost all the time-consuming modules. To meet different application scenarios, five different speed levels are designed in iAVS2 to provide flexible tradeoffs between compression efficiency and encoding speed. The experimental results show that the fastest speed level of iAVS2 can accelerate the AVS2 reference software (RD12.0) by $144\times $ on average. Compared with the well-known HEVC encoder platform $\times 265$ , iAVS2 can provide over 10% bit rate saving at a similar coding speed. For the UHD and 1080 sequences, iAVS2 outperforms $\times 265$ at all speed levels. [ABSTRACT FROM PUBLISHER]

Dictionary learning (DL) plays an important role in pattern classification. However, learning a discriminative dictionary has not been well addressed in analysis dictionary learning (ADL). This letter proposes a Class-aware Analysis Dictionary Learning (CADL) model to improve the classification performance of conventional ADL. The objective function of CADL mainly includes two parts to promote the discriminability. The first part aims to learn a discriminative analysis subdictionary for each class instead of a global dictionary for all classes. The learned analysis dictionary is class-aware, generating a block-diagonal coding coefficient matrix. The second part aims to enhance the discrimination of coding coefficients by integrating a max-margin regularization term into our proposed framework. This term ensures the coefficients of different classes to be separated by a max-margin, which boosts the confidence of classification. A theoretical analysis is also given to support the max-margin regularization term from the perspective of preserving the pairwise relations of samples in coding space. We employ an alternating minimization algorithm to iteratively find the convergent solution. By evaluating our method on four pattern classification datasets, we demonstrate the superiority of our CADL method to the state-of-the-art DL methods. [ABSTRACT FROM AUTHOR]

In C++, test code is often interwoven with the unit we want to test. During the test development process we often have to modify the public interface of a class to replace existing dependencies; e.g. a supplementary setter or constructor function is added for dependency injection. In many cases, extra template parameters are used for the same purpose. All existing solutions have serious detrimental effects on the code structure and sometimes on the run-time performance as well. In this paper, we overview existing dependency replacement techniques of C++ and we evaluate their advantages and disadvantages. We introduce our non-intrusive, compiler instrumentation based testing approach that does not have such disadvantages. All non-intrusive testing methods (including our new method) require access to an object's internal state in order to setup a test. Thus, to complement our new solution, we also present different approaches to conveniently access private members in C++. To evaluate these techniques, we created a proof-of-concept implementation which is publicly available for further testing. [ABSTRACT FROM AUTHOR]

The unmatched growth in the automation and application of software code segments for automation is the main reactive reason for improvements in industrial, education, and healthcare and security sectors. The deployed code segments or the complete application used for the purpose is developed extensively with ample amount of features. The number of lines of code and number of man-hours deployed to build the applications are gigantic. In addition to that, the testing of the applications is the added cost for the development cycle. However, in spite of the best practice efforts, the applications can fail in real-time due to undetected errors resulting in fault and failure. Hence, the demand of the modern code development industry to the current research trend is to automate the testing process and derive a framework for enhanced defects detection. This work proposes a novel code defect detection technique to deep scan the code and report all possible bugs and defects and errors. To justify the thoughts, the framework tests the most popular java open source APIs and demonstrates the results. Another novel outcome of this work is to build a generic defect metric for all classes of source code. [ABSTRACT FROM AUTHOR]

This paper proposes a model of switched quasilogarithmic quantizer for speech signal based on G.711 standard with usage of Golomb-Rice (GR) coding. In order to achieve better performances a method with switched quantizer is applied. Variance range is split into quantizers and for each of them a separate quantizer is designed, i.e. the support region is determined. Optimization of the support region and choice of the parameter μ is done in order to obtain a quantizer that obeys G.712 standard and gives minimal average bit rate. Every quantizer within the variance range has own model with a two-stage coder. Two stages are introduced with purpose to reduce the bit rate, whereby GR code plays its role as Variable Length Code (VLC). The first stage uses a GR coder for coding segments of the quantizer's support region, whereas the second stage applies the coding method with fixed code lengths for coding cells within a segment. GR has simpler and cheaper hardware realization than other VLC codes, Huffman's for instance, with very satisfying results regarding quality of quantized signal. [ABSTRACT FROM AUTHOR]

The noise model of deletions poses significant challenges in coding theory, with basic questions like the capacity of the binary deletion channel still being open. In this paper, we study the harder model of worst case deletions, with a focus on constructing efficiently decodable codes for the two extreme regimes of high-noise and high-rate. Specifically, we construct polynomial-time decodable codes with the following tradeoffs (for any \varepsilon > 0 ): 1) codes that can correct a fraction 1- \varepsilon of deletions with rate \mathop \mathrm poly\nolimits ( \varepsilon ) over an alphabet of size \mathop \mathrm poly\nolimits (1/ \varepsilon ) ; 2) binary codes of rate 1-\tilde O(\sqrt \varepsilon ) that can correct a fraction $ \varepsilon $ of deletions; and 3) Binary codes that can be list-decoded from a fraction (1/2- \varepsilon )$ of deletions with rate \mathop {\mathrm {poly}}\nolimits ( \varepsilon ) . This paper gives the first efficient constructions which meet the qualitative goals of correcting a deletion fraction approaching 1 over bounded alphabets, and correcting a constant fraction of bit deletions with rate approaching 1 over a fixed alphabet. The above-mentioned results bring our understanding of deletion code constructions in these regimes to a similar level as worst case errors. [ABSTRACT FROM PUBLISHER]

In this paper, a new multiphase segmentation which has two stages is proposed. At the first stage, independent from the kind of image, k equidistant real numbers within [0, 1] interval are set as the labels of k main regions. At the second stage, two factors are used, which consist of the intensity function for distinguishing similar regions, as well as the eigenvector of Hessian matrix for distinguishing similar ridges with an auxiliary parameter for controlling the influence of this factor in different images. Also, an iterative algorithm is applied for gradually growing the region. Numerical experiences are given to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

A novel normalized least mean square (NLMS)-based algorithm is proposed to locate the active taps of the unknown impulse response in the application of network echo cancellation. Starting with the full length of the unknown echo path, the start-tap and end-tap estimates of the active region adapt, respectively, in the form of fractional tap. The effective tap-length estimate is defined by the length between the start-tap and end-tap estimates. The filter tap-weight vector is then updated with this effective tap-length estimate following the NLMS algorithm, while the tap weights located beyond the effective tap-length estimate are directly set to zero. In case that the active region of the unknown echo path shifts in a large scale, the start-tap and end-tap estimates are reset to the full length when the effective tap-length estimate is lower than a predetermined threshold value. Simulation results demonstrate that the proposed fractional tap-based algorithm can efficiently locate and track the effective tap length of the unknown echo path when the active coefficients change abruptly in locations and magnitudes, outperforming the existing stochastic tap-based schemes. [ABSTRACT FROM AUTHOR]

This paper considers the effect of multiple quantizers and channel packet dropouts in state estimation of networked system. Taking into account the limit capacity of the quantizer, multiple quantizers in the networked system with respect to the multichannels are modeled firstly. In addition, channel packet dropouts with different packet loss probabilities in different channels are also proposed in this paper. To minimize the effect of the quantizers and the disturbances, state estimators are constructed under a given performance requirement. Finally, a simulation example is used to illustrate the effectiveness of the theoretical results. [ABSTRACT FROM AUTHOR]

This paper describes the implementation on field programmable gate array (FPGA) of a turbo decoder for 3GPP Long-Term Evolution standard. Considering the high data rates required by this standard, parallel decoding architecture is used. The parallel decoding latency is reduced N times compared with the serial decoding latency, N being the parallelization factor, usually a power of 2. The decoding performances are similar for both serial and parallel schemes, when very low decoding latency is added to this theoretical parallel latency value. Taking advantage of the quadratic permutation polynomial interleaver properties, and considering some specific FPGA block memory characteristics, a novel simplified parallel decoding scheme is proposed, including only one interleaver, independently of the N value. Moreover, for the single interleaver, we propose a solution that exploits key arithmetic properties of the corresponding equation to perform the address computation in a recursive manner. The proposed method replaces divisions and multiplications by comparisons and subtractions. In addition, an even-odd merge sorting network provides correct data to all N decoding units. [ABSTRACT FROM AUTHOR]

The problem of blocking artifacts is very common in block-based image and video compression, especially at very low bit rates. In this paper, we propose a post-processing method for JPEG-coded image deblocking via sparse representation and adaptive residual threshold. This method includes three steps. First, we obtain the dictionary by online dictionary learning and the compressed images. The dictionary is then modified by the histogram of oriented gradient (HOG) feature descriptor and K-means cluster. Second, an adaptive residual threshold for orthogonal matching pursuit (OMP) is proposed and used for sparse coding by combining blind image blocking assessment. At last, to take advantage of human visual system (HVS), the edge regions of the obtained deblocked image can be further modified by the edge regions of the compressed image. The experimental results show that our proposed method can keep the image more texture and edge information while reducing the image blocking artifacts. [ABSTRACT FROM AUTHOR]

The evolution of modern web application involves a broad range of web technologies such as ActiveX, JavaScript and CGI. It mitigates the demand of bolt-on security services, but remains suffered from code vulnerabilities. Two common issues of web application code vulnerability are the wrong style of writing code and improper server configuration. Enhancing the web application's functionalities and ease of use are the primary concern of developers. Security is their second concern, resulting in code vulnerabilities. The application developers may effectively deal with code vulnerabilities through adhering to Secure Coding Standards. But manually applying all the Secure Coding Standard is susceptible to human errors. Hence, a graph-based interactive system is developed in the context of Secure Coding Standards to handle code vulnerabilities. Evaluation of the developed system is carried out by using standard available datasets such as CVE, NVD, Syhunt Vulnerable PHP Code and OWASP. [ABSTRACT FROM AUTHOR]

In this paper we propose two new cooperative relaying schemes which enable distributed implementation of the orthogonal space time block coding (OSTBC) with 3/4 code rate. These proposed schemes are compared with cooperative relaying scheme with virtual OSTBC and 1/2 code rate. The considered schemes are used for creating virtual 4 × 1 multiple input-single output (MISO) channel, and include one base station with two antennas, two relay stations each with a single antenna and one mobile station with a single antenna. Obtained results show that in the case of the same bit rate the proposed schemes provide better bit error rate (BER) performances than virtual OSTBC with 1/2 code rate. On the other side, for the same symbol constellations the proposed schemes have almost identical BER performances as virtual OSTBC with 1/2 code rate, but with a benefit of 1.5 times increased code rate. [ABSTRACT FROM AUTHOR]

Modern video coding standards such as High Efficiency Video Coding (HEVC) and H.264/MPEG-4 advanced video coding (AVC) supersede the previous coding standards because of their improved coding efficiency. These standards adopt variable block sizes in frame coding ranging from 4 × 4 to 16 × 16 and 4 × 4 to 64 × 64 for H.264/AVC and HEVC, respectively. The use of variable block sizes for inter prediction provides a significant coding gain compared to coding a macroblock (MB) using regular block size. However, this new feature greatly increases the computational complexity of the encoder when brute-force rate distortion optimization (RDO) algorithm is used for coding parameter selection. This paper proposes an efficient inter prediction mode selection scheme based on motion homogeneity and residual complexity measures of an MB to speed up the encoding process. The motion homogeneity is assessed through the normalized motion vector (MV) field, and residual complexity is evaluated by the sum of absolute difference (SAD). To acquire the MVs and SADs, motion estimation at 8 × 8 block size is performed using a lightweight recursive motion estimator in which the vector field tends toward true object motion. Based on motion homogeneity and residual complexity of an MB, only a small number of inter prediction modes are selected for the RDO process. The experimental results for H.264/AVC show that the proposed scheme reduces the encoding time by 64% on average without any significant degradation of coding efficiency. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Aim: During 2008-2011 Australian Coding Standards mandated a causal relationship between diabetes and inpatient care as a criterion for recording diabetes as a comorbidity in hospital administrative datasets. We aim to measure the effect of the causality mandate on recorded diabetes and associated inter-hospital variations.Method: For patients with diabetes, all admissions between 2004 and 2013 to all New South Wales acute public hospitals were investigated. Poisson mixed models were employed to derive adjusted rates and variations.Results: The non-recorded diabetes incidence rate was 20.7%. The causality mandate increased the incidence rate four fold during the change period, 2008-2011, compared to the pre- or post-change periods (32.5% vs 8.4% and 6.9%). The inter-hospital variation was also higher, with twice the difference in the non-recorded rate between hospitals with the highest and lowest rates (50% vs 24% and 27% risk gap). The variation decreased during the change period (29%), while the rate continued to rise (53%). Admission characteristics accounted for over 44% of the variation compared with at most two per cent attributable to patient or hospital characteristics. Contributing characteristics explained less of the variation within the change period compared to pre- or post-change (46% vs 58% and 53%). Hospital relative performance was not constant over time.Conclusion: The causality mandate substantially increased the non-recorded diabetes rate and associated inter-hospital variation. Longitudinal accumulation of clinical information at the patient level, and the development of appropriate adoption protocols to achieve comprehensive and timely implementation of coding changes are essential to supporting the integrity of hospital administrative datasets. [ABSTRACT FROM AUTHOR]

A multi-layer authentication scheme for HEVC compressed video is proposed. The combination of CU sizes, which is unique to HEVC and sensitive to video manipulation, is considered along with other elements in the HEVC coding standard to generate the authentication tag. Temporal dependency was enforced, where the authentication tag generated in one slice is embedded into its subsequent slice. By design, the authentication tag is repeatedly but selectively embedded into various elements in a HEVC video, including nonzero DCT coefficients, QP parameter values, and prediction modes, depending on the bit segment in the generated tag. Our scheme offers three layers of authentication to detect and localize the tampered regions in a HEVC video, as well as verifying the source/sender of the video using a shared secret key. Video sequences from various classes (resolutions) are considered to verify the performance of the proposed multi-layer authentication scheme. Results show that, at the expense of slight degradation in perceptual quality, the proposed scheme is robust against several common attacks. A functional comparison is performed between the proposed multi-layer authentication scheme and the conventional schemes. [ABSTRACT FROM AUTHOR]

Reduced-reference (RR) and no-reference (NR) models for video quality estimation, using features that account for the impact of coding artifacts, spatio-temporal complexity, and packet losses, are proposed. The purpose of this study is to analyze a number of potentially quality-relevant features in order to select the most suitable set of features for building the desired models. The proposed sets of features have not been used in the literature and some of the features are used for the first time in this study. The features are employed by the least absolute shrinkage and selection operator (LASSO), which selects only the most influential of them toward perceptual quality. For comparison, we apply feature selection in the complete feature sets and ridge regression on the reduced sets. The models are validated using a database of H.264/AVC encoded videos that were subjectively assessed for quality in an ITU-T compliant laboratory. We infer that just two features selected by RR LASSO and two bitstream-based features selected by NR LASSO are able to estimate perceptual quality with high accuracy, higher than that of ridge, which uses more features. The comparisons with competing works and two full-reference metrics also verify the superiority of our models. © 2016 SPIE and IS&T [DOI: 10.1117/1.JEI.25.5.053012] [ABSTRACT FROM AUTHOR]

With the support of cloud computing techniques, social coding platforms have changed the style of software development. Github is now the most popular social coding platform and project hosting service. Software developers of various levels keep entering Github, and use Github to save their public and private software projects. The large amounts of software developers and software repositories on Github are posing new challenges to the world of software engineering. This paper tries to tackle one of the important problems: analyzing the importance and influence of Github repositories. We proposed a HITS based influence analysis on graphs that represent the star relationship between Github users and repositories. A weighted version of HITS is applied to the overall star graph, and generates a different set of top influential repositories other than the results from standard version of HITS algorithm. We also conduct the influential analysis on per-month star graph, and study the monthly influence ranking of top repositories. [ABSTRACT FROM AUTHOR]

High Efficiency Video Coding (HEVC) Standard, as the latest coding standard, introduces satisfying compression structures with respect to its predecessor Advanced Video Coding (H.264/AVC). The new coding standard can offer improved encoding performance compared with H.264/AVC. However, it also leads to enormous computational complexity that makes it considerably difficult to be implemented in real time application. In this paper, based on machine learning, a fast partitioning method is proposed, which can search for the best splitting structures for Intra-Prediction. In view of the video texture characteristics, we choose the entropy of Gray-Scale Difference Statistics (GDS) and the minimum of Sum of Absolute Transformed Difference (SATD) as two important features, which can make a balance between the computation complexity and classification performance. According to the selected features, adaptive decision trees can be built for the Coding Units (CU) with different size by offline training. Furthermore, by this way, the partition of CUs can be resolved as a binary classification problem. Experimental results have shown that the proposed algorithm can save over 34% encoding time on average, with a negligible Bjontegaard Delta (BD)-rate increase. [ABSTRACT FROM AUTHOR]

The emerging market of Internet of things has created great demand for low-cost, low-power wireless technologies. Existing IEEE 802.15.4 standard is designed for low-rate wireless personal area networks (LR-WPANs). However, current standard does not fully utilise the benefit of the code redundancy. In this study, the authors propose new coding schemes for LR-WPANs with improved coding gain. They first propose a block code based on extended Bose-Chaudhuri-Hocquenghem (BCH) code that increases the minimum Hamming distance compared with the existing code used in LR-WPANs. The computational complexity of the encoder and decoder remains about the same. In addition, by applying the extended BCH code directly to LR-WPANs, the data rate of the system can be increased without sacrificing coding performance. They further propose a tail-biting convolutional (TBC) code with optimum generator polynomials for LR-WPANs. The proposed TBC code enjoys significant performance improvement while preserving the effective code rate as well as a low decoding complexity. Simulation results validate the effectiveness of the proposed coding schemes. [ABSTRACT FROM AUTHOR]

The German World War II Enigma suffered from design weaknesses that facilitated its large-scale decryption by the British throughout the war. The author shows that the main technical weaknesses (self-coding and reciprocal coding) could have been avoided using simple contemporary technology, and therefore the true cause of the weaknesses is not technological but must be sought elsewhere. Specifically, human factors issues resulted in the persistent failure to seek out more effective designs. Similar limitations seem to beset the literature on the period, which misunderstands the Enigma weaknesses and therefore inhibits broader thinking about design or realising the critical role of human factors engineering in cryptography. [ABSTRACT FROM AUTHOR]

Sparse coding or sparse dictionary learning has been widely used to recover underlying structure in many kinds of natural data. Here, we provide conditions guaranteeing when this recovery is universal; that is, when sparse codes and dictionaries are unique (up to natural symmetries). Our main tool is a useful lemma in combinatorial matrix theory that allows us to derive bounds on the sample sizes guaranteeing such uniqueness under various assumptions for how training data are generated. Whenever the conditions to one of our theorems are met, any sparsity-constrained learning algorithm that succeeds in reconstructing the data recovers the original sparse codes and dictionary. We also discuss potential applications to neuroscience and data analysis. [ABSTRACT FROM PUBLISHER]

This paper details recent extensions to the HEVC/H.265 video compression standard, notably the inclusion of higher bit depths, enhanced color sampling, and different types of scalability. It describes the implementation of enhanced HEVC/H.265 encoders that extend the capabilities, performance, and functionalities of previously available encoders. It presents a new set of higher-quality requirements and how those can be satisfied. It explains different types of scalability and how they can be used to facilitate the transition to new services and to increase the functionality of existing ones. The paper concludes with some implementation challenges and shows how to address them. [ABSTRACT FROM AUTHOR]

Phase induced intensity noise (PIIN) and multiple access interference (MAI) are the main parameters that affect the performance of optical code division multiple access (OCDMA) systems, leading to degradations in system performance and reduction in the number of active users. So, this paper presents an efficient modified multi-service (MMS) code that can be used for encoding the spectral amplitude of the optical source in OCDMA systems to avoid these limitations. The proposed code disposes the effect of MAI, PIIN, and gives better performance than the other traditional codes. It can support a large number of active users (80 at bit error rate of 10) with a small code weight ( w = 4). Also, it achieves a practical code length with a simple receiver structure. [ABSTRACT FROM AUTHOR]

This paper focuses on 16-QAM labelings of bit-interleaved space-time coded modulation with iterative decoding (BI-STCM-ID). What is contributed is an algorithm to generate (with no random search) optimal labelings for BI-STCM-ID systems with any number of transmit- and receive antennas, transmitting over Rayleigh fading channel. Along with the algorithm, a couple of corollaries are brought, which give an account of the optimal labelings' features. Having a complete set of optimal 16-QAM BI-STCM-ID labelings at hand, it is possible to advance research on labeling diversity scheme by finding all such labeling pairs that-if applied to a system with two different labeling maps within adjacent transmit streams-bring maximum asymptotic coding gain . [ABSTRACT FROM AUTHOR]

Channel quality indicator (CQI) feedback in long-term evolution (LTE) system is an essential technique in describing the instantaneous channel state information. The CQI calculations highly depend on the accuracy of the channel estimation process in order to assign appropriate modulation and coding scheme. However, one of the critical issues affecting the LTE system performance is obtaining the CQI for each transmission period which will inevitably cost many resources. Therefore, an appropriate method for reducing CQI feedback overhead along with accurate channel estimation technique is required to manage the allocated resources and obtains significant improvements in system performance. In this paper, an adaptive threshold feedback compression scheme based on CQI scheme is proposed to obtain better system performance in terms of system throughput and error rate in LTE system. This proposed adaptive scheme dynamically adapts its threshold level to the signal to noise ratio variations, thus increasing the throughput and reducing the CQI feedback overhead. Results show that the proposed CQI based adaptive threshold feedback compression scheme enhances the tradeoff between system throughput and block error rate. [ABSTRACT FROM AUTHOR]

In the context of fix-free codes, the most important and immediate consequence of the 3/4-conjecture (if it is proven), is that the redundancy of an optimal binary fix-free code never exceeds 1 bit, as with the optimal prefix-free codes, i.e. Huffman codes. In this paper, this bound on the redundancy is proven without requiring the conjecture to be true. To do so, we use two known sufficient conditions for the existence of binary fix-free codes to derive an improved upper bound on the redundancy of an optimal fix-free code in terms of the largest symbol probability. [ABSTRACT FROM AUTHOR]

A hardwired design of embedded compression engine targeting the reduction of full high-definition (HD) video transmission bandwidth over the wireless network is developed. It adopts an intra-coding framework and supports both lossless and rate-controlled near lossless compression options. The lossless compression algorithm is based on a simplified Context-Based, Adaptive, Lossless Image Coding (CALIC) scheme featuring pixelwise gradient-adjusted prediction and error-feedback mechanism. To reduce the implementation complexity, an adaptive Golomb-Rice coding scheme in conjunction with a context modeling technique is used in lieu of an adaptive arithmetic coder. With the measures of prediction adjustment, the near lossless compression option can be implemented on top of the lossless compression engine with minimized overhead. An efficient bit-rate control scheme is also developed and can support rate or distortion-constrained controls. For full HD (previously encoded) and nonfull HD test sequences, the lossless compression ratio of the proposed scheme, on average, is 21% and 46%, respectively, better than the Joint Photographic Experts Group-Lossless Standard and the Fast, Efficient Lossless Image Compression System (FELICS) schemes. The near lossless compression option can offer additional 6%–20% bit-rate reduction while keeping the Peak Signal-to-Noise Ratio value 50 dB or higher. The codec is further optimized complexity-wise to facilitate a high-throughput chip implementation. It features a five-stage pipelined architecture and two parallel computing kernels to enhance the throughput. Fabricated using the Taiwan semiconductor manufacturing company 90-nm complementary metal-oxide–semiconductor technology, the design can operate at 200 MHz and supports a 64 frames/s processing rate for full HD videos. [ABSTRACT FROM AUTHOR]

In this article, we formalize a torsion ℤ-module and a torsion-free ℤ-module. Especially, we prove formally that finitely generated torsion-free ℤ-modules are finite rank free. We also formalize properties related to rank of finite rank free ℤ-modules. The notion of ℤ-module is necessary for solving lattice problems, LLL (Lenstra, Lenstra, and Lovász) base reduction algorithm [20], cryptographic systems with lattice [21], and coding theory [11]. [ABSTRACT FROM AUTHOR]