Sensei: Enforcing secure coding guidelines in the integrated development environment

We discuss the potential benefits, requirements, and implementation challenges of a security-by-design approach in which an integrated development environment plugin assists software developers to write code that complies with secure coding guidelines. We discuss how such a plugin can enable a company's policy-setting security experts and developers to pass their knowledge on to each other more efficiently, and to let developers more effectively put that knowledge into practice. This is achieved by letting the team members develop customized rule sets that formalize coding guidelines and by letting the plugin check the compliance of code being written to those rule sets in real time, similar to an as-you-type spell checker. Upon detected violations, the plugin suggests options to quickly fix them and offers additional information for the developer. We share our experience with proof-of-concept designs and implementations rolled out in multiple companies, and present some future research and development directions.     

粮仓环境监测系统设计

随着科学技术的发展,粮食行业信息化发展得到了强有力的科技支撑。为满足粮库整体信息化建设的要求,打破"信息孤岛"现状,实现资源整合、数据共享,为大数据分析和数据应用提供数据基础,设计一款能够实时采集粮仓内温湿度、氧气、二氧化碳气体浓度、粮堆高度的数据集成系统。系统采用分层分布式结构,由数据集中器和多种传感器模块组成,数据集中器与各传感器模块间通过RS485总线进行数据通讯,并由数据集中器通过网络专线传输汇总的环境监测数据,通过专用软件进行数据处理和挖掘,从而实现粮仓环境监测和预警等功能。     

基于MR弱覆盖提升TD-LTE终端驻留比的方法

LTE驻留比作为LTE网络优化的重要参数，移动在多网并存的情况下，令更多的用户体验到更快更好的网络是运营商的奋斗目标。本文通过调整弱覆盖参数的方法来提高LTE驻留比及MR覆盖率，从而让更多的用户驻留在4G上，实验证明该方法对LTE驻留比的提升有一定作用。     

3D holoscopic image coding scheme using HEVC with Gaussian process regression

3D holoscopic image, also known as integral imaging, light field imaging and plenoptic imaging, can provide a natural and fatigue-free 3D visualization. However, a large amount of data is required to represent the 3D holoscopic content. Therefore, efficient coding schemes for such particular type of image are needed. In this paper, we propose a Gaussian process regression based prediction scheme to compress the 3D holoscopic image. In the proposed scheme, the coding block and its prediction supports are modeled as a Gaussian process (GP) and Gaussian process regression (GPR) is used to obtain a better prediction of the coding block. Limited searching windows in horizontal and vertical directions are used to obtain the prediction supports, and a filtration method is designed to judge the reliability of the obtained prediction supports. Moreover, in order to alleviate the high complexity caused by GPR, a sparsification method is also put forward. Experimental results demonstrate the advantage of the proposed scheme for 3D holoscopic image coding in terms of different quality metrics as well as the visual quality of the views rendered from decompressed 3D holoscopic content, compared to the HEVC intra-prediction method and several other prediction methods in this field.     

Two-Phase Bidirectional Dual-Relay Selection Strategy for Wireless Relay Networks

In this article, we introduce a new bi-directional dual-relay selection strategy with its bit error rate (BER) performance analysis. During the first step of the proposed strategy, two relays out of a set of N relay-nodes are selected in a way to optimize the system performance in terms of BER, based on the suggested algorithm which checks if the selected relays using the max-min criterion are the best ones. In the second step, the chosen relay-nodes perform an orthogonal space-time coding scheme using the two-phase relaying protocol to establish a bi-directional communication between the communicating terminals, leading to a significant improvement in the achievable coding and diversity gain. To further improve the overall system performance, the selected relay-nodes apply also a digital network coding scheme. Furthermore, this paper discusses the analytical approximation of the BER performance of the proposed strategy, where we prove that the analytical results match almost perfectly the simulated ones. Finally, our simulation results show that the proposed strategy outperforms the current state-of-the-art ones.     

Image denoising via sparse coding using eigenvectors of graph Laplacian

Image denoising plays an important role in image processing, which aims to separate clean images from the noisy images. A number of methods have been presented to deal with this practical problem in the past decades. In this paper, a sparse coding algorithm using eigenvectors of the graph Laplacian (EGL-SC) is proposed for image denoising by considering the global structures of images. To exploit the geometry attributes of images, the eigenvectors of the graph Laplacian, which are derived from the graph of noised patches, are incorporated in the sparse model as a set of basis functions. Sequently, the corresponding sparse coding problem is presented and efficiently solved with a relaxed iterative method in the framework of the double sparsity model. Meanwhile, as the denoising performance of the EGL-SC significantly depends on the number of the used eigenvectors, an optimal strategy for the number selection is employed. A parameter called as out-of-control rate is set to record the percentage of the denoised patches that suffer from serious residual errors in the sparse coding procedure. Thus, with the eigenvector number increasing, the appropriate number can be heuristically selected when the out-of-control rate falls below an empirical threshold. Experiments illustrate that the EGL-SC can achieve a better performance than some other well-developed denoising methods, especially in the structural similarity index for the noise of large deviations.     

Disparity-based just-noticeable-difference model for perceptual stereoscopic video coding using depth of focus blur effect

Human 3D perception provides an important clue to the removal of redundancy in stereoscopic 3D (S3D) videos. Because objects outside the binocular fusion limit cannot be fused on retina, the human visual system (HVS) makes them blur according to the depth-of-focus (DOF) effect to increase the binocular fusion limit and suppress diplopia, i.e. double vision. Based on human depth perception, we propose a disparity-based just-noticeable-difference model (DJND) to save bit-rate and improve visual comfort in S3D videos. We combine the DOF blur effect with conventional JND models in the pixel domain into DJND. Firstly, we use disparity information to get the average disparity value of each block. Then, we integrate the DOF blur effect into luminance JND (LJND) by a selective low pass Gaussian filter to minimize the visual stimulus in S3D videos. Finally, we incorporate disparity information into the filtered JND models to obtain DJND. Experimental results demonstrate that the proposed method successfully improves both image quality and visual comfort in viewing S3D videos without increasing the bit-rate.     

新型瓦斯检测系统硬件设计

针对矿用瓦斯检测系统中使用传感器的特点以及工作环境,加入温度、湿度数据采集环节,在软件算法方面提高测量准确度。设计中主要采用高共模抑制比的差分放大电路、开关电容滤波器提高信号源的精确度,同时抑制电源噪声以提高系统抗干扰性。     

Generalization of recommender systems: Collaborative filtering extended to groups of users and restricted to groups of items

In this paper we present a collaborative filtering method which opens up the possibilities of traditional collaborative filtering in two aspects: (1) it enables joint recommendations to groups of users and (2) it enables the recommendations to be restricted to items similar to a set of reference items. By way of example, a group of four friends could request joint recommendations of films similar to “Avatar” or “Titanic”. In the paper, using experiments, we show that the traditional approach of collaborative filtering does not satisfactorily resolve the new possibilities contemplated; we also provide a detailed formulation of the method proposed and an extensive set of experiments and comparative results which show the superiority of designed collaborative filtering compared to traditional collaborative filtering in: (a) number of recommendations obtained, (b) quality of the predictions, (c) quality of the recommendations. The experiments have been carried out on the databases Movielens and Netflix.     

Syntactic compression codes at the zero entropy point

Syntactic compression codes compress the tree, which is the syntax of a binary source message. The ones considered here originate from image processing. The syntactic trees usedhave a constant valency and their binary labels distinguish whether the source substring derived from a node is completely zero or not. We compress them simply by deleting some redundant subtrees.

These codes fall into a theoretically new class of codes which is wider than the classical ones. They are here studied in the neighborhood of a zero of the binary entropy function. There, their behavior is close to that of an infinite run length encoding and the optimum valency is three. Finally, we open a problem, related with automata theory, which perhaps could provide a further link between Information Theory and Algorithmic Information Theory.