应用软件可信要素实现方法研究

软件可信是指软件系统能按照其设定目标所期望的方式运行,能适应环境和需求的变化,有抵御异常情况的能力,在受到干扰时仍能持续提供服务。为了验证软件在真实运行环境中的实际行为是否与其期望的功能相符,需要在软件中嵌入一系列可信要素。本文讨论了如何通过安全编译等手段在软件中加入可信要素,真实的监测软件运行的实际行为,并结合软件行为声明,提供对软件可信度量的数据基础。     

A general technique to embed non-uniform discontinuities into standard solid finite elements

A general technique to embed non-uniform displacement discontinuities into standard solid finite elements is presented. The technique is based on the decomposition of the kinematic fields into a component related to the deformation of the solid portion of the element and one related to the rigid-body motion due to a displacement discontinuity. This decomposition simplifies the incorporation of discontinuity interfaces and provides a suitable framework to account for non-uniform discontinuity modes. The present publication addresses two families of finite element formulations: displacement-based and stress hybrid finite element.     

An overview of rate control techniques in HEVC and SHVC video encoding

Video standards are crucial for exchanging video content, enabling a myriad of services and supporting a wide variety of devices ranging from personal devices to clouds and IoT. One of the core requirements in video standards is the rate control that regulates the bit allocation and picture quality. This paper presents an overview of rate control techniques in the HEVC video coding standard. While providing an insight into the rate control mechanism specific to HEVC, it describes the basic operating principle of rate control algorithms, including their essential parameter, outputs, and performance measures. We review rate control in past coding standards and bring out the basic features of HEVC that drive the need for new rate control algorithms. Alongside, we delineate the Rate-Distortion model-based taxonomy of various algorithms, including their classification criteria. The paper gives out another classification of the rate control algorithms based on their basic principle and mechanisms. The article also explains the scalable extension of HEVC, namely SHVC, while highlighting some of the possible SHVC rate control design challenges. Finally, we present some of the unresolved research issues in HEVC rate control and outline possible future research directions.

     

The use of colour in language syntax analysis

The use of colour to reflect the syntax of typed-in language statements can make a language processor much more user-friendly. This paper shows how colour has been used in MicroCODIL and suggests ways in which the approach could be applied to other systems.     

Performance analysis of inter-layer prediction in scalable extension of HEVC (SHVC) for adaptive media service

Scalable video coding (SVC) has been a popular research topic to provide an adaptive media service for many years. To deliver very high quality content such as ultra high definition (UHD) video in various environment, a scalable extension of high efficiency video coding (SHVC) has been developed by the Joint Collaborative Team on Video Coding (JCT-VC) of ISO/IEC MPEG and ITU-T VCEG. This paper introduces the SHVC standard technology and analyzes the performance of inter-layer prediction as an important feature. Unlike the previous scalable video coding technologies, the SHVC standard employs a multi-loop decoding structure. Also, inter-layer prediction scheme is used to remove the redundancy between layers when encoding enhancement layer syntax elements, such as motion parameters and the intra prediction mode. This paper reviews inter-layer prediction techniques that have been developed for the SHVC standard. The performance of inter-layer prediction techniques is verified and analyzed using the SHVC reference software 5.0.     

HAS QoE prediction based on dynamic video features with data mining in LTE network

Evaluation of HTTP adaptive streaming (HAS) quality of experience (QoE) over LTE network is a challenging topic because of multi-segment and multi-rate features of dynamic video sequences. Different from the traditional QoE evaluation methods based on network parameters, this paper proposes the HAS QoE prediction methods based on its dynamic video segment features with data mining. Considering the application requirement of the trade-off between accuracy and complexity, two sets of methodologies are designed to evaluate the HAS QoE including regression and classification. In regression method, we propose the evolved PSNR (ePSNR) model using differential peak signal to noise ratio (dPSNR) statistics as the segment features to evaluate HAS QoE. In classification method, we propose the improved weighted k-nearest neighbors (WkNN) by using dynamic weighted mapping according to the position of video chunk to meet the dynamic segment and rate features of HAS. In order to train and test these methods, we build a real-time HAS video-on-demand (VOD) system in LTE network and do subjective test in different video scenes. With the mean opinion score (MOS), the regression and classification methods are trained to predict the HAS QoE. The validated results show that the proposed ePSNR and WkNN methods outperform other evaluation methods.     

A comparison of algorithms for data base compression by use of fragments as language elements

The paper describes the advantages of using variable length equifrequent fragments as the language elements for compression coding of large data bases. The problem of finding the minimum space representation of the fragment compressed data base is equivalent to solving a shortest path problem. Three alternate algorithms for compression are described and their performance is tested on both word and text fragments. It is found that text fragments selected by a longest match algorithm produce the best results with regard to compression and use of processing time.     

NDNetGaming - development of a no-reference deep CNN for gaming video quality prediction

Multimedia Tools and Applications - Gaming video streaming services are growing rapidly due to new services such as passive video streaming of gaming content, e.g. Twitch.tv, as well as cloud...     

A low complexity detection method for video data discontinuity implemented on SoC-FPGA by using pixel location prediction scheme

Multimedia Tools and Applications - Image/video processing in real-time is always in high demand for the quality of video. There are several factors which cause the loss of the video content, such...     

A combined approach to ensure data security in cloud computing

Cloud computing is a forthcoming revolution in information technology (IT) industry because of its performance, accessibility, low cost and many other luxuries. It is an approach to maximize the capacity or step up capabilities vigorously without investing in new infrastructure, nurturing new personnel or licensing new software. It provides gigantic storage for data and faster computing to customers over the internet. It essentially shifts the database and application software to the large data centers, i.e., cloud, where management of data and services may not be completely trustworthy. That is why companies are reluctant to deploy their business in the cloud even cloud computing offers a wide range of luxuries. Security of data in cloud is one of the major issues which acts as an obstacle in the implementation of cloud computing. In this paper, a frame work comprising of different techniques and specialized procedures is proposed that can efficiently protect the data from the beginning to the end, i.e., from the owner to the cloud and then to the user. We commence with the classification of data on the basis of three cryptographic parameters presented by the user, i.e., Confidentiality (C), Availability (A) and Integrity (I).The strategy followed to protect the data utilizes various measures such as the SSL (Secure Socket Layer) 128-bit encryption and can also be raised to 256-bit encryption if needed, MAC (Message Authentication Code) is used for integrity check of data, searchable encryption and division of data into three sections in cloud for storage. The division of data into three sections renders supplementary protection and simple access to the data. The user who wishes to access the data is required to provide the owner login identity and password, before admittance is given to the encrypted data in Section 1, Section 2, and Section 3.     

AVS解码器自适应帧内预测的硬件实现

分析了先进音视频编码标准（Audio and Video Standard,AVS）的帧内预测算法,提出了实现自适应帧内预测的硬件架构。该硬件架构采用8×8块级自适应流水线,利用滑动窗口获取片上存储器中的参考样本,使用8个并行的处理单元（PE）计算预测值,用脉动阵列实现复杂色度Plane模式预测值的计算。基于Verilog HDL硬件描述语言实现设计并进行功能验证,仿真和综合结果表明设计符合要求。     

The combined use of axi-symmetric and solid elements for three dimensional stress analysis

This paper presents a simple but effective finite element technique to analyze the realistic compound structures composed of axi-symmetric as well as asymmetric components for which axi-symmetric elements are adopted to deal with axi-symmetric portions and solid elements are employed only for the rest of asymmetric parts. The connections between adjacent axi-symmetric and solid elements are achieved through the use of a Lagrangean multiplier technique and the inter-element compatibility conditions are also satisfied. Monotone convergence of the solutions is thus guaranteed. Several numerical experiments are carried out to demonstrate the versatility and high efficiency of this work. Excellent correlations between the calculated results and the referenced solutions obtained by the complete three dimensional analysis can be found. Since no restrictions are imposed on the formulation of this work, the present technique is quite general and can be further extended to deal with other types of elements considered.     

Artificial neural network prediction of clozapine response with combined pharmacogenetic and clinical data

Although one third to one half of refractory schizophrenic patients responds to clozapine, however, there are few evidences currently that could predict clozapine response before the use of the medication. The present study aimed to train and validate artificial neural networks (ANN), using clinical and pharmacogenetic data, to predict clozapine response in schizophrenic patients. Five pharmacogenetic variables and five clinical variables were collated from 93 schizophrenic patients taking clozapine, including 26 responders. ANN analysis was carried out by training the network with data from 75% of cases and subsequently testing with data from 25% of unseen cases to determine the optimal ANN architecture. Then the leave-one-out method was used to examine the generalization of the models. The optimal ANN architecture was found to be a standard feed-forward, fully-connected, back-propagation multilayer perceptron. The overall accuracy rate of ANN was 83.3%, which is higher than that of logistic regression (LR) (70.8%). By using the area under the receiver operating characteristics curve as a measure of performance, the ANN outperformed the LR (0.821+/-0.054 versus 0.579+/-0.068; p<0.001). The ANN with only genetic variables outperformed the ANN with only clinical variables (0.805+/-0.056 versus 0.647+/-0.066; p=0.046). The gene polymorphisms should play an important role in the prediction. Further validation of ANN analysis is likely to provide decision support for predicting individual response.     

基于FPGA的AVS帧内预测电路设计

提出了一种AVS高清视频编码器帧内预测模块硬件结构。通过对AVS帧内预测各个预测模式的分析,设计了帧内预测编码流水线结构和模式预测运算单元电路。根据各预测模式的编码运算关系,合理安排流水线结构,采用8 bit数据并行流水处理,实现了高清视频帧内预测实时编码。将除Plane模式之外的其他预测模式采用同一硬件电路来实现,对运算比较复杂的Plane模式单独设计了硬件结构,节省了硬件资源。     

A fast and efficient saliency detection model in video compressed-domain for human fixations prediction

Multimedia Tools and Applications - Research and application of human fixations detection in video compressed-domain have gained an increasing attention in the latest years. However, both...     

Evaluating the use of problem-based video podcasts to teach mathematics in higher education

Problem-based video podcasts provide short, web-based, audio-visual explanations of how to solve specific procedural problems in subject areas such as mathematics or science. A series of 59 problem-based video podcasts covering five key areas (operations with functions, solving equations, linear functions, exponential and logarithmic functions, and trigonometric functions) were created as self-study tools and used by 288 higher education students to acquire pre-calculus skills over a three week period. The results indicated that a majority of students used the video podcasts frequently, rated them as useful or very useful, viewed them as easy to use, effective learning tools, and reported significant knowledge gains in pre-calculus concepts.     

A data mining application to deposit pricing: Main determinants and prediction models

This study provides unique empirical evidence regarding the determinants of deposit pricing by employing data mining methods and making use of proprietary data provided by a commercial bank. Results highlight the importance of taking into account customer- and account-specific characteristics in the determination of deposit rates. Contrary to existing evidence obtained from macro-level bank data, the customer-level data used in this study suggest that depositors with a multi-faceted and long-term relationship with the same bank seem to benefit from higher deposit rates as a reward for being a core depositor. The location of the customer is also shown to have a limited effect on the deposit rates.     

数据挖掘在电信行业客户流失预测中的应用

客户流失是电信行业发展过程中所面临的一个严重问题,直接影响到运营商的企业效益。本文主要介绍了对电信行业客户流失情况进行数据挖掘的过程,改进了已有模型存在的缺乏灵活性、难以处理高维度数据的缺点,根据运营商的历史数据资料,利用SAS/EM模块对客户的固有特征和行为特征进行挖掘分析,采用决策树分类算法的CART算法建立了聚类分析模型和包括评估模块在内的一套完整的流失预测模型,能够直观地显示出流失客户的基本特征,并且可以对任意的数据集进行分析,有效提高了模型的普遍应用性和准确性。