基于动态贝叶斯网络的社交圈归属匹配模型

为了帮助社交网中新成员寻找与之最为合适的社交圈,尝试采用动态贝叶斯网（DBN）理论解决社交网分析应用中成员（节点）与社交圈（集合）的匹配问题。将圈内成员个人的多项兴趣爱好程度作为描述社交圈基本属性的特征向量,对每一类圈子建立了带有辅助信息形式的DBN模型,求解最大输出概率即为最佳匹配对象。结果表明,在客观测试和主观评价两方面,该模型都收到了较为满意的结果。     

无线传感器网络路由协议及安全问题研究

无线传感器网络在军事和民用领域得到广泛的应用。由于传感器节点的资源有限以及通信的开放性使得其安全性显得尤为重要。出于对能量消耗的考虑,目前的路由协议设计得比较简单,作者对路由的安全性能以及可能受到的攻击进行分析,并给出相应的防范对策。     

Error compensation in machine tools: a neural network approach

For a non-idealized machine tool, each point in the workspace is associated with a tool point positioning error vector. If this error map can be determined, then it is possible to substantially improve the positioning performance of the machine by introducing suitable compensation into the control loop. This paper explores the possibility of using an artifical neural network (ANN) to compute this mapping. The training set for the ANN is obtained by mounting a physical artifact whose dimensions are precisely known in the machine's workspace. The machine, equipped with a touch trigger probe, measures the positions of features on the artifact. The difference between the machine reading and the known dimension is the machine error at that point in the workspace. Using standard modeling techniques, the kinematic error model for a CNC turning center was developed. This model was parameterized by measurement of the parametric error functions using a laser interferometer, electronic levels and a precision square. The kinematic model was then used to simulate the artifact-measuring process and develop the ANN training set. The effect of changing artifact geometry was explored and a machining operation was simulated using the ANN output to provide compensation. The results show that the ANN is capable of learning the error map of a real machine, and that ANN-based compensation can significantly reduce part-dimensional errors.     

Design of a 2-DOF-PID controller using an improved sine–cosine algorithm for load frequency control of a three-area system with nonlinearities

This paper proposes an improved sine–cosine algorithm (ISCA) based 2-DOF-PID controller for load frequency control. A three-area test system is built for study, while some physical constraints (nonlinearities) are considered for the investigation of a realistic power system. The proposed method is used as the parameter optimizer of the LFC controller in different scenarios. The 2-DOF-PID controllers are used because of their capability of fast disturbance rejection without significant increase of overshoot in set-point tracking. The 2-DOF-PID controllers’ efficacy is observed by examining the responses with the outcomes obtained with PID and FOPID controllers. The simulation results with the suggested scheme are correlated with some of the existing algorithms, such as SCA, SSA, ALO, and PSO in three different scenarios, i.e., a disturbance in two areas, in three areas, and in the presence of physical constraints. In addition, the study is extended to a four-area power system. Statistical analysis is performed using the Wilcoxon Sign Rank Test (WSRT) on 20 independent runs. This confirms the supremacy of the proposed method.     

Transfer Learning on Deep Neural Networks to Detect Pornography

While the internet has a lot of positive impact on society, there are negative components. Accessible to everyone through online platforms, pornography is, inducing psychological and health related issues among people of all ages. While a difficult task, detecting pornography can be the important step in determining the porn and adult content in a video. In this paper, an architecture is proposed which yielded high scores for both training and testing. This dataset was produced from 190 videos, yielding more than 19 h of videos. The main sources for the content were from YouTube, movies, torrent, and websites that hosts both pornographic and non-pornographic contents. The videos were from different ethnicities and skin color which ensures the models can detect any kind of video. A VGG16, Inception V3 and Resnet 50 models were initially trained to detect these pornographic images but failed to achieve a high testing accuracy with accuracies of 0.49, 0.49 and 0.78 respectively. Finally, utilizing transfer learning, a convolutional neural network was designed and yielded an accuracy of 0.98.     

从法律视角看网络泄密

随着互联网用户的剧增,网络安全成为困扰中国互联网健康发展的重要问题之一。与此同时,日趋严重的网络泄密问题已逐渐成为与黑客入侵、病毒袭击、垃圾邮件、流氓插件并行的第五大网络安全隐患．从法律角度来看,网路泄密实质上是对网络隐私权的侵犯,笔者通过对网路隐私权的分析,从现行法律制度与未来法律制度来解读网络泄密。     

网络教学平台在计算机语言类课程教学中应用的反思

根据教学实践,文章深入分析计算机语言类课程的教学现状;提出网络教学平台作为传统教学方式的一种重要的辅助工具,在丰富教学内容、提高教学质量、拓展教学空间和时间、促进教学改革等方面具有明显的优势;同时也指出在当前网络教学平台的利用过程中存在着网络资源匮乏、利用率低等不足之处,并提出了相应解决对策和措施。     

Approximate dynamic programming solutions with a single network adaptive critic for a class of nonlinear systems

Approximate dynamic programming (ADP) formulation implemented with an adaptive critic (AC)-based neural network (NN) structure has evolved as a powerful technique for solving the Hamilton-Jacobi-Bellman (HJB) equations. As interest in ADP and the AC solutions are escalating with time, there is a dire need to consider possible enabling factors for their implementations. A typical AC structure consists of two interacting NNs, which is computationally expensive. In this paper, a new architecture, called the ‘cost-function-based single network adaptive critic (J-SNAC)’ is presented, which eliminates one of the networks in a typical AC structure. This approach is applicable to a wide class of nonlinear systems in engineering. In order to demonstrate the benefits and the control synthesis with the J-SNAC, two problems have been solved with the AC and the J-SNAC approaches. Results are presented, which show savings of about 50% of the computational costs by J-SNAC while having the same accuracy levels of the dual network structure in solving for optimal control. Furthermore, convergence of the J-SNAC iterations, which reduces to a least-squares problem, is discussed; for linear systems, the iterative process is shown to reduce to solving the familiar algebraic Ricatti equation.     

医院网络安全的技术实现与改进

随着信息科技的高速发展,网络在越来越多地为人们生活提供便利的同时,也为医院节省了大量的人力和物力,如何在现有的条件下,搞好局域网络的安全,是医院内网络管理人员的一个重要课题.本文从系统安全、网络运行安全和内部网络安全分析,并应用到实践中,以保证网络安全.     

"震网"引发网络安全新思考

本文概述了近期发生的"震网"事件.同时分析了"震网"的特点和行为特征.并根据我国的具体情况给出了安全警示和安全防范建议.