浅析变电站运行安全措施与管理

电力系统最主要的构成部分就是变电站，肩负着许多义务，包括改变电压级别，集合分配电能。变电站能够正常运行，最重要的就是运行管理。本文就变电站运行管理的定义与关键点进行讨论，研究管理内容，运行措施，分析故障原因，制定出最合理的变电站运行管理计划。     

基于高压隔离开关发热的原因及措施分析

高压隔离开关是电网在运行过程中重要的组成部分,主要的作用就是隔离,由于其特殊的特点,长期以来,都是电力系统中使用量较为广泛的设备。在电力系统中,高压隔离开关在接通高压线路、无载情况下断开设备以及检修时对电气进行隔离,更好的保证高压隔离开关处于正常的工作状态,确保线路安全运行,同时为人们的生命财产安全提供保障。基于此基础上,本文通过对高压隔离开关发热的原因分析及措施进行分析,以期能够为界内的相关人士提相关的参考资料。     

分析汽轮机异常振动的原因及应对措施

作为火电厂中关键设备的汽轮机,其能否正常的运行将会对火电厂的稳定与安全造成最为直接的影响。因为在汽轮机使用的过程当中不可能避免各种故障的发生与出现,而其中的异常振动又是这些问题里最为常见而且最为难以确定的一种状况。本文首先是较为简单的分析了汽轮机异常震动的现象,又进一步的探讨了汽轮机的异常振动的原因以及应对的措施,这样做对有使得汽轮机的异常振动问题有效的解决以及促使火电厂安全的运行具有着非常重要的意义。     

浅谈计算机网络信息安全及其防护措施

在时代飞速发展的过程中,互联网得到了普及应用,对人们的生活和工作方式造成了巨大的改变,让人们的生活更加便捷,但是也带来了一些信息安全隐患,影响到计算机网络的正常使用。针对这种情况,就需要采取相应的防护措施,保证计算机网络信息安全。本文简要分析了计算机网络信息安全及防护措施,希望能够提供一些有价值的参考意见。     

关于水电站运行管理节能措施分析及运用效果研究

水电站运行管理的节能效果直接影响着水电站发电过程中对水资源和电能的损耗,影响着水电站发电的总量和效率,关系到水电站是否能够创造更多的经济效益和社会效益。本文从水电站运行的几个方面着手进行分析和探讨,分析影响水电站中水资源损耗、电能损耗的主要原因,探讨提升水电站运行管理效果和节能效果的方式方法,以及水电站应用节能措施后的运行管理效果,目的在于推动水力发电这一潜力巨大的发电方式实现优化升级,使水电站的环保效益和经济效益接近最大程度。     

浅析电能计量装置综合误差的造成和采取的措施

在电力系统正常运行的过程中,一定要采取有效的措施来降低电能计量装置的综合误差,才能体现我国基础设施使用过程中的公平公正原则,以提高电力企业获得的经济效益。文中概述了产生电能计量装置综合误差的原因,阐述了降低电能计量装置综合误差的措施,有效保证了电力系统中电能计量装置电能计量的精确性。     

电力调度自动化系统中通信网络故障分析与解决措施

随着电力系统的不断发展,越来越广泛地开始应用自动化通信网络技术,然而,在广泛应用自动化通信网络技术的同时,电力调度系统的通信网络组成变得越来越复杂。所以,电力调度自动化系统中的通信网络技术在其安全性以及可靠性上都无法得到保障。为了能够让电力调度系统中的通信网络正常运行得到保障,本文对电力调度自动化系统中通信网络技术产生故障的主要原因进行了分析,同时针对其原因提出了一些解决措施,希望可以有助于电力调度自动化系统的正常运行。     

10kV配电线路故障原因跳闸分析

近年来,国民经济飞速发展,电力事业也随之进入了快速发展时期.电网能否安全稳定的运行,直接关系到用户的切身利益,因而越来越受到社会各界的广泛重视.10kV配电线路作为电压等级较低、更接近人们日常生活的电力网络,其运行方式多样、运行环境复杂等因素导致其安全可靠性远远低于高电压等级电网.在日常的运行管理中,因各种原因引起线路跳闸的情况时有发生,故障原因种类繁多,原因查找困难,不仅影响用户的正常用电,也给用户带来较大的经济损失.为了进一步提高配电网安全运行的水平,本文就10kV配网常见的线路故障及跳闸原因进行了简要的分析,并阐述了预防跳闸故障的有效措施.     

配电线路故障原因和运维管理控制

在电力系统中,配电线路是非常重要的组成部分,要想保证电力系统能够正常运转,就首先要保证配电线路能够安全稳定的运行,这是保障电力系统最为可靠和稳定的条件之一.所以,在电力系统实际运行过程中切实加强对于配电线路的运行管理是非常有必要的.本文主要分析了配电线路出现故障的具体原因,并且针对不同的原因,简要探讨了对于电力系统配电线路的运行管理控制措施,希望能给我国有关部门和企业提供可借鉴之处.     

电力调度自动化系统中通信网络故障分析与解决措施

在电力系统的发展过程中,自动化通信网络技术在各企业中应用的越来越广泛,但是在得到广泛应用的同时,电力调度系统的通信网络组成也越来越繁琐,因此影响了电力调度自动化系统中的通信网络技术的安全性与可靠性。为了保障电力调度系统中通信网络的正常运行,文章主要分析电力调度自动化系统中通信网络技术所产生的故障原因,并根据该原因提出解决措施,从而为电力调度自动化系统的正常运行提供相应胡技术支持。     

The role of online news and social media in preventive action in times of infodemic from a social capital perspective: The case of the COVID-19 pandemic in South Korea

Infodemic, the spread of false information during the COVID-19 pandemic, has been raised as one of the major concerns aggravating the confusion in the global society. In this regard, the role of media as an information channel in delivering the reliable information and motivating the active participation of citizens in complying with government’s preventive actions becomes much more important. In this study, the role of online news and social media on people’s preventive actions considering the role of trust in citizens and government from the perspective of social capital is investigated. For the empirical study, a structural equation modeling is employed by using survey material gathered from South Korea in the early days of the COVID-19 outbreak. South Korea was selected as its COVID-19 prevention strategy focused not only on the provision of medical support, but also on the enhancement of social trust through active engagement with people through media channels. Our results reveal that the perceived characteristics of online news and social media influence preventive actions through the trust in citizens or in government. In addition, while online news media enhances trust in both the citizens and the government, social media only influences trust in citizens. Based on our findings, the role of media in preventing the spread of COVID-19 is dicussed.     

Complex Network-based features extraction in RGB-D human action recognition

Analysis of human behavior through visual information has been one of the active research areas in computer vision community during the last decade. Vision-based human action recognition (HAR) is a crucial part of human behavior analysis, which is also of great demand in a wide range of applications. HAR was initially performed via images from a conventional camera; however, depth sensors have recently embedded as an additional informative resource to cameras. In this paper, we have proposed a novel approach to largely improve the performance of human action recognition using Complex Network-based feature extraction from RGB-D information. Accordingly, the constructed complex network is employed for single-person action recognition from skeletal data consisting of 3D positions of body joints. The indirect features help the model cope with the majority of challenges in action recognition. In this paper, the meta-path concept in the complex network has been presented to lessen the unusual actions structure challenges. Further, it boosts recognition performance. The extensive experimental results on two widely adopted benchmark datasets, the MSR-Action Pairs, and MSR Daily Activity3D indicate the efficiency and validity of the method.     

A Bayes procedure for estimation of current system reliability

During development of a new system, a test-analyze-and-fix program is often applied to eliminate the flaws in the first design of the system. If the corrective actions are effective, the system reliability increase. This process can be carried out for a planned time period or until a fixed reliability goal is achieved. In both cases, it is important to evaluate the system reliability during the test phase. Reliability growth can be reasonably modeled by a nonhomogeneous Poisson process with a decreasing power intensity law. For such a process, a Bayes procedure for estimating the failure intensity at the time of the last failure and of the current system reliability is analyzed for failure-truncated sampling. A large simulation study shows that the procedure, even for vague prior information, is more efficient than maximum likelihood and at least as efficient as the quasi-Bayes method of J.J. Higgins and C.P. Tsokos (1981)     

Characterization of EMG Patterns From Proximal Arm Muscles During Object- and Orientation-Specific Grasps

Reach-to-grasp tasks are composed of several actions that are more and more considered as simultaneously controlled by the central nervous system in a feedforward manner (at least for well-known activities). If this hypothesis is correct, during prehension tasks, the activity of proximal muscles (and not only of the distal ones used to control finger movements) is modulated according to the kind of object to be grasped and its position. This means that different objects could be identified by processing the electromyographic (EMG) signals recorded from proximal muscles. In this paper, specific experiments have been carried out to support this hypothesis in able-bodied subjects. The results achieved seem to confirm this possibility by showing that the activation of proximal muscles can be statistically different for different grip types. This finding supports the hypothesis that proximal and distal muscles are simultaneously controlled during reaching and grasping. Moreover, this kind of information could allow the development of an EMG-based control strategy based on the natural muscular activities selected by the central nervous system.     

Network implications of multicast in electronic commerce

Electronic commerce (EC) systems have been in existence for many years. In the financial industry, for example, electronic trading has been in place for well over a decade. Momentum has gathered pace to the point where EC is considered at least an essential adjunct to a company's business or, in some cases, the primary means of connecting vendors to their customers. This momentum has been at least, partly inspired by the convergence of content, commerce, communication, and the Internet. In many EC systems, the state of the market (current value and availability of goods and services) or another event needs to be disseminated to consumers so that they can take actions based on the information. IP multicasting is an emerging network technology that can greatly improve the efficiency of providing such information     

A self-adaptive weighted affinity propagation clustering for key frames extraction on human action recognition

In this paper, we propose a novel approach for key frames extraction on human action recognition from 3D video sequences. To represent human actions, an Energy Feature (EF), combining kinetic energy and potential energy, is extracted from 3D video sequences. A Self-adaptive Weighted Affinity Propagation (SWAP) algorithm is then proposed to extract the key frames. Finally, we employ SVM to recognize human actions on the EFs of selected key frames. The experiments show the information including whole action course can be effectively extracted by our method, and we obtain good recognition performance without losing classification accuracy. Moreover, the recognition speed is greatly improved.     

Vom Lehren zum Lernen in Synergie mit Hypermedia

The technical and cultural evolution is generating an information environment which is continually becoming more and more complex: the information society. If it is to be designed in a manner consistent with humanity, generations and internationality, widespread instructional teaching will no longer suffice. In a learning environment in which a change of paradigms from teaching to learning has taken place, new media with a constructive design can generate additional educational values. With hypermedia learning can gain a new quality.     

The Study of Content Security for Mobile Internet

The vast amount of information carried over Mobile Internet and the high speed are providing unprecedented convenience for users, Mobile Internet is facing growing threat of lack of security. It is crucial to maintain and improve safety and security for Mobile Internet for it to thrive and develop. At content level, users are facing increasing amount of malicious or spam content, jeopardizing public??s interest in legitimate internet content. Therefore, Mobile Internet information security has become an important research topic. In this paper we first propose a framework for content security management system for Mobile Internet, and then discuss how to acquire relevant information from Mobile Internet in a fast and efficient manner, how to process and analyze the vast amount of information collected, how to quickly discover negative or illegal information within the network, and provide detection and early warnings for potential hot topics. At the same time, we study how to perform audit and evaluation on the information content so that the relevant security management actions can be done.     

Efficiency performance, control charts, and process improvement:complementary measurement and evaluation

Data envelopment analysis provides an assessment of the efficiency performance of production processes by including in its modeling framework technologically critical input/output variables. In order to create the conceptual linkage to traditional control charts, input/output production specifications may use the concepts of process and product characteristics. Process control charts track the variability and central tendency of production processes by studying the stochastic behavior of a single product characteristic. On the other hand, efficiency measurement approaches include, as part of their evaluation, the entire set of critical product and/or process characteristics simultaneously. This research shows that these two approaches can be used in a complementary manner to identify unusual or extreme production instances, benchmark production occurrences, and evaluate the contribution of individual process and product characteristics to the overall performance of the production process. The identification of extreme production instances in conjunction with the evaluation of their technological and managerial characteristics can help identify potential root causes. This information can be used by decision makers to make specific process improvements. These issues are illustrated by studying a production process of a circuit board manufacturing facility     

Memory-boosting RNN with dynamic graph for event-based action recognition

Existing action recognition methods based on event cameras have not fully exploited the advantages of event cameras, such as compressing event streams into frames for subsequent calculation, which greatly sacrifices the time information of event streams. Meanwhile, the conventional Point Cloud-based methods suffer from large computational complexity while processing event data, which make it difficult to handle long-term actions. To tackle the above problems, we propose a dynamic graph memory-bo...