WIRELESS SENSOR NETWORK (Reshma Bhat‚ 3rd sem‚EC) Abstract A Wireless Sensor network (WSN) consists of spatially distributed autonomous sensors to cooperatively monitor physical or environmental conditions‚ such as temperature‚ sound‚ vibration‚ pressure‚ motion or pollutants. The development of wireless sensor networks was motivated by military applications such as battlefield surveillance and are now used in many industrial and civilian application areas‚ including industrial
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wireless sensor networks can be promptly understood simply by thinking about what they essentially are: a large number of small sensing self-powered nodes which gather information or detect special events and communicate in a wireless fashion‚ with the end goal of handing their processed data to a base station. Sensing‚ processing and communication are three key elements whose combination in one tiny device gives rise to a vast number of applications [A1]‚ [A2]. Sensor networks provide endless
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SOCIAL NETWORKS FOR HUMAN RESOURCES PROCESSES 1. Introduction and evolution of the Technologies in our form of to work Companies have often played catch-up in understanding how to harness new technologies without over-managing them. In the early years of the World Wide Web‚ in the mid-to-late 1990s‚ many organisations feared that employees would spend too much time idly surfing the Web‚ so they tried to control access. While some employees undoubtedly did waste time that way‚ many soon figured
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“virtual” network that is kept private by “tunneling” private data through the underlying infrastructure of a public Internet. VPN technology provides a way of using public network infrastructures‚ such as the Internet‚ to provide private‚ secure access to applications and company resources to employees in remote or home offices‚ to business partners‚ and even to customers. A VPN is one or more WAN links over a shared public network‚ typically over the Internet or an IP backbone from a Network Service
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how to create a network diagram‚ and how to do a forward and backward pass to determine the ES‚ LS‚ EF‚ LF and slack (float). You will also learn how to determine the duration of the project‚ and the critical path. In this homework assignment‚ you will be working through four Activity In Box (AIB) problems. Using the activity‚ duration‚ and predecessor information given in this document‚ you should first construct a network for each "project." [Each problem will have its own network.] Once you
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ARTIFICIAL NEURAL NETWORKS AND THEIR APPLICATIONS IN BUSINESS Ankit Chauhan Ist Semester – MBA (GEN) University School of Management Guru Gobind Singh Indraprastha University Abstract- This report is an introduction to Artificial Neural Networks. The various types of neural networks are explained and demonstrated‚ applications of neural networks like ANNs in business and organizations are described‚ and a detailed historical background is provided. The connection between the artificial
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SOCIAL NETWORKS. Nowadays in most Western countries there is an increase in the use of social networks. The most famous are for example youtube‚ Facebook and Twitter‚ but often these communication media are not used in the right way. There is no doubt‚ the use of the social networks might have positive and negative aspects. First of all the major advantage of using social networks is the possibility to keep in touch with friends that live abroad or people that we are unable to see because of
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Chapter 1 1. INTRODUCTION Artificial Neural Networks are being touted as the wave of the future in computing. They are indeed self learning mechanisms which don ’t require the traditional skills of a programmer. But unfortunately‚ misconceptions have arisen. Writers have hyped that these neuron-inspired processors can do almost anything. Fig. 1.1 Neural Network These exaggerations have created disappointments for some potential users who
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Problems in Network Security Problems in Network Security Calvin C. Tippit CM107-59 Problems in Network Security Outline I. Introduction a. Information security vulnerabilities b. More training is needed for employees working in the Network Security field to prevent common mistakes from happening. II. Mobile Insecurities a. Mobile devices being intruded by cybercriminals. b. The importance of Anit-Virus softwares and system updates. III. Privacy and Security
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EE5904/EE5404 Neural Network 2014/1/16 EE5904/ME5404 Neural Networks Lecture 1 EE5904R/ME5404: Neural Networks Xiang Cheng Associate Professor Department of Electrical & Computer Engineering The National University of Singapore Phone: 65166210 Office: Block E4-08-07 Email: elexc@nus.edu.sg EE5904/ME5404 Neural Networks 1 Lecture 1 Lecturers •Dr. Xiang Cheng •Dr. Chen Chao Yu‚ Peter‚ Dept. of Mechanical Engineering‚ NUS Teaching Assistant •Ramesh Bharath Office:
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