No abstract
The Dynamic Voltage Restorer (DVR) is used to regulate the voltage at the load terminals from various power quality problems like sag, swell, harmonics, unbalance etc. in supply voltage. This paper presents modelling aspects of several types of Dynamic Voltage Restorer (DVR) working against various voltage sags by simulation. Dynamic voltage restorers (DVRs) are used to protect sensitive loads from the effects of voltage sags on the distribution feeder. Significant simulation results show that these several types of the modelled device can work very well against balanced and/or unbalanced voltages caused by faults in a distribution system. Detailed analyses illustrate that with suitable parameter setting these devices can deal with different levels of voltage sag severity. In addition, appropriate ways to obtain a good quality output voltage by a DVR during voltage sag is also presented. It then provides analyses of working performance of the device, including capability and quality of compensation.
At present in our digital world, data comes and leaves cyberspace at huge rates. A representative organization transfers millions of email messages and downloads, stores, and transmits millions of data sets via various channels on a regular basis. Companies always hold private data of customers, stake holders, industry partners, regulators and they expect them to protect. Unfortunately, today’s industries constantly fall victim to massive data loss, and high-profile data leakages involving sensitive personal and corporate data continue to appear (http://opensecurityfoundation.org). Loss of data could significantly damage a company’s goodwill and reputation and could also invite legal issues or regulatory consequences for negligent security. That’s why, organizations should take measures to manage the sensitive data they carried out, how it’s restricted, and how to prevent the loss from being leaked or compromised. In this respect, over the years the database security community has developed a number of different techniques and approaches to assure data confidentiality, integrity, and availability[14]. Thus data loss prevention and in particular protection of data from unauthorized accesses remain important goal of any data management system. Multi Category Security labeling from a user and system administrator standpoint is straightforward. It consists of configuring a set of categories, which are simply text labels, such as "Company_Confidential" or "Medical_Records", and then assigning users to those categories. The system administrator first configures the categories, then assigns users to them as required. The users can then use the labels as they see fit. A system in a home environment may have only one category of "Private", and be configured so that only trusted local users are assigned to this category. In this paper, we first survey the most relevant concepts underlying the notion of database security, types of losses and summarize the menaces to databases and different categories of vulnerabilities in database. This paper focused on Virtual private database, stops various sensitive data from leaving the corporation’s private confines. This paper illustrates and demonstrates how to enable mutli-level access restrictions which ensures accuracy and security,
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