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The travelling salesman problem (TSP) is one of the most intensively studied problems in optimization. Loosely speaking, given a set of cities on a map, the problem consists of finding a tour that goes through each city exactly once and ends in the same city it started with. There has been much research done on finding efficient heuristics to get provably optimal and close to optimal solutions to TSP problems. Recently a polynomial time approximation scheme was discovered for the Euclidian TSP problem. With parallel and cloud computing gaining prominence in the past few years, finding efficient parallelization of existing algorithms will gain importance. Furthermore, given the push towards cloud computing, it will become increasingly necessary to adopt algorithms to existing cluster computing frameworks like MapReduce. This project deals with Parallelizing Ant Colony Optimization for travelling salesman problem Over Hadoop Map-Reduce.There’s already been much work done in parallelizing TSP heuristics. However there doesn't seem to be any literature on using advantage of existing cluster computing architectures for solving TSP. In this project we explore the problem of parallelizing the Ant Colony Optimization algorithm for TSP on the MapReduce cluster computing framework. We focus on parallelizing Ant Colony Optimization for travelling salesman problem Over Hadoop Map-Reduce.
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In this Computer Science Project, a new authentication scheme called Color Scheme Authentication is proposed for PDAs. These schemes authenticate the user by session passwords. Session passwords are passwords that are used only once. Once the session is terminated, the session password is no longer useful. For every login process, users input different passwords. The session passwords provide better security against dictionary and brute force attacks as password changes for every session. The proposed authentication schemes use text and colors for generating session passwords.
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For medication therapy to be effective, it is critical that the patient take their medicine on an effective schedule. Taking their medicine correctly is medication adherence and is vital for the medicine to produce its maximal benefit. For healthcare professionals, understanding the drug’s action is a major part of their clinical training. However, from a patient’s perspective, many times incorrect, and possibly, erroneous information drug prevails, creating negative atmosphere for medication adherence. Prescription Viewer App is an easy to use medication management app which helps you to monitor and keep track of your medication. It is an android app which helps you to view your medication anytime, anywhere through your phone. A website is created for the doctor to enter the prescription details. The prescription is then sent to the Prescription Viewer App, installed in the patient’s phone, using Google cloud messaging (GCM). The app stores the prescription and displays it in the patient’s phone.
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File sorting and file content sorting are the solutions to the most pressing situation of the organizing and maintaining the data for any systems. Sorting the files may be on the basis of their size or the date of creation. This is significant in the archiving of files. This helps in the reorganization of files in the systems with vast amounts of data which are updated frequently. Content sorting can be counted as a real world application that requires the sorted output for further manipulation. Apache hadoop provides a framework for large scale parallel processing using a distributed file system and the map-reduce programming paradigm. Both of these sorting programs are implemented within the framework with the help of map reduce module that forms one of the major pillar of Hadoop framework.
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As Cloud Computing becomes prevalent, more and more sensitive information are being centralized into the cloud, such as emails, personal health records, government documents, etc. By storing their data into the cloud, the data owners can be relieved from the burden of data storage and maintenance so as to enjoy the on-demand high quality data storage service. However, the fact that data owners and cloud server are not in the same trusted domain may put the outsourced data at risk, as the cloud server may no longer be fully trusted. It follows that sensitive data usually should be encrypted prior to outsourcing for data privacy and combating unsolicited accesses.
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Computer Science Projects on Fuzzy Keyword Search Over Encrypted Data In Cloud Computing based on Wild-card and Gram-based scheme. Since the cloud is not trusted, the data should be stored in an encrypted form at the server. But the problem is how to query the encrypted data efficiently. Data encryption also demands the protection of keyword privacy since keywords usually contain important information related to the data files. Although encryption of keywords can protect keyword privacy.
In our project, we propose fuzzy keyword search scheme based on the following techniques
- Wild card based scheme
- Gram based scheme
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Coding algorithms are intended to minimize the bit rate in the digitized version of a signal. It does so without any major loss in signal quality during encoding process. Speech coding became one of the integral part of digitized speech signal processing. High quality is attained at low bit rates by exploiting signal redundancy as well as the knowledge that certain types of coding distortion are difficult because they are masked by the signal. With the recent advancements in the microelectronics, cheap programmable processors and chips are available. This helps various players to make complex coding algorithms for signal redundancy and distortion masking which in turn help us in improving the quality of low bit rate signals.
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Diversity techniques mitigate the adverse effects of fading in wireless communications. One of the several forms of diversity is spatial diversity, which creates multiple fading paths between the transmitter and the receiver. Achieving spatial diversity in a mobile unit requires the use of multiple antennas, which, in turn, increases its hardware complexity and size. To overcome this problem, a recent development envisages a type of spatial diversity called distributed spatial diversity, where mobile units that are distributed in different geographical locations generate multiple communication paths. Practical implementation of distributed spatial diversity requires some sort of cooperation among the mobile units. A new method of cooperation called user cooperation, where mobile units share their antennas with other mobile units, thereby forming a virtual antenna array.
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This Computer Science Project is based on Energy efficient Secure Routing in Wireless Sensor Networks, discuss in detail about various aspects of energy efficient wireless sensor networks implementation and its use in real world applications. Wireless sensor networks can sense changes in environment and send it across to control center for various analysis. Major advantage of sensor nodes are that they can be deployed over large areas in hostile environments for military and civilian use. Secure routing algorithms are used to send the data collected by sensor networks to the data center.Sensors are small devices with limited data storage, power backup and analysis capability. Since sensors have limited backup power and analysis capability, security mechanism for sensor network must be energy efficient.
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This computer science project topic on DNA Microarray Image Processing discuss about various Microarray technologies, workflow management of micro array data processing, issues associated with Micro array image processing, Micro-array file format and layouts, image processing steps, image processing requirements and existing spot variations. DNA Micro array data processing is used in research and development of
- Micro array image analysis
- Data cleaning, perprocessing, semantic integration of distributed biomedical databases
- Exploration of existing data mining tools for bio-data analysis
- Development of advanced and scalable data mining methods in bio data analysis