Bitcoin is an experimental, decentralized digital currency that enables instant payments to anyone, anywhere in the world. Bitcoin uses peer-to-peer technology to operate with no central authority. Wallet is the place where Bitcoins are stored. Once Bitcoin wallet is installed on a computer or mobile phone, it will generate initial Bitcoin address and then the user can create an address for each transaction. Wallet first generates a private key and next it will converts private key to Bitcoin address. Wallet keeps track of private keys, usually by storing them in an encrypted wallet file, either on hard drive, on a server on the Internet, or elsewhere.The overall objective of this paper is to propose a biometric ele ctronic wallet to store and transfer digital currencies with high security/encryption using Biometric External USB Sensor. All client side data in mobile Bitcoin wallets will be stored in a file in mobile device only. So, anybody can access that file. Therefore, the main objective is to provide a security for client side file by using Biometric External USB Sensor and AES algorithm.

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The recognition of optical characters is known to be one of the earliest applications of Artificial Neural Networks. In this paper, a simplified neural approach to recognition of optical or visual characters is portrayed and discussed. OCR (Optical Character Recognition) System or to improve the quality of an existing one. The use of artificial neural Network simplifies development of an optical character recognition application, while achieving highest quality of recognition and good performance. The ANN is trained using the Back Propagation algorithm. In the proposed system, each typed English letter is represented by binary numbers that are used as input to a simple feature extraction system whose output, in addition to the input, are fed to an ANN.

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Previously, the aim was to connect the two systems, but now the internet has changed from mere a connection to a greater perspective so for coping with the usage of internet we need to give more emphasis on the information retrieval and hence this new concept emerges as a solution. ICN is an approach which is been developed by great efforts for last one decade various approaches are proposed like CCN, NDN, SDN, Internet of things and many despite what they call it the main approach is same. The main aim of this approach is giving the data the additional information to play central role. But there are still major challenges that are to be overcome. Hence currently it is being tried on small scenarios like media distribution where it is performing outstandingly. So this paper will focus on what is the present state of this approach and its limitations and challenges.

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Human face detection and recognition is an important technology in biometric verification and has been used in various applications such as video monitor system, interaction with human-computer and security. This paper describes about student attendance system. For every schools, colleges and library attendance is mandatory. Traditional method for taking attendance is lecture calling student name and record the attendance in sheet. For each lecture its wastage of time. It is very difficult to verify each and every student in a large classroom. To avoid these losses, we use automatic attendance system. The proposed system describes a method like when he\she enters the class room and marks the attendance by extracting the image using Personal Component Analysis (PCA) algorithm. The system will record the attendance of the student in class room environment automatically. The student database is collected. The student database includes name of the students, there images & roll number. It maintains a log report entry of each student with respect to each subject and also generates a report of the student attendance. Using Simple Mail Transfer Protocol (SMTP) the report of the attendance information will be sent to the faculty and also to the parents.

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The cyber physical world has computation and communication power which grows in vast manner. Thus as because of this it produces large volume of data to handle this processes. There are four main challenges related to Big data and they are volume, variety, velocity, veracity. Volume and variety are managed by some store data processing system like Hadoop. But the velocity and veracity of such large amount of data is too much complex process. In this paper we are going to implement such system which can handle high speed and different pattern of data with its large volume. We are going to implement correlation analytics and mining on the data stream to extract meaningful information. The system should provide real time data processing so that it used Event processing engine as Esper which has different language queries to generate different events. To catch real time data and for simple filtering of that data stream Storm is used which used topology. Correlation and mining takes place by two different algorithm Apriori and FP-Growth algorithm.

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The advancement in the information and communication (ICT) technologies have resulted in the improvement of number of time consuming tasks and activities. These tasks have been automated with the help of advance information and communication (ICT) technologies. The artificial intelligence and multi-agents systems have made possible to automate number of tasks which required human decisions and complex calculations. This paper presents a system design approach for the development of Multi Agent Meeting Scheduling Simulation model and the VOMAS framework have being utilized for the verification and validation (V&V) of this simulation Model. The verification and validation (V&V) of the Meeting simulation model is based on VOMAS techniques. Our technique will permit the validation of agent based simulations using (VOMAS) a Virtual Overlay Multi-agent System. This overlay multi-agent system can comprise various types of agents, which form an overlay on top of the agent based simulation model that needs to be validated. To demonstrate the effectiveness of Multi agent meeting scheduling system and VOMAS approach, the research have shown its broad applicability in a wide variety of simulation models ranging from social sciences to computer networks in spatial and non-spatial conceptual models.

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Abstract—Assisting Voice Input Recognition Application (in short, AVIRA) is a multifunctional software programming application capable of managing computer’s basic operations. It employs a user interface that is capable of receiving user’s voice as its input, process it and perform a necessary operation. It communicates back with the user via synthesized speech. The application requests users input in English and responds in the same. Also this system will be very much useful to the differently abled persons and the visually challenged persons who cannot read and, wants to know the details in their education and in any other aspects of the real world. Normally, the visually challenged persons acquire knowledge and exchange information with others mainly through the speech and writing. This system will help those persons in their education and the computer will be made user friendly to achieve this purpose. This paper is based on the fact that the computer will be able to interact with the user and fulfill their needs in the computer world. In this, we have introduced a new approach of using Speech recognition and Speech synthesis to have a two way communication. This makes the user feel as if they are getting a reply from another person. A visually challenged person can easily interact with the computer systems without the help of other persons. Thus we have made an effort in making this an intelligent environment in the speech processing with the computer system by getting the Input from the user as speech input and artificially generate the synthesized voice which makes the process easy.

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Disruption-tolerant network (DTN) technologies are becoming successful solutions that allow wireless devices carried by soldiers to communicate with each other and access the confidential information or command reliably by exploiting external storage nodes. Disruption-tolerant network (DTN) innovations are getting to be fruitful results that permit remote device conveyed by officers to speak with one another and access the confidential data or secret data or summon dependably by abusing outside capacity nodes or storage nodes. Thus a new methodology is introduced to provide successful communication between each other as well as access the confidential information provided by some major authorities like commander or other superiors. The methodology is called Disruption-Tolerant Network (DTN). This system provides efficient scenario for authorization policies and the policies update for secure data retrieval in most challenging cases. The most promising cryptographic solution is introduced to control the access issues called Cipher text Policy Attribute Based Encryption (CP-ABE). Some of the most challenging issues in this scenario are the enforcement of authorization policies and the policies update for secure data retrieval. Ciphertext -policy attribute-based encryption (CP-ABE) is a guaranteeing cryptographic answer for the right to gain entrance control issues. However, the problem of applying CP-ABE in decentralized
DTNs introduces several security and privacy challenges with regard to the attribute revocation, key escrow, and coordination of attributes issued from different authorities. In this paper, we propose a secure data retrieval scheme using CP-ABE for decentralized DTNs where multiple key authorities manage their attributes independently. We demonstrate how to apply the proposed mechanism to safely and proficiently deal with the classified information dispersed in the Interruption or disruption tolerant network.

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By the rise and rapid growth of E-Commerce, use of credit cards for online purchases has more increased and it caused an explosion in the credit card fraud. The most accepted payment mode is credit card for both online as well as regular purchase, pay bills etc. So frauds associated with it are also rising. In real life, fraudulent transactions are scattered with genuine transactions and simple pattern matching techniques are not often sufficient to detect those frauds accurately. Implementation of efficient fraud detection systems has thus become imperative for all credit card issuing banks to minimize their losses. Many modern mechanisms are developed such as CHIP & PIN the mechanism do not prevent the most common fraud type such as fraudulent credit card usages over virtual POS terminals through internet or mail orders. Finally fraud detection is the essential for stop such type of frauds. In this study, classification model based on Artificial Neural Networks (ANN) and Logistic Regression (LR) are developed and applied on credit card fraud detection problem.

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Today social networking websites has evolved to become a source of various kind of information. This is because of the nature of these websites on which peoples comments and post their opinions on different types of topics i.e. they express positive or negative sentiments about any product that they use in daily life, complains and current issues etc. These sentiments help in getting information about various current trends and can be used further in deciding usefulness of some tasks, products and themes. Also social web data like twitter has a large amount of data that people post so it’s become important to work on efficient intelligent systems that can do data refinement, analysis of tasks intelligently and efficiently. This paper presents a comprehensive overview of past and current research on twitter sentiment analysis and identifies outstanding research questions for the future.

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For purpose of military reconnaissance, the world wars had spurred advanced developments in remote sensing-viewing, imaging and identifying the things from the space with the aid of space technology. Objective of remote sensing and its application have been obtained with different space aid e.g. balloons, missile, aero plane and spacecraft with the application of multeity of sensors be like photographic visual device, multi spectrum scanning device and several other remote sensing devices. These space technologies have yielded interesting scientific information about the Earth’s resources and the atmosphere. Other applications envisaged are forecasting natural resources, estimating crops and monitoring crops disease, surveying minerals deposits, geographic information collection besides the increasing military applications, ubiquitous spying military applications through this space aid. GIS (geographic information system) defined with other sub name geospatial information system is instrumental in captivating, accumulating, diagnosing also enterprising data and appertinent virtue spatially contexted to the globe. Remote sensing and GIS al-together find many applications in study and management of natural resources, atmospheric change, water resource management etc.

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With the rapidly increasing use of social media like Facebook, Twitter, LinkedIn, and Instagram, business organizations are now moving towards adapting this technology to drive business advantages. This paper explores the power of social media in general and how it can be used by banks to provide an edge over their competitors by providing with improved products and services to their customers thereby making their experience easy and responsive. The paper also proposes “SocBan”, a social banking framework and its important components. This study found that even though social media has a power which is ample enough to address all the technical and business aspects of the retail banking, however, what customer expects from this medium and what banks offer to them needs to be widely studied and understood.

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