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  We provide projects on wireless communication, WEKA, SentiWordNet, SDN, QUALlNet, OPNET, OpenCV, MiniNet, PEERSIM and so on

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  We do research on Wordnet, Grid Computing, Cloud Computing, Computer Networking, etc

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  We provide electrical projects based on power electronics, MATLAB Simulink and SIM Power

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  For Electronics Engineering Students we support technologies like ARM, GSM, GPS, RFID, Robotics, VLSI, NSL, NS3, OMNet++, OPNet, QUALNET, PeerSim

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  For Computer Science Students we support NS2, NS3, MATLAB, Java, OMNeT++, OPNet, CloudSim, Qualnet, Weka, Wordnet, Dot Net, Hadoop,….

Final Year Projects allocate all B.TECH / M.TECH / MS students. All universities asked to the students to do their projects in final semester. Universities highly believe final year projects improve the student subject level.

Classifications of final year projects are many, full guidance is provided to all types of classifications a very few are spoken in detail. Data gather from the large database is called data mining.

Final year project

Number of steps involved in the data mining process like Classification, Clustering, Association Rules, Sequential Patterns, Regression, Deviation Detection. Our technical team have good working experience in all data mining algorithms.

Optical character recognition is called as OCR. To find the text from the image we use OCR techniques. JAVA, OPEN CV, MATLAB, MATLAB, SCILAB used to calculate the OCR concepts. Lack of Access, Time management, priority, Hot spot, power consumption these are the challenging issues in cloud computing. In our Students & Research scholars we assist the cloud computing projects support.

Final year projects

Long Term Evolution (LTE) helps to Telecommunication. Third Generation Partnership Project (3GPP), Universal Mobile Telecommunication System (UMTS), Global System for Mobile Communications (GSM) some stages of the LTE.

SAE, OFDM, MIMO are the major techniques in LTE. OPNET simulator have LTE MODULE. We cannot access the module free. We need to pay to buy this module. Most of our students prepare NS2 & OMNET++ to solve the LTE projects.

LATEST IEEE PROJECTS:

• Method for Preventing Direct and Indirect Discrimination in Data Mining
• Analyzing data mining techniques for wireless sensor network protocols
• Building a Distributed Generic Recommender Using Scalable Data Mining Library
• Creation of an Adaptive Classifier to enhance the classification accuracy of existing classification algorithms in the field of Medical Data Mining
• Predictions in heart disease using techniques of data mining
• Crawler intelligence with machine learning and Data Mining integration
• i 2 MapReduce: Incremental MapReduce for Mining Evolving Big Data
• Data mining application in banking sector with clustering and classification methods
• Extended performance appraise of Bayes, Function, Lazy, Rule, Tree data mining classifier in novel transformed fractional content based image classification
• A model for predicting the eligibility for placement of students using data mining technique
• Automatic classification of movie trailers using data mining techniques: A review
• Clustering techniques in data mining: A comparison
• A cryptographic approach for achieving privacy in data mining
• Detection of adverse drug events through data mining techniques
• Fraud detection in health insurance using data mining techniques
• Mining information assurance data with a hybrid intelligence/multi-agent system
• Trust-but-Verify: Verifying Result Correctness of Outsourced Frequent Itemset Mining in Data-mining-as-a-service Paradigm
• Data Mining of Online Diagnosed Waveforms for Probabilistic Condition Assessment of SF   Circuit Breakers
• A Model to Predict Low Academic Performance at a Specific Enrollment Using Data Mining
• Energy-Aware Migration of Virtual Machines Driven by Predictive Data Mining Models
• Implementation of data generator for process mining applications
• Network-Based Modeling and Intelligent Data Mining of Social Media for Improving Care
• Integrating Human Behavior Modeling and Data Mining Techniques to Predict Human Errors in Numerical Typing
• Four Decades of Data Mining in Network and Systems Management
• Data mining diagnostics and bug MRIs for HW bug localization

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