Now showing items 1-17 of 17

  • Adaptive Routing Using SDN and NFV 

    Parab, Tejas Balkrishna (University of Missouri--Kansas City, 2017)
    In recent times, the primary focus of every ISP is to deliver high quality of service for multimedia applications. Due to ever-increasing network traffic, it is challenging for ISPs to accomplish optimal network ...
  • Advanced Design and Analysis of UWB U-slot Microstrip Patch Using Theory of Characteristic Modes 

    Khan, Mahrukh (University of Missouri--Kansas City, 2017)
    Ultra wide band is rapidly advancing as a high data rate wireless communication technology. As is the case in conventional wireless communication systems, an antenna also plays a very crucial role in UWB systems. ...
  • Algorithms on Majority Problem 

    Tarafdar, Rajarshi (University of Missouri--Kansas City, 2017)
    The main idea of the paper to give solutions to the majority problem where we are counting the number of occurrences of the majority element more than half of the total number of the elements in the input set and also ...
  • Assessment Of Overcurrent Relay Coordination In A Microgrid With High PV Penetration Deployment 

    Alshmoos, Ameer (University of Missouri--Kansas City, 2017)
    The existing distribution system is experiencing radical changes with the rapid proliferation of Distributed Energy Resources (DERs)[1]. Microgrids have been proposed as a way of integrating large numbers of distributed ...
  • Building a Knowledge Graph for Food, Energy, and Water Systems 

    Gharibi, Mohamed (University of Missouri--Kansas City, 2017)
    A knowledge graph represents millions of facts and reliable information about people, places, and things. Several companies like Microsoft, Amazon, and Google have developed knowledge graphs to better customer experience. ...
  • Context Based Multi-Image Visual Question Answering (VQA) in Deep Learning 

    Peddinti, Sudhakar Reddy (University of Missouri--Kansas City, 2017)
    Image question answering has gained huge popularity in recent years due to advancements in Deep Learning technologies and computer processing hardware which are able to achieve higher accuracies with faster processing ...
  • Distributed Perimeter Firewall Policy Management Framework 

    Maddumala, Mahesh Nath (University of Missouri--Kansas City, 2017)
    A perimeter firewall is the first line of defense that stops unwanted packets (based on defined firewall policies) entering the organization that deploys it. In the real world, every organization maintains a perimeter ...
  • H3DNET: A Deep Learning Framework for Hierarchical 3D Object Classification 

    Patel, Marmikkumar (University of Missouri--Kansas City, 2017)
    Deep learning has received a lot of attention in the fields such as speech recognition and image classification because of the ability to learn multiple levels of features from raw data. However, 3D deep learning is ...
  • Improving Cuckoo Hashing with Perfect Hashing 

    Chadalavada, Moulika (University of Missouri--Kansas City, 2017)
    In computer science, the data structure is a systematic way of organizing data such that it can be used efficiently. There are many hashing techniques that aim at storing keys in memory to increase key access efficiency ...
  • NCC-EM: A hybrid framework for decision making with missing information 

    Chavakula, Varun (University of Missouri--Kansas City, 2017)
    Accounting for uncertainty is important in any data driven decision making. The popular treatment of uncertainties is to employ classical probability theory by expressing variables as random variables or processes in ...
  • Next-Generation Flash Memories Using Two-Dimensional Materials 

    Shishupal, Hemanshu (University of Missouri -- Kansas City, 2017)
    This thesis presents a model that provides the output characteristics of next-generation flash memories using two-dimensional materials. Multi-Layer Graphene Nanoribbon (MLGNR) and Graphene are used as the channel and ...
  • Numerical Simulation and Performance Optimization of Perovskite Solar Cell 

    Nanduri, Sai Naga Raghuram (University of Missouri--Kansas City, 2017)
    The organic-metal halide perovskite is emerging technology in photo voltaic solar cells. For any solar cell to get the significant efficiency depends on various design parameters such as material thickness, device ...
  • One-Shot Learning Model for Cancer Diagnosis from Histopathological Images 

    Yarlagadda, Dig Vijay Kumar (University of Missouri--Kansas City, 2017)
    Cancer diagnosis from tissue biomarker scoring is a vital technique used in determining type and grade of cancer. This is a significant part of workload for pathologists, the process is tedious, time consuming, subjective, ...
  • Point Cloud Compression and Low Latency Streaming 

    Ainala, Karthik (University of Missouri--Kansas City, 2017)
    With the commoditization of the 3D depth sensors, we can now very easily model real objects and scenes into digital domain which then can be used for variety of application in gaming, animation, virtual reality, immersive ...
  • Practical Memristor Emulator Circuit Development Techniques for Analog Applications 

    Alharbi, Abdullah G. (University of Missouri -- Kansas City, 2017)
    Emerging memristor technology is drawing widespread attention during recent time due to its potential diverse applications in nanoelectronic memories, logic and neu romorphic computer architectures, digital and analog ...
  • Study of QoE for DASH at Sub-representational Level 

    Swamy, Deepthi Basavapatna Narayana (University of Missouri--Kansas City, 2017)
    Dynamic Adaptive Streaming over HTTP has become the most commonly used technology in video streaming. It enables the player to adapt to the bitrate of the video while streaming to ensure continuous playback. DASH ...
  • Topic-Based Video Classification and Retrieval Using Machine Learning 

    Vadlamudi, Naga Krishna (University of Missouri--Kansas City, 2017)
    Machine learning has made significant progress for many real-world problems. The Deep Learning (DL) models proposed primarily concentrate on object detection, image classification, and image captioning. However, very ...