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  • Exploring security metrics for electric grid infrastructure leveraging attack graphs

    Creator:
    Patapanchala, Panini Sai
    Abstract:
    Electric grid is a critical cyber-physical infrastructure that serves as lifeline for modern society. With the increasing trend of cyber-attacks, electric grid security has become a significant concern. Electric grid operators are working hard to reduce the risk of these attacks towards the system. Having security metrics for monitoring the...
    Resource Type:
    Masters Thesis
    Full Text:
    got from you people. A very special thanks to Dr. Eduardo Cotilla-Sanchez, Dr. Jinsub Kim and Dr

  • How to innovate Korean election by emerging technology

    Creator:
    Lee, Philiph
    Abstract:
    The core element of democracy is elections. Modern elections not only cost a lot of money to conduct elections, but we also bear a lot of social costs when the election is questioned. For this reason, the US and European countries have been considering ways to innovate by introducing IT...
    Resource Type:
    Presentation

  • People Counting System Using MmWave MIMO Radar with 3D Convolutional Neural Network

    Creator:
    Shih, Cheng-Che
    Abstract:
    Recent advances in computing, communication, and artificial intelligence (AI) technologies have made our world more interconnected and data-rich than ever with the proliferation of smart devices and sensors. As a result, we are increasingly dependent on electronic devices and sensors to automate away life’s mundane parts. For example, in business...
    Resource Type:
    Masters Thesis

  • Decoding EEG Signals to Detect and Classify Hand Movement

    Creator:
    McGrath, Patrick
    Abstract:
    Electroencephalogram (EEG) signals have recently gained attention to classify associated hand movement. This is particularly useful for amputees with prostatic hands or people who are unable to move their hands voluntarily. Among the decoding algorithms used to classify hand movements are support vector machines and multilayer perceptron networks. In this...
    Resource Type:
    Honors College Thesis
    Full Text:
    _____________________________________________________________________ Jinsub Kim, Committee Member, representing Oregon State University EECS

  • Deep Learning Based Automatic Modulation Classication for Wideband Access Using Cyclostationarity Analysis

    Creator:
    Mejri, Seifeddine
    Abstract:
    RF-based signal identification and classification has received growing attention during recent years due to its potential use in many application domains. Of particular interest is Automatic Modulation Classification (AMC), which has been useful in addressing various spectrum related challenges such as signal jamming, policy enforcement, and spectrum sharing. Adopting AMC...
    Resource Type:
    Capstone Project
    Full Text:
    members Professor Jinsub Kim and Professor Bella Bose, for accepting to serve as members of the committee

  • Weak-supervision Time-series Analysis

    Creator:
    You, Zeyu
    Abstract:
    Efficient time-series analysis can impact multiple application domains such as motif discovery in gene analysis or music data, extracting spectro-temporal patterns in acoustic scene analysis, or annotating and classifying electrical bio-signals (such as ECG, EEG, and EMG) for medical applications. Time-series analysis involves a variety of tasks. To predict future...
    Resource Type:
    Dissertation
    Full Text:
    : Prof. Xiaoli Fern, Prof. Jinsub Kim, Prof. Xiao Fu, Prof. Sarah Emerson, Prof. Liang Huang and Prof

  • Hybrid, Proactive In-Network Caching for Mobile On-Demand Video Streaming

    Creator:
    Abuhadra, Ragda
    Abstract:
    Mobile video streaming has become an essential application in mobile wireless networks,making up most of the mobile data of today’s Internet traffic. Studies have shown that mobile video data is projected to make up about 78 percent of the global mobile data traffic, and that global mobile data traffic is...
    Resource Type:
    Masters Thesis
    Full Text:
    – 1189. 30 [44] G. S. Park, W. Kim, S. H. Jeong, and H. Song, “Smart base station-assisted partial

  • Channel Estimation in TDD Massive MIMO Systems with Subsampled Data at BS

    Creator:
    Tian, Yichuan
    Abstract:
    Massive MIMO is a promising technique for future 5G communications due to its high spectrum and energy efficiency. To realize its potential performance gain, accurate channel state information at transmitter side (CSIT) is essential. Frequency division duplex (FDD) is widely employed by the most cellular systems today. However, it requires...
    Resource Type:
    Masters Thesis

  • Joint Resource Scheduling and Peak Power Shaving for Cloud Data Centers with Distributed Uninterruptible Power Supply

    Creator:
    AlAnazi, Sultan (Sultan Abdulaziz)
    Abstract:
    The grid company enforces high penalties for the peak power demands of cloud data centers. These high penalties result in high electricity bills that can be avoided by relying on the servers' Uninterruptible Power Supply (UPS) as a source of energy during peak load periods. This thesis proposes a management...
    Resource Type:
    Masters Thesis
    Full Text:
    Professor Larry Cheng, Professor Lizhong Chen, Professor Jinsub Kim and Professor Leonard Coop, for

  • Secrecy of massive MIMO systems under antenna failure

    Creator:
    Assiri, Mohammad
    Abstract:
    As the fifth generation of mobile communication systems (5G) is being deployed, massive multiple-input multiple-output (MIMO) serves as one of its enabling technologies where reliable and ultra low latency communications are achieved while being power and spectrum efficient. This thesis studies the security aspect of massive MIMO system from the...
    Resource Type:
    Dissertation