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Articles 61 - 90 of 114
Full-Text Articles in Systems and Communications
Feasibility And Security Analysis Of Wideband Ultrasonic Radio For Smart Home Applications, Qi Xia
Feasibility And Security Analysis Of Wideband Ultrasonic Radio For Smart Home Applications, Qi Xia
School of Computing: Dissertations, Theses, and Student Research
Smart home Internet-of-Things (IoT) accompanied by smart home apps has witnessed tremendous growth in the past few years. Yet, the security and privacy of the smart home IoT devices and apps have raised serious concerns, as they are getting increasingly complicated each day, expected to store and exchange extremely sensitive personal data, always on and connected, and commonly exposed to any users in a sensitive environment. Nowadays wireless smart home IoT devices rely on electromagnetic wave-based radio-frequency (RF) technology to establish fast and reliable quality network connections. However, RF has its limitations that can negatively affect the smart home user …
Underground Environment Aware Mimo Design Using Transmit And Receive Beamforming In Internet Of Underground Things, Abdul Salam
Underground Environment Aware Mimo Design Using Transmit And Receive Beamforming In Internet Of Underground Things, Abdul Salam
Faculty Publications
In underground (UG) multiple-input and multiple-output (MIMO), the transmit beamforming is used to focus energy in the desired direction. There are three different paths in the underground soil medium through which the waves propagates to reach at the receiver. When the UG receiver receives a desired data stream only from the desired path, then the UG MIMO channel becomes three path (lateral, direct, and reflected) interference channel. Accordingly, the capacity region of the UG MIMO three path interference channel and degrees of freedom (multiplexing gain of this MIMO channel requires careful modeling). Therefore, expressions are required derived the degrees of …
Ka-Band Planar Vivaldi Antenna With A Core For High-Gain, Manh Ha Hoang, Kansheng Yang, Matthias John, Patrick Mcevoy, Max Ammann
Ka-Band Planar Vivaldi Antenna With A Core For High-Gain, Manh Ha Hoang, Kansheng Yang, Matthias John, Patrick Mcevoy, Max Ammann
Articles
A planar Vivaldi antenna structure with a core element is proposed for high gain. Techniques to achieve a significant gain improvement over the full Ka (24-40 GHz) band are implemented; including a frequency-independent excitation method, the introduction of logarithmic ripple on the lateral edges and enclosing the antenna in a dielectric material.
Convolutional Neural Network Architecture Study For Aerial Visual Localization, Jedediah M. Berhold
Convolutional Neural Network Architecture Study For Aerial Visual Localization, Jedediah M. Berhold
Theses and Dissertations
In unmanned aerial navigation the ability to determine the aircraft's location is essential for safe flight. The Global Positioning System (GPS) is the default modern application used for geospatial location determination. GPS is extremely robust, very accurate, and has essentially solved aerial localization. Unfortunately, the signals from all Global Navigation Satellite Systems (GNSS) to include GPS can be jammed or spoofed. To this response it is essential to develop alternative systems that could be used to supplement navigation systems, in the event of a lost GNSS signal. Public and governmental satellites have provided large amounts of high-resolution satellite imagery. These …
Machine Translation With Image Context From Mandarin Chinese To English, Brooke E. Johnson
Machine Translation With Image Context From Mandarin Chinese To English, Brooke E. Johnson
Theses and Dissertations
Despite ongoing improvements in machine translation, machine translators still lack the capability of incorporating context from which source text may have been derived. Machine translators use text from a source language to translate it into a target language without observing any visual context. This work aims to produce a neural machine translation model that is capable of accepting both text and image context as a multimodal translator from Mandarin Chinese to English. The model was trained on a small multimodal dataset of 700 images and sentences, and compared to a translator trained only on the text associated with those images. …
Preserving Privacy In Automotive Tire Pressure Monitoring Systems, Kenneth L. Hacker
Preserving Privacy In Automotive Tire Pressure Monitoring Systems, Kenneth L. Hacker
Theses and Dissertations
The automotive industry is moving towards a more connected ecosystem, with connectivity achieved through multiple wireless systems. However, in the pursuit of these technological advances and to quickly satisfy requirements imposed on manufacturers, the security of these systems is often an afterthought. It has been shown that systems in a standard new automobile that one would not expect to be vulnerable can be exploited for a variety of harmful effects. This thesis considers a seemingly benign, but government mandated, safety feature of modern vehicles; the Tire Pressure Monitoring System (TPMS). Typical implementations have no security-oriented features, leaking data that can …
Autonomous Association Of Geo Rso Observations Using Deep Neural Networks, Ian W. Mcquaid
Autonomous Association Of Geo Rso Observations Using Deep Neural Networks, Ian W. Mcquaid
Theses and Dissertations
Ground-based non-resolved optical observations of resident space objects (RSOs) in geosynchronous orbit (GEO) represent the majority of the space surveillance network’s (SSN’s) deep-space tracking. Reliable and accurate tracking necessitates temporal separation of the observations. This requires that subsequent observations be associated with prior observations of a given RSO before they can be used to create or refine that RSO’s ephemeris. The use of astrometric data (e.g. topocentric angular position) alone for this association task is complicated by RSO maneuvers between observations, and by RSOs operating in close proximity. Accurately associating an observation with an RSO thus motivates the use of …
Orthogonal Frequency Division Multiplexed Waveform Effects On Passive Bistatic Radar, Forrest D. Taylor
Orthogonal Frequency Division Multiplexed Waveform Effects On Passive Bistatic Radar, Forrest D. Taylor
Theses and Dissertations
Communication waveforms act as signals of opportunity for passive radars. However, these signals of opportunity suffer from range-Doppler processing losses due to their high range sidelobes and pulse-diverse waveform aspects. Signals such as the long term evolution (LTE) encode information within the phase and amplitude of the waveform. This research explores aspects of the LTE, such as the encoding scheme and bandwidth modes on passive bistatic Doppler radar. Signal space-time adaptive processing (STAP) performance is evaluated and parameters are compared with the signal to interference-plus-noise ratio (SINR) metric.
Serious Game Design Using Mda And Bloom’S Taxonomy, Senobio V. Chavez
Serious Game Design Using Mda And Bloom’S Taxonomy, Senobio V. Chavez
Theses and Dissertations
The field of Serious Games (SG) studies the use of games as a learning tool and it has been in existence for over forty years. During this period the primary focus of the field has been designing systems to evaluate the educational efficacy of existing games. This translates to a lack of systems designed to aid in the creation of serious games, but this does not have to remain an issue. The rise in popularity of games means that there is no shortage of ideas on how to methodically create them for commercial production which can just as easily be …
A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari
A State-Of-The-Art Survey On Deep Learning Theory And Architectures, Md Zahangir Alom, Tarek M. Taha, Christopher Yakopcic, Stefan Westberg, Paheding Sidike, Mst Shamima Nasrin, Mahmudul Hasan, Brian C. Van Essen, Abdul A. S. Awwal, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
In recent years, deep learning has garnered tremendous success in a variety of application domains. This new field of machine learning has been growing rapidly and has been applied to most traditional application domains, as well as some new areas that present more opportunities. Different methods have been proposed based on different categories of learning, including supervised, semi-supervised, and un-supervised learning. Experimental results show state-of-the-art performance using deep learning when compared to traditional machine learning approaches in the fields of image processing, computer vision, speech recognition, machine translation, art, medical imaging, medical information processing, robotics and control, bioinformatics, natural language …
Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler
Development Of A Myoelectric Detection Circuit Platform For Computer Interface Applications, Nickolas Andrew Butler
Master's Theses
Personal computers and portable electronics continue to rapidly advance and integrate into our lives as tools that facilitate efficient communication and interaction with the outside world. Now with a multitude of different devices available, personal computers are accessible to a wider audience than ever before. To continue to expand and reach new users, novel user interface technologies have been developed, such as touch input and gyroscopic motion, in which enhanced control fidelity can be achieved. For users with limited-to-no use of their hands, or for those who seek additional means to intuitively use and command a computer, novel sensory systems …
A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak
A Theoretical Model Of Underground Dipole Antennas For Communications In Internet Of Underground Things, Abdul Salam, Mehmet C. Vuran, Xin Dong, Christos Argyropoulos, Suat Irmak
Faculty Publications
The realization of Internet of Underground Things (IOUT) relies on the establishment of reliable communication links, where the antenna becomes a major design component due to the significant impacts of soil. In this paper, a theoretical model is developed to capture the impacts of change of soil moisture on the return loss, resonant frequency, and bandwidth of a buried dipole antenna. Experiments are conducted in silty clay loam, sandy, and silt loam soil, to characterize the effects of soil, in an indoor testbed and field testbeds. It is shown that at subsurface burial depths (0.1-0.4m), change in soil moisture impacts …
Magnetic Field Aided Indoor Navigation, William F. Storms
Magnetic Field Aided Indoor Navigation, William F. Storms
Theses and Dissertations
This research effort examines inertial navigation system aiding using magnetic field intensity data and a Kalman filter in an indoor environment. Many current aiding methods do not work well in an indoor environment, like aiding using the Global Positioning System. The method presented in this research uses magnetic field intensity data from a three-axis magnetometer in order to estimate position using a maximum – likelihood approach. The position measurements are then combined with a motion model using a Kalman filter. The magnetic field navigation algorithm is tested using a combination of simulated and real measurements. These tests are conducted using …
Radar Detection, Tracking And Identification For Uav Sense And Avoid Applications, Erik George Moore
Radar Detection, Tracking And Identification For Uav Sense And Avoid Applications, Erik George Moore
Electronic Theses and Dissertations
Advances in Unmanned Aerial Vehicle (UAV) technology have enabled wider access for the general public leading to more stringent flight regulations, such as the "line of sight" restriction, for hobbyists and commercial applications. Improving sensor technology for Sense And Avoid (SAA) systems is currently a major research area in the unmanned vehicle community. This thesis overviews efforts made to advance intelligent algorithms used to detect, track, and identify commercial UAV targets by enabling rapid prototyping of novel radar techniques such as micro-Doppler radar target identification or cognitive radar. To enable empirical radar signal processing evaluations, an S-Band and X-Band frequency …
Assessing The Time Synchronisation Of Eeg Systems, Yongxiang Wang, Charles Markham, Catherine Deegan
Assessing The Time Synchronisation Of Eeg Systems, Yongxiang Wang, Charles Markham, Catherine Deegan
Conference Papers
This study compared the synchronisation of a medical grade Electroencephalography (EEG) system, the g.Tec, and a consumer grade EEG system, the Emotiv. Data was collected from both systems using the lab streaming layer (LSL). Both EEG systems recorded an electric signal from the surface of a customised gel phantom. The electric signal was generated using a solar cell which was illuminated by a monitor presenting a sequence of black and white images. Test results show that the g.Tec had a mean delay of 51.22 ms from the stimulus onset and the Emotiv had a mean delay of 162.69 ms from …
Fall Detection Using Channel State Information From Wifi Devices, D.M Sameera Palipana
Fall Detection Using Channel State Information From Wifi Devices, D.M Sameera Palipana
PhDs
Falls among the independently living elderly population are a major public health worry, leading to injuries, loss of confidence to live independently and even to death. Each year, one in three people aged 65 and older falls and one in five of them suffers fatal or non fatal injuries. Therefore, detecting a fall early and alerting caregivers can potentially save lives and increase the standard of living. Existing solutions, e.g. push-button, wearables, cameras, radar, pressure and vibration sensors, have limited public adoption either due to the requirement for wearing the device at all times or installing specialized and expensive infrastructure. …
Jitana: A Modern Hybrid Program Analysis Framework For Android Platforms, Yutaka Tsutano, Shakthi Bachala, Witawas Srisa-An, Gregg Rothermel, Jackson Dinh
Jitana: A Modern Hybrid Program Analysis Framework For Android Platforms, Yutaka Tsutano, Shakthi Bachala, Witawas Srisa-An, Gregg Rothermel, Jackson Dinh
School of Computing: Faculty Publications
Security vetting of Android apps is often performed under tight time constraints (e.g., a few minutes). As such, vetting activities must be performed “at speed”, when an app is submitted for distribution or a device is analyzed for malware. Existing static and dynamic program analysis approaches are not feasible for use in security analysis tools because they require a much longer time to operate than security analysts can afford. There are two factors that limit the performance and efficiency of current analysis approaches. First, existing approaches analyze only one app at a time. Finding security vulnerabilities in collaborative environments such …
Qoe Enhancement In Next Generation Wireless Ecosystems: A Machine Learning Approach, Eva Ibarrola, Mark Davis, Camille Voisin, Ciara Close, Leire Cristobo
Qoe Enhancement In Next Generation Wireless Ecosystems: A Machine Learning Approach, Eva Ibarrola, Mark Davis, Camille Voisin, Ciara Close, Leire Cristobo
Articles
Next-generation wireless ecosystems are expected to comprise heterogeneous technologies and diverse deployment scenarios. Ensuring quality of service (QoS) will be one of the major challenges on account of a variety of factors that are beyond the control of network and service providers in these environments. In this context, ITU-T is working on defining new Recommendations related to QoS and users' quality of experience (QoE) for the 5G era. Considering the new ITU-T QoS framework, we propose a methodology to develop a global QoS management model for next generation wireless ecosystems taking advantage of big data and machine learning (ML). The …
Performance Of Detection Algorithms For Massive Mimo Systems, Mohammad Abdellatif, Ayatalla Abdelrahman
Performance Of Detection Algorithms For Massive Mimo Systems, Mohammad Abdellatif, Ayatalla Abdelrahman
Electrical Engineering
MIMO or Multiple- input- Multiple- output is one of the latest technologies, which has been developed to combat the major problems encountering wireless communications. MIMO was developed to improve communication's capacity, range, reliability, throughput, to overcome bandwidth limitations, and to combat fading. This paper investigates the performance of massive MIMO which is the core of the fifth generation that is expected to be released by 2020. Massive MIMO is a promising technology that allows the use of hundreds of antennas at the base station to achieve optimal reliability, capacity, and throughput. However, it suffers from multiple limitations in the detection …
Telemedicine: An Iot Application For Healthcare Systems, Mohammad Abdellatif, Walaa Mohamed
Telemedicine: An Iot Application For Healthcare Systems, Mohammad Abdellatif, Walaa Mohamed
Electrical Engineering
Telemedicine is the abstract term used to define medical services delivered through Information Technology and Telecommunications. With the growing advancements in the field of data mining, pattern recognition, expert systems, and image processing, the motivation of such a technology has increased. This allowed Telemedicine to be a stable solution especially because people are starting to trust the system more for its higher accuracy. This paper proposes a Telemedicine platform between the patient and the doctor. This platform belongs to the internet of medical things (IoMT) by enabling multiple medical sensors to connect to a server either using Wi-Fi, Bluetooth or …
Submerged Solar Energy Harvesters Performance For Underwater Applications, Mohammad Abdellatif, Salsabeel Kamal, Ghazal M. Al-Sayyad, Rana Abdelmoteleb, Sameh O. Abdellatif
Submerged Solar Energy Harvesters Performance For Underwater Applications, Mohammad Abdellatif, Salsabeel Kamal, Ghazal M. Al-Sayyad, Rana Abdelmoteleb, Sameh O. Abdellatif
Electrical Engineering
underwater communications is the transmission of data in an unguided water medium through wireless carriers such as; optical waves, radio-frequency waves and acoustic waves. Such type of communication system is utilized to enable the realization of the ocean exploration system and other marine monitoring/exploration systems. Seeking for a sustainable setup, the enrolment of energy harvesting sources in these wireless nodes have been presented as a replacement of the short-life-time battery sources. In this paper, there are experimental measurements as well as theoretical studies for two different light harvesters have been conducted underwater with considering the air measurements as a reference. …
Wirelessly Powered Cognitive Radio Communication Networks., Mohammad Abdellatif, Haitham H. Mahmoud
Wirelessly Powered Cognitive Radio Communication Networks., Mohammad Abdellatif, Haitham H. Mahmoud
Electrical Engineering
Many energy harvesting techniques have been investigated in the literature to solve the limitation of power supply problems as it has been one of the crucial challenges in wireless communication networks. With the relatively large numbers of sensors that are expected to be deployed in the upcoming Fifth Generation (5G) and Internet-of-Things (IoT), it has become harder to implement reasonably priced networks with the normal power supplying techniques. In this paper, a proposal of a Cognitive Radio Network (CRN) is presented where the SUs have the ability of Secondary-Users (SUs) to wirelessly harvest energy from a broadcasted energy which is …
An Intrusion Detection Framework For Energy Constrained Iot Devices, Mohammad Abdellatif, Junaid Arshad, Muhammad Ajmal Azad, Khaled Salah
An Intrusion Detection Framework For Energy Constrained Iot Devices, Mohammad Abdellatif, Junaid Arshad, Muhammad Ajmal Azad, Khaled Salah
Electrical Engineering
Industrial Internet of Things (IIoT) exemplifies IoT with applications in manufacturing, surveillance, automotive, smart buildings, homes and transport. It leverages sensor technology, cutting edge communication and data analytics technologies and the open Internet to consolidate IT and operational technology (OT) aiming to achieve cost and performance benefits. However, the underlying resource constraints and ad hoc nature of such systems have significant implications especially in achieving effective intrusion detection. Consequently, contemporary solutions requiring a stable infrastructure and extensive computational resources are inadequate to fulfill these characteristics of an IIoT system. In this paper, we propose an intrusion detection framework for the …
Performance Analysis Of A Wirelessly Powered Cognitive Radio Communication Network, Mohammad Abdellatif, Haitham Hassan
Performance Analysis Of A Wirelessly Powered Cognitive Radio Communication Network, Mohammad Abdellatif, Haitham Hassan
Electrical Engineering
Over the years, many energy harvesting techniques were proposed in the literature. These techniques are used to solve power supply problems as it has been one of the crucial challenges in wireless communication. With the relatively large numbers of devices that are expected to be deployed starting 2020, it has become harder to implement reasonably priced networks with sufficient power supplying techniques. In this paper, a novel cognitive radio network (CRN) is proposed in which the secondary-users (SUs) have the ability to wirelessly harvest energy from a broadcasted energy signal sent from a central node (CN). Additionally, nodes that might …
Matlab Gui Based Educational Simulation Tool Box For Power Analysis, Tharuka Senevirathne
Matlab Gui Based Educational Simulation Tool Box For Power Analysis, Tharuka Senevirathne
All Graduate Theses, Dissertations, and Other Capstone Projects
One of the most important and complex tasks in power engineering is the analysis of power systems under fault conditions. The detection and analysis of these faults are important to guarantee that the dependability and stability of the power system does not decline as a result of a critical event such as a fault. This thesis will conduct research on how a power system under fault conditions behaves and will examine the various scenarios of faults such as three-phase, single line-to-ground, line-to-line, and double line-to-ground faults. A simplified method based on symmetrical components is used to construct the mathematical models …
Optimization Of Energy Harvesting Mobile Nodes Within Scalable Converter System Based On Reinforcement Learning, Chengtao Xu
Optimization Of Energy Harvesting Mobile Nodes Within Scalable Converter System Based On Reinforcement Learning, Chengtao Xu
All Graduate Theses, Dissertations, and Other Capstone Projects
Microgrid monitoring focusing on power data, such as voltage and current, has become more significant in the development of decentralized power supply system. The power data transmission delay between distributed generator is vital for evaluating the stability and financial outcome of overall grid performance. In this thesis, both hardware and simulation has been discussed for optimizing the data packets transmission delay, energy consumption, and collision rate. To minimize the transmission delay and collision rate, state-action-reward-state-action (SARSA) and Q-learning method based on Markov decision process (MDP) model is used to search the most efficient data transmission scheme for each agent device. …
Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari
Active Recall Networks For Multiperspectivity Learning Through Shared Latent Space Optimization, Theus Aspiras, Ruixu Liu, Vijayan K. Asari
Electrical and Computer Engineering Faculty Publications
Given that there are numerous amounts of unlabeled data available for usage in training neural networks, it is desirable to implement a neural network architecture and training paradigm to maximize the ability of the latent space representation. Through multiple perspectives of the latent space using adversarial learning and autoencoding, data requirements can be reduced, which improves learning ability across domains. The entire goal of the proposed work is not to train exhaustively, but to train with multiperspectivity. We propose a new neural network architecture called Active Recall Network (ARN) for learning with less labels by optimizing the latent space. This …
Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai
Deep Temporal Convolutional Networks For Short-Term Traffic Flow Forecasting, Wentian Zhao, Yanyun Gao, Tingxiang Ji, Xili Wan, Feng Ye, Guangwei Bai
Electrical and Computer Engineering Faculty Publications
To reduce the increasingly congestion in cities, it is essential for intelligent transportation system (ITS) to accurately forecast the short-term traffic flow to identify the potential congestion sites. In recent years, the emerging deep learning method has been introduced to design traffic flow predictors, such as recurrent neural network (RNN) and long short-term memory (LSTM), which has demonstrated its promising results. In this paper, different from existing work, we study the temporal convolutional network (TCN) and propose a deep learning framework based on TCN model for short-term city-wide traffic forecast to accurately capture the temporal and spatial evolution of traffic …
Evaluation Of An Extended Pics (Epics) For Calibration And Stability Monitoring Of Optical Satellite Sensors, Md Nahid Hasan
Evaluation Of An Extended Pics (Epics) For Calibration And Stability Monitoring Of Optical Satellite Sensors, Md Nahid Hasan
Electronic Theses and Dissertations
Pseudo Invariant Calibration Sites (PICS) have been increasingly used as an independent data source for on-orbit radiometric calibration and stability monitoring of optical satellite sensors. Generally, this would be a small region of land that is extremely stable in time and space, predominantly found in North Africa. Use of these small regions, referred to as traditional PICS, can be limited by: i) the spatial extent of an individual Region of Interest (ROI) and/or site; ii) and the frequency of how often the site can be acquired, based on orbital patterns and cloud cover at the site, both impacting the time …
Reinforcement Learning And Game Theory For Smart Grid Security, Shuva Paul
Reinforcement Learning And Game Theory For Smart Grid Security, Shuva Paul
Electronic Theses and Dissertations
This dissertation focuses on one of the most critical and complicated challenges facing electric power transmission and distribution systems which is their vulnerability against failure and attacks. Large scale power outages in Australia (2016), Ukraine (2015), India (2013), Nigeria (2018), and the United States (2011, 2003) have demonstrated the vulnerability of power grids to cyber and physical attacks and failures. These incidents clearly indicate the necessity of extensive research efforts to protect the power system from external intrusion and to reduce the damages from post-attack effects. We analyze the vulnerability of smart power grids to cyber and physical attacks and …