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Articles 151 - 180 of 341
Full-Text Articles in Computer Engineering
Energy Efficient And Secure Wireless Sensor Networks Design, Afraa Attiah
Energy Efficient And Secure Wireless Sensor Networks Design, Afraa Attiah
Electronic Theses and Dissertations
Wireless Sensor Networks (WSNs) are emerging technologies that have the ability to sense, process, communicate, and transmit information to a destination, and they are expected to have significant impact on the efficiency of many applications in various fields. The resource constraint such as limited battery power, is the greatest challenge in WSNs design as it affects the lifetime and performance of the network. An energy efficient, secure, and trustworthy system is vital when a WSN involves highly sensitive information. Thus, it is critical to design mechanisms that are energy efficient and secure while at the same time maintaining the desired …
Joint Optimization Of Illumination And Communication For A Multi-Element Vlc Architecture, Sifat Ibne Mushfique
Joint Optimization Of Illumination And Communication For A Multi-Element Vlc Architecture, Sifat Ibne Mushfique
Electronic Theses and Dissertations
Because of the ever increasing demand wireless data in the modern era, the Radio Frequency (RF) spectrum is becoming more congested. The remaining RF spectrum is being shrunk at a very heavy rate, and spectral management is becoming more difficult. Mobile data is estimated to grow more than 10 times between 2013 and 2019, and due to this explosion in data usage, mobile operators are having serious concerns focusing on public Wireless Fidelity (Wi-Fi) and other alternative technologies. Visible Light Communication (VLC) is a recent promising technology complementary to RF spectrum which operates at the visible light spectrum band (roughly …
Bridging The Gap Between Application And Solid-State-Drives, Jian Zhou
Bridging The Gap Between Application And Solid-State-Drives, Jian Zhou
Electronic Theses and Dissertations
Data storage is one of the important and often critical parts of the computing system in terms of performance, cost, reliability, and energy. Numerous new memory technologies, such as NAND flash, phase change memory (PCM), magnetic RAM (STT-RAM) and Memristor, have emerged recently. Many of them have already entered the production system. Traditional storage optimization and caching algorithms are far from optimal because storage I/Os do not show simple locality. To provide optimal storage we need accurate predictions of I/O behavior. However, the workloads are increasingly dynamic and diverse, making the long and short time I/O prediction challenge. Because of …
Real-Time Sil Emulation Architecture For Cooperative Automated Vehicles, Nitish Gupta
Real-Time Sil Emulation Architecture For Cooperative Automated Vehicles, Nitish Gupta
Electronic Theses and Dissertations
This thesis presents a robust, flexible and real-time architecture for Software-in-the-Loop (SIL) testing of connected vehicle safety applications. Emerging connected and automated vehicles (CAV) use sensing, communication and computing technologies in the design of a host of new safety applications. Testing and verification of these applications is a major concern for the automotive industry. The CAV safety applications work by sharing their state and movement information over wireless communication links. Vehicular communication has fueled the development of various Cooperative Vehicle Safety (CVS) applications. Development of safety applications for CAV requires testing in many different scenarios. However, the recreation of test …
A Game-Theoretic Model For Regulating Freeriding In Subsidy-Based Pervasive Spectrum Sharing Markets, Mostafizur Rahman
A Game-Theoretic Model For Regulating Freeriding In Subsidy-Based Pervasive Spectrum Sharing Markets, Mostafizur Rahman
Electronic Theses and Dissertations
Cellular spectrum is a limited natural resource becoming scarcer at a worrisome rate. To satisfy users' expectation from wireless data services, researchers and practitioners recognized the necessity of more utilization and pervasive sharing of the spectrum. Though scarce, spectrum is underutilized in some areas or within certain operating hours due to the lack of appropriate regulatory policies, static allocation and emerging business challenges. Thus, finding ways to improve the utilization of this resource to make sharing more pervasive is of great importance. There already exists a number of solutions to increase spectrum utilization via increased sharing. Dynamic Spectrum Access (DSA) …
Masquerading Techniques In Ieee 802.11 Wireless Local Area Networks, Omar Nakhila
Masquerading Techniques In Ieee 802.11 Wireless Local Area Networks, Omar Nakhila
Electronic Theses and Dissertations
The airborne nature of wireless transmission offers a potential target for attackers to compromise IEEE 802.11 Wireless Local Area Network (WLAN). In this dissertation, we explore the current WLAN security threats and their corresponding defense solutions. In our study, we divide WLAN vulnerabilities into two aspects, client, and administrator. The client-side vulnerability investigation is based on examining the Evil Twin Attack (ETA) while our administrator side research targets Wi-Fi Protected Access II (WPA2). Three novel techniques have been presented to detect ETA. The detection methods are based on (1) creating a secure connection to a remote server to detect the …
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Development Of A Locomotion And Balancing Strategy For Humanoid Robots, Emile Bahdi
Electronic Theses and Dissertations
The locomotion ability and high mobility are the most distinguished features of humanoid robots. Due to the non-linear dynamics of walking, developing and controlling the locomotion of humanoid robots is a challenging task. In this thesis, we study and develop a walking engine for the humanoid robot, NAO, which is the official robotic platform used in the RoboCup Spl. Aldebaran Robotics, the manufacturing company of NAO provides a walking module that has disadvantages, such as being a black box that does not provide control of the gait as well as the robot walk with a bent knee. The latter disadvantage, …
Categorical Range Reporting In 2d Using Wavelet Tree, Swathi Kanthareddy Sumithra
Categorical Range Reporting In 2d Using Wavelet Tree, Swathi Kanthareddy Sumithra
Electronic Theses and Dissertations
The research involved optimizing the space and bounding the output time by the output size in categorical range reporting of points within the given rectangle query Q in two dimension using wavelet trees and range counting. The time taken to report those points and space to tore n points in set S can be done using wavelet tree and range counting. Consider set S consisting of n points in two-dimension. An orthogonal range reporting query rectangle Q = [a,b] x [c,d] on set S is sent to report the set of points in S which interacts with the query rectangle[Q]. …
Managing Io Resource For Co-Running Data Intensive Applications In Virtual Clusters, Dan Huang
Managing Io Resource For Co-Running Data Intensive Applications In Virtual Clusters, Dan Huang
Electronic Theses and Dissertations
Today Big Data computer platforms employ resource management systems such as Yarn, Torque, Mesos, and Google Borg to enable sharing the physical computing among many users or applications. Given virtualization and resource management systems, users are able to launch their applications on the same node with low mutual interference and management overhead on CPU and memory. However, there are still challenges to be addressed before these systems can be fully adopted to manage the IO resources in Big Data File Systems (BDFS) and shared network facilities. In this study, we mainly study on three IO management problems systematically, in terms …
A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun
A Scale Space Local Binary Pattern (Sslbp) – Based Feature Extraction Framework To Detect Bones From Knee Mri Scans, Jinyeong Mun
Electronic Theses and Dissertations
The medical industry is currently working on a fully autonomous surgical system, which is considered a novel modality to go beyond technical limitations of conventional surgery. In order to apply an autonomous surgical system to knees, one of the primarily responsible areas for supporting the total weight of human body, accurate segmentation of bones from knee Magnetic Resonance Imaging (MRI) scans plays a crucial role. In this paper, we propose employing the Scale Space Local Binary Pattern (SSLBP) feature extraction, a variant of local binary pattern extractions, for detecting bones from knee images. The proposed methods consist of two phases. …
A Framework For Clustering And Adaptive Topic Tracking On Evolving Text And Social Media Data Streams., Gopi Chand Nutakki
A Framework For Clustering And Adaptive Topic Tracking On Evolving Text And Social Media Data Streams., Gopi Chand Nutakki
Electronic Theses and Dissertations
Recent advances and widespread usage of online web services and social media platforms, coupled with ubiquitous low cost devices, mobile technologies, and increasing capacity of lower cost storage, has led to a proliferation of Big data, ranging from, news, e-commerce clickstreams, and online business transactions to continuous event logs and social media expressions. These large amounts of online data, often referred to as data streams, because they get generated at extremely high throughputs or velocity, can make conventional and classical data analytics methodologies obsolete. For these reasons, the issues of management and analysis of data streams have been researched extensively …
Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi
Dynamic Adversarial Mining - Effectively Applying Machine Learning In Adversarial Non-Stationary Environments., Tegjyot Singh Sethi
Electronic Theses and Dissertations
While understanding of machine learning and data mining is still in its budding stages, the engineering applications of the same has found immense acceptance and success. Cybersecurity applications such as intrusion detection systems, spam filtering, and CAPTCHA authentication, have all begun adopting machine learning as a viable technique to deal with large scale adversarial activity. However, the naive usage of machine learning in an adversarial setting is prone to reverse engineering and evasion attacks, as most of these techniques were designed primarily for a static setting. The security domain is a dynamic landscape, with an ongoing never ending arms race …
An Interactive Interface For Nursing Robots., Ankita Sahu
An Interactive Interface For Nursing Robots., Ankita Sahu
Electronic Theses and Dissertations
Physical Human-Robot Interaction (pHRI) is inevitable for a human user while working with assistive robots. There are various aspects of pHRI, such as choosing the interface, type of control schemes implemented and the modes of interaction. The research work presented in this thesis concentrates on a health-care assistive robot called Adaptive Robot Nursing Assistant (ARNA). An assistive robot in a health-care environment has to be able to perform routine tasks and be aware of the surrounding environment at the same time. In order to operate the robot, a teleoperation based interaction would be tedious for some patients as it would …
A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener
A Data Science Pipeline For Educational Data : A Case Study Using Learning Catalytics In The Active Learning Classroom., Asuman Cagla Acun Sener
Electronic Theses and Dissertations
This thesis presents an applied data science methodology on a set of University of Louisville, Speed School of Engineering student data. We used data mining and classic statistical techniques to help educational researchers quickly see the data trends and peculiarities. Our data includes scores and information about two Engineering Fundamental Class. The format of these classes is called an inverted classroom model or flipped class. The purpose of this study is to analyze the data in order to uncover potentially hidden information, tell interesting stories about the data, examine student learning behavior and learning performance in an active learning environment, …
Vehicle Make And Model Recognition For Intelligent Transportation Monitoring And Surveillance., Faezeh Tafazzoli
Vehicle Make And Model Recognition For Intelligent Transportation Monitoring And Surveillance., Faezeh Tafazzoli
Electronic Theses and Dissertations
Vehicle Make and Model Recognition (VMMR) has evolved into a significant subject of study due to its importance in numerous Intelligent Transportation Systems (ITS), such as autonomous navigation, traffic analysis, traffic surveillance and security systems. A highly accurate and real-time VMMR system significantly reduces the overhead cost of resources otherwise required. The VMMR problem is a multi-class classification task with a peculiar set of issues and challenges like multiplicity, inter- and intra-make ambiguity among various vehicles makes and models, which need to be solved in an efficient and reliable manner to achieve a highly robust VMMR system. In this dissertation, …
Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., Aneseh Alvanpour
Uncovering Exceptional Predictions Using Exploratory Analysis Of Second Stage Machine Learning., Aneseh Alvanpour
Electronic Theses and Dissertations
Nowadays, algorithmic systems for making decisions are widely used to facilitate decisions in a variety of fields such as medicine, banking, applying for universities or network security. However, many machine learning algorithms are well-known for their complex mathematical internal workings which turn them into black boxes and makes their decision-making process usually difficult to understand even for experts. In this thesis, we try to develop a methodology to explain why a certain exceptional machine learned decision was made incorrectly by using the interpretability of the decision tree classifier. Our approach can provide insights about potential flaws in feature definition or …
Using A Multi Variate Pattern Analysis (Mvpa) Approach To Decode Fmri Responses To Fear And Anxiety., Sajjad Torabian Esfahani
Using A Multi Variate Pattern Analysis (Mvpa) Approach To Decode Fmri Responses To Fear And Anxiety., Sajjad Torabian Esfahani
Electronic Theses and Dissertations
This study analyzed fMRI responses to fear and anxiety using a Multi Variate Pattern Analysis (MVPA) approach. Compared to conventional univariate methods which only represent regions of activation, MVPA provides us with more detailed patterns of voxels. We successfully found different patterns for fear and anxiety through separate classification attempts in each subject’s representational space. Further, we transformed all the individual models into a standard space to do group analysis. Results showed that subjects share a more common fear response. Also, the amygdala and hippocampus areas are more important for differentiating fear than anxiety.
Peeking Into The Other Half Of The Glass : Handling Polarization In Recommender Systems., Mahsa Badami
Peeking Into The Other Half Of The Glass : Handling Polarization In Recommender Systems., Mahsa Badami
Electronic Theses and Dissertations
This dissertation is about filtering and discovering information online while using recommender systems. In the first part of our research, we study the phenomenon of polarization and its impact on filtering and discovering information. Polarization is a social phenomenon, with serious consequences, in real-life, particularly on social media. Thus it is important to understand how machine learning algorithms, especially recommender systems, behave in polarized environments. We study polarization within the context of the users' interactions with a space of items and how this affects recommender systems. We first formalize the concept of polarization based on item ratings and then relate …
Data Driven Discovery Of Materials Properties., Fadoua Khmaissia
Data Driven Discovery Of Materials Properties., Fadoua Khmaissia
Electronic Theses and Dissertations
The high pace of nowadays industrial evolution is creating an urgent need to design new cost efficient materials that can satisfy both current and future demands. However, with the increase of structural and functional complexity of materials, the ability to rationally design new materials with a precise set of properties has become increasingly challenging. This basic observation has triggered the idea of applying machine learning techniques in the field, which was further encouraged by the launch of the Materials Genome Initiative (MGI) by the US government since 2011. In this work, we present a novel approach to apply machine learning …
Abstraction Hierarchies For Multi-Agent Pathfinding, Aaron R. Kraft
Abstraction Hierarchies For Multi-Agent Pathfinding, Aaron R. Kraft
Electronic Theses and Dissertations
Multi-Agent Pathfinding is an NP-Complete search problem with a branching factor that is exponential in the number of agents. Because of this exponential feature, it can be difficult to solve optimally using traditional search techniques, even for relatively small problems. Many recent optimal solvers have attempted to reduce the complexity of the problem by resolving the conflicts between agent paths separately. Very little of this research has focused on creating quality heuristics to help solve the problem. In this thesis, we create heuristics using sub-problems created by removing agents from a complete problem instance. We combine this with the Independence …
Optimized Trajectory Generation For Car-Like Robots On A Closed Loop Track, Tyler Friedl
Optimized Trajectory Generation For Car-Like Robots On A Closed Loop Track, Tyler Friedl
Electronic Theses and Dissertations
This thesis presents a method for generating an optimized path through a given track. The path is generated by choosing waypoints throughout the track then iteratively optimizing the position of these waypoints. The waypoints are then connected by optimized paths represented by curvature polynomials. The end result is a path through the track represented as a spline of curvature polynomials. This method is applied to multiple simulated tracks and the results are presented. By generating and representing the paths in the continuous domain, the method has improved computational efficiency from many of the discrete methods used to generate an optimal …
Explaining The Performance Of Bidirectional Dijkstra And A* On Road Networks, Sneha Sawlani
Explaining The Performance Of Bidirectional Dijkstra And A* On Road Networks, Sneha Sawlani
Electronic Theses and Dissertations
The heuristic search community traditionally uses A* as the baseline algorithm for their research methods. Research papers in the road networks community, however, often build upon Dijkstra's algorithm and use Bidirectional Dijkstra's algorithm as their baseline. This thesis investigates the performance of A* and Bidirectional Dijkstra in road networks to see how they compare and to see if there is a principled explanation for the different approaches. Our analysis reveals why Bidirectional Dijkstra can perform well in this domain, but also shows a simple mistake that can be made when building test problems that hurts the performance of A*.
Load-Balancing In Local And Metro-Area Networks With Mptcp And Openflow, Austin Jerome
Load-Balancing In Local And Metro-Area Networks With Mptcp And Openflow, Austin Jerome
Electronic Theses and Dissertations
In this thesis, a novel load-balancing technique for local or metro-area traffic is proposed in mesh-style topologies. The technique uses Software Defined Networking (SDN) architecture with virtual local area network (VLAN) setups typically seen in a campus or small-to-medium enterprise environment. This was done to provide a possible solution or at least a platform to expand on for the load-balancing dilemma that network administrators face today. The transport layer protocol Multi-Path TCP (MPTCP) coupled with IP aliasing is also used. The trait of MPTCP of forming multiple subflows from sender to receiver depending on the availability of IP addresses at …
Improving The Performance Of Data-Intensive Computing On Cloud Platforms, Wei Dai
Improving The Performance Of Data-Intensive Computing On Cloud Platforms, Wei Dai
Electronic Theses and Dissertations
Big Data such as Terabyte and Petabyte datasets are rapidly becoming the new norm for various organizations across a wide range of industries. The widespread data-intensive computing needs have inspired innovations in parallel and distributed computing, which has been the effective way to tackle massive computing workload for decades. One significant example is MapReduce, which is a programming model for expressing distributed computations on huge datasets, and an execution framework for data-intensive computing on commodity clusters as well. Since it was originally proposed by Google, MapReduce has become the most popular technology for data-intensive computing. While Google owns its proprietary …
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack
Optimized Multilayer Perceptron With Dynamic Learning Rate To Classify Breast Microwave Tomography Image, Chulwoo Pack
Electronic Theses and Dissertations
Most recently developed Computer Aided Diagnosis (CAD) systems and their related research is based on medical images that are usually obtained through conventional imaging techniques such as Magnetic Resonance Imaging (MRI), x-ray mammography, and ultrasound. With the development of a new imaging technology called Microwave Tomography Imaging (MTI), it has become inevitable to develop a CAD system that can show promising performance using new format of data. The platform can have a flexibility on its input by adopting Artificial Neural Network (ANN) as a classifier. Among the various phases of CAD system, we have focused on optimizing the classification phase …
Towards High-Efficiency Data Management In The Next-Generation Persistent Memory System, Xunchao Chen
Towards High-Efficiency Data Management In The Next-Generation Persistent Memory System, Xunchao Chen
Electronic Theses and Dissertations
For the sake of higher cell density while achieving near-zero standby power, recent research progress in Magnetic Tunneling Junction (MTJ) devices has leveraged Multi-Level Cell (MLC) configurations of Spin-Transfer Torque Random Access Memory (STT-RAM). However, in order to mitigate the write disturbance in an MLC strategy, data stored in the soft bit must be restored back immediately after the hard bit switching is completed. Furthermore, as the result of MTJ feature size scaling, the soft bit can be expected to become disturbed by the read sensing current, thus requiring an immediate restore operation to ensure the data reliability. In this …
End To End Brain Fiber Orientation Estimation Using Deep Learning, Nandakishore Puttashamachar
End To End Brain Fiber Orientation Estimation Using Deep Learning, Nandakishore Puttashamachar
Electronic Theses and Dissertations
In this work, we explore the various Brain Neuron tracking techniques, one of the most significant applications of Diffusion Tensor Imaging. Tractography is a non-invasive method to analyze underlying tissue micro-structure. Understanding the structure and organization of the tissues facilitates a diagnosis method to identify any aberrations which can occur within tissues due to loss of cell functionalities, provides acute information on the occurrences of brain ischemia or stroke, the mutation of certain neurological diseases such as Alzheimer, multiple sclerosis and so on. Under all these circumstances, accurate localization of the aberrations in efficient manner can help save a life. …
Energy-Aware Data Movement In Non-Volatile Memory Hierarchies, Navid Khoshavi Najafabadi
Energy-Aware Data Movement In Non-Volatile Memory Hierarchies, Navid Khoshavi Najafabadi
Electronic Theses and Dissertations
While technology scaling enables increased density for memory cells, the intrinsic high leakage power of conventional CMOS technology and the demand for reduced energy consumption inspires the use of emerging technology alternatives such as eDRAM and Non-Volatile Memory (NVM) including STT-MRAM, PCM, and RRAM. The utilization of emerging technology in Last Level Cache (LLC) designs which occupies a signifcant fraction of total die area in Chip Multi Processors (CMPs) introduces new dimensions of vulnerability, energy consumption, and performance delivery. To be specific, a part of this research focuses on eDRAM Bit Upset Vulnerability Factor (BUVF) to assess vulnerable portion of …
Reducing Side-Sweep Accidents With Vehicle-To-Vehicle Communications, Gamini Bulumulle
Reducing Side-Sweep Accidents With Vehicle-To-Vehicle Communications, Gamini Bulumulle
Electronic Theses and Dissertations
This dissertation present contributions to the understanding of the causes of a side-sweep accidents on multi-lane highways using computer simulation. Side-sweep accidents are one of the major causes of loss of life and property damage on highways. This type of accident is caused by a driver initiating a lane change while another vehicle is blocking the road in the target lane. Our objective in the research described in this dissertation was to understand and simulate the different factors which affect the likelihood of side sweep accidents. For instance, we know that blind spots, parts of the road that are not …
System Identification Of A Circulation Control Unmanned Aerial Vehicle, Mohammed Agha
System Identification Of A Circulation Control Unmanned Aerial Vehicle, Mohammed Agha
Electronic Theses and Dissertations
The advancement in automation and sensory systems in recent years has led to an increase the demand of UAV missions. Due to this increase in demand, the research community has gained interest in investigating UAV performance enhancing systems. Circulation Control (CC), which is an active control flow method used to enhance UAV lift, is a performance enhancing system currently studied. In prior research, experimental studies have shown that Circulation Control wings (CCW) implemented on class-I UAVs can reduce take-off distance by 54%. Wind tunnel tests reveal that CC improves aircraft payload capabilities through lift enhancement. Increasing aircraft payload capabilities causes …