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Articles 1 - 30 of 404
Full-Text Articles in Engineering
Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee
Statistics-Based Anomaly Detection And Correction Method For Amazon Customer Reviews, Ishani Chatterjee
Dissertations
People nowadays use the Internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source of gathering information for data analytics, sentiment analysis, natural language processing, etc. The most critical challenge is interpreting this data and capturing the sentiment behind these expressions. Sentiment analysis is analyzing, processing, concluding, and inferencing subjective texts with the views. Companies use sentiment analysis to understand public opinions, perform market research, analyze brand reputation, recognize customer experiences, and study social media influence. According to the different needs for aspect granularity, …
Machine Learning Techniques For Network Analysis, Irfan Lateef
Machine Learning Techniques For Network Analysis, Irfan Lateef
Dissertations
The network's size and the traffic on it are both increasing exponentially, making it difficult to look at its behavior holistically and address challenges by looking at link level behavior. It is possible that there are casual relationships between links of a network that are not directly connected and which may not be obvious to observe. The goal of this dissertation is to study and characterize the behavior of the entire network by using eigensubspace based techniques and apply them to network traffic engineering applications.
A new method that uses the joint time-frequency interpretation of eigensubspace representation for network statistics …
On Resource-Efficiency And Performance Optimization In Big Data Computing And Networking Using Machine Learning, Wuji Liu
Dissertations
Due to the rapid transition from traditional experiment-based approaches to large-scale, computational intensive simulations, next-generation scientific applications typically involve complex numerical modeling and extreme-scale simulations. Such model-based simulations oftentimes generate colossal amounts of data, which must be transferred over high-performance network (HPN) infrastructures to remote sites and analyzed against experimental or observation data on high-performance computing (HPC) facility. Optimizing the performance of both data transfer in HPN and simulation-based model development on HPC is critical to enabling and accelerating knowledge discovery and scientific innovation. However, such processes generally involve an enormous set of attributes including domain-specific model parameters, network transport …
A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko
A Practical Approach To Automated Software Correctness Enhancement, Aleksandr Zakharchenko
Dissertations
To repair an incorrect program does not mean to make it correct; it only means to make it more-correct, in some sense, than it is. In the absence of a concept of relative correctness, i.e. the property of a program to be more-correct than another with respect to a specification, the discipline of program repair has resorted to various approximations of absolute (traditional) correctness, with varying degrees of success. This shortcoming is concealed by the fact that most program repair tools are tested on basic cases, whence making them absolutely correct is not clearly distinguishable from making them relatively more-correct. …
Algorithm Hardware Codesign For High Performance Neuromorphic Computing, Haowen Fang
Algorithm Hardware Codesign For High Performance Neuromorphic Computing, Haowen Fang
Dissertations - ALL
Driven by the massive application of Internet of Things (IoT), embedded system and Cyber Physical System (CPS) etc., there is an increasing demand to apply machine intelligence on these power limited scenarios. Though deep learning has achieved impressive performance on various realistic and practical tasks such as anomaly detection, pattern recognition, machine vision etc., the ever-increasing computational complexity and model size of Deep Neural Networks (DNN) make it challenging to deploy them onto aforementioned scenarios where computation, memory and energy resource are all limited. Early studies show that biological systems' energy efficiency can be orders of magnitude higher than that …
Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor
Enhanced Security Utilizing Side Channel Data Analysis, Michael Taylor
Computer Science and Engineering Theses and Dissertations
The physical state of a system is affected by the activities and processes in which it is tasked with carrying out. In the past there have been many instances where such physical changes have been exploited by bad actors in order to gain insight into the operational state and even the data being held on a system. This method of side channel exploitation is very often effective due to the relative difficulty of obfuscating activity on a physical level. However, in order to take advantage of side channel data streams one must have a detailed working knowledge of how a …
Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang
Robotic Olfactory-Based Navigation With Mobile Robots, Lingxiao Wang
Doctoral Dissertations and Master's Theses
Robotic odor source localization (OSL) is a technology that enables mobile robots or autonomous vehicles to find an odor source in unknown environments. It has been viewed as challenging due to the turbulent nature of airflows and the resulting odor plume characteristics. The key to correctly finding an odor source is designing an effective olfactory-based navigation algorithm, which guides the robot to detect emitted odor plumes as cues in finding the source. This dissertation proposes three kinds of olfactory-based navigation methods to improve search efficiency while maintaining a low computational cost, incorporating different machine learning and artificial intelligence methods.
A. …
Graph Based Management Of Temporal Data, Alex Fotso
Graph Based Management Of Temporal Data, Alex Fotso
Master of Science in Computer Science Theses
In recent decades, there has been a significant increase in the use of smart devices and sensors that led to high-volume temporal data generation. Temporal modeling and querying of this huge data have been essential for effective querying and retrieval. However, custom temporal models have the problem of generalizability, whereas the extended temporal models require users to adapt to new querying languages. In this thesis, we propose a method to improve the modeling and retrieval of temporal data using an existing graph database system (i.e., Neo4j) without extending with additional operators. Our work focuses on temporal data represented as intervals …
Precision Grasp Planning For Integrated Arm-Hand Systems, Shuwei Qiu
Precision Grasp Planning For Integrated Arm-Hand Systems, Shuwei Qiu
Electronic Thesis and Dissertation Repository
The demographic shift has caused labor shortages across the world, and it seems inevitable to rely on robots more than ever to fill the widening gap in the workforce. The robotic replacement of human workers necessitates the ability of autonomous grasping as the most natural but rather a vital part of almost all activities. Among different types of grasping, fingertip grasping attracts much attention because of its superior performance for dexterous manipulation. This thesis contributes to autonomous fingertip grasping in four areas including hand-eye calibration, grasp quality evaluation, inverse kinematics (IK) solution of robotic arm-hand systems, and simultaneous achievement of …
3d Shape Estimation Of Negative Obstacles Using Lidar Point Cloud Data, Viswadeep Lebakula
3d Shape Estimation Of Negative Obstacles Using Lidar Point Cloud Data, Viswadeep Lebakula
Theses and Dissertations
Obstacle detection and avoidance plays a crucial role in the autonomous navigation of unmanned ground vehicles (UGV). Information about the obstacles decreases as the distance between the UGV and obstacles increases. However, this information decreases much more rapidly for negative obstacles than for positive obstacles. UGV navigation becomes more challenging in off-road environments due to the higher probability of finding negative obstacles (e.g., potholes, ditches, trenches, etc.) compared with on-road environments. One approach to solve this problem is to avoid the candidate path with a negative obstacle, but in off-road environments avoiding negative obstacles in all situations is not possible. …
Detecting Malware In Memory With Memory Object Relationships, Demarcus M. Thomas Sr.
Detecting Malware In Memory With Memory Object Relationships, Demarcus M. Thomas Sr.
Theses and Dissertations
Malware is a growing concern that not only affects large businesses but the basic consumer as well. As a result, there is a need to develop tools that can identify the malicious activities of malware authors. A useful technique to achieve this is memory forensics. Memory forensics is the study of volatile data and its structures in Random Access Memory (RAM). It can be utilized to pinpoint what actions have occurred on a computer system.
This dissertation utilizes memory forensics to extract relationships between objects and supervised machine learning as a novel method for identifying malicious processes in a system …
Design Of Plastic Contaminant Eliminator In Seed Cotton, Joshua H. Tandio
Design Of Plastic Contaminant Eliminator In Seed Cotton, Joshua H. Tandio
Theses and Dissertations
Plastic contamination in cotton is a problem in cotton industry and researchers have worked on this problem with different approaches. This thesis documents the design of mechanical and electronic real-time systems for detecting and removing plastic contaminants. The mechanical system was designed to expose plastic embedded inside the seed cotton to the sensor and to separate plastic contaminated cotton from the process stream. The detection system consisted of an embedded computer interfaced with a USB camera and Neural Network (NN) software running in it. Two NN models were tested, a transfer learning model and a built-from-scratch original model. The original …
The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik
The Application Of Design Thinking On Evaluating A User Self-Service Data Analytics/Science Platform, Aheeka Pattnaik
Dissertations and Theses
This thesis is aimed at utilising design thinking and the first half of the double diamond framework to i) set-up a research and select the appropriate participants, ii) gather requirements and define user personas from those eligible participants, and then iii) define the framework for evaluating a user self-service data analytics/science platform. Derived from the author’s own experiences, both as a Business Analyst (BA) and Citizen Data Scientist, with no-, low-, and code-based data analytics and science platforms are being implemented for enabling user self-service analytics – for users who are completely new to the space of data analysis and …
Autonomous Control And Signal Acquisition System, Rion Cadell Krampe
Autonomous Control And Signal Acquisition System, Rion Cadell Krampe
Honors College Theses
Our goal is to continue a previous teams project to build a NDE autonomous control and signal acquisition system that is more precise, more customizable with both code and mechanical parts, and cheaper than a similar system bought by the school. This goal has two stages to it. First, to repair the system from considerable damage it received during transportation. Secondly, to continue designing and developing the system to make considerable progress towards the goal of a fully functional NDE system. Along with making progress we must consider the team after us and create an easy stepping off point for …
Iot Greenhouse Monitoring System, Raj Basnet
Iot Greenhouse Monitoring System, Raj Basnet
Honors Theses
Our project is a greenhouse monitoring system. The customer states that they need a complete monitoring system for their greenhouse. There are a lot of items within the greenhouse that need to be watered at the right time and kept at a certain temperature. The customer is not always around to check the status of these items due to their busy lifestyle. They would like a system to monitor all these items so they can check it on their smartphone no matter how far away they are from the greenhouse. The customer wants this to be a low-cost and energyefficient …
Federated Agentless Detection Of Endpoints Using Behavioral And Characteristic Modeling, Hansaka Angel Dias Edirisinghe Kodituwakku
Federated Agentless Detection Of Endpoints Using Behavioral And Characteristic Modeling, Hansaka Angel Dias Edirisinghe Kodituwakku
Doctoral Dissertations
During the past two decades computer networks and security have evolved that, even though we use the same TCP/IP stack, network traffic behaviors and security needs have significantly changed. To secure modern computer networks, complete and accurate data must be gathered in a structured manner pertaining to the network and endpoint behavior. Security operations teams struggle to keep up with the ever-increasing number of devices and network attacks daily. Often the security aspect of networks gets managed reactively instead of providing proactive protection. Data collected at the backbone are becoming inadequate during security incidents. Incident response teams require data that …
Profile-Guided Data Management For Heterogeneous Memory Systems, Matthew B. Olson
Profile-Guided Data Management For Heterogeneous Memory Systems, Matthew B. Olson
Doctoral Dissertations
Market forces and technological constraints have led to a gap between CPU and memory performance that has widened for decades. While processor scaling has plateaued in recent years, this gap persists and is not expected to diminish for the foreseeable future. This discrepancy presents a host of challenges for scaling application performance, which have only been exacerbated in recent years, as increasing demands for fast and effective data analytics are driving memory energy, bandwidth, and capacity requirements to new heights.
To address these trends, hardware architects have introduced a plethora of memory technologies. For example, most modern memory systems include …
Qualitative And Quantitative Improvements For Positron Emission Tomography Using Different Motion Correction Methodologies, Tasmia Rahman Tumpa
Qualitative And Quantitative Improvements For Positron Emission Tomography Using Different Motion Correction Methodologies, Tasmia Rahman Tumpa
Doctoral Dissertations
Positron Emission Tomography (PET) data suffers from low image quality and quantitative accuracy due to different kinds of motion of patients during imaging. Hardware-based motion correction is currently the standard; however, is limited by several constraints, the most important of which is retroactive data correction. Data-driven techniques to perform motion correction in this regard are active areas of research. The motivation behind this work lies in developing a complete data-driven approach to address both motion detection and correction. The work first presents an algorithm based on the positron emission particle tracking (PEPT) technique and makes use of time-of-flight (TOF) information …
Respiratory Sound Analysis For The Evidence Of Lung Health, Priyanka Sreerama
Respiratory Sound Analysis For The Evidence Of Lung Health, Priyanka Sreerama
Dissertations and Theses
Significant changes have been made on audio-based technologies over years in several different fields along with healthcare industry. Analysis of Lung sounds is a potential source of noninvasive, quantitative information along with additional objective on the status of the pulmonary system. To do that medical professionals listen to sounds heard over the chest wall at different positions with a stethoscope which is known as auscultation and is important in diagnosing respiratory diseases. At times, possibility of inaccurate interpretation of respiratory sounds happens because of clinician’s lack of considerable expertise or sometimes trainees such as interns and residents misidentify respiratory sounds. …
Addressing Security And Privacy Issues By Analyzing Vulnerabilities In Iot Applications, Francsico Javier Candelario Burgoa
Addressing Security And Privacy Issues By Analyzing Vulnerabilities In Iot Applications, Francsico Javier Candelario Burgoa
Open Access Theses & Dissertations
The Internet of Things (IoT) environment has been expanding rapidly for the past few years into several areas of our lives, from factories, to stores and even into our own homes. All these new devices in our homes make our day-to-day lives easier and more comfortable with less effort on our part, converting our simple houses into smart homes. This increase in inter-connectivity brings multiple benefits including the improvement in energy efficiency in our homes, however it also brings with it some potential dangers since more points of connection mean more potential vulnerabilities in our grid. These vulnerabilities bring security …
The Network Link Outlier Factor (Nlof) For Localizing Network Faults, Christopher Mendoza
The Network Link Outlier Factor (Nlof) For Localizing Network Faults, Christopher Mendoza
Open Access Theses & Dissertations
This work presents the Network Link Outlier Factor (NLOF), a data analytics pipeline for network fault detection and localization solution that consists of four stages. In the first stage, flow record throughput values are clustered in two sub-stages: using Density-Based Spatial Clustering of Applications with Noise (DBSCAN) and then a novel domain-specific ThroughPut Cluster (TPCluster) technique. In the second stage, Flow Outlier Factor (FOF) scores are computed for each flow. In the third stage, flows are traced onto the network. Finally, in the fourth stage, each link is given a Network Link Outlier Factor (NLOF) score which is the ratio …
Automated Report Based System To Encourage A Greener Commute To Campus, Ronald Velasquez
Automated Report Based System To Encourage A Greener Commute To Campus, Ronald Velasquez
Computer Science and Computer Engineering Undergraduate Honors Theses
This project consists of the design and implementation of a tool to encourage greener commutes to the University of Arkansas. Trends in commuting of the last few years show a decline in not so environment-friendly commute modes. Nevertheless, ensuring that this trend continues is vital to assure a significant impact. The created tool is an automated report system. The report displays information about different commute options. A Google form allows users to submit report requests, and a web app allows the sustainability office to process them in batches. This system was built in the Apps Script platform. It implements several …
Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil
Network Management, Optimization And Security With Machine Learning Applications In Wireless Networks, Mariam Nabil
Theses and Dissertations
Wireless communication networks are emerging fast with a lot of challenges and ambitions. Requirements that are expected to be delivered by modern wireless networks are complex, multi-dimensional, and sometimes contradicting. In this thesis, we investigate several types of emerging wireless networks and tackle some challenges of these various networks. We focus on three main challenges. Those are Resource Optimization, Network Management, and Cyber Security. We present multiple views of these three aspects and propose solutions to probable scenarios. The first challenge (Resource Optimization) is studied in Wireless Powered Communication Networks (WPCNs). WPCNs are considered a very promising approach towards sustainable, …
Synthesis Methodologies For Robust And Reconfigurable Clock Networks, Necati Uysal
Synthesis Methodologies For Robust And Reconfigurable Clock Networks, Necati Uysal
Electronic Theses and Dissertations, 2020-2023
In today's aggressively scaled technology nodes, billions of transistors are packaged into a single integrated circuit. Electronic Design Automation (EDA) tools are needed to automatically assemble the transistors into a functioning system. One of the most important design steps in the physical synthesis is the design of the clock network. The clock network delivers a synchronizing clock signal to each sequential element. The clock signal is required to be delivered meeting timing constraints under variations and in multiple operating modes. Synthesizing such clock networks is becoming increasingly difficult with the complex power management methodologies and severe manufacturing variations. Clock network …
Approaches To Improve The Execution Time Of A Quantum Network Simulation, Joseph B. Tippit
Approaches To Improve The Execution Time Of A Quantum Network Simulation, Joseph B. Tippit
Theses and Dissertations
Evaluating quantum networks is an expensive and time-consuming task that benefits from simulation. A potential improvement is to utilize GPUs, namely by leveraging NVIDIA's programming framework, CUDA. To avoid performance pitfalls of higher level languages and programming models such as the so called "two language problem," the Julia Programming Language provides the basis for the development effort. This research develops a two module prototype quantum network simulation framework using GPUs and Julia. Performance of the software is measured and compared against other languages such as MATLAB.
Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr
Augmented Communications : A Solution For Overcoming High Spatial Correlation Of The Massive-Miso Vlc Channel, Monette Khadr
Legacy Theses & Dissertations (2009 - 2024)
A key challenge for future wireless networks is to come upon a riveting compromise between spectral efficiency, complexity, and energy efficiency. The challenge is also intensified due to the pace at which the Internet-of-Things (IoT) technology is arriving, causing an upheaval to pre-existing network infrastructures in terms of elevating spectrum scarcity. To keep pace with the exploding data demand forecasts, a circumvention is required. One realization is by utilizing the high-band spectrum and the rich body of knowledge on multiple-input multiple-output (MIMO) technologies. One of the prominent high frequency technologies is visible light communications (VLC). VLC provide a large unregulated …
Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler
Contrastive Learning For Unsupervised Auditory Texture Models, Christina Trexler
Computer Science and Computer Engineering Undergraduate Honors Theses
Sounds with a high level of stationarity, also known as sound textures, have perceptually relevant features which can be captured by stimulus-computable models. This makes texture-like sounds, such as those made by rain, wind, and fire, an appealing test case for understanding the underlying mechanisms of auditory recognition. Previous auditory texture models typically measured statistics from auditory filter bank representations, and the statistics they used were somewhat ad-hoc, hand-engineered through a process of trial and error. Here, we investigate whether a better auditory texture representation can be obtained via contrastive learning, taking advantage of the stationarity of auditory textures to …
A Human-Embodied Drone For Dexterous Aerial Manipulation, Dongbin Kim
A Human-Embodied Drone For Dexterous Aerial Manipulation, Dongbin Kim
UNLV Theses, Dissertations, Professional Papers, and Capstones
Current drones perform a wide variety of tasks in surveillance, photography, agriculture, package delivery, etc. However, these tasks are performed passively without the use of human interaction. Aerial manipulation shifts this paradigm and implements drones with robotic arms that allow interaction with the environment rather than simply sensing it. For example, in construction, aerial manipulation in conjunction with human interaction could allow operators to perform several tasks, such as hosing decks, drill into surfaces, and sealing cracks via a drone. This integration with drones will henceforth be known as dexterous aerial manipulation.
Our recent work integrated the worker’s experience into …
A Youthful Metaverse: Towards Designing Safe, Equitable, And Emotionally Fulfilling Social Virtual Reality Spaces For Younger Users, Divine Maloney
A Youthful Metaverse: Towards Designing Safe, Equitable, And Emotionally Fulfilling Social Virtual Reality Spaces For Younger Users, Divine Maloney
All Dissertations
Social virtual reality (VR) represents the modern rendition of the metaverse, this dissertation aims to fill the research gaps while highlighting trends of youth in VR. The scientific contributions of this research include 1) expanding the current HCI understanding of the social dynamics and the interactions of teens in emerging novel online digital spaces; 2) bridging two research areas that have not been widely studied in HCI, social VR and young users in social VR; and 3) generating design implications to inform the design of future social VR platforms to better support and protect teens’ online social experiences, results which …
Factors Influencing Service Robot Adoption: A Comparative Analysis Of Hotel-Specific Service Robot Acceptance Models, Ying Dong
UNLV Theses, Dissertations, Professional Papers, and Capstones
The market for service robots is expected to expand significantly owing to the increasing relevance of service automation under the outbreak of the COVID-19 pandemic. Despite the growing managerial interest in robotic applications in the hotel industry, current robotic research has been mostly conceptual with limited robot data on hand. In light of this issue, this paper will conduct a comparative analysis of hotel-specific service robot acceptance models between the Service Robot Acceptance Model (sRAM) and the Service Robot Integration Willingness (SRIW) framework. By identifying key elements of each service robot acceptance model, this paper puts an emphasis on investigating …