Computer Engineering Commons^™

Improving Network Policy Enforcement Using Natural Language Processing And Programmable Networks, Pinyi Shi

Theses and Dissertations--Computer Science

Computer networks are becoming more complex and challenging to operate, manage, and protect. As a result, Network policies that define how network operators should manage the network are becoming more complex and nuanced. Unfortunately, network policies are often an undervalued part of network design, leaving network operators to guess at the intent of policies that are written and fill in the gaps where policies don’t exist. Organizations typically designate Policy Committees to write down the network policies in the policy documents using high-level natural languages. The policy documents describe both the acceptable and unacceptable uses of the network. Network operators …

Protocols And Architecture For Privacy-Preserving Authentication And Secure Message Dissemination In Vehicular Ad Hoc Networks, Shafika Showkat Moni

Theses and Dissertations--Computer Science

The rapid development in the automotive industry and wireless communication technologies have enhanced the popularity of Vehicular ad hoc networks (VANETs). Today, the automobile industry is developing sophisticated sensors that can provide a wide range of assistive features, including accident avoidance, automatic lane tracking, semi-autonomous driving, suggested lane changes, and more. VANETs can provide drivers a safer and more comfortable driving experience, as well as many other useful services by leveraging such technological advancements. Even though this networking technology enables smart and autonomous driving, it also introduces a plethora of attack vectors. However, the main issues to be sorted out …

A Proportionality-Based Framework For Government Regulation Of Digital Tracing Apps In Times Of Emergency, Sharon Bassan

Dickinson Law Review (2017-Present)

Times of emergency present an inherent conflict between the public interest and the preservation of individual rights. Such times require granting emergency powers to the government on behalf of the public interest and relaxing safeguards against government actions that infringe rights. The lack of theoretical framework to assess governmental decisions in times of emergency leads to a polarized and politicized discourse about potential policies, and often, to public distrust and lack of compliance.

Such a discourse was evident regarding Digital Tracing Apps (“DTAs”), which are apps installed on cellular phones to alert users that they were exposed to people who …

Developing Reactive Distributed Aerial Robotics Platforms For Real-Time Contaminant Mapping, Joshua Ashley

Theses and Dissertations--Electrical and Computer Engineering

The focus of this research is to design a sensor data aggregation system and centralized sensor-driven trajectory planning algorithm for fixed-wing aircraft to optimally assist atmospheric simulators in mapping the local environment in real-time. The proposed application of this work is to be used in the event of a hazardous contaminant leak into the atmosphere as a fleet of sensing unmanned aerial vehicles (UAVs) could provide valuable information for evacuation measures. The data aggregation system was designed using a state-of-the-art networking protocol and radio with DigiMesh and a process/data management system in the ROS2 DDS. This system was tested to …

Garden Bot: Autonomous Home Garden Weed Removal Robot, Brendon Lovejoy, Robert Connolly, Isaac Lucas, Stevan Veselinov

Williams Honors College, Honors Research Projects

With frequent weeding being a tedious chore and an essential task for a successful garden, there is need for an automated method of handling this routine. Existing technologies utilize computer vision, GPS, multiple units and other tools to remove weeds from garden plots. However, these solutions are often complex and expensive, suited for large agricultural plots in contrast to small-scale home gardens. In addition, many of these technologies, along with manual tillers and cultivators suited for home use, are unable to perform weeding within rows of crops in a process known as intra-row weeding. The Garden Bot is an autonomous, …

Lapnitor: A Web Service That Protects Your Laptop From Theft., Michael Ameteku

Williams Honors College, Honors Research Projects

Laptop theft is an issue worldwide. According to an article from 2018, Security Boulevard stated that a laptop is stolen every 53 seconds. Using a laptop's camera, we can monitor the surroundings of the laptop and reduce a laptop's probability of being stolen. According to the University of Pittsburgh, a laptop has a 1-in- 10 chance of being stolen and nearly half of these thefts occur in offices or classrooms. These thefts mostly occur when a laptop owner leaves their device unattended for a certain period of time to maybe go visit the restroom or attend to a call when …

An Analysis Of Compressive Convolutional Autoencoders For Image Archiving In Medical Informatics, Charles Warren

Dissertations, Master's Theses and Master's Reports

Within a given enterprise network, an array of data types needs to be communicated. These network transmissions consist of images, videos, text, and binaries that have unique requirements of bandwidth and computational overhead to transmit. With respect to medical informatics, these include a multitude of varying subjects, standards, and modalities which are communicated to and from imaging equipment, clinicians, and medical archives. To reduce the required bandwidth to transmit, or provide adequate storage capacity for archival purposes, the data may be compressed in such a way that reduces the size of the image when it is transferred or stored. The …

Evaluating The Factors Influencing Alignment Of It And Business In A Cloud Computing Environment, Dr. Shailja Tripathi

Journal of International Technology and Information Management

Aligning IT with business strategically is the recent area of attention among researchers and practitioners because of its potential impact on organizational performance. Currently, large numbers of enterprises are migrating towards cloud computing as on-premise implementation of Information technology (IT) infrastructure is expensive. The purpose of this research is to examine the factors that influence the alignment of IT and business in cloud computing environment. Therefore, this study used the Strategic Alignment Maturity (SAM) model as a framework to validate the evolution of IT-business alignment in a cloud computing platform. A questionnaire-based survey method was employed for data collection. The …

E-Payment Adoption In Saudi Arabia, Alexander N. Chen, Joseph Y. Thomas, Mark E. Mcmurtrey Ph.D., Michael E. Ellis

Journal of International Technology and Information Management

Internet technology has influenced banking systems because of its capability to enhance the performance of financial operations. Several factors influence the adoption of new technology within the financial industry. Namely the customers’ perception of benefit, quality, Ease of Use, Security, Self-Efficacy, and Trust. However, various cultures and geopolitical issues influence technology adoption and are therefore worth further study. This paper focuses on the factors that influence the behaviors of Saudi Arabians and their adoption of e-payment systems. The paper shows the fundamental discoveries of an investigation examining the dispersion and the adoption of e-payment technology in …

Examining Factors Influencing Intention To Use M-Health Applications For Promoting Healthier Life Among Smartphone Users In Tanzania, Herman Mandari, Mahija Yahaya

Journal of International Technology and Information Management

Deaths related with Non-Communicable Diseases (NCDs) have recently increases, similarly, development of mobile technologies have paved a way in which Smartphone users can use m-health applications to address high level of sedentary behaviours that relates to negative health consequences. Therefore, this study was conducted to examine factors which may influence generation Y who are Smartphone users to adopt m-health applications in controlling NCDs in Tanzania. TAM theory was extended with awareness, trust and perceived cost to develop a research conceptual model of this study. Google form was used to developed online questionnaire which was distributed through social media platforms to …

Leveraging Machine Learning For Detecting Iot-Based Interference In Operational Wifi Networks, Josh Pulse

Honors Program Theses

IoT (Internet of Things) devices have become increasingly popular in recent years while WiFi continues to serve as primary network provider indoors. With the advancements in technology, the networks of IoT devices continue to weave closely with indoor WiFi network deployments. Both kinds of these networks primarily operate in 2.4 GHz ISM Band (though latest WiFi standards can operate in 5 GHz and 60 GHz bands, too). With the multitude of tiny IoT sensors being deployed indoors alongside operational WiFi networks, severe interference scenarios cannot be ruled out. As a result of this interference, performance of WiFi networks is bound …

Speaker Encoding For Zero-Shot Speech Synthesis, Tristin W. Cory

Graduate Theses/Dissertations

Spoken communication, for many, is an essential part of everyday life. Some individuals can lose or not be born with the ability to speak. To function on a day-to-day basis, these individuals find other ways of communication. Adaptive speech synthesis is one of those ways. It recreates a user’s previous voice or creates a voice that blends with their regional dialect. Current adaptive speech synthesis techniques that achieve human-like speech require thirty minutes, to a few hours of high-quality audio recordings of a target speaker. This amount of recorded audio is not commonly possessed by people in need of a …

Multimodal Adversarial Learning, Uche Osahor

Graduate Theses, Dissertations, and Problem Reports (ETD)

Deep Convolutional Neural Networks (DCNN) have proven to be an exceptional tool for object recognition, generative modelling, and multi-modal learning in various computer vision applications. However, recent findings have shown that such state-of-the-art models can be easily deceived by inserting slight imperceptible perturbations to key pixels in the input. A good target detection systems can accurately identify targets by localizing their coordinates on the input image of interest. This is ideally achieved by labeling each pixel in an image as a background or a potential target pixel. However, prior research still confirms that such state of the art targets models …

Jitim Front Cover Vol 31 1 2022

Journal of International Technology and Information Management

Table of Content JITIM Vol 31. issue 1, 2022

Incentive Analysis Of Blockchain Technology, Rahul Reddy Annareddy

Graduate Theses, Dissertations, and Problem Reports (ETD)

Blockchain technology was invented in the Bitcoin whitepaper released in 2008. Since then, several decentralized cryptocurrencies and applications have become mainstream. There has been an immense amount of engineering effort put into developing blockchain networks. Relatively few projects backed by blockchain technology have succeeded and maintained a large community of developers, users, and customers, while many popular projects with billions of dollars in funding and market capitalizations have turned out to be complete scams.

This thesis discusses the technological innovations introduced in the Bitcoin whitepaper and the following work of the last fifteen years that has enabled blockchain technology. A …

Effect Of Connection State & Transport/Application Protocol On The Machine Learning Outlier Detection Of Network Intrusions, George Yuchi, Torrey J. Wagner, Paul Auclair, Brent T. Langhals

Faculty Publications

The majority of cyber infiltration & exfiltration intrusions leave a network footprint, and due to the multi-faceted nature of detecting network intrusions, it is often difficult to detect. In this work a Zeek-processed PCAP dataset containing the metadata of 36,667 network packets was modeled with several machine learning algorithms to classify normal vs. anomalous network activity. Principal component analysis with a 10% contamination factor was used to identify anomalous behavior. Models were created using recursive feature elimination on logistic regression and XGBClassifier algorithms, and also using Bayesian and bandit optimization of neural network hyperparameters. These models were trained on a …

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 …

Lapindo Embankment Security Monitoring System Based On Iot, Shazana Dhiya Ayuni, Syamsudduha Syahrorini, Jamaaluddin Jamaaluddin

Elinvo (Electronics, Informatics, and Vocational Education)

Since 2006 Lapindo mudflow caused by natural gas drilling in Sidoarjo. Nowdays the mudflow still can't be stopped, and to prevent it from resident's houses, embankments were built. Eventough the embankments and guardrails has been built but sometimes the mud flowing into resident's houses while its raining or the embankments were subsidence or reep. Severity, the distance between the embankment and the residents' houses is about 500 m. So far, the handling action while embankments ware subsidence is residents report the accidents to related parties, namely PPLS. But the response is too late and take a long time to occur …

The Automatic Monitoring System For Wpp, Spp, And Pln Based On The Internet Of Things (Iot) Using Sonoff Pow R2, Yosi Apriani, Muhammad Rama Bagaskara, Ian Mochamad Sofian, Wiwin A. Oktaviani, Muhammad Hurairoh

Elinvo (Electronics, Informatics, and Vocational Education)

The usefulness of monitoring systems in the electric power system supports the importance of people's work today. One of which is the monitoring system at the generator. The monitoring system for Wind Power Plant (WPP), Solar Power Plant (SPP), and electricity from State Electricity Company (PLN) use IoT (Internet of Things) in the form of Sonoff Pow R2. With the monitoring system on this tool, the parameter values for WPP, SPP, and PLN can be seen and monitored online via a smartphone. The purpose of this research is to design a monitoring system for WPP, SPP, and PLN based on …

Crowd Detection System Using Blimp Drones As An Effort To Mitigate The Spread Of Covid-19 Based On Internet Of Things, Mashoedah Mashoedah, Oktaf Agni Dhewa, Zulhakim Seftiyana Roviyan, Dheni Leo, Silvia Larasatul Masyitoh

Elinvo (Electronics, Informatics, and Vocational Education)

The application of health protocols is a regulation that is applied to prevent the spread of Covid-19. Public awareness of the implementation of health protocols is still lacking. This study aims to determine the performance of the detection system using the Blimp Drone as an effort to mitigate the spread of Covid-19 based on the Internet of Things. The method used in system development consists of literature review, needs analysis, design, manufacture, and testing. This system uses the Blimp Drone as a vehicle to carry out flight missions. Raspberry pi camera as a component for distance detection in …

Power Monitoring And Passenger Classification On Logistics Elevator, Isa Hafidz, Aldhitiansyah Putra, Billy Montolalu, Dimas Adiputra, Rifky Dwi Putranto, Rafly Daffaldi, Dinda Karisma Ulfa

Elinvo (Electronics, Informatics, and Vocational Education)

The elevator has an important role in assisting transportation and logistics activities in a building. However, if the elevator is not used wisely, then the power consumption will be inefficient. A policy of elevator usage is necessary to ensure the effectiveness of elevator power consumption. Therefore, in this study, elevator power consumption monitoring is proposed. The power consumption behavior can be learned so a suitable policy can be made accordingly. Two elevators in Telkom Campus Surabaya are monitored to understand the daily electrical energy usage. Internet of Things (IoT) based real-time power monitoring system is used to monitor the electrical …

Comparative Analysis Of Rgb-Based Eye-Tracking For Large-Scale Human-Machine Applications, Brett Thaman, Trung Cao

Posters-at-the-Capitol

Gaze tracking has become an established technology that enables using an individual’s gaze as an input signal to support a variety of applications in the context of Human-Computer Interaction. Gaze tracking primarily relies on sensing devices such as infrared (IR) cameras. Nevertheless, in the recent years, several attempts have been realized at detecting gaze by acquiring and processing images acquired from standard RGB cameras. Nowadays, there are only a few publicly available open-source libraries and they have not been tested extensively. In this paper, we present the result of a comparative analysis that studied a commercial eye-tracking device using IR …

Improving Noise Immunity And Efficiency Using High-Precision Iterative Codes, Sherzod Shukhratovich Atadjanov, Aziza Ahmadjanovna Tursunova

Bulletin of TUIT: Management and Communication Technologies

The article discusses the issues of ensuring noise immunity in digital broadcasting systems, shows the importance of the transition to the optimal code and the need to use it in the field of noiseless coding in various areas of telecommunication transmission and reception of digital signals. The previous algorithms and error-correcting coding methods based on the Gray code, which are used in multi-level digital broadcast modulation schemes to minimize the intensity of bit errors, are highlighted. A model of error-correcting coding by the Gray method and methods for estimating the probability of error for the Gray code are presented. Based …

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 …

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 …

Deep Learning Based Speech Enhancement And Its Application To Speech Recognition, Ju Lin

All Dissertations

Speech enhancement is the task that aims to improve the quality and the intelligibility of a speech signal that is degraded by ambient noise and room reverberation. Speech enhancement algorithms are used extensively in many audio- and communication systems, including mobile handsets, speech recognition, speaker verification systems and hearing aids. Recently, deep learning has achieved great success in many applications, such as computer vision, nature language processing and speech recognition. Speech enhancement methods have been introduced that use deep-learning techniques, as these techniques are capable of learning complex hierarchical functions using large-scale training data. This dissertation investigates the deep learning …

Wi-Fi Sensing: Device-Free In-Zone Object Movement Detection, Nicholas P. Schnorr

Master's Theses

Wi-Fi Sensing is becoming a prominent field with a wide range of potential applications. Using existing hardware on a wireless network such as access points, cell phones, and smart home devices, important information can be inferred about the current physical environment. Through the analysis of Channel State Information collected in the Neighborhood Discovery Protocol process, the wireless network can detect disturbances in Wi-Fi signals when the physical environment changes. This results in a system that can sense motion within the Wi-Fi network, allowing for movement detection without any wearable devices.

The goal of this thesis is to answer whether Wi-Fi …

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, …

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.

Machine Learning For Unmanned Aerial System (Uas) Networking, Jian Wang

Doctoral Dissertations and Master's Theses

Fueled by the advancement of 5G new radio (5G NR), rapid development has occurred in many fields. Compared with the conventional approaches, beamforming and network slicing enable 5G NR to have ten times decrease in latency, connection density, and experienced throughput than 4G long term evolution (4G LTE). These advantages pave the way for the evolution of Cyber-physical Systems (CPS) on a large scale. The reduction of consumption, the advancement of control engineering, and the simplification of Unmanned Aircraft System (UAS) enable the UAS networking deployment on a large scale to become feasible. The UAS networking can finish multiple complex …