Computer Engineering Commons^™

Towards Improving The Security Of The Software Supply Chain, Hammad Afzali

Dissertations

A software supply chain comprises a series of steps performed to develop and distribute a software product. History has shown that each of these steps is vulnerable to attacks that can have serious repercussions and can affect many users at once. To address the attacks against the software supply chain, end users must be provided with verifiable guarantees about the individual steps of the chain and with assurances that the steps are securely chained together.

In this dissertation, the security of several individual steps in the software supply chain is enhanced. The first step of the chain, managing the source …

Improving Multi-Threaded Qos In Clouds, Weiwei Jia

Dissertations

Multi-threading and resource sharing are pervasive and critical in clouds and data-centers. In order to ease management, save energy and improve resource utilization, multi-threaded applications from different tenants are often encapsulated in virtual machines (VMs) and consolidated on to the same servers. Unfortunately, despite much effort, it is still extremely challenging to maintain high quality of service (QoS) for multi-threaded applications of different tenants in clouds, and these applications often suffer severe performance degradation, poor scalability, unfair resource allocation, and so on.

The dissertation identifies the causes of the QoS problems and improves the QoS of multi-threaded execution with three …

Convolutional Neural Networks For Deflate Data Encoding Classification Of High Entropy File Fragments, Nehal Ameen

LSU New Orleans Theses and Dissertations

Data reconstruction is significantly improved in terms of speed and accuracy by reliable data encoding fragment classification. To date, work on this problem has been successful with file structures of low entropy that contain sparse data, such as large tables or logs. Classifying compressed, encrypted, and random data that exhibit high entropy is an inherently difficult problem that requires more advanced classification approaches. We explore the ability of convolutional neural networks and word embeddings to classify deflate data encoding of high entropy file fragments after establishing ground truth using controlled datasets. Our model is designed to either successfully classify file …

Characterization Of Time-Variant And Time-Invariant Assessment Of Suicidality On Reddit Using C-Ssrs, Manas Gaur, Vamsi Aribandi, Amanuel Alambo, Ugur Kursuncu, Krishnaprasad Thirunarayan, Jonathan Beich, Jyotishman Pathak, Amit Sheth

Publications

Suicide is the 10th leading cause of death in the U.S (1999-2019). However, predicting when someone will attempt suicide has been nearly impossible. In the modern world, many individuals suffering from mental illness seek emotional support and advice on well-known and easily-accessible social media platforms such as Reddit. While prior artificial intelligence research has demonstrated the ability to extract valuable information from social media on suicidal thoughts and behaviors, these efforts have not considered both severity and temporality of risk. The insights made possible by access to such data have enormous clinical potential - most dramatically envisioned as a trigger …

Stock Markets Performance During A Pandemic: How Contagious Is Covid-19?, Yara Abushahba

Theses and Dissertations

Background and Motivation: The coronavirus (“COVID-19”) pandemic, the subsequent policies and lockdowns have unarguably led to an unprecedented fluid circumstance worldwide. The panic and fluctuations in the stock markets were unparalleled. It is inarguable that real-time availability of news and social media platforms like Twitter played a vital role in driving the investors’ sentiment during such global shock.

Purpose:The purpose of this thesis is to study how the investor sentiment in relation to COVID-19 pandemic influenced stock markets globally and how stock markets globally are integrated and contagious. We analyze COVID-19 sentiment through the Twitter posts and investigate its …

Bibliometric Analysis On Dynamic Target Tracking By Mobile Robot, Gaurav Atha Mr., Siddhant Chaturvedi Mr., Atishraj Desai Mr., Dhrumil Desai Mr., Shripad V. Deshpande Mr.

Library Philosophy and Practice (e-journal)

The survey and bibliometric research on dynamic target tracking by a mobile robot are discussed in this paper. The primary goal of this bibliometric analysis is to comprehend and analyze the scope of the literature in the field of mobile robots for obstacle avoidance, path planning and target tracking using Robot Operating System (ROS). The ROS contains various tools for data analysis, incorporates multiple robots and their sensors, and supports devices interaction for target seeking and localization in mobile robots. This detailed review was performed on various research publications about the mapping of the unknown field/environment by the ROS based …

Arm-Hand Systems As Hybrid Parallel-Serial Systems: A Novel Inverse Kinematics Solution, Shuwei Qiu, Mehrdad Kermani Ph.D., P.Eng.

Electrical and Computer Engineering Publications

No abstract provided.

A Probabilistic Broadcasting Protocols In Mobile Ad Hoc Networks: A Bibliometric Survey, Sumit Kumar, Ayushi Kamboj

Library Philosophy and Practice (e-journal)

Broadcasting in Mobile ad hoc network is very crucial process and if not taken care led to Broadcast storm problem. Several Broadcasting techniques are proposed in the literature, but probabilistic broadcasting is the one the major technique which can really avoid the broadcasting storm problem. The protocols employing probabilistic broadcasting is surveyed in this bibliometric paper. The bibliometric survey aims to throw light on several types of protocols employed in Mobile ad hoc Network. The primary aim of this paper is to assess the amount of work done in the field of Probabilistic Broadcasting in Mobile ad hoc Network, as …

A Bibliometric Analysis Of Plant Disease Classification With Artificial Intelligence Using Convolutional Neural Network, Sumit Kumar, Rutuja Rajendra Patil, Vasu Kumawat, Yashovardhan Rai, Navaneeth Krishnan, Shubham Kumar Singh

Library Philosophy and Practice (e-journal)

In 2021 and the modern future which everyone is going to be a part of, Artificial intelligence is going to be the biggest part of our livelihood. In the future there is going to be a huge expansion of population especially at the rate right now which we are moving but the biggest problem which everyone should be concerned about is the food supply as many of the nations would not be able to feed and make survive their population as even now, there is scarcity of it. Currently in the world the people revolving around the artificial intelligence are …

Body And Tail Coordination In The Bluespot Salamander (Ambystoma Laterale) During Limb Regeneration, Cassandra M. Donatelli, Keegan Lutek, Keshav Gupta, Emily M. Standen

Engineering Faculty Articles and Research

Animals are incredibly good at adapting to changes in their environment, a trait envied by most roboticists. Many animals use different gaits to seamlessly transition between land and water and move through non-uniform terrains. In addition to adjusting to changes in their environment, animals can adjust their locomotion to deal with missing or regenerating limbs. Salamanders are an amphibious group of animals that can regenerate limbs, tails, and even parts of the spinal cord in some species. After the loss of a limb, the salamander successfully adjusts to constantly changing morphology as it regenerates the missing part. This quality is …

Bibliometric Analysis On Optimal Path Planning For Robots, Varad Sandeep Nerlekar, Tathaagat Nihar Mamtura, Nishant Singh, Suket Anand, Sushma Parihar

Library Philosophy and Practice (e-journal)

Traversing from a given point to another while avoiding collision with obstacles is one of the key goals of path planning for robots [1]. Doing so in the most optimal way - the minimum total distance traveled by the robot is the objective of our study [2,3]. To do so, the algorithms implemented on the robots need to constantly map the environment or workspace in real time and subsequently create paths for the traversal in the environment without colliding with objects or obstacles [4,5]. Throughout the years, many researchers have conducted their own studies, researches and have proposed approaches for …

A Bibliometric Analysis Of Face Presentation Attacks Based On Domain Adaptation, Smita C. Khairnar, Shilpa Shailesh Gite Dr., Sudeep D. Thepade Dr.

Library Philosophy and Practice (e-journal)

Background: This research aims to look into the work that has been done on Face Presentation attacks and detection with domain adaptation techniques from 2011 to 2021 utilizing bibliography methods.

Approaches: Diverse research articles on Face Presentation Attacks were retrieved using the two most popular databases Web of Science & Scopus. Research articles consider between 2011-2021. Some research results, such as documents by year, documents by source, documents by funding agencies, countries, etc are obtained using Web of Science and Scopus Analyzers. The analysis is performed using Vos Viewer version 1.6.16 and various parameters such as keywords, co-authorship, co-occurrences, citation …

Inference And Learning In Spiking Neural Networks For Neuromorphic Systems, Amar Shrestha

Dissertations - ALL

Neuromorphic computing is a computing field that takes inspiration from the biological and physical characteristics of the neocortex system to motivate a new paradigm of highly parallel and distributed computing to take on the demands of the ever-increasing scale and computational complexity of machine intelligence esp. in energy-limited systems such as Edge devices, Internet-of-Things (IOT), and cyber physical systems (CPS). Spiking neural network (SNN) is often studied together with neuromorphic computing as the underlying computational model . Similar to the biological neural system, SNN is an inherently dynamic and stateful network. The state and output of SNN do not only …

Neuromorphic Systems For Pattern Recognition And Uav Trajectory Planning, Yilan Li

Dissertations - ALL

Detection and control are two essential components in an intelligent system. This thesis investigates novel techniques in both areas with a focus on the applications of handwritten text recognition and UAV flight control. Recognizing handwritten texts is a challenging task due to many different writing styles and lack of clear boundary between adjacent characters. The difficulty is greatly increased if the detection algorithms is solely based on pattern matching without information of dynamics of handwriting trajectories. Motivated by the aforementioned challenges, this thesis first investigates the pattern recognition problem. We use offline handwritten texts recognition as a case study to …

Control Traffic And Queueing Latencies: Implicit Overheads In Bandwidth Sliced Software Defined Networks, Jesse Chen

Computer Science and Engineering Master's Theses

The southbound control protocols used in Software Defined Networks (SDNs) allow for centralized control and management of the data plane. However, these protocols introduce additional traffic and delay between network controllers and switches. Despite the well understood capabilities of SDNs, current representations of control traffic overhead consist of approximations at best. In addition to high reactivity to incoming flows, the need for resource allocation and deterministic messaging delay necessitates a thorough understanding and modeling of the amount of control traffic and its effect on latency. Software switching facilitates the development of edge and fog computing networks by allowing the use …

Using An Integrative Machine Learning Approach To Study Microrna Regulation Networks In Pancreatic Cancer Progression, Roland Madadjim

School of Computing: Dissertations, Theses, and Student Research

With advances in genomic discovery tools, recent biomedical research has produced a massive amount of genomic data on post-transcriptional regulations related to various transcript factors, microRNAs, lncRNAs, epigenetic modifications, and genetic variations. In this direction, the field of gene regulation network inference is created and aims to understand the interactome regulations between these molecules (e.g., gene-gene, miRNA-gene) that take place to build models able to capture behavioral changes in biological systems. A question of interest arises in integrating such molecules to build a network while treating each specie in its uniqueness. Given the dynamic changes of interactome in chaotic systems …

Impact Assessment, Detection, And Mitigation Of False Data Attacks In Electrical Power Systems, Sagnik Basumallik

Dissertations - ALL

The global energy market has seen a massive increase in investment and capital flow in the last few decades. This has completely transformed the way power grids operate - legacy systems are now being replaced by advanced smart grid infrastructures that attest to better connectivity and increased reliability. One popular example is the extensive deployment of phasor measurement units, which is referred to PMUs, that constantly provide time-synchronized phasor measurements at a high resolution compared to conventional meters. This enables system operators to monitor in real-time the vast electrical network spanning thousands of miles. However, a targeted cyber attack on …

Neuromorphic Systems For Pattern Recognition And Uav Trajectory Planning, Yilan Li

Dissertations - ALL

Detection and control are two essential components in an intelligent system. This thesis investigates novel techniques in both areas with a focus on the applications of handwritten text recognition and UAV flight control. Recognizing handwritten texts is a challenging task due to many different writing styles and lack of clear boundary between adjacent characters. The difficulty is greatly increased if the detection algorithms is solely based on pattern matching without information of dynamics of handwriting trajectories. Motivated by the aforementioned challenges, this thesis first investigates the pattern recognition problem. We use offline handwritten texts recognition as a case study to …

Inference And Learning In Spiking Neural Networks For Neuromorphic Systems, Amar Shrestha

Dissertations - ALL

Neuromorphic computing is a computing field that takes inspiration from the biological and physical characteristics of the neocortex system to motivate a new paradigm of highly parallel and distributed computing to take on the demands of the ever-increasing scale and computational complexity of machine intelligence esp. in energy-limited systems such as Edge devices, Internet-of-Things (IOT), and cyber physical systems (CPS). Spiking neural network (SNN) is often studied together with neuromorphic computing as the underlying computational model . Similar to the biological neural system, SNN is an inherently dynamic and stateful network. The state and output of SNN do not only …

Person Re-Identification And An Adversarial Attack And Defense For Person Re-Identification Networks, Yu Zheng

Dissertations - ALL

Person re-identification (ReID) is the task of retrieving the same person, across different camera views or on the same camera view captured at a different time, given a query person of interest. There has been great interest and significant progress in person ReID, which is important for security and wide-area surveillance applications as well as human computer interaction systems. In order to continuously track targets across multiple cameras with disjoint views, it is essential to re-identify the same target across different cameras. This is a challenging task due to several reasons including changes in illumination and target appearance, and variations …

Design And Implementation Of A Microservices Web-Based Architecture For Code Deployment And Testing, Soin Abdoul Kassif Traore

Symposium of Student Scholars

Design and Implementation of a Microservices Web-based Architecture for CodeDeployment and Testing

Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing of IoT technologies. Since the IoT industry has an exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job …

An Investigation On Non-Invasive Brain-Computer Interfaces: Emotiv Epoc+ Neuroheadset And Its Effectiveness, Md Jobair Hossain Faruk

Symposium of Student Scholars

Neurotechnology describes as one of the focal points of today’s research around the domain of Brain-Computer Interfaces (BCI). The primary attempts of BCI research are to decoding human speech from brain signals and controlling neuro-psychological patterns that would benefit people suffering from neurological disorders. In this study, we illustrate the progress of BCI research and present scores of unveiled contemporary approaches. First, we explore a decoding natural speech approach that is designed to decode human speech directly from the human brain onto a digital screen introduced by Facebook Reality Laband University of California San Francisco. Then, we study a recently …

Framework For Collecting Data From Iot Device, Md Saiful Islam

Symposium of Student Scholars

The Internet of Things (IoT) is the most significant and blooming technology in the 21st century. IoT has rapidly developed by covering hundreds of applications in the civil, health, military, and agriculture areas. IoT is based on the collection of sensor data through an embedded system, and this embedded system uploads the data on the internet. Devices and sensor technologies connected over a network can monitor and measure data in real-time. The main challenge is to collect data from IoT devices, transmit them to store in the Cloud, and later retrieve them at any time for visualization and data analysis. …

Data Analysis Methods For Health Monitoring Sensors, Shahriar Sobhan

Symposium of Student Scholars

Innovations in health monitoring systems are fundamental for the continuous improvement of remote healthcare. With the current presence of SARS-CoV-2, better known as COVID-19, in people’s daily lives, solutions for monitoring heart and especially respiration and pulmonary functions are more needed than ever. Besides, health monitoring systems are widely used for patients who need isolated care, unconscious patients who cannot get medical attention for themselves. As it is well-known, monitoring systems rely on sensor technologies. Currently, there are multiple research studies for remote monitoring using different types of sensors. In this effort, we survey the current approaches that utilize the …

Do I Have Your Attention ? Predicting Users' Engagement During Interviews With Biofeedback, Voice, And Supervised Machine Learning, Thaide Huichapa

Symposium of Student Scholars

Studies show that the quality of the information collected during an elicitation interview, and consequently the quality of the software product that needs to be developed, highly depends on the interviewee's engagement. Because of social expectations, interviewees tend to hide if they are bored or not engaged. To overcome this problem and support the analyst during the interviews, this research uses biometric data and voice features, together with supervised machine learning algorithms, to predict the interviewee's engagement. We built our solution on an experiment consisted of interviewing 31 participants. We collected the data using an Empatica wristband and a default …

A Bibliometric Survey On The Use Of Long Short-Term Memory Networks For Multivariate Time Series Forecasting, Vidur Sood Mr., Manobhav Mehta Mr., Vedansh Mishra Mr., Akash Upadhyay Mr., Shilpa Hudnurkar, Shilpa Gite Dr., Neela Rayavarapu Dr.

Library Philosophy and Practice (e-journal)

In this paper, we aim to review and analyze the publications related to the utilization of Long Short-Term Memory (LSTM) networks for multivariate time series forecasting. The purpose of this bibliometric survey was to study how technology in the field of LSTM has evolved over the years. There were 242 research papers published, by over 50 researchers, over 6 years, on the topic of “Multivariate time series forecasting using LSTM”. The majority of these papers were published between the years 2018 and 2020. The Scopus database was utilized for analyzing recent trends in this area and to determine the …

Fatigue Monitoring Through Wearable Sensors For Construction Workers, Srikanth Sagar Bangaru

LSU Doctoral Dissertations

About 40% of the US construction workforce experiences high-level fatigue, which leads to poor judgment, increased risk of injuries, a decrease in productivity, and a lower quality of work. Excessive fatigue from working in unpleasant working conditions, long working hours, or heavy workloads can aggravate fatigue's adverse effects, leading to work-related musculoskeletal disorders (WMSDs) and productivity loss. Therefore, it is essential to monitor fatigue to reduce the adverse effects and preventing long-term health problems. However, since fatigue demonstrates itself in several complex processes, there is no single standard measurement method for fatigue detection. This research aims to develop a system …

Demo: Codec-Aware Video Delivery Over Sdns, Obinna Izima, Ruairí De Fréin, Ali Malik

Other resources

To guarantee quality of delivery for video streaming over software defined networks, efficient predictors and adaptive routing frameworks are required. We demonstrate an agent that predicts video quality of delivery metrics in a scalable way using a bespoke codec-aware learning model. We also demonstrate the integration of this agent with an adaptive framework for centrally controlled software-defined networks that re-configures network operational paths in response to the learning agent, ensuring that good quality of delivery of video is maintained during periods of congestion. The demo scenario highlights the feasibility, scalability and accuracy of the framework.

Bibliometric Survey On Effect Of Socio-Economic Factors On Spread Of Corona Virus (Covid-19), Seema Patil Prof., Aayushi Verma Ms, Isha Patil Ms, Ravneesh Singh Mr, Raghav Gaur Mr

Library Philosophy and Practice (e-journal)

The Novel Coronavirus disease has been rapidly spreading all around the globe, from the time when it was first reported in the Wuhan city of China. The primary focus of this bibliometric survey is to distinguish the documents which have hypothesized and expanded on the effects of various socio-economic factors when it comes to the spread of the Coronavirus.

This survey does the evaluation on the 480 documents found. The United Kingdom of the Great Britain and United States have contributed the largest number of publications in this field of research followed closely by India and Italy.

The survey includes …

Grandparent-Grandchild Virtual Communication Study, Tanya Keval

Undergraduate Honors Theses

The cross generational bond between a grandparent and grandchild is extremely important. The stories, traditions, and beliefs that grandparents share with their grandchildren have the ability to shape their grandchildren’s beliefs. For grandparents, the role of being a grandparent and creating shared memories with their grandchildren leaves a positive impact on their mental health. Although the elderly population prefers to connect with others in-person, including their grandchildren, this face-to-face connection is not always possible due to schedules, distance, or health. Many products have been designed for grandparents and grandchildren to try to fill this communication gap when they are apart. …