Computer Engineering Commons^™

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. …

Performance Analysis Of Whale Optimization Based Data Clustering, Ahamed Shafeeq B M, Zahid Ahmed Ansari, Shyam Karanth

Future Computing and Informatics Journal

Data clustering is the method of gathering of data points so that the more similar points will be in the same group. It is a key role in exploratory data mining and a popular technique used in many fields to analyze statistical data. Quality clusters are the key requirement of the cluster analysis result. There will be tradeoffs between the speed of the clustering algorithm and the quality of clusters it produces. Both the quality and speed criteria must be considered for the state-of-the-art clustering algorithm for applications. The Bio-inspired technique has ensured that the process is not trapped in …

Multilayer Perceptron With Auto Encoder Enabled Deep Learning Model For Recommender Systems, Subhashini Narayan

Future Computing and Informatics Journal

In this modern world of ever-increasing one-click purchases, movie bookings, music, health- care, fashion, the need for recommendations have increased the more. Google, Netflix, Spotify, Amazon and other tech giants use recommendations to customize and tailor their search engines to suit the user’s interests. Many of the existing systems are based on older algorithms which although have decent accuracies, require large training and testing datasets and with the emergence of deep learning, the accuracy of algorithms has further improved, and error rates have reduced due to the use of multiple layers. The need for large datasets has declined as well. …

Deep Feature Learning For Fog Episodes Prediction In Patients With Pd, Hadeer Elziaat, Nashwa El-Bendary, Ramdan Mowad

Future Computing and Informatics Journal

A common symptom of Parkinson's Disease is Freezing of Gait (FoG) that causes an interrupt of the forward progression of the patient’s feet while walking. Therefore, Freezing of Gait episodes is always engaged to the patient's falls. This paper proposes a model for Freezing of Gait episodes detection and prediction in patients with Parkinson's Disease. Predicting Freezing of Gait in this paper considers as a multi-class classification problem with 3 classes namely, FoG, pre-FoG, and walking episodes. In this paper, the extracted feature scheme applied for the detection and the prediction of FoG is Convolutional Neural Network (CNN) spectrogram time-frequency …

A Literature Review For Contributing Mining Approaches For Business Process Reengineering, Noha Ahmed Bayomy Nab, Ayman E. Khedr Aek, Laila A. Abd-Elmegid Laa, Amira M. Idrees Ami

Future Computing and Informatics Journal

Due to the changing dynamics of the business environment, organizations need to redesign or reengineer their business processes in order to provide services with the lowest cost and shortest response time while increasing quality. Thence, Business Process Re-engineering (BPR) provides a roadmap to achieve operational goals that leads to enhance flexibility and productivity, cost reduction, and quality of service/product. In this paper, we propose a literature review for the different proposed models for Business Process Reengineering. The models specify where the breakdowns occur in BPR implementation, justifies why such breakdowns occur, and propose techniques to prevent their occurrence again. The …