Other Electrical and Computer Engineering Commons^™

Deep Learning Approaches For Ctenophore Identification And Tracking, Anagha Bharadwaj

Theses

Ctenophores are translucent marine organisms with nearly invisible tentacles and pose significant challenges due to their transparent morphology and ambiguous structural features. This research addresses the classification and tracking of these organisms and evaluates the performance of current computer vision models under sparse-data environments.

A dataset from the NJIT Life History Lab consisting of microscopic laboratory videos and photographs of different growth stages is used to train and assess a number of convolutional neural network designs, including VGG16, ResNet, BioCLIP2, YOLO, and DeepLabCut. Additionally, a web-based interface is developed to evaluate expert-labeled ground truth with the model's performance.

The findings …

A Parametric Numerical Analysis Investigation To Optimize The Performance Of The Ranque-Hilsch Vortex Tube, Muneer Ahmad Sungur

Theses

A vortex tube is a device that separates compressed air into two streams: one with a higher temperature (hot stream) and the other with a lower temperature (cold stream). It is a popular cooling option because it is small, safe, and affordable. The main objective of this thesis is to examine the energy separation performance of RHVT by varying the internal tapering angles of convergent angles (2°, 1.75°, 1.5°, 1.25°, 1°, 0.75°, and 0.5°), straight angles (0°), and divergent angles (0.5°, 1°, 2°, 4°, and 6°), While the cold mass fraction is constant (0.317). Length-to-diameter ratio (Lt/Dt), inlet pressure, and …

The Design Of A Point Of Care Fet Biosensor To Detect And Screen Covid-19, Nisreen Amer Mohammad Alnaji

Theses

This work proposes and demonstrates a biosensor with reduced Graphene Oxide (rGO) based Field Effect Transistor (FET) for rapid and selective detection of Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2). The main objective of this thesis is to detect the SARS-CoV-2 spike protein antigen on spot selectively and rapidly. The rGO channel is coated with the spike protein antibodies to achieve selectivity. Moreover, the biosensing performance and specificity are governed by decorating the sensor’s channel with Metal Nanoparticles (MNPs) such as, copper, and silver. The designed sensor successfully detects the SARS-CoV-2 spike protein and shows singular electrical behavior for detection. …

Robust Detection Of Coronary Heart Disease Using Machine Learning Algorithms, Anas Haitham Domyati

Theses

Predicting whether or not someone will get heart or cardiac disease is now one of the most difficult jobs in the area of medicine. Heart disease is responsible for the deaths of about one person per minute in the contemporary age. Processing the vast amounts of data that are generated in the field of healthcare is an important application for data science. Because predicting cardiac disease is a difficult undertaking, there is a pressing need to automate the prediction process to minimize the dangers that are connected with it and provide the patient with timely warning. The chapter one in …

Predicting Energy And Water Consumption On Dairy Farms Through Statistical Analysis And Machine-Learning Methods, Philip Shine

Theses

With the abolishment of milking quotas across all European Union member states in April 2015, dairy farmers must adjust their farming practises to minimise milk production costs to adequately prepare for potential periods of reduced revenue. Milk production is an intense energy and water consuming process. Coupled with challenging European greenhouse gas reduction targets and legislation regarding the prevention of groundwater pollution and deterioration, increasing the production of milk in Ireland must be met with the sustainable consumption of on-farm energy and direct water resources, to ensure the future monetary and environmental sustainability of Ireland’s dairy industry. Thus, this body …

Comprehensive Mapping And Benchmarking Of Esaki Diode Performance, David John Pawlik

Theses

The tunneling-FET (TFET) has been identified as a prospective MOSFET replacement technology with the potential to extend geometric and electrostatic scaling of digital integrated circuits. However, experimental demonstrations of the TFET have yet to reliably achieve drive currents necessary to power large scale integrated circuits. Consequentially, much effort has gone into optimizing the band-to-band tunneling (BTBT) efficiency of the TFET. In this work, the Esaki tunnel diode (ETD) is used as a short loop element to map and optimize BTBT performance for a large design space. The experimental results and tools developed for this work may be used to (1) …