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Articles 1 - 17 of 17
Full-Text Articles in Physical Sciences and Mathematics
Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu
Data-Driven Deep Learning-Based Analysis On Thz Imaging, Haoyan Liu
Graduate Theses and Dissertations
Breast cancer affects about 12.5% of women population in the United States. Surgical operations are often needed post diagnosis. Breast conserving surgery can help remove malignant tumors while maximizing the remaining healthy tissues. Due to lacking effective real-time tumor analysis tools and a unified operation standard, re-excision rate could be higher than 30% among breast conserving surgery patients. This results in significant physical, physiological, and financial burdens to those patients. This work designs deep learning-based segmentation algorithms that detect tissue type in excised tissues using pulsed THz technology. This work evaluates the algorithms for tissue type classification task among freshly …
Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown
Divide-And-Conquer Distributed Learning: Privacy-Preserving Offloading Of Neural Network Computations, Lewis C.L. Brown
Graduate Theses and Dissertations
Machine learning has become a highly utilized technology to perform decision making on high dimensional data. As dataset sizes have become increasingly large so too have the neural networks to learn the complex patterns hidden within. This expansion has continued to the degree that it may be infeasible to train a model from a singular device due to computational or memory limitations of underlying hardware. Purpose built computing clusters for training large models are commonplace while access to networks of heterogeneous devices is still typically more accessible. In addition, with the rise of 5G networks, computation at the edge becoming …
Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot
Design And Comparison Of Asynchronous Fft Implementations, Julie Bigot
Graduate Theses and Dissertations
Fast Fourier Transform (FFT) is a widely used digital signal processing technology in a large variety of applications. For battery-powered embedded systems incorporating FFT, its physical implementation is constrained by strict power consumption, especially during idle periods. Compared to the prevailing clocked synchronous counterpart, quasi-delay insensitive asynchronous circuits offer a series of advantages including flexible timing requirement and lower leakage power, making them ideal choices for these systems. In this thesis work, various FFT configurations were implemented in the low-power Multi-Threshold NULL Convention Logic (MTNCL) paradigm. Analysis illustrates the area and power consumption trends along the changing of the number …
Multivariate Fairness For Paper Selection, Reem Alsaffar
Multivariate Fairness For Paper Selection, Reem Alsaffar
Graduate Theses and Dissertations
Peer review is the process by which publishers select the best publications for inclusion in a journal or a conference. Bias in the peer review process can impact which papers are selected for inclusion in conferences and journals. Although often implicit, race, gender and other demographics can prevent members of underrepresented groups from presenting at major conferences. To try to avoid bias, many conferences use a double-blind review process to increase fairness during reviewing. However, recent studies argue that the bias has not been removed completely. Our research focuses on developing fair algorithms that correct for these biases and select …
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Electrical Modeling For Dynamic Performance Prediction And Optimization Of Mcpms Layout, Quang Minh Le
Graduate Theses and Dissertations
In recent years, the fast development of Multichip Power Modules (MCPM) packaging and Wide Bandgap (WBG) technology has enabled higher voltage and current ratings, better thermal performance, lower parasitic parameters, and higher mechanical reliability. However, the design of the MCPM layout is a multidisciplinary problem leading to many time-consuming analyses and tedious design processes. Because of these challenges, the design automation tool for MCPM layout has become an emerging research area and gained much attention from the power electronics community. The two critical objectives of a design automation tool for MCPM layout are fast and accurate models for design insights …
Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata
Movie Reviews Sentiment Analysis Using Bert, Gibson Nkhata
Graduate Theses and Dissertations
Sentiment analysis (SA) or opinion mining is analysis of emotions and opinions from texts. It is one of the active research areas in Natural Language Processing (NLP). Various approaches have been deployed in the literature to address the problem. These techniques devise complex and sophisticated frameworks in order to attain optimal accuracy with their focus on polarity classification or binary classification. In this paper, we aim to fine-tune BERT in a simple but robust approach for movie reviews sentiment analysis to provide better accuracy than state-of-the-art (SOTA) methods. We start by conducting sentiment classification for every review, followed by computing …
Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman
Data-Driven Research On Engineering Design Thinking And Behaviors In Computer-Aided Systems Design: Analysis, Modeling, And Prediction, Molla Hafizur Rahman
Graduate Theses and Dissertations
Research on design thinking and design decision-making is vital for discovering and utilizing beneficial design patterns, strategies, and heuristics of human designers in solving engineering design problems. It is also essential for the development of new algorithms embedded with human intelligence and can facilitate human-computer interactions. However, modeling design thinking is challenging because it takes place in the designer’s mind, which is intricate, implicit, and tacit. For an in-depth understanding of design thinking, fine-grained design behavioral data are important because they are the critical link in studying the relationship between design thinking, design decisions, design actions, and design performance. Therefore, …
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Scheduling, Complexity, And Solution Methods For Space Robot On-Orbit Servicing, Susan E. Sorenson
Graduate Theses and Dissertations
This research proposes problems, models, and solutions for the scheduling of space robot on-orbit servicing. We present the Multi-Orbit Routing and Scheduling of Refuellable On-Orbit Servicing Space Robots problem which considers on-orbit servicing across multiple orbits with moving tasks and moving refuelling depots. We formulate a mixed integer linear program model to optimize the routing and scheduling of robot servicers to accomplish on-orbit servicing tasks. We develop and demonstrate flexible algorithms for the creation of the model parameters and associated data sets. Our first algorithm creates the network arcs using orbital mechanics. We have also created a novel way to …
The Effects Of Side-Channel Attacks On Post-Quantum Cryptography: Influencing Frodokem Key Generation Using The Rowhammer Exploit, Michael Jacob Fahr
The Effects Of Side-Channel Attacks On Post-Quantum Cryptography: Influencing Frodokem Key Generation Using The Rowhammer Exploit, Michael Jacob Fahr
Graduate Theses and Dissertations
Modern cryptographic algorithms such as AES and RSA are effectively used for securing data transmission. However, advancements in quantum computing pose a threat to modern cryptography algorithms due to the potential of solving hard mathematical problems faster than conventional computers. Thus, to prepare for quantum computing, NIST has started a competition to standardize quantum-resistant public-key cryptography algorithms. These algorithms are evaluated for strong theoretical security and run-time performance. NIST is in the third round of the competition, and the focus has shifted to analyzing the vulnerabilities to side-channel attacks. One algorithm that has gained notice is the Round 3 alternate …
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Constraint-Aware, Scalable, And Efficient Algorithms For Multi-Chip Power Module Layout Optimization, Imam Al Razi
Graduate Theses and Dissertations
Moving towards an electrified world requires ultra high-density power converters. Electric vehicles, electrified aerospace, data centers, etc. are just a few fields among wide application areas of power electronic systems, where high-density power converters are essential. As a critical part of these power converters, power semiconductor modules and their layout optimization has been identified as a crucial step in achieving the maximum performance and density for wide bandgap technologies (i.e., GaN and SiC). New packaging technologies are also introduced to produce reliable and efficient multichip power module (MCPM) designs to push the current limits. The complexity of the emerging MCPM …
Effective Knowledge Graph Aggregation For Malware-Related Cybersecurity Text, Phillip Ryan Boudreau
Effective Knowledge Graph Aggregation For Malware-Related Cybersecurity Text, Phillip Ryan Boudreau
Graduate Theses and Dissertations
With the rate at which malware spreads in the modern age, it is extremely important that cyber security analysts are able to extract relevant information pertaining to new and active threats in a timely and effective manner. Having to manually read through articles and blog posts on the internet is time consuming and usually involves sifting through much repeated information. Knowledge graphs, a structured representation of relationship information, are an effective way to visually condense information presented in large amounts of unstructured text for human readers. Thusly, they are useful for sifting through the abundance of cyber security information that …
Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey
Deep Learning Applications In Industrial And Systems Engineering, Winthrop Harvey
Graduate Theses and Dissertations
Deep learning - the use of large neural networks to perform machine learning - has transformed the world. As the capabilities of deep models continue to grow, deep learning is becoming an increasingly valuable and practical tool for industrial engineering. With its wide applicability, deep learning can be turned to many industrial engineering tasks, including optimization, heuristic search, and functional approximation. In this dissertation, the major concepts and paradigms of deep learning are reviewed, and three industrial engineering projects applying these methods are described. The first applies a deep convolutional network to the task of absolute aerial geolocalization - the …
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Supervised Representation Learning For Improving Prediction Performance In Medical Decision Support Applications, Phawis Thammasorn
Graduate Theses and Dissertations
Machine learning approaches for prediction play an integral role in modern-day decision supports system. An integral part of the process is extracting interest variables or features to describe the input data. Then, the variables are utilized for training machine-learning algorithms to map from the variables to the target output. After the training, the model is validated with either validation or testing data before making predictions with a new dataset. Despite the straightforward workflow, the process relies heavily on good feature representation of data. Engineering suitable representation eases the subsequent actions and copes with many practical issues that potentially prevent the …
Robust And Fair Machine Learning Under Distribution Shift, Wei Du
Robust And Fair Machine Learning Under Distribution Shift, Wei Du
Graduate Theses and Dissertations
Machine learning algorithms have been widely used in real world applications. The development of these techniques has brought huge benefits for many AI-related tasks, such as natural language processing, image classification, video analysis, and so forth. In traditional machine learning algorithms, we usually assume that the training data and test data are independently and identically distributed (iid), indicating that the model learned from the training data can be well applied to the test data with good prediction performance. However, this assumption is quite restrictive because the distribution shift can exist from the training data to the test data in many …
A Novel Data Lineage Model For Critical Infrastructure And A Solution To A Special Case Of The Temporal Graph Reachability Problem, Ian Moncur
Graduate Theses and Dissertations
Rapid and accurate damage assessment is crucial to minimize downtime in critical infrastructure. Dependency on modern technology requires fast and consistent techniques to prevent damage from spreading while also minimizing the impact of damage on system users. One technique to assist in assessment is data lineage, which involves tracing a history of dependencies for data items. The goal of this thesis is to present one novel model and an algorithm that uses data lineage with the goal of being fast and accurate. In function this model operates as a directed graph, with the vertices being data items and edges representing …
Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan
Optimized Damage Assessment And Recovery Through Data Categorization In Critical Infrastructure System., Shruthi Ramakrishnan
Graduate Theses and Dissertations
Critical infrastructures (CI) play a vital role in majority of the fields and sectors worldwide. It contributes a lot towards the economy of nations and towards the wellbeing of the society. They are highly coupled, interconnected and their interdependencies make them more complex systems. Thus, when a damage occurs in a CI system, its complex interdependencies make it get subjected to cascading effects which propagates faster from one infrastructure to another resulting in wide service degradations which in turn causes economic and societal effects. The propagation of cascading effects of disruptive events could be handled efficiently if the assessment and …
Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen
Framework Of Hardware Trojan Detection Leveraging Structural Checking Tool, Rafael Dacanay Del Carmen
Graduate Theses and Dissertations
Since there is a significant demand for obtaining third-party soft Intellectual Property (IP) by first-party integrated circuit (IC) vendors, it is becoming easier for adversaries to insert malicious logic known as hardware Trojans into designs. Due to this, vendors need to find ways to screen the third-party IPs for possible security threats and then mitigate them. The development of the Structural Checking (SC) tool provides a solution to this issue. This tool analyzes the structure of an unknown soft IP design and creates a network of all the signals within the design and how they are connected to each other. …