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Articles 91 - 120 of 666

Full-Text Articles in Computer Sciences

Graph Representation Learning For Heterogeneous Multimodal Biomedical Data, Nhat Chau Tran Dec 2022

Graph Representation Learning For Heterogeneous Multimodal Biomedical Data, Nhat Chau Tran

Computer Science and Engineering Dissertations - Archive

The emergence of high-throughput sequencing technology has generated a wealth of “multi-omics” data, capturing information about different types of biomolecules at multiple levels. Since large-scale genomics, transcriptomics, and proteomics data are becoming publicly available, integrated systems analysis utilizing these data sources has taken the front seat in deriving valuable insights for identifying cancer biomarkers or predicting interactions and functions for novel molecules such as LncRNAs. The graph representation learning paradigm can address these challenging tasks as among the most promising approaches to improve predictions over sparsely annotated molecular entities and to provide representation capacity and interpretability over heterogeneous and hierarchically …

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Understanding Human Actions: Cognitive Assessment And Action Segmentation Using Human Object Interaction, Saif Sayed Dec 2022

Understanding Human Actions: Cognitive Assessment And Action Segmentation Using Human Object Interaction, Saif Sayed

Computer Science and Engineering Dissertations - Archive

Automatic understanding of human behavior has several applications in medicine and surveillance. Analysing human actions can enable cognitive assessment of children by measuring their hyperactivity and response inhibition which can give physicians better understanding of their cognitive state. Automatic and non-invasive assessment for cognitive disorders will increase the affordability and reach for these detection methods and can prove life-changing in child’s development. Human activity can also be analysed in common settings such as cooking in kitchen and understanding the information of human object interaction can give priors on the underlying activity they are performing. In the first section, we focus …

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Semi Automatic Hand Pose Annotation Using A Single Depth Camera, Marnim Galib Aug 2022

Semi Automatic Hand Pose Annotation Using A Single Depth Camera, Marnim Galib

Computer Science and Engineering Dissertations - Archive

This thesis investigates the problem of 3D hand pose annotation using a single depth camera. While hand pose annotations are critically important for training deep neural networks, creating such reliable training data is challenging and manual labor intensive. Current datasets that rely on manual annotation on real images are limited in size due to the difficulty of annotating them. Although, large datasets have been generated using tracking based methods followed by manual refinement, these methods are prone to annotation errors due to tracking failure. Synthetic images have also been used to create large datasets but synthetic frames does not capture …

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Effective Sequence Models And Graph Neural Networks For Molecular Data Analysis, Chaochao Yan Aug 2022

Effective Sequence Models And Graph Neural Networks For Molecular Data Analysis, Chaochao Yan

Computer Science and Engineering Dissertations - Archive

Drug discovery is the process of discovering new candidate medications. New drugs are continually developed by pharmaceutical industries to address increasing medical needs. Drug discovery involves a series of processes including target identification and validation, hit identification, lead generation and optimization, and finally the identification of a candidate for further development. The development further includes optimization of chemical synthesis and its formulation, toxicological studies in animals, clinical trials, and eventually regulatory approval. Both of these processes are time-consuming and cost-expensive. Computer-aided drug discovery mainly relies on modern computers to model drug molecules, which can speed up the process of drug …

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A Real-Time Activity Recognition In A Congested Wireless Environment, Israel Oludayo Elujide Aug 2022

A Real-Time Activity Recognition In A Congested Wireless Environment, Israel Oludayo Elujide

Computer Science and Engineering Dissertations - Archive

ABSTRACT: This dissertation reports on how to achieve real-time activity recognition in a congested wireless environment. Recently, human activity recognition with WiFi has been the focus of many researchers due to the limitations of legacy approaches like video cameras and sensors. Users have concerns with privacy when it comes to video activity recognition. Likewise, activity recognition sensors can be expensive, obtrusive, and inconvenient to be worn for an extended period of time. The urgency for implementing contactless activity recognition has also been accelerated due to changes in society and social interaction because of the COVID-19 pandemic. Many public facilities like …

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Hand Analysis From Depth Images, Mohammad Rezaei Aug 2022

Hand Analysis From Depth Images, Mohammad Rezaei

Computer Science and Engineering Dissertations - Archive

Hand analysis using vision systems is necessary for interaction between people and digital devices and thus is crucial in many applications relating to computer vision and human computer interaction (HCI). The proposed dissertation will explore hand analysis from depth images along two lines: hand part segmentation and 3D hand pose estimation. First, we investigate hand part segmentation from depth images, which is formulated as a semantic segmentation task. We explore a method aimed at determining for every pixel what hand part it belongs to. This method attempts to perform this task without requiring the ground-truth segmentation labels for training. It …

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Towards High Performance Cancer Staging From Histology Images, Ashwin Raju Aug 2022

Towards High Performance Cancer Staging From Histology Images, Ashwin Raju

Computer Science and Engineering Dissertations - Archive

Digital Pathology (DP) has been recently used in replacement to traditional microscopy samples as it easy to navigate and can be analysed, processed and saved. With the invention of Digital pathology, there has been exponential increase of automated process to make the life of Doctors easier. One such automated process is Artificial Intelligence (AI) where the AI is used as an assistant to Humans and to make the analysis and guide the experts. With the advent of AI and in particular Deep Learning, research has been divided and focused to solve multiple problems in Digital Pathology. One such important application …

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Gan-Based Domain Translation For Hand Pose Estimation And Face Reconstruction, Farnaz Farahanipad Aug 2022

Gan-Based Domain Translation For Hand Pose Estimation And Face Reconstruction, Farnaz Farahanipad

Computer Science and Engineering Dissertations - Archive

Deep learning solutions for hand pose estimation are now very reliant on comprehensive datasets covering diverse camera perspectives, lighting conditions, shapes, and pose variations. Since, acquiring such datasets is a challenging task that may be infeasible for many novel applications, several studies aim to develop semi/self supervised learning methods, that learn to estimate hand pose from a few labeled/unlabeled data. Therefore, in this dissertation, we investigate new advances in semi/self supervised learning which will remove the bottleneck of obtaining time-consuming frameby- frame manual annotations through generative adversarial networks (GANs). To handle above mentioned challenges, this thesis makes the following contributions. …

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Deep Learning For Protein Property And Structure Prediction, Yuzhi Guo Aug 2022

Deep Learning For Protein Property And Structure Prediction, Yuzhi Guo

Computer Science and Engineering Dissertations - Archive

I present my work towards solving the fundamental, challenging, and valuable problem for protein property and structure prediction. Specifically, I focus on solving the problem from three critical aspects: (1) designing powerful deep learning networks for specific protein structure property prediction tasks; (2) proposing general methods that enhancing the protein sequence homologous feature, which is an important input feature of relevant tasks; (3) developing a self-supervised pre-training model for learning structure embeddings from protein tertiary structures. To evaluate the effectiveness of the developed methods, I apply several protein downstream tasks including protein secondary structure, solvent accessibility, backbone dihedral angles, protein …

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Towards Security Aware Crowdsourcing, Mingyan Xiao Aug 2022

Towards Security Aware Crowdsourcing, Mingyan Xiao

Computer Science and Engineering Dissertations - Archive

Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates addressing problems by outsourcing them to the crowd. The openness of crowdsourcing renders it vulnerable to misbehaving workers that impair data trustworthiness. They may attempt to submit calibrated data/parameters to manipulate crowdsourcing outcomes for higher beneficial gain. Those misbehaviors would infringe crowdsourcing's process and, overall, its usefulness. In this dissertation, I intend to secure the crowdsourcing platform from worker's untrustworthy data reporting. The main contributions are mainly threefold. First, we secure task allocation, an essential but vulnerable stage in crowdsourcing, from individual misreporting. To be specific, misbehaving workers may manipulate …

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Human Behavior Modeling In Long Videos: Drowsiness Detection And Action Segmentation, Reza Ghoddoosian May 2022

Human Behavior Modeling In Long Videos: Drowsiness Detection And Action Segmentation, Reza Ghoddoosian

Computer Science and Engineering Dissertations - Archive

"In this thesis we focus on two instances of human behavior modeling in long untrimmed videos: drowsiness detection, and action segmentation. In the first section, we focus on drowsiness detection. Specifically, we introduce a large and public real-life dataset and a baseline temporal model to classify drowsiness into three stages of alert, low vigilant, or drowsy. In the second section, we study action segmentation in instructional videos under weak supervision. In order to save time and cost, weakly supervised methods are trained based on only video-level action sequences as opposed to a fully supervised method which is trained using frame-level …

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Learning Topology Preserving Embeddings For Speeding Up Nearest Neighbor Retrieval, Mason Lary May 2022

Learning Topology Preserving Embeddings For Speeding Up Nearest Neighbor Retrieval, Mason Lary

Computer Science and Engineering Theses - Archive

Given a database of objects and a query object, it’s possible to gather a number of the closest neighbors to the query object. This operation is important to a number of diverse fields such as computer vision, content- based information retrieval, and chemistry. However, distance measures used to determine neighbors can cause queries to be computationally expensive, either because the distance measure is complex or because it is nonmetric and prevents efficient indexing methods. This work presents novel methods of triplet mining that enable neural networks using triplet loss to learn the manifold that data resides in. These neural networks …

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Distraction Detection And Intention Recognition For Gesture-Controlled Unmanned Aerial Vehicle Operation, Debayan Datta May 2022

Distraction Detection And Intention Recognition For Gesture-Controlled Unmanned Aerial Vehicle Operation, Debayan Datta

Computer Science and Engineering Theses - Archive

Gesture Control as a way to replace more conventional remote-control operations has been pursued for a significant period of time with different levels of success. The use of gestures to control different types of human interfaces is today predominantly seen in the multimedia sector. People perform easy and intuitive gestures to control their televisions, to interact with multimedia, and to play games. Also, much research has been carried out to experiment with human interfaces to numerous augmented and virtual reality devices and tasks. The results of these experiments were so exciting that researchers started to expand the use of gestures …

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Detection And Classification Of Object Presence And Characteristics In A Water Container Using High Frequency Ultrasound, Mehul Vishal Sadh May 2022

Detection And Classification Of Object Presence And Characteristics In A Water Container Using High Frequency Ultrasound, Mehul Vishal Sadh

Computer Science and Engineering Theses - Archive

Detection and characterization of soluble, diffuse, and solid objects and their characteristics in water has important implications in various applications, including water quality assessment and incontinence monitoring for health applications. In particular in the latter task, it is essential to be able to non-intrusively detect the appearance, presence, and consistency of materials in the water without the need for special purpose instruments or a special purpose setting. Rather, it would be important that sensing could be performed int he context of existing toilet systems. To achieve this, this work investigates the potential use of high frequency sonar sensors retrofitted to …

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A Combinatorial Approach To Fairness Testing Of Machine Learning Models, Ankita Ramjibhai Patel May 2022

A Combinatorial Approach To Fairness Testing Of Machine Learning Models, Ankita Ramjibhai Patel

Computer Science and Engineering Theses - Archive

Machine Learning (ML) models could exhibit biased behavior, or algorithmic discrimination, resulting in unfair or discriminatory outcomes. The bias in the ML model could emanate from various factors such as the training dataset, the choice of the ML algorithm, or the hyperparameters used to train the ML model. In addition to evaluating the model’s correctness, it is essential to test ML models for fair and unbiased behavior. In this thesis, we present a combinatorial testing-based approach to perform fairness testing of ML models. Our approach is model agnostic and evaluates fairness violations of a pre-trained ML model in a two-step …

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“Strict Moderation?” The Impact Of Increased Moderation On Parler Content And User Behavior, Nihal Kumarswamy May 2022

“Strict Moderation?” The Impact Of Increased Moderation On Parler Content And User Behavior, Nihal Kumarswamy

Computer Science and Engineering Theses - Archive

Social media platforms have brought people from different backgrounds, ethnicity, race, gender, etc together to form a platform to share ideas and opinions and discuss news events among other social events. Unfortunately, these platforms have also been a safe haven for abusive users who harass, bully other users or spread misinformation and disinformation. Social media platforms have a huge incentive to police these abusive users and keep them in check to allow other genuine users to use their platform. Social media platforms employ several different content moderation techniques to perform this task. These techniques vary across platforms, for example, Parler …

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A Non-Contact Based System To Measure Spo2 And Systolic/Diastolic Blood Pressure Using Rgb-Nir Camera, Divya Saxena May 2022

A Non-Contact Based System To Measure Spo2 And Systolic/Diastolic Blood Pressure Using Rgb-Nir Camera, Divya Saxena

Computer Science and Engineering Theses - Archive

In recent times, people have increasingly self-assessed their health using different devices on their bodies that monitor physiological attributes such as their oxygen level and blood pressure (BP) to monitor their health. One of the most popular health concerns that became prominent during the COVID-19 pandemic was the blood oxygen saturation (SPO2) level. It became increasingly important to monitor SPO2 in patients, time and again to determine whether the right amount of oxygen is in the blood. Low oxygen levels usually indicate there may be an issue with oxygen circulation or supply and thus informs diagnostic and treatment decisions such …

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Robust Noise-Based Attacks Against Audio Event Detection Systems, Rodrigo Augusto Silva Dos Santos May 2022

Robust Noise-Based Attacks Against Audio Event Detection Systems, Rodrigo Augusto Silva Dos Santos

Computer Science and Engineering Dissertations - Archive

The massive advances on the field of deep neural networks in the 2000 and 2010 decades led to an overwhelming adoption of these algorithms on all sorts of domains and applications. Under this widespread adoption scenario, it is natural that these neural networks have also been employed on safety-related use cases, bringing substantial improvements to the performance of existing as well as novel systems. Examples of these safety-inclined applications include scene recognition, object detection and tracking, speech recognition, audio event detection and classification, just to cite a few ones. Unfortunately, these neural network algorithms have been shown to be vulnerable …

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Designing Large-Scale Key-Value Systems On High-Speed Storage Devices, Xingsheng Zhao May 2022

Designing Large-Scale Key-Value Systems On High-Speed Storage Devices, Xingsheng Zhao

Computer Science and Engineering Dissertations - Archive

With the evolution of new technologies, such as edge computing, full self-driving, virtual reality, and multi-media streaming, the volume of data is growing at an accelerated speed. The global data volume could achieve 175~zettabytes by 2025. With this huge amount of data, the focus of data management has been shifted from traditional SQL databases to NoSQL databases, which provide higher performance and better scalability. Key-value (KV) stores are a common type of NoSQL database and are becoming a major storage infrastructure in various application domains. With the development of high-speed storage devices, such as NVMe SSD, Open-channel SSD, and non-volatile …

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Efficient Algorithms And Human-In-The-Loop Approaches For Attribute Design And Selection, Md Abdus Salam May 2022

Efficient Algorithms And Human-In-The-Loop Approaches For Attribute Design And Selection, Md Abdus Salam

Computer Science and Engineering Dissertations - Archive

Feature engineering and feature selection are two important aspects of data science pipeline. Due to the advancement of data collection techniques in recent years, huge amount of data is becoming available in different industries. Consequently, the importance of data science is increasing for business analytic purpose. Different tools and techniques are being developed to assist data scientists to complete their tasks efficiently. One of the main human involvements in the data science task is for feature engineering and selection. These pre-processing steps will prepare the data in the format desired to be fed into various machine learning algorithms to accomplish …

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Machine Learning Methods For Statistical Analysis And Representation Learning On Neuroimaging Data, Fan Yang May 2022

Machine Learning Methods For Statistical Analysis And Representation Learning On Neuroimaging Data, Fan Yang

Computer Science and Engineering Dissertations - Archive

With the recent advance and widespread adoption of imaging technological innovations, clinical practitioner and scientists can easily acquire and store a large amount of various neuroimaging modalities, such as Diffusion Tensor Imaging (DTI), Magnetic Resonance Imaging (MRI), resting-state functional MRI (rs-fMRI) and Positron Emission Tomography (PET), etc. These novel imaging data sources cover a rich amount of factors that influence patients' cognitive health, offer an objective view of patients at unprecedented multi-resolution for the understanding of brain structure and function, and have the significant potential to improve healthcare by aiding better decision-making in diagnosing, monitoring and treating diseases. Machine Learning …

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Using Antipatterns To Improve Database Code Fragments, And Utilizing Knowledge Graphs And Nlp Patterns To Extract Standardized Data Element Names, Bader Alshemaimri May 2022

Using Antipatterns To Improve Database Code Fragments, And Utilizing Knowledge Graphs And Nlp Patterns To Extract Standardized Data Element Names, Bader Alshemaimri

Computer Science and Engineering Dissertations - Archive

Database code fragments exist in software systems by using SQL as the stan- dard language for relational databases. Traditionally, developers bind databases as backends to software systems for supporting user applications. However, these bind- ings are low-level code and implemented to persist user data, so Object Relational Mapping (ORM) frameworks take place to abstract database access details. These approaches are prone to problematic database code fragments that negatively im- pact the quality of software systems. In the first part of the dissertation, we survey problematic database code fragments in the literature and examine antipatterns that occur in low-level database access …

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Unsupervised Domain Adaptation With Deep Neural Networks, Jinyu Yang May 2022

Unsupervised Domain Adaptation With Deep Neural Networks, Jinyu Yang

Computer Science and Engineering Dissertations - Archive

Deep neural networks (DNNs) demonstrate unprecedented achievements on various machine learning problems and applications. However, such impressive performance heavily relies on massive amounts of labeled data which requires considerable time and labor efforts to collect and annotate. To remedy this limitation, unsupervised domain adaptation (UDA) has attracted more and more attention in the past decade, owing to its capability in transferring the knowledge learned from a labeled source domain to an unlabeled target domain. UDA has proved its wide applicability in various vision tasks, for example, image classification and semantic segmentation. Despite its impressive success, the limitations of existing UDA …

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Learning Causal Bounds Using Marginal Independence Information With Applications To Gene Expression Analysis, Borzou Alipourfard May 2022

Learning Causal Bounds Using Marginal Independence Information With Applications To Gene Expression Analysis, Borzou Alipourfard

Computer Science and Engineering Dissertations - Archive

ABSTRACT: Discovering causal relations is a fundamental goal of science. Randomized controlled experiments were often considered to be the only reliable method for tackling this task. However, in recent years, various causal discovery methods have been proposed that are capable of identifying causal relations from purely observational data. While these causal discovery methods provide a theoretical framework for bridging the gap from statistical relations to causal conclusions, causal discovery remains a challenging task in practice; this challenge arises because many of the assumptions made in obtaining these theoretical results are often not met in practice. This is especially true when …

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Optimal Utility-Based Traffic Control For Datacenter Networks, Akshit Singhal May 2022

Optimal Utility-Based Traffic Control For Datacenter Networks, Akshit Singhal

Computer Science and Engineering Dissertations - Archive

As datacenter applications with diverse service requirements proliferate, it becomes imperative to enable datacenter network flow rate allocation that satisfies minimum user-utility requirements, while allowing for user-utility-based fair resource allocation. Multiple Path Transmission Control Protocols (MPTCPs) allow flows to explore path diversity of datacenter networks and multihoming to improve throughput, reliability, and network resource utilization. The work in this dissertation aims to develop optimal utility-based datacenter traffic control protocols to meet diverse service requirements for datacenter applications. Specifically, this dissertation makes contributions on four highly related research topics. First, we put forward a HOListic traffic control framework for datacenter NETworks …

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Extracting Clinical Event Sequence By Using Association Rule Mining To Predict Clinical Events From Health Records, Aashara Shrestha Dec 2021

Extracting Clinical Event Sequence By Using Association Rule Mining To Predict Clinical Events From Health Records, Aashara Shrestha

Computer Science and Engineering Dissertations - Archive

Data mining is the process of extracting useful information from large amounts of data. Data mining has been around for a long time, and there are many multiple methods of performing data mining. However, the abundance of data that has become available in the last decade has made it possible to mine through this data to uncover important patterns and sequences. The relationship between variables and the way in which they can lead to a specific outcome is an interesting area of research. Today's healthcare industry faces a number of challenges. Providers must reduce costs, improve transparency, and improve the …

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Adaptive Human-Robot Motion Transfer For Complete Body Imitation, Francisco Villa Dec 2021

Adaptive Human-Robot Motion Transfer For Complete Body Imitation, Francisco Villa

Computer Science and Engineering Theses - Archive

Programming robot systems to perform certain tasks is a big challenge especially if such programming is to be performed by persons who are not experts in robotics. For example, when programming a robot to serve as an exercise trainer, the person defining the motions might more naturally be a person in the exercise domain rather than a robotics expert. To address this, this thesis investigates programming by demonstration or teleoperation using full direct body motion. The goal is to reproduce gaits, gestures, and postures on a humanoid robot from observed human demonstrations. Fine motor movements such as movement of fingers …

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Translation Of Array-Based Loop Programs To Optimized Sql-Based Distributed Programs, Md Hasanuzzaman Noor Dec 2021

Translation Of Array-Based Loop Programs To Optimized Sql-Based Distributed Programs, Md Hasanuzzaman Noor

Computer Science and Engineering Dissertations - Archive

Most programs written to operate on data are usually expressed in terms of array operations in sequential loops. However, these programs do not scale to large amount of data generated by scientific experiments and industrial and commercial markets. Given the success of machine learning algorithms on large amount of data and the recent shift of industries to data-driven decision making, the data scientists who are not familiar with Big Data frameworks have to rewrite the sequential programs to distributed data-parallel programs by hand. We present a novel framework, called SQLgen, that automatically translates sequential loops to distributed data-parallel programs. SQLgen …

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Language Pre-Training And Auxiliary Tasks For Vision And Language Navigation, Saumya Bhatt Dec 2021

Language Pre-Training And Auxiliary Tasks For Vision And Language Navigation, Saumya Bhatt

Computer Science and Engineering Theses - Archive

The Vision and Language Navigation task came to life from the idea that we can build a robot or an autonomous system that can be instructed in human language and that will navigate using the instructions given. For example, we tell the agent to “Go down past some room dividers toward a glass top desk and turn into the dining area. Wait next to the large glass dining table” and not only does it reach the goal state but it follows the instructions while navigating. With the current developments, this may not seem like a distant problem anymore and in …

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Representation And Strategy Learning For Variable-Size Tree Transformation Using Reinforcement Learning, Shirin Hosseini Shirvani Aug 2021

Representation And Strategy Learning For Variable-Size Tree Transformation Using Reinforcement Learning, Shirin Hosseini Shirvani

Computer Science and Engineering Dissertations - Archive

Trees as acyclic graphs are ubiquitous in representing different context where they encode connectivity patterns at all scales of organization, from biological systems to social networks. Trees are powerful resources which have been used many times for the exploration and discovery of interactions and properties in different context. Tree data structure representation approaches have led to remarkable discoveries in different real-world applications. In the last decades, extensive research and algorithms have been developed on tree or acyclic graph data structures with deep theoretical properties. The cost of solving these various problems ranges from simple linear time algorithms, to more complex …

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