Digital Commons Network^™

Identification Of Copy Number Variations (Cnvs) Of Epigenetic Factors Related To The Progression Of Pancreatic Ductal Adenocarcinoma (Pdac), Pavithra Raju

Master's Projects

Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge in oncology due to its aggressive form and late-stage detection. PDAC is known to be influenced by various epigenetic factors like DNA methylation and histone modifications. This study focuses on copy number variations (CNVs) within epigenetic factors which for their role in early diagnosis. Thus, paving the way for identification of potential biomarkers. The epigenetic pipeline was extended based on CNVs and the CNV modified sequences extracted were compared with the wild type sequences of epigenetic PDAC genes. The epigenetic gene KCNJ11 with copy number gain of CNV id 46771406 was used …

Ensemble Transformer Architecture For Efficient And Real Time Sign Language Translation, Sumeet Ghegade

Master's Projects

Sign language is a form of visual language that uses face expression and hand gestures to communicate thoughts and concepts. The term refers to multiple visual languages that share some common visual cues but differ in their grammar and syntax. Sign language translation (SLT) is a crucial step in closing the communication gap between hearing and hearingimpaired people. The study of SLT using machine learning has gotten a lot of interest during the last three years but despite progress, SLT research is still in its early phases. Most of the previous approaches first convert the signs to glosses and then …

Pygrapherconnect, Shubham Jain

Master's Projects

The evolving landscape of backend computational systems especially in biomedical research involving heavy data operations which have a gap of not being used properly. It is due to the lack of communication standard between the frontend and backend. This gap presents a problem to researchers who need to use the frontend for visualizing and manipulating their data but also want to do complex analysis. CAPRI a python-based backend system specializing in analyzing Evidential Reasoning data also has the same issue. This project offers a solution PyGrapherConnect module acting as a data conversion layer between CAPRI and PyGrapher, its frontend interface. …

Mild Cognitive Impairment And Alzheimer’S Disease Detection And Testing Interface (Mci-Addti) Modeller10.4 Integrating Structure-Function Prediction Modules, Grant Galileo Jacobson

Master's Projects

In the population of adult human patients who over express Beta and Tau Amyloids, it is unclear why 40% of them do not have Alzheimer’s Disease (AD), when all patients with AD have an overexpression of Beta and Tau Amyloids. The MCI-AD-DTI project’s epigenetic pipeline is an evolving computation tool that seeks epigenetic-related information related to the observed disparity. The MCI-AD-DTI’s epigenetic pipeline’s ability to identify mutations currently relies solely on PyPDB for verification of its protein functionality evaluation. The assessment process of the industry standard application, Modeller10.4, is independent from the current epigenetic pipeline’s protein evaluation algorithm. Thus, this …

An Incentivization Mechanism Towards Network-Slice As A Service, Yosha Mundhra

Master's Projects

Next-generation communication networks are expected to support many different types of services. Network slicing virtually divides one physical network into several virtual networks in order to accommodate diverse demands for network connections. Assuming multiple network domains are stitched together to provide end-to-end network slices for such diverse services, it is critical to consider the economic behaviors and revenue models of the stakeholders. This project analyzes the economic behaviors from the perspective of a Global Slice Coordinator (GSC) that receives a slice request and coordinates the end-to-end resource allocations across multiple network domains. The primary role of the GSC is to …

Xai-Driven Cnn For Diabetic Retinopathy Detection, Vikas Shenoy Pete

Master's Projects

Diabetes, a chronic metabolic disorder, poses a significant health threat with potentially severe consequences, including diabetic retinopathy, a leading cause of blindness. In this project, we tackle this threat by developing a Convolutional Neural Network (CNN) to support the diagnosis based on eye images. The aim is early detection and intervention to mitigate the effects of diabetes on eye health. To enhance transparency and interpretability, we incorporate explainable AI techniques. This research not only contributes to the early diagnosis of diabetic eye disease but also advances our understanding of how deep learning models arrive at their decisions, fostering trust and …

On Measuring The Degree Of Resource Isolation In Elastic Network Slicing, Nitin Datta Movva

Master's Projects

With the growing popularity of 5G networks and their vast use cases, users must be provided with the services they request. Network slicing is a technique for establishing numerous distinct logical and virtualized networks over a shared multi-domain infrastructure. In particular, the emerging elastic slicing, which allows users to scale up or down the reserved amount of resources during the slice life cycle, is a promising technique to accommodate diverse network services more affordably. However, users may sometimes need more resources, which is impossible to provide due to the abundance of users and lack of additional resources. To our knowledge, …

Uncertainty-Aware And Explainable Artificial Intelligence For Identification Of Human Errors In Nuclear Power Plants, Bhavya Reddy Kotla

Master's Projects

Nuclear Power Plants (NPPs) can face challenges in maintaining standard operations due to a range of issues, including human mistakes, mechanical breakdowns, electrical problems, measurement errors, and external influences. Swift and precise detection of these issues is crucial for stabilizing the NPPs. Identifying such operational anomalies is complex due to the numerous potential scenarios. Additionally, operators need to promptly discern the nature of an incident by tracking various indicators, a process that can be mentally taxing and increase the likelihood of human errors. Inaccurate identification of problems leads to inappropriate corrective actions, adversely affecting the safety and efficiency of NPPs. …

Never Too Young: The Existence, Impact, And Sustainability Of Ethnic Studies In Elementary School, Angela R. Guzmán

Dissertations

Ethnic Studies has existed in higher education for more than fifty years. In high school, critical education researchers have recognized Ethnic Studies as vital to improving attendance, lowering suspension rates, and boosting GPAs for BIPOC students. This has given rise to the recent K-12 Ethnic Studies model curriculum adoption by the State Board of Education, and the signing of Assembly Bill 101, making California the first state to require that all high school students complete a semester-long course in Ethnic Studies. Regrettably, Ethnic Studies continues to be mostly limited to higher education and grades 9-12 in public schools despite research …

Image-Based Malware Classification On Noise Extraction, Venkata Sai Sathwik Nadella

Master's Projects

Any malicious software designed to cause harm or damage to a computer system can be termed as malware. One common form of malware is as executable files. Such files are often used as a delivery mechanism for malware since they can be easily disguised as legitimate software and can be executed without raising suspicion. They are often used to exploit vulnerabilities in software, allowing malware to bypass security measures and gain access to sensitive information.

There are several methods used to detect malware in executable files, including Signaturebased detection, Behavioral-based detection, Heuristic-based detection, Sandboxing, Machine Learning and Artificial Intelligence (AI). …

Vehicle-Based Disconnected Data Distribution, Aditya Singhania

Master's Projects

The world today is highly connected and there is an immense dependency on this connectivity to accomplish basic everyday tasks. However much of the world lacks connectivity. Even in well-connected locations, natural disasters can cause infrastructure disruption. To combat these situations, Delay Tolerant Networks

(DTNs) employ to store and forward techniques along with intermittently connected transports to provide data connectivity. DTNs focus on intermittently connected networks however what if the regions are never connected? For example, Region A - is never connected to the internet, and Region B – has internet connectivity. Using a vehicle that travels between the two …

A Novel Efficient Deep Learning Framework For Facial Inpainting - Face Reconstruction From Masked Images, Akshay Ravi

Master's Projects

The use of face masks due to the covid-19 pandemic has made surveillance of people very difficult. Since a mask covers most of the facial components, security cameras are rendered of little to no use in the identification of criminals. In order to realize what a face looks like behind a mask, we have to construct the facial features in the masked region. On a higher level, this falls under the field of image inpainting, i.e. filling missing regions of images or correcting irregularities in images. Current research on image inpainting shows promising results on images that have missing/incorrect patches …

Eye Movements Behaviors In A Driving Simulator During Simple And Complex Distractions, Pradeep Narayana

Master's Projects

Road accidents occur frequently due to driving distractions all around the world. A driving simulator has been created to explore the cognitive effects of distractions while driving in order to address this problem. The purpose of this study is to discover the distraction-causing elements and how they affect driving performance. The simulator offers a secure and regulated setting for carrying out tests while being distracted by different visual distractions, such as solving mathematical equations and number memorizations.

Several trials have been conducted in the studies, which were carried out under varied circumstances like varying driving sceneries and by displaying different …

Twitter Bot Detection Using Nlp And Graph Classification, Warada Jayant Kulkarni

Master's Projects

Social media platforms are one of the primary resources for information as it is easily accessible, low in cost, and provides a high rate of information spread. Online social media (OSM) have become the main source of news information around the world, but because of the distributed nature of the web, it has increased the risk of fake news spread. Fake news is misleading information that is published as real news. Therefore, identifying fake news and flagging them as such, as well as detecting sources that generate them is an ongoing task for researchers and OSM companies. Bots are artificial …

Differential Gene Expression Analysis Of Rodent Mammary Tissue Reveals Dysregulation Of Greb1 And An Age-Dependent Response To Spaceflight, Cleoma Arnold

Master's Projects

Life aboard spacecraft poses a danger to astronaut health, with hazards including microgravity, radiation, and enclosed spaces. Research into mitigating these health issues includes analysis of the transcriptome of rodents sent to the International Space Station. This project investigates the effects of spaceflight on the mammary tissue of female mice of two age groups, 10-12 and 32 weeks, in order to assess the impact of age and spaceflight on gene expression in a tissue relevant to female health. Analysis of the OSD-511 dataset from NASA’s Open Science Data Repository utilized a containerized implementation of their RNA-Seq pipeline on the San …

Intersections Of Disproportion: A Critical Quantitative Examination Of Dis/Ability And Gender In Black Students’ School Discipline Outcomes, Ceema Samimi, Noah Jefferson, Shelby Flanagan, Yolanda Anyon

Faculty Research, Scholarly, and Creative Activity

This study uses critical race quantitative intersectionality to examine the impacts of gender and dis/ability type on Black students’ school discipline outcomes. We use multilevel logistic regression models to analyze data from a large urban school district, considering the intersectional impact of gender and dis/ability type on school discipline outcomes among Black students (suspension, restorative justice, referral to law enforcement). We found that Black students identified as male, labeled with emotional dis/abilities, or identified as having ADHD were more likely to experience school discipline consequences than those who were not. These findings suggest that gender and dis/ability status are significant …

Application Of Artificial Intelligence In Detection And Mitigation Of Human Factor Errors In Nuclear Power Plants: A Review, Meenu Sethu, Bhavya Kotla, Darrell Russell, Mahboubeh Madadi, Nesar Ahmed Titu, Jamie Baalis Coble, Ronald L. Boring, Klaus Blache, Vivek Agarwal, Vaibhav Yadav, Anahita Khojandi

Faculty Research, Scholarly, and Creative Activity

Human factors and ergonomics have played an essential role in increasing the safety and performance of operators in the nuclear energy industry. In this critical review, we examine how artificial intelligence (AI) technologies can be leveraged to mitigate human errors, thereby improving the safety and performance of operators in nuclear power plants (NPPs). First, we discuss the various causes of human errors in NPPs. Next, we examine the ways in which AI has been introduced to and incorporated into different types of operator support systems to mitigate these human errors. We specifically examine (1) operator support systems, including decision support …

Sleep Health Education To Promote Public Health: Attitudes And Desired Learning Goals Among Social Work Students, Christine Spadola, Danielle B. Groton, Kerry Littlewood, Cassie Hilditch, Shanna Burke, Suzanne M. Bertisch

Faculty Research, Scholarly, and Creative Activity

Social workers are often front line behavioral health providers for underserved populations, many of whom experience sleep disturbances. Inadequate sleep presents a public health challenge and is associated with many adverse physical health and mental health consequences. Social workers are uniquely positioned to promote sleep health among individuals experiencing health inequities. However, sleep is rarely included as part of the curricula in social work programs in the U.S. We conducted qualitative formative research to investigate social work students’ perceptions of sleep education and desired sleep learning objectives. Twenty-five social work students were recruited via a listserv e-mail to participate in …

Sex Differences In Perceptions Of Sleep Inertia Following Nighttime Awakenings, Cassie J. Hilditch, Sean Pradhan, Gregory Costedoat, Nicholas G. Bathurst, Zachary Glaros, Kevin B. Gregory, Nita L. Shattuck, Erin E. Flynn-Evans

Faculty Research, Scholarly, and Creative Activity

Study Objectives: The influence of biological sex on sleep inertia symptoms is currently unknown. We investigated the role of sex differences in the subjective experience and objective cognitive manifestation of sleep inertia following nighttime awakenings. Methods: Thirty-two healthy adults (16 female, 25.91 ± 5.63 years) completed a 1-week at-home study with one experimental night during which sleep was measured by polysomnography and participants were awakened during their habitual sleep time. Participants completed a psychomotor vigilance task, Karolinska Sleepiness Scale (KSS), visual analog mood scales, and a descending subtraction task (DST) prior to sleep (baseline) and at 2, 12, 22, and …

A Step-By-Step Hhl Algorithm Walkthrough To Enhance Understanding Of Critical Quantum Computing Concepts, Anika Zaman, Hector Jose Morrell, Hiu Yung Wong

Faculty Research, Scholarly, and Creative Activity

After learning basic quantum computing concepts, it is desirable to reinforce the learning using an important and relatively complex algorithm through which students can observe and appreciate how qubits evolve and interact with each other. Harrow-Hassidim-Lloyd (HHL) quantum algorithm, which can solve linear system problems with exponential speed-up over the classical method and is the basis of many important quantum computing algorithms, is used to serve this purpose. The HHL algorithm is explained analytically followed by a 4-qubit numerical example in bra-ket notation. Matlab code corresponding to the numerical example is available for students to gain a deeper understanding of …

Evaluation Of Nanoclay Additives For Improving Resistance To Moisture Damage In Hot Mix Asphalt (Hma), Amro El Badawy, Ashraf Rahim

Mineta Transportation Institute

Transportation has an enormous impact on the U.S. economy and on the lives of all Americans. Many modes of transportation rely on pavement, but pavement conditions deteriorate over time because of the combined effects of traffic and climate. Exposure to moisture often causes premature failure of asphalt pavements as it reduces the stiffness of the asphalt and enables stripping of the asphalt from the aggregate. This research evaluates the effectiveness of clay nanomaterials (i.e., nanoclays) in improving the resistance of hot mix asphalt (HMA) to moisture damage and compares the enhancement results to anti-stripping additives commonly used in pavement construction. …

The Future Of Mobility-As-A-Service: Trust Transfer Across Automated Mobilities, From Road To Sidewalk, Jacob G. Hunter, Elise Ulwelling, Matthew Konishi, Noah Michelini, Akhil Modali, Anne Mendoza, Jessie Snyder, Shashank Mehrotra, Zhaobo Zheng, Anil R. Kumar, Kumar Akash, Teruhisa Misu, Neera Jain, Tahira Reid

Faculty Research, Scholarly, and Creative Activity

While trust in different types of automated vehicles has been a major focus for researchers and vehicle manufacturers, few studies have explored how people trust automated vehicles that are not cars, nor how their trust may transfer across different mobilities enabled with automation. To address this objective, a dual mobility study was designed to measure how trust in an automated vehicle with a familiar form factor—a car—compares to, and influences, trust in a novel automated vehicle—termed sidewalk mobility. A mixed-method approach involving both surveys and a semi-structured interview was used to characterize trust in these automated mobilities. Results found that …

Beta Cortical Oscillatory Activities And Their Relationship To Postural Control In A Standing Balance Demanding Test: Influence Of Aging, Yang Hu, Steven J. Petruzzello, Manuel E. Hernandez

Faculty Research, Scholarly, and Creative Activity

Background: Age-related changes in the cortical control of standing balance may provide a modifiable mechanism underlying falls in older adults. Thus, this study examined the cortical response to sensory and mechanical perturbations in older adults while standing and examined the relationship between cortical activation and postural control. Methods: A cohort of community dwelling young (18–30 years, N = 10) and older adults (65–85 years, N = 11) performed the sensory organization test (SOT), motor control test (MCT), and adaptation test (ADT) while high-density electroencephalography (EEG) and center of pressure (COP) data were recorded in this cross-sectional study. Linear mixed models …

Network Anatomy In Logopenic Variant Of Primary Progressive Aphasia, Maria Luisa Mandelli, Diego L. Lorca-Puls, Sladjana Lukic, Maxime Montembeault, Andrea Gajardo-Vidal, Abigail Licata, Aaron Scheffler, Giovanni Battistella, Stephanie M. Grasso, Rian Bogley, Buddhika M. Ratnasiri, Renaud La Joie, Nidhi S. Mundada, Eduardo Europa, Gil Rabinovici, Bruce L. Miller, Jessica De Leon, Maya L. Henry, Zachary Miller, Maria Luisa Gorno-Tempini

Faculty Research, Scholarly, and Creative Activity

The logopenic variant of primary progressive aphasia (lvPPA) is a neurodegenerative syndrome characterized linguistically by gradual loss of repetition and naming skills resulting from left posterior temporal and inferior parietal atrophy. Here, we sought to identify which specific cortical loci are initially targeted by the disease (epicenters) and investigate whether atrophy spreads through predetermined networks. First, we used cross-sectional structural MRI data from individuals with lvPPA to define putative disease epicenters using a surface-based approach paired with an anatomically fine-grained parcellation of the cortical surface (i.e., HCP-MMP1.0 atlas). Second, we combined cross-sectional functional MRI data from healthy controls and longitudinal …

Maximizing External Action With Information Provision Over Multiple Rounds In Online Social Networks, Masaaki Miyashita, Norihiko Shinomiya, Daisuke Kasamatsu, Genya Ishigaki

Faculty Research, Scholarly, and Creative Activity

Online social networks have increased their impact on the real world, which motivates information senders to control the propagation process of information to promote particular actions of online users. However, the existing works on information provisioning seem to oversimplify the users? decision-making process that involves information reception, internal actions of social networks, and external actions of social networks. In particular, characterizing the best practices of information provisioning that promotes the users? external actions is a complex task due to the complexity of the propagation process in OSNs, even when the variation of information is limited. Therefore, we propose a new …

Low-Density Star Cluster Formation: Discovery Of A Young Faint Fuzzy On The Outskirts Of The Low-Mass Spiral Galaxy Ngc 247, Aaron J. Romanowsky, Søren S. Larsen, Alexa Villaume, Jeffrey L. Carlin, Joachim Janz, David J. Sand, Jay Strader, Jean P. Brodie, Sukanya Chakrabarti, Chloe M. Cheng, Denija Crnojević, Duncan A. Forbes, Christopher T. Garling, Jonathan R. Hargis, Ananthan Karunakaran, Ignacio Martín-Navarro, Knut A.G. Olsen, Nicole Rider, Bitha Salimkumar, For Full Author List, See Comments Below

Faculty Research, Scholarly, and Creative Activity

The classical globular clusters found in all galaxy types have half-light radii of rh ~2-4 pc, which have been tied to formation in the dense cores of giant molecular clouds. Some old star clusters have larger sizes, and it is unclear if these represent a fundamentally different mode of low-density star cluster formation. We report the discovery of a rare, young 'faint fuzzy' star cluster, NGC 247-SC1, on the outskirts of the low-mass spiral galaxy NGC 247 in the nearby Sculptor group, and measure its radial velocity using Keck spectroscopy. We use Hubble Space Telescope imaging to measure the cluster …

2023 Silicon Valley Pain Index, Scott Myers-Lipton, William Armaline

Faculty Research, Scholarly, and Creative Activity

No abstract provided.

Never Lose Your Ecg: A Novel Key Generation And Authentication Scheme For Implantable Medical Devices, Nima Karimian, Gokay Saldamli, Younghee Park, Victor Lui

Faculty Research, Scholarly, and Creative Activity

Implantable medical devices, such as pacemakers, cardiac defibrillators, and insulin pumps, play a crucial role in monitoring patients' vital signs within healthcare systems. However, these networked devices are susceptible to external attacks and breaches of trust, hindering the potential innovation and social benefits of eHealth services. To address these concerns, we propose a novel ECG-based key generation scheme and blockchain-based authentication protocol to build a trustworthy healthcare service under any situation. The key will be extracted in a single heartbeat using fiducial features. Compared with the existing works, the proposed key generation achieves the most efficient and secure method by …

2d-3d Facial Image Analysis For Identification Of Facial Features Using Machine Learning Algorithms With Hyper-Parameter Optimization For Forensics Applications, Gangothri Sanil, Krishna Prakash, Srikanth Prabhu, Vinod C. Nayak, Saptarshi Sengupta

Faculty Research, Scholarly, and Creative Activity

Recognizing a face is a remarkable process that humans naturally use. Computer vision has tried to resemble this ability of human vision as a biometric tool to identify humans. Commercial and law enforcement applications are increasingly using face recognition technology to identify people. Currently, it is one of the most sought-after detection methods used in forensics for criminal identification purposes. Owing to similarities in the appearance of certain faces, especially in criminal cases, this problem poses a great challenge in forensic investigation and detection. The novelty of this work lies in the development of a framework for face recognition using …

Investigation To Density And Metallurgical Characteristics Of Selective Laser Melted Ti-5al-5 V-5mo-3cr Versus Ti-6al-4 V, David Yan, Roman Bolzowski

Faculty Research, Scholarly, and Creative Activity

Ti-5Al-5 V-5Mo-3Cr (Ti-5553) is a metastable near beta titanium alloy with excellent fatigue performance and corrosion resistance. Hence, it is of significant importance in several high-performance aerospace applications such as aircraft landing gear components. The selective laser melting (SLM) technique shows great potential compared to subtractive methods in generating complex geometries. However, the poor surface finish of the SLMed Ti-5553 components means that post-machining is required to achieve the desired surface quality and dimensional accuracy. Although there is a profound knowledge about the surface integrity of SLMed α + β Ti alloys (typically Ti-6Al-4 V), there is a lack of …