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Articles 17341 - 17370 of 198061
Full-Text Articles in Engineering
Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano
Linear And Nonlinear Topology Optimization With Morphing Beam Networks, Andrew S. Montalbano
All Dissertations
Topology optimization (TO) is an engineering design discipline dedicated to optimizing material distribution within a given domain. In traditional gradient-based topology optimization, the solid domain is discretized into small volumetric elements. Using finite element analysis (FEA) of the structure, the gradient of the objective function with respect to the design variables (the pseudo densities) is computed, and these design variables are updated iteratively until convergence is achieved. Although gradient-based TO methods are well-established, sensitivity analyses of objective functions and constraints can be both mathematically complex and computationally intensive. The nonconvex nature of most TO problems often complicates efficient convergence. Furthermore, …
Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh
Hybrid Physics-Infused Machine Learning Framework For Fault Diagnostics And Prognostics In Cyber-Physical System Of Diesel Engine, Shubhendu Kumar Singh
All Dissertations
Fault diagnosis is required to ensure the safe operation of various equipment and enables real-time monitoring of associated components. As a result, the demand for new cognitive fault diagnosis algorithms is the need of the hour. Existing deep learning algorithms can detect, classify, and isolate faults. Still, most depend solely on data availability and do not incorporate the system's underlying physics into their prediction. Therefore, the results generated by these fault-detecting algorithms sometimes need to make more sense and deliver when tested in actual operating conditions.
Similar to diagnosis, the fault prognosis of diesel engines is paramount in numerous industries. …
An Emergency Response System To Assist The Movement Of Vehicles During Emergency Operations In Urban Transportation Networks, Jamal Nahofti Kohneh
An Emergency Response System To Assist The Movement Of Vehicles During Emergency Operations In Urban Transportation Networks, Jamal Nahofti Kohneh
All Dissertations
Emergency responders need to arrive at the emergency scene as soon as possible, but operating vehicles under emergency conditions can pose a risk to both the responders and other road users, potentially resulting in crashes or delays in emergency operations. In this research, an emergency response system is proposed to assist emergency and non-emergency response vehicles (ERVs and non-ERVs) during emergency operations in a connected vehicle environment. This system collects the information from connected ERVs and non-ERVs, utilizes this information as inputs in the proposed models, and sends instruction messages back to vehicles. The proposed models provide the fastest ERV …
Feasibility Assessment And Container Traffic Forecasting Of Inland Waterway Container On Barge Transportation, Fan Bu
Graduate Theses and Dissertations
Container on Barge (COB) transportation is an intermodal freight transport mode that moves shipping containers via barges on navigable inland and intracoastal waterways. During the past twenty years, COB has been a growing mode of container shipping globally due to its low-cost, eco-friendly, and congestion-reducing characteristics. Europe and China are currently leading global COB transportation, and the United States (U.S.) may have the potential to achieve economic benefits through the implementation of COB within its intermodal transportation system. To explore this potential, this dissertation investigates the implementation feasibility of COB transportation within the U.S. intermodal freight transportation system. Three contributions …
Cubic Soft Ideals On B-Algebra For Solving Complex Problems: Trend Analysis, Proofs, Improvements, And Applications, Muhammad Saeed, Hafiz Inam Ul Haq, Mubashir Ali
Cubic Soft Ideals On B-Algebra For Solving Complex Problems: Trend Analysis, Proofs, Improvements, And Applications, Muhammad Saeed, Hafiz Inam Ul Haq, Mubashir Ali
Neutrosophic Systems with Applications
In this paper, we introduce the concepts of cubic soft (CS) algebra, CS o-subalgebra, and CS ideals within the framework of B-algebra. We provide comprehensive characterizations of these new structures, elucidating their unique properties and interrelationships. Specifically, we present detailed conditions under which a CS subalgebra can be classified as a closed CS ideal. Our analysis explores the intricate relationships among closed cubic soft ideals, cubic soft subalgebras, and cubic soft o-subalgebras. By doing so, we aim to provide a deeper understanding of how these structures interact and coexist within the broader context of B-algebra The findings offer significant insights …
Divergence Measures And Aggregation Operators For Single-Valued Neutrosophic Sets With Applications In Decision-Making Problems, Surender Singh, Sonam Sharma
Divergence Measures And Aggregation Operators For Single-Valued Neutrosophic Sets With Applications In Decision-Making Problems, Surender Singh, Sonam Sharma
Neutrosophic Systems with Applications
Single-valued neutrosophic sets (SVNSs) facilitate the representation of uncertain information more extensively than conventional methods. The study of divergence measures of SVNSs is important due to their applications in different areas like multi-criteria decision-making (MCDM), pattern recognition, cluster analysis, machine learning, etc., In this paper, we introduce a divergence measure for SVNSs. The suggested divergence measure is applied to cluster analysis for the classification of imprecise data. For establishing the reasonability and advantage of the suggested divergence measure in a clustering problem over the existing measures, a comparative assessment is also presented. Furthermore, we introduce, an inferior ratio method for …
Dual Modification Of Reverse Osmosis Membranes With Nh2-Mil-125 And Functionalised Multiwalled Carbon Nanotubes For Enhanced Nanoplastic Removal, Javad Farahbakhsh, Mohadeseh Najafi, Mitra Golgoli, Seyedeh Zahra Haeri, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar
Dual Modification Of Reverse Osmosis Membranes With Nh2-Mil-125 And Functionalised Multiwalled Carbon Nanotubes For Enhanced Nanoplastic Removal, Javad Farahbakhsh, Mohadeseh Najafi, Mitra Golgoli, Seyedeh Zahra Haeri, Mehdi Khiadani, Amir Razmjou, Masoumeh Zargar
Research outputs 2022 to 2026
The present study describes a novel double-modified strategy for developing high-performance thin-film composite reverse osmosis (TFC-RO) membranes by incorporating titanium-based metal organic frameworks (NH2-MIL-125) and functionalised multiwalled carbon nanotubes (MWCNTs) into the support layer and selective layer, respectively. Initially, the support layer was subjected to successive modifications using NH2-MIL-125 mixed with polysulfone (PSF) in dimethylformamide DMF solution to investigate their impact on the performance and properties of the support layer and resultant TFC-RO membranes. Results indicated that the new structure of the modified support layer had significant influences on the developed TFC-RO membranes. Notably, the pristine PSF support exhibited a …
Recent Progress In Microencapsulation Technology And Its Applications In Petroleum Industry, Jingyi Zhu, Jiayu He, Jie Zhou, Zhaozhong Yang, Xiaogang Li, Ying Li, Zhenjiang You
Recent Progress In Microencapsulation Technology And Its Applications In Petroleum Industry, Jingyi Zhu, Jiayu He, Jie Zhou, Zhaozhong Yang, Xiaogang Li, Ying Li, Zhenjiang You
Research outputs 2022 to 2026
Oilfield chemicals play a pivotal role in optimizing the development of oil and gas resources. Emerging technologies for the controlled release of these chemicals have captured considerable interest among petroleum engineers. Microencapsulation, a method widely employed for controlled release in various industries such as biotechnology, pharmaceuticals, and agriculture, is gaining traction in the realm of oil and gas exploitation. This paper provides a comprehensive review of encapsulation technologies, including solvent evaporation, coacervation, and polymerization methods. Special emphasis is placed on recent advancements in the applications of microcapsules within the oil and gas sector. Given the profound impact of release behavior …
Simulation Modeling Of An Earth Entry System And Solar Radiation Pressure Module Development, Michael Sean Manwell
Simulation Modeling Of An Earth Entry System And Solar Radiation Pressure Module Development, Michael Sean Manwell
Mechanical & Aerospace Doctoral and Master's Level Projects and Papers
Several trajectory simulation tools are used to model different phases of the Approach, Entry, Descent and Landing (AEDL) phase of NASA’s Mars Sample Return Campaign. Working towards a single simulation tool that models all AEDL phases, this project utilizes Program to Optimize Simulated Trajectories II to simulate the 72-hour exoatmospheric phase of AEDL up till the point of Earth atmospheric entry. This involves developing a new feature for POST2 that captures the forces and moments caused by solar radiation pressure (SRP). Generalizing the vehicle geometry as a combination of primitive shapes, a generalized SRP module was created and implemented into …
Reactive Processing Of Hf-Nb-Ti-Ta Melts Into A B4c/C Packed Bed, Laura Leticia Sandoval
Reactive Processing Of Hf-Nb-Ti-Ta Melts Into A B4c/C Packed Bed, Laura Leticia Sandoval
Open Access Theses & Dissertations
The reactivity of liquid Hf-Nb-Ti-Ta alloy in B4C/C packed bed to form boride-carbide precipitates for ultra-high temperature ceramics was investigated at 2800 K. The objectives were to predict the thermodynamic phases formed and verify them with microstructural characterization. A pseudo-isopiestic technique was used to significantly lower the oxygen potential as the liquid Hf alloy infused and reacted into a B4C packed bed within a graphite enclosure. The technique had a low temperature region (at 1300 K) to control the oxygen potential with a Y-Al/Y2O3-Al2O3/carbide mixture as a liquid Hf alloy at 2800 K and reacted with B4C/C. In addition, any …
Development Of Electric Vehicle Charging Station Microgrid With Simulation Modelling, Tenzin Lhaden
Development Of Electric Vehicle Charging Station Microgrid With Simulation Modelling, Tenzin Lhaden
Open Access Theses & Dissertations
The rapid adoption of electric vehicles (EVs) necessitates innovative solutions to overcome challenges in energy management, sustainability, and grid reliance. This research develops a hybrid simulation model for EV charging stations, integrating renewable energy sources, such as solar photovoltaic (PV) systems, with energy storage systems (ESS). Leveraging discrete-event simulation (DES) and agent-based modeling (ABM) in AnyLogic, the model offers a comprehensive analysis of charging station operations, incorporating stochastic EV arrivals, dynamic energy allocation, and user-defined customization.Key contributions include the development of hybrid simulation model integrating solar PV, energy storage, and energy management systems (EMS) that dynamically optimizes energy distribution from …
Development Of 3d Human Cardiovascular And Cancer Tissue Model Within A Self-Driven Microfluidic Platform For Preclinical Drug Screening, Aibhlin Alexis Esparza
Development Of 3d Human Cardiovascular And Cancer Tissue Model Within A Self-Driven Microfluidic Platform For Preclinical Drug Screening, Aibhlin Alexis Esparza
Open Access Theses & Dissertations
According to the American Heart Association and World Health Organization, cardiovascular diseases (CVDs) are the leading cause of death worldwide. Monolayer cell culture (2D) and animal models are conventional methods to study CVDs, however, they limit researcherâ??s ability to simulate the human cardiovascular cellular microenvironments and accurate predication of pharmaceutical drug responses. Human induced pluripotent stem cell derived cardiomyocytes (hiPSC-CMs), biomaterials, and microfluidic technologies can be combined to create a controlled, reproducible 3D platform to study physiologically-relevant cellular responses to biochemical and physical changes in the microenvironment. My dissertation work demonstrates the development of novel self-driven microfluidic devices designed with …
Using Causal Inference To Understand Public Perception Towards Electric Vehicle Adoption, Jesus Alejandro Gutierrez Araiza
Using Causal Inference To Understand Public Perception Towards Electric Vehicle Adoption, Jesus Alejandro Gutierrez Araiza
Open Access Theses & Dissertations
Why despite all efforts to promote Electric Vehicles (EVs) as an alternative transportation method through strategies such as tax credits on unit purchasing or long-term environmental benefits communication, its market penetration has not reached the expected goals in the United States? Even though there have been important advancements in the EV technical perspective and financial EV purchasing incentives, the final EV customers still face barriers on their scenarios that do not allow them to purchase this type of contemporary transportation means. Not understanding their local barriers could be a mistake that could reduce EVA expectations in the country and keep, …
Integrating Machine Learning And Simulation For Resource Planning Of Hospital Systems Based On Predicted Length Of Stay, S M Atikur Rahman
Integrating Machine Learning And Simulation For Resource Planning Of Hospital Systems Based On Predicted Length Of Stay, S M Atikur Rahman
Open Access Theses & Dissertations
Recently Hospital Systems faced a high invasion of patients generated by several events such as health crisis related epidemic (COVID, FLU) or seasonal flows. Hence, managing hospital bed availability and efficiency with proper care is obligatory for addressing the challenges associated with the overburden of patients. However, the Length of stay (LOS) is often increased due to the high patient influx and overcrowding problem occurs within the Hospital. It resolves these issues, it is essential for hospital authority to predict the Patients LOS which is the crucial indicator for the use of medical resources (allocation, utilization of providers and resource) …
Home Care Work Of Caregivers For Mexican American Adults With Dementia: A Culturally Informed Model Integrating Work System Analyses And Health Disparities Research Framework, Laura Cristina Tovar Felix
Home Care Work Of Caregivers For Mexican American Adults With Dementia: A Culturally Informed Model Integrating Work System Analyses And Health Disparities Research Framework, Laura Cristina Tovar Felix
Open Access Theses & Dissertations
Dementia is an umbrella term for different diseases such as Alzheimer's, vascular dementia, Lewy body, frontotemporal, and mixed dementias. Dementia is caused by a variety of diseases that cause damage to brain cells interfering with the ability of brain cells to communicate between each other. Dementia is associated with different types of brain cell damage in a specific region of the brain (What Is Dementia?, 2024).Dementia affects 55 million people worldwide, where the most affected population is the low-income and the middle-income countries. (Greenblat, 2023). Every 20 years the number almost double, and by 2039 is estimated to reach 78 …
Exploring Telehealth Utilization Through Data Analytics, Statistical Analyses, And Machine Learning Techniques, Aysenur Betul Cengil
Exploring Telehealth Utilization Through Data Analytics, Statistical Analyses, And Machine Learning Techniques, Aysenur Betul Cengil
Graduate Theses and Dissertations
This dissertation investigates the utilization of telehealth services, initially focusing on the Arkansas healthcare system and then extending the analysis nationwide. It aims to understand the factors influencing telehealth adoption and its impact on healthcare delivery. After examining telehealth utilization in Arkansas from 2018 to 2022, the research utilizes a comprehensive dataset from Epic Cosmos, which includes a wide range of patient and visit data from multiple healthcare facilities across the United States from 2018 to 2023. This timeframe allows for a detailed analysis of telehealth trends before, during, and after the COVID-19 pandemic. In Chapter 2, we analyze key …
Development Of A High-Throughput Screening Platform To Profile Gene Delivery And Transcriptional Control In Macrophages, Alexis Ivy
Graduate Theses and Dissertations
Macrophages are an important cell type in the body responsible for orchestrating the inflammatory response and return to homeostasis. Macrophages are often implicated in a multitude of disease pathologies including delayed wound healing, excessive fibrosis, autoimmune disease, and immunosuppression within the tumor microenvironment. Although macrophages have been targeted for therapeutic applications, success in utilizing them has remained elusive due to their relative ease of phenotype switching between inflammatory and anti-inflammatory. The challenge that remains is developing clinically relevant delivery vehicles that can target macrophages without causing a phenotypic switch counter-productive to the desired response. This is especially important when targeting …
Molecular Beam Epitaxy Of Gesn On Iii-V Substrates For Photonic Applications, Calbi Gunder
Molecular Beam Epitaxy Of Gesn On Iii-V Substrates For Photonic Applications, Calbi Gunder
Graduate Theses and Dissertations
This dissertation explores the advancement of germanium-tin (GeSn) as a tuneable narrow bandgap material, crucial for the development of high-efficiency photodetectors and laser devices in near- and mid-infrared technologies. We investigate the synthesis challenges, particularly the lattice mismatch between GeSn alloys and substrates, which significantly affects their crystalline and optical qualities. Through molecular beam epitaxy, we examine the growth of Ge and GeSn on GaAs (001) substrates, employing Ge/GaAs and Ge/AlAs buffer layers to investigate these challenges. Our findings, characterized by X-ray diffraction, atomic force microscopy, reflection high-energy electron diffraction, and photoluminescence, demonstrate the production of high-quality Ge layers, achieving …
Application Of Electrical Impedance Tomography To Cementitious Composites, Hugo Zazueta
Application Of Electrical Impedance Tomography To Cementitious Composites, Hugo Zazueta
Theses and Dissertations
This thesis explores the feasibility of using Electrical Impedance Tomography (EIT) for detecting damage in cementitious composites. Cementitious composites, such as concrete and cement mortar, are insulating; any conductive properties arise from the moisture within their pores and capillary structures. The proposed concept herein is that formed internal damages in cementitious composites consequently alter their pore and capillary structure, which can then be detected through EIT imaging. To construct tomographic images, the Gaussian Newton (GN) reconstruction algorithm, enhanced with priors, was employed. The results were then compared across different reconstruction processes. Cylindrical cement pastes and cement mortar samples were prepared, …
A Real-Time Iot-Based Data Acquisition And Monitoring System For Photovoltaic Applications, Adam Barbosa, Hamza Mubarak, Fazel Mohammadi, Mohammad J. Sanjari, Mehrdad Saif
A Real-Time Iot-Based Data Acquisition And Monitoring System For Photovoltaic Applications, Adam Barbosa, Hamza Mubarak, Fazel Mohammadi, Mohammad J. Sanjari, Mehrdad Saif
Electrical & Computer Engineering and Computer Science Faculty Publications
The transition to low-carbon energy systems, driven by climate change and fossil fuel scarcity, highlights technologies, such as Photovoltaic (PV) technology, for sustainable energy generation. This paper focuses on enhancing the efficiency of PV monitoring systems by leveraging Internet of Things (IoT) technology for accurate and real-time monitoring of essential parameters, such as voltage, current, and output power. Significant gaps in cost-effective and reliable IoT integration for PV monitoring are addressed, with an emphasis on predictive modeling. In this regard, a low-cost real-time IoT-based data acquisition and monitoring system for PV systems, as a proof of concept for future endeavors …
Computational Studies Of Charge-Transfer Mechanisms In Electrochemical Materials, Mohammadreza Reza Nouri
Computational Studies Of Charge-Transfer Mechanisms In Electrochemical Materials, Mohammadreza Reza Nouri
Dissertations and Doctoral Documents, University of Nebraska-Lincoln, 2023–
Understanding charge transfer mechanisms of electrochemical reactions is critical for advancing a variety of electrochemical energy storage and conversion technologies such as water electrolysis, fuel cells, and batteries. (Photo)electrochemical water splitting, involving OER at the anode and HER at the cathode, presents an environmentally friendly way of storing energy from renewable sources in the form of pure hydrogen. While a lot of emphasis has been placed on developing highly active and stable OER/HER catalysts, our atomic-level understanding of the underlying charge transfer mechanisms falls behind.
In this work, we focus on both Faradaic and non-Faradaic charge transfer mechanisms to investigate …
Analysis Of The Relationship Between Flow Patterns In The Post-Stenotic Region Of Model Arteries And Stenosis Severity., Michael Laroche
Analysis Of The Relationship Between Flow Patterns In The Post-Stenotic Region Of Model Arteries And Stenosis Severity., Michael Laroche
Electronic Theses and Dissertations
In this study, contour fields of mean age and turbulence kinetic energy (TKE) in the post-stenotic region of model arteries were analyzed to explore their correlation with FFR. While both high and low FFR cases exhibited similarities with an inner low-age region and an outer high-age region, low FFR cases displayed asymmetry in their low-age regions due to eccentric stenosis. Moreover, gradients of age across the artery diameter were more pronounced for low FFR cases. Additionally, low FFR cases demonstrated significantly higher TKE in the post-stenotic blood jet stream compared to high FFR cases that are reflected in low-age boundary …
Investigating The Detection And Transport Of Low Molecular Weight Species To Better Understand Their Impact On Disease Pathology And Treatment, Haley Michelle Duncan
Investigating The Detection And Transport Of Low Molecular Weight Species To Better Understand Their Impact On Disease Pathology And Treatment, Haley Michelle Duncan
Graduate Theses and Dissertations
Due to the drastic differences in the projects involved, this dissertation will be split into two sections: Alzheimer’s disease and chronic kidney disease. Each chapter will contain an introduction, materials and methods section, results and discussion, conclusions, and works cited section. The Alzheimer’s disease chapter will also have a supplemental figures section containing the polyacrylamide gels that were silver stained and quantified via ImageJ. The presence of elevated levels of amyloid beta oligomeric species in the brain has been related to the pathology of Alzheimer’s disease. As these oligomeric species are transient in nature, their kinetics pose a challenge to …
Leveraging Machine Learning And Stochastic Programming To Address Vaccine Hesitancy In Public Health Resource Allocation, Hieu Trung Bui
Leveraging Machine Learning And Stochastic Programming To Address Vaccine Hesitancy In Public Health Resource Allocation, Hieu Trung Bui
Graduate Theses and Dissertations
Infectious disease outbreaks highlight the urgent need for effective strategies to distribute vaccines and allocate critical healthcare resources to contain the disease and reduce its negative impacts on the population. Managing these allocations is a significant challenge, especially in marginalized communities facing uncertainty in healthcare demand and logistical constraints. This dissertation addresses these challenges by investigating factors that influence dynamic changes in vaccine hesitancy (VH) and its implications for disease spread and healthcare resource demand. It develops optimization models for vaccine distribution and resource allocation under uncertainty, validated with data from the COVID-19 pandemic in the U.S. The first study …
Physics-Informed Machine Learning Methods For Inverse Design Of Multi-Phase Materials With Targeted Mechanical Properties, Yunpeng Wu
All Dissertations
Advances in machine learning algorithms and applications have significantly enhanced engineering inverse design capabilities. This work focuses on the machine learning-based inverse design of material microstructures with targeted linear and nonlinear mechanical properties. It involves developing and applying predictive and generative physics-informed neural networks for both 2D and 3D multiphase materials.
The first investigation aims to develop a machine learning method for the inverse design of 2D multiphase materials, particularly porous materials. We first develop machine learning methods to understand the implicit relationship between a material's microstructure and its mechanical behavior. Specifically, we use ResNet-based models to predict the elastic …
Data-Driven Enhanced Energy Management System Applications For Energy Control Centers, Dulip Madurasinghe
Data-Driven Enhanced Energy Management System Applications For Energy Control Centers, Dulip Madurasinghe
All Dissertations
This dissertation explores the pressing needs of modern bulk power system operation and control and delves into enhancements to EMS applications with minimal infrastructure development. The dissertation investigates three main EMS application enhancements. The transmission network topology processing (TNTP) is a foundational application of the EMS. A physics-based hierarchical transmission network topology processing (H-TNTP), including substation configuration identification, to improve efficiency and reliability is proposed. Secondly, a multi-level distributed linear state estimation (D-LSE) approach solely based on PMUs is proposed utilizing H-TNTP as the network modeling tool. The D-LSE can conduct linear state estimation (LSE) at either substation, area or …
Integrating Artificial Intelligence And Augmented Reality For Enhanced Task Performance In The Construction Industry, Aasish Chandrika Bhanu
Integrating Artificial Intelligence And Augmented Reality For Enhanced Task Performance In The Construction Industry, Aasish Chandrika Bhanu
All Dissertations
The Architecture, Engineering, and Construction (AEC) sector, characterized by its complex tasks, often faces challenges in adopting cutting-edge technologies, a trend that can significantly hinder productivity improvements compared to other industries. This dissertation explores the emerging integration of Artificial Intelligence (AI) and Augmented Reality (AR) within the AEC domain, investigating how effectively this can be implemented to potentially revolutionize industry practices. AI could be used in the AEC domain for advanced analytical and decision-making processes, while AR could be used for training, visualization, and remote collaboration.
In scenarios where construction site workers require expert guidance, these technologies could be helpful. …
Opioid Overdose Epidemic Modeling, Chelsea Spence
Opioid Overdose Epidemic Modeling, Chelsea Spence
All Dissertations
The opioid overdose crisis in the United States has led to thousands of lost lives and thousands more people struggling with opioid dependence. Disease modeling allows researchers to examine the course that the disease may take and to investigate policies to determine the effects they may have. Disease models can be used to model non-communicable diseases and have been used to study opioid use disorder. Many types of disease models exist with their own inherent benefits and drawbacks.
In this dissertation, we provide a scoping review of the disease models that have been used to study the opioid overdose epidemic. …
The Role Of Kinases Signaling In Organogenesis, Fatemeh Nasehi
The Role Of Kinases Signaling In Organogenesis, Fatemeh Nasehi
All Dissertations
Kinases are crucial regulators of organ development and differentiation. This thesis investi- gates the roles of TAK1, TGFbeta-Activate Kinase 1 (TAK1/Map3K7), and Akt3 kinases in skeletal, cardiac muscle, and cartilage. TAK1 is pivotal for the differentiation of various organ systems, including sinoatrial node and cartilage, and is responsible for phosphorylat- ing a diverse array of downstream kinases. We identified several novel proteins, including phospho-Akts, that are upregulated in response to TAK1 activation. We discovered severe Dilated Cardiomyopathy (DCM) and cartilage defects in Akt3 mutant mice. Although this mouse mutant has been studied for over two decades, we are the first …
Hardware-Oriented Protection And Acceleration For Machine Learning Application, Antian Wang
Hardware-Oriented Protection And Acceleration For Machine Learning Application, Antian Wang
All Dissertations
The security of Machine Learning (ML) grows along with the development of high-performance models and expanding application scenarios. Numerous users are benefiting from the convenience brought by transformative ML applications. In the meantime, various attackers are trying to find vulnerabilities within ML deployment service models, thereby undermining the performance of ML and jeopardizing stakeholders’ interests. The dissertation focuses on the two aspects of secure ML applications: acceleration and protection. Homomorphic Encryption (HE) emerges as a widely recognized security primitive suitable for the cloud computing service model, where the computation can be performed over ciphertext without decryption. However, evaluations in the …