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Articles 31 - 60 of 168417

Full-Text Articles in Engineering

Renewing The Paradigm: Simulating The Miso Region Electrical Grid Using Renewable Energy Generation With Implementation Of Long-Term Hydrogen Storage, Jackson C. Henningfield May 2021

Renewing The Paradigm: Simulating The Miso Region Electrical Grid Using Renewable Energy Generation With Implementation Of Long-Term Hydrogen Storage, Jackson C. Henningfield

Macalester Journal of Physics and Astronomy

The current electrical grid regime is not optimized to include renewable sources of power generation such as wind and solar. Electrical storage, as of now, is primarily established through the short-term generation and demand-meeting consumption leaving much of the grid susceptible to inefficiencies and power loss during natural events that leave grids out of commission. Delineating a new type of long-term storage, a hydrogen fuel cell, would ensure a reliable source of power to the masses regardless of the physical and climatic geography. The MISO region provides a perfect case study to introduce the ideas of diverse energy generation and ...


Identification Of Emergent Collaborative Behaviors In Multi-Agent Systems, Bryson Howell May 2021

Identification Of Emergent Collaborative Behaviors In Multi-Agent Systems, Bryson Howell

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

Identification of Emergent Collaborative Behaviors in Multi-Agent Systems

Bryson Howell

Multi-Agent Reinforcement Learning (MARL) has been used to allow groups of autonomous agents to perform complex cooperative tasks. When MARL methods such as the Multi-Agent Deep Deterministic Policy Gradient (MADDPG) algorithm [1] are used to train teams of agents in cooperative tasks, it has been observed that the actions of individual agents are significantly influenced by the actions of their teammates [2]. Additionally, prior work has shown that teams of agents trained independently of one another under identical conditions display a variety of behaviors [3]. Since these teams have been ...


Project Alien, Rebecca Mccallin, Madelyn Hoying, Alex Evans, Matthew Nestler, Karli Rae Sutton, Garett Craig, Lucia Secaia Del Cid, Alexander Guy, Rachel Fernandez, Amanda Trusiak, Paige Aley, Ingabire Gakwerere, Nina Dorfner, Maria Mosbacher, Mary Flavin, Selvin Hernandez, Audrey Steen, Benjamin Kazimer May 2021

Project Alien, Rebecca Mccallin, Madelyn Hoying, Alex Evans, Matthew Nestler, Karli Rae Sutton, Garett Craig, Lucia Secaia Del Cid, Alexander Guy, Rachel Fernandez, Amanda Trusiak, Paige Aley, Ingabire Gakwerere, Nina Dorfner, Maria Mosbacher, Mary Flavin, Selvin Hernandez, Audrey Steen, Benjamin Kazimer

Undergraduate Research and Scholarship Symposium

Project ALIEN is a comprehensive plan to send humans to Mars to look for life on the Martian surface while exploring the viability and adaptability of terrestrial microbes in Martian atmospheric conditions. ALIEN will use a ballistic capture trajectory to get to Mars and stay in aerostationary orbit for a 30-day surface mission, during which two surface crewmembers will perform a variety of experiments to achieve the mission’s goals of Martian microbial discovery within brines of the Gale Crater and terrestrial microbe adaptability and viability to Martian conditions. Experimentation is based on the presumption that Martian microbes are metabolically ...


Bioprinting Alginate Structures Using The Fresh Method, Amanda Pellegrino May 2021

Bioprinting Alginate Structures Using The Fresh Method, Amanda Pellegrino

Undergraduate Research and Scholarship Symposium

Three-dimensional bioprinting is a tissue engineering and regenerative medicine technique that utilizes biomaterials to print clinically relevant scaffolds. These scaffolds are used for tissue repair and to treat disease, such as end-organ failure. The main problem with 3D bioprinting is its inability to print soft biomaterials, which collapse due to gravitational forces. In addition, the materials that can be used do not mimic native tissue’s mechanical properties and texture. To combat this, Dr Feinberg’s laboratory at Carnegie Mellon University developed the freeform reversible embedding of suspended hydrogels (FRESH) method. The FRESH method allows for soft biomaterials to be ...


Developing A Multimedia Interface For Electrical Biosignal Interpretation, Christopher Cox May 2021

Developing A Multimedia Interface For Electrical Biosignal Interpretation, Christopher Cox

Undergraduate Research and Scholarship Symposium

In the last ten years, a great deal of interest has been generated around the practice of using plants’ electrical signals to create sound or music. In order to render biosignals capable of producing sound electronically, some kind of interface is necessary that converts a plant’s natural electrical signals into data that a computer can understand. Existing commercial interfaces cost at minimum $3001,2 . Worse yet, two popular off-the-shelf interfaces conform their output signals to stereotypical human notions of what a plant might “sound like”. In this project we fabricated a simple but high-performance interface for less than $5 ...


Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook May 2021

Understanding The Effect Of Adaptive Mutations On The Three-Dimensional Structure Of Rna, Justin Cook

Undergraduate Research and Scholarship Symposium

Single-nucleotide polymorphisms (SNPs) are variations in the genome where one base pair can differ between individuals.1 SNPs occur throughout the genome and can correlate to a disease-state if they occur in a functional region of DNA.1According to the central dogma of molecular biology, any variation in the DNA sequence will have a direct effect on the RNA sequence and will potentially alter the identity or conformation of a protein product. A single RNA molecule, due to intramolecular base pairing, can acquire a plethora of 3-D conformations that are described by its structural ensemble. One SNP, rs12477830, which ...


Effect Of Galvanic Corrosion On Crack Propagation Of Cold Expanded Holes In Aa2024-T3, Ken Shishino May 2021

Effect Of Galvanic Corrosion On Crack Propagation Of Cold Expanded Holes In Aa2024-T3, Ken Shishino

PhD Dissertations and Master's Theses

A search for the balance between weight reduction and durability of a structure has always been a popular topic within the aerospace industry. Among numerous researches to improve a structure’s fatigue life, processes on mechanically fastened joints have been a topic of focus as it is naturally a discontinuity in the material leading to a local stress concentration under loading. Cold expansion is a well-known technique with a wide range of applications in both new and repaired structures. The benefits include the extension of fatigue life and a delay in crack growth without addition of weight. However, localized galvanic ...


International Analysis On The Traffic Impact Of The Covid-19 Pandemic, Fanny Margaretha Kristiansson May 2021

International Analysis On The Traffic Impact Of The Covid-19 Pandemic, Fanny Margaretha Kristiansson

PhD Dissertations and Master's Theses

The purpose of this research was to assess, compare, and contrast the impact of COVID-19 activity restrictions on road-based transportation activity in regions of the US, Sweden, and China from January 1st to December 31st, 2020. Roadway traffic volumes were used to relate the progression of reported COVID-19 cases and government directives for social separation in three countries with diverse governmental responses.

Among the contributions of this paper was the illustration of the timeline and level of public responses to closures, lockdowns, and reopening as represented through rapid traffic decreases and increases. Traffic was greatly impacted, showing that the pandemic ...


Designing And Testing Of A System For Aerosolization And Recovery Of Viable Porcine Reproductive And Respiratory Syndrome Virus (Prrsv): Theoretical And Engineering Considerations, Peiyang Li, Jacek A. Koziel, Jeffrey J. Zimmerman, Steven J. Hoff, Jianqiang Zhang, Ting-Yu Cheng, Wannarat Yim-Im, Myeongseong Lee, Baitong Chen, William S. Jenks May 2021

Designing And Testing Of A System For Aerosolization And Recovery Of Viable Porcine Reproductive And Respiratory Syndrome Virus (Prrsv): Theoretical And Engineering Considerations, Peiyang Li, Jacek A. Koziel, Jeffrey J. Zimmerman, Steven J. Hoff, Jianqiang Zhang, Ting-Yu Cheng, Wannarat Yim-Im, Myeongseong Lee, Baitong Chen, William S. Jenks

Agricultural and Biosystems Engineering Publications

Porcine reproductive and respiratory syndrome virus (PRRSV) infections cause significant economic losses to swine producers every year. Aerosols containing infectious PRRSV are an important route of transmission, and proper treatment of air could mitigate the airborne spread of the virus within and between barns. Previous bioaerosol studies focused on the microbiology of PRRSV aerosols; thus, the current study addressed the engineering aspects of virus aerosolization and collection. Specific objectives were to (1) build and test a virus aerosolization system, (2) achieve a uniform and repeatable aerosol generation and collection throughout all replicates, (3) identify and minimize sources of variation, and ...


Prediction Of Stocks And Stock Price Using Artificial Intelligence : A Bibliometric Study Using Scopus Database, Priyanka Tupe-Waghmare, Priyanka Tupe-Waghmare May 2021

Prediction Of Stocks And Stock Price Using Artificial Intelligence : A Bibliometric Study Using Scopus Database, Priyanka Tupe-Waghmare, Priyanka Tupe-Waghmare

Library Philosophy and Practice (e-journal)

Prediction of stocks and the prices of the stock is one of the most crucial points of discussion amongst the researchers and analysts in the financial domain to date. Every stakeholder and most importantly the investor desires to earn higher profit for his investment in the market and try to use several different strategies to invest their money. There are numerous methods to predict and analyse the movement of the stock prices. They are broadly divided into – statistical and artificial intelligence-based methods. Artificial intelligence is used to predict the futuristic prices of stocks and use wide range of algorithms like ...


Exploration Of The Sludge Biodiesel Pathway, Zachary Christman May 2021

Exploration Of The Sludge Biodiesel Pathway, Zachary Christman

Theses, Dissertations, and Student Research in Agronomy and Horticulture

Wastewater sludge is an overlooked source of fat, oil, and grease (FOG) that could be converted into biodiesel. The United States produces about 8 million tons of sludge per year. The disposal cost for this amount of sludge is about 2 billion dollars. The widespread availability and low cost of sludge compared to other biodiesel raw materials make it an economical choice for a renewable fuel. Using sludge as a raw material can produce 25 to 30 mg per gram of fatty acid methyl ester (FAME); the main component of biodiesel. Sludge biodiesel has the potential of transforming a portion ...


Device Development For Long-Term Systemic Oral Biologic Drug Delivery, Benjamin Wankum May 2021

Device Development For Long-Term Systemic Oral Biologic Drug Delivery, Benjamin Wankum

Mechanical (and Materials) Engineering -- Dissertations, Theses, and Student Research

A biologic drug is a drug that is produced by a living organism. Biologic drugs are used to treat various medical conditions such as arthritis, diabetes, or certain forms of cancers due to their high potency and high selectivity of action. Drawbacks of biologics include their poor stability in the gastrointestinal tract and their poor absorption. In effect, this gives the drugs very low bioavailability and short therapeutic half-lives. To combat these obstacles, current delivery methods include subcutaneous injections at home or intravenous or intramuscular injections in a medical facility.

The overall scientific goal of the research was to utilize ...


Pharyngeal Constriction As A Cause For Late Acquisition And Speech Sound Disorders Of Rhotic Sounds In English, Spanish, And French, Connor Mahon May 2021

Pharyngeal Constriction As A Cause For Late Acquisition And Speech Sound Disorders Of Rhotic Sounds In English, Spanish, And French, Connor Mahon

The Downtown Review

This paper attempts to explain why rhotic sounds are cross-linguistically late developing among the sound inventory of children. Included is a summary of the current literature regarding classification of rhotic sounds, an examination of the articulatory movement of the tongue root, and an overview of the clinical implications on the field of speech-language pathology. The evidence presented supports the hypothesis that pharyngeal constriction is characteristic of rhotic sounds in many languages, and that it is related to the relative late acquisition and higher rate of speech sound disorders, as seen in English, Spanish, and French.


Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai May 2021

Collaborative City Digital Twin For The Covid-19 Pandemic: A Federated Learning Solution, Junjie Pang, Yan Huang, Zhenzhen Xie, Jianbo Li, Zhipeng Cai

Tsinghua Science and Technology

The novel coronavirus, COVID-19, has caused a crisis that affects all segments of the population. As the knowledge and understanding of COVID-19 evolve, an appropriate response plan for this pandemic is considered one of the most effective methods for controlling the spread of the virus. Recent studies indicate that a city Digital Twin (DT) is beneficial for tackling this health crisis, because it can construct a virtual replica to simulate factors, such as climate conditions, response policies, and people’s trajectories, to help plan efficient and inclusive decisions. However, a city DTsystem relies on long-term and high-quality data collection to ...


A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li May 2021

A Data-Driven Clustering Recommendation Method For Single-Cell Rna-Sequencing Data, Yu Tian, Ruiqing Zheng, Zhenlan Liang, Suning Li, Fang-Xiang Wu, Min Li

Tsinghua Science and Technology

Recently, the emergence of single-cell RNA-sequencing (scRNA-seq) technology makes it possible to solve biological problems at the single-cell resolution. One of the critical steps in cellular heterogeneity analysis is the cell type identification. Diverse scRNA-seq clustering methods have been proposed to partition cells into clusters. Among all the methods, hierarchical clustering and spectral clustering are the most popular approaches in the downstream clustering analysis with different preprocessing strategies such as similarity learning, dropout imputation, and dimensionality reduction. In this study, we carry out a comprehensive analysis by combining different strategies with these two categories of clustering methods on scRNA-seq datasets ...


A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang May 2021

A Computer-Aided System For Ocular Myasthenia Gravis Diagnosis, Guanjie Liu, Yan Wei, Yunshen Xie, Jianqiang Li, Liyan Qiao, Ji-Jiang Yang

Tsinghua Science and Technology

The current mode of clinical aided diagnosis of Ocular Myasthenia Gravis (OMG) is time-consuming and laborious, and it lacks quantitative standards. An aided diagnostic system for OMG is proposed to solve this problem. The values calculated by the system include three clinical indicators: eyelid distance, sclera distance, and palpebra superior fatigability test time. For the first two indicators, the semantic segmentation method was used to extract the pathological features of the patient’s eye image and a semantic segmentation model was constructed. The patient eye image was divided into three regions: iris, sclera, and background. The indicators were calculated based ...


Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang May 2021

Robust Segmentation Method For Noisy Images Based On An Unsupervised Denosing Filter, Ling Zhang, Jianchao Liu, Fangxing Shang, Gang Li, Juming Zhao, Yueqin Zhang

Tsinghua Science and Technology

Level-set-based image segmentation has been widely used in unsupervised segmentation tasks. Researchers have recently alleviated the influence of image noise on segmentation results by introducing global or local statistics into existing models. Most existing methods are based on the assumption that the distribution of image noise is known or observable. However, real-time images do not meet this assumption. To bridge this gap, we propose a novel level-set-based segmentation method with an unsupervised denoising mechanism. First, a denoising filter is acquired under the unsupervised learning paradigm. Second, the denoising filter is integrated into the level-set framework to separate noise from the ...


Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han May 2021

Efficient Scheduling Mapping Algorithm For Row Parallel Coarse-Grained Reconfigurable Architecture, Naijin Chen, Zhen Wang, Ruixiang He, Jianhui Jiang, Fei Cheng, Chenghao Han

Tsinghua Science and Technology

Row Parallel Coarse-Grained Reconfigurable Architecture (RPCGRA) has the advantages of maximum parallelism and programmable flexibility. Designing an efficient algorithm to map the diverse applications onto RPCGRA is difficult due to a number of RPCGRA hardware constraints. To solve this problem, the nodes of the data flow graph must be partitioned and scheduled onto the RPCGRA. In this paper, we present a Depth-First Greedy Mapping (DFGM) algorithm that simultaneously considers the communication costs and the use times of the Reconfigurable Cell Array (RCA). Compared with level breadth mapping, the performance of DFGM is better. The percentage of maximum improvement in the ...


Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu May 2021

Game Theoretical Approach For Non-Overlapping Community Detection, Baohua Sun, Richard Al-Bayaty, Qiuyuan Huang, Dapeng Wu

Tsinghua Science and Technology

Graph clustering, i.e., partitioning nodes or data points into non-overlapping clusters, can be beneficial in a large varieties of computer vision and machine learning applications. However, main graph clustering schemes, such as spectral clustering, cannot be applied to a large network due to prohibitive computational complexity required. While there exist methods applicable to large networks, these methods do not offer convincing comparisons against known ground truth. For the first time, this work conducts clustering algorithm performance evaluations on large networks (consisting of one million nodes) with ground truth information. Ideas and concepts from game theory are applied towards graph ...


Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu May 2021

Inertial Motion Tracking On Mobile And Wearable Devices: Recent Advancements And Challenges, Zhipeng Song, Zhichao Cao, Zhenjiang Li, Jiliang Wang, Yunhao Liu

Tsinghua Science and Technology

Motion tracking via Inertial Measurement Units (IMUs) on mobile and wearable devices has attracted significant interest in recent years. High-accuracy IMU-tracking can be applied in various applications, such as indoor navigation, gesture recognition, text input, etc. Many efforts have been devoted to improving IMU-based motion tracking in the last two decades, from early calibration techniques on ships or airplanes, to recent arm motion models used on wearable smart devices. In this paper, we present a comprehensive survey on IMU-tracking techniques on mobile and wearable devices. We also reveal the key challenges in IMU-based motion tracking on mobile and wearable devices ...


Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang May 2021

Deep Reinforcement Learning Based Mobile Robot Navigation: A Review, Kai Zhu, Tao Zhang

Tsinghua Science and Technology

Navigation is a fundamental problem of mobile robots, for which Deep Reinforcement Learning (DRL) has received significant attention because of its strong representation and experience learning abilities. There is a growing trend of applying DRL to mobile robot navigation. In this paper, we review DRL methods and DRL-based navigation frameworks. Then we systematically compare and analyze the relationship and differences between four typical application scenarios: local obstacle avoidance, indoor navigation, multi-robot navigation, and social navigation. Next, we describe the development of DRL-based navigation. Last, we discuss the challenges and some possible solutions regarding DRL-based navigation.


Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang May 2021

Decomposition-Based Multi-Objective Optimization For Energy-Aware Distributed Hybrid Flow Shop Scheduling With Multiprocessor Tasks, Enda Jiang, Ling Wang, Jingjing Wang

Tsinghua Science and Technology

This paper addresses the Energy-Aware Distributed Hybrid Flow Shop Scheduling Problem with Multiprocessor Tasks (EADHFSPMT) by considering two objectives simultaneously, i.e., makespan and total energy consumption. It consists of three sub-problems, i.e., job assignment between factories, job sequence in each factory, and machine allocation for each job. We present a mixed inter linear programming model and propose a Novel Multi-Objective Evolutionary Algorithm based on Decomposition (NMOEA/D). We specially design a decoding scheme according to the characteristics of the EADHFSPMT. To initialize a population with certain diversity, four different rules are utilized. Moreover, a cooperative search is designed ...


Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng May 2021

Towards "General Purpose" Brain-Inspired Computing System, Youhui Zhang, Peng Qu, Weimin Zheng

Tsinghua Science and Technology

Brain-inspired computing refers to computational models, methods, and systems, that are mainly inspired by the processing mode or structure of brain. A recent study proposed the concept of "neuromorphic completeness" and the corresponding system hierarchy, which is helpful to determine the capability boundary of brain-inspired computing system and to judge whether hardware and software of brain-inspired computing are compatible with each other. As a position paper, this article analyzes the existing brain-inspired chips’ design characteristics and the current so-called "general purpose" application development frameworks for brain-inspired computing, as well as introduces the background and the potential of this proposal. Further ...


Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang May 2021

Distributed Scheduling Problems In Intelligent Manufacturing Systems, Yaping Fu, Yushuang Hou, Zifan Wang, Xinwei Wu, Kaizhou Gao, Ling Wang

Tsinghua Science and Technology

Currently, manufacturing enterprises face increasingly fierce market competition due to the various demands of customers and the rapid development of economic globalization. Hence, they have to extend their production mode into distributed environments and establish multiple factories in various geographical locations. Nowadays, distributed manufacturing systems have been widely adopted in industrial production processes. In recent years, many studies have been done on the modeling and optimization of distributed scheduling problems. This work provides a literature review on distributed scheduling problems in intelligent manufacturing systems. By summarizing and evaluating existing studies on distributed scheduling problems, we analyze the achievements and current ...


Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou May 2021

Multi-Agent Modeling And Simulation In The Ai Age, Wenhui Fan, Peiyu Chen, Daiming Shi, Xudong Guo, Li Kou

Tsinghua Science and Technology

With the rapid development of artificial intelligence (AI) technology and its successful application in various fields, modeling and simulation technology, especially multi-agent modeling and simulation (MAMS), of complex systems has rapidly advanced. In this study, we first describe the concept, technical advantages, research steps, and research status of MAMS. Then we review the development status of the hybrid modeling and simulation combining multi-agent and system dynamics, the modeling and simulation of multi-agent reinforcement learning, and the modeling and simulation of large-scale multi-agent. Lastly, we introduce existing MAMS platforms and their comparative studies. This work summarizes the current research situation of ...


Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang May 2021

Convergence Of Broadband And Broadcast/Multicast In Maritime Information Networks, Jun Du, Jian Song, Yong Ren, Jintao Wang

Tsinghua Science and Technology

Recently, the fifth-generation (5G) of wireless networks mainly focuses on the terrestrial applications. However, the well-developed emerging technologies in 5G are hardly applied to the maritime communications, resulting from the lack of communication infrastructure deployed on the vast ocean, as well as different characteristics of wireless propagation environment over the sea and maritime user distribution. To satisfy the expected plethora of broadband communications and multimedia applications on the ocean, a brand-new maritime information network with a comprehensive coverage capacity in terms of all-hour, all-weather, and all-sea-area has been expected as a revolutionary paradigm to extend the terrestrial capacity of enhanced ...


Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang May 2021

Ambipolar Transport Compact Models For Two-Dimensional Materials Based Field-Effect Transistors, Zhaoyi Yan, Guangyang Gou, Jie Ren, Fan Wu, Yang Shen, He Tian, Yi Yang

Tsinghua Science and Technology

Three main ambipolar compact models for Two-Dimensional (2D) materials based Field-Effect Transistors (2D-FETs) are reviewed: (1) Landauer model, (2) 2D Pao-Sah model, and (3) virtual Source Emission-Diffusion (VSED) model. For the Landauer model, the Gauss quadrature method is applied, and it summarizes all kinds of variants, exhibiting its state-of-art. For the 2D Pao-Sah model, the aspects of its theoretical fundamentals are rederived, and the electrostatic potentials of electrons and holes are clarified. A brief development history is compiled for the VSED model. In summary, the Landauer model is naturally appropriate for the ballistic transport of short channels, and the 2D ...


Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen May 2021

Design And Tool Flow Of A Reconfigurable Asynchronous Neural Network Accelerator, Jilin Zhang, Hui Wu, Weijia Chen, Shaojun Wei, Hong Chen

Tsinghua Science and Technology

Convolutional Neural Networks (CNNs) are widely used in computer vision, natural language processing, and so on, which generally require low power and high efficiency in real applications. Thus, energy efficiency has become a critical indicator of CNN accelerators. Considering that asynchronous circuits have the advantages of low power consumption, high speed, and no clock distribution problems, we design and implement an energy-efficient asynchronous CNN accelerator with a 65 nm Complementary Metal Oxide Semiconductor (CMOS) process. Given the absence of a commercial design tool flow for asynchronous circuits, we develop a novel design flow to implement Click-based asynchronous bundled data circuits ...


Assessment Of Cardiorespiratory Interactions During Life Threatening Events In Preterm Infants Using Point Process And Bivariate Algorithms, Mohammed T. Alenazi May 2021

Assessment Of Cardiorespiratory Interactions During Life Threatening Events In Preterm Infants Using Point Process And Bivariate Algorithms, Mohammed T. Alenazi

Electrical Engineering Theses

Cardiorespiratory interactions considered as an important indicator of neurodevelopment of preterm infants. The strength of cardiorespiratory interactions are presumed to be weak and rapidly fluctuating. The current signal processing algorithms are insufficient to capture such time varying weak interactions. In addition, detection of these interactions becomes difficult during life threatening events due to lack of information available due to apnea (absence of output from respiratory system) and the transient temporal destabilization of cardiac system due to bradycardia. To detect the cardiorespiratory interactions, a point process algorithm of cardiac system with respiration as covariates is proposed. The bivariate model is embedded ...


Water Exchange Rate Across The Blood-Brain Barrier Is Associated With Csf Amyloid-Β 42 In Healthy Older Adults, Brian T. Gold, Xingfeng Shao, Tiffany L. Sudduth, Gregory A. Jicha, Donna M. Wilcock, Elayna R. Seago, Danny J. J. Wang May 2021

Water Exchange Rate Across The Blood-Brain Barrier Is Associated With Csf Amyloid-Β 42 In Healthy Older Adults, Brian T. Gold, Xingfeng Shao, Tiffany L. Sudduth, Gregory A. Jicha, Donna M. Wilcock, Elayna R. Seago, Danny J. J. Wang

Sanders-Brown Center on Aging Faculty Publications

INTRODUCTION: We tested if water exchange across the blood-brain barrier (BBB), estimated with a noninvasive magnetic resonance imaging (MRI) technique, is associated with cerebrospinal fluid (CSF) biomarkers of Alzheimer's disease (AD) and neuropsychological function.

METHODS: Forty cognitively normal older adults (67–86 years old) were scanned with diffusion‐prepared, arterial spin labeling (DP‐ASL), which estimates water exchange rate across the BBB (kw). Participants also underwent CSF draw and neuropsychological testing. Multiple linear regression models were run with kw as a predictor of CSF concentrations and neuropsychological scores.

RESULTS: In multiple brain regions, BBB kw was positively associated ...