Open Access. Powered by Scholars. Published by Universities.®
- Discipline
-
- Engineering (17307)
- Computer Engineering (13035)
- Artificial Intelligence and Robotics (11148)
- Databases and Information Systems (7250)
- Numerical Analysis and Scientific Computing (6662)
-
- Electrical and Computer Engineering (5273)
- Social and Behavioral Sciences (4827)
- Operations Research, Systems Engineering and Industrial Engineering (4777)
- Information Security (4669)
- Software Engineering (4315)
- Systems Science (3919)
- Business (2514)
- Mathematics (2386)
- Graphics and Human Computer Interfaces (2371)
- Theory and Algorithms (2153)
- Education (2099)
- Life Sciences (2075)
- Programming Languages and Compilers (1844)
- Medicine and Health Sciences (1803)
- Other Computer Sciences (1793)
- OS and Networks (1760)
- Arts and Humanities (1456)
- Communication (1446)
- Law (1175)
- Data Science (1157)
- Applied Mathematics (1134)
- Statistics and Probability (1061)
- Bioinformatics (986)
- Institution
-
- Singapore Management University (9003)
- China Simulation Federation (3880)
- TÜBİTAK (3106)
- Wright State University (2694)
- Purdue University (2077)
-
- Old Dominion University (1996)
- Missouri University of Science and Technology (1938)
- University of Nebraska - Lincoln (1739)
- Edith Cowan University (1285)
- Air Force Institute of Technology (1277)
- University of Texas at El Paso (1174)
- Kennesaw State University (1161)
- Dartmouth College (1104)
- San Jose State University (1053)
- City University of New York (CUNY) (956)
- Embry-Riddle Aeronautical University (950)
- Washington University in St. Louis (830)
- Brigham Young University (823)
- Technological University Dublin (816)
- California Polytechnic State University, San Luis Obispo (788)
- Zayed University (677)
- University of Texas at Arlington (666)
- University for Business and Technology in Kosovo (637)
- Portland State University (625)
- Chulalongkorn University (618)
- Nova Southeastern University (577)
- New Jersey Institute of Technology (571)
- Syracuse University (532)
- University of Nebraska at Omaha (497)
- University of Central Florida (490)
- Keyword
-
- Machine learning (1665)
- Artificial intelligence (1020)
- Deep learning (1003)
- Machine Learning (761)
- Computer Science (712)
-
- Security (648)
- Cybersecurity (558)
- Artificial Intelligence (484)
- Deep Learning (434)
- Computer science (412)
- Privacy (410)
- Simulation (391)
- Technical Reports (390)
- UTEP Computer Science Department (389)
- Classification (375)
- Algorithms (357)
- Optimization (352)
- Computer vision (349)
- Neural networks (345)
- Data mining (337)
- AI (301)
- Natural language processing (293)
- Department of Computer Science and Engineering (291)
- Engineering (269)
- Education (268)
- Reinforcement learning (259)
- Blockchain (255)
- Cloud computing (255)
- College for Professional Studies (253)
- Software engineering (252)
- Publication Year
- Publication
-
- Research Collection School Of Computing and Information Systems (8458)
- Journal of System Simulation (3880)
- Turkish Journal of Electrical Engineering and Computer Sciences (3106)
- Theses and Dissertations (2733)
- Department of Computer Science Technical Reports (1721)
-
- Computer Science & Engineering Syllabi (1312)
- Computer Science Faculty Publications (928)
- Computer Science Faculty Research & Creative Works (919)
- Departmental Technical Reports (CS) (914)
- Master's Projects (859)
- Computer Science Technical Reports (772)
- The R Journal (708)
- All Computer Science and Engineering Research (683)
- All Works (675)
- Faculty Publications (663)
- C-Day Computing Showcase (653)
- Chulalongkorn University Theses and Dissertations (Chula ETD) (618)
- Dissertations (568)
- Electronic Theses and Dissertations (567)
- Kno.e.sis Publications (542)
- Journal of Digital Forensics, Security and Law (536)
- CCAC Theses and Dissertations (512)
- Walden Dissertations and Doctoral Studies (469)
- Computer Science Faculty Publications and Presentations (404)
- Theses (403)
- USF Tampa Graduate Theses and Dissertations (378)
- Neutrosophic Systems with Applications (375)
- Computer Science and Engineering Theses - Archive (365)
- Computer Science: Faculty Publications (364)
- Browse all Theses and Dissertations (359)
- Publication Type
Articles 17791 - 17820 of 63037
Full-Text Articles in Computer Sciences
Research On Digital Protection System Of Intangible Cultural Heritage Based On Mobile Augmented Reality Technology, Shouming Hou, Ge Qian, Yanyan Liu
Research On Digital Protection System Of Intangible Cultural Heritage Based On Mobile Augmented Reality Technology, Shouming Hou, Ge Qian, Yanyan Liu
Journal of System Simulation
Abstract: Aiming at the problem of the single form and poor interaction of intangible cultural heritage protection, a non-heritage digital online display system is designed and implemented based on mobile augmented reality technology. Taking clay sculpture non-heritage protection as an example, the main functional modules of the system cloud and mobile terminal are designed. Based on a combination of 3D scanning and iterative mesh simplification, a fast modeling method is proposed. ORB-FV and optical flow tracking algorithm are used for online recognition and tracking registration of images. The system is developed based on Unity3D. The test results show that, …
Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li
Fault Diagnosis Of Mechanical Equipment Based On Ga-Svr With Missing Data In Small Samples, Jingjing Wei, Qinming Liu, Chunming Ye, Guanlin Li
Journal of System Simulation
Abstract: In view of the equipment fault diagnosis with small and missing sample data, a method of missing data filling based on support vector regression optimized by genetic algorithm is proposed to improve the accuracy of equipment fault diagnosis. The support vector regression optimized by genetic algorithm was trained by other data values of missing data, and univariate prediction results were obtained. The training set was reconstructed through correlation analysis, so as to obtain the multivariate prediction results. Dynamic weights were established to combine univariate prediction results and multivariate prediction results to fill in the missing data. The …
Active Learning Intelligent Soft Sensor Based On Probability Selection, Xuezhi Dai, Weili Xiong
Active Learning Intelligent Soft Sensor Based On Probability Selection, Xuezhi Dai, Weili Xiong
Journal of System Simulation
Abstract: Aiming at lack of tag samples and high cost of sampling tags in complex industrial processes, an active learning algorithm based on probability selection is proposed. Firstly, unlabeled samples are performed subspace integration by using the principal component analysis. Then, the information of unlabeled samples is evaluated by the uncertainty, which is calculated based on the out put of all sub learners. And the most valuable samples are selected to mark manually. Finally, the function of unlabeled samples and labeled samples are analyzed, and the termination conditions are designed by introducing the performance index of training set. Through simulations …
Virtual Training System For Spacecraft Maintenance Based On Desktop Virtual Reality, Shisong Wei, Zhengdong Zhou, Xuling Zhang, Mao Ling, Junshan Jia, Chuanle Liu
Virtual Training System For Spacecraft Maintenance Based On Desktop Virtual Reality, Shisong Wei, Zhengdong Zhou, Xuling Zhang, Mao Ling, Junshan Jia, Chuanle Liu
Journal of System Simulation
Abstract: In order to shorten the training period of aerospace maintenance personnel and improve their operation proficiency, a spacecraft maintenance simulation system based on the desktop virtual reality technology is designed and developed. It is superior to the head-mounted display, which is bulky, isolated from the real world, easy to make users dizzy and hard to be shared. The assembly management scheme based on XMind and SqlServer database is proposed to realize the visualization of assembly rule editing, which makes assembly and disassembly flexible and convenient.
Technical Characteristics Of Digital Twins And Application Prospects In The Field Of Flight Testing, Liu Yu, Xie Qiang
Technical Characteristics Of Digital Twins And Application Prospects In The Field Of Flight Testing, Liu Yu, Xie Qiang
Journal of System Simulation
Abstract: For the application of digital twins in flight tests, the connotation and technical characteristics of digital twins were studied and analyzed. Six flight test digital twins typical application scenarios, such as the requirements development and overall planning of flight test, the flight test mission designing, the integrated testing and modification of flight test, the flight test organization and implementation, the fast maintenance and support and the training of flight test engineers have been designed by mapping the behavior and performance of flight test objects. The synchronize updates, parallel validation and spiral evolution were achieved between the digital models …
Research On The Offset Of Elliptical Quiet Zone In Catr Of Multiple Feed, Liu Yong, Liwei Guo, Wangyang Song, Jiang Xing, Simin Li, Peng Lin
Research On The Offset Of Elliptical Quiet Zone In Catr Of Multiple Feed, Liu Yong, Liwei Guo, Wangyang Song, Jiang Xing, Simin Li, Peng Lin
Journal of System Simulation
Abstract: Electromagnetic target simulator based on CATR of the quiet zone movement,which adopt the multi-feed source CATR RF signal feeding by reflecting to get the quiet zone movement of simulated far field. It can be used in simulation of seekers in a multi-target mobile environment. The phase of the feeds of the 1×4 horn array is changed to realize the movement of the quiet zone in the CATR. The phase consistency of the millimeter wave quiet zone of the target simulation system determines the target simulation accuracy. The amplitude and phase characteristics of the array feeding with different beam …
Energy Management Of Marine Current Power Generation System Based On Fuzzy Logical Control, Jingang Han, Li Xu
Energy Management Of Marine Current Power Generation System Based On Fuzzy Logical Control, Jingang Han, Li Xu
Journal of System Simulation
Abstract: The fluctuation of marine current velocity leads to the fluctuation of power generation. The hybrid energy storage system composed of vanadium redox flow battery and super capacitor is used to improve the power quality and smooth the marine current power generation. With the research and commercialization of large scale power marine current power generation system, the capacity of energy storage system has been increasing. To reduce the rated capacity of super capacitor banks in energy storage system, an energy management strategy based on low-pass filter optimization algorithm of fuzzy control is proposed and the simulation model of 3 MW …
Development Of Semi-Physical Simulation Platform For Monitoring Municipal Solid Waste Incineration Process, Aijun Yan, Xia Heng, Xizhi Liu
Development Of Semi-Physical Simulation Platform For Monitoring Municipal Solid Waste Incineration Process, Aijun Yan, Xia Heng, Xizhi Liu
Journal of System Simulation
Abstract: In order to research and test the modeling, control and optimization of MSW (Municipal Solid Waste) incineration process, a semi-physical simulation platform with three-layer structure by combining the physical control system with the virtual object is developed. The physical control system of the platform is composed of an intelligent control optimization layer and basic control layer; and the virtual object layer includes simulated instrument, actuator and incineration process model. The software for man-machine interface with OPC (Object Linking and Embedding (OLE) for Process Control), equipment/parameter monitoring, and incineration process model are developed. The functions of intelligent control optimization layer …
Development Paths Of New Energy Vehicles Incorporating Co2 Emissions Trading Scheme, Wenxiang Li, Li Ye, Jieshuang Dong, Yiming Li
Development Paths Of New Energy Vehicles Incorporating Co2 Emissions Trading Scheme, Wenxiang Li, Li Ye, Jieshuang Dong, Yiming Li
Journal of System Simulation
Abstract: New energy vehicles in China have entered the “post-subsidy era”, and it is urgent to explore and establish a long-term mechanism for market-oriented development. The CO2 emission trading scheme for road transport (ETS-RT) is introduced to replace financial subsidies, forming a market-oriented incentive and punishment mechanism. Therefore, a market mechanism is established where internal combustion engine vehicles feed new energy vehicles. A causal loop diagram of system dynamics was used to analyze the key policy parameters of the ETS-RT that affect the development of new energy vehicles. Then a multi-agents-based model of ETS-RT is established to simulate the …
Review On Key Technologies Of Industrial Control System Security Simulation, Bailing Wang, Hongri Liu, Yaofang Zhang, Sicai Lü, Zibo Wang, Qimeng Wang
Review On Key Technologies Of Industrial Control System Security Simulation, Bailing Wang, Hongri Liu, Yaofang Zhang, Sicai Lü, Zibo Wang, Qimeng Wang
Journal of System Simulation
Abstract: In order to cope with the increasingly serious industrial internet security problems, simulation is viewed as a critical backboned technology for drilling of network attack and defense, tracking back and analyzing of security incidents, as well as validating of pre-research technology. On the basis of summarizing the studies of three types of typical industrial control system security simulation platform, the key technologies used in industrial control cyber range and industrial control honeynets are highlighted. Technologies are summarized, such as the virtualization technology of industrial control network and industrial control components, the construction technology of industrial control target field dominated …
Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski
Universal Biological Motions For Educational Robot Theatre And Games, Rajesh Venkatachalapathy, Martin Zwick, Adam Slowik, Kai Brooks, Mikhail Mayers, Roman Minko, Tyler Hull, Bliss Brass, Marek Perkowski
Complex Systems Faculty Publications and Presentations
Paper presents a concept that is new to robotics education and social robotics. It is based on theatrical games, in motions for social robots and animatronic robots. Presented here motion model is based on Drift Differential Model from biology and Fokker-Planck equations. This model is used in various areas of science to describe many types of motion. The model was successfully verified on various simulated mobile robots and a motion game of three robots called "Mouse and Cheese."
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Analyzing Public Sentiment On Covid-19 Pandemic, Pradeepika Gedupudi
Master's Projects
Sentiment analysis is a method of understanding the user sentiment expressed in the form of text. Social media is the best place to capture the public's opinion regarding how they feel about current events. The Corona Virus Disease-2019 (COVID-19) is one of the worst pandemics we have experienced so far. An important observation is that this pandemic has not only affected the public's physical health but also took a toll on their mental health. Reddit is a social news discussion site where people discuss topics around current affairs in smaller groups called subreddits. The project's primary focus is to build …
Improving The Security And Performance Of Web Applications Running On The Distributed Ipfs, Vu Le
Improving The Security And Performance Of Web Applications Running On The Distributed Ipfs, Vu Le
Master's Projects
While cloud computing is gaining widespread adoption these days, some challenges are emerging around security, performance, and reliability of centralized cloud resources. Decentralized services are introduced as an effective way to overcome the limitations of cloud services. Blockchain technology with its associated decentralization is used to develop decentralized application platforms. The interplanetary file system (IPFS) is built on top of a distributed system consisting of a group of nodes that shares the data and also takes advantage of blockchain to permanently store the data. The IPFS is very useful in transferring data between people. This project focuses on blockchain technology, …
Classification And Analysis Of Android Malware Images Using Feature Fusion Technique, Jaiteg Singh, Deepak Thakur, Tanya Gera, Babar Shah, Tamer Abuhmed, Farman Ali
Classification And Analysis Of Android Malware Images Using Feature Fusion Technique, Jaiteg Singh, Deepak Thakur, Tanya Gera, Babar Shah, Tamer Abuhmed, Farman Ali
All Works
The super packed functionalities and artificial intelligence (AI)-powered applications have made the Android operating system a big player in the market. Android smartphones have become an integral part of life and users are reliant on their smart devices for making calls, sending text messages, navigation, games, and financial transactions to name a few. This evolution of the smartphone community has opened new horizons for malware developers. As malware variants are growing at a tremendous rate every year, there is an urgent need to combat against stealth malware techniques. This paper proposes a visualization and machine learning-based framework for classifying Android …
Improving Facial Emotion Recognition With Image Processing And Deep Learning, Ksheeraj Sai Vepuri
Improving Facial Emotion Recognition With Image Processing And Deep Learning, Ksheeraj Sai Vepuri
Master's Projects
Humans often use facial expressions along with words in order to communicate effectively. There has been extensive study of how we can classify facial emotion with computer vision methodologies. These have had varying levels of success given challenges and the limitations of databases, such as static data or facial capture in non-real environments. Given this, we believe that new preprocessing techniques are required to improve the accuracy of facial detection models. In this paper, we propose a new yet simple method for facial expression recognition that enhances accuracy. We conducted our experiments on the FER-2013 dataset that contains static facial …
Task Classification During Visual Search With Deep Learning Neural Networks And Machine Learning Methods, Siddartha Thentu
Task Classification During Visual Search With Deep Learning Neural Networks And Machine Learning Methods, Siddartha Thentu
Master's Projects
Studies have shown the possibility to classify user tasks from eye-movement data. We present a new way to determine the optimal model for different visual attention tasks using data that includes two types of visual search tasks, a visual exploration task, a blank screen task, and a task where a user needs to fixate at the center of any scene. We used deep learning and SVM models on RGB images generated from fixation scan paths from these tasks. We also used AdaBoost on filtered eye movement data as a baseline. Our study shows that deep learning gives the best accuracy …
Who Uses Multi-Factor Authentication?, Leah Roberts
Who Uses Multi-Factor Authentication?, Leah Roberts
Undergraduate Honors Theses
A sample of 47 BYU students were recruited to participate in this study to determine who was using Multi-factor Authentication (MFA) on their online accounts. This study determined that there were many different factors that separated those who used MFA and those who did not. Some of those factors included: time spent on the internet each day, gender, the website itself, and personal privacy behaviors.
Machine Learning Models And Big Data Tools For Evaluating Kidney Acceptance, Lirim Ashiku, Md Al-Amin, Sanjay Kumar Madria, Cihan H. Dagli
Machine Learning Models And Big Data Tools For Evaluating Kidney Acceptance, Lirim Ashiku, Md Al-Amin, Sanjay Kumar Madria, Cihan H. Dagli
Computer Science Faculty Research & Creative Works
The rise of on-demand healthcare and the unprecedented growth of electronic health records has given rise to big data opportunities and data analysis using machine learning. The massive and disparate data management using conventional databases is incredibly challenging and expensive to manage. It often requires specialized analytical tools for developing advanced data-driven capabilities and performing data analytics. This paper explores the capability of an open-source framework 'Apache Spark' capable of processing large amounts of data on clusters of nodes to analyze Big data and integrate technologies to provide decision support systems in healthcare settings. Next, we propose machine learning models …
Adaptive Network Slicing In Fog Ran For Iot With Heterogeneous Latency And Computing Requirements: A Deep Reinforcement Learning Approach, Almuthanna Nassar
Adaptive Network Slicing In Fog Ran For Iot With Heterogeneous Latency And Computing Requirements: A Deep Reinforcement Learning Approach, Almuthanna Nassar
USF Tampa Graduate Theses and Dissertations
In view of the recent advances in Internet of Things (IoT) devices and the emerging new breed of smart city applications and intelligent vehicular systems driven by artificial intelligence, fog radio access network (F-RAN) has been recently introduced for the next generation wireless communications. The capability of F-RAN has emerged to overcome the latency limitations of cloud-RAN (C-RAN) and assure the quality-of-service (QoS) requirements of the ultra-reliable-low-latency-communication (URLLC) for IoT applications. To this end, fog nodes (FNs) are equipped with computing, signal processing and storage capabilities to extend the inherent operations and services of the cloud to the edge. However, …
Optimization And Machine Learning Methods For Solving Combinatorial Problems In Urban Transportation, Aigerim Bogyrbayeva
Optimization And Machine Learning Methods For Solving Combinatorial Problems In Urban Transportation, Aigerim Bogyrbayeva
USF Tampa Graduate Theses and Dissertations
This dissertation investigates three applications of emerging technologies for urban trans- portation. In the first chapter, we design a new market for fractional ownership of au- tonomous vehicles (AVs), in which an AV is co-leased by a group of individuals. We present a practical iterative auction based on the combinatorial clock auction to match the interested customers together and determine their payments. In designing such an auction, we con- sider continuous-time items (time slots) which are defined by bidders, and naturally exploit driverless mobility of AVs to form co-leasing groups. To relieve the computational burdens of both bidders and the …
Characterizing And Optimizing Asynchronous Event-Driven Architecture For Modern Cloud Systems, Shungeng Zhang
Characterizing And Optimizing Asynchronous Event-Driven Architecture For Modern Cloud Systems, Shungeng Zhang
LSU Doctoral Dissertations
Achieving good performance and high efficiency simultaneously is an essential requirement for emerging modern cloud systems such as e-commerce due to their business impact. For example, Akamai reported that every 100ms delay in website load time could lead to a 6% drop in sales. Unfortunately, achieving good performance (e.g., low latency) for modern cloud systems at high resource utilization is significantly challenging. Despite continuing efforts by cloud professionals, however, they have consistently experienced performance degradation problems (e.g., the long-tail latency problem) due to the bursty workload in the cloud. To resolve the performance degradation problems, many previous research efforts have …
Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney
Flying Free: A Research Overview Of Deep Learning In Drone Navigation Autonomy, Thomas Lee, Susan Mckeever, Jane Courtney
Articles
With the rise of Deep Learning approaches in computer vision applications, significant strides have been made towards vehicular autonomy. Research activity in autonomous drone navigation has increased rapidly in the past five years, and drones are moving fast towards the ultimate goal of near-complete autonomy. However, while much work in the area focuses on specific tasks in drone navigation, the contribution to the overall goal of autonomy is often not assessed, and a comprehensive overview is needed. In this work, a taxonomy of drone navigation autonomy is established by mapping the definitions of vehicular autonomy levels, as defined by the …
A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead
A Quantitative Validation Of Multi-Modal Image Fusion And Segmentation For Object Detection And Tracking, Nicholas Lahaye, Michael J. Garay, Brian D. Bue, Hesham El-Askary, Erik Linstead
Mathematics, Physics, and Computer Science Faculty Articles and Research
In previous works, we have shown the efficacy of using Deep Belief Networks, paired with clustering, to identify distinct classes of objects within remotely sensed data via cluster analysis and qualitative analysis of the output data in comparison with reference data. In this paper, we quantitatively validate the methodology against datasets currently being generated and used within the remote sensing community, as well as show the capabilities and benefits of the data fusion methodologies used. The experiments run take the output of our unsupervised fusion and segmentation methodology and map them to various labeled datasets at different levels of global …
Toward An Intelligent Driving Behavior Adjustment Based On Legal Personalized Policies Within The Context Of Connected Vehicles, Fatma Outay, Nafaa Jabeur, Hedi Haddad, Zied Bouyahia, Hana Gharrad
Toward An Intelligent Driving Behavior Adjustment Based On Legal Personalized Policies Within The Context Of Connected Vehicles, Fatma Outay, Nafaa Jabeur, Hedi Haddad, Zied Bouyahia, Hana Gharrad
All Works
The advent of Connected Vehicles (CVs) is creating new opportunities within the transportation sector. It is, indeed, expected to improve road traffic safety, enhance mobility, reduce fuel consumption and gas emissions, as well as foster economic growth via investments and jobs. However, to motivate the deployment of CVs and maximize their related benefits, policymakers must create appropriate neutral legal frameworks. These frameworks should promote the innovation of current road infrastructures, support cooperation and interoperability between transportation systems, and encourage fair competition between companies while upholding consumer privacy as well as data protection. We argue that policymakers should also support innovative …
Affectivetda: Using Topological Data Analysis To Improve Analysis And Explainability In Affective Computing, Hamza Elhamdadi
Affectivetda: Using Topological Data Analysis To Improve Analysis And Explainability In Affective Computing, Hamza Elhamdadi
USF Tampa Graduate Theses and Dissertations
We present an approach utilizing Topological Data Analysis to study the structure of face poses used in affective computing, i.e., the process of recognizing human emotion. The approach uses conditional comparison of different emotions, both respective and irrespective of time, with multiple topological distance metrics, dimension reduction techniques, and face subsections (e.g., eyes, nose, mouth, etc.). The results confirm that our topology-based approach captures known patterns, distinctions between emotions, and distinctions between individuals, which is an important step towards more robust and explainable emotion recognition by machines.
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Networks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Weihua Zhou, Et. Al.
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Networks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Weihua Zhou, Et. Al.
Michigan Tech Publications, Part 1
We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the …
Artificial Intelligence (Ai) And Augmented Reality (Ar): Disambiguated In The Telemedicine / Telehealth Sphere, Sharon L. Burton
Artificial Intelligence (Ai) And Augmented Reality (Ar): Disambiguated In The Telemedicine / Telehealth Sphere, Sharon L. Burton
Publications
The world is navigating through unfamiliar and incomprehensible times – COVID-19, international economic crisis, and crumbling healthcare systems. The United States (US) healthcare industry is grappling with an increased workload and advancing digitization technological concerns. The failure of organizations to offer suitable cybersecurity controls within the critical infrastructure leads to advanced persistent threat (APT) that could have incapacitating effects on organizations. A keen understanding of cybersecurity is vital for leaders and the need is referenced in US policy that advances a national unity of effort to strengthen and maintain secure, functioning, and resilient critical infrastructure. Akin to the Presidential Policy …
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Netwoks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou
St-V-Net: Incorporating Shape Prior Into Convolutional Neural Netwoks For Proximal Femur Segmentation, Chen Zhao, Joyce H. Keyak, Jinshan Tang, Tadashi S. Kaneko, Sundeep Khosla, Shreyasee Amin, Elizabeth J. Atkinson, Lan-Juan Zhao, Michael J. Serou, Chaoyang Zhang, Hui Shen, Hong-Wen Deng, Weihua Zhou
Faculty Publications
We aim to develop a deep-learning-based method for automatic proximal femur segmentation in quantitative computed tomography (QCT) images. We proposed a spatial transformation V-Net (ST-V-Net), which contains a V-Net and a spatial transform network (STN) to extract the proximal femur from QCT images. The STN incorporates a shape prior into the segmentation network as a constraint and guidance for model training, which improves model performance and accelerates model convergence. Meanwhile, a multi-stage training strategy is adopted to fine-tune the weights of the ST-V-Net. We performed experiments using a QCT dataset which included 397 QCT subjects. During the experiments for the …
Automated Decision Making And Machine Learning: Regulatory Alternatives For Autonomous Settings, Alyssa Heminger
Automated Decision Making And Machine Learning: Regulatory Alternatives For Autonomous Settings, Alyssa Heminger
University Honors Theses
Given growing investment capital in research and development, accompanied by extensive literature on the subject by researchers in nearly every domain from civil engineering to legal studies, automated decision-support systems (ADM) are likely to see a place in the foreseeable future. Artificial intelligence (AI), as an automated system, can be defined as a broad range of computerized tasks designed to replicate human neural networks, store and organize large quantities of information, detect patterns, and make predictions with increasing accuracy and reliability. By itself, artificial intelligence is not quite science-fiction tropes (i.e. an uncontrollable existential threat to humanity) yet not without …
Functional Role Of The N-Terminal Domain In Connexin 46/50 By In Silico Mutagenesis And Molecular Dynamics Simulation, Umair Khan
University Honors Theses
Connexins form intercellular channels known as gap junctions that facilitate diverse physiological roles, from long-range electrical and chemical coupling to nutrient exchange. Recent structural studies on Cx46 and Cx50 have defined a novel and stable open state and implicated the amino-terminal (NT) domain as a major contributor to functional differences between connexin isoforms. This thesis presents two studies which use molecular dynamics simulations with these new structures to provide mechanistic insight into the function and behavior of the NTH in Cx46 and Cx50. In the first, residues in the NTH that differ between Cx46 and Cx50 are swapped between the …