Research On Model Reuse Technology Based On Semantic Matching And Composition,
2022
1. School of Automation Science and Electrical Engineering, Beihang University, Beijing 100191, China; ;
Research On Model Reuse Technology Based On Semantic Matching And Composition, Xingyu Tian, Guangxun Zeng, Yunbo Gao, Lili Ye, Guanghong Gong, Li Ni
Journal of System Simulation
Abstract: In order to solve the data barriers between the conceptual model and the simulation scenario of the combat system, the intelligent mapping and model reuse technology of the simulation scenario is researched. The conceptual model is analyzed using DOM technology. Based on the ontology theory, the knowledge base of the combat domain is constructed and the web crawler is customized to build the domain thesaurus. Through the SWRL rule library, the reasoning engine is called to realize the relational reasoning at the semantic level. An intelligent matching algorithm is designed to map the semantic relationship to the combination relationship …
Research On Cloud Tool Integration And Management Methods,
2022
1. Beijing Complex Product Advanced Manufacturing Engineering Research Center, Beijing Simulation Center, Beijing 100854, China; ;2. State Key Laboratory of Intelligent Manufacturing System Technology, Beijing Institute of Electronic System Engineering, Beijing 100854, China; ;3. Science and Technology on Space System Simulation Laboratory, Beijing Simulation Center, Beijing 100854, China;
Research On Cloud Tool Integration And Management Methods, Tianying Zhang, Ji Hang, Junhua Zhou, Tao Luan
Journal of System Simulation
Abstract: In response to the application needs of using professional tools to develop complex products in the fields of aerospace, aviation, weapons, ships, etc., it is urgent to implement centralized management of cloud tools and cross-professional sharing of tools through tool service-oriented methods, so as to solve issues such as inconsistent tool versions, cross-professional resource barriers, and high thresholds for tool mastery during the traditional model development process. By studying the integration and calling methods of cross-professional and different versions of self-developed tools, as well as methods of tool server operation control, authority management, etc., and taking the local …
Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station,
2022
Department of Civil Engineering, Tsinghua University, Beijing 100084, China;
Predictive Control Method Of Peak Hour Passenger Flow At Urban Rail Station, Xiaohe Li, Jianping Wu, Depin Peng
Journal of System Simulation
Abstract: With the rapid development of subway in China, the urban rail station, especially the transfer station, is prone to generate passenger congestion in the peak period. After analyzing the types of passenger flow in and out of the platform, a predictive control model of passenger flow is established based on the discrete linear quadratic optimal control theory. Taking Fuxingmen Station as an example, the simulation environment of the station is built by using the simulation software of Anylogic. The historical passenger flow data in peak period and the optimal passenger flow control sequence obtained by solving the passenger flow …
Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections,
2022
School of Traffic Management, People's Public Security University of China, Beijing 102163, China;
Study And Effect Evaluation On The Setting Of Contraflow Left-Turn At Intersections, Zhao Dan, Xuejun Niu, Shuhao Zhang, Jiaxu Wei
Journal of System Simulation
Abstract: Contraflow left-turn is one of the traffic organization ways at intersections. By analyzing the setting parameters of the contraflow left-turn, the length and the range of the contraflow left-turn lane, the constrained conditions of the contraflow left-turn are determined, and the applicable conditions are determined from the road, traffic and signal control. VISSIM software is used to analyze a road intersection, simulate and evaluate the indicators related to the intersection entrance, optimize the timing plan of contraflow left-turn lane, and validate the feasibility and advantages of contraflow left-turn lane. The results show that the intersection delays are reduced by …
Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel,
2022
1. Institute of Agricultural Economics and Information, Henan Academy of Agricultural Sciences, Zhengzhou 450002, China; ;2. Henan Engineering and Technology Research Center for Intelligent Agriculture, Zhengzhou 450002, China; ;
Variety Recognition Based On Deep Learning And Double-Sided Characteristics Of Maize Kernel, Feng Xiao, Zhang Hui, Zhou Rui, Qiao Lu, Wei Dong, Dandan Li, Yuyao Zhang, Guoqing Zheng
Journal of System Simulation
Abstract: In order to construct a maize kernel variety recognition model with high recognition accuracy and suitable for mobile phone application, a mobile phone is used to obtain maize kernel double-sided (embryonic and non-embryonic) images. Based on the lightweight convolutional neural network MobileNetV2 and transfer learning, a maize kernel image variety recognition model is constructed. In view of the existing research methods are mainly for single-sided recognition of maize kernel variety, the performance of single-sided and double-sided characteristics modeling and recognition is compared. The results show that the double-sided recognition accuracy of maize kernel double-sided characteristics modeling is 99.83%, which …
Artificial Intelligence Framework Identifies Candidate Targets For Drug Repurposing In Alzheimer’S Disease,
2022
Cleveland Clinic Foundation
Artificial Intelligence Framework Identifies Candidate Targets For Drug Repurposing In Alzheimer’S Disease, Jiansong Fang, Pengyue Zhang, Quan Wang, Chien Wei Chiang, Yadi Zhou, Yuan Hou, Jielin Xu, Rui Chen, Bin Zhang, Stephen J. Lewis, James B. Leverenz, Andrew A. Pieper, Bingshan Li, Lang Li, Jeffrey Cummings, Feixiong Cheng
Brain Health Faculty Research
Background: Genome-wide association studies (GWAS) have identified numerous susceptibility loci for Alzheimer’s disease (AD). However, utilizing GWAS and multi-omics data to identify high-confidence AD risk genes (ARGs) and druggable targets that can guide development of new therapeutics for patients suffering from AD has heretofore not been successful. Methods: To address this critical problem in the field, we have developed a network-based artificial intelligence framework that is capable of integrating multi-omics data along with human protein–protein interactome networks to accurately infer accurate drug targets impacted by GWAS-identified variants to identify new therapeutics. When applied to AD, this approach integrates GWAS findings, …
Can Lethal Autonomous Weapons Be Just?,
2022
College of Saint Benedict/Saint John's University
Can Lethal Autonomous Weapons Be Just?, Noreen L. Herzfeld, Robert H. Latiff
Computer Science Faculty Publications
In 2018 the United States Department of Defense (DoD) created a new Joint Artificial Intelligence Center to study the adoption of AI by the military. Their strategy, outlined in a document entitled, “Harnessing AI to Advance Our Security and Prosperity,” proposes to accelerate the adoption of AI in the military by fostering a culture of experimentation and calculated risk taking, noting that AI will change the character of the future battlefield and, even more, the pace of battle. Is there any way to ensure that this future battlefield will be just? Can the age-old precepts of just warfare help guide …
Explainabilityaudit: An Automated Evaluation Of Local Explainability In Rooftop Image Classification,
2022
Kennesaw State University
Explainabilityaudit: An Automated Evaluation Of Local Explainability In Rooftop Image Classification, Duleep Rathgamage Don, Jonathan Boardman, Sudhashree Sayenju, Ramazan Aygun, Yifan Zhang, Bill Franks, Sereres Johnston, George Lee, Dan Sullivan, Girish Modgil
Published and Grey Literature from PhD Candidates
Explainable Artificial Intelligence (XAI) is a key concept in building trustworthy machine learning models. Local explainability methods seek to provide explanations for individual predictions. Usually, humans must check these explanations manually. When large numbers of predictions are being made, this approach does not scale. We address this deficiency for a rooftop classification problem specifically with ExplainabilityAudit, a method that automatically evaluates explanations generated by a local explainability toolkit and identifies rooftop images that require further auditing by a human expert. The proposed method utilizes explanations generated by the Local Interpretable Model-Agnostic Explanations (LIME) framework as the most important superpixels of …
An Attention-Based Resnet Architecture For Acute Hemorrhage Detection And Classification: Toward A Health 4.0 Digital Twin Study,
2022
COMSATS University Islamabad
An Attention-Based Resnet Architecture For Acute Hemorrhage Detection And Classification: Toward A Health 4.0 Digital Twin Study, Aftab Hussain, Muhammad Usman Yaseen, Muhammad Imran, Muhammad Waqar, Adnan Akhunzada, Mohammad Al-Ja'afreh, Abdulmotaleb El Saddik
Computer Vision Faculty Publications
Due to the advancement of digital twin (DT) technology, Health 4.0 applications have become reality and starting to take roots. In this article, we focus on intracranial hemorrhage (ICH) which is a life-threatening emergency that needs immediate diagnosis and treatment. ICH is caused by bleeding inside the skull or brain. Radiologists typically examine computed tomography (CT) scans of the patients to determine the ICH and its subtype. But the manual assessment of the CT scan is a complex and time-consuming task. The existing pre-trained convolutional neural network (CNN) models are state-of-the-art for ICH classification. However, they employ poor feature extraction …
Module 1: Introduction To Technology Foresight, Risk Management, And Insurtech,
2022
Old Dominion University
Module 1: Introduction To Technology Foresight, Risk Management, And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Instructional Module 1 for course, Developing Technology Foresight: Case Study of AI in InsurTech.
Module 2: Case Studies Of Ai And Insurtech,
2022
Old Dominion University
Module 2: Case Studies Of Ai And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Instructional Module 2 for course, Developing Technology Foresight: Case Study of AI in InsurTech.
Module 3: Technology Foresight And Insurtech,
2022
Old Dominion University
Module 3: Technology Foresight And Insurtech, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Instructional Module 3 for course, Developing Technology Foresight: Case Study of AI in InsurTech.
Insurtech And Distribution,
2022
Old Dominion University
Insurtech And Distribution, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Questions regarding InsurTech and distribution.
Insurtech And Actuarial,
2022
Old Dominion University
Insurtech And Actuarial, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Questions regarding InsurTech and actuarial work.
Introduction To The Course,
2022
Old Dominion University
Introduction To The Course, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
This PDF document describes the course, Developing Technology Foresight: Case Study of AI in InsurTech, and includes learning outcomes and a course outline.
Insurtech And Underwriting,
2022
Old Dominion University
Insurtech And Underwriting, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Questions regarding InsurTech and underwriting work.
Insurtech And Claims,
2022
Old Dominion University
Insurtech And Claims, Michael Mcshane, C. Ariel Pinto, Hesamoddin Tahami, Hengameh Fakhravar
Developing Technology Foresight: Case Study of AI in InsurTech
Questions related to InsurTech and claims.
Nlp@Vcu: Crop Characteristic Extraction Framework,
2022
Macalester College
Nlp@Vcu: Crop Characteristic Extraction Framework, Cora Lewis, Bridget Mcinnes, Getiria Onsongo
Summer REU Program
We developed a crop characteristic extraction framework. Starting from a custom SpaCy named entity recognition model, we added pre-trained word embeddings and a part-of-speech based entity expansion post-processing step. Then, we implemented an evaluation framework that functioned as a 5-fold cross validation wrapper for SpaCy custom training. Preliminary results showed improvement in the extraction framework after these additions.
Multi-Agent Pathfinding In Mixed Discrete-Continuous Time And Space,
2022
University of Denver
Multi-Agent Pathfinding In Mixed Discrete-Continuous Time And Space, Thayne T. Walker
Electronic Theses and Dissertations
In the multi-agent pathfinding (MAPF) problem, agents must move from their current locations to their individual destinations while avoiding collisions. Ideally, agents move to their destinations as quickly and efficiently as possible. MAPF has many real-world applications such as navigation, warehouse automation, package delivery and games. Coordination of agents is necessary in order to avoid conflicts, however, it can be very computationally expensive to find mutually conflict-free paths for multiple agents – especially as the number of agents is increased. Existing state-ofthe- art algorithms have been focused on simplified problems on grids where agents have no shape or volume, and …
Could Alexa Increase Your Social Worth?,
2022
University of Denver
Could Alexa Increase Your Social Worth?, Peter Tripp
Electronic Theses and Dissertations
People have historically used personal introductions to build social capital, which is the foundation of career networking and is perhaps the most effective way to advance a career (Lin, 2001). With societal changes, such as the pandemic (Venkatesh & Edirappuli, 2020), and the increasing capabilities of Artificial Intelligence (AI), new approaches may emerge that impact societal relationships. Social capital theory highlights the need for reciprocal agreements to establish the trust between parties (Gouldner, 1960). My theoretical prediction and focus of this research include two principles: The impact of reciprocity in evaluating trust of the source of the introduction and the …
