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Articles 5821 - 5850 of 63265
Full-Text Articles in Entire DC Network
Localization Of Synthetic Manipulations In Western Blot Images, Anmol Manjunath, Viola Negroni, Sara Mandelli, Daniel Moreira, Paolo Bestagini
Localization Of Synthetic Manipulations In Western Blot Images, Anmol Manjunath, Viola Negroni, Sara Mandelli, Daniel Moreira, Paolo Bestagini
Computer Science: Faculty Publications and Other Works
Recent breakthroughs in deep learning and generative systems have significantly fostered the creation of synthetic media, as well as the local alteration of real content via the insertion of highly realistic synthetic manipulations. Local image manipulation, in particular, poses serious challenges to the integrity of digital content and societal trust. This problem is not only confined to multimedia data, but also extends to biological images included in scientific publications, like images depicting Western blots. In this work, we address the task of localizing synthetic manipulations in Western blot images. To discriminate between pristine and synthetic pixels of an analyzed image, …
Artificial Intelligence In Fetal And Pediatric Echocardiography, Alan Wang, Tam T Doan, Charitha Reddy, Pei-Ni Jone
Artificial Intelligence In Fetal And Pediatric Echocardiography, Alan Wang, Tam T Doan, Charitha Reddy, Pei-Ni Jone
Faculty, Staff and Students Publications
Echocardiography is the main modality in diagnosing acquired and congenital heart disease (CHD) in fetal and pediatric patients. However, operator variability, complex image interpretation, and lack of experienced sonographers and cardiologists in certain regions are the main limitations existing in fetal and pediatric echocardiography. Advances in artificial intelligence (AI), including machine learning (ML) and deep learning (DL), offer significant potential to overcome these challenges by automating image acquisition, image segmentation, CHD detection, and measurements. Despite these promising advancements, challenges such as small number of datasets, algorithm transparency, physician comfort with AI, and accessibility must be addressed to fully integrate AI …
Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang
Digital Twin And Cybersecurity In Additive Manufacturing, Lidong Wang
Journal of Cybersecurity Education, Research and Practice
Additive manufacturing (AM) has been applied to automotive, aerospace, medical sectors, etc., but there are still challenges such as parts’ porosity, cracks, surface roughness, intrinsic anisotropy, and residual stress because of the high level of thermal gradient. It is significant to conduct the modeling and simulation of the AM process and achieve quality products. Digital Twin (DT) can help AM with forecasting defects/errors through simulation and real-time process monitoring. DT is a concept of Industry 4.0, and its digital structure reflects the real-time behaviors of a cyber-physical or physical system. This paper introduces the progress of DT applications in AM, …
Measurement Of Breast Artery Calcification Using An Artificial Intelligence Detection Model And Its Association With Major Adverse Cardiovascular Events, Suzanne Rose, Josette Hartnett, Zachary Estep, Daniyal Ameen, Shweta Karki, Edward Schuster, Rebecca Newman, David Hsi
Measurement Of Breast Artery Calcification Using An Artificial Intelligence Detection Model And Its Association With Major Adverse Cardiovascular Events, Suzanne Rose, Josette Hartnett, Zachary Estep, Daniyal Ameen, Shweta Karki, Edward Schuster, Rebecca Newman, David Hsi
Department of Medicine Faculty Papers
Breast artery calcification (BAC) obtained from standard mammographic images is currently under evaluation to stratify risk of major adverse cardiovascular events in women. Measuring BAC using artificial intelligence (AI) technology, we aimed to determine the relationship between BAC and coronary artery calcification (CAC) severity with Major Adverse Cardiac Events (MACE). This retrospective study included women who underwent chest computed tomography (CT) within one year of mammography. T-test assessed the associations between MACE and variables of interest (BAC versus MACE, CAC versus MACE). Risk differences were calculated to capture the difference in observed risk and reference groups. Chi-square tests and/or Fisher's …
Coding For Decentralized Systems And Forensic 3d Fingerprinting, Canran Wang
Coding For Decentralized Systems And Forensic 3d Fingerprinting, Canran Wang
McKelvey School of Engineering Graduate Student Theses & Dissertations
This dissertation presents novel coding techniques that optimize communication costs and address security challenges in decentralized systems and 3D printing technologies. The first part focuses on encoding data in distributed systems in a decentralized manner, i.e., without a central processor which orchestrates the operation. In such systems, processors require coded data generated from inputs provided by source processors. An example is a distributed storage system with geographically dispersed nodes storing a large database collected by specific source processors. To reduce communication costs, we propose a universal solution applicable to any linear code, with optimizations for systematic Reed-Solomon and Lagrange codes, …
Editorial: Artificial Intelligence For Smart Health: Learning, Simulation, And Optimization, Bing Yao, Nathan Gaw, Hyo Kyung Lee
Editorial: Artificial Intelligence For Smart Health: Learning, Simulation, And Optimization, Bing Yao, Nathan Gaw, Hyo Kyung Lee
Faculty Publications
With rapid developments in medical sensing and imaging, we now live in an era of data explosion in which large amounts of data are readily available in clinical environments. The fast-growing biomedical and healthcare data provide unprecedented opportunities for data-driven scientific knowledge discovery and clinical decision support. Our Research Topic aims to catalyze synergies among biomedical informatics, machine learning, computer simulation, operations research, systems engineering, and other related fields with three specific goals: (1) develop cutting-edge data-driven models to accelerate scientific knowledge discovery in biomedicine using healthcare data collected from laboratory systems, imaging systems, and medical and sensing devices; (2) …
Ethical Aspects Of Utilising Artificial Intelligence In Clinical Settings, Jeffrey Byrnes, Michael Robinson
Ethical Aspects Of Utilising Artificial Intelligence In Clinical Settings, Jeffrey Byrnes, Michael Robinson
Philosophy Faculty Articles and Research
In response to recent proposals to utilize artificial intelligence (AI) to automate ethics consultations in healthcare, we raise two main problems for the prospect of having healthcare professionals rely on AI-driven programs to provide ethical guidance in clinical matters. The first cause for concern is that, because these programs would effectively function like black boxes, this approach seems to preclude the kind of transparency that would allow clinical staff to explain and justify treatment decisions to patients, fellow caregivers, and those tasked with providing oversight. The other main problem is that the kind of authority that would need to be …
Transparency And Authority Concerns With Using Ai To Make Ethical Recommendations In Clinical Settings, Jeffrey Byrnes, Michael Robinson
Transparency And Authority Concerns With Using Ai To Make Ethical Recommendations In Clinical Settings, Jeffrey Byrnes, Michael Robinson
Philosophy Faculty Articles and Research
In response to recent proposals to utilize artificial intelligence (AI) to automate ethics consultations in healthcare, we raise two main problems for the prospect of having healthcare professionals rely on AI-driven programs to provide ethical guidance in clinical matters. The first cause for concern is that, because these programs would effectively function like black boxes, this approach seems to preclude the kind of transparency that would allow clinical staff to explain and justify treatment decisions to patients, fellow caregivers, and those tasked with providing oversight. The other main problem is that the kind of authority that would need to be …
Measuring And Improving Api Usability And Quality: A Comprehensive Framework And Empirical Study, Sultan Alanazy
Measuring And Improving Api Usability And Quality: A Comprehensive Framework And Empirical Study, Sultan Alanazy
Computer Science and Engineering Theses and Dissertations
Cloud computing provides on-demand access to flexible computing resources, enabling rapid application deployment without substantial infrastructure investment. Application Programming Interfaces (APIs) play an important role in ensuring the success of cloud applications. The primary users of APIs are the extensive community of application programmers who search, read, and understand APIs before integrating them into their applications or systems. In addition, developers often turn to online API support when seeking help. Problems in such support can result in incorrect API usage and integration problems. There is an urgent need to measure API usability and support issues to identify, characterize, and assess …
Optimization Of The Starch Chitosan-Based Flocculant Crosslinked By Ethylene Glycol Dimethacrylate On Removing Dypro 19 Textile Dye From Wastewater, Asep Nurohmat Majalis, Putri Ramadhani, Hendris Hendarsyah Kurniawan, Axel Dimaz Sanusi Pasaribu, Hafiizh Prasetia, Fitri Yuliani, Andreas Andreas, Hartati Hartati
Optimization Of The Starch Chitosan-Based Flocculant Crosslinked By Ethylene Glycol Dimethacrylate On Removing Dypro 19 Textile Dye From Wastewater, Asep Nurohmat Majalis, Putri Ramadhani, Hendris Hendarsyah Kurniawan, Axel Dimaz Sanusi Pasaribu, Hafiizh Prasetia, Fitri Yuliani, Andreas Andreas, Hartati Hartati
Karbala International Journal of Modern Science
Dyes used in industry, especially textile dyes, are one of the water pollutants that receive much attention because they are potentially toxic, carcinogenic, mutagenic, and generally challenging to decompose naturally. Textile dyes from wastewater can be removed through coagulation-flocculation. However, conventional coagulation-flocculation based on Fe and Al salts and synthetic polymers often leaves residual pollution. In this research, the performance of the new biopolymer-based flocculant, namely starch-ethylene glycol dimetacrylate-chitosan (SEC), which can act as coagulants and flocculants in solid-liquid separation of textile dyes, has been optimized using response surface methodology (RSM) approach. The influences of several independent variables, such …
Breast Cancer Area Identification In Mammograms Using Expectation Maximization Gaussian Mixture Model, Rizki Khoirun Nisa, Dian Kurniasari, Favorisen R. Lumbanraja, Warsono Warsono
Breast Cancer Area Identification In Mammograms Using Expectation Maximization Gaussian Mixture Model, Rizki Khoirun Nisa, Dian Kurniasari, Favorisen R. Lumbanraja, Warsono Warsono
Karbala International Journal of Modern Science
Breast cancer accounts for 25% of all cancer diagnoses and 16% of cancer-related deaths among women globally, with high mortality rates due to late diagnosis. Early detection relies on imaging techniques such as mammography, histopathology, and breast ultrasound, with mammography being the gold standard due to its proven to detect breast cancer, thus it is effective for breast cancer treatment. However, mammogram images often produce noise and artefacts, complicating early-stage cancer detection and emphasizing the need for advanced image processing. Clustering algorithms such as K-means and Expectation Maximization - Gaussian Mixture Model (EM-GMM) have shown potential in image segmentation. This …
Simulation Of Cascade Failure In Urban Rail Transit Hypernetworks Based On Hypergraph Theory, Zijin Han, Mingjun Qian, Xixian Wang, Kaiyue Zhang
Simulation Of Cascade Failure In Urban Rail Transit Hypernetworks Based On Hypergraph Theory, Zijin Han, Mingjun Qian, Xixian Wang, Kaiyue Zhang
Journal of System Simulation
Abstract: In order to enhance the resilience of urban rail transit networks to ensure stable operations and passenger safety in the face of emergencies, hypergraph theory is introduced to construct a hypergraph based urban rail transit hypernetwork model, and a nonlinear load-capacity cascading failure model based on passenger flow weighting is established. In response to the passenger evacuation process at actual transportation network stations, a load redistribution mechanism is proposed, taking into consideration both the network level and the importance of passenger flow. To address scenarios where stations in actual traffic networks can still accommodate loads during shutdowns, a node …
A Fast Federated Learning-Based Crypto-Aggregation Scheme And Its Simulation Analysis, Boshen Lü, Xiao Song
A Fast Federated Learning-Based Crypto-Aggregation Scheme And Its Simulation Analysis, Boshen Lü, Xiao Song
Journal of System Simulation
Abstract: To solve the problem of increased computation and communication costs caused by using homomorphic encryption (HE) to protect all gradients in traditional cryptographic aggregation (cryptoaggregation) schemes, a fast crypto-aggregation scheme called RandomCrypt was proposed. RandomCrypt performed clipping and quantization to fix the range of gradient values and then added two types of noise on the gradient for encryption and differential privacy (DP) protection. It conducted HE on noise keys to revise the precision loss caused by DP protection. RandomCrypt was implemented based on a FATE framework, and a hacking simulation experiment was conducted. The results show that the proposed …
Critical Node Identification Method For Unmanned Aerial Vehicle Cluster Considering Localized Features, Chenglong Shi, Xiang Hua, Dong Wang, Jinjin Zhang, Tianqi Jiang, Yuanzhang Dang
Critical Node Identification Method For Unmanned Aerial Vehicle Cluster Considering Localized Features, Chenglong Shi, Xiang Hua, Dong Wang, Jinjin Zhang, Tianqi Jiang, Yuanzhang Dang
Journal of System Simulation
Abstract: Aiming at the problem that the UAV cluster critical node identification methods focus on the global network and ignore the correlation between nodes and their local features, a critical nodes identification method for unmanned aerial vehicle cluster considering local features is proposed. An unmanned aerial vehicle cluster network model is constructed based on complex network theory. The Laplacian energy is introduced to evaluate the importance of node within two hops, and information entropy is combined to evaluate the importance of node in a specific motif to comprehensive identify the critical nodes. Simulation results demonstrate that this method identifies critical …
Optimization Of Urban Agglomeration Transportation Network Evacuation Paths, Bowei He, Chengbing Li, Shida Nie, Jialin Wang
Optimization Of Urban Agglomeration Transportation Network Evacuation Paths, Bowei He, Chengbing Li, Shida Nie, Jialin Wang
Journal of System Simulation
Abstract: Given the complexity of the internal transportation network structure within urban agglomerations and the presence of numerous alternative routes, this paper proposes an enhanced ant colony algorithm to address the evacuation path problem of urban agglomeration transportation networks. A comprehensive urban agglomeration transportation network model is constructed, in which the issue of virtual transfer edges within the urban scope is considered and a weighting function is constructed taking into account the travelling time cost and the transferring time cost. Optimizations are applied to the ant colony algorithm, constructing an adaptive adjustment of state transitions and an information pheromone update …
A Threat Assessment Method In Uncertain Dynamic Environments, Mei Yang, Bingkun Wang, Zhongjie Zhang, Yan Zeng, Jian Huang
A Threat Assessment Method In Uncertain Dynamic Environments, Mei Yang, Bingkun Wang, Zhongjie Zhang, Yan Zeng, Jian Huang
Journal of System Simulation
Abstract: A threat assessment method based on priori information and dynamic observation results is studied for the existence of dynamic uncertainty in complex war systems. The data mining is applied to obtain prior knowledge on the battlefield situation and construct an equipment-related confidence matrix. The sensor model is constructed to dynamically update the number of blue-side entities under the current situation by using the Bayesian method and considering both intelligence and observation results. The threat evaluation indicators and their weights are determined, and the TOPSIS method is used to finish the threat assessment. This method can well describe the complex …
Research On Adaptive Scheduling Of Single-Arm Cluster Tools For Throughput Ratio Of Multiple Wafer Types With Concurrent Processing, Chunrong Pan, Yu Cui, Wenqing Xiong, Hao Zhou, Jiliang Luo
Research On Adaptive Scheduling Of Single-Arm Cluster Tools For Throughput Ratio Of Multiple Wafer Types With Concurrent Processing, Chunrong Pan, Yu Cui, Wenqing Xiong, Hao Zhou, Jiliang Luo
Journal of System Simulation
Abstract: Concurrent processing makes the wafer fabrication process prone to deadlocks and completion node ambiguity. A Petri net model is established to describe the system operation process by taking for the single-arm cluster tools for fully parallel processing of two wafer types as the research object, and a control strategy is developed to avoid the system deadlock. Based on the Petri net model, the temporal properties of the system is analyzed based on earliest starting strategy, and the action cycle sequence of robot is determined during the monitoring cycle for different scenarios of lot switching in a single production monitoring …
Research On Latent Space-Based Anime Face Style Transfer And Editing Techniques, Haixin Deng, Fengquan Zhang, Nan Wang, Wancai Zhang, Jierui Lei
Research On Latent Space-Based Anime Face Style Transfer And Editing Techniques, Haixin Deng, Fengquan Zhang, Nan Wang, Wancai Zhang, Jierui Lei
Journal of System Simulation
Abstract: To address issues such as image distortion and style uniformity in existing anime style transfer networks within the field of image simulation, we propose the TGFE-TrebleStyleGAN (textguided facial editing with TrebleStyleGAN) for anime facial style transfer and editing. This framework leverages vector guidance within the latent space to generate facial imagery and incorporates a detail control module and a feature control module to constrain the aesthetic attributes of the generated images. The images generated by the transfer network serve as style control signals and constraints for fine-grained segmentation. Text-to-image generation technology captures correlations between styletransferred images and semantic information. …
Research On Digital Twin Simulation Method Of Industrial Robot Integrated With Reinforcement Learning, Tianyue Miao, Lu Wang, Jiaxiao He, Nenggang Xie
Research On Digital Twin Simulation Method Of Industrial Robot Integrated With Reinforcement Learning, Tianyue Miao, Lu Wang, Jiaxiao He, Nenggang Xie
Journal of System Simulation
Abstract: In response to the lack of comprehensive functionality and limited application scenarios in the current field of industrial robot digital twin systems, which results in low versatility, a method for constructing a digital twin system for industrial robots with high versatility is proposed. A four-dimensional system architecture for the digital twin is designed, and the components and functions of the four-dimensional system are analyzed, based on the system level planning of the four-dimensional system, the concept of integrating reinforcement learning into the virtual replacement of real concept is defined. By constructing a multi-attribute virtual model and using TCP communication …
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Research On Multi-Objective Gait Planning Of Biped Robot Based On Virtual Prototype, Yankai Zhang, Xuesong Wang, Yubin Jin, Dongsheng Zhang
Journal of System Simulation
Abstract: A multi-objective gait optimization method based on virtual prototype is proposed to address the difficulty of balancing personalisation and performance in gait planning for bipedal robots. A scale prototype of a planar underactuated biped robot is created according to the body structure of Chinese people, and an identification approach is used to determine the robot's exact inertial parameters. A virtual prototype of the robot is created, and three optimization goals—speed, energy use, and stability are developed. Using the enhanced NSGA-II algorithm, the Pareto optimal solution set for the robot multi-objective gait planning issue is produced. Numerous gaits that conform …
Intersection Braking Guidance For Trams Based On Lineside Signs, Wencong Tong, Jing Teng, Junxian Li, Xing Yao, Zhongjie Zhang
Intersection Braking Guidance For Trams Based On Lineside Signs, Wencong Tong, Jing Teng, Junxian Li, Xing Yao, Zhongjie Zhang
Journal of System Simulation
Abstract: Trams need to brake frequently due to signal control and safety speed limits at intersections. Due to the inaccuracy of distance judgment, tram drivers tend to reserve extra braking distance at intersections, resulting in lower braking coefficients and a decrease in speed. An intersection braking guidance method using lineside signs is proposed for trams to reduce braking distance redundancy and improve running speed. Drivers are guided to brake with the shortest possible distance by marking the initial braking position and speed of trams with fixed lineside signs. A tram driving simulation system was developed based on a vehicle dynamics …
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
Multimodal Representation Learning Frameworks For Modeling Progression And Heterogeneity In Alzheimer’S Disease, Sayantan Kumar
McKelvey School of Engineering Graduate Student Theses & Dissertations
Alzheimer’s Disease (AD) is the leading cause of dementia, characterised by cognitive and functional impairments that disrupt daily activities. Different clinical modalities such as neuroimaging biomarkers, cognitive assessments, fluid biomarkers and genetic data provide unique and complementary information, contributing to a more comprehensive understanding of disease progression and heterogeneity in disease characteristics. With recent advancements in computational capabilities, particularly in deep learning, multimodal representation learning frameworks aim to integrate diverse clinical modalities into a cohesive framework, capturing the most significant patterns within each modality. Existing data-driven multimodal representation learning frameworks in AD research have two major limitations. First, AD progresses …
Noise-Enhanced Network Science, Reyhaneh Abdolazimi
Noise-Enhanced Network Science, Reyhaneh Abdolazimi
Dissertations - ALL
Graphs are a versatile and powerful data structure used to model complex relationships in diverse domains such as social networks, biological systems, and transportation networks. In graphs, entities are represented by nodes, and interactions or relationships between them are represented by edges. For example, in the World Wide Web, web pages are considered vertices, and if there is a link from one page to another page on the web, there will be a directed edge between those pages in its graph data structure. These structures allow us to analyze and solve important problems like community detection (identifying closely related clusters …
A Clustering-Based Location Allocation Method For Delivery Sites Under Epidemic Situations, Yaqiong Zhou, Junqi Chen, Weishi Li, Sihang Qiu, Rusheng Ju
A Clustering-Based Location Allocation Method For Delivery Sites Under Epidemic Situations, Yaqiong Zhou, Junqi Chen, Weishi Li, Sihang Qiu, Rusheng Ju
Journal of System Simulation
Abstract: To address the poor performance of commonly used intelligent optimization algorithms in solving location problems—specifically regarding effectiveness, efficiency, and stability—this study proposes a novel location allocation method for the delivery sites to deliver daily necessities during epidemic quarantines. After establishing the optimization objectives and constraints, we developed a relevant mathematical model based on the collected data and utilized traditional intelligent optimization algorithms to obtain Pareto optimal solutions. Building on the characteristics of these Pareto front solutions, we introduced an improved clustering algorithm and conducted simulation experiments using data from Changchun City. The results demonstrate that the proposed algorithm outperforms …
Research On Verification Method Of Motor Startups In Nuclear Power Plants Based On Topology Recognition, Baozhu Li, Weijie Dong, Chao Chen
Research On Verification Method Of Motor Startups In Nuclear Power Plants Based On Topology Recognition, Baozhu Li, Weijie Dong, Chao Chen
Journal of System Simulation
Abstract: There are many motors in operation or on standby in nuclear power plants, and the startup of group motors will have a great impact on the voltage of the emergency bus. At present, there is no special or inexpensive software to solve this problem, and the experience of engineers is not accurate enough. Therefore, this paper developed a method and system for the startup calculation of group motors in nuclear power plants and proposed an automatic generation method of circuit topology in nuclear power plants. Each component in the topology was given its unique number, and the component class …
Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao
Modeling And Integration Method Of Sysml Model For Complex Business Scenarios, Bing Yu, Baoran An, Shicao Zhao
Journal of System Simulation
Abstract: The development process of complex equipment involves multi-stage business processes, multi-level product architecture, and multi-disciplinary physical processes. The relationship between its system model and various disciplinary models is extremely complicated. In the modeling and integration process, extensive customized development is needed to realize model integration and interoperability in different business scenarios. Meanwhile, the differences in modeling and interaction between different modeling tools make it difficult to support the consistent representation of models in complex scenarios. To improve the efficiency of system modeling and integration in complex business scenarios, a system modeling and integration method was proposed. This method took …
Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang
Algorithm And Semi-Physical System Simulation For Command Intent Recognition Of Uav In Low-Resource Environment, Hongfu Liu, Yajing Fu, Wanpeng Zhang, Hu Zhang
Journal of System Simulation
Abstract: When a communication network is partially disabled or disrupted, an UAV is plunged into a "low-resource environment" and must rely on local hardware resources. This situation imposes constraints on computing power, storage capacity, and energy availability. To address the need for command intent recognition in such environments, a semi-physical simulation system for UAV in emergency rescue operations has been designed and implemented. Based on the low resource airborne hardware in the loop, the system simulates UAV command intention recognition and mission planning through GIS+BIM 3D environment modeling task scenarios. A new lightweight algorithm for intent recognition has been proposed, …
Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li
Uav Swarm Obstacle Avoidance Based On Visual Filed And Adaptive Radius, Gaohang Ai, Chuntao Li
Journal of System Simulation
Abstract: Aiming at the obstacle avoidance problem of large-scale UAV swarm tracking flight route, a swarm obstacle avoidance algorithm based on distributed model predictive control combined with visual field and adaptive obstacle avoidance radius is proposed. In the process of swarm flight, the UAV obtains the reference route information of the current moment according to its own position, and obtains the predicted trajectory of its neighbors through local information interaction. When encountering obstacles, the adaptive obstacle avoidance radius and field of view topology method are combined to effectively solve the problem that the internal safety distance cannot be maintained and …
A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng
A Novel Research Pattern For The Simulation Of Complex Systems Sigd, Bin Chen, Runkang Guo, Zhengqiu Zhu, Yong Zhao, Yatai Ji, Aiguo Chen, Guangquan Cheng
Journal of System Simulation
Abstract: The complexity of the system is mainly reflected in the numerous components and extremely complex interactions. Combined with the current trend of artificial intelligence development, this paper analyzes and considers the changes in thinking mode brought by simulation discipline research, and forms an understanding of the connotation and research scope of simulation intelligence. A new pattern for complex system simulation research is proposed: "simulation intelligence based generating decisions (SIGD)". In the SIGD pattern, the similar principles, modeling methods, and decision-guiding modes in simulation disciplines are different from those in traditional simulation. Under the guidance of this concept, a connection-oriented …
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
Reimagining The Machine Vision Pipeline In Cyber Physical Systems For Trustworthiness And Efficiency, Adith Boloor
McKelvey School of Engineering Graduate Student Theses & Dissertations
Cyber-physical systems (CPS), including autonomous vehicles, drones, and mobile robots, rely on intricate sensors, actuators, and machine learning algorithms to perceive the physical world and execute actions within their surroundings. In the context of vision-driven CPS, achieving this demands processing a substantial volume of visual data captured by on-board cameras. The data is subsequently channeled through digital processors and harnessed by deep neural networks for tasks such as image classification, object detection, and depth perception. This data-centric, machine-vision-infused CPS fosters intelligent decision-making, thereby enhancing overall system performance. Trustworthiness, encompassing the robustness of the entire machine-vision pipeline, and system-level efficiency are …