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Articles 5431 - 5460 of 11180
Full-Text Articles in Artificial Intelligence and Robotics
Assessing Photogrammetry Artificial Intelligence In Monumental Buildings’ Crack Digital Detection, Said Maroun, Mostafa Khalifa, Nabil Mohareb
Assessing Photogrammetry Artificial Intelligence In Monumental Buildings’ Crack Digital Detection, Said Maroun, Mostafa Khalifa, Nabil Mohareb
Architecture and Planning Journal (APJ)
Natural and human-made disasters have significant impacts on monumental buildings, threatening them from being deteriorated. If no rapid consolidations took into consideration traumatic accidents would endanger the existence of precious sites. In this context, Beirut's enormous 4th of August 2020 explosion damaged an estimated 640 historical monuments, many volunteers assess damages for more than a year to prevent the more crucial risk of demolitions. This research aims to assist the collaboration ability among photogrammetry science, Artificial Intelligence Model (AIM) and Architectural Coding to optimize the process for better coverage and scientific approach of data specific to the crack disorders to …
Improving Robustness Of Deep Learning Models And Privacy-Preserving Image Denoising, Hadi Zanddizari
Improving Robustness Of Deep Learning Models And Privacy-Preserving Image Denoising, Hadi Zanddizari
USF Tampa Graduate Theses and Dissertations
Applications of deep learning models and convolutional neural networks have been rapidly increased. Although state-of-the-art CNNs provide high accuracy in many applications, recent investigations show that such networks are highly vulnerable to adversarial attacks. The black-box adversarial attack is one type of attack that the attacker does not have any knowledge about the model or the training dataset, but it has some input data set and theirlabels.
In this chapter, we propose a novel approach to generate a black-box attack in a sparse domain, whereas the most critical information of an image can be observed. Our investigation shows that large …
Novel Methodology For The Investigation Of Dmrt3a Interneurons In Larval Zebrafish, Alfred Amendolara
Novel Methodology For The Investigation Of Dmrt3a Interneurons In Larval Zebrafish, Alfred Amendolara
Annual Research Symposium
No abstract provided.
Energy-Based Latent Aligner For Incremental Learning, K.J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian
Energy-Based Latent Aligner For Incremental Learning, K.J. Joseph, Salman Khan, Fahad Shahbaz Khan, Rao Muhammad Anwer, Vineeth N. Balasubramanian
Computer Vision Faculty Publications
Deep learning models tend to forget their earlier knowledge while incrementally learning new tasks. This behavior emerges because the parameter updates optimized for the new tasks may not align well with the updates suitable for older tasks. The resulting latent representation mismatch causes forgetting. In this work, we propose ELI: Energy-based Latent Aligner for Incremental Learning, which first learns an energy manifold for the latent representations such that previous task latents will have low energy and the current task latents have high energy values. This learned manifold is used to counter the representational shift that happens during incremental learning. The …
The Global Rise Of Online Devices, Cyber Crime And Cyber Defense: Enhancing Ethical Actions, Counter Measures, Cyber Strategy, And Approaches, Naresh Kshetri
The Global Rise Of Online Devices, Cyber Crime And Cyber Defense: Enhancing Ethical Actions, Counter Measures, Cyber Strategy, And Approaches, Naresh Kshetri
Dissertations
The rise of online devices, online users, online shopping, online gaming, and online teaching has ultimately given rise to online attacks and online crimes. As cases of COVID-19 seem to increase day by day, so do online crimes and attacks (as many sectors and organizations went 100% online). Technological advancements and cyber warfare already generated many ethical issues, as internet users increasingly need ethical cyber defense strategies.
Individual internet users have challenges on their end; and on the other end, nation states (some secretly, some openly), are investing in robot weapons and autonomous weapons systems (AWS). New technologies have combined …
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Research On 3d Path Planning Algorithm Based On Fast Rrt Algorithm, Zhaoqiang Li, Shiyu Zhang
Journal of System Simulation
Abstract: RRT (rapidly exploring random tree) algorithm is a sampling-based path planning algorithm, which can search a path in high-dimensional environment. The traditional RRT algorithm has the problems of low node utilization and large amount of calculation. To solve these problems, the fast RRT* (Quick RRT*) algorithm is improved by optimizing the strategy of reselection of parent node and pruning range, improving the sampling method and introducing adaptive step size, which makes the algorithm time-consuming and path length shorter. At the same time, the node connection screening strategy is added to eliminate the excessive turning angle in the path. …
Research On Real-Time Motion Matching Of Shadow Play Based On Kinect, Chuanqian Tang, Zhiqiang Liu, Yijun Su, Xiaojing Liu
Research On Real-Time Motion Matching Of Shadow Play Based On Kinect, Chuanqian Tang, Zhiqiang Liu, Yijun Su, Xiaojing Liu
Journal of System Simulation
Abstract: In the inheritance of shadow play culture, due to the aging of the audience and the discontinuity of inheritance, the shadow play culture is gradually facing decline. Real-time matching of shadow play movements based on Kinect can inject new vitality into traditional shadow play culture. According to the characteristics of shadow play, a joint point shadow play model is constructed, and the static digitization of shadow play is realized. The human body depth image is obtained based on Kinect, and the human skeleton point coordinates are obtained through segmentation mask and machine learning to generate the human skeleton.Bone …
Effectiveness Evaluation Of Surface Ship Air Defense And Antimissile Combat In Complex Electromagnetic Environment, Gaofeng Zhang, Liang Wu
Effectiveness Evaluation Of Surface Ship Air Defense And Antimissile Combat In Complex Electromagnetic Environment, Gaofeng Zhang, Liang Wu
Journal of System Simulation
Abstract: In order to effectively evaluate the effectiveness of surface ship air defense and antimissile combat in complex electromagnetic environment, a surface ship air defense and antimissile combat effectiveness index system is established considering the influence of equipment, environment and human behavior, the evaluation process of surface ship air defense and antimissile combat effectiveness based on analytic hierarchy process(AHP) is proposed, and a hierarchical structure model of effectiveness evaluation is constructed including five levels of target layer, sub-efficiency layer, capability layer, constraint layer and plan layer. The application shows that the evaluation process and structure model can fully reflect the …
New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang
New Embedded Simulation Technology For Smart Internet Of Things, Bohu Li, Xudong Chai, Lin Zhang, Duzheng Qing, Guoqiang Shi, Tingyu Lin, Liqin Guo, Chen Yang, Mu Gu, Zhengxuan Jia, Hui Gong, Zhen Tang
Journal of System Simulation
Abstract: Human society in the new development era and journey is facing the new situation. The operation paradigm, technology and ecosystem of industries related to the national economy and people's livelihood、national security are changing significantly towards the digital, networked, cloud-based and intelligent "Smart Internet of Things". The new embedded simulation technology, with the capabilities of online and continuous analysis, cognition, learning, decision-making, operation and optimization,is urgently needed for the development of "Smart Internet of Things". "Smart Internet of Things" is briefly introduced and the connotation, characteristics and application mode of the new embedded simulation technology are proposed and its architecture, …
Open Cloud Architecture Design For Complex Product Modeling And Simulation System, Guoqiang Shi, Zewei Liu, Tingyu Lin, Zhao Xu, Xingyi Yang, Liqin Guo, Zhengxuan Jia
Open Cloud Architecture Design For Complex Product Modeling And Simulation System, Guoqiang Shi, Zewei Liu, Tingyu Lin, Zhao Xu, Xingyi Yang, Liqin Guo, Zhengxuan Jia
Journal of System Simulation
Abstract: Aiming at the problem that the complex product modeling and simulation system focuses on co-simulation of heterogeneous models and cannot realize the on-demand sharing and collaboration of simulation resources, this paper proposes an open cloud architecture for complex product modeling and simulation systems, realized on-demand sharing and collaboration of cross-organizational simulation software and hardware resources, thereby supporting complex product system-wide, full-lifecycle, anytime, anywhere, real-time, coherent, and transparently requesting accessing and obtaining simulation services. The object-process methodology (OPM) is used to model and deduce the simulation interoperability of the system and the on-demand sharing and collaborative process of simulation resources. …
Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang
Research On Integrated Scheduling Of Agv And Machine In Flexible Job Shop, Kui Chen, Li Bi, Wenya Wang
Journal of System Simulation
Abstract: Aiming at the flexible job shop scheduling problem with AGV (automated guided vehicle), a dual resource integrated scheduling optimization model with the objective of minimizing makespan is established. In the process of population initialization, a heuristic initialization method is proposed to improve the quality of population initial solution and accelerate the convergence speed of the algorithm. A hybrid discrete particle swarm optimization algorithm that can effectively avoid premature maturation is proposed by combining the competitive learning mechanism and the random restart mechanism to address the disadvantages of discrete particle swarm algorithms that are prone to premature maturation. Simulation experiments …
Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu
Cause Analysis Of Vocs Hazards In Related Areas Based On Object Function Petri Net, Guangqiu Huang, Tiantian Wu
Journal of System Simulation
Abstract: The multi-resolution formal description based on discrete event system specification (DEVS) has the ability of hierarchical and structured description, but the description of the intelligent behavior inside the module is relatively lacking, while Agent-based modeling can describe the characteristics of individual perception, behavior, communication, cooperation, learning and evolution. Under the framework of multi-resolution modeling, DEVS and Agent model descriptions are combined to provide the description capabilities for events, behaviors, mechanisms, etc. Based on the description of multi-resolution DEVS models, a formal model description method with coupling closure is proposed, which includes the description of the multi-resolution entity-level atomic model …
Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu
Electronic Solid Waste Prediction Based On Intelligent Optimization Grey Model, Xiaoan Sun, Xiaoli Luan, Fei Liu
Journal of System Simulation
Abstract: Aiming at the problems of complex modeling mechanism and low modeling accuracy in the prediction of electronic solid waste production, an intelligent modeling method combining fractional order multiple gray model and neural network compensation model is proposed. Particle swarm optimization is used to optimize the accumulative order and background parameters of the gray model to maximize the performance of the gray model. BP neural network is used to compensate the error of gray modeling and improve the prediction accuracy of solid waste production. The effectiveness of the proposed method is verified by Washington state electronic solid waste data. The …
Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang
Job Shop Rescheduling Under Recessive Disturbance Based On Digital Twin, Dinghui Wu, Tongrui Zhang, Xiuli Zhang
Journal of System Simulation
Abstract: A new shop rescheduling model driven by digital twin is proposed to solve the problems of disturbance cumulative rescheduling. A scheduling parameter updating method is proposed and a random probability distribution is used to describe the distribution of scheduling parameters to improve the accuracy of scheduling parameters. An implicit disturbance detection model is built based on Siamese Network using real-time data as input to realize the start time of rescheduling. The sample data for scheduling knowledge mining are extracted from the historical scheduling scenarios. Through the Pseudo-Siamese CNN, the mapping relationship between the Process state and machine state is …
Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing
Research On Binocular Ranging System Based On Image Features, Jinghui Yang, Dekang Liu, Wanhe Du, Lining Xing
Journal of System Simulation
Abstract: Aiming at the problems of large measurement error, single image information, and poor real-time performance in binocular vision ranging, a binocular ranging method based on ORB (oriented fast and rotated brief) features is proposed. Median filtering is performed on the video frame, the ORB feature of the image is extracted, and the Hamming distance with the best matching effect is selected through experiments. The RANSAC (random sample consensus) model estimation is performed on the selected matching points, the mismatches are removed, the model relationship between parallax and true distance is analyzed, the optimal ranging model is constructed and verified …
Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang
Research On Optimization Of Airport Cargo Business Based On Deep Reinforcement Learning, Hongwei Wang, Peng Yang
Journal of System Simulation
Abstract: An intelligent agent technology architecture is adopted to the simulation model development of airport cargo business. Aiming at the optimization of airport cargo resources, a decision support system framework combining deep reinforcement learning (DRL) and airport cargo business simulation model is proposed. The simulated results are applied as the training data of the DRL network, and the DRL is used to optimize operation parameter of the simulation model. The mature system can be run online, which can provide optimized operation order in real time. In order to verify the effectiveness of the architecture, model development and experiments are conducted …
Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong
Research On Active Learning Method And Application Based On Covariance Matrix, Bowen Zhou, Weili Xiong
Journal of System Simulation
Abstract: Since the data collected from industrial processes often contain a large number of unlabeled samples, while the number of labeled samples is small and the cost of manual labeling is high, an active learning method based on covariance matrix is proposed. This method uses labeled samples to establish a Gaussian process regression model, and constructs the covariance matrix between the unlabeled samples, using the value of the determinant of the covariance matrix as an evaluation indicator. While selecting informative unlabeled samples, the similarity between samples is measured to avoid redundant addition of samples, which finally improves model prediction accuracy …
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Research On Algebraic Loop Of Synchronous Generator Simulation Based On Simulink, Shuang Wang, Zhaohui Gao, Siyu Chen, Xiao Tang, Zhan Xi
Journal of System Simulation
Abstract: The problem of algebraic loop is common in Simulink simulation. The existence of algebraic loop will reduce the speed and accuracy of simulation, and even lead to errors in simulation results. Taking the simulation of synchronous generator as an example, the problem of algebraic loop and its elimination method in Simulink simulation are discussed. Starting from the analysis of the basic equations of synchronous generator, the cause of algebraic loop in simulation is discussed, the influence of the algebraic loop on the system simulation is pointed out, using disassembly method and transformation method, focusing on eliminating the algebraic loop, …
An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li
An Improved Atomic Search Algorithm, Jianfeng Li, Di Lu, Hexiang Li
Journal of System Simulation
Abstract: The atom search algorithm (ASO) is a new optimization algorithm proposed by imitating the movement of atoms in the natural world. An improved atomic search algorithm (IASO) is proposed to address the problems of prematureness and slow convergence of ASO in solving complex functions. IASO adds the binding force generated by the historical optimal solution of individual atoms to correct the acceleration of ASO and enhance the global search capability. The two multiplier coefficients are adaptively updated to coordinate the algorithm's global search and local development capabilities. The Gaussian mutation strategy is used to re-update the atomic position and …
Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo
Research On The Simulation Method Of Urban Rail Transit Feedback Assignment, Jianpeng Hu, Xia Luo
Journal of System Simulation
Abstract: Based on the characteristics of a large number of transfer routes in rail transit network, an improved depth first search algorithm is proposed to get the effective travel time of transfer routes between stations. Based on passenger entry and exit timing obtained from the automatic fare collection (AFC) data, the connect relationship between passengers and trains in time and route is obtained from the arrival time and route selection behavior of passengers. Considering the difference of route choice behavior between departure passenger and transfer passenger, the two are distinguished from each other. The dynamically updated travel …
Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang
Simulation Of Robust Optimal Synchronization Control For Direct Drive H-Type Motion Platform, Limei Wang, Hongyan Yao, Kang Zhang
Journal of System Simulation
Abstract: Cell manufacturing is an important organizational form of modern production systems. In scheduling of cell manufacturing systems, machine failures or interruptions are very common in practice, meanwhile the waste due to energy consumption during machine idle time cannot be ignored. Hence the relevant research is with strong significance. This paper considers the problems of machine interruption and energy consumption in cell scheduling, and developed an integer programming model to minimize the makespan as well as the cost of energy consumption during machine idling and the interruption cost. A mixed optimization method is proposed based on improved wolf pack algorithm …
Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang
Modeling Time Series Using Multi-Modality Fuzzy Cognitive Maps, Guoliang Feng, Wei Lu, Jianhua Yang
Journal of System Simulation
Abstract: A multi-modality modeling method for time series data based on fuzzy cognitive maps is proposed to address the problem that a single model is difficult to accurately reflect the multi-modal characteristics of time series.The bootstrap method is used to select multiple sub-sequences from the original time serieswhich contain the diverse modality in the original time series. The fuzzy cognitive map sub-models are constructed on each sub-sequencesrespectively. The formed sub-models are further merged by means of granular computing method and the merging performance with different weighting strategies is analyzed. The developed multi-modal model not only has prediction abilities at …
Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng
Research On Information Flow Integrated M&S Method For Project Type Manufacturing Process, Mindong Liu, Longjun Wu, Mingchao Tang, Mei Meng
Journal of System Simulation
Abstract: The project type manufacturing process is quite common in shipbuilding and construction industries. Aiming at the problem that the existing discrete manufacturing system modeling and simulation method for flow shop cannot effectively express and imitate this process, taking shipyard dock shop hoisting process as an example, we analyze its components structure, propose a working network-centric, information flow and work flow integrated simulation modelling method, and design a dedicated simulation algorithm with the task process interactive idea. A prototype simulation program is developed with Python language, and the effectiveness of the proposed modelling and simulation method is verified through …
Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang
Research On Optimization Of Network Resource Utilization In Static Segment Of Flexray Bus, Xinhang He, Erkang Li, Hongchao Zhang
Journal of System Simulation
Abstract: In order to improve the utilization of the network resources of the FlexRay bus, the network is optimized for static segment scheduling. The FlexRay communication mechanism is analyzed, the message model is established and the calculation method of bandwidth loss is derived, while considering the protocol overhead and network idling, taking the number of static frames and the length of the static frame payload as design variables, the overall optimal packaging scheme is obtained by solving this multi-objective optimization problem. This solution is finally applied to the vehicle chassis integrated control system for simulation analysis and verification. The results …
Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye
Research On Joint Optimization Of Energy-Saving Distributed Manufacturing And Preventive Maintenance For Semiconductor Wafers, Jun Dong, Chunming Ye
Journal of System Simulation
Abstract: Aiming at the joint optimization problem of energy-saving distributed manufacturing and preventive maintenance for semiconductor wafers, a two-stage green scheduling model considering both the manufacturing stage and the inspection and repair stage is established to minimize the makespan, the total carbon emissions and the total preventive maintenance cost. An improved hybrid multi-objective grey wolf optimization (IHMGWO)algorithm is proposed. The decoding schemes of factory allocation strategy, machine allocation strategy and synchronous scheduling maintenance strategy considering the flexibility of maintenance workers are designed in IHMGWO. By designing the initial population fusion strategy, predation behavior search strategy, and sub-population mutation strategy, the …
Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan
Research On The Construction Method Of Simulation Evaluation Index Of Operation Effectiveness Operation Concept Traction, Ziwei Zhang, Liang Li, Zhiming Dong, Yifei Wang, Li Duan
Journal of System Simulation
Abstract: Agents are difficult to be directly modeled and simulated due to the complexity of their own interaction and learning behaviors. Aiming at the common problems in the discrete simulation of the agent, the event transfer mechanism of the discrete event system specification (DEVS) atomic model is applied to express the interaction and learning of an agent. Through the interaction mode of the agent, the transfer control of multi-state external events, the port connection mode, as well as the introduction of reinforcement learning event transfer representation, a discrete simulation construction method of the agent based on the DEVS atomic model …
Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan
Path-Based Model For The Heterogeneous-Fleet Electric Vehicle Routing Problem With Partial Linear Recharging, Weiquan Wang, Ding Ding, Linsha Yan
Journal of System Simulation
Abstract: The heterogeneous-fleet electric vehicle routing problem with partial linear recharging is studied for realistic logistics distribution scenarios using multiple electric vehicle fleets with different transport capacities, driving ranges and acquisition costs. A path-based mixed integer linear model is proposed. The model enumerates the paths visited by all vehicle types between any non-charging nodes, eliminates the infeasible paths through capacity constraints and time window constraints, and eliminates the dominated paths by the dominance criterion. Compared with the traditional charging station replica-based model, this model eliminates the need to set the number of charging station replicas. The results show that the …
Chatgpt Goes To Law School, Jonathan H. Choi, Kristin E. Hickman, Amy B. Monahan, Daniel Schwarcz
Chatgpt Goes To Law School, Jonathan H. Choi, Kristin E. Hickman, Amy B. Monahan, Daniel Schwarcz
Journal of Legal Education
No abstract provided.
Objective Measure Of Working Memory Capacity Using Eye Movements, James Owens, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas G. Ashok, Sampath Jayarathna
Objective Measure Of Working Memory Capacity Using Eye Movements, James Owens, Gavindya Jayawardena, Yasasi Abeysinghe, Vikas G. Ashok, Sampath Jayarathna
Undergraduate Research Symposium
Human-autonomy teaming (HAT) has become an important area of research due to the autonomous systems being developed for different applications, such as remotely controlled aircraft. Many remotely controlled vehicles will be controlled by automated systems, with a human monitor that may be monitoring multiple vehicles simultaneously. The attention and working memory capacity of operators of remote-controlled vehicles must be maintained at appropriate levels during operation. However, there is currently no direct method of determining working memory capacity, which is important because it is a measure for how memory is being stored for a short term and interacting with long term …
Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin
Two-Stage Transfer Learning For Facial Expression Classification In Children, Gregory Hubbard, Megan Witherow, Khan Iftekharuddin
Undergraduate Research Symposium
Studying facial expressions can provide insight into the development of social skills in children and provide support to individuals with developmental disorders. In afflicted individuals, such as children with Autism Spectrum Disorder (ASD), atypical interpretations of facial expressions are well-documented. In computer vision, many popular and state-of-the-art deep learning architectures (VGG16, EfficientNet, ResNet, etc.) are readily available with pre-trained weights for general object recognition. Transfer learning utilizes these pre-trained models to improve generalization on a new task. In this project, transfer learning is implemented to leverage the pretrained model (general object recognition) on facial expression classification. Though this method, the …