Towards Smart City Security: Violence And Weaponized Violence Detection Using Dcnn,
2022
Mohamed bin Zayed University of Artificial Intelligence
Towards Smart City Security: Violence And Weaponized Violence Detection Using Dcnn, Toluwani Aremu, Li Zhiyuan, Reem Alameeri, Moayad Aloqaily, Mohsen Guizani
Machine Learning Faculty Publications
In this ever connected society, CCTVs have had a pivotal role in enforcing safety and security of the citizens by recording unlawful activities for the authorities to take actions. In a smart city context, using Deep Convolutional Neural Networks (DCNN) to detection violence and weaponized violence from CCTV videos will provide an additional layer of security by ensuring real-time detection around the clock. In this work, we introduced a new specialised dataset by gathering real CCTV footage of both weaponized and non-weaponized violence as well as non-violence videos from YouTube. We also proposed a novel approach in merging consecutive video …
Student
Computational Models To Detect Radiation In Urban Environments: An Application Of Signal Processing Techniques And Neural Networks To Radiation Data Analysis, Jose Nicolas Gachancipa
Beyond: Undergraduate Research Journal
Radioactive sources, such as uranium-235, are nuclides that emit ionizing radiation, and which can be used to build nuclear weapons. In public areas, the presence of a radioactive nuclide can present a risk to the population, and therefore, it is imperative that threats are identified by radiological search and response teams in a timely and effective manner. In urban environments, such as densely populated cities, radioactive sources may be more difficult to detect, since background radiation produced by surrounding objects and structures (e.g., buildings, cars) can hinder the effective detection of unnatural radioactive material. This article presents a computational model …
Self-Distilled Vision Transformer For Domain Generalization,
2022
Mohamed bin Zayed University of Artificial Intelligence
Self-Distilled Vision Transformer For Domain Generalization, Maryam Sultana, Muzammal Naseer, Muhammad Haris Khan, Salman Khan, Fahad Shahbaz Khan
Computer Vision Faculty Publications
In recent past, several domain generalization (DG) methods have been proposed, showing encouraging performance, however, almost all of them build on convolutional neural networks (CNNs). There is little to no progress on studying the DG performance of vision transformers (ViTs), which are challenging the supremacy of CNNs on standard benchmarks, often built on i.i.d assumption. This renders the real-world deployment of ViTs doubtful. In this paper, we attempt to explore ViTs towards addressing the DG problem. Similar to CNNs, ViTs also struggle in out-of-distribution scenarios and the main culprit is overfitting to source domains. Inspired by the modular architecture of …
Reinforcement Actor-Critic Learning As A Rehearsal In Microrts,
2022
The University of Southern Mississippi
Reinforcement Actor-Critic Learning As A Rehearsal In Microrts, Shiron Manandhar
Master's Theses
Real-time strategy (RTS) games have provided a fertile ground for AI research with notable recent successes based on deep reinforcement learning (RL). However, RL remains a data-hungry approach featuring a high sample complexity. In this thesis, we focus on a sample complexity reduction technique called reinforcement learning as a rehearsal (RLaR), and on the RTS game of MicroRTS to formulate and evaluate it. RLaR has been formulated in the context of action-value function based RL before. Here we formulate it for a different RL framework, called actor-critic RL. We show that on the one hand the actor-critic framework allows RLaR …
A Modified Point Matching Method For Non-Rigid Image Registration,
2022
1.Dept. of Computer Science and Technology, Changzhi College, Changzhi 046011, China;
A Modified Point Matching Method For Non-Rigid Image Registration, Jintai Shangguan, Yawen Dang, Wei Lian
Journal of System Simulation
Abstract: Aiming at the problem that the registration results tend to converge to local minima due to the complexity of the relative position changes between two point sets in the non-rigid body point matching process, a joint estimation method for non-rigid body point matching based on precenter alignment is proposed, a modified matching method for non-rigid image registration based on centre preregistration is proposed. To better achieve the point matching accuracy between two point sets, a centre preregistration step is applied before the iterative closest point matching algorithm, which converges to a solution more close to a global optimum and …
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning,
2022
1.Graduate school, National Defense University, Beijing 100091;2.Joint Operations College, National Defense University, Beijing 100091;
Transfer Method Of Operational Simulation Experiment Scope Using Compromised Case-Based Reasoning, Jun Ma, Jingyu Yang, Xi Wu
Journal of System Simulation
Abstract: The scope of operational simulation experiment is usually determined by experts, which costs relatively high. In order to transfer the knowledge of experimental scope selection from historical data of operational simulation experiment to new operational experiment cases, the method of compromised case-based reasoning is proposed. According to the data characteristics of the case, the representation method of the operational simulation experiment case is proposed; according to the structure and attribute characteristics of the case, the hybrid similarity calculation method of subjective and objective comprehensive weighting is proposed; aiming at the problems of retrieval failure and less information content …
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading,
2022
1.North China Electric Power University, Beijing 102206, China;
Optimal Dispatch Of Integrated Energy System Considering Ladder-Type Carbon Trading, Liying Wang, Jialin Lin, Houqi Dong, Ming Zeng, Yuqing Wang
Journal of System Simulation
Abstract: With the development of the electricity market and carbon market,the introduction of demand response and carbon trading mechanisms into the operation and dispatch of integrated energy systems will help guide users and system operators to optimize electricity consumption and dispatch plans.The comprehensive incentive measures such as time-of-use electricity prices and demand response incentive subsidies are used to guide users to participate in demand response.A two-layer stochastic optimal scheduling model for a comprehensive energy system considering the ladder-type carbon trading mechanism and demand response is constructed based on IGDT (information gap decision theory) theory.The two-layer model is converted …
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage,
2022
1.State Grid Anhui Electric Power Company, Bengbu Power Supply Company, Bengbu 233000, China;
Bi-Level Optimization Of Distribution Network For Hybrid Energy Storage System Of Storage Battery And Hydrogen Storage, Feibo Feng, Xingde Yan, Baoqiang Zheng, Xiaofeng Yin, Mengzhen Zhou, Xin Jiang
Journal of System Simulation
Abstract: Under the background of carbon neutralization and emission peaking goals and the utilization of clean hydrogen energy, aiming at the demand of distribution network configuring electrochemical energy storage and hydrogen energy storage system to form a hybrid energy storage system to improve power quality, a bi-level optimization model of the hybrid energy storage system is established. The upper level location and capacity model comprehensively considers the investment cost, network loss cost and voltage offset, while the lower level optimization operation model considers the operation cost of hybrid energy storage system, and the voltage stability index is introduced for evaluation. …
Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation,
2022
1.State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;
Modeling And Simulation Of Optimal Strategy For Electric Vehicles Participating In Power Grid Frequency Regulation, Li Yao, Junjie Hu, Wenshuai Ma, Zhile Yang
Journal of System Simulation
Abstract: Electric vehicles (EVs) have similar characteristics of distributed energy storage, and making full use of the flexibility of EVs can provide ancillary services to the grid and gain benefits. Considering the influence of uncertain factors, a bidding model for electric vehicle aggregator (EVA) to participate in the day-ahead energy market and frequency regulation ancillary service market is constructed with the maximum revenue expectation of EVA as the target. A real-time energy distribution incentive strategy based on contract theory is proposed to realize the distribution of EVA's frequency regulation demand under the condition of maximizing social welfare. Through case studies, …
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence,
2022
1.School of Computer and Information Engineering, Central South University of Forestry & Technology, Changsha 410004, China;
Simulation Model Of Forest Fire Spread Based On Swarm Intelligence, Aibin Chen, Fubo Ding, Guoxiong Zhou, Bo Zhou
Journal of System Simulation
Abstract: Aiming at the shortcomings of high computational complexity and low simulation accuracy of traditional forest fire spread model, a forest fire spread simulation model based on swarm intelligence is proposed.By establishing fuel factor matrix and landform factor matrix, and combining with the real-time meteorological information, the computational complexity is reduced; the spread behavior of the forest fire is abstracted as the cluster behavior of each module fire point, and the correlation between modules is considered to improve the accuracy of forest fire spread simulation model.The model is compared with Wang Zhengfei model and two-dimensional cellular automata model. …
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem,
2022
1.Faculty of Information Engineering and Automation, Kunming University of Science and Technology, Kunming 650500, China;
Two Stage Optimization Algorithm To Solve The Green Packing Vehicle Routing Problem, Rong Hu, Wen Jiang, Bin Qian, Naikang Yu
Journal of System Simulation
Abstract: The green open vehicle routing problem with two-dimensional loading constraints (2L-GOVRP) is integration of the green open vehicle routing problem and two-dimensional bin packing problem. The model of 2L-GOVRP is established and a two-stage optimization algorithm (TSOA) is proposed to minimize fuel consumption. In the first stage of TSOA, adaptive whale optimization algorithm (AWOA) is designed to solve the vehicle routing problem, which determine the initial delivery route of the vehicle (the initial solution of 2L-GOVRP). The algorithm has four kinds of variable neighborhoods local operation to perform a local search. In the second stage of TSOA, the skyline …
A Method Of Loose Coupling Entity Modeling Based On Variable Rules,
2022
Electronic Encounter Institution, National University of Defense Technology, Hefei 230037, China;
A Method Of Loose Coupling Entity Modeling Based On Variable Rules, Zheng Yang, Zhimin Xiang, Shiwen Ma
Journal of System Simulation
Abstract: Operational Entity Modeling is a hot research topic in the field of combat simulation. A loose coupling entity modeling method based on variable rules is proposed. The architecture of operational entity model based on variable rules and the internal and external interaction mechanism of the model are presented in terms of entity, mission, action, interaction, event and rule. On this basis, the running framework of operational entity model is designed, and the entity model uniform scheduling mechanism is standardized, which solves the problems of over-tight coupling of operational rules in the operational entity model and low reliability of the …
Research On Prediction Of Model Based On Multi-Scale Lstm,
2022
School of Information Science and Engineering, East Chines of Science and Technology, Shanghai 200237, China;
Research On Prediction Of Model Based On Multi-Scale Lstm, Junjie Qiu, Hong Zheng, Yunhui Cheng
Journal of System Simulation
Abstract: Aircraft engine remaining useful life (RUL) prediction is the core issue in equipmentfailure prognostics and health management (PHM). Aiming at the characteristics of high dimensionality, high lag and complexity of engine data, a multi-scale attention-based bidirectional long short-term memory neural network model based on self-training weights is proposed. Multi-scale features are extracted through bidirectional long short-term memory neural network (BiLSTM) of different scales. A fusion algorithm based on self-training weights is proposed, and an attention mechanism is introduced to screen features at different scales to improve prediction accuracy. Various models are compared on the NASA's C-MAPSS data set. The …
Space Science Satellite Data Processing Framework Research And System Implementation,
2022
1.Computer Network Information Center, Chinese Academy of Sciences, Beijing 100190, China;2.National Space Science Center, Chinese Academy of Sciences, Beijing 100190, China;3.University of Chinese Academy of Sciences, Beijing 100049, China;
Space Science Satellite Data Processing Framework Research And System Implementation, Wenzhen Ma, Ziming Zou, Jianhui Li, Qinsi Yu, Jizhou Tong, Jingjing Li
Journal of System Simulation
Abstract: Based on the needs of China's space science strategy and series of on-orbit and forthcoming satellite missions in China's Strategic Priority Program on space science, data processing framework and key technologies of the satellite ground segment are studied. A general technical framework SDPF (space science satellite data processing framework) is proposed with two-layer scheduling engine, including mission-level and resource-level. The design and implementation of an automatic, efficient, real-time and standard space science satellite data processing system has been established. In this way, complicated processing procedures on large-scale data from multi-satellite missions and multi-payload can be completed quickly in parallel. …
Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks,
2022
Academy of Military Science, Beijing 100091, China;
Ultra-Real-Time Visual Simulation System For Multi-View Rendering Tasks, Xunyun Liu, Xinhai Xu, Chengzhang Zhu, Hao Li, Lei Zeng
Journal of System Simulation
Abstract: For multi-view rendering tasks, a theoretical analysis of ultra-real-time visual simulation is given in terms of implementation principle and feasibility. Based on the theoretical results, an ultra-real-time visual simulation architecture is designed, which decouples the simulation and rendering computation. A parallel-rendering-based ultra-real-time visual simulation method is proposed to solve the problems of rendering task assignment, simulation world synchronization, and rendering-execution time selection. An ultra-real-time visual simulation system is implemented based on Unreal Engine 4 (UE4), the performance of which is demonstrated on a designated application case per rendering efficiency and ultra-real-time simulation.
Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn,
2022
School of Information Science and Engineering, East China University of Science and Technology, Shanghai 200237, China;
Verification Of Transaction Ordering Dependence Vulnerability Of Smart Contract Based On Cpn, Hong Zheng, Zerun Liu, Jianhua Huang, Shihui Qian
Journal of System Simulation
Abstract: The formal verification of smart contracts researches mainly focus on programming language-level vulnerabilities, and the transaction ordering dependence is more difficult to be detected as a blockchain-level vulnerability.The latent transaction ordering dependence vulnerability in smart contracts is formally verified based on colored Petri nets.The latent vulnerability in the Decode reward contractis analyzed, anda colored Petri net model of the contract itself and its execution environment is established from top to bottom.The attacker model is introduced to consider the situation that the contract is attacked. By running the model to verify the existence of transaction ordering dependence vulnerability in …
Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components,
2022
Zhejiang Provincial Key Laboratory of Solar Energy Utilization & Energy Saving Technology, Zhejiang Energy Group R&D, Hangzhou 311121, China;
Modeling And Simulation Of Sofc System With Heat Transfer Among Bop Components, Ling Hong, Rongmin Wu, Jianwu Zhou, Tian Xia, Xiaojie Li, Pengjie Tian, Hao Peng, Chunhui Shou
Journal of System Simulation
Abstract: High temperature solid oxide fuel cell (SOFC) is a high temperature and efficient hydrogen-electric conversion device. Its high temperature operating environment puts forward higher requirements for thermal insulation of stack and balance of plants(BoP) in the system. In this paper, a lumped SOFC system model is established based on the thermal efficiency-heat transfer unit number method (ε-NTU method), in combination with limited measurable parameters for high-temperature system.Quantitative analysis of components temperature and heat transfer among components can be achieved by heat exchange simulation between components and BoP hot-box environment. A simple feedback controlleris designed for system self-starting and operation. …
Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics,
2022
College of Information and Communication Engineering, Harbin Engineering University, Harbin 150001, China;
Research On Multi-Robot Slam Map Fusionmethod Based On Heuristics, Tong Wang, Guangtao Shang, Shan Gao
Journal of System Simulation
Abstract: Simultaneous Localization and Mapping (SLAM) is a key technology for mobile robots to complete map construction and positioning tasks in an unknown environment. Aiming at the map fusion problem in multi-robot SLAM, a heuristic search method is proposed to guide the repeated regions of the local map for map fusion. Each robot can build a local map without knowing its relative position, and send the local map information to the same workstation, and use the similarity of the local map as the judgment index to fuse to obtain the optimal global map.Verified on the robot physical platform, the …
Aerial Target Threat Assessment Method Based On Deep Learning,
2022
1.School of Computer Science and Technology, Xidian University, Xi'an 710071, China;2.Science and Technology on Electro-Optical Information Security Control Laboratory, Tianjin 300308, China;
Aerial Target Threat Assessment Method Based On Deep Learning, Huimin Chai, Yong Zhang, Xinyue Li, Yanan Song
Journal of System Simulation
Abstract: Due to many factors of aerial target threat assessment and the lack of self-learning ability of current assessment methods, a deep neural network model for aerial target threat assessment is established using deep learning theory. In order to improve the fitting effect of the model training, a symmetric pre-training method is given. The hidden layers of the model are pre-trained layer by layer, and finally the whole model is trained. Sample data and air to air simulation scene experiments are carried out respectively. The experiments results show that the accuracy of the model using the symmetric pre-training method is …
Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System,
2022
School of Computer and Information, Hohai University, Nanjing 211100, China;
Game-Based Resource Allocation And Task Offloading Scheme In Collaborative Cloud-Edge Computing System, Xuewen Wu, Jingxian Liao
Journal of System Simulation
Abstract: Considering the delay, energy consumption and computing resource cost, the utility maximization problem in collaborative cloud-edge system is constructed, and divided into three subproblems: computing resource allocation, uplink power allocation and task offloading strategy. A game-based resource allocation and task offloading(GRATO) scheme is proposed to solve those subproblems. The optimal solution of computing resource allocation is obtained by using convex optimization conditions; a low complexity uplink power allocation method is designed to reduce wireless interfere; a game-based distributed task offloading algorithm (GDTOA) is proposed to optimize the task offloading strategy. Simulation results show that the performance of GRATO is …
