Study On Three-Dimensional Scene Sar Radio Frequency Simulation Technology,
2020
1. Science and Technology on Complex System Control and Intelligent Agent Cooperation Laboratory, Beijing 100074, China;;2. Beijing Electro-mechanical Engineering Institute, Beijing 100074, China;
Study On Three-Dimensional Scene Sar Radio Frequency Simulation Technology, Guijie Diao, Ni Hong, Yang Liang
Journal of System Simulation
Abstract: Synthetic Aperture Radar (SAR) radio frequency simulation technology for three-dimensional scene is significant for SAR system test and the research of signal processing algorithms. A SAR radio frequency signal simulation is the core technology. Based on preliminary SAR frequency simulation scheme, a real-time SAR radio frequency signal simulation method for three-dimensional scene is proposed, and key parameters such as backward scattering coefficient, range between radar and target, shielding factor, antenna pattern weighting factor are calculated in real time according to the flight path information of SAR radar platform. Finally, the test results proved the validity of the method.
Matching Between Mac Address And Object Based On Rssi Change Sequence,
2020
Tianjin Key Lab of Advanced Signal Processing, Civil Aviation University of China, Tianjin 300300, China;
Matching Between Mac Address And Object Based On Rssi Change Sequence, Zhang Liang, Kaifeng Hao
Journal of System Simulation
Abstract: The connection between real people and the MAC of the communications device is of high value to public and network security. A better solution was proposed to improve the existing methods. MAC and real-time RSSI changes of the communication device were obtained by multiple Wi-Fi probes, then the RSSI status change sequence was constructed. The distance between object and multiple Wi-Fi probes was obtained by the object tracking, and the sequence of distance state change was constructed. After two kinds of sequences were compared, the optimal result was selected as the matching result between the moving object and the …
State Of Charge Estimation Of The Lithium-Ion Battery Based On Improved Extended Kalman Particle Filter Algorithm,
2020
1. College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China;;
State Of Charge Estimation Of The Lithium-Ion Battery Based On Improved Extended Kalman Particle Filter Algorithm, Xia Fei, Zhicheng Wang, Shuotao Hao, Daogang Peng, Beili Yu, Yimin Huang
Journal of System Simulation
Abstract: The three order Thevenin model of 18650 Lithium-Ion battery is established based on the experimental data of UTS divided capacity tester. The extended kalman filtering (EKF) algorithm is adopted as the important density function of particle filter (PF) algorithm, and the extended Kalman particle filter (EKPF) algorithm is formed. The sample degradation and lack of diversity in the re-sampling stage of EKPF algorithm is optimized by an improved re-sampling algorithm which based on a weight sorting and survival of the fittest particles. The improved EKPF algorithm is applied to estimate the State of Charge (SOC) of the three order …
Curvature-Based Bp Algorithm Optimization And Its Application In Fnn,
2020
1. School of Internet of Things Engineering, Jiangnan University, Wuxi 214122, China;;2. Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education), Jiangnan University, Wuxi 214122, China;
Curvature-Based Bp Algorithm Optimization And Its Application In Fnn, Weili Xiong, Wenxin Sun, Xudong Shi
Journal of System Simulation
Abstract: In order to improve the optimization efficiency of BP algorithm affected by the selection of step size, a step size optimization BP algorithm based on curvature information is proposed and applied to the training process of FNN (Fuzzy Neural Network). Reference to Newton's method, The gradient of the cost function and the curvature information in the direction are calculated to determine the direction and magnitude of the parameter adjustment in each iteration. This method only needs to consider the two order information of the gradient direction, so it does not need the storage and processing of Hessian matrix. The …
Low-Complexity Apit Algorithm And Its Opnet Simulation Of Underwater Acoustic Sensor Networks,
2020
Key Laboratory of Underwater Acoustic Communication and Marine Information Technology of Ministry of Education, Xiamen University, Xiamen 361005, China;
Low-Complexity Apit Algorithm And Its Opnet Simulation Of Underwater Acoustic Sensor Networks, Jiahui Xu, Keyu Chen, En Chen
Journal of System Simulation
Abstract: Due to the energy limitations of underwater acoustic sensor networks, low-complexity location algorithms are more suitable for underwater acoustic sensor networks. The traditional APIT algorithm can obtain better location accuracy with less control overhead, which is beneficial to the location of underwater sensor networks, but it has high complexity and large redundancy errors. This paper proposes a low-complexity APIT algorithm replaced the traditional grid SCAN algorithm with a point scanning method, and builds an underwater acoustic sensor network environment on the OPNET platform, and elaborates the implementation process of the location algorithm in underwater sensor network. Simulation results …
Study On Infrared Radiation Of Nmp Recovery System In Lithium Battery Pole Piece,
2020
School of Mechanical Engineering, Hebei University of Technology, Tianjin 300132, China;
Study On Infrared Radiation Of Nmp Recovery System In Lithium Battery Pole Piece, Yanjun Xiao, Yang Huan, Yanping Kang
Journal of System Simulation
Abstract: The structure design of the NMP recovery system in the lithium battery pole piece coating process has many technology difficulties, including the vacuum and infrared radiation heating technology. For vacuum system, after the analysis of its impact on the coating process, and the drying needs of the NMP recovery system, through the analytic hierarchy process, the most suitable infrared radiation heater type can be determined. The process of recovering gaseous NMP is numerically simulated, and the simulation results of the system flow performance are obtained. The parameters of the drying time, arrangement mode and other parameters are determined by …
Research On The Mvc-Based Generation Of Test Paper And The Algorithm Of Subjective Criterion,
2020
1. School of Computer and Information, Hefei University of Technology, Hefei 230009, China;;
Research On The Mvc-Based Generation Of Test Paper And The Algorithm Of Subjective Criterion, Cuicui Zhang, Guoxiang Zhou, Yu Lei, Shi Lei, Qingqing Wang
Journal of System Simulation
Abstract: At home and abroad, the formed test system has a mature algorithm to the objective problem. However, there are still some problems in the subjective questioning. Therefore, it is feasible to design a MVC(Model View Controller) framework for the dynamic generation of papers, and to propose an automatic algorithm. In the paper volume generation system, the paper page is generated dynamically by the distributed view and the component loading technique. In the subjective automatic questioning algorithm, a bidirectional traversal space model algorithm is proposed, which uses the key words bidirectional matching and vector space model to calculate the answer …
Research On Evacuation Simulation Method Considering Social Behavior,
2020
VCC Laboratory, School of Computer and Information, Hefei University of Technology, Hefei 230009, China;
Research On Evacuation Simulation Method Considering Social Behavior, Yuanyuan Deng, Liping Zheng, Ruiwen Cai
Journal of System Simulation
Abstract: In an emergency evacuation scenario, the typical social attributes of an individual impact their evacuation behavior. Two kinds of social factors, such as individual familiarity to the environment and the individual group, are introduced and applied in crowd evacuation simulation. An evacuation simulation method is proposed. The real-time collision avoidance technique of RVO library is used to simulate the dynamic motion of the population. The local target points and its selection mechanism are used to simulate the different social behaviors of the population. Experiments show that the familiarity to the environment and group factors have influence on the evacuation …
Research On Flexray Network Optimization Based On Switched Message Scheduling Algorithm,
2020
Department of Electronic and communication Yanbian University, Yanji 133002, China;
Research On Flexray Network Optimization Based On Switched Message Scheduling Algorithm, Yinan Xu, Xiangqi Kong, Mengzhuo Liu
Journal of System Simulation
Abstract: The development of vehicle electronic technology needs advanced in-vehicle communication network. Because of the high transmission speed, reliability and the flexible topology structure, the FlexRay network has become the most popular in-vehicle communication protocol in recent years. In order to meet the demand of network development, a scheduling algorithm based on switched FlexRay network was designed, and a new method that could calculate the Static segment and the worst case response time of Dynamic segment was put forward. The result of the simulation experiment shows that the transmission speed improves 26%, the slot number decreases by 44% and …
Cruise Missile Path Planning Based On Aco Algorithm And Bezier Curve Optimization,
2020
1. Dept. of Military Oceanography & Hydrography, Dalian Naval Academy, Dalian 116018, China;;
Cruise Missile Path Planning Based On Aco Algorithm And Bezier Curve Optimization, Shi Yan, Lihua Zhang, Shouquan Dong, Jue Wang
Journal of System Simulation
Abstract: For the low-altitude penetration of cruise missile, there is a large number of steering points and a larger steering angle in missile path planning based on ant colony algorithm. In order to solve this problem, a three-dimensional path planning method based on ant colony algorithm and Bezier curve optimization is proposed. The planning path node generated by ant colony algorithm was used as the control point to generate the flight path of Bezier curve, and then the curve was changed to be broken lines path. In order to avoid the unnavigable section, using the breadth first search algorithm to …
Research On Active Training Compliance Control Of Ankle Rehabilitation Robot,
2020
1. School of Mechatronics Engineering, Henan University of Science and Technology, Luoyang 471003, China;;2. Collaborative Innovation Center of Machinery Equipment Advanced Manufacturing, Henan Province, Henan University of Science and Technology, Luoyang 471003, China;
Research On Active Training Compliance Control Of Ankle Rehabilitation Robot, Yanbin Liu, Xiangyuan Pang, Yanbin Zhang, Bingjing Guo, Jianhai Han
Journal of System Simulation
Abstract: In order to ensure that ankle rehabilitation robot can accurately supply arbitrary characteristic training force for patient during active training, the pneumatic muscle redundant parallel driving ankle rehabilitation robot was taken as research objects, the zero error force tracking method and the compliance control strategy for active training were researched. The dynamics model of the ankle rehabilitation robot were set up, based on the impedance control theory, the trajectory planning method for the zero error force tracking was researched, and based on the Lyapunov’s stability theory, the pneumatic muscle redundant parallel driving compliance control strategy was proposed. Rehabilitation training …
Final Presentation To The Library Of Congress On Digital Libraries, Intelligent Data Analytics, And Augmented Description,
2020
University of Nebraska - Lincoln
Final Presentation To The Library Of Congress On Digital Libraries, Intelligent Data Analytics, And Augmented Description, Elizabeth Lorang, Leen-Kiat Soh, Yi Liu, Chulwoo Pack
University of Nebraska-Lincoln Libraries: Presentations
This presentation to Library of Congress staff, delivered onsite on January 10, 2020, presents a tour through the demonstration project pursued by the Aida digital libraries research team with the Library of Congress in 2019-2020. In addition to providing an overview and analysis of the specific machine learning projects scoped and explored, this presentation includes a number of high-level take-aways and recommendations designed to influence and inform the Library of Congress's machine learning efforts going forward.
Digital Libraries, Intelligent Data Analytics, And Augmented Description: A Demonstration Project,
2020
University of Nebraska - Lincoln
Digital Libraries, Intelligent Data Analytics, And Augmented Description: A Demonstration Project, Elizabeth Lorang, Leen-Kiat Soh, Yi Liu, Chulwoo Pack
University of Nebraska-Lincoln Libraries: Faculty Publications
From July 16-to November 8, 2019, the Aida digital libraries research team at the University of Nebraska-Lincoln collaborated with the Library of Congress on “Digital Libraries, Intelligent Data Analytics, and Augmented Description: A Demonstration Project.“ This demonstration project sought to (1) develop and investigate the viability and feasibility of textual and image-based data analytics approaches to support and facilitate discovery; (2) understand technical tools and requirements for the Library of Congress to improve access and discovery of its digital collections; and (3) enable the Library of Congress to plan for future possibilities. In pursuit of these goals, we focused our …
The Future Of Work Now: Medical Coding With Ai,
2020
Babson College
The Future Of Work Now: Medical Coding With Ai, Thomas H. Davenport, Steven M. Miller
Research Collection School Of Computing and Information Systems
The coding of medical diagnosis and treatment has always been a challenging issue. Translating a patient’s complex symptoms, and a clinician’s efforts to address them, into a clear and unambiguous classification code was difficult even in simpler times. Now, however, hospitals and health insurance companies want very detailed information on what was wrong with a patient and the steps taken to treat them— for clinical record-keeping, for hospital operations review and planning, and perhaps most importantly, for financial reimbursement purposes.
Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework,
2020
Mike Illitch School Of Business, Wayne State University, Detroit, MI
Machine Learning In Manufacturing: Review, Synthesis, And Theoretical Framework, Ajit Sharma, Zhibo Zhang, Rahul Rai
Business Administration Faculty Research Publications
There has been a paradigmatic shift in manufacturing as computing has transitioned from the programmable to the cognitive computing era. In this paper we present a theoretical framework for understanding this paradigmatic shift in manufacturing and the fast evolving role of artificial intelligence. Policy, Strategic and Operational implications are discussed. Implications for the future of strategy and operations in manufacturing are also discussed. Future research directions are presented.
Robotically Steered Needles: A Survey Of Neurosurgical Applications And Technical Innovations,
2020
Old Dominion University
Robotically Steered Needles: A Survey Of Neurosurgical Applications And Technical Innovations, Michel A. Audette, Stéphane P.A. Bordas, Jason E. Blatt
Computational Modeling & Simulation Engineering Faculty Publications
This paper surveys both the clinical applications and main technical innovations related to steered needles, with an emphasis on neurosurgery. Technical innovations generally center on curvilinear robots that can adopt a complex path that circumvents critical structures and eloquent brain tissue. These advances include several needle-steering approaches, which consist of tip-based, lengthwise, base motion-driven, and tissue-centered steering strategies. This paper also describes foundational mathematical models for steering, where potential fields, nonholonomic bicycle-like models, spring models, and stochastic approaches are cited. In addition, practical path planning systems are also addressed, where we cite uncertainty modeling in path planning, intraoperative soft tissue …
Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management,
2020
University of Denver
Deep Reinforcement Learning For The Optimization Of Building Energy Control And Management, Jun Hao
Electronic Theses and Dissertations
Most of the current game-theoretic demand-side management methods focus primarily on the scheduling of home appliances, and the related numerical experiments are analyzed under various scenarios to achieve the corresponding Nash-equilibrium (NE) and optimal results. However, not much work is conducted for academic or commercial buildings. The methods for optimizing academic-buildings are distinct from the optimal methods for home appliances. In my study, we address a novel methodology to control the operation of heating, ventilation, and air conditioning system (HVAC).
We assume that each building in our campus is equipped with smart meter and communication system which is envisioned in …
Automated Change Detection In Privacy Policies,
2020
University of Denver
Automated Change Detection In Privacy Policies, Andrick Adhikari
Electronic Theses and Dissertations
Privacy policies notify Internet users about the privacy practices of websites, mobile apps, and other products and services. However, users rarely read them and struggle to understand their contents. Also, the entities that provide these policies are sometimes unmotivated to make them comprehensible. Due to the complicated nature of these documents, it gets even harder for users to understand and take note of any changes of interest or concern when these policies are changed or revised.
With recent development of machine learning and natural language processing, tools that can automatically annotate sentences of policies have been developed. These annotations can …
Deep Siamese Neural Networks For Facial Expression Recognition In The Wild,
2020
University of Denver
Deep Siamese Neural Networks For Facial Expression Recognition In The Wild, Wassan Hayale
Electronic Theses and Dissertations
The variation of facial images in the wild conditions due to head pose, face illumination, and occlusion can significantly affect the Facial Expression Recognition (FER) performance. Moreover, between subject variation introduced by age, gender, ethnic backgrounds, and identity can also influence the FER performance. This Ph.D. dissertation presents a novel algorithm for end-to-end facial expression recognition, valence and arousal estimation, and visual object matching based on deep Siamese Neural Networks to handle the extreme variation that exists in a facial dataset. In our main Siamese Neural Networks for facial expression recognition, the first network represents the classification framework, where we …
Facial Action Unit Detection With Deep Convolutional Neural Networks,
2020
University of Denver
Facial Action Unit Detection With Deep Convolutional Neural Networks, Siddhesh Padwal
Electronic Theses and Dissertations
The facial features are the most important tool to understand an individual's state of mind. Automated recognition of facial expressions and particularly Facial Action Units defined by Facial Action Coding System (FACS) is challenging research problem in the field of computer vision and machine learning. Researchers are working on deep learning algorithms to improve state of the art in the area. Automated recognition of facial action units has man applications ranging from developmental psychology to human robot interface design where companies are using this technology to improve their consumer devices (like unlocking phone) and for entertainment like FaceApp. Recent studies …
