Interference Management Mechanism In Next Generation Dense Wlan,
2020
School of Telecommunications Engineering, Xidian University, Xi'an 710071, China;
Interference Management Mechanism In Next Generation Dense Wlan, Ronghui Hou, Xiaoyao Ma, Liu Yi, Hongyan Li
Journal of System Simulation
Abstract: Aiming at the unfairness and low throughput in a wireless local area network with dense access points and terminals deployment, a user-centered resource allocation method which can configure the specific channel and power level for each user is proposed. This method can maximize the network throughput while ensuring the minimum throughput requirement for each user. The proposed interference management mechanism and user identification method can be easily implemented in the current wireless local area network system. Simulation results show that the proposed resource allocation scheme enhances about 47.3% throughput to a basic service set. In particular, 190% improvement can …
Cuckoo Search Algorithm With Dynamic Step And Discovery Probability,
2020
1. Institute of Intelligent Network System, Henan University, Kaifeng 475004, China;;2. College of Software, Henan University, Kaifeng 475004, China;;
Cuckoo Search Algorithm With Dynamic Step And Discovery Probability, Jingsen Liu, Xiaozhen Liu, Li Yu
Journal of System Simulation
Abstract: In order to further improve the low accuracy and slow convergence speed of algorithm search, a cuckoo search algorithm with dynamic step size and probability of discovery is proposed. The algorithm dynamically constrains the Levy's moving step of each generation by introducing the step adjustment factor, which makes the Levy's flight mechanism adaptive. In the probability of finding, the random inertia weight with uniform distribution and F distribution is used to change the fixed value of the probability of discovery, to strengthen the diversity of the population and to keep the balance between global search and local exploration. The …
Improving The Efficiency Of Transport Systems Using Simulation,
2020
China Simulation Federation
Improving The Efficiency Of Transport Systems Using Simulation, Bushuev Sergey, Kovalev Igor, Permikin Vadim, Anashkina Nataliia
Journal of System Simulation
Abstract: The article describes the possibilities of application of simulation modeling for the analysis of infrastructure and technology of transport services of enterprises. The main technological and possible economic effects for the enterprises arising at performance of modeling of a transport component of their work are resulted.
Optimization Model And Method Of Urban Road Traffic Signal Control Under Rainfall Environment,
2020
1. Beijing Union University, Beijing 100101, China;;
Optimization Model And Method Of Urban Road Traffic Signal Control Under Rainfall Environment, Shaohu Tang, Zhou Jin, Chunlin Shang, Guorong Zheng
Journal of System Simulation
Abstract: The efficiency of urban road traffic operation fell obviously during a rain, and the existing road traffic signal control has not yet established a relevant signal optimization scheme. Considering the traffic operation scenario under the influence of rainfall and road water, an urban road traffic cyber physical systems is designed, a framework of urban road traffic control based on cyber physical systems is built, an optimization model of traffic signal control is established, and further more, the solution method of the model is designed by using BP neural network. Building a traffic simulation model of the example intersection, comparing …
Simulation Research And Application On Urban Rail Transit Fully Automatic Operation System,
2020
1. Traffic Control Technology Co., Ltd, Bejing 100070, China;;
Simulation Research And Application On Urban Rail Transit Fully Automatic Operation System, Du Heng, Chunhai Gao, Huang Qing, Huaiming Cang
Journal of System Simulation
Abstract: Following the development of the key technologies for the Fully Automatic Operation (FAO) of urban rail transit and the application of autonomous fully automatic operation system demonstration projects, more and more urban rail transit lines choose the FAO system. High availability, high reliability and high security also need high requirements on the testing and verification before the line is operated. Through the simulation research of the fully automatic operation system, combined with the comprehensive debugging and verification management platform of the Yanfang Line's fully automatic independent demonstration project, the scenario-based FAO system simulation model is established, the key technologies …
Research On Glide Width Simulation System Of Instrument Landing System,
2020
1. School of Mechatronics, Shenyang Aerospace University, Shenyang 110136, China;;
Research On Glide Width Simulation System Of Instrument Landing System, Chunying Jiang, Yuxiang Kang, Xiaofeng You, Xiaoxin Zhang, Changlong Ye
Journal of System Simulation
Abstract: Based on the principle of the formation of the instrumental landing system ILS(Instrument Landing System) gliding DDM(Different in the Depth of Modulation) index, and the factors that affect DDM are found as the amplitude of SBO(Sideband Only) signal. The relationmodel between the amplitude and the glide width, of the Half-width SBO signal in the linear variation range of DDM are obtained by the control variable method. And Based on the measured data, the correctness of the model is verified. Based on the mathematical model and combined with the NM7000 equipment, a simulation system is built to dynamically …
Monocular Depth Image Mark-Less Pose Estimation Based On Feature Regression,
2020
Key Laboratory of Advanced Control Light Process, Jiangnan University, Wuxi 214000, China;
Monocular Depth Image Mark-Less Pose Estimation Based On Feature Regression, Chen Ying, Shen Li
Journal of System Simulation
Abstract: Monocular camera mark-less pose estimation system suffers low accuracy, robustness and efficiency due to variety of action, self-occlusion of human body. A method of feature exaction from point clouds was proposed, in which a single-to-multiple (S2M) feature regressor and a joint position regressor were designed to quickly and accurately predict the 3D positions of body joints from a single depth image without any temporal information. Experiment result shows that the estimation accuracy is superior to that of state-of-the-arts and multi-camera based methods.
Simulation And Optimization Of Aircraft Sliding Path,
2020
1. College of Electronic Information and Automation, Civil Aviation University of China, Tianjin 300300, China;;
Simulation And Optimization Of Aircraft Sliding Path, Zhiwei Xing, Mingyi Xu, Luo Xiao, Luo Qian
Journal of System Simulation
Abstract: Variable taxiing time is an important indicator to the characteristics of the airport traffic flow assessment, which affects the airport operating efficiency, the passenger satisfaction for the airline and the pollution emissions. For a large hub airport, according to the principle of cellular automata and the congestion of traffic flow, the airport taxiing area is regarded as the network topology of nodes and links, and the conflict between taxi rules and aircraft is taken as the constraint. The simulation analysis is carried out on the basis of constructing the model of airplane departure traffic flow, using Monte Carlo algorithm …
Modelling And Simulation For NoX Emission Concentration Of Scr Denitrification System,
2020
Hebei Technology Innovation Center of Simulation & Optimized Control for Power Generation, North China Electric Power University, Baoding 071003, China;
Modelling And Simulation For NoX Emission Concentration Of Scr Denitrification System, Dong Ze, Laiqing Yan
Journal of System Simulation
Abstract: The selective catalytic reduction (SCR) denitrification system has the features of non-linearity, large lag and strong disturbance, when the operating condition changes. Based on mutual information (MI) and Kernel-based Orthogonal Projections to Latent Structures (KOPLS), the model for NOx emission concentration is proposed. The time-delay of each input variable is estimated by mutual information, and phase space construction is performed, KOPLS is utilized to modelling. KOPLS shows the merits of strong generalization, nonlinear fitting and anti-noise in the simulation of benchmark datasets. According to field data analysis, RMSE of MI-KOPLS in training and test are reduced by 17% …
Research On Approximate Reference Algorithm Of Svdbn Based On Sliding Window,
2020
School of Information and Electronics, Xi'an Polytechnic University, Xi'an 710048, China;
Research On Approximate Reference Algorithm Of Svdbn Based On Sliding Window, Haiyang Chen, Chai Bing, Ruilan Wang, Cao Lu
Journal of System Simulation
Abstract: Structure-variable dynamic Bayesian networks (SVDBN) have the special advantage in dealing with the uncertainty of the unstable processes. In order to overcome the disadvantage that the inference algorithms of the SVDBN are unable to apply online, introducing the concepts of SVDBN sliding window and the window width, the online approximate inference mechanism of structure-variable dynamic Bayesian networks based on sliding window is explained, and two online algorithms are proposed, that is the recursive inference algorithm of structure-variable discrete dynamic Bayesian networks (SVDDBN) based on sliding window and the fast inference algorithm of SVDDBN based on sliding window. Experimental simulations …
Situation Cognition And Decision Modeling Method For Submarine Operation Based On Discriminant Matrix,
2020
1. 92337 Troops, Dalian 116023, China;;
Situation Cognition And Decision Modeling Method For Submarine Operation Based On Discriminant Matrix, Dongjun Zhang, Weiping Wang, Li Xiao, Zhang Lei, Xiaobo Li, Guojie Liu
Journal of System Simulation
Abstract: Submarine operations have the characteristics of dynamic game confrontation in complex environments. Situation cognition and decision (SCD) behavior of combatants have an important impact on the effectiveness of submarine operations. Aiming at the SCD modeling in submarine engagement-level operational experiments, based on analyzing the SCD process, the representative variable set is refined, and a SCD modeling method for submarine operation based on the discrimination matrix is proposed. The submarine engagement-level confrontation is used as an example to study the SCD process in the given scenarios, and the feasibility and effectiveness of the method are verified. The established model …
Responsive Economic Model Predictive Control For Next-Generation Manufacturing,
2020
Wayne State University
Responsive Economic Model Predictive Control For Next-Generation Manufacturing, Helen Durand
Chemical Engineering and Materials Science Faculty Research Publications
There is an increasing push to make automated systems capable of carrying out tasks which humans perform, such as driving, speech recognition, and anomaly detection. Automated systems, therefore, are increasingly required to respond to unexpected conditions. Two types of unexpected conditions of relevance in the chemical process industries are anomalous conditions and the responses of operators and engineers to controller behavior. Enhancing responsiveness of an advanced control design known as economic model predictive control (EMPC) (which uses predictions of future process behavior to determine an economically optimal manner in which to operate a process) to unexpected conditions of these types …
A Collaboration Between Neural Networks And Reinforcement Learning: Applying Concepts To A Brick Breaking Game,
2020
Augsburg College
A Collaboration Between Neural Networks And Reinforcement Learning: Applying Concepts To A Brick Breaking Game, Bryce Kadrlik
Augsburg Honors Review
The intent of this work is to explore the interactions of artificial neural networks and digital games. It details the development of an artificial neural network trained upon a brick breaking game like the Atari game Breakout. This network was designed with the goals of not dropping the ball and maximizing the game score. Full game and network integration was not completed. However, two versions of the network were developed to move the paddle to the right or left based on the ball's point of impact on the paddle. In preliminary testing using manual inputs, these networks eventually learned to …
Evaluation Of Text Mining Techniques Using Twitter Data For Hurricane Disaster Resilience,
2020
Creighton University
Evaluation Of Text Mining Techniques Using Twitter Data For Hurricane Disaster Resilience, Joshua Eason, Sathish Kumar
SDSU Data Science Symposium
Data obtained from social media microblogging websites such as Twitter provide the unique ability to collect and analyze conversations of the public in order to gain perspective on the thoughts and feelings of the general public. Sentiment and volume analysis techniques were applied to the dataset in order to gain an understanding of the amount and level of sentiment associated with certain disaster-related tweets, including a topical analysis of specific terms. This study showed that disaster-type events such as a hurricane can cause some strong negative sentiment in the period of time directly preceding the event, but ultimately returns quickly …
A Monte Carlo Approach To Closing The Reality Gap,
2020
Fordham University
A Monte Carlo Approach To Closing The Reality Gap, Damian Lyons, James Finocchiaro, Michael Novitzky, Christopher Korpela
Faculty Publications
We propose a novel approach to the ’reality gap’ problem, i.e., modifying a robot simulation so that its performance becomes more similar to observed real world phenomena. This problem arises whether the simulation is being used by human designers or in an automated policy development mechanism. We expect that the program/policy is developed using simulation, and subsequently deployed on a real system. We further assume that the program includes a monitor procedure with scalar output to determine when it is achieving its performance objectives. The proposed approach collects simulation and real world observations and builds conditional probability functions. These are …
Singapore’S National Ai Strategy,
2020
Singapore Management University
Singapore’S National Ai Strategy, Singapore Management University
Perspectives@SMU
The island state is banking on industry-wide projects and building an AI ecosystem to transform its economy
Noise Reduction Of Eeg Signals Using Autoencoders Built Upon Gru Based Rnn Layers,
2020
Technological University Dublin
Noise Reduction Of Eeg Signals Using Autoencoders Built Upon Gru Based Rnn Layers, Esra Aynali
Dissertations
Understanding the cognitive and functional behaviour of the brain by its electrical activity is an important area of research. Electroencephalography (EEG) is a method that measures and record electrical activities of the brain from the scalp. It has been used for pathology analysis, emotion recognition, clinical and cognitive research, diagnosing various neurological and psychiatric disorders and for other applications. Since the EEG signals are sensitive to activities other than the brain ones, such as eye blinking, eye movement, head movement, etc., it is not possible to record EEG signals without any noise. Thus, it is very important to use an …
Robust Neural Machine Translation,
2020
CUNY Graduate Center
Robust Neural Machine Translation, Abdul Rafae Khan
Dissertations, Theses, and Capstone Projects
This thesis aims for general robust Neural Machine Translation (NMT) that is agnostic to the test domain. NMT has achieved high quality on benchmarks with closed datasets such as WMT and NIST but can fail when the translation input contains noise due to, for example, mismatched domains or spelling errors. The standard solution is to apply domain adaptation or data augmentation to build a domain-dependent system. However, in real life, the input noise varies in a wide range of domains and types, which is unknown in the training phase. This thesis introduces five general approaches to improve NMT accuracy and …
Multi-Level Fine-Scaled Sentiment Sensing With Ambivalence Handling,
2020
Singapore Management University
Multi-Level Fine-Scaled Sentiment Sensing With Ambivalence Handling, Zhaoxia Wang, Seng-Beng Ho, Erik Cambria
Research Collection School Of Computing and Information Systems
Social media represent a rich source of information, such as critiques, feedback, and other opinions posted online by Internet users. Such information is typically a good reflection of users’ sentiments and attitudes towards various services, topics, or products. Sentiment analysis has become an increasingly important natural language processing (NLP) task to help users make sense of what is happening in the Internet blogosphere and it can be useful for companies as well as public organizations. However, most existing sentiment analysis techniques are only able to analyze data at the aggregate level, merely providing a binary classification (positive vs. negative), and …
Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network,
2020
Singapore Management University
Zero-Shot Ingredient Recognition By Multi-Relational Graph Convolutional Network, Jingjing Chen, Liangming Pan, Zhipeng Wei, Xiang Wang, Chong-Wah Ngo, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Recognizing ingredients for a given dish image is at the core of automatic dietary assessment, attracting increasing attention from both industry and academia. Nevertheless, the task is challenging due to the difficulty of collecting and labeling sufficient training data. On one hand, there are hundred thousands of food ingredients in the world, ranging from the common to rare. Collecting training samples for all of the ingredient categories is difficult. On the other hand, as the ingredient appearances exhibit huge visual variance during the food preparation, it requires to collect the training samples under different cooking and cutting methods for robust …
