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Articles 2641 - 2670 of 4524
Full-Text Articles in Computer Sciences
Adaptive Loss-Aware Quantization For Multi-Bit Networks, Zhongnan Qu, Zimu Zhou, Yun Cheng, Lothar Thiele
Adaptive Loss-Aware Quantization For Multi-Bit Networks, Zhongnan Qu, Zimu Zhou, Yun Cheng, Lothar Thiele
Research Collection School Of Computing and Information Systems
We investigate the compression of deep neural networks by quantizing their weights and activations into multiple binary bases, known as multi-bit networks (MBNs), which accelerate the inference and reduce the storage for the deployment on low-resource mobile and embedded platforms. We propose Adaptive Loss-aware Quantization (ALQ), a new MBN quantization pipeline that is able to achieve an average bitwidth below one-bit without notable loss in inference accuracy. Unlike previous MBN quantization solutions that train a quantizer by minimizing the error to reconstruct full precision weights, ALQ directly minimizes the quantizationinduced error on the loss function involving neither gradient approximation nor …
Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng
Editing-Enabled Signatures: A New Tool For Editing Authenticated Data, Binanda Sengupta, Yingjiu Li, Yangguang Tian, Robert H. Deng
Research Collection School Of Computing and Information Systems
Data authentication primarily serves as a tool to achieve data integrity and source authentication. However, traditional data authentication does not fit well where an intermediate entity (editor) is required to modify the authenticated data provided by the source/data owner before sending the data to other recipients. To ask the data owner for authenticating each modified data can lead to higher communication overhead. In this article, we introduce the notion of editing-enabled signatures where the data owner can choose any set of modification operations applicable on the data and still can restrict any possibly untrusted editor to authenticate the data modified …
Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Visual Commonsense R-Cnn, Tan Wang, Jianqiang Huang, Hanwang Zhang, Qianru Sun
Research Collection School Of Computing and Information Systems
We present a novel unsupervised feature representation learning method, Visual Commonsense Region-based Convolutional Neural Network (VC R-CNN), to serve as an improved visual region encoder for high-level tasks such as captioning and VQA. Given a set of detected object regions in an image (e.g., using Faster R-CNN), like any other unsupervised feature learning methods (e.g., word2vec), the proxy training objective of VC R-CNN is to predict the contextual objects of a region. However, they are fundamentally different: the prediction of VC R-CNN is by using causal intervention: P(Y|do(X)), while others are by using the conventional likelihood: P(Y|X). This is also …
Mnemonics Training: Multi-Class Incremental Learning Without Forgetting, Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun
Mnemonics Training: Multi-Class Incremental Learning Without Forgetting, Yaoyao Liu, Yuting Su, An-An Liu, Bernt Schiele, Qianru Sun
Research Collection School Of Computing and Information Systems
Multi-Class Incremental Learning (MCIL) aims to learn new concepts by incrementally updating a model trained on previous concepts. However, there is an inherent trade-off to effectively learning new concepts without catastrophic forgetting of previous ones. To alleviate this issue, it has been proposed to keep around a few examples of the previous concepts but the effectiveness of this approach heavily depends on the representativeness of these examples. This paper proposes a novel and automatic framework we call mnemonics, where we parameterize exemplars and make them optimizable in an end-to-end manner. We train the framework through bilevel optimizations, i.e., model-level and …
A Machine Learning Approach For Vulnerability Curation, Yang Chen, Andrew E. Santosa, Ming Yi Ang, Abhishek Sharma, Asankhaya Sharma, David Lo
A Machine Learning Approach For Vulnerability Curation, Yang Chen, Andrew E. Santosa, Ming Yi Ang, Abhishek Sharma, Asankhaya Sharma, David Lo
Research Collection School Of Computing and Information Systems
Software composition analysis depends on database of open-source library vulerabilities, curated by security researchers using various sources, such as bug tracking systems, commits, and mailing lists. We report the design and implementation of a machine learning system to help the curation by by automatically predicting the vulnerability-relatedness of each data item. It supports a complete pipeline from data collection, model training and prediction, to the validation of new models before deployment. It is executed iteratively to generate better models as new input data become available. We use self-training to significantly and automatically increase the size of the training dataset, opportunistically …
Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun
Provably Robust Decisions Based On Potentially Malicious Sources Of Information, Tim Muller, Dongxia Wang, Jun Sun
Research Collection School Of Computing and Information Systems
Sometimes a security-critical decision must be made using information provided by peers. Think of routing messages, user reports, sensor data, navigational information, blockchain updates. Attackers manifest as peers that strategically report fake information. Trust models use the provided information, and attempt to suggest the correct decision. A model that appears accurate by empirical evaluation of attacks may still be susceptible to manipulation. For a security-critical decision, it is important to take the entire attack space into account. Therefore, we define the property of robustness: the probability of deciding correctly, regardless of what information attackers provide. We introduce the notion of …
Mutation Testing Of Smart Contracts At Scale, Pieter Hartel, Richard Schumi
Mutation Testing Of Smart Contracts At Scale, Pieter Hartel, Richard Schumi
Research Collection School Of Computing and Information Systems
It is crucial that smart contracts are tested thoroughly due to their immutable nature. Even small bugs in smart contracts can lead to huge monetary losses. However, testing is not enough; it is also important to ensure the quality and completeness of the tests. There are already several approaches that tackle this challenge with mutation testing, but their effectiveness is questionable since they only considered small contract samples. Hence, we evaluate the quality of smart contract mutation testing at scale. We choose the most promising of the existing (smart contract specific) mutation operators, analyse their effectiveness in terms of killability …
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers, Terrance Mok, Colin Matthew Au Yueng, Anthony Tang, Lora Oehlberg
Talk Like Somebody Is Watching: Understanding And Supporting Novice Live Streamers, Terrance Mok, Colin Matthew Au Yueng, Anthony Tang, Lora Oehlberg
Research Collection School Of Computing and Information Systems
We built a chatbot system–Audience Bot–that simulates an audience for novice live streamers to engage with while streaming. New live streamers on platforms like Twitch are expected to perform and talk to themselves, even while no one is watching. We ran an observational lab study on how Audience Bot assists novice live streamers as they acclimate to multitasking–simultaneously playing a video game while performing for a (simulated) audience.
Don't Hit Me! Glass Detection In Real-World Scenes, Haiyang Mei, Xin Yang, Yang Wang, Yuanyuan Liu, Shengfeng He, Qiang Zhang, Xiaopeng Wei, Rynson W.H. Lau
Don't Hit Me! Glass Detection In Real-World Scenes, Haiyang Mei, Xin Yang, Yang Wang, Yuanyuan Liu, Shengfeng He, Qiang Zhang, Xiaopeng Wei, Rynson W.H. Lau
Research Collection School Of Computing and Information Systems
Glass is very common in our daily life. Existing computer vision systems neglect it and thus may have severe consequences, e.g., a robot may crash into a glass wall. However, sensing the presence of glass is not straightforward. The key challenge is that arbitrary objects/scenes can appear behind the glass, and the content within the glass region is typically similar to those behind it. In this paper, we propose an important problem of detecting glass from a single RGB image. To address this problem, we construct a large-scale glass detection dataset (GDD) and design a glass detection network, called GDNet, …
Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua
Knowledge Enhanced Neural Fashion Trend Forecasting, Yunshan Ma, Yujuan Ding, Xun Yang, Lizi Liao, Wai Keung Wong, Tat-Seng Chua
Research Collection School Of Computing and Information Systems
Fashion trend forecasting is a crucial task for both academia andindustry. Although some efforts have been devoted to tackling this challenging task, they only studied limited fashion elements with highly seasonal or simple patterns, which could hardly reveal thereal fashion trends. Towards insightful fashion trend forecasting,this work focuses on investigating fine-grained fashion element trends for specific user groups. We first contribute a large-scale fashion trend dataset (FIT) collected from Instagram with extracted time series fashion element records and user information. Furthermore, to effectively model the time series data of fashion elements with rather complex patterns, we propose a Knowledge Enhanced …
Ntire 2020 Challenge On Video Quality Mapping: Methods And Results, D. Fuoli, Zhiwu Huang, M. Danelljan, R. Timofte, H. Wang, L. Jin, D. Su, J. Liu, J. Lee, M. Kudelski, L. Bala, D. Hryboy, M. Mozejko, M. Li, S. Li, B. Pang, C. Lu, Li C., He D., Li F.
Ntire 2020 Challenge On Video Quality Mapping: Methods And Results, D. Fuoli, Zhiwu Huang, M. Danelljan, R. Timofte, H. Wang, L. Jin, D. Su, J. Liu, J. Lee, M. Kudelski, L. Bala, D. Hryboy, M. Mozejko, M. Li, S. Li, B. Pang, C. Lu, Li C., He D., Li F.
Research Collection School Of Computing and Information Systems
This paper reviews the NTIRE 2020 challenge on video quality mapping (VQM), which addresses the issues of quality mapping from source video domain to target video domain. The challenge includes both a supervised track (track 1) and a weakly-supervised track (track 2) for two benchmark datasets. In particular, track 1 offers a new Internet video benchmark, requiring algorithms to learn the map from more compressed videos to less compressed videos in a supervised training manner. In track 2, algorithms are required to learn the quality mapping from one device to another when their quality varies substantially and weaklyaligned video pairs …
Cookgan: Causality Based Text-To-Image Synthesis, Bin Zhu, Chong-Wah Ngo
Cookgan: Causality Based Text-To-Image Synthesis, Bin Zhu, Chong-Wah Ngo
Research Collection School Of Computing and Information Systems
This paper addresses the problem of text-to-image synthesis from a new perspective, i.e., the cause-and-effect chain in image generation. Causality is a common phenomenon in cooking. The dish appearance changes depending on the cooking actions and ingredients. The challenge of synthesis is that a generated image should depict the visual result of action-on-object. This paper presents a new network architecture, CookGAN, that mimics visual effect in causality chain, preserves fine-grained details and progressively upsamples image. Particularly, a cooking simulator sub-network is proposed to incrementally make changes to food images based on the interaction between ingredients and cooking methods over a …
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Sensing, Computing, And Communications For Energy Harvesting Iots: A Survey, Dong Ma, Guohao Lan, Mahbub Hassan, Wen Hu, Sajal K. Das
Research Collection School Of Computing and Information Systems
With the growing number of deployments of Internet of Things (IoT) infrastructure for a wide variety of applications, the battery maintenance has become a major limitation for the sustainability of such infrastructure. To overcome this problem, energy harvesting offers a viable alternative to autonomously power IoT devices, resulting in a number of battery-less energy harvesting IoTs (or EH-IoTs) appearing in the market in recent years. Standards activities are also underway, which involve wireless protocol design suitable for EH-IoTs as well as testing procedures for various energy harvesting methods. Despite the early commercial and standards activities, IoT sensing, computing and communications …
Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection, Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai
Self-Trained Deep Ordinal Regression For End-To-End Video Anomaly Detection, Guansong Pang, Cheng Yan, Chunhua Shen, Anton Van Den Hengel, Xiao Bai
Research Collection School Of Computing and Information Systems
Depression is among the most prevalent mental disorders, affecting millions of people of all ages globally. Machine learning techniques have shown effective in enabling automated detection and prediction of depression for early intervention and treatment. However, they are challenged by the relative scarcity of instances of depression in the data. In this work we introduce a novel deep multi-task recurrent neural network to tackle this challenge, in which depression classification is jointly optimized with two auxiliary tasks, namely one-class metric learning and anomaly ranking. The auxiliary tasks introduce an inductive bias that improves the classification model’s generalizability on small depression …
Learning Transferable Deep Convolutional Neural Networks For The Classification Of Bacterial Virulence Factors, Dandan Zheng, Guansong Pang, Bo Liu, Lihong Chen, Jian Yang
Learning Transferable Deep Convolutional Neural Networks For The Classification Of Bacterial Virulence Factors, Dandan Zheng, Guansong Pang, Bo Liu, Lihong Chen, Jian Yang
Research Collection School Of Computing and Information Systems
Motivation: Identification of virulence factors (VFs) is critical to the elucidation of bacterial pathogenesis and prevention of related infectious diseases. Current computational methods for VF prediction focus on binary classification or involve only several class(es) of VFs with sufficient samples. However, thousands of VF classes are present in real-world scenarios, and many of them only have a very limited number of samples available.Results: We first construct a large VF dataset, covering 3446 VF classes with 160 495 sequences, and then propose deep convolutional neural network models for VF classification. We show that (i) for common VF classes with sufficient samples, …
Simulation Modeling Method Of Distributed Supply Chain Based On Has, Wang Jian, Huang Yang
Simulation Modeling Method Of Distributed Supply Chain Based On Has, Wang Jian, Huang Yang
Journal of System Simulation
Abstract: There are some shortcomings in simulation modeling method of distributed supply chain based on High Level Architecture (HLA) and Supply Chain Operation Reference (SCOR), which result in low development efficiency of system simulation modeling and low reusability of simulation objects inside the federates. To solve the problems, a simulation modeling method of distributed supply chain based on HAS(HLA-Agent-SCOR) was put forward. The supply chain structure modeling based on HLA for building structure model of supply chain was discussed. Modeling of Agent blocks integrating processes from SCOR and modeling of federates based on Agent were illustrated to create model of …
Multi-Robots Global Path Planning Based On Pso Algorithm And Cubic Spline, Qiang Ning, Gao Jie, Fengju Kang
Multi-Robots Global Path Planning Based On Pso Algorithm And Cubic Spline, Qiang Ning, Gao Jie, Fengju Kang
Journal of System Simulation
Abstract: There are shortcomings such as premature convergence, high encoding dimension and unsmooth path for particle swarm optimization (PSO) algorithm to solve the robot path planning problem under free space. The particle coding is coordinates of several path nodes in the environment. The number of spline curves and the maximum turnings of path were determined by the number of path nodes. The cubic spline function was used to interpolate on the path of the starting point, path nodes and target point, thus a full path which was formed by connecting all interpolation points was obtained. Simulation results show that …
Improved Marching Cubes Algorithmand Its Three-Dimensional Meteorological Simulation, Shuoben Bi, Lu Yuan, Xiaowen Zeng, Mingyue Lu, Yonghua Zhang
Improved Marching Cubes Algorithmand Its Three-Dimensional Meteorological Simulation, Shuoben Bi, Lu Yuan, Xiaowen Zeng, Mingyue Lu, Yonghua Zhang
Journal of System Simulation
Abstract: Methodof obtaining intersection points of isosurface and vowex by linear interpolation in original Marching Cubes algorithm has been replaced by the method of trisecting element boundaries. The problem of linear interpolation not suitable for meteorological data simulation is therefore solved and the number of triangular facets in isosurfacemapping is effectively reduced. While reducing redundancy and improving mapping speed, the quality of isosurface mapping is further improved. The improved Marching Cubes algorithm is applied to the simulation of meteorological model data, i.e., the isosurface of WRF data, and good results are obtained in both the speed of image rendering and …
Trajectory Capture And Sway Frequency Analysis Of Trees Based On Kinect, He Peng, Shaojun Hu, Dongjian He
Trajectory Capture And Sway Frequency Analysis Of Trees Based On Kinect, He Peng, Shaojun Hu, Dongjian He
Journal of System Simulation
Abstract: The morphology and structure of plants were complex. It is of great significance to investigate the inherent motion law of plants under the action of external force, such as realistic animation formation, plant pruning, vibration picking and forest protection. A low cost outdoor tree complex motion capture method was explored, and the relationship between the stem motion and the external force was analyzed. The Kinect was used to capture the branches motion; MeanShift algorithm was used for tracking branches markers and the three-dimensional trajectory of the trunk was extracted according to the principle of Kinect coordinate transformation. A method …
Realistic Real-Time Road Rendering Technology Based On Road Boundaryalpha-Map, Jinlian Du, Shang Xin, Fengchao Zhao
Realistic Real-Time Road Rendering Technology Based On Road Boundaryalpha-Map, Jinlian Du, Shang Xin, Fengchao Zhao
Journal of System Simulation
Abstract: A method of realistic real-time rendering based on road boundary alpha-map was proposed to eliminate the blur and aliasing issues produced by traditional rendering method based on buffer mechanism. In the method, the road was generated by buffer mechanism based on grid model of terrain, and the road's borders were constructed by analyzing the characteristics of road boundary grids. Based on these, three types of road boundary alpha-maps were designed for producing the road borders with realistic visual effects. Experiment shows that the method can improve the rendering realism of the road borders than traditional method. Another advantage of …
Simulation On Psychosocial Adaption Of Urban New Migrants Based On Catastrophe Theory, Zhao Xu, Chuanchao Huang, Bin Hu
Simulation On Psychosocial Adaption Of Urban New Migrants Based On Catastrophe Theory, Zhao Xu, Chuanchao Huang, Bin Hu
Journal of System Simulation
Abstract: Based on the mental recovery and adaptive behavior translation of the new urban migrants, a two system decision-making model for psychological adaption was built. The simulation research of psychosocial adaption process was studied through the stochastic catastrophe theory and the specific artificial social environment. Simulation experiments indicate that the sustained pressure-bearing suffers from outside situation and the policy system result in the fluctuation of migrants' psychosocial adaption with the former more significant. In the translation of adaptive psychology to adaptive behavior, the attitude orientation and psychological cognition of migrants are critical. The duration or degree of the adaptive process …
Multiple Faults Identification Of Three-Level Inverter, Yanxia Shen, Wu Juan, Zhipu Zhao, Zhicheng Ji
Multiple Faults Identification Of Three-Level Inverter, Yanxia Shen, Wu Juan, Zhipu Zhao, Zhicheng Ji
Journal of System Simulation
Abstract: A three-level neutral point clamped (NPC) inverter was taken as an example, phase current and bridge voltage in the fault states of single switch open and several switches open at the same time were analyzed, and a method based on reconstructive phase space (RPS) and wavelet packet analysis was proposed to identify three-level inverter faults. Based on RPS method, totally different reconstructed current trajectories were obtained, which showed the features of the inverter under different fault conditions. With the help of image processing technology, all kinds of faults with different phase currents were identified. The wavelet packet analysis was …
Simulation Of Joint Power Control Routing Algorithm For Interference And Energy Consumption In Crahns, Zhufang Kuang, Zhigang Chen
Simulation Of Joint Power Control Routing Algorithm For Interference And Energy Consumption In Crahns, Zhufang Kuang, Zhigang Chen
Journal of System Simulation
Abstract: Problems of interference power to primary user by secondary userand the secondary user's running out of energy under underlay spectrum access model in cognitive radio ad hoc networks (CRAHNs) were investigated. Joint power control, routing and spectrum (channel) allocation algorithm (PRSA) based on particle swarm optimization were proposed. The goal of PRSA was to minimize interference power to primary user and prolong lifetime of CRAHNs. Particle encoding, particle initialization, fitness function, particle flight were included in PRSA. An Adjacency matrix with two-tuples containing allocated channel and power level was designed, and three operation rules for particle were redefined. …
Improved Design Scheme And Simulation Analysis Of Non-Valve Controlled Hydraulic Impact System, Liu Zhong, Zou Yu, Zhang Kai, Zhao Fei, Junjun Liu
Improved Design Scheme And Simulation Analysis Of Non-Valve Controlled Hydraulic Impact System, Liu Zhong, Zou Yu, Zhang Kai, Zhao Fei, Junjun Liu
Journal of System Simulation
Abstract: Due to valve port commutation of traditional hydraulic impact system caused valve leakage. For the above shortcomings, an improved structure principle of the new type of non-valve controlled hydraulic impact system was proposed establishing dynamic equations of impact system andconducting simulation analysis based on AMESim. Due to the simulation results which was inconsistent with design goal, two improvement schemes were proposed adding throttle device and controlling inlet and outlet circuit. The simulation results suggest that the working performance of impact system has been improved by adding throttle device, and its efficiency has been increased from 11.8% to 18.3% …
Study Of Model Predictive Control Of Pwm Voltage Source Converterwithout Ac Electromotive Force Sensor, Li Hui, Li Zhi, Zhang Jin, Hanmei Peng
Study Of Model Predictive Control Of Pwm Voltage Source Converterwithout Ac Electromotive Force Sensor, Li Hui, Li Zhi, Zhang Jin, Hanmei Peng
Journal of System Simulation
Abstract: The traditional model-predictive-control (MPC), applied to three-phase converter, requires to use AC electromotive force sensor, and then it reduces the system reliability. A three-phase converter model predictive control without AC electromotive force sensor was proposed, and the virtual flux observer was constructed by DC bus voltage, switching signal and AC current. On this basis, a mathematical model of three-phase converter model predictive control quadratic programming (QP-MPC) based on virtual flux oriented was established. Using quadratic programming algorithm, the system can quickly calculate the optimal change, minimize the objective function, and obtain the optimal switch control signal, so as to …
Under-Determined Blind Source Separation Anti-Collision Algorithm For Rfid Based On Hamming Weight Grouping, Yungang Jin, Xiaohong Zhang, Qiuli Wang
Under-Determined Blind Source Separation Anti-Collision Algorithm For Rfid Based On Hamming Weight Grouping, Yungang Jin, Xiaohong Zhang, Qiuli Wang
Journal of System Simulation
Abstract: The results of the algorithm ofunder-determined blind source separation RFID (Radio Frequency IDentification) system become worse or even lead to the degradation of overall system performancewith the large increase in the number of tags. Anovel parallelizable identification anti-collision algorithm based on constrained non negative matrix factorization (NMF) and Hamming weight grouping technology was proposed. The tag groupings were made by calculating the Hamming weight of the tag's front M bits, which were within the reader identification range. Each group was identified by the RFID reader according to the grouping sequence. Simulation results show that when the antenna number is …
Inertia Effect In Dynamic Tensile Tests Of Concrete-Like Materials, Zhang Shu, Yubin Lu, Dongmei Zhao, Chen Xing
Inertia Effect In Dynamic Tensile Tests Of Concrete-Like Materials, Zhang Shu, Yubin Lu, Dongmei Zhao, Chen Xing
Journal of System Simulation
Abstract: The different understanding on the influential degree of the inertial effect does exist among researchers, and it has not been uniformly defined in dynamic tensile tests. The finite element numerical simulation method was employed to analyze the three typical dynamic tensile tests, without considering the real strain-rate effect in these models, where a constitutive model only considered the influence of hydrostatic pressure was used for modeling the specimen in these models. It is found that the dynamic tensile strength of concrete specimens in the three models mentioned is strengthened with the increase of loading strain-rate, owing to the …
Fluid Flow, Heat And Mass Transfer In Hot Dip Galvanizing Bath, Shouqun Sun, Zhongshuang Wei, Huayang Lu
Fluid Flow, Heat And Mass Transfer In Hot Dip Galvanizing Bath, Shouqun Sun, Zhongshuang Wei, Huayang Lu
Journal of System Simulation
Abstract: Zinc dross is produced inevitably as a metallurgical phenomenon of continuous hot galvanizing process, and the quality of galvanizing is affected. The phenomenon is closely related to the physical field of molten zinc and more surface defects are easily produced if the zinc dross removal process is improperly handled. By constructing a three-dimensional viscous standard k-ε two equation turbulence model, the fluid flow, heat and mass transfer law and the distribution regularities of flow vortex were obtained under the specific initial conditions and boundary conditions. The simulation results of the observation points are basically in agreement with the experimental …
Rtds Simulation Of Quasi-Proportional Resonant Control Of Statcom Under High Voltage, Zhang Yang, Xiaopin Yang
Rtds Simulation Of Quasi-Proportional Resonant Control Of Statcom Under High Voltage, Zhang Yang, Xiaopin Yang
Journal of System Simulation
Abstract: ±100 MVar high voltage static synchronous compensator (STATCOM) device is used for high voltage DC transmission which needs higher reliability. Faster response for its control system to deal with metal ground fault and other situations is required. Direct Current Control (DCC) can be used for these situations. Quasi- Proportional Resonant (quasi-PR) controller under DCC was studied and its parameters settings were discussed. The calculation methods of key parameters such as Kp and Kr were explained by mathematical deduction process. The STATCOM under higher voltage in Yunnan-Guangxi Funing transaction station was taken as an example for the calculation …
Simulation Of Adaptive Dangerous Weather Warning Method Based On Airborne Weather Radar, Wang Lei, Xingang Liu, Wei Ming
Simulation Of Adaptive Dangerous Weather Warning Method Based On Airborne Weather Radar, Wang Lei, Xingang Liu, Wei Ming
Journal of System Simulation
Abstract: A kind of suitable airborne weather radar algorithm for different seasons, latitude and longitude and underlying surface in China was proposed. A simulation model of airborne weather radar for detecting strong storm weather based on the ground-based weather radar data was established. The improved algorithm of region segmentation and TITAN were used to identify strong storms and their characteristic parameters. China was divided into 16 climate characteristic regions (including East China Sea and South China Sea) per the latitude and longitude. The threshold of strong hail storm radar echo characteristic parameters in these areas was obtained, and the dangerous …