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2nd International Conference on Biofilms, ChinaBiofilms 2019

作者： Li, Ying Huang, Wencong Guangxi Colleges Universities Key Laboratory of Scientific Computing and Intelligent Information Processing Nanning Normal University Nanning530299 China School of Physical Education and Health Nanning Normal University Nanning530299 China

Protein is the specific executor of life activities, but there is no protein-based disease network and the current disease networks cannot show that a disease group share the same factors. We propose a method to construct a protein-based network by assigning disease pairs to different intervals according to their similarities and searching for disease groups in each interval. Statistical methods are used to analyze the disease network, and the result indicates that: in the case where a disease belongs to only one disease group, most diseases have their own protein characteristics, but the common protein of them is not obvious;the more diseases a protein is related to, the more likely the protein becomes common protein;diseases grouping at protein level in this study are different from traditional disease classification;there is a certain relationship between disease symptoms and underlying proteins, but not one-to-one correspondence. © 2019 The Authors, published by EDP Sciences.

关键词： Proteins

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A Realistic and Non-linear Charging Process Model for Parking Lot’s Decision on Electric Vehicles Recharging Schedule

A Realistic and Non-linear Charging Process Model for Parkin...

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IEEE Transportation Electrification Conference and Expo (ITEC)

作者： Hao Wu Grantham Kwok Hung Pang Xia Li The Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University Shenzhen P.R. China Department of Electrical and Electronic Engineering The University of Hong Kong Hong Kong P.R. China

ISBN: (数字)9781728146294

ISBN: (纸本)9781728146300

In this paper, a non-linear charging processing model based on realistic electric vehicle (EV) recharging scheme is proposed. For this purpose, mathematical functions are designed to formulate the constant-current/constant-voltage (CC/CV) scheme used for EV charging, and the consequent variables related to schedule decision are determined. To fit different types of EV charger, this paper gives the derivation process that to determine the charger parameters. Besides, a comprehensive EV charging profile is introduced in this work, which includes the battery's states, charger characteristics and PL's operation specification. With the use of proposed charging process model and EV profile, the estimated electric quantity for each charging time slot can be determined as crucial features in schedule constraints. Lastly, a detailed numerical study is present to evaluate the viability of our proposed model, including non-linear process, charger parameter, EV profile and electric quantity estimation.

关键词： Batteries Mathematical model Numerical models State of charge Schedules Electric vehicle charging Optimization

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Research on the Assistant Decision-making of Gas Regulator Based on Case-based Reasoning

Research on the Assistant Decision-making of Gas Regulator B...

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第32届中国控制与决策会议

作者： Sijie Li Yahui Wang Yinxing Dong School of Electrical and Information Engineering Beijing University of Civil Engineering and Architecture Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing North Hua chuang Vacuum Technology Co Ltd

In order to improve the efficiency of fault decision-making of gas surge tank, this paper proposes a casebased reasoning(CBR) for assistant decision-making of gas surge tank. On the basis of the real case of surge tank fault, the characteristic attributes of the case are extracted, and the case is represented by the frame representation method. Through analytic hierarchy process, local similarity calculation model and global similarity calculation model, the assistant decision-making method of gas surge tank based on case-based reasoning is established. Finally, the source case and target case are analyzed, and the results are proved. The application of this method in assistant decision-making of gas surge tank fault has practical significance.

关键词： gas surge tank assistant decision-making case-based reasoning similarity calculation analytic hierarchy process frame representation

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Object tracking by the least spatiotemporal searches

arXiv

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arXiv 2020年

作者： Yu, Zhiyong Han, Lei Chen, Chao Guo, Wenzhong Yu, Zhiwen College of Mathematics and Computer Sciences Fuzhou University Key Laboratory of Spatial Data Mining and Information Sharing Ministry of Education Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou350108 China School of Computer Science Northwestern Polytechnical University Xi'an710072 China School of Computer Science Chongqing University Chongqing400044 China

Tracking a suspicious car or a person in a city efficiently is crucial in urban safety management. But how can we complete the task with the minimal number of spatiotemporal searches when massive camera records are involved? To this end, this study proposes a strategy named intermediate searching at heuristic moments (IHMs). At each step, we determine which moment is the best one for the search based on a heuristic indicator. Then, at that moment, locations are searched one by one in descending order of predicted appearing probabilities until a search hit is obtained. We iterate this step until we derive the object's current location. Five searching strategies are compared via experiments. Among these strategies, the IHMs strategy is validated as the most efficient. IHMs can save up to 1/3 of the total cost. This result provides evidence that "searching at intermediate moments can save cost. Copyright © 2020, The Authors. All rights reserved.

关键词： Heuristic algorithms

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An improved Gaussian Mixture Model algorithm for background representation

An improved Gaussian Mixture Model algorithm for background ...

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2019 International Conference on Artificial Intelligence Technologies and Applications, ICAITA 2019

作者： Wang, Ping Dong, Shaoxiong School of Electrical Engineering and Electronic Information Xihua University Chengdu Sichuan610039 China Artificial Intelligence Key Laboratory of Sichuan Province Sichuan University of Science and Engineering Zigong Sichuan643000 China Science Computing Intelligent Information Processing GuangXi Higher Education Key Laboratory Guangxi Teachers Education University Nanning530023 China

Initializing a background frame for Gaussian Mixture Model requires no moving objects in the background scene. In this paper, in order to obtain an initial frame when there is a moving object in the background scene, filtering algorithm is used for background frame initialization. This paper proposes an improved method for updating Gaussian mixture models. In the initial stage of the GMM, the update rate of the mean and variance is taken as a larger value, so that the model mean and variance update speed becomes faster, and the model learning speed is accelerated;after training for a period of time with a large update rate, let The mean update rate is unchanged, and the variance update rate becomes smaller, so that the background model can be more stable. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Gaussian distribution

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Extraction of transitional relations in healthcare processes from Chinese medical text based on deep learning 2019

Extraction of transitional relations in healthcare processes...

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4th International Conference on Mathematics and Artificial Intelligence, ICMAI 2019

作者： Ren, Fangwen Yuan, Song Gao, Feng School of Computer Science and Technology Key Laboratory of Intelligent Information Processing and Real-time Industrial System in Hubei Province Institute of Big Data Science and Engineering Wuhan University of Science and Technology China

ISBN: (纸本)9781450362580

Knowledge extraction in healthcare has become a recent research hotspot due to the rapid development of AI technology as well as the urgent demand in the medicine research and practice. Traditional methods focus on extracting terms and relations using pattern matching and machine learning, but they depend on the construction of rules and the accuracy of feature extraction. In contrast, deep learning methods have a stronger ability to process data with high dimensions. Moreover, current study neglects the fact that the key knowledge in medicine is the process of diagnosing and treating patients, i.e., the relations that causes the status change in a healthcare workflow. This paper first identifies the relations relevant for medical processes, and adopts the method of relationship extraction based on Bidirection Gated Recurrent Unit (BiGRU) model and attention mechanism (BiGRU-ATT), in order to retrieve these relations from Chinese medical text. The experimental results show that regarding Chinese medical entity relationship extraction, we can achieve better accuracy rate and recall rate than using convolutional neural network(CNN). © 2019 Association for Computing Machinery.

关键词： Extraction

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Optimize SPL test cases with adaptive simulated annealing genetic algorithm 19

Optimize SPL test cases with adaptive simulated annealing ge...

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2019 ACM Turing Celebration Conference - China, ACM TURC 2019

作者： Yan, Liu Hu, Wenxin Han, Longzhe College of Computer and Software Engineering East China Normal University Shanghai China JiangXi Province Key Laboratory of Water Information Cooperative Sensing and Intelligent Processing Nanchang Institute of Technology Nanchang China

ISBN: (纸本)9781450371582

In Software Product Line (SPL) testing, reduced test suite with high coverage is useful for early features interaction detection. sGA (simplified genetic algorithm) and SAGA(simulated annealing genetic algorithm) can generate high coverage test suite. However, small probability mutations in updating test suite may reduce search efficiency and thus miss better solutions. An improved test cases generation method based on ASAGA (Adaptive simulated annealing genetic algorithm) is proposed. Experiments on SPLOT (Software Product Lines Online Tools) feature models show that the proposed hybrid ASAGA method can ensure local optimization accuracy and achieve smaller-size test suite with higher coverage. © 2019 Association for Computing Machinery.

关键词： Simulated annealing

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Chinese-lao cross-language test similarity computing based on wordnet

Chinese-lao cross-language test similarity computing based o...

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International Conference on Mechatronics and intelligent Robotics, ICMIR 2018

作者： Li, Sizhuo Zhou, Lanjiang Zhang, Jianan Zhou, Feng Guo, Jianyi Huo, Wenjie School of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China The Key Laboratory of Intelligent Information Processing Kunming University of Science and Technology KunmingYunnan650500 China Information Engineering University Kunming Team of the Three Schools Kunming650500 China

ISBN: (纸本)9783030002138

Text similarity calculation is widely used by information retrieval, question answering system, plagiarism detection and so on. At present, most research just aim at text similarity of the same language, and research on cross-language text similarity calculation is rarely, differences between languages make cross-language text similarity calculation very difficult, in view of this situation, this paper propose a WordNet-based method of Chinese-Lao cross-language text similarity calculation. First, preprocessing and feature selection for Chinese text and Lao text which in medicine, then use the semantic dictionary WordNet to convert the Chinese text and Lao text into a middle layer language, finally, compute the text similarity between Chinese and Lao in the middle layer. © Springer Nature Switzerland AG 2019.

关键词： Semantics

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Deep Learning Based Fluid Segmentation in Retinal Optical Coherence Tomography Images 15th

Deep Learning Based Fluid Segmentation in Retinal Optical Co...

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15th International Conference on intelligent Computing, ICIC 2019

作者： Liu, Xiaoming Liu, Dong Li, Bo Wang, Shaocheng College of Computer Science and Technology Wuhan University of Science and Technology Wuhan430065 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-Time Industrial System Wuhan430065 China

ISBN: (纸本)9783030267629

Macular Edema (ME) is the accumulation of fluid in the macular region of the eye, and it may lead to the distortion of center vision. It often occurs in diabetic retinopathy. It is important to measure fluid accumulation in ME patients for disease monitor. Segmentation of the fluid region in the retinal layer is an essential step for quantitatively analysis. However, manual segmentation is time consuming and also subjective. In this paper, a new deep learning based segmentation method is proposed. The attention mechanism is introduced to automatically locate the fluid region, which can reduce the number of parameters compared to typical two-stage approaches. In addition, dense skip connection makes the segmentation result more accurate. Joint losses are used, including cross entropy loss, dice loss and regression loss. The proposed method is evaluated on a public available dataset, results show that the proposed method can adapt to the OCT scans acquired by various imaging scanning devices, and this method is more effective than other methods. © 2019, Springer Nature Switzerland AG.

关键词： Optical tomography

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Sleep Anomaly Events Detection Based on Adaptive Double Threshold CFAR Detector Using UWB Radar

Sleep Anomaly Events Detection Based on Adaptive Double Thre...

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IEEE International Conference on Signal processing, Communications and Computing

作者： Yige Cheng Zhaocheng Yang Dongcai Hong Jiongzhang Chen Guangdong Key Laboratory of Intelligent Information Processing College of Electronics and Information Engineering Shenzhen University

ISBN: (纸本)9781728117096

Detection of sleep anomaly events, such as get up, sit up and turn over, is one of the most important tasks in human sleep monitoring. In this paper, we propose a novel sleep anomaly events detection algorithm based on an adaptive double threshold constant-false-alarm-rate (ADT-CFAR) detector using ultra-wideband (UWB) radar. The proposed algorithm firstly removes the static clutter, detects the human and performs the time-frequency transform for the received signals. By extracting the power burst curve (PBC) from the obtained time-frequency maps, we can formulate the sleep anomaly events detection by a binary hypothesis test and then develop an ADT-CFAR detector, which is based on log-normal distribution. A series of experiments are conducted and the results show the effectiveness of the proposed detector.

关键词： Sleep anomaly events detection UWB radar CFAR detector Sleep monitoring ultra wideband radar Polysomnography Event detection dual threshold anomaly detector Sleep

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