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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Duan, Shihong Wu, Hang Xu, Cheng Wan, Jiawang School of Computer and Communication Engineering University of Science and Technology Beijing Beijing China Shunde Graduate School University of Science and Technology Beijing Foshan China Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China

ISBN: (纸本)9783030788100

Real-time high-precision navigation has a wide range of applications in scenarios. In practice, the measurement models are often non-linear, and sequential Bayesian filters, such as Kalman and particle filter, suffer from the problem of accumulative errors, which cannot provide long-time high-precision services for localization. To solve the problem of arbitrary noise distribution, this paper proposes a Gaussian condensation filter to achieve high-precision localization in a non-Gaussian noise environment. To this end, we proposed an error-ellipse re-sampling-based Gaussian condensation (EER-GCF) filter, which establishes error-ellipses with different confidence probabilities and implements a re-sampling algorithm based on the sampling points’ geometrical positions. Furthermore, a cooperative Gaussian condensation filter based on error-ellipse re-sampling (CEER-GCF) is proposed to enhance information fusion in the swarm robots network. this study accomplishes swarm robots tracking based on spatial-temporal constraints to enhance tracking accuracy. Experiment results show that the accuracy of EER-GCF reaches 0.80 m, while CEER-GCF achieves a localization accuracy of 0.27 m. © 2021, Springer Nature Switzerland AG.

关键词： Condensation

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Adaptive Task Distribution Approach Using threshold Behavior Tree for Robotic Swarm 12th

Adaptive Task Distribution Approach Using Threshold Behavior...

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12th international conference on advances in Swarm Intelligence, ICSI 2021

作者： Ma, Li Bao, Weidong Zhu, Xiaomin Wu, Meng Yuan, Yutong Wang, Ji Chen, Hao College of Systems Engineering National University of Defense Technology Changsha410073 China Department of Electronic Engineering Shantou University Guangdong China Unit 75831 of PLA Guangdong510000 China

ISBN: (纸本)9783030788100

Online task distribution is a typical problem for the cooperation of robotic swarm. However, there exist several challenges such as the distributed system, large-scale swarm and limited communication. therefore, this paper proposes an adaptive task distribution approach based on the threshold behavior tree, which solves the task distribution problem of the large-scale robotic swarm. through observation and perception towards outside, the robot obtains information of targets and neighboring robots in the field of view. In the condition of lacking communication, each robot makes its own decision on which kind of tasks to perform according to its threshold behavior tree. Finally, the robotic swarm can achieve the expected task distribution ratio which equals to that of the targets. © 2021, Springer Nature Switzerland AG.

关键词： Multi agent systems

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Predicting Customer Churn in Banking Based on Data Mining Techniques 4th

Predicting Customer Churn in Banking Based on Data Mining Te...

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4th IFIP TC 12 international conference on Computational Intelligence in Data science, ICCIDS 2021

作者： Alsubaie, Wafaa A. Albishi, Haya Z. Aljoufi, Khloud A. Alghamdi, Wedyan S. Alyahyan, Eyman A. Computer Science Department College of Science and Humanities Imam Abdulrahman Bin Faisal University P.O. Box 31961 Jubail Saudi Arabia

ISBN: (纸本)9783030925994

One of the most critical challenges facing banking institutions is customer churn, as it dramatically affects a bank’s profits and reputation. therefore, banks use customer churn forecasting methods when selecting the necessary measures to reduce the impact of this problem. this study applied data mining techniques to predict customer churn in the banking sector using three different classification algorithms, namely: decision tree (J48), random forest (RF), and neural network (MLP) using WEKA. the Results showed that J48 had an overall superior performance over the five performance measures, compared to other algorithms using the 10-fold cross-validation. Additionally, the InfoGain and correlation features selection method was used to identify significant features to predict customer churn. the experiment revealed that both algorithms work better when all features are utilized. In short, the results obtained help in predicting which customer is likely to leave the bank. Furthermore, identifying these essential features will help banks keep customers from churning out and compete with rival banks. © 2021, IFIP international Federation for Information Processing.

关键词： Data mining

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Artificial Intelligence and Geodata for Local Community Sensibilization to Sustainable Spatial Development 41st

Artificial Intelligence and Geodata for Local Community Sens...

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41st IBIMA international conference on Artificial intelligence and Machine Learning, IBIMA-AI 2023

作者： Hernik, Jozef Linke, Hans Joachim Krol, Karol Salata, Tomasz Kukulska-Koziel, Anita Cegielska, Katarzyna Department of Land Management and Landscape Architecture University of Agriculture in Krakow Faculty of Environmental Engineering and Land Surveying Aleja Mickiewicza 21 Krakow31-120 Poland Institute of Geodesy Technische Universität Darmstadt Franziska-Braun-Straße 7 Darmstadt64287 Germany

ISBN: (纸本)9783031628429

Ongoing urbanisation processes call for immediate monitoring of land-use changes combined with sustainable spatial management. advances in technology result in a tendency towards digital monitoring. What is more, digitalisation is provided for in legal regulations on spatial planning. there is, however, a research gap regarding methodological and practical aspects of the role of new technologies and geodata in the process. the problem captured the attention of researchers and practitioners from an international and interdisciplinary GeoSen team. the project’s objective is to devise an IT system to identify land-use and land-cover changes with dedicated tools and computing algorithms. GeoSen uses remote-sensing data processed with artificial intelligence algorithms. Its macroscale research is intended to identify trends and changes in land management and landscape, while the microscale segment tests the IT system. Final algorithms will be published as an interactive online platform that will stimulate the activity of participants in spatial planning, leading to effective and sustainable use of space and its resources. © the Author(s), under exclusive license to Springer Nature Switzerland AG 2024.

关键词： Artificial intelligence

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Analysis and Recognition of Brain Networks for EEG-based Upper-limb Motion 7

Analysis and Recognition of Brain Networks for EEG-based Upp...

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7th international conference on Information, Cybernetics, and Computational Social Systems, ICCSS 2020

作者： Zhou, Yizhi Gao, Farong Xie, Cui Zhang, Qizhong Intelligent Control Robotics Institute Hangzhou Dianzi University Hangzhou China

ISBN: (纸本)9781728162461

Recent advances in Brain-computer-Interface (BCI) have allowed us to construct robotic arms for remote control and rehabilitation systems. the analysis and recognition of motor-related brain signals and activities are the key of such BCI systems. However, most previous studies are powerless to deeply reveal the working mechanism of the brain during motion executions and adopt low-accuracy strategies for modeling and pattern recognition. With the introduction and development of network neuroscience in the field of BCI, it allowed us to analyze brain activities for motor-related EEG signals and build principled models to improve the performance of feature extraction and pattern recognition. therefore, this study concentrates on the construction and analysis of brain networks. Partial directed coherence (PDC) was employed to construct brain networks based on EEG signals for analyzing and recognizing brain activities of different movements (hand opening, hand closing, elbow flexion, and wrist flexion). Features were extracted from brain networks for pattern recognition, and Random Forest (RF) classifier was used to classify different movements. the results indicate that different motion patterns can be related to corresponding network structures and illustrates significant differences among information transmissions. In addition, the results of motion recognition based on RF achieve an accuracy of 75.5%, which demonstrate that the proposed method based on brain networks is reliable to analyze EEG signals and can improve the performance of motion recognition. © 2020 IEEE.

关键词： Brain computer interface

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Preface

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Journal of Physics: conference Series 2024年第1期2872卷 011001页

作者： Xiangmo, Zhao Zhongsheng, Wang George, Wang Yan, Cao Hongbo, Zhong Bo, Li Yao, Liu Changming, Wang Shufeng, Zhou Han, Shen Xi’an University of Architecture and Technology Xi'an China Xi'an Technological University China Wang Missouri Western State University United States State and Provincial Joint Engineering Lab. of Advanced Network Monitoring and Control China James Cook University Australia Xi`an University of Science and Technology China Xi’an Polytechnic University China Shaanxi University of Science & Technology China Zhejiang University China

the 7th international conference on computer Network, Electronic and Automation (ICCNEA 2024) was held in Xi’an Technological University from Sep. 20 to 22, 2024. the conference took place in the beautiful city of Xi’an, China, a city with a history of three thousand *** conference aims to provide a high-level international forum for engineers and scholars to present their new advances and research results. the main topics of ICCNEA 2024 were: Networks and Computing, computer Software and theory, Control and Automation, Electronic technology. In addition, the conference also invited six technical experts to give keynote speech. A total of 218 manuscripts were submitted to the conference. three rounds of review were adopted, the first round was subject scope, scientific, technical and innovative review, and 132 articles were left after this round of review; the second round was double-expert blind review to strive for the originality, scientific and applied value of the articles, and 86 manuscripts were left in the second round. Finally, the third round was the process committee’s collective decision to accept the final articles. Finally, 79 excellent articles were *** the main venue, four sub-venues were set up to conduct technical exchanges in the four areas of manuscript solicitation. Each author presented their research *** conference was supported by State and Provincial Joint Engineering Lab. of Advanced Network, Monitoring and Control, China, Xi’an Technological University, China, Missouri Western State University, USA, Belarusian State University of Transport, Republic of Belarus, James Cook University, Australia, Chang’an University, Xi’an, China, Shaanxi science and technology Exchange Center, Xi’an, China, Base of Information of Vehicle-Infrastructure Sensing and ITS, China, Xi’an University of Architecture and technology, Xi’an *** organizers would like to express their gratitude and thank all the participants for their val

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On the Design of a Secure Anonymous User Authentication Scheme for Multiple Base Stations Based Wireless Sensor Networks 5th

On the Design of a Secure Anonymous User Authentication Sche...

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5th international conference on Mathematics and Computing, ICMC 2019

作者： Banerjee, Soumya Odelu, Vanga Das, Ashok Kumar Chattopadhyay, Samiran Giri, Debasis Department of Information Technology Jadavpur University Salt Lake City Kolkata700 098 India Department of Computer Science and Information Systems Birla Institute of Technology and Science Pilani Hyderabad Campus Hyderabad500 078 India Center for Security Theory and Algorithmic Research International Institute of Information Technology Hyderabad500 032 India Department of Information Technology Maulana Abul Kalam Azad University of Technology Kolkata700064 India

ISBN: (纸本)9789811554100

In recent years, security and data privacy in Wireless Sensor Networks (WSNs) have gained great thrust. Several anonymity-preserving user authentication and key establishment mechanisms for WSNs with single base station have been suggested in the literature. However, sometimes a single base station may be insufficient to maintain the proper quality of services or it may be a single point of failure in WSNs. Very recently Amin et al. suggested a multiple base stations based anonymous user authentication and key establishment approach for WSNs to address the aforementioned problem. In this paper, we first demonstrate that Amin et al.’s scheme has several security pitfalls. To address the security issues in Amin et al.’s scheme, we design a more secure and anonymous user authentication and key establishment mechanism for WSNs that is also based on multiple base stations concept. An exhaustive comparative study demonstrates that the proposed mechanism gives significantly better security and more functionality attributes with comparable commutation as well as computation overheads while those are compared with Amin et al’s. approach. © 2021, the Editor(s) (if applicable) and the Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Wireless sensor networks

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Adaptive Feature Selection and Classification Using Optimization Technique 7th

Adaptive Feature Selection and Classification Using Optimiz...

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7th international conference on Frontiers of Intelligent Computing: theory and Applications, FICTA 2018

作者： Naveen, Nekuri Sookshma, Mandala School of Computer and Information Sciences University of Hyderabad Hyderabad500046 India Computer Science and Engineering School of Technology GITAM University Hyderabad India

ISBN: (纸本)9789813291850

Today, the dimensions of the datasets are becoming more and more. From the existing or collected features, some are useful and some are not useful. In order to analyze the dataset, a feature subset can be selected by applying feature selection method. To select best features in lesser time, optimization algorithms like Particle Swarm Optimization (PSO) can be implemented. there is a possibility of redundant features getting selected based on the correlation among features. Pearson correlation coefficient is being employed to reduce the redundancy. Further, PSO is implemented for classification. Datasets analyzed in this research work are, namely, Australian credit, German credit, Iris, thyroid, Vehicle, WBC, and Wine. It is observed that convincing results were obtained from the proposed method. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Feature Selection

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Barriers to adoption of information technology in healthcare 27

Barriers to adoption of information technology in healthcare

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27th Annual international conference on computer science and Software Engineering, CASCON 2017

作者： Christodoulakis, Christina Asgarian, Azin Easterbrook, Steve Department of Computer Science University of Toronto Canada

Healthcare is an important pillar of society, critical for effectively responding to public health emergencies, and addressing disease, ill health, and poverty brought on by communicable disease and non communicable disease and cancer [7]. the increasing need for cost effective, time effective, and preventive healthcare is forcing radical changes in current healthcare systems, requiring them to take full advantage of capabilities of modern technology, including information technology. However, this is not straightforward. Despite constant advances in modern information technology, adoption in healthcare is very slow. In this report, we take a systems thinking perspective to identify barriers to the application of information technology in healthcare and adoption of those advances through the prism of two use cases: electronic medical records (EMR) and remote patient monitoring (RPM) technology. Finally, we outline solutions to individual barriers and consider the negative effects those solutions might have on other barriers. We expect that our analysis of adoption of information technology in healthcare as presented in our use cases will strengthen the case for systems thinking and help requirements analysts decide on appropriate steps to boost adoption of new technology to achieve more effective and efficient next generation healthcare. © 2017 Copyright held by the owner/author(s).

关键词： Systems thinking

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Using Microsoft Kinect V2 for Custom Upper-Limb Rehabilitation Exercises 12th

Using Microsoft Kinect V2 for Custom Upper-Limb Rehabilitati...

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12th international conference on Soft Computing and Pattern Recognition, SoCPaR 2020 and 16th international conference on Information Assurance and Security, IAS 2020

作者： Rabbani, Shourav Bin Ali, Amin Ahsan Amin, M. Ashraful Agency Lab Department of Computer Science and Engineering Independent University Bangladesh Dhaka Bangladesh

ISBN: (纸本)9783030736880

Motor disability due to stroke, accident, or other illnesses in many cases can be partially or fully recovered with guided and/or prescribed physiotherapy. Moreover, due to the nature of the problem, in most of the case, the treatment is needed to be continued for years. thus, one of the main challenges in this is the availability of an expert physiotherapist to guide the treatment. Most of the time, after initial guided physiotherapy sessions, patients are prescribed exercises to practice at home by themselves. Patients may be able to perform the task at home;however, the expert is present during home sessions, hence, no performance assessment. In this paper, we present a prototype system to resolve this problem using 3D sensor technology: Microsoft Kinect v2. An expert can record an exercise by performing it in front of the 3D camera and provide the prescription (how many times and when the exercise should be performed) on the system. At home, the patient performs the exercise in front of our Kinect-powered system which guides the patient through visual cues on the monitor. In this initial study, five occupational arthritis exercises on the right arm were recorded. We matched these exercises with 15 healthy volunteers (10 male, 5 female) standing 1.5 ms from the system. To overcome different body shapes, we used geometric coordinates from recorded frames and recreated the visual cues. Our system matched the exercises with uncertainty of 10px (2% of depth resolution) and volunteers adapted to screen instructions with minimum supervision. © 2021, the Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Human computer interaction

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