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3rd Management and Innovation Technology International Conference, MITiCON 2016

作者： Ketthong, P. Wannaboon, C. San-Um, W. Srisuchinwong, B. Masayoshi, T. Intelligent Electronics System Research Laboratory Thai-Nichi Institute of Technology 1771/1 Pattanakarn Rd Suan Luang Bangkok10250 Thailand Department of Electronic and Photonic Engineering School of Systems Engineering Kochi University of Technology Tosayamada Kami-city782-8502 Japan School of Information Computer and Communication Technology Sirindhorn International Institute of Technology Thammasat University P.O. Box 22 Pathum Thani12121 Thailand

ISBN: (纸本)9781509041053

A CMOS chaotic jerk oscillator is presented based on inherently hyperbolic tangent nonlinearity. The circuit comprises three Gm-C integrators, a current mirror and a differential Operational Transconductance Amplifier (OTA). The OTA provides inherently hyperbolic tangent nonlinearity for chaos. A balanced double-scroll strange attractor is capable of continuously smooth transition to an unbalanced double-scroll and, finally, to either a right-half or a left-half single-scroll attractor. Such transition is adjustable by varying a DC voltage. The circuit is implemented in a 0.18-μm CMOS technology with full-custom design. © 2016 IEEE.

关键词： Operational amplifiers

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Attitude synchronization of multiple rigid bodies in SE(3) over proximity networks

Attitude synchronization of multiple rigid bodies in SE(3) o...

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第35届中国控制会议

作者： Juan Deng Zhixin Liu Lin Wang John S.Baras Key Laboratory of Systems and Control Academy of Mathematics and Systems ScienceCAS Department of Automation Shanghai Jiao Tong Universityand the Key Laboratory of System Control and Information ProcessingMinistry of Education Department of Electrical and Computer Engineering and the Institute for Systems Research University of MarylandCollege Park

ISBN: (纸本)9781509009107

This paper investigates the attitude synchronization of a group of moving rigid bodies whose states including positions and rotation matrices evolve in the Lie group SE(3).The commonly used circular neighborhood is adopted,and the neighbor graphs are described by proximity *** order to avoid introducing discussions on the abrupt changes of neighbor graphs,a dwell time is *** distributed sampled-data control law for the angular velocity is *** the assumptions on the initial states,we provide sufficient conditions for the attitude synchronization of multiple rigid body *** with the existing results,our condition depends only on the neighborhood radius,the moving velocity and the dwell time.

关键词： rigid body SE(3) attitude synchronization sampled-data control proximity network

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An Event-Triggered Approach to State Estimation for Neural Networks with Individual Triggering Thresholds

An Event-Triggered Approach to State Estimation for Neural N...

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第35届中国控制会议

作者： Licheng Wang Zidong Wang Lei Zou Guoliang Wei Shanghai Key Lab of Modern Optical System Department of Control Science and EngineeringUniversity of Shanghai for Science and Technology Department of Computer Science Brunel University LondonUxbridge Research Institute of Intelligent Control and Systems Harbin Institute of Technology

ISBN: (纸本)9781509009107

In this paper, the state estimation problem is investigated for a class of discrete-time stochastic neural networks with event-triggered transmission(ETT) mechanism. Different from the traditional periodic communication mechanism, the ETT mechanism employed in this paper possesses the advantage of mitigating the network traf c resulting from the unnecessary sending and receiving data between the sensors and the estimators. Moreover, the proposed ETT mechanism is implemented individually for each neuron. That is, the measurement output of each neuron is transmitted to the estimator only when its corresponding triggering condition with the speci ed triggering threshold is satis ed, thereby re ecting the engineering practice in a more realistic way. The aim of the addressed problem is to design an estimator for the neural networks subject to the ETT mechanism such that the estimation error is asymptotically bounded in the mean square. Furthermore, the estimator gain matrix is explicitly parameterized in the sense of minimizing such an asymptotic error upper bound. Finally, a numerical example is presented to demonstrate the effectiveness of the results.

关键词： Event-triggered scheme Neural networks Individual triggering threshold State estimation Asymptotic boundedness

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Author Correction: The FLUXNET2015 dataset and the ONEFlux processing pipeline for eddy covariance data

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Scientific data 2021年第1期8卷 72页

作者： Gilberto Pastorello Carlo Trotta Eleonora Canfora Housen Chu Danielle Christianson You-Wei Cheah Cristina Poindexter Jiquan Chen Abdelrahman Elbashandy Marty Humphrey Peter Isaac Diego Polidori Markus Reichstein Alessio Ribeca Catharine van Ingen Nicolas Vuichard Leiming Zhang Brian Amiro Christof Ammann M Altaf Arain Jonas Ardö Timothy Arkebauer Stefan K Arndt Nicola Arriga Marc Aubinet Mika Aurela Dennis Baldocchi Alan Barr Eric Beamesderfer Luca Belelli Marchesini Onil Bergeron Jason Beringer Christian Bernhofer Daniel Berveiller Dave Billesbach Thomas Andrew Black Peter D Blanken Gil Bohrer Julia Boike Paul V Bolstad Damien Bonal Jean-Marc Bonnefond David R Bowling Rosvel Bracho Jason Brodeur Christian Brümmer Nina Buchmann Benoit Burban Sean P Burns Pauline Buysse Peter Cale Mauro Cavagna Pierre Cellier Shiping Chen Isaac Chini Torben R Christensen James Cleverly Alessio Collalti Claudia Consalvo Bruce D Cook David Cook Carole Coursolle Edoardo Cremonese Peter S Curtis Ettore D'Andrea Humberto da Rocha Xiaoqin Dai Kenneth J Davis Bruno De Cinti Agnes de Grandcourt Anne De Ligne Raimundo C De Oliveira Nicolas Delpierre Ankur R Desai Carlos Marcelo Di Bella Paul di Tommasi Han Dolman Francisco Domingo Gang Dong Sabina Dore Pierpaolo Duce Eric Dufrêne Allison Dunn Jiří Dušek Derek Eamus Uwe Eichelmann Hatim Abdalla M ElKhidir Werner Eugster Cacilia M Ewenz Brent Ewers Daniela Famulari Silvano Fares Iris Feigenwinter Andrew Feitz Rasmus Fensholt Gianluca Filippa Marc Fischer John Frank Marta Galvagno Mana Gharun Damiano Gianelle Bert Gielen Beniamino Gioli Anatoly Gitelson Ignacio Goded Mathias Goeckede Allen H Goldstein Christopher M Gough Michael L Goulden Alexander Graf Anne Griebel Carsten Gruening Thomas Grünwald Albin Hammerle Shijie Han Xingguo Han Birger Ulf Hansen Chad Hanson Juha Hatakka Yongtao He Markus Hehn Bernard Heinesch Nina Hinko-Najera Lukas Hörtnagl Lindsay Hutley Andreas Ibrom Hiroki Ikawa Marcin Jackowicz-Korczynski Dalibor Janouš Wilma Jans Rachhpal Jassal Shicheng Jiang Tomomichi Kato Myr Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. gzpastorello@lbl.gov. DIBAF University of Tuscia Viterbo 01100 Italy. Euro-Mediterranean Centre on Climate Change Foundation (CMCC) Lecce 73100 Italy. Climate & Ecosystem Sciences Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Computational Research Division Lawrence Berkeley National Laboratory Berkeley CA 94720 USA. Department of Civil Engineering California State University Sacramento CA 95819 USA. Department of Geography Environment and Spatial Sciences Michigan State University East Lansing MI 48823 USA. Department of Computer Science University of Virginia Charlottesville VA 22904 USA. TERN Ecosystem Processes Menzies Creek VIC3159 Australia. Max Planck Institute for Biogeochemistry Jena 07701 Germany. Laboratoire des Sciences du Climat et de l'Environnement (LSCE) CEA CNRS UVSQ UPSACLAY Gif sur Yvette 91190 France. Key Laboratory of Ecosystem Network Observation and Modeling Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences Beijing 100101 China. Department of Soil Science University of Manitoba Winnipeg MB R3T2N2 Canada. Department of Agroecology and Environment Agroscope Research Institute Zürich 8046 Switzerland. School of Geography and Earth Sciences McMaster University L8S4K1 Hamilton ON Canada. Department of Physical Geography and Ecosystem Science Lund University Lund 22362 Sweden. Department of Agronomy and Horticulture University of Nebraska-Lincoln Lincoln NE 68583 USA. School of Ecosystem and Forest Sciences The University of Melbourne Richmond VIC3121 Australia. Department of Biology Research Group PLECO University of Antwerp Antwerp 2610 Belgium. Joint Research Centre European Commission Ispra 21027 Italy. TERRA Teaching and Research Center University of Liege Gembloux B-5030 Belgium. Finnish Meteorological Institute Helsinki 00560 Finland. ES

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Web based testing application security system using semantic comparison method

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IOP Conference Series: Materials Science and engineering 2018年第1期420卷

作者： Akbar Iskandar Muhammad Resa Fahlepi Tuasamu Suryadi Syamsu M Mansyur Tri Listyorini Sulfikar Sallu S Supriyono Kundharu Saddhono Darmawan Napitupulu Robbi Rahim Informatics Engineering STMIK AKBA Makassar Indonesia. Graduate Program Universitas Negeri Makassar Makassar Indonesia. Informatics Engineering Universitas Maria Kudus Central Java Indonesia. Computer Information Systems Universitas Sembilan Belas November Kolaka Indonesia. Department of Geography Education Universitas Prof Dr Hazairin SH Bengkulu Indonesia. Indonesian Language Education Departement Faculty of Teacher Training and Education Universitas Sebelas Maret Surakarta Indonesia. Research Center for Quality System and Testing Technology Indonesian Institute of Sciences Indonesia. Sekolah Tinggi Ilmu Manajemen Sukma Medan Indonesia

computer and web security system is an attempt to avoid attacks from crackers because a form and method of crime on internet network can not be predicted. Therefore, we just keep trying to use various methods in securing the system that is running. It is the same in web testing that can be accessed online by people who are not responsible from along distance to change and remove the test results or even damage the web testing system. So, the purpose of this paper is to design and implement web security testing system by using semantic comparison method to avoid structured query language injection (SQLI) attack and to do security on web testing application using Message Digest 5 encryption (MD5). Research data were obtained by using direct observation and documentation and literature review. After the design and application of the system, it can be obtained that by using semantic comparison method in web testing can prevent the occurrence of SQL injection attacks and can secure account from web testing users by using MD5.

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Vision-based Unmanned Aerial Vehicle detection and tracking for sense and avoid systems

Vision-based Unmanned Aerial Vehicle detection and tracking ...

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IEEE/RSJ International Conference on Intelligent Robots and systems

作者： Krishna Raj Sapkota Steven Roelofsen Artem Rozantsev Vincent Lepetit Denis Gillet Pascal Fua Alcherio Martinoli Computer Vision Laboratory School of Communication and Computer Sciences école Polytechnique Fédérale de Lausanne (EPFL) Switzerland Distributed Intelligent Systems and Algorithms Laboratory School of Architecture Civil and Environmental Engineering EPFL Switzerland Institute for Computer Graphics and Vision TU Graz Austria Coordination and Interaction System Group School of Engineering EPFL Switzerland

ISBN: (纸本)9781509037636

We propose an approach for on-line detection of small Unmanned Aerial Vehicles (UAVs) and estimation of their relative positions and velocities in the 3D environment from a single moving camera in the context of sense and avoid systems. This problem is challenging both from a detection point of view, as there are no markers on the targets available, and from a tracking perspective, due to misdetection and false positives. Furthermore, the methods need to be computationally light, despite the complexity of computer vision algorithms, to be used on UAVs with limited payload. To address these issues we propose a multi-staged framework that incorporates fast object detection using an AdaBoost-based approach, coupled with an on-line visual-based tracking algorithm and a recent sensor fusion and state estimation method. Our framework allows for achieving real-time performance with accurate object detection and tracking without any need of markers and customized, high-performing hardware resources.

关键词： Target tracking Object detection Collision avoidance Cameras Visualization Detectors

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A Two-Step Fault Diagnosis Framework for Rolling Element Bearings with Imbalanced Data

A Two-Step Fault Diagnosis Framework for Rolling Element Bea...

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2016 13th International Conference on Ubiquitous Robots and Ambient Intelligence (URAI)

作者： Yuan Lan Weiwei Zong Xiaojian Ding Xiaoyan Xiong Xiaohang Han Jiahai Huang Bing Ma Key Laboratory of Ministry of Education in Advance Transducers and Intelligent Control System Institute of Mechatronics Engineering under School of Mechanical EngineeringTaiyuan University of Technology Department of Computer Science Wayne State University Science and Technology on Information Systems Engineering Laboratory The Second Research Institute of China Electronic Technology Group Corporation

Rolling element bearings constitute the key parts on rotating machinery and their fault diagnosis are of great importance. In this paper, a novel Two-Step fault diagnosis framework is proposed to diagnose the status of rolling element bearings with imbalanced data. The Wavelet Packet Transform(WPT) is used to determine the feature vectors. 16-dimensional wavelet packet node energies were extracted from the original datasets as the feature vectors prepared to input to the ***, our proposed framework consists of two steps for the fault diagnosis, where Step One makes use of Weighted Extreme Learning Machine(weighted ELM) in an effort to classify the normal or abnormal categories, and Step Two further diagnoses the underlying anomaly in details. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our institute,and the empirical results showed that our approach is really fast and can achieve the diagnosis accuracies more than 95%.

关键词： Two-Step fault diagnosis framework Weighed ELM ELM Bearing fault diagnosis

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A Two-Step Fault Diagnosis Framework for Rolling Element Bearings with Imbalanced Data

A Two-Step Fault Diagnosis Framework for Rolling Element Bea...

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International Conference on Ubiquitous Robots and Ambient Intelligence

作者： Yuan Lan Weiwei Zong Xiaojian Ding Xiaoyan Xiong Xiaohang Han Jiahai Huang Bing Ma Key Laboratory of Ministry of Education in Advance Transducers and Intelligent Control System Institute of Mechatronics Engineering under School of Mechanical Engineering Taiyuan University of Technology Department of Computer Science Wayne State University Science and Technology on Information Systems Engineering Laboratory The Second Research Institute of China Electronic Technology Group Corporation

ISBN: (纸本)9781509008223

Rolling element bearings constitute the key parts on rotating machinery and their fault diagnosis are of great importance. In this paper, a novel Two-Step fault diagnosis framework is proposed to diagnose the status of rolling element bearings with imbalanced data. The Wavelet Packet Transform (WPT) is used to determine the feature vectors. 16-dimensional wavelet packet node energies were extracted from the original datasets as the feature vectors prepared to input to the classifiers. Next, our proposed framework consists of two steps for the fault diagnosis, where Step One makes use of Weighted Extreme Learning Machine (weighted ELM) in an effort to classify the normal or abnormal categories, and Step Two further diagnoses the underlying anomaly in details. The effectiveness of our proposed approach is testified on the raw data collected from the rolling element bearing experiments conducted in our institute, and the empirical results showed that our approach is really fast and can achieve the diagnosis accuracies more than 95%.

关键词： Two-Step fault diagnosis framework Weighed ELM ELM Bearing fault diagnosis

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Estimating communication skills based on multimodal information in group discussions

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Transactions of the Japanese Society for Artificial Intelligence 2016年第6期31卷

作者： Okada, Shogo Matsugi, Yoshihiro Nakano, Yukiko Hayashi, Yuki Huang, Hung-Hsuan Takase, Yutaka Nitta, Katsumi School of Computing Tokyo Institute of Technology Japan Department of Computational Intelligence and Systems Interdisciplinary Graduate School of Science and Engineering Tokyo Institute of Technology Japan Department of Computer and Information Science Seikei University Japan College of Sustainable System Sciences Osaka Prefecture University Japan Department of Information and Communication Science College of Information Science and Engineering Ritsumeikan University Japan

This paper focuses on developing a model for estimating communication skills of each participant in a group from multimodal (verbal and nonverbal) features. For this purpose, we use a multimodal group meeting corpus including audio signal data and head motion sensor data of participants observed in 30 group meeting sessions. The corpus also includes the communication skills of each participant, which is assessed by 21 external observers with the experience of human resource management. We extracted various kinds of features such as spoken utterances, acoustic features, speaking turns and the amount of head motion to estimate the communication skills. First, we created a regression model to infer the level of communication skills from these features using support vector regression to evaluate the estimation accuracy of the communication skills. Second, we created a binary (high or low) classification model using support vector machine. Experiment results show that the multimodal model achieved 0.62 in R2 as the regression accuracy of overall skill, and also achieved 0.93 as the classification accuracy. This paper reports effective features in predicting the level of communication skill and shows that these features are also useful in characterizing the difference between the participants who have high level communication skills and those who do not. © 2016, Japanese Society for Artificial Intelligence. All rights reserved.

关键词： Human resource management

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2016 IEEE International Conference on systems, Man, and Cybernetics, SMC 2016

作者： Nguyen, Linh Anh Nguyen, Thi Hong Khanh Nguyen, Ngoc-Thanh Ha, Quang-Thuy Division of Knowledge and System Engineering for ICT Faculty of Information Technology Ton Duc Thang University Ho Chi Minh City Viet Nam Institute of Informatics University of Warsaw Banacha 2 Warsaw02-097 Poland Electric Power University 235 Hoang Quoc Viet Tu Liem Hanoi Viet Nam Department of Information Systems Faculty of Computer Science and Management Wroclaw University of Technology Poland Faculty of Information Technology VNU University of Engineering and Technology 144 Xuan Thuy Hanoi Viet Nam

ISBN: (纸本)9781509018970

We introduce comparisons with respect to information between interpretations in paraconsistent description logics and use them to define bisimilarity for such logics. As bisimilarity is a natural notion for characterizing indiscernibility in modal and description logics, it is useful for concept learning in description logics also when inconsistencies occur. We give preservation results and the Hennessy-Milner property for comparisons with respect to information in paraconsistent description logics. As consequences, we also obtain invariance results and the Hennessy-Milner property for bisimilarity in paraconsistent description logics. © 2016 IEEE.

关键词： Data description

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