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Lecture Notes on Data Engineering and Communications Technologies 2021年 62卷 ix-x页

作者： Balas, Valentina E. Hassanien, Aboul Ella Chakrabarti, Satyajit Mandal, Lopa Department of Automation and Applied Informatics and Department of International Relations Programs and Projects Intelligent Systems Research Centre Aurel Vlaicu University of Arad Arad Romania Department of Information Technology Faculty of Computer and Artificial Intelligence Cairo University Giza Egypt Institute of Engineering and Management Kolkata West Bengal India Department of Information Technology Institute of Engineering and Management Kolkata West Bengal India

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Modelling and Essential Control of an Oceanographic Monitoring Remotely Operated Underwater Vehicle

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IFAC-PapersOnLine 2018年第29期51卷 213-219页

作者： Rojas, Jorge Baatar, Ganzorig Cuellar, Francisco Eichhorn, Mike Glotzbach, Thomas Institute for Automation and Systems Engineering Technische Universität Ilmenau P.O.Box 10 05 65 Ilmenau98684 Germany Branch of Fraunhofer IOSB Ilmenau98693 Germany Centro de Tecnologías Avanzadas de Manufactura Pontificia Universidad Católica del Perú Lima Peru Faculty Electrical Engineering & Computer Science Aalen University Aalen Germany

Remotely Operated Vehicles (ROVs) are of great importance for a wide range of underwater missions. Although being controlled by a human operator, there is yet the desire to enable some basic autonomous behavior to relieve the operator from controlling every single movement. An accurate model is the basis for any reasonable controller design, not only to find suitable controller parameters, but also to test and optimize controllers in simulation before using them at the vehicle in reality. This paper discusses the procedures of modelling, parameter identification and the design of essential control algorithms for an existing ROV. The model considers kinematics, kinetics and thruster allocation. Two used procedures for parameter identification are presented; a third one as well was recently published in another paper. Finally, we discuss the controller design and show the simulative validation for set-point regulation and waypoint tracking. © 2018

关键词： Remotely operated underwater vehicles Actuators Controllers Electronic guidance systems Identification (control systems) Marine navigation Models Navigation Parameter estimation Propulsion Remote control Remotely operated vehicles Marine systems Marine vehicles Propulsion system simulation thrusters

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Corrigendum to “An Optimized RBF Neural Network Based on Beetle Antennae Search Algorithm for Modeling the Static Friction in a Robotic Manipulator Joint”

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Mathematical Problems in Engineering 2020年第1期2020卷

作者： Yuxiang Wang Zhangwei Chen Hongfei Zu Xiang Zhang State Key Laboratory of Fluid Power and Mechatronics Systems Zhejiang University Hangzhou 310000 *** Faculty of Mechanical Engineering and Automation Zhejiang Sci-Tech University Hangzhou 310000 *** Institute of Computer Science Hangzhou Dianzi University Hangzhou 310000 ***

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Large margin multi-modal multi-task feature extraction for image classification

arXiv

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arXiv 2019年

作者： Luo, Yong Wen, Yonggang Tao, Dacheng Gui, Jie Xu, Chao School of Electronics Engineering and Computer Science Peking University Beijing China Division of Networks and Distributed Systems School of Computer Engineering Nanyang Technological University Singapore Centre for Quantum Computation & Intelligent Systems Faculty of Engineering & Information Technology University of Technology Sydney Sydney Australia Centre for Quantum Computation & Intelligent Systems Faculty of Engineering and Information Technology University of Technology Sydney 81 Broadway Street UltimoNSW2007 Australia Hefei Institute of Intelligent Machines Chinese Academy of Sciences Hefei230031 China Center for Research on Intelligent Perception and Computing National Laboratory of Pattern Recognition Institute of Automation Chinese Academy of Sciences Beijing100190 China

The features used in many image analysis-based applications are frequently of very high dimension. Feature extraction offers several advantages in high-dimensional cases, and many recent studies have used multi-task feature extraction approaches, which often outperform single-task feature extraction approaches. However, most of these methods are limited in that they only consider data represented by a single type of feature, even though features usually represent images from multiple modalities. We therefore propose a novel large margin multi-modal multi-task feature extraction (LM3FE) framework for handling multi-modal features for image classification. In particular, LM3FE simultaneously learns the feature extraction matrix for each modality and the modality combination coefficients. In this way, LM3FE not only handles correlated and noisy features, but also utilizes the complementarity of different modalities to further help reduce feature redundancy in each modality. The large margin principle employed also helps to extract strongly predictive features so that they are more suitable for prediction (e.g., classification). An alternating algorithm is developed for problem optimization and each sub-problem can be efficiently solved. Experiments on two challenging real-world image datasets demonstrate the effectiveness and superiority of the proposed method. Copyright © 2019, The Authors. All rights reserved.

关键词： Feature extraction

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Design of stable and new polysaccharide nanoparticles composite and their interaction with solid cellulose surfaces

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Nano-Structures and Nano-Objects 2020年 24卷

作者： Czabany, Ivana Hribernik, Silvo Bračič, Matej Kurečič, Manja Thomas, Sabu Stana Kleinschek, Karin Mohan, Tamilselvan Institute of Chemistry University of Graz Heinrichstrasse 28 Graz 8010 Austria Institute of Automation Faculty of Electrical Engineering and Computer Science University of Maribor Koroska cesta 46 Maribor 2000 Slovenia Laboratory for Characterisation and Processing of Polymers Faculty of Mechanical Engineering University of Maribor Smetanova 17 Maribor 2000 Slovenia School of Energy Materials International and Inter University Centre for Nanoscience and Nanotechnology School of Chemical Sciences Mahatma Gandhi University Priyadarshini Hills P.O. Kottayam 686560 Kerala India Institute for Chemistry and Technology of Biobased Systems (IBioSys) Graz University of Technology Stremayrgasse 9 Graz 8010 Austria

This study presents a simple and straightforward method for the preparation of aqueous-based stable polysaccharide-metal oxide nanoparticles composites — composed of carboxymethyl cellulose (CMC) and titanium dioxide nanoparticles (TiO₂ NPs), and their interaction with the cellulose surface, is presented. Using a combination of anionic polysaccharide CMC as a stabilizer agent and ultrasound probe sonication technique as an agitation tool, a highly stable dispersion of CMC/TiO₂ NPs composites is prepared in water, with and without the presence of calcium chloride electrolyte, at various pH values. The results of the dynamic light scattering and the zeta-potential measurements showed that the quality, the stability of the dispersions and the hydrodynamic radius of the particles (ca, 200–300 nm) remain well-preserved for several weeks under normal storage conditions. The transmission electron microscope revealed that the morphology and size of the dry particles size (ca. 25–50 nm) remain unchanged and are not influenced by the addition of the stabilizer CMC, the electrolyte or the pH value of the solution. The presence of electrolyte and the low pH of the dispersions strongly favored an irreversible and enhanced deposition of CMC/TiO₂ NPs on cellulose surface as showed by a quartz crystal microbalance with dissipation. A linear correlation between the concentration of CMC and the adsorbed mass of polymer and NPs, and the water content of the adsorbed layers is observed. X-ray photoelectron spectroscopy and atomic force microscopy are combined to prove the successful immobilization of polymer and NPs on the cellulose surface. The knowledge gained from this study can be extended not only for the stabilization of various metal oxide nanoparticles but also for the development of green polymer/NPs composites, that may have the potential to be used as functional coatings in biomedical (e.g. wound dressing) applications. © 2020

关键词： Adsorption Carboxmethyl cellulose QCM-D Thin films Titanium dioxide nanoparticles Water content Zeta potential

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Control of multi-channel multiphase queuing system based on optimal aggregation methodology

Control of multi-channel multiphase queuing system based on ...

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International Scientific and Technical Conference on computer Science and Information Technologies

作者： Taisa Borovska Inna Vernigora Irina Kolesnyk Andriy Kushnir Department of Computer Control Systems (CCS) Vinnytsia National Technical University Vinnytsia Ukraine Department of Computer Engineering (CE) Vinnytsia National Technical University Vinnytsia Ukraine Faculty of Computer Systems and Automation Vinnytsia National Technical University Vinnytsia Ukraine

The control systems of multi-channel multiphase queuing systems are considered. The control system is based on the methodology of optimal aggregation, therefore there are no restrictions on the form of the functions "costs, output" and probability distribution functions. The methods of optimal aggregation solve the optimization problem for continuous, discrete and integer functions of the class "costs, output". Processes for servicing the flow of objects has two modes: the absence and presence of queues. Software modules for analyzing and predicting of the requirements flow, optimal service in the presence and absence of queues are developed.

关键词： Service Queue Optimal aggregation Costs Output Probabilities distribution

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Evaluation of uncertainty in the measurement of sense of natural language constructions

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International Journal of Metrology and Quality Engineering 2017年第6期8卷 1-8页

作者： Bisikalo, Oleg V. Vasilevskyi, Oleksandr M. Dean of the Faculty of Computer Systems and Automation Vinnytsya National Technical University 95 Khmelnitskoye Shose Vinnitsya21021 Ukraine Department of Metrology and Industrial Automation Vinnytsya National Technical University 95 Khmelnitskoye Shose Vinnitsya21021 Ukraine

The task of evaluating uncertainty in the measurement of sense in natural language constructions (NLCs) was researched through formalization of the notions of the language image, formalization of artificial cognitive systems (ACSs) and the formalization of units of meaning. The method for measuring the sense of natural language constructions incorporated fuzzy relations of meaning, which ensures that information about the links between lemmas of the text is taken into account, permitting the evaluation of two types of measurement uncertainty of sense characteristics. Using developed applications programs, experiments were conducted to investigate the proposed method to tackle the identification of informative characteristics of text. The experiments resulted in dependencies of parameters being obtained in order to utilise the Pareto distribution law to define relations between lemmas, analysis of which permits the identification of exponents of an average number of connections of the language image as the most informative characteristics of text. © 2017 O.V. Bisikalo and O.M. Vasilevskyi, published by EDP Sciences.

关键词： Cognitive systems

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Correction: Gut microbiome in endometriosis: a cohort study on 1000 individuals

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BMC medicine 2024年第1期22卷 448页

作者： Inmaculada Pérez-Prieto Eva Vargas Eduardo Salas-Espejo Kreete Lüll Analuce Canha-Gouveia Laura Antequera Pérez Juan Fontes Andres Salumets Reidar Andreson Oliver Aasmets Katrine Whiteson Elin Org Signe Altmäe Department of Biochemistry and Molecular Biology I Faculty of Sciences University of Granada Granada Spain. inmapprieto@ugr.es. Instituto de Investigación Biosanitaria Ibs.GRANADA Granada Spain. inmapprieto@ugr.es. Department of Biochemistry and Molecular Biology I Faculty of Sciences University of Granada Granada Spain. Instituto de Investigación Biosanitaria Ibs.GRANADA Granada Spain. Systems Biology Unit Department of Experimental Biology Faculty of Experimental Sciences University of Jaen Jaen Spain. Institute of Genomics Estonian Genome Centre University of Tartu Tartu Estonia. Department of Physiology Faculty of Veterinary University of Murcia Campus Mare Nostrum Murcia Spain. Department of Computer Engineering Automation and Robotics University of Granada Granada Spain. U. Reproducción UGC Laboratorio Clínico y UGC Obstetricia y Ginecología. HU Virgen de Las Nieves Granada Spain. Competence Centre On Health Technologies Tartu Estonia. Division of Obstetrics and Gynaecology Department of Clinical Science Intervention and Technology Karolinska Institutet Huddinge Stockholm Sweden. Department of Gynaecology and Reproductive Medicine Karolinska University Hospital Huddinge Stockholm Sweden. Department of Obstetrics and Gynaecology Institute of Clinical Medicine University of Tartu Tartu Estonia. Institute of Molecular and Cell Biology University of Tartu Tartu Estonia. School of Biological Sciences University of California Irvine CA USA.

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RF chain reduction for MIMO systems: A hardware prototype

arXiv

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arXiv 2019年

作者： Gong, Tierui Shlezinger, Nir Ioushua, Shahar Stein Namer, Moshe Yang, Zhijia Eldar, Yonina C. State Key Lab of Robotics Key Lab of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China University of Chinese Academy of Sciences Beijing100049 China Faculty of Mathematics and Computer Science Weizmann Institute of Science Rehovot Israel School of Electrical Engineering Tel Aviv University Tel Aviv Israel Faculty of Electrical Engineering Technion Haifa Israel

RF chain circuits play a major role in digital receiver architectures, allowing passband communication signals to be processed in baseband. When operating at high frequencies, these circuits tend to be costly. This increased cost imposes a major limitation on future multiple-input multiple-output (MIMO) communication technologies. A common approach to mitigate the increased cost is to utilize hybrid architectures, in which the received signal is combined in analog into a lower dimension, thus reducing the number of RF chains. In this work we present a hardware prototype implementing analog combining for RF chain reduction. The prototype consists of a specially designed configurable combining board as well as a dedicated experimental setup. Our hardware prototype allows to evaluate the effect of analog combining in MIMO systems using actual communication signals. The experimental study, which focuses on channel estimation accuracy in MIMO channels, demonstrates that using the proposed prototype, the achievable channel estimation performance is within a small gap in a statistical sense from that obtained using a costly receiver in which each antenna is connected to a dedicated RF chain. Furthermore, in the considered scenarios, this gap becomes negligible when the reduction rate, i.e., the ratio of the number of RF chains to the number of antennas, is above 62.5%. Copyright © 2019, The Authors. All rights reserved.

关键词： Channel estimation

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A hybrid deep-learning approach for complex biochemical named entity recognition

arXiv

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arXiv 2020年

作者： Liu, Jian Gao, Lei Guo, Sujie Ding, Rui Huang, Xin Ye, Long Meng, Qinghua Nazari, Asef Thiruvady, Dhananjay HeFei University of Technology Hefei230009 China CSIRO Waite Campus UrrbraeSA5064 Australia Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Shanghai Engineering Center for Microsatellites Shanghai201203 China Xi’an Jiaotong University Xi’an710049 China College of Computer and Information Engineering Tianjin Normal University Tianjin300387 China School of Mechatronic Engineering and Automation Shanghai University Shanghai200072 China Faculty of Business Information Shanghai Business School Shanghai201400 China School of Information Technology Deakin University Geelong Australia Anhui Province Key Laboratory of Industry Safety and Emergency Technology Hefei Anhui230601 China

Named entity recognition (NER) of chemicals and drugs is a critical domain of information extraction in biochemical research. NER provides support for text mining in biochemical reactions, including entity relation extraction, attribute extraction, and metabolic response relationship extraction. However, the existence of complex naming characteristics in the biomedical field, such as polysemy and special characters, make the NER task very challenging. Here, we propose a hybrid deep learning approach to improve the recognition accuracy of NER. Specifically, our approach applies the Bidirectional Encoder Representations from Transformers (BERT) model to extract the underlying features of the text, learns a representation of the context of the text through Bi-directional Long Short-Term Memory (BILSTM), and incorporates the multi-head attention (MHATT) mechanism to extract chapter-level features. In this approach, the MHATT mechanism aims to improve the recognition accuracy of abbreviations to efficiently deal with the problem of inconsistency in full-text labels. Moreover, conditional random field (CRF) is used to label sequence tags because this probabilistic method does not need strict independence assumptions and can accommodate arbitrary context information. The experimental evaluation on a publicly-available dataset shows that the proposed hybrid approach achieves the best recognition performance;in particular, it substantially improves performance in recognizing abbreviations, polysemes, and low-frequency entities, compared with the state-of-the-art approaches. For instance, compared with the recognition accuracies for low-frequency entities produced by the BILSTM-CRF algorithm, those produced by the hybrid approach on two entity datasets (MULTIPLE and IDENTIFIER) have been increased by 80% and 21.69%, respectively. Copyright © 2020, The Authors. All rights reserved.

关键词： Random processes

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