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2021 IEEE International Conference on Emergency Science and Information Technology, ICESIT 2021

作者： Lodhi, Ehtisham Yang, Pu Wang, Lina Khan, M. Adil Lodhi, Zeeshan Javed, Usman Saleem, Qasim School of Automation Science and Electrical Engineering Beihang University Beijing100191 China SKL for Management and Control of Complex Systems Institute OfAutomation Chinese Academy of Sciences Beijing100190 China Chang'an University Department of Computer and Technology Xi'an710062 China COMSATS University Department of Electrical and Computer Engineering Islamabad22060 Pakistan Lahore54000 Pakistan

ISBN: (纸本)9781665435314

Currently, Photovoltaic (PV) technology has higher demand in the market and gaining momentum day by day. However, partial shading is the most significant concern as it reduces the efficiency of standalone PV systems. Partially shading is typically induced by non-uniform sunlight and uncertain temperature fluctuations. The maximum power point tracking (MPPT) algorithms play a major role in determining the overall system's efficiency. The PV system creates several peaks in its power voltage (P-V) characteristic curve under partial shadowing. To make the PV system run under partial shading at global maximum power point (GMPP), the dragonfly optimization (DFO) algorithm is put forward in this research article. The proposed DFO technique and other commonly used MPPT techniques, such as Particle swarm optimization (PSO), Perturb and Observe (PO), is investigated through theoretical analysis and simulation using Matlab/Simulink to authenticate the overall performance of the DFO approach under partial shading. Furthermore, the comparison demonstrates that the suggested DFO strategy provides very high reliability, efficiency, robustness, rapid power tracking and lower response time to trace the GMPP than PSO and PO techniques. Hence, the DFO technique's overall performance under partial shading is appropriate and satisfying. © 2021 IEEE.

关键词： Simulink

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Artificial intelligence in cancer target identification and drug discovery

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Signal Transduction and Targeted Therapy 2022年第6期7卷 1951-1974页

作者： Yujie You Xin Lai Yi Pan Huiru Zheng Julio Vera Suran Liu Senyi Deng Le Zhang College of Computer Science Sichuan UniversityChengdu 610065China Laboratory of Systems Tumor Immunology Friedrich-Alexander-Universität Erlangen-Nürnberg(FAU)and Universitätsklinikum ErlangenErlangen 91052Germany Faculty of Computer Science and Control Engineering Shenzhen Institute of Advanced TechnologyChinese Academy of SciencesRoom D5131068 Xueyuan AvenueShenzhen University TownShenzhen 518055China School of Computing Ulster UniversityBelfast BT151EDUK Institute of Thoracic Oncology Department of Thoracic SurgeryWest China HospitalSichuan UniversityChengdu 610065China Key Laboratory of Systems Biology Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesChinese Academy of SciencesHangzhou 310024China Key Laboratory of Systems Health Science of Zhejiang Province Hangzhou Institute for Advanced StudyUniversity of Chinese Academy of SciencesHangzhou 310024China

Artificial intelligence is an advanced method to identify novel anticancer targets and discover novel drugs from biology networks because the networks can effectively preserve and quantify the interaction between components of cell systems underlying human diseases such as ***,we review and discuss how to employ artificial intelligence approaches to identify novel anticancer targets and discover ***,we describe the scope of artificial intelligence biology analysis for novel anticancer target ***,we review and discuss the basic principles and theory of commonly used network-based and machine learning-based artificial intelligence ***,we showcase the applications of artificial intelligence approaches in cancer target identification and drug *** together,the artificial intelligence models have provided us with a quantitative framework to study the relationship between network characteristics and cancer,thereby leading to the identification of potential anticancer targets and the discovery of novel drug candidates.

关键词： drugs cancer drug

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Geometric Parameterized Macromodel of Uniaxial Capacitance Accelerometer Based on Modal Superposition

Geometric Parameterized Macromodel of Uniaxial Capacitance A...

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International Conference on Actual Problems of Electronic Instrument engineering (APEIE)

作者： Aleksandr V. Gridchin Aleksei N. Koleda Evgenii S. Barbin Tamara G. Nesterenko Vladimir A. Kolchuzhin Department of Semiconductor Devices and Microelectronics Novosibirsk State Technical University Novosibirsk Russia Department of Electronic Engineering National Research Tomsk Polytechnic University Tomsk Russia Laboratory of Intelligent Computer Systems Tomsk State University of Control Systems and Radioelectronics Tomsk Russia Advanced Cellular Group Qorvo Munich GmbH Munich Germany

The paper presents a piecewise geometric parameterization method and a parametric analysis of uniaxial capacitance accelerometer using a reduced model formulated on the modal superposition method. The extraction of parameters for the macromodel such as modal frequencies, modal masses, modal stiffnesses, strain energy, and capacitances are described. The reduced model consists of the two modes: torsion mode, and transversal mode, three electrodes in the electrostatic domain, and eight master nodes in the geometrical domain located at the edges of the plate. The generation of the discrete macromodels is executed using commercial software. The thickness of the plate has been selected as a design parameter. Linear piecewise interpolation is used for macromodel parameterization which have been done inside VHDL-AMS code. The accelerometer’s dynamic response simulated using of parametrized macromodel considering the mechanical contact phenomena and the nonlinear electrostatic interaction are presented and discussed. The developed approach can be applied for fast system level simulations in view of the variation of the geometric parameters.

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Partially Double-Pass Structure in Serial Hybrid Fiber Amplifier

Partially Double-Pass Structure in Serial Hybrid Fiber Ampli...

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engineering, Science and Advanced Technology (ICESAT), International Conference on

作者： Ali Yaseen Ali Mohammed Kamil Salh Al-Mashhadani Thamer Fahad Al-Mashhadani Rabi Noori Hammudi Yassine Bouteraa Control and Energy Management Laboratory (CEM Lab)Ecole Nationaled Ingenieurs de Sfax (ENIS) Institut Superieur de Biotechnologie de Sfax (ISBS) University of Sfax Tunisia Department of Petroleum Systems Control Engineering Tikrit University Saladdin Iraq Department of Electrical Engineering Tikrit University Saladdin Iraq Department of Laser Engineering and optoelectronics Kut Univeristy College Alkut Wasit Iraq Department of Computer Engineering Prince Sattam Bin Abdulaziz University Al-Kharj Saudi Arabia

In this paper, a partially double pass configuration in serial hybrid fiber amplifier is experimentally demonstrated. In the proposed design, a double pass erbium gain and single pass Raman gain are achieved serially. A total pump power of 450 mW (400 mW for 1495 nm Raman amplifier and 50 mW for1480 nm in erbium amplifier) were used. At -30 dBm input signal power and optimum pumps conditions, the achieved flatness bandwidth is 80 nm (1530–1610 nm) in the conventional and long bands (C+L) bands. In addition, the obtained average gain level is 33 dB. While the obtained flatness gain is 85 nm (1525–1610 nm) within the large input signal power region at -5 dBm. By choosing a proper pump wavelength that avoid the overlapping between Raman and erbium peaks gain, a wide flatness gain is obtained.

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An Improved Machine Learning Technique with Effective Heart Disease Prediction System

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computers, Materials & Continua 2021年第12期69卷 4169-4181页

作者： Mohammad Tabrez Quasim Saad Alhuwaimel Asadullah Shaikh Yousef Asiri Khairan Rajab Rihem Farkh Khaled Al Jaloud College of Computing and Information Technology University of BishaBisha67714Saudi Arabia King Abdulaziz City for Science and Technology P.O.Box 6086Riyadh11442Saudi Arabia College of Computer Science and Information Systems Najran UniversityNajran61441Saudi Arabia College of Engineering Muzahimiyah BranchKing Saud UniversityRiyadh11451Saudi Arabia Department of Electrical Engineering Laboratory for AnalysisConception and Control of SystemsLR-11-ES20National Engineering School of TunisTunis El Manar University1002Tunisia

Heart disease is the leading cause of death *** heart disease is challenging because it requires substantial experience and *** research studies have found that the diagnostic accuracy of heart disease is *** coronary heart disorder determines the state that influences the heart valves,causing heart *** indications of coronary heart disorder are strep throat with a red persistent skin rash,and a sore throat covered by tonsils or strep *** work focuses on a hybrid machine learning algorithm that helps predict heart attacks and arterial *** first,we achieved the component perception measured by using a hybrid cuckoo search particle swarm optimization(CSPSO)*** this perception measure,characterization and accuracy were improved,while the execution time of the proposed model was *** CSPSO-deep recurrent neural network algorithm resolved issues that state-of-the-art methods *** proposed method offers an illustrative framework that helps predict heart attacks with high *** proposed technique demonstrates the model accuracy,which reached 0.97 with the applied dataset.

关键词： Machine learning deep recurrent neural network effective heart disease prediction framework

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On the Approximation of the Quotient of Two Gaussian Densities for Multiple-Model Smoothing

On the Approximation of the Quotient of Two Gaussian Densiti...

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International Conference on Information Fusion

作者： Yi Liu Xi Li Le Yang Lyudmila Mihaylova Yanbo Xue Department of Electrical and Computer Engineering University of Canterbury Christchurch NZ State Key Lab of Complex Electromagnetic Environment Effects on Electronics and Information Systems National University of Defense Technology Changsha China Department of Automatic Control and System Engineering University of Sheffield Sheffield UK Career Science Lab Beijing China

The quotient of two multivariate Gaussian densities can be written as an unnormalized Gaussian density, which has been applied in some recently developed multiple-model fixed-interval smoothing algorithms. However, this expression is invalid if instead of being positive definite, the covariance of the unnormalized Gaussian density is indefinite (i.e., it has both positive and negative eigenvalues) or undefined (i.e., computing it requires inverting a singular matrix). This paper considers approximating the quotient of two Gaussian densities in this case using two different approaches to mitigate the caused numerical problems. The first approach directly replaces the indefinite covariance of the unnormalized Gaussian density with a positive definite matrix nearest to it. The second approach computes the approximation through solving, using the natural gradient, an optimization problem with a Kullback-Leibler divergence-based cost function. This paper illustrates the application of the theoretical results by incorporating them into an existing smoothing method for jump Markov systems and utilizing the obtained smoothers to track a maneuvering target.

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An Exact Algorithm for Finite Metric Space Embedding into a Euclidean Space When the Dimension of the Space Is Not Known 21st

An Exact Algorithm for Finite Metric Space Embedding into a ...

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21st International Conference on Computational Science, ICCS 2021

作者： Skubalska-Rafajlowicz, Ewa Rafajlowicz, Wojciech Department of Computer Engineering Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50 370 Poland Department of Control Systems and Mechatronics Wroclaw University of Science and Technology Wyb. Wyspianskiego 27 Wroclaw50 370 Poland

ISBN: (纸本)9783030779603

We present a O(n3) algorithm for solving the Distance Geometry Problem for a complete graph (a simple undirected graph in which every pair of distinct vertices is connected by a unique edge) consisting of n+ 1 vertices and non-negatively weighted edges. It is known that when the solution of the problem exists, the dimension of the Euclidean embedding is at most n. The algorithm provides the smallest possible dimension of the Euclidean space for which the exact embedding of the graph exists. Alternatively, when the distance matrix under consideration is non-Euclidean, the algorithm determines a subset of graph vertices whose mutual distances form the Euclidean matrix. The proposed algorithm is an exact algorithm. If the distance matrix is a Euclidean matrix, the algorithm provides a geometrically unambiguous solution for the location of the graph vertices. The presented embedding method was illustrated using examples of the metric traveling salesman problem that allowed us in some cases to obtain high dimensional partial immersions. © 2021, Springer Nature Switzerland AG.

关键词： Undirected graphs

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Hand Gesture Recognition from an Open-Set Perspective

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IEEE Transactions on Multimedia 2025年

作者： Zhou, Jun Xu, Chi Cheng, Li China University of Geosciences School of Automation Wuhan430074 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China Ministry of Education Engineering Research Center of Intelligent Technology for Geo-Exploration Wuhan430074 China University of Alberta Vision and Learning Laboratory Department of Electrical and Computer Engineering EdmontonABT6G 2R3 Canada

Existing hand gesture recognition methods predominantly rely on a close-set assumption, which in essence limits the viewpoints, gesture categories, and hand shapes at test time to closely resemble those seen during training. This requirement is however rarely met in practice, as images are often captured from unconstrained viewpoints, with novel gestures and unseen hand shapes that can differ significantly from the training data. This motivates us to investigate an open-set hand gesture recognition problem, where hand gestures are still recognizable from unconstrained viewpoints, and novel gesture classes and hand shapes can be incrementally learned with just a few examples. To address this, we propose a viewpoint influence elimination network that extracts view-independent features, significantly improving performance in scenarios with unconstrained viewpoints. Moreover, a joint-weighted classification scheme is introduced to augment the cosine similarity metric for evaluating few-shot incremental learning of novel gestures and shapes. Finally, as existing hand gesture recognition datasets primarily adhere to the close-set assumption, a new hand gesture recognition dataset, OHG, is introduced in this paper, that includes a wide range of viewpoints, diverse gesture classes, and distinct hand shapes. Experimental hand gesture recognition results demonstrate the superior performance of our approach in both unconstrained viewpoint and few-shot incremental learning scenarios. The source code and the OHG dataset are to be made available at https://***/zhoujun-7/OSHGR. © 1999-2012 IEEE.

关键词： Palmprint recognition

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A New Mutimodel approach for modelling of fractional order interval transfer functions

A New Mutimodel approach for modelling of fractional order i...

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IEEE SSD International Multi-Conference on systems, Signals and Devices

作者： Samia Talmoudi Moufida Lahmari Ksouri Department of Computer Science Applied College University of Tabuk Tabuk Saudi Arabia University of Tunis El Manar National Engineering School of Tunis LR11ES20 Analysis Design and Control of Systems Laboratory Tunis Tunisia

This paper is focused on uncertain fractional order systems. In this context, a new modelling approach of uncertain fractional order systems represented by an explicit fractional order interval transfer function is proposed. This approach is based, essentially, on multimodel approach. In fact, firstly, two new determination methods of models’ library, inspired from the Kharitonov approach, are exposed. Then, we propose to compute the validity degree of each model of the obtained library, by optimizing a constrained least squares problem. The global model is, finally deduced by fusion of outputs of the different library’ models. To prove its efficiency and its precision, the proposed approach is then compared to the approximation approach of Oustaloup through two simulation examples.

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Intelligent Verbal Interaction Methods with Non-Player Characters in Metaverse Applications

Intelligent Verbal Interaction Methods with Non-Player Chara...

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International Conference on Advanced Information and Communication Technologies (AICT)

作者： Vladislav Pariy Khrystyna Lipianina-Honcharenko Ruslan Brukhanskyi Anatoliy Sachenko Fedir Tkachyk Dmytro Lendiuk Department for Information Computer Systems and Control West Ukrainian National University Ternopil Ukraine Department of Business Analytics and Innovative Engineering West Ukrainian National University Ternopil Ukraine Research Institute for Intelligent Computer Systems West Ukrainian National University Ternopil Ukraine Department of Informatics and Teleinformatics Kazimierz Pulaski University of Technology and Humanities in Radom Radom Poland Department of Taxes and Fiscal Policy West Ukrainian National University Ternopil Ukraine

This article is devoted to the development of Intelligent Verbal Interaction Methods with Non-Player Characters in Metaverse Applications. The creation of a character model using MetaHuman Creator and the implementation of dialogue animation are considered. The construction of answers based on text analysis and their submission to the chat window is described. The system has been tested and found to be stable and have a satisfactory response time of approximately 2 seconds. The results show the successful implementation of methods of verbal interaction with non-game characters in metaverse, which can be useful for further research and development in this area.

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