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arXiv 2021年

作者： Abousaleh, Fatma S. Cheng, Wen-Huang Yu, Neng-Hao Tsao, Yu Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Institute of Information Science Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan Department of Computer Science National Chengchi University Taipei11605 Taiwan The Institute of Electronics Department of Electronics Engineering National Chiao Tung University Hsinchu30010 Taiwan The College of Design Department of Design National Taiwan University of Science and Technology Taipei10607 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan

Billions of photos are uploaded to the web daily through various types of social networks. Some of these images receive millions of views and become popular, whereas others remain completely unnoticed. This raises the problem of predicting image popularity on social media. The popularity of an image can be affected by several factors, such as visual content, aesthetic quality, user, post metadata, and time. Thus, considering all these factors is essential for accurately predicting image popularity. In addition, the efficiency of the predictive model also plays a crucial role. In this study, motivated by multimodal learning, which uses information from various modalities, and the current success of convolutional neural networks (CNNs) in various fields, we propose a deep learning model, called visual-social convolutional neural network (VSCNN), which predicts the popularity of a posted image by incorporating various types of visual and social features into a unified network model. VSCNN first learns to extract high-level representations from the input visual and social features by utilizing two individual CNNs. The outputs of these two networks are then fused into a joint network to estimate the popularity score in the output layer. We assess the performance of the proposed method by conducting extensive experiments on a dataset of approximately 432K images posted on Flickr. The simulation results demonstrate that the proposed VSCNN model significantly outperforms state-of-the-art models, with a relative improvement of greater than 2.33%, 7.59%, and 14.16% in terms of Spearman’s Rho, mean absolute error, and mean squared error, respectively. Copyright © 2021, The Authors. All rights reserved.

关键词： Social networking (online)

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ZETA: a library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems

arXiv

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arXiv 2025年

作者： Rego, Brenner S. Scott, Joseph K. Raimondo, Davide M. Terra, Marco H. Raffo, Guilherme V. Department of Electrical and Computer Engineering University of São Paulo SP São Carlos13566-590 Brazil Department of Chemical and Biomolecular Engineering Georgia Institute of Technology 311 Ferst Dr. AtlantaGA30318 United States Department of Engineering and Architecture University of Trieste Trieste34127 Italy Department of Electronics Engineering Graduate Program in Electrical Engineering Federal University of Minas Gerais MG Belo Horizonte31270-901 Brazil

This paper introduces ZETA, a new MATLAB library for Zonotope-based EsTimation and fAult diagnosis of discrete-time systems. It features user-friendly implementations of set representations based on zonotopes, namely zonotopes, constrained zonotopes, and line zonotopes, in addition to a basic implementation of interval arithmetic. This library has capabilities starting from the basic set operations with these sets, including propagations through nonlinear functions using various approximation methods. The features of ZETA allow for reachability analysis and state estimation of discrete-time linear, nonlinear, and descriptor systems, in addition to active fault diagnosis of linear systems. Efficient order reduction methods are also implemented for the respective set representations. Some examples are presented in order to illustrate the functionalities of the new library. © 2025, CC BY.

关键词： Digital arithmetic

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Integrated data envelopment analysis, multi-criteria decision making, and cluster analysis methods: Trends and perspectives

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Decision Analytics Journal 2023年 8卷

作者： de Oliveira, Maiquiel Schmidt Steffen, Vilmar de Francisco, Antonio Carlos Trojan, Flavio Academic Department of Physics Statistics and Mathematics (DAFEM) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão Paraná 85602-863 Brazil Academic Departments of Engineering (DAENG) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Francisco Beltrão 85602-863 Paraná Brazil Academic Department of Electronics (DAELE) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa 84017-220 Paraná Brazil Post-Graduate Program in Production Engineering (PPGEP) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Ponta Grossa 84017-220 Paraná Brazil

Data Envelopment Analysis (DEA), Multi-criteria Decision Analysis (MCDA), and Cluster Analysis (CA) are techniques widely used to help decision-makers determine the solution to problems with multiple and often conflicting criteria. This study presents a comprehensive review of the literature on the DEA, MCDA, and CA models to identify existing and potential applications and future development trends. To this end, the Methodi Ordinatio was applied to determine which publications have the greatest impact, considering articles in three databases: Scopus, ScienceDirect, and Web of Science. We pair the techniques two by two since no results were found to integrate the three techniques. The results point to a portfolio with 490 articles, in which approximately 43.87% of the articles combine DEA and MCDA techniques for solving efficiency and productivity analysis problems. © 2023 The Author(s)

关键词： Cluster analysis Combined decision techniques Data envelopment analysis Literature review Methodi ordinatio Multi-criteria decision making

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An integrated data envelopment analysis framework for operational efficiency assessment in Brazilian international airports

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Decision Analytics Journal 2024年 12卷

作者： de Oliveira, Maiquiel Schmidt Steffen, Vilmar Krukoski, Franklin Angelo Mezoni, Maressa Fontana Trojan, Flávio Academic Department of Physics Statistics and Mathematics (DAFEM) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Paraná Francisco Beltrão 85602-863 Brazil Post-Graduate Program in Production Engineering (PPGEP) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Paraná Ponta Grossa 84017-220 Brazil Academic Departments of Engineering (DAENG) Federal University of Technology - Parana (UTFPR) Rua Gelindo João Folador 2000 Paraná Francisco Beltrão 85602-863 Brazil State University of Western Parana (UNIOESTE) Rua Maringá 1200 Francisco Beltrão 85605-010 Brazil Academic Department of Electronics (DAELE) Federal University of Technology - Parana (UTFPR) Rua Doutor Washington Subtil Chueire 330 Paraná Ponta Grossa 84017-220 Brazil

International airports play a significant role in a country's economic development. We propose an integrated framework for operational efficiency analysis using Data Envelopment Analysis, Windows Analysis, and Malmquist Index to identify inefficiencies and areas of improvement in the air transportation industry. This study analyzed 23 Brazilian international airports from 2010 to 2021, using the DEA Window Analysis (DEAWA) combined with the Index (MI). The airports were grouped geographically in southern Brazil. The integration of these methods brought an important insight to the evaluation processes, even for those previously analyzed using DEA. The analyses found that COVID-19 potently influenced the drop in the efficiency index. No airport was fully efficient over the analyzed periods. Private airports achieved an efficiency index slightly higher than public ones, but the difference of the efficiency index by public–private management type is not clear. This type of analysis provides a strategic and comparative tool, making it possible to understand better the weaknesses of the air transportation system. © 2024 The Author(s)

关键词： Airports management COVID-19 Data envelopment analysis Efficiency index Malmquist index Window analysis

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Multi-class classification of COVID-19 and other infections using machine learning model with wavelet and laws features

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AIP Conference Proceedings 2024年第1期2919卷

作者： Shaik Mahaboob Basha Aloísio Vieira Lira Neto Mohamed Abd Elaziz Shaik Hashmitha Mohisin Victor Hugo C. e Albuquerque Department of Electronics& Communication Engg N.B.K.R. Institute of Science &Technology Vidyanagar India Graduation Program in Telecommunication Engineering Federal Institute of Ceará Fortaleza-CE Brazil Faculty of Computer Science and Engineering Galala University Suez 435611 Egypt Department of Avionics Indian Institute of Space Science and Technology Thiruvananthapuram India Department of Teleinformatics Engineering Federal University of Ceará Fortaleza-CE Brazil

Corona virus disease (COVID-19) was responsible for inevitable chaos in the human life due to its inherent nature of high contagious across the globe. This very reason also hindered the physicians and healthcare support systems to provide in-time medical aid to the suffering *** diagnosis of COVID-19 using clinical information is the prime source for detection and treatment. However, computerised tomography (CT) and Chest X-ray (CXR) images have found useful for screening purposes due to the successful usage of image based analysis by physicians which was aided by image processing based *** means of screening, diagnosis and prognostic studies using CT and CXR with the help of comprehensive image processing pipelines could invariably augment the efficiency in the respective tasks. The main objective of this study is to implement multi-class classification of COVID-19, viral-pneumonia (VP) and lung opacity (LO) using threshold-based segmented CXR images further transformed using wavelet transform (WT)and Laws based texture representation. Machine learning (ML) based implementation and comparison was carried using Random Forest (RF) and Logistic regression (LR) techniques with of the WT and Laws features individually as well as with combined feature vectors. The ML based implementation was aimed to classify the CXR image based on the individual or combined features into COVID-19, VP or LO pathology. The validation of the ML techniques was further carried using confusion matrix and other validation measures. The performance of the RF classifier was superior with WT features than Laws texture features on individual category of features than LR technique. Amarginal improvement was observed in the classifier performance when WT and Laws based features were combined.

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Single quantum emitters with spin ground states based on Cl bound excitons in ZnSe

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Physical Review A 2022年第3期106卷 L030402-L030402页

作者： Aziz Karasahin Robert M. Pettit Nils von den Driesch Marvin Marco Jansen Alexander Pawlis Edo Waks Institute for Research in Electronics and Applied Physics Department of Electrical and Computer Engineering and Joint Quantum Institute University of Maryland College Park Maryland 20742 USA Intelligence Community Postdoctoral Research Fellowship Program University of Maryland College Park Maryland 20742 USA Peter-Grünberg-Institute (PGI-9) Forschungszentrum Jülich GmbH 52425 Jülich Germany JARA-FIT (Fundamentals of Future Information Technology) Jülich-Aachen Research Alliance 52062 Aachen Germany

Defects in wide-band-gap semiconductors are promising qubit candidates for quantum communication and computation. Epitaxially grown II-VI semiconductors are particularly promising host materials due to their direct band gap and potential for isotopic purification to a spin-zero nuclear background. Here, we show an alternative type of single photon emitter with potential electron spin qubits based on Cl impurities in ZnSe. We utilize a quantum well to increase the binding energies of donor emission and confirm single photon emission with short radiative lifetimes of 192 ps. Furthermore, we verify that the ground state of the Cl donor complex contains a single electron by observing two-electron-satellite emission, leaving the electron in higher orbital states. We also characterize the Zeeman splitting of the exciton transition by performing polarization-resolved magnetic spectroscopy on single emitters. Our results suggest single Cl impurities are suitable as a single photon source with a potential photonic interface.

关键词： Impurities Quantum information with solid state qubits Single photon sources Quantum wells Wide band gap systems Spectroscopy

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Fringe Field Assisted Electrostatic Discharge in Polypropylene Manufacturing

Fringe Field Assisted Electrostatic Discharge in Polypropyle...

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International Electrical engineering Congress (iEECON)

作者： Panudda Charoensorn Siwapon Srisonphan Weerawoot kanokbannakorn Varakorn Kasemsuwan Graduate program in safety engineering Kasetsart University Bangkok Thailand Department of Electrical Engineering Kasetsart University Bangkok Thailand Department of Electronics Engineering King Mongkut’s Institute of Technology Ladkrabang Bangkok

ISBN: (数字)9781728130767

ISBN: (纸本)9781728130774

Polypropylene (PP) is an electrical insulation material, and it can store electrostatic charge easily once they have friction with the metal or rubber rollers. Herein we present electrostatic issues in non-woven fabric manufacturing based on the roll to roll production processes. By using portable electrostatic-field meter measurements, we provide a low-cost and highly effective solution for discharging electrostatic charge before exposed or in contact with the operators, and we also identify where to install charge-dissipation technology to make it most useful. We employed the benefit of a highly and localized fringe field to discharge the electrostatic charge along the edge of the grounded metal rod placed at ~30 cm away. After placing the metal rod, the average of electrostatic potential of winding stock roll during spinning is decreased ~10 times, corresponding to ~0.2 μc/m 3 accumulated electrostatic charge on synthetic fabrics. The electric field distribution via the finite element method was illustrated corresponding to the reduction of electrostatic charge distribution in PP winding stock roll before and after inserting the grounded metal rod.

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The Effect of Blended Learning Model to Improve the Conceptual Understanding of Computer and Network engineering Students 2

The Effect of Blended Learning Model to Improve the Conceptu...

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2nd International Conference on Electrical, electronics, Informatics, and Vocational Education, ICE-ELINVO 2019

作者： Hawi, F.M. Sudira, P. Electronics and Informatics Engineering Education Department Postgraduate Program Universitas Negeri Yogyakarta Yogyakarta Indonesia Vocational Technology Education Postgraduate Program Universitas Negeri Yogyakarta Yogyakarta Indonesia

Grounded by students' lack of conceptual understanding in identifying and comprehending basic concepts of computer network, this quasi-experimental study aims to identify the effect of applying blended learning model toward the improvement of students' conceptual understanding. It was designed using non-equivalent control group design in which the experimental group and the control group were differently treated using, respectively, blended learning and conventional learning model. There were 58 students selected as the sample of the research;30 students in experimental class and 28 students in control class. Essay test was chosen to collect the data of the conceptual understanding of the students in both groups. Using MANOVA, the data analysis revealed the significant effect of applying blended learning model toward students' conceptual understanding with P = 0.000 © Published under licence by IOP Publishing Ltd.

关键词： Students

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MMP Net: A feedforward neural network model with sequential inputs for representing continuous multistage manufacturing processes without intermediate outputs

A I I E Transactions

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A I I E Transactions 2024年第10期56卷

作者： Hojin Cho Kyeongbin Kim Kihyuk Yoon Jaewook Chun Jaeyong Kim Kyeongmin Lee Junghye Lee Chiehyeon Lim a Department of Industrial Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Korea b LG Electronics Seoul Republic of Korea c SK Enmove Ulsan Republic of Korea d Technology Management Economics and Policy Program Seoul National University Seoul Republic of Korea a Department of Industrial Engineering Ulsan National Institute of Science and Technology Ulsan Republic of Koreae Graduate School of Artificial Intelligence Ulsan National Institute of Science and Technology Ulsan Republic of Korea

Machine learning models that are used for the prediction and control of production can improve quality and yield. However, developing models that are highly accurate and reflective of real-world processes is challenging. We propose a feedforward neural network model specifically designed for continuous Multistage Manufacturing Processes (MMPs) without intermediate outputs. This model, which is termed “MMP Net,” can accurately represent the control mechanism of continuous MMPs. Whereas existing studies on learning MMPs assume an intermediate output data, the MMP Net does not require such an unrealistic assumption. We use the MMP Net to develop prediction models for the lubricant base oil production process of a world-leading lubricant manufacturer. Evaluation results show that the MMP Net is superior to other deep neural network and machine learning models. Consequently, the MMP Net was actually implemented in a real factory in 2022 and is expected to save 900,000 dollars per year for each production line. We believe that our work can serve as a basis to develop customized machine learning solutions for improving continuous MMPs.

关键词： Multistage manufacturing process neural network petrochemical manufacturing system quality prediction real-world application

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An Efficient and Accurate Algorithm for Electromagnetic Wave Propagation Modeling Based on Wavelet Transforms

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Journal of Microwaves, Optoelectronics and Electromagnetic Applications 2024年第1期23卷

作者： Rocha, Alexandre Parada, Diego Tami, Diego Guevara, Dinael Rego, Cássio G. Graduate Program in Electrical Engineering Universidade Federal de Minas Gerais Av. Antônio Carlos 6627 MG Belo Horizonte31270-901 Brazil Institute of Science Technology and Innovation - ICTIN Universidade Federal de Lavras Rua Antônio Carlos Pinheiro de Alcântara 855 MGSão Sebastião do Paraíso 37950-000 Brazil Institute of Technological Sciences Universidade Federal de Itajubá Rua Irmã Ivone Drumond 200 MG Itabira35903-087 Brazil Department of Electricity and Electronics Universidad Francisco de Paula Santander - AV. Gran Colombia 12e-96 Colsag Norte de Santander Cúcuta540003 Colombia Department of Electronic Engineering Universidade Federal de Minas Gerais Av. Antônio Carlos 6627 MG Belo Horizonte31270-901 Brazil

In this article, a comprehensive analysis of the approach known as Split-Step Wavelet Parabolic Equation (SSW-PE) in modeling radio wave propagation is presented. The SSW-PE introduces innovations, such as the application of narrow-angle and wide-angle approaches, referred to as NAPE and WAPE, respectively. Furthermore, the SSW-PE demonstrates the incorporation of refractivity variations, modifications in terrain modeling for better representation, and considerations of surface boundary conditions. In addition to its innovative aspects, this study aims to provide a complete guide for effectively replicating the algorithm, thereby promoting the advancement of propagation studies using wavelets. The effectiveness and applicability of this approach are validated through comparative studies with well-established solutions, including the Discrete Mixed Fourier Transform (DMFT) version of the Split-Step Parabolic Equation (SSPE) method. Comparisons with measurements from real propagation cases are also conducted. Statistical analysis confirms the innovative potential of the SSW-PE algorithm, which also offers computational efficiency for rapid and consistent simulations. Thus, this article contributes to a comprehensive and innovative analysis, providing tangible resources for the research community interested in expanding this methodology. © 2024 SBMO/SBMag.

关键词： Wavelet transforms

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