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IEEE International Conference on Bioinformatics and Biomedicine (BIBM)

作者： Ming Liu Wei Dai Wei Peng Yu Fu Yi Pan Faculty of Information Engineering and Automation Kunming University of Science and Technology Computer Technology Application Key Lab of Yunnan Province Kunming University of Science and Technology Kunming China Medical school Kunming University of Science and Technology Kunming China Georgia State University Atlanta GA USA

ISBN: (数字)9781728162157

ISBN: (纸本)9781728162164

Microbes play a crucial role in human health and disease. Understanding the relationship between microbes and diseases is conducive to the treatment and diagnosis of diseases. Recently, many computational methods have been proposed to predict disease-microbe associations. However, most of the existing methods only consider a single model and explore the disease-microbe associations from a single view. To improve the prediction accuracy, we propose a novel multi-view approach that fuses the linear and nonlinear features to predict new potential associations between diseases and microbes. We first design a non-negative matrix tri-factorization method to extract the linear features of diseases and microbes. We input the linear features from the non-negative matrix tri-factorization model and bi-random walk model into a capsule neural network to obtain the diseases and microbes' nonlinear features. Finally, we leverage a logistic regression model to combine the non-negative matrix tri-factorization model predictions, bi-random walk model predictions and the capsule neural network predictions to obtain the final association scores between microbes and diseases. We apply our method to predict human microbedisease associations. Experimental results show that our fusion model outperforms the non-negative matrix tri-factorization model, bi-random walk model and other existing models.

关键词： Diseases Predictive models Neural networks Feature extraction Computational modeling Logistics Kernel

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Magnetic and levitation properties of YBCO/polymer composite drop-casting films

Next Materials

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Next Materials 2025年 8卷

作者： Beatriz Lucas Miguel Brito Canan Aksoy Bakiye Cakir Elvan Coşkun Ali Gencer Anabela Pronto Isabel Ferreira CENIMAT|i3N Department of Materials Science School of Science and Technology NOVA University Lisbon Caparica Portugal Electrical and Computer Engineering Department School of Science and Technology NOVA University Lisbon Caparica Portugal Electronics and Communication Engineering Faculty of Technology Karadeniz Technical University Trabzon 61830 Turkiye Vocational School of Health Services Artvin Çoruh University Artvin 08000 Turkiye Ankara University Superconductor Technologies Application and Research Center Gölbaşı Ankara Turkiye Ankara University Faculty of Sciences Physics Department Ankara 06100 Turkiye Center of Technology and Systems CTS/UNINOVA School of Science and Technology NOVA University Lisbon Caparica Portugal

Superconducting materials have been extensively studied for various applications, with YBCO alloys among the most researched and widely applied. This paper investigates the feasibility of using YBCO powder-based inks to produce cost-effective films with magnetic properties. Our studies demonstrate that levitation in liquid nitrogen is consistently observed in all fabricated films, regardless of ink composition or application method. Both drop-casting and spray-coating techniques were successfully employed to create levitating films. Additionally, various substrates—including aluminum foil (with and without adhesive), plastic foil, Teflon, and paper—were evaluated, with no significant impact on levitation performance. The levitation height was also compared to samples without a substrate. Depending on the binder, the resulting films exhibit rigidity or flexibility while maintaining their levitation capabilities even after multiple bending cycles. However, film conductivity is influenced by the binder type and concentration, which also affects the critical current density. A film with a thickness of 300 μm demonstrated a Jc of 2 kA/cm² at 65 K and zero magnetic field.

关键词： YBCO superconductor powders Polymers superconductor hybrid materials Selfsustained drop-casting films Levitation and magnetic properties Surface and chemical analysis

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S-shaped binary whale optimization algorithm for feature selection 1st

S-shaped binary whale optimization algorithm for feature sel...

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1st International Symposium on Signal and Image Processing, ISSIP 2017

作者： Hussien, Abdelazim G. Hassanien, Aboul Ella Houssein, Essam H. Bhattacharyya, Siddhartha Amin, Mohamed Faculty of Science Fayoum University Faiyum Egypt Faculty of Computers and Information Cairo University Giza Egypt Faculty of Computers and Information Minia University Minya Egypt Department of Computer Application RCC Institute of Information Technology Kolkata700 015 India Faculty of Science Menoufia University Shibin El Kom Egypt

ISBN: (纸本)9789811088629

Whale optimization algorithm is one of the recent nature-inspired optimization technique based on the behavior of bubble-net hunting strategy. In this paper, a novel binary version of whale optimization algorithm (bWOA) is proposed to select the optimal feature subset for dimensionality reduction and classifications problem. The new approach is based on a sigmoid transfer function (S-shape). By dealing with the feature selection problem, a free position of the whale must be transformed to their corresponding binary solutions. This transformation is performed by applying an S-shaped transfer function in every dimension that defines the probability of transforming the position vectors’ elements from 0 to 1 and vice versa and hence force the search agents to move in a binary space. K-NN classifier is applied to ensure that the selected features are the relevant ones. A set of criteria are used to evaluate and compare the proposed bWOA-S with the native one over eleven different datasets. The results proved that the new algorithm has a significant performance in finding the optimal feature. © Springer Nature Singapore Pte Ltd. 2019.

关键词： Classification (of information)

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ASEAN entrepreneurship profiling: A new model for mobile-based application development

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AIP Conference Proceedings 2023年第1期2938卷

作者： Reinhart Previano Koentjoro Sasmoko Sonya Rapinta Manalu Yasinta Indrianti Jurike Moniaga School of Computer Science Bina Nusantara University Jakarta Indonesia 11470 Primary Teacher Education Department Faculty of Humanities Bina Nusantara University Jakarta Indonesia 11470 Research Interest Group in Educational Technology Bina Nusantara University Jakarta Indonesia 11470 Mobile Application & Technology School of Computer Science Bina Nusantara University Jakarta Indonesia 11470 Entrepreneurship Department Universitas Agung Podomoro Jakarta Indonesia 11480

The ASEAN Entrepreneurship Profiling (AEP) mobile application is an application developed to measure the profile of entrepreneurs in ASEAN. By utilizing this application, it is hoped that entrepreneurs can conduct self-assessments independently and obtain a self-profile picture that can be used to see the gaps in indicators of successful entrepreneurs. The purpose of this research is to develop AEP mobile application with Flutter and Laravel based application development. The application can be used for Android and iOS considering the variety of mobile phones used by entrepreneurs. The AEP mobile application backend uses the Laravel framework and the PHP programming language. The research method used is the waterfall method as a simple and systematic development model that divides the entire work into several stages, namely communication, planning, modeling, construction, and deployment. The results of the research are in the form of AEP mobile application that are ready to be implemented by entrepreneurs so that they can quickly find out their profile as entrepreneurs. This application can assist entrepreneurs in setting self-development strategies based on a priority scale according to the conditions experienced.

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Data Mining Implementation for Monitoring Network Intrusion

Data Mining Implementation for Monitoring Network Intrusion

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International Conference on Informatics and Computational Sciences (ICICoS)

作者： Annisa Andarrachmi Wahyu Catur Wibowo Faculty of Computer Science Universitas Indonesia Agency for the Assessment and Application of Technology Jakarta Indonesia Faculty of Computer Science Universitas Indonesia Jakarta Indonesia

The Information and Communication Network Center (BJIK) is one of the centers in the Agency for the Assessment and application of technology (BPPT). BJIK develops a network monitoring information system called Simontik to protect the BPPT system from threats where antivirus softwares and firewalls fail to give the level of protection needed. The random nature of threats makes it difficult to develop a rule-based system to predict the existence of intrusion. In this research, we apply a deep learning model to predict network intrusion. We found that our deep learning model using deep neural network and random forest algorithm can produce 99.91% accuracy compared to 98.11% using support vector machine algorithm.

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Estimating red noise in quasi-periodic signals with MCMC-based Bayesian

arXiv

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arXiv 2020年

作者： Liang, Bo Meng, Yao Feng, Song Yang, Yunfei Faculty of Information Engineering and Automation Kunming University of Science and Technology Kunming650500 China Key Laboratory of Solar Activity National Astronomical Observatories Chinese Academy of Sciences Beijing100012 China Yunnan Key Laboratory of Computer Technology Application Kunming650500 China

Multi-parameter Bayesian inferences based on Markov chain Monte Carlo (MCMC) samples have been widely used to estimate red noise in solar period-periodic signals. To MCMC, proper priors and sufficient iterations are prerequisites ensuring the accuracy of red noise estimation. We used MCMC-based Bayesian inferences to estimate 100 groups of red noise synthesized randomly for evaluating its accuracy. At the same time, the Brooks-Gelman algorithm was employed to precisely diagnose the convergence of the Markov chains generated by MCMC. The root-mean-square error of parameter inferences to the synthetic data is only 1.14. Furthermore, we applied the algorithm to analyze the oscillation modes in a sunspot and a flare. A 70 s period is detected in the sunspot umbra in addition to 3- and 5-minute periods, and a 40 s period is detected in the flare. The results prove that estimating red noise with MCMC-based Bayesian has more high accuracy in the case of proper priors and convergence. We also find that the number of iterations increases dramatically to achieve convergence as the number of parameters grows. Therefore, we strongly recommend that when estimating red noise with MCMC-based Bayesian, different initial values must be selected to ensure that the entire posterior distribution is covered. Copyright © 2020, The Authors. All rights reserved.

关键词： Bayesian networks

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Mobile game application for Religion engagement

Mobile game Application for Religion engagement

引用

2019 International Congress on Applied Information technology, AIT 2019

作者： Kristiadi, Dedy Prasetya Vindy, V. Sambera, Richard Julianto, Andy Warnars, Harco Leslie Hendric Spits Hashimoto, Kiyota STMIK Raharja Computer Systems Department Tangerang15117 Indonesia Game Application Technology Program School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia School of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia BINUS Graduate Program - Doctor of Computer Science Bina Nusantara University Computer Science Department Jakarta11480 Indonesia Faculty of Technology and Environment Prince Songkla University Phuket Campus Thailand

ISBN: (纸本)9781728158624

Religion is a part of a fundamental human right to serve and worship their God according to their religion and belief. Mobile game application along with the development of mobile phone technology such as a smartphone, tablet, and laptop, can be used to increase the player or user interest to engage with religion thing. Using the mobile game application in mobile gadgets will expand quickly to install and use for religion engagement. The player can learn religion things with fun and entertain ways, where the player does not realize that they do something serious in an unserious way. This paper will explain the model system design for mobile game application for learning Catholicism in fun and entertaining way and for the first development was limited to only three Catholic catechisms such as bible learning, church lesson, and liturgy celebration. For the early development, three types of games were developed such as True or False game, Scramble words game, and multiple-choice game. The mobile game model was designed with a use case diagram, storyboard, and class diagram, where for the current implementation the mobile game application was implemented using a ten tables database. © 2019 IEEE.

关键词： Serious games

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Response to "Comment on 'A novel two-dimensional boron-carbon-nitride (BCN) monolayer: A first-principles insight [J. Appl. Phys. 2021, 130, 114301]'"

arXiv

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arXiv 2022年

作者： Bafekry, Asadollah Naseri, Mosayeb Fadlallah, Mohamed M. Sarsari, Ismaeil Abdolhosseini Faraji, Mehrdad Khatibani, Abbas bagheri Ghergherehchi, Mitra Gogova, Daniela Department of Radiation Application Shahid Beheshti University Tehran*** Iran Department of Physics Kermanshah Branch Islamic Azad University Kermanshah*** Iran Department of Physics Faculty of Science Benha University Benha13518 Egypt Department of Physics Isfahan University of Technology Isfahan84156-83111 Iran Micro and Nanotechnology Graduate Program TOBB University of Economics and Technology Sogutozu Caddesi No 43 Sogutozu Ankara06560 Turkey Nano Research Lab Lahijan Branch Islamic Azad University Lahijan1616 Iran Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of Department of Physics Chemistry and Biology Linkoping University Linköping581 83 Sweden

Mortazavi et al. comment on the results of our paper "A novel two-dimensional boron-carbon-nitride BCN monolayer: A First-principles insight," in which we have considered different configurations of BCN. For clarification, we applied the fingerprint theory [1-3] to examine the similarity between the distinct structures. The fingerprint function is a crystal structure descriptor, an 1D-function related to the pair correlation function and diffraction patterns. It does not depend on absolute atomic coordinates, but only on interatomic distances. Small deviations in atomic positions will influence the fingerprints only slightly [1-3]. Fingerprint theory allows quantification of the degree of order and complexity of a crystal structure. © 2022, CC BY.

关键词： Monolayers

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Machine learning based calculation of refractive index of polyethylene glycol polymer

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Results in Chemistry 2025年 16卷

作者： Walid Abdelfattah Munthar Kadhim Abosaoda Hardik Doshi H.S. Shreenidhi Manoranjan Parhi Devendra Singh Prabhjot Singh Bilakshan Purohit Kamal Kant Joshi Ahmad Abumalek Department of Mathematics College of Science Northern Border University Arar Saudi Arabia College of pharmacy the Islamic University Najaf Iraq College of pharmacy The Islamic University of Al Diwaniyah Al Diwaniyah Iraq Marwadi Universitly Research Center Department of Computer Engineering Faculty of Engineering & Technology Marwadi University Rajkot Gujarat India Assistant Professor Department of Computer Science and Engineering School of Engineering and Technology JAIN (Deemed to be University) Bangalore Karnataka India Department of Computer Science and Engineering Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar Odisha 751030 India Department of Computer science & Engineering Uttaranchal Institute of Technology Uttaranchal University Dehradun 248007 Uttarakhand India Department of Computer Application Chandigarh Engineering College Chandigarh Group of Colleges-Jhanjeri Mohali 140307 Punjab India Centre for Research Impact & Outcome Chitkara University Institute of Engineering and Technology Chitkara University Rajpura 140401 Punjab India Department of Allied Science Graphic Era Hill University Dehradun India Graphic Era Deemed to be University Dehradun Uttarakhand India Faculty of Engineering Balkh University Balkh Afghanistan

This study develops advanced machine learning algorithms to accurately predict the refractive index of polyethylene glycol (PEG) polymers using temperature and molecular weight as key input variables. A databank comprising 99 experimental measurements were utilized to train and assess multiple algorithms, including Extra Trees, Random Forests, Decision Trees, Ensemble Learning, AdaBoost, K-Nearest Neighbors, Multilayer Perceptron Artificial Neural Networks (MLP-ANN), Linear Regression, and Elastic Net. The dataset demonstrated a strong correlation between molecular weight and refractive index ( r = 0.64), and an inverse correlation with temperature ( r = −0.72). Model performance was assessed using R 2 , MSE, and AARE%, revealing that MLP-ANN, Linear Regression, and Elastic Net models yielded the highest accuracy on the testing dataset. Furthermore, SHAP analysis identified molecular weight as the dominant factor influencing refractive index predictions. The proposed approach significantly reduces the need for experimental measurements and offers a reliable, time-efficient solution for estimating the optical behavior of PEG polymers under varying conditions.

关键词： Machine learning Artificial intelligence Polyethylene glycol Refractive index Outlier detection SHAP analysis

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Preface

Smart Innovation, Systems and Technologies

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Smart Innovation, Systems and Technologies 2022年 281卷 viii-xv页

作者： Nayak, Janmenjoy Behera, H.S. Naik, Bighnaraj Vimal, S. Pelusi, Danilo University Baripada Odisha India Department of Computer Application Veer Surendra Sai University of Technology Odisha Sambalpur India Faculty of Communication Sciences University of Teramo Teramo Italy Department of Information Technology Veer Surendra Sai University of Technology Odisha Sambalpur India Department of AI & DS Ramco Institute of Technology Tamil Nadu Rajapalayam India

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