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IEEE International Conference on Communication, Networks and Satellite (ComNetSat)

作者： Syariful Ikhwan Adi Wibowo Budi Warsito Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia D3 Telecommunication Engineering Institut Teknologi Telkom Purwokerto Banyumas Indonesia Computer Science Informatics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia Statistics Department of Science and Mathematics Faculty Diponegoro University Semarang Indonesia

ISBN: (数字)9781665460309

ISBN: (纸本)9781665460316

The increasing use of IoT devices on future networks is very helpful for humans in their lives. However, the increase in devices connected to IoT networks also increases the potential for attacks against those networks. Vulnerabilities in Internet of Things (IoT) networks can be exposed at any time. Artificial intelligence can be used to protect the IoT network by being able to detect attacks on the network so that they can be prevented. In this study, network detection was carried out using the Deep Neural Network (DNN) algorithm. The test was carried out using the UNSW Bot-IoT dataset with a comparison of training data of 75% of the overall data. The results obtained show the ability of the algorithm to detect attacks on average with 99.999% accuracy. The validation loss and training loss look very small. In this study, there is a validation loss that still occurs in overfitting, but the difference is very small.

关键词： Deep learning Training Satellites Neural networks Intrusion detection Training data Feature extraction

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Design ethnomathematics mobile module to improve mathematics thinking ability

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AIP Conference Proceedings 2023年第1期2614卷

作者： Ratri Rahayu Henry Suryo Bintoro Alif Catur Murti Mathematics Education Study Program Teacher Training and Education Faculty Universitas Muria Kudus PO.BOX 53 Gondangmanis Bae Kudus Indonesia Informatics Engineering Study Program Faculty of Engineering Universitas Muria Kudus PO.BOX 53 Gondangmanis Bae Kudus Indonesia

The aims of this study are (1) analyzing the need for teaching materials in the form of mobile modules in mathematics learning; (2) produce a draft outline of the ethnomathematics mobile module. The subjects of this study were the principal, mathematics teacher, seventh-grade students of Junior High School in Kudus, Indonesia. Data obtained from literature studies and field surveys include questionnaires, interviews, and FGD. The data analysis technique used is data triangulation with stages: reduction, data presentation, and conclusions based on data descriptions. The results showed that (1) students’ mathematical thinking skills are still low, teachers have not used application-based media, teachers have not developed ethnomathematical-based media, students need learning media that can improve mathematical thinking skills and make students interested in learning mathematics; (2) the ethnomathematics component of the mobile module is divided into 3 main parts, namely the introduction, the core, and the end. The introductory section includes the initial login page, instructions for use, and information regarding basic competencies. The core section contains the content of learning activities that contain ASEP (apperception), JAYA (cultural bridge), SITI (material description), EDI (self-evaluation). The last part contains motivational sentences.

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Estimating action plans for smart poultry houses

arXiv

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arXiv 2020年

作者： Klotz, Darlan Felipe Ribeiro, Richardson Enembreck, Fabrcio Denardin, Gustavo Barbosa, Marco Casanova, Dalcimar Teixeira, Marcelo Graduate Program in Electrical Engineering Federal University of Technology Paran Pato Branco Brazil Graduate Program in Informatics of the Pontifical Catholic University of Paran Curitiba Brazil

In poultry farming, the systematic choice, update, and implementation of periodic (t) action plans define the feed conversion rate (FCRhti), which is an acceptable measure for successful production. Appropriate action plans provide tailored resources for broilers, allowing them to grow within the so-called thermal comfort zone, without wast or lack of resources. Although the implementation of an action plan is automatic, its configuration depends on the knowledge of the specialist, tending to be inefficient and error-prone, besides to result in different FCRhti for each poultry house. In this article, we claim that the specialist’s perception can be reproduced, to some extent, by computational intelligence. By combining deep learning and genetic algorithm techniques, we show how action plans can adapt their performance over the time, based on previous well succeeded plans. We also implement a distributed network infrastructure that allows to replicate our method over distributed poultry houses, for their smart, interconnected, and adaptive control. A supervision system is provided as interface to users. Experiments conducted over real data show that our method improves 5% on the performance of the most productive specialist, staying very close to the optimal FCR(t).MSC Codes 68T35 (Primary) 93C40 (Secondary) Copyright © 2020, The Authors. All rights reserved.

关键词： Adaptive control systems

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Improving Clinical NLP Performance through Language Model-Generated Synthetic Clinical Data

arXiv

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arXiv 2024年

作者： Chen, Shan Gallifant, Jack Guevara, Marco Gao, Yanjun Afshar, Majid Miller, Timothy Dligach, Dmitriy Bitterman, Danielle S. Program Mass General Brigham Harvard Medical School BostonMA United States Department of Radiation Oncology Brigham and Women's Hospital Dana-Farber Cancer Institute BostonMA United States Computational Health Informatics Program Boston Children's Hospital Harvard Medical School BostonMA United States Institute for Medical Engineering and Science Massachusetts Institute of Technology CambridgeMA United States Department of Critical Care Guy's & St Thomas' NHS Trust London United Kingdom Department of Medicine University of Wisconsin School of Medicine and Public Health MadisonWI United States Department of Computer Science Loyola University Chicago ChicagoIL United States

Brief communication 70 words: Generative models have been showing potential for producing data in mass. This study explores the enhancement of clinical natural language processing performance by utilizing synthetic data generated from advanced language models. Promising results show feasible applications in such a high-stakes domain. © 2024, CC BY-NC-SA.

关键词： Natural language processing systems

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Bayesian non-parametric clustering of single-cell mutation profiles 24th

Bayesian non-parametric clustering of single-cell mutation p...

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24th Annual Conference on Research in Computational Molecular Biology, RECOMB 2020

作者： Borgsmüller, Nico Bonet, Jose Marass, Francesco Gonzalez-Perez, Abel Lopez-Bigas, Nuria Beerenwinkel, Niko Department of Biosystems Science and Engineering ETH Zürich Basel Switzerland SIB Swiss Institute of Bioinformatics Basel Switzerland The Barcelona Institute of Science and Technology Barcelona Spain Research Program on Biomedical Informatics Universitat Pompeu Fabra Barcelona Spain Barcelona Spain

Cancer is an evolutionary process characterized by the accumulation of mutations that drive tumor initiation, progression, and treatment resistance. © Springer Nature Switzerland AG 2020.

ISBN: (纸本)9783030452568

Cancer is an evolutionary process characterized by the accumulation of mutations that drive tumor initiation, progression, and treatment resistance. © Springer Nature Switzerland AG 2020.

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Testing Real-Time Applications on Windows 10 IOT Using the Nyquist Theory 1

Testing Real-Time Applications on Windows 10 IOT Using the N...

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1st International Conference on Computer Science and Applied Mathematic, ICCSAM 2018

作者： Syahputa, Zulfahmi Zarlis, M. Nasution, Beny B. Informatics Engineering Study Program Magister Faculty of Computer Science Information Technology Universitas Sumatera Utara Medan Indonesia

Raspberry Pi is a mini-computer that is provided to carry out activities quickly and precisely, but Raspberry Pi was created to not be able to do the real-time system with the support of Windows 10 IoT operating system, so the real-time system can be done on Raspberry Pi. The real-time applied in the application needs to be tested with the Nyquist theory. The purpose of this study was to get real-time system measurements available on Windows 10 IoT. This test is done using the Nyquist theory by calculating the results of measurements on mp3 streaming performed on Windows 10 IoT. © Published under licence by IOP Publishing Ltd.

关键词： Real time systems

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Organizational indicators on startup software for implementing secure software development lifecycle (SSDL): A systematic literature review

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AIP Conference Proceedings 2023年第1期2683卷

作者： Doddy Ferdiansyah Rizal Isnanto Jatmiko E. Suseno Program of Information System Doctoral Diponegoro University Semarang Indonesia Departement of Informatics Engineering Pasundan University Bandung Indonesia Departement of Computer Engineering Diponegoro University Semarang Indonesia Departement of Physics Diponegoro University Semarang Indonesia

The development of companies called startups is a company that has a lot to do with the world of technology and information; even in Indonesia, it has become a new trend, including the rise of startups engaged in software development. Many software startups have started to emerge by developing innovative software products to increase economic value to increase job opportunities. However, not a few software products that have been produced have failed. One of the causes of product failure is organizational factors, where the organisation’s culture is still a very complex problem for software startups. The role of top-level management in software startups also affects the organization in supporting the success of the products produced. In this study, we conduct a review of the literature in the organizational area in implementing information security governance, focusing on its application to secure software development. Information security governance is part of an organisation’s overall governance where it protects the organisation’s existence. Thereby, the focus of this review is to explain governance associated with organizations with a standardized approach to information security governance and investigate the variables that influence top-level management structures on secure software development.

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Protocol to explain support vector machine predictions via exact Shapley value computation

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STAR Protocols 2024年第2期5卷 103010页

作者： Mastropietro, Andrea Bajorath, Jürgen Deparment of Computer Control and Management Engineering “Antonio Ruberti” Sapienza University of Rome Via Ariosto 25 Rome 00185 Italy Department of Life Science Informatics and Data Science B-IT LIMES Program Unit Chemical Biology and Medicinal Chemistry Rheinische Friedrich-Wilhelms-Universität Friedrich-Hirzebruch-Allee 5/6 Bonn 53115 Germany Lamarr Institute for Machine Learning and Artificial Intelligence Friedrich-Hirzebruch-Allee 5/6 Bonn 53115 Germany

Shapley values from cooperative game theory are adapted for explaining machine learning predictions. For large feature sets used in machine learning, Shapley values are approximated. We present a protocol for two techniques for explaining support vector machine predictions with exact Shapley value computation. We detail the application of these algorithms and provide ready-to-use Python scripts and custom code. The final output of the protocol includes quantitative feature analysis and mapping of important features for visualization. For complete details on the use and execution of this protocol, please refer to Feldmann and Bajorath¹ and Mastropietro et al.² © 2024 The Author(s)

关键词： Bioinformatics Chemistry Computer sciences

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Work system method as an e-learning design framework in private universities

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Journal of Physics: Conference Series 2021年第1期1810卷

作者： C E Supriana Informatics Engineering Study Program Faculty of Engineering Pasundan University Bandung Indonesia

The development of information and communication technology, especially the internet provides opportunities to improve the ability of lecturers to deliver courses to students without being limited by distance and time. This can be done by utilizing e-learning which will accelerate the transfer of knowledge and skills. E-learning is distance education that utilizes various digital tools and platforms. These tools and platform are used to support interaction, lectures and delivery of instructions between lecturers and students. This study will discuss the use of work system methods and the use of e-learning technology in a business entity. The work system methods are used to design information systems. Meanwhile e-learning technology in a business entity serves lecturers and students, conduct lectures at private universities in increasing knowledge dissemination, educational affordability and the use of technology and information as its support. The result of this research is the works system method model which refers to the analysis of data from the internet accessibility survey of students, analysis of its components, the system development cycle, the revision of the vision, mission and resources in private universities and recommendations of opportunities for the development of higher quality e-learning implementation.

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Variational quantum circuit-based quantum machine learning approach for predicting corrosion inhibition efficiency of pyridine-quinoline compounds

Materials Today Quantum

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Materials Today Quantum 2024年 2卷

作者： Muhamad Akrom Supriadi Rustad Hermawan Kresno Dipojono Study Program in Informatics Engineering Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Research Center for Materials Informatics Faculty of Computer Science Universitas Dian Nuswantoro Semarang 50131 Indonesia Quantum and Nano Technologies Research Group Faculty of Industrial Technology Institut Teknologi Bandung Bandung 40132 Indonesia

This work used a variational quantum circuit (VQC) in conjunction with a quantitative structure-property relationship (QSPR) model to completely investigate the corrosion inhibition efficiency (CIE) displayed by pyridine-quinoline compounds acting as corrosion inhibitors. Compared to conventional methods like multilayer perceptron neural networks (MLPNN), the VQC model predicts the CIE more accurately. With a coefficient of determination (R 2 ), root mean square error (RMSE), mean absolute error (MAE), and mean absolute deviation (MAD) values of 0.989, 0.027, 0.024, and 0.019, respectively, VQC performs better. The established VQC model predicts the CIE with outstanding predictive accuracy for four newly synthesized pyrimidine derivative compounds: 1-(4-fluorophenyl)- 3-(4-(pyridin-4-ylmethyl)phenyl)urea (P1) , 1-phenyl-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P2) , 1-(4-methylphenyl)-3-(4-(pyridin-4-ylmethyl)phenyl)urea (P3) , and quaternary ammonium salt dimer (P4) . It generates remarkably high CIE values of 92.87, 94.05, 94.96, and 96.93 for P1, P2, P3, and P4, respectively. With its ability to streamline the testing and production processes for novel anti-corrosion materials, this innovative approach holds the potential to revolutionize the market.

关键词： Variational quantum circuit QSPR Corrosion inhibition Pyridine-quinoline

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