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International Seminar on Intelligent Technology and Its Applications (ISITIA)

作者： Gita Widarma Rice Novita Mustakim Nesdi Evrilyan Rozanda Information Systems Department Universitas Islam Negeri Sultan Syarif Kasim Riau Graduate Program Pekanbaru Indonesia Information Systems Postgraduate Programs Universitas Negeri Padang Pekanbaru Indonesia Master of Informatics Engineering Postgraduate Programs Institut Pertanian Bogor Pekanbaru Indonesia Master of Information Systems Management Postgraduate Programs Universiti Teknologi Malaysia Pekanbaru Indonesia

Twitter is currently used as one of the applications that is often used to convey opinions or unrest by the public such as the current issue that is currently rife, namely regarding the increase in fuel oil prices (BBM) in Indonesia. With so much data scattered in a tweet that only consists of a few fragments of words, there must be valuable information or meaning that Twitter users want to convey. Text mining is a very appropriate method to do the analysis because in text mining there is a method that focuses on an opinion which will be concluded into positive and negative opinions. There are several algorithms that are most often used in data mining, namely K-Nearest Neighbor, Decision Tree, and Naive Bayes. The three algorithms used in this study were also compared with the use of feature selection Particle Swarm Optimization (PSO) which is well known for improving the performance of algorithms. There are 2165 negative opinion data and 2835 positive sentiment data. The data will be tried based on distinctive sums of data namely 1000 data, 3000 data, and 5000 data. The classic K-Nearest Neighbor algorithm obtained an accuracy result of 75.60% and made it the best when tested with 1000 data. The use of Particle Swarm Optimization (PSO) is proven to improve accuracy as when tested using 3000 data with an accuracy value of 78.21% on the K-Nearest Neighbor algorithm. In the mean time, in testing 5000 Data, the classic K-Nearest Neighbor once more gotten the most elevated exactness with a esteem of 74.02%.

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Effect of Cu addition on electrochemical activity of ribbons of Mg-Al-Ca anode materials for magnesium rechargeable batteries manufactured by rapid solidification method

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 14-17页

作者： Fukui, Shunsaku Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

The potential for magnesium storage batteries to become the next generation of rechargeable batteries is high. This is largely due to the abundance of magnesium metal resources and their high safety and electric capacity per volume. Our research team has been studying magnesium alloys as anode materials for these batteries. Specifically, we have been investigating the electrochemical activity and mechanism of adding copper to Mg-9mass%Al and Mg-9mass%Al-3mass%Ca. Our findings indicate that the electrochemical activity increased with the addition of 1mass%Cu, but decreased with the addition of 3mass%Cu. In addition, changes in lattice constant and basal orientation were also observed. These changes decreased with 1mass%Cu and increased with 3mass%Cu. SEM observations showed that the cell delimitation was indistinct for the 1%Cu addition. © 2024 The Japan Institute of Light Metals.

关键词： Secondary batteries

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Gaussian Process Port-Hamiltonian systems: Bayesian Learning with Physics Prior

arXiv

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arXiv 2023年

作者： Beckers, Thomas Seidman, Jacob Perdikaris, Paris Pappas, George J. Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States graduate program in Applied Mathematics and Computational Science University of Pennsylvania PhiladelphiaPA19104 United States Department of Mechanical Engineering and Applied Mechanics University of Pennsylvania PhiladelphiaPA19104 United States

Data-driven approaches achieve remarkable results for the modeling of complex dynamics based on collected data. However, these models often neglect basic physical principles which determine the behavior of any real-world system. This omission is unfavorable in two ways: The models are not as data-efficient as they could be by incorporating physical prior knowledge, and the model itself might not be physically correct. We propose Gaussian Process Port-Hamiltonian systems (GP-PHS) as a physics-informed Bayesian learning approach with uncertainty quantification. The Bayesian nature of GP-PHS uses collected data to form a distribution over all possible Hamiltonians instead of a single point estimate. Due to the underlying physics model, a GP-PHS generates passive systems with respect to designated inputs and outputs. Further, the proposed approach preserves the compositional nature of Port-Hamiltonian systems. © 2023, CC BY-NC-ND.

关键词： Hamiltonians

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Effect of chemical composition and microstructure on the thermal conductivity of Mg-Al-Ca alloys

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Keikinzoku/Journal of Japan Institute of Light Metals 2024年第1期74卷 9-13页

作者： Kirimoto, Yuichi Kondo, Natsuki Ito, Mizuki Tsukeda, Tadayoshi Aida, Tetsuo Tabata, Hironobu Kurihara, Hideki Suzuki, Mayumi Department of Nano and Functional Material Science Graduate School of Science and Engineering for Education University of Toyama 3190 Gofuku Toyama-shi Toyama930-8555 Japan School of Sustainable Design Materials and Engineering University of Toyama Toyama-shi Toyama Japan Program of Materials Science and Engineering Studies in Science and Engineering Graduate School of Science and Engineering University of Toyama Toyama-shi Toyama Japan Faculty of Sustainable Design Academic Assembly University of Toyama Toyama-shi Toyama Japan CHUETSU METAL WORKS CO. LTD. Nakaniikawa-gun Toyama Japan Saitama Industrial Technology Center Kawaguchi-shi Saitama Japan Department of Mechanical Systems Engineering Faculty of Engineering Toyama Prefectural University Imizu-shi Toyama Japan

In recent years, the increasing demand for electric vehicles, digital devices such as PCs and smartphones, and renewable energy storage systems has created a need for higher-performance batteries. Accordingly, the thermal conductivity of the case that houses the battery is becoming increasingly important. In this study, compositions with high thermal conductivity and good castability were investigated, focusing on Mg-Al-Ca alloys, and the relationship between the two was examined through thermal conductivity measurements and microstructural observations. As a result, the Mg-6%Al-4%Ca alloy was optimal in terms of castability and thermal conductivity. It was confirmed that a lower Al solid solution capacity and a higher purity of the matrix phase are important to improve the thermal conductivity. It is also suggested that the second phase, platelet Al2Ca, is likely to be recognized and enriched in the matrix, contributing to the improvement of thermal conductivity. The amount of Ca solid solution in the matrix was suggested to be reduced by the enrichment of Al in the matrix. The Ca solid solution in the matrix was found to be less effective in reducing thermal conductivity than the Al solid solution. © 2024 The Japan Institute of Light Metals.

关键词： Magnesium alloys

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Synthesis of Zeolite from Waste Concrete Powder

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Funtai Oyobi Fummatsu Yakin/Journal of the Japan Society of Powder and Powder Metallurgy 2022年第5期69卷 208-212页

作者： Harada, Satori Kanda, Yasuyuki Mechanical Systems Engineering Course Graduate School of University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa903-0213 Japan Mechanical Engineering Program School of Engineering Faculty of Engineering University of the Ryukyus 1 Senbaru Nishihara-cho Nakagami-gun Okinawa903-0213 Japan

This study investigated the conditions for zeolite synthesis from waste concrete powder (WCP) using the hydrothermal synthesis method. The WCP was prepared by milling the waste concrete using pot mill equipment. The synthesis conditions, i.e., the heating time, heating temperature, and NaOH solution concentration were varied. Furthermore, hydrochloric acid-treated WCP (WCP-HCl), which is removed the calcium component, was prepared to examine the effectiveness of acid treatment in the zeolite synthesis. The zeolite synthesis was investigated using X ray diffraction (XRD) and scanning electron microscopy (SEM). Analcime-type zeolite was synthesized using WCP and WCP-HCl. The requirements of synthesis conditions for analcime were as follows: heating time above 12 h, heating temperature above 433 K, and NaOH solution concentration above 2 mol/ L. With a progressive increase in the concentration of the NaOH solution from 5 to 7 mol/L, analcime could be synthesized at NaOH concentrations below 4 mol/L, while cancrinite was synthesized at NaOH concentrations exceeding 5 mol/L. The peak intensity of analcime and cancrinite of WCP-HCl showed high value in comparison to the WCP. Thus, the effectiveness of the HCl treatment of WCP was confirmed from the XRD patterns. ©2022 Japan Society of Powder and Powder Metallurgy.

关键词： Hydrothermal synthesis

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Extending the Core Ontology on Decision Making according to Behavioral Economics 14

Extending the Core Ontology on Decision Making according to ...

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14th Seminar on Ontology Research in Brazil, ONTOBRAS 2021 and 5th Doctoral and Masters Consortium on Ontologies, WTDO 2021

作者： Ramos, Eduardo C. Campos, Maria Luiza M. Baião, Fernanda Guizzardi, Renata Graduate Program in Informatics Universidade Federal do Rio de Janeiro RJ Rio de Janeiro Brazil RJ Rio de Janeiro Brazil Department of Industrial Engineering and Business Information Systems University of Twente Enschede Netherlands

Decisions are constantly made and some of them may be extremely critical. However, most decision makers are unaware that their decisions may be biased. We used Behavioral Economics as a foundation to propose an ontology that shows how decision makers’ preferences are set and the situation in which they occur in an intuitive decision under risk and uncertainty. Our aim is that this ontology be used to improve their decisions by allowing them a better understanding of how they decide. In addition, this ontology can be used as part of a strategy to reduce biases. © 2021 Copyright for this paper by its authors.

关键词： Ontology

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Space and Time Efficiency Analysis of Data-Driven Methods Applied to Embedded systems

Space and Time Efficiency Analysis of Data-Driven Methods Ap...

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IEEE Symposium Series on Computational Intelligence (SSCI)

作者： Iron Tessaro Roberto Zanetti Freire Viviana Cocco Mariani Leandro dos Santos Coelho Industrial and Systems Engineering Graduate Program (PPGEPS) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil Mechanical Engineering Graduate Program (PPGEM) Pontifical Catholic University of Parana (PUCPR) Curitiba Brazil

ISBN: (纸本)9781728190495

One of the applications of data-driven methods in the industry is the creation of real-time, embedded measurements, whether to monitor or replace sensor signals. As the number of embedded systems in products raises over time, the energy efficiency of such systems must be considered in the design. The time (processor) efficiency of the embedded software is directly related to the energy efficiency of the embedded system. Therefore, when considering some embedded software solutions, such as data-driven methods, time efficiency must be taken into account to improve energy efficiency. In this work, the energy efficiency of three data-driven methods: the Sparse Identification of Nonlinear Dynamics (SINDy), the Extreme Learning Machine (ELM), and the Random-Vector Functional Link (RVFL) network were assessed by using the creation of a real-time in-cylinder pressure sensor for diesel engines as a task. The three methods were kept with equivalent performances, whereas their relative execution time was tested and classified by their statistical rankings. Additionally, the space (memory) efficiency of the methods was assessed. The contribution of this work is to provide a guide to choose the best data-driven method to be used in an embedded system in terms of efficiency.

关键词： Support vector machines Ranking (statistics) Radio frequency Embedded systems Neurons Energy efficiency Real-time systems

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Reliable operation of Cr2O3:Mg/β-Ga2O3 p-n heterojunction diodes at 600◦C

arXiv

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arXiv 2024年

作者： Callahan, William A. Egbo, Kingsley Lee, Cheng-Wei Ginley, David O'Hayre, Ryan Zakutayev, Andriy Materials Science Center National Renewable Energy Laboratory GoldenCO80401 United States Advanced Energy Systems Graduate Program Colorado School of Mines GoldenCO80401 United States Department of Metallurgical and Materials Engineering Colorado School of Mines GoldenCO80401 United States

β-Ga2O3-based semiconductor heterojunctions have recently demonstrated improved performance at high voltages and elevated temperatures and are thus promising for applications in power electronic devices and harsh-environment sensors. However, the long-term reliability of these ultra-wide band gap (UWBG) semiconductor devices remains barely addressed and may be strongly influenced by chemical reactions at the p-n heterojunction interface. Here, we experimentally demonstrate operation and evaluate the reliability of Cr2O3:Mg/β-Ga2O3 p-n heterojunction diodes at during extended operation at 600◦C, as well as after 30 repeated cycles between 25-550◦C. The calculated pO3-temperature phase stability diagram of the Ga-Cr-O material system predicts that Ga2O3 and Cr2O3 should remain thermodynamically stable in contact with each other over a wide range of oxygen pressures and operating temperatures. The fabricated Cr2O3:Mg/β-Ga2O3 p-n heterojunction diodes show room-temperature on/off ratios >104 at ±5V and a breakdown voltage (VBr) of -390V. The leakage current increases with increasing temperature up to 600◦C, which is attributed to Poole-Frenkel emission with a trap barrier height of 0.19 eV. Over the course of a 140-hour thermal soak at 600◦C, both the device turn-on voltage and on-state resistance increase from 1.08V and 5.34 mΩ-cm2 to 1.59V and 7.1 mΩ-cm2 respectively. This increase is attributed to the accumulation of Mg and MgO at the Cr2O3/Ga2O3 interface as observed from TOF-SIMS analysis. These findings inform future design strategies of UWBG semiconductor devices for harsh environment operation and underscore the need for further reliability assessments for β-Ga2O3 based devices. © 2024, CC BY.

关键词： Gallium compounds

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Factors that Influence E-Satisfaction and Their Impact on Online Purchase Intention of Telemedicine Applications

Factors that Influence E-Satisfaction and Their Impact on On...

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International Conference on Computing, engineering, and Design (ICCED)

作者： Anderes Gui Idris Gautama So Dea Novantia Elfindah Princes Nesti Fronika Sianipar Hasnah Haron Information System Program School of Information Systems Bina Nusantara University Jakarta Indonesia Management Department Binus Business School Bina Nusantara University Jakarta Indonesia Information Systems Management Department Binus Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Food Technology Department Faculty of Engineering Bina Nusantara University Jakarta Indonesia Faculty of Economics and Muamalat Universiti Sains Islam Malaysia Nilai Malaysia

This study embarked on a rigorous examination of the factors driving user satisfaction and usage behavior in the context of telehealth applications. Utilizing a well- structured Google Form survey, distributed through an array of social media platforms, including WhatsApp, Discord, Instagram, and Line, the research gathered 251 responses. The purposive sampling technique was employed to ensure that the data captured the experiences of individuals who had actively engaged with telehealth services. One hypothesis, relating to the influence of Online Reviews, was found to be unsupported. This surprising result suggests that, contrary to expectations, the opinions and reviews shared online do not significantly affect users’ satisfaction or their behavioral decisions in the context of telehealth applications. This finding highlights the need for a more nuanced understanding of the factors influencing user preferences and choices in this rapidly evolving sector. Conversely, other hypotheses examining factors such as Social Influence, Facilitating Conditions, Perceived Reliability, Price Value, and Purchase Intention were substantiated. The positive influence of these factors on customer usage behavior underscores their significance in shaping user experiences and satisfaction within the telehealth ecosystem. Furthermore, the study posits that facilitating conditions should be closely aligned with technological advancements, as this alignment is conducive to the development of enhanced application features. This insight suggests that telehealth providers should continuously innovate and integrate advanced technologies to ensure that the facilitating conditions meet the ever-evolving needs and expectations of users.

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Leverage from Blockchain in Commodity Exchange: Asset-Backed Token with Ethereum Blockchain Network and Smart Contract 4th

Leverage from Blockchain in Commodity Exchange: Asset-Backed...

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4th International Conference on Smart Trends for Computing and Communications, SmartCom 2020

作者： Richard Heryadi, Yaya Lukas Trisetyarso, Agung Information Systems Department School of Information Systems Bina Nusantara University Jakarta11840 Indonesia Computer Science Department BINUS Graduate Program Doctor of Computer Science Bina Nusantara Univesity Jakarta11840 Indonesia Faculty of Engineering Universitas Katolik Indonesia Atma Jaya Jakarta12930 Indonesia

ISBN: (纸本)9789811552236

Ethereum is one of the most popular blockchain platforms with a high number of adoption in the blockchain world today. Ethereum token (ERC-20) can tokenize any real-world object while it is also possible to exchange the token across the network participants. This utility from the token drives many blockchain enthusiasts to create decentralized applications. ERC-20 token could be used to collect project funds, decision voting, or even can be used to provide investment platforms for people that want to hedge the volatility of the currency with buying an asset that is back to back with the crypto-token. This research shows the main characteristics of asset-backed token and its implementation on a complete end-to-end "digitalization assets system" (assets buy and assets redemption). The result shows that asset-backed token needs support from government and other legalizing parties to verify the legitimacy of the asset that backing the token itself. © 2021, The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Blockchain

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