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Consumer Technology (ICCT-Pacific), International Conference on

作者： Ni Luh Wiwik Sri Rahayu Ginantra Christina Purnama Yati I Gusti Ayu Agung Diatri Indradewi I Komang Agus Yudiawan Technology and Informatics Informatics Engineering Institut Bisnis dan Teknologi Indonesia (INSTIKI) Denpasar Indonesia Department of Informatics Engineering Information Systems Study Program Faculty of Engineering and Vocational Studies Universitas Pendidikan Ganesha (UNDIKSHA) Denpasar Indonesia

ISBN: (数字)9798331504120

ISBN: (纸本)9798331504137

Ornamental fish are a type of fish that live in freshwater or seawater habitats and are typically maintained for aesthetic purposes, often in ornamental ponds or as household pets. The diversity of colors, shapes, and patterns observed in ornamental fish presents a challenge in their classification. Therefore, a method capable of accurately recognizing the visual characteristics of these fish is required. The objective of this study is to evaluate the performance of two Convolutional Neural Network (CNN) architectures, specifically VGG-16 and U-Net, using five distinct types of ornamental fish, namely Angel Fish, Betta Fish, Clown Fish, Gold Fish, and Guppy Fish. The dataset comprises 3.240 images that have been processed using TensorFlow and Keras on Google Collaboratory. The results demonstrated that U-Net demonstrated superior performance in segmentation, with an Average Intersection over Union (IoU) of 58.91 % and an Average Dice Coefficient of 73.72%. In contrast, VGG-16 exhibited signs of overfitting, as evidenced by lower evaluation metrics. To enhance the efficacy of the transfer learning model, further optimization is recommended.

关键词： Measurement Image segmentation Visualization Shape Transfer learning Fish Internet Convolutional neural networks Optimization Overfitting

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The Influence of Acetylene Black Microparticles as a Fuel Additive in Pure Palm Oil and its Performance Characteristic on Diesel Engine

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SSRN 2024年

作者： Prahmana, Rico Aditia Darmanto, Prihadi Setyo Juangsa, Firman Bagja Reksowardojo, Iman Kartolaksono Hendrarsakti, Jooned Serunting, Muhamad Allan Yuwazama, Zido Ahmad, Azaria Haykal Prakoso, Tirto Doctoral Program of Mechanical Engineering Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung40132 Indonesia Thermal Science and Engineering Research Group Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Program of Mechanical Engineering Department of Production and Industrial Technology Institut Teknologi Sumatera South Lampung 3536 Indonesia Departement of Chemical Engineering Faculty of Industrial Technology Institut Teknologi Bandung Bandung40132 Indonesia Program of Mechanical Engineering Faculty of Industrial Technology Universitas Pertamina Jakarta12220 Indonesia Program of Chemistry Faculty of Science Institut Teknologi Sumatera Lampung Selatan Indonesia

Fuel additives are recognized for their potential to make diesel engines cleaner and more efficient. However, the use of Pure Palm Oil (PPaO) as a fuel faces challenges due to its inherent combustion inefficiencies. This study explores how Acetylene Black (AB), as an additive, affects the combustion performance and spray characteristics of a diesel engine. Observations of spray phenomena were conducted using a High-Speed Camera Phantom C110. The addition of AB to PPaO resulted in an increase in engine power and torque by 11.43% at a 60% load, averaging a 2.97% improvement over diesel fuel (DF). PPaO demonstrated the most significant improvement in Specific Fuel Consumption (SFC) by 17.2% at a 40% load, averaging an 8.2% increase. For PPaO with AB (PPaOAB), the greatest enhancement in SFC occurred at a 10% load, showing a 9.2% improvement over DF, with an average increase of 2.1%. The study also found that thermal efficiency was optimally enhanced with PPaOAB at a 20% load, achieving a remarkable 17.7% improvement compared to DF. Notably, the inclusion of AB in PPaO significantly improved spray angle and penetration compared to PPaO alone. These findings suggest that AB could be a promising additive for PPaO, sparking further research interest in the application of AB in other fuels. © 2024, The Authors. All rights reserved.

关键词： Palm oil

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Advancing electrochemical impedance analysis through innovations in the distribution of relaxation times method

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Joule 2024年第7期8卷 1958-1981页

作者： Maradesa, Adeleke Py, Baptiste Huang, Jake Lu, Yang Iurilli, Pietro Mrozinski, Aleksander Law, Ho Mei Wang, Yuhao Wang, Zilong Li, Jingwei Xu, Shengjun Meyer, Quentin Liu, Jiapeng Brivio, Claudio Gavrilyuk, Alexander Kobayashi, Kiyoshi Bertei, Antonio Williams, Nicholas J. Zhao, Chuan Danzer, Michael Zic, Mark Wu, Phillip Yrjänä, Ville Pereverzyev, Sergei Chen, Yuhui Weber, André Kalinin, Sergei V. Schmidt, Jan Philipp Tsur, Yoed Boukamp, Bernard A. Zhang, Qiang Gaberšček, Miran O'Hayre, Ryan Ciucci, Francesco Department of Mechanical and Aerospace Engineering The Hong Kong University of Science and Technology Hong Kong Metallurgical and Materials Engineering Colorado School of Mines Golden80401 United States Beijing Key Laboratory of Green Chemical Reaction Engineering and Technology Department of Chemical Engineering Tsinghua University Beijing China Green Energy Storage Trento38123 Italy Department of Manufacturing and Production Engineering Faculty of Mechanical Engineering and Ship Technology Institute of Machine and Materials Technology Gdańsk University of Technology Gdańsk Poland Electrode Design for Electrochemical Energy Systems University of Bayreuth Bayreuth Germany School of Chemistry University of New South Wales Sydney Australia School of Advanced Energy Sun Yat-Sen University Shenzhen China Sustainable Energy Center CSEM Neuchâtel2002 Switzerland Interdisciplinary Faculty of Science and Engineering Shimane University Matsue Japan Centre for Electronic and Optical Materials National Institute for Materials Science Tsukuba Japan Department of Civil and Industrial Engineering University of Pisa Pisa Italy Department of Materials Imperial College London Exhibition Road LondonSW7 2AZ United Kingdom Department of Chemical Engineering Massachusetts Institute of Technology Cambridge02139 United States Electrical Energy Systems University of Bayreuth Bayreuth Germany Ruder Boskovic Institute Zagreb Croatia Department of Materials and Minerals Resources Engineering National Taipei University Taipei Taiwan Finland Johann Radon Institute for Computational and Applied Mathematics Linz Austria School of Science and Engineering Nanjing Tech. University Nanjing China Karlsruhe Germany Department of Materials Science and Engineering University of Tennessee KnoxvilleTN37996 United States Physical Science Division Pacific Northwest National Laboratory RichlandWA99354 United States Systems Engineering for Electrical Energy Storage University of B

Electrochemical impedance spectroscopy (EIS) is widely used in electrochemistry, energy sciences, biology, and beyond. Analyzing EIS data is crucial, but it often poses challenges because of the numerous possible equivalent circuit models, the need for accurate analytical models, the difficulties of nonlinear regression, and the necessity of managing large datasets within a unified framework. To overcome these challenges, non-parametric models, such as the distribution of relaxation times (DRT, also known as the distribution function of relaxation times, DFRT), have emerged as promising tools for EIS analysis. For example, the DRT can be used to generate equivalent circuit models, initialize regression parameters, provide a time-domain representation of EIS spectra, and identify electrochemical processes. However, mastering the DRT method poses challenges as it requires mathematical and programming proficiency, which may extend beyond experimentalists’ usual expertise. Post-inversion analysis of DRT data can be difficult, especially in accurately identifying electrochemical processes, leading to results that may not always meet expectations. This article examines non-parametric EIS analysis methods, outlining their strengths and limitations from theoretical, computational, and end-user perspectives, and provides guidelines for their future development. Moreover, insights from survey data emphasize the need to develop a large impedance database, akin to an impedance genome. In turn, software development should target one-click, fully automated DRT analysis for multidimensional EIS spectra interpretation, software validation, and reliability. Particularly, creating a collaborative ecosystem hinged on free software could promote innovation and catalyze the adoption of the DRT method throughout all fields that use impedance data. © 2024 Elsevier Inc.

关键词： Electrochemical impedance spectroscopy

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Image Processing Implementation to Classify Coffee Fruit Ripeness Using K-Nearest Neighbor (KNN) Algorithm 8

Image Processing Implementation to Classify Coffee Fruit Rip...

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8th International Conference on Information Management and Technology, ICIMTech 2023

作者： Hussaini Dermawan, M. Farhan Witarsyah, Deden Syamsuar, Dedy Fakhrurroja, Hanif Luthfi, Ahmad Herdiansyah, Muhammad Izman Telkom University Faculty of Industrial Engineering Bandung Indonesia School of Information Systems Bina Nusantara University Information Systems Department Jakarta11480 Indonesia Islamic University of Indonesia Faculty of Industrial Technology Department of Informatics Jogjakarta Indonesia Universitas Bina Darma Informatics Study Program Faculty of Science and Technology Palembang Indonesia

ISBN: (纸本)9798350326093

Coffee is one of the plantation crops that has long been a cultivated plant in Indonesia. The classification of coffee fruit maturity manually still has several weaknesses and requires a long process, has low accuracy and is inconsistent, this is because the determination is made subjectively by coffee farmers. As for the classification of coffee fruit maturity levels automatically, it can be faster with objective determination, therefore the use of image processing is relatively easier, faster, and based on a quantified descriptive assessment to determine coffee maturity. Image Processing is a method used to process or manipulate images in 2-dimensional form. In the classification process, there are many methods used to obtain classification of objects based on training data. One of the algorithms used for the classification process is K-Nearest Neighbor (KNN). KNN is a classification technique for objects based on training data that is the closest or has similar characteristics to the object. KNN includes supervised learning algorithms, where the results of the new query instance are classified based on the majority of the categories in K-Nearest Neighbors (K-NN). The finding indicated that class classification of ripe and unripe were 88,24 % and 100% respectively with 93,33% accuracy level. © 2023 IEEE.

关键词： Classification (of information)

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Machine Learning Stroke Prediction in Smart Healthcare:Integrating Fuzzy K-Nearest Neighbor and Artificial Neural Networks with Feature Selection Techniques

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Computers, Materials & Continua 2025年第3期82卷 5115-5134页

作者： Abdul Ahad Ira Puspitasari Jiangbin Zheng Shamsher Ullah Farhan Ullah Sheikh Tahir Bakhsh Ivan Miguel Pires Department Information System Study Program Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Software Northwestern Polytechnical UniversityXi’an710072China Research Center for Quantum Engineering Design Faculty of Science and TechnologyUniversitas AirlanggaSurabaya60286Indonesia School of Computer Science and Software Engineering Shenzhen UniversityShenzhen518061China Cybersecurity Center Prince Mohammad Bin Fahd University617Al JawharahKhobarDhahran34754Saudi Arabia Cardiff School of Technologies Cardiff Metropolitan UniversityWestern AvenueCardiffCF52YBUK Instituto de Telecomunicacoes Escola Superior de Tecnologia e Gestao de AguedaUniversidade de Aveiroágueda3750-127Portugal

This research explores the use of Fuzzy K-Nearest Neighbor(F-KNN)and Artificial Neural Networks(ANN)for predicting heart stroke incidents,focusing on the impact of feature selection methods,specifically Chi-Square and Best First Search(BFS).The study demonstrates that BFS significantly enhances the performance of both *** BFS preprocessing,the ANN model achieved an impressive accuracy of 97.5%,precision and recall of 97.5%,and an Receiver Operating Characteristics(ROC)area of 97.9%,outperforming the Chi-Square-based ANN,which recorded an accuracy of 91.4%.Similarly,the F-KNN model with BFS achieved an accuracy of 96.3%,precision and recall of 96.3%,and a Receiver Operating Characteristics(ROC)area of 96.2%,surpassing the performance of the Chi-Square F-KNN model,which showed an accuracy of 95%.These results highlight that BFS improves the ability to select the most relevant features,contributing to more reliable and accurate stroke *** findings underscore the importance of using advanced feature selection methods like BFS to enhance the performance of machine learning models in healthcare applications,leading to better stroke risk management and improved patient outcomes.

关键词： Fuzzy K-nearest neighbor artificial neural network accuracy precision recall F-measure Chi-Square best search first heart stroke

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The Design of VBee Diary Writing Application 9

The Design of VBee Diary Writing Application

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9th International Conference on Education and Technology, ICET 2023

作者： Sidupa, Christiana Nugroho, Hermawan Perdani, Yella Dezas Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Jakarta Indonesia Faculty of Information Technology Satya Wacana Christian University Informatics Engineering Study Program Salatiga Indonesia Faculty of Humanities Bina Nusantara University Digital Language Learning Center Interior Design Department Bandung Indonesia

ISBN: (纸本)9798350358292

The development of critical thinking, creativity, and communication abilities is facilitated by the acquisition of writing skills, which are significant for students. Nevertheless, a considerable number of students presently encounter difficulties in locating the impetus and enthusiasm required for engagement in writing endeavors. The focus of the present paper is application design. The VBee application is a web-based application that facilitates the expression of user creativity and fosters a deeper appreciation for the art of writing. The application boasts a highly intuitive interface that effortlessly enables users to document their thoughts and experiences. It offers a plethora of features that not only facilitate writing but also foster self-expression, including customizable emoticons and the option to provide feedback. By designing the application, it could help support vocational school students in improving the quality of skill-focused education, particularly their English creative writing skill in enjoyment. Besides, the teachers are assisted to guide their students with technologically advanced and entertaining learning tools. © 2023 IEEE.

关键词： Students

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Occurrence of cadmium in groundwater in China: a review

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Arabian Journal of Geosciences 2022年第17期15卷 1-13页

作者： Hoareau, Carol Emilly Hadibarata, Tony Yılmaz, Murat Environmental Engineering Program Faculty of Engineering and Science Curtin University Malaysia Miri Malaysia Department of Chemical Engineering Faculty of Engineering Osmaniye Korkut Ata University Osmaniye Türkiye

China has one of the world’s fastest-growing economies due to its increase in various industrial activities. A side effect of economic growth is severe environmental problems such as heavy metal contamination of soil and groundwater. Anthropogenic activities are the main sources of cadmium which is highly mobile and toxic with the potential to bioaccumulate in the ecosystem. It can contaminate ground and river water consequently negatively impacting agriculture and water sources. Anthropogenic source of Cd concentrations in China is 0.002 mg/L in drinking water, 0.102 mg/kg in soil, and 0.23–0.96 mg/kg in paddy soil. Geological trends and health implications of cadmium contamination in Human, southern China were analyzed. Source, transportation, and various conventional remediation processes exist today and can be categorized as biological, physical, and chemical. Using nanoparticle technology, it has been found that adsorption capacities can be 3 to 4 times higher compared to using powdered activated carbon. From the experiment carried out, a maximum adsorption capacity of 10.86 mg/g for cadmium was obtained. Cadmium intake in south China populations occurred at an alarming rate and most children were at greater risk of being affected. Therefore, cadmium contamination should be taken seriously by the responsible authorities.

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Analysis of marine debris at Alue Naga and Ulee Lheue beaches in Banda Aceh City using the transect method

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Materials Today: Proceedings 2022年 63卷 S339-S345页

作者： Windari, Wulan Saiful, Saiful Gani, Asri Mahidin Master of Environment Management Postgraduate Program Syiah Kuala University Banda Aceh Indonesia Chemistry Department Faculty of Mathematics and Natural Science Syiah Kuala University Banda Aceh Indonesia Chemical Engineering Faculty of Engineering Syiah Kuala University Banda Aceh Indonesia Research Center for Environmental and Natural Resources Universitas Syiah Kuala Darussalam Banda Aceh 23111 Indonesia

Alue Naga Beach and Ulee Lheue Beach are beaches located in Banda Aceh City, Aceh Province, these two beaches have a fairly large role in the fields of fisheries, transportation, and tourism. During the last few years, the population growth rate of Banda Aceh City has increased by 2% per year, this causes the volume of waste generated to be even greater, unfortunately, the municipal waste management office cannot manage it fully. Most of the untreated waste enters water bodies and has the potential to pollute the marine and coastal environment. So it is necessary to do research to provide an overview of the level of marine debris pollution on the two beaches. This study uses the transect method, the waste obtained is grouped according to size and type. The results showed that marine debris on Ulee Lheue beach was found to be more numerous and varied than marine debris on Alue Naga beach. Overall, macro waste with a size range of 2.5−1 m was the most commonly found and plastic was the waste with the highest yield with a density value of 65.8 g/m2, an abundance of 6.56 items/m2, and a percentage of 75%. © 2022

关键词： Beaches

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Systematic designs of single metal compounds synthesized using ammonia fluoride-based complex as structure directing agents for energy storage

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Journal of Colloid and Interface Science 2023年第PartA期652卷 294-304页

作者： Kuo, Tsung-Rong Zher Yu, You Wu, Chung-Hsien Lee, Pin-Yan Kongvarhodom, Chutima Chen, Hung-Ming Husain, Sadang Yougbaré, Sibidou Lin, Lu-Yin International PhD Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Graduate Institute of Nanomedicine and Medical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei Taiwan Department of Chemical Engineering King Mongkut's University of Technology Thonburi 126 Pracha-u-thit Toong-kru Bangkok10140 Thailand Gingen technology Co. LTD. Rm. 7 10F. No.189 Sec. 2 Keelung Rd. Xinyi Dist. Taipei11054 Taiwan Department of Physics Faculty of Mathematics and Natural Science Lambung Mangkurat University Banjarmasin70124 Indonesia /Nanoro 03 B.P 7192 Ouagadougou 03 Burkina Faso

Tailoring morphology and composition of metal organic frameworks (MOF) can improve energy storage by establishing high surface area, large porosity and multiple redox states. Structure directing agents (SDA) is functional of designing surface properties of electroactive materials. Ammonium fluoride has functional abilities for designing MOF derivatives with excellent energy storage abilities. Systematic design of MOF derivatives using ammonia fluoride-based complex as SDA can essentially create efficient electroactive materials. Metal species can also play significant roles on redox reactions, which are the main energy storage mechanism for battery-type electrodes. In this work, 2-methylimidazole, two novel SDAs of NH4BF4 and NH4HF2, and six metal species of Al, Mn, Co, Ni, Cu and Zn are coupled to synthesize MOF derivatives for energy storage. Metal species-dependent compositions including hydroxides, oxides, and hydroxide nitrates are observed. The nickel-based derivative (Ni-HBF) shows the highest specific capacitance (CF) of 698.0F/g at 20 mV/s, due to multiple redox states and advanced flower-like surface properties. The diffusion and capacitive-control contributions of MOF derivatives are also analyzed. The battery supercapacitor hybrid with Ni-HBF electrode shows a maximum energy density of 27.9 Wh/kg at 325 W/kg. The CF retention of 170.9% and Coulombic efficiency of 93.2% are achieved after 10,000 cycles. © 2023 Elsevier Inc.

关键词： Supercapacitor

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Review of mayflies (Insecta Ephemeroptera) as a bioindicator of heavy metals and microplastics in freshwater

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Science of the Total Environment 2025年 958卷 178057页

作者： Benhadji, Nadhira Kurniawan, Setyo Budi Imron, Muhammad Fauzul Institute of Technology and Life Sciences—National Research Institute Falenty Hrabska Avenue 3 Raszyn05-090 Poland Department of Chemical and Process Engineering Faculty of Engineering and Built Environment Universiti Kebangsaan Malaysia Selangor UKM Bangi43600 Malaysia Study Program of Environmental Engineering Department of Biology Faculty of Science and Technology Universitas Airlangga Campus C UNAIR Jalan Mulyorejo Surabaya60115 Indonesia Department of Water Management Faculty of Civil Engineering and Geosciences Delft University of Technology Stevinweg 1 CN Delft2628 Netherlands

Heavy metal and microplastic pollutions are prevalent in freshwater ecosystems, with many freshwater bodies being contaminated by one or both of these pollutants. Recent studies reported extreme detections of Cd, Pb and Zn, high concentrations of Cr, Pb and Cu and microplastics acting as vectors of pollutants, including heavy metals. Mayflies can serve as bioindicators of heavy metal contamination in freshwater ecosystems because changes in their community structure, physiology, and behaviour can reflect and help predict the concentrations of metals in these environments. This review discusses the ecological alterations induced by tissue metal concentration in mayflies and other macroinvertebrates. As sensitive taxa to heavy metal contamination, mayflies can reflect the impacts of this pollution through their ethology and relationship to the substrate, highlighting issues such as eutrophication, alterations in community structure, inhibitory effects and sediment toxicity. Mayflies are also highly affected by microplastic exposure, which leads to ingestion, bioaccumulation, biomagnification, habitat and community alteration, behavioural changes, physiology alteration and toxicity. Mayflies bioindication metrics for assessing the impact of heavy metals and microplastics include the examination of community alteration, functional feeding behaviour, molecular structure, dietary and toxicity impacts, bioaccumulation and biomagnification and biomarkers. Current challenges for the utilization of mayflies as bioindicators include temporal variations in sensitivity, lack of universally recognised protocols and need for standardised protocols for microplastic analysis. Additionally, the applicability of mayflies as bioindicators may vary across different ecosystems, emphasising the need for selecting suitable indicators that align with the unique characteristics of the ecosystem. © 2024 The Authors

关键词： Macroinvertebrates

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