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SSRN 2024年

作者： Sae-Long, Worathep Chompoorat, Thanakorn Limkatanyu, Suchart Damrongwiriyanupap, Nattapong Sukontasukkul, Piti Chub-Uppakarn, Tanan Thepumong, Thanakit Civil Engineering Program School of Engineering University of Phayao Phayao56000 Thailand Department of Civil and Environmental Engineering Faculty of Engineering Prince of Songkla University Songkhla90110 Thailand Construction and Building Materials Research Center Department of Civil Engineering King Mongkut’s University of Technology North Bangkok Bangkok10800 Thailand

Recycled concrete aggregate (RCA) is widely used as an alternative recycled material in engineering, while para-wood ash (PWA) is a natural agricultural waste product. To advance sustainable construction, it is crucial to thoroughly examine their impact on concrete’s mechanical properties to ensure safety in engineering applications. This paper conducts a series of experiments on recycled aggregate concrete (RAC) with PWA to investigate these replacement effects. RCA replaces natural coarse aggregate (NCA) at 0%, 50%, and 100%, while PWA substitutes cement at 0%, 10%, and 20%. The experiments include compression tests on mortar as well as compressive, tensile, and flexural tests on RAC, along with microstructure investigations. The results indicate a decrease in strength with higher proportions of RCA and PWA. Microstructure investigations were conducted via scanning electron microscopy with energy-dispersive X-ray analysis (SEM/EDX). SEM provides micro images of the testing specimens, while EDX offers insight into their chemical compositions. The EDX results reveal a direct correlation between the Ca/Si ratio and the strengths of mortar and RAC. Correlation studies between compressive strength-replacement parameters, tensile-compressive strength, and flexural-compressive strength demonstrate that the proposed equations accurately predict the experimental data with R2 values of 0.60 (for mortar), and 0.94, 0.95, and 0.71 (for RAC), respectively. Two numerical simulations validate the proposed model and showcase potential engineering applications. Finally, a 10% replacement of PWA for cement can reduce the embodied energy value (EEV) by approximately 9.46% for mortar mixed with PWA and around 10% for RAC mixed with RCA and PWA. © 2024, The Authors. All rights reserved.

关键词： Mortar

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The Impact of Water Flow Variability on Brackish Water Distribution in Prokljan Lake, Croatia 9th

The Impact of Water Flow Variability on Brackish Water Distr...

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9th International Conference on Water Resource and Environment, WRE 2023

作者： Galešić Divić, Morena Divić, Vladimir Kvesić Ivanković, Marija Rumenović, Ružica Andričević, Roko Faculty of Civil Engineering Architecture and Geodesy University of Split Matice Hrvatske 15 Split Croatia Center of Excellence for Science and Technology-Integration of Mediterranean Region University of Split Ruđera Boškovića 31 Split Croatia Doctoral Study of Biophysics Faculty of Science University of Split Ruđera Boškovića 33 Split Croatia

ISBN: (纸本)9789819709472

Investigating the complex dynamics of the Prokljan Lake ecosystem in Croatia, this study examines the influence of the variability of water flow on the distribution of brackish water. The microtidal Mediterranean environment, characterized by limited vertical mixing, forms a distinct bidirectional two-layer flow system within the river channels. The study focuses on the upper section of the Krka River Estuary that includes Prokljan Lake, an essential habitat with diverse ecosystem services. Vertical profiles of salinity data were collected via multiple field campaigns, reaffirming the highly stratified nature of the estuary. The novel Brackish Water Fraction (BWF) index was introduced, offering a rapid assessment tool to quantify salinity distribution. Correlations between the BWF and river flow have been established, shedding light on the intricate interplay between flow dynamics and estuarine behaviour. This index holds promise for similar estuarine systems and offers insights into sustainable management practices. The study enriches our understanding of the complex interactions that shape coastal and estuarine ecosystems. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lakes

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Effect of High-Flow Nasal Cannula on Capnogram Waveform for studying Non-Invasive Human Ventilation

Effect of High-Flow Nasal Cannula on Capnogram Waveform for ...

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Biomedical engineering Conference (NBEC), IEEE National

作者： Tjokorda Gde Tirta Nindhia Nursyasa Aqila Mohammed Julia Jais Jamaludin Pagupathi Devandran Nabiel Rafa Angel Bhaswara Thalitakum Hutajulu M.B. Malarvili Study Program of Mechanical Engineering Engineering Faculty Udayana University Jimbaran Bali Indonesia School of Biomedical and Health Science Engineering Universiti Teknologi Malaysia Johor Malaysia

This study is conducted to compare three different cannulas; all purpose nasal cannula with 2 prongs, nasal pressure cannula with 2 prongs and single port nasal cannula which are commonly used for capnography device. These cannulas or sometimes called as nasal prong is connected to the device via nose of subjects studied. This procedure is a part of respiratory study to monitor lungs condition and breathing pattern. This study involves 47 subject where the exhaled breath was recorded to make comparison and choose the most suitable and effective for capnography waveform analysis. Utilizing Statistical Package for the Social Sciences (SPSS) to find the normality of all the nasal cannula data based on capnogram waveform. The result from the analysis shows that the frequency distribution for type 1 nasal cannula which is also known as all-purpose nasal cannula had the feature values closer to the standard value. Our study proofs that all purpose nasal cannula sampling is the most suitable to capture exhaled breath for monitoring respiratory conditions.

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Classification Of Ornamental Fish Types Using CNN Method With VGG-16 And U-NET Architecture

Classification Of Ornamental Fish Types Using CNN Method Wit...

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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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Hydrodynamic Properties of a Moored Floating Breakwater using CFD Approach 8

Hydrodynamic Properties of a Moored Floating Breakwater usin...

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8th International Seminar on Ocean and Coastal engineering, Environmental and Natural Disaster Management, ISOCEEN 2020

作者： Abdullah, S.F. Fitriadhy, A. Mohd, M.H. Rahman, M.A.A. Suntoyo Kurniawan, A. Pratikto, W. Program of Maritime Technology Faculty Ocean Engineering Technology and Informatics Universiti Malaysia Terengganu Malaysia Surabaya Indonesia Program of Ocean Engineering Faculty of Civil and Environmental Engineering Institut Teknologi Bandung Indonesia

In presence of complex-hydrodynamic interaction between water wave and moving structure, a reliable method that can analyse nonlinear phenomena is necessarily required. This paper presents numerical investigation of a moored floating breakwater using computational fluid dynamic (CFD) approach. The mathematical model is based on the extended Reynolds Average Navier-Stokes (RANS) solver for solid-porous obstacle. A high amplitude wave with several wave periods were deliberately considered in the simulation to allow nonlinear wave effects on the floating structure such as wave breaking, overtopping, including viscous friction. Here, the two fluid calculation method for interface boundary between water and air is proposed to capture the complex free surface changes. In addition, the fractional average volume obstacle representation (FAVOR) using partial cell treatment method is employed to simulate the motion of breakwater boundary on the free surface. Approximations and validations on the hydrodynamic properties of the structure have been carried out which include wave transmission coefficient, sway, heave, pitch, and mooring forces. The results show that the CFD model can fairly simulate well on hydrodynamics of the floating breakwater. The discrepancies between numerical and experimental data can be partly attributed to the nonlinearity in the incident wave definition. © Published under licence by IOP Publishing Ltd.

关键词： Computational fluid dynamics

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The Application of Artificial Neural Network Model to Predicting the Acid Mine Drainage from Long-Term Lab Scale Kinetic Test

arXiv

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arXiv 2024年

作者： Abfertiawan, Muhammad Sonny Kautsar, Muchammad Daniyal Hasan, Faiz Palinggi, Yoseph Pranoto, Kris Water and Wastewater Research Group Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Department of Electrical and Information Engineering Universitas Gadjah Mada Indonesia Environmental Engineering Master Program Faculty of Civil and Environmental Engineering Bandung Institute of Technology Indonesia Environmental Department PT Kaltim Prima Coal Indonesia

Acid mine drainage (AMD) is one of the common environmental problems in the coal mining industry that was formed by the oxidation of sulfide minerals in the overburden or waste rock. The prediction of acid generation through AMD is important to do in overburden management and planning the post-mining land use. One of the methods used to predict AMD is a lab-scale kinetic test to determine the rate of acid formation over time using representative samples in the field. However, this test requires a long-time procedure and large amount of chemical reagents lead to inefficient cost. On the other hand, there is potential for machine learning to learn the pattern behind the lab-scale kinetic test data. This study describes an approach to use artificial neural network (ANN) modeling to predict the result from lab-scale kinetic tests. Various ANN model is used based on 83 weeks experiments of lab-scale kinetic tests with 100% potential acid-forming rock. The model approaches the monitoring of pH, ORP, conductivity, TDS, sulfate, and heavy metals (Fe and Mn). The overall Nash-Sutcliffe Efficiency (NSE) obtained in this study was 0.99 on training and validation data, indicating a strong correlation and accurate prediction compared to the actual lab-scale kinetic tests data. This show the ANN ability to learn patterns, trends, and seasonality from past data for accurate forecasting, thereby highlighting its significant contribution to solving AMD problems. This research is also expected to establish the foundation for a new approach to predict AMD, with time efficient, accurate, and cost-effectiveness in future applications. © 2024, CC BY-NC-SA.

关键词： Coal industry

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Projection of climate change effects on flood inundation in the Gin River basin, Sri Lanka 9

Projection of climate change effects on flood inundation in ...

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9th International Conference on Flood Management, ICFM 2023

作者： Jayapadma, Jayapadma Mudalige Miyuru Uthpala Souma, Kazuyoshi Ishidaira, Hiroshi Magome, Jun Wickramaarachchi, Thushara Navodani Special Educational Program on River Basin Environmental Science Integrated Graduate School of Medicine Engineering and Agricultural Sciences University of Yamanashi 4-3-11 Takeda Yamanashi Kofu400-8511 Japan Interdisciplinary Centre for River Basin Environment University of Yamanashi 4-3-11 Takeda Yamanashi Kofu400-8511 Japan Department of Civil and Environmental Engineering Faculty of Engineering University of Ruhuna Galle Hapugala Sri Lanka

Human-induced climate change has altered the frequency and severity of heavy precipitation, droughts, and floods worldwide. Sri Lanka, a developing country in the Indian Ocean, has suffered frequent floods, affecting over 64 % of the population in the past decade. The Gin River, the primary drinking water source of the densely populated Galle district with over 1 million residents, faces recurrent flood disasters. Therefore, this study employed a multi-model ensemble to simultaneously simulate the impact of climate change on both river flow and inundation extent in the frequently flooded Gin River basin located in humid tropical monsoon region. Bias-corrected climate projections of an ensemble of five General Circulation Models (GCMs) from the Coupled Model Inter-comparison Project Phase 5 (CMIP5) under Representative Concentration Pathway (RCP) 4.5 emission scenario were used to project future river flow and flood inundation in the Gin River basin, Sri Lanka. The validated Rainfall-Runoff-Inundation (RRI) model projected a 5 % increase in high flows (flows exceeding a 5 % probability of exceedance ( Copyright © 2024 Jayapadma Mudalige Miyuru Uthpala Jayapadma et al.

关键词： Floods

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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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