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9th International Conference on Business and Industrial Research, ICBIR 2024

作者： Totok Suryawan, I Gede Putra, I Wayan Murmayasa Adi Informatics Engineering Study Program Faculty of Technology and Informatics Denpasar Indonesia

ISBN: (纸本)9798350383010

Cataracts are the main factor causing blindness in Indonesia. Traditional diagnostic methods involving clinical examination by an ophthalmologist using a slit-lamp and visual tests have many challenges such as limited resources, time, and medical expertise may not be available in all locations, especially in less developed areas. Utilizing medical image technology is a wise choice because it allows early detection and monitoring of the development of this cataract disease Technology is needed to identify medical images that have valuable information so that early detection or monitoring of cataract development can be carried out. CNN as a part of deep learning has the ability to perform automatic feature extraction so that it can identify eye images. A CNN model for recognizing cataracts in eye images taken directly from Bhayangkara Hospital in Denpasar Bali has been developed in this research. The model developed is equipped with a dropout layer technique to prevent overfitting. The test results show that the CNN developed in this research produces very good performance with an average accuracy level of 92% on public dataset images, and 94% on primary dataset images. Tested using the primary dataset and public dataset, this CNN model shows very good performance because it can correctly identify an average of 94% of eye images in the primary dataset, and 92% of eye images in the public dataset.. © 2024 IEEE.

关键词： Convolutional neural networks

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Influence of Fly Ash, Volcanic Ash and Rice Husk Ash as Filler Asphalt Concrete Wearing Course Based on Marshall Characteristics 1st

Influence of Fly Ash, Volcanic Ash and Rice Husk Ash as Fill...

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1st International Conference on Emerging Smart Cities, ICESC 2022

作者： Magfirona, Alfia Billad, Riza Syaiful Wibowo, Gurawan Djati Amar, Tsulis Iq’bal Khairul Centre for Transport Studies Universitas Muhammadiyah Surakarta Surakarta Indonesia Civil Engineering Study Program Engineering Faculty Universitas Muhammadiyah Surakarta Surakarta Indonesia

ISBN: (纸本)9789819911103

Filler serves as a filling for the voids between coarse aggregate and fine aggregate in the AC-WC mixture. The filler has a significant effect on the marshall characteristics of the AC-WC mixture even though it is only as a filler. This study aims to investigate the effect of fly ash, volcanic ash, rice husk ash on marshall characteristics. The research data obtained from secondary data based on previous researchers, (Pratama 2021) for fly ash filler, (Rezi 2021) for volcanic ash filler, (Malacca 2021) for rice husk ash filler. The data is in the form of variations in the percentage of filler (fly ash, rice husk and volcano ash) with the same asphalt content. The sample was processed for statistical testing using SPSS version 26 software to determine the effect of asphalt content and filler percentage on marshall characteristics. Optimum Asphalt Content (OAC) test results obtained 6.1% fly ash, 6.2% volcanic ash, 6.7% rice husk ash. The test results on Marshall showed the most influential filler in the 2% rice husk ash filler with density, stability, Marshall Quontient (MQ) and VMA values, while the Flow value obtained the highest value in 1% volcanic ash filler. For the VFB of fly ash and rice husk ash, there was a decrease in the value of the filler content of 2% and 2.5% and an increase in the filler content of 3%. The results of statistical tests using SPSS show that those that have a significant positive linear influence on the asphalt content and filler percentage are Stability and Marshall Quotient (MQ). Research has contributed to research in the field of materials for AC-WC mixtures. © 2024, Institute of Technology PETRONAS Sdn Bhd.

关键词： Fillers

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Variable Length Multi-Objective Whale Optimization for Trust Aware Data Gathering in Wireless Sensor Network

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IEEE Access 2025年 13卷 32100-32121页

作者： Saad, Mohammed Ayad Jaafar, Rosmina Chellappan, Kalaivani Faculty of Engineering and Built Environment Department of Electrical Electronics and System Engineering Selangor Bangi43600 Malaysia Al-Kitab University Department of Medical Instrumentations Technique Engineering Kirkuk36001 Iraq Universitas Airlangga Biomedical Engineering Study Program Faculty of Science and Technology Surabaya60115 Indonesia

Efficient data collection in wireless sensor networks (WSNs) is crucial. While traditional approaches rely on stationary data sinks, the use of mobile sinks, like unmanned aerial vehicles (UAVs), has shown promise in enhancing data-gathering capabilities. However, existing methods often overlook the importance of trust, leaving the network susceptible to malicious or faulty nodes. To address this issue, we propose a novel trust-aware data-gathering algorithm, Variable Length Multi-Objective Whale Optimization Data Gathering (VLMOWO-DG). Our algorithm simultaneously optimizes energy consumption, delay, and trust while employing mobile sinks to collect data from sensor nodes. By considering trust as a key performance metric, we improve data reliability and security. The VLMOWO-DG algorithm introduces flexibility through variable-length solution representation and application-oriented operators, allowing for efficient exploration of the solution space. Simulation results demonstrate that our proposed algorithm significantly outperforms established benchmarks, NSGA-II and NSGA-III, in terms of domination and hypervolume. This leads to a remarkable improvement of 200% in data gathering performance. © 2015 The Authors.

关键词： Data collection

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The use of Carica papaya seeds as bio coagulant for laundry wastewater treatment

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Journal of engineering and Applied Science 2024年第1期71卷 99页

作者： Vezar, Siti Alfinna Naulita Belinda, Zeriyatina Tri Rendana, Muhammad Agustina, Tuty Emilia Nasir, Subriyer Hanum, Laila Andarini, Desheila Undergraduate Student of Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Chemical Engineering Program Faculty of Engineering Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Biology Department Faculty of Mathematics and Natural Sciences Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia Public Health Program Study Faculty of Public Health Universitas Sriwijaya Sumatra Selatan Indralaya30662 Indonesia

The study aims to analyze the effectiveness of wastewater treatment by using Carica papaya seeds as bio coagulants to diminish total suspended solids (TSS) and excess phosphate. This method has some advantages because it does not use chemical materials, is simple to apply, and is safe for the environment and human health. The wastewater samples were taken from an active laundry site in Palembang City, South Sumatra Province of Indonesia. The study found that the best dosage of coagulant was 3 g for the wastewater samples. The pH and BOD parameters showed slight changes after treatment, with pH 7.63–7.19 and 33–27 mg/L values, respectively. The TSS removal efficiency ranged from 9.3 to 15.6%, while the COD and phosphate removals were obtained from 11.7 to 39.3% and 56.3 to 68.4%, respectively. The treated TSS, COD, and phosphate concentrations have met the Indonesian domestic wastewater quality standard and environmental protection organization (EPO) guidelines. In addition, the statistical analysis and t-test showed significant differences (p © The Author(s) 2024.

关键词： Wastewater treatment

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Beyond p-y method:A review of artificial intelligence approaches for predicting lateral capacity of drilled shafts in clayey soils

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Journal of Rock Mechanics and Geotechnical engineering 2024年第9期16卷 3812-3840页

作者： M.E.Al-Atroush A.E.Aboelela Ezz El-Din Hemdan Civil and Environmental Engineering Program Engineering Management DepartmentCollege of EngineeringPrince Sultan UniversityRiyadhSaudi Arabia Department of Structural Engineering Faculty of EngineeringAin Shams UniversityCairoEgypt Structure and Materials Research Lab Prince Sultan UniversityRiyadhSaudi Arabia Computer Science and Engineering Department Faculty of Electronic EngineeringMenoufia UniversityMenoufiaEgypt

In 2023,pivotal advancements in artificial intelligence(AI)have significantly *** that in mind,traditional methodologies,notably the p-y approach,have struggled to accurately model the complex,nonlinear soil-structure interactions of laterally loaded large-diameter drilled *** study undertakes a rigorous evaluation of machine learning(ML)and deep learning(DL)techniques,offering a comprehensive review of their application in addressing this geotechnical challenge.A thorough review and comparative analysis have been carried out to investigate various AI models such as artificial neural networks(ANNs),relevance vector machines(RVMs),and least squares support vector machines(LSSVMs).It was found that despite ML approaches outperforming classic methods in predicting the lateral behavior of piles,their‘black box'nature and reliance only on a data-driven approach made their results showcase statistical robustness rather than clear geotechnical insights,a fact underscored by the mathematical equations derived from these ***,the research identified a gap in the availability of drilled shaft datasets,limiting the extendibility of current findings to large-diameter *** extensive dataset,compiled from a series of lateral loading tests on free-head drilled shaft with varying properties and geometries,was introduced to bridge this *** paper concluded with a direction for future research,proposes the integration of physics-informed neural networks(PINNs),combining data-driven models with fundamental geotechnical principles to improve both the interpretability and predictive accuracy of AI applications in geotechnical engineering,marking a novel contribution to the field.

关键词： Laterally loaded drilled shaft load transfer and failure mechanisms Physics-informed neural networks(PINNs) P-y curves Artificial intelligence(AI) Dataset

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Analysis of Chiller Machine Energy Efficiency in the Paint Shop Air Handling Unit (AHU) Process 7

Analysis of Chiller Machine Energy Efficiency in the Paint S...

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7th Astechnova International Energy Conference, ASTECHNOVA 2023

作者： Maulana, H. Kusumah, L.H. Study Program of Industrial Engineering Faculty of Technique Universitas Mercubuana Jakarta Indonesia

The Energy Efficiency in Industrial, Commercial, and Public Sector (EINCOPS) program is the result of a collaboration between the Indonesian Ministry of Energy and Mineral Resources and Danida (Danish International Development Assistance), which began in 2008 to support Indonesian government policies in achieving development goals in the field of sustainable environmental management. Energy users have gradually adopted energy efficiency measures in the industrial, commercial, and public sectors, starting with a large class. This research aims to obtain the optimal temperature range for using a chiller machine so that it continues to run efficiently. The method used is to calculate the coefficient of performance and energy efficiency ratio of each chiller when it is used. The number of chillers can be affected by the temperature range of the air handling unit (AHU), which uses wind from the environment as the main source for processing, and the temperature range is linear with weather conditions. This research found that in the environmental temperature range of 26°-29° Celsius taken by AHU for distribution to production areas, chiller performance is still not optimal. In the previous operation, three chillers were used out of the four available units, so after knowing the results of the chiller load analysis in this temperature range were still below standard or not optimal, the number of chillers could be reduced from three units full time to only two units when the temperature environment was in the range of 26°-29° Celsius. The results of calculating the average Coefficient of Performance and Efficiency Energy Ratio using two chillers when the temperature range of 26°-29° Celsius is still included in the standard, namely by increasing 0.15, the pre-improvement value is 5,833, and the chiller efficiency load increases to 14 percent. © Published under licence by IOP Publishing Ltd.

关键词： Mineral resources

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Nanoparticle formulation of ZnO: TiO2 as sunscreen cream for Cutaneous Lupus Erythematosus (CLE) patients 12

Nanoparticle formulation of ZnO: TiO2 as sunscreen cream for...

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12th International Conference on Physics and Its Applications, ICOPIA 2024

作者： Siswanto Qulub, Fitriyatul Junico, Vallery Ofelia Viannco Physics Program Study Faculty Science and Technology Universitas Airlangga Surabaya Indonesia Biomedical Engineering Program Study Faculty Science and Technology Universitas Airlangga Surabaya Indonesia

Cutaneous Lupus Erythematosus (CLE) is a form of lupus that affects the skin and is highly sensitive to ultraviolet (UV) light. UV-B. in particular. can trigger inflammation and apoptosis in CLE patients. making a sunscreen with effective UVB protection crucial. This study evaluates the effectiveness of zinc oxide (ZnO) and titanium dioxide (TiO2) nanoparticles in sunscreen. ZnO and TiO2 nanoparticles were prepared using the High Energy Milling method. resulting in particle sizes of 7.77 nm and 4.44 nm. respectively. The creams containing these nanoparticles were tested for physical stability and UV protection. Results showed that the creams were physically stable and provided good UV protection. with ZnO and TiO2 nanoparticles making up 12.60% of the total cream ingredients. resulting in the highest SPF (Sun Protection Factor) value of 62.0 ± 1.37. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： TiO2 nanoparticles

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Aerodynamic Analysis of Obhi-Mec Unud Bio-Hybrid Electric Vehicle Using Computational Fluid Dynamics 4

Aerodynamic Analysis of Obhi-Mec Unud Bio-Hybrid Electric Ve...

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4th International Symposium on Advances and Innovation in Mechanical engineering, ISAIME 2023

作者： Robert, Rivaldo Anderson Sucipta, Made Made Widiyarta, I. Meylinda, Cindy Dwi Sinaga, Betty Florensia Study Program of Mechanical Engineering Faculty of Engineering University of Udayana Kampus Unud Jimbaran Bali Badung80362 Indonesia

The aerodynamic properties of a vehicle are a factor in vehicle body development, such as the drag force, lift force, and flow pattern that occurs on the vehicle body. Using computational fluid dynamics (CFD), such as ANSYS Fluent, those properties can be investigated to design and analyze in many applications. Obhi-Mec Unud Bio-Hybrid is one of the electric vehicles developed to support the decarbonization program investigated through the fluid flow phenomenon to evaluate the drag and lift forces. The ANSYS Fluent with a realizable k-epsilon flow model with a pressure-based solver and steady flow was simulated with various vehicle velocities of 30, 40, and 50 km/h. It is found that the increase in vehicle velocity increases the drag and lift forces experienced by the vehicle. These results are due to the flow disturbance phenomena observed around the vehicle body, such as flow stagnation points, boundary layers, flow separation, and wake and vortex formation. © 2025 Institute of Physics Publishing. All rights reserved.

关键词： Computational fluid dynamics

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Design Implementation of Flood Early Warning System for Residential Monitoring

Design Implementation of Flood Early Warning System for Resi...

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2023 International Conference on Radar, Antenna, Microwave, Electronics, and Telecommunications, ICRAMET 2023

作者： Simatupang, Joni Welman Arrazaq, Thariq Auliya Faculty of Engineering President University Electrical Engineering Study Program Cikarang Indonesia

ISBN: (纸本)9798350343892

The efforts to mitigate floods are necessary. One of the tools that can contribute to flood mitigation is the Flood Early Warning System (FEWS). The main goal of this study is to design a prototype of FEWS that can be easily used anywhere, anytime, and provide accurate water level readings. The prototype system is designed using an Ultrasonic Sensor for water level detection, an alarm system, and Blynk as a web and mobile dashboard. The prototype consists of four main components: Ultrasonic Sensor HC-SR04, Arduino Nano, NodeMCU, and HC-12. It comprises two units: a transmitter unit and a receiver unit. To determine the accuracy and consistency of the Ultrasonic Sensor, the author conducted testing using calibration, non-continuous, and continuous methods. The accuracy obtained was 99.71%. Additionally, the author observed high consistency in the readings of the ultrasonic sensor, as evident from continuous sensor reading test results. Furthermore, the receiver unit successfully displayed output according to the water level threshold for each condition. Additionally, the Blynk web and mobile dashboard were able to display output as per the design. However, we suggest adding data logging features and also solar panels as a renewable power source to support the improved prototype system. © 2023 IEEE.

关键词： Floods

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An integrated decision-making approach to resilience–LCC Bridge network retrofitting using a genetic algorithm-based framework

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Resilient Cities and Structures 2025年第1期4卷 16-40页

作者： Omidian, Pedram Khaji, Naser Aghakouchak, Ali Akbar Faculty of Civil and Environmental Engineering Tarbiat Modares University Tehran P.O. Box 14115-397 Iran Civil and Environmental Engineering Program of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima Hiroshima739-8527 Japan

Bridge networks are essential components of civil infrastructure, supporting communities by delivering vital services and facilitating economic activities. However, bridges are vulnerable to natural disasters, particularly earthquakes. To develop an effective disaster management strategy, it is critical to identify reliable, robust, and efficient indicators. In this regard, Life-Cycle Cost (LCC) and Resilience (R) serve as key indicators to assist decision-makers in selecting the most effective disaster risk reduction plans. This study proposes an innovative LCC–R optimization framework to identify the most optimal retrofit strategies for bridge networks facing hazardous events during their lifespan. The proposed framework employs both single- and multi-objective optimization techniques to identify retrofit strategies that maximize the R index while minimizing the LCC for the under-study bridge networks. The considered retrofit strategies include various options such as different materials (steel, CFRP, and GFRP), thicknesses, arrangements, and timing of retrofitting actions. The first step in the proposed framework involves constructing fragility curves by performing a series of nonlinear time-history incremental dynamic analyses for each case. In the subsequent step, the seismic resilience surfaces are calculated using the obtained fragility curves and assuming a recovery function. Next, the LCC is evaluated according to the proposed formulation for multiple seismic occurrences, which incorporates the effects of complete and incomplete repair actions resulting from previous multiple seismic events. For optimization purposes, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II) evolutionary algorithm efficiently identifies the Pareto front to represent the optimal set of solutions. The study presents the most effective retrofit strategies for an illustrative bridge network, providing a comprehensive discussion and insights into the resulting tactical approaches

关键词： Genetic algorithms

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