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H Hadiyanto
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jese@cbiore.id
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Journal of Emerging Science and Engineering
Published by CBIORE Scientia Academy
ISSN : 30260817     EISSN : 30260183     DOI : https://doi.org/10.61435/jese.xxx.xxx
Core Subject : Social, Engineering,
Engineering Environmental Science
Journal of Emerging Science and Engineering (JESE) is peer-reviewed, and it is devoted to a wide range of subfields in the engineering sciences. JESE publishes two issues of rigorous and original contributions in the Science and Engineering disciplines such as Biological Sciences, Chemistry, Earth Sciences, and Physics, Chemical, Civil, Computer Science and Engineering, Electrical, Mechanical, Petroleum , and Systems Engineering.. JESE publishes original research papers, reviews, short communications, expository articles, and reports. Manuscripts must be submitted in the English language and authors must ensure that the article has not been published or submitted for publication elsewhere in any format, and that there are no ethical concerns with the contents or data collection. The authors warrant that the information submitted is not redundant and respects general guidelines of ethics in publishing. All papers are evaluated by at least two international referees, who are known scholars in their fields. We encourage and request all academics and practitioners in the field of science and engineering to send their valuable works and participate in this journal.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 5 Documents
 1 
Search results for , issue "Vol. 2 No. 1 (2024)" : 5 Documents clear
Shrimp and fish underwater image classification using features extraction and machine learning Setiawan, Arif; Hadiyanto, H.; Widodo, Catur Edi
Journal of Emerging Science and Engineering Vol. 2 No. 1 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e14

Abstract

Shrimp cultivation is one type of cultivation that has a significant impact on the social status of coastal communities. Shrimp farming traditionally faces several challenges, including water pollution, imbalances in temperature, feed, media, and costs. Monitoring the condition of shrimp in the cultivation environment is very necessary to determine the condition of shrimp in the water. Classification of shrimp and fish is the first step in monitoring the condition of shrimp underwater. This research proposes the development of a method for classifying shrimp and fish underwater using feature extraction and machine learning. The flow of this research is: (1) preparing data from ROI detection results, (2) extraction process of morphometric characteristics P and T, (3) calculating the value of morphometric characteristics P and T, (4) data breakdown for training data and testing data, (5) Model creation process, data training and data testing using SVM, RF, DT, and KNN, (6) Evaluation of classification results using a confusion matrix. From this research, it was found that the Random Forest method obtained the highest accuracy, namely 0.93. From this matrix, the values ​​obtained are True Positive = 349, False Positive = 28, True Negative = 223, False Negative = 0.
Hyperparameter optimization for hourly PM2.5 pollutant prediction Barid, Aziz Jihadian; Hadiyanto, H.
Journal of Emerging Science and Engineering Vol. 2 No. 1 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e15

Abstract

Air pollution, particularly the presence of Particulate Matter (PM) 2.5, poses significant health risks to humans, with industrial growth and urban vehicle emissions being major contributors. This study utilizes machine learning techniques, specifically K-Nearest Neighbors (KNN) and Support Vector Machine (SVM) algorithms, to predict PM2.5 levels. A dataset from Kaggle consisting of PM2.5 and other pollutant parameters is preprocessed and split into training and testing sets. The models are trained, evaluated, and compared using Mean Squared Error (MSE) and Root Mean Squared Error (RMSE) metrics. Additionally, hyperparameters are applied to optimize the models. Results show that SVM with hyperparameters performs better, indicating its potential for accurate air quality prediction. These findings can aid policymakers in implementing effective pollution control strategies.
Analysis of the surface roughness of 3D-printed occlusal splints fabricated using biocompatible resins Gahletia, Sumit; Kaushik, Ashish; Kumar Garg, Ramesh
Journal of Emerging Science and Engineering Vol. 2 No. 1 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e17

Abstract

Nowadays, in order to promote innovation and sustainable product design and manufacturing of occlusal splints, the dental profession requires significant upgrades in the form of novel materials and cutting-edge manufacturing technologies. Researchers and Industry frontrunners are constantly challenged to improve the properties of splint developed using three dimensional scanning and resin printing to meet consumer demand, as the ability of dental practitioners to take accurate impressions remains a major obstacle in dental laboratories. The proposed study outlines a digital manufacturing process for occlusal splints created with three-dimensional scanning and resin printing. The study also analysed the occlusal splints in terms of geometrical preciseness and surface roughness along with the costs involved during 3D printing a resin-based occlusal splint. Occlusal splints were created by scanning impressions made on a typodont model and then designing them in 3D modelling software. The splints were developed in MIMICS and 3D printed to a thickness of 10 microns using Rigid white methacryalate based resin material on a 3D systems DLP Figure IV standalone resin 3D printer to create a biocompatible occlusal splint. Splint tooth height was determined for geometric analysis. Surface roughness of splintwas measured using SURFCOM surface roughness tester. Resins used in 3D printing were proven to produce geometrically precise splints, the study showed. In conclusion, UV curable resin-based occlusal splints that have been 3D printed and cured are recommended for patient usage due to their increased accuracy and the ability to save processing time.
Theoretical and simulation of central elliptical hole with rectangular plate Sivaramakrishnaiah, M; Reddy, S.N. Pradeepkumar; Raghava, P. Madhu; Amaranathareddy, B.V.
Journal of Emerging Science and Engineering Vol. 2 No. 1 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e18

Abstract

A study on design engineering components with slot, notches is very important, because there is a stress increases/failure region area, where the force/stress is concentrating more and more. The elastic stress concentration mainly depends on the mode of loading, materials, and geometry of the design engineering components. The design engineers, academicians, and researchers concentrated and focused on fail-safe design and safe life design. A Plate is considered with different slots, such as circular and elliptical. The main objective of this study is to find out the stress concentration factor in plates with various cutout shapes. This concept is used in design components/structures, for finding the elastic stress concentration. The methods compared are tabulated with their findings. Singularities of the circular hole and elliptical hole in rectangular plates are considered in the present study. The finite Element Method (FEM) was used for fine mesh and ANSYS WORKBENCH software was used for extracting the results and results were validated by analytical or experimental methods.
Investigations on co-gasification and combustion characteristics of coal biomass blend as an alternative transport fuel for tri-cycles Kariuki, Benson; Njogu, Paul; Kamau, Joseph; Kinyua, Robert; Malessa, Reiner; Bachani, Sameer
Journal of Emerging Science and Engineering Vol. 2 No. 1 (2024)
Publisher : BIORE Scientia Academy

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.61435/jese.2024.e20

Abstract

Kenya discovered huge deposit of lignite-coal, better utilized through co-gasification to produce syngas, a clean and environmental friendly fuel, with easier application in engines. Blends of Mui-basin coal (MBC), Prosporis juliflora(PJ), Hyphanae compressa(HC) and rice husk(RH) were co-fired with resultant upgraded-syngas operating tricycle engine. Analyzed upgraded-syngas reported improved yields on combustible gases and Hydrogen/Carbon-monoxide ratio (low rank to moderate). Calorific values reported 3.2-11.2% increase. At half-load and relative to neat diesel (ND), peak-pressure improved by 31.6%(MBC-PJ), 24.0%(MBC-HC) and 14.6%(MBC-RH). Additionally, peak-pressure increases as load increases and shifts to the right of top-dead-centre with reported increase of 13.1%MBC-PJ, 15.4%MBC-HC, 18.3 % MBC-RH and 16.5 % for ND. Moreover, Net heat release rate (NHRR) in J/degree increased rapidly at 15-25oafter/TDC for all loads and also increased as the load increased with values of 33.4(HC), 26.8(ND), 28.8(RH) and 37.8(PJ) at no load and 35(HC), 27.8(ND), 30(RH), and 38.9(PJ) at full load condition. The optimal approach for sustainably utilization of MBC is through the novel fuel, in which MBC-PJ ranks the best followed by MBC-HC and lastly MBC-RH.

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