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Journal of Novel Engineering Science and Technology
Published by Indonesian Institute of Science and Technology Research
ISSN : 29618916     EISSN : 29618738     DOI : https://doi.org/10.56741/jnest.v1i02
Core Subject : Science, Social, Engineering,
Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Environmental Science Mechanical Engineering
Journal of Novel Engineering Science and Technology is a multi-disciplinary international open-access journal dedicated to natural science, technology, and engineering, as well as its derived applications in various fields. JNEST publishes high-quality original research articles and reviews in all of the disciplines mentioned above. All papers submitted will go through a rapid peer-review process to ensure their quality. Submissions must contain original research and contributions to their field. The manuscript must adhere to the author’s guidelines and have never been published before. All accepted manuscripts will be indexed in DOAJ, EBSCO, and Google Scholar. The indexation in SINTA, Scopus, and WoS will be provided in the future to provide maximum exposure to the articles.
Arjuna Subject : Teknik (semua kategori) - Teknik (Lain-Lain)
Articles 8 Documents
 1 
Search results for , issue "Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology" : 8 Documents clear
Developing New PVT Correlations for Libyan Crude Oil Using Samples from Different Reservoirs Burgan, Taha A.; Moammer, Saleh F.; Aghanaya, Mahfoud Z.; Khair, Ali A.
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.541

Abstract

Five PVT correlations including bubble point pressure, solution gas-oil ratio, oil formation volume factor, dead oil viscosity, and oil density were used to analyze a total of 102 data sets from the Libyan crude oil reservoirs representing Sirte, Ghdames, Murzug, and offshore Tripolitania basins, to find a new more accurate correlation. Linear & nonlinear regression and statistical software packages (Excel, Minitab, and Mat lab software) were applied to the above-mentioned crude samples. The application of multilinear regression and statically software on the solution gas, oil ratio, temperature, and API gravity, exhibit a direct proportionality with the bubble point, whereas in the case of gas gravity, the correlation shows inversely proportionality with the bubble point. The relationships between the solution gas oil and other properties show that the distribution of the tested points in these investigations are located very close to the 45° trend line fourth solution gas oil ratio, indicating that the correlations have higher accuracy with our newly developed PVT equations for the analyzed Libyan crude oil samples. The cross plots between measured vs. calculated oil formation factor, dead oil viscosity, and oil density play a very good reliable correlation compared with previously published correlations done by other researchers as well as in the statistical calculation, in addition, the AARE and R2 results were calculated for previous published correlation in different locations over the world. Based on the obtained results in this research, the proposed correlations are more accurate than all the other previously published correlations, exclusively for Libyan crude oil.
Advanced Exergy Analysis on the Turbofan Engine Indriyati, Feni; Mahandari, Cokorda Prapti; Yamin, Mohamad
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.543

Abstract

Studies on energy utilization underscore the paramount importance of energy, as evidenced by numerous researchers. This research encompasses both conventional and advanced exergy analyses. Advanced exergy analysis aims to ascertain the extent of energy loss in each component, influenced by irreversibility, and to account for component interactions within the system. Furthermore, advanced exergy analysis seeks to enhance the operational efficiency of each engine component. The findings reveal that the combustion chamber exhibits the highest level of energy loss, amounting to 32.817 MW. This energy loss primarily stems from irreversibility triggered by chemical reactions leading to heat transfer. Overall, the study results indicate that the exergy influx from external sources surpasses that generated internally in each component system.
Performance Optimization of Brain Tumor Detection and Classification Based MRI by Using Batch Normalization Algorithms in Deep Convolution Neural Network Tin, Thein Aung; Aye, Mya Mya; Khin, Ei Ei; Oo, Thandar; Tun, Hla Myo; Pradhan, Devasis
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.567

Abstract

Brain tumor is represented as an essential part of critical cancers around the world. These cells multiply and accumulate uncontrolled, forming a mass or lump that can interfere with normal brain function. Primer detection systems not only took too must time in analyzing and setting error, but also extended more datasets to become overfitting, more computation time, and lack accuracy. Supervised ML and traditional CNN are not convenient for estimating the vita feature engineering in larger datasets and they need to be modified using normalization techniques in deep convolutional Neural Networks (CNNs) architectures. The proposed of the research MRI image datasets were evaluated and combined with two popular benchmark data sets, Kaggle, and BRATS. This main objective is to reduce the computational cost avoid overfitting and underfitting and then improve the classification accuracy. In addition, this paper follows the concept of the CNN model and evaluates the modified DCNN with six normalization layers benefits acceptable results with batch normalization techniques and the average number of epochs in a limited time. In this regard, we exploited to extend inside the layer DCNN for the problem of brain tumor classification. This model achieved the best result for the enhanced dataset, with a training accuracy of 99.9%, 98.9% in validation accuracy, 0.0074 in training loss, and a validation loss of 0.0566 in validation loss.
Transparent Film Profiling and Analysis by White Light Scanning Interferometry Hlaing, Nway Nway; Win, Lei Lei Yin; Tun, Hla Myo; Pradhan, Devasis
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.569

Abstract

This paper describes the use of white light scanning interferometry with a Super luminescent diode (SLD) for thin film surface measurement. The technique provides 3D top surface and thickness profiles of transparent films, as well as detailed properties of multilayer film stacks, including material optical properties. The setup involves splitting a laser beam with a beam splitter, generating interference signals detected by a photodetector, and then converting analog signals to digital using an A/D converter for further analysis with LabView and MATLAB software. In this paper, the theoretical analysis and simulation study of white light scanning interferometry for transparent film measurement is discussed. This approach offers a flexible tool for both engineering and structured surface measurements.
Designing the Future: Exploring the Smart Manufacturing Ecosystem and Future Landscape Bouguern, Siham
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.603

Abstract

The manufacturing industry has continuously evolved alongside technological advancements, progressing from steam engines to electricity, microprocessors, computers, automation, and most recently, artificial intelligence, the Internet of Things (IoT), and cyber-physical systems. This digital transformation has ushered in the era of smart manufacturing, characterized by the development of intelligent systems. In this paper, we provide a comprehensive exploration of the smart manufacturing ecosystem, assessing its current status and forecasting future trends. Key elements and technologies central to smart manufacturing and Industry 4.0 (I4.0) encompass digital manufacturing, big data analytics, cloud manufacturing, digital twins, IoTs, and smart factories. Our research adopts a qualitative approach, offering a broad perspective on the concept of smart manufacturing. This paper aims to explore these emerging trends and shed light on future opportunities associated with this digital transformation. Consequently, enterprises need to redesign their businesses and models to achieve the benefits disclosed by these new settings.
Development of Novel Solar Cell Design based on Current Energy Converted from Phonon Energy by Controlling the Phonon Transport Tin Swe, Hsu Myat; Hla Myo Tun; Pradhan, Devasis; Win, Lei Lei Yin; Khin, Ei Ei; Soe, Khaing Thandar
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.626

Abstract

The paper mainly focuses on the Development of Novel Solar Cell Design based on Current Energy Converted from Phonon Energy by Controlling the Phonon Transport. The research challenges in this study are: to find a means of the control of phonon transport or phonon accumulation and propose a novel solar cell structure to convert the phonon energy to the current energy; to study phonon control method for III-nitrides and the properties of phonon transport; to analyze the phonon absorption in a short time for III-nitrides is higher than gallium arsenide by one order, which makes it possible to extract higher current than previous materials. The research objectives are: to design the novel solar cell structure to convert Phonon Energy to Current Energy; to analyze the physics of solar cell structure with numerical approaches; to model the Quantum Well in the proposed solar cell structure; to set the experimental measurement system for physical characteristics of novel solar cells; to confirm the results from the analysis of Control of Phonon Transport. The conversion of current energy from the phonon energy by controlling the phonon transport depends on the structure of the solar cell stacking system. The implementation of this study was accomplished based on the specific model, especially Quantum Well Structure. The results confirm that the performance specification of targeted solar cell structures in real-world applications.
Implementation of the Process for Contamination in Electromyography (EMG) Signal by Using Noise Removal Techniques Oo, Nandar; Tun, Hla Myo; Pradhan, Devasis; Win, Lei Lei Yin; Aye, Mya Mya; Oo, Thandar
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.627

Abstract

The paper describes the analysis of electromyography (EMG) signals using noise removal techniques. The problem in this study is to consider a noise removal technique for basic EMG signal processing by the Band Pass Filter method. A research approach to designing simulation codes for observing EMG signal modeling and noise removal techniques through mathematical methods from signals and systems concepts. The results confirm that it can provide high-performance target monitoring of the EMG signal in real-world applications.
A Preliminary Study on the Measurement of Supply Chain Performance: The Determination of Key Performance Indicator (KPI) Weights Firmansyah, Reza; Budijati, Siti Mahsanah; De’e, Silvia
Journal of Novel Engineering Science and Technology Vol. 3 No. 03 (2024): Journal of Novel Engineering Science and Technology
Publisher : The Indonesian Institute of Science and Technology Research

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.56741/jnest.v3i03.745

Abstract

Supply chain performance measurement is crucial in determining strategies to improve company performance. PT XYZ is an export-scale sweet potato-based food processing company. The obstacle the company often faces is the mismatch in the quantity of raw material delivered from suppliers, resulting in delays in production and fulfillment of demand to consumers. For this reason, it is important to measure the performance of the supply chain, so that the company knows the parts of the supply chain that must be improved. Supply Chain Operations Reference (SCOR) is a method for measuring supply chain performance. Before applying the SCOR method, the first step that needs to be done is determining the Key Performance Indicator (KPI) and its weight. This research aims to determine KPI weights using the Analytical Hierarchy Process (AHP) method, at PT XYZ. The AHP method was chosen because of its ability to provide objective weights based on priorities determined by experts. The results showed that there were 6 KPIs at level 1, 19 KPIs at level 2 which were grouped in 6 dimensions, and 50 KPIs at level 3 which were grouped in 19 dimensions. The KPI determination is adjusted to the SCOR dimensions and the real conditions of the company. Furthermore, based on the AHP method analysis, the weight of each KPI is obtained, and the weight comparison between KPIs is known. The implementation of strategies that focus on the KPIs with the highest weights is expected to improve the overall supply chain performance.

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