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INDONESIA
Emerging Science Journal
Published by Ital Publication
ISSN : 26109182     EISSN : -     DOI : -
Core Subject : Social,
Environmental Science
Emerging Science Journal is not limited to a specific aspect of science and engineering but is instead devoted to a wide range of subfields in the engineering and sciences. While it encourages a broad spectrum of contribution in the engineering and sciences. Articles of interdisciplinary nature are particularly welcome.
Arjuna Subject : -
Articles 15 Documents
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Search results for , issue "Vol 8, No 1 (2024): February" : 15 Documents clear
Topic Modeling: A Consistent Framework for Comparative Studies Ana Amaro; Fernando Bacao
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-09

Abstract

In recent years, the field of Topic Modeling (TM) has grown in importance due to the increasing availability of digital text data. TM is an unsupervised learning technique that helps uncover latent semantic structures in large sets of documents, making it a valuable tool for finding relevant patterns. However, evaluating the performance of TM algorithms can be challenging as different metrics and datasets are often used, leading to inconsistent results. In addition, many current surveys of TM algorithms focus on a limited number of models and exclude state-of-the-art approaches. This paper has the objective of addressing these issues by presenting a comprehensive comparative study of five TM algorithms across three different benchmark datasets using five different metrics. We offer an updated survey of the latest TM approaches and evaluation metrics, providing a consistent framework for comparing different algorithms while introducing state-of-the art approaches that have been disregarded in the literature. The experiments, which primarily use Context Vectors (CV) Topic Coherence as an evaluation metric, show that Top2Vec is the best-performing model across all datasets, disrupting the tendency for Latent Dirichlet Allocation to be the best performer. Doi: 10.28991/ESJ-2024-08-01-09 Full Text: PDF
Improving the Quality Indicators of Multilevel Data Sampling Processing Models Based on Unsupervised Clustering Ilya S. Lebedev; Mikhail E. Sukhoparov
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-025

Abstract

This paper presents a solution for building and implementing data processing models and experimentally evaluates new possibilities for improving ensemble methods based on multilevel data processing models. This study proposes a model to reduce the cost of retraining models when transforming data properties. The research objective is to improve the quality indicators of machine learning models when solving classification problems. The novelty is a method that uses a multilevel architecture of data processing models to determine the current data properties in segments at different levels and assign algorithms with the best quality indicators. This method differs from the known ones by using several model levels that analyze data properties and assign the best models to individual segments of data and training. The improvement consists of using unsupervised clustering of data samples. The resulting clusters are separate subsamples for assigning the best machine-learning models and algorithms. Experimental values of quality indicators for different classifiers on the whole sample and different segments were obtained. The findings show that unsupervised clustering using multilevel models can significantly improve the quality indicators of “weak” classifiers. The quality indicators of individual classifiers improve when the number of data clusters is increased to a certain threshold. The results obtained are applicable to classification when developing models and machine learning methods. The proposed method improved the classification quality indicators by 2–9% due to segmentation and the assignment of models with the best quality indicators in individual segments. Doi: 10.28991/ESJ-2024-08-01-025 Full Text: PDF
Cycloartobiloxanthone, a Flavonoid with Antidiabetic, Antibacterial and Anticancer Activities from Artocarpus kemando Miq. Tati Suhartati; Antin S. Prihatin; Armidla N. Kurniati; Hendri Ropingi; Yandri Yandri; Sutopo Hadi
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-04

Abstract

In this present work, a cycloartobiloxanthone compound was isolated from the stem wood and root bark of the Pudau plant (Artocarpus kemando Miq.). The purity of the compound was determined using thin-layer chromatography with three eluent systems and melting point tests. The sample was then analyzed using UV-Vis, IR, and NMR spectroscopy, ensuring that the compound is cycloartobilox-anthone. The cycloartobiloxanthone compound was obtained in a yellow crystalline form with a melting point of 285.1-294°C. The compound was then investigated for antidiabetic, anticancer, and antibacterial properties, showing that the compound has an anti-diabetic effect by reducing the activity of the α-amylase enzyme, with the highest percentage of inhibition of 48.53 ± 1.84% achieved with the use of 1000 ppm of the compound. Cycloartobiloxanthone isolated has an IC50 value of 9.21 µg/mL for anticancer activity against MCF-7 cells, indicating that the compound shows active cytotoxic actions. Staphylococcus aureus was very strongly inhibited by the compound in the antibacterial test at all doses, whereas for Salmonellasp., the activity was categorized as moderate at concentrations of 0.4 and 0.3 mg/disc and strong at 0.5 mg/disc. The anti-diabetic, anti-cancer, and antibacterial bioactivity studies indicated that the cycloartobiloxanthone compound isolated has a broad spectrum of pharmacological actions, indicating that the compound has promising potential. Doi: 10.28991/ESJ-2024-08-01-04 Full Text: PDF
Design and Study the Performance of a CMOS-Based Ring Oscillator Architecture for 5G Mobile Communication Abdul Rahman; Siddharth Kishore; A. R. Abdul Rajak
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-020

Abstract

Oscillator circuits are used to make accurate and reliable clock signals for systems as simple as a wristwatch and as complicated as satellites, which are important for long-distance communication. There are many ways to build an oscillator circuit, using either passive or active parts. Each option has pros and cons, but at the current level of mobile communication development, the most important things are interoperability and low power use. This need has driven the development of compact, battery-operated electronics, and Very Large-Scale Integration (VLSI)-based ring oscillators provide the ideal solution. These oscillators ought to dissipate less power, have a large tuning range, and be compact. The paper presents a novel Complementary Metal Oxide Silicon (CMOS) ring oscillator that serves as a Voltage Controlled Oscillator. The suggested architecture utilizes the advantages of both a current-starved ring oscillator and a negative-skewed delay by combining their constituent parts. The proposed architecture has a control voltage of 1.15 V and a supply voltage of 2 V, generating a 9.35 GHz dominant frequency with a 13.82% harmonic distortion between the inputs and outputs. The proposed architecture can implement 5G-based applications that require high frequency and low power by carefully selecting the passive components within the design. Doi: 10.28991/ESJ-2024-08-01-020 Full Text: PDF
Visitor Experience Map and NFC-Based Scoring for Data-Driven Exhibition Enhancement Siti Fatimah Abdul Razak; Jeslyn Pik Syuen Hee; Rashidah Ahmad; Sumendra Yogarayan; Noor Hisham Kamis; Md Shohel Sayeed
Emerging Science Journal Vol 8, No 1 (2024): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2024-08-01-015

Abstract

In the current exhibition industry, it is crucial for organizers and exhibitors to comprehend and enhance visitor experiences. The objective of this study is to improve the exhibition setting by utilizing Near Field Communication (NFC) technology to capture, monitor, and analyze visitor behavior, engagement, and satisfaction. The main approach entails combining NFC technology with the Visitor Experience Map to fully understand the complexities of the visitor experience. NFC-enabled smartphones facilitate seamless interaction with the system, as users simply need to bring their smartphones close to NFC tags. This enables data collection and triggers the activation of a visitor scoring form for ratings and feedback. The study's findings indicate a mean system usability score of 81.4, which demonstrates successful implementation and great usability. This confirms the effective and easy-to-use nature of the strategy, guaranteeing that visitors can effortlessly provide their ratings and feedback. The originality and enhancement reside in the successful integration of NFC technology with the Visitor Experience Map, providing a strong and user-focused approach for organizers and exhibitors to enhance the exhibition experience. This study creates a favorable situation for both visitors and stakeholders, demonstrating the potential of technological advancements to greatly influence the exhibition industry. Doi: 10.28991/ESJ-2024-08-01-015 Full Text: PDF

Page 2 of 2 | Total Record : 15

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