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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 803 Documents
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Effect of One-Time Application of Biochar and Compost on Soil and Maize During 5-Time Consecutive Periods of Crop Cultivation Wijitkosum, Saowanee; Sriburi, Thavivongse; Toonsiri, Phasita
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-07

Abstract

This study evaluates the impact of a single-time biochar application during initial cultivation on the performance of five consecutive crop cycles. The research compares the effects of biochar alone versus biochar combined with soybean compost on maize yield and soil properties over a period of 2.8 years. Fundamental soil properties—including pH, cation exchange capacity, organic matter content, and macronutrient levels—were assessed before each planting cycle and at the end of the fifth cycle. Maize yield and productivity were evaluated based on the number of maize ears, kernel biomass, and both fresh and dry kernel weights. Five experimental plots, each with four replicates, were established with the following treatments: compost applied at 0.56 kg/sq m (TM), cassava stem (CS) biochar applied alone at 2.5 kg/sq m (TB2.5) and 3.0 kg/sq m (TB3.0), and combinations of compost at 0.56 kg/sq m with CS biochar at 2.5 kg/sq m (TMB2.5) and 3.0 kg/sq m (TMB3.0). Results indicated that the sole application of biochar and its combination with compost positively affected soil properties and maize yield. Biochar applications alone significantly improved soil nutrient levels and maize yields compared to the compost alone. Notably, the beneficial effects of biochar on maize and soil were observed from the first cultivation and persisted throughout all five cycles. Based on these findings, it is recommended to apply biochar at 3.0 kg/sq m, in combination with compost at 0.56 kg/sq m, every three crop cycles to sustain nutrient levels and enhance maize yields effectively. Doi: 10.28991/ESJ-2025-09-01-07 Full Text: PDF
Mechatronic System Based on Bluetooth Communication with a Mobile Application for Automatic Irrigation in Greenhouses Tasayco, Juan; Villanueva, Anthony; Yauri, Ricardo
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-02

Abstract

Non-automatic irrigation in greenhouses presents significant disadvantages, such as waste of water and loss of time, although they are highly widespread and low cost. Research highlights the importance of rationally managing and using water through information technologies to improve crop quality, recommending the use of automated irrigation systems, although challenges are faced in the proper integration of electronic devices in agricultural environments. For this reason, it is considered that the use of drip irrigation, the integration of embedded systems with Bluetooth connection, and mobile applications facilitates its use. This paper describes the design and implementation of a prototype mechatronic system to manage greenhouse irrigation, using an embedded system based on a microcontroller. In this case, temperature and humidity sensors are used that control a water pump, monitor environmental factors, and display data in the mobile application connected via Bluetooth, activating the water pump automatically. The results show that the prototype is functional, meets the stated objectives, and proposes improvements related to the range of Bluetooth communication and the implementation of a solar panel for use in areas without electricity supply. Doi: 10.28991/ESJ-2025-09-01-02 Full Text: PDF
Clustering and Network Analysis of Mobility Patterns as an Analysis Tool for Lean Project Rácz-Szabó, András; Ruppert, Tamás; Abonyi, János
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-013

Abstract

The study aims to optimize internal logistics processes by applying Lean philosophy and data science tools, with a primary focus on qualifying processes to determine their value-added contribution within the logistics context. Utilizing a novel two-step methodology, the research first employs a modified DBSCAN algorithm to analyze indoor positioning data and categorize activities. This is followed by multi-layer network modeling to understand processes and create a framework that enables the reduction of idle activities through optimization algorithms. A real warehouse case study, using a UWB-based Indoor Positioning System (IPS) to track forklifts, demonstrates the method's effectiveness in identifying non-value-added activities. The results reveal specific opportunities for reducing idle, enhancing resource utilization, and improving operational efficiency. This innovative combination of advanced data analysis techniques and Lean principles provides a comprehensive framework for logistics optimization, significantly enhancing process efficiency through optimized task scheduling and resource allocation. Doi: 10.28991/ESJ-2025-09-01-013 Full Text: PDF
Development and Testing of a Patient Outcome Measure for Interprofessional Tuberculosis Care: A Delphi Study Ardyansyah, Bau D.; Cordier, Reinie; Brewer, Margo; Parsons, Dave
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-08

Abstract

Background: A chronic medical condition such as tuberculosis can be physically and emotionally challenging for both health practitioners and patients and their families. Tuberculosis requires a team-based care model that provides resilience and coordinated work, such as the one offered by an interprofessional collaborative practice team. Despite the increasing interest in interprofessional-based care globally, there is a notable lack of measures to assess patient impact. We aimed to develop a patient outcome measure to quantify the functional impact of interprofessional care on tuberculosis patients. Methods: The study involved four phases: 1) developing a conceptual framework and creating items, 2) evaluating the construct through Delphi studies to obtain international consensus, 3) back-to-back translation into Indonesian, and 4) re-evaluating the construct with Delphi study to obtain Indonesian consensus. The consensus was reached if the Content Validity Index covers at least 70% agreement from experts, an interquartile range <1, and a median score of 4 or 5 on a 5-point Likert-type scale. The COnsensus-based Standards for the Selection of Health Measurement INstruments (COSMIN) guidelines were used to assess item relevance, comprehensibility, and comprehensiveness. Results: A total of 65 international and 61 Indonesian participants in the Delphi studies. The final instrument consists of 44 items organized into five domains. All items were relevant to the construct being measured and deemed understandable, and significant concerns related to TB care were comprehensively addressed in the instrument. Conclusion:The findings indicate that the instrument content validity was good, fulfilling COSMIN requirements for items' relevance, comprehensibility, and comprehensiveness. Doi: 10.28991/ESJ-2025-09-01-08 Full Text: PDF
Unlocking Potential Score Insights of Sentimental Analysis with a Deep Learning Revolutionizes Alzahrani, Ibrahim R.
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-03

Abstract

Online hate has emerged as a rapidly growing issue worldwide, often stemming from differences in opinion. It is crucial to use appropriate language and words on social media platforms, as inappropriate communication can negatively impact others. Consequently, detecting hate speech is of significant importance. While manual methods are commonly employed to identify hate and offensive content on social media, they are time-consuming, labor-intensive, and prone to errors. Therefore, AI-based approaches are increasingly being adopted for the effective classification of hate and offensive speech. The proposed model incorporates various text preprocessing techniques, such as removing extraneous elements like URLs, emojis, and blank spaces. Following preprocessing, tokenization is applied to break down the text into smaller components or tokens. The tokenization technique utilized in this study is TF-IDF (Term Frequency–Inverse Document Frequency). After tokenization, the model performs the classification of hate and offensive speech using the proposed BiLSTM-based SM-CJ (Scalable Multi-Channel Joint) framework. The BiLSTM-based SM-CJ model is particularly effective in detecting hate, offensive, and neutral tweets due to its ability to capture both forward and backward contexts within a given text. Detecting hate speech requires a comprehensive understanding of the text and the identification of patterns spanning across multiple words or phrases. To achieve this, the LSTM component of the BiLSTM model is designed to capture long-term dependencies by utilizing information from earlier parts of the text. The proposed SM-CJ framework further aligns the input sequence lengths fetched from the input layer, enabling the model to focus on specific segments of the input sequence that are most relevant for hate speech detection. This approach allows the model to accurately capture derogatory language, and subtle nuances present in hate speech. Finally, the performance of the proposed framework is evaluated using various metrics, including accuracy, recall, F1-score, and precision. The results are compared with state-of-the-art approaches, demonstrating the effectiveness of the proposed model. Doi: 10.28991/ESJ-2025-09-01-03 Full Text: PDF
Enhancing User Differentiation in the Electronic Personal Synthesis Behavior (EPSBV01) Algorithm by Adopting the Time Series Analysis Shakir, Mohanaad
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-014

Abstract

The progress of contemporary technology has rendered information systems essential in our everyday existence, underscoring the crucial necessity to safeguard information security and privacy. In password authentication, the Electronic Personal Synthesis Behaviour (EPSB) heightens the accuracy of authorizing an authenticated user based on three parameters: EPSBERROR, EPSBTime, and EPSBStyle. EPSBTime suffers from a lack of indicators associated with the legitimate user; containing only six indicators, there arose the need to adopt methods for generating additional reliable indicators by analyzing old indicators and generating new indicators related to the legitimate user. Therefore, this study aims to test the impact of adopting time series analysis in the EPSB time indicator on improving the differentiation of user legitimacy in the case of password-stolen attacks. The research methodology, which involves analyzing and evaluating existing authentication methods in web-based systems, is a key component of this study. The study is divided into stages, with the first phase focusing on enhancing the existing EPSB model, the second phase implementing EPSBalgorithmV01, and the final stage ensuring validation. Thus, two preliminary experiments were conducted with 22 users from January 13 to February 1, 2024. The final phase involved comparing EPSBV01's accuracy in determining unauthorized users before and after using the ARIMA method. Thus, the EPSBV01algorithm successfully identified 17 unauthorized users during a stolen password attack simulation, outperforming the normal EPSB by 22.73%. Doi: 10.28991/ESJ-2025-09-01-014 Full Text: PDF
Mediating Role of Information Flow in Enhancing Nursing Service Quality and Patient Satisfaction Huang, Ying; Ali, Dhakir Abbas; Wang, Shuangshuang; Zhang, Rongmei
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-09

Abstract

Patient satisfaction is a key factor in the success of hospitals worldwide, making it an important focus for contemporary research. This study aims to examine the impact of service quality, employee satisfaction, and the organizational environment on patient satisfaction in Chinese hospitals. Additionally, it investigates the mediating role of information flow in the relationships between service quality, employee satisfaction, the organizational environment, and patient satisfaction in Chinese hospitals. Data for the study was collected through survey questionnaires administered to patients in government hospitals in China. The reliability of the data and the relationships among the constructs were analyzed using Smart-PLS software. The findings revealed that service quality, employee satisfaction, and the organizational environment positively influence patient satisfaction in Chinese hospitals. Moreover, the results indicated that information flow significantly mediates the relationships between service quality, employee satisfaction, the organizational environment, and patient satisfaction. These findings provide valuable insights for policymakers, offering guidance on strategies to enhance patient satisfaction by focusing on improving service quality, ensuring effective information flow, and fostering a positive organizational environment. Doi: 10.28991/ESJ-2025-09-01-09 Full Text: PDF
A Novel Approach to Enhancing the Effectiveness of Chemistry Teaching by Preservice Teachers Meirbekov, Akylbek; Berdi, Dinara; Burayeva, Zhanat; Ikramov, Ilyas; Sarbaeva, Makpal
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-04

Abstract

The objective of this article is to develop a new approach for improving the effectiveness of chemistry teaching, which involves transforming the teaching process via the use of interactive digital technologies. The research methodology is based on the Self-Determination Theory (SDT) and the Stimulus-Organism-Response (SOR) model. The study explores key constructs such as Perceived Usability (PU), Perceived Autonomy (PAU), Perceived Teaching Support (PTS), Perceived Competency (PCM), Perceived Relatedness (PRT), Perceived Ease of Use (PEOU), Cognitive Teaching Involvement (CTI), and Affective Teaching Involvement (ATI), examining their influence on teaching performance. Data were collected from 254 preservice chemistry teachers trained at Akhmet Yassawi International Kazakh-Turkish University, Kazakhstan. Structural equation modeling (SEM) was applied to test the scientific hypotheses. The findings showed that PU, PEOU, PAU, and PTS have a significant effect on CTI and ATI, which in turn have a positive effect on teaching effectiveness. In other words, the study confirms the importance of user-friendly and effective digital tools in developing positive attitudes towards technology adoption. The novelty of this paper comprises the author's concept of the educational process transformation through the usage of interactive digital technologies, which increases the chemistry education effectiveness. Doi: 10.28991/ESJ-2025-09-01-04 Full Text: PDF
Intelligence Based Controlling Models for Effective Power Tracking and Voltage Enhancement in Grid-PV Systems Naidu, I. E. S.; Padmavathi, T.; Padmavathi, S. Venkata; Kumar, Budidi U.
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-015

Abstract

The underlying research work is focused on enhancement in the efficiency and voltage gain for solar PV systems with the help of designing a novel regulating framework that includes advanced converter topologies integrated with intelligent control techniques. Optimization in extracting energy from the solar panel at different climatic conditions, voltage gain with minimum losses, and enhancing overall system efficiency and power quality are major tasks to be undertaken. The proposed control architecture presents a new Fractional Order Proportional-Integral-Derivative Control (FOPTC) technique and its adaptation mechanism for correct MPPT under dynamic variations of meteorological conditions. Consequently, it offers improved energy harvesting because it is able to identify the global maximum power point with higher speed and precision than traditional control techniques that apply hybrid approaches. The improved topological structure will ensure a substantial rise in voltage gain and efficiency with reduced voltage and current stresses upon the circuit components. In addition, the idea of a Neuro Feed Quadratic Controller (NFQC) is introduced to generate the regulating pulses for switching components of the converter for optimizing the voltage conversion process. Simulation and analytical studies confirm the higher efficiency, improved voltage gain, and reduced total harmonic distortion in the proposed framework over conventional systems. Doi: 10.28991/ESJ-2025-09-01-015 Full Text: PDF
Pioneering the Security of EHRs Using an Immersive Blockchain Conceptual Framework Benaich, Rihab; Gahi, Youssef; El Mendili, Saida
Emerging Science Journal Vol 9, No 1 (2025): February
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-01-010

Abstract

This study develops a conceptual framework to enhance the security and functionality of Electronic Health Records (EHRs) in response to advancing healthcare needs. Objectives include strengthening data protection against both traditional and quantum cyber threats, increasing system resilience, and improving user experience and operational efficiency. Methods/Analysis involve a novel combination of Advanced Encryption Standard (AES) and quantum cryptographic algorithms CRYSTALS-Dilithium and CRYSTALS-Kyber within a hybrid blockchain architecture to secure EHRs. Decentralized Autonomous Organizations (DAOs) are incorporated to decentralize control and reinforce security, while artificial intelligence and metaverse integration facilitate user engagement and streamline operations. Findings indicate that this hybrid blockchain model, enhanced with quantum-resistant cryptography and decentralized governance, significantly improves EHR security. AI and the metaverse contribute to user interaction and operational flow. Novelty/Improvement lies in integrating hybrid blockchain, quantum cryptography, AI, and the metaverse into a unified framework, effectively addressing current and future healthcare data management challenges. This multi-layered approach represents a significant advancement over existing systems by bolstering EHR security, user engagement, and operational capabilities. Doi: 10.28991/ESJ-2025-09-01-010 Full Text: PDF

Page 71 of 81 | Total Record : 803

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