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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 837 Documents
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Leaving No One Behind in Access to Higher Education in the Baltic States and Poland Pikturnaitė, Ilvija; Paužuolienė, Jurgita; Mironova, Julija; Karczewska, Małgorzata
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-017

Abstract

The article presents research on the accessibility of higher education in the Baltic States and Poland and its compliance with the principle of “Leaving No One Behind”. A qualitative approach was used to achieve the research objective using analysis of statistical indicators and the contents of documents. The results of the study reveal that the progress on higher education attainment is not homogeneous and not consistent in the countries analyzed. Document analysis indicates that higher education accessibility differs across Lithuania, Latvia, Estonia, and Poland. Lithuania and Latvia are the most accessible due to unified application systems, while Poland lacks such a system, creating extra costs and delays. A comparison of the mandatory examinations and minimum requirements set by the countries shows that Lithuania has the highest barriers to access to higher education: people with lower results or learning gaps in secondary education are deprived of the opportunity to acquire higher education, and their chances of avoiding falling behind are lower. Lithuania does not provide for exceptions for the admission of people with disabilities: they must meet the same requirements as other applicants. Another group of people who may face exclusion in Lithuania, Latvia, and Poland are members of national minorities. These results suggest that the governments of the countries and universities need to be more inclusive in their admission policies.
Influence of Digital Infrastructure on Project Management Success: Readiness, Fitness, and Tools as Moderators Khasawneh, Mohammad Awni; Dweiri, Fikri
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-024

Abstract

In an era defined by rapid digital transformation, project-based organizations face increasing pressure to modernize and digitalize their operational frameworks to ensure competitive advantage and Project Management Success. However, only limited research has examined how foundational pillars of digital infrastructure interact and jointly influence project outcomes, leaving a gap in understanding the structural pathways that link digital infrastructure to Project Management Success and informed decision-making. This study investigates how the three pillars of digital infrastructure (Digital Readiness, Digital Fitness, and Digital Tools) jointly and individually influence Project Management Success through applying Partial Least Squares Structural Equation Modeling (PLS-SEM) to analyze survey data collected from experienced project management professionals who possess appreciable experience in digital technology systems and digital transformation leadership. The developed model captures both direct effects of the Digital Infrastructure Pillars on Project Management Success and the moderation effects between them. The results show that all three pillars significantly enhance Project Management Success, with Digital Readiness emerging as the most influential strategic enabler. Moreover, Digital Readiness positively moderates the effect of Digital Tools on Project Management Success, indicating that digital technology investments are more effective when supported by foundational digital preparedness. These findings offer a validated framework for assessing digital maturity in project environments and provide strategic and leadership guidance for organizations seeking to enhance project performance and achieve Project Management Success through balanced investment in digital infrastructure, integrated digital transformation strategies, digital technology adoption, and digital competencies.
Evaluating Sensitivity of Double EWMA Chart for ARL Under Trend SAR(1) Model and Applications Areepong, Yupaporn; Karoon, Kotchaporn
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-026

Abstract

The goal of this study is to offer the precise average run length (ARL) on the Double Exponentially Weighted Moving Average (double EWMA) control chart for the data underlying the first-order seasonal autoregressive (SAR(1)L) with trend model. A comparison was made between the explicit formula and the computed ARL obtained using the numerical integral equation (NIE) approach, employing four quadrature methods: the midpoint, Simpson’s, trapezoidal, and Boole’s rules. The comparison was based on accuracy percentage (%Acc) and computation time (in seconds). The results showed that there was not much variation in accuracy between the ARL results of the explicit ARL and ARL via the NIE method. The findings indicate that the explicit ARL and NIE approaches produce very consistent accuracy values; however, the explicit formula is significantly more rapid (instantaneous compared to 1.5–26 seconds). The advantage of the double EWMA chart compared to the extended EWMA chart in identifying process changes is demonstrated, encompassing evaluations under both one-sided and two-sided setups with varied LCL values. The results are additionally corroborated by sensitivity measures (AEQL, PCI, RMI) and checked with actual durian export data, guaranteeing that the conclusions are firmly established in both simulated and empirical evidence.
Development of Control and Measurement Procedures for Geometrically Complex Surfaces Alexandrov, Islam A.; Karpov, Nikita S.; Ivanov, Naur Z.; Lampezhev, Abas H.; Titova, Anastasia P.
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-08

Abstract

This study aims to develop and automate control and measurement procedures for parts with complex geometric surfaces under multiproduct manufacturing conditions. By integrating combinatorial analysis, statistical testing, and probe trajectory optimization into a unified framework, the proposed methodology formalizes measurement planning within an automated system. The actual dimensional characteristics of each workpiece are determined at the design stage, enabling the adaptation of the technological process to specific components. Experimental validation was performed on a FARO 9 ARM coordinate measuring machine using six types of complex parts, and statistical testing was performed to identify the optimal number of control points (108) with a minimum measurement time of 72 min per part. The methodology achieved a defect rate reduction of 5% and demonstrated an annual cost savings of 641,172 Rubles. This study integrates control point selection, probe trajectory planning, and measuring instrument choice into a single automated system that adapts to actual workpiece geometry, advancing Metrology 4.0 principles. The proposed approach significantly improves performance compared with conventional methods, reducing metrological preparation time by 76%, lowering defect rates by 50%, and decreasing the number of measurement operations by over 40%. These results confirm the potential of the methodology for enhancing productivity and economic efficiency in digital manufacturing environments.
FedBHAD: Energy-Efficient Federated Learning for Black Hole Attack Detection in RPL-Based Low-Power IoT Networks Mathi, Senthilkumar; Rohan Lal, Gudivada; Madala, Lokesh Chowdary; Reddy, Karri Ammi; Jagadhabhiram, Putta; Neelakanta Iyer, Ganesh
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-01

Abstract

The internet of things is a network of connected devices that share and send information over the internet, frequently in resource-constrained situations. These are often built using the routing protocol for low-power and lossy networks (RPL), face significant security problems because of their limited computing power, and have energy constraints. The objective of this study is to design an efficient and lightweight mechanism for detecting black hole attacks on RPL-based internet of things networks. The proposed framework presents a distributed collaborative learning framework to reduce the processing load on central nodes while enhancing real-time threat detection. The novelty of the present work lies in integrating distributed learning with feature-based anomaly detection tailored for RPL environments, thereby improving IoT network security while reducing communication and energy overhead. A customized data retrieval algorithm is developed with the Cooja simulator’s configuration and extracts essential network parameters, including rank, expected transmission count, power consumption, forward count, and reception count. The analysis of this dataset allows the detection of black hole attacks. The research analysis indicates that the proposed framework achieves 99.6% detection accuracy, surpassing existing machine learning and deep learning techniques and offering enhanced security, reduced overhead, and lower computational needs.
Enhancing Math Skills in Children with Learning Difficulties Using Smartphone Apps Al-Barakat, Ali A.; AlAli, Rommel M.; Al-Hassan, Omayya M.; Alakashee, Bushra A.; Aboud, Yusra Z.; Abdullatif, Ali K.
Emerging Science Journal Vol. 9 (2025): Special Issue "Emerging Trends, Challenges, and Innovative Practices in Education"
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-SIED1-021

Abstract

This study aimed to examine the effectiveness of smartphone applications in enhancing the acquisition of mathematical concepts among children with learning difficulties. The research involved 80 students from private schools in northern Jordan, randomly assigned to an experimental group, which received instruction through smartphone and tablet applications, and a control group, which followed conventional teaching methods. Pre- and post-intervention cognitive assessments were conducted over a 12-week instructional period to measure mathematical understanding. The results revealed that students in the experimental group showed a significant improvement in mathematical performance compared to the control group. Furthermore, no statistically significant differences were found between male and female students, and no interaction effect between gender and instructional method was observed, indicating equitable outcomes across genders. The study highlights that smartphone-based educational applications provide an interactive, adaptive, and supportive learning environment that caters to the specific needs of students with learning difficulties. The novelty of this research lies in demonstrating the practical benefits of integrating digital tools into mathematics instruction, supporting constructivist and inclusive learning approaches, and offering evidence-based strategies to enhance student engagement and conceptual understanding. These findings suggest that technology-enhanced learning can effectively supplement traditional methods, promoting improved academic performance and inclusive educational practices.
Retrieval-Augmented Generation Assistant for Anatomical Pathology Laboratories Pires, Diogo; Perezhohin, Yuriy; Castelli, Mauro
Emerging Science Journal Vol. 9 No. 6 (2025): December
Publisher : Ital Publication

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.28991/ESJ-2025-09-06-013

Abstract

Accurate and efficient access to laboratory protocols is essential in Anatomical Pathology (AP), where up to 70% of medical decisions depend on laboratory diagnoses. However, static documentation such as printed manuals or PDFs is often outdated, fragmented, and difficult to search, creating risks of workflow errors and diagnostic delays. This study proposes and evaluates a Retrieval-Augmented Generation (RAG) assistant tailored to AP laboratories, designed to provide technicians with context-grounded answers to protocol-related queries. We curated a novel corpus of 99 AP protocols from a Portuguese healthcare institution and constructed 323 question-answer pairs for systematic evaluation. Ten experiments were conducted, varying chunking strategies, retrieval methods, and embedding models. Performance was assessed using the RAGAS framework (faithfulness, answer relevance, context recall) alongside top-k retrieval metrics. Results show that recursive chunking and hybrid retrieval delivered the strongest baseline performance. Incorporating a biomedical-specific embedding model (MedEmbed) further improved answer relevance (0.74), faithfulness (0.70), and context recall (0.77), showing the importance of domain-specialized embeddings. Top-k analysis revealed that retrieving a single top-ranked chunk (k=1) maximized efficiency and accuracy, reflecting the modular structure of AP protocols. These findings highlight critical design considerations for deploying RAG systems in healthcare and demonstrate their potential to transform static documentation into dynamic, reliable knowledge assistants, thus improving laboratory workflow efficiency and supporting patient safety.

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