Emerging Science Journal (ESJ)
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Structural Equation Modeling of Factors Affecting Accountability-Based Accounting in Public Sector Entities
No full textObjectives: This study aims to identify factors influencing accountability-based accounting and propose a conceptual framework for public-sector accounting to enhance decision-making and accountability. Methods/Analysis: Conducted in Vietnam in 2023, the research employs quantitative analysis of survey data collected from 492 civil servants across 282 public entities, using SmartPLS for structural equation modeling. Findings: There are significant positive correlations between accountability-based accounting and four key factors: accrual-based accounting, felt accountability, information disclosure, and financial report quality. Among these, accrual-based accounting exerts the most substantial direct influence on the use of accounting information for accountability purposes. Felt accountability demonstrates direct and indirect effects, mediating relationships between other factors. The study highlights that effective accountability requires account givers to align with account holders’ needs, legitimacy, and expertise, while accrual-based accounting must prioritize improving user comprehension and usability of information. Novelty/Improvement: Transparency and publicity are critical for ensuring public-sector accounting information is reliable, relevant, and actionable. The proposed framework advances public-sector accounting theory by integrating accountability as a foundational principle, offering practical guidance for policymakers to strengthen accountability mechanisms. This research contributes a novel perspective by empirically validating the interplay of accounting components within an accountability-centric model, providing a basis for future conceptual and regulatory developments in public sector
Machinery Usage and Productivity in Manufacturing: Firm-Level Matter in Developing Countries
No full textThis study examines the determinants of machinery usage and its relationship with productivity outcomes among Vietnamese manufacturing firms, using nationally representative panel data from 2010 to 2019. A multinomial logit model and panel regressions with first- and second-differences reveal substantial heterogeneity in machinery choices, reflecting differences in firm size, ownership, and sectoral contexts. Medium and large enterprises tend to use computer-controlled machinery and are more likely to exhibit positive associations with labor productivity, although these effects often diminish over time. In contrast, micro and small firms remain reliant on handheld tools and show mixed or short-lived productivity gains. Foreign-invested enterprises demonstrate more consistent productivity benefits from advanced machinery than state-owned firms. These findings suggest that sustained productivity improvements require more than technological upgrades alone. The study highlights the potential importance of complementary investments – such as workforce development, managerial capacity, and institutional support – for fostering inclusive and effective machinery usage. These insights may inform targeted policy efforts aimed at narrowing technology gaps across heterogeneous firms in developing economies
Investigating High School Student Misconceptions: A Rasch-Based Three-Level Diagnostic Evaluation of Osmoregulation and Excretion Systems
No full textThis study aimed to develop and validate a three-tier multiple-choice diagnostic assessment instrument to identify misconceptions related to osmoregulation and the excretion system among Indonesian high school students. A total of 281 students from West Sumatra and Jambi Province participated in the research. Employing a quantitative approach, the psychometric properties of a 20-item test were analyzed using Rasch modeling. The analysis revealed that the instrument had strong item reliability (0.84), though person reliability was relatively low (0.55), indicating variability in students’ response consistency. Despite this, the test demonstrated high internal consistency, as shown by a Cronbach's Alpha of 0.90. The mean student ability level (-2.37) was significantly lower than the item difficulty level (0.00), suggesting widespread conceptual gaps among participants. All items met the model’s expectations, with average Outfit Mean Square (MNSQ) at 1.02 and Z-Standard at 0.1. The findings highlight the diagnostic tool’s effectiveness in detecting prevalent misconceptions in biology education. This study contributes to the field by offering a structured and psychometrically sound instrument, supporting more targeted instructional strategies to enhance conceptual understanding in science education
Enhanced Optimization Strategy to Maximize Achievable Rate of Millimeter-Wave Full-Duplex UAV on Multiple User
Full text linkThis study proposes an enhanced optimization strategy to maximize the achievable data rate of millimeter-wave (mmWave) full-duplex (FD) unmanned aerial vehicles (UAVs) in multi-user scenarios. The objective is to address signal degradation from high-frequency path loss and self-interference while ensuring efficient resource allocation across multiple user equipment (UEs). A joint optimization framework is introduced, integrating UAV positioning, beamforming vector design at both the gateway and UAV, and power allocation. Initially, the Alternating Interference Suppression (AIS) algorithm is adapted for multiple UEs, but due to emerging non-convexity, the problem is reformulated using a first-order approximation approach. The solution is decomposed into two iterative sub-problems—optimizing UAV location and then solving for beamforming and power distribution. MATLAB-based simulations validate the proposed approach, revealing a threefold increase in achievable data rate and a 40.85% improvement in power efficiency compared to non-optimized systems. The novelty of this work lies in its scalable multi-user adaptation and its integrated, power-aware optimization algorithm, outperforming conventional FD and half-duplex strategies. This contribution significantly advances the design of efficient, high-throughput UAV communication systems for next-generation wireless networks, especially in environments with frequent line-of-sight obstructions
Multi-Objective Optimization of Injection Molding Using Taguchi, Fuzzy Methods, and GA
No full textThe objective of this research is to optimize the injection molding process of an automotive window regulator bracket by improving the moldability index while minimizing key defects. To achieve this, a multi-objective framework is developed that combines the Taguchi method with Fuzzy Analytic Hierarchy Process (FAHP) and Fuzzy-TOPSIS. Five critical processing parameters—melt temperature, mold temperature, filling time, holding pressure time, and cooling time—were investigated, with polypropylene as the base material. A Taguchi L25 orthogonal array was employed to reduce the number of experimental trials from 3,125 to just 25, thereby saving resources while maintaining reliability. The evaluation considered warpage, residual stress, and shear stress, which are the most influential defects affecting part performance. Finite Element Analysis (FEA) was incorporated to validate the accuracy of the results, while a hybrid ANFIS-GA predictive model was applied to forecast the moldability index, demonstrating an improvement of about 1% over conventional optimization methods. The optimized settings resulted in minimized warpage (1.8122 mm), residual stress (43.03 MPa), and shear stress (0.08 MPa). The novelty of this work lies in integrating Taguchi with FAHP and Fuzzy-TOPSIS for a single-objective transformation, offering a systematic and efficient approach for multi-objective optimization in injection molding applications
Driving Mangrove Recovery: Community Engagement and Socio-Economic Shifts in Aquaculture Areas
Full text linkLand-use change and recovery patterns of mangroves in the Tha Sak subdistrict, Nakhon Si Thammarat, Thailand, were examined utilizing multi-temporal Landsat images and socio-economic data from 1988 to 2023. Land use was classified through visual interpretation, and potential changes were predicted using a Markov chain model. The results showed a significant expansion of mangrove forests (1.11 km² to 9.10 km²), indicating a clear recovery. At the same time, the aquaculture area decreased drastically (from 25.69 km² to 8.79 km²), indicating a significant change in land use. The recovery of mangroves is primarily attributed to the cessation of aquaculture and the active involvement of the Tha Sak subdistrict's Small-Scale Fishermen Group, highlighting the success of community-based restoration. This study provides evidence of the critical role local communities play in bringing about positive environmental change and enabling Sustainable Development Goals (SDGs) 15: Life on Land from ecosystem restoration, SDG 14: Life Below Water for conservation of coastal areas, and SDG 11: Sustainable Cities and Communities for increasing community resilience. Involving local communities in mangrove restoration and preservation is key to long-term sustainability
Predicting EFL Students’ Use of Artificial Intelligence Tool in Advancing Their Writing Skills
No full textThis study examines the factors influencing the adoption and use of artificial intelligence (AI) tools to enhance writing skills among English as a Foreign Language (EFL) learners in Oman, guided by the Unified Theory of Acceptance and Use of Technology (UTAUT). The objectives were to assess the impact of performance expectancy, effort expectancy, social influence, and facilitating conditions on students’ behavioral intention and actual AI usage, and to test the moderating role of prior AI experience. A cross-sectional quantitative design was employed, with data collected from 255 undergraduate female EFL students through a validated questionnaire. Structural equation modeling (SEM) and confirmatory factor analysis were used to validate the measurement model and test hypothesized relationships. Findings indicate that behavioral intention and facilitating conditions significantly predicted actual AI tool use, while performance expectancy, effort expectancy, and social influence strongly shaped behavioral intention. Mediation tests confirmed that behavioral intention served as a key pathway linking UTAUT constructs to actual adoption, and moderation analysis showed that prior AI experience strengthened the intention–usage relationship. This research contributes to a context-specific, evidence-based framework for AI adoption in EFL writing, offering novel insights for educators, institutions, and technology designers to integrate AI ethically and effectively in language learning
Rateless Polar Codes Exploiting Repetition Coding Principle with EXIT Analysis for Broadband Transmissions
No full textThis paper proposes a novel design of polar codes for rateless transmissions employing extended parity (EP) to enhance performance under broadband channel conditions. The idea of the proposed design is to achieve diversity across all samples by employing simple butterfly XOR operations, which inherently support rateless broadband transmissions. In particular, the design exploits the principle of repetition, where simple XOR operations do not only contribute to error protection but also strengthen the polarization effect and reinforce the rateless property of polar codes. The proposed codes are evaluated over Rayleigh fading, fully interleaved, and additive white Gaussian noise (AWGN) channels. The results show that the proposed codes achieve significant performance improvements, particularly in AWGN and fully interleaved environments, thereby confirming that the use of XOR operations effectively enhances transmission reliability. Furthermore, the proposed codes are investigated through extrinsic information transfer (EXIT) analysis using closed-form expressions. The analysis reveals that the decoding process exhibits faster convergence when EP is employed. In addition, computational complexity analysis shows that the additional overhead introduced by EP remains minimal. Importantly, the proposed structure preserves the standard polar transform and decoding graph, ensuring scalability similar to conventional polar codes. Hence, the proposed design balances performance and computational efficiency, making it a compelling solution for broadband scenarios and dynamic channel environments
Cost-Effective Manufacturing of Microfluidics Through the Utilization of Direct Ink Writing
Full text linkMicrofluidics is essential for precise manipulation of fluids in small channels. However, conventional manufacturing processes for microfluidic devices are expensive, time-consuming, and require specialized equipment in a clean room. While recent studies have improved the cost-effectiveness of this device, there is still a need for further advancement in cost efficiency. Therefore, this study aimed to develop a custom-built direct-ink writing (DIW) printer for manufacturing microfluidic devices that is more affordable. Custom-built DIW directly printed microfluidic channels onto microscope slide glass using RTV (Room Temperature Vulcanizing) silicone sealant. To finish the microfluidics manufacturing, the printed channel will be assembled by placing the same glass on top of the printed layer. This method eliminated the need for polydimethylsiloxane (PDMS) molds and casting processes that were still found in recent studies. This innovative 0.071 (USD) compared to $0.90 (USD) in previous studies. This study makes microfluidics more affordable and accessible for biomedical use. Doi: 10.28991/ESJ-2025-09-01-01 Full Text: PD
Effect of Antenna Polarization Arrangement on MIMO Channel Capacity
Full text linkThis study investigates the effect of antenna polarization configurations on the channel capacity of Multiple-Input Multiple-Output (MIMO) systems. Theoretical modeling and computational simulations are conducted to examine the impact. The theoretical model is predicated on a MIMO arrangement with a half-wavelength Dipole antenna as the MIMO element. The influence of antenna polarization on MIMO capacity is expressed via mutual impedance as a function of antenna polarization. Theoretical and simulation results indicate that antenna polarization influences the capacity of MIMO channels. Cross-polarized antenna arrays provide enhanced polarization by optimizing polarization diversity. Research on large-scale MIMO systems suggests that the selection of antenna polarization significantly influences MIMO channel capacity. The polarization configuration substantially influences MIMO capacity under high SNR scenarios. An appropriate polarization configuration enhances MIMO channel capacity at low signal-to-noise ratio (SNR) more efficiently than inappropriate polarization. This may be advantageous in mitigating capacity degradation resulting from low SNR levels. Furthermore, the research findings indicate that the antenna polarization configuration is essential in designing massive MIMO antennas comprising several antennas. In creating a massive MIMO antenna, achieving the ideal polarization configuration of the antenna elements is critical to ensure that increases in the number of antennas correlate with the optimum channel capacity. Doi: 10.28991/ESJ-2025-09-02-028 Full Text: PD