Suranaree Journal of Science and Technology

AN EFFICIENT HOMOMORPHIC ENCRYPTION AND PUF AUTHENTICATION WITH SWO-QBFT CONSENSUS ALGORITHM FOR SECURE SMART GRID INFRASTRUCTURE

Prasanna Kumar Mallikarjunaiah — 2025-11-10

Smart grid is an advanced electrical infrastructure that incorporates communication and information technologies to enable power firms and consumers to exchange data in bidirectional. However, there are serious security risks associated with relying on an unsecured open network. To overcome the drawbacks, an efficient HEAAN-PUF based IoT device authentication with SWO-QBFT for smart grid infrastructure has been proposed. Initially IoT device is registered and authenticated using Physical Unclonable Function (PUF) authentication, which provides a unique response for each device with an Interplanetary File System (IPFS). Homomorphic Encryption for Arithmetic of Approximate Numbers (HEAAN) cryptography algorithm was then utilized to generate the key for encrypting the data and stored in IPFS. Blockchain based on consensus algorithm as Spider Wasp Optimization (SWO) with Quorum Byzantine Fault Tolerance Protocol (SWO-QBFT) utilized to choose the best validators for secure data transmission and stored an IPFS hash address. Performance metrics-based analysis and comparison of the proposed HEAAN-OQBFT technique with existing approaches are conducted. Performance metrics like encryption and decryption times, key and block generation times, throughput, Packet Delivery Ratio (PDR), and Packet Loss (PL) are acquired in order to determine the performance of the proposed method. Time required for Block creation, encryption, decryption, and key generation takes up 0.19 ms, 0.013 ms, 0.023 ms and 0.93 ms with is 497 Kbps throughput, 1% packet loss, and 99% PDR. The metrics therefore clearly show that the proposed method successfully stores and secures smart grid data by integrating OQBFT with an effective HEAAN cryptography.

IDENTIFYING THE HAZARDOUS LOCATIONS USING GEOGRAPHIC INFORMATION SYSTEM NETWORK ANALYSIS: A CASE STUDY OF BUENG KAN PROVINCE, THAILAND

Panuwat Wisutwattanasak — 2025-11-07

This study aims to identify high - crash - risk locations on local roads in Bueng Kan province, Thailand, using Geographic Information System (GIS) - based spatial analysis. Despite being Thailand’s newest and one of its least populated provinces, Bueng Kan consistently reports one of the highest fatality rates per capita, highlighting the urgency of evidence-based road safety planning. The study employed Kernel Density Estimation (KDE) to detect spatial concentrations of road crashes and a Chi-square test to assess whether crash severity proportions differed significantly across districts. Crash data from 2018 to 2020 were collected, georeferenced using linear referencing techniques, and analyzed in ArcMap. KDE was applied to generate crash density surfaces. The KDE results revealed spatially distinct crash hotspots in five districts, with Seka district showing the highest crash density despite Mueang Bueng Kan recording the highest number of incidents. This underscores the importance of considering spatial overlap-not just frequency-in identifying hazardous areas. Chi-square test found no statistically significant difference in the proportion of fatal versus non-fatal crashes among districts (p = 0.403), suggesting that crash severity is spatially uniform. This supports the need for province-wide interventions rather than district-specific responses. The integrated use of KDE and statistical testing provides a robust analytical framework for supporting local traffic safety strategies. Recommendations include incorporating exposure data and advanced modeling techniques in future studies to improve risk prediction and policy development.

FACTORS AFFECTING FIELD SETTLEMENT EVALUATION OF PREFABRICATED VERTICAL DRAINS PERFORMANCE IN SOFT BANGKOK CLAY BY ASAOKA AND HYPERBOLIC METHODS

Sinat Koslanant — 2025-11-10

The study highlights the importance of these factors in field settlement evaluation and back-calculating the horizontal drainage consolidation coefficient in Bangkok clay. Longer evaluation periods induce higher ultimate settlement and lower consolidation degrees with the Asaoka method, while the Hyperbolic method predicts constant values. The coefficient of consolidation in horizontal drainage back-analyzed by the Asaoka method decreases with longer evaluation periods but is similar to CRS-R at the final stress level. Both methods’ predicted settlement versus time curves agree well with field curves, especially for longer evaluation periods. Therefore, the paper recommends adopting the settlement versus time curves predicted by both methods for their simplicity and proficiency in practice. These findings provide valuable insights for evaluating the degree of consolidation and improving soft clay using prefabricated vertical drains, especially in areas with similar soil conditions.

IMPROVEMENT OF INVENTORY MANAGEMENT SYSTEM: CHEMICAL RAW MATERIALS FOR HEALTHCARE AND PERSONAL CARE PRODUCTS MANUFACTURER

Thitima Wonginta — 2025-11-11

This research presents a case study examining the optimization of the inventory management system for a manufacturer of healthcare and personal care products within the fast-moving consumer goods (FMCG) industry. The study's objective is to enhance the inventory management process by employing the VED-FSN-SDE classification approach to prioritize and categorize items within an analytical framework. Following this classification, inventory management policies were established using the Economic Order Quantity (EOQ) model and the Silver-Meal heuristic method. The findings indicate that for the EFE category, where the variability coefficient (VC) was less than 0.2, the EOQ model was appropriate, resulting in a 27.42% reduction in annual inventory costs. For the DFD category, characterized by a VC greater than 0.2, the Silver-Meal heuristic method was applied, leading to a 35.99% reduction in inventory costs. These results demonstrate the effectiveness of the applied models in achieving significant cost savings and improved inventory efficiency. The practical implications of this study suggest that adopting tailored classification and control techniques can enable managers to optimize inventory levels, reduce costs, and enhance overall supply chain performance in the competitive healthcare and personal care products industry.

ANALYSIS AND MITIGATION OF DELAY RISKS IN THE CONSTRUCTION OF THE CENTRAL SURGICAL INSTALLATION BUILDING USING THE HOUSE OF RISK METHOD

Hafnidar Rani — 2025-11-10

One of the ongoing construction projects in Banda Aceh City is the Central Surgical Installation Building at Meuraxa Regional General Hospital. However, based on contractor observations, this project has experienced delays beyond the planned schedule. This study identifies the factors contributing to these delays using the House of Risk (HOR) method and explores mitigation strategies. The research involved a questionnaire survey with 20 respondents, which included contractors and supervising consultants. The study examined six key delay factors: planning and scheduling (E1), work documents (E2), control systems (E3), resource readiness (E4), financial delays (E5), and material delays (E6). The HOR Phase 1 analysis identified three primary risk agents: inaccurate project specifications (A1) with an ARP value of 180, slow administrative processes (A2) with 128, and unreliable cost estimation (A3) with 108, all contributing significantly to project delays. In HOR Phase 2, five mitigation strategies were proposed, including improving communication with the project owner (PA1), expediting administrative processes (PA2), developing a detailed cost estimation framework (PA3), optimizing material procurement and supplier coordination (PA4), and allocating additional workforce and equipment (PA5). These actions aim to minimize risks and enhance project efficiency. By implementing these mitigation strategies, construction delays can be effectively reduced, ensuring timely project completion. This study highlights the importance of structured risk management in construction projects and provides valuable insights for contractors, project managers, and policymakers.

HYDROLOGICAL IMPLICATIONS OF USING RECYCLED ASPHALT PAVEMENT AND WASTE-BASED REJUVENATORS IN SUSTAINABLE INFRASTRUCTURE

Suraj Kalgonda Patil — 2025-11-10

The depletion of natural resources has accelerated the demand for sustainable solutions in urban infrastructure, especially concerning hydrological impacts. This study explores the influence of Recycled Asphalt Pavement (RAP), in combination with rejuvenators such as Waste Cooking Oil (WCO) and Waste Engine Oil (WEO), on surface runoff and water infiltration behavior in urban environments. Aimed at restoring aged bituminous binder properties, the research involves comprehensive physical, chemical, and rheological analyses to ensure pavement durability while enhancing hydrological performance. Experimental findings show that WCO significantly improves the rheological and physical characteristics of aged asphalt binders, enhancing flexibility and reducing surface impermeability. Fourier Transform Infrared Spectroscopy (FTIR) confirms chemical compatibility between VG 30 bitumen and the rejuvenators, ensuring effective binder blending. Dynamic Shear Rheometer (DSR) tests indicate that aging increases stiffness, as evidenced by a higher complex shear modulus and lower phase angles. However, WCO rejuvenation effectively reverses this, achieving a peak shear stress of 120 kPa at 10% strain, outperforming the 80 kPa at 5% strain for WEO-modified RAP. Hydrological assessments reveal that RAP mixtures with 4% WCO improve infiltration rates by 12–15% and reduce surface runoff by approximately 10% compared to conventional pavements. These outcomes underscore the dual benefits of RAP and WCO in sustainable pavement design-enhancing structural performance while supporting urban stormwater management. The study establishes a clear linkage between environmentally conscious pavement technologies and improved urban hydrology, promoting the adoption of RAP-based pavements in climate-resilient infrastructure planning.

MATHEMATICAL MODEL OF HYDROGEN POWERED BICYCLE ELECTRIFICATION

Kitsada Thongaram — 2025-11-11

Mathematical modeling plays a crucial role in the study of system behavior, design, and analysis of power systems. This paper presents the development of a time-invariant mathematical model for the power system of a hydrogen-powered electric bicycle. The mathematical model is derived based on the General State-Space Averaging (GSSA) method. The model is validated through computer-based simulation using MATLAB/SIMULINK. The simulation results demonstrate that the system responses obtained from the proposed model are in good areement with those from the simulation, under both transient and steady-state conditions. Furthermore, the use of the developed mathematical model significantly reduces computation time compared to direct simulation. Consequently, the proposed model is both accurate and efficient. The proposed averaging model is also suitable for artificial intelligence applications requiring iterative searching due to its fast computational time.