Science & Technology Asia

The Effectiveness of Mixed Non – Parametric Process Monitoring Charts based on Tukey for ZIB and ZIP Processes

Saowanit Sukparungsee — 2026-06-30

This study examines the application of non-parametric Tukey-based control charts to address the limitations of standard control charts in monitoring high-yield manufacturing processes that frequently exhibit zero counts. Specifically, it compares the Tukey control chart (TCC), Tukey-based mixed exponentially weighted moving average - moving average control chart (TEMCC), and Tukey-based mixed moving average - exponentially weighted moving average control chart (TMECC) in their ability to detect parameter shifts in zero-inflated binomial and Poisson (ZIB/ZIP) processes, better suited for this data type. Through a Monte Carlo simulation, TMECC demonstrated superior performance in detecting process changes, especially under high zero inflation. A case study highlights the practical advantages of utilizing ZIB and ZIP models for enhanced quality control in manufacturing environments.

Cyclic Behavior and Microstructure of Recycled Concrete Aggregate as a Pavement Base Layer

Chokchai Traiyasut — 2026-06-30

Mechanical analysis of resilient and permanent deformation is critical for pavement design and construction, as repeated traffic loading is the primary factor influencing material stability. This study investigates the cyclic mechanical behavior and microstructural characteristics of Recycled Concrete Aggregate (RCA) to evaluate its suitability as a sustainable pavement base material. Geotechnical characterization classified the RCA as a well-graded gravel (GW) adhering to Department of Highways Thailand Type D specifications, with a maximum dry unit weight of 18.85 kN/m³. Multi-stage repeated load triaxial testing was performed to determine resilient modulus and permanent deformation characteristics under varying deviatoric stress states. Results indicated that the RCA exhibits a robust resilient modulus ranging from 125 to 260 MPa. Based on Werkmeister’s and shakedown theory, the material remained within the stable Plastic Creep zone (Range B) across all loading stages (150–450 kPa), demonstrating high resistance to incremental collapse. Scanning Electron Microscopy (SEM) and X-ray Diffraction (XRD) analyses revealed a complex matrix of carbonated adhered mortar and quartz-rich natural aggregates. While the porous interfacial transition zone (ITZ) contributed to elevated water absorption (6.65–7.46%), the non-plastic nature of cementitious fines prevented moisture-induced instability. The integration of macro-mechanical results with micro-scale mineralogical findings validates that RCA provides sufficient structural integrity for high-traffic pavement foundations. This research supports the transition toward a circular economy in Thailand’s infrastructure sector by providing a technical basis for the wide-scale implementation of recycled construction and demolition waste in transportation projects.

Targeting Bacterial DNA Gyrase-B with Fenugreek-Derived Phytochemicals: An In Silico Strategy for Antibacterial Lead Discovery

Daniel Bauta Musa — 2026-06-30

Antibiotic resistance poses a major public health challenge globally. Fenugreek (Trigonella foenum-graecum) contains phytochemicals that have been studied for possible antibacterial activity. This study examines the interaction of fenugreek seed phytochemicals with DNA gyrase-B using computational methods. GC-MS was employed to identify bioactive compounds. Lipinski’s Rule of Five and Absorption, Distribution, Metabolism, Excretion, and Toxicity (ADMET) analyses were used to evaluate drug-likeness and pharmacokinetic properties. Selected ligands were docked with bacterial DNA gyrase-B using AutoDock Vina and analyzed using BIOVIA Discovery Studio. GC-MS revealed 29 compounds from the aqueous and methanolic extracts, 12 of which passed the drug -likeness screening. ADMET profiling indicated favorable ADMET profiles for several candidates. Molecular docking revealed that cyclodocosane, ethyl exhibited the highest binding affinity (-9.6 kcal/mol) against DNA gyrase-B. Although, only one specific hydrophobic interaction was observed. This hydrophobic contact involves a nonpolar amino acid residue (Leu294) in the binding pocket of the protein, key to maintaining the complex's integrity. This compound outperformed the standard drug ciprofloxacin (-9.2 kcal/mol). The result indicate that the ligand may serve as a starting point for further optimization. Fenugreek seeds contain phytochemicals with promising antibacterial potential, especially against DNA gyrase-B. Cyclodocosane, ethyl may serve as a lead compound for novel antibacterial drug development, pending further validation and optimization.

Bioprospecting Actinomycetes from the Un-tapped Mangrove Sediments of North Kerala for Antimicrobial and Hydrolytic Enzyme Activities

Kiran Kishore — 2026-06-30

Actinomycetes from unexplored environments are regarded as a potential source of novel metabolites with a diverse array of biological activities. Sediments from mangrove habi-tats, characterized by their distinct environment, are regarded as essential for the identification of Actinomycetes strains with potent industrial, biotechnological, and therapeutic applications. The primary goal of the present study was to investigate the distribution, hydrolytic enzyme potential, and antimicrobial properties of actinomycetes strains from the mangrove sediments of north Kerala with respect to sediment characteristics. Sediment samples were collected from 8 stations in 5 districts along the northern coast of Kerala state. Sediments were subjected to different pretreatment methods to eliminate the growth of unwanted contaminants and plated on three different media for the selective isolation of actinomycetes. The pH of sediments ranged from 6.0-7.0, temperature from 28℃- 35℃, salinity from 1.8-3.2%, and percentage of organic matter from 1.0% - 9.2%. A total of 117 actinomycetes were isolated based on their distinct morphology, colony appearance, sporulation, and pigment production, out of which 86% of isolates exhibited hydrolytic enzyme potential and 64% isolates exhibited antagonistic activity against pathogenic strains. Based on 16S rRNA sequencing, the isolates exhibited the greatest resemblance to four distinct genera: Streptomyces, Brevibacterium, Microbacterium, and Nonomuraea. Further research into the isolation and identification of secondary bioactive compounds from these groups will be advantageous for uncovering new biomolecules that are beneficial to humans.

Green Synthesized Copper Oxide Incorporated on Transparent Nata de Coco Bacterial Cellulose Composite for Optical Detection of Cadmium(II) in Landfill Waste Leachate

Siti Linda Cahayani Fanihu — 2026-06-30

Reliable analytical techniques with low detection limits for cadmium are essential for environmental monitoring. This study developed transparent nata de coco bacterial cellulose films incorporated with copper(II) oxide (CuO) nanostructures for optical detection of cadmium(II) in landfill leachate. The cellulose–CuO composite film was produced through bacterial cellulose fermentation using Acetobacter xylinum, CuO nanostructure synthesis via alkaline precipitation and thermal treatment, and incorporation of CuO into transparent cellulose films. Dragon fruit peel extract served as a natural capping and stabilizing agent, while epoxy resin reinforcement improved film durability. The sensor’s optical response to cadmium(II) was evaluated by UV–Vis spectrophotometry. The composite film showed excellent analytical performance with an RSD of 0.46%, recovery of 104.7%, LOD and LOQ of 0.04993 ppm and 0.05133 ppm, respectively, and robustness RSD of 0.7%, demonstrating its potential as an environmentally friendly sensor for rapid cadmium detection.

Bibliometric Mapping of Rambutan (Nephelium lappaceum L.) Research: Trends and Directions

Yasmin A.C. Yahaya — 2026-06-30

This study presents a comprehensive bibliometric analysis of 551 journal articles retrieved from the Web of Science (WoS) database to evaluate the biological and pharmacological potential of rambutan (Nephelium lappaceum L.). Using co-citation and co-word analyses, the research identifies key thematic clusters and emerging trends. Bibliographic mapping highlights four dominant themes: (1) valorization of rambutan byproducts, (2) its role as a functional food source, (3) investigation of different plant parts for diverse applications, and (4) utilization of rambutan peel in nanomaterial synthesis. Co-word analysis further emphasizes four critical research directions: (i) applications of rambutan-derived compounds, (ii) biological activities of their constituents, (iii) sustainable extraction and production methods, and (iv) fruit waste valorization for environmental sustainability. Overall, the findings provide a holistic understanding of rambutan’s multifaceted significance across food science, pharmacology, and environmental domains. The study also identifies existing research gaps and future opportunities, offering valuable insights into advancing both scientific inquiry and industrial applications.

Optimization of Agrobacterium tumefaciens- Mediated Transformation Conditions in Coffea arabica cv. Catimor CIFC 7963

Thidarat Panphlai — 2026-06-30

Agrobacterium-mediated plant genetic transformation is one of the established methods for plant breeding. In this study, conditions for Agrobacterium-mediated delivery of the GUS reporter gene into Coffea arabica cv. Catimor CIFC 7963 calli were optimized. The calli were cocultivated with Agrobacterium tumefaciens and cultured in a liquid medium for 20 and 24 hours. The Agrobacterium suspensions consisted of three treatments: undiluted (control), 1:5 dilution, and 1:10 dilution. The calli were transferred to MS/2 medium containing 500 mg/L cefotaxime for 1 month. Subsequently, they were moved to MS/4 medium with 17.76 μM BA, 50 mg/L hygromycin, and 250 mg/L cefotaxime for another month. Finally, they were subcultured on MS/4 medium with 17.76 μM BA, 50 mg/L hygromycin, and 125 mg/L cefotaxime for 1 month. The results showed that the survival rate of calli co-cultivated with Agrobacterium cultured for 20 hours was better than that of the 24-hour condition. The friable callus was then selected to co-cultivate with Agrobacterium cultured for 20 hours. The callus survival rates for the undiluted, 1:5 dilution, and 1:10 dilution treatments were 0%, 62%, and 64%, respectively. Notably, somatic embryos developed from the friable callus after the 1:5 dilution treatment. Additionally, GUS expression varied between compact and friable calli. Therefore, co-cultivation of friable calli with a 1:5 dilution of Agrobacterium cultured for 20 hours was considered the optimal treatment, as it enhanced the frequency of putative transformation. This transformation system offers an advantage for improving the development of desired traits in coffee.

Model Selection of Simultaneous Equations Model Based on Kullback Information Criterion for Small Sample Case

Warangkhana Riansut — 2026-06-30

This paper introduces a new criterion called SKICc, designed specifically for selecting simultaneous equations models (SEM) in small sample cases. The efficiency of SKICc was compared to that of SAIC, SBIC, and SKIC, considering the percentage of correct model selection and the L₂ efficiency. The study’s scope was defined under the assumption that the independent variables were normally distributed, had a mean of zero, a variance of one, and no issues of multicollinearity. Additionally, the errors in the model had a mean of zero but exhibited contemporaneous correlations among the equations. The small sample sizes examined in the study included 15, 20, and 25 units, with 1,000 simulated data sets generated for each size. The results of the study indicated that the SKICc created had the following formula:

The efficiency comparison revealed that SKICc demonstrated the highest efficiency for small sample sizes. It achieved the best performance in terms of correct model selection and had the highest mean and lowest standard deviation of the L₂ efficiency. However, as the sample size increased, SKIC exhibited the best efficiency. Furthermore, the research findings indicated that SAIC and SBIC tended to select models with too many variables due to their low penalty function values. In contrast, SKIC often selects models with too few variables because of its high penalty function value. Overall, SKICc effectively addressed the issue of selecting models with either too many or too few variables, outperforming the other criteria studied.

Green Synthesis of Copper Nanoparticles Using Anredera cordifolia Stem Extract and Evaluation of Their Antidiabetic Activity

Nurharis Munandar — 2026-06-30

Copper nanoparticles (CuNPs) were successfully synthesized through a green synthesis approach using extract of Anredera cordifolia as a natural reducing and stabilizing agent. The formation of CuNPs was confirmed using several characterization techniques including UV–Visible spectroscopy, Fourier Transform Infrared (FTIR), X-ray Diffraction (XRD), Scanning Electron Microscopy (SEM), and Particle Size Analyzer (PSA). UV–Vis analysis showed an absorption peak at approximately 325 nm, indicating the formation of copper nanoparticles. FTIR spectra revealed the presence of functional groups associated with plant metabolites that contribute to nanoparticle reduction and stabilization. PSA analysis showed particle size distribution in the range of 10–150 nm with a dominant peak around 30 nm and a median particle size (D50) of approximately 36 nm. The α-amylase inhibition assay demonstrated that the combination of A. cordifolia extract and CuNPs exhibited stronger inhibitory activity compared to the extract or CuNPs alone, suggesting potential application as a natural antidiabetic agent.

Confidence Interval Methods for Parameter Estimation of the Odoma Distribution with Engineering Application

Panicha Kaskasamkul — 2026-06-30

Four confidence intervals (CIs) for parameter estimation in the Odoma distribution, which is used in lifetime data analysis, were developed and evaluated in this study. These included the likelihood-based, Wald-type, bootstrap-t, and bias-corrected and accelerated (BCa) bootstrap methods. We used a Monte Carlo simulation study and a real data set to compare the CIs. The criteria in CI comparison are based on their empirical coverage probability (ECP) and average length (AL) in various situations. The explicit formula of the Wald type CI was derived in this study. The simulation results indicated that the ECPs of the likelihood-based and Wald-type CIs approached the nominal confidence level of 0.95 in almost all cases. In cases of small sample sizes (n = 10, 20, or 30), the bootstrap-t and BCa bootstrap CIs yielded ECPs below 0.95. With the increase of sample sizes, the ECPs of the bootstrap-t and BCa bootstrap CIs converged to the nominal confidence level, while the parameter values also influenced the ECP. For low parameter values, the ECPs of the likelihood-based and Wald-type CIs approached the nominal confidence level of 0.95. On the other hand, the ECPs for the bootstrap-t and BCa bootstrap CIs showed low coverage at high parameter values and small sample sizes. The performance of these proposed CIs
has been confirmed by their application to the strength data of aircraft window glass, with results corresponding with those from the simulation study.

Generation of Julia and Mandelbrot Sets via Modified Sp-Iterative Schemes with Image Security Applications

Nabaraj Adhikari — 2026-06-30

This paper explores modified SP-iterations for both fractal generation and image security applications. We analyze the complex maps , , and for all and the parameter establishing an escape criterion that enables generation of diverse Julia and Mandelbrot sets. Algorithm implementation demonstrates parameterdependent variations in fractal patterns and symmetry. Using these chaotic properties, we develop an integrated encryption-enhancement system combining modified SP-iteration based security with median filtering. The method achieves strong encryption (NPCR > 99.6%, UACI > 33.4%) and high-quality reconstruction (PSNR up to 45.73 dB, SSIM > 0.99). This work bridges fractal mathematics with practical image processing, demonstrating how complex iterations can simultaneously produce aesthetic fractals and secure digital images.

Forecasting Patent Trends and Emerging Technologies in the Construction Industry Using BERTopic

Sirikan Samranrom — 2026-06-30

This study aims to forecast patent trends and exploring technologies in the construction industry using BERTopic, with patent data as the primary database. In addition, the study forecasts trends in patent registrations related to BIM technology using the Moving Average, Single Exponential Smoothing, and ARIMA methods. The results indicate that ARIMA(0,2,1) yields the lowest mean squared error (MSE) of 1.12. Furthermore, in exploring technology trends of BIM technology through keyword-based BERTopic analysis, the findings show that patents related to BIM technology can be classified into four main topics: (1) Topic 0, related to BIM-based methods and systems, such as the application of BIM in construction systems, management, and methodologies; (2) Topic 1, related to Augmented Reality (AR) and Virtual Reality (VR); (3) Topic 2, related to Digital Twin technology, including Digital Twinning methods integrated with BIM; and (4) Topic 3, related to interior and decoration design using BIM. The findings of this study are intended to support construction firms, research and development departments, and technology policymakers in making informed strategic decisions regarding BIM adoption, innovation investment, and long-term technology planning in the construction sector.

A Multi-Criteria Decision-Making Approach for Transparency Assessment in Donation-Dependent Foundations Using TOPSIS

Wichai Witayakiattilerd — 2026-06-30

In this research, factors influencing corruption are studied. The transparency of charitable foundations accepting donations is evaluated using the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Factor Analysis. The research process starts with Factor Analysis, employed to identify and cluster related factors. Expert judgment then determines pairwise comparisons of these factor groups’ importance, with weights for these groups derived through the Analytical Hierarchy Process (AHP). These weighted factors are then used to assess the foundations’ transparency. Furthermore, the TOPSIS model ranks the foundations based on their operational transparency. The research offers an innovative approach for comprehensively evaluating the transparency of charitable foundations, thereby providing potential strategies to minimize corruption. It holds substantial implications for improving the transparency of non-profit organizations, contributing to their operational integrity and efficacy.

A Satisfaction-Based Multi-Objective Mixed-Integer Programming Model for the Nurse Rostering Problem

Noppadon Sakulsom — 2026-06-30

A well-balanced working schedule for nurses also means a better patient service quality. Yet, the nurse scheduling problem—also known as a nurse rostering problem—is one of challenging optimization problems, as we need to assign groups of nurses to work functions under a wide variety set of practical constraints. To this end, a nurse may be able to perform limited work functions. Furthermore, the number of assignments must not exceed that allowed by the law—despite the fact that each work function must have at least a predefined number of nurses to perform services. We aim to address this problem, with an overall goal to maximize nurse’s quality of life, which is achieved by a multi-objective mixed-integer programming modeling approach. Four different objectives, under different objective orders, are herein considered and the resulting model is solved by means of the epsilon constraint method. With this solution methodology, we are able to determine a group of well-balanced solutions that helps enhance nurse’s satisfaction in a long run.

Network Revenue Management Approach to Multi-Channel Hotel Inventory Control

Sarun Dunsathit — 2026-06-30

This study aimed to improve revenue management efficiency for four-star hotels in Chonburi Province by applying demand data analysis together with room capacity allocation. The research methodology began with a comparison of the performance of eight time series forecasting models for four main customer segments: Direct bookings, Online Travel Agencies (OTA), Group bookings, and Travel Agents (TA). The results showed that the Prophet, ARIMA, Naïve, and Mean models provided the highest forecasting accuracy for the Group, OTA, TA, and Direct segments, respectively. The forecasting results were then applied to a network model to plan room allocation. This model was integrated with the concept of price elasticity of demand to improve pricing strategies during periods of high demand. Simulation results indicated that increasing room rates for the Group segment on Fridays and Saturdays generated additional revenue of 37,765.73 THB. These findings confirmed that selecting forecasting tools that match the specific behavior of each customer segment, together with proactive pricing management, was a key approach to significantly improving hotel profitability.

A Linear-Programming–Driven Two-Level Factorial Design for Cost-Efficient Alternative Fuel Experiments in a Simulated Cement Calciner

Pongchanun Luangpaiboon — 2026-06-30

The cement industry is among the most energy-intensive sectors and a major contributor to global CO₂ emissions. Although increasing alternative fuel (AF) utilization in calciner operation can reduce coal consumption, laboratory-scale screening of multiple AFs is costly. This study proposes a mathematical framework that embeds a two-level full factorial design within a Linear Programming (LP) model to generate an economically optimized experimental plan under energy constraints. For a given number of AF factors 𝐾, the model (i) assigns Low–High usage levels to each AF, (ii) constructs the complete 2^𝐾 factorial design, (iii) computes the Mixed Coal (MC) required in each treatment to satisfy the target NCV_as-received, and (iv) minimizes the total cost of executing the full factorial design. The LP formulation incorporates decision variables for AF and MC quantities, subject to limits on total AF mass, minimum Low–High separation, and separate line calciner energy requirements. A five-AF case study demonstrates that the optimized 32-run design satisfies all constraints while achieving approximately 41–42% coal substitution relative to pure-coal operation at the same NCV_{as- received}. The results confirm that the proposed framework provides a general, cost-aware planning tool for factorial mixture experiments and is readily extendable to other energy and engineering systems.

Evaluation of Combustion Grate Damage: A Comprehensive Review of Grate Deterioration in Biomass Power Plants

Wirasak Khongkaew — 2026-06-30

Biomass-fired power plants in the VSPP scale increasingly rely on agricultural and woody residues, yet grate components frequently experience premature failure that leads to unplanned outages and high maintenance costs. This study provides a quantitative evaluation of grate-bar degradation mechanisms using long-term operational data, in-situ temperature measurements, and metallurgical characterization. Surface temperatures of 1000–1200 °C and radiative heat fluxes of 65–78 kW/m^² were identified as the dominant thermal drivers of overheating, particularly in zones intermittently exposed during fuel-bed collapse. A six-year dataset from a 9.9-MW reciprocating-grate power plant, supplemented by laboratory material analysis and combustion-zone mapping, was used to identify the controlling failure modes. The results show that persistent primary-air (PA) maldistribution, unstable fuel-bed conversion, and periodic loss of ash/fuel coverage significantly increase radiative exposure and thermal cycling. Metallurgical examination revealed oxide-scale spallation, carburization, and creep deformation, consistent with thermomechanical–chemical mechanisms reported in prior studies. Although para-rubber woodchip contains relatively low concentrations of corrosive species, localized high-temperature oxidation and chloride-assisted attack were still observed, confirming that chemical effects—while secondary—accelerate degradation under fluctuating oxygen and temperature conditions. The study provides engineering recommendations for improving PA–SA distribution control, optimizing grate-motion strategies, and selecting alloys resistant to combined thermal fatigue and carburization. These findings offer a validated mechanistic framework explaining grate-bar failure in reciprocating-grate biomass systems and support more reliable, cost-effective operation of biomass power plants.

A Spatial Analysis of Crime Trends and Solution Efficiency across Philippine Police Regional Offices

Resa Mae Sangco — 2026-06-30

Monitoring and analysis of crime trends is crucial for improving public safety and effective law enforcement, especially in a country which has a large geographic and socioeconomic diversity such as the Philippines. While past studies have demonstrated the value of hotspot mapping and spatial statistics in urban contexts, few studies have systematically addressed the inter-regional disparities in both crime incidence solution efficiency across regions using advanced spatial analysis. This study seeks to fill this gap through spatial- statistical techniques such as hotspot mapping, Global Moran's I, Spatial Lag Modeling, and spatial scan statistics on crime data from the Philippines for a period from January 2022 to September 2023. The analysis showed a high spatial clustering of reported crimes in highly urbanized areas like the NCR, CALABARZON, and Central Visayas. Spatial regression identified unemployment, population, and the number of police stations as significant factors influencing reported crime cases The spatial clustering highlighted regions with low-risk that had significantly a smaller number of crime cases than expected. The study’s findings underscore the need for prioritizing resources in high-crime urban regions, enhancing community policing and inter-agency coordination, and investing in education and employment opportunities. Finally, the study recommends future research at finer geographic and temporal levels for more refined policy development.

Synthesis and Application of Activated Carbon from Oil Palm Fronds Biomass for One-Step Glycerol Purification

Fitri Rowiyah Rambe — 2026-06-30

This study aims to synthesize and apply oil palm frond activated carbon (OPFAC) as an adsorbent for one-step processing of crude glycerol. OPFAC was prepared through chemical activation using 10% of Na₂CO₃ followed by carbonization at 400°C. Several techniques, including SEM-EDX, FTIR, and SAA, were performed to evaluate its morphology, elemental composition, functional groups, and pore characteristics. In crude glycerol purification, the OPFAC dosage was varied at 1%, 3%, 5%, and 7% (w/w) relative to glycerol mass to determine its effect on purification performance. The initial crude glycerol purity of 50.64% increased progressively with increasing OPFAC dosage, reaching a maximum of 96.66% at 7%, which met SNI 06-1564-1995, BS 2621:1979, and classified as USP Degree II grade. FTIR analysis revealed the presence of methylene groups and aromatic C–H vibrations in OPFAC. Surface area analysis indicated a micropore surface area of 44.41 m²/g and a micropore volume of 0.0132 cc/g. The external mass-transfer coefficient (k_f) decreased from 1.32×10^-4 to 3.78×10^-5 cm/min with increasing adsorbent mass, consistent with film-diffusion theory and supported by previous studies. Overall, the results demonstrate that OPFAC is a promising, low-cost, and sustainable adsorbent capable of achieving high-purity glycerol through a simplified one-step process.

Multi-Tiered Security Framework for Container-Based Secure Data Migration in Cloud Environment Using Hardy Weinberg-Apiary Organization-Based Optimization Algorithm

S. Durgaprasad — 2026-06-30

Cloud data migration transfers services, applications, and data from local infrastructure to the cloud to improve scalability, flexibility, and cost efficiency. However, migration faces challenges including security risks, data loss, downtime, performance degradation, and
energy consumption. To address these issues, this study proposes a multi-tiered security framework consisting of five phases: encryption, load balancing, virtual machine (VM) selection, VM privacy protection, and data migration. User tasks are collected and allocated to containers for efficient resource utilization. A novel document-based chunking Blowfish algorithm (DBC-BA) enhances data confidentiality and processing speed during encryption. For load balancing, the proposed LPF-DBSCAN algorithm employs Local Poisson Forest density estimation to improve clustering accuracy under varying data densities. VM selection is optimized using the Hardy Weinberg–Apiary Organization-Based Optimization Algorithm (HW-AOBOA), while T-Closeness protects sensitive VM information. Implemented in Python, the proposed method achieves secure cloud data migration with low energy consumption (38.56 J) and reduced delay (1857 ms).