The Journal of King Mongkut’s University of Technology North Bangkok

ปกวารสารวิชาการพระจอมเกล้าพระนครเหนือ

- - — 2025-09-29

บรรณาธิการวารสารวิชาการพระจอมเกล้าพระนครเหนือ

บรรณาธิการ วารสารวิชาการพระจอมเกล้าพระนครเหนือ — 2025-09-29

บรรณาธิการวารสารวิชาการพระจอมเกล้าพระนครเหนือ

คำแนะนำในการเตรียมต้นฉบับบทความวารสารวิชาการพระจอมเกล้าพระนครเหนือ

คำแนะนำในการเตรียมต้นฉบับบทความ วิชาการพระจอมเกล้าพระนครเหนือ — 2025-09-29

คำแนะนำในการเตรียมต้นฉบับบทความวารสารวิชาการพระจอมเกล้าพระนครเหนือ

Suggested Amendments to the Law Regarding the Use of Artificial Intelligence in Processing Personal Data

Worawit Kitikusoun — 2025-01-27

This academic article focuses on analyzing the legal frameworks and practices of the General Data Protection Regulation (GDPR) and Thailand’s Personal Data Protection Act B.E. 2562 (2019) concerning the use of AI in personal data protection. The study emphasizes understanding the key principles of both laws related to data processing by AI, such as automated decision-making, privacy impact assessments, and the protection of data subjects' rights. The article compiles best practices and examples of the safe and lawful use of AI in various contexts. Furthermore, it presents approaches from the GDPR and Thailand’s Personal Data Protection Act B.E. 2562 (2019) to mitigate risks and enhance the efficiency of personal data protection. It also discusses the challenges and limitations of implementing these laws within Thailand’s context, suggesting the need for clearer and more comprehensive regulations to address AI-based data processing. Particular attention is given to cases where AI decision-making may impact the rights of data subjects. It recommends the inclusion of provisions requiring notification and providing opportunities for data subjects to object or request human review of AI decisions.

Machine Learning-Based Multiclass Classification for Predicting the Cumulative Blood Sugar Levels in Type 2 Diabetes Patient

Naphat Posri — 2024-11-27

This research aims to classify cumulative blood sugar levels (Hemoglobin A1c) and assess disease control in type 2 diabetes patients using machine learning models. A total of 28,431 medical records with 37 attributes were collected and processed through data preparation. Feature selection was performed using Information Gain (IG), Recursive Feature Elimination (RFE), and Random Forest Importance (RFI) methods. Imbalanced data was addressed using the Synthetic Minority Over-sampling Technique; SMOTE (SM), Borderline-SMOTE (BM), and Adaptive Synthetic (ADA) techniques. Models were developed using five multiclass classification algorithms. The results demonstrated that the IG + SM model, combined with the Random Forest algorithm, yielded the highest performance, with an accuracy, precision, recall, and F1 score of 81.89%, 82.13%, 81.89%, and 81.83% respectively. These findings can be applied to support decision-making for additional cumulative blood sugar level testing beyond routine practices and to enhance the efficiency of diabetes control within the hospital's service area.

Incorporating a Directed Graph in Bayesian Variable Selection for a Highdimensional Regression Model

Busarakam Pratansup — 2024-10-30

In high-dimensional regression models, effective variable selection is critical for enhancing model interpretability and accuracy. This paper introduces a novel method, ICM/MD, which incorporates directed graphs into the Bayesian variable selection framework to capture directional relationships among variables. We compare the performance of ICM/MD with Lasso, ICM/M without considering a network, and ICM/M with undirected graph incorporation methods across various simulation scenarios in a genomic context. The results demonstrate that ICM/MD achieves significantly lower false positive rates while maintaining competitive false negative rates, especially in cases where not all genes in the network are related to the response and the number of predictors is large. This balance of precision and recall ensures more reliable and interpretable models. The ICM/MD method proves to be a robust and valuable tool for researchers dealing with complex high-dimensional datasets, particularly in genomics and bioinformatics, by providing a more accurate representation of underlying biological or network structures.

Development of Ready-to-Eat Nutritional Corn Silk Soup for The Elderly and NCDs Patients

Chanita Inthathong — 2024-10-30

This research focuses on developing a ready-to-eat corn silk soup aimed at improving nutrition for the elderly and individuals with chronic Non-communicable Diseases (NCDs), such as hypertension, diabetes, and stroke. These conditions often cause difficulties with chewing, swallowing, and maintaining proper nutrition. The primary objectives of the study were to determine the optimal proportions of corn silk (5%, 10%, 15%) and brown rice protein powder (2%, 4%) in the soup formulation, and to explore methods for extending the product’s shelf life. The soup was sterilized using an autoclave (First Toy International Co. Ltd., Thailand) at 121°C for varying durations (15, 20, 25 minutes), with observations of texture andprecipitation changes. Nutritional analysis was conducted using AOAC International 2023 methods, while physical properties such as pH, viscosity, and color were evaluated using in-house methods (WI-TMC-109), IDDSI Testing Methods, and a colorimeter (Hunter Lab, USA). Microbiological quality was assessed in accordance with the Notification of the Ministry of Public Health No. 355, B.E. 2556 (2013). Sensory evaluation and consumer acceptance were analyzed using SPSS version 29. The optimal sterilization condition was found to be 119°C for 20 minutes using a retort sterilizer, balancing safety with the preservation of nutritional and sensory qualities. This temperature prevented overcooking of delicate proteins and ensured adequate starch gelatinization, resulting in a safe and appealing product for elderly consumers. The soup provides 100 kcal per 130 g serving, with low sugar content (less than 1 g) and cholesterol (5 g), making it suitable for seniors. The preferred formulation, consisting of 15% corn silk and 4% brown rice protein powder, achieved an overall preference score of 7.79 ±1.01. Additionally, the soup is classified as moderately thick (Level 3) according to IDDSI criteria, and microbiological tests confirmed that it is free from harmful pathogens, ensuring its safety for consumption. This innovation also supports Thai farmers by creating economic value from underutilized corn components, contributing to sustainable agricultural development.

Participatory Action Research (PAR), Innovation to Eliminate Fat Oil and Grease, FOGiATK in Prototype Area

Somphop Nakwun — 2024-11-15

Innovation to Eliminate Fat, Oil, and Grease (FOGiATK) was conducted following the Participatory Action Research (PAR) approach. This research project aims to implement core biotechnology in a prototype area in cooperation with stakeholders. These operations were performed to assess the level of social readiness (SRL) for the development of process innovation. FOGiATK not only applies knowledge from biological sciences but also promotes the green production concept by utilizing renewable resources. Food waste, especially protein waste from the processed food industry and restaurants, is reused as a culturing medium for microorganisms in this system. Several advantages are gained from utilizing the FOGiATK system. The maintenance costs of grease trap systems can be reduced threefold compared to commercial microbe products. Additionally, worker welfare can be improved through communication tools developed using the PAR approach. This research project meets the criteria of both the ESG matrix and the Sustainable Development Goals (SDGs), directly addressing SDGs 6, 12, and 13. It also indirectly impacts SDGs 11, 14, 15, and 17. Over a 5-year period, FOGiATK can reduce wastewater treatment costs four times compared to physical methods and twelve times compared to commercial microbes, resulting in savings of 144,100 and 529,800 baht, respectively.

Non-linear Programming Model for Dairy Cattle Feed Production Planning

Thitiphorn Ponjantuk — 2025-03-03

This research applied a nonlinear programming model to plan feed production for dairy cattle. The model objective is to maximize total profit subject to the constraints of the amount of available raw materials, required nutritional value, nutritional value of each type of raw material, raw material prices, production costs, product selling prices, safety stock, and customer demand. The developed model was processed using the LINGO program. The results show that the case study should use 10 raw materials in various proportions to mix dairy cattle feed. The most used raw materials are soybean meal, cassava, powdered mimosa leaves, and rice bran. The results also include information on production and inventory decisions for each month of the annual production planning. In addition, the model sensitivity was analyzed by varying the parameters that are expected to affect total profit and decision variables. The results showed that the case study establishment had the highest total profit of 6,217,715.98 baht, which was 24.23% higher than the profit from the original operation. In addition, the research also provides sensitivity analysis of the model by varying the parameters that are expected to fluctuate in the future and may affect the overall profit and the values of the decision variables. It was found that when the selling price or demand increased, the total profit would increase significantly. As for the increase in the price of raw materials, especially cassava and soybean meal, the total profit would decrease significantly. However, the increase in the price of food ingredients and production costs had only a slight impact on the total profit. Therefore, the research results provide solutions for production planning of dairy cattle feed appropriately, leading to decisions about raw material mixing ratios, production volume, and inventory volume that are consistent with the customers demand in each period.

THE The Close Range Photogrammetry Technique for Thai-architecture: A Case Study Sihing Buddha Statue Mandapa at RMUTK

Puttipong Sudjamnong — 2025-01-10

The challenge of generating three-dimensional models using digital close range photogrammetry technique in Thai architecture, characterized by intricate features, necessitates the usage of many equipment types, as each sensor offers distinct perspectives and resolutions. To enhance the comprehensiveness of the 3D model, the aim of this research was to investigate a digital close range photogrammetry method for amalgamating photographic data from three sensor types: 1) images captured by the DJI Mavic 3 Classic while orbiting the point of interest at six distinct altitudes; 2) photographic data recorded with a Canon DSLR equipped with a 20 mm fixed lens within the Buddha Sihing area and the mandap's interior; and 3) photographic data obtained with a smartphone focusing on the staircase details. Processing of all photographic bundle blocks segmented into four bundle blocks from three types of sensors. The system integrated photo bundle blocks and sets parameters for identifying manual tie points and photo control points. The distribution factor of the manual tie points influenced the overlap and alignment of bundle blocks. The outcomes of the three-dimensional modelling of the Buddha Sihing mandap encompassed a comprehensive and precise representation of color, texture, shape, and spatial positioning of things. It demonstrated that sensor integration could enhance the constraints associated with utilizing a singular sensor type, making it appropriate for Thai architectural applications.

Cold Atmospheric Plasma Technology for Enhancing Glioblastoma Cell Death

Prakaykan Wichitthanabodee — 2025-05-29

Currently, aggressive brain cancer is one of the most severe types of cancer and is difficult to treat. It accounts for up to 45% of all brain cancers. Therefore, the researcher aims to study and explore potential approaches for treating aggressive brain cancer. This study focuses on utilizing Cold Atmospheric Plasma (CAP) to eliminate glioblastoma cells (LN229), an aggressive form of brain cancer. The experiments employed the Cool Air Plasma Jet model Nightingale and implemented a Full Factorial Design (2k) to investigate four factors: plasma intensity level, airflow rate, electrode-to-media surface distance, and plasma discharge duration. The findings revealed that cold plasma achieved a maximum cancer cell elimination rate of 49.91% under optimal conditions: plasma intensity at 0.62 watts, airflow rate at 3 liters per minute, electrode-to-media distance at 2 cm, and discharge time of 210 seconds. Cell death was quantified using trypan blue staining, while cell morphology was studied via fluorescence staining with propidium iodide and Hoechst 33342. In three-dimensional models, the maximum cancer cell elimination rate was 23.00%. The results suggest that cold plasma has significant potential in generating Reactive Oxygen and Nitrogen Species (RONS), which contribute to cancer cell apoptosis. This research highlights the potential of cold plasma technology as a future treatment for brain cancer. However, further advanced studies are required to enhance its efficacy and applicability at the clinical level.

Improvement of Lateritic Soil with Oil Palm Ash, Dust Stone, and Cement to Develop Road Surface Materials

Phongphoom Sornchomkaew — 2024-11-15

Palm oil is the main raw material for biodiesel production, rapidly becoming an important energysource due to its high potential energy and reduced environmental contamination compared to petroleum.Promoting biodiesel has the advantage of reducing the dependence on petroleum and helping to manageenergy costs. In addition, biodiesel production generates palm oil waste, including empty fruit bunches,fibers, and palm kernel shells, which are used as fuel for electricity generation, resulting in palm oil ash asan industrial by-product. This study aimed to study the physical and engineering properties of laterite soilmixed with rock dust, oil palm ash, and Portland cement type 1. The study used different mixing ratios,with oil palm ash at 0%, 1.25%, 3.75%, and 5%, rock dust at 16% and 18%, and cement at 6% and 8%.Physically, the limits were found to be fluid, with plastic and shrinkage limits increasing as the amountof oil palm ash increased. The study employed a standard compaction test and a uniaxial compressiontest. The compaction test results showed that the maximum dry unit weight decreased as the oil palmash content increased. The optimum moisture content increased with the addition of oil palm ash, rockdust, and cement. The uniaxial compression test revealed that mixing the right proportions of rock dust,cement, and oil palm ash could result in high strength. However, excessive amounts of oil palm ashnegatively affected the compressive strength, leading to a decrease.

A Study on the Efficiency of a Low-Cost Air Purifier Using a Microcontroller and Reusable Filters for Air Quality Improvement

Vissavavit Rachnarong — 2025-03-12

This study investigates the removal efficiency of PM2.5, PM10 and Total Volatile Organic Compounds (TVOC) using a Low-cost Air Purifier (LCAP). The filtration efficiency and Clean Air Delivery Rate (CADR) of both standard and reusable filters in the LCAP were compared with those of two popular air purifier models (AP_1 and AP_2) in a 126 m³ test chamber. The test results indicate that the LCAP equipped with a standard antibacterial filter (LCAP_B) removes PM2.5 and PM10 at a level comparable to AP_2, while the LCAP equipped with a formaldehyde filter (LCAP_F) exhibits superior TVOC removal efficiency compared to AP_2. Specifically, LCAP_B reduces PM2.5 and PM10 from hazardous levels (approximately 700 μg/m³) to an excellent air quality level within 82 and 62 minutes, respectively. For reusable filters, the results show that LCAP outperforms AP_2 in removing PM2.5, PM10, and TVOC. The filter cleaned with a vacuum cleaner and blower (LCAP_BCV) demonstrates a slight improvement in removal efficiency over the dirty filter (LCAP_BD), with increases of approximately 0.38%, 0.34%, and 1.79% for PM2.5, PM10, and TVOC, respectively. The filter cleaned with detergent (LCAP_BCD) improves TVOC removal by approximately 26.44% and 21.01% compared to LCAP_BD and LCAP_B, respectively. However, LCAP_BCD is less effective in removing PM2.5 and PM10 than LCAP_BD, with reductions of approximately 5.96% and 5.73%, respectively. Furthermore, the combined operation of three LCAP units (LCAP_T) achieves excellent air quality levels, reducing PM2.5 and PM10 within 36 and 28 minutes, respectively.The advantages of LCAP over AP_1 and AP_2 include an internal battery and a Master-Slave operation, where LCAP-Slave units do not require pollution sensors.

Study the Effect of Grinding Parameter on the Surface Hardness and Structure of the Hot Forged Product

Anas Chalermsilp — 2024-11-04

This research aims to investigate how the surface hardness of S45C metal, which has been hot-forged and heat-treated, is affected by the parameters of the abrasive belt grinding process. The experiment was designed using the Design of Experiments (DOE) method to identify significant factors. Four factors were analyzed: the cross-sectional area, the weight applied to the specimens, the grinding duration, and the abrasive belt stages, including the size of the abrasive grains. Initially, the surface hardness of the specimens was measured between 20–26 HRC. The results showed that the surface hardness of the specimens increased to over 26 HRC. As a result, the experiment identified three significant factors that influence the surface hardness of the material. It was found that as the abrasive belt wore down and became completely flat, it affected the stress applied during the experiment. Consequently, the research sought to examine the stress associated with hard materials.

Design and Develop a Smart System for Monitoring Sleep Posture of Elderly Patients on a Bed

Sumet Umchid — 2024-11-18

Falls from bed are a significant problem affecting the elderly population worldwide, leading to injuries and prolonged hospital stays, which can result in complications such as pressure ulcers. Therefore, monitoring the sleeping posture of elderly individuals is crucial, as it helps prevent falls and provides timely alerts. The objective of this research is to design and develop a smart system that detects real-time sleeping postures using 10 pressure sensors installed on a bed mattress. The system identifies 8 sleep positions: off bed, supine position, left lateral position, right lateral position, raised position, sitting on the bed, legs hanging down from the left side of the bed, and legs hanging down from the right side of the bed. Additionally, temperature and humidity sensors monitor the environmental conditions to ensure comfort. The data is processed by a microcontroller, which sends alerts through a Wi-Fi module to a server on a computer and notifies caregivers via a mobile application. The efficiency of the developed bed system was tested on 4 individuals, with 8 different sleeping positions per person. The results showed that the system accurately detected the following positions: off bed, sitting on the bed, and sitting with legs hanging off the left side of the bed, with 100% accuracy. It achieved 91.67% accuracy for the supine and left-side lying positions, 75.00% accuracy for the right-side lying position, and 66.67% accuracy for sitting with legs hanging off the right side of the bed and sitting up from the bed. Finally, during a 2-hour test in which the subjects maintained the same sleeping position, the system provided accurate alerts.

Effects of Moisture Content on the Performance and Quality of Sugarcane Bagasse Biomass Pellet

Kantapon Premprayoon — 2025-01-27

This study analyzes the effects of varying moisture levels (10%, 15%, and 20%) on the performance and quality of pelletized fuel made from sugarcane bagasse obtained from juice extraction. This agricultural waste material holds significant potential for value-added processing. The experiment revealed that a moisture level of 15% was optimal for producing pelletized fuel, achieving the highest production rate of 70.65 kg/hour. The pellets produced at this moisture level exhibited the highest durability (98.25 ±0.41%) and calorific value (16.11 ±0.06 MJ/kg), both of which meet industry standards. Additionally, the diameter and length of the pellets conformed to the required specifications. However, the bulk density ranged from 535.00 to 575.88 kg/m³, which falls below the values specified by the Thai Industrial Standard (TIS) 2772–2560, highlighting the need for equipment improvements. At a moisture level of 20%, pelletizing performance significantly decreased, and durability fell below the acceptable threshold. These findings underscore the importance of raw material management, including precise moisture control and material preparation, to enhance pellet quality and production efficiency. This research provides a foundation for industrial applications, such as equipment optimization, storage, and transportation processes. Furthermore, it contributes to the development of a comprehensive database to support the efficient and sustainable
management of agricultural residues in the sugarcane industry.

Punching Shear Performance of Recycled Aggregate Concrete Slabs Reinforced with Thin Zigzag Steel Plates

Prapatsorn Rittigun — 2024-11-19

With the growing environmental concerns associated with construction and demolition waste, research on Recycled Concrete Aggregate (RCA) and Recycled Aggregate Concrete (RAC) has gained momentum over the past few decades. The results, however, have been variable due to differences in the quality of RCA used. Nonetheless, most studies demonstrate the feasibility and potential of RCA as a substitute for natural aggregate, providing strength that meets the design standards of ACI 318. This article presents an experimental investigation of slabs composed of 100 percent RCA. Controlled RAC slabs measuring 1,200 × 1,200 × 12 mm were tested under monolithic simple at the middle column over eight simply supports. The test results revealed that the punching shear strength of the controlled RAC slab is lower compared to the one reinforced with thin zigzag steel plates. The plates, tested under impact shear stress, provided more accurate results according to Eurocode predictions and are suitable for all grades of recycled aggregate concrete with low flexural reinforcement.

Influence of Hot Air Drying Combined with Ultrasonic Vibration System on the Energy Consumption and Bioactive Compounds of White Fingerroot Drying

Patipat Thanompongchart — 2024-11-18

This research aims to investigate the efficiency of combining a hot air dryer with an ultrasonic vibration system in drying white turmeric and to study the properties of white turmeric after drying. For the hot air dryer combined with the 40 kilohertz of ultrasonic vibration system, a product placement tray was developed, with the installation of the ultrasonic vibration system along with a heat dissipation system for the vibrating head to dissipate accumulated heat. This system design allowed drying at higher temperatures. White turmeric was chosen as the experimental sample due to its medicinal properties and the presence of various important compounds. The drying experiments were conducted at temperatures of 50, 60, and 70 degrees Celsius using both the hot air dryer and the hot air dryer combined with the ultrasonic vibration system to compare drying performance. The results showed that the hot air dryer combined with the ultrasonic vibration system required less time for drying white turmeric, exhibited higher moisture removal rates, and achieved better drying efficiency compared to the hot air dryer alone at all drying temperature ranges. Additionally, at 70 degrees Celsius, the lowest specific energy consumption for drying the product was observed. Comparative analysis of product color, antioxidant activity, phenolics, flavonoids, pinostrobin, and panduratin A was also conducted. The optimal condition for preserving the active compounds in dried white fingerroot at the highest levels is drying at 60 degrees Celsius combined with an ultrasonic vibration system. The evaporation rate, thermal efficiency, and energy consumption were 0.250 kilogram/hour, 20.72 percent, and 29.960 kilowatt-hour/kilogram, respectively.

Warehouse Layout Design and Product Placement Analysis of Fast–Moving Consumer Goods by Considering the Intra– and Inter–Relationsbetween Common Items and Group Products Demand

Ratthaprasat Rakbanglaem — 2024-12-02

Layouts and storage location assignments play an important role in reducing unproductive travel distances. Typically, fast-moving consumer goods warehouses determine product placement based on picking frequencies. However, this approach may be insufficient when dealing with situations where requested items are correlated, such as the intra- and inter-relations between common items and product groups. Considering these correlations can improve picking operation efficiency. The objective of this study is to determine optimal storage locations by recognizing associations within and between product groups. The case study data includes two distinct groups: 336 SKUs of consumer brands and 81 SKUs of common items. The proposed method involves two phases. First, the degree of association for each product is determined based on intra- and inter-relations among groups using association-rule concepts. Second, the optimal locations are designed and analyzed to accommodate both correlated groups and individual items. Performance evaluations on 10 picking lists indicate that layouts designed with inter- and intra-group product relations outperform other approaches. Compared to the original travel distance, the proposed storage locations reduce unproductive travel from 11,897.6 meters to 3,996.4 meters, achieving a reduction of up to 66.41%.

The Development of Potential Model for Software Engineer in the Digital Industry for the Industrial Business Competitiveness in the Digital Economy Era

Teerapakorn Teeraphattarapakorn — 2025-04-04

Digital technology is disrupting human society to be the digital economy era. As a result, business organizations have to employ software engineers to change the organization's business operations to be in line with such changes. However, Thailand is confronting a shortage of potential software engineers. The business organizations must therefore give importance to development of software engineers to make the software engineers to be the ones who can drive business operations to be successful and achieved their targets. This research aims to study the necessary potential components of software engineers to build the potential of business organizations in the digital economy era and to provide business organizations an appropriate model for software engineers’ potential development for the proper use in practice. This study uses Delphi technique and focus group discussion to analyze the potential components that software engineers need to have in their work and create a model for the potential of software engineers for the industrial business competitiveness in the digital economy era. The results of the research found that the potential components that meet the consensus in the Delphi technique were 11 knowledge components (15.71 percent), 21 skill components (30.00 percent), and 24 attributes components (34.28 percent). The components that meet the consensus criteria were used to create a potential model for software engineers, which knowledge comprised of code and algorithm, software development tools, software development processes, software infrastructure, business which is developing the software and innovation development. Key skills include software development, software design, cognitive abilities, management, communication, and English proficiency. Essential attributes encompass accountability, professional work ethics, self-development, teamwork, innovative creativity, and leadership.

Potential Model Development for Heads of the Customs House’s Effective Management in the Digital Era

Naiyarat Pongsakdinon — 2025-03-06

In an era of rapid and sudden global societal changes, known as the VUCA World (Volatility, Uncertainty, Complexity, and Ambiguity), organizations face challenges in adapting to the digital age, advanced technology, and modern innovations. This affects how Customs House Chiefs must adapt to keep pace with these changes. Therefore, it was necessary to conduct research to develop a model for Customs House Chiefs' competencies in the digital era. Using the Delphi technique, interviews were conducted with 21 customs experts. The research findings showed that most aspects, both in terms of Chiefs' competencies and management processes, had importance levels (Mdn) ranging from 4.00–5.00, indicating high to highest importance, and consensus levels (IQR) of 0.0–1.0, showing high to very high consensus. The results were used to categorize components and develop a competency model for Customs House Chiefs, which comprises 3 dimensions, 4 main components, and 20 sub-components, with each main component containing 5 sub- components as follows: 1) Knowledge competencies: Cyber & Innovative Knowledge, Customs & Law Knowledge, Corporate Management, Constitutional Policy, and Cross-border Relations; 2) Skills competencies: Critical Thinking Skills, Communication & Coordination Skills, Coaching Leadership Skills, and Cyber Technology Skills.; 3) Desirable attributes: leadership qualities, Chief Leader Character, Code of Ethics and Conduct, Continuous Learning & Development, Creative Thinking, and Collaborative Teamwork & Connection Dimension; and 4) Management processes: Corporate Management in the Digital Era, Capital, Budget & Technology Resource Management, Command & Leadership, Crisis & Risk management, and Control & Evaluation. The development guidebook consists of 3 learning categories: TRUST, TEAM, and TECH+, comprising a total of 11 guidelines that emphasize development in technology and innovation for organizational management in the digital era.

Biorefinery Challenges and Strategic Solutions for a Sustainable Bioeconomy

Pooja Ranganayaki Anand — 2025-03-10

Biorefining is the sustainable processing of natural biomass into a wide range of marketable products and energy. A biorefinery integrates various processes and technologies to convert biomass into valuable products, aligning with the zero-waste concept [1]. Over the past few decades, biorefinery processes have been at the forefront of sustainability, offering an alternative to traditional non-renewable fuel sources. As global energy reserves continue to deplete due to population growth and rising consumption, biorefineries have played a transformative role in reshaping the energy sector with sustainable solutions.