Operational Level Research Articles

Effect of Organizational Cynicism on Job Performance: Evidence from the Rubber Manufacturing Industry in Sri Lanka

Human capital serves as a beacon of any organization in the 21st century. Organizational cynicism, a pervasive negative attitude towards one's workplace, has been recognized as a significant factor influencing employee behavior and outcomes. In the last two decades, the global market has embraced Sri Lanka’s Rubber industry for its value-added products. Since the Sri Lankan context is obsessed with an empirical in exploring the organizational cynicism in the Rubber manufacturing sector, this research aims to ex-amine the impact of organizational cynicism on the job performance of operational-level employees within the rubber manufacturing industry, focusing on Gampaha District. This study is deductive and quantitative, deploying a sample consisting of 170 operational level employees in the rubber manufacturing industry in the Gampaha District, selected through the stratified sampling technique. Data were collected using an online structured survey questionnaire and analyzed using SPSS (version 21). By deploying Pearson Correlation analysis and Multiple Regression Analysis, four hypotheses of the study were tested and three hypotheses were accepted. The thorough investigation of these hypotheses collectively confirms the detrimental influence of organizational cynicism on the job performance of operational-level employees in Sri Lankan Rubber manufacturing firms. Two facets of cynicism—cognitive, and behavioral—exerts a distinct yet interconnected role in mitigating job performance while the affective component was removed from the model. These revelations advocate for a paradigm shift in organizational strategies, urging managers to not only address the visible symptoms but also delve into the root causes of cynicism.

From challenges to competencies: informal female entrepreneurship in emerging economies

PurposeInformal female entrepreneurs in emerging economies operate in challenging business environments. This research examines the competencies of informal female entrepreneurs (IFEs) to explore how they persist because and despite the unique set of challenges they face.Design/methodology/approachWe undertake a qualitative study focusing on IFE in the Indian context. Using the abilities–motivation–opportunity (AMO) framework as a theoretical lens, we interviewed 14 IFEs to gain insights into their entrepreneurial challenges and understand how they address the challenges.FindingsThe results demonstrate that IFEs are prone to various challenges around the individual level, business challenges on an operating and functional level and other challenges rooted in their business environment. Further, the study sheds light on the competencies of IFEs on three fronts, namely, ability-enhancing competencies, including – technical skills, problem solving, communication and adaptability; motivation-enhancing competencies, including – self-motivation, resilience and optimism and lastly, opportunity-enhancing competencies, including – local-centric approach, networking and resourcefulness.Research limitations/implicationsThe study highlights the nuanced settings of informal female entrepreneurship in an emerging economy context. By highlighting the challenges and competency interplay, our study opens novel avenues for the interrelationships to be studied in further detail.Originality/valueOur study provides close insight into the everyday challenges of IFEs operating in informal economies. Their competencies and perseverance-related attributes contribute to the mainstream entrepreneurship literature, as these entrepreneurs exhibit unique competencies that allow them to thrive in challenging contextual settings. Their willingness to learn new skills, opportunity recognition, motivation and adaptability skills contribute to a better understanding of the phenomenon of informal female entrepreneurship.

Learning super-resolution and pyramidal convolution residual network for vehicle re-identification

Vehicle re-identification (Vehicle Re-ID) aims at retrieving and tracking the specified target vehicle with multiple other cameras, which can provide help in checking violations and catching fugitives, but there are still the following problems that need to be solved urgently. First, the existing collected Vehicle Re-ID data often have low resolution and blur in local regions, so that the Vehicle Re-ID algorithm cannot accurately extract subtle feature representations. In addition, small features are easy to cause the disappearance of features under the operation of a large convolution kernel, which makes the model unable to capture and learn subtle features, resulting in inaccurate judgment of vehicles. In this study, we propose a Vehicle Re-ID method based on super resolution and pyramidal convolution residual network. Firstly, a super-resolution image generation network leveraging generative adversarial networks (GANs) is proposed. This network employs both content loss and adversarial loss as optimization criteria, ensuring an efficient transformation from a low-resolution image into a super-resolution counterpart, while meticulously preserving intricate high-frequency details. Then, multi levels of pyramidal convolution operations are designed to generate multi-scale features, which can capture information on different scales. Moreover, the concept of residual learning is applied between the multi levels of pyramidal convolution operations to expedite model optimization and enhance recognition capabilities. Ultimately, the double pyramidal convolutions are meticulously employed on both the original image and the super-resolution image, yielding low-noise feature representations and intricate semantic information respectively. By seamlessly fusing these two diverse sources of information, the resultant combined features exhibit heightened discrimination capabilities and significantly bolster the robustness of image features. In order to verify the effectiveness of the proposed method, extensive experiments are carried out on VeRi-776 and VehicleID datasets. The experimental results show that the method proposed in this paper effectively captures the detail information of vehicle images, accurately distinguishes the subtle differences between different vehicles of the same type, and is superior to state-of-the-art methods.

Rapid deep learning prediction model using satellite imagery for radiation accident Announcement system in Serbia

Radioactivity environmental monitoring with the help of the Radiation Accident Announcement System (RAAS) established in the Republic of Serbia is of vital importance for rapid response in the event of intervention dose values being reached such as Operational Intervention levels (OILs). There are cases of impossibility of using a ground-based model in order to predict the transport and spread of radiation during a nuclear accident such as the one in the Fukushima Daiichi nuclear power plant 2011. Modern technology has made it possible to use machine learning models with remote sensing data in addition (or an alternative) to atmospheric models with ground data collection methods. Deep learning (DL) model was developed and trained on a satellite-based cloud fraction dataset to forecast diurnal cloud drift. By forecasting the movement of clouds that are potential carriers of radioactive materials, decision-makers can provide an adequate response with an Action Plan in the case of nuclear and radiation accidents and incidents. Designed Application Programming Interface (API) has been developed and integrated between the DL model and the RAAS. In this way, the monitoring, data sharing and exchange processes were automated in order to trigger the DL model when an OILs value of 1 μSv/h is reached. The hyperparameter optimization process of the DL model was done with grid search and Particle Swarm Optimization (PSO) to achieve maximum performance on the data in a reasonable amount of time. The evolution metrics to monitor and measure the performance of the DL model were cosine similarity (CS) and structural similarity (SS) with the best score of 0.78282 and 0.27063 for grid search, respectively, while 0.27065 and 0.78282 for PSO, respectively. It can be concluded that remote sensing imagery with DL model is an alternative approach against a ground-based forecasting system, and is able to predict in near real-time independently of ground network system and data.

Coordinated Optimal Operation Method for Snow-Shaped Distribution Networks Based on Game Theory

The snow-shaped distribution network is developed and upgraded from the traditional single-loop network and double-loop network structure. It is composed of three or four groups of single-loop networks in pairs that form a feeder cluster in the form of a ring network. Based on this topology, the coordinated optimization operation problem is studied. First, the game elements are analyzed, and then a cooperative game-based, coordinated optimization operation model is established by taking the minimum network loss and voltage deviation of the system as the utility function. Then, the alternating direction multiplier method (ADMM) is employed in Cplex solver to solve the established optimization model. Finally, a numerical case is given to verify the effectiveness of the proposed model and method. The results show that, by using the complementary difference relationship of source–charge characteristics between different regions in the snow-shaped distribution networks, the cooperative game model can realize the energy interconnection among different regions to improve the operation level.

A Study of the Rainwater Pumping Station Operation Plan to Reduce River Water Level

Urban flood damage is caused by various and complex effects such as inland flood and external water flooding, so research on this is necessary. This study presented a rainwater pumping station operation technique that can suppress the rise in water levels in discharge rivers based on rainfall and pump operation scenarios in order to reduce inland water flooding and simultaneously consider external water levels. The research method used genetic algorithm (GA) optimization techniques to calculate the optimal operating level for each pump, and based on this, an operating scenario was created to minimize pump operation. In addition, after constructing a rainfall scenario based on the probability rainfall in Seoul, an optimal pump operation technique that can reduce the external water level while minimizing the inundation of domestic water was proposed. The results of the study showed that as the rainfall intensity increases, the flooding increases and the peak depth of the runoff increases. In addition, as the pumping scenario changes from 1 to 11, the number of pumping operations decreases, which reduces the drainage volume of the pumps, which increases the flooding.

Data Delivery Indicators in EIDA: Designing a Consistent Metrics System in a Distributed Services Environment

The European Integrated Data Archive (EIDA) is a data service within Observatories and Research Facilities for European Seismology (ORFEUS) which distributes seismological waveform data across, presently, 12 federated data centres, so-called EIDA nodes. EIDA is also integrated into the European Research Infrastructure EPOS (European Plate Observing System). The increasing need of quantifying the scientific impact of such Research Infrastructures at all levels of operations has led EIDA to develop a unified system able to provide global indicators for data delivery across all EIDA nodes. To achieve this goal, EIDA implemented a system where the numbers are collected and aggregated by each EIDA node and ingested in a centralised database, accessible through an online API. The successful implementation of the system stems from carefully identifying the relevant indicators for well-defined groups of users. The implementation combines simplicity and robustness whilst respecting the distributed design of EIDA. The architecture and implementation choices may be of interest to other multi-site data distribution research infrastructures that face the challenge of providing meaningful key performance indicators.

Adequacy of measures to threats as one of the fundamental ­principles of safety riskology

Purpose. To justify the need to apply the “principle of adequacy of probabilities” as a measure to improve the risk management methodology, to prevent (counteract) existing and emerging risks (threats) to the security of complex systems. Methodology. The well-known methodological principle called “Ockam’s Razor” was used. In the course of the research, a complex method was used, which included formal and logical analysis of normative and scientific and technical literature, analysis of statistical data, synthesis, abstraction, experiment, observation, generalization of data, description. Findings. In the course of the research, one of the threats (danger, risk) was identified, which simultaneously affects the existence of such a system due to traffic safety of rolling stock of rail transport enterprises, and the full implementation of the system’s capabilities due to axle loads, mass and speed movement of rolling stock, level of operating costs, passenger flow, regularity of transportation, etc. Experimental application of the lubricant “Mariol NT” in SPP 12-5, GS-3 lubrication systems showed a decrease in wear intensity by 240 %. Due to the use of a new lubricating material applied to the friction surface of wheel rims as part of the paint coating, the wear intensity of flanges of twin-wheel rims is reduced by 2.2 times, and that of locomotives by 2.4 times. Originality. It was determined that the “principle of adequacy of probabilities” as a measure of improvement of the risk management methodology, prevention (counteraction) of existing and prospective risks (threats, dangers) during the safety assessment of complex systems is currently not applied, but its consideration helps to prevent (countermeasures) to existing and emerging risks (threats) to the safety of complex systems. Practical value. The use of the “principle of adequacy of probabilities” allows for the theoretical and experimental determination of the numerical value of the ratio between the probability of an event occurring, caused by the action of an identified threat that negatively affects the state (level) of safety and operability of system elements at all stages of its existence, and the probability of a positively compensatory effect of the developed countermeasure to the identified threat.

Development of a mechanism for managing the quality of customs services at the post-customs control stage

Subject. The article discusses the need for methodological support and technological justification of assessment and improvement of the customs services quality at the post-customs control stage. Objectives. The study aims to develop a comprehensive methodology to evaluate the effectiveness of structural units and the quality of rendered services as a basic element of the management mechanism. Methods. The study rests on the system methodology. We decomposed the mechanism of customs services quality management, and developed its morphological model during the analysis of individual components of the mechanism. Results. We developed a mechanism to manage the quality of services provided at the stage of post-customs control. It is divided into operational and strategic levels of management decision-making. Furthermore, we disclosed individual elements of the quality management mechanism, identified the main activities of the post-control units, within which key performance indicators are evaluated. As a pragmatic example, we developed a matrix for calculating performance indicators for one of the main areas of activity. Conclusions. The further direction of scientific research should be a model of the consumer of customs services, which determines the economic essence of solving the problem of developing the activities of the Federal Customs Service of Russia at the stage of post-customs control.

E-participation in Local Self-Government in Croatia

Today, cities play a crucial role as drivers of global change, as well as leaders in implementation of UN’s Sustainable Development Goals. They must capture and satisfy diverse needs of their citizens. On the other hand, e-participation adoption is crucial in open government movement as it allows the government to involve the public in their work, making it more transparent. This can be achieved through e-information, e-consultation and e-decision making as levels of e-participation adoption. This research puts focus on e-participation adoption in Croatian local governments and explores supply side of e-participation adoption with local governments’ officials. After consulting relevant literature, public sector and ICT experts, a questionnaire (i.e. measurement items) has been developed to assess e-participation levels in cities/municipalities with over 8,000 inhabitants. More than 240 responses have been collected from local governments’ heads of departments and departmental managers. The results show that the adoption of e-participation at the local level is modest with a score of 59%. E-participation sub-levels show very good adoption of e-information (e-information services widely available), mediocre results for e-consultation (mostly only compliance with respective law), and a low level of adoption of e-decision-making. The differences in adoption levels of e-participation are statistically significant between smaller and larger cities/municipalities. Therefore, the population size of the city/municipality has proven to be significant, with larger cities having higher adoption rates, especially of e-consultation practices. The author suggests a greater variety of tools and formalization of e-participation at strategic and operational levels to achieve higher levels of adoption. In addition, local governments should adopt more advanced engagement tools to enhance citizens’ (and other stakeholders’) e-participation (with voting and rating options), as current utilization is still low.

A two-stage hybrid flow-shop formulation for sterilization processes in hospitals

Sterile processing is a critical secondary process and a major cost factor in the processing, acquisition, and storage of costly medical devices. This article aims to improve the performance of sterile processing by developing, implementing, and evaluating a dispatching rule-based algorithm to reduce the time medical devices spend in the central sterile supply department using a two-stage hybrid flow-shop formulation. The algorithm combines dispatching rules with stage decomposition and compatibility conditions. A genetic algorithm is designed to benchmark the performance in addition to an analytic bound. Real-world data from a large German hospital were used to test the effectiveness of the heuristics. The case study demonstrated the practical implications of the approach, leading to a reduction in the time medical devices spend in the system and improved utilization of washer-disinfector machines and sterilizers. It also highlighted the importance of aligning machine capacity with demand and the potential trade-offs associated with batch processing decisions. Our approach can contribute to substantial operational cost savings and efficiency gains, offering significant benefits to decision makers at both the operational and tactical levels.

Learning Motivation as Mediating Variable on The Effect of Transformational Leadership on Job Performance

This study examines and analyzes the effect of transformational leadership on learning motivation and job performance and the effect of learning motivation as a mediating variable. This research was conducted by distributing questionnaires to research respondents, namely employees in factory 1 grade 5, 6, and 7 (operator level) at PT. Petrokimia Gresik, Indonesia, with 207 employees as the respondents. Data were analyzed using Structural Equation Modeling (SEM) Partial Least Square (PLS). Findings: The results of this study state that transformational leadership has a significant positive effect on learning motivation and job performance. Learning motivation also has a significant positive effect on job performance. In addition. The existence of this research has implications that state that in increasing employee job performance, transformational leadership and learning motivation need to be improved. Learning motivation acts as a partial mediating variable in mediating the relationship between transformational leadership and job performance, which later becomes a new finding in this study.

Organisation of medical care in large scale incidents: a practice-oriented research in Belgium

Abstract Background CBRNe incidents are emergency situations involving the release of chemical (C) or biological (B) substances or radiological/nuclear (RN) contamination, sometimes through an explosion (e). They can result from intentional malicious acts (e.g. terrorism) or unintentional situations (e.g. accidents). In this context, people (victims, care providers, witnesses), equipment (infrastructure, vehicles), animals, objects and/or the environment (buildings, ambulances) may be contaminated by a substance that could pose a threat to health. CBRNe incidents can quickly overwhelm the response capabilities of the affected region and put the healthcare system under great pressure. This research investigated ways of improving the organisation of medical care in CBRNe incidents in Belgium. Methods this study involved a mixed method approach in 2022-2023 with scoping and in-depth interviews with actors at operational and strategic levels (public health, Internal Affairs, army, fire departments), participative workshops with stakeholders, contextual desk search, ad hoc literature review and international comparison completed with interviews with national experts (Norway, The Netherlands, France and United Kingdom, United States of America). Results hospitals need to be distinguished in type 1 specialized hospitals for decontamination, major trauma management and advanced care for severely burned patients and in type 2 hospitals managing spontaneous arrivals of victims and non-specialised care. All hospitals need to have a strict lock-down policy. On the incident site, an emergency medical mobile team needs to manage the decontamination with the firefighters before the transfer to the most appropriate facility. Additional conditions were found to improve the efficiency of medical care. Conclusions this practice-oriented research contributes to a better organization of medical care in case of CBRNe incidents, with the emergence of practical and feasible solutions. Key messages • Hospitals need to be distinguished according to the need for specialised care in case of CBRNe incidents. • On site decontamination needs to be performed by health professionals and firefighters.

Mechanism Analysis and Path Study of Digital Transformation on Corporate Governance: Evidence from Chinese Listed Companies

Corporate digital transformation, primarily driven by data and leveraging digital technologies and mathematical algorithms such as Internet+, big data, cloud computing, artificial intelligence, and blockchain, is a crucial enabler of sustainable development. This transformation integrates various aspects of corporate production and operations, enhancing the level of digital operations and ultimately contributing to high-quality and sustainable development. This paper, based on data from listed companies in China’s A-shares from 2007 to 2021, theoretically articulates the intrinsic mechanism between corporate digital transformation and corporate governance level, with a focus on sustainability. It empirically finds that a higher degree of digital transformation correlates with an improved level of corporate governance, fostering sustainable practices. Further investigation reveals that digital transformation elevates corporate governance by enhancing innovation capabilities, reducing information asymmetry, and promoting sustainable strategies. This paper provides policy insights for promoting corporate digital transformation as a means to achieve sustainability goals and optimizing management’s corporate governance level for long-term sustainable success.

Use of Standard Operating Procedures for Supporting Cross-Organizational Emergency Management: Challenges and Opportunities Identified from a Tabletop Exercise

AbstractThis study investigated the crucial role of formulating and applying standard operating procedures (SOPs) in the context of emergency planning and response. The effective application of SOPs during operations is essential in order to address challenges that surpass individual organizational capacities. A specific focus on fostering efficient information sharing and executing specified actions maximizes the prospect of success. To explore the collective functionality of SOPs across organizations, we conducted a comprehensive tabletop exercise involving 10 organizations spanning tactical, operational, and strategic levels. Our analysis identified six key challenges, primarily related to the structures for information sharing, communication pathways, and the complex integration and application of common SOPs within these diverse organizational contexts. This research contributes insights into the use of SOPs in large-scale, cross-organizational scenarios.

Navigating organizational change through a processual perspective on the transition toward the circular economy: Save The Duck case study

PurposeBy rooting our study in Lewin’s change management theory, we conduct an in-depth case study of a medium-sized fashion firm transitioning toward a CE. Through adopting a multi-level and processual perspective, we offer empirical evidence of the change process and elucidate the drivers and resistance to change factors.Design/methodology/approachWe opt for a single in-depth longitudinal case study of a fashion firm that was born with a sustainable business model and that is in transition toward the CE. We involve multiple informants, and we adopt a processual approach to uncover the drivers and resistance to change factors at different organizational levels (i.e. top and middle management and operational levels).FindingsOur findings enable us to highlight novel key drivers and resistance factors at the organizational level. Regarding the former, we reveal the involvement of top and middle management in the decision-making process and the recruitment of young people. For the resistance factors, we identify adaptation to structural change, reluctant mindset, internal divergence of ideas, and commitment of all organizational levels to the CE.Research limitations/implicationsThe paper presents some limitations. First, our research is based on a single in-depth case study, which, while allowing for rich, detailed exploration, inherently limits the statistical generalizability of our findings. Focusing just on one organization located in a specific industry and geographical context means that our results may not be directly applicable to all organizational settings. Firms belonging to other industries would probably show different patterns of change due to industry-specific drivers and barriers. Also, the institutional and geographical contexts of our case study inevitably influence the cognitive and cultural aspects of the drivers and barriers we identified. Then, our research provides a processual yet not longitudinal view of OCCE, thus not fully capturing the long-term dynamics of the phenomenon.Practical implicationsOur findings underscore the critical role of visionary leadership, particularly stemming from the CEO, in driving CE transition. Leaders should articulate a clear vision for sustainability, foster a culture of experimentation and actively identify opportunities for CE implementation. Moreover, our results suggest that organizational culture plays a fundamental role in supporting CE transition. Creating a dedicated sustainability team to coordinate CE initiatives and counter the internal resistance, fostering the engagement of all organizational levels in CE initiatives, developing training programs to enhance CE knowledge and skills throughout the organization and recruiting young talents are some of the key recommendations we posit to firms aiming to start the process of CE transition.Originality/valueThis paper contributes to the emerging literature on “Organizational Change toward a Circular Economy” (OCCE) by providing a processual analysis of organizational change toward the CE. Through an in-depth exploratory study of a fashion firm in transition toward the CE, we were able to identify drivers and resistance factors and to offer a visual map of our findings to graphically show the change toward the CE and the drivers and resistance to change factors that have thus far been under-investigated from an organizational level (Graessler et al., 2024).

Dynamic Flexible Allocation of Slots in Container Line Transport

Due to the imbalance between supply and demand, liner container transportation often faces the problem of low slot utilization, which will occur in the shipping process, such as dry container demand exceeding the available dry slots and reefer slots not being fully utilized. This makes it important and challenging to maintain a balance between the actual demand and the limited number of slots allocated for liner container transport. Therefore, this study proposes a flexible allocation method: expanding the types of containers that can be loaded in the same slot. This method is suitable for handling each dynamic arrival container booking request by shipping enterprises, making decisions to accept or reject, and flexibly allocating shipping slots. In order to maximize the total revenue generated by accepting container booking requests during the entire booking acceptance cycle, we establish a dynamic programming model for the flexible allocation of slots. For model solving, we use the Q-learning reinforcement learning algorithm. Compared with traditional heuristic algorithms, this algorithm can improve solving efficiency and facilitate decision-making at the operational level of shipping enterprises. In terms of model performance, examples of different scales are used for comparison and training; the results are compared with the model without flexible allocation, and it is proved that the model proposed in this paper can obtain higher returns than the model without flexible allocation. The results show that the model and Q-learning algorithm can help enterprises solve the problem of the flexible allocation of shipping slots, and thus, this research has practical significance.

Vocational Education Administration, Bilateral System under the Office of the Vocational Education Commission Kalasin Province

Background and Aims: Vocational education administration Dual system of educational institutions under the Office of the Vocational Education Commission. It is a professional education arrangement that arises from an agreement between an educational institution and a business establishment. The main objective is to develop and train professional skills for students. To prepare for future work the objectives of this research are to study the following: (1) Level of administration of vocational education, dual system, of vocational education in Kalasin Province. According to the standards for managing vocational education in the dual system of the Vocational Education Commission. To assess the quality and efficiency of operations at the operational level. 2) Compare the level of vocational education administration in the dual system of vocational education in Kalasin Province. To find differences in management in various areas and the use of various approaches to develop educational quality. (3) Study guidelines for promoting or developing the administration of vocational education, a dual system, of educational institutions under the Office of the Vocational Education Commission, Kalasin Province. To suggest ways to improve and develop educational administration to be more efficient. Methodology: In this research the sample group used was a total of 196 people. The research tool was a questionnaire with a 5-level rating scale, which had a confidence value of 0.81 and an internal consistency (IOC) in the range of 0.6-1.00. This questionnaire was designed to inquire about the administration of vocational education. Dual system of educational institutions under the Kalasin Provincial Vocational Education Institute. For data analysis use basic statistics, including frequency, percentage, mean, standard deviation and statistical tests used to compare differences, including t-test and F-test. Results: The results of the research found that: (1) Vocational education administration overall, it was at a high level. (2) Results of comparative analysis of opinions regarding vocational education administration classified by position, educational level, and size of educational institution found that there was no difference. (3) Guidelines for developing vocational education administration It is necessary to be supported and encouraged to be able to develop and adapt to the changes in today's industrial world. The various areas that should be developed include: 1) Quality of graduates: They must have knowledge and abilities that are accepted by the industry. 2) Curriculum development: Curriculum should be developed together with entrepreneurs and other stakeholders. 3) Measurement and evaluation: An effective measurement and evaluation system should be developed. 4) Cooperation between Educational institutions and business establishments: There should be strong relationships and cooperation in developing students. Conclusion: Vocational education administration Dual system of educational institutions under the Office of the Vocational Education Commission Kalasin Province. It is necessary to strengthen cooperation between educational institutions and enterprises. By giving the private sector an opportunity to participate in setting criteria and guidelines in various areas to be clear and consistent with the needs of the labor market. In this regard, there should be an effective evaluation process in order for management to be systematic and produce good results.

The Role of Educational Institution Administrators in Operating the Student Care and Assistance System at Vocational Colleges in Chonburi Province

Background and Aims: The objectives of this research are as follows: 1. to study and evaluate the operational level of the student care and assistance system. Students in vocational colleges in Chonburi Province 2. To compare the performance of the student care and assistance system in such colleges classified by status. and 3. to propose guidelines for operations related to the role of school administrators in developing student care and support systems for students in vocational colleges in Chonburi Province. Methodology: The sample group in this research consisted of administrators and teachers from vocational educational institutions in Chonburi province, totaling 269 people, using questionnaires as a tool for collecting data. which has a reliability value of the questionnaire at 0.97. For data analysis, basic statistics were used, including frequency, percentage, mean, and standard deviation. As for hypothesis testing, t-test statistics were used. Results: The finding found that (1) The opinion regarding the role of educational institution administrators in operating the student care and support system Students in vocational colleges in Chonburi Province Overall it is at a high level. (2) Level of opinions regarding the role of educational institution administrators in operating the student care and assistance system, classified by gender, found that overall there was no difference. When considering each aspect, it was found that the areas of student promotion and development were significantly different at the 0.05 level. While knowing each student individually student screening Preventing and solving student problems. And in the forwarding aspect, no differences were found. (3) Level of opinion regarding the role of educational institution administrators in operating the student care and assistance system, classified by status It was found that there was a statistically significant difference at the 0.05 level. Especially in the area of ​​student screening and in the area of ​​student promotion and development. which were significantly different at the 0.05 level, while no differences were found in other aspects. Conclusion: The study discovered that vocational college administrators in Chonburi Province are widely perceived to play an important role in student care and support. While gender had no overall impact on these opinions, there were differences in student promotion and development, and status had a significant influence on perceptions in areas such as student screening and development (p < 0.05).

Numerical modeling of an offshore shellfish farm exposed to extreme wave conditions

Shellfish cultivation is a sustainable method of providing human food and can help remove large amounts of CO2 from the atmosphere. Over the last two decades, longline-based structures have dominated farming systems. So far, the innovative technologies for open-ocean shellfish farming remain stagnant and need to be developed. As such, this paper preliminarily studies the operation and survivability abilities of an innovative shellfish farm under extreme wave conditions. To that end, an efficient numerical scheme with a robust implicit finite element method is established. First, the numerical modeling of a single module of the shellfish farm is conducted and the numerical results are verified against physical model tests. Then, the numerical modeling is implemented in a full-scale shellfish farm containing nine floating rafts with suspended lantern nets in a 3×3 configuration exposed to extreme wave conditions. Different angles of wave attack and shellfish rafts with and without lantern nets are fully considered, allowing an assessment of the operation and survivability abilities of the shellfish farm under extreme wave conditions in various situations. The results highlight that the angle of wave attack significantly affected the energy absorption of the mooring system. Moreover, non-linear instability such as subharmonics, which existed in the motion dynamics, can be manipulated to avoid resonant motions. This study provides insights into the evaluation of the safety design of a shellfish farm at both operational and survivability levels. The numerical method can also model other advanced offshore marine structures with multi-modules, such as floating bridges, airports, and even floating energy islands.