Search Results (22)

Background: Demand for Hamburg’s ambulance rescue system (ARS) in Germany, which is managed by the fire service, increased by more than 10% between 2019 and 2021. This increase was mainly driven by a more than 20% increase in non-critical ambulance rescues, while critical rescues decreased over the same period. Factors contributing to this trend include demographic changes, longer waiting times in primary care and declining quality in out-of-hospital care. To address this issue, the introduction of community emergency paramedics (CEPs)—who provide treatment and advice to patients at home before ambulance services are called—has been proposed as a potential solution to alleviate pressure on the ARS. Methods: In this study, 17 ARS stations in Hamburg, categorized into three operational areas (East, South, West), were analyzed using comprehensive statistical methods such as hypothesis testing, correlation analysis, regression modeling and clustering. Data from 2019 and 2021 were examined to assess the feasibility of integrating CEPs into the existing system. Results: Key findings identified specific stations with high potential for CEP support and optimal mission times (based on time of day, day of week and calendar week) to improve operational efficiency. The impact of regulatory measures introduced during the COVID-19 pandemic was also evident in the 2021 data. Conclusions: Finally, four policy scenarios—taking into account different synergy effects among the 17 stations—are presented, providing projections of the managerial and economic benefits for Hamburg policymakers. These policy implications aim to support the development of a robust CEP strategy to improve the overall efficiency and sustainability of the ARS. Full article

Conducting health monitoring on entire large-scale structures is challenging. Compared to non-critical regions, local damage in critical regions significantly impacts the overall structural performance, with even minor damage posing a threat to structural safety. Therefore, identifying the critical regions of a structure is essential to enable prioritized and focused monitoring, evaluation, and management. This paper proposes a method for identifying critical regions in cable-stayed bridges based on dynamic eigensensitivity analysis. The method integrates the sensitivity of multi-order eigenvalues and eigenvectors with respect to elemental stiffness parameters, designating regions with high sensitivity values as critical. The results demonstrate that the midspan region of the main girder, the longest stay cable, and the junctions between the upper, middle, and lower bridge towers and the foundation are identified as critical regions in a cable-stayed bridge. These findings are consistent with established engineering experience. The proposed critical region identification method holds significant potential for improving the efficiency of health monitoring and assessment, as well as optimizing the allocation of manpower and material resources. Full article

Geological hazards impede regional economy sustainability. To limit their destructive impacts on human life and property, the Chinese government has independently developed automated monitoring and early-warning equipment, which has been deployed in over 250,000 locations nationwide, yielding effective early warnings. The smooth operation of this equipment necessitates substantial human, material, and financial resources for its maintenance. To allocate funds rationally, the Ministry of Finance of China has mandated the urgent establishment of budget standards for the operation and maintenance of automated monitoring and early-warning systems for geological hazards. Addressing the research gap in this area, this study meticulously develops a cost model, subcategorizing operating costs, maintenance costs, and management costs. Addressing the intricate issue of maintenance expenditures, this study ingeniously breaks down routine operations and urgent repairs stipulated in technical standards into personnel, materials, and vehicular needs for each equipment type. Considering the total manpower involved in equipment maintenance, the per-unit maintenance cost is determined. This method allocates costs to individual pieces of equipment, thereby sidestepping the quantification hurdle created by varying types and quantities of monitoring equipment at each monitoring site due to various geological disaster types and magnitudes, and technical personnel’s maintenance responsibility for multiple equipment types in a single operation. Finally, incorporating regional adjustment coefficients, we have formulated theoretical costs for the operation and maintenance of automated monitoring and early-warning equipment for geological hazards. By contrasting theoretical costs with actual project budgets, the error margin is within 2%. Following nationwide consultation, these theoretical costs have been officially endorsed as the budget standard. These standards will lay the groundwork for project budgeting and review, facilitate efficient fund utilization, and ensure the financial sustainability of monitoring and warning systems for geological hazards. Concurrently, this paper bridges the global lack in budget norms for the operation and upkeep of automated geological disaster monitoring systems. The cost calculation model introduced serves as a pivotal reference globally for the evaluation of analogous system’s operations and maintenance expenses. Full article

(1) Background: This work focuses on improving the efficiency of warehouse operations with the goal of promoting efficiency in the logistics industry and mitigating logistics-related labor shortages. Many factors are involved in warehouse operations, such as the optimal allocation of manpower, the optimal layout design, and the use of automatic guided vehicles, which together affect operational efficiency. (2) Methods: In this work, we developed an optimal method for operating a limited number of workers or picking robots in a specific area, coping with cases of sudden disruptions such as a change in picking order or the blockage of aisles. For this purpose, the number of pickers, the storage capacity, and other constraints such as sudden changes in picking orders during the picking process, as well as blockages in the aisles of a warehouse site, are considered. The total travel distance is minimized using Gurobi, an optimization solver. (3) Results: The picking routes were optimized in three different scenarios using the shortest route between the starting point and the picking points, resulting in up to a 31% efficiency improvement in terms of the total distance traveled. (4) Conclusions: The main contribution of this work is that it focuses on the day-to-day work situations of sudden changes in the picking order and the presence of route blocks in real-world logistics warehouse sites. It demonstrates the feasibility of responding to sudden disruptions and simultaneously optimizing picking routes in real time. This work contributes to the overall efficiency of logistics by providing a simple, yet practical, data-driven solution for the optimization of warehouse operations. Full article

Background and Objectives: Presenteeism, when employees continue to work despite being sick, may have increased among intern physicians during the COVID-19 pandemic due to the necessity of performing unfamiliar tasks. This study aimed to investigate the prevalence of presenteeism among intern physicians (IPs) in Thailand, its associated factors, and outcomes. Material and Methods: A total of 254 IPs participated in this cross-sectional study conducted from June to July 2022. Participants completed a nationwide online questionnaire including demographics, financial status, underlying diseases, hospital location and affiliation, department, resource problems, manpower shortage, workload intensity, presenteeism, and its outcomes. IPs were recruited via various social media platforms. Statistical analysis was performed using multivariable zero-inflated Poisson regression and multivariable linear regression. Results: The average age of IPs was 25.5 years (SD 1.9), and 57.5% were female. The majority of IPs reported dealing with resource problems (74.8%), insufficient manpower (94.9%), and intense workload (83.5%). Presenteeism was prevalent among 63.8% of IPs, with the most common of the diseases being allergic rhinitis (31.3%). IPs with underlying diseases had an increased rate of presenteeism (adjusted odds ratio (aOR) 2.50, 95% confidence interval (CI) 1.33–4.55). IPs working in community hospitals during their rotations exhibited a lower rate of presenteeism (aOR 0.39, 95% CI 0.16–0.94) compared to other departments within general or regional hospitals. The IPs frequently exposed to insufficient manpower had an increased rate of presenteeism (aOR 4.35, 95% CI 1.02–20.00) compared to those not exposed. Additionally, IPs with presenteeism had more exhaustion (β 1.40, 95% CI 0.33 to 2.46), lower perceived well-being (β −0.65, 95% CI −1.26 to −0.03), and job satisfaction (β −0.33, 95% CI −0.63 to −0.03). Conclusions: During COVID-19, intern physicians in Thailand often exhibit presenteeism due to physical conditions, resource scarcity, and personnel shortages, impacting exhaustion, well-being, and job satisfaction. Recommendations include assessing healthcare workforces, allocating resources more effectively, enforcing policies to promote responsible use of sick leave, and implementing sick leave systems. Full article

The global economy’s slow recovery has led to an increased need for transformers in organizations in recent years. An optimal strategy for production line optimization is to enhance the allocation of staff at each workstation and increase the amount of operational equipment. The focus of this study is the investigation of the transformer production line. This study carried out a comprehensive examination of manufacturing area one, manufacturing area two, and manufacturing area three, respectively. The findings revealed that the case factory requires enhancements in the allocation of its workers. The simulation approach allows for the implementation of multi-scenario evaluation and adjustment, ensuring optimal utilization of resources in the enhanced production line, hence enhancing production efficiency and total productivity. Implementing both rotational shifts and night shifts in manufacturing area one enhances the overall production efficiency of the manufacturing area. By redistributing the workforce in area two, it proved feasible to manage the production capacity of a manufacturing area and maintain the operation of the gas-phase drying furnace. With regard to the final aspect, it is imperative to enhance the processing time of preprocessing goods in order to guarantee a consistent supply of the appropriate quantity of products. This will effectively minimize production line delays and enhance overall production efficiency. These enhancement strategies aid the manufacturing company in optimizing resource allocation to enhance production efficiency and productivity. Full article

Effective waste management is of paramount importance as it contributes significantly to environmental preservation, mitigates health hazards, and aids in the preservation of precious resources. Conversely, mishandling waste not only presents severe environmental risks but can also disrupt the balance of ecosystems and pose threats to biodiversity. The emission of carbon dioxide, methane, and greenhouse gases (GHGs) can constitute a significant factor in the progression of global warming and climate change, consequently giving rise to atmospheric pollution. This pollution, in turn, has the potential to exacerbate respiratory ailments, elevate the likelihood of cardiovascular disorders, and negatively impact overall public health. Hence, efficient management of trash is extremely crucial in any society. It requires integrating technology and innovative solutions, which can help eradicate this global issue. The internet of things (IoT) is a revolutionary communication paradigm with significant contributions to remote monitoring and control. IoT-based trash management aids remote garbage level monitoring but entails drawbacks like high installation and maintenance costs, increased electronic waste production (53 million metric tons in 2013), and substantial energy consumption for always-vigilant IoT devices. Our research endeavors to formulate a comprehensive model for an efficient and cost-effective waste collection system. It emphasizes the need for global commitment by policymakers, stakeholders, and civil society, working together to achieve a common goal. In order to mitigate the depletion of manpower, fuel resources, and time, our proposed method leverages quick response (QR) codes to enable the remote monitoring of waste bin capacity across diverse city locations. We propose to minimize the deployment of IoT devices, utilizing them only when absolutely necessary and thereby allocating their use exclusively to central garbage collection facilities. Our solution places the onus of monitoring garbage levels at the community level firmly on the shoulders of civilians, demonstrating that a critical aspect of any technology is its ability to interact and collaborate with humans. Within our framework, citizens will employ our proposed mobile application to scan QR codes affixed to waste bins, select the relevant garbage level, and transmit this data to the waste collection teams’ database. Subsequently, these teams will plan for optimized garbage collection procedures, considering parameters such as garbage volume and the most efficient collection routes aimed at minimizing both time and fuel consumption. Full article

Taichung is the center of the Taiwanese precision optical industry. Optics companies are modernized and automated, with most running 24 h production lines. With machines running around the clock, production lines must be assigned engineers to handle unexpected situations. The optical lens industry depends on precision technology. For fully automated production lines, each production process requires an engineer to be on call to troubleshoot production problems in real-time. However, shifts are currently scheduled manually, and the staff of each unit are responsible for scheduling the various production processes for each month. Administrative staff for each engineering department must take half a day to one day to complete the shift for a month, with results that usually do not ensure the best average workload, often leading engineers to question its fairness. Considering the manpower requirements for the actual production line shift and the fairness of balancing shifts, the scope of this study is the shift scheduling of engineering staff in the assembly line to perform different duties during a fixed cycle. The research aims to provide a solution for Glorytek to increase the efficiency of engineering shift scheduling and optimize the allocation of engineering staff. We will compare the duty allocation and efficiency of the current manual shift scheduling system with a new automated one. The results show that the efficiency of shift scheduling arrangements increased by more than 96%, and the maximum number of days of staff attendance (5 days) is less than that for manual assignment (6 days) while still satisfying the shift limits stipulated by the company. Two factors remain when implementing the proposed system. First, due to technical concerns, the internal process of the scheduling arrangement would be shifted from administrative staff to the IT department. Another concern is the inevitable investment in off-the-shelf optimization software. Full article

In this paper, we propose a deterministic shift design model with task-based demand and give the corresponding stochastic version with a probability constraint such that the shift plan designed is staffed with the workforce with a certain probability of performing all given tasks. Since we currently find no suitable methods for solving this stochastic model from the literature related to solving stochastic shift design models, we developed a single-stage heuristic method based on statistics, whose main idea is to reduce the occurrence of manpower shortage by prolonging the resource occupation time of a task, but this leads to a serious waste of resources, which is common in solving resource allocation problems with uncertain durations. To reduce the cost of wastage, we also propose a two-stage heuristic approach that is a two-stage heuristic with an evolutionary strategy. The two heuristics show their effectiveness in solving the proposed stochastic model in numerical experiments, and the two-stage heuristic significantly outperforms the one-stage heuristic in cost optimization and solution time stability. Full article

Ecological cultivation is a promising regime for medicinal plant production. For a long time, unreasonable farming methods have threatened soil health and medicinal agriculture and restricted the sustainable development of ecological agriculture for medicinal plants. However, there is a lack of comprehensive discourse and discussion about the pros and cons of different tillage regimes. Here, the research trend and application prospects of no-tillage (NT) are comprehensively reviewed, and the ecological benefits, challenges, and opportunities of the NT system in ecological agriculture of medicinal plants are scrutinized, aiming to call for an about-face in the sustainable conservation and utilization of both phytomedicine resources and agricultural/ecological resources. An exhaustive literature search in PubMed, Bing, Scopus, and CNKI was performed to outline the research trend in conservation tillage and medicinal plants during the recent four decades. The application of NT has a long history and can reduce tillage frequency and intensity and protect soil from erosion and deterioration. NT is often combined with organic mulch to significantly reduce soil disturbance. NT and stover mulching have the advantages of saving manpower and resources and improving soil quality, crop yield, and quality. The ecological and economic benefits of NT in long-term medicinal plant cultivation could be prominent. In developing medicinal plant cultivation, competing with food crops should be avoided as much as possible, and the impact on the production of major grain crops should be minimized. Therefore, the full utilization of soil resources in forests, mountains, and wasteland is advocated, and sustainable soil utilization is the core issue in the process of land reclamation. NT and stover mulching not only inherit the traditional concept of “natural farming”, conform to the basic laws of ecology, as well as the growth characteristics of medicinal plants, but also protect the ecological environment of the production area. It would become the core strategy of ecological agriculture for medicinal plants. Our summary and discussions would help propose countermeasures to popularize NT and organic mulch, promote relevant research and scientific allocation of resources, and adapt to local conditions to achieve precise management and harmonize conservation and production of medicinal plants. Full article

The outbreak of the COVID-19 pandemic has led construction companies to prioritize the intelligent and optimal scheduling of human resources in construction projects to reduce costs. This study addresses the problem of heterogeneity in human resource scheduling in construction projects, presents a mathematical model with generic human resources as an example, proposes an improved artificial immune system (NAIS) algorithm to solve the problem, and verifies its effectiveness. Experimental results show that the NAIS algorithm achieves the optimal duration of 9 days in just 2 s using the Matrix Laboratory (MATLAB), which is significantly faster than mathematical optimization technique software (CPLEX), thus confirming the feasibility of the NAIS algorithm. Additionally, the average PD values for the NAIS algorithm, calculated for different worker counts, skills, and the number of tasks, were lower compared to the comparison algorithm. Overall, the NAIS algorithm effectively addresses the heterogeneous problem of human resource scheduling in construction projects with multiple modes, thereby optimizing construction engineering labor allocation. Full article

Managing aircraft turnaround is a complex process due to various factors, including passenger handling. Airport ground handling, resource planning, optimal manpower, and equipment utilisation are some cost-cutting strategies, particularly for airlines and ground handling service teams. Scheduled aircraft arrival and departure times are critical aspects of the entire ground management and passenger handling process. This research aimed to optimise airport ground resource allocation for multiple aircraft using machine learning-based prediction methodologies to enhance the prediction of aircraft arrival time, an uncontrollable variable. Our proposed models include a multiple linear regression (MLR) model and a multilayer perceptron (MLP)-based model, both of which are used for predicting round-trip arrival times. Additionally, we developed a MLP-based model for multiclass classification of arrival delays based on departure time and delay from the same airport. Under normal weather conditions and operational scenarios, the models were able to predict round-trip arrival times with a root mean squared error of 8 min for each origin–destination pair and classify arrival delays with an average accuracy of 93.5%. Our findings suggest that machine learning-based approaches can be used to predict round-trip arrival times based on the departure time from the same airport, and thereby accurately estimate the number of actual flight movements per hour well in advance. This predictability enables optimised ground resource planning for multiple aircraft based on constrained airport resource deployment and utilisation. Full article

The production of precast components in the construction industry is a labor-intensive process. The objectives of this study are to prove the feasibility of using rough set theory to classify and weigh impact attributes, and to develop a model to assess the total quantities of labor needed for precast structural elements using a rough set enhanced K-Nearest Neighbor (KNN). Three main building components (beams, girders, and columns) were collected from the production of precast elements in Taiwan. After trimming and analyzing the basic data, the rough set approach is used to classify and weight the attributes into three levels of impact based on their frequency. A rough set enhanced KNN is accordingly developed, yielding an accuracy rate of 92.36%, which is 8.09% higher than the result obtained when using the KNN algorithm. A practical and effective prediction model would assist managers to estimate the manpower requirement of precast projects. Full article

Spent fuel reprocessing is of great significance to the nuclear fuel cycle and the sustainable development of nuclear energy. At the same time, nuclear security radiation incidents in the spent fuel reprocessing plant are also related to national personal and property safety, which play a pivotal role. In this paper, the spent fuel reprocessing plant is divided into four plant areas: the main process area, the three-waste area, the auxiliary equipment area, and the pre-plant area, which are further subdivided into 12 evaluation units. The expert scoring method is used to score and evaluate the possibility of eight basic nuclear accident types in each area, namely radioactive dispersal device, computer nuclear security, destruction of nuclear facilities, transportation nuclear security, internal threat, potential threat, illegal transfer, and theft. According to the professional titles, length of service, education and other qualifications of experts, different weights are assigned to the experts. The scoring results are applied to the Fault Tree Analysis (FTA) of nuclear security events as the probability of basic events, so as to obtain the risk of each basic event. At the same time, the fuzzy comprehensive evaluation method and probability–mathematical statistics method are used to evaluate each evaluation unit to determine the risk of each evaluation unit and the plant area. There results show that the main process area has the highest risk degree, while the pre-plant area has the lowest risk degree, and there is a 1.5-fold relationship. This research provides theoretical and technical support for the safety management and operation of spent fuel reprocessing plants. The analysis results of this paper can be used as a reference for the proportion of nuclear security protection improvements in each plant area, so as to achieve an efficient safety protection effect. The research method in this paper can be also applicable to other similar places by providing as input the corresponding probability of occurrence to obtain the index of its risk degree, so as to reasonably allocate funds and manpower and reduce risks. Full article

Background: COVID-19 is in its epidemic period, and China is still facing the dual risks of import and domestic rebound. To better control the COVID-19 pandemic under the existing conditions, the focus of this study is to simulate the nucleic acid testing for different population size cities in China to influence the spread of COVID-19, assess the situation under different scenarios, the demand for the laboratory testing personnel, material resources, for the implementation of the nucleic acid screening measures, emergency supplies, and the configuration of human resources to provide decision-making basis. Methods: According to the transmission characteristics of COVID-19 and the current prevention and control strategies in China, four epidemic scenarios were assumed. Based on the constructed SVEAI_iQHR model, the number of people infected with COVID-19 in cities with populations of 10 million, 5 million, and 500,000 was analyzed and predicted under the four scenarios, and the demand for laboratory testing resources was evaluated, respectively. Results: For large, medium, and small cities, whether full or regional nucleic acid screening can significantly reduce the epidemic prevention and control strategy of different scenarios laboratory testing resource demand difference is bigger, implement effective non-pharmaceutical interventions and regional nucleic acid screening measures to significantly reduce laboratory testing related resources demand, but will cause varying degrees of inspection staff shortages. Conclusion: There is still an urgent need for laboratory testing manpower in China to implement effective nucleic acid screening measures in the event of an outbreak. Cities or regions with different population sizes and levels of medical resources should flexibly implement prevention and control measures according to specific conditions after the outbreak, assess laboratory testing and human resource need as soon as possible, and prepare and allocate materials and personnel. Full article