Traditional Management Methods Research Articles

Efficacy of a full management model in daytime surgery for gastrointestinal polyps based on WeChat: A study protocol for randomized controlled trials.

The objective of this study is to improve the efficiency of daytime surgery for gastrointestinal polyp and ensure the safety of patients. We tried an information management method based on WeChat platform in patients undergoing daytime gastrointestinal polypectomy and to explore the feasibility and effectiveness of a full management model. Five hundred and ninety-three patients were randomly divided into two groups: the control group was treated with traditional management methods and the experimental group was treated with the whole-process management mode based on the WeChat platform. The WeChat platform-based full management model included establishing a day surgery management WeChat group, developing multidisciplinary, full-management protocols and processes for day surgery, establishing an information-based surgical scheduling system and adopting diverse forms of day surgery education and continuity of care. This feature included illustrated brochures, vivid verbal presentations, WeChat public numbers and Internet management platforms. The treatment time, hospitalization cost and patient satisfaction of the two groups were counted. In the experimental group, 408 patients were enrolled. The preoperative waiting time and patients' length of stay were 3 days and 1 day, respectively. The medical and nursing intake time was 7 min. The procedure cancellation rate and postoperative complications rate was 0.07% and 0.02%. In the control group, 185 patients were enrolled in the study, The preoperative waiting time and patients' length of stay was 7 days and 3 days. The medical and nursing intake time was 28 min. The procedure cancellation rate and postoperative complications rate were 0.13% and 0.05%, respectively. The hospitalization costs were reduced by an average of $140/person and the satisfaction scores were higher than the control group. In summary, the preoperative waiting time, medical reception time, surgical cancellation rate, length of hospital stay and hospitalization cost in the observation group were less than those in the control group (p < 0.05). Patient satisfaction scores were significantly higher than those in the control group (p < 0.05). Through the full management model based on WeChat, the preoperative waiting time, medical reception time, surgical cancellation rate, length of hospital stay and hospitalization cost in the experimental group were less than those in the control group. Patient satisfaction scores were significantly higher than those in the control group and the difference was statistically significant.

Empowering E-Commerce: Revolutionizing Inventory Management with Seamless API Integration

In today's dynamic e-commerce markets, effective inventory management is crucial for businesses to thrive. This paper explores the transformative potential of integrating Inventory Management APIs with e-commerce websites to streamline operations, enhance customer satisfaction, and maximize profitability. Beginning with an overview of the challenges posed by traditional inventory management methods in the digital age, we delve into the motivations behind adopting Inventory Management APIs and their alignment with the objectives of modern enterprises. Through a comprehensive literature review, we highlight the key dimensions of consumer behavior in online shopping and their implications for inventory management strategies. The methodology section outlines a systematic approach to developing an e-commerce website seamlessly integrated with an Inventory Management API, emphasizing agile principles and iterative development. Challenges and limitations associated with API reliability, data synchronization, scaling, and security are discussed, alongside strategies for mitigating these challenges. The results section showcases the tangible outcomes of the integration, including improved user experience, operational efficiency, and inventory accuracy. Looking ahead, the paper identifies future directions for geographical expansion, enhanced personalization, community features, mobile app optimization, integration of emerging technologies, and advanced analytics. In conclusion, the integration of Inventory Management APIs with e-commerce websites marks a significant milestone in redefining the standards for online retail, offering a comprehensive solution that combines user-friendly interfaces with robust inventory management capabilities. The findings underscore the importance of a holistic approach to e-commerce, addressing both customer-facing aspects and back-end complexities to drive sustainable growth in the digital marketplace.

Application of Landscape Smart Lighting in Construction Projects

Currently, to effectively construct high-quality smart cities and achieve comprehensive governance goals, various industries must embrace the transformation and upgrading of traditional management methods through the integration of new technologies. Among these, landscape smart lighting serves as a crucial tool for advancing smart city development. By judiciously applying this technology, it is possible to enhance traditional lighting methods and offer people novel experiences in their daily lives. Recognizing this importance, this article analyzes and organizes the content of landscape smart lighting, delves into its system characteristics, and summarizes its principles and practices in the field of architectural engineering as practical references for application scenarios.

REVISITING E-WASTE MANAGEMENT: GLOBAL SCENARIO, STRATEGIES, AND SUSTAINABLE DEVELOPMENT

With rapid population growth, as well as, technological advancement, the generation of e-wastes is increasing day by day and has become a fact of emergent concern for scientific and research communities worldwide. Though the most developed territories generate the highest amount of e-wastes, little efforts has been put towards managing them. European countries, including UK, Germany, and France are managing significant amount of e-wastes responsibly. The informal and unscientific management of e-wastes led to severe health and environmental hazards. The traditional waste management methods, such as, landfilling, and incineration expels significant amount of heavy and toxic chemicals to the environment, leading to severe air, water, and soil pollution. However, proper management strategies for e-wastes not only inhibit the associated harmful effect towards the lives on earth, but also favour circular economy. The sustainability of the strategies for managing e-wastes lie in the responsibility of all stakeholders associated with it. In this review, we have discussed the statistics of global of e-wastes generation and recycling, effect of e-wastes towards lives and the environment, different methodologies of managing e-wastes, and strategies for sustainable e-waste management.

Integrating Water Management Practices with Modern Irrigation Technologies in Aalo, West Siang District, Arunachal Pradesh

This research addresses the imperative of harmonizing traditional water management practices with contemporary irrigation technologies to ensure sustainable water use in Aalo, West Siang District, Arunachal Pradesh. Given the pressing need to optimize water resources for agricultural pursuits while upholding environmental integrity and socio-economic progress, a multidisciplinary methodology is employed. Aalo faces multifaceted challenges such as water scarcity, erratic rainfall patterns, and escalating agricultural demands. While traditional water management methods have historically upheld agricultural livelihoods, the advent of modern irrigation technologies presents promising avenues for bolstering water efficiency, crop productivity, and sustainable development. Through a mixed-methods approach, including quantitative analysis, qualitative assessments, and participatory research methods, the study endeavors to comprehensively understand water management practices and irrigation technologies in Aalo. Surveys, interviews, and field observations will facilitate the assessment of traditional water management systems' efficacy in mitigating water scarcity and supporting agricultural productivity. Concurrently, the study will evaluate the adoption and impact of modern irrigation technologies on water use efficiency, crop yields, and socio-economic indicators in the region. Anticipated findings are poised to unveil synergies and prospects for integrating traditional wisdom with modern irrigation practices to fortify sustainability and resilience in water management. Consequently, the study will offer actionable recommendations targeted at policymakers, agricultural extension services, and local communities. These recommendations encompass preserving traditional water management systems, promoting the uptake of modern irrigation technologies, fostering knowledge exchange, capacity-building initiatives, and nurturing community engagement in water management endeavors. Through these initiatives, the research aims to foster a holistic approach towards sustainable water management practices in Aalo, poised at the nexus of traditional knowledge and contemporary innovation.

Revolutionizing energy management: A two-step optimal day-ahead scheduling approach for advanced distribution systems with enhanced transactional efficiency

This study makes a significant contribution to advancing smart energy management systems, crucial for effective control of energy supply and demand. Traditional methods for optimal energy management in power grids often encounter computational challenges due to the nonline ar and discrete nature of the optimization problem. In response, our research introduces a novel two-step Optimal Day-Ahead Scheduling approach for an Advanced Distribution System. This system incorporates Renewable Energy Sources, Distributed Generation units, Electric Vehicles, and Energy Storage Systems, while also facilitating surplus electricity sales to electricity markets. The proposed optimal day-ahead scheduling involves both central and local controllers collaborating to optimize a unified program. The Active Distribution System engages in electricity transactions with multiple descending energy hubs, including Combined Cooling, Heating, and Power plants. Each energy hub (EH) operator optimizes day-ahead scheduling problems, submitting bids to the distribution system operator. This unique approach integrates Demand Load Curtailment and Time-of-Use schemes as demand response programs in descending energy hubs. Addressing the inherent complexity of this optimization challenge, the study introduces a novel path-finding algorithm leveraging an improved local search operator. The application of this proposed method to a 33-bus system demonstrates significant advantages. Results showcase a notable increase of up to 193% in the benefit of selling electricity, coupled with an impressive 84% reduction in distribution system operating costs, considering base values. This contribution highlights the effectiveness of the proposed approach in optimizing energy transactions and enhancing the overall efficiency of distribution system operations.

Efficient Model on Corp Disease and Pest Detection with Deep Learning

Agricultural production faces significant challenges due to pests and diseases, causing substantial losses in crop yield globally. Traditional methods of pest and disease management are often manual, time-consuming, and prone to errors. In recent years, the integration of artificial intelligence (AI) techniques, particularly deep learning algorithms, with modern information and communication technology has shown promising results in addressing these challenges. This paper presents a comprehensive review of recent advancements in applying deep learning for detecting and classifying agricultural pests, diseases, and weeds. Various deep learning models, including convolutional neural networks (CNNs) such as Faster R-CNN, InceptionV3, DenseNet, and AlexNet, have been explored for their efficacy in identifying pests, diseases, and weeds in crops. While models like Faster R-CNN, InceptionV3, and DenseNet have demonstrated high accuracy rates ranging from 78.71% to 99.62% in classification tasks across different datasets and crops, the AlexNet architecture has also shown promising results in certain applications within agricultural image analysis. Additionally, the development of lightweight CNN architectures and the fusion of deep features with traditional handcrafted features have further enhanced the accuracy and efficiency of detection systems. Furthermore, the review discusses challenges and future research directions in the field, emphasizing the importance of large-scale datasets, model optimization, and real-time applications for practical implementation in agriculture. Overall, the findings highlight the potential of deep learning technologies, including models like AlexNet, in revolutionizing pest and disease management practices, leading to improved crop yield, food security, and sustainable agriculture. Keywords: Agricultural pests, plant diseases, deep learning, convolutional neural networks (CNNs), AlexNet, classification

HR Sphere

In today's dynamic organizational landscape, efficient management of human resources is imperative for sustained growth and competitiveness. The HR Sphere (Employee Management System) is a comprehensive software solution designed to streamline and enhance various aspects of employee management within organizations. This abstract provides an overview of the purpose, features, benefits, scope, methodology, and outcomes of the HR Sphere system. The primary objective of the HR Sphere system is to address the challenges associated with traditional manual methods of employee management, such as attendance tracking, payroll management, and performance evaluation. By leveraging advanced technologies and automation, the system aims to improve operational efficiency, accuracy, and compliance while empowering both HR personnel and employees

Trialling a new method to attract feral cats (Felis catus) in situ – the Mata Hari Judas queen

Context Feral cats are a significant threat to wildlife in Australia and globally. Current feral cat management techniques have limitations that can result in wary, remnant individuals persisting in the landscape and reducing overall pest control efficacy, thus there is a need for additional innovative management techniques. Aims This research aimed to identify whether the Mata Hari Judas technique could be applied to female cats (queens) in situ as a means of attracting and assisting the capture of feral cats. Methods Three queens were induced into prolonged oestrus and contained in enclosures (vennels) in situ with traps attached to capture attracted feral cats. Two vennel treatments were trialled, one housing a Mata Hari Judas queen (queen vennel) and another using auditory and olfactory lures from a Mata Hari Judas queen (faux queen vennel) to compare the attractiveness of the two treatments at three study sites. Camera traps and soil plots were used to monitor and compare cat activity surrounding the vennels prior to, during and after the presence of a Mata Hari Judas queen or her lures. Key results Both vennel treatments attracted multiple feral cats of both sexes, and each trapped one male cat, demonstrating proof of concept for this technique. The queen vennel was significantly more attractive than the faux queen vennel, as demonstrated by higher frequency of cat detections and the duration of time feral cats spent at this vennel. Comparisons between monitoring periods and when the vennels were active showed significant differences in the frequency of cats attracted to the area, further supporting that both the queen and her lures were attractive to cats. Conclusions This research is the first instance where Mata Hari Judas queens have been successfully used in situ to attract and capture feral cats. Future studies should aim to assess this technique in a controlled area with a known cat population to allow for a direct comparison of efficacy with more traditional feral cat management methods. Implications With further refinement, the use of Mata Hari Judas queens in situ could provide an efficient technique for removing remnant cats.

Development of a Real-Time Crowd Flow Prediction and Visualization Platform for Crowd Management

Crowd management at large-scale events and specific facilities is a critical issue from the perspectives of safety and service quality improvement. Traditional methods for crowd management often rely on empirical knowledge, which has limitations in quickly grasping the on-site situation and making decisions on the spot. In this study, we developed a real-time crowd flow prediction and visualization platform incorporating an agent-based crowd simulation and an advanced crowd management system called crowd management platform as a service. In a case study focused on the area around the Tokyo Dome, we demonstrated that capturing pedestrian flow allows for accurate predictions of congestion at the nearest train station up to 10 min in advance. Moreover, the time required to predict the situation 20 min ahead for 3,000 agents was 1 min and 35 s, confirming the feasibility of real-time processing. To enhance the accuracy and reliability of the simulation results, a sensitivity analysis considering errors in pedestrian flow measurement revealed that simple linear models cannot capture the complexity of crowd dynamics adequately. Notably, the agent-based simulation replicated stop-and-go wave patterns observed in actual measurements under specific crowd conditions, confirming the advantage of using agent-based simulations. Finally, we proposed a method that enables facility managers and security personnel to conduct a more comprehensive evaluation. This method integrates their existing experience with the aggregated display of multiple simulation results, which includes consideration of errors in pedestrian flow measurement through a visualization platform.

Comparative Analysis in Indigenous Women's Ecological Practices Across Indonesia: A Systematic Literature Review

Indigenous women in Indonesia have long practiced ecological management and sustainable resource use, deeply embedded in their cultural beliefs, traditional wisdom, and strong connection to the land. However, their specific ecological practices have been the subject of limited research, especially compared to broader studies of the relationship between gender and ethnicity in sectors such as mining. These existing studies often highlight negative impacts on women in general but focus less on the specific practices of indigenous women, especially in relation to their contributions to biodiversity conservation and sustainable use of natural resources. Recognizing this gap, this research aims to conduct an in-depth analysis of the ecological practices of indigenous women in various regions of Indonesia, focusing on their role in environmental conservation and sustainable development. The motivation for this research is to understand how these practices, shaped by cultural, traditional, and land-based relationships, contribute to ecological management and provide lessons for sustainable living. To achieve this, this study used a systematic literature review. The literature review will involve a comprehensive examination of existing academic literature, using databases such as JSTOR, Scopus, and local Indonesian research repositories. Literature selection criteria will include relevance to indigenous practices, focus on ecological management, and contribution to biodiversity conservation. Although specific findings have not been presented, the study expects to reveal a wide variety of indigenous ecological practices. This is expected to include traditional methods of land and resource management, contributions to the resilience of local ecosystems, and sustainable practices passed down from generation to generation. This study aims to highlight the important role of indigenous women in maintaining biodiversity and adapting to environmental change. A multidimensional approach that considers the institutionalization of gender and ethnicity in mining governance, as well as the role of gender and ethnic identity, will be adopted. The findings from this literature review and field study will make a significant contribution to our understanding of the rich ecological knowledge and practices of indigenous women in Indonesia. They will also highlight the importance of incorporating these practices into broader conservation and sustainability efforts, providing policy recommendations for a more inclusive and holistic environmental approach.

Complementary and alternative therapies for managing postoperative pain after lower third molar surgery: a systematic review and network meta-analysis.

The objective of this study was to evaluate the impact of complementary and alternative treatments on postoperative pain following lower third molar surgeries. A comprehensive search of Electronic databases (Embase, MEDLINE via PubMed, and Cochrane Library) and grey literature was conducted up until May 2022. Randomized clinical trials investigating the effect of acupuncture, ozone therapy, laser (LLLT), drainage tube, kinesio-taping, ice therapy, and compressions on pain after LTM surgeries were included. The estimated mean differences (MD) for alternative therapies were pooled using the frequentist approach to random-model network meta-analysis NMA. Eighty-two papers were included in the qualitative analysis; 33 of them were included in the quantitative analyzes. NMA revealed that drainage tube and kinesio-taping were superior in controlling pain 24-hours postoperatively than no-treatment. At 48-hours follow-up, kinesio-taping and LLLT more effective than placebo and drainage tube; and kinesio-taping and LLLT were superior to no treatment. At 72h postoperatively, ozone therapy was superior to placebo; and drainage tube, kinesio-taping, and LLLT were better than no treatment. At 7-days follow-up, ozone and LLLT were superior to placebo; and LLLT and kinesio-taping were superior to no treatment. The SUCRA-ranking placed drainage tube as top-ranking intervention at 48-hours (98.2%) and 72-hours (96%) follow-ups, and ozone (83.5%) at 7-days follow-up. The study findings suggest that these alternative and complementary therapies may be useful in reducing postoperative pain after LTM surgeries, and may offer advantages when combined to traditional pain management methods. Non-pharmacological therapies are gaining popularity among healthcare professionals and patients. This study found that some of these therapies, specifically kinesio-taping and drainage tube were effective in controlling postoperative pain after third molar surgeries. These findings have important implications for clinical practice, as they highlight the potential benefits of incorporating these therapies into postoperative pain management plans.

HUMAN RESOURCE MANAGEMENT IN CHINA UNDER ECONOMIC GLOBALIZATION

Economic globalization is the development characteristic and advantage of modern economy, especially the in-depth development of knowledge economy and people-oriented era, which has become the decisive factor of the world economy in the 21st century. In this context, competition among countries increasingly revolves around the quantity, quality and development level of human resources. This transformation has brought both opportunities and challenges to human resource management (HRM) in China. Economic globalization has prompted China's human resources management concepts to be re-examined and updated, and the field of human resources management has shown a more diversified pattern. The subjects of human resources management are constantly changing, and it is necessary to adjust the human resource’s structure and improve the overall quality of the workforce. While economic globalization has brought opportunities to China, it has also brought tremendous pressure to China's human resources management. Fierce international competition has posed a severe test to human resources and challenged traditional human resource management methods and structures. This article deeply explores the impact of economic globalization on human resource management in China. It analyzes how China's human resources management responds to the emergence of diverse talent market, the growing demand for cross-cultural skills, the fluidity of global talent flows, the need for technology and digital transformation, and the regulation and compliance faced in operations challenge. Globalized environment. By understanding and responding to these changes, China's human resource management can proactively respond to the changing situation and seize the opportunities brought by economic globalization.

Isolation, characterization and application of noble bacteriophages targeting potato common scab pathogen Streptomyces stelliscabiei

Bacteriophages have emerged as promising alternatives to pesticides for controlling bacterial pathogens in crops. Among these pathogens, Streptomyces stelliscabiei (syn. S. stelliscabiei) is a primary causative agent of potato common scab (PCS), resulting in substantial global economic losses. The traditional management methods for PCS face numerous challenges, highlighting the need for effective and environmentally friendly control strategies. In this study, we successfully isolated three novel bacteriophages, namely Psst1, Psst2, and Psst4, which exhibited a broad host range encompassing seven S. stelliscabiei strains. Morphological analysis revealed their distinct features, including an icosahedral head and a non-contractile tail. These phages demonstrated stability across a broad range of temperatures (20–50°C), pH (pH 3–11), and UV exposure time (80 min). Genome sequencing revealed double-stranded DNA phage with open reading frames encoding genes for phage structure, DNA packaging and replication, host lysis and other essential functions. These phages lacked genes for antibiotic resistance, virulence, and toxicity. Average nucleotide identity, phylogenetic, and comparative genomic analyses classified the three phages as members of the Rimavirus genus, with Psst1 and Psst2 representing novel species. All three phages efficiently lysed S. stelliscabiei in the liquid medium and alleviated scab symptom development and reduced pathogen abundance on potato slices. Furthermore, phage treatments of radish seedlings alleviated the growth inhibition caused by S. stelliscabiei with no disease symptoms. In soil potted experiments, phages significantly reduced disease incidence by 40%. This decrease is attributed to a reduction in pathogen density and the selection of S. stelliscabiei strains with reduced virulence and slower growth rates in natural environments. Our study is the first to report the isolation of three novel phages that infect S. stelliscabiei as a host bacterium. These phages exhibit a broad host range, and demonstrate stability under a variety of environmental conditions. Additionally, they demonstrate biocontrol efficacy against bacterial infections in potato slices, radish seedlings, and potted experiments, underscoring their significant potential as biocontrol agents for the effective management of PCS.

Innovations and Future Trends in Storage Pest Management

Current innovations and future trends in storage pest management, with a specific focus on the Indian context. The critical role of effective pest management in agriculture and food security is underscored, considering its impact on economic stability and public health. It begins by detailing the challenges faced in storage pest management, including the variety of pests like insects and rodents, and the damage they inflict on stored agricultural products. It critiques the limitations of traditional pest management methods, particularly chemical control, and highlights emerging issues such as climate change effects and pesticide resistance. The core examines the latest innovations in storage pest management. Advanced chemical approaches like novel pesticides and controlled release formulations are discussed, alongside the rise of nanotechnology applications in pest control, including nano-pesticides and smart delivery systems. The emergence of biological control innovations, particularly new biocontrol agents, and genetic control strategies like the sterile insect technique, marks a significant shift towards more sustainable pest management methods. Additionally, It explores developments in physical and mechanical control methods, emphasizing improved storage facilities and environmental control techniques. Integrated Pest Management (IPM) approaches are identified as a key future trend, promoting holistic and sustainable strategies, with case studies underscoring their success and practical application. It also addresses the vital role of policy and regulatory developments, considering the impact of global regulations and the importance of international cooperation and standards in shaping pest management practices in India. Ethical and environmental considerations form a crucial part of the discourse, focusing on the ecological impact of pest management and the balance between control measures and conservation efforts. It concludes with an examination of practical applications and case studies, providing insights into real-world challenges and the strategies employed to overcome them. Overall, It offers a thorough analysis of the state-of-the-art in storage pest management, highlighting the intersection of innovation, sustainability, and practicality. It aims to provide valuable guidance for researchers, policymakers, and practitioners in the field, contributing to the advancement of more effective, environmentally responsible, and sustainable pest management strategies in India.

МЕТОДОЛОГИЯ СОЗДАНИЯ ИНДИВИДУАЛЬНОЙ МОДЕЛИ ЗДОРОВЬЯ ЧЕЛОВЕКА С ИСПОЛЬЗОВАНИЕМ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА

Background. In the modern world, the role of artificial intelligence in healthcare is becoming increasingly significant, providing new opportunities to transform traditional methods of diagnosis, treatment and medical data management. This technological breakthrough not only improves the efficiency of medical procedures, but also opens up new per-spectives in the prevention and treatment of diseases. The aim. To emphasize the need to create a personalized health model using artificial intelligence to help an individual achieve and maintain optimal health and well-being. In the field of personalized treatment, artificial intelligence plays an important role, taking into account the unique characteristics of each patient. Algorithms analyze genetic information, medical history and responses to previous therapies to develop optimal treatment plans. This opens the way to individualized medicine, where the approach to each patient is based on his or her unique characteristics. Despite all the positive aspects, the introduction of artificial intelligence in healthcare also raises questions of data privacy, ethical issues and technology security. However, if these issues are resolved, artificial intelligence promises to significantly improve the quality and accessibility of medical treatment, opening new horizons in healthcare. Results. In this article, we describe breakthroughs in artificial intelligence technologies and biomedical applications, identify problems of using and further development in medical artificial intelligence systems and summarize the economic, legal and social consequences of using artificial intelligence in healthcare, and propose a scheme for constructing a model of individual human health using artificial intelligence. Conclusion. The results of the analysis of modern scientific literature allow us to draw a conclusion about the potential for creating more effective and personalized approaches to the problem of individual health using integrated artificial intelligence technologies. The proposed methodology can serve as the basis for the development of innovative deci-sion support systems in medicine and improving the quality of medical care.

Pricing longevity bond with affine-jump-diffusion multi-cohort mortality model

Facing increasingly severe longevity problems, traditional longevity risk management methods are no longer the final answer. Longevity risk securitization provides a good hedging method, which transfers the longevity risks to a wider capital market and realizes the cross-market transfer of risks. The pricing process of longevity derivatives depends on the underlying risk factors (stochastic processes of mortality and interest rate). We adopt an affine-jump-diffusion process to model the dynamics of mortality and estimate the model parameters with the actual mortality data in China. The measure implied by the annuity market price is chosen as the risk-neutral pricing measure. We use the Chinese annuity market price to calculate the concrete form of the measure transformation and use the risk-neutral pricing measure thereby to price the longevity bond designed by Denuit et al. (2007).

Rapid pre-typhoon safety inspection system for improving construction site resilience

Coastal cities are vulnerable to typhoon disasters due to their unique geographical location. Although significant progress has been made in the safety early warning system for construction sites, there are few studies on site safety management under typhoon disasters. Moreover, traditional manual methods of on-site emergency management are lagging behind and rigid, making it difficult to respond quickly to safety inspections manually. This study aims to automatically identify safety hazards and provide effective response measures during typhoon warnings, ultimately enhancing the safety of construction sites. Therefore, based on the MATLAB platform, this study developed a rapid safety inspection system (RSS-Typh) for the construction site during the typhoon warning period. In addition, the standard operating procedures (SOP) related to the system are formulated to assist the comprehensive safety inspection of the site before the typhoon and improve the inspection efficiency. The specific operation can be divided into three steps: 1.Using a combination of drones and handheld laser scanners to complete the complete construction site data acquisition in less than 2 h, and complete the modeling and refinement of the point cloud model in 5 h; 2.Using the developed hidden danger detection algorithm based on automatic point cloud to effectively identify the deformation-related hidden dangers at the construction site; 3.Use the designed automatic query security countermeasure GUI system to make rapid rectification. This study assists site managers in swiftly implementing effective safety management on construction sites, elevating the safety level of the site before typhoon. Furthermore, it serves to advance the automation of safety management in construction sites, promoting further developments in this field.

Research on the Application and Effectiveness of the DRG Model on Perioperative Medical Management of Cholecystectomy

Objective: This study aimed to explore the application and effectiveness of the DRG model in the perioperative management of cholecystectomy. By comparing the DRG model with traditional management methods, this study focused on evaluating the potential impact of the DRG model in improving surgical efficiency and reducing complication rates and medical costs. Methods: The random envelope method was used to divide patients scheduled for cholecystectomy from January 2021 to October 2023 into two groups: one group underwent surgery under the DRG model (experimental group), and the other group underwent the traditional management model (control group). Data including basic information, surgery-related data, length of stay, complication records, and medical expenses were collected. Data analysis was carried out using a t-test and chi-square (χ2) test. Results: Results showed that the DRG model shortened the average length of stay, decreased the incidence of complications, reduced medical expenses, and increased patient satisfaction. These results demonstrate the effectiveness of the DRG model in the perioperative management of cholecystectomy, especially in improving surgical efficiency, reducing medical costs, and improving patient satisfaction. Conclusion: The DRG model in the perioperative management of cholecystectomy can significantly improve medical service quality and efficiency and enhance patient satisfaction as compared to traditional treatment methods.

Enhancing Urban Waste Management: Development and Application of Smart Garbage Bin Technologies

With urbanization and population growth, the volume of waste generated is also increasing. Traditional waste management methods may become insufficiently efficient, necessitating more intelligent and sustainable solutions to meet this challenge. In traditional waste management systems, garbage trucks often collect waste according to a fixed schedule without considering the actual fill level of the garbage bins. This can lead to resource wastage and unnecessary carbon emissions. The research background of smart garbage bins is also closely related to environmental protection. By managing waste more effectively, reducing pollution to land and water sources is possible, contributing to achieving sustainable development goals. This study investigates the application of smart waste bin technology in urbanization, focusing on its potential in waste classification and environmental protection. The research encompasses three main stages: system design, prototype construction, and functional testing. In the system design phase, key components such as LED displays, ultrasonic sensors, and servo motors were selected based on functional requirements, and intelligent control was implemented using Arduino boards and the U8g2lib library. During the prototype construction phase, 3D printing and precise assembly were employed to ensure the effective layout of electronic components. The testing phase involved evaluating the performance of humidity sensors, ultrasonic sensors, and voice modules. The test indicates that the smart waste bins perform well in terms of sorting accuracy and ease of operation, but improvements are needed in real-time monitoring and user interaction. Overall, this study provides significant insights into the technological development of smart waste bins and their application in urban environments.