With the acceleration of economic development and urban construction, urban security accidents have occurred around the world with alarming frequency, causing serious casualties and economic losses. Urban security planning and management as emerging areas of research have drawn widespread attention. For city development plans, urban security planning and management have become one of major topics. This paper first outlines the principles of urban security planning and management, combined with the construction of a digital and intelligent platform for urban emergency management. This research then analyzes the core technology and equipment support system of urban security management and its practical application. It also presents a new model based on urban security planning and management, followed by examples of its application in some mega infrastructure development for security planning and design (for example, Singapore Changi Airport and Shanghai Hongqiao Airport Transportation Hub). Additionally, a blast protection concept of urban security planning and management is provided.
In the process of teaching and learning at any stage, the important role of interest guidance cannot be ignored. Especially in college mathematics teaching, mathematical knowledge is very complex and abstract, and most students are unable to effectively understand and master it during the learning process. So it is even more important to fully stimulate students' interest in learning. This article analyzes the significance and current situation of stimulating students' learning interest in university mathematics teaching, and conducts effective strategy analysis. In order to effectively awaken students' desire for knowledge, guide students to change from passive learning to active learning, so that students can continue to grow and progress in this process.
Managing business development related to the innovation of intelligent supply chains is an important task for many companies in the modern world. The study of management mechanisms, their content and interrelations of elements contributes to the optimization of business processes and improvement of efficiency. This article examines the experience of China in the context of the implementation of intelligent supply chains. The study uses the methods of thematic search and systematic literature review. The purpose of the article is to analyze current views on intelligent supply chain management and identify effective business management practices in this area. The analysis included publications devoted to various aspects of supply chain management, innovation, and the implementation of digital technologies. The main findings of the article are as follows: Firstly, the key elements of intelligent supply chain management mechanisms are identified, secondly, successful experiences are summarized and the main challenges that companies face in their implementation are identified. In addition, the article focuses on the gaps in research related to the analysis of successful experiences and the reasons for achieving them.
In the process of the kindergarten project implementation research, we have been thinking: how to combine the early childhood health education with the curriculum gamification concept? How to come from the activities of children's life materials, problems, situations, to close to the way of children's life permeated in children's daily life? How to integrate the GOALS, contents and requirements of health education into the game, attract children's participation, and make children become the subject of learning and development? ... The puzzles are pushing us to project implementation ways and strategies of thinking, to help children improve the level of awareness of health, to improve the attitude to personal hygiene and public health, the good habits of life and health, learning, health habit and the habit of physical exercise, cultivate children's health, happy, confident, studious, good quality.
Introduction: With the adoption of the rural rehabilitation strategy in recent years, China’s rural tourist industry has entered a golden age of growth. Due to the lack of management and decision-support systems, many rural tourist attractions in China experience a “tourist overload” problem during minor holidays or Golden Week, an extended vacation of seven or more consecutive days in mainland China formed by transferring holidays during a specific holiday period. This poses a severe challenge to tourist attractions and relevant management departments. Objective: This study aims to summarize the elements influencing passenger flow by examining the features of rural tourist attractions outside China’s largest cities. Additionally, the study will investigate the variations in the flow of tourists. Method: Grey Model (1,1) is a first-order, single-variable differential equation model used for forecasting trends in data with exponential growth or decline, particularly when dealing with small and incomplete datasets. Four prediction algorithms—the conventional GM(1,1) model, residual time series GM(1,1) model, single-element input BP neural network model, and multi-element input BP network model—were used to anticipate and assess the passenger flow of scenic sites. Result: The multi-input BP neural network model and residual time series GM(1,1) model have significantly higher prediction accuracy than the conventional GM(1,1) model and unit-input BP neural network model. A multi-input BP neural network model and the residual time series GM(1,1) model were used in tandem to develop a short-term passenger flow warning model for rural tourism in China’s outskirts. Conclusion: This model can guide tourists to staggered trips and alleviate the problem of uneven allocation of tourism resources.
The hospital is a complex system, which evolving practices, knowledge, tools, and risks. This study aims to assess the level of knowledge about risks at Hassan II Hospital among healthcare workers (HCWs) working in three COVID-19 units. The action-research method was adopted to address occupational risks associated with the pandemic. The study involved 82 healthcare professionals in the three COVID-19 units mentioned above. All participants stated they were familiar with hospital risks. Seventy-four HCPs reported no knowledge of how to calculate risk criticality, while eight mentioned the Occurrence rating, Severity rating, and Detection rating (OSD) method, considering Occurrence rating, Severity rating, and Detection rating as key elements for risk classification. Staff indicated that managing COVID-19 patients differs from other pathologies due to the pandemic’s evolving protocols. There is a significant lack of information among healthcare professionals about risks associated with COVID-19, highlighting the need for a hospital risk management plan at a subsequent stage.
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