The research paper deals with the role of the place making in eco-tourism through a review of international experiences in the eco-tourism industry and its contribution to advancing the reality of tourism there, and attracting the largest number of tourists. The study is divided into five axes: the first is a study of related concepts, and the second is a study of global experiences, which included three countries: (South Bank (Gabriel's Wharf) - London, Rotterdam in the Netherlands, and dealt with each of Happy Streets and Kendrick Mills, and then the Perak River tourist corridor - Malaysia). As for the third axis, it is concerned with analyzing these experiences to reach the fourth axis, which is related to the practical framework and the field study of the city of Hit and the most important ingredients and capabilities it possesses for environmental tourism attraction, and then analyzing the region to know the types of ecotourism available and that may be available in it, as well as the capabilities and determinants that hinder its availability, as well as Clarifying the types of place making that can be applied in the city of Heat and clarifying some examples of them to advance the environmental tourism situation in it, using the method of making the tourist place. Finally, the fifth axis is related to the conclusions and recommendations that can be taken toadvance the environmental tourism reality of tourist destinations. Place Making Ecotourism Gabriel Wharf Rotterdam Heet Perak River Heet Waterwheels.
With the increasing reliance on microgrids as flexible and sustainable solutions for energy distribution, securing decentralized electricity grids requires robust cybersecurity strategies tailored to microgrid-specific vulnerabilities. The research paper focuses on enhancing detection capabilities and response times in the face of coordinated cyber threats in microgrid systems by implementing advanced technologies, thereby supporting decentralized operations while maintaining robust system performance in the presence of attacks. It utilizes advanced power engineering techniques to strengthen cybersecurity in modern power grids. A real-world CPS testbed was utilized to simulate the smart grid environment and analyze the impact of cyberattack
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One of the diseases on a global scale that causes the main reasons of death is lung cancer. It is considered one of the most lethal diseases in life. Early detection and diagnosis are essential for lung cancer and will provide effective therapy and achieve better outcomes for patients; in recent years, algorithms of Deep Learning have demonstrated crucial promise for their use in medical imaging analysis, especially in lung cancer identification. This paper includes a comparison between a number of different Deep Learning techniques-based models using Computed Tomograph image datasets with traditional Convolution Neural Networks and SequeezeNet models using X-ray data for the automated diagnosis of lung cancer. Although the simple details p
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<span>As a result of numerous applications and low installation costs, wireless sensor networks (WSNs) have expanded excessively. The main concern in the WSN environment is to lower energy consumption amidst nodes while preserving an acceptable level of service quality. Using multi-mobile sinks to reduce the nodes' energy consumption have been considered as an efficient strategy. In such networks, the dynamic network topology created by the sinks mobility makes it a challenging task to deliver the data to the sinks. Thus, in order to provide efficient data dissemination, the sensor nodes will have to readjust the routes to the current position of the mobile sinks. The route re-adjustment process could result in a significant m
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