The global unemployment rate in youth present a much bigger increase compared to adults, which indicates the exclusiveness young people have suffered from the job market. AI, as one of the contributors, will worsen youth’s status by being prioritized as one of the hiring factors. In this case, a survey of 520 respondents of various ages is conducted to check different performances of using AI and viewing AI, especially those who are under 25 years old. By using frequency count, response rate and penetration rate and cross (chi-square) analysis, we have come to three results: 1) young groups present high acceptance towards using AI, both from their frequency of using relevant tools and the areas these tools are applied to; 2) young people share the worries that AI will replace the repetitive labor positions, only after the exposure of personal information; 3) Gen AI tools youth use and application areas are in accordance with the way how they spend their time, so school is the most favorable way for knowledge acquisition. It is easy to infer, based on the above results, that young generation has a rather ambivalent attitude towards AI. On one hand, they are used to using AI and Gen AI tools for the improvement of learning, working or even entertainment. On the other hand, they clearly know how AI will do harm to their lives and what AI’s disadvantages are. This research thus gives rise the emergency of integrating relevant AI acquisition into the present education system and future researches are recommended to explore a successful design of AI acquisition in schools at all levels.
This short communication examines four case studies from the Caribbean and the Philippines to summarize practical lessons on the implementation of nature-based solutions (NbS) for coastal flood protection. Each project, ranging from hybrid breakwaters to mangrove restoration, illustrates the benefits of integrating ecological restoration with participatory governance to enhance coastal resilience. Findings highlight that the effectiveness of NbS is highly site-specific, contingent upon local ecological conditions, governance structures, and socio-economic factors. While these interventions can offer significant co-benefits, including erosion control, biodiversity enrichment, and alternative livelihoods, challenges persist related to maintenance, funding, institutional coordination, and risk of maladaptation. This communication underscores the need to embed NbS within broader adaptation frameworks, combining scientific knowledge and community engagement to achieve durable outcomes. These insights are particularly relevant for low-lying coastal regions and small island developing states facing rising sea levels and intensifying storm impacts.
Wireless Networks are becoming an increasingly important technology that is bringing the world closer together. In this type of network environment there could be more chances of attacks. The packets cannot be easily transferred over the network. It affects network performance degrade. While eavesdropping and message injection can be prevented using cryptographic methods, jamming attacks are much harder to counter. They have been shown to actualize severe Denial-of- Service (DoS) attacks against networks. In Simplest form adversary blocks the packets that are transmitted over wireless network. Typically, jamming attacks has been considered under an external threat model, in which the jammer is not part of the network. To overcome the above problem of network traffic and performance in this paper we have considered a packet hiding methods that can be securely transmit packets over the network. We are addressing the problem of jamming attacks under internal threat model and two schemes are proposed that prevent real-time packet classification of packets by combining hiding scheme based on cryptographic primitives. Keywords: Selective Jamming, Denial-of-Service, Wireless Networks, Packet Classification.
