A smart city focuses on enhancing and interconnecting facilities and services through digital technology to offer convenient services for both people and businesses. The basic infrastructure of smart cities consists of modern technologies such as the Internet of Things (IoT), cloud computing and artificial intelligence. These urban areas utilize different networks, such as the Internet and IoT, to share real-time information, improving convenience for the inhabitants. However, the reliance of smart cities on modern technologies exposes them to a range of organized, diverse, and sophisticated cyber threats. Therefore, prioritizing cybersecurity awareness and implementing appropriate measures and solutions are essential to protect the privacy and security of citizens. This study aims to identify cyber threats and their impact on smart cities, as well as the methods and measures required for key areas such as smart government, smart healthcare, smart mobility, smart environment, smart economy, smart living, and smart people. Furthermore, this study seeks to evaluate previous research in this field, establish necessary policies to mitigate these threats, and propose an appropriate model for the infrastructure associated with IT networks in smart cities.

Global trade is based on coordinated factors, that means labor and products are moved from their point of origin to the point of use. Strategies have a significant impact on global trade because they enable the effective development of goods across international borders. The decision making is an important task for the development of Logistics Supply Chain (LSC) infrastructure and process. Decisions on supplier selection, production schedule, transportation routes, inventory levels, pricing strategies, and other issues need to be made. These decisions may have a big influence on customer service, profitability, operational efficiency, and overall competitiveness. The Artificial Intelligence (AI) approach of Fuzzy Preference Ranking Organization Method for Enrichment Evaluation (Fuzzy-Promethee-2) is used to assess the priority selection of the factors associated with the LSC and evaluate the importance in global trade. The role of AI is very useful compare to statistical analysis in terms of decision making. The computational analysis placed promotion of exports as the most important priority out of five selected attributes in LSC, with infrastructure development. The result suggests that LSC depends heavily on export promotion as the most significant attribute. Infrastructural development also appeared another factor influencing LSC. The foreign investment was ranked the lowest. The evaluated results are useful for the policy makers, supply chain managers and the logistics professionals associated with the supply chain management.

The fear of ghosts is a common thing that can be managed as a social condition that turns out to have an impact on the continuity of forest maintenance. Applying a qualitative approach supported by in-depth interview methods, observation, and literature study. This research does not attempt to prove the existence of ghosts or discuss the psychological conditions of people who fear ghosts. The main finding of this research is the reality of the reproduction of stories and experiences of fear of ghosts, as well as the implementation of traditions or rituals related to community activities in the forest. Stories of fear of ghosts with various forms and versions of naming not only enrich the cultural life of the community but also encourage social conditioning in the form of togetherness to agree on the fear of ghosts as a means of creating a social system in order to carry out activities in the forest. The social system is identified in the form of pamali traditions or things that should not be done in the forest, balian rituals to eliminate or treat ghost disturbances, and besoyong rituals to utilize forest products, which then have an impact on the awareness to respect the continuity of these rituals and tradition. So, even though the fear of ghosts can be overcome psychologically and disappear quickly, the reality of respect for the social system related to the forest can still survive. In addition, ghost stories’ reproduction continues to be rolled out and adapted to the times. In turn, ghosts and forest rituals continue to be conditioned into a social system that has implications for forest conservation.

Indonesia has experienced problems with refugees in recent years. Despite not being a state party to the 1951 Refugee Convention, Indonesia is still subject to the principle of non-refoulement as a norm that binds all states (jus cogens). This principle is regulated in Presidential Regulation Number 125 of 2016 and Regulation of the Director General of Immigration of 2016 as basic regulations for handling refugees. However, the principle of non-refoulement is not applied absolutely to refugees in Indonesia. The government is in a difficult situation and seems hesitant in taking a legal political stance, to accept or expel the presence of refugees. This research article aims to evaluate the application of the principle of non-refoulement in Indonesian national law. The findings of this research show that the state cannot apply the principle of non-refoulement to refugees in an absolute manner as it will have an impact on national security stability. The legal position of the Presidential Regulation and the Regulation of the Director General of Immigration contradict other regulations, potentially leading to norm conflicts and legal uncertainty. This regulation cannot be applied in all situations. Although this regulation is binding, its application is highly dependent on the needs and urgency of the country. The principle of non-refoulement does not apply to refugees if their presence threatens national security or disturbs public order in transit countries, especially for Indonesia, which has not ratified the 1951 Refugee Convention. Normatively, the application of this principle can be limited by the Constitution, Immigration Law, the theory of state sovereignty, the theory of primordial monism of national law, the principle of selective immigration policy, the principle of immigration essence, and the principle of immigration traffic control. This provision emphasizes that the application of this principle is relative and can be limited based on state sovereignty and national security interests.

To study the environment of the Kipushi mining locality (LMK), the evolution of its landscape was observed using Landsat images from 2000 to 2020. The evolution of the landscape was generally modified by the unplanned expansion of human settlements, agricultural areas, associated with the increase in firewood collection, carbonization, and exploitation of quarry materials. The problem is that this area has never benefited from change detection studies and the LMK area is very heterogeneous. The objective of the study is to evaluate the performance of classification algorithms and apply change detection to highlight the degradation of the LMK. The first approach concerned the classifications based on the stacking of the analyzed Landsat image bands of 2000 and 2020. And the second method performed the classifications on neo-images derived from concatenations of the spectral indices: Normalized Difference Vegetation Index (NDVI), Normalized Difference Building Index (NDBI) and Normalized Difference Water Index (NDWI). In both cases, the study comparatively examined the performance of five variants of classification algorithms, namely, Maximum Likelihood (ML), Minimum Distance (MD), Neural Network (NN), Parallelepiped (Para) and Spectral Angle Mapper (SAM). The results of the controlled classifications on the stacking of Landsat image bands from 2000 and 2020 were less consistent than those obtained with the index concatenation approach. The Para and DM classification algorithms were less efficient. With their respective Kappa scores ranging from 0.27 (2000 image) to 0.43 (2020 image) for Para and from 0.64 (2000 image) to 0.84 (2020 image) for DM. The results of the SAM classifier were satisfactory for the Kappa score of 0.83 (2000) and 0.88 (2020). The ML and NN were more suitable for the study area. Their respective Kappa scores ranged between 0.91 (image 2000) and 0.99 (image 2020) for the LM algorithm and between 0.95 (image 2000) and 0.96 (image 2020) for the NN algorithm.

This study provides an empirical examination of the design and modification of China’s urban social security programme. In doing so, this study complements the popular assumption regarding the correlation between economic growth and social security development. Focusing on the economic and political motivations behind the ruling party’s decision to implement social security, this study first discusses the modification of urban social security and welfare in China. It then empirically demonstrates the mechanisms behind the system’s operation. This study proposes the following hypothesis: in a country like China, a change in the doctrine of the ruling party will affect government alliances, negating the positive impact of economic growth on the development of social security. In demonstrating this hypothesis, this study identifies a political precondition impacting the explanatory power of popular conceptions of social security development.