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As smart cities become a global topic, interest in smart mobility, the core of smart cities, is also growing. The technology that comes closest to general users is “autonomous driving”. In particular, the successful market entry and establishment of some private companies proved that “autonomous driving” is not technology of the future but imminent reality. However, safety in autonomous vehicles that rely on sensors instead of the driver’s five senses has been the focus of attention from the beginning and continues to be so. In this study, we attempted to counter this interest. Based on the actual data of thirty traffic accidents, assuming the AEBS (Autonomous Emergency Braking System) was installed to assist the driver in safe driving, it was reinterpreted through simulation to see what changes occurred in the accident. In the computer program, PC-Crash, the results were first analyzed through simulation using Euro NCAP (New Car Assessment Program)’s AEBS test standards. Subsequently, the other variables in the AEBS were controlled and the accident was reinterpreted by changing only the angle of the radar detection sensor. As a result, it was confirmed that a total of 27 accidents out of thirty accidents could have been prevented with the AEBS. In addition, it proved that the crash avoidance rate of vehicles gradually increased as the radar angle increased.

The assessment of voltage stability margins is a promising direction for wide-area monitoring systems. Accurate monitoring architectures for long-term voltage instability are typically centralized and lack scalability, while completely decentralized approaches relying on local measurements tend towards inaccuracy. Here we present distributed linear algorithms for the online computation of voltage collapse sensitivity indices. The computations are collectively performed by processors embedded at each bus in the smart grid, using synchronized phasor measurements and communication of voltage phasors between neighboring buses. Our algorithms provably converge to the proper index values, as would be calculated using centralized information, but but do not require any central decision maker for coordination. Modifications of the algorithms to account for generator reactive power limits are discussed. We illustrate the effectiveness of our designs with a case study of the New England 39 bus system. 10 pages, submitted for publication

AbstractThe penetration of financialization into the biocultural geographies of islands builds upon processes of commodification and privatization of environments, entailing enclosures of resource commons, environmental destruction and displacement of people, their livelihoods, knowledge and practices, with implications for sustainability. Against this background I critique the growing literature on acronym models of island development, arguing for more careful consideration of issues concerning democracy, human rights and sustainability. Drawing on the ‘right to the city’ literature, I highlight the importance of the ‘right to the island’ in an effort to move beyond the policy imperatives of MIRAB, SITE and PROFIT. Exercising the right to the island involves cultivating radically pluralistic democracy through struggles for alternative island futures. In so doing it problematizes what it means to develop and achieve sustainability.

Domestic agro-byproduct potential in Korea is estimated to be approximately 4,018 × 103 tons of oil equivalent per year. Majority of agro-byproducts are unused and discarded. These unused agro-byproducts can potentially be converted into solid fuel for value addition. The energy potentials of solid fuels are generally characterized by proximate analysis and measuring calorific value; however, owing to the use of coal and coke, both the analyses could be expensive and time-consuming. Proximate analysis via thermogravimetric analysis is a relatively low cost and less time-consuming method than proximate analysis by ISO method (ISO 18134-1:2015, ISO 18123:2015, ISO 18122:2015). Thermogravimetric analysis-based proximate analysis of four agro-byproducts (pepper stem, perilla stem, corn stalk, and kenaf) was conducted. Additionally, the calorific values obtained from several equations based on the proximate analysis results were compared to that of the calorific value measured using calorimeter. The maximum difference between proximate analysis using thermogravimetric analysis and ISO method was 4.73%p, which was attributed to change in moisture content. It is recommended to measure the moisture content of biomass for 120–150 min (at 105 °C) and ash content for 80–120 min (at 815 °C). Three of the equations indicated a difference of less than 1.5 MJ kg−1 between the TGA-derived and the measured calorific value. For this study, It was determined that both proximate analysis and prediction calorific value can be conducted by thermogravimetric analysis.

Pollution is a significant problem in both industrialized and developing countries, as well as in some developed countries. Heavy metal pollution poses a crucial concern for communities due to its detrimental impact on human health and the long-term well-being of the planet. Heavy metals, such as cadmium, chromium, arsenic, lead, and mercury, do not degrade and can enter the food chain, leading to significant health risks. Therefore, it is essential to monitor and take necessary steps to eliminate heavy metal residues that may be present in food, beverages, and the environment. Although the exact role of nanomaterials in pollution cleanup is still unclear, nanotechnology holds promise as a future solution. In the first part of this comprehensive review, a brief overview of nanoremediation is provided. The subsequent sections delve into various nanomaterials and their potential applications in different pollution cleanup scenarios. Following that, critical analysis is conducted on different nano-remediation methods, including oxidation, adsorption, chemical precipitation, filtration, ion exchange, coagulation-flocculation, and photo-catalysis. Lastly, further suggestions are put forward regarding the future utilization of nanotechnology for more effective and enduring pollution cleanup, particularly in eliminating heavy metals.

To meet international efforts to prevent climate change, the South Korean government is seeking to transform its main power source from coal to natural gas (NG), which emits less carbon dioxide (CO2) than coal. The government needs information about public preferences for increasing NG-fired generation. Therefore, the purpose of this paper is to provide the government with this information by gathering the data on public preferences for increasing NG-fired generation for reducing CO2 emissions, analyzing these data, and obtaining the implications from the analysis. To this end, a survey of 1000 people, after explaining the merits and demerits of NG-fired power, were asked to determine the proper ratio of NG-fired generation by choosing one of six examples: lower than 10%, 10%–20%, 20%–30%, 30%–40%, 40%–50%, and higher than 50%. An interval data model was employed to deal with the data. The average value of the ratio was estimated to be 26.7% with statistical significance, which is greater than the actual value of 22.2% from 2017. Finally, whether and how much some variables such as education level, age, gender, and income level of the respondent affected their preferences for NG-fired generation were investigated.