This research paper examines the role of cloud computing in promoting sustainable development. Cloud Computing (CC) has emerged as a transformative technology that has the potential to reduce the environmental impact of businesses and organizations, while also enabling economic growth and social development. The paper explores the environmental benefits of cloud computing, including energy efficiency, reduced carbon emissions, and the potential for renewable energy integration. It also examines the economic and social benefits of cloud computing, including cost savings, increased productivity, and improved access to technology. The paper concludes by highlighting the potential challenges and opportunities associated with the adoption of cloud computing for sustainable development and identifies key areas for future research and policy action. Overall, the paper argues that cloud computing has the potential to play a critical role in promoting sustainable development, and that further research and policy action are needed to realize its full potential.

This paper presents the engineering basis for a document, Residential Design and Construction Guidelines (hereafter, Guidelines). The Guidelines is developed by the engineers of Build Change and its partners based on their technical reconnaissance after the 2013 earthquake in Bohol on October 15, 2013, and Typhoon Haiyan on November 8, 2013. The Guidelines are centered on the observations of typical residential construction and damage in these areas and the requirements of the 2010 National Structural Code of the Philippines. The Guidelines provide illustrated and simple instructions on residential construction, making them accessible to homeowners and local builders. The Guidelines are designed for disaster-resistant, permanent low-rise housing construction, endorsed by the Department of Public Works and Highways of the Philippines (in March 2016). Increasing understanding and application of the Guidelines in residential construction in earthquake- and typhoon-prone areas will increase the structural safety of houses and the country's resiliency.

The trend toward sustainable city development is associated with intelligent transportation systems (ITS). Automation, efficiency, safety, security, and cost-effectiveness are critical factors in establishing each aspect of a smart city. Real-time data obtained from ITS play an essential role in improving the level of service of road segments, enhancing road safety, and supporting road users with road circumstances information. Travel time information is applicable in travel time maps, decision makings for traffic congestion, dynamic pricing of the network, emergency relief services, traffic flow monitoring, traffic jams management, and air quality analysis. Travel time on a road segment highly depends on geometrical specifications, environmental and weather conditions, traffic flow, and driving behavior. Due to specific driving behavior and road conditions, the above parameters are not essentially applicable in another region. The present research uses the data collected from loop detectors and License Plate Recognition (LPR) systems to develop a Bureau of Public Roads (BPR) model for Iran’s freeway network (Tehran-Qom Freeway). Because of the large amount of data, the SQL server program was used for creating and organizing the database and the BPR model was calibrated using SPSS statistical software. The results of the BPR model were evaluated with an ANOVA test, indicating that the derived model can estimate the travel time at freeway sections with a %5.2 error for the volume-to-capacity ratio (V/C) of less than 0.8.

During the last decades, environmental crises through energy consumption and economic growth were noticed as a growing concern among researchers. The industrial sector is the main part of economic growth in each country using conservative energy and emitting carbon dioxide that causes global warming. The Paris agreement and Kyoto protocol were two agreements to prevent governments from emitting CO2 freely. Purpose of this research was to investigate the cement industry, steel industry, and automobile industry products’ effects on CO2 emissions in Iran and to rank them according to their measured effects on CO2 emissions. The methodology used in this study was to estimate equations with CO2 emissions as a dependent variable and cement, steel, and automobile industries’ products with ordinary least squares (OLS) and generalized moment method (GMM) approaches. Stationary, Johansen cointegration, Durbin-Watson, Breusch-Godfrey, Chow breakpoint, and normal residual tests were checked. In-sample forecasting was implemented to check the precision of the estimation and an updated ranking was reported as a final result to consider which industry has affected CO2 emissions more than the others per unit of production cost. In conclusion, the cement industry, steel industry, and automobile industry had the most positive effects on CO2 emissions, respectively. This result is suitable to prioritize the industries for enhancing green technology and optimizing industrial production for a more sustainable economy.

Uber and its main competitor Lyft are competing aggressively to attract more drivers and in turn limit the access of their competitors in the drivers’ supply base. To control the supply side, it is important to analyze the ride-sharing platforms from drivers’ perspective. Using Uber and Lyft drivers’ online reviews, it is shown that drivers are slightly rating Uber higher than Lyft. Additionally, comparing Uber and Lyft rating trend over time, the analysis shows that they are closely competing to attract more drivers. On the aggregate level, drivers count job flexibility, work/life balance, and meeting new people as the main advantages of working in the ride-sharing platforms. On the other hand, the results show that drivers suffer from insufficient compensation of their op-erating costs, poor job security, experiencing bad riders’ behavior, and poor customer service.