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Notable energy losses and voltage deviation issues in low-voltage radial distribution systems are a major concern for power planners and utility companies because of the integration of electric vehicles (EVs). Electric vehicle charging stations (EVCSs) are the key components in the network where the EVs are equipped to energize their battery. The purpose of this paper is coordinating the EVCS and distributed generation (DG) so as to place them optimally using swarm-based elephant herding optimization techniques by considering energy losses, voltage sensitivity and branch current as key indices. The placement and sizing of the EVCS and DG were found in steps.

The IEEE 33-bus test feeder and 52-bus Indian practical radial networks were used as the test system for the network characteristic analysis. To enhance the system performance, the radial network is divided into zones for the placement of charging stations and dispersed generation units. Balanced coordination is discussed with three defined situations for the EVCS and DG.

The proposed analysis shows that DG collaboration with EVCS with suitable size and location in the network improves the performance in terms of stability and losses.

Stability and loss indices are handled with equal weight factor to find the best solution.

The proposed method is coordinating EVCS and DG in the existing system; the EV integration in the low-voltage side can be incorporated suitably. So, it has societal impact.

In this study, the proposed method shows improved results in terms EVCS and DG integration in the system with minimum losses and voltage sensitivity. The results have been compared with another population-based particle swarm optimization method (PSO). There is an improvement of 18% in terms of total power losses and 9% better result in minimum node voltage as compared to the PSO technique. Also, there is an enhancement of 33% in the defined voltage stability index which shows the proficiency of the proposed analysis.

This paper aims to evaluate the effect of optimal use of rooftop photovoltaic (PV) systems on improving the loss of life (LOL) of distribution transformers, reducing power losses as well as the unbalance rate of the 69-bus distribution network.

The problem is studied in three scenarios, considering different objective functions as multi-objective optimization in balanced and unbalanced operations. Meta-heuristic golden ratio optimization method (GROM) is used to determine the optimal size of the rooftop PV in the network.

The simulation results show that in all scenarios, the GROM by optimally installing the rooftop PV is significantly capable to reduce the transformer distribution loss of loss, unbalance rate and power loss as well as reduce the temperature of the oil and transformer winding. Also, the lowest %LOL, power loss and unbalance rate occurred in the second scenario for the balanced network and first scenario, respectively. In addition, the results showed that the unbalance of the network results in increased power losses and LOL of the distribution transformer.

The better capability of GROM is proved compared with the grey wolf optimization algorithm with better objective function and by achieving better values of LOL, unbalance rate and power loss. The results also showed that the %LOL, unbalance and power losses are weakened compared to without considering the PV cost but the achieved results are realistic and cost-effective.

This paper aims to illustrate the extensive benefits of qualitative data analysis as a rarely undertaken process in post-occupancy evaluation surveys. As a result, there is limited evidence of what occupants say about their buildings, especially for operational parameters, as opposed to how they rate them. While quantitative analyses provide useful information on how workers feel about workplace operational factors, qualitative analyses provide richer information on what aspects of the workplace workers identify as influential to their comfort, well-being and productivity.

The authors analysed 6,938 comments from office buildings worldwide on workers’ perception of workplace operational factors: design, storage, needs, space at desks and storage in their work environments. These factors were analysed based on the buildings’ design intent and use, and the associated comments were coded into positive, negative and balanced comments. The authors used a combination of coding, descriptive analysis, content analysis and word cloud to dissect the comments.

The findings showed that whereas workers rated these operational factors favourably, there were significantly more negative comments about each factor. Also, the Chi-square test showed a significant association (p < 0.01) between the satisfaction scale and the type of comments received for all the operational factors. This means that when a factor is rated high in the satisfaction score (5–7), there were fewer negative and more positive comments and vice versa. The word cloud analysis highlighted vital aspects of the office environment the workers mostly commented on, such as open plan design, natural lighting, space and windows, toilets, facilities, kitchens, meeting room booking systems, storage and furniture.

This study highlights the importance of dissecting building occupants’ comments as integral to building performance monitoring and measurement. These emphasise the richness and value of respondents’ comments and the importance of critically analysing them. A limitation is that only 6,938 comments were viable for analysis because most comments were either incomplete with no meaning or were not provided. This underlines the importance of encouraging respondents to comment and express their feelings in questionnaire surveys. Also, the building use studies questionnaire data set presents extensive opportunities for further analyses of interrelationships between demographics, building characteristics and environmental and operational factors.

The findings from this study can be applied to future projects and facility management to maintain and improve office buildings throughout their life cycle. Also, these findings are essential in predicting the requirements of future workplaces for robust workplace designs and management.

The authors identified specific comments on the performance of workplaces across the globe, showing similarities and differences between sustainable, conventional, commercial and institutional buildings. Specifically, the analysis showed that office workers’ comments do not always corroborate the ratings they give their buildings. There was a significantly higher percentage of negative comments than positive comments despite the high satisfaction scores of the operational factors.

The study evaluates the accident-adjusted dynamic efficiency of public bus operators providing bus transportation services in eight major metropolitan cities of India.

The slack-based measure (SBM)–undesirable window analysis approach is used to gauge the dynamic efficiency levels and identify the sources of inefficiency in bus transportation services. This innovative approach integrates the SBM model developed by Tone (2001, 2004) and the window analysis approach of Charnes et al. (1985). The main advantage of this approach is that one can explicitly incorporate the number of accidents in the production technology specification as an undesirable (bad) output and potently handle the issue of the “curse of dimensionality” in a small sample like ours.

The key empirical findings suggest wide variations in average efficiency levels across sample bus operators in metropolitan cities. The Chennai Transport Corporation is observed as the most efficient and consistent bus operator due to its most stable efficiency performance. The results additionally unveil that the role of managerial inefficiency was diminutive, and the scale-related issues were the real cause of sub-optimal or supra-optimal behaviour of sample bus operators in the resource-utilisation process.

There is an urgent requirement for effective policy intercessions to mitigate the sizeable observed inefficiency in the production process and resolve scale-related issues of public bus operators offering transit services in major metropolitan cities of India.

This paper is maybe the first to assess the dynamic efficiency of public bus transit systems in India's major metropolitan cities after treating accidents.

This study aims to analyze the effectiveness of the spin-off policy which includes clarity of objectives and criteria, implementation and monitoring and evaluation functions.

The method used is a qualitative method with a theme approach and the analytical hierarchy process (AHP). Data were obtained from the results of focus group discussions and AHP questionnaires with informants from Indonesian Sharia Insurance Association (AASI), the sharia life and general insurance industry, the Sharia Supervisory Board, the government and regulators.

The results of the research are the effectiveness of the clarity of goals and criteria has not been realized optimally, the effectiveness of increasing profitability has not been realized, and the effectiveness of the monitoring and evaluation functions by the government and regulators has been realized. The supporting factor that has the highest level of importance is the role of the government and regulator.

The limitation of this research is that it has not used a wider range of profitability test tools and projections. The theoretical implication of this research is as a reference for robust research in identifying spin-off success factors because this study uses a mixed method where qualitative methods are used in the study using data from theory and expert informants from three parties: regulatory parties, associations (AASI) and the insurance company (life insurance and general insurance). These results form the basis for compiling a questionnaire with a quantitative method so that the data is become relevant based on theory (design) and practical side.

Practical implication of the study is that the Islamic insurance industry has to prepare to achieve condition of Tabarru funds and the investment reaches 50% of the main insurance fund. AASI, as the sharia insurance industry organization, continues innovating the most suitable form of spin-off that can be achieved by the Sharia business unit and also continues to coordinate with regulators to discuss existing problems. The government and regulators also support the implementation of the spin-off by providing convenience in various aspects such as spin-off period relaxation and government incentive and relaxation to enhance sharia insurance industry.

The contribution of the results of this research for the government and regulatory agencies is as input in setting policies and regulations related to spin-offs, for the industry is expected to be more prepared in terms of resources, commitment and strategy.

The concept of green urban mobility has emerged as one of the best approaches for promoting environmental-friendly transportation in local communities. Green urban mobility aims to reshape public transportation system and enhance mobility, with emphasis on deploying digital technologies to promote sustainable public transportation. Therefore, this study aims to analyze existing public transportation policies by exploring how local communities can facilitate green urban mobility by developing a sociotechnical urban-based mobility model highlighting key factors that impact regions transitioning toward sustainable transportation.

This study investigates “the role of data for green urban mobility policies toward sustainable public transportation in local communities” in the form of a systematic literature review and insights from Norway. Secondary data from the literature and qualitative analysis of the national transport plan document was descriptively analyzed to provide inference.

Findings from this study provides specific measures and recommendations as actions for achieving a national green mobility practice. More important, findings from this study offers evidence from the Norwegian context to support decision-makers and stakeholders on how sustainable public transportation can be achieved in local communities. In addition, findings present data-driven initiatives being put in place to promote green urban mobility to decrease the footprint from public transportation in local municipalities.

This study provides green mobility policies as mechanisms to be used to achieve a sustainable public transportation in local communities. Practically, this study advocates for the use of data to support green urban mobility for transport providers, businesses and municipalities administration by analyzing and forecasting mobility demand and supply in terms of route, cost, time, network connection and mode choice.

This study provides factors that would promote public and nonmotorized transportation and also aid toward achieving a national green urban mobility strategy. Socially, findings from this study provides evidence on specific green urban mobility measures to be adopted by stakeholders in local communities.

This study presents a sociotechnical urban-based mobility model that is positioned between the intersection of “human behavior” and “infrastructural design” grounded on the factors that influence green urban mobility policies for local communities transiting to a sustainable public transportation. Also, this study explores key factors that may influence green urban mobility policies for local communities toward achieving a more sustainable public transportation leading to a more inclusive, equitable and accessible urban environment.

The purpose of the study is distributed generation planning in a radial delivery framework to identify an appropriate location with a suitable rating of DG units energized by renewable energy resources to scale back the power loss and to recover the voltage levels. Though several algorithms have already been proposed through the target of power loss reduction and voltage stability enhancement, further optimization of the objectives is improved by using a combination of heuristic algorithms like DE and particle swarm optimization (PSO).

The identification of the candidate buses for the location of DG units and optimal rating of DG units is found by a combined differential evolution (DE) and PSO algorithm. In the combined strategy of DE and PSO, the key merits of both algorithms are combined. The DE algorithm prevents the individuals from getting trapped into the local optimum, thereby providing efficient global optimization. At the same time, PSO provides a fast convergence rate by providing the best particle among the entire iteration to obtain the best fitness value.

The proposed DE-PSO takes advantage of the global optimization of DE and the convergence rate of PSO. The different case studies of multiple DG types are carried out for the suggested procedure for the 33- and 69-bus radial delivery frameworks and a real 16-bus distribution substation in Tamil Nadu to show the effectiveness of the proposed methodology and distribution system performance. From the obtained results, there is a substantial decrease in the power loss and an improvement of voltage levels across all the buses of the system, thereby maintaining the distribution system within the framework of system operation and safety constraints.

A comparison of an equivalent system with the DE, PSO algorithm when used separately and other algorithms available in literature shows that the proposed method results in an improved performance in terms of the convergence rate and objective function values. Finally, an economic benefit analysis is performed if a photo-voltaic based DG unit is allocated in the considered test systems.

The purpose of this paper is to present a verification methodology for custom micro coded components designed for Avionics projects. Every electronic hardware which will be developed for an aircraft must be designed with the compliance of DO-254 processes. Requirements are the key elements of the aviation. All the requirements must be covered by the design to be considered as completed. Therefore, verification of the custom micro coded components against requirements should be comprehensively addressed. The verification using the manual testing approach is less preferable, as humans can possibly make mistakes. Therefore, the most used verification method today is the automated simulation.

The industry has developed a common methodology for generating automated testbenches by following the standardized guideline. This methodology is named as the universal verification methodology (UVM). In this paper, the verification study of ARINC-429 data bus digital design is presented to describe the DO-254 verification process using the UVM.

The results are supported with functional coverage and code coverage in addition to the assertions. It is observed that the design worked correctly.

To the best of the authors’ knowledge, this is the first study comprehensively describing the DO-254 verification process and demonstrating it by the UVM application of ARINC-429 on programmable logic devices.

Smart cities are concepts much loved by politicians and technologists but are very difficult to bring about in practice. There are many isolated applications in cities such as operating streetlamps, but very few, if any, examples of integrated applications sharing data and managing the city as a holistic entity rather than a set of disparate and unconnected applications. This is despite hundreds of trials and indicates how difficult bringing about a smart city will be. The key challenge is the wide range of interested parties in a city including the elected city authority, subcontractors and suppliers to the authority, emergency services, transport providers, businesses, residents, workers, tourists, and other visitors. Some of these entities will be primarily driven by finance, such as businesses and transport providers. Some will be driven by political considerations. Some will be concerned with the quality of life as well as financial costs. In some cases, there will be conflicting interests – the city may want as much information as possible on people in the city, whereas individuals may want privacy and the minimum data stored concerning their movements and attributes. COVID-19 does not change any of these issues, but it does increase the importance of some applications such as smart health, logistics, people surveillance, data security, and crisis management, while reducing the importance of others such as traffic management. It may result in more willingness for monitoring and data sharing if this can be shown to result in better control of the virus.

Open data are characterized by a number of economic, environmental, technological, innovative, and social benefits. They are seen as a significant contributor to the city’s transformation into smart city. This is all the more so when the society is on the border of Society 5.0, that is, shift from the information society to a super smart society or society of imagination takes place. However, the question constantly asked by open data experts is, what are the key factors to be met and satisfied in order to achieve promised benefits? The current trend of openness suggests that the principle of openness should be followed not only by data but also research, education, software, standard, hardware, etc., it should become a philosophy to be followed at different levels, in different domains. This should ensure greater transparency, eliminating inequalities, promoting, and achieving sustainable development goals (SDGs). Therefore, many agendas (sustainable development strategies, action plans) now have openness as a prerequisite. This chapter deals with concepts of open (government) data and Society 5.0 pointing to their common objectives, providing some success stories of open data use in smart cities or transformation of cities toward smart cities, mapping them to the features of the Society 5.0. We believe that this trend develops a new form of society, which we refer to as “open data-driven society.” It forms a bridge from Society 4.0 to Society 5.0. This chapter attempts to identify the role of openness in promoting human-centric smart society, smart city, and smart living.