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The purpose of the study is to develop a cloud supporting model for green computing. In today's contemporary world, information technology (IT) plays a significant role. Because of the rapid growth of the IT business and the high level of greenhouse gas emissions, salient data centers are increasingly considering green IT techniques to reduce their environmental impacts. Both developing and underdeveloped countries are widely adopting green infrastructure and services over the cloud because of its cost-effectiveness, scalability and guaranteed high uptime. Several studies have investigated the fact that cloud computing provides beyond green information and communication technology (ICT) services and solutions. Therefore, anything offered over clouds also needs to be green to reduce the adverse influence on the environment.

This paper examines the rationale for the use of green ICT in higher education and finds crucial success variables for the implementation of green ICT on the basis of an analysis of chosen educational organizations and interviews with key academic experts from the Universities of Ethiopia, in general, and BuleHora University, in particular.

Finally, this paper described the design and development of a green cloud selection supporting model for green ICTs in higher educational institutions that helps cloud service customers choose the most green cloud-based ICT products as well as services.

This study may be a significant source of new information for green ICT design and implementation in higher education institutions to preserve the environment and its impact on human life.

In India, there are various religions and cultures. Several festivals are celebrated through the year, and a variety of specific foods are prepared for each of the festivals. The aim was to study the extent of consumption of colours during festivals.

A household survey was carried out in the urban areas of Hyderabad among individuals in the age groups 1‐5 years, 6‐18 years and >18 years from three socio‐economic groups – high, middle, and low income – from government quarters. The respondents of the study were interviewed using a food frequency questionnaire to elicit information on the intake of colours during festivals. The festivals selected for the study were Sankranthi, Diwali, Holi and Christmas.

The consumption pattern of various foods among all the subjects of the study during the four festivals indicated that a majority of the subjects (44 per cent) consumed sweetmeats. The intake of tartrazine and sunset yellow was observed to be higher during festivals due to the extensive use of these colours in sweetmeats, savouries and beverages that are most commonly available during festivals. The present investigation showed that there has been a shift in the preferences for foods during festivals (i.e. mainly sweetmeats and the type of colours consumed).

As there was an excessive consumption of yellow colours like tartrazine and sunset yellow and lesser consumption of red colours like ponceau 4R and carmoisine, the Indian government needs to take into consideration such situations when setting maximum permissible limits.

The labor regulatory framework in India provides a conducive environment for social dialogue and collective participation in the organizational decision-making process (Venkata Ratnam, 2009). Using data from a survey of workplace union representatives in the federal state of Maharashtra, India, this paper examines union experiences of social dialogue and collective participation in public services, private manufacturing, and private services sector. Findings indicate that collective worker participation and voice is at best modest in the public services but weak in the private manufacturing and private services. There is evidence of growing employer hostility to unions and employer refusal to engage in a meaningful social dialogue with unions. These findings are discussed within the political economy framework of employment relations in India examining the role of the state and judiciary in employment relations and, the links between political parties and trade unions in India.

This paper is an empirical analysis of first-price sealed-bid procurement auctions in Sweden, with and without combinatorial bidding. The data comprises procurement auctions of identical contracts (road resurfacing) with identical bidders conducted under the same time period (2009-2011) in two different regions in Sweden. Given the comparison of the suppliersʼ offered price per tons of asphalt, we cannot reject the hypothesis of identical distribution of standalone bids generated in both types of auction. The distribution of package bids within the combinatorial format is significantly lower than the distribution of standalone bids within the non-combinatorial format, suggesting substantial cost reduction of allowing package bidding. Also, within the combinatorial format, our analysis of data indicates higher costs when packages are predetermined by the purchaser rather than chosen freely by the suppliers.

Combinatorial procurement auctions are increasingly being employed in the private and public sector as an alternative to simultaneous single contract auctions. This mechanism has the advantage that it enables suppliers to express synergies across bundles of public contracts. This mitigates the exposure problem and also has the potential to both lower the price paid by the procuring authority and to enhance efficiency. This paper provides stylized facts of recently performed combinatorial public procurements in various markets in Sweden.

Based on the aerodynamic loads and dynamic performances of trains, this study aims to investigate the effect of crosswinds and raindrops on intercity trains operating on viaducts to ensure the safe operation of intercity railways in metropolitan areas.

An approach coupled with the Euler multiphase model as well as the standard k-ɛ turbulence model is used to investigate the coupled flow feature surrounding trains and viaducts, including airflow and raindrops, and the numerical results are validated with those of the wind tunnel test. Additionally, the train’s dynamic response and the operating safety region in different crosswind speeds and rainfall is investigated based on train’s aerodynamic loads and the train wheel–rail dynamics simulation.

The aerodynamic loads of trains at varying running speeds exhibit an increasing trend as the increase of wind speed and rainfall intensity. The motion of raindrop particles demonstrates a significant similarity with the airflow in wind and rain environments, as a result of the dominance of airflow and the supplementary impacts of droplets. As the train’s operating speed ranged between 120 and 200 km/h and within a rainfall range of 20–100 mm/h, the safe operating region of trains decreased by 0.56%–7.03%, compared with the no-rain condition (0 mm/h).

The impact of crosswind speeds and rainfall on the train’s aerodynamic safety is studied, including the flow feature of crosswind and different particle-sized raindrops around the train and viaduct, aerodynamic loads coefficients suffered by the intercity train as well as the operating safety region of intercity trains on the viaduct.

Marketing is sometimes viewed as manipulative and as enticing consumers to live beyond their means. Artificial intelligence (AI)-powered systems can change the image of the marketing discipline and improve the marketing decision-making process. This chapter argues that embedding AI in the marketing process can help to alleviate public and consumer concerns about the marketing discipline. AI has the potential to make the marketing process transparent, but this is dependent on trust and privacy variables. Openness about using AI in the customer experience and how it is applied will put marketing on an objective framework. However, marketing decisions will be a mix of data and information mediated by intuition, reasoning, experience and empathy and these are qualities that are associated with marketers. AI customer experience requires decisions that are objective (personalisation) and those that are empathy related.

These authors reported work on cutting oils in our September/October 1972 issue and this paper describes a continuation of their work. The selection of special cutting fluids and lubricants can significantly affect metal cutting operations. Friction forces during metal cutting can increase the amount of work to be done to deform the material, can increase tool wear, and can increase surface roughness of the workpiece. The frictional force can be reduced by the correct selection of cutting oil. In this paper the authors describe work to investigate the performance of molybdenum disulphide and graphite‐based cutting fluids and lubricants when machining mild steel under different processes. The results suggest that graphite‐based fluids give the better results under these experimental conditions.

Introduction: The current study provides a conceptual base for big data analytics in the insurance industry that might be useful for academics, researchers, and practitioners conducting future studies in the respective field.

Purpose: This study intends to investigate the transformative impact of big data analytics in the insurance industry. It elaborates on how advanced data analytics techniques are reshaping the insurance landscape, from customer acquisition and retention to risk modeling, pricing, and claims management.

Methodology: The current study incorporates a thorough review of existing literature, industry reports and academic articles related to big data analytics in the insurance sector. The aim is to develop an in-depth comprehension of the subject by synthesizing key insights and trends.

Findings: The findings underscore the evolutionary potential of the insurance sector through big data analytics, emphasizing its role as a catalyst for innovation, efficiency, and growth. Embracing data-driven strategies is essential for insurers to adapt to evolving market dynamics, meet customer expectations, and maintain a competitive edge in the digital age.