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Entrepreneurship, innovation, marketing and strategy.

Master’s, postgraduate and executive level programs.

The fashion industry has evolved over the generations. Fashion is what defines any person. Your style and quotient statement gives you an edge. In a world which is getting smaller and smaller with evolving mobile and computer technology connectivity, there has been a rise in new startups in personalized fashion. This sector of personal styling has seen an investment of over US$220m in the past two years. Social media is connecting billions of people around the globe. Roposo is the brand of Relevant E-solutions and was launched in 2012. It is the brainchild idea of Avinash Saxena, Kaushal Shubhank and Mayank Bhangadia. It has created a buzz in the fashion and social media industry. This case illustrates the connective power of social media and personalized fashion. Roposo has over 2 million active users which includes a number of Bollywood stars. These users are creating their own stories related to styling and fashion tips and inspiring millions worldwide. The case explores the journey of how Roposo has changed the style statement of millions of people.

The expected learning outcomes are as follows: to identify the new business opportunity in the fashion industry with the use of a social media platform; to understand the evolution of fashion with the boom in social media and mobile communications; to learn how the brand grows and how celebrities are also motivated to be a part of it to connect to their fans for free; to provide inspiration for students to start up an entrepreneurial venture; to find out how the use of recommendation engines should be done to keep users engaged; and to discuss threats of competitors.

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CSS 3: Entrepreneurship.

The purpose of the research is to concentrate on the most important smart metropolitan applications which are smart living, smart security and smart maintainable. In that, Power management and security is a most important problem in the current metropolitan situation.

A smart metropolitan area utilizes recent innovative technologies to improve its living, security and maintainable. The aim of this study is to recognize and resolve the difficulties in metropolitan area applications.

The main aim of this study is to reduce the metropolitan foremost energy consumption, to recharge the electric vehicles and to increase the lifetime of smart street lights.

The hybrid renewable energy street light applies smart resolutions to substructure and facilities in rural and metropolitan areas to create them well. This study will be applying smart metropolitan solar and wind turbine street light using renewable energy for existing areas. In future, the smart street light work will be implemented everywhere else.

Test suite prioritization technique is the process of modifying the order in which tests run to meet certain objectives. Early fault detection and maximum coverage of source code are the main objectives of testing. There are several test suite prioritization approaches that have been proposed at the maintenance phase of software development life cycle. A few works are done on prioritizing test suites that satisfy modified condition decision coverage (MC/DC) criteria which are derived for safety-critical systems. The authors know that it is mandatory to do MC/DC testing for Level A type software according to RTCA/DO178C standards. The paper aims to discuss this issue.

This paper provides a novel method to prioritize the test suites for a system that includes MC/DC criteria along with other important criteria that ensure adequate testing.

In this approach, the authors generate test suites from the input Java program using concolic testing. These test suites are utilized to measure MC/DC% by using the coverage calculator algorithm. Now, use MC/DC% and the execution time of these test suites in the basic particle swarm optimization technique with a modified objective function to prioritize the generated test suites.

The proposed approach maximizes MC/DC% and minimizes the execution time of the test suites. The effectiveness of this approach is validated by experiments on 20 moderate-sized Java programs using average percentage of fault detected metric.