{"title":"Using innovation science to minimize entrepreneurial risk","authors":"Joseph S. Nadan","doi":"10.1109/INNOTEK.2014.6877372","DOIUrl":"https://doi.org/10.1109/INNOTEK.2014.6877372","url":null,"abstract":"Most universities today encourage their students to experience entrepreneurial activities such as workshops, boot camps, internships, pitch events, competitions, and startups. Although these activities are extremely popular, the resultant startups have very low success rates - typically less than 2%. This situation may be improved by enhancing competencies in both the art and science of innovation such that students will “succeed sooner” rather than “failing fast.” The results of a 2013 survey are presented revealing a large gap between perceived and actual competencies in innovation; and, that less than half of the participants had the innovation skills necessary to have a reasonable chance of being successful in an entrepreneurial activity. What competencies they had were skewed toward the art rather than the science of innovation, a system-level science that studies the behavior of complex systems that are multidisciplinary often including engineering, technology, design and business. Three innovation science methods (Outcome Driven Innovation, I.D.E.A.S! brainstorming and Mind Genomics) illustrate both why innovation is a science and how it may be applied to minimize the risk of entrepreneurship. The paper concludes with a forward-looking overview of the International Association of Innovation Professionals (IAOIP), a global organization that is supporting and certifying innovation professionals, that was founded in January 2013 by the senior editors of the International Journal of Innovation Science (IJIS) now in its sixth year of publication.","PeriodicalId":217120,"journal":{"name":"2014 IEEE Innovations in Technology Conference","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126251847","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Vertical Axis Wind Turbine performance prediction for low wind speed environment","authors":"Franklyn Kanyako, I. Janajreh","doi":"10.1109/INNOTEK.2014.6877366","DOIUrl":"https://doi.org/10.1109/INNOTEK.2014.6877366","url":null,"abstract":"Vertical Axis Wind Turbine is the most favorable for urban wind turbine integration in future smart grid as they do not suffer from frequent change in wind direction, can simply integrate with building architecture, and have better response in turbulence wind flow which is common in urban areas. This work contributes to the development of aerodynamic model for studying Vertical Axis Wind Turbine for low speed environment. Based on the available wind speed at Masdar City (24.4202° N, 54.6132° E) the Double Multiple Stream Tube model (DMST) was developed to predict the performance of small scale fixed pitch VAWT using NACA0015 and NACA0018 airfoils. Numerical simulation is conducted for three-dimensional unsteady flow around the same VAWT model. Comparison of the analytical results with computational fluid dynamics (CFD) simulation has been performed. Both the CFD and DMST results have shown minimum and/or negative torque and performance at lower tip speed ratios for the modeled turbine, which implies the inability of turbine to self start.","PeriodicalId":217120,"journal":{"name":"2014 IEEE Innovations in Technology Conference","volume":"83 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126271449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Optimal distribution network reconfiguration using dynamic fuzzy based genetic algorithm","authors":"A. Asrari, S. Lotfifard","doi":"10.1109/INNOTEK.2014.6877364","DOIUrl":"https://doi.org/10.1109/INNOTEK.2014.6877364","url":null,"abstract":"Optimal reconfiguration of power distribution systems is a complex combinatorial optimization problem with the purpose of identifying a radial network that optimizes given objectives. In this paper, a dynamic fuzzy-based genetic algorithm is presented to find an optimal configuration for the distribution networks that minimizes the total power loss of the network. The efficiency of the proposed algorithm is demonstrated by its application on a 33-bus distribution system. The simulation results demonstrate the superior performance of the proposed method compared to the classic genetic algorithm based methods.","PeriodicalId":217120,"journal":{"name":"2014 IEEE Innovations in Technology Conference","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124195651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
R. Raman, H. Vachhrajani, Avinash Shivdas, Prema Nedungadi
{"title":"Low cost tablets as disruptive educational innovation: modeling its diffusion within Indian K12 system","authors":"R. Raman, H. Vachhrajani, Avinash Shivdas, Prema Nedungadi","doi":"10.1109/INNOTEK.2014.7137053","DOIUrl":"https://doi.org/10.1109/INNOTEK.2014.7137053","url":null,"abstract":"The world of today is not looking for innovations that are mere incremental but those that are disruptive. Aakash, the Low Cost Tablet (LCT) initiative by Indian govt. was launched in 2011 amidst dominance by the likes of Apple, Amazon, and Samsung etc. Single most objective of this initiative was affordable ICT learning tool for the 220+ million students. LCT like Aakash can be seen as a disruptive innovation from the as they are simple to use, cheap, low performing, targeted at low portion of mainstream market and focused on social sectors like education, health to increase access and equity. Within Rogers theory of Diffusion of Innovation, we propose a framework for innovation attributes that can significantly predict student and teacher behavior intentions and motivations towards LCT for use in classrooms. Authors investigate the innovation attributes for adoption of LCT in a social group comprising of (N=121) potential-adopter students and teachers from India. The results revealed that motivations for adopting LCT are strongly associated with innovation attributes like relative advantage, compatibility, ease of use, peer influence, perceived enjoyment and perceived usefulness. Overall, both teachers and students expressed positive attitude towards using LCT as it enhanced their digital literacy skills. Bigger question is to identify what kind of new teacher training program, models and approaches and learning environment are required for successful adoption of educational innovation like LCT. Findings contribute to the design of new pedagogical models that maximizes learning potential of LCTs for K12 education.","PeriodicalId":217120,"journal":{"name":"2014 IEEE Innovations in Technology Conference","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130354771","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}