Jisun Kim

A look into the future of wireless mobile communication technologies

The number of wireless mobile communication service subscribers reached 4.6 billion worldwide in 2009, and mobile revenues are expected to be over US

Forecasting wireless communication technologies

1 trillion around 2012 according to the International Telecommunication Union (ITU). A significant number of studies have been made to forecast the growing market and evaluate the new generation technology, the ‘beyond 3rd generation’ (B3G). However, there is no study that forecasts when any of these new technologies will be commercialised. This paper presents a technical framework for forecasting the commercialisation timeline of B3G technologies and provides insight on technology trajectories from 1G to 4G. The results show that a combination of technical parameters can explain heterogeneous wireless mobile communication technologies. Three parameters selected include channel bandwidth, channel bit rate and data capacity for technical framework.

University technology transfer: A conceptual model of impacting factors and phased process

The purpose of the paper is to present a formal comparison of a variety of multiple regression models in technology forecasting for wireless communication. We compare results obtained from multiple regression models to determine whether they provide a superior fitting and forecasting performance. Both techniques predict the year of wireless communication technology introduction from the first (1G) to fourth (4G) generations. This paper intends to identify the key parameters impacting the growth of wireless communications. The comparison of technology forecasting approaches benefits future researchers and practitioners when developing a prediction of future wireless communication technologies. The items of focus will be to understand the relationship between variable selection and model fit. Because the forecasting error was successfully reduced from previous approaches, the quadratic regression methodology is applied to the forecasting of future technology commercialisation. In this study, the data will show that the quadratic regression forecasting technique provides a better fit to the curve.

Policies and Programs for Sustainable Energy Innovations: Renewable Energy and Energy Efficiency

This paper provides a comprehensive review of literature on university technology transfer. The success of nations depends on how efficient research can be translated into commercial products. Universities play a key role in this. There are two major areas that need to be understood to build an efficient technology transfer mechanisms. First are the characteristics of each university. The literature provides evidence that university characteristics play a role. Second is having right set of metrics. Therefore this paper concludes with a set of propositions for impacting factors and a proposed process made up of phases that can be used to measure the technology transfer success accurately.

Forecasting the Electric Transformation in Transportation: The Role of Battery Technology Performance

Preface.- Ch 1 Review of Policies Towards the Acceleration of the Adoption of Renewable Energy Technologies.- Ch 2 Renewable Energy Technology Adoption in the Pacific Northwest.- Ch 3 Evaluating Polices Towards the Adoption of Renewable Energy Technologies.- Ch 4 Assessment of Wind Potential in Kalar Kahar Region by Comparing On-Site Data with NREL Wind Resource Map of Pakistan.- Ch 5 Technological Assessment of Emerging Technologies in Conversion of Municipal Solid Waste of Energy.- Ch 6 Bio-fuel Adoption.- Ch 7 Assessing Alternatives for District Heating.- Ch 8 Technology Adoption.- Ch 9 Portfolio Optimization in the Electricity Market-Investors Perspective.- Ch 10 Energy Efficiency Technologies.- Ch 11 Evaluating Energy Efficiency.- Ch 12 Evaluating Consumer Preferences for Clothes Dryers.- Ch 13 Technology Intelligence on Clothes Dryers.- Ch 14 Furnace Fan Motor Technology Assessment.- Ch 15 Technology Assessment of Insulation Material for Home Construction.

Forecasting New Features and Market Adoption of Wearable Devices Using TRIZ and Growth Curves: Case of Fitness Tracking Products

ABSTRACT In an effort to encourage consumers to purchase electric vehicles (EVs), the government has been funding battery research to solve some of these problems. This paper presents a study using technology forecasting using data envelopment analysis (TFDEA) to forecast future battery performance characteristics. The results were compared against the performance goals established by the US Department of Energy (DOE). We find that the foreseen progress of EV battery performance will be insufficient to meet the DOE projected goals for the range that EVs can travel before running out of power. Therefore, a new battery technology must be developed because the incremental improvements in current battery technologies leave EVs considerably short of the DOE performance specification for longer trip ranges.

Forecasting Super-Efficient Dryers Adoption in the Pacific Northwest

This paper describes the application of a combination of TRIZ and Bass modeling to forecast the technology growth projections for one of the wearable devices, fitness trackers. For the TRIZ modeling, the fitness tracking system was divided into three subsystems and each was analyzed as per the technology trends from current literature. The subsystems’ combined assessment was then visualized via a radar plot. The analysis showed the technology to be in an emergent state with primary growth in the hardware and software subsystem areas. The Bass model showed the market peaking at eight and saturating in 15 years.

Technology Forecasting: Case of 3D Printing

Energy efficiency (EE) is an important source of electricity in the USA, by ways of saving electricity and curbing demand growth through the use of more efficient products, and the Pacific NW is a leading region in the EE efforts in America. Some of these efforts include studies and policies aiming to introduce energy efficient home appliances into the market and boosting its adoption, and organizations such as the Northwest Energy Efficiency Alliance (NEEA) are focused on the development of those studies and policies. As a way to assist and inform NEEA, the present chapter uses the Bass Model as a methodology to predict the adoption of Super-Efficient Clothes Dryers (SED) in the Pacific NW. A literature review is conducted to better understand the role of NEEA and clothes dryers in the EE realm, the model inputs and assumptions are explained and its results are discussed. Conclusions, for both NEEA and for the general EE community are drawn, and future work opportunities are identified.

Technology Forecasting: Case of Electric Vehicle Technology

This purpose of this paper is to try and forecast the adoption rate of “consumer grade” 3D printers for use in a typical United States household. Several assumptions are made. The first assumption is made that the consumer will treat the 3D printer as a “durable good”. The second assumption is that the consumer’s purchasing limit will be

Forecasting Battery Electric Vehicles

1000. The third assumption is that the cost of consumables will be less than the equivalent cost of the product when purchased.