Key Note Abstracts

Prof. Kazuo Kiguchi

Department of Mechanical Engineering
Kyushu University, Japan

Future Directions of Human Assist Robot Systems

Many studies of human assist robot systems have been carried out to help daily living activities of physically weak persons in these days. Power-assist robot systems or robotic limbs are examples of the human assist robot system. In order to help the daily living activities of the robot user, the motion intention of the robot user must be estimated in real-time and the estimated motion must be assisted without time delay. Furthermore, the motion of the robot user must be assisted safely. In this presentation, the control methods for the human assist robot systems to help the daily living activities of the physically weak persons are explained. Future directions of the human assist robot systems are also discussed considering the latest related studies.


Prof. Sudharman K. Jayaweera

Communications and Information Sciences Laboratory (CISL)
Dept. of Electrical and Computer Engineering,
University of New Mexico, Albuquerque, NM, USA.

Spectrum Situational Awareness (SSA) with Autonomous Cognitive Radios

Historically, spectrum has been segmented and allocated for different services and systems by regulatory authorities in regions and/or countries. However, with the proliferation of wireless communications technologies for various applications, such static spectrum management has shown to be ineffective and inefficient. In commercial contexts, static spectrum allocations have shown to result in inexcusably wasteful underutilization of spectrum resources. In military, homeland security and emergency communications contexts, on the other hand, static spectrum management is increasingly becoming, simply, unacceptable. In these applications, dynamic spectrum management is not a luxury but a requirement. Dynamic spectrum management, however, requires improved spectrum situational awareness (SSA) capability: The ability to monitor, comprehend and act on RF spectrum.

Many years ago, we envisioned the wideband autonomous cognitive radios (WACR) as a technology solution to providing spectrum situational awareness (SSA). WACRs are radios that can sense and comprehend the state of the overall system made of the radio, spectrum, the network and the end-user and have the ability to self-configure the mode of operation over a wide non-contiguous spectrum range in response to this spectrum state. A WACR achieves spectrum awareness through a process called the wideband spectrum knowledge acquisition. Unlike spectrum sensing discussed in dynamic spectrum sharing (DSS) literature, wideband spectrum knowledge acquisition is aimed at fully characterizing a wide spectrum of interest by not only detecting signals, or the absence of them, but also classifying and associating signals in order to identify all spectral activities. Thus, WACR technology provides an ideal platform to build RF spectrum situational awareness systems needed for defense, military, homeland security and space applications as well as consumer wireless telecommunications.

Recently, there is an increasing desire to achieve spectrum situational awareness over several GHz-wide spectrum. This is a challenging task given the limitation of instantaneous bandwidths of state-of-the-art radios to only several hundred of MHz of spectrum. The WACRs provides a solution by developing a technology that integrates software-defined radios, machine-learning and reconfigurable hardware.

This keynote address will discuss how a comprehensive SSA solution can be developed around the spectrum knowledge acquisition capability of a WACR. Machine-learning aided, context-aware decision-policies are developed to effectively scan several GHz-wide spectrum within the instantaneous bandwidth limitations imposed by state-of-the-art radios. Detected spectral activities are then isolated and relevant features are extracted. The approach calls for on-demand, context-based feature extraction. To handle real-time requirements, a hierarchical SSA framework is developed with the aid of a hierarchical signal classification approach. The hierarchical SSA framework allows for the fact that SSA needs can be dynamic and thus it must be able to support redefining the SSA needs in real-time. For example, at one time the interest may be in distinguishing an out-of-place radar signal in a spectrum band primarily allocated by communications systems, whereas another time it may be to identify a possible GPS spoofing signal before it succeeds. In the hierarchical SSA framework, powerful machine learning techniques are combined with advanced decision-making algorithms to achieve these goals.


Dr. Priyantha Wijayatunga

South Asia Energy Division
Asian Development Bank, Philippines

Role of High-Level Technologies in Sustainable Energy Sector Development

The global trend in energy sector development is mostly concentrated in its environmental sustainability because of the increasing awareness and responsibility of the countries towards addressing climate change and local adverse environmental impacts due to energy sector emissions. Though in the recent past environmental sustainability was the focus of largely the developed countries, currently it is at the forefront of the developing countries agenda too due to its local impact. The large developing countries like China and India are making great strides in this regard with a strong emphasis on clean energy development.

Clean energy development which includes not only the use of renewable energy sources such as hydro, wind and solar power but also increased emphasis on energy efficiency and optimal use of existing energy sector assets, requires increasing use of new and high-level technologies to ensure better use of such interventions. For instance, renewable energy penetration of up to about 20-25% of the system generation capacity can be accommodated in a typical power system without a major issue of system stability. However, any level of penetration beyond these limits require use of non-conventional technologies such as new types of energy storage, variable conventional generation, energy management systems and demand response mechanisms coupled with smart metering. Also, these technology interventions require wide use of information communication technologies to ensure that these new devices can communicate with each other for optimal use of these assets and efficient operation of the overall power system. Similarly, countries with small power systems where subcritical coal power plants used to be the most attractive option for thermal power generation can now adopt liquified natural gas (LNG) fired power plants based on small-scale floating storage and regasification units (FSRU) at competitive generation costs with significantly reduced adverse environmental impacts.

In the case of developing countries, since the power systems are fast growing, they can leapfrog in technology adoption and deployment. For instance, small developing power systems can move towards large scale penetration of renewable energy with storage and small-scale LNG based power generation along with smart metering coupled with demand response for power system control. Asian Development Bank (ADB) is playing a central role in supporting the developing countries in these efforts. Its support has been extended to increase awareness on these technologies and to pilot them to increase confidence in deployment. Also, it has been supporting capacity development to install, operate and maintain these systems with high-level technologies. These activities are funded through several trust funds established within ADB. Some of the recent ADB support included latest energy storage and energy management systems, urban and rural mico-grid pilot projects, mobile technology based business models and energy sharing in small solar home systems, floating solar power systems, smart electricity metering and renewable energy dispatch control systems. These efforts will continue with developing countries increasingly embracing high-level technologies for environmentally sustainable energy system development.


Dr. Sandun Perera

School of Management,
University of Michigan, USA

New Trends in Supply Chain and Operations Management

Techniques used for Operations and Supply Chain Optimization have been adopted in many domains due to their tremendous success; the area of Pricing and Revenue Management is perhaps the best modern example for this. Other emerging applications of these techniques include, but are not limited to, Financial Engineering, Healthcare Management and Business Analytics. The introduction of eminent concepts in Behavioral Economics has taken contemporary supply chain management to a level that is essential for today’s business environment. These new trends in supply chain and operations management will be discussed in this keynote presentation.