Arcot Desai Narasimhalu

Identifying faces using multiple retrievals

During a police investigation, officers often have to sort through hundreds of photographs to identify a suspect. To aid this task, we at the Institute of Systems Science developed and implemented a flexible database system that can retrieve faces using personal information, fuzzy and free-text descriptors, and classification trees.<<ETX>>

Designing the Value Curve for Your Next Innovation

This paper introduces an additional feature to the strategy canvas and value curve that will make innovation designers more effective. The new feature is to let the innovators carry out the designs of their new innovations taking into account both the cost of improving the quality of a parameter that the users value highly and the savings accrued from the drop in provisioning for parameters that users place less emphasis in an innovation.

Management of technology deployed in service innovations

Services form a major portion of the GDP of several nations, especially that of the first world nations. These nations also experience high cost of providing services of different kinds. This has resulted in the displacement of non-customer facing services to countries that can offer them at lower prices. Nations have to be concerned about sustaining their economies even as such off-shoring of services continue to grow. It is therefore important to understand how countries can create those service innovations that will help them retain the growth trajectory of their economies. We believe that the different types of service innovations need different approaches to the use of technologies. This paper review related work, introduce a new perspective on service innovation and identify how technologies can be managed to create optimal value from service innovations.

Innovation Stack - Choosing Innovations for Commercialization

This paper describes a method for enterprises to order the innovations of interest according to a number of parameters including their own business strategy and core competencies. The method takes into account aspects such as ability to create entry barriers and complementary assets. Enterprises can now use this method to both filter out innovations that may not be of interest to them and then order the short listed or selected innovations according to their attractiveness.

A Framework for Technology Transfer

Technology transfer is often perceived to be transfer of intellectual property (IP). Very few realize that there are other means of transferring technology. Most common means of technology transfer is the transfer of the IP alone. While this is interesting in itself, it is not the best means of transferring technology in all cases. IP such as patents, trademark and copyrighted material can easily be transferred in this manner. However, that is the lowest level of technology transfer possible. The next level of technology transfer is the ability to handover technology from the originating team to the recipient team. This involves having the creator(s) of technology innovation working with a team from the recipient side handing over technology and know-how. Transfer of software works best in this manner. This level is followed by the next higher form wherein the person or team creating the intellectual property is transferred over to the recipient company. This would certainly be of immense value in situations where a trade secret is being transferred. Excellent examples of level three technology transfer are leading and bleeding edge technologies in domains such as space and military. The best form of technology transfer is when the team/the entire organization and the culture are transferred over. This is where the most challenges are met in merger and acquisition situations. The paper will illustrate some examples from experience working in a publicly funded research lab

RECAMM: A Research Capability Maturity Model for Managing Technological Innovations

Companies, private and publicly funded research institutions have been engaged in research projects and research programs. This paper describes a research capability maturity model for managing technological innovations. The insights for this proposal were derived from studying a variety of research organizations for managing technological innovations in a publicly funded research institute in Singapore. The model was implemented over a period of time with different degrees of success in Kent Ridge Digital Labs, Singapore which has since been renamed Institute for Infocomm Research. The suggested maturity model has five layers - Ad-Hoc, Directed, Managed, Optimized, and Outsourced. Every research organization is likely to operate in any one of these five levels. The first fours levels can easily be managed entirely within an organization. The transition from the fourth to the fifth level is indeed very challenging and requires establishing the right set of frameworks for collaboration. The paper will describe the relationship between an organizations researchers and the research partners and the issues that become important at each of these levels. Some research organizations may have technology innovation directed research projects that operate across all the five levels. The paper will discuss the nature of technology innovation projects that lend themselves best to each of the five levels

Re-engineering XID Technologies - From Enterprise to Consumer Markets

Several studies have addressed the process of taking ideas to markets but few have shared the experiences of start up companies that have reexamined their product strategies and repositioned their products and services for better revenues and profits. This paper reports the efforts related to repositioning of XID technologies, a start up company, into new markets while continuing to exploit its core technical competencies.

Crossing the Chasm: The XID Technologies Story

XID Technologies is a face processing start up company built initially around a disruptive face recognition technology. The technology innovation came from Kent Ridge Digital Labs, a publicly funded software research laboratory in Singapore. Face recognition is the least intrusive and harmless among the various biometric solutions available in the market. The basic approach to human face recognition is to identify a robust feature set that was unique enough to differentiate amongst the many millions of human faces that the system was required to verify. The technology innovation used by XID framed the problem differently and thereby overcame the challenges posed by poor lighting and tilted or rotated heads. XID developed a pilot application that was in an undiscovered market. This new and yet undiscovered market gave the young company a protection from established face recognition solution vendors focused on well established biometrics markets. XID was emboldened to explore developing solutions for other markets once its initial solutions were accepted. It has now several parallel products under development even as its main offering is being brought to market by some of the large solution integrators. The paper describes the transition of XID from a young one product start up to its present position as a technology and new solution generator

A ubiquitous secure and reliable digital data depository system

The authors present DigiSafe-a secure and reliable system for public or corporation users to store and retrieve valuable digital data over untrusted networks. It is the electronic analogy to the physical safe boxes provided by a bank whereby customers keep their valuable belongings. DigiSafe follows a typical client/server model where online digital data depository services are provided by a service provider: the system is secure, highly reliable, easy to use, and accessable from anywhere.

A Framework for the Integration of Expert Systems with Multimedia Technologies

Abstract Expert system (ES) technology allows the capture and replication of expertise in an application domain. So far, the type of data that is used by an expert system for its reasoning process remains primarily alphanumeric. Image, graphics, and other dynamic data such as voice and video are part of an emerging technology generally termed multimedia technology. This article highlights the critical issues in building a successful application combining the two technologies. Based on these critical issues, it also provides a framework for the integration of multimedia technology with expert systems technology.