Fingerprint verification by fusion of optical and capacitive sensors

A few works have been presented so far on information fusion for fingerprint verification. None, however, have explicitly investigated the use of multi-sensor fusion, in other words, the integration of the information provided by multiple devices to capture fingerprint images. In this paper, a multi-sensor fingerprint verification system based on the fusion of optical and capacitive sensors is presented. Reported results show that such a multi-sensor system can perform better than traditional fingerprint matchers based on a single sensor. (C) 2004 Elsevier B.V. All rights reserved

Public Service Delivery: Role of Information and Communication Technology in Improving Governance and Development Impact

The focus of this paper is on improving governance through the use of information and communication technology (ICT) in the delivery of services to the poor, i.e., improving efficiency, accountability, and transparency, and reducing bribery. A number of papers recognize the potential benefits but they also point out that it has not been easy to harness this potential. This paper presents an analysis of effective case studies from developing countries where the benefits have reached a large number of poor citizens. It also identifies the critical success factors for wide-scale deployment. The paper includes cases on the use of ICTs in the management of delivery of public services in health, education, and provision of subsidized food. Cases on electronic delivery of government services, such as providing certificates and licenses to rural populations, which in turn provide entitlements to the poor for subsidized food, fertilizer, and health services are also included. ICT-enabled provision of information to enhance rural income is also covered

Information reuse in dynamic spectrum access

Dynamic spectrum access (DSA), where the permission to use slices of radio spectrum is dynamically shifted (in time an in different geographical areas) across various communications services and applications, has been an area of interest from technical and public policy perspectives over the last decade. The underlying belief is that this will increase spectrum utilization, especially since many spectrum bands are relatively unused, ultimately leading to the creation of new and innovative services that exploit the increase in spectrum availability. Determining whether a slice of spectrum, allocated or licensed to a primary user, is available for use by a secondary user at a certain time and in a certain geographic area is a challenging task. This requires 'context information' which is critical to the operation of DSA. Such context information can be obtained in several ways, with different costs, and different quality/usefulness of the information. In this paper, we describe the challenges in obtaining this context information, the potential for the integration of various sources of context information, and the potential for reuse of such information for related and unrelated purposes such as localization and enforcement of spectrum sharing. Since some of the infrastructure for obtaining finegrained context information is likely to be expensive, the reuse of this infrastructure/information and integration of information from less expensive sources are likely to be essential for the economical and technological viability of DSA. © 2013 IEEE

Faster, Smaller, Cheaper: An Hedonic Price Analysis of PDAs

We compute quality-adjusted price indexes for Personal Digital Assistants (PDAs) for the period 1999-2004, using data on prices and characteristics of 203 models sold by 12 manufacturers. The PDA market is growing in size, it is technologically dynamic with very substantial changes in measured characteristics over time, and it has experienced rapid rates of product introduction. Hedonic regressions consistently show prices to be positively related to processor performance, RAM memory, permanent storage capacity, and battery life, as well as several measures of screen size and quality. Features such as networking, biometric identification, camera, and cellphone capability are also positively associated with price. Hedonic price indexes implied by these regressions decline at an AAGR of 21.1% to 25.6% per year during this period. A matched model price index computed from a subset of observations declines at 18.75% per year. Though these PDA rates of price decline are lower than have been estimated for desktop and laptop PCs, consumers in this "ultra-portable" segment of the computer market appear to have enjoyed substantial welfare gains over the past five years.

IoT Device Fingerprint using Deep Learning

Device Fingerprinting (DFP) is the identification of a device without using its network or other assigned identities including IP address, Medium Access Control (MAC) address, or International Mobile Equipment Identity (IMEI) number. DFP identifies a device using information from the packets which the device uses to communicate over the network. Packets are received at a router and processed to extract the information. In this paper, we worked on the DFP using Inter Arrival Time (IAT). IAT is the time interval between the two consecutive packets received. This has been observed that the IAT is unique for a device because of different hardware and the software used for the device. The existing work on the DFP uses the statistical techniques to analyze the IAT and to further generate the information using which a device can be identified uniquely. This work presents a novel idea of DFP by plotting graphs of IAT for packets with each graph plotting 100 IATs and subsequently processing the resulting graphs for the identification of the device. This approach improves the efficiency to identify a device DFP due to achieved benchmark of the deep learning libraries in the image processing. We configured Raspberry Pi to work as a router and installed our packet sniffer application on the Raspberry Pi . The packet sniffer application captured the packet information from the connected devices in a log file. We connected two Apple devices iPad4 and iPhone 7 Plus to the router and created IAT graphs for these two devices. We used Convolution Neural Network (CNN) to identify the devices and observed the accuracy of 86.7%

Spott : on-the-spot e-commerce for television using deep learning-based video analysis techniques

Spott is an innovative second screen mobile multimedia application which offers viewers relevant information on objects (e.g., clothing, furniture, food) they see and like on their television screens. The application enables interaction between TV audiences and brands, so producers and advertisers can offer potential consumers tailored promotions, e-shop items, and/or free samples. In line with the current views on innovation management, the technological excellence of the Spott application is coupled with iterative user involvement throughout the entire development process. This article discusses both of these aspects and how they impact each other. First, we focus on the technological building blocks that facilitate the (semi-) automatic interactive tagging process of objects in the video streams. The majority of these building blocks extensively make use of novel and state-of-the-art deep learning concepts and methodologies. We show how these deep learning based video analysis techniques facilitate video summarization, semantic keyframe clustering, and (similar) object retrieval. Secondly, we provide insights in user tests that have been performed to evaluate and optimize the application's user experience. The lessons learned from these open field tests have already been an essential input in the technology development and will further shape the future modifications to the Spott application

Employing Information and Communications Technologies in Homes and Cities for the Health and Well-Being of Older People

YesHe X and Sheriff RE (Eds.) Employing ICT in Homes and Cities for the Health and Well-Being of Older People. Workshop Proceedings of ICT4HOP’16. 15-17 Aug 2016. Sichuan University, Chengdu, China.British Council, Researcher Links, Newton Fund, NSF