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The development of the combined voltage reference and temperature sensor is focused on the RFID applications. The passive RFID systems derive power in the tag solely from rectifying the incident RF power. The dc power supply may be coupled with the RF signal, voltage drop, and noise. The voltage reference here is to provide a stable voltage for well‐biasing the internal analog circuitry. For the temperature sensing RFID applications, the combined device also gives a highly linear temperature sensor for wide‐temperature range measurements. Seeks to discuss this subject.

For voltage reference design, a self‐PTAT current is generated for compensating the diode‐connected NMOS transistor to achieve temperature‐stable voltage reference. Moreover, a temperature sensor with high linearity is developed by amplifying the linear portion and restricting the nonlinear part of temperature information.

Owing to better‐compensation, the voltage reference provides a stable voltage of 718.7±2.9 mV, and the temperature sensor has linearity over 99.8 percent for a wide‐temperature operation from −50 to 150°C.

Owing to the small size, 0.38 × 0.24 mm², of the combined device, it can be embedded into a RFID tag without increasing the RFID size. The voltage reference can serve as a stable voltage for stabilizing the behavior of analog circuits of the tag, and the temperature sensor probes the environment temperature. Then the information will be delivered to the RFID reader by the tag.

To review the innovative products of a particular UK company.

Looks at the history and philosophy of the company, the design and advantages of their brand authenticator product, and then presents their latest spectrophotometric instruments.

Starting in the field of miniature spectrophotometers, which soon became very competitive, the company found a niche market and developed an instrument well‐suited to that market. Their latest products build on that success.

An encouraging report for technologists and entrepreneurs.

To report on the evaluation of error of a face matching system consisting of a 3D sensor for obtaining the surface of the face, and a two‐stage matching algorithm that matches the sensed surface to a model surface.

Rigid mannikin face that was, otherwise, fairly realistic was obtained, and several sensing and matching experiments were performed. Pose position, lighting and face color were controlled.

The combined sensor‐matching system typically reported correct face surface matches with trimmed RMS error of 0.5 mm or less for a generous volume of parameters, including roll, pitch, yaw, position, lighting, and facecolor. Error accelerated beyond this “approximately frontal” set of parameters. Mannikin results are compared to results with thousands of cases of real faces. The sensor accuracy is not a limiting component of the system, but supports the application well.

The sensor supports the application well (except for the current cost). Equal error rates achieved appear to be practical for face verification.

No similar report is known for sensing faces.

This paper aims to provide an overview of the electronic product code (EPC) and related RFID standards that are currently being rolled out in the retail industry.

It considers the EPC numbering schemes, air interface protocols, middleware aspects as well as scenarios for practical use.

Identifies possibilities and limitations of EPC standards, the current status of technology adoption and future fields of application.

Of interest to those concerned with RFID technology selection and infrastructure development.

This paper describes the development of a novel automated vision system used to detect the visual defects on painted slates.

The vision system that has been developed consists of two major components covering the opto‐mechanical and algorithmical aspects of the system. The first component addresses issues including the mechanical implementation and interfacing the inspection system with the development of a fast image processing procedure able to identify visual defects present on the slate surface.

The inspection system was developed on 400 slates to determine the threshold settings that give the best trade‐off between no false positive triggers and correct defect identification. The developed system was tested on more than 300 fresh slates and the success rate for correct identification of acceptable and defective slates was 99.32 per cent for defect free slates based on 148 samples and 96.91 per cent for defective slates based on 162 samples.

The experimental data indicates that automating the inspection of painted slates can be achieved and installation in a factory is a realistic target. Testing the devised inspection system in a factory‐type environment was an important part of the development process as this enabled us to develop the mechanical system and the image processing algorithm able to perform slate inspection in an industrial environment. The overall performance of the system indicates that the proposed solution can be considered as a replacement for the existing manual inspection system.

The development of a real‐time automated system for inspecting painted slates proved to be a difficult task since the slate surface is dark coloured, glossy, has depth profile non‐uniformities and is being transported at high speeds on a conveyor. In order to address these issues, the system described in this paper proposed a number of novel solutions including the illumination set‐up and the development of multi‐component image‐processing inspection algorithm.

To describe the light detection and ranging (LIDAR) technique and to discuss recent surveys by Environment Canada which have employed a novel scanning LIDAR system, the “RASCAL”, to study air pollution in British Columbia.

The RASCAL LIDAR system is based on a Nd:YAG laser which emits 0.5 J pulses of IR light at 1,064 nm and green light at 532 nm into the atmosphere at a rate of 20 Hz. The beam is steered by two 24‐inch mirrors and the backscattered signal is detected by a system based on high sensitivity avalanche photodiodes and photomultiplier tubes. The unit is mobile and housed in a small van.

Surveys with the mobile LIDAR identified and located sources of airborne particulate pollution at various locations in British Columbia. A series of high‐resolution elevation scans revealed the complex vertical structure of aerosol layers above the town of Golden. An outcome of this survey was the introduction of local laws banning wood‐burning stoves in new homes in the region. Further, Saharan sand was identified in the atmosphere in the region for the first time.

The surveys showed that mobile LIDAR can detect and characterise airborne particulate pollution and contribute to an understanding of its dispersion and motion in the atmosphere. It will also aid in assessing the associated risks to human health.

This research project focuses on developing techniques and technologies for automatically identifying human faces from images in the situations where face sample collections in the database as well as in the input query images are “as is”, i.e. no standard data collection environment is available. The developed method can also be used in other biometric applications.

The specific method presented in this paper is called scale independent identification (SII). SII allows direct “comparison” between two images in terms of whether the two objects (e.g. faces) in the two images are the same object (i.e. the same individual). SII is developed by extensively using the matrix computation theory and in particular, the singular value decomposition theory.

It is found that almost all the existing methods in the literature or technologies in the market require that a normalization in scale be done before any identification processing. However, it is also found that normalization in scale not only adds additional processing complexity, but also may reduce the identification accuracy. In addition, it is difficult to anticipate an “optimal” scale in advance. The developed SII complements the existing methods in all these aspects.

The only limitation which is also the limitation for many other biometric identification methods is that each object (e.g. individual in human face identification) must have a sufficient number of training samples collected before the method works well.

SII is particularly suitable in law enforcement and/or intelligence applications in which it is difficult or impossible to collect data in a standard, “clean” environment.

The SII method is new, and the paper should be interesting to researchers or engineers in this area, and should also be interesting to companies developing any biometrics‐based identification technologies as well as government agencies.

The purpose of this paper is to outline the level of audible carbon monoxide (CO) alarm ownership. In this particular paper the data collected by the fire and rescue services from West Midlands and Merseyside will be analysed, and discussed.

Research was conducted in two stages. Using the indices of multiple deprivation identified whether households in the top and bottom four areas owned an audible alarm. In stage two data loggers were placed into homes to take readings every minute for a total period of three days to three weeks.

There was a noticeable trend that deprived areas were less likely to own audible CO alarms than homes in non-deprived areas. All homes surveyed in stage two had CO levels >0 which further emphasises that anyone can be under health risk and that perhaps the maintenance of gas appliances and other sources is not being conducted at regular intervals.

This paper aims to raise awareness regarding not only the symptoms during CO poisoning but also the ones that have been reported to occur after treatment. It will also disseminate information as to what areas have low alarm ownership and thus more at risk of poisoning. It is hoped that findings from papers such as this one will promote more stringent maintenance and replacement requirements for gas or solid fuel appliances.

Pilot study for the comparison of two English cities has not been conducted before and may lead to more studies of this kind.

The paper aims to characterize anomaly detection in hyperspectral imagery.

This paper develops an adaptive causal anomaly detector (ACAD) to investigate several issues encountered in hyperspectral image analysis which have not been addressed in the past. It also designs extensive synthetic image‐based computer simulations and real image experiments to substantiate the work proposed in this paper.

This paper developed an ACAD and custom‐designed computer simulations and real image experiments to successfully address several issues in characterizing anomalies for detection, which are – first, how large size for a target to be considered as an anomaly? Second, how an anomaly responds to its proximity? Third, how sensitive for an anomaly to noise? Finally, how different anomalies to be detected? Additionally, it also demonstrated that the proposed ACAD can be implemented in real time processing and implementation.

This paper is the first work on investigation of several issues related to anomaly detection in hyperspectral imagery via extensive synthetic image‐based computer simulations and real image experiments. In addition, it also develops a new developed an ACAD to address these issues and substantiate its performance.

To design an efficient and integrated framework for automated and simple data acquisition and processing targeted for first response scenarios.

Utilizes existing software/hardware integration tools and primarily off‐the‐shelf components. Use the modular system architecture for development of new applications. System construction is preceded by the analysis of currently available devices for specific data acquisition and processing.

The development and integration of data acquisition and processing tools for first responder scenarios can be rapidly achieved by the modular and already existing software/hardware integration platform. Data types processed by this system are biometrics, live video/audio and textual/command data. The data acquisition is followed by the prompt dissemination of information from the incident scene thus overcoming interoperability issues.

Integration of new modules is achieved through simple system upgrades – new applications are created and integrated while the rest of the platform remains intact. Off‐the‐shelf components used eliminate the need for specialized hardware development. The speech user interface allows simple interaction with the system in an eyes‐off, hands‐off manner.

The system represents an efficient platform for integrated data acquisition and processing specially targeted for first response. The test‐bed flexibility allows for straightforward integration of devices/applications handling new data type as required by the user.