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Automated Identification (Auto ID) applications can provide corporate information systems with the identity of each physical item in the supply chain in an automated and timely manner. The real time availability of item identity allows other information, related to the item, to be drawn on in order to assess both the current state of the product and future actions required. In the context of supply chain operations, widespread introduction of such systems represents a major opportunity to overhaul and improve tracking and tracing systems, process control and inventory management. In the longer term, it is possible that Auto ID systems may enable a complete re‐engineering of the supply chain, by removing a number of the constraints that limit today's supply chain structures. In this paper, we review some key challenges in supply chain operations and introduce the main elements of an Auto ID system. Using a simple categorization of supply chain operations, areas for short term deployment of Auto ID are identified and opportunities for longer term re‐engineering of different sections of the supply chain are highlighted.

Production responsiveness refers to the ability of a production system to achieve its operational goals in the presence of supplier, internal and customer disturbances, where disturbances are those sources of change which occur independently of the system’s intentions. A set of audit tools for assessing the responsiveness of production operations is being prepared as part of an EPSRC funded investigation. These tools are based on the idea that the ability to respond is linked to: the nature of the disturbances or changes requiring a response; their impact on production goals; and the inherent response capabilities of the operation. These response capabilities include information gathering and processing (to detect disturbances and production conditions), decision processes (which initiate system responses to disturbances) and various types of process flexibilities and buffers (which provide the physical means of dealing with disturbances). The paper discusses concepts and issues associated with production responsiveness, describes the audit tools that have been developed and illustrates their use in the context of a steel manufacturing plant.

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.