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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 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.

Radio frequency identification (RFID) is a technology for tracking objects that is expected to be widely adopted in very near future. A reader device sends probes to a set of RFID tags, which then respond to the request. A tag is recognized only when it is the only one to respond to the probe. Only reader has collision detection capability. The problem considered here is to minimize the number of probes necessary for reading all the tags, assuming that the number of tags is known in advance.

Well known binary and n‐ary partitioning algorithms can be applied to solve the problem for the case of known number of tags. A new randomized hybrid tag identification protocol has been proposed, which combines the two partitioning algorithms into a more efficient one. The new scheme optimizes the binary partition protocol for small values of n (e.g. n=2, 3, 4). The hybrid scheme then applies n‐ary partition protocol on the whole set, followed by binary partition on the tags that caused collision.

It is analytically proved that the expected number of time slots in the hybrid algorithm with known number of users is less than 2.20 n. Performance of these algorithms was also evaluated experimentally, and an improvement from en to approximately 2.15 n was obtained.

The algorithm shown here is efficient both by theory and practice and outperforms existing ones.

This paper discusses how corruption, in its various manifestations, has had — and continues to have — a very serious impact on the economic and political stability of the Asia‐Pacific region.

I. INTRODUCTION This study attempts to extend and expand previous research conducted by the Department of Marketing at Strathclyde on the adoption and diffusion of industrial products.

A distinction must be drawn between a dismissal on the one hand, and on the other a repudiation of a contract of employment as a result of a breach of a fundamental term of that contract. When such a repudiation has been accepted by the innocent party then a termination of employment takes place. Such termination does not constitute dismissal (see London v. James Laidlaw & Sons Ltd (1974) IRLR 136 and Gannon v. J. C. Firth (1976) IRLR 415 EAT).