Adaptive optical flow for person tracking

Person tracking systems are dependent on being able to locate a person accurately across a series of frames. Optical flow can be used to segment a moving object from a scene, provided the expected velocity of the moving object is known; but successful detection also relies on being able segment the background. A problem with existing optical flow techniques is that they don’t discriminate the foreground from the background, and so often detect motion (and thus the object) in the background. To overcome this problem, we propose a new optical flow technique, that is based upon an adaptive background segmentation technique, which only determines optical flow in regions of motion. This technique has been developed with a view to being used in surveillance systems, and our testing shows that for this application it is more effective than other standard optical flow techniques.

The effect of consumer risk perceptions and information search on willingness to buy GM food products: A cross cultural analysis

This paper seeks to address the widespread call in the literature for the cross-cultural examination ( and validation) of accepted concepts within consumer behaviour, such as consumer risk perceptions and information search. The findings of the study provide support for a number of accepted relationships, whilst identifying distinct cross cultural differences in external information search and willingness to buy genetically modified (GM) food products by consumers.

In search of a theory of integrated marketing communication

For the most part, the literature base for Integrated Marketing Communication (IMC) has developed from an applied or tactical level rather than from an intellectual or theoretical one. Since industry, practitioner and even academic studies have provided little insight into what IMC is and how it operates, our approach has been to investigate that other IMC community, that is, the academic or instructional group responsible for disseminating IMC knowledge. We proposed that the people providing course instruction and directing research activities have some basis for how they organize, consider and therefore instruct in the area of IMC. A syllabi analysis of 87 IMC units in six countries investigated the content of the unit, its delivery both physically and conceptually, and defined the audience of the unit. The study failed to discover any type of latent theoretical foundation that might be used as a base for understanding IMC. The students who are being prepared to extend, expand and enhance IMC concepts do not appear to be well-served by the curriculum we found in our research. The study concludes with a model for further IMC curriculum development.

Search engine content analysis

Search engines have forever changed the way people access and discover knowledge, allowing information about almost any subject to be quickly and easily retrieved within seconds. As increasingly more material becomes available electronically the influence of search engines on our lives will continue to grow. This presents the problem of how to find what information is contained in each search engine, what bias a search engine may have, and how to select the best search engine for a particular information need. This research introduces a new method, search engine content analysis, in order to solve the above problem. Search engine content analysis is a new development of traditional information retrieval field called collection selection, which deals with general information repositories. Current research in collection selection relies on full access to the collection or estimations of the size of the collections. Also collection descriptions are often represented as term occurrence statistics. An automatic ontology learning method is developed for the search engine content analysis, which trains an ontology with world knowledge of hundreds of different subjects in a multilevel taxonomy. This ontology is then mined to find important classification rules, and these rules are used to perform an extensive analysis of the content of the largest general purpose Internet search engines in use today. Instead of representing collections as a set of terms, which commonly occurs in collection selection, they are represented as a set of subjects, leading to a more robust representation of information and a decrease of synonymy. The ontology based method was compared with ReDDE (Relevant Document Distribution Estimation method for resource selection) using the standard R-value metric, with encouraging results. ReDDE is the current state of the art collection selection method which relies on collection size estimation. The method was also used to analyse the content of the most popular search engines in use today, including Google and Yahoo. In addition several specialist search engines such as Pubmed and the U.S. Department of Agriculture were analysed. In conclusion, this research shows that the ontology based method mitigates the need for collection size estimation.

A framework for analyzing system intelligence of the building control system : a study of the integrated building management system

The lack of satisfactory consensus for characterizing the system intelligence and structured analytical decision models has inhibited the developers and practitioners to understand and configure optimum intelligent building systems in a fully informed manner. So far, little research has been conducted in this aspect. This research is designed to identify the key intelligent indicators, and develop analytical models for computing the system intelligence score of smart building system in the intelligent building. The integrated building management system (IBMS) was used as an illustrative example to present a framework. The models presented in this study applied the system intelligence theory, and the conceptual analytical framework. A total of 16 key intelligent indicators were first identified from a general survey. Then, two multi-criteria decision making (MCDM) approaches, the analytic hierarchy process (AHP) and analytic network process (ANP), were employed to develop the system intelligence analytical models. Top intelligence indicators of IBMS include: self-diagnostic of operation deviations; adaptive limiting control algorithm; and, year-round time schedule performance. The developed conceptual framework was then transformed to the practical model. The effectiveness of the practical model was evaluated by means of expert validation. The main contribution of this research is to promote understanding of the intelligent indicators, and to set the foundation for a systemic framework that provide developers and building stakeholders a consolidated inclusive tool for the system intelligence evaluation of the proposed components design configurations.

Identifying and implementing adaptive strategy in the U.S. military

Changes in the environment, including increased environmental complexity, require military supply units to employ a more adaptive strategy in order to enhance military agility. We extend the Lumpkin and Dess (1996) model and develop propositions that explore the interrelationships between/amongst entrepreneurial orientation (EO); opportunity recognition, evaluation and exploitation; environmental and organizational factors; and organizational performance. We propose that the innovativeness, proactiveness, and risk-taking dimensions of EO are of primary importance in identifying adaptive solutions and that these relationships are moderated by environmental factors. The autonomy and competitive aggressiveness dimensions of EO are important in implementing solutions as adaptive strategies, especially in a military context, and these relationships are moderated by organizational factors. This chapter extends existing theory developed primarily for the civilian sector to the military. Military organizations are more rigid hierarchical structures, and have different measures of performance. At an applied level, this research provides insights for military commanders that can potentially enhance agility and adaptability.

Managing infrastructure transitions : a complex adaptive systems perspective

Engineering assets such as roads, rail, bridges and other forms of public works are vital to the effective functioning of societies {Herder, 2006 #128}. Proficient provision of this physical infrastructure is therefore one of the key activities of government {Lædre, 2006 #123}. In order to ensure engineering assets are procured and maintained on behalf of citizens, government needs to devise the appropriate policy and institutional architecture for this purpose. The changing institutional arrangements around the procurement of engineering assets are the focus of this paper. The paper describes and analyses the transition to new, more collaborative forms of procurement arrangements which are becoming increasingly prevalent in Australia and other OECD countries. Such fundamental shifts from competitive to more collaborative approaches to project governance can be viewed as a major transition in procurement system arrangements. In many ways such changes mirror the shift from New Public Management, with its emphasis on the use of market mechanisms to achieve efficiencies {Hood, 1991 #166}, towards more collaborative approaches to service delivery, such as those under network governance arrangements {Keast, 2007 #925}. However, just as traditional forms of procurement in a market context resulted in unexpected outcomes for industry, such as a fragmented industry afflicted by chronic litigation {Dubois, 2002 #9}, the change to more collaborative forms of procurement is unlikely to be a panacea to the problems of procurement, and may well also have unintended consequences. This paper argues that perspectives from complex adaptive systems (CAS) theory can contribute to the theory and practice of managing system transitions. In particular the concept of emergence provides a key theoretical construct to understand the aggregate effect that individual project governance arrangements can have upon the structure of specific industries, which in turn impact individual projects. Emergence is understood here as the macro structure that emerges out of the interaction of agents in the system {Holland, 1998 #100; Tang, 2006 #51}.

Memoirs of a trainer : The search for a balance between quality and best practice

The field of research training (for students and supervisors) is becoming more heavily regulated by the Federal Government. At the same time, quality improvement imperatives are requiring staff across the University to have better access to information and knowledge about a wider range of activities each year. Within the Creative Industries Faculty at the Queensland University of Technology (QUT), the training provided to academic and research staff is organised differently and individually. This session will involve discussion of the dichotomies found in this differentiated approach to staff training, and begin a search for best practice through interaction and input from the audience.

Adaptive load shedding and regional protection

The requirement for improved efficiency whilst maintaining system security necessitates the development of improved system analysis approaches and the development of advanced emergency control technologies. Load shedding is a type of emergency control that is designed to ensure system stability by curtailing system load to match generation supply. This paper presents a new adaptive load shedding scheme that provides emergency protection against excess frequency decline, whilst minimizing the risk of line overloading. The proposed load shedding scheme uses the local frequency rate information to adapt the load shedding behaviour to suit the size and location of the experienced disturbance. The proposed scheme is tested in simulation on a 3-region, 10-generator sample system and shows good performance.