Thesis (Ph. D.)--University of Texas at Austin, 2001. / Vita. Includes bibliographical references (leaves 175-187). Available also in a digital version from Dissertation Abstracts.

Thesis (M.S. in Information Technology Management)--Naval Postgraduate School, December 2003. / Thesis advisor(s): Nita L. Miller, Thomas J. Housel. Includes bibliographical references (p. 115-117). Also available online.

Thesis (Ph. D.)--Hong Kong University of Science and Technology, 2003. / Includes bibliographical references. Also available in electronic version. Access restricted to campus users.

Thesis (Ph. D.)--University of Washington, 2002. / Vita. Includes bibliographical references (leaves 81-85).

A consumer research panel is a representative collection of individuals whose consumption habits are continually monitored by a marketing research company. It is designed to study the behaviour rather than the attitudes of consumers in the fast moving consumer goods (FMCG) sector. The analysed and interpreted reports help the retailer and manufacturing clients to better understand their markets and the changing dynamics within markets which are largely overseen by retail studies. It is shown that consumer research panels have a very high per panellist cost due to the nature of the data collection methodologies currently used being either very labour-intensive with the in-home interviewer visits, or due to the cost of the technology needed when using an in-home audit terminal to scan the barcode of items. The ubiquitous use of the mobile phone begs the question whether this technology, already in the hands of people, could be used as a data collection device. In 2007, Robert Adelmann demonstrated that it is possible to recognise linear barcodes using a mobile phone equipped with a camera and a barcode recognition algorithm. Three requirements are set for a mobile phone to be used as a data collection device in a consumer panel and are indicated by various studies researching each, focused on Gauteng, South Africa. The technology is shown to be quick and accurate enough to be used in everyday barcode scanning albeit not very prevalent among the responding sample. The data communication infrastructure needed to communicate the audited data was found to be 100% present although few of the respondents displayed their interest in joining a research panel based on mobile phones. It is, therefore, recommended that a phone-based consumer panel be used to supplement existing consumer panels to extend in hard-to-reach demographics like the upper-LSM households, and that the privacy and usage concerns raised by the respondents be addressed. It is also recommended that similar studies be conducted in developed economies where required mobile phone technology could be more prevalent. / Thesis (M.B.A.)--North-West University, Vaal Triangle Campus, 2010.

A consumer research panel is a representative collection of individuals whose consumption habits are continually monitored by a marketing research company. It is designed to study the behaviour rather than the attitudes of consumers in the fast moving consumer goods (FMCG) sector. The analysed and interpreted reports help the retailer and manufacturing clients to better understand their markets and the changing dynamics within markets which are largely overseen by retail studies. It is shown that consumer research panels have a very high per panellist cost due to the nature of the data collection methodologies currently used being either very labour-intensive with the in-home interviewer visits, or due to the cost of the technology needed when using an in-home audit terminal to scan the barcode of items. The ubiquitous use of the mobile phone begs the question whether this technology, already in the hands of people, could be used as a data collection device. In 2007, Robert Adelmann demonstrated that it is possible to recognise linear barcodes using a mobile phone equipped with a camera and a barcode recognition algorithm. Three requirements are set for a mobile phone to be used as a data collection device in a consumer panel and are indicated by various studies researching each, focused on Gauteng, South Africa. The technology is shown to be quick and accurate enough to be used in everyday barcode scanning albeit not very prevalent among the responding sample. The data communication infrastructure needed to communicate the audited data was found to be 100% present although few of the respondents displayed their interest in joining a research panel based on mobile phones. It is, therefore, recommended that a phone-based consumer panel be used to supplement existing consumer panels to extend in hard-to-reach demographics like the upper-LSM households, and that the privacy and usage concerns raised by the respondents be addressed. It is also recommended that similar studies be conducted in developed economies where required mobile phone technology could be more prevalent. / Thesis (M.B.A.)--North-West University, Vaal Triangle Campus, 2010.

Drug development in general and clinical trials in particular is expensive and time consuming processes. One mandatory procedure in clinical trials are data collection, about 15 years ago almost all data were collected with a paper based approach but with new digitalised technology for data collection the process were about to become more efficient in regard to time, cost and quality of data. However the adoption rate of these systems for data collection were much lower than anticipated and most previous research points toward poorly developed products as the main reason for the adoption failure. Nevertheless, these systems have become more user friendly and efficient and today almost all studies use Electronic Data Capture (EDC) as the primary method for data collection. This project aim to investigate if the reason for the slow diffusion was a result of poorly developed products or if there are external factors such as social or organisational aspects that caused this delay. Semi structured interviews were conducted with 15 informants who works with EDC systems daily and are professionals within this industry. The result indicates that the slow diffusion is partly caused by initially bad systems that in turn might have caused a resistance among the end users and partly caused by slow decision organisations such as multinational pharmaceutical companies. The advice given to the project owner who intends to acquire this market is to focus on electronic Patient Reported Outcome (ePRO), which is a tool used by individual patients for self-reporting of data in clinical trials. ePRO is an extension of the EDC systems and must be user friendly for the patients and easy to connect to other systems. The company should rather focus on small Contract Research Organisation (CRO) as main customers rather than Big Pharma. Big Pharma often conduct multinational studies and decisions regarding the protocol and how data is to be collected are centrally decided. Since the project owner is a newly started, small firm with limited experience of clinical trials my advice would be to target CROs that conduct smaller studies.

Large-scale earthmoving activities make up a costly and air-polluting aspect of many construction projects and mining operations, which depend entirely on the use of heavy construction equipment. The long-term jobsites and manufacturing nature of the mining sector has encouraged the application of automated controlling systems, more specifically GPS, to control the earthmoving fleet. Computer vision-based methods are another potential tool to provide real-time information at low-cost and to reduce human error in surface earthmoving sites as relatively clear views can be selected and the equipment offer recognizable targets. Vision-based methods have some advantages over positioning devices as they are not intrusive, provide detailed data about the behaviour of each piece of equipment, and offer reliable documentation for future reviews. This dissertation explains the development of a vision-based system, named server-customer interaction planner (SCIT), to recognize and estimate earth material loading cycles. The SCIT system consists of three main modules: object recognition, tracking, and action recognition. Different object recognition and tracking algorithms were evaluated and modified, and then the ideal methods were used to develop the object recognition and tracking modules. A novel hybrid tracking framework was developed for the SCIT system to track dump trucks in the challenging views found in the loading zones. The object recognition and tracking engines provide spatiotemporal data about the equipment which are then analyzed by the action recognition module to estimate loading cycles. The entire framework was evaluated using videos taken under varying conditions. The results highlight the promising performance of the SCIT system with the hybrid tracking engine, thereby validating the possibility of its practical application.

Large-scale earthmoving activities make up a costly and air-polluting aspect of many construction projects and mining operations, which depend entirely on the use of heavy construction equipment. The long-term jobsites and manufacturing nature of the mining sector has encouraged the application of automated controlling systems, more specifically GPS, to control the earthmoving fleet. Computer vision-based methods are another potential tool to provide real-time information at low-cost and to reduce human error in surface earthmoving sites as relatively clear views can be selected and the equipment offer recognizable targets. Vision-based methods have some advantages over positioning devices as they are not intrusive, provide detailed data about the behaviour of each piece of equipment, and offer reliable documentation for future reviews. This dissertation explains the development of a vision-based system, named server-customer interaction planner (SCIT), to recognize and estimate earth material loading cycles. The SCIT system consists of three main modules: object recognition, tracking, and action recognition. Different object recognition and tracking algorithms were evaluated and modified, and then the ideal methods were used to develop the object recognition and tracking modules. A novel hybrid tracking framework was developed for the SCIT system to track dump trucks in the challenging views found in the loading zones. The object recognition and tracking engines provide spatiotemporal data about the equipment which are then analyzed by the action recognition module to estimate loading cycles. The entire framework was evaluated using videos taken under varying conditions. The results highlight the promising performance of the SCIT system with the hybrid tracking engine, thereby validating the possibility of its practical application.

This degree project is a part of information and communication technology supported self-care system for the diabetes, mainly in diabetes data collection and visualization. The report is organized in four main sections: investigation and internet search, literature review, application design and implementation, system test and evaluation. Existed applications and research studies has been compared and, a responsive web application is developed aiming at providing relevant functionalities and services regarding diabetes self-management.