Historically, coatings were processed from natural oils, fats, and resins; the first well-known and widely used being lacquer [Meir-Westhues, 2007]. In the 20th century, synthetic resins were developed to achieve coatings with improved properties. Of these coating compositions, polyurethanes (PURs) were one of the most prevalent. Polyurethanes became possible in 1937 when Otto Bayer developed the diisocyanate polyaddition process [Randall et al, 2002]. Since that time, literally thousands of PUR compositions have been used commercially. The primary application of interest in this study is that of coatings for wood substrates. It is well-known among materials researchers that there can be a number of differences between microwave and conventional materials treatment techniques [Clark et al, 1996], including enhanced reaction rates, lowered processing temperatures for some products, and selective interactions in composite systems. The primary goals of this research were to determine (1) whether microwave energy affected the cure rate in a water-based, aliphatic PUR, and (2) if there was an effect of microwave frequency on the cure rate. The primary tool for determining extent of cure in the PUR samples was Fourier transform infrared spectroscopy (FTIR). Using this characterization method, the changes in intensities of four bonds specific to the PUR composition were followed. It was determined that, in the particular PUR composition studied, microwave energy had an effect on the cure rate when compared with conventional heating, and that there was a frequency effect on the cure rate. Additionally, a deeper understanding of the use of FTIR spectroscopy techniques for studying cure kinetics was developed. / Master of Science

No / The application of computer vision in face processing remains an important research field. The aim of this chapter is to provide an up-to-date review of research efforts of computer vision scientist in facial image processing, especially in the areas of entertainment industry, surveillance, and other human computer interaction applications. To be more specific, this chapter reviews and demonstrates the techniques of visible facial analysis, regardless of specific application areas. First, the chapter makes a thorough survey and comparison of face detection techniques. It provides some demonstrations on the effect of computer vision algorithms and colour segmentation on face images. Then, it reviews the facial expression recognition from the psychological aspect (Facial Action Coding System, FACS) and from the computer animation aspect (MPEG-4 Standard). The chapter also discusses two popular existing facial feature detection techniques: Gabor feature based boosted classifiers and Active Appearance Models, and demonstrate the performance on our in-house dataset. Finally, the chapter concludes with the future challenges and future research direction of facial image processing.

Since its discovery, in the 1940's, radar (Radio Detection and Ranging) has become an important ranging sensor in many areas of technology and science. Most of the military and many civilian applications are unimaginable today without radar. With technology development, radar application areas have become larger and more available. One of these applications is Synthetic Aperture Radar (SAR), where an airborne radar is used to create high resolution images of the imaged scene. Although known since the 1950's, the SAR methods have been continuously developed and improved and new algorithms enabling real-time applications have emerged lately. Together with making the hardware components smaller and lighter, SAR has become an interesting sensor to be mounted on smaller unmanned aerial vehicles (UAV's). One important thing needed in the SAR algorithms is the estimate of the platform's motion, like position and velocity. Since this estimate is always corrupted with errors, particularly if lower grade navigation system, common in UAV applications, is used, the SAR images will be distorted. One of the most frequently appearing distortions caused by the unknown platform's motion is the image defocus. The process of correcting the image focus is called auto-focusing in SAR terminology. Traditionally, this problem was solved by methods that discard the platform's motion information, mostly due to the off-line processing approach, i.e. the images were created after the flight. Since the image (de)focus and the motion of the platform are related to each other, it is possible to utilise the information from the SAR images as a sensor and improve the estimate of the platform's motion. The auto-focusing problem can be cast as a sensor fusion problem. Sensor fusion is the process of fusing information from different sensors, in order to obtain best possible estimate of the states. Here, the information from sensors measuring platform's motion, mainly accelerometers, will be fused together with the information from the SAR images to estimate the motion of the flying platform. Two different methods based on this approach are tested on the simulated SAR data and the results are evaluated. One method is based on an optimisation based formulation of the sensor fusion problem, leading to batch processing, while the other method is based on the sequential processing of the radar data, leading to a filtering approach. The obtained results are promising for both methods and the obtained performance is comparable with the performance of a high precision navigation aid, such as Global Positioning System (GPS). / LINK-SIC

Typescript (photocopy). / Digitized by Kansas Correctional Industries

Published Article / Limits of artificial intelligent, expert systems are defined by the specific hardware limitation of the specific system. Limits can be overcome, or addressed, by giving an intelligent system web access; therefore giving it access to Google's™ vast hardware, search functions and databases. Reverse image searches can be done directly in Google's™ image search bar since October 2011. This reverse image search function is used by the proposed system to do object recognition. Computational creativity, or the ability of a program or computer to show human-level creativity and interaction, is achieved by means of a voice communication of the object identification result to the user. The proposed system interprets the result by doing a definition web search and communicating this to the user. The results show that with the novel interpretation software, it should be possible to use Google™ as an artificial intelligent, computational creative system. This proposed system thus has the ability to do object classification by accessing Google's™ vast hardware, search functions and databases, thereafter would the proposed system search a suitable definition for the classification. All of this information is communicated to the user using voice. These techniques could be used on an automatic guided vehicle, robots or expert systems

Published Article / The initial section of this manuscript focus on the ultra-structure of a unique class of heat stable cell-bound lipopolysaccharides (endotoxin) produced by Gram-negative bacteria. Subsequently, this paper summarises literature on the human body's response when challenged with endotoxins present in food and further explores the influence of food manufacturing and storage practices on endotoxin production and release by bacteria commonly isolated from food. Finally, this paper presents a brief description on the methods applied by the food industry to quantify endotoxins.

Published Article / The genus Chryseobacterium is often found in food and is regarded as a food spoilage organism. In this study, the source of the chryseobacteria was uncertain. As an exploratory investigation, the potential source of chryseobacterial contamination was determined. Total bacteria counts and yellow-pigmented colony counts were performed. Chryseobacterium species were present on poultry carcasses at all stages of processing. Total Chryseobacterium counts increased from 5.6 to 11.8 % after the brine injection stage. A significant increase in total Chryseobacterium counts (20.0 and 25.2 %) in the processing waters occurred where cutting up of the carcasses was involved. It is speculated that live chickens are the source of contamination.

No description available.

No description available.

International Telemetering Conference Proceedings / October 26-29, 1992 / Town and Country Hotel and Convention Center, San Diego, California / Our telemetry department has an application for a data categorization/compression of a high speed transient signal in a short period of time. Categorization of the signal reveals important system performance and compression is required because of the terminal nature of our telemetry testing. Until recently, the hardware for the system of this type did not exist. A new exploratory device from Intel has the capability to meet these extreme requirements. This integrated circuit is an analog neural network capable of performing 2 billion connections per second. The two main advantages of this chip over traditional hardware are the obvious computation speed of the device and the ability to compute a three layer feed-forward neural network classifier. The initial investigative development work using the Intel chip has been completed. The results from this proof of concept will show data categorization/compression performed on the neural network integrated circuit in real time. We will propose a preliminary design for a transient measurement system employing the Intel integrated circuit.