Kenneth Unklesbay

A comparison of pulsed and continuous ultraviolet light sources for the decontamination of surfaces

The experimental results on the development of a decontamination process that uses ultraviolet light and chemical photosensitizer for disinfecting surfaces and solutions are reported. Reduction in the microbial viability as a function of applied UV fluence is presented for the inactivation of Bacillus subtilis spores. Results obtained with aqueous solutions and with surfaces indicate that pulsed UV light is more effective than continuous UV light. Nearly three orders of magnitude of enhanced inactivation have been achieved with the photosensitized UV process on surfaces.

The development of photosensitized pulsed and continuous ultraviolet decontamination techniques for surfaces and solutions

The experimental results of a decontamination process that uses an ultraviolet (UV) light and a chemical photosensitizer for disinfecting surfaces and solutions are reported. Reduction in the microbial viability as a function of applied UV fluence and initial photosensitizer concentration is presented for the inactivation of both the vegetative and spore forms of Bacillus subtilis niger. Encouraging results have been obtained with both aqueous solutions and surfaces; and with both continuous and pulsed UV light sources. Extrapolation of the results and an estimate of the process speed and efficiency permit a comparison with other decontamination methods.

AN APPROXIMATE REASONING TECHNIQUE FOR RECOGNITION IN COLOR IMAGES OF BEEF STEAKS

Visual information plays in important role in food science research and applications. Color and color distribution act as cues in many such discrimination problems. In the determination of degree of doneness in beef steaks, for example, it is the distribution of red and brown which serve as visual indicators. In previous work, we developed capabilities to perform the basic color processing of food images. In this paper we present a methodology, based on approximate reasoning, for automatically determining the degree of doneness from the color images. We define a meaning vector of fuzzy sets for the fuzzy variables representing doneness classes from several of the color histograms of the steak images. We then construct a decision function which produces a fuzzy degree of agreement between the meaning of vector of an unknown sample and the prototypical vector corresponding to each class This approach produces good classification results when the final class memberships are converted to a crisp partition. Ho...

Air temperature transfer function of a convection oven

Abstract The effect on air temperature of variations in heater power for a forced convection oven were modelled. The transfer functions for five operating ranges, from 140 °C to 236 °C, were determined experimentally. The oven power control was excited using a pseudo-random binary signal and the resulting effect on the air temperature was measured. From this information, transfer functions in the ARMAX form were determined. It was found that while the denominator coefficients of the system do not vary for different ranges of air temperature, the numerator coefficients of the system do vary significantly.

Determination of doneness of beef steaks using fuzzy pattern recognition

Abstract The c -means and k -nearest neighbor algorithms of pattern recognition were used as methods of determining the degree of doneness of beef ribeye steaks. For each method, an approach employing the theory of fuzzy sets was used in addition to the traditional crisp approach. Steaks were heat processed to various degrees of doneness. The red, green and blue components of the steak images were acquired using a digital image processing system. Values were then converted to the hue, intensity and saturation. The use of the mean and standard deviation of these six values as features was investigated. The means of the red, intensity and saturation and the standard deviation of the red were found to be of most value as features for the classification techniques investigated.

Heat processing menu items with rotating hot air versus deep fat frying

Abstract Two heat processing methods, rotating hot air and deep fat frying, were compared for energy consumption and their effect on quality of four menu items. The rotating hot air system simulated the frying process. The menu items were steak fries, veal patties, chicken strips and cod fillets. Quality attributes measured included product yields, moisture, crude fat, food energy, and shear force. For the small batch sizes studied, the hot air system consumed less energy than the fryer. The moisture content was always less in the fryer; the fat content and food energy levels were always greater. Reasons for these trends were discussed.

Optimal design of journal bearings

Abstract A new mathematical optimization technique, geometric programming, is used to optimize a number of journal bearing design problems. Though a few simplifying assumptions must be made in order to write the bearing design problem mathematically, no additional simplifying assumptions are required in order to apply geometric programming. Geometric programming is found to be a powerful technique for optimizing journal bearing design problems.

Preparing Undergraduate Students To Manage Foodservice Energy

Can an intensive energy study provide undergraduate foodservice management students with sufficient information and experience to affect their future role as managers of foodservice facilities? Early in 1980, the faculty in the Department of Dietetics, Restaurant and Institutional Management at Kansas State University (KSU) posed this crucial question as part of its effort to provide the information and training students need to work effectively