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When assessing preferences of individuals with developmental disabilities, choices can be described vocally or presented using objects or pictures in preference assessments. For individuals who are unable to perform auditory-visual discriminations and visual identity matching, objects instead of pictures or vocalizations need to be used for preference assessments to be effective. Considering the practical advantages of using pictures over objects, recent research has begun to focus on identifying and teaching skills needed for picture preference assessments. Although object-to-picture, picture-to-object, and generalized matching have been implicated as possible skills needed for picture preference assessments, further systematic studies are needed. The present study examined the relation between preference assessments (object vs. picture groups) and 5 discrimination skills. Based on direct paired-stimulus preference assessments completed at the beginning of the study, participants who could indicate their preferences with objects, but not with picture or vocal presentation, were assigned to the Object Group (n = 11); and participants who could indicate their preferences with both objects and pictures, but not vocal presentation, were assigned to the Picture Group (n = 9). The 5 discrimination tasks included: (a) object-picture matching and (b) its symmetry, picture-object matching; (c) generalized object-picture matching and (d) its symmetry, generalized picture-object matching; and (e) generalized identity picture-picture matching. All task stimuli were parts from everyday objects. Independent sample t-tests with Bonferroni correction showed that the percentages of correct responses were significantly higher in the Picture Group than in the Object Group on 4 of the 5 tasks (p < .01). Individual data showed that 8 of the 9 Picture Group participants met the pass criterion (80% or higher correct responses) on at least 1 discrimination task, with 6 participants passing 2 or more tasks. In contrast, only 1 of the 11 Object Group participants met the pass criterion on 1 discrimination task. The findings suggest that the effectiveness of picture preference assessments is not dependent on one specific discrimination, but possibly the ability to perform generalized matching.

Large quantities of bulk grain are moved using graincars in Canada and other parts of the world. Automation has not progressed significantly in the grain industry probably because the market is limited for automated systems. A prototype of a robot (“Grain-o-bot”) using machine vision to automatically open and close graincar hopper gates and detect the contents of the graincar was built and studied. The “Grain-o-bot” was a Cartesian robot equipped with two cameras and an opening tool as the end-effector. One camera acted as the eye to determine the sprocket location, and guided the end-effector to the sprocket opening. For most applications, machine vision solutions based on pattern recognition were developed using images acquired in a laboratory setting. Major constraints with these solutions occurred when implementing them in real world applications. So the first step for this automation was to correctly identify the hopper gate sprocket on the grain car. Algorithms were developed to detect and identify the sprocket under proper lighting conditions with 100% accuracy. The performance of the algorithms was also evaluated for the identification of the sprocket on a grain car exposed to different lighting conditions, which are expected to occur in typical grain unloading facilities. Monochrome images of the sprocket from a model system were acquired using different light. Correlation and pattern recognition techniques using a template image combined with shape detection were used for sprocket identification. The images were pre-processed using image processing techniques, prior to template matching. The template image developed from the light source that was similar to the light source used to acquire ii images was more successful in identifying the sprocket than the template image developed using different light sources. A sample of the graincar content was taken by slightly opening and immediately closing the hopper gates. The sample was identified by taking an image using the second camera and performing feature matching. An accuracy of 99% was achieved in identifying Canada Western Red Spring (CWRS) wheat and 100% for identifying barley and canola.

Recognizing that two sounds are the same is a part of accurate vocal imitation, and the teaching of vocal imitation is an important part of language training for persons with developmental disabilities (DD) and children with autism. Researchers have developed an Auditory-Auditory Identity Matching Prototype Task (AAIM PT) to assess whether persons with DD can identify whether two sounds are the same (Harapiak, Martin, & Yu, 1999). Thus far, the one study (Sewell, 2005) that attempted to teach AAIM tasks to persons with DD who failed the AAIM PT had little success in doing so. The purpose of this research was to evaluate several procedures for teaching AAIM tasks to persons with DD and children with autism. In Experiment 1, the trainer said a word, a matching word was played out of one computer speaker, and a non-matching word was played out of another. The participant was required to point to the speaker that played the matching word. In a single-subject alternating-treatments design, volume fading of the non-matching word (from zero to full volume) was compared to the fading out of a pointing prompt to the speaker that played the matching word. Only one of five participants learned an AAIM task, and that participant did not pass the AAIM PT. Three pilot studies were then conducted to explore various prompting and fading strategies for teaching AAIM tasks, and all were unsuccessful. In Experiment 2, I examined a procedure for teaching AAIM in which the participant was actively involved in producing the sample sound and the matching and non-matching comparison sounds. This procedure also incorporated visual cues and sounds from the operation of a toy airplane as a possible natural, built-in reinforcer. In a single-subject AB design with replication within and across three participants (one person with DD and two children with autism), all three participants learned two AAIM tasks, two participants generalized to a third AAIM task, and one participant passed the AAIM PT. The encouraging results from Experiment 2 provide a promising starting point for future research on teaching AAIM tasks to persons with DD and children with autism.

When assessing preferences of individuals with developmental disabilities, choices can be described vocally or presented using objects or pictures in preference assessments. For individuals who are unable to perform auditory-visual discriminations and visual identity matching, objects instead of pictures or vocalizations need to be used for preference assessments to be effective. Considering the practical advantages of using pictures over objects, recent research has begun to focus on identifying and teaching skills needed for picture preference assessments. Although object-to-picture, picture-to-object, and generalized matching have been implicated as possible skills needed for picture preference assessments, further systematic studies are needed. The present study examined the relation between preference assessments (object vs. picture groups) and 5 discrimination skills. Based on direct paired-stimulus preference assessments completed at the beginning of the study, participants who could indicate their preferences with objects, but not with picture or vocal presentation, were assigned to the Object Group (n = 11); and participants who could indicate their preferences with both objects and pictures, but not vocal presentation, were assigned to the Picture Group (n = 9). The 5 discrimination tasks included: (a) object-picture matching and (b) its symmetry, picture-object matching; (c) generalized object-picture matching and (d) its symmetry, generalized picture-object matching; and (e) generalized identity picture-picture matching. All task stimuli were parts from everyday objects. Independent sample t-tests with Bonferroni correction showed that the percentages of correct responses were significantly higher in the Picture Group than in the Object Group on 4 of the 5 tasks (p < .01). Individual data showed that 8 of the 9 Picture Group participants met the pass criterion (80% or higher correct responses) on at least 1 discrimination task, with 6 participants passing 2 or more tasks. In contrast, only 1 of the 11 Object Group participants met the pass criterion on 1 discrimination task. The findings suggest that the effectiveness of picture preference assessments is not dependent on one specific discrimination, but possibly the ability to perform generalized matching.

Large quantities of bulk grain are moved using graincars in Canada and other parts of the world. Automation has not progressed significantly in the grain industry probably because the market is limited for automated systems. A prototype of a robot (“Grain-o-bot”) using machine vision to automatically open and close graincar hopper gates and detect the contents of the graincar was built and studied. The “Grain-o-bot” was a Cartesian robot equipped with two cameras and an opening tool as the end-effector. One camera acted as the eye to determine the sprocket location, and guided the end-effector to the sprocket opening. For most applications, machine vision solutions based on pattern recognition were developed using images acquired in a laboratory setting. Major constraints with these solutions occurred when implementing them in real world applications. So the first step for this automation was to correctly identify the hopper gate sprocket on the grain car. Algorithms were developed to detect and identify the sprocket under proper lighting conditions with 100% accuracy. The performance of the algorithms was also evaluated for the identification of the sprocket on a grain car exposed to different lighting conditions, which are expected to occur in typical grain unloading facilities. Monochrome images of the sprocket from a model system were acquired using different light. Correlation and pattern recognition techniques using a template image combined with shape detection were used for sprocket identification. The images were pre-processed using image processing techniques, prior to template matching. The template image developed from the light source that was similar to the light source used to acquire ii images was more successful in identifying the sprocket than the template image developed using different light sources. A sample of the graincar content was taken by slightly opening and immediately closing the hopper gates. The sample was identified by taking an image using the second camera and performing feature matching. An accuracy of 99% was achieved in identifying Canada Western Red Spring (CWRS) wheat and 100% for identifying barley and canola.

Recognizing that two sounds are the same is a part of accurate vocal imitation, and the teaching of vocal imitation is an important part of language training for persons with developmental disabilities (DD) and children with autism. Researchers have developed an Auditory-Auditory Identity Matching Prototype Task (AAIM PT) to assess whether persons with DD can identify whether two sounds are the same (Harapiak, Martin, & Yu, 1999). Thus far, the one study (Sewell, 2005) that attempted to teach AAIM tasks to persons with DD who failed the AAIM PT had little success in doing so. The purpose of this research was to evaluate several procedures for teaching AAIM tasks to persons with DD and children with autism. In Experiment 1, the trainer said a word, a matching word was played out of one computer speaker, and a non-matching word was played out of another. The participant was required to point to the speaker that played the matching word. In a single-subject alternating-treatments design, volume fading of the non-matching word (from zero to full volume) was compared to the fading out of a pointing prompt to the speaker that played the matching word. Only one of five participants learned an AAIM task, and that participant did not pass the AAIM PT. Three pilot studies were then conducted to explore various prompting and fading strategies for teaching AAIM tasks, and all were unsuccessful. In Experiment 2, I examined a procedure for teaching AAIM in which the participant was actively involved in producing the sample sound and the matching and non-matching comparison sounds. This procedure also incorporated visual cues and sounds from the operation of a toy airplane as a possible natural, built-in reinforcer. In a single-subject AB design with replication within and across three participants (one person with DD and two children with autism), all three participants learned two AAIM tasks, two participants generalized to a third AAIM task, and one participant passed the AAIM PT. The encouraging results from Experiment 2 provide a promising starting point for future research on teaching AAIM tasks to persons with DD and children with autism.

Equitable romantic relationships are relationships in which partners perceive that they are giving benefits to their partner that equal the benefits they receive from their partner (e.g., Walster, Traupmann, & Walster, 1978), and such relationships promote commitment (Rusbult, 1980). But do equity considerations influence observers’ impressions of a romantic couple? In the present study, I tested this possibility by examining observers’ impressions of romantic partners who were mismatched in physical attractiveness (i.e., one partner will be more physically attractive than the other). In this situation, heterosexual observers instinctually categorize the opposite-sex member of the couple as a potential mate and the same-sex member of the couple as a competitor for the potential mate’s affection (e.g., Buss & Dedden, 1990; Fisher & Cox, 2009). Furthermore, observers also conclude that a potential mate who is more attractive than his or her current partner (i.e., the competitor) is not committed to his or her current relationship (Stinson & Reddoch, unpublished data). Thus, when evaluating a romantic couple, I hypothesize that observers’ will demonstrate mating-motivated biased perceptions of potential mates and competitors when the mate is more attractive than the competitor, because such more-attractive potential mates will be perceived as romantically “available.” Participants viewed photos of dating couples who matched in attractiveness, or viewed photos of dating couples where the mate was more attractive or less attractive than the competitor. Participants then rated the potential mates’ and competitors’ status-resources (SR; Fletcher et al., 1999). Results supported my theory of mating-motivated person-perception: Observers derogated the SRs of competitors who were paired with a more attractive (and romantically available) potential mate. / Graduate / 0623 / 0451 / c.joordens@gmail.com

A simple and feasible method of computer colour matching involving fluorescent dyes was developed. An ordinary abridged-spectroreflectometer with polychomatic illumination and a simulated D65 xenon light source was employed for all measurements. In addition to the normal K/S constants for non-fluorescent dyes and the non-fluorescent portion of the fluorescent dye'.. constants responsible for the fluorescent portion were necessary. Two sets of equations to relate the total radiance factors of dyeings with a fluorescent dye and its concentration were developed respectively for self and compound shades where a non-fluorescent dye is admixed. Finding constants responsible for the compound shades required a number of calibration mixture dyeings. Negative K/S constants were found useful when the total radiance factor was above that for the substrate but below one hundred. Three computer programs? s were developed to deal with calibration constants for self and compound shade and also for match prediction. Optimization was used in all cases to minimize errors in total radiance factors or colour differences. Half of the actual dyeingq formulations from the predicted were visually passed by a panel of five dyers. In this study, disperse dyes on polyester were used. Moreover, a commercial matching package was studied using non-fluorescent dyes. The dyeing system affected its accuracy. The polyester/disperse dye system was better than the cotton/reactive dye system. The sample size and luminancefactor of target colours; were also studied. The accuracy was affected slightly by the latter but not the former.