ABSTRACT RECOGNITION OF EMOTIONAL FACIAL EXPRESSION IN ALCOHOL DEPENDENT INPATIENTS Dursun, Pinar M.S., Department of Psychology Supervisor: Assoc. Prof. Faruk Gen&ccedil / &ouml / z June 2007, 130 pages The ability to recognize emotional facial expressions (EFE) is very critical for social interaction and daily functioning. Recent studies have shown that alcohol dependent individuals have deficits in the recognition of these expressions. Thereby, the objective of this study was to explore the presence of impairment in the decoding of universally recognized facial expressions -happiness, sadness, anger, disgust, fear, surprise, and neutral expressions- and to measure their manual reaction times (RT) toward these expressions in alcohol dependent inpatients. Demographic Information Form, CAGE Alcoholism Inventory, State- Trait Anxiety Inventory (STAI), Beck Depression Inventory (BDI), The Symptom Checklist, and lastly a constructed computer program (Emotion Recognition Test) were administered to 50 detoxified alcohol dependent inpatients and 50 matched-control group participants. It was hypothesized that alcohol dependents would show more deficits in the accuracy of reading EFE and would react more rapidly toward negative EFE -fear, anger, disgust, sadness than control group. Series of ANOVA, ANCOVA, MANOVA and MANCOVA analyses revealed that alcohol dependent individuals were more likely to have depression and anxiety disorders than non-dependents. They recognized less but responded faster toward disgusted expressions than non-dependent individuals. On the other hand, two groups did not differ significantly in the total accuracy responses. In addition, the levels of depression and anxiety did not affect the recognition accuracy or reaction times. Stepwise multiple regression analysis indicated that obsessive-compulsive subscale of SCL, BDI, STAI-S Form, and the recognition of fearful as well as disgusted expressions were associated with alcoholism. Results were discussed in relation to the previous findings in the literature. The inaccurate identification of disgusted faces might be associated with organic deficits resulted from alcohol consumption or cultural factors that play very important role in displaying expressions.

Master thesis, Master's degree program Marketing, Economic School Linnaeus University, Växjö Sweden, Spring semester 2015. Author: Andersson Anthon, Guntell Robin Tutor: Soniya Billore Examiner: Anders Pehrsson Title: Advancing the COO Construct From an Affective Dimension: The Application of Projective Technique Purpose: The purpose in this article is to break from traditional research and its accompanying cognitive research methods in order to advance the COO field from a more accurate perspective that also involves an affective dimension as well. Design/methodology/approach: Drawing from prior research in the COO field, the methodology accounted for assumptions that were tested in collage technique and ad copy technique. Findings: The results shows that some people only seems to be susceptible to COO influence when communicating emotional CSAs nonverbally, whilst some people only reveal rational CSAs when being cognitively asked about COO influence in a directed manner. As a result, the present findings might suggest that prior research in the academic field might suffer from bias. Practical implications: In the light of COO, managers should bear in mind that some people cannot be targeted with solely rely on a cognitive marketing communication strategy. More specifically, the ad copy technique provides guidelines for appropriate design of advertisements when one consider to serving the brand’s origin as salient cue in consumers’ minds. Originality/value: Advancing the COO construct with using collage technique, this study is to the best our knowledge the second to account for an affective dimension as well.

This thesis is a benchmark performed on three commercial Optical Character Recognition (OCR) engines. The purpose of this benchmark is to characterize the performance of the OCR engines with emphasis on the correlation of errors between each engine. The benchmarks are performed for the evaluation of the effect of a multi-OCR system employing a voting scheme to increase overall recognition accuracy. This is desirable since currently OCR systems are still unable to recognize characters with 100% accuracy. The existing error rates of OCR engines pose a major problem for applications where a single error can possibly effect significant outcomes, such as in legal applications. The results obtained from this benchmark are the primary determining factor in the decision of implementing a voting scheme. The experiment performed displayed a very high accuracy rate for each of these commercial OCR engines. The average accuracy rate found for each engine was near 99.5% based on a less than 6,000 word document. While these error rates are very low, the goal is 100% accuracy in legal applications. Based on the work in this thesis, it has been determined that a simple voting scheme will help to improve the accuracy rate.

Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: Accurate water usage information is very important for municipalities in order to provide accurate billing information for high volume water users. Meter reading are currently obtained by sending a person out to every meter to obtain a manual reading. This is very costly with regards to time and money, and it is also very error prone. In order to improve on this system, an image based telemetry system was developed that can be retrofitted on currently installed bulk water meters. Images of the meter dials are captured and transmitted to a central server where they are further processed and enhanced. Character recognition is performed on the enhanced images in order to extract meter readings. Through tests it was found that characters can be recognised to 100% accuracy for cases which the character recognition software has been trained, and 70% accuracy for cases which is was not trained. Thus, an overall recognition accuracy of 85% was achieved. These results can be improved upon in future work by statistically analysing results and utilizing the inherent heuristic information from the meter dials. Overall the feasibility of the approach was demonstrated and a way forward was indicated. / AFRIKAANSE OPSOMMING: Dit is belangrik vir munisipaliteite om akkurate water verbruikingssyfers te hê sodat hulle akkurate rekeninge aan hoë volume water gebruikers kan stuur. Tans besoek ’n persoon fisies elke meter om meterlesings te verkry. Dit is egter baie oneffektief ten opsigte van tyd en geld. Die metode is ook baie geneig tot foute. Ten einde te verbeter op hierdie stelsel was ’n beeld gebaseerde telemetrie stelsel ontwerp wat geïnstalleer word op huidig geïnstalleerde hoë volume water meters. Beelde van die meters word na ’n sentrale bediener gestuur waar dit verwerk word en die beeld kwaliteit verbeter word. Karakter herkenning sagteware word gebruik om die meter lesings te verkry vanuit die verbeterde beelde. Deur middel van toetse is gevind dat karakters herken kan word tot op 100% graad van akkuraatheid in gevalle waar die karakter herkenning sagteware opgelei is, en 70% akkuraatheid vir gevalle waarvoor dit nie opgelei was nie. Dus was ’n algehele herkennings akkuraatheid van 85% behaal. Hierdie resultate kan verbeter word in die toekoms deur die resultate statisties te analiseer en die inherente heuristieke inligting van die meter syfers te benutting. Ten slotte, in die tesis was die haalbaarheid van die benadering gedemonstreer en ’n weg vorentoe vir toekomstige werk aangedui.