Children with fetal alcohol spectrum disorders (FASD) have deficits across many cognitive, behaviour and social domains. However, despite social difficulty being proposed as a main deficit following prenatal alcohol exposure, the nature of their deficient social behaviour is largely unknown. One process that may underlie difficulties in social functioning is poor social cognition, which refers to one’s understanding of the self, others and social world. The primary goal of this dissertation was to determine whether social cognitive deficits represent a core disability underlying the socio-behavioural problems of FASD using a bottom-up approach. The first level of this approach is represented by face processing. Global and independent face feature processing was compared between FASD and normal controls (NC) using experimental and clinical measures. Eye gaze processing was investigated next using experimental and clinical tasks. At the highest level of the bottom-up approach, social perspective taking, including theory of mind and empathy were examined, along with how these abilities related to parent-rated behaviour. Finally, the lowest level consisted of specific aspects of the social neural network. White matter in three limbic pathways was investigated using diffusion tensor imaging (DTI). Results generally supported the bottom-up approach of social cognition in FASD. These children showed impaired processing of face features, when matching mouth shapes and partially occluded identity, compared with NC. The FASD group was slower to process gaze and arrow cues, suggesting impaired attention shifting. Children with FASD also showed impairments in social perspective taking, including understanding false beliefs and empathy, and these impairments were related to parent-rated attention and social problems, and autistic-like traits. Deficits in theory of mind got worse with age in FASD and empathy showed distinct sex-related differences. Although no group differences were observed on DTI indices, groups did show different age-related changes in white matter. In conclusion, deficits at each level of the current bottom-up approach may underlie the social impairments in FASD and may contribute to their broader social behavioural phenotype. The results from this dissertation have potential to inform clinical practice and lead to more effective diagnostic and treatment approaches in FASD.

Traditional methods of identity recognition are based on the knowledge of a password or a PIN, or possession factors such as tokens and ID cards. Such strategies usually afford low level of security, and can not meet the requirements of applications with high security demands. Biometrics refer to the technology of recognizing or validating the identity of an individual based on his/her physiological and/or behavioral characteristics. It is superior to conventional methods in both security and convenience since biometric traits can not be lost, forgotten, or stolen as easily, and it is relatively difficult to circumvent. However, although biometrics based solutions provide various advantages, there exist some inherent concerns of the technology. In the first place, biometrics can not be easily changed or reissued if compromised due to the limited number of biometric traits that humans possess. Secondly, since biometric data reflect the user's physiological or behavioral characteristics, privacy issues arise if the stored biometric templates are obtained by an adversary. To that end, changeability and privacy protection of biometric templates are two important issues that need to be addressed for widespread deployment of biometric technology. This dissertation systematically investigates random transformation based methods for addressing the challenging problems of changeability and privacy protection in biometrics enabled recognition systems. A random projection based approach is first introduced. We present a detailed mathematical analysis on the similarity and privacy preserving properties of random projection, and introduce a vector translation technique to achieve strong changeability. To further enhance privacy protection as well as to improve the recognition accuracy, a sorted index number (SIN) approach is proposed such that only the index numbers of the sorted feature vectors are stored as templates. The SIN framework is then evaluated in conjunction with random additive transform, random multiplicative transform, and random projection, for producing reissuable and privacy preserving biometric templates. The feasibility of the introduced solutions is well supported by detailed theoretical analyses. Extensive experimentation on a face based biometric recognition problem demonstrates the effectiveness of the proposed methods.

In a nuclear power plant, one of the most important systems for both safety and performance is the reactor cooling system. The cooling system is generally driven by one or more very large centrifugal pumps. Most reactor coolant pumps utilize a multi-stage mechanical face seal system for fluid containment. As a result, these seal systems are critical to safe, continued operation of a nuclear reactor. Without adequate sealing, loss of coolant volume can occur, and a reactor may be forced to shut down, costing the operating utility significantly until it can be brought online again. The main advantage of mechanical face seals is their self-adjusting properties. These seals are tuned so that they automatically adjust to varying fluid conditions to provide adequate leakage control. Because of the enormous pressures, complicated water chemistry, and possible large temperature transients, the mechanical seals inside a reactor coolant pump must be some of the most robust seals available. In addition, their long service life and continuous operation demand durability and the capability to adjust to a wide range of conditions. However, over time, wear, chemical deposition, or changing operating conditions can alter the face gap, which is the critical geometry between the sealing faces of a seal. An altered face gap can lead to undesirable conditions of too much or not enough leakage, which must be maintained within a certain range to provide lubrication and cooling to the seal faces without resulting in uncontrolled coolant volume loss. Nuclear power plants operate within strict leakage ranges, and long-term effects causing undesirable leakage can eventually necessitate a reactor shutdown if the seal cannot self-adjust to control the leakage. This document will examine possible causes of undesirable leakage rates in a commonly-used reactor coolant pump assembly. These causes will be examined to determine the conditions which promote them, the physical explanation for their effect on the operation of a mechanical seal, and possible methods of mitigation of both the cause and its effect. These findings are based on previous publications by utilities and technical and incident reports from reactor stations which detail actual incidents of abnormal seal performance and their root causes as determined by the utilities. Next, a method of increasing the ability of a mechanical seal to adapt to a wider range of conditions will be proposed. This method involves modifying an existing seal face to include a method of active control. This active control focuses on deliberately deforming one face of the mechanical sealing face pair. This deformation alters the face gap in order to make the fluid conditions inside the face gap more preferable, generating more or less leakage as desired. Two methods of actuation, hydraulic pressure and piezoelectric deformation, will be proposed. Finally, a model of the actively controlled seal faces will be introduced. This model includes a method of numerically solving the Reynolds equation to determine the fluid mechanics that drive the lubrication problem in the seal face and coupling the solution with a deformation analysis in a finite element model of a seal face. The model solves iteratively until a converged solution of a sealed pressure distribution, a resulting face deformation, and a calculated leakage rate is reached. The model includes a study of the effects of induced deformation in the seal via both hydraulic and piezoelectric actuation and the ability of this deformation to control the leakage rate.

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The accurate integration of audio-visual emotion cues is critical for social interactions and requires efficient processing of facial cues. Gaze behavior of typically developing (TD) individuals and individuals with autism spectrum disorders (ASD) was measured via eye-tracking during the perception of dynamic audio-visual emotion (DAVE) stimuli. This study provides information about the regions of the face sampled during an emotion perception task that is relatively more complex than those used in previous studies, providing both bimodal (auditory and visual) and dynamic (biological motion) cues. Results indicated that the ASD group was less accurate at emotion detection and demonstrated less of a visual-affective bias than TD individuals. Both groups displayed similar fixation patterns across regions during the perception of congruent audio-visual stimuli. However, between-group analyses revealed that fixation patterns differed significantly by facial regions during the perception of both congruent and incongruent movies together. In addition, fixation duration to critical regions (i.e., face, core, eyes) was negatively correlated with measures of ASD symptomatology and social impairment. Findings suggest weaknesses in the early integration of audio-visual information, automatic perception of emotion, and efficient detection of affective conflict in individuals with ASD. Implications for future research and social skills intervention programs are discussed.

The purpose of this master’s thesis was to study the possibility to use computer vision methods to detect and classify objects in the front passenger seat in a car. This work presents different approaches to solve this problem and evaluates the usefulness of each technique. The classification information should later be used to modulate the speed and the force of the airbag, to be able to provide each occupant with optimal protection and safety. This work shows that computer vision has a great potential in order to provide data, which may be used to perform reliable occupant classification. Future choice of method to use depends on many factors, for example costs and requirements on the system from laws and car manufacturers. Further, evaluation and tests of the methods in this thesis, other methods, the ABE approach and post-processing of the results should also be made before a reliable classification algorithm may be written.

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Face detection and pose estimation are two widely studied problems - mainly because of their use as subcomponents in important applications, e.g. face recognition. In this thesis I investigate a new approach to the general problem of object detection and pose estimation and apply it to faces. Face detection can be considered a special case of this general problem, but is complicated by the fact that faces are non-rigid objects. The basis of the new approach is the use of scale and orientation invariant feature structures - feature triplets - extracted from the image, as well as a biologically inspired associative structure which maps from feature triplets to desired responses (position, pose, etc.). The feature triplets are constructed from curvature features in the image and coded in a way to represent distances between major facial features (eyes, nose and mouth). The final system has been evaluated on different sets of face images.

Redeye artifact is the most prevalent problem in the flash photography, especially using compact cameras with built-in flash, which bothers both amateur and professional photographers. Hence, removing the affected redeye pixels has become an important skill. This thesis work presents a completely automatic approach for the purpose of redeye detection and removal and it consists of two modules: detection and correction of the redeye pixels in an individual eye, detection of two red eyes in an individual face.This approach is considered as a combination of some of the previous attempts in the area of redeye removal together with some minor and major modifications and novel ideas. The detection procedure is based on the redness histogram analysis followed by two adaptive methods, general and specific approaches, in order to find a threshold point. The correction procedure is a four step algorithm which does not solely rely on the detected redeye pixels. It also applies some more pixel checking, such as enlarging the search area and neighborhood checking, to improve the reliability of the whole procedure by reducing the image degradation risk. The second module is based on a skin-likelihood detection algorithm. A completely novel approach which is utilizing the Golden Ratio in order to segment the face area into some specific regions is implemented in the second module. The proposed method in this thesis work is applied on more than 40 sample images; by considering some requirements and constrains, the achieved results are satisfactory.

Syftet med denna pilotstudie var att skapa hypoteser om och hur utmattningssyndrom påverkar förmågan att känna igen emotioner i ansiktsuttryck. En grupp patienter med utmattningssyndrom jämfördes med en matchad frisk kontrollgrupp (N=14). Grupperna undersöktes med ett datorbaserat test beståendes av färgbilder av autentiska ansiktsuttryck som gradvis i steg om 10% förändrades från ett neutralt ansiktsuttryck till någon av de fem grundemotionerna ilska, avsky, rädsla, glädje och ledsenhet. Mätningarna gjordes i termer av igenkänningsprecision och responshastighet. Resultatet visade att patientgruppen responderade signifikant långsammare än kontrollgruppen sett över samtliga emotioner i testet. Inga emotionsspecifika skillnader såväl som skillnader i igenkänningsprecision kunde påvisas mellan grupperna. Orsakerna till diskrepansen i responshastighet diskuterades utifrån fyra tänkbara förklaringsområden: ansiktsperceptuell funktion, visuell uppmärksamhet, självfokuserad uppmärksamhet samt noggrannhet/oro. Rekommendationer gjordes till framtida forskning om att utforska dessa områden närmare.