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Although there is abundant research on the etiology of Alzheimer's disease and its impact on primary caregivers, there is relatively little research that examines the consequences of the disease for entire families, and no literature that exclusively studies the experiences of non-caregiving family members. Seeking to explore the experience of non-caregivers, this qualitative study examined how adult children of an Alzheimer's patient who were not the caregiver for their parent experienced the onset and progression of the disease. Using the guiding theoretical frameworks of phenomenology, family systems theory, and ambiguous loss, in-depth interviews were conducted with three individuals and were coded for themes. The main themes found included externalization of symptoms, belief in the Alzheimer's diagnosis, acceptance, flexibility, sibling and parental relationships, communication, planning, shared family philosophy, family of origin roles, and boundary ambiguity. Implications for clinical practice and suggestions for future research are included. / Master of Science

Autism is a behaviourally defined disorder. The impairments in social communication and repetitive behaviours are individually non-specific. The disorder has indistinct boundaries both with other psychiatric disorders and with normal personality types. At the cognitive level, groups of people with autistic disorder can be differentiated from people without the disorder by their ability to reason about beliefs and knowledge (Theory of Mind) and by tests of visual disembedding (central coherence). This study examined whether young people with some of the behavioural features of autism but not necessarily a diagnosis, would show this distinctive cognitive profile. In a sample of 60 young people with additional learning support needs, we found that those with high levels of autistic traits (n=40) showed the same cognitive profile as has been found in people diagnosed with autistic disorder. This supports the view that autism is an extreme on a continuum of cognitive traits. Given the highly heritable nature of autism, we hypothesised that the parents of the young people with autistic traits will also display these cognitive features. The results indicated that there was no difference between the groups of parents on an advanced test of social cognition. Parents of people with high autistic traits were more resistant to one of the visual illusions and saw fewer reversals of an ambiguous figure when IQ was statistically controlled. These results in a sample with a low genetic load suggest ambiguous figures will be important in delineating the broader cognitive phenotype of autism.

Faces, along with the personal identities behind them, are effective elements in organizing a collection of consumer photos, as they represent who was involved. However, the accurate discrimination and subsequent recognition of face appearances is still very challenging. This can be attributed to the fact that faces are usually neither perfectly lit nor captured, particularly in the uncontrolled environments of consumer photos. Unlike, for instance, passport photos that only show faces stripped of their surroundings, Consumer Photo Collections contain a vast amount of meaningful context. For example, consecutively shot photos often correlate in time, location or scene. Further information can also be provided by the people appearing in photos, such as their demographics (ages and gender are often easier to surmise than identities), clothing, or the social relationships among co-occurring people. Motivated by this ubiquitous context, we propose and research people recognition approaches that consider contextual information within photos, as well as across entire photo collections. Our aim of leveraging additional contextual information (as opposed to only considering faces) is to improve recognition performance. However, instead of requiring users to explicitly label specific pieces of contextual information, we wish to implicitly learn and draw from the seemingly coherent content that exists inherently across an entire photo collection. Moreover, unlike conventional approaches that usually predict the identity of only one person’s appearance at a time, we lay out a semi-supervised approach to jointly recognize multiple peoples’ appearances across an entire photo collection simultaneously. As such, our aim is to find the overall best recognition solution. To make context-based joint recognition of people feasible, we research a sparse but efficient graph-based approach that builds on Markov Networks and utilizes distance-based face description methods. We show how to exploit the following specific contextual cues: time, social semantics, body appearances (clothing), gender, scene and ambiguous captions. We also show how to leverage crowd-sourced gamified feedback to iteratively improve recognition performance. Experiments on several datasets demonstrate and validate the effectiveness of our semisupervised graph-based recognition approach compared to conventional approaches.

The number of Americans living abroad currently is estimated at over four million, with over 37,000 matriculating into U.S. universities each year. If the social media giant Facebook were a country, it would be third largest in the world, with over 300 million users outside of America. The trajectory of our society is increasingly global. Amidst this shift, there is a unique multicultural subpopulation emerging-- Third Culture Kids (TCK), who experience a collision of cultures and form hybrid identities in the course of their development. TCKs are more specifically when a person spends a significant part of their developmental years outside their parents’ culture. The TCK takes on pieces of each culture, while never fully ‘belonging’ to any. They are most at home around others of a similar transient background. This report synthesizes research about globally mobile populations from across disciples, highlighting grief and ambiguous losses, acculturation stresses, and identity development. Potential implications for the college campus— at institutional and individual levels— will be discussed. This overview of current research and resources equips college counselors with a frame of reference for engaging this third culture in a holistic and contextualized manner. / text

Communicating with natural language interfaces is a long-standing, ultimate goal for artificial intelligence (AI) agents to pursue, eventually. One core issue toward this goal is "grounded" language learning, a process of learning the semantics of natural language with respect to relevant perceptual inputs. In order to ground the meanings of language in a real world situation, computational systems are trained with data in the form of natural language sentences paired with relevant but ambiguous perceptual contexts. With such ambiguous supervision, it is required to resolve the ambiguity between a natural language (NL) sentence and a corresponding set of possible logical meaning representations (MR). In this thesis, we focus on devising effective models for simultaneously disambiguating such supervision and learning the underlying semantics of language to map NL sentences into proper logical MRs. We present probabilistic generative models for learning such correspondences along with a reranking model to improve the performance further. First, we present a probabilistic generative model that learns the mappings from NL sentences into logical forms where the true meaning of each NL sentence is one of a handful of candidate logical MRs. It simultaneously disambiguates the meaning of each sentence in the training data and learns to probabilistically map an NL sentence to its corresponding MR form depicted in a single tree structure. We perform evaluations on the RoboCup sportscasting corpus, proving that our model is more effective than those proposed by previous researchers. Next, we describe two PCFG induction models for grounded language learning that extend the previous grounded language learning model of Börschinger, Jones, and Johnson (2011). Börschinger et al.’s approach works well in situations of limited ambiguity, such as in the sportscasting task. However, it does not scale well to highly ambiguous situations when there are large sets of potential meaning possibilities for each sentence, such as in the navigation instruction following task first studied by Chen and Mooney (2011). The two models we present overcome such limitations by employing a learned semantic lexicon as a basic correspondence unit between NL and MR for PCFG rule generation. Finally, we present a method of adapting discriminative reranking to grounded language learning in order to improve the performance of our proposed generative models. Although such generative models are easy to implement and are intuitive, it is not always the case that generative models perform best, since they are maximizing the joint probability of data and model, rather than directly maximizing conditional probability. Because we do not have gold-standard references for training a secondary conditional reranker, we incorporate weak supervision of evaluations against the perceptual world during the process of improving model performance. All these approaches are evaluated on the two publicly available domains that have been actively used in many other grounded language learning studies. Our methods demonstrate consistently improved performance over those of previous studies in the domains with different languages; this proves that our methods are language-independent and can be generally applied to other grounded learning problems as well. Further possible applications of the presented approaches include summarized machine translation tasks and learning from real perception data assisted by computer vision and robotics. / text

Modern processor architectures suffer from an ever increasing gap between processor and memory performance. The current memory-register model attempts to hide this gap by a system of cache memory. Line Associative Registers(LARs) are proposed as a new system to avoid the memory gap by pre-fetching and associative updating of both instructions and data. This thesis presents a fully LAR-based architecture, targeting a previously developed instruction set architecture. This architecture features an execution pipeline supporting SWAR operations, and a memory system supporting the associative behavior of LARs and lazy writeback to memory.

This thesis presents the results of three studies that extend understanding of ethical decision making in negotiation. First, by comparing how Chinese and Australian negotiators think about contextual variables in an interpretive study, an extended model of ethical decision making in negotiation is offered. This study suggested differences in how codes of ethics and perception of the other party were understood as well as a shared understanding of the influence of the legal environment across the two cultures. Importance of organisational goals and personal and business reputation also emerged as important variables in negotiators' ethical decision making. The next study began testing the extended model with an investigation of the interaction between culture and closeness of the relationship with the other party using the SINS scale (Robinson, Lewicki, & Donahue, 2000). It was found that Chinese negotiators generally rated ethically ambiguous negotiation tactics as more appropriate than Australians, and that Chinese differentiated more in their ratings of appropriateness according to the social context. In the test for metric equivalence of the SINS scale, this study found that the existing approach of inductively deriving types of ethically ambiguous negotiation tactics based on ratings of perceived appropriateness is flawed since patterns of ratings are likely to vary across groups of negotiators. In light of this, a new typology of ethically ambiguous negotiation tactics is offered based on an a priori identification of conceptually distinct types of tactics. This new inventory of items represents the first step in the process of producing a cross-culturally generalisable scale of ethically ambiguous negotiation tactics.

The field of autism in epidemiology has received much attention in recent times especially as scientific information evolves on the causes and impact of autism spectrum disorder. Just as medical research is conducting to arrest the growing pace of autism with current research indicating one out of every 68 children in the United States diagnosed autistic, the field of the social science has equally produced some literature on the subject. Much of the social science and epidemiological information in the field has bothered on framing the concept (Murray, 2008), historical dimension and causation of the disease, and its associative influence on family (Grinker, 2007). However, not much has been done to assess the phenomenon from the point of view of conflict analysis and resolution (Sabatelli & Waldron, 1995) to fully understand their sense of conflict ambiguity and ambiguous loss of a child with autism (Cridland et al. 2014; O'Brien, 2007). This research therefore attempted to bridge that gap through reflexive analysis of transcripts from phenomenological interviewing of 19 participants comprised of 14 single parents and 5 married couples with autistic children. While the primary focus of the research was Single parents, married couples served comparative analytical purpose of data validation. Theories of phenomenology, Resilience, human needs, stereotypes & identity, relative deprivation, attribution, critical theory, ambiguous loss, etc. operationalize to frame the research language for hermeneutical transformative interpretation and social action about the phenomenon. Results from the study indicate conflict behavioral experience, a burden curve and resilient risk factors associated with caring for an autistic child leading to possible crisis borderline.

Historically, “offender”-focused discourses have dominated the field of criminology while overlooking those family members who become subject to justice intervention by virtue of their familial bonds. In this qualitative study, unstructured interviews were conducted with eight nuclear family members of criminalized persons in Ontario and Quebec. Participant accounts reveal that the interviewed family members self-imposed significant moral and legal responsibilities for their relatives following criminal justice intervention and simultaneously experienced negative role re-evaluation driven by feelings of guilt, failure, and self-blame. Participants’ inherent lack of control over their criminalized relatives’ behaviours and the criminal justice system’s decisions exacerbate negative impacts of criminalization on non-criminalized relatives’ self-concepts. This lack of control increases the stress of criminal justice intervention while straining family resources. When relatives are justice-involved for prolonged period, the family becomes stuck in a constant state of stress and uncertainty, which may have lasting consequences on the family if left unmanaged. Criminal justice intervention as a disruptive event then reconfigures the family in ways that often leave lasting impacts on nuclear family relationships. This thesis engages with Boss’ (1999, 2006) theory of Ambiguous Loss to analyze participants’ experiences and demonstrate the consequences of criminalization on various nuclear family members in a Canadian context. To mitigate certain limitations of Boss’ (1999, 2006) theory, criminal justice intervention is first defined as a disruptive event that transforms family members’ known realities into threatening and uncertain environments. This thesis then explores the stress and strain that justice intervention places upon the family and applies the theory of Ambiguous Loss to understand criminalization as a source of ambiguous loss. Further, this thesis expands the scope of Boss’ (1999) theory beyond the experiences of certain populations (i.e. children of incarcerated parents) and discovers the limitations of this theory in the context of criminological research. It also opens the door for future research to apply this theory to criminalized populations.