Properties and algorithms of the hyper-star graph and its related graphs

The hyper-star interconnection network was proposed in 2002 to overcome the drawbacks of the hypercube and its variations concerning the network cost, which is defined by the product of the degree and the diameter. Some properties of the graph such as connectivity, symmetry properties, embedding properties have been studied by other researchers, routing and broadcasting algorithms have also been designed. This thesis studies the hyper-star graph from both the topological and algorithmic point of view. For the topological properties, we try to establish relationships between hyper-star graphs with other known graphs. We also give a formal equation for the surface area of the graph. Another topological property we are interested in is the Hamiltonicity problem of this graph. For the algorithms, we design an all-port broadcasting algorithm and a single-port neighbourhood broadcasting algorithm for the regular form of the hyper-star graphs. These algorithms are both optimal time-wise. Furthermore, we prove that the folded hyper-star, a variation of the hyper-star, to be maixmally fault-tolerant.

A comparison of functional behaviour assessment rating scales in a sample of children and youth with autism spectrum disorders

This study sought to compare the results of the Motivation Assessment Scale (MAS; Durand & Crimmins, 1988), Questions About Behavior Function Scale (QABF; Matson & Vollmer, 1996) and Functional Analysis Screening Tool (FAST; Iwata & Deleon, 1996), when completed by parent informants in a sample of children and youth with autism spectrum disorders (ASD) who display challenging behaviour. Results indicated that there was low agreement between the functional hypotheses derived from each of three measures. In addition, correlations between functionally analogous scales were substantially lower than expected, while correlations between non-analogous subscales were stronger than anticipated. As indicated by this study, clinicians choosing to use FBA questionnaires to assess behavioural function, may not obtain accurate functional hypotheses, potentially resulting in ineffective intervention plans. The current study underscores the caution that must be taken when asking parents to complete these questionnaires to determine the function(s) of challenging behaviour for children/youth with ASD.

Creativity and the schizophrenia spectrum unveiled : the similarities and the differences

This study examined the commonalities and the differences between creativity and the schizophrenia spectrum. The variables measured as potential commonalities and differences were creativity, schizotypy, cognitive inhibition, spatial ability, balancing skills, positive and negative presence, absorption, mystical experiences, childhood abuse, and neuroticism. Three community groups were recruited, consisting of 31 artists, 10 people with schizophrenia, and 31 comparisons matched for gender and age with the artists. A larger student group consisting of 102 students was also recruited in order to examine the correlations among the same variables within a larger, more normative, group. The largest commonality between the artist and the schizophrenic groups, who represented the extreme end of the schizophrenia spectrum, was the propensity to mystical experiences. The greatest differences between the artist and the schizophrenic groups were that the artists were higher in creativity, performed better on spatial abilities, had better balance, had more positive states of presence, and were lower in neuroticism than the schizophrenic group. In the student group, creativity was correlated with spatial ability, positive presence, absorption, and mystical experiences. In addition, creativity was significantly related to two facets of schizotypy, unusual experiences and impulsive nonconformity. In other words, students high in certain facets of schizotypy, who may share certain characteristics with those who have schizophrenia, are higher in creativity, but people who are on the extreme end of the schizophrenia spectrum, who have been diagnosed with schizophrenia, are not. The differences between the artist and schizophrenic groups on spatial ability, balance, sense of presence, and neuroticism may help to determine whether mystical experiences help to integrate creative work or destabilize and disorganize the sense of self. It may be that mystical experiences can be used more positively by the creative individuals than people with schizophrenia, in that artists and people high in creativity were higher in positive traits such as positive presence and lower on negative variables such as neuroticism, and introvertive anhedonia.

Functional analysis and treatment of OCD-related behaviour in a child with Autism Spectrum Disorder

Research indicates that Obsessive-Compulsive Disorder (OCD; DSM-IV-TR, American Psychiatric Association, 2000) is the second most frequent disorder to coincide with Autism Spectrum Disorder (ASD; Leyfer et aI., 2006). Excessive collecting and hoarding are also frequently reported in children with ASD (Berjerot, 2007). Although functional analysis (Iwata, Dorsey, Slifer, Bauman, & Richman, 1982/1994) has successfully identified maintaining variables for repetitive behaviours such as of bizarre vocalizations (e.g., Wilder, Masuda, O'Connor, & Baham, 2001), tics (e.g., Scotti, Schulman, & Hojnacki, 1994), and habit disorders (e.g., Woods & Miltenberger, 1996), extant literature ofOCD and functional analysis methodology is scarce (May et aI., 2008). The current studies utilized functional analysis methodology to identify the types of operant functions associated with the OCD-related hoarding behaviour of a child with ASD and examined the efficacy of function-based intervention. Results supported hypotheses of automatic and socially mediated positive reinforcement. A corresponding function-based treatment plan incorporated antecedent strategies and differential reinforcement (Deitz, 1977; Lindberg, Iwata, Kahng, and DeLeon, 1999; Reynolds, 1961). Reductions in problem behaviour were evidenced through use of a multiple baseline across behaviours design and maintained during two-month follow-up. Decreases in symptom severity were also discerned through subjective measures of treatment effectiveness.

Using the Reliable Change Index Statistic to Analyze Developmental Changes in Infants at Risk for Autism Spectrum Disorder

Longitudinal studies of the development of autism spectrum disorders (ASD) provide an understanding of which variables may be important predictors of an ASD. The objective of the current study is to apply the reliable change index (RCI) statistic to examine whether the Parent Observation of Early Markers Scale (POEMS) is sensitive to developmental change, and whether these changes can be quantified along a child’s developmental trajectory. Ninety-six children with older siblings with autism were followed from 1-36 months of age. Group-based RCI analysis confirms that the POEMS is capable of detecting significant changes within pre-defined diagnostic groups. Within-subject analysis suggests that ongoing monitoring of a child at-risk for an ASD requires interpretation of both significant intervals identified by the RCI statistic, as well as the presence of repeated high (i.e., >70) scores. This study provides preliminary evidence for a reasonably sensitive and specific means by which individual change can be clinically monitored via parent report.

Comparison of the Behavioural Development of Infants at Low and High-Risk for Autism Spectrum Disorders

By identifying early signs of Autism Spectrum Disorder, early intervention or parent training could be implemented and assist in increasing the developmental trajectory for these infants. This cross sectional study used the Parent Observation of Early Markers Scale (POEMS) to identify early signs of ASD in 69 high-risk (older sibling diagnosed with ASD) and 69 matched low-risk infants' families (no family history of ASD) between 6 and 36 months of age. The preliminary results showed the high-risk children had significantly more elevated POEMS items than the low-risk children at 12, 18,24,30 and 36 months of age. The results suggest that at-risk infants may show signs of ASD as early as 12 months of age, and that the POEMS could be used to guide early intervention or parent training for children 12 months or older.

Automatic Inference of Graph Models for Complex Networks with Genetic Programming

Complex networks can arise naturally and spontaneously from all things that act as a part of a larger system. From the patterns of socialization between people to the way biological systems organize themselves, complex networks are ubiquitous, but are currently poorly understood. A number of algorithms, designed by humans, have been proposed to describe the organizational behaviour of real-world networks. Consequently, breakthroughs in genetics, medicine, epidemiology, neuroscience, telecommunications and the social sciences have recently resulted. The algorithms, called graph models, represent significant human effort. Deriving accurate graph models is non-trivial, time-intensive, challenging and may only yield useful results for very specific phenomena. An automated approach can greatly reduce the human effort required and if effective, provide a valuable tool for understanding the large decentralized systems of interrelated things around us. To the best of the author's knowledge this thesis proposes the first method for the automatic inference of graph models for complex networks with varied properties, with and without community structure. Furthermore, to the best of the author's knowledge it is the first application of genetic programming for the automatic inference of graph models. The system and methodology was tested against benchmark data, and was shown to be capable of reproducing close approximations to well-known algorithms designed by humans. Furthermore, when used to infer a model for real biological data the resulting model was more representative than models currently used in the literature.

Cognitive Behavior Therapy for Obsessive-Compulsive Behavior in Children with Autism Spectrum Disorder: A Comparison of Hierarchical Linear Modelling and Visual Analysis

Behavioral researchers commonly use single subject designs to evaluate the effects of a given treatment. Several different methods of data analysis are used, each with their own set of methodological strengths and limitations. Visual inspection is commonly used as a method of analyzing data which assesses the variability, level, and trend both within and between conditions (Cooper, Heron, & Heward, 2007). In an attempt to quantify treatment outcomes, researchers developed two methods for analysing data called Percentage of Non-overlapping Data Points (PND) and Percentage of Data Points Exceeding the Median (PEM). The purpose of the present study is to compare and contrast the use of Hierarchical Linear Modelling (HLM), PND and PEM in single subject research. The present study used 39 behaviours, across 17 participants to compare treatment outcomes of a group cognitive behavioural therapy program, using PND, PEM, and HLM on three response classes of Obsessive Compulsive Behaviour in children with Autism Spectrum Disorder. Findings suggest that PEM and HLM complement each other and both add invaluable information to the overall treatment results. Future research should consider using both PEM and HLM when analysing single subject designs, specifically grouped data with variability.

Exploring the Therapeutic Alliance in Cognitive-Behavior Therapy with Children with Autism Spectrum Disorder: An Interpretative Phenomenological Approach

Abstract The therapeutic alliance (TA) is the most studied process of adult psychotherapeutic change (Zack et al., 2007) and has been found to have a moderate but robust relationship with therapeutic outcome regardless of treatment modality (Horvath, 2001). The TA is loosely described as the extent to which the therapist and the participant connect emotionally and work together towards goals. Conceptualizations of the TA with children have relied on adult models, even though it is widely acknowledged that the pediatric population will rarely willingly commit to therapy, nor readily admit to any challenges that they may be experiencing (Keeley, Geffken, McNamara & Storch, 2011). For children with Autism Spectrum Disorder (ASD) the therapeutic alliance may require an even greater retheorizing considering the communicative and social difficulties of this particular population. Despite this need, research on children with ASD and the therapeutic TA is almost non-existent. In this qualitative study, transcripts from semi-structured interviews with mothers of children with ASD were analyzed using Interpretative Phenomenological Analysis (IPA). IPA closely examines how individual people make sense of their life experiences using a theme-by-theme approach. The three interviewees were mothers whose children were participants in a nine-week Cognitive Behaviour Therapy (CBT) group for obsessive-compulsive behaviours (OCB). A total of four superordinate themes were identified: (i) Centralization and disremembering the TA, (ii) Qualities of the therapist, (iii) TA and the importance of time, and (iv) Signs of a healthy TA. The mothers’ perspectives on the TA suggest that, for them and their children, a strong TA was a required component of the therapy. Implications for clinicians and researchers are discussed.

Network Similarity Measures and Automatic Construction of Graph Models using Genetic Programming

A complex network is an abstract representation of an intricate system of interrelated elements where the patterns of connection hold significant meaning. One particular complex network is a social network whereby the vertices represent people and edges denote their daily interactions. Understanding social network dynamics can be vital to the mitigation of disease spread as these networks model the interactions, and thus avenues of spread, between individuals. To better understand complex networks, algorithms which generate graphs exhibiting observed properties of real-world networks, known as graph models, are often constructed. While various efforts to aid with the construction of graph models have been proposed using statistical and probabilistic methods, genetic programming (GP) has only recently been considered. However, determining that a graph model of a complex network accurately describes the target network(s) is not a trivial task as the graph models are often stochastic in nature and the notion of similarity is dependent upon the expected behavior of the network. This thesis examines a number of well-known network properties to determine which measures best allowed networks generated by different graph models, and thus the models themselves, to be distinguished. A proposed meta-analysis procedure was used to demonstrate how these network measures interact when used together as classifiers to determine network, and thus model, (dis)similarity. The analytical results form the basis of the fitness evaluation for a GP system used to automatically construct graph models for complex networks. The GP-based automatic inference system was used to reproduce existing, well-known graph models as well as a real-world network. Results indicated that the automatically inferred models exemplified functional similarity when compared to their respective target networks. This approach also showed promise when used to infer a model for a mammalian brain network.

A Phenomenologically Sensitized Analysis of Images Depicting Stressed Embodiment in an Adolescent Male with Autism Spectrum Disorder (ASD)

Each person with Autism Spectrum Disorder (ASD) comes with unique characteristics (idiosyncratic) that give clues to the world they know (Connolly, 2008). It is through their body that they (a) know the world they are experiencing, (b) make meaning, and (c) express certain behaviours. I used Laban’s Movement Analysis (LMA) to practice an attuned and appreciative approach to describing and understanding the body movement in one severe manifestation of autism in an adolescent male. LMA observes human movement across many disciplines and can be applied in many contexts providing a body honoring discourse for description (Connolly, 2008). The framework examines movement in body, space, quality, and relation. Each theme provides a detailed description of the individual’s movement, thus, giving us a richer understanding of patterns and possible triggers to self-injurious behaviours (SIB). During the summer of August 2013, I participated in Brock University’s annual Autism Camp and worked with a 15 year old male named “Aaron” who manifests with low functioning autism. The purpose of my research project was to code and analyze a series of photos taken to help gain insight into movement patterns associated with stressed embodiment and self-injury in “Aaron”. As I understood more about these embodied expressions, I uncovered valuable information on how to read patterns and discover what triggers these events, thus providing strategies on how to help people do more refined observations and make meaning of the behaviour. Laban’s movement analysis provided a sensitized discourse appropriate to the embodied expressions depicted in the photos.

Using HeadSprout Early Reading with a child with Autism Spectrum Disorder: An examination of phonological awareness, participant engagement, and participant enjoyment

This study examined the effectiveness of a 9-week reading program in improving the phonological awareness (PA) skills of a seven year old boy with Autism Spectrum Disorder (ASD), Attention Deficit Hyperactivity Disorder (ADHD), and Oppositional Defiant Disorder (ODD). The study’s secondary goal was to describe how the participant engaged with and enjoyed the HeadSprout computer program. The participant attended a one hour reading program incorporating 30 minutes of HeadSprout Early Reading three days a week for 9 weeks. Results demonstrated that the participant’s PA scores increased from the 16th percentile at pre-test to the 35th percentile post program. Four of five measures of PA increased, segmenting nonwords decreased to the 2nd percentile post program. Momentary time sampling procedures revealed the participant was engaged with the computer program 94.5% of the time. Perceived ratings of enjoyment indicated the participant enjoyed using the program. Specific components of the program which may have influenced participant enjoyment and engagement are discussed. Study limitations and implications of these findings are discussed in reference to future research.

Perspectives of Parents of Children with Autism Spectrum Disorder on a Community-Based Parent Education Program

In 2012 a community-based agency that oversees Intensive Behaviour Intervention services for young children diagnosed with Autism Spectrum Disorder (ASD) began delivering newly developed curricula to parents of eligible children. The curricula’s intent was to inform parents about ASD and Applied Behaviour Analysis, to increase their awareness of available community resources, and assist them to be active and engaged in their child’s learning. This mixed-method study used a program-specific survey and focus groups to explore the perspectives parents had on their involvement in these education sessions. Through constant comparison analysis 4 major and 3 minor themes emerged. In general, parents acknowledged that this parent education program included relevant content and a favourable delivery format. The study summarized a number of well-articulated, practical suggestions parents provided. Implications for practice would be applicable to educators interested in providing quality group-based education to parents of young children with ASD.

Object-Oriented Genetic Programming for the Automatic Inference of Graph Models for Complex Networks

Complex networks are systems of entities that are interconnected through meaningful relationships. The result of the relations between entities forms a structure that has a statistical complexity that is not formed by random chance. In the study of complex networks, many graph models have been proposed to model the behaviours observed. However, constructing graph models manually is tedious and problematic. Many of the models proposed in the literature have been cited as having inaccuracies with respect to the complex networks they represent. However, recently, an approach that automates the inference of graph models was proposed by Bailey [10] The proposed methodology employs genetic programming (GP) to produce graph models that approximate various properties of an exemplary graph of a targeted complex network. However, there is a great deal already known about complex networks, in general, and often specific knowledge is held about the network being modelled. The knowledge, albeit incomplete, is important in constructing a graph model. However it is difficult to incorporate such knowledge using existing GP techniques. Thus, this thesis proposes a novel GP system which can incorporate incomplete expert knowledge that assists in the evolution of a graph model. Inspired by existing graph models, an abstract graph model was developed to serve as an embryo for inferring graph models of some complex networks. The GP system and abstract model were used to reproduce well-known graph models. The results indicated that the system was able to evolve models that produced networks that had structural similarities to the networks generated by the respective target models.

Parent Prediction of Autism Spectrum Disorder in Infants At Risk: A Follow-up Study

Later-born siblings of children with autism spectrum disorder (ASD) are considered at biological risk for ASD and the broader autism phenotype. Early screening may detect early signs of ASD and facilitate intervention as soon as possible. This follow-up study revisits and re-examines a second-degree autism screener for children at biological risk of autism, the Parent Observation Early Markers Scale (POEMS, Feldman et al., 2012). Using available follow-up information, 110 children (the original 108 infants plus 2 infants recruited after the completion of the original study) were divided into three groups: diagnosed group (n = 13), lost diagnosis group (n = 5), and undiagnosed group (n = 92). The POEMS continued to show acceptable predictive validity. The POEMS total scores and mean number of elevated items were significantly higher in the diagnosed group than the undiagnosed group. The lost diagnosis group did not differ from the undiagnosed group on POEMS total scores and elevated items at any age, but the lost diagnosis group had significantly lower total scores and number of elevated items than the diagnosed group starting at 18 months. Both ASD core and subsidiary behaviours differentiated the diagnosed and undiagnosed groups from 9−36 months of age. Using 70 as a cut-off score, sensitivity, specificity, and positive predictive value (PPV) were .69, .84, and .38, respectively. The study provides further evidence that the POEMS may serve as a low-cost early screener for ASD in at risk children and pinpoint specific developmental and behavioural problems that may be amenable to very early intervention.