The aim of this study was to investigate the intra- and intermodal impact of different kinds of early sensory experience on the development of specific neural/perceptual systems. The manipulations of the rats' early experience involved a combination of early binocular deprivation through dark-rearing, somatosensory restriction through cauterization of mystacial vibrissae, and multimodal enrichment through rearing in a complex environment. Specific lesions to somatosensory (Parl) and visual (Oc2M) cortex in differentially reared animals were included in an attempt to gain further insight into the plasticity surrounding manipulations of early stimulation history. Five tasks were used to assess these effects of early rearing condition in combination with later cortical lesions. Behavioral assessment focused on the ability of the animals to encode, abstract, and remember specific relationships between stimuli within the deprived modality itself, their ability to do so with information presented in other modalities, and on the basic species specific behavior. The only effect found was a main effect for rearing condition. Basically, complex-reared rats were more competent on several of the behavioral tasks than were dark-reared rats. However, this result provided little behavioral support for ideas of modality interdependence. Dendritic proliferation is considered to be a general mechanism supporting behavioral change. The subsequent neuroanatomical assessment focused on dendritic branching of neurons in specific cortical areas thought to be most affected by early environmental manipulations. Animals that were raised in a complex environment, but had experienced early tactile restriction through cauterization of vibrissae, showed significantly more dendritic branching than animals from all other rearing conditions in all cortical areas measured. This finding is consistent with ideas of both intra- and intermodal compensation following damage to an early developing modality, as well as behavioral demand acting as a significant factor in determining the impact of early somatosensory restriction. It is reasonable to assume that anatomical changes should be manifested behaviorally. Suggestions for smaller, more restricted studies, that would be more effective in describing the behavioral impact of early manipulations of the environment, were outlined. / Arts, Faculty of / Psychology, Department of / Graduate

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This dissertation focuses on the topic of building group generalization by considering the detection of building patterns. Generalization is an important research field in cartography, which is part of map production and the basis for the derivation of multiple representation. As one of the most important features on map, buildings occupy large amount of map space and normally have complex shape and spatial distribution, which leads to that the generalization of buildings has long been an important and challenging task. For social, architectural and geographical reasons, the buildings were built with some special rules which forms different building patterns. Building patterns are crucial structures which should be carefully considered during graphical representation and generalization. Although people can effortlessly perceive these patterns, however, building patterns are not explicitly described in building datasets. Therefore, to better support the subsequent generalization process, it is important to automatically recognize building patterns. The objective of this dissertation is to develop effective methods to detect building patterns from building groups. Based on the identified patterns, some generalization methods are proposed to fulfill the task of building generalization. The main contribution of the dissertation is described as the following five aspects: (1) The terminology and concept of building pattern has been clearly explained; a detailed and relative complete typology of building patterns has been proposed by summarizing the previous researches as well as extending by the author; (2) A stroke-mesh based method has been developed to group buildings and detect different patterns from the building groups; (3) Through the analogy between line simplification and linear building group typification, a stroke simplification based typification method has been developed aiming at solving the generalization of building groups with linear patterns; (4) A mesh-based typification method has been developed for the generalization of the building groups with grid patterns; (5) A method of extracting hierarchical skeleton structures from discrete buildings have been proposed. The extracted hierarchical skeleton structures are regarded as the representations of the global shape of the entire region, which is used to control the generalization process. With the above methods, the building patterns are detected from the building groups and the generalization of building groups are executed based on the patterns. In addition, the thesis has also discussed the drawbacks of the methods and gave the potential solutions.:Abstract I Kurzfassung III Contents V List of Figures IX List of Tables XIII List of Abbreviations XIV Chapter 1 Introduction 1 1.1 Background and motivation 1 1.1.1 Cartographic generalization 1 1.1.2 Urban building and building patterns 1 1.1.3 Building generalization 3 1.1.4 Hierarchical property in geographical objects 3 1.2 Research objectives 4 1.3 Study area 5 1.4 Thesis structure 6 Chapter 2 State of the Art 8 2.1 Operators for building generalization 8 2.1.1 Selection 9 2.1.2 Aggregation 9 2.1.3 Simplification 10 2.1.4 Displacement 10 2.2 Researches of building grouping and pattern detection 11 2.2.1 Building grouping 11 2.2.2 Pattern detection 12 2.2.3 Problem analysis . 14 2.3 Researches of building typification 14 2.3.1 Global typification 15 2.3.2 Local typification 15 2.3.3 Comparison analysis 16 2.3.4 Problem analysis 17 2.4 Summary 17 Chapter 3 Using stroke and mesh to recognize building group patterns 18 3.1 Abstract 19 3.2 Introduction 19 3.3 Literature review 20 3.4 Building pattern typology and study area 22 3.4.1 Building pattern typology 22 3.4.2 Study area 24 3.5 Methodology 25 3.5.1 Generating and refining proximity graph 25 3.5.2 Generating stroke and mesh 29 3.5.3 Building pattern recognition 31 3.6 Experiments 33 3.6.1 Data derivation and test framework 33 3.6.2 Pattern recognition results 35 3.6.3 Evaluation 39 3.7 Discussion 40 3.7.1 Adaptation of parameters 40 3.7.2 Ambiguity of building patterns 44 3.7.3 Advantage and Limitation 45 3.8 Conclusion 46 Chapter 4 A typification method for linear building groups based on stroke simplification 47 4.1 Abstract 48 4.2 Introduction 48 4.3 Detection of linear building groups 50 4.3.1 Stroke-based detection method 50 4.3.2 Distinguishing collinear and curvilinear patterns 53 4.4 Typification method 55 4.4.1 Analogy of building typification and line simplification 55 4.4.2 Stroke generation 56 4.4.3 Stroke simplification 57 4.5 Representation of newly typified buildings 60 4.6 Experiment 63 4.6.1 Linear building group detection 63 4.6.2 Typification results 65 4.7 Discussion 66 4.7.1 Comparison of reallocating remained nodes 66 4.7.2 Comparison with classic line simplification method 67 4.7.3 Advantage 69 4.7.4 Further improvement 71 4.8 Conclusion 71 Chapter 5 A mesh-based typification method for building groups with grid patterns 73 5.1 Abstract 74 5.2 Introduction 74 5.3 Related work 75 5.4 Methodology of mesh-based typification 78 5.4.1 Grid pattern classification 78 5.4.2 Mesh generation 79 5.4.3 Triangular mesh elimination 80 5.4.4 Number and positioning of typified buildings 82 5.4.5 Representation of typified buildings 83 5.4.6 Resizing Newly Typified Buildings 85 5.5 Experiments 86 5.5.1 Data derivation 86 5.5.2 Typification results and evaluation 87 5.5.3 Comparison with official map 91 5.6 Discussion 92 5.6.1 Advantages 92 5.6.2 Further improvements 93 5.7 Conclusion 94 Chapter 6 Hierarchical extraction of skeleton structures from discrete buildings 95 6.1 Abstract 96 6.2 Introduction 96 6.3 Related work 97 6.4 Study area 99 6.5 Hierarchical extraction of skeleton structures 100 6.5.1 Proximity Graph Network (PGN) of buildings 100 6.5.2 Centrality analysis of proximity graph network 103 6.5.3 Hierarchical skeleton structures of buildings 108 6.6 Generalization application 111 6.7 Experiment and discussion 114 6.7.1 Data statement 114 6.7.2 Experimental results 115 6.7.3 Discussion 118 6.8 Conclusions 120 Chapter 7 Discussion 121 7.1 Revisiting the research problems 121 7.2 Evaluation of the presented methodology 123 7.2.1 Strengths 123 7.2.2 Limitations 125 Chapter 8 Conclusions 127 8.1 Main contributions 127 8.2 Outlook 128 8.3 Final thoughts 131 Bibliography 132 Acknowledgements 142 Publications 143

We introduce Domain Aware Continual Zero-Shot Learning (DACZSL), the task of visually recognizing images of unseen categories in unseen domains sequentially. We created DACZSL on top of the DomainNet dataset by dividing it into a sequence of tasks, where classes are incrementally provided on seen domains during training and evaluation is conducted on unseen domains for both seen and unseen classes. We also proposed a novel Domain-Invariant CZSL Network (DIN), which outperforms state-of-the-art baseline models that we adapted to DACZSL setting. We adopt a structure-based approach to alleviate forgetting knowledge from previous tasks with a small per-task private network in addition to a global shared network. To encourage the private network to capture the domain and task-specific representation, we train our model with a novel adversarial knowledge disentanglement setting to make our global network task-invariant and domain-invariant over all the tasks. Our method also learns a class-wise learnable prompt to obtain better class-level text representation, which is used to represent side information to enable zero-shot prediction of future unseen classes. Our code and benchmarks are made available at https://zero-shot-learning.github.io/daczsl.

Recombinative generalization is a generative outcome that involves responding to novel stimulus combinations, and it can be facilitated through an instructional approach called matrix training. A learner's history with constituent stimuli and the arrangement of combination stimuli within the instructional matrix may affect the likelihood of recombinative generalization. To investigate this further, the current project assessed recombinative generalization with novel combinations of abstract stimuli by programming specific training histories for undergraduate student participants. The matrix training conditions were: (a) trained constituents with overlap training, (b) untrained constituents with overlap training, (c) trained constituents with nonoverlap training, and (d) untrained constituents with nonoverlap training. We evaluated whether and the extent to which recombinative generalization occurred in each matrix training condition in comparison to a condition that included training the constituents and providing a word-order rule. Finally, we compared the training trials in experimental conditions to directly training all constituents and combinations. The results suggested both overlap conditions and the trained constituents with nonoverlap condition produced recombinative generalization, and the trained constituents with nonoverlap condition was the most efficient. These results could inform the training order and stimulus arrangements practitioners employ to program for recombinative generalization.

Ten developmentally disabled children participated in an assessment of stimulus control and transfer of training. Each subject was taught to perform a simple, nonverbal, imitative task in a training room, and transfer to a novel setting was assessed. During training, subjects were video-taped in order to determine how often each visual stimulus in the training room was looked at. After an initial transfer t est each subject participated in a test of the stimulus control acquired by visual stimuli from the training room. Utilizing two groups (N = 5 each), subjects received an additional transfer test in the novel setting while in the presence of a stimulus that had been either frequently or infrequently looked at during the training process. Subjects tested in the presence of a frequently-looked-at stimulus produced a greater number of correct responses during the transfer tests than subjects tested in the presence of an infrequently-looked-at stimulus. Individual data are also presented fer the subjects. The implications of these results are discussed.

Generalization of LOD2 building models using the aggregation method Abstract The thesis proposes and implements a method of 3D building models aggregation. The procedure achieves global optima by the means of mathematic optimization. Buildings are aggregated according to similarity characteristics typical for LOD2, e. g. roof type. Aggregation process is driven by minimalization of volume changes and of the aggregate count. The optimization problem was implemented as a Python script with optional parameters to meet custom demands of a wide range of users. Input data models of buildings are created by the method of procedural modelling. Its outcome is further restructured into form of continuous blocks. Finally, the visualization procedure is designed and implemented to illustrate the results of optimized aggregation of 3D building models. Keywords: 3D GIS, generalization, aggregation, mathematical optimization, procedural modelling

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The Substance Abuse Subtle Screening Inventory (SASSI) is a 10 scale indirect screening instrument used to detect substance use disorders. The current meta-analytic study described reliability reporting practices across 48 studies involving the SASSI. Reliability generalization methods were then employed to evaluate typical score reliability for the screening measure. Results showed approximately 73 of studies did not report reliability estimates. Analysis of data from the remaining studies revealed adequate reliability for the total scale (α .87) and face valid scales (FVA α .88 and FVOD α .92), but substantially lower reliability estimates for the indirect scales (range of α .23.65). The study's findings underscore the need for improved reliability reporting for the SASSI and suggest cautious use of the measure, especially its indirect scales, as an indicator of problematic substance use/abuse in clinical settings.

Three drug and alcohol use screening scales are embedded within the Minnesota Multiphasic Personality Inventory-2: the MacAndrew Alcoholism Scale (MAC) and its revised version (MAC-R), the Addiction Acknowledgement Scale (AAS), and the Addiction Potential Scale (APS). The current study evaluated the reliability reporting practices among 210 studies administering the MAC/MAC-R, APS, and/or AAS. Furthermore, reliability generalization methods were used to characterize the previously reported reliability estimates associated with each instrument. The vast majority of studies (90.6%) did not provide measurement reliability data, suggesting a need for improved psychometric reporting. Data from the remaining studies yielded mean and median score reliability estimates below.70 for each of the identified measures. Although limited in some instances by sample size constraints, results suggest that these instruments tend not to produce scores with acceptable levels of reliability for most research or clinical situations.