What Archetypes of Representation Do Children between the Ages of Four and Seven Employ When Creating Route Maps of Familiar Interior Spaces?

This study investigated the symbols of representation young children choose to incorporate when they draw route maps of familiar interior spaces, based on the premise that development of map-making skills might unfold in much the same stage-like manner as the development of the ability to draw the human figure. In this investigation, children between the ages of 4 and 7 enrolled in a small independent elementary school were each asked to draw a map showing the route a person unfamiliar to the school would take to travel from the child\u27s classroom to the school gymnasium. Strategies during map-making were noted; completed maps were analyzed to identify archetypal representations of pathway, context, landmark, and figure. Statistically significant differences were found in archetypal use between the 4.5-5.0 and the 6.0-7.0 age groups, suggesting that archetypes of representation both appear and wane in a stage-like manner. The results imply further study is required to more closely identify archetypes and patterns of emergence and disappearance in the population at large. The results also suggest that offering more curricular opportunities in the earliest grades for young children to create maps may be warranted

Framework development for providing accessibility to qualitative spatial calculi

Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.Qualitative spatial reasoning deals with knowledge about an infinite spatial domain using a finite set of qualitative relations without using numerical computation. Qualitative knowledge is relative knowledge where we obtain the knowledge on the basis of comparison of features with in the object domain rather then using some external scales. Reasoning is an intellectual facility by which, conclusions are drawn from premises and is present in our everyday interaction with the geographical world. The kind of reasoning that human being relies on is based on commonsense knowledge in everyday situations. During the last decades a multitude of formal calculi over spatial relations have been proposed by focusing on different aspects of space like topology, orientation and distance. Qualitative spatial reasoning engines like SparQ and GQR represents space and reasoning about the space based on qualitative spatial relations and bring qualitative reasoning closer to the geographic applications. Their relations and certain operations defined in qualitative calculi use to infer new knowledge on different aspects of space. Today GIS does not support common-sense reasoning due to limitation for how to formalize spatial inferences. It is important to focus on common sense geographic reasoning, reasoning as it is performed by human. Human perceive and represents geographic information qualitatively, the integration of reasoner with spatial application enables GIS users to represent and extract geographic information qualitatively using human understandable query language. In this thesis, I designed and developed common API framework using platform independent software like XML and JAVA that used to integrate qualitative spatial reasoning engines (SparQ) with GIS application. SparQ is set of modules that structured to provides different reasoning services. SparQ supports command line instructions and it has a specific syntax as set of commands. The developed API provides interface between GIS application and reasoning engine. It establishes connection with reasoner over TCP/IP, takes XML format queries as input from GIS application and converts into SparQ module specific syntax. Similarly it extracts given result, converts it into defined XML format and passes it to GIS application over the same TCP/IP connection. The most challenging part of thesis was SparQ syntax analysis for inputs and their outputs. Each module in Sparq takes module specific query syntax and generates results in multiple syntaxes like; error, simple result and result with comments. Reasoner supports both binary and ternary calculi. The input query syntax for binary-calculi is different for ternary-calculi in the terms of constraint-networks. Based on analysis I, identified commonalities between input query syntaxes for both binary and ternary calculi and designed XML structures for them. Similarly I generalized SparQ results into five major categories and designed XML structures. For ternary-calculi, I considered constraint-reasoning module and their specific operations and designed XML structure for both of their inputs and outputs

Computational intelligence approaches to robotics, automation, and control [Volume guest editors]

No abstract available

DYNAMICS OF COLLABORATIVE NAVIGATION AND APPLYING DATA DRIVEN METHODS TO IMPROVE PEDESTRIAN NAVIGATION INSTRUCTIONS AT DECISION POINTS FOR PEOPLE OF VARYING SPATIAL APTITUDES

Cognitive Geography seeks to understand individual decision-making variations based on fundamental cognitive differences between people of varying spatial aptitudes. Understanding fundamental behavioral discrepancies among individuals is an important step to improve navigation algorithms and the overall travel experience. Contemporary navigation aids, although helpful in providing turn-by-turn directions, lack important capabilities to distinguish decision points for their features and importance. Existing systems lack the ability to generate landmark or decision point based instructions using real-time or crowd sourced data. Systems cannot customize personalized instructions for individuals based on inherent spatial ability, travel history, or situations. This dissertation presents a novel experimental setup to examine simultaneous wayfinding behavior for people of varying spatial abilities. This study reveals discrepancies in the information processing, landmark preference and spatial information communication among groups possessing differing abilities. Empirical data is used to validate computational salience techniques that endeavor to predict the difficulty of decision point use from the structure of the routes. Outlink score and outflux score, two meta-algorithms that derive secondary scores from existing metrics of network analysis, are explored. These two algorithms approximate human cognitive variation in navigation by analyzing neighboring and directional effect properties of decision point nodes within a routing network. The results are validated by a human wayfinding experiment, results show that these metrics generally improve the prediction of errors. In addition, a model of personalized weighting for users\u27 characteristics is derived from a SVMrank machine learning method. Such a system can effectively rank decision point difficulty based on user behavior and derive weighted models for navigators that reflect their individual tendencies. The weights reflect certain characteristics of groups. Such models can serve as personal travel profiles, and potentially be used to complement sense-of-direction surveys in classifying wayfinders. A prototype with augmented instructions for pedestrian navigation is created and tested, with particular focus on investigating how augmented instructions at particular decision points affect spatial learning. The results demonstrate that survey knowledge acquisition is improved for people with low spatial ability while decreased for people of high spatial ability. Finally, contributions are summarized, conclusions are provided, and future implications are discussed

Unlocking Environmental Narratives

Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities

Unlocking environmental narratives: towards understanding human environment interactions through computational text analysis

Understanding the role of humans in environmental change is one of the most pressing challenges of the 21st century. Environmental narratives – written texts with a focus on the environment – offer rich material capturing relationships between people and surroundings. We take advantage of two key opportunities for their computational analysis: massive growth in the availability of digitised contemporary and historical sources, and parallel advances in the computational analysis of natural language. We open by introducing interdisciplinary research questions related to the environment and amenable to analysis through written sources. The reader is then introduced to potential collections of narratives including newspapers, travel diaries, policy documents, scientific proposals and even fiction. We demonstrate the application of a range of approaches to analysing natural language computationally, introducing key ideas through worked examples, and providing access to the sources analysed and accompanying code. The second part of the book is centred around case studies, each applying computational analysis to some aspect of environmental narrative. Themes include the use of language to describe narratives about glaciers, urban gentrification, diversity and writing about nature and ways in which locations are conceptualised and described in nature writing. We close by reviewing the approaches taken, and presenting an interdisciplinary research agenda for future work. The book is designed to be of interest to newcomers to the field and experienced researchers, and set out in a way that it can be used as an accompanying text for graduate level courses in, for example, geography, environmental history or the digital humanities

Walking Along, Wandering Off and Going Astray A Critical Normativity Approach to Walking as a Situated Architectural Experience

There is a lack of attention toward the diversity in experiences of architecture that are expressed through walking. Through the application of autoethnography and critical perspectives of queer and feminist theory, this dissertation develops a method for investigating experiences of architecture in regard to the activity of walking. In addition, this thesis addresses the influence of form, materiality, and social aspects on walk conditions, thus providing architectural perspectives on design and planning that aim to address a heterogeneity among people who walk or are involved in walk matters in their everyday life. The result is an investigatory framework—critical normativity—that consists of three components: observations through a walk diary, the walk technique going astray, and the theoretical application of a critical terminology. These components work to address and situate experiences of spatiality and materiality and their impact on our walk experiences. The walk diary is a data collecting technique that stresses subjectivity of experiences, going astray is an approach that should encourage associations and openness in attitude in the investigatory phase, and the critical terminology is a theoretical framework addressing normativity and thereby positioning the interpretations of the empirical material. The applied main concepts of the critical terminology are: dis-/orientation, background/foreground, performativity, differences, situated knowledges and partial perspective, all of which are derived from queer and feminist theory. The dissertation shows that the researchers, eventually also designers and planners, will benefit from actively engaging themselves in the world of walking by reflecting and incorporating their own walk experiences into their methods and work, in order to develop empathy with the research topic, as well as critically situating their own knowledge perspectives. This way—i.e. by applying a critical normativity—the formation of walk related identities will inevitably activate: questions of e.g. desires; power to act; identity formation; subjectivity and temporality in regard to the experiences of space and materiality. In the application of the investigatory framework—critical normativity—the impact and dynamics of time, in regard to variation in action possibilities, are also addressed. This points to the fact that, in order to include a range of walk needs and behaviors, perception of difference—in particular difference that has not been pre-defined—in itself should be addressed, along with further development of performativity perspectives and identity formation as important constituents of walk conditions

A Case Study of Stakeholders’ Motivation to Invest in Classical Christian Education

The purpose of this qualitative case study is to describe the motivation of parents, teachers, and school board members to invest their efforts in classical Christian education in a modern American K-12 school. The theory guiding this study is expectancy-value theory as it relates to the evaluative aspects of stakeholders’ beliefs about classical Christian education and their motives to become involved in it. Classical Christian education includes the concepts of the trivium, explicit instruction, the Socratic method, and basic skills mastery, as well as carrying on the traditions of the West; all steeped in a Christian worldview. Data came in the form of interviews, documents, and focus groups from parents, teachers, and school board members who are involved with a classical Christian education. An analysis of the data revealed that stakeholders are motivated to invest their efforts in a classical Christian school by a variety of factors including, a disapproval of the mainstream educational philosophy and a strong desire to experience the core elements of the classical Christian philosophy. This study found that no matter what participants believed about classical Christian education, they placed a great deal of value on their expectations about the philosophy, and those expectations were being met, with few exceptions

Data-Driven Operational and Safety Analysis of Emerging Shared Electric Scooter Systems

The rapid rise of shared electric scooter (E-Scooter) systems offers many urban areas a new micro-mobility solution. The portable and flexible characteristics have made E-Scooters a competitive mode for short-distance trips. Compared to other modes such as bikes, E-Scooters allow riders to freely ride on different facilities such as streets, sidewalks, and bike lanes. However, sharing lanes with vehicles and other users tends to cause safety issues for riding E-Scooters. Conventional methods are often not applicable for analyzing such safety issues because well-archived historical crash records are not commonly available for emerging E-Scooters. Perceiving the growth of such a micro-mobility mode, this study aimed to investigate E-Scooter operations and safety by collecting, processing, and mining various unconventional data sources. First, origin-destination (OD) data were collected for E-Scooters to analyze how E-Scooters have been used in urban areas. The key factors that drive users to choose E-Scooters over other options (i.e., shared bikes and taxis) were identified. Concerning user safety tied to the growing usage, we further assessed E-Scooter user guidelines in urban areas in the U.S. Scoring models have been developed for evaluating the adopted guidelines. It was found that the areas with E-Scooter systems have notable disparities in terms of the safety factors considered in the guidelines. Built upon the usage and policy analyses, this study also creatively collected news reports as an alternative data source for E-Scooter safety analysis. Three-year news reports were collected for E-Scooter-involved crashes in the U.S. The identified reports are typical crash events with great media impact. Many detailed variables such as location, time, riders’ information, and crash type were mined. This offers a lens to highlight the macro-level crash issues confronted with E-Scooters. Besides the macro-level safety analysis, we also conducted micro-level analysis of E-Scooter riding risk. An all-in-one mobile sensing system has been developed using the Raspberry Pi platform with multiple sensors including GPS, LiDAR, and motion trackers. Naturalistic riding data such as vibration, speed, and location were collected simultaneously when riding E-Scooters. Such mobile sensing technologies have been shown as an innovative way to help gather valuable data for quantifying riding risk. A demonstration on expanding the mobile sensing technologies was conducted to analyze the impact of wheel size and riding infrastructure on E-Scooter riding experience. The quantitative analysis framework proposed in this study can be further extended for evaluating the quality of road infrastructure, which will be helpful for understanding the readiness of infrastructure for supporting the safe use of micro-mobility systems. To sum up, this study contributes to the literature in several distinct ways. First, it has developed mode choice models for revealing the use of E-Scooters among other existing competitive modes for connecting urban metro systems. Second, it has systematically assessed existing E-Scooter user guidelines in the U.S. Moreover, it demonstrated the use of surrogate data sources (e.g., news reports) to assist safety studies in cases where there is no available crash data. Last but not least, it developed the mobile sensing system and evaluation framework for enabling naturalistic riding data collection and risk assessment, which helps evaluate riding behavior and infrastructure performance for supporting micro-mobility systems