1,699 research outputs found

    Undergraduate Catalog of Studies, 2023-2024

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    Undergraduate Catalog of Studies, 2022-2023

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    Advances and Applications of DSmT for Information Fusion. Collected Works, Volume 5

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    This fifth volume on Advances and Applications of DSmT for Information Fusion collects theoretical and applied contributions of researchers working in different fields of applications and in mathematics, and is available in open-access. The collected contributions of this volume have either been published or presented after disseminating the fourth volume in 2015 in international conferences, seminars, workshops and journals, or they are new. The contributions of each part of this volume are chronologically ordered. First Part of this book presents some theoretical advances on DSmT, dealing mainly with modified Proportional Conflict Redistribution Rules (PCR) of combination with degree of intersection, coarsening techniques, interval calculus for PCR thanks to set inversion via interval analysis (SIVIA), rough set classifiers, canonical decomposition of dichotomous belief functions, fast PCR fusion, fast inter-criteria analysis with PCR, and improved PCR5 and PCR6 rules preserving the (quasi-)neutrality of (quasi-)vacuous belief assignment in the fusion of sources of evidence with their Matlab codes. Because more applications of DSmT have emerged in the past years since the apparition of the fourth book of DSmT in 2015, the second part of this volume is about selected applications of DSmT mainly in building change detection, object recognition, quality of data association in tracking, perception in robotics, risk assessment for torrent protection and multi-criteria decision-making, multi-modal image fusion, coarsening techniques, recommender system, levee characterization and assessment, human heading perception, trust assessment, robotics, biometrics, failure detection, GPS systems, inter-criteria analysis, group decision, human activity recognition, storm prediction, data association for autonomous vehicles, identification of maritime vessels, fusion of support vector machines (SVM), Silx-Furtif RUST code library for information fusion including PCR rules, and network for ship classification. Finally, the third part presents interesting contributions related to belief functions in general published or presented along the years since 2015. These contributions are related with decision-making under uncertainty, belief approximations, probability transformations, new distances between belief functions, non-classical multi-criteria decision-making problems with belief functions, generalization of Bayes theorem, image processing, data association, entropy and cross-entropy measures, fuzzy evidence numbers, negator of belief mass, human activity recognition, information fusion for breast cancer therapy, imbalanced data classification, and hybrid techniques mixing deep learning with belief functions as well

    A study of the inter-relationship of identity and urban heritage in Chiang Mai Old City, Thailand

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    The urban heritage identity of historical cities has received growing attention due to the weakening of their urban identity. For this reason, urban identity has been identified as a preliminary study of this research. Forty years ago, many researchers attempted to explain a broader understanding of urban heritage identity, which is relevant to human factors that affect urban, place, and built environment relationships. This involved the three interrelated concepts of identity: distinctiveness; urban heritage; and place attachment. These establish a balance between people and their identification with places. Urban heritage identity is associated a place's physicality and heritage attributes that reflect socio-cultural values. It can be concluded that urban heritage identity becomes significant through concepts of environmental psychology. Distinctiveness theory, as a part of identity theory, has been used in this study to describe the genuine perception of local participants and is a fundamental part of defining place identity. Furthermore, the definition of place attachment has been used to explain the relationship of distinct places on time of residence, frequency of use, emotional, physical, social, and activities. The study also explores Chiang Mai Old City’s built environment, which especially analyses the façade and streetscape characteristics that reflect the city's socio-cultural value. The research concludes with suggestions for preserving the city's urban heritage characteristics. Chiang Mai Old City has unprecedented diversity and cultural dynamics related to its intangible and tangible urban heritage. Moreover, the city is in the critical stage of being nominated as a new World Heritage Site by UNESCO, with the city's distinctiveness and place attachment being significant in supporting further heritage management strategies. The research mainly focuses on how local people interpret and understand the urban heritage identity of Chiang Mai Old City. This has been achieved through surveys of four hundred participants living in the Old City, two-way focus groups with five participants in each group, in-depth interviews with twenty-five participants, and ten architects drawing suggestions for further built environment management strategies. The results are described through seven aspects that explore the distinctiveness and place attachment theories of Chiang Mai Old City. The findings can be described in seven aspects: historical value; cultural activities; a particular character; landmark; identity; community; and everyday life. The results reveal that there are five distinct places in the city: Pra Singha Temple; Chedi Luang Temple; Three Kings monument square; Tha-Pare gate square; and Chiang Mai Old City's Moat. The results can also be used to develop an assessment indicator for defining the distinctiveness of other historic cities through the engagement of local people. The study repeatedly employs distinct places to describe in-place attachment theory. The results reveal positivity, emotion, and the spiritual anchor of place attached to local people in social engagement, explicitly divulging the rootedness of religion, culture, and community activities through the length of time. All five distinct places have an inseparable ability to display tangible heritage value and such a positive emotion to places is crucial in contributing to urban heritage characteristics. Moreover, the time or length of residency is a vital aspect to people’s perception of the city's distinctiveness; however, the value of the physical setting itself can increase the sense of belonging of newcomers.This research used a mixed methods approach in defining place identity process and socio-cultural values in distinctive streetscapes scenes in the city. This study strongly believes that the findings demonstrate that local people can help to develop the management of the city. The results presented suggest that the heritage value of streetscapes is related to historical attributes, natural objects, people, and cultural events in the scenes that explain the meanings ascribed to places associated with social and cultural values. The built environment characteristics and heritage value can be assumed from human experience. The study can be a new perspective for local authorities, urban designers, and heritage teams to determine whether projects will strengthen the existing urban heritage identity. Most importantly, this research has revealed new perspectives on urban heritage identity and practical study methods whilst also contributing to management strategies. In addition, continuing research into urban heritage identity will significantly improve knowledge development, practical support, and collaboration with local people and architects to establish and maintain cherished distinct places and living environments for urban residents

    The Evolution of the Child Character with Learning Differences

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    In this paper, I will analyze the various representations of learning disabilities in selected children’s literature from the early twentieth century to recent literature published in the last decade. In the typical American classroom specific learning disabilities account for about 20% of students. It is the largest classified group to receive services in special education, and also the broadest: “Learning disabilities are disorders that affect the ability to understand or use spoken or written language, do mathematical calculations, coordinate movements or direct attention” (NIH, 2022). I will use the term “learning differences” as it encompasses all children who learn differently from neurotypical students

    Frontiers of Humanity and Beyond: Towards new critical understandings of borders. Working Papers

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    UIDB/04666/2020 UIDP/04666/2020publishersversionpublishe

    Caribbean cultural heritage and the nation:Aruba, Bonaire and Curaçao in a regional context

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    Centuries of intense migrations have deeply impacted expressions of cultural heritage on the ABC islands: Aruba, Bonaire, and Curaçao. This volume queries how cultural heritage on these Dutch Caribbean islands relates to the work of nation building and nation-branding. How does the imagining of a shared political “we” relates to images deliberately produced to market these islands to a world of capital? The contributing authors in this volume address this leading question in their essays that describe and analyze the expressions of the ABC islands. In doing so they compare and contrast nation building and branding on the ABC islands to those taking place in the wider Caribbean. The expressions of cultural heritage discussed range from the importance of sports, music, literature and visual arts to those related to the political economy of tourism, the work of museums, the activism surrounding the question of reparations, and the politics and policies affecting the Caribbean Diasporas in the North Atlantic. This volume adds to the understanding of the dynamics of nation, culture and economy in the Caribbean

    2023 GREAT Day Program

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    SUNY Geneseo’s Seventeenth Annual GREAT Day. Geneseo Recognizing Excellence, Achievement & Talent Day is a college-wide symposium celebrating the creative and scholarly endeavors of our students. http://www.geneseo.edu/great_dayhttps://knightscholar.geneseo.edu/program-2007/1017/thumbnail.jp

    Dynamics Of Flood Flow In Red River Basin

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    In recent decades, flooding has become a major issue in many areas of the Upper Midwest. Many rivers and streams in the region had considerable increases in mean annual peak flows during this period, which was driven by a combination of natural factors including discharge synchrony with the spring thaw, ice jams, glacial lake plain, and a decrease in gradient downstream. The Red River of the North is a prominent river in the United States and Canada\u27s Upper Midwest. It flows from its headwaters in Minnesota and North Dakota to Lake Winnipeg in Manitoba. The river is well-known for its spring floods, which can cause havoc on communities along its banks. There is an increasing need to improve the characterization and identification of precursors in the Red River basin that affect the hydrological conditions that cause spring snowmelt floods and improve predictions to reduce Red River flood damage. This dissertation has developed different research that concerns the dynamics of floods in the Red River basin by integrating hydrological, hydraulic, and machine-learning models. The primary objectives were to improve flood prediction accuracy by deriving the parameters of the Muskingum Routing method using discharge measurements obtained by an Autonomous Surface Vehicle, to predict scour potential of the river through HEC-RAS modeling, and to provide an estimate of the flood progression downstream based on the flow characteristics. The study also compared the effectiveness of Seasonal Autoregressive Integrated Moving Average (SARIMA), Random Forest (RF), and Long Short-Term Memory (LSTM) algorithms for flood prediction. Additionally, the research investigated the surface water area variation and response to wet and dry seasons across the entire Red River basin, which can inform the development of effective flood mitigation strategies. The results of this study contributed to a better understanding of flood control strategies in the Red River Basin and helped to inform policy decisions related to flood mitigation in the region. Ultimately, this research aimed to understand the complex dynamics of the RRB and derive hydrological and hydraulic models that could help to improve flood prediction. The first research developed a linear and nonlinear Muskingum model with lateral inflows for flood routing in the Red River Basin using Salp Swarm Algorithm (SSA). The distributed Muskingum model is introduced to improve the accuracy and efficiency of the calculations. The study focuses on developing a linear and nonlinear Muskingum model for the Grand Forks and Drayton USGS stations deriving the parameters of the Muskingum Routing method using discharge measurements based on spatial variable exponent parameters. The suggested approach minimizes the Sum of Square Errors (SSE) between observed and routed outflows. The results show for an icy river like Red River, the Muskingum method proposed is a convenient way to predict outflow hydrographs caused by snowmelt. The second study improved flood inundation mapping accuracy in flood-prone rivers, such as the Red River of the North, by using simulation tools in HEC-RAS for flood modeling and determining Manning\u27s n coefficient. An Autonomous Surface Vehicle (ASV) was used to collect bathymetry and discharge data, including a flood event with a 16.5-year return period in 2022. The results showed that Manning\u27s n-coefficient of 0.07 and 0.15 for the channel and overbanks, respectively, agreed well with the observed and simulated water level values under steady flow conditions. The study also demonstrated the efficiency of using ASVs for flood mapping and examined the scour potential and any local scour development in the streambed near the bridge piers. The third study of this dissertation used hourly level records from three USGS stations to evaluate water level predictions using three methods: SARIMA, RF, and LSTM. The LSTM method outperformed the other methods, demonstrating high precision for flood water level prediction. The results showed that the LSTM method was a reliable choice for predicting flood water levels up to one week in advance. This study contributes to the development of data-driven forecasting systems that provide cost-effective solutions and improved performance in simulating the complex physical processes of floods using mathematical expressions. This last study focused on the spatiotemporal dynamics of surface water area in the Red River Basin (RRB) by using a high-resolution global surface water dataset to investigate the changes in surface water extent from 1990 to 2019. The results showed that there were four distinct phases of variation in surface water: wetting (1990-2001), dry (2002-2005), recent wetting (2006-2013), and recent drying (2014-2019). The transition from bare land to permanent and seasonal water area was observed during the wetting phase, while the other phases experienced relatively little fluctuation. Overall, this study contributes to a better understanding of the spatiotemporal variation of surface water area in the RRB and provides insights into the impact of recent wetting and drying periods on the lakes and wetlands of the RRB
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