Sökning: "Spatial modeling"

Visar resultat 1 - 5 av 114 uppsatser innehållade orden Spatial modeling.

1. 1. The Sound of Skepticism Analyzing Climate Change Denial in Swedish Podcasts and YouTube Channels

   Kandidat-uppsats, Göteborgs universitet / / Institutionen för sociologi och arbetsvetenskap

   Författare :Victoria Vallström; [2024-02-14]
   Nyckelord :denialism; climate skepticism; social movements; countermovements; digital media; digital data; computational grounded theory; topic modeling; computational text analysis;

   Sammanfattning : This study explores Sweden's climate change denial by analyzing the spoken-word discourse of its countermovement, focusing on digital media content from Swedish parliament member Elsa Widding with an aim to provide empirical insights into the discourse of Sweden's Climate Change Countermovement (CCCM). Questions guiding this study are: What are the most prevalent topics and themes related to climate change denial and skepticism? How do they align with established categories of climate change denial, shaping the overall narrative? What mobilizing ideas and meanings are present, how are they shaped, and how do they contribute to the movement's goals? The material consists of Elsa Widding's complete audio-based "movement texts'' from 2019-2023, including YouTube content, podcasts, and appearances on Riks, totaling over 2000 minutes of audio transcribed into text via AI technology. LÄS MER

3. 2. Replacing Objects in Point Cloud stream with Real-time Meshes using Semantic Segmentation

   Master-uppsats, Blekinge Tekniska Högskola

   Författare :Abhinav Chitta; [2024]
   Nyckelord :;

   Sammanfattning : Background: The evolving landscape of 3D data processing, particularly pointcloud manipulation, is pivotal in numerous applications ranging from architecturaldesign to spatial analysis. Traditional methods, primarily mesh generation from point clouds, face challenges in adapting to complex real-world scenarios. LÄS MER

4. 3. A spatially explicit model of segregation dynamics : Comparing the Schelling and the Sakoda model

   Master-uppsats, Linköpings universitet/Institutet för analytisk sociologi, IAS

   Författare :Philip Öberg; [2023]
   Nyckelord :residential segregation; agent-based modeling ABM ; social simulation; multi-dimensional measurement; multi-scale measurement;

   Sammanfattning : The scientific consensus has for long been that residential segregation is best conceived of as a multidimensional phenomenon that can exist on several geographical scales (Massey & Denton, 1988; Lee et al., 2008; Reardon & O’Sullivan, 2004; Reardon et al., 2008). LÄS MER

5. 4. Space-Division-Multiplexing Platform for a Delayed-Choice Experiment

   Master-uppsats, Linköpings universitet/Informationskodning

   Författare :Hilma Karlsson; [2023]
   Nyckelord :Wheeler s delayed choice; wave-particle delayed choice; Sagnac interferometer; Mach-Zehnder interferometer; complementarity relation; spatial modes; space-division-multiplexing; LP-modes; few-mode fibers; quantum communication; quantum optics;

   Sammanfattning : This master’s thesis explores a space-division-multiplexing (SDM) platform fora delayed-choice experiment. SDM is a multiplexing technique for optical datatransmission that employs spatial modes in a multi- or few-mode fiber to increasethe transmission capacity. The spatial modes can thus be used as separate channels. LÄS MER

7. 5. Implementing SAE Techniques to Predict Global Spectacles Needs

   Master-uppsats, Högskolan Dalarna/Institutionen för information och teknik

   Författare :Yuxue Zhang; [2023]
   Nyckelord :small area estimation; area-level model; empirical best linear unbiased prediction EBLUP ; generalized linear mixed models; Conditional Autoregressive; spatial correlation; spectacle needs; assistive products; auxiliary data; hglm; relative standard error; simulation;

   Sammanfattning : This study delves into the application of Small Area Estimation (SAE) techniques to enhance the accuracy of predicting global needs for assistive spectacles. By leveraging the power of SAE, the research undertakes a comprehensive exploration, employing arange of predictive models including Linear Regression (LR), Empirical Best Linear Unbiased Prediction (EBLUP), hglm (from R package) with Conditional Autoregressive (CAR), and Generalized Linear Mixed Models (GLMM). LÄS MER