Thesis Timeline

>>> arcpy.RasterToPolygon_conversion(in_raster="D:/curso_de_backend_js_python_R_arcgis_qgis_-01-20-26^^/servers/DATOS/descargas_shp/descarga_img/clip-mapa_base-terreno22_dem^utm.tif", out_polygon_features="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/RasterT_clipma2.shp", simplify="SIMPLIFY", raster_field="Value", create_multipart_features="SINGLE_OUTER_PART", max_vertices_per_feature="") <Result 'D:\\curso_de_backend_r_y_python\\python_rstudio_1242_pubs\\shapes_export-arcpy\\RasterT_clipma2.shp'> >>> arcpy.Clip_analysis(in_features="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/rasterxpoligono_RasterT_tif2.shp", clip_features="D:/curso_de_backend_js_python_R_arcgis_qgis_-01-20-26^^/servers/DATOS/descargas_shp/descarga_img4/ant_shp.shp", out_feature_class="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/rasterxpoligono_RastercolT_tif2_Clip.shp", cluster_tolerance="") <Result 'D:\\curso_de_backend_r_y_python\\python_rstudio_1242_pubs\\shapes_export-arcpy\\rasterxpoligono_RastercolT_tif2_Clip.shp'> >>> raxpolcolT_clip2 <- st_read("rasterxpoligono_RastercolT_tif2_Clip.shp") plot(st_geometry(raxpolcolT_clip2), axes=TRUE) raxpolcolT_clip2 <- st_transform(raxpolcolT_clip2, crs = 4324) ggplot() + geom_sf(data = raxpolcolT_clip2 ) mapview(raxpolcolT_clip2)

This survey examines what factors may influence people’s willingness to use AI companions (AICs). It focuses on four areas: acceptance of emerging technology, health beliefs, prior experience with AI and AI companions, and mental health. Your responses will help us better understand the main factors that may shape interest in AI companions.

>>> arcpy.RasterToPolygon_conversion(in_raster="D:/curso_de_backend_js_python_R_arcgis_qgis_-01-20-26^^/servers/DATOS/descargas_shp/descarga_img/clip-mapa_base-terreno22_dem^utm.tif", out_polygon_features="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/RasterT_clipma2.shp", simplify="SIMPLIFY", raster_field="Value", create_multipart_features="SINGLE_OUTER_PART", max_vertices_per_feature="") <Result 'D:\\curso_de_backend_r_y_python\\python_rstudio_1242_pubs\\shapes_export-arcpy\\RasterT_clipma2.shp'> >>> arcpy.Clip_analysis(in_features="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/rasterxpoligono_RasterT_tif2.shp", clip_features="D:/curso_de_backend_js_python_R_arcgis_qgis_-01-20-26^^/servers/DATOS/descargas_shp/descarga_img4/ant_shp.shp", out_feature_class="D:/curso_de_backend_r_y_python/python_rstudio_1242_pubs/shapes_export-arcpy/rasterxpoligono_RastercolT_tif2_Clip.shp", cluster_tolerance="") <Result 'D:\\curso_de_backend_r_y_python\\python_rstudio_1242_pubs\\shapes_export-arcpy\\rasterxpoligono_RastercolT_tif2_Clip.shp'> >>>raxpolcolT_tif2 <- st_read("rasterxpoligono_RasterT_tif2.shp") plot(st_geometry(raxpolcolT_tif2), axes=TRUE) raxpolcolT_tif2 <- st_transform(raxpolcolT_tif2, crs = 4324) ggplot() + geom_sf(data = raxpolcolT_tif2 ) mapview(raxpolcolT_tif2)