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華藝線上圖書館全期下載(Full Issue Download) : 26(1).pdf
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Pages : 1-12    結合土地利用迴歸與極限梯度提升演算法發展高雄都會區二氧化氮之推估模型
論文名稱 結合土地利用迴歸與極限梯度提升演算法發展高雄都會區二氧化氮之推估模型
Title Development of an Integrated Model for NO2 Variation Prediction in Kaohsiung Metropolis Using Land-Use Regression and XGBoost
作者 翁佩詒、吳治達、蘇慧貞
Author Pei-Yi Wong, Chih-Da Wu, Huey-Jen Su
中文摘要 暴露二氧化氮 (NO2) 會對人體造成不良健康效應,然而過去空氣污染暴露評估模式仍有高估或低估的問題,因此使用高時空解析度之預測模型探討大範圍暴露濃度有其必要性。本研究以高雄都會區為研究區,使用土地利用迴歸模型、並結合極限梯度提升 (Extreme Gradient Boosting, XGBoost) 演算法,發展高時空解析度之NO2濃度推估模型。結果顯示,土地利用迴歸結合XGBoost模型R2為0.82,均方根誤差為4.53 ppb,具有高度預測與解釋力,十折交叉驗證R2為0.82,顯示模型沒有過度擬合的問題,最後利用此模型推估高雄都會區NO2之時空變異情形,結果發現高值熱點出現在南高雄之工商業發達以及人口密集處。
Abstract Exposing to Nitrogen Dioxide (NO2) may cause adverse health effects. Previous air pollution estimating models still face overfitting or underfitting problems. Thus, using estimation model with high spatial and temporal resolution to assess NO2 exposure is important. This study utilized Land-Use Regression (LUR) coupled with Extreme Gradient Boosting (XGBoost) algorithm to feature NO2 concentration distribution in Kaohsiung metropolis. The results showed that R2 value for LUR integrated XGBoost model was 0.82, RMSE was 4.53 ppb, which had highly explanatory ability. Besides, 10-fold cross validation R2 for the proposed model was 0.82, which showed that the model did not encounter overfitting issue. Finally, this study used the model to depict estimation maps for NO2 concentration variation in Kaohsiung. The results showed that higher polluted regions were clustered in south Kaohsiung where industries were well developed and population was densely distributed.
關鍵字 空氣污染、二氧化氮、土地利用迴歸、極限梯度提升演算法
Keywords Air Pollution, Nitrogen Dioxide (NO2), Land-Use Regression (LUR), Extreme Gradient Boosting (XGBoost)
Pages : 13-29    以虛擬原鄉輔助傳統生態知識教學之研究
論文名稱 以虛擬原鄉輔助傳統生態知識教學之研究
Title Virtual Indigenous Tribe for Teaching Traditional Ecological Knowledge
作者 周孜恆、王聖鐸
Author Tzu-Heng Chou, Sendo Wang
中文摘要 本研究提出虛擬原鄉 (Virtual Indigenous Tribe),透過沉浸式虛擬實境技術,重現原鄉環境,並融入傳統生態知識,讓都市原住民族學生以更具臨場感的方式認識部落的環境與知識。本研究以臺東成功重安部落作為虛擬原鄉建置對象,將傳統生態知識融入利用無人飛行載具 (Unmanned Aerial Vehicle, UAV)所拍攝之像片和360°全景相機所拍攝的全景像片和全景影片,以Unity軟體開發沉浸式虛擬原鄉APP。本研究與樹林高中原住民族專班合作進行虛擬原鄉教學實測,以認知試題和情意量表前後測問卷作為評量工具。研究結果顯示,虛擬原鄉教學相較於一般教學更能明顯提升學生對於傳統生態知識的認知程度。
Abstract The indigenous peoples have been living in Taiwan for thousands of years. Comparing to the western-style science education, they have completely different pedagogy to establish and to pass their own environmental knowledge, living styles, and cultures. However, the young generation of the indigenous people is losing their traditional point of view to their environment under current western-style science education system. Especially for the indigenous peoples who moved to cities for living, the opportunities for their young generation to learn how to interact with natural environmental resources are significantly decreased. Based on the above, we proposed a concept called “Virtual Indigenous Tribe” in this study. We integrate traditional ecological knowledge into Immersive Virtual Reality to let urban indigenous youths learn the knowledge in a more intuitive way. We collected traditional ecological knowledge through the interviews with elders, integrating it into panoramic videos and images taken by 360° panoramic cameras and the Unmanned Aerial Vehicle (UAV) to build Virtual Indigenous Tribe. Finally, we use Unity to develop immersive virtual tribe APP. We cooperate with urban indigenous class of Shulin Senior High School to evaluate the effectiveness of Virtual Indigenous Tribe teaching. The results show that Virtual Indigenous Tribe teaching can significantly improve more students' cognition of traditional ecological knowledge than general teaching. In this study, we hope that “Virtual Indigenous Tribe” can be used as an auxiliary teaching tool to enable urban indigenous students to break through the limitations of time and space to learn traditional ecological knowledge in a more authentic way, and increase students’ curiosity about their own tribal history, culture and knowledge.
關鍵字 虛擬實境、傳統生態知識、都市原住民、數位學習、全景像片
Keywords Virtual Reality, Traditional Ecological Knowledge, Urban Indigenous People, Digital Learning, Panoramic Image
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