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    61356 research outputs found

    Performance comparison of deep and transfer learning models for smart soil texture classification

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    Classification of soil is crucial for implementing precision agriculture practices to achieve better crop planning and resource utilization. The method of this study involved utilizing a deep learning-based transfer learning model for soil texture classification using image data. For background removal to precisely extract soil features, we processed a dataset of 720 soil images from six different soil types using YOLOv5. Nine state-of-the-art transfer learning models, namely, DenseNet121, Xception, MobileNetV2, and VGG19, were evaluated in terms of classification accuracy, computational efficiency, and memory usage. Experimental results showed that the test accuracy for DenseNet121 was the best with 97.22 %, Xception was 93.52 %, and MobileNetV2 was 72.22 %. The computational efficiency analysis showed that MobileNetV2 converged the fastest (769.53 sec) and used the smallest memory (0.74 GB). On the contrary, DenseNet121 and Xception, though consuming more memory, showed a better reliability of classification. Future research may focus on improving lightweight architecture or optimizing facility extraction techniques to enhance classification accuracy and reduce computational costs. These results indicate the promise of deep learning models for soil texture classification, which can be applied in accurate agriculture and sustainable land management

    Determining the global citizenship tendencies of international university students for a sustainable world

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    This study examines the relationship between the global citizenship awareness of international students studying at universities in Turkey and their orientation toward sustainability. While global citizenship and sustainability have often been explored separately in the literature, the way international students connect these two concepts has not been sufficiently addressed. Therefore, this study aims to fill this gap. A convergent parallel mixed-methods design was employed. Quantitative data were collected from 634 international students (323 women, 311 men) enrolled at four Turkish universities using the Global Citizenship Scale. Qualitative data were gathered through face-to-face interviews with 37 volunteer students. Quantitative findings indicated a moderate level of global citizenship awareness among students. In contrast, qualitative results revealed a more nuanced and higher level of awareness, with students demonstrating the ability to interpret global citizenship from multiple perspectives. Both sets of findings suggest that students develop awareness of environmental and social issues, that active participation enhances their global citizenship awareness, and that they adopt sustainable living practices (e.g., sustainable consumption, resource management). Furthermore, many participants reported applying global citizenship principles in their daily lives. These findings suggest that international students can play a significant role in promoting sustainability and global awareness. The study highlights the importance of integrating global citizenship and sustainability education into higher education curricula to strengthen students’ roles as agents of sustainable change

    İç Anadolu Bölgesinde Akıllı Kent Uygulamaları: Büyükşehir Belediyeleri Arası Karşılaştırmalı Bir Analiz

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    Bu çalışma, İç AnadoluBölgesi'nde yer alan dört büyükşehir belediyesinin (Ankara, Konya, Eskişehir veKayseri) akıllı kent uygulamalarını karşılaştırmalı olarak analiz etmektedir.Akıllı kentler, bilgi ve iletişim teknolojileri kullanılarak şehirlerin dahayaşanabilir, sürdürülebilir ve verimli hale getirilmesini amaçlayan kentselyönetim sistemleridir. Çalışmada, akıllı ulaşım, akıllı çevre ve enerjiyönetimi, dijital belediyecilik, afet yönetimi ve akıllı altyapı gibi başlıca unsurlarele alınmıştır. Ankara Büyükşehir Belediyesi, akıllı ulaşım sistemleri vedijital yönetişim alanlarında öncü projeler geliştirirken; Konya BüyükşehirBelediyesi, sürdürülebilir enerji ve yerli-milli teknoloji çözümleri ile akıllışehir stratejisini bütüncül bir yaklaşımla uygulamaktadır. Eskişehir BüyükşehirBelediyesi, çevre ve sürdürülebilirlik temelli akıllı kent uygulamalarına odaklanarakenerji tasarrufu, atık yönetimi ve yeşil ulaşım projelerine ağırlıkvermektedir. Kayseri Büyükşehir Belediyesi ise dijital belediyecilik alanındageniş çaplı uygulamalar hayata geçirerek, veri yönetimi ve akıllı şehirteknolojilerini kentsel yönetime entegre etmiştir. Çalışmanın sonuçları,belediyelerin akıllı kent projelerini kendi demografik, ekonomik ve coğrafiözelliklerine uygun şekilde şekillendirdiğini göstermektedir. Ancak,belediyeler arası iş birliğinin artırılması, ortak veri paylaşımı sistemleriningeliştirilmesi ve sürdürülebilir finansman modelleri ile bu projelerin dahaetkin hale getirilebileceği vurgulanmaktadır. Sonuç olarak, İç Anadolu’dakibüyükşehir belediyeleri, akıllı kent uygulamalarını farklı ölçeklerde hayatageçirmiş olup, bu uygulamaların entegrasyonu ve sürdürülebilirliği gelecektekent yönetiminde kritik bir rol oynayacaktır.Anahtar Kelimeler: AkıllıKent, İç Anadolu Bölgesi, Büyükşehir Belediyeleri</p

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