Utilizing Machine Learning-based Classification Models for Tracking Air Pollution Sources: A Case Study in Korea by Yelim Choi, Bogyeong Kang, Daekeun Kim

“…The findings suggest the potential of machine learning techniques in addressing air pollution challenges, and the classifier model implemented in this study shows great promise for effective emission source identification.…”
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Secured DICOM medical image transition with optimized chaos method for encryption and customized deep learning model for watermarking by R. Abirami, C. Malathy

“…The fields of telemedicine and aided medical diagnostics are benefiting greatly from medical imaging. For healthcare professionals to view patient medical images, a secure online transmitting technique is essential. …”
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Unveiling farmers’ perceptions: a citizen science and machine learning approach to exploring drivers in the adequacy and fairness of water systems by Vasilios Plakandaras, Fahad Khan Khadim, Vassiliki Kazana, Emmanouil Anagnostou, Amvrossios C Bagtzoglou

“…Harnessing the analytical power of machine learning models in extracting patterns from data, the informational content of social surveys coupled with hydrological data for the survey region from a calibrated MODFLOW-NWT groundwater (GW) model, we draw inferences on the importance of socioeconomic rather than hydrological variables as drivers in agricultural decisions about crop selection and planting period, underscoring those factors as potential criteria in drawing successful agricultural policies for crop yield optimization in the Great South area. …”
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Prevention and management of degenerative lumbar spine disorders through artificial intelligence-based decision support systems: a systematic review by Paolo Giaccone, Federico D’Antoni, Fabrizio Russo, Luca Ambrosio, Giuseppe Francesco Papalia, Onorato d’Angelis, Gianluca Vadalà, Albert Comelli, Luca Vollero, Mario Merone, Rocco Papalia, Vincenzo Denaro

“…Several different machine learning and deep learning algorithms were employed, and their predictive ability on clinical, demographic, psychosocial, and imaging data was assessed. …”
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A hybrid approach for intrusion detection in vehicular networks using feature selection and dimensionality reduction with optimized deep learning. by Fayaz Hassan, Zafi Sherhan Syed, Aftab Ahmed Memon, Saad Said Alqahtany, Nadeem Ahmed, Mana Saleh Al Reshan, Yousef Asiri, Asadullah Shaikh

“…Autonomous transportation systems have the potential to greatly impact the way we travel. A vital aspect of these systems is their connectivity, facilitated by intelligent transport applications. …”
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Evolving prognostic paradigms in lung adenocarcinoma with brain metastases: a web-based predictive model enhanced by machine learning by Min Liang, Zhiwen Zhang, Langming Wu, Mafeng Chen, Shifan Tan, Jian Huang

“…A well-crafted prognostic model could greatly assist clinicians in patient counseling and in devising tailored therapeutic strategies. …”
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FedBFGCN: A Graph Federated Learning Framework Based on Balanced Channel Attention and Cross-Layer Feature Fusion Convolution by Hefei Wang, Ruichun Gu, Jingyu Wang, Xiaolin Zhang, Hui Wei

“…Graph Federated Learning (GFL) is an emerging distributed training paradigm that combines federated learning with graph data. …”
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Genome data based deep learning identified new genes predicting pharmacological treatment response of attention deficit hyperactivity disorder by Yilu Zhao, Zhao Fu, Eric J. Barnett, Ning Wang, Kangfuxi Zhang, Xuping Gao, Xiangyu Zheng, Junbin Tian, Hui Zhang, XueTong Ding, Shaoxian Li, Shuyu Li, Qingjiu Cao, Suhua Chang, Yufeng Wang, Stephen V. Faraone, Li Yang

“…Abstract Although the efficacy of pharmacy in the treatment of attention deficit/hyperactivity disorder (ADHD) has been well established, the lack of predictors of treatment response poses great challenges for personalized treatment. The current study employed a comprehensive approach, combining genome-wide association analyses (GWAS) and deep learning (DL) methods, to elucidate the genetic underpinnings of pharmacological treatment response in ADHD. …”
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Lessons learned in migrating from one commercial genetics clinical decision-making tool to another: Assessment of data integrity and utilization by Calvin Le, Kevin Tatunay, Wayne Liu, Haibo Lu, Nicole-Ann Rodis, Thomas Nam, Mercy Y. Laurino, Marianne E. Dubard-Gault

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Exploring benefits of a collaborative Scottish university-organization alternative credentials approach to re-skilling by Christopher J. M. Smith, Constantinos Choromides, Alicia Clyde, Fiona Stewart-Knight

“…Credit-rating of learning has great potential to support national priorities, but this service needs to be better understood by companies and employers for it to reach its potential.…”
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Analysis of graphene coatings on various metallic/oxide crystal/composite material substrates using machine learning for enhanced solar thermal energy conversion by Khaled Aliqab, Dhruvik Agravat, Shobhit K. Patel, Ammar Armghan, Naim Ben Ali, Meshari Alsharari

“…Thus, the data collection time is greatly reduced using ML compared to running simulations which have a step size of about 8 h per change. …”
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The Role of Artificial Intelligence (AI) in Transforming Small and Medium Enterprises (SMEs): by Mugisha, Justin, Francis Adyanga, Akena, Ocan, Johnson

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Transforming Alzheimer’s Disease Diagnosis: Implementing Vision Transformer (ViT) for MRI Images Classification by Dian Kurniasari, Muhammad Dwi Pratama, Akmal Junaidi, Ahmad Faisol

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ANALISIS KEMAMPUAN PENGUASAAN KONSEP IPA TERPADU DAN KEPEDULIAN LINGKUNGAN MAHASISWA MELALUI PENGGUNAAN BAHAN AJAR PENGOLAHAN TEBU SEBAGAI ENERGI TERBARUKAN by Lailatul Nuraini, Supeno Supeno, Sudarti Sudarti, Sri Astutik, Shinta Nuriyah Mahbubiyah Royani

“…Kata Kunci: IPA Terpadu, Penguasaan Konsep, Kesadaran Lingkungan, Tanaman Tebu ABSTRACT   Jember is a regency which has a great potential of sugar cane. Meanwhile, the potential of the processing of sugar cane was not yet to be developed as a learning resource and hence was not able to grow the environment awareness which was caused by the waste of sugar cane factory. …”
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Automatic detection and counting of wheat spike based on DMseg-Count by Hecang Zang, Yilong Peng, Meng Zhou, Guoqiang Li, Guoqing Zheng, Hualei Shen

“…Abstract The automatic detection and counting of wheat spike images are of great significance for yield prediction and variety evaluation. …”
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KNOWLEDGE, ATTITUDES AND PRACTICES TOWARDS OPEN EDUCATIONAL RESOURCES IN HIGHER EDUCATION INSTITUTIONS IN THE PHILIPPINES by Liezel G. Mohillo, Angie R. Jalandoon, Dave E. Marcial

“…With the update in education and the shift in learning modality a great need for educational resources - free and open to the public increases, especially in the outrage of the pandemic. …”
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Clinical validation of an artificial intelligence algorithm for classifying tuberculosis and pulmonary findings in chest radiographs by Thiago Fellipe Ortiz de Camargo, Thiago Fellipe Ortiz de Camargo, Guilherme Alberto Sousa Ribeiro, Guilherme Alberto Sousa Ribeiro, Maria Carolina Bueno da Silva, Luan Oliveira da Silva, Pedro Paulo Teixeira e Silva Torres, Denise do Socorro Rodrigues da Silva, Mayler Olombrada Nunes de Santos, William Salibe Filho, Marcela Emer Egypto Rosa, Magdala de Araujo Novaes, Thiago Augusto Massarutto, Osvaldo Landi Junior, Elaine Yanata, Marcio Rodrigues da Cunha Reis, Gilberto Szarf, Pedro Vieira Santana Netto, Joselisa Peres Queiroz de Paiva

“…Artificial Intelligence (AI) algorithms could be of great help, but using real-world data is crucial to ensure their effectiveness in diverse healthcare settings. …”
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A U-Net-based denoising method for semi-airborne transient electromagnetic data and its application by Dong LIU, Hao FENG, Yongxin WANG, Xiaosheng ZHOU, Yuhong YAO, Huaifeng SUN

“…The encoder learns and extracts noise features from data, while the decoder reconstructs the noise features and restores denoised data. …”
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