MULTI-MODEL STACK ENSEMBLE DEEP LEARNING APPROACH FOR MULTI-DISEASE PREDICTION IN HEALTHCARE APPLICATION by Bhaskar Adepu, T. Archana

“…Datasets for lung cancer, cervical cancer, chronic renal disease, Parkinson's illness, and HCC survival are sourced from the trustworthy UCI repository for experimentation. …”
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AI-Powered Mobile App for Nuclear Cataract Detection by Alicja Anna Ignatowicz, Tomasz Marciniak, Elżbieta Marciniak

“…The proposed solution utilizes a multi-stage classification approach to analyze ocular images acquired with a slit lamp, sourced from the Nuclear Cataract Database for Biomedical and Machine Learning Applications. …”
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User Preferences of Airbnb Accommodation Spatially in The Special Region of Yogyakarta, Indonesia by Azis Musthofa, Arief Wicaksono, Raden Rijanta

“…Airbnb's accommodation concept is highly efficient in utilizing unused assets, aligning with SDG Goal 11. …”
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THE IMPACT OF CORPORATE SOCIAL RESPONSIBILITY ON BANK PERFORMANCE IN NIGERIA by Ibrahim Yinka Agbeyinka

“…Larger firms generally enjoy higher returns on equity and are more efficient in utilizing their assets to generate returns. …”
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Evaluating pedestrian crossing safety: Implementing and evaluating a convolutional neural network model trained on paired aerial and subjective perspective images by Dylan Russon, Antoine Guennec, Juan Naredo-Turrado, Binbin Xu, Cédric Boussuge, Valérie Battaglia, Benoit Hiron, Emmanuel Lagarde

“…This study proposes the deployment of advanced deep learning neural networks to automate the assessment of pedestrian crossings and roundabouts, leveraging aerial and street-level imagery sourced from Google Maps and Google Street View. Utilizing ConvNextV2, ResNet50, and ResNext50 models, we conducted a comprehensive analysis of pedestrian crossings across various urban and rural settings in France, focusing on nine identified risk factors.Our methodology incorporates Mask R-CNN for precise segmentation and detection of zebra crossings and roundabouts, overcoming traditional data annotation challenges and extending coverage to underrepresented areas. …”
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Blockchain-Assisted Generation Rescheduling in Imperfect Market Environments by Salman Tariq, Mohamed Shaaban, Hazlie Mokhlis, Nurulafiqah N. Mansor, Hasmaini Mohamad

“…The proposed BC-based structure allows generators to participate in the short-term scheduling mechanism (such as day-ahead) in a trust-free environment without sharing their vital data yet achieving efficient, market-grade solutions. The feasibility of this new proposition is demonstrated through three different application scenarios, utilizing real-world load and renewable generation profiles sourced from the respective Grid System Operators databases. …”
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Recent HPLC-UV Approaches for Cannabinoid Analysis: From Extraction to Method Validation and Quantification Compliance by Eduarda M. P. Silva, Antonella Vitiello, Agnese Miro, Carlos J. A. Ribeiro

“…Notably, ultrasound extraction has emerged as the most widely utilized technique across various matrices, with Deep Eutectic Solvents (DESs) offering a promising, efficient, and environmentally friendly extraction alternative. …”
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Use ATCCfinder to identify commercially available American Type Culture Collection strains based on sequence queries by Samuel I. Koehler, Earl A. Middlebrook, Blake T. Hovde, Erik R. Hanschen

“…Microbiology research was conducted for decades before widespread availability of sequencing resources and large culture collection sequence repositories, making it challenging to efficiently identify and validate strains used in historical studies. …”
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Predicting the mechanical performance of industrial waste incorporated sustainable concrete using hybrid machine learning modeling and parametric analyses by Md. Alhaz Uddin, Md. Habibur Rahman Sobuz, Md. Kawsarul Islam Kabbo, Md. Kanan Chowdhury Tilak, Ratan Lal, Md. Selim Reza, Fahad Alsharari, Mohamed AbdelMongy, Masuk Abdullah

“…A total of 441 data entries were sourced from various publications. Multiple machine learning techniques, such as light gradient boosting (LGB), extreme gradient boosting (XGB), and decision trees (DT), along with hybrid approaches like XGB-LGB and XGB-DT, were utilized to study how these variables influence compressive strength. …”
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UrduSER: A comprehensive dataset for speech emotion recognition in Urdu languageMendeley Data by Muhammad Zaheer Akhtar, Rashid Jahangir, QuratUl Ain, Muhammad Asif Nauman, Mueen Uddin, Syed Sajid Ullah

“…This comprehensive metadata index enables researchers and developers to efficiently access, organize, and utilize the UrduSER dataset. …”
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Protecting the Autonomy of Patients with Severe Mental Illness Through Psychiatric Advance Directive Peer-Facilitation by Nicholas Karasik

“…PERSONAL PERSPECTIVE As someone who has voluntarily been admitted to a psychiatric health facility twice to treat manic episodes stemming from Bipolar I Disorder, I recognize the autonomy-persevering utility of psychiatric advance directives on a theoretical and experiential level. …”
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Deep Learning Based 3D Visualization Health Condition Monitoring Method for Anchor Digging Machines by YANG Xueqi, GAO Xinqin, ZHENG Haiyang, YANG Jun

“…Experimental validation was conducted using the actual production dataset sourced from the coal mine and the Intelligent Maintenance System (IMS) dataset. …”
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