A Novel approach to ship valuation prediction: An application to the supramax and ultramax secondhand markets. by Elif Tuçe Bal, Ercan Akan, Huseyin Gencer

“…(ii) For the two linear regression models created; Price predictions were made with Linear Regression, Decision Tree, Random Forest and XGBoost ML algorithms. …”
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The impact of artificial intelligence on research efficiency by Mitra Madanchian, Hamed Taherdoost

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THE ROLE OF BIG DATA IN DIGITALIZING INFORMATION by Elena COFAS

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Beyond the cybernetic loop: smart” pain technology in a recursive society by Benjamin Lipp, Stephen Hilgartner

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Towards sustainable agriculture in Iran using a machine learning-driven crop mapping framework by Iman Khosravi

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Analysis of signals from air conditioner compressors with ordinal patterns and machine learning by Keila Barbosa, Alejandro C Frery, George DC Cavalcanti

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A framework for systematically applying humanistic ethics when using AI as a design material by Kyle Dent, Richelle Dumond, Mike Kuniavsky

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A Novel Active RFID and TinyML based system for livestock Localization in Pakistan by Syed Atir Raza Shirazi, Maham Fatima, Abdul Wahab, Sadaf Ali

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Upholding human dignity in AI: Advocating moral reasoning over consensus ethics for value alignment by Octavian-Mihai Machidon

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An Analysis of Intelligent Turkish Text Classification Models for Routing Calls in Call Centers: A Case Study on the Republic of Turkiye Ministry of Trade Call Center by Muammer Özdemir, Yasin Ortakcı

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Revolutionizing Midwifery Education : A Scoping Review of Artificial Intelligence Methods by Harridhil Silmi, Ari Indra Susanti

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A novel hybrid vision UNet architecture for brain tumor segmentation and classification by M. Renugadevi, K. Narasimhan, K. Ramkumar, N. Raju

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Work Place Safety: Machine Learning Techniques for Assessing Workplace Incident Severity by Munayr Hasan Khalleefah Hassan, Wagdi M. S. Khalifa

“…Analyzing a comprehensive dataset of occupational injury records from Occupational Safety and Health Administration (OSHA), this research explores the efficacy of seven distinct ML algorithms AdaBoostClassifier (ABC), K-Nearest Neighbors (KNN), Decision Tree Classifier (DTC), Extreme Learning Machine (ELM), Support Vector Classifier (SVC), Multi-Layer Perceptron (MLP), and Stacked Model (SM). …”
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Dynamic Foraging in Swarm Robotics: A Hybrid Approach with Modular Design and Deep Reinforcement Learning Intelligence by Ali Hammoud, Alaa Iskandar, Béla Kovács

“…This paper proposes a hybrid approach that combines intelligent algorithms and modular design to solve a foraging problem within the context of swarm robotics. …”
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Predictive Analysis of Carbon Emissions in China’s Construction Industry Based on GIOWA Model by Tianyue Hu, Zhiheng Bao, Baiyang Zhang, Xinnan Gao

“…A case study is conducted based on historical data (1997–2021) from the construction industry, and the research findings indicate that: (1) the GIOWA combination forecasting model effectively integrates the algorithmic strengths of SVR and LSTM, achieving an average prediction accuracy of 98.16%, which signifies a remarkable improvement over both individual models; (2) the carbon emissions in China’s construction industry will maintain a downward trend during the period 2022–2030, although the decline rate is expected to decrease gradually; (3) by 2030, a reduction of nearly 35% in carbon emissions is anticipated relative to the historical peak. …”
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Diabetic Retinopathy Detection Using DL-Based Feature Extraction and a Hybrid Attention-Based Stacking Ensemble by Sanjana Rajeshwar, Shreya Thaplyal, Anbarasi M., Siva Shanmugam G.

“…This paper addresses this challenge by utilizing advanced deep learning (DL) algorithms with established image processing techniques to enhance accuracy and efficiency in detection. …”
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An IoT-enabled AI system for real-time crop prediction using soil and weather data in precision agriculture by MD Shaifullah Sharafat, Nilavro Das Kabya, Rahimul Islam Emu, Mehrab Uddin Ahmed, Jakaria Chowdhury Onik, Mohammad Aminul Islam, Riasat Khan

“…The dataset consists of 3,300 samples covering 22 crops and eight soil and environmental features. …”
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Artificial neural networks for predicting first-lactation 305-day milk yield in crossbred cattle by SM Usman, A Kumar, A Sherasiya, IM Youssef, MM Abo Ghanima, J Chandrakar, R Tiwari, NP Singh, QS Sahib, T Dutt, AA Swelum

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An interpretable machine learning model based on computed tomography radiomics for predicting programmed death ligand 1 expression status in gastric cancer by Lihuan Dai, Jinxue Yin, Xin Xin, Chun Yao, Yongfang Tang, Xiaohong Xia, Yuanlin Chen, Shuying Lai, Guoliang Lu, Jie Huang, Purong Zhang, Jiansheng Li, Xiangguang Chen, Xi Zhong

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Landing State Recognition of Carrier-Based Aircraft Based on Adaptive Feature Enhancement and Fusion by WANG Ke, LIU Yiyang, YANG Jie, LU Aiguo, LI Zhe, XU Mingliang

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