Two-dimensional QSAR-driven virtual screening for potential therapeutics against Trypanosoma cruzi by Naseer Maliyakkal, Sunil Kumar, Ratul Bhowmik, Harish Chandra Vishwakarma, Prabha Yadav, Bijo Mathew

“…Following the calculation of molecular descriptors and feature selection approaches, Support Vector Machine (SVM), Artificial Neural Network (ANN), and Random Forest (RF) models were developed and optimized to elucidate and predict the inhibition mechanism of novel inhibitors. …”
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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

“…The results indicate that a combination of the Random Forest classifier and Word2Vec text vectorization method is the optimal model that can manage to route calls in real-time.…”
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Temperature Field Prediction of Glulam Timber Connections Under Fire Hazard: A DeepONet-Based Approach by Jing Luo, Guangxin Tian, Chen Xu, Shijie Zhang, Zhen Liu

“…This paper presents an integrated computational framework for predicting temperature fields in glulam beam–column connections under fire conditions, combining finite element modeling, automated parametric analysis, and deep learning techniques. …”
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The Impact of Natural and Cultural Landscape Quality on Attachment to Place and the Intention to Recommend Tourism in a UNESCO World Heritage City by Dong Lv, Shukun Qin, Rui Sun, Xuxin Jiang, Ruxia Cheng, Weimin Sun

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Trends in the use of information and communication technologies in the teaching of foreign languages and translator training by N. Kovalchuk

“…These include, in particular: developing a methodology for the formation of skills included in the model of technological competence of a future translator; clarifying the comparative effectiveness of different MT systems and their potential areas of application; specifying the differences between machine and human translation and determining their optimal correlation in translator training and translation practice; identifying the optimal proportion of MT in the content of translator training and ways of evaluating texts translated using MT; developing a model for the effective integration of post-editing into the content of training; investigating ways of increasing the influence of the translation industry on the content of translator training.…”
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An intelligent algorithm for identifying dropped blocks in wellbores by Qian Wang, Zixuan Yang, Chenxi Ye, Wenbao Zhai, Xiao Feng

“…The XGBoost algorithm was then used to optimize the feature parameters and improve the classification model. …”
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Biogas Production Using Flexible Biodigester to Foster Sustainable Livelihood Improvement in Rural Households by Charles David, Venkata Krishna Kishore Kolli, Karpagaraj Anbalagan

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Multi-Agent Mapping and Tracking-Based Electrical Vehicles with Unknown Environment Exploration by Chafaa Hamrouni, Aarif Alutaybi, Ghofrane Ouerfelli

“…The framework further enhances sustainability by integrating an adaptive optimization model that continuously refines EV paths in response to real-time changes in traffic flow and charging station availability. …”
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A comprehensive review of data analytics and storage methods in geothermal energy operations by Ali Basem, Ahmed Kateb Jumaah Al-Nussairi, Dana Mohammad Khidhir, Narinderjit Singh Sawaran Singh, Mohammadreza Baghoolizadeh, Mohammad Ali Fazilati, Soheil Salahshour, S. Mohammad Sajadi, Ali Mohammadi Hasanabad

“…The study also delves into the potential of machine learning to optimize geothermal design, monitor performance, improve performance, find errors, and more. …”
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From molecules to data: the emerging impact of chemoinformatics in chemistry by Anup Basnet Chetry, Keisuke Ohto

“…Sophisticated molecular modeling techniques, such as multi-scale modeling and free energy calculations, have enhanced the accuracy of predictions, while big data analytics has enabled the extraction of valuable insights from vast datasets. …”
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Lightweight Anomaly-Based Detection Using Cuckoo Search Algorithm and Decision Tree to Mitigate Man-in-the-Middle Attacks in DNS by Ramahlapane Lerato Moila, Mthulisi Velempini

“…This study designed an anomaly-based detection scheme that identifies and mitigates MitM attacks on DNS. The proposed model utilizes machine learning algorithms and statistical analysis techniques to ensure that the analysis of DNS query patterns can efficiently detect anomalies associated with the MitM. …”
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A PatchTST-GRU based heterogeneous seq2seq model with numerical weather prediction refinement for multi-step wind power forecasting by Shiwei Xu, Yongjun Wang, Xinglei Xu, Guang Shi, He Huang, Yingya Zheng

“…To address these issues, this paper proposes a heterogeneous sequence-to-sequence (seq2seq) model based on PatchTST-GRU, integrated with NWP refinement. …”
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Comprehensive review of artificial intelligence applications in renewable energy systems: current implementations and emerging trends by Chukwuebuka Joseph Ejiyi, Dongsheng Cai, Dara Thomas, Sandra Obiora, Emmanuel Osei-Mensah, Caroline Acen, Francis O. Eze, Francis Sam, Qingxian Zhang, Olusola O. Bamisile

“…We discuss the use of Artificial Intelligence techniques including machine learning, deep learning, and reinforcement learning models for optimizing energy production, forecasting demand, predictive maintenance, and managing decentralized energy systems. …”
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Under frequency load shedding aware unit commitment in island power systems by Miad Sarvarizadeh, Mohammad Rajabdorri, Enrique Lobato, Lukas Sigrist, Behzad Kazemtabrizi, Matthias Troffaes

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Wear Characterization and Coefficient of Friction Prediction Using a Convolutional Neural Network Model for Chromium-Coated SnSb11Cu6 Alloy by Mihail Kolev, Vladimir Petkov, Veselin Petkov, Rositza Dimitrova, Shaban Uzun, Boyko Krastev

“…This study not only advances the understanding of chromium coatings for babbitt materials but also demonstrates the potential of machine learning in optimizing tribological performance.…”
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Sensor-Based Gait Analysis: A Comparative Study of Ultrasonic and Laser Sensors for Gait Monitoring in Rollator-Assisted Walking by Ivan Omeko, Stefan Twieg, Martin Obert

“…The study concludes that the HC-SR04-P is the optimal choice for the rollator Machine Learning algorithms due to its balance of accuracy, compatibility, and cost-effectiveness. …”
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Integrating bulk and single cell sequencing data to identify prognostic biomarkers and drug candidates in HBV associated hepatocellular carcinoma by Yanjie Zhong, Antony Stalin, Yushi Dai, Zhiqiang He, Siqi Yang, Ruiqi Zou, Aoqiang Zhai, Fuyu Li, Haijie Hu

“…By analyzing the mean C-index of 101 machine learning models, the optimal model—combining stepwise Cox regression (forward) with RSF—was developed to characterize the immune risk index. …”
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Exploring the role of artificial intelligence in chemotherapy development, cancer diagnosis, and treatment: present achievements and future outlook by Bassam Abdul Rasool Hassan, Ali Haider Mohammed, Souheil Hallit, Souheil Hallit, Souheil Hallit, Diana Malaeb, Hassan Hosseini, Hassan Hosseini

“…Keywords included “Artificial Intelligence (AI),” “Machine Learning (ML),” and “Deep Learning (DL)” combined with “chemotherapy development,” “cancer diagnosis,” and “cancer treatment.” …”
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Dimensional Accuracy Analysis of Splined Shafts and Hubs Obtained by Fused-Deposition Modeling 3D Printing Using a Genetic Algorithm and Artificial Neural Network by Alin-Daniel Rizea, Cristina-Florena Banică, Tatiana Georgescu, Alexandru Sover, Daniel-Constantin Anghel

“…A full factorial experimental design was implemented, and measurements were conducted using a high-precision coordinate measuring machine (CMM). To optimize dimensional accuracy, artificial neural networks (ANNs) were trained using experimental data, and a genetic algorithm (GA) was employed for multi-objective optimization. …”
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Research on the Demands of GFM Converters Considering the Stability Enhancement for Large Receiving Power Grids by SUN, W., WANG, Q., LIU, Q., GE, Y., CAI, H., HAN, X., XIE, Z.

“…Finally, the effectiveness of the proposed method is verified through a modified IEEE 39-bus model based on the Matlab/Simulink platform.…”
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