An Empirical Configuration Study of a Common Document Clustering Pipeline by Anton Eklund, Mona Forsman, Frank Drewes

“…The results suggest that BERT embeddings combined with UMAP dimension reduction to no less than 15 dimensions provides a good basis for clustering, regardless of the specific clustering algorithm used. …”
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Serum peptide biomarkers by MALDI-TOF MS coupled with machine learning for diagnosis and classification of hepato-pancreato-biliary cancers by Piya Prajumwongs, Attapol Titapun, Vasin Thanasukarn, Apiwat Jareanrat, Natcha Khuntikeo, Krit Rattanarak, Nisana Namwat, Poramate Klanrit, Arporn Wangwiwatsin, Jarin Chindaprasirt, Supinda Koonmee, Prakasit Sa-Ngiamwibool, Nattha Muangritdech, Sawanya Charoenlappanit, Janthima Jaresitthikunchai, Sittiruk Roytrakul, Watcharin Loilome

“…Feature selection on the training set identified 71 informative peptide mass fingerprints, which were then used to construct predictive models using SVM and RF algorithms. Visualization using heatmap, PLS-DA, and multiclass RF analysis showed clear separation between healthy individuals and HPB cancer patients, as well as among different HPB cancer subtypes. …”
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The Future of Economic Modelling by A.O. Moscardini, K. Lawler, T. Vlasova, E. Merza

“…Traditional Economic modelling is still a useful tool for understanding and teaching but Data Analytics and intelligent algorithms are better for economic predictions.…”
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Application of Categorical Boosting to Modelling the Friction Behaviour of DC05 Steel Sheets in Strip Drawing Test by Marek Szewczyk, Krzysztof Szwajka, Sherwan Mohammed Najm, Salwa O Mohammed

“…A Shapley decision plot exhibits the coefficient of friction prediction models via cumulative SHapley Additive exPlanations (SHAP) data. …”
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Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

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METHOD OT DATA AND KNOWLEDGE PROCESSING IN INTERNET WITH CIPHERING SUPPORT by V. A. Vishniakov, D. S. Borodaenko

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A Comparative Analysis of Automated Machine Learning Libraries for Electricity Price Forecasting by O’Leary Christian, Lynch Conor, Toosi Farshad Ghassemi

“…Reliable and accurate electricity price forecasting algorithms can be used to inform efficient energy consumption schedules and maximise profits for electricity traders. …”
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AI and Custom Marketing for Cultural Initiatives in Regional Projects: Perspectives on the Territorial Integration of Communities with Tourism by Mariflora Caruso, Laura Leopardi, Saverio Giulio Malatesta

“…This approach aims to predict and meet individual preferences, redefining engagement and outreach strategies in cultural settings.…”
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Low-intensity behavioral activation smartphone app to support low mood: description, engagement and log data analysis by Paul Farrand, Patrick J. Raue, Earlise Ward, Sandra Healey, Jonathan Baker

“…For those completing the PHQ-8 and GAD-7 outcome measures, there was a significant reduction in PHQ-8 (t(48) = 5.2; p < 0.01) and GAD-7 (t(48) = 3.5; p < 0.01) scores, respectively, with reductions greater with higher baseline severity. …”
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Using Satellites to Monitor Soil Texture in Typical Black Soil Areas and Assess Its Impact on Crop Growth by Liren Gao, Yuhong Zhang, Deqiang Zang, Qian Yang, Huanjun Liu, Chong Luo

“…The results show that (1) the order of prediction accuracy differs for different soil texture types; April is determined to have the highest prediction accuracy for silt and sand, while May exhibits the greatest accuracy for clay. (2) Adding environmental variables can significantly improve the accuracy of soil texture predictions; the root mean square error (RMSE) has decreased to varying degrees (silt: 0.84; clay: 0.04; sand: 0.85). (3) Soybean growth has the strongest response to soil texture; clay grain is the key factor affecting crop growth in drought scenarios, and sand grain is the dominant factor influencing flooding. …”
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Turning Energy-Aware Route Planning With an Extended TSP and Double-Layer State Graph: Experimental Evaluation With a Crawler Mobile Robot by Namihei Adachi, Hisashi Date

“…The routes that minimized energy consumption showed an average 17 % reduction in energy consumption, while the routes that minimized travel time achieved an average 5 % reduction in travel time compared to the standard TSP algorithm.…”
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A Reinforcement Learning-Based Generative Approach for Event Temporal Relation Extraction by Zhonghua Wu, Wenzhong Yang, Meng Zhang, Fuyuan Wei, Xinfang Liu

“…To bridge the gap between the optimization objective and task performance metrics, we employ the REINFORCE algorithm to optimize our generative model, designing a novel reward function to simultaneously capture the accuracy of temporal prediction and the quality of generation. …”
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SIMULATION TRAINING IN MEDICAL STUDENT PREPARATION by Oleg V. Zinchenko, Alla A. Muravyeva, Oksana V. Vladimirova

“…Elements of this method can be used in different stages of educational process: in development of practical skills in emergency care, in training to render the first aid in traumas and wounds, and in state attestation.…”
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RLK-YOLOv8: multi-stage detection of strawberry fruits throughout the full growth cycle in greenhouses based on large kernel convolutions and improved YOLOv8 by Lei He, Lei He, Lei He, Dasheng Wu, Dasheng Wu, Dasheng Wu, Xinyu Zheng, Xinyu Zheng, Xinyu Zheng, Fengya Xu, Fengya Xu, Fengya Xu, Shangqin Lin, Shangqin Lin, Shangqin Lin, Siyang Wang, Siyang Wang, Siyang Wang, Fuchuan Ni, Fang Zheng

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Catatonia in anti-NMDA receptor encephalitis: a case series and approach to improve outcomes with electroconvulsive therapy by F. Gabriela Kraiter, Dakota T. May, Ryan D. Slauer, Nandini Abburi, Christopher Eckstein, Suma Shah, Jonathan R. Komisar, Jacob P. Feigal

“…Patients received an average of 29.9 ECT treatments in total.Conclusions Based on clinical prediction scores, this cohort had better than expected functional outcomes. …”
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Intelligent Methods of Operational Response to Accidents in Urban Water Supply Systems Based on LSTM Neural Network Models by Aliaksey A. Kapanski, Nadezeya V. Hruntovich, Roman V. Klyuev, Aleksandr E. Boltrushevich, Svetlana N. Sorokova, Egor A. Efremenkov, Anton Y. Demin, Nikita V. Martyushev

“…The objective of this study was to evaluate the effectiveness of LSTM models for pressure prediction tasks. To acquire real-time pressure data, an information system based on Internet of Things (IoT) technology using the MQTT protocol was proposed. …”
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Integration of AI with artificial sensory systems for multidimensional intelligent augmentation by Changyu Tian, Youngwook Cho, Youngho Song, Seongcheol Park, Inho Kim, Soo-Yeon Cho

“…We introduce specialized AI algorithms and raw data processing methods for each function, designed to enhance and optimize sensing performance. …”
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Investigating imperceptibility of adversarial attacks on tabular data: An empirical analysis by Zhipeng He, Chun Ouyang, Laith Alzubaidi, Alistair Barros, Catarina Moreira

“…Adversarial attacks are a potential threat to machine learning models by causing incorrect predictions through imperceptible perturbations to the input data. …”
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Energy-Environmental Analysis of Retrofitting of a Chilled Water Production System in an Industrial Facility—A Case Study by Tomasz Mróz, Kacper Fórmaniak

“…It achieved a 370 MWh annual primary energy consumption reduction and a 1140 Mg annual carbon dioxide emission reduction. …”
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A Multi-Objective Decision-Making Method for Optimal Scheduling Operating Points in Integrated Main-Distribution Networks with Static Security Region Constraints by Kang Xu, Zhaopeng Liu, Shuaihu Li

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