Question-matching approach based on gradual machine learning by Xuejian HE, Anqi CHEN, Zhiqiang GUO, Zhiru WANG, Qun CHEN

“…Extensive experiments demonstrate that compared with pure deep learning models, the proposed solution effectively improves the accuracy of question matching, and its performance advantage generally increases with a decrease in labeled training data. Our experiments also demonstrate that the performance of the proposed solution is very robust w.r.t key algorithmic parameters, indicating its applicability in real-world scenarios. …”
Get full text

Trade-Offs Between Simplifying Inertial Measurement Unit–Based Movement Recordings and the Attainability of Different Levels of Analyses: Systematic Assessment of Method Variations... by Manu Airaksinen, Okko Räsänen, Sampsa Vanhatalo

“…The IMU data can be used for an algorithmic detection of different postures and movements, which may support more detailed assessments of complex behaviors, such as daily activities. …”
Get full text

A stacked ensemble machine learning model for the prediction of pentavalent 3 vaccination dropout in East Africa by Meron Asmamaw Alemayehu, Shimels Derso Kebede, Agmasie Damtew Walle, Daniel Niguse Mamo, Ermias Bekele Enyew, Jibril Bashir Adem

“…While RF and GLM meta-learners were also evaluated, they were outperformed by the XGBoost meta-learner. …”
Get full text

Real-world study on adverse drug reactions of pembrolizumab in endometrial cancer treatment: insights from the FAERS database by Huiping Zhang, Man Di, Jingjing Wang, Shan Wang, Yini Dai, Jingjing Huang, Zhuo Zhou

“…To validate the robustness of the results, three additional algorithms—Proportional Reporting Ratio (PRR), Bayesian Confidence Propagation Neural Network (BCPNN), and Multi-Item Gamma Poisson Shrinker (MGPS)—were also applied. …”
Get full text

Projecting future changes in potato yield using machine learning techniques: a case study for Prince Edward Island, Canada by Dania Tamayo-Vera, Kai Liu, Antonio Bolufé-Röhler, Xiuquan Wang

“…Although machine learning algorithms have been extensively applied in agricultural yield prediction, previous studies have not fully leveraged the potential of capturing both short- and long-term dependencies. …”
Get full text

Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…This review not only charts a course for the rational design of HEAs, but also envisages their role in advancing material science towards novel applications, urging a concerted effort to overcome existing hurdles and explore uncharted territories in HEA research.…”
Get full text

Dark Energy Survey Year 6 Results: Synthetic-source Injection Across the Full Survey Using Balrog by Dhayaa Anbajagane, M. Tabbutt, J. Beas-Gonzalez, B. Yanny, S. Everett, M. R. Becker, M. Yamamoto, E. Legnani, J. De Vicente, K. Bechtol, J. Elvin-Poole, G. M. Bernstein, A. Choi, M. Gatti, G. Giannini, R. A. Gruendl, M. Jarvis, S. Lee, J. Mena-Fernández, A. Porredon, M. Rodriguez-Monroy, E. Rozo, E. S. Rykoff, T. Schutt, E. Sheldon, M. A. Troxel, N. Weaverdyck, V. Wetzell, M. Aguena, A. Alarcon, S. Allam, A. Amon, F. Andrade-Oliveira, D. Brooks, A. Carnero Rosell, J. Carretero, C. Chang, M. Crocce, L. N. da Costa, M. E. S. Pereira, T. M. Davis, S. Desai, H. T. Diehl, S. Dodelson, P. Doel, A. Drlica-Wagner, A. Ferté, J. Frieman, J. García-Bellido, E. Gaztanaga, D. Gruen, G. Gutierrez, W. G. Hartley, K. Herner, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. Huterer, D. J. James, E. Krause, K. Kuehn, O. Lahav, J. L. Marshall, R. Miquel, J. Muir, J. Myles, A. Pieres, A. A. Plazas Malagón, J. Prat, M. Raveri, S. Samuroff, E. Sanchez, D. Sanchez Cid, I. Sevilla-Noarbe, M. Smith, E. Suchyta, G. Tarle, D. L. Tucker, A. R. Walker, P. Wiseman, Y. Zhang, The DES Collaboration

“…The consistency between the two catalogs also extends to their correlations with survey observing properties (seeing, airmass, depth, extinction, etc.). …”
Get full text

The global water resources and use model WaterGAP v2.2e: description and evaluation of modifications and new features by H. Müller Schmied, H. Müller Schmied, T. Trautmann, S. Ackermann, D. Cáceres, M. Flörke, H. Gerdener, E. Kynast, T. A. Peiris, L. Schiebener, M. Schumacher, P. Döll, P. Döll

“…WaterGAP v2.2e improves the handling of inland sinks and now excludes not only large but also small human-made reservoirs when simulating naturalized conditions. …”
Get full text

DISPEL: A Python Framework for Developing Measures From Digital Health Technologies by A. Scotland, G. Cosne, A. Juraver, A. Karatsidis, J. Penalver-Andres, E. Bartholome, C. M. Kanzler, C. Mazza, D. Roggen, C. Hinchliffe, S. Del Din, S. Belachew

“…<italic>Methods</italic>: Modularity, integrability and flexibility were achieved adopting an object-oriented architecture for data modelling and SDM extraction, which also allowed standardizing SDM generation, naming, storage, and documentation. …”
Get full text

LLM in the Loop: A Framework for Contextualizing Counterfactual Segment Perturbations in Point Clouds by Veljka Kocic, Niko Lukac, Dzemail Rozajac, Stefan Schweng, Christoph Gollob, Arne Nothdurft, Karl Stampfer, Javier del Ser, Andreas Holzinger

“…Point Cloud Data analysis has seen a major leap forward with the introduction of PointNet algorithms, revolutionizing how we process 3D environments. …”
Get full text

Remote Sensing Time Series Analysis: A Review of Data and Applications by Yingchun Fu, Zhe Zhu, Liangyun Liu, Wenfeng Zhan, Tao He, Huanfeng Shen, Jun Zhao, Yongxue Liu, Hongsheng Zhang, Zihan Liu, Yufei Xue, Zurui Ao

“…., a constellation strategy, increasing computing power and advancing deep learning algorithms, are driving a paradigm shift from traditional point-in-time mapping to near-real-time monitoring tasks, and even to modeling integration of parameter inversion and prediction in land, water, and air science. …”
Get full text

Unveiling the power of high-dimensional cytometry data with cyCONDOR by Charlotte Kröger, Sophie Müller, Jacqueline Leidner, Theresa Kröber, Stefanie Warnat-Herresthal, Jannis Bastian Spintge, Timo Zajac, Anna Neubauer, Aleksej Frolov, Caterina Carraro, DELCODE Study Group, Frank Jessen, Simone Puccio, Anna C. Aschenbrenner, Joachim L. Schultze, Tal Pecht, Marc D. Beyer, Lorenzo Bonaguro

“…To bridge this data analysis gap in HDC we develop cyCONDOR, an easy-to-use computational framework covering not only all essential steps of cytometry data analysis but also including an array of downstream functions and tools to expand the biological interpretation of the data. …”
Get full text

The relationship between the CYP2C19*17 genetic polymorphism and the efficacy and safety of diazepam in patients with alcohol withdrawal syndrome by V. Yu. Skryabin, M. S. Zastrozhin, E. A. Grishina, K. A. Ryzhikova, V. V. Shipitsyn, I. V. Barna, T. E. Galaktionova, A. S. Sorokin, E. A. Bryun, D. A. Sychev

“…The scores on the UKU scale, which was used to evaluate the safety of therapy, were also different: (CC) 8,0 [6,0; 12,0], (CT + TT) 6,0 [6,0; 12,0], p = 0,006.Conclusion. …”
Get full text

Measuring the Intracluster Light Fraction with Machine Learning by Louisa Canepa, Sarah Brough, Francois Lanusse, Mireia Montes, Nina Hatch

“…However, only small samples have been studied to date due to its very low surface brightness and the heavy manual involvement required for the majority of measurement algorithms. Upcoming large imaging surveys such as the Vera C. …”
Get full text

Listener Acoustic Personalization Challenge - LAP24: Head-Related Transfer Function Upsampling by Aidan O. T. Hogg, Roberto Barumerli, Rapolas Daugintis, Katarina C. Poole, Fabian Brinkmann, Lorenzo Picinali, Michele Geronazzo

“…The submissions to Task 2 employed both algorithmic and machine learning-based approaches, which were evaluated on three key spatial audio objective metrics, including the log-spectral distortion (LSD), interaural time difference (ITD), and the interaural level difference (ILD). …”
Get full text

Recognition and management of auditory verbal hallucinations in borderline personality disorder by M. B. A. Niemantsverdriet, M. B. A. Niemantsverdriet, C. W. Slotema, C. W. Slotema, I. H. A. Franken, J. Brandsma, M. J. P. M. Verbraak, M. L. Deen, J. D. Blom, J. D. Blom, J. D. Blom, M. Van der Gaag

“…Further research is needed to develop algorithms to optimize doses in individual patients, to develop treatment guidelines, and to explore the effects of nonpharmacological treatments.…”
Get full text

The development and psychometric properties of the persian linguistic inquiry and word count (P-LIWC): Emotions and cognitive processes categories by Mohammad Ali Soltani, Peyman MamSharifi, Reza Salehi Chegeni, Ali Safari, Soudabeh Ershadi Manesh, Hamidreza Keshavarz, Majid Afshari, MohamadSajad Ghafouri, Mojtaba Mohammadi, Fateme Tavakoli

“…Specifically, with the help of algorithms and computational processes, it can analyze elements such as emotions, cognitions, attitudes, vocabulary, language style and social communication in texts, and the lack of a Persian version was one of the most important reasons for conducting this research. …”
Get full text

NeuroSense: A Novel EEG Dataset Utilizing Low-Cost, Sparse Electrode Devices for Emotion Exploration by Tommaso Colafiglio, Angela Lombardi, Paolo Sorino, Elvira Brattico, Domenico Lofu, Danilo Danese, Eugenio Di Sciascio, Tommaso Di Noia, Fedelucio Narducci

“…We develop a comprehensive preprocessing pipeline and employ machine learning algorithms to translate EEG data into meaningful insights about emotional states. …”
Get full text

Personalized treatment strategies for breast adenoid cystic carcinoma: A machine learning approach by Sakhr Alshwayyat, Mahmoud Bashar Abu Al Hawa, Mustafa Alshwayyat, Tala Abdulsalam Alshwayyat, Siya sawan, Ghaith Heilat, Hanan M. Hammouri, Sara Mheid, Batool Al Shweiat, Hamdah Hanifa

“…We also performed a Kaplan-Meier (K-M) survival analysis. …”
Get full text

Automatic location and recognition of horse freezing brand using rotational YOLOv5 deep learning network by Zhixin Hua, Yitao Jiao, Tianyu Zhang, Zheng Wang, Yuying Shang, Huaibo Song

“…The two-step method can accurately identify brand numbers with complex backgrounds. It also provides a stable and lightweight method for livestock individual identification.…”
Get full text