Prediction-Based Tip-Over Prevention for Planetary Exploration Rovers by Siddhant Shete, Raúl Domínguez, Ravisankar Selvaraju, Mariela De Lucas Álvarez, Frank Kirchner

“…By leveraging deep learning algorithms, the system evaluates predictions and true measurements in real time to identify potential tip-overs. …”
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Predicting the Tensile Strength of Plant Leaves Based on GA-SVM by Wei Chang, Meihong Liu, Yayu Huang, Junjie Lei, Kai Wu

“…A comparative analysis with other predictive algorithms demonstrates that the GA-SVM model achieves the lowest prediction error and highest accuracy, with mean absolute error and root mean squared error values of 0.0774 and 0.0745, respectively. …”
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Delving into Underwater Image Utility: Benchmark Dataset and Prediction Model by Jiapeng Liu, Yi Liu, Qiuping Jiang

“…On the other hand, based on this newly constructed OD-UIUA dataset, we train a deep UIUA network (DeepUIUA) that can automatically and accurately predict UIUS. To the best of our knowledge, this is the first benchmark dataset for UIUA and also the first model focusing on the specific UIUA problem. …”
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Advancements in handwritten Devanagari character recognition: a study on transfer learning and VGG16 algorithm by Chetan Sharma, Shamneesh Sharma, Sakshi, Hsin-Yuan Chen

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Algorithm for analyzing the movement pattern of the temporomandibular joint musculararticular system based on multichannel electromyogram processing by I. V. Samuylov, М. V. Davydov, G. G. Sagaimaruf, I. N. Baradina, S. P. Rubnikovich

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Impact of stain variation and color normalization for prognostic predictions in pathology by Siyu Lin, Haowen Zhou, Mark Watson, Ramaswamy Govindan, Richard J. Cote, Changhuei Yang

“…This highlights the need to develop an entirely new way to process and collect consistent microscopy images from histologic slides that can be used to both train and allow for the general application of predictive DNN algorithms.…”
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Optimizing Deep Learning Models with Improved BWO for TEC Prediction by Yi Chen, Haijun Liu, Weifeng Shan, Yuan Yao, Lili Xing, Haoran Wang, Kunpeng Zhang

“…The prediction of total ionospheric electron content (TEC) is of great significance for space weather monitoring and wireless communication. …”
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Co-folding, the future of docking – prediction of allosteric and orthosteric ligands by Eva Nittinger, Özge Yoluk, Alessandro Tibo, Gustav Olanders, Christian Tyrchan

“…Recently, computational biology has seen a breakthrough with deep learning algorithms capable of predicting protein structures based on amino acid sequences. …”
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Development of time to event prediction models using federated learning by Rasmus Rask Kragh Jørgensen, Jonas Faartoft Jensen, Tarec El-Galaly, Martin Bøgsted, Rasmus Froberg Brøndum, Mikkel Runason Simonsen, Lasse Hjort Jakobsen

“…Method We propose two methods for training time-to-event prediction models based on distributed data, relying on FL algorithms, for time-to-event prediction models. …”
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Predicting the generalization of computer aided detection (CADe) models for colonoscopy by Joel Shor, Carson McNeil, Yotam Intrator, Joseph R. Ledsam, Hiro-o Yamano, Daisuke Tsurumaru, Hiroki Kayama, Atsushi Hamabe, Koji Ando, Mitsuhiko Ota, Haruei Ogino, Hiroshi Nakase, Kaho Kobayashi, Masaaki Miyo, Eiji Oki, Ichiro Takemasa, Ehud Rivlin, Roman Goldenberg

“…Abstract Generalizability of AI colonoscopy algorithms is important for wider adoption in clinical practice. …”
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Crop Yield Prediction: Data Structure and Ai-Powered Methods by V. K. Kalichkin, K. Yu. Maksimovich, O. A. Aleshchenko, V. V. Aleshchenko

“…(Research purpose) The aim of this study is to analyze data structures and compare machine learning and deep learning algorithms used in used in crop yield prediction. (Materials and methods) Using a convergent approach and applying methods of cognitive and semantic analysis, the authors examined the subject area of artificial intelligence applications in crop yield prediction. …”
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Predicting Quality of Multimedia Experience Using Electrocardiogram and Respiration Signals by Sowmya Vijayakumar, Ronan Flynn, Peter Corcoran, Niall Murray

“…We compare the performances of several machine learning (ML) and deep learning (DL) models in predicting QoE subjective scores from electrocardiograms and respiration signals. …”
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State of Charge Estimation of Lithium Battery Utilizing Strong Tracking H-Infinity Filtering Algorithm by Tianqing Yuan, Yang Liu, Jing Bai, Hao Sun

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Post-processing methods for mitigating algorithmic bias in healthcare classification models: An extended umbrella review by Shaina Mackin, Vincent J. Major, Rumi Chunara, Remle Newton-Dame

“…Abstract Background AI and predictive analytics have increased the speed of innovation in medicine. …”
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An Analytic Policy Gradient-Based Deep Reinforcement Learning Motion Cueing Algorithm for Driving Simulators by Xiaowei Huang, Xuhua Shi, Peiyao Wang, Hongzan Xu, Xiaojun Tang, Gaoran Zhang

“…At higher prediction horizons, the algorithm achieves performance on par with state-of-the-art MPC-based motion cueing algorithms while exhibiting reduced algorithmic delay. …”
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Optimization of Table Tennis Swing Action Supported by the Temporal Convolutional Network Algorithm in Deep Learning by Shaoxuan Sun, Hongyu Zheng, Zhixin Lin

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Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm by Jiaju Zhu, Zhong Zhang, Runnan Liu, Meixue Ren, Guodong Ma

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Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…[Conclusion] The experiments verify that the WM-CTA model delivers optimal prediction performance with high computational efficiency. …”
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Application of machine learning techniques for churn prediction in the telecom business by Raji Krishna, D. Jayanthi, D.S. Shylu Sam, K. Kavitha, Naveen Kumar Maurya, T. Benil

“…The primary objective of this work is to examine various machine learning algorithms necessary for creating customer churn prediction (CP) models and identifying the reasons for churn. …”
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IECO: an improved educational competition optimizer for state-of-the-art engineering optimization by Xiaojie Tang, Junbo Jacob Lian, Ling Ma, Xincan Wu, Rui Zhong, Yujun Zhang, Huiling Chen

“…Abstract The Educational Competition Optimizer (ECO) is a novel human-based optimization algorithm inspired by educational competition phenomena in society. …”
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