TIM-FEM-ML synthetic technology for longitudinal optimization of tunnel excavated in the interlayered rock mass by Hui Li, Weizhong Chen, Xiaoyun Shu, Xianjun Tan, Qun Sui

“…Python codes are programmed to realize automatic processing of numerical simulation and results are extracted to the ML algorithm for the prediction model. An optimization algorithm is implanted in the numerical stream file to retrieve the optimal relative intersection angle between the tunnel axis and the trend of rocks. …”
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Two-Level Distributed Multi-Source Information Fusion Model for Aphid Monitoring and Forecasting in the Greenhouse by Xiaoyin Li, Lixing Wang, Min Dai, Yongji Zhang, Wei Su, Mingyou Wang, Hong Miao

“…Aphids are the main agricultural pests that affect the quality and yield of peppers in the greenhouse. Efficient early prediction of aphid occurrence is of great significance for the development of digitization and information technology in intelligent agriculture. …”
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Vulnerability of peatland fires in bengkalis regency during the ENSO El nino phase using a machine learning approach by Fauziah, Lilik B. Prasetyo, Nonon Saribanon, Nur Hayati

“…Therefore, the development of a peatland fire prediction model is necessary. This study aims to identify peatland fire vulnerability in Bengkalis Regency using burn area from MODIS 2019. …”
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Enhancing students performance through dynamic personalized learning path using ant colony and item response theory (ACOIRT) by Imamah, Umi Laili Yuhana, Arif Djunaidy, Mauridhi Hery Purnomo

“…Generating personalized learning paths (PLP) tailored to each student's characteristics and abilities is challenging, especially when using multiple-choice test scores to predict knowledge levels, which can be affected by guessing. …”
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A deep learning approach to real-time Markov modeling of ion channel gating by Efthymios Oikonomou, Yannick Juli, Rajkumar Reddy Kolan, Linda Kern, Thomas Gruber, Christian Alzheimer, Patrick Krauss, Andreas Maier, Tobias Huth

“…In addition, we propose a method to evaluate the goodness of a predicted model by re-simulating the prediction. Finally, we tested the algorithm with data recorded on a patch-clamp setup. …”
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Creating prognostic systems for cancer patients: A demonstration using breast cancer by Mathew T. Hueman, Huan Wang, Charles Q. Yang, Li Sheng, Donald E. Henson, Arnold M. Schwartz, Dechang Chen

“…Abstract Integrating additional prognostic factors into the tumor, lymph node, metastasis staging system improves the relative stratification of cancer patients and enhances the accuracy in planning their treatment options and predicting clinical outcomes. We describe a novel approach to build prognostic systems for cancer patients that can admit any number of prognostic factors. …”
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Developing and validating a drug recommendation system based on tumor microenvironment and drug fingerprint by Yan Wang, Xiaoye Jin, Rui Qiu, Bo Ma, Sheng Zhang, Xuyang Song, Jinxi He

“…This study aimed to develop a personalized drug recommendation model leveraging genomic profiles to optimize therapeutic outcomes.MethodsA content-based filtering algorithm was implemented to predict drug sensitivity. …”
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Application and Challenges of Artificial Intelligence in Different Branches of Dentistry by Ali Mirzaei, Melika Mollaei, Anahita Lotfizadeh, Mehdi Aryana, Alireza Ebrahimpour

“…Maxillofacial applications include surgical outcome prediction and pathology identification. Forensic applications facilitate age and gender determination through radiographic analysis. …”
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Correlation learning based multi-task model and its application by XU Wei, LUO Jianping, LI Xia, CAO Wenming

“…In order to solve the problem of inherent conflicts of task differences that can damage the prediction of some tasks, a multi-task learning model based on correlation learning layer (CLL) is proposed. …”
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Design and optimization of an open personalized human-computer interaction system for New Year Painting based on the learner's model by Zaozao Guo, Muhamad Firdaus Ramli, Wenpeng Zhang

“…Firstly, the attention mechanism based long and short term memory network is used to mine the emotion from the course review text of learners, and the association rule algorithm and ID3 algorithm are used to initialize and dynamically update the text. …”
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Deep learning for sea surface temperature applications: A comprehensive bibliometric analysis and methodological approach by Redouane Larbi Boufeniza, Luo Jingjia, Kemal Adem Abdela, Karam Alsafadi, Mohammad M Alsahli

“…Moreover, the long short‐term memory (LSTM) algorithm was the predominant computational deep learning algorithm extensively used in this specific context. …”
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Comprehensive evaluation of phosphoproteomic-based kinase activity inference by Sophia Müller-Dott, Eric J. Jaehnig, Khoi Pham Munchic, Wen Jiang, Tomer M. Yaron-Barir, Sara R. Savage, Martin Garrido-Rodriguez, Jared L. Johnson, Alessandro Lussana, Evangelia Petsalaki, Jonathan T. Lei, Aurelien Dugourd, Karsten Krug, Lewis C. Cantley, D. R. Mani, Bing Zhang, Julio Saez-Rodriguez

“…We used benchmarKIN to evaluate kinase-substrate libraries, inference algorithms and the potential of adding predicted kinase-substrate interactions to overcome the coverage limitations. …”
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Identifying potential biomarkers and molecular mechanisms related to arachidonic acid metabolism in vitiligo by Xiaoqing Li, Xiaoqing Li, Li Yang, Longfei Zhu, Jingying Sun, Jingying Sun, Cuixiang Xu, Cuixiang Xu, Lijun Sun, Lijun Sun

“…A biomarker-based nomogram was constructed to predict the risk of vitiligo.Results15 overlapping candidate genes were obtained between the DEGs and AAM-RGs. …”
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Determining of Treatment Tactic and Planning of Atypical Removal of Asymptomatic and Without Any Pathological Changes Impacted Mandibular Third Molars by Vares Y., Kyyak S.

“…In order to perform a correct planning, prediction of atypical removal and analysis of potential postoperative complications we created a computer program ″Xray analyzer″. …”
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Mesosphere data assimilation based on the intelligent optimization of the uncertainty parameters in a theoretical model by Dexin Ren, Jiuhou Lei, Xuetao Chen, Tong Dang, Yu Liu

“…This algorithm was employed to improve the accuracy of mesospheric state simulation via the injection of sparse observations. …”
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Komparasi Performa Algoritma Kompresi Data Lossless Menggunakan Rasio Kompresi Dan Penghematan Ruang by Aswar Hanif, Endang Wahyudi, Harna Adianto, Lilik Martanto

“…Beberapa metode dan algoritma kompresi lossless diantaranya seperti Lempel–Ziv–Markov chain algorithm (LZMA), Prediction by partial matching (PPM), Burrows-Wheeler block sorting text compression algorithm and Huffman coding (BZip2), dan Deflate. …”
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Real-time torque distribution simulation of parallel hybrid vehicle engine by Jing Wang

“…While energy utilization during deceleration braking remains suboptimal, future work will optimize regenerative braking strategies through road condition prediction and advanced power devices. This approach provides a viable pathway to improve energy sustainability in hybrid transportation systems.…”
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Review on the recent trends of food dryer technologies and optimization methods of drying parameters by Dawit Andualem Asrate, Addisu Negash Ali

“…Furthermore, tools with better optimization and prediction capabilities for various food types such as Computational Fluid Dynamics (CFD), ANSYS Multi-Objective Genetic Algorithm (MOGA), Adaptive Neuro-Fuzzy Inference Systems (ANFIS), Genetic Algorithm (GA)-tuned Artificial Neural Networks (ANN), Analysis of Variance (ANOVA), and Response Surface Methodology (RSM) are reviewed in detail. …”
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Characteristics stochastic analysis of long and narrow deep excavations under soil spatial variability by Shouhua Liu, Zhaoliang Wang, Yadong Chen, Guohua Fang, Yiding Zhao, Junsheng Yang, Huasheng Sun

“…In summary, soil spatial variability significantly impacts deformation prediction and safety control during the design and construction stages of deep excavations. …”
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Estimating global precipitation fields by interpolating rain gauge observations using the local ensemble transform Kalman filter and reanalysis precipitation by Y. Muto, S. Kotsuki, S. Kotsuki, S. Kotsuki, S. Kotsuki

“…Additionally, the global rain gauge observations provided by the National Oceanic and Atmospheric Administration Climate Prediction Center (NOAA CPC) are used for observation inputs in the LETKF algorithm.…”
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