F-DATA: A Fugaku Workload Dataset for Job-centric Predictive Modelling in HPC Systems by Francesco Antici, Andrea Bartolini, Jens Domke, Zeynep Kiziltan, Keiji Yamamoto

“…Abstract In the last decades, High Performance Computing (HPC) systems have accelerated scientific discoveries and innovations across different domains, from epidemic studies to climate science. …”
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Analysis of drug crystallization by evaluation of pharmaceutical solubility in various solvents by optimization of artificial intelligence models by Wael A. Mahdi, Adel Alhowyan, Ahmad J. Obaidullah

“…The novelty of the work is to maximize the performance of the model by using methods including the isolation forest for anomaly detection and the tree-structured Parzen estimator for hyperparameter fine-tuning. …”
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A Structural Analysis of the Chinese Patriarchal Family Business Model: What Happens in the Corridors of the Shrine? by Kerbouche Mohammed, Bouguesri Imene

“…The family business features a replica of the family model, carrying the DNA of its structural foundational principles that sow the seeds of the vision of its creator (the family head). …”
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Automated Classification Model for Elementary Mathematics Diagnostic Assessment Data Based on TF-IDF and XGBoost by Seonghyun Park, Seungmin Oh, Woncheol Park

“…After preprocessing, TF-IDF was employed to extract relevant features, and XGBoost was used to train a classification model. …”
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Cardioattentionnet: advancing ECG beat characterization with a high-accuracy and portable deep learning model by Youfu He, Youfu He, Youfu He, Yu Zhou, Yu Zhou, Yu Qian, Jingjie Liu, Jinyan Zhang, Debin Liu, Qiang Wu, Qiang Wu

“…The architecture of CANet allows for effective processing of extended ECG patterns and detailed feature extraction without a substantial increase in model size.ResultsEmpirical results indicate that CANet outperformed traditional models in terms of predictive performance and stability, as confirmed by comprehensive cross-validation. …”
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Ultrasound radiomics models improve preoperative diagnosis and reduce unnecessary biopsies in indeterminate thyroid nodules by Lu Chen, Yan Wang, Yan Wang, Haoyu Jing, Haoyu Jing, Rui Bao, Bin Sun, Mingbo Zhang, Yukun Luo

“…Independent training (n=136) and validation (n=61) cohorts were used to develop three radiomics models. Model performance was evaluated using receiver operating characteristic analysis and compared to two existing assisted diagnostic tools and two junior radiologists.ResultsThe Radunion model achieved the highest performance, with 90.5% sensitivity, 56.8% specificity, 75.0% positive predictive value, 80.7% negative predictive value, and 76.6% accuracy. …”
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Identification of anti-fibrotic compounds from Piper longum L via hollow fiber cell fishing and high-performance liquid chromatography with in vivo and in vitro validation by Jie Tian, Nan Zhou, Heng Wang, Wanghui Jing, Guoping Zheng

“…Methods HK-2 cells with fibrotic features induced by transforming growth factor-β (TGF-β) were used to develop a hollow fiber cell fishing coupled with high-performance liquid chromatography (HFCF-HPLC) mode. …”
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Machine learning discrimination of Gleason scores below GG3 and above GG4 for HSPC patients diagnosis by Bingyu Zhu, Longguo Dai, Huijian Wang, Kun Zhang, Chongjian Zhang, Yang Wang, Feiyu Yin, Ji Li, Enfa Ning, Qilin Wang, Libo Yang, Hong Yang, Ruiqian Li, Jun Li, Chen Hu, Hongyi Wu, Haiyang Jiang, Yu Bai

“…Abstract This study aims to develop machine learning (ML)-assisted models for analyzing datasets related to Gleason scores in prostate cancer, conducting statistical analyses on the datasets, and identifying meaningful features. …”
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A Radiomic-based model to predict the depth of myometrial invasion in endometrial cancer on ultrasound images by Francesca Arezzo, Annarita Fanizzi, Rosanna Mancari, Emiliano Cocco, Samantha Bove, Maria Colomba Comes, Mariangela Gianciotta, Giorgia Lanza, Salvatore Lopez, Gerardo Cazzato, Erica Silvestris, Elsa Vitale, Enrico Vizza, Gennaro Cormio, Raffaella Massafra, Vera Loizzi

“…After a pre-processing phase of ultrasound images, a pre-trained Inception-V3 convolutional neural network (CNN) was used as features extractor. Then, a binary classification model and a multiclass model were trained, after a double step of feature selection; the first selection stage performed feature filtering based on a nonparametric test, the second stage selected features by evaluating not only the relationship with the outcome of interest, but also the relationship with other predictive features. …”
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Deeper insight into speech characteristics of patients at ultra-high risk using classification and explainability models by Deok-Hee Kim-Dufor, Michel Walter, Marie-Odile Krebs, Yannis Haralambous, Philippe Lenca, Christophe Lemey, Christophe Lemey

“…The Synthetic Minority Oversampling Technique was used to handle imbalanced data, and the SHapley Additive exPlanations (SHAP) values were computed to measure feature importance and each feature’s contributions to the classification.ResultsThe model yielded good performance, that is, 0.82 accuracy, 0.82 F2-score, 0.85 precision, 0.82 recall, and 0.86 ROC–AUC score, with four linguistic variables that concern weak coherence, the use of “I,” and filled pauses.DiscussionThe findings in this study suggest that weak coherence play a key role in classification. …”
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Characterizing low femoral neck BMD in Qatar Biobank participants using machine learning models by Nedhal Al-Husaini, Rozaimi Razali, Amal Al-Haidose, Mohammed Al-Hamdani, Atiyeh M. Abdallah

“…Logistic regression algorithms were implemented to predict femoral neck BMD, and the area under the curve (AUC) was used to evaluate model performance. Features associated with low femoral neck BMD were subjected the statistical analysis to establish associated risk. …”
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Adaptability Study of an Unmanned Aerial Vehicle Actuator Fault Detection Model for Different Task Scenarios by Lulu Wang, Yuehua Cheng, Bin Jiang, Yanhua Zhang, Jiajian Zhu, Xiaoyang Tan

“…To validate the proposed model, we conducted flight experiments, demonstrating its superior performance in actuator fault detection compared to conventional deep learning methods. …”
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A Mental Workload Evaluation Model Based on Improved Multibranch LSTM Network with Attention Mechanism by Hongning Zhang

“…This model introduces an attention mechanism based on the classic LSTM network, which can screen the features differently, not only improving the utilization of effective information but also reducing calculation parameters and simplifying the model. …”
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Forecasting the number of rural migrant workers in Chongqing using the optimized grey N_Verhulst model by Dai Liu, Chengxiang He, Jianlong Ma

“…Based on the evolutionary patterns and data features of Chongqing’s migrant workers, a new grey prediction model is constructed. …”
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Matching dynamically varying forces with multi-motor-unit muscle models: a simulation study by T. Murtola, C. Richards

“…To investigate how these features affect a muscle’s ability to generate desired force profiles, we performed simulations with nine alternative MU pool models for two cases: (i) a tibialis anterior muscle generating an isometric trapezoidal force profile, and (ii) a generic shoulder muscle generating force for a reaching movement whilst undergoing predetermined length changes. …”
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Intelligent Fruit Localization and Grasping Method Based on YOLO VX Model and 3D Vision by Zhimin Mei, Yifan Li, Rongbo Zhu, Shucai Wang

“…Comprehensive comparative experiments between the improved YOLO v12n model and earlier versions were conducted to validate its performance. …”
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Grid-Forming Buck-Type Current-Source Inverter Using Hybrid Model-Predictive Control by Gianni Avilan-Losee, Hang Gao

“…In the following study, GFM control is instead applied to a buck-type current-source inverter (CSI) using a combination of linear droop-control and finite-control-set (FCS) mode-predictive control (MPC) that will be referred to herein as hybrid model-predictive control (HMPC). The resulting inverter features a simple topology, inherent current limiting capabilities, and a relatively simple and intuitive control structure. …”
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Real-Time Adaptive Traffic Flow Prediction Based on a GE-GRU-KNN Model by Xiangyu YI, Hongmei ZHOU, Shaopeng ZHONG

“…The results show that compared with traditional methods, the prediction error of this method is reduced by 1.08%–14.71%, indicating that the hybrid GE-GRU-KNN model exhibits good performance.…”
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Data-Driven Estimation Models for Chloride Ion Diffusion Coefficient in Concrete Using Bayesian Approach by Ruifu Cui, Huihui Yang, Jiehong Li, Honghui Tang, Guowen Yao, Yang Yu, Xuanrui Yu

“…Although various models have been proposed to estimate chloride diffusivity, many empirical models remain unavailable due to database limitations or the oversight of certain factors. …”
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A deep classification model to assess environment following hazards using remote sensing images by Madhusmita Sahu, Rasmita Dash

“…Additionally, an independent T-test is performed to statistically validate the performance improvements over comparative models. …”
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