Classification of mammograms: Comparing a graphical to a geometrical approach by Anirban Ghosh, Priya Ranjan, Kumar Dron Shrivastav, Rajiv Janardhanan

“…In this scenario, the large-scale deployment of computer-aided diagnosis using well-trained algorithms could significantly reduce the morbidity and mortality associated with this carcinoma. …”
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Advanced Deep Learning and Machine Learning Techniques for MRI Brain Tumor Analysis: A Review by Rim Missaoui, Wided Hechkel, Wajdi Saadaoui, Abdelhamid Helali, Marco Leo

“…In this study, we focus on current advances in medical imaging, particularly magnetic resonance imaging (MRI), and how machine learning (ML) and deep learning (DL) algorithms might be combined with clinical assessments to improve brain tumor diagnosis. …”
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Nuevos modelos para la Caracterización, Detección y Diagnóstico de Fallas en Máquinas Eléctricas Rotativas by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Therefore, modern techniques based on machine learning offer significant improvements in fault detection and prediction, allowing the identification of complex patterns and more precise diagnoses, expanding the capabilities of conventional approaches to facilitate predictive maintenance. …”
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Do Machine Learning and Business Analytics Approaches Answer the Question of ‘Will Your Kickstarter Project be Successful? by Murat Kılınç, Can Aydın, Çiğdem Tarhan

“…Within the scope of machine learning, various algorithms were applied for success classification and the best results were given by 91% Random Forest, 85% Decision Tree, 84% K-Nearest Neighbors (KNN) algorithms. …”
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Processing of Polymers Stress Relaxation Curves Using Machine Learning Methods by Anton S. Chepurnenko, Tatiana N. Kondratieva, Ebrahim Al-Wali

“…The maximum value of model error predictions was 0.86 for the MAPE metric, and the minimum value of model error predictions was 0.001 for the MSE metric. …”
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Integrated multiomics analysis and machine learning refine neutrophil extracellular trap-related molecular subtypes and prognostic models for acute myeloid leukemia by Fangmin Zhong, Fangyi Yao, Zihao Wang, Jing Liu, Bo Huang, Xiaozhong Wang

“…Additionally, patients with a high risk score were also predicted to exhibit a favorable response to anti-PD-1 therapy, suggesting that these individuals may derive greater benefits from immunotherapy.ConclusionThe NET-related signature, derived from a combination of diverse machine learning algorithms, has promising potential as a valuable tool for prognostic prediction, preventive measures, and personalized medicine in patients with AML.…”
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Non-Destructive Detection of External Defects in Potatoes Using Hyperspectral Imaging and Machine Learning by Ping Zhao, Xiaojian Wang, Qing Zhao, Qingbing Xu, Yiru Sun, Xiaofeng Ning

“…Firstly, Savitzky–Golay (SG), standard normal variate transformation (SNV), multiplicative scatter correction (MSC), the normalization algorithm, and different preprocessing algorithms combined with SG were used to preprocess the hyperspectral data. …”
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NEURAL NETWORK FORECASTING OF ENERGY CONSUMPTION OF A METALLURGICAL ENTERPRISE by Anna Bakurova, Olesia Yuskiv, Dima Shyrokorad, Anton Riabenko, Elina Tereschenko

“…The LSTM network turned out to be the most effective among the considered neural networks, for which the indicator of the maximum prediction error had the minimum value. Conclusions: analysis of forecasting results using the developed models showed that the chosen approach with experimentally selected architectures and learning algorithms meets the necessary requirements for forecast accuracy when developing a forecasting model based on artificial neural networks. …”
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A novel mechanism-guided residual network for accurate modelling of scroll expander under noisy and sparse data conditions by Xiaoshuang Lv, Xin Ma, Wei Peng, Ke Li, Chengdong Li

“…Finally, comparative prediction experiments are carried out to validate the proposed MGResNet. …”
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Elbow Joint Angle Estimation Using a Low-Cost and Low-Power Single Inertial Device for Daily Home-Based Self-Rehabilitation by Manon Fourniol, Rémy Vauché, Guillaume Rao, Eric Watelain, Edith Kussener

“…Moreover, its power consumption can be reduced by more than the increase in the error when reducing the rate of the data output by the sensor. In this work, a reduction in the data rate from 100 Hz to 10 Hz increased the RMSE by a factor of 1.8 but could reduce the power consumption associated with the sensor and the algorithm’s computation by a factor of 10. …”
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A novel bias-alleviated hybrid ensemble model based on over-sampling and post-processing for fair classification by Fang He, Xiaoxia Wu, Wenyu Zhang, Xiaoling Huang

“…Three datasets with different sensitive attributes and four evaluation metrics were used to evaluate the prediction accuracy and fairness of the BAHEM. The experimental results verify the superior fairness of the BAHEM with little accuracy reduction.…”
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Advancements in Intelligent Sensing Technologies for Food Safety Detection by Wenhui Jiang, Changhong Liu, Wei Liu, Lei Zheng

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Multi-function supported privacy protection data aggregation scheme for V2G network by Baiji HU, Xiaojuan ZHANG, Yuancheng LI, Rongxin LAI

“…In view of the problem that the functions of the current privacy protection data aggregation scheme were insufficient to meet the increasingly rich application requirements, a multi-function supported privacy protection data aggregation (MFPDA) scheme for V2G network was proposed.By using cryptographic algorithms such as BGN, BLS, and Shamir’s secret sharing, as well as fog computing and consortium blockchain technology, multiple security functions like fault tolerance, resistance to internal attacks, batch signature verification, no need for trusted third parties, and multiple aggregation functions were integrated into one privacy protection data aggregation scheme.Security analysis shows that the proposed scheme can protect data aggregation’s security, privacy and reliability.The performance evaluation shows that the introduction of fog computing can significantly reduce the computing overhead of the control center, and the reduction rate can be as high as 66.6%; the improvement of the consortium blockchain can effectively reduce the communication and storage overhead of the system, and the reduction rate can reach 16.7% and 24.9% respectively.…”
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Energy-Efficient Scheduling for Resilient Container-Supply Hybrid Flow Shops Under Transportation Constraints and Stochastic Arrivals by Huaixia Shi, Huaqiang Si, Jiyun Qin

“…Moreover, it achieves about an 8% reduction in energy consumption compared to traditional algorithms. …”
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Modeling pine forest growing stock volume in subtropical regions of China using airborne Lidar data by Zige Lan, Xiandie Jiang, Guiying Li, Yagang Lu, Hongwen Yao, Dengsheng Lu

“…When combining PPF and MXF together to develop GSV models, HBA(Site/Type) with double stratification factors (i.e. typical site and forest type) showed similar performance, with only a minor reduction in RMSE by 0.45 m3/ha for PPF and 0.15 m3/ha for MXF. …”
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Optimization of engine parameters and emission profiles through bio-additives: Insights from ANFIS Modeling of Diesel Combustion by Abbas Rohani, Javad Zareei, Kourosh Ghadamkheir, Seyed Alireza Farkhondeh

“…Various machine learning configurations and training algorithms were employed to optimize the model's performance. …”
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Intelligent Integration Method of AI English Teaching Resource Information under Multi-Agent Collaboration by Minjuan Liu

“…In order to improve the intelligent effect of English teaching in the era of intelligent education, this article conducts an intelligent integration system of AI English teaching resources and information on the basis of multi-agent collaboration. …”
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LH-YOLO: A Lightweight and High-Precision SAR Ship Detection Model Based on the Improved YOLOv8n by Qi Cao, Hang Chen, Shang Wang, Yongqiang Wang, Haisheng Fu, Zhenjiao Chen, Feng Liang

“…However, detecting multi-scale ship targets in complex backgrounds leads to issues of false positives and missed detections, posing challenges for lightweight and high-precision algorithms. There is an urgent need to improve accuracy of algorithms and their deployability. …”
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Hyperspectral Detection of Pesticide Residues in Black Vegetable Based on Multi-Classifier Entropy Weight Method by Rongchang Jiang, Guoqiang Zhuang, Shijie Xie, Yang Wang, Guoqi Zhang, Dandan Qu, Wanzhi Wen

“…Three dimensionality reduction techniques, competitive adaptive reweighted sampling, random frog leaping, and successive projections algorithm, were compared. …”
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Analysis of Brand Communication Influence of Professional Sports Clubs Based on Complex System Discrete Model by Hui Zhang

“…In recent years, because the complex system discrete model has brought good results in the application of many research directions such as human management analysis, control system prediction, and animal group prediction, how to combine the complex system discrete model with the prediction of enterprise brand communication effect has become a current research hotspot. …”
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