Sparse wavelet decomposition in problems of vibration-based diagnostics of rotary equipment by Y. P. Aslamov, A. P. Aslamov, I. G. Davydov, A. V. Borsuk

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IDENTIFICATION OF TRAJECTORY INFORMATION BY APPLYING FUZZY AUTOMATIC CLASSIFICATION IN THE INFORMATION ASSOCIATION PROBLEM by A. V. Khizhniak, A. A. Belous, A. S. Bely

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Comparison of tone mapping methods during images processing on liquid crystal displays by A. V. Sycev, A. A. Stepanov, A. G. Smirnov, K. .. Blankenbach

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The value of machine learning based on spectral CT quantitative parameters in the distinguishing benign from malignant thyroid micro-nodules by Zuhua Song, Qian Liu, Jie Huang, Dan Zhang, Jiayi Yu, Bi Zhou, Jiang Ma, Ya Zou, Yuwei Chen, Zhuoyue Tang

“…Recursive feature elimination was employed for variable selection. Three ML algorithms—support vector machine (SVM), logistic regression (LR), and naive Bayes (NB)—were implemented to construct predictive models. …”
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Anomaly Detection Method for Hydropower Units Based on KSQDC-ADEAD Under Complex Operating Conditions by Tongqiang Yi, Xiaowu Zhao, Yongjie Shi, Xiangnan Jing, Wenyang Lei, Jiang Guo, Yang Meng, Zhengyu Zhang

“…This paper proposes a hydropower unit anomaly detection method based on K-means seeded quadratic discriminant clustering and an adaptive density-aware ensemble anomaly detection algorithm (KSQDC-ADEAD). The method first employs the KSQDC algorithm to identify different operating conditions of hydropower units. …”
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A digital twin-enabled fog-edge-assisted IoAT framework for Oryza Sativa disease identification and classification by Goluguri N.V. Rajareddy, Kaushik Mishra, Satish Kumar Satti, Gurpreet Singh Chhabra, Kshira Sagar Sahoo, Amir H. Gandomi

“…To boost the model's predictive accuracy, the Chaotic Honey Badger Algorithm (CHBA) is employed to optimize the CNN hyperparameters, resulting in an impressive average accuracy of 93.5 %. …”
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Machine learning based on pangenome-wide association studies reveals the impact of host source on the zoonotic potential of closely related bacterial pathogens by Cheng Han, Shiying Lu, Pan Hu, Jiang Chang, Deying Zou, Feng Li, Yansong Li, Qiang Lu, Honglin Ren

“…Integrating these genes into an ML model based on the support vector machine (SVM) algorithm allows us to predict the zoonotic potential of various Brucella strains with high accuracy. …”
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Non-invasive detection of Parkinson’s disease based on speech analysis and interpretable machine learning by Huanqing Xu, Wei Xie, Mingzhen Pang, Ya Li, Luhua Jin, Fangliang Huang, Xian Shao

“…SHAp values highlighted the importance of fundamental frequency variation and harmonic-to-noise ratio in distinguishing PD patients from healthy individuals.ConclusionThe developed machine learning model accurately predicts Parkinson’s disease using speech recordings, with Random Forest and Gradient Boosting algorithms demonstrating superior performance. …”
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Artificial Intelligence Empowers Solid-State Batteries for Material Screening and Performance Evaluation by Sheng Wang, Jincheng Liu, Xiaopan Song, Huajian Xu, Yang Gu, Junyu Fan, Bin Sun, Linwei Yu

“…The achievements of various ML algorithms in predicting different performances of the battery management system are discussed. …”
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A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN by S. Ambareesh, Pundalik Chavan, S. Supreeth, Rajesh Nandalike, P. Dayananda, S. Rohith

“…To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA). This modern framework employs weighted ensemble clustering and matched ensemble choice techniques, facilitating strong cluster formation and resulting in a substantial 98% development in community lifetime, an 80% enhancement in packet delivery ratio (PDR), and a 45% reduction in average power consumption while as compared to current protocols. …”
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A Novel Dynamic Weight Neural Network Ensemble Model by Kewen Li, Wenying Liu, Kang Zhao, Mingwen Shao, Lu Liu

“…The paper proposes a novel dynamic weight neural network ensemble model (DW-NNE). The Bagging algorithm generates certain neural network individuals which then are selected by the K -means clustering algorithm. …”
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Heart failure and atrial fibrillation: updates and perspectives by V. N. Larina, I. K. Skiba, A. S. Skiba, V. G. Larin, E. A. Vartanyan

“…The article discusses modern approaches and features of management, as well as predicting the risk of complications in patients with cardiac arrhythmias, in particular, atrial fibrillation, and the potential of using conservative and interventional treatment methods for heart failure (HF), taking into account updates and achievements in clinical practice. …”
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Differential diagnosis of hematogenous osteomyelitis and malignant bone tumors by A. N. Tkachenko, O. F. Nur, A. A. Korneenkov, L. E. Sharova, I. E. Itskovich, I. I. Kushnirchuk, A. Yu. Cherkasov

“…Indicators of the validity of the test was: Sensitivity – 83.05 %, Specificity (Sp) – 86.67 %. Positive Predictive Value (PPV) was 96.08 %, Negative Predictive Value (NPV) – 56.52 %, Accuracy – 83.78 %, which allowed to shorten the time of examination and send patients to specialized hospitals.…”
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Optimal fusion β-quaternion filtering from delayed observations and packet losses with compensation strategy under properness by J. D. Jiménez-López, R. M. Fernández-Alcalá, F. Gutiérrez-Trujillo, E. Grassucci, D. Comminiello

“…A numerical example is presented to illustrate, among other aspects, the substantial reduction in computational time achieved by the proposed algorithm, as well as its superior estimation accuracy compared to conventional quaternion processing methods.…”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…Thermal comfort analysis through Predicted Mean Vote (PMV) and Predicted Percentage of Dissatisfied (PPD) metrics showed better indoor conditions, with the hybrid model keeping room temperatures within ±0.8 °C of the setpoint and bringing the PPD index down to 8.5 %. …”
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Idiopathic Intrahepatic Cholestasis as an Unusual Presentation of Hodgkin’s Disease by Hande Atalay, Banu Boyuk, Muhammet Ates, Aslan Celebi, Ismail Ekizoglu, Arzu A. Didik, Aysenur A. Igdem

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Computational design exploration of rocket nozzle using deep reinforcement learning by Aagashram Neelakandan, Arockia Selvakumar Arockia Doss, Natrayan Lakshmaiya

“…The DRL-generated nozzles achieve a 10.5 % reduction in surface area and an 11.8 % reduction in volume compared to analytically designed minimum-length nozzles (MLNs), while maintaining similar Mach numbers at the outlet. …”
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Application of Wireless Sensor Networks for Indoor Temperature Regulation by Biljana Risteska Stojkoska, Andrijana Popovska Avramova, Periklis Chatzimisios

“…In this paper we focus on a system used for temperature regulation for residential, educational, industrial, and commercial premises, and so forth. …”
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Subgrouping suicidal ideations: an ecological momentary assessment study in psychiatric inpatients by Stephanie Homan, Zachary Roman, Anja Ries, Prabhakaran Santhanam, Sofia Michel, Anna-Marie Bertram, Nina Klee, Carlo Berther, Sarina Blaser, Marion Gabi, Philipp Homan, Hanne Scheerer, Michael Colla, Stefan Vetter, Sebastian Olbrich, Erich Seifritz, Isaac Galatzer-Levy, Tobias Kowatsch, Urte Scholz, Birgit Kleim

“…Abstract Background Suicidal ideation (SI) is one of the strongest predictors of suicide attempts, yet reliable prediction models for suicide risk remain scarce. A key challenge is that SI can fluctuate over time, potentially reflecting different subgroups that may offer important insights for suicide risk prediction. …”
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Frequency-constrained optimal power-gas flow with fast frequency response from power-to-gas units by Yu Liang, Xia Zhao

“…The substantial increase in renewable energy integration has resulted in a reduction in inertia and frequency regulation resources within the power system. …”
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