A Low-Discrepancy and Latency-Aware, Scenario-Sensitive Resource Allocation Approach for Cloud Systems Using Latin Square-Based Improvised Genetic Optimization (LSBGO) by Aman Kumar Routh, Prabhat Ranjan, Asisa Kumar Panigrahy

“…Hence, the core problem is how to place tasks while ensuring that no virtual machine begins its execution overloaded with work, and how to adjust this placement on the fly as demand, failures, and scale changes occur. …”
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SPPMFN: Efficient Multimodal Financial Time-Series Prediction Network With Self-Supervised Learning by Ningxin Li, Gang Chao, Jianke Zou, Gaozhe Jiang

“…Additionally, the limited parameters of one-dimensional financial time series signals constrain feature representation. …”
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Formation permeability estimation using mud loss data by deep learning by Yaser Abdollahfard, Seyed Morteza Mirabbasi, Mohammad Ahmadi, Abdolhossein Hemmati-Sarapardeh, Sefatallah Ashoorian

“…This study focuses on a novel method to estimate the formation’s permeability with appropriate accuracy using the mud loss data. Machine learning applications are becoming more popular nowadays and can succeed in many fields. …”
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Combining artificial intelligence assisted image segmentation and ultrasound based radiomics for the prediction of carotid plaque stability by Jiajia Song, Liwen Zou, Yu Li, Xiaoyin Wang, Junlan Qiu, Kailin Gong

“…Subsequently, a Support Vector Machine (SVM) model was constructed and validated using the selected features. …”
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Effects of Disbudding, Re-Cutting and Wounding in Grafted Grapevine Sapling Production by Rüstem Cangi, Gözde Öncel Deveci

“…Scions of Royal cultivar were grafted on 5BB,1613 Couderc and 140 Ruggeri rootstocks by omega grafting machine. Grafted cuttings were planted and grown in plastic pots in a greenhouse. …”
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Changes in biomechanical properties of the cornea after modified transepithelial crosslinking by I. B. Medvedev, V. Ju. Evgrafov, S. N. Bagrov, R. S. Kemov, N. N. Dergacheva

“…After 1 month the euthanasia of the animals was performed with subsequent enucleation for corneal research on a tensile testing machine. In the control and experimental group compared, the relaxation curves and the following parameters were analyzed: initial stress (MPa), equilibrium stress (MPa) modulus of elasticity.Results and their discussion. …”
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Sparse coding-based multiframe superresolution for efficient synchrotron radiation microspectroscopy by Yasuhiko Igarashi, Naoka Nagamura, Masahiro Sekine, Hirokazu Fukidome, Hideitsu Hino, Masato Okada

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Intelligent ESG portfolio optimization: A multi-objective AI-driven framework for sustainable investments in the Indian stock market by Apurv Gaurav, Kripamay Baishnab, Piyush Kumar Singh

“…For predictive modeling, MBi-LSTM showed the lowest errors in all the parameters. The NSG-enabled portfolio allocation method achieved 68.58 % higher similarity to actual returns than the Mean-Variance Markowitz (MVM) model while maximizing the ESG-Sortino Ratio. …”
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Preparation and hot compression deformation of biomedical Ni-Ti alloy by WANG Zhen, XU Xiao-wen, WANG Kuai-she, WANG Wen

“…This study provides a theoretical and data basis for the development of forging process parameters of Ni-Ti alloy.…”
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Three-Dimensional Reconstruction, Phenotypic Traits Extraction, and Yield Estimation of Shiitake Mushrooms Based on Structure from Motion and Multi-View Stereo by Xingmei Xu, Jiayuan Li, Jing Zhou, Puyu Feng, Helong Yu, Yuntao Ma

“…The computed phenotype correlated strongly with manual measurements, yielding <i>R</i>² > 0.8 and <i>nRMSE</i> < 0.09 for the pileus transverse and longitudinal diameters, <i>R</i>² = 0.53 and <i>RMSE</i> = 3.26 mm for the pileus height, <i>R</i>² = 0.79 and <i>nRMSE</i> = 0.12 for stipe diameter, and <i>R</i>² = 0.65 and RMSE = 4.98 mm for the stipe height. Using these parameters, yield estimation was performed using PLSR, SVR, RF, and GRNN machine learning models, with GRNN demonstrating superior performance (<i>R</i>² = 0.91). …”
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The Improved-EFI Score: A Multi-Omics-Based Novel Efficacy Predictive Tool for Predicting the Natural Fertility of Endometriosis Patients by He Q, Zhang C, Hu Y, Deng J, Zhang S

“…An improved endometriosis fertility index (EFI) predictive model was created based on ultrasound radiomics and urinary proteomics gathered during the patient’s initial admission, using two machine learning algorithms. The predictive model was evaluated for C-index, calibration, and clinical applicability through receiver working characteristic curve, decision curve analysis.Results: The improved EFI prediction model nomogram, based on five ultrasound radiomics parameters and three urine proteomics, had AUC values of 0.921 (95% CI: 0.864– 0.978) and 0.909 (95% CI: 0.852– 0.966) in the training and validation sets, respectively, while the traditional EFI prediction model had AUC values of 0.889 (95% CI: 0.832– 0.946) and 0.873 (95% CI: 0.816– 0.930) in the training and validation sets, respectively. …”
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A human behavior-based model for respiratory infectious diseases prediction by Zhengwen Ma, Min Zhu, Chen Zhi, Huaguo Zhang, Minye Li, Nan Zhang, Hui Ma, Hui Ma

“…ObjectivesThe research aims to develop a human behavior-based model to predict respiratory infectious diseases.MethodsThis research employs semi-supervised machine learning techniques in conjunction with an RGB-depth camera to collect micro-level data. …”
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The influence of nano-additives on the technical properties of drilling mud for drilling and well reconstruction by A.Y. Abusal Yousef, Irina A. Chetvertneva, Rustem A. Ismakov, Artur R. Yakhin, Marianna E. Loginova

“…The influence of additives on general technological parameters of Clay-Free Drilling Mud (CFDM) was evaluated. …”
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Diurnal Variations of Infrared Land Surface Emissivity in the Taklimakan Desert: An Observational Analysis by Yufen Ma, Kang Zeng, Ailiyaer Aihaiti, Junjian Liu, Zonghui Liu, Ali Mamtimin

“…Future research should focus on multi-angle observation experiments and the exploration of machine learning’s potential in cross-scale emissivity modeling.…”
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Diagnostic accuracy of wearable ECG and assessment of ventricular repolarization and its cardiovascular risks post cold stress by Renzheng Chen, Fengbo Miao, Yujia Wang, Tingting Lu, Cheng Qin, Yan Fang, Yabin Wang, Huiquan Wang, Feng Cao

“…The results from testing under an outdoor cold environment indicated that the parameters of the ECG measured by the wearable device were in good agreement with those measured by the conventional machine. …”
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Quick-Delivery Mold Fabricated via Stereolithography to Enhance Manufacturing Efficiency by Jae Hyang Lee, Seonghwan Park, Jeon Taik Lim, Hyung Sun Yoon, Jae Won Choi, Cheol Woo Ha, Jiyong Park

“…In addition, the SLA mold was assembled into an injection machine, and an injection molding test was conducted. …”
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Effects of Different Titanium Anodized Surfaces on Peri-Implant Soft Tissue Healing Around Dental Abutments: In Vitro and Proteomic Study by Francisco Romero-Gavilán, Andreia Cerqueira, Carlos Arias-Mainer, David Peñarrocha-Oltra, Claudia Salavert-Martínez, Juan Carlos Bernabeu-Mira, Iñaki García-Arnáez, Félix Elortza, Mariló Gurruchaga, Isabel Goñi, Julio Suay

“…Results: The anodization process resulted in a reduction in the surface roughness parameter (Ra) relative to the machined titanium (<i>p</i> < 0.05). …”
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Autonomous Drilling and the Idea of Next-Generation Deep Mineral Exploration by George Nikolakopoulos, Anton Koval, Matteo Fumagalli, Martyna Konieczna-Fuławka, Laura Santas Moreu, Victor Vigara-Puche, Kashish Verma, Bob de Waard, René Deutsch

“…The shift toward machine automation involves transitioning from human-operated machines to systems powered by artificial intelligence, which are capable of making real-time decisions. …”
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Calculation and Experimental Study of the Dynamics of the Track Mover Bypass of a Cross-Country Transport Vehicle by Alexey I. Taratorkin, Sergey V. Abdulov, Viktor B. Derzhanskii, Alexandr A. Volkov, Evgeniy B. Sarach, Alexandr I. Komissarov

“…The substantiation of the technical solution option for the problem is given, installation of a free branch damper, and the results of determining the numerical parameters of its dynamic loading in relation to the object of study, a cross-country tracked transport vehicle. …”
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Multi-component attention graph convolutional neural network for QoS-aware cloud job scheduling and resource management enhancing efficiency and performance in cloud computing by Deepak Dharrao, Sarika Deokate, Nagamma Hudgi, Shrinivas Shirkande, Vinod Mahajan, Madhuri Pangavhane, Anupkumar Bongale

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