Formation of a heterogeneous group of UAVS with a reasonable number of false and real drones by Volodymyr Prymirenko, Andrii Demianiuk, Roman Shevtsov, Serhii Bazilo, Andrey Pilipenko, Mykola Vovchanskyi

“…The availability of the developed mathematical model, algorithm, and program code makes it possible to predict the possible results of the combat use of heterogeneous groups of UAVs based on the initial parameters and to substantiate recommendations for a possible composition of such groups.…”
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SECONDGRAM: Self-conditioned diffusion with gradient manipulation for longitudinal MRI imputation by Brandon Theodorou, Anant Dadu, Mike Nalls, Faraz Faghri, Jimeng Sun

“…These models are computer algorithms that simulate how information changes. SECONDGRAM addresses data scarcity by generating realistic follow-up MRI imaging features, thereby enriching limited datasets. …”
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A Mitochondria‐Related Signature in Diffuse Large B‐Cell Lymphoma: Prognosis, Immune and Therapeutic Features by Zhen‐Zhong Zhou, Jia‐Chen Lu, Song‐Bin Guo, Xiao‐Peng Tian, Hai‐Long Li, Hui Zhou, Wei‐Juan Huang

“…Conclusions We established a novel prognostic mitochondria‐related signature by machine learning algorithm, which also demonstrated outstanding predictive value in tumor microenvironment and responses to therapies.…”
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Estimating Winter Canola Aboveground Biomass from Hyperspectral Images Using Narrowband Spectra-Texture Features and Machine Learning by Xia Liu, Ruiqi Du, Youzhen Xiang, Junying Chen, Fucang Zhang, Hongzhao Shi, Zijun Tang, Xin Wang

“…Subsequently, machine learning algorithms were applied to develop estimation models for winter canola biomass. …”
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Factors influencing the response to periodontal therapy in patients with diabetes: post hoc analysis of a randomized clinical trial using machine learning by Nidia CASTRO DOS SANTOS, Arthur MANGUSSI, Tiago RIBEIRO, Rafael Nascimento de Brito SILVA, Mauro Pedrine SANTAMARIA, Magda FERES, Thomas VAN DYKE, Ana Carolina LORENA

“…We tested seven different algorithms: K-Nearest Neighbors, Decision Tree, Support Vector Machine, Random Forest, Extreme Gradient Boosting, and Logistic Regression. …”
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Developing a Sleep Algxorithm to Support a Digital Medicine System: Noninterventional, Observational Sleep Study by Jeffrey M Cochran

“…ACC and ECG features were derived for each 5-minute window. The algorithm that most accurately predicted sleep parameters against PSG data was compared to commercially available wearable devices to further benchmark model performance. …”
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Classification and Comparison of Eight Different Growth Curve Methods for Pekin Duck by Hasan Önder, Mine Yılmaz, Mustafa Şahin, Uğur Şen, Sibel Bozkurt, Kadir Erensoy, İsmail Gök, Tolga Tolun, Ahmet Uçar

“…These models can be used for predicting body weight for a specific age from a dimensional perspective. …”
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Covariate Model Selection Approaches for Population Pharmacokinetics: A Systematic Review of Existing Methods, From SCM to AI by Mélanie Karlsen, Sonia Khier, David Fabre, David Marchionni, Jérôme Azé, Sandra Bringay, Pascal Poncelet, Elisa Calvier

“…AALASSO, a hybrid genetic algorithm, FREM with a clinical significance criterion and SCM+ with stagewise filtering were the best covariate model selection techniques—AALASSO being the very best one. …”
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Eagle-YOLOv8: UAV Object Detection Inspired by the Eagle-Eye Vision System by Dianwei Wang, Zehao Gao, Jie Fang, Yuanqing Li, Zhijie Xu

“…Confronting such challenges, we propose Eagle-YOLOv8, an object detection algorithm for UAV imagery inspired by the eagle-eye vision system. …”
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Spatiotemporal Analysis of Soil Moisture Variability and Precipitation Response Across Soil Texture Classes in East Kazakhstan by Dmitry Chernykh, Roman Biryukov, Andrey Bondarovich, Lilia Lubenets, Anatoly Pavlenko, Kamilla Rakhymbek, Denis Revenko, Zheniskul Zhantassova

“…The study of the hydrological regimes of rivers in different regions of the globe has revealed the need to include the soil moisture content in flood prediction models. This paper investigates the nature of the dependence of soil moisture content on soil texture in the East Kazakhstan region. …”
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Pilot Protection of New Energy Transmission Line in Active Distribution Network Based on 5G Communication by Tiecheng LI, Hui FAN, Weiming ZHANG, Xianzhi WANG, Yihong ZHANG, Zhihui DAI

“…Traditional pilot differential protection will have the problem of reliability reduction or even failure to operate after the access of new energy stations. …”
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Automating attendance management in human resources: A design science approach using computer vision and facial recognition by Bao-Thien Nguyen-Tat, Minh-Quoc Bui, Vuong M. Ngo

“…Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. …”
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Insights from UKCTOCS for design, conduct and analyses of large randomised controlled trials by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Sophia Apostolidou, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Anne Dawnay, Mahesh Parmar, Ian J Jacobs

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Online variational Gaussian process for time series data by Weidong Wang, Mian Muhammad Yasir Khalil, Leta Yobsan Bayisa

“…In this paper, we propose the OnLine Variational Gaussian Process (OLVGP) algorithm, which introduces a novel approach for dynamically managing the number of inducing points based on the concept of eigenfunction inducing features. …”
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Improved simulation of thunderstorm characteristics and polarimetric signatures with LIMA two-moment microphysics in AROME by C. David, C. Augros, B. Vié, F. Bouttier, T. Le Bastard

“…<p>Thunderstorm forecasting remains challenging despite advances in numerical weather prediction (NWP) systems. The microphysics scheme that represents clouds in the model partly contributes to the introduction of uncertainties in the simulations. …”
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AI-Assisted Detection for Early Screening of Acute Myeloid Leukemia Using Infrared Spectra and Clinical Biochemical Reports of Blood by Chuan Zhang, Jialun Li, Wenda Luo, Sailing He

“…Subsequently, these vectors were assessed using a linear discriminant analysis (LDA) algorithm to estimate the likelihood of acute myeloid leukemia. …”
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Uncertainty Impact on Aggregator Performance for Peak Shaving by Ismail Arafat, Eduardo Castillo Guerra, Julian Meng

“…Accurate peak period forecasting and load consumption profile prediction are critical for utility resource planning and emergency response preparedness. …”
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A Two-Stage Deep Learning Method for Marine Oil Spill Localization and Segmentation From Synthetic Aperture Radar Images by Xudong Huang, Biao Zhang, William Perrie

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Rapid and Non-destructive Detection of Rice Protein Content Based on Near Infrared Spectroscopy by Siping TAN, Jicheng YUE, Ying CHEN, Cuihong HUANG, Danhua ZHOU, Huijuan ZHANG, Guili YANG, Hui WANG

“…Based on near infrared spectroscopy (NIRS), four pretreatment methods were used: first-order smooth derivative (SG1), second-order smooth derivative (SG2), standard normal variable (SNV) and detrend algorithm (Detrend). The near infrared detection model of rice protein contents in rice, brown rice and milled rice were established by using partial least square (PLS) method.…”
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Non-Destructive Detection and Visualization of Chlorophyll Content in Cherry Tomatoes Based on Hyperspectral Technology and Machine Learning by Peng Huang, Pan Yang, Libiao Yang, Futong Xiao, Yanqi Feng, Yuchao Wang

“…Firstly, Moving-Average (MA) preprocessing was chosen as the pretreatment method for this paper, and three regression models of principal component regression (PCR), random forest (RF), and partial least squares regression (PLSR) were established with leaf chlorophyll under different nitrogen concentrations. The CARS_PLSR algorithm has the highest prediction accuracy with accuracy, precision, RMSEC, and RMSEP of 0.8790, 0.9187, 2.9581, and 2.5578, respectively. …”
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