Predicting Relative Density of Pure Magnesium Parts Produced by Laser Powder Bed Fusion Using XGBoost by Kristijan Šket, Snehashis Pal, Janez Gotlih, Mirko Ficko, Igor Drstvenšek

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Volcano-Seismic Event Detection and Clustering by Joe Carthy, Pablo Rey-Devesa, Manuel Titos, Carmen Benitez

“…Due to the resource intensive labeling process required to understand volcano-seismic signals it is important to explore unsupervised analysis techniques in this domain. …”
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Evaluating species richness, turnover, and range shifts under climate change for fluvial fishes in Northeastern and Midwestern USA by Hao Yu, Dana M. Infante, Arthur R. Cooper, Jared A. Ross

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Optimizing control strategies for DC-DC boost converters: Real-time application of an adaptive gain scheduled ISA-PI controller with hybrid state-space and linear parameter-varying... by Cağfer Yanarateş

“…This paper introduces an innovative sophisticated control scheme for a DC-DC boost converter (DCBC), employing an adaptive gain scheduled ISA-PI controller. …”
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A 60 GHz Class-C Wide Tuning-Range Two-Core VCO Utilizing a Gain-Boosting Frequency Doubling Technique and an Adaptive Bias Scheme for Robust Startup by Ioannis Dimitrios Psycharis, Vasileios Tsourtis, Grigorios Kalivas

“…The proposed architecture consists of a two-core 30 GHz fundamental VCO, a gain-boosted frequency doubler and an adaptive bias configuration. …”
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Investigation of Micro-Scale Damage and Weakening Mechanisms in Rocks Induced by Microwave Radiation and Their Associated Strength Reduction Patterns: Employing Meta-Heuristic Opti... by Zhongyuan Gu, Xin Xiong, Chengye Yang, Miaocong Cao

“…Utilizing the Pied Kingfisher Optimizer (PKO) alongside Extreme Gradient Boosting (XGBoost), we developed a PKO-XGBoost machine learning model to elucidate the relationship between UCSA and the nine additional parameters. …”
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ZO-1 boosts the in vitro self-renewal of pre-haematopoietic stem cells from OCT4-reprogrammed human hair follicle mesenchymal stem cells through cytoskeleton remodeling by Yingchun Ruan, Xingang Huang, Pengpeng Sun, Xiaozhen Yu, Xiaohua Tan, Yaolin Song, Hua Chen, Zhijing Liu

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State of Health Estimation for Lithium-Ion Batteries Using an Explainable XGBoost Model with Parameter Optimization by Zhenghao Xiao, Bo Jiang, Jiangong Zhu, Xuezhe Wei, Haifeng Dai

“…This paper investigates an adaptive and explainable battery SOH estimation approach using the eXtreme Gradient Boosting (XGBoost) model. First, several battery health features extracted from various charging and relaxation processes are identified, and their correlation with battery aging is analyzed. …”
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Deep Learning-Based Image Processing for Cotton Leaf Disease and Pest Diagnosis by Azath M., Melese Zekiwos, Abey Bruck

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An AI‐Enabled Data Processing Pipeline for Ingesting Borehole Data in Peridotite Environments by John M. Aiken, Elliot Dufornet, Hamed Amiri, Lotta Ternieten, Oliver Plümper

“…The study focuses on the alteration of peridotite core segments taken from Borehole BA1B, utilizing a gradient‐boosted trees (CatBoost) regression model trained on an integrated data set of machine‐learning segmented core images, physical measurements, geological, lithographic data, and AI‐summarized expert texts and feature selection. …”
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Parallelizing analog in-sensor visual processing with arrays of gate-tunable silicon photodetectors by Zheshun Xiong, Wen Liang, Meiyue Zhang, Dacheng Mao, Qiangfei Xia, Guangyu Xu

“…Both arrays are built in CMOS compatible processes and operated with zero static power. Furthermore, their bipolar analog output captures the amplitude of event-driven light changes and the spatial convolution of optical power densities at the device level, a feature that helps boost their performance in classifying dynamic motions and static images. …”
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Recent Trends and Advances in Utilizing Digital Image Processing for Crop Nitrogen Management by Bhashitha Konara, Manokararajah Krishnapillai, Lakshman Galagedara

“…A total of 95 articles remained after the screening and selection process. Interest in integrating machine learning and deep learning algorithms with DIP has increased, with the frequently used algorithms—Random Forest, Support Vector Machine, Extreme Gradient Boost, and Convolutional Neural Networks—achieving higher prediction accuracy levels. …”
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Catching a CAPTCHA: the impact of variable input on the processing of emerging orthographic representations by Olga Solaja, María Fernández-López, Davide Crepaldi, Manuel Perea

“…Therefore, letter shape variability when learning to read does not seem to boost orthographic processing.…”
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Rabbit meat quality with an approach to its processing using spices or specific ingredients as antioxidants by Simone Mancini, Simona Mattioli, Alessandro Dal Bosco

“…The addition of spices can help improve the flavour and appeal of processed products made from rabbit meat while also increasing the antioxidant content and boosting nutritious value and shelf life. …”
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Understanding the flowering process of litchi through machine learning predictive models by SU Zuanxian, NING Zhenchen, WANG Qing, CHEN Houbin

“…And the characteristic features screened out were helpful to understand the complex influence of external meteorological factors on the flowering process.…”
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Intermittent fasting boosts antitumor immunity by restricting CD11b+Ly6Clow Ly6Glow cell viability through glucose metabolism in murine breast tumor model by Chenghao Fu, Zhehao Liang, Zemiao Niu, Ning Chen, Yuemin Li, Zhenhua Liang, Yanwei Huo, Hao Xi, Rong Wang, Yonghuan Yan, Xiaoru Gano, Mengtian Wang, Yun Huang, Yan Zhang, Mingming Gao, Pin Lü

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A comparative analysis of emotion recognition from EEG signals using temporal features and hyperparameter-tuned machine learning techniques by Rabita Hasan, Sheikh Md. Rabiul Islam

“…This study explores improving emotion recognition performance by applying traditional machine learning classifiers and boosting techniques to EEG data from the DEAP dataset. …”
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Modeling and simulation of residual stress in metal cutting process: A review by Ruihu Zhou

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Interdisciplinary methodological approach to the process of brownfield revitalisation of traditional industrial areas by Lučka Lorber, Ph.D., Assistant Professor

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The Role of Hydrochar as Anaerobic Digestion Process Additive and CO2 Adsorbent by Annalinda Capone, Antonio Panico, Annarita Travaglino, Lucio Zaccariello, Hèlène Ageorges, Biagio Morrone

“…This article focuses on the sequential integration of HTC with Anaerobic Digestion (AD) utilizing HTC products as a boost to the AD process and CO2 capture. This study investigates the sequential integration of HTC and AD, evaluating the effect of hydrochar addition on methane production from sewage sludge under mesophilic (35°C) conditions. …”
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