Intra-landscape distribution of snow storage in the Mayma river basin (low-mountain area of the Russian Altai) by L. F. Lubenets, D. V. Chernykh

“…The paper presents the results of observations and cartographic modeling of distribution of maximum snow storages (snowpack water equivalent) in the low-mountain forest landscapes of the Maima river basin in different by snow amount winters. …”
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Quasi-Analytical Least-Squares Generative Adversarial Networks: Further 1-D Results and Extension to Two Data Dimensions by Graham W. Pulford

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Kernel Density Estimation: a novel tool for visualising training intensity distribution in biathlon by Craig A. Staunton, Craig A. Staunton, Andreas Kårström, Andreas Kårström, Hannes Kock, Hannes Kock, Marko S. Laaksonen, Glenn Björklund

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Evaluation of data driven low-rank matrix factorization for accelerated solutions of the Vlasov equation. by Bhavana Jonnalagadda, Stephen Becker

“…At inference time, the model outputs a low-rank decomposition of the distribution field of the charged particles, and we demonstrate that this step is faster than the standard linear algebra technique. …”
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Human action recognition based on low- and high-level data from wearable inertial sensors by Irvin Hussein Lopez-Nava, Angélica Muñoz-Meléndez

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Parameter uncertainties for imperfect surrogate models in the low-noise regime by Thomas D Swinburne, Danny Perez

“…However, this loss ignores model form error, or misspecification, meaning parameter uncertainties are significantly underestimated and vanish in the large data limit. …”
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A model for correlation-based choreographic programming by Saverio Giallorenzo, Fabrizio Montesi, Maurizio Gabbrielli

“…Choreographies provide a clear way to specify the intended communication behaviour of concurrent and distributed systems. Previous theoretical work investigated the translation of choreographies into (models of) programs based on message passing. …”
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Constraint Learning-based Optimal Power Dispatch for Active Distribution Networks with Extremely Imbalanced Data by Yonghua Song, Ge Chen, Hongcai Zhang

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Study of Internal Spatial Temperature Distribution of Lubricating Oil Based on Transmission Spectroscopy by Liangyu Li, Run Zou, Yanzhe Liu, Shiliang Yao, Tiexiong Su

“…By formulating a mathematical model that correlates the temperature distribution with light intensity, the optical characteristics of lubricating oil undergoing a phase change at a single interface in low-temperature environments were thoroughly investigated. …”
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Optimizing feature selection and deep learning techniques for precise detection of low-rate distributed denial of service (LDDoS) attack by Naeem Ali Al-Shukaili, Miss Laiha M. Kiah, Ismail Ahmedy

“…Abstract The solution for cybersecurity faces significant challenges due to the growing complexity of denial of service (DoS) attacks, especially Low-rate Distributed Denial of Service (LDDoS) attacks. …”
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Optimized transmission of multi-path low-latency routing for electricity internet of things based on SDN task distribution. by Qi Jin

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A Topology Identification Strategy of Low-Voltage Distribution Grids Based on Feature-Enhanced Graph Attention Network by Yang Lei, Fan Yang, Yanjun Feng, Wei Hu, Yinzhang Cheng

“…Accurate topological connectivity is critical for the safe operation and management of low-voltage distribution grids (LVDGs). However, due to the complexity of the structure and the lack of measurement equipment, obtaining and maintaining these topological connections has become a challenge. …”
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Low Saturation Confidence Distribution-based Test-Time Adaptation for cross-domain remote sensing image classification by Yu Liang, Shilei Cao, Juepeng Zheng, Xiucheng Zhang, Jianxi Huang, Haohuan Fu

“…In practical cross-domain RS image classification, achieving a balance between adaptation speed and accuracy is crucial. Therefore, we propose Low Saturation Confidence Distribution Test-Time Adaptation (LSCD-TTA), marketing the first attempt to explore Test-Time Adaptation for cross-domain RS image classification without requiring source or target training data. …”
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Data-Driven Optimization for Low-Carbon Prefabricated Components Production Based on Ant Colony Algorithms by Chun-Ling Ho, Chien-Chih Wang, Shenjun Qi, Zichen Zhang

“…This study initially examines the development and current status of prefabricated concrete component factories in Fujian Province, focusing on regional distribution and production conditions. It also gathers data on carbon emissions, time, and costs to formulate a multi-objective optimization model. …”
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Modeling and Analysis on Congestion Control for Data Transmission in Sensor Clouds by Jun Huang, Donggai Du, Qiang Duan, Yanguang Zhang, Yanxiao Zhao, Hongshan Luo, Zhuoqi Mai, Qian Liu

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A Breakthrough on Modeling Cancer Prevention and Elimination by Low Radiation Doses by Bobby R. Scott

“…The greatly improved HRR model is quite flexible and was applied to lung cancer and reticulum cell sarcoma prevention/elimination data from a study involving more than 15 000 gamma-ray exposed mice. …”
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Towards Autonomous Operation of UAVs Using Data-Driven Target Tracking and Dynamic, Distributed Path Planning Methods by Jae-Young Choi, Rachit Prasad, Seongim Choi

“…A hybrid real-time path planning method has been developed that employs data-driven target UAV trajectory tracking methods. …”
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Testing effects of Pleistocene climate change on the altitudinal and horizontal distributions of frogs from the Colombian Andes: a species distribution modeling approach by Andrea Paz, Angélica González, Andrew J. Crawford

“…We used environmental information and species occurrence data to model the distribution of 14 amphibian species (seven highland and seven lowland) which we projected to the Last Glacial Maximum (LGM) using two past climatic reconstructions. …”
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Model-Aware XGBoost Method Towards Optimum Performance of Flexible Distributed Raman Amplifier by Anand Prakash, Jaisingh Thangaraj, Sharbani Roy, Shaury Srivastav, Jitendra K. Mishra

“…Toward the next-generation ultra-long-haul optical network, an extremely gradient boosting (XGBoost)-aided machine learning (ML) model is proposed to maximize the flexibility and uniformity in the performance of distributed Raman amplifier (DRA). …”
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A task decomposition and scheduling model for power IoT data acquisition with overlapping data efficiency optimization by Jindong Cui, Yuqing Wang, Zengchen Zhu, Ruotong Li

“…Abstract To address the challenges of low efficiency and high redundancy in massive data acquisition within the Power Internet of Things (PIoT), existing systems suffer from redundant acquisition and resource waste due to insufficient identification of overlapping regions, while traditional scheduling mechanisms struggle to balance task priorities with dynamic scenario requirements. …”
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