Assessment and Validation of i-Skyradiometer Retrievals Using Broadband Flux and MODIS Data by S. Dipu, G. Pandithurai, A. S. Panicker, T. Takamura, Dong-In Lee, Dongchul Kim

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A Preliminary Study on 2D Convolutional Neural Network-Based Discontinuous Rail Position Classification for Detection on Rail Breaks Using Distributed Acoustic Sensing Data by Hye-Yeun Chun, Jungtai Kim, Dongkue Kim, Ilmu Byun, Kyeongjun Ko

“…To analyze the vibration data, a preprocessing algorithm for determining train occupancy is applied first. …”
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The cost-effectiveness of different diagnostic options of TB among HIV-infected patients by V. E. Shumlyanskaya, A. V. Rudakova

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Increased Extreme Precipitation in Western North America from Cut-Off Lows Under a Warming Climate by Henri Pinheiro, Tercio Ambrizzi, Kevin Hodges

“…This study examines projected COL changes and their drivers in western North America under a high greenhouse gas concentration pathway (SSP585) using a multi-model ensemble from CMIP6 and a feature-tracking algorithm. We compare historical simulations (1980–2009) and future projections (2070–2099), revealing a marked increase in COL track density during summer in the northeast Pacific and western United States, while a strong decrease is projected for winter, associated with shifts in jet streams. …”
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Detection of Pathogenic Microorganisms by Fusion of Recursive Feature Pyramid by HUANGZhitian, XIEYining, ZHAOJing, HEYongjun

“…Aiming at the problems of less research on the detection of pathogenic microorganisms , large differences in target size and complex background , a multi-scale detection method of pathogenic microorganisms fused with recursive feature pyramid was proposed. …”
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Predicting the compressive strength of rubberized concrete incorporating brick powder based on MLP and RBF neural networks by David Sinkhonde, Destine Mashava, Tajebe Bezabih, Derrick Mirindi

“…It is shown that MLP is superior in predicting the compressive strength of rubberized concrete incorporating CBP compared with RBF. However, regardless of the algorithm used, the R2 and adjusted R2 values are higher than 0.75. …”
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NOMA Performance Improvement with Downlink Sectorization by Hurianti Vidyaningtyas, . Iskandar, . Hendrawan, Aloysius A. Pramudita

“…A Sequential Power Allocation (SePA) algorithm was introduced to enhance power distribution within sectors, aiming to maximize both user capacity and overall sum rate. …”
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Imaging techniques for diffuse myocardial fibrosis as a marker of high cardiovascular risk in young patients with type 1 diabetes mellitus by Oksana I. Vengrzhinovskaya, Irina Z. Bondarenko, Olga A. Shatskaia, Natalia V. Tarbaeva, Anastasya Iu. Korneluk, Victor Iu. Kalashnikov, Marina V. Shestakova, Natalia G. Mokrysheva

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Scheduling and Evaluation of a Power-Concentrated EMU on a Conventional Intercity Railway Based on the Minimum Connection Time by Yinan Wang, Limin Xu, Xiao Yang, Jingjing Bao, Feng Lin, Yiwei Guo, Yixiang Yue

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Eliminating geometric distortion with dual-orbit Sentinel-1 SAR fusion for accurate glacial lake extraction in Southeast Tibet Plateau by Renzhe Wu, Guoxiang Liu, Xin Bao, Jichao Lv, Age Shama, Bo Zhang, Wenfei Mao, Jie Chen, Zhihan Yang, Rui Zhang

“…This serves as a reference for research that investigates the mechanisms of glacier-GL-climate change.…”
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Crowd Evacuation in Stadiums Using Fire Alarm Prediction by Afnan A. Alazbah, Osama Rabie, Abdullah Al-Barakati

“…These findings underscore the necessity of intelligent fire detection systems in high-occupancy venues, demonstrating that AI-based predictive modeling can drastically improve fire response and evacuation efficiency. Future research should focus on integrating IoT-enabled emergency navigation, reinforcement learning algorithms, and real-time crowd management systems to further enhance predictive accuracy and minimize casualties. …”
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Deep Learning Frontiers in 3D Object Detection: A Comprehensive Review for Autonomous Driving by Ambati Pravallika, Mohammad Farukh Hashmi, Aditya Gupta

“…The progression of reference datasets, such as KITTI, Waymo, and NuScenes, was examined, emphasizing their crucial role in propelling detection algorithms forward and enabling comparative studies across diverse methodologies. …”
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Compatible matching and synergy operation optimization of hydrogen-electric hybrid energy storage system in DC microgrid by Banghua Du, Yanyu Peng, Yang Li, Changjun Xie, Shihao Zhu, Wenchao Zhu, Yang Yang, Li You, Leiqi Zhang, Bo Zhao

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3D Solar Analysis of the Street Network and Impact Estimation of the Shade of Trees at the District Scale by E. Shirinyan, K. Stefanov, D. Petrova-Antonova

“…The study demonstrated up to a 30% decrease in solar radiation on streets compared to analysis that excludes trees, as well as an 18% increase in solar access to street surfaces compared to raster-based calculations in GIS. …”
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A Comparison Between the Use of an Infrared Contact Mat and an IMU During Kinematic Analysis of Horizontal Jumps by Bjørn Johansen, Jono Neville, Roland van den Tillaar

“…Background/Objectives: This study compared step-by-step kinematic measurements from an infrared contact mat (IR-mat) and an inertial measurement unit (IMU) system during bounding and single leg jumping for speed, while also evaluating the validity of algorithms originally developed for sprinting and running when applied to horizontal jumps. …”
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Dual FOPID-neural network controller based on fast grey wolf optimizer: application to two-inputs two-outputs helicopter by Amar Rezoug, Jamshed Iqbal, Abdelkrim Nemra

“…The DRF-FG showed robustness in trajectory tracking compared to the controllers based on the Ant Lion Optimizer (DRF-A) and the Whale Optimization Algorithm (DRF-W). …”
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Deepfake detection method based on patch-wise lighting inconsistency by Wenxuan WU, Wenbo ZHOU, Weiming ZHANG, Nenghai YU

“…The rapid development and widespread dissemination of deepfake techniques has caused increased concern.The malicious application of deepfake techniques also poses a potential threat to the society.Therefore, how to detect deepfake content has become a popular research topic.Most of the previous deepfake detection algorithms focused on capturing subtle forgery traces at pixel level and have achieved some results.However, most of the deepfake algorithms ignore the lighting information before and after generation, resulting in some lighting inconsistency between the original face and the forged face, which provided the possibility of using lighting inconsistency to detect deepfake.A corresponding algorithm was designed from two perspectives: introducing lighting inconsistency information and designing a network structure module for a specific task.For the introduction of lighting task, a new network structure was derived by designing the corresponding channel fusion method to provide more lighting inconsistency information to the network feature extraction layer.In order to ensure the portability of the network structure, the process of feature channel fusion was placed before the network extraction information, so that the proposed method can be fully planted to common deepfake detection networks.For the design of the network structure, a deepfake detection method was proposed for lighting inconsistency based on patch-similarity from two perspectives: network structure and loss function design.For the network structure, based on the characteristic of inconsistency between the forged image tampering region and the background region, the extracted features were chunked in the network feature layer and the feature layer similarity matrix was obtained by comparing the patch-wise cosine similarity to make the network focus more on the lighting inconsistency.On this basis, based on the feature layer similarity matching scheme, an independent ground truth and loss function was designed for this task in a targeted manner by comparing the input image with the untampered image of this image for patch-wise authenticity.It is demonstrated experimentally that the accuracy of the proposed method is significantly improved for deepfake detection compared with the baseline method.…”
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EUS-based intratumoral and peritumoral machine learning radiomics analysis for distinguishing pancreatic neuroendocrine tumors from pancreatic cancer by Shuangyang Mo, Shuangyang Mo, Nan Yi, Fengyan Qin, Huaying Zhao, Huaying Zhao, Yingwei Wang, Haiyan Qin, Haixiao Wei, Haixing Jiang, Shanyu Qin

“…Following this, the radiomic features underwent dimensionality reduction through the utilization of the least absolute shrinkage and selection operator (LASSO) algorithm. Six machine learning algorithms were utilized to train prediction models employing features with nonzero coefficients. …”
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THE AUGMENTED REALITY FUNCTIONS TO SUPPORT THE STEAM EDUCATION AT GENERAL EDUCATION INSTITUTIONS by Наталія Сороко

“…AR provide the formation and development of a new information method of presentation and assimilation of material, are high-tech didactic tools. Our further research is the creation of algorithms for the use of AR for lessons and projects using the STEAM approach, which will improve the quality of education at general education institutions.…”
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Model-based quantitative analysis in two-time-scale decomposed on–off optimal control of greenhouse cultivation by Dan Xu, Yanfeng Li, Anguo Dai, Shumei Zhao, Weitang Song

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