A machine learning driven computationally efficient horse shoe shaped antenna design for internet of medical things. by Umhara Rasool Khan, Javaid A Sheikh, Aqib Junaid, Shazia Ashraf, Altaf A Balkhi

“…In this article, regression-based Machine learning (ML) techniques are used to facilitate the design of Horse shoe shaped patch antenna to predict the frequency of operation, radiation efficiency and Specific Absorption Rate (SAR) values to accelerate its design process for on-body applications. …”
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Intelligent design and synthesis of energy catalytic materials by Linkai Han, Zhonghua Xiang

“…We provide the illustrations of predicting the properties of catalytic materials with ML assistance in different material types. …”
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Vehicle Pose Estimation Method Based on Maximum Correntropy Square Root Unscented Kalman Filter by Shuyu Liu, Ying Guo

“…The method first generates an estimate of the predicted state and covariance matrix through the Unscented Transform (UT), and then obtains the square root matrix of the covariance through Cholesky and QR decomposition to replace the original covariance, effectively preserving the positive definiteness of the covariance and improving the accuracy of the algorithm. …”
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DIGITAL TWINS AND THEIR APPLIANCE IN TRANSPORT ECONOMICS by O. N. Rimskaya, I. V. Anokhov

“…The consequence of this is the emergence of digital twins that allow modeling and predicting the behavior of both individual processes and enterprises as a whole.The aim of the article is to investigate the process of digitalization in the transport industry. …”
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CALCULATION OF WEIGHT COEFFICIENTS IN CONTINUOUS PARTICLE FILTER by K. A. Rybakov

“…In addition, it is planned to develop algorithms for predicting the states of stochastic diffusion and jump-diffusion systems based on the calculation of weight coefficients in the particle filter considered in this article.…”
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Energy‐based PINNs for solving coupled field problems: Concepts and application to the multi‐objective optimal design of an induction heater by Marco Baldan, Paolo Di Barba

“…Eventually, the ePINN predicts the temperature field within the graphite plate.…”
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Modeling Particle Transport in Astrophysical Outflows and Simulations of Associated Emissions from Hadronic Microquasar Jets by D. A. Papadopoulos, O. T. Kosmas, S. Ganatsios

“…Then, we concentrate on predictions of the associated emissions, focusing on detectable high-energy neutrinos and γ-rays originated from the extragalactic M33 X-7 system, which is an X-ray binary discovered in 2006, located in the neighboring galaxy Messier 33, and has not yet been modeled in detail. …”
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Parametric optimization of the slot waveguide characteristics using a machine-learning approach by Yadvendra Singh, Suraj Jena, Harish Subbaraman

“…In the present work, we combine machine learning (ML) algorithms and finite element simulation to predict the power confinement ( $$\hbox {P}_{conf}$$ ) and mode effective index ( $$\hbox {n}_{eff}$$ ) of slot waveguides with respect to geometric parameters such as gap, slab width, and slab height. …”
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Research on the Location-Routing Optimization of International Freight Trains Considering the Implementation of Blockchain by Zhichao Hong, Hao Shen, Wenjie Sun, Jin Zhang, Hongbin Liang, Gang Zhao

“…This algorithm is based on opposition-based learning and its dominant strength. …”
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SAFE-CAST: secure AI-federated enumeration for clustering-based automated surveillance and trust in machine-to-machine communication by Yusuf Kursat Tuncel, Kasım Öztoprak

“…The results show significant improvements in energy efficiency (21.6% reduction), throughput (14.5% increase), security strength (15.3% enhancement), latency (33.9% decrease), and packet loss rate (12.9% reduction) compared to state-of-the-art approaches. …”
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Residential Building Renovation Considering Energy, Carbon Emissions, and Cost: An Approach Integrating Machine Learning and Evolutionary Generation by Rudai Shan, Wanyu Lai, Huan Tang, Xiangyu Leng, Wei Gu

“…Using the heuristic optimization algorithm and entropy-weighted method, the framework achieved average energy savings of 56.62%, a reduction in carbon emissions of 51.60%, and a 24.27% decrease in life-cycle costs. …”
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Subspace-based local compilation of variational quantum circuits for large-scale quantum many-body simulation by Shota Kanasugi, Yuichiro Hidaka, Yuya O. Nakagawa, Shoichiro Tsutsui, Norifumi Matsumoto, Kazunori Maruyama, Hirotaka Oshima, Shintaro Sato

“…Here, we propose a hybrid quantum-classical algorithm, called local subspace variational quantum compilation (LSVQC), for compiling the time-evolution operator of quantum many-body systems. …”
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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

“…The research utilizes the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), a multi-objective evolutionary algorithm (MOEA), to reduce data dimensionality and identify key features for traffic analysis related to global human trafficking (HTr). …”
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Two-Dimensional Direction of Arrival (DOA) Estimation for Rectangular Array via Compressive Sensing Trilinear Model by Huaxin Yu, Xiaofeng Qiu, Xiaofei Zhang, Chenghua Wang, Gang Yang

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Kun–Qi birth cohort (KQBC) study for the incidence, aetiology and risk factors of chronic kidney disease in Chinese children: a cohort profile by Yan Ma, Xingdong Chen, Jie Wei, Li Guo, Jian Huang, Li Xie, Lei Chen, Ping Lu, Wei Sun, Wei Shi, Feng Ding, Liping Zhang, Yue Zhang, Linlin Zhang, Rui Song, Yi Huang, Jun Shen, Hong Xu, Zhigang Chen, Qian Shen, Ying Ma, Yiwen Zhang, Hongxia Li, Yihui Zhai, Biao Xu, Xian Zhou, Jun Sun, Bing Wu, Rui Su, Xiaoyan Yu, Jianhong Zhu, Yihong Huang, Ling Gong, Nana Wu, Jingjing Sun, Tianyi Liu, He Yuan, Yiwen Shen, Jiaojiao Liu, Xia Han, Juanjuan Wu, Yinghua Sun, Suxiang Xu, Qinyi Zhang, Na Xie, Jianfeng Ji, Weizhi Mo, Yuanxin Liu, Xinghua Shi, Wanshan Qiu, Jiapeng Mi, Juhua Yan, Minghui Zhu, Pei Feng, Wenqian Sheng, Mingqin Tai, Chunqin Zhou, Qian Jin, Chengyu Gu, Xiujuan Huang, Qinfang Qian, Yixin Cao, Haochen Shen, Ziwen Xue, Yucui Ma, Juan Tian, Yingdan Zhang, Weiyuan Zhuang, Kaiqun Yang, Xiaohui Shen, Yanwei Gu, Beibei Shi, Chenhong Pan, Hongmei Zhou, Xiuchen Zhang, Meihua Tang, Kaixuan Gu, Hongping Liu, Yuanxian Li

“…We aim to develop multimodal risk prediction models by integrating genomics and artificial intelligence algorithms. …”
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Remote Sensing of Particle Absorption Coefficient of Pigments Using a Two-Stage Framework Integrating Optical Classification and Machine Learning by Xietian Xia, Shaohua Lei, Hui Lu, Zenghui Xu, Xiang Li, Xing Chen, Niancheng Hong, Jie Xu, Kun Shi, Jiacong Huang

“…Focusing on inland waters—key areas for eutrophication monitoring—we first developed an intelligent clustering method combining Kernel Principal Angle-based Component (KPAC) dimensionality reduction and Chameleon Swarm Algorithm (CSA)-optimized k-medoids to classify water bodies into four optical types based on hyperspectral reflectance features. …”
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Identification and validation of a KRAS-macrophage-associated gene signature as prognostic biomarkers and potential therapeutic targets in melanoma by Beichen Cai, Beichen Cai, Beichen Cai, Qian Lin, Qian Lin, Qian Lin, Ruonan Ke, Ruonan Ke, Ruonan Ke, Jiaqi Yu, Jiaqi Yu, Jiaqi Yu, Lu Chen, Lu Chen, Xuejun Ni, Xuejun Ni, Hekun Liu, Xiuying Shan, Xiuying Shan, Biao Wang, Biao Wang, Biao Wang

“…The KMPAG gene signature presents a novel prognostic tool, offering insights into personalized treatment strategies and predictive biomarkers for immunotherapy in SKCM. Further exploration of CLEC4A’s role in melanoma progression may provide new therapeutic avenues for targeted intervention.…”
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Difficulties in Diagnosing a Patient with Fever of Unknown Origin by E. I. Fomina, E. E. Gubernatorova, T. V. Adasheva, T. V. Baturina, P. S. Samoszhenova, N. U. Timofeeva

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Application of neural network technology for public opinion analysis by Kyrylo Perevoznyk, Yurii Parzhyn

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Insights into Nitrogen-Associated Protein 50 (NAP50) as a Tyrosyl–DNA Phosphodiesterase in Dinoflagellates by Lu Tang, Nora Fung-Yee Tam, Winnie Lam, Thomas Chun-Hung Lee, Steven Jing-Liang Xu, Fred Wang-Fat Lee

“…The three-dimensional structure and biological functions of NAP50 are predicted using deep learning algorithms. Based on evolutionary relationships and functional predictions, NAP50 may play a role in repairing plastid DNA damage and potentially contribute to the transcription of plastid genes in dinoflagellates.…”
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