Research on Global Dispatching Technology for Fully Automatic Operation System Based on Interconnection Technology by LIU Long, WANG Yeliu, REN Ying, LI Denggen, ZHANG Datao

“…Then, a global dispatching solution was devised based on networked rail transit lines, including the relevant system architecture and a multi-objective optimization model. …”
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Larsen’s cairn: the birth of a new historical site in Antarctica by Pablo Gabriel Fontana, María Angélica Guerriere

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Evolutionary Polynomial Regression Algorithm with Uncertain Variables: Two Case-Studies in the Field of Civil Engineering by Alessandra Fiore, Sebastiano Marasco, Rita Greco

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Graph neural networks with configuration cross-attention for tensor compilers by Dmitrii Khizbullin, Eduardo Rocha de Andrade, Thanh Hau Nguyen, Matheus Pedroza Ferreira, David R. Pugh

“…We propose TGraph, a neural graph architecture that allows screening for fast configurations of the target computational graph, thus representing an artificial intelligence (AI) tensor compiler in contrast to traditional heuristic-based compilers. …”
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Mix design and performance prediction of EPS lightweight structural concrete based on orthogonal experimentation by Qianhui Zhang

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Investigation of Resonance Modes in Iced Transmission Lines Using Two Discrete Methods by Rui Chen, Wanyu Bao, Mengqi Cai

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Microservice Adaptability and Self-Organization of UAV-Assisted Wireless Networks in Failure Rural Scenarios by Andrés García-López, Diego Ramos-Ramos, Santiago García-Gil, José Gómez-delaHiz, Juan Manuel Murillo, Jaime Galán-Jiménez

“…This paper presents a UAV-based wireless network architecture combined with a microservice model to ensure the dynamic deployment of IoT applications in rural environments. …”
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AFNE-Net: Semantic Segmentation of Remote Sensing Images via Attention-Based Feature Fusion and Neighborhood Feature Enhancement by Ke Li, Hao Ji, Zhijiang Li, Zeyu Cui, Chengkai Liu

“…To address these challenges, this paper proposes AFNE-Net, a general network architecture for remote sensing image segmentation. First, the model introduces an attention-based feature fusion module. …”
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Mitigating Online Banking Fraud Using Machine Learning and Anomaly Detection by Sheunesu Makura, Caden Dobson, Seani Rananga

“…The framework’s semi-supervised architecture enables zero-day fraud detection without reliance on labeled attack data, addressing a fundamental limitation of signature-based systems. …”
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A comprehensive molecular interaction map of the budding yeast cell cycle by Kazunari Kaizu, Samik Ghosh, Yukiko Matsuoka, Hisao Moriya, Yuki Shimizu‐Yoshida, Hiroaki Kitano

“…Toward leveraging the map as a framework to explore the underlying network architecture, we abstract the molecular components into three planes—signaling, cell‐cycle core and structural planes. …”
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The Kinematics of a New Schönflies Motion Generator Parallel Manipulator Using Screw Theory by Jaime Gallardo-Alvarado, Horacio Orozco-Mendoza, Ramon Rodriguez-Castro, Alvaro Sanchez-Rodriguez, Luis A. Alcaraz-Caracheo

“…In this work, an innovative Schönflies motion generator manipulator is introduced, featuring a parallel architecture composed of serial chains with mixed degrees of freedom. …”
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Technological innovation and cleaner energy consumption impact on economic growth and employment in the MENA region by Salwa Bajja, Gabriel Mordzifa Sackitey, Michael Provide Fumey

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A novel 3D hemispherical reconfigurable antenna with a switchable radiation pattern using Butler matrix by Amani Cherif, Sylvain Dubois, Mohamed Himdi, Hamsakutty Vettikalladi, Ali M. Almuhlafi

“…Abstract In this paper, we present a compact three-dimensional hemispherical reconfigurable antenna system designed for 5G networks operating around 3.6 GHz. The proposed architecture combines a four-element Vivaldi antenna array with a passive $$4\times 4$$ Butler matrix to enable electronically switchable beams in three main directions: upward, rightward, and backward. …”
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Spectrum Sensing for Noncircular Signals Using Augmented Covariance-Matrix-Aware Deep Convolutional Neural Network by Songlin Chen, Zhenqing He, Wenze Song, Guohao Sun

“…By feeding augmented sample covariance matrices into the designed CNN architecture, the proposed approach effectively learns discriminative patterns from the underlying data structure, without stringent model constraints. …”
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The development of the generative adversarial supporting vector machine for molecular property generation by Qing Lu

“…In this work, we propose a new generative model by introducing the supporting vector machine into the GAN architecture. Such modification reduces the hyper-parameter space by half, thus making the training more accessible. …”
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Machine Learning-Based Methodology for Fast Assessment of Battery Health Status by Woongchul Choi

“…While conventional methods require significant measurement time, this study demonstrates that accurate static capacity estimation is possible using only short-term partial discharge data (6 min under 1C-rate CC conditions) by leveraging an RNN (recurrent neural network) architecture specialized for time-series data processing. …”
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Assessing green innovation, energy transition and natural resources abundance for sustainable footprint in Paris club by Jinghai Luo, Ying Zhang, Muhammad Waqas

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Genomic signatures of adaptation in seed traits in the wild plant Brassica incana by Lucrezia Laccetti, Angelino Carta, Maria Rosaria Barone Lumaga, Léa Frachon, Giovanni Scopece

“…We observed a complex genetic architecture potentially involved in seed trait adaptation, which varied depending on the seed trait function. …”
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A multimodal deep reinforcement learning approach for IoT-driven adaptive scheduling and robustness optimization in global logistics networks by Yao Lu

“…We propose an integrated framework comprising a multimodal data fusion mechanism that synthesizes heterogeneous IoT sensor data, historical records, and contextual information; an adaptive deep reinforcement learning architecture that generates dynamic scheduling policies; and a multi-objective robust optimization method that balances operational efficiency with system resilience. …”
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GKCAE: A graph-attention-based encoder for fine-grained semantic segmentation of high-voltage transmission corridors scenario LiDAR data by Su Zhang, Haibo Liu, Jingguo Rong, Yaping Zhang

“…To tackle this limitation, we propose a novel network architecture—Graph-Kernel Convolution Attention Encoder (GKCAE)—designed for multi-class, fine-grained semantic segmentation of transmission corridor point clouds. …”
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