Introducing a Novel Method to Identify the Future Trend of Nikkei 225 Stock Price in Order to Reduce Investment Risk by Freyr Björgvinsson

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Novel logic mining incorporating log linear approach by Siti Zulaikha Mohd Jamaludin, Nurul Atiqah Romli, Mohd Shareduwan Mohd Kasihmuddin, Aslina Baharum, Mohd. Asyraf Mansor, Muhammad Fadhil Marsani

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Redefining Object Detection for Open-World Settings: A Framework for Simultaneous Identification of Known and Unknown Classes by Muhammad Ali Iqbal, Yeo Chan Yoon, Soo Kyun Kim

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Binocular stereo vision-based relative positioning algorithm for drone swarm by Qing Cheng, Yazhe Wang

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A Holistic Approach to the Efficient Estimation of Operational Flexibility From Distributed Resources by Nikolaos Savvopoulos, Nikos Hatziargyriou, Hannu Laaksonen

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Comparison of marker-less 2D image-based methods for infant pose estimation by Lennart Jahn, Sarah Flügge, Dajie Zhang, Luise Poustka, Sven Bölte, Florentin Wörgötter, Peter B. Marschik, Tomas Kulvicius

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Aircraft Multi-stage Altitude Prediction Under Satellite Signal Loss by Mengchan HUANG, Qiang MIAO

“…The relative error ratios of the LTCA–TCN model for all three phases are within 1, indicating that the model’s predictions are generally more accurate than the inertial pressure altitude.Conclusions The results indicated that the LTCA–TCN model achieves high prediction accuracy across multiple stages, outperforming commonly used neural network algorithms in the field and providing optimal predictive performance. …”
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SEAGET: Seasonal and active hours guided graph enhanced transformer for the next POI recommendation by Alif Al Hasan, Md. Musfique Anwar

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A condition diagnosis method for subway track structures employing distributed optical fiber sensing by Hong Han, Xiaopei Cai, Liang Gao

“…First, a method for constructing a correlation model for strain monitoring data based on the optimal space window is proposed to realize the division of measuring points to reduce the computational complexity, and then, the deep generative adversarial network model with residual learning is constructed. …”
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Research on SeaTreasure Target Detection Technology Based on Improved YOLOv7-Tiny by Xiang Shi, Yunli Zhao, Jinrong Guo, Yan Liu, Yongqi Zhang

“…Experimental results demonstrate that our optimized algorithm achieves a mAP0.5 of 79.5%, representing a 2.0 percentage point improvement over the baseline YOLOv7-tiny model (77.5%) while maintaining computational efficiency at 45.2 GFLOPs. …”
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I-AIR: intention-aware travel itinerary recommendation via multi-signal fusion and spatiotemporal constraints by Xiao Cui, Zhihua Wang, Ping Li, Qiang Xu

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Evading control flow graph based GNN malware detectors via active opcode insertion method with maliciousness preserving by Hao Peng, Zehao Yu, Dandan Zhao, Zhiguo Ding, Jieshuai Yang, Bo Zhang, Jianming Han, Xuhong Zhang, Shouling Ji, Ming Zhong

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Data-Driven Solutions and Parameters Discovery of the Chiral Nonlinear Schrödinger Equation via Deep Learning by Zekang Wu, Lijun Zhang, Xuwen Huo, Chaudry Masood Khalique

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Real‐Time Hot‐Rolled Coil Placement Recommendation System with Data‐Driven Model by Chihun Lee, Da Seul Shin, Youn Hee Kang, Kanghyouk Choi, Dong Yong Park, Junsuk Rho

“…We developed a novel management system that integrates two trained artificial neural networks with deep and wide networks using hyperparameter tuning to improve prediction speed, a known limitation of FEM. …”
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Hybrid Channel Attention Regression U-Net (ARU-Net): An Enhanced Architecture for Brain Tumour Segmentation in Magnetic Resonance Imaging by Noman Ahmed Siddiqui, Muhammad Tahir Qadri, Zain Anwar Ali, Muhammad Ovais Akhter, Ahmed Alsanad, Areej Abdullah Alhogail, Abdu H. Gumaei

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FPGA Hardware Acceleration of AI Models for Real-Time Breast Cancer Classification by Ayoub Mhaouch, Wafa Gtifa, Mohsen Machhout

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DGCLCMI: a deep graph collaboration learning method to predict circRNA-miRNA interactions by Chao Cao, Mengli Li, Chunyu Wang, Lei Xu, Quan Zou, Yansu Wang, Wu Han

“…Next, we present a joint model that combines an improved neural graph collaborative filtering method with a feature extraction network for optimization. Deep interaction information is embedded as informative features within the sequence representations for prediction. …”
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Machine learning technique for the identification of two-phase (oil-water) flow patterns through pipelines by Daniel Yesid Uribe-Tarazona, Carlos Mauricio Ruiz-Diaz, Octavio Andrés González-Estrada

“…After evaluating 104 network configurations, the optimal model was selected, achieving an overall accuracy of 95.4%, with training, validation, and testing accuracies of 97.1%, 92.8%, and 90.3%, respectively, and a cross-entropy error of 0.024. …”
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AMNED: An Efficient Framework for Spiking Neuron Coding in AirComp Federated Learning by Juncheng Ji, Chan-Tong Lam, Ke Wang, Benjamin K. Ng

“…This reduces communication overhead and alleviates computational burdens at central aggregation points. …”
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Evaluating machine learning models comprehensively for predicting maximum power from photovoltaic systems by Samir A. Hamad, Mohamed A. Ghalib, Amr Munshi, Majid Alotaibi, Mostafa A. Ebied

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