Fusion of Visual Attention and Scene Descriptions With Deep Reinforcement Learning for AAV Indoor Autonomous Navigation by Hussein Samma, Ahmed Abubaker, Mubarak Badamasi Aremu, Mohammed Abdel-Nasser, Sami El-Ferik

“…This ensures safe and efficient navigation in complex indoor spaces. The approach was tested in a simulated indoor environment with pedestrians, created using Unreal Engine. …”
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A Systematic Survey of Machine Learning and Deep Learning Models Used in Industrial Internet of Things Security by Ersin Enes Eryılmaz, Erdal Kılıç, Yankı Ertek, Sedat Akleylek

“…IIoT devices vary from sensors to complex industrial robots. Security measures such as patch management, access control, network monitoring, authentication, service isolation, encryption, unauthorized entry detection, and application security are implemented for IIoT networks and devices. …”
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ATM: Adaptive transformer model for reconstruction of remote sensing multi-temporal non-equispaced sequence imagery by Zhi-peng Qi, Zi-yi Zhao, Xing Jin

“…Abstract Due to the influence of the imaging characteristics of the solar orbiting satellite and atmospheric conditions, the multi-spectral observation data often have the missing of phase image, which brings difficulties to the efficient and automatic processing of regional remote sensing data. …”
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A Platform For Solar Energy An Alternative Source For Kabale District at Kabale University. by Amanya, Devis

“…In terms of cost, it is cheaper, less complex, and still achieves the required efficiency.…”
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Retrospective study on NIPT or NIPT plus combined with ultrasound in screening fetal chromosomal abnormalities by Meilin Chen, Peisong Chen, Siyang Yu, Lu Ai, Xuegao Yu, Ruizhi Wang, Jinghai Yan, Shaobin Lin

“…False negatives were more prevalent in standard NIPT, particularly for SCA, MMS, and RAT, emphasizing its limitations for detecting complex chromosomal abnormalities. NIPT plus, when combined with ultrasound, offers significant improvements in the detection of rare chromosomal abnormalities like SCA, MMS, and RAT, while maintaining high detection rates for common trisomies. …”
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3D-SCUMamba: An Abdominal Tumor Segmentation Model by Juwita, Ghulam Mubashar Hassan, Amitava Datta

“…The proposed model efficiently models global dependencies while maintaining stable training dynamics and efficient inference. …”
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Research on COP Prediction Model of Chiller Based on PSO-SVR by Zhou Xuan, Cai Panpan, Lian Sizhen, Yan Junwei

“…So this model can provide theoretical basis for the chiller energy efficiency analysis, fault detection and diagnosis and optimizing control.…”
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IIoT’s Risk Odyssey: Navigating the Risk Propagation of Illegal Information Flows by Argiro Anagnostopoulou, Ioannis Mavridis, Michael Athanasopoulos, Alexios Mylonas, Dimitris Gritzalis

“…In our prior research, we introduced a methodology for the assessment of information flows in IIoT environments and the detection of the illegal ones. Specifically, we utilized a risk-based methodology to model complex business processes as directed graphs. …”
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IMU-Based Online Kinematic Calibration of Robot Manipulator by Guanglong Du, Ping Zhang

“…Compared with the existing vision-based self-calibration methods, the great advantage of this method is that it does not need the complex steps, such as camera calibration, images capture, and corner detection, which make the robot calibration procedure more autonomous in a dynamic manufacturing environment. …”
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Benchmarking metabolic RNA labeling techniques for high-throughput single-cell RNA sequencing by Xiaowen Zhang, Mingjian Peng, Jianghao Zhu, Xue Zhai, Chaoguang Wei, He Jiao, Zhichao Wu, Songqian Huang, Mingli Liu, Wenhao Li, Wenyi Yang, Kai Miao, Qiongqiong Xu, Liangbiao Chen, Peng Hu

“…This technique, which tags newly synthesized RNA for detection through induced base conversions, relies on conversion efficiency, RNA integrity, and transcript recovery. …”
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Graph Neural Networks for Digital Pathology by Vincenzo DELLA MEA, Hafsa AKEBLI, Kevin ROITERO

“…GNNs are well-suited for analyzing data such as social networks, molecular structures, and medical images, capturing both local and global patterns. The complexity and high dimensionality of medical images make them suitable for analysis using GNNs, which can leverage the relationships between elements in the data, offering a more complex and complete analysis that can improve both the accuracy and efficiency of medical image processing tasks such as classification, segmentation, and detection of abnormalities. …”
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A Systematic Review of the Advances and New Insights into Copy Number Variations in Plant Genomes by Saimire Silaiyiman, Jiaxuan Liu, Jiaxin Wu, Lejun Ouyang, Zheng Cao, Chao Shen

“…The advancement in sequencing technologies has made the detection and analysis of CNVs more efficient, not only revealing their crucial roles in plant disease resistance, adaptability, and growth development, but also demonstrating broad application potential in crop improvement, particularly in selective breeding and genomic selection. …”
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Quantum chimp-enanced SqueezeNet for precise diabetic retinopathy classification by Anas Bilal, Muhammad Shafiq, Waeal J. Obidallah, Yousef A. Alduraywish, Alishba Tahir, Haixia Long

“…Firstly, SqueezeNet enables efficient feature extraction from segmented fundus images with minimal computational complexity, ensuring that critical retinal features are captured effectively. …”
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Research on cardiac image segmentation algorithm based on improved level set modeling by Shuaishuai ZHANG, Ruixia LIU, Ke SHAN, Zhenhua GUO

“…It offers significant improvements in accuracy, computational efficiency, and cost-effectiveness.…”
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Recent Advances in the Fabrication and Application of Electrochemical Paper-Based Analytical Devices by Zarfashan Shahid, Kornautchaya Veenuttranon, Xianbo Lu, Jiping Chen

“…This review traces the evolution of ePADs from simple designs to complex multilayered structures that optimize analyte flow and improve detection. …”
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Comparison of Manhattan and Chebyshev Distance Metrics in Quantum-Based K-Medoids Clustering by Solikhun Solikhun, Muhammad Rahmansyah Siregar, Lise Pujiastuti, Mochamad Wahyudi, Deny Kurniawan

“…Therefore, Manhattan distance is more recommended for medical applications that require the detection of more positive cases, while Chebyshev is more efficient for scenarios that prioritize accuracy and cost.…”
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Implementation of Automatic Segmentation Framework as Preprocessing Step for Radiomics Analysis of Lung Anatomical Districts by Alessandro Stefano, Fabiano Bini, Nicolò Lauciello, Giovanni Pasini, Franco Marinozzi, Giorgio Russo

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Design and Simulation of Magnetic Shielding Structure Based on Closed-Loop TMR Current Sensor by Qiuyang Li, Suqin Xiong, Shuo Wang, Xianguang Dong, Haifeng Zhang

“…Simulation results demonstrate that the shielding efficiency of this structure improves by 44.3% compared to a single magnetic ring under a stray magnetic field of 0.1 mT along the sensing axis. …”
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A Deep Learning Inversion Method for Airborne Time-Domain Electromagnetic Data Using Convolutional Neural Network by Xiaodong Yu, Peng Zhang, Xi Yu

“…Due to the high detection efficiency of the airborne time-domain electromagnetic method, it can quickly collect electromagnetic response data for large area-wide regions, but it also brings great challenges to the inversion interpretation of the data because there are numerous survey data that need to be inverted. …”
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Artificial Intelligence for Financial Accountability and Governance in the Public Sector: Strategic Opportunities and Challenges by Ceray Aldemir, Tuğba Uçma Uysal

“…The study reveals that AI-driven solutions such as predictive analytics, fraud detection systems, and automated reporting significantly improve operational efficiency, transparency, and decision making. …”
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