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Multi-Scale Fusion and Decomposition Network for Single Image Deraining

IEEE Transactions on Image Processing 2024年 33卷 191-204页

作者： Wang, Qiong Jiang, Kui Wang, Zheng Ren, Wenqi Zhang, Jianhui Lin, Chia-Wen Wuhan University National Engineering Research Center for Multimedia Software School of Computer Science Wuhan430072 China Sun Yat-sen University School of Cyber Science and Technology Guangzhou510275 China Hangzhou Dianzi University College of Computer Science and Technology Hangzhou310018 China National Tsing Hua University Department of Electrical Engineering The Institute of Communications Engineering Hsinchu30013 Taiwan

Convolutional neural networks (CNNs) and self-attention (SA) have demonstrated remarkable success in low-level vision tasks, such as image super-resolution, deraining, and dehazing. The former excels in acquiring local connections with translation equivariance, while the latter is better at capturing long-range dependencies. However, both CNNs and Transformers suffer from individual limitations, such as limited receptive field and weak diversity representation of CNNs during low efficiency and weak local relation learning of SA. To this end, we propose a multi-scale fusion and decomposition network (MFDNet) for rain perturbation removal, which unifies the merits of these two architectures while maintaining both effectiveness and efficiency. To achieve the decomposition and association of rain and rain-free features, we introduce an asymmetrical scheme designed as a dual-path mutual representation network that enables iterative refinement. Additionally, we incorporate high-efficiency convolutions throughout the network and use resolution rescaling to balance computational complexity with performance. Comprehensive evaluations show that the proposed approach outperforms most of the latest SOTA deraining methods and is versatile and robust in various image restoration tasks, including underwater image enhancement, image dehazing, and low-light image enhancement. The source codes and pretrained models are available at https://***/qwangg/MFDNet. © 1992-2012 IEEE.

关键词： Image reconstruction

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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

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UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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Segmented-Based and Segmented-Free Approach for COVID-19 Detection 5th

Segmented-Based and Segmented-Free Approach for COVID-19 D...

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5th International Conference on Computational Intelligence in Communications and Business Analytics, CICBA 2023

作者： Lasker, Asifuzzaman Ghosh, Mridul Das, Sahana Obaidullah, Sk Md Chakraborty, Chandan Goncalves, Teresa Roy, Kaushik Department of Computer Science and Engineering Aliah University Kolkata700160 India Department of Computer Science Shyampur Siddheswari Mahavidyalaya Howrah711312 India School of Computer Science Swami Vivekananda University Kolkata700121 India Department of Computer Science and Engineering National Institute of Technical Teachers’ Training and Research Kolkata700106 India Computer Science Department and ALGORITMI Center University of Évora Évora Portugal Department of Computer Science West Bengal State University Barasat700126 India

ISBN: (纸本)9783031488788

According to WHO, lung infection is one of the most serious problems across the world, especially for children under five years old and older people over sixteen years old. In this study, we designed a deep learning-based model to aid medical practitioners in their diagnostic process. Here, U-Net based segmentation framework is considered to get the region of interest (ROI) of the lung area from the chest x-ray images. Two standard deep learning models and a developed CNN model comprise this framework. A deep ensemble framework method is presented to detect COVID-19 disease from a collection of chest X-ray images of disparate cases in both segment-free and segmented-based lung images. Different public datasets were used for segmentation and classification to test the system’s robustness. The performance of segmentation and classification approaches returns promising outcomes compared to the state-of-the-art. © 2024, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： COVID-19

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Cross-Layer Distributed Attack Detection Model for the IoT

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International Journal of Ambient Computing and Intelligence 2022年第1期13卷 1-17页

作者： Ahmed, Hassan I. Nasr, Abdurrahman A. Abdel-Mageid, Salah M. Aslan, Heba K. Informatics Department Electronics Research Institute Cairo Egypt Computer Engineering Faculty of Engineering Al-Azhar University Cairo Egypt Computer Engineering Department College of Computer Science and Engineering Taibah University Saudi Arabia Center of Informatics Science Faculty of Information Technology and Computer Science Nile University Egypt

The security of IoT that is based on layered approaches has shortcomings such as the redundancy, inflexibility, and inefficiently of security solutions. There are many harmful attacks in IoT networks such as DoS and DDoS attacks, which can compromise the IoT architecture in all layers. Consequently, cross layer approach is proposed as an effective and practical security defending mechanism. Cross-layer distributed attack detection model (CLDAD) is proposed to enhance security solutions for IoT environments. CLDAD presents a general detection method of DDoS in sensing layer, network layer, and application layer. CLDAD is based on big data analytics techniques, which enable the detection process to be performed in a distributed way, so the model can detect DDoS attacks in any layer on-the-fly and the model support the scalability of the IoT environment. CLDAD is tested based on three datasets, namely artificial jamming attack dataset, BoT-IoT dataset, and BoT-IoT-based HTTP. The results showed that the proposed model is efficient in detecting attacks in the three layers of the IoT. Copyright © 2022, IGI Global.

关键词： Big data

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Online optimization for optical readout of a single electron spin in diamond

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Frontiers of physics 2023年第2期18卷 189-196页

作者： Xue Lin Jingwei Fan Runchuan Ye Mingti Zhou Yumeng Song Dawei Lu Nanyang Xu School of Microelectronics and School of Physics Hefei University of TechnologyHefei 230009China Research Center for Quantum Sensing Zhejiang LaboratoryHangzhou 311000China Shenzhen Institute for Quantum Science and Engineering and Department of Physics Southern University of Science and TechnologyShenzhen 518055China

The nitrogen-vacancy(NV)center in diamond has been developed as a promising platform for quantum sensing,especially for magnetic field measurements in the nano-tesla range with a nano-meter *** spin readout performance has a direct effect on the signal-to-noise ratio(SNR)of *** this work,we introduce an online optimization method to customize the laser waveform for *** simulations and experiments reveal that our new scheme optimizes the optically detected magnetic resonance in NV *** SNR of optical spin readout has been witnessed a 44.1%increase in *** addition,we applied the scheme to the Rabi oscillation experiment,which shows an improvement of 46.0%in contrast and a reduction of 12.1%in mean deviation compared to traditional constant laser power SNR *** scheme is promising to improve sensitivities for a wide range of NV-based applications in the future.

关键词： NV center readout signal-to-noise ratio online optimization

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Exploring red-edge spectral indices for mangrove canopy height mapping using random forest regression with Sentinel-2 and spaceborne GEDI LiDAR data 5

Exploring red-edge spectral indices for mangrove canopy heig...

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Land Surface and Cryosphere Remote Sensing V 2024

作者： Jamaluddin, Ilham Chen, Ying-Nong Ayudyanti, Amalia Gita Fan, Kuo-Chin Department of Computer Science and Information Engineering National Central University Taiwan Center for Space and Remote Sensing Research National Central University Taiwan

ISBN: (数字)9781510682696

ISBN: (纸本)9781510682689

Mangroves are coastal vegetation and considered as one of the blue carbon ecosystems. Canopy height is a critical parameter in understanding these ecosystems and related to biomass information. Remote sensing and machine learning techniques are increasingly utilized for large-scale mangrove canopy height mapping. Sentinel-2 is an optical satellite with various bands, including red-edge (RE) bands that are related to vegetation biophysical information. This study investigates the potential of red-edge spectral indices for mangrove canopy height mapping using Random Forest Regression (RFR). The study area is located around Charlotte Harbor Preserve State Park, Florida, USA in 2020. Sentinel-2 data was used to produce several red-edge spectral indices including NDVI, NDVIRE1, NDVIRE2, NDVIRE3, CIRE1, CIRE2, CIRE3, and CIVI which served as inputs for the RFR model. Spaceborne GEDI LiDAR rh98 canopy height data was used here to produce the target data. The dataset was divided into 80% training and 20% testing subsets. Our results indicate that CIVI utilizing red-edge 1 and 2 is the most important feature of RFR for mangrove canopy height estimation. The mean absolute error (MAE) and the root mean squared error (RMSE) based on the testing dataset were 1.662 m and 2.291 m, respectively. To further validate the results, we introduced an independent testing dataset using a canopy height model from the airborne LiDAR data located near the study area. We used the trained RFR model to predict the mangrove canopy height in the testing area and found the MAE and RMSE from the independent testing dataset were 2.511 m and 2.812 m, respectively. Based on the results, most of the red-edge spectral indices have a better performance than the spectral index without red-edge bands, and the use of several red-edge spectral indices provides promising results for mangrove canopy height mapping. © 2025 SPIE.

关键词： Mean square error

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Thermoelastic damping in MEMS gyroscopes at high frequencies

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Microsystems & Nanoengineering 2023年第1期9卷 137-148页

作者： Daniel Schiwietz Eva M.Weig Peter Degenfeld-Schonburg Robert Bosch GmbH Corporate Research71272RenningenGermany Department of Electrical&Computer Engineering Technical University of Munich85748GarchingGermany Munich Center for Quantum Science and Technology(MCQST) 80799MunichGermany TUM Center for Quantum Engineering(ZQE) 85748GarchingGermany

Microelectromechanical systems(MEMS)gyroscopes are widely used,e.g.,in modern automotive and consumer applications,and require signal stability and accuracy in rather harsh environmental *** many use cases,device reliability must be guaranteed under large external loads at high *** sensitivity of the sensor to such external loads depends strongly on the damping,or rather quality factor,of the high-frequency mechanical modes of the *** this paper,we investigate the influence of thermoelastic damping on several high-frequency modes by comparing finite element simulations with measurements of the quality factor in an application-relevant temperature *** measure the quality factors over different temperatures in vacuum,to extract the relevant thermoelastic material parameters of the polycrystalline MEMS *** simulation results show a good agreement with the measured quantities,therefore proving the applicability of our method for predictive purposes in the MEMS design ***,we are able to uniquely identify the thermoelastic effects and show their significance for the damping of the high-frequency modes of an industrial MEMS *** approach is generic and therefore easily applicable to any mechanical structure with many possible applications in nano-and micromechanical systems.

关键词： uniquely generic quantities

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On Construction of Precise Positioning System via IEEE 802.11ax

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IEEE Internet of Things Journal 2023年第14期10卷 12951-12960页

作者： Tsung, Chen-Kun Yang, Chao-Tung Liu, Jung-Chun Hsiung, Chun Chang, Shih-Kuang Hsu, Ming-Shang National Chin-Yi University of Technology Department of Computer Science and Information Engineering Taichung41170 Taiwan Tunghai University Department of Computer Science and Research Center for Smart Sustainable Circular Economy Taichung407224 Taiwan Tunghai University Department of Computer Science Taichung40704 Taiwan Krystal Technology Company Ltd. Network Department Taichung42756 Taiwan

Wireless network stability is critical for organizations. Most companies rely on a solid Internet connection for at least part of their day-to-day activities. It is essential to show the fast and high capacity of Wi-Fi. Wireless network management also significantly supplies the user with quality service and helps the system administrator manage and track the network infrastructure. The user must be able to stay connected. The Wi-Fi connection engine was applied in this article using the analysis and locations engine (ALE). ALE provides the information, including MAC address, location, floor information, and the building where the device belongs. From this data, we presented the Web visualization of the Wi-Fi network monitoring system on the map using Cesium. Except for the common information about Wi-Fi users, this work presents the vertical position visualization in the buildings to provide more details about user usage. This work analyzes the user experience of using the proposed system, and latency is the appropriate metric to measure the user experience. The experiment results show that the optimized number of cluster partitions is four, and the latency is less than 1.3 s for 4-MB data. Therefore, the system provides a visualization platform with acceptable system response, and Internet managers would consider the proposed system as the management tool. © 2014 IEEE.

关键词： Engines

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Log Preservation in Custody Dual Blockchain With Energy Regime and Obfuscation Shuffle

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IEEE Transactions on Network science and engineering 2024年第4期11卷 3495-3511页

作者： Chew, Chit-Jie Lee, Wei-Bin Chen, Tzu-Hao Lin, Iuon-Chang Lee, Jung-San Feng Chia University Department of Information Engineering and Computer Science Taichung407 Taiwan Hon Hai Research Institute Information Security Research Center Taipei236 Taiwan National Chung Hsing University Department of Management Information Systems Taichung402 Taiwan

The rise of cybercrime has led to an explosion of threats in recent years, resulting in the increasingly important of digital forensics. To achieve successful investigation and prosecution, the log preservation is a critical aspect of incident response. The blockchain technology is considered as one of the powerful log storage mechanism, which bringing data transparency and non-tempering property aside from taking off the hypothesis of a trusted third party. Nevertheless, the sensitivity of the data makes it vulnerable to malicious attacks, and the adoption of blockchain has significantly burdened participants regarding consensus time and storage. To address these challenges, we aim to develop a custody dual blockchain (CDB) to secure the confidentiality and integrity of log data. The design of reputation consensus attains that only attractive participants need to offer computation and storage for efficiency enhancing, while the energy regime constructs a positive feedback loop that invigorates users to contribute to CDB. Moreover, the obfuscation shuffle effectively obscures the explicit log plaintext to prevent illegal access. Thus, the confidential data on the CDB nodes can even be used as evidence of digital forensics. Simulation results have demonstrated that the ledger overhead can be significantly reduced, and CDB could pass the robust examination of two formal proof tools: Proverif (Blanchet et al. 2021) and AVISPA. © 2013 IEEE.

关键词： Blockchain

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Federated Learning Integration in O- RAN: A Concise Review 33

Federated Learning Integration in O- RAN: A Concise Review

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33rd International Telecommunication Networks and Applications Conference, ITNAC 2023

作者： Islam, Noureen Monir, Fahad Mahbubul Syeed, M.M. Hasan, Mahady Uddin, Mohammad Faisal Independent University Department of Computer Science & Engineering Bangladesh Independent University RIoT Research Center Bangladesh

ISBN: (纸本)9798350317138

The rapid growth of the telecommunication industry presents a global challenge in maintaining data security and privacy amid increasing data traffic and diverse applications. Applying Federated Learning (FL) to the upcoming Next Generation Wireless Networks (NextG) or Open Radio Access Network (O-RAN) holds great potential as a solution for addressing these challenges. With this in consideration, our paper explores a secure and privacy-conscious solution, focusing on the potential of FL in upcoming wireless networks or O-RAN. FL's cooperative learning approach ensures data confidentiality, offering significant advancements in security issues associated with growing user numbers, and supports the migration to the NextG. In this paper, the concise review provides valuable insights into O-RAN, FL, and related works, with an emphasis on security and privacy. Additionally, it explores framework utilization and outlines future research directions for integrating FL within O-RAN. This approach aims to offer the readers a quick and clear understanding of FL integration within O-RAN, avoiding the need to navigate through extensive survey papers. © 2023 IEEE.

关键词： Wireless networks

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