Home / Advanced Search

  • Title/Keywords

  • Author/Affliations

  • Journal

  • Article Type

  • Start Year

  • End Year

Update SearchingClear
  • Articles
  • Online
Search Results (102)
  • Open Access

    ARTICLE

    Intrusion Detection Model Using Chaotic MAP for Network Coding Enabled Mobile Small Cells

    Chanumolu Kiran Kumar, Nandhakumar Ramachandran*

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3151-3176, 2024, DOI:10.32604/cmc.2023.043534

    Abstract Wireless Network security management is difficult because of the ever-increasing number of wireless network malfunctions, vulnerabilities, and assaults. Complex security systems, such as Intrusion Detection Systems (IDS), are essential due to the limitations of simpler security measures, such as cryptography and firewalls. Due to their compact nature and low energy reserves, wireless networks present a significant challenge for security procedures. The features of small cells can cause threats to the network. Network Coding (NC) enabled small cells are vulnerable to various types of attacks. Avoiding attacks and performing secure “peer” to “peer” data transmission is a challenging task in small… More >

  • Open Access

    ARTICLE

    A Normalizing Flow-Based Bidirectional Mapping Residual Network for Unsupervised Defect Detection

    Lanyao Zhang1, Shichao Kan2, Yigang Cen3, Xiaoling Chen1, Linna Zhang1,*, Yansen Huang4,5

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1631-1648, 2024, DOI:10.32604/cmc.2024.046924

    Abstract Unsupervised methods based on density representation have shown their abilities in anomaly detection, but detection performance still needs to be improved. Specifically, approaches using normalizing flows can accurately evaluate sample distributions, mapping normal features to the normal distribution and anomalous features outside it. Consequently, this paper proposes a Normalizing Flow-based Bidirectional Mapping Residual Network (NF-BMR). It utilizes pre-trained Convolutional Neural Networks (CNN) and normalizing flows to construct discriminative source and target domain feature spaces. Additionally, to better learn feature information in both domain spaces, we propose the Bidirectional Mapping Residual Network (BMR), which maps sample features to these two spaces… More > Graphic Abstract

    A Normalizing Flow-Based Bidirectional Mapping Residual Network for Unsupervised Defect Detection

  • Open Access

    ARTICLE

    Mapping of Land Use and Land Cover (LULC) Using EuroSAT and Transfer Learning

    Suman Kunwar1,*, Jannatul Ferdush2

    Revue Internationale de Géomatique, Vol.33, pp. 1-13, 2024, DOI:10.32604/rig.2023.047627

    Abstract As the global population continues to expand, the demand for natural resources increases. Unfortunately, human activities account for 23% of greenhouse gas emissions. On a positive note, remote sensing technologies have emerged as a valuable tool in managing our environment. These technologies allow us to monitor land use, plan urban areas, and drive advancements in areas such as agriculture, climate change mitigation, disaster recovery, and environmental monitoring. Recent advances in Artificial Intelligence (AI), computer vision, and earth observation data have enabled unprecedented accuracy in land use mapping. By using transfer learning and fine-tuning with red-green-blue (RGB) bands, we achieved an… More > Graphic Abstract

    Mapping of Land Use and Land Cover (LULC) Using EuroSAT and Transfer Learning

  • Open Access

    ARTICLE

    Contributions of Remote Sensing and GIS to the Inventory and Mapping of Colonial Geodetic Markers in the Katangese Copper Belt

    John Tshibangu Wa Ilunga1,*, Donatien Kamutanda Kalombo1, Olivier Ngoie Inabanza1, Dikumbwa N’landu1,2, Joseph Mukalay Muamba1,3, Patrice Amisi Mwana1, Urcel Kalenga Tshingomba1, Junior Muyumba Munganga1, Catherine Nsiami Mabiala1

    Revue Internationale de Géomatique, Vol.33, pp. 15-35, 2024, DOI:10.32604/rig.2024.046629

    Abstract The mutation of spaces observed in the Katangese Copper Belt (KCB) causes significant topographical changes. Some colonial geodetic markers are easily noticeable on many of the hills making up the KCB. These hills are subject to mining which ruins the completeness of the network of triangulations: geometric and trigonometric Katangese. In order to keep control of the latter, the study shows on the one hand the possibility of using SRTM data (Shuttle Radar Topography Mission) in the monitoring of the macro-change of the reliefs, from 442 positions, and on the other hand, an indirect (remote) inventory method of the existing… More >

  • Open Access

    ARTICLE

    Optical Based Gradient-Weighted Class Activation Mapping and Transfer Learning Integrated Pneumonia Prediction Model

    Chia-Wei Jan1, Yu-Jhih Chiu1, Kuan-Lin Chen2, Ting-Chun Yao3, Ping-Huan Kuo1,4,*

    Computer Systems Science and Engineering, Vol.47, No.3, pp. 2989-3010, 2023, DOI:10.32604/csse.2023.042078

    Abstract Pneumonia is a common lung disease that is more prone to affect the elderly and those with weaker respiratory systems. However, hospital medical resources are limited, and sometimes the workload of physicians is too high, which can affect their judgment. Therefore, a good medical assistance system is of great significance for improving the quality of medical care. This study proposed an integrated system by combining transfer learning and gradient-weighted class activation mapping (Grad-CAM). Pneumonia is a common lung disease that is generally diagnosed using X-rays. However, in areas with limited medical resources, a shortage of medical personnel may result in… More >

  • Open Access

    REVIEW

    An Overview of Modern Cartographic Trends Aligned with the ICA’s Perspective

    Maan Habib1,*, Maan Okayli2

    Revue Internationale de Géomatique, Vol.32, pp. 1-16, 2023, DOI:10.32604/rig.2023.043399

    Abstract This study provides a comprehensive overview of modern cartography innovations and emerging trends, highlighting the importance of geospatial representation in various fields. It discusses recent advancements in geospatial data collection techniques, including satellite and aerial imagery, Light Detection and Ranging (LiDAR) technology, and crowdsourcing. The research also investigates the integration of big data, machine learning, and real-time processing in Geographic Information Systems (GIS), as well as advances in geospatial visualization. In addition, it examines the role of cartography in addressing global challenges such as climate change, disaster management, and urban planning in line with the International Cartographic Association’s (ICA) perspectives.… More >

  • Open Access

    ARTICLE

    Design and Production of a Patient Guide to Support Return to Work after Breast Cancer: An Application of Intervention Mapping

    Conception et production d’un guide patient pour accompagner la reprise du travail après un cancer du sein : une application de l’Intervention Mapping

    Guillaume Broc1,*, Julien Carretier2,3, Sabrina Rouat4, Laure Guittard5,6, Julien Péron7,8, Béatrice Fervers3,9, Laurent Letrilliart6,10, Philippe Sarnin4, Jean-Baptiste Fassier11,12, Marion Lamort-Bouché6,10

    Psycho-Oncologie, Vol.17, No.3, pp. 167-179, 2023, DOI:10.32604/po.2023.044730

    Abstract Aims: Return to work (RTW) after breast cancer is a complex process that questions the individual trajectories of patients and stakeholders. Program planning in this context requires relying on appropriate methods like Intervention Mapping (IM) which encompasses such complexity. The aim of the methodological study is to describe an application of IM for both the design and production of a patient guide supporting RTW after breast cancer. Procedure: According to IM, the guide was co-constructed with a Community Advisory Board (CAB) of stakeholders (patients/associations, health professionals, companies, institutions) after considering other options (interactive website, mobile application). The design was done… More >

  • Open Access

    ARTICLE

    An Improved Honey Badger Algorithm through Fusing Multi-Strategies

    Zhiwei Ye1, Tao Zhao1, Chun Liu1,*, Daode Zhang1, Wanfang Bai2

    CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1479-1495, 2023, DOI:10.32604/cmc.2023.038787

    Abstract The Honey Badger Algorithm (HBA) is a novel meta-heuristic algorithm proposed recently inspired by the foraging behavior of honey badgers. The dynamic search behavior of honey badgers with sniffing and wandering is divided into exploration and exploitation in HBA, which has been applied in photovoltaic systems and optimization problems effectively. However, HBA tends to suffer from the local optimum and low convergence. To alleviate these challenges, an improved HBA (IHBA) through fusing multi-strategies is presented in the paper. It introduces Tent chaotic mapping and composite mutation factors to HBA, meanwhile, the random control parameter is improved, moreover, a diversified updating… More >

  • Open Access

    ARTICLE

    An Improved High Precision 3D Semantic Mapping of Indoor Scenes from RGB-D Images

    Jing Xin1,*, Kenan Du1, Jiale Feng1, Mao Shan2

    CMES-Computer Modeling in Engineering & Sciences, Vol.137, No.3, pp. 2621-2640, 2023, DOI:10.32604/cmes.2023.027467

    Abstract This paper proposes an improved high-precision 3D semantic mapping method for indoor scenes using RGB-D images. The current semantic mapping algorithms suffer from low semantic annotation accuracy and insufficient real-time performance. To address these issues, we first adopt the Elastic Fusion algorithm to select key frames from indoor environment image sequences captured by the Kinect sensor and construct the indoor environment space model. Then, an indoor RGB-D image semantic segmentation network is proposed, which uses multi-scale feature fusion to quickly and accurately obtain object labeling information at the pixel level of the spatial point cloud model. Finally, Bayesian updating is… More >

  • Open Access

    ARTICLE

    Quantitative Trait Loci (QTL) Mapping and Marker Analysis of Fatty Acids in Peanut

    Xiao Han, Songnan Yang, Xueying Li, Qiulin Wu, Yongyi Xing, Jun Zhang*, Fenglou Ling*

    Phyton-International Journal of Experimental Botany, Vol.92, No.9, pp. 2577-2589, 2023, DOI:10.32604/phyton.2023.029440

    Abstract Peanut, with high oil content, has been a major oil and food crop globally. The compositions of the fatty acids are the common factors in determining the oil quality. In the present study, an F2 segregated population with 140 individuals derived from the cross of Weihua8 (a cultivar) and 12L49 (a line with high oleic acid concentration) was used to construct a genetic map and conduct QTL mapping analysis. A total of 103 polymorphic SSR primers were utilized for genotyping the RILs and finally generating the SSR loci. Within the 103 SSR loci, a genetic linkage map, covering a total… More >

Displaying 1-10 on page 1 of 102. Per Page