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  • Open Access


    A Novel 6G Scalable Blockchain Clustering-Based Computer Vision Character Detection for Mobile Images

    Yuejie Li1,2,*, Shijun Li3

    CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3041-3070, 2024, DOI:10.32604/cmc.2023.045741

    Abstract 6G is envisioned as the next generation of wireless communication technology, promising unprecedented data speeds, ultra-low Latency, and ubiquitous Connectivity. In tandem with these advancements, blockchain technology is leveraged to enhance computer vision applications’ security, trustworthiness, and transparency. With the widespread use of mobile devices equipped with cameras, the ability to capture and recognize Chinese characters in natural scenes has become increasingly important. Blockchain can facilitate privacy-preserving mechanisms in applications where privacy is paramount, such as facial recognition or personal healthcare monitoring. Users can control their visual data and grant or revoke access as needed.… More >

  • Open Access


    A Health State Prediction Model Based on Belief Rule Base and LSTM for Complex Systems

    Yu Zhao, Zhijie Zhou*, Hongdong Fan, Xiaoxia Han, Jie Wang, Manlin Chen

    Intelligent Automation & Soft Computing, Vol.39, No.1, pp. 73-91, 2024, DOI:10.32604/iasc.2024.042285

    Abstract In industrial production and engineering operations, the health state of complex systems is critical, and predicting it can ensure normal operation. Complex systems have many monitoring indicators, complex coupling structures, non-linear and time-varying characteristics, so it is a challenge to establish a reliable prediction model. The belief rule base (BRB) can fuse observed data and expert knowledge to establish a nonlinear relationship between input and output and has well modeling capabilities. Since each indicator of the complex system can reflect the health state to some extent, the BRB is built based on the causal relationship… More >

  • Open Access


    Experimental Study of the Effect of Water Salinity on the Parameters of an Equilibrium Droplet Cluster Levitating over a Water Layer

    Alexander A. Fedorets1, Eduard E. Kolmakov1, Leonid A. Dombrovsky1,2,3,*

    Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 1-14, 2024, DOI:10.32604/fhmt.2024.049335

    Abstract New experimental results, which are important for the potential use of small levitating droplets as biochemical microreactors, are reported. It is shown that the combination of infrared heating and reduced evaporation of saline water under the droplet cluster is sufficient to produce equilibrium saltwater droplets over a wide temperature range. The resulting universal dependence of droplet size on temperature simplifies the choice of optimal conditions for generating stable droplet clusters with droplets of the desired size. A physical analysis of the experimental results on the equilibrium size of saltwater droplets makes it possible to separate More > Graphic Abstract

    Experimental Study of the Effect of Water Salinity on the Parameters of an Equilibrium Droplet Cluster Levitating over a Water Layer

  • Open Access


    Classification and clustering of buildings for understanding urban dynamics

    A framework for processing spatiotemporal data

    Perez Joan1, Fusco Giovanni1, Sadahiro Yukio2

    Revue Internationale de Géomatique, Vol.31, No.2, pp. 303-327, 2022, DOI:10.3166/RIG.31.303-327©2022

    Abstract This paper presents different methods implemented with the aim of studying urban dynamics at the building level. Building types are identified within a comprehensive vector-based building inventory, spanning over at least two time points. First, basic morphometric indicators are computed for each building: area, floor-area, number of neighbors, elongation, and convexity. Based on the availability of expert knowledge, different types of classification and clustering are performed: supervised tree-like classificatory model, expert-constrained k-means and combined SOM-HCA. A grid is superimposed on the test region of Osaka (Japan) and the number of building types per cell and More >

  • Open Access


    Clustering building morphometrics using national spatial data

    Alessandro Araldi1, David Emsellem2, Giovanni Fusco1, Andrea Tettamanzi3, Denis Overal2

    Revue Internationale de Géomatique, Vol.31, No.2, pp. 265-302, 2022, DOI:10.3166/RIG.31.265-302©2022

    Abstract The identification and description of building typologies play a fundamental role in the understanding of the overall built-up form. A growing body of research is developing and implementing sophisticated, computer-aided protocols for the identification of building typologies. This paper shares the same goal. An innovative data-driven procedure for the unsupervised identification and description of building types and organization is here presented. After a specific pre-processing procedure, we develop an unsupervised clustering combining a new algorithm of Naive Bayes inference and hierarchical ascendant approaches relying on six morphometric features of buildings. This protocol allows us to More >

  • Open Access


    Maximum Correntropy Criterion-Based UKF for Loosely Coupling INS and UWB in Indoor Localization

    Yan Wang*, You Lu, Yuqing Zhou, Zhijian Zhao

    CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 2673-2703, 2024, DOI:10.32604/cmes.2023.046743

    Abstract Indoor positioning is a key technology in today’s intelligent environments, and it plays a crucial role in many application areas. This paper proposed an unscented Kalman filter (UKF) based on the maximum correntropy criterion (MCC) instead of the minimum mean square error criterion (MMSE). This innovative approach is applied to the loose coupling of the Inertial Navigation System (INS) and Ultra-Wideband (UWB). By introducing the maximum correntropy criterion, the MCCUKF algorithm dynamically adjusts the covariance matrices of the system noise and the measurement noise, thus enhancing its adaptability to diverse environmental localization requirements. Particularly in… More >

  • Open Access


    Unknown DDoS Attack Detection with Fuzzy C-Means Clustering and Spatial Location Constraint Prototype Loss

    Thanh-Lam Nguyen1, Hao Kao1, Thanh-Tuan Nguyen2, Mong-Fong Horng1,*, Chin-Shiuh Shieh1,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2181-2205, 2024, DOI:10.32604/cmc.2024.047387

    Abstract Since its inception, the Internet has been rapidly evolving. With the advancement of science and technology and the explosive growth of the population, the demand for the Internet has been on the rise. Many applications in education, healthcare, entertainment, science, and more are being increasingly deployed based on the internet. Concurrently, malicious threats on the internet are on the rise as well. Distributed Denial of Service (DDoS) attacks are among the most common and dangerous threats on the internet today. The scale and complexity of DDoS attacks are constantly growing. Intrusion Detection Systems (IDS) have… More >

  • Open Access


    Robust and Trustworthy Data Sharing Framework Leveraging On-Chain and Off-Chain Collaboration

    Jinyang Yu1,2, Xiao Zhang1,2,3,*, Jinjiang Wang1,2, Yuchen Zhang1,2, Yulong Shi1,2, Linxuan Su1,2, Leijie Zeng1,2,*

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2159-2179, 2024, DOI:10.32604/cmc.2024.047340

    Abstract The proliferation of Internet of Things (IoT) systems has resulted in the generation of substantial data, presenting new challenges in reliable storage and trustworthy sharing. Conventional distributed storage systems are hindered by centralized management and lack traceability, while blockchain systems are limited by low capacity and high latency. To address these challenges, the present study investigates the reliable storage and trustworthy sharing of IoT data, and presents a novel system architecture that integrates on-chain and off-chain data manage systems. This architecture, integrating blockchain and distributed storage technologies, provides high-capacity, high-performance, traceable, and verifiable data storage… More >

  • Open Access


    A Trust Evaluation Mechanism Based on Autoencoder Clustering Algorithm for Edge Device Access of IoT

    Xiao Feng1,2,3,*, Zheng Yuan1

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1881-1895, 2024, DOI:10.32604/cmc.2023.047243

    Abstract First, we propose a cross-domain authentication architecture based on trust evaluation mechanism, including registration, certificate issuance, and cross-domain authentication processes. A direct trust evaluation mechanism based on the time decay factor is proposed, taking into account the influence of historical interaction records. We weight the time attenuation factor to each historical interaction record for updating and got the new historical record data. We refer to the beta distribution to enhance the flexibility and adaptability of the direct trust assessment model to better capture time trends in the historical record. Then we propose an autoencoder-based trust… More >

  • Open Access


    A Machine Learning Approach to User Profiling for Data Annotation of Online Behavior

    Moona Kanwal1,2,*, Najeed A. Khan1, Aftab A. Khan3

    CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2419-2440, 2024, DOI:10.32604/cmc.2024.047223

    Abstract The user’s intent to seek online information has been an active area of research in user profiling. User profiling considers user characteristics, behaviors, activities, and preferences to sketch user intentions, interests, and motivations. Determining user characteristics can help capture implicit and explicit preferences and intentions for effective user-centric and customized content presentation. The user’s complete online experience in seeking information is a blend of activities such as searching, verifying, and sharing it on social platforms. However, a combination of multiple behaviors in profiling users has yet to be considered. This research takes a novel approach… More >

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