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  • Open Access

    ARTICLE

    Modeling for application data with 3D spatiale feature in MADS

    Chamseddine Zaki1 , Mohamed Ayet1,2, Allah Bilel Soussi2

    Revue Internationale de Géomatique, Vol.29, No.3, pp. 255-262, 2019, DOI:10.3166/rig.2019.00086

    Abstract A conceptual spatiotemporal data model must be able to offer users a semantic richness of expression to meet their diverse needs concerning the modeling of spatio-temporal data. The conceptual spatiotemporal data model must be able to represent the objects, relationships and events that can occur in a field of study, track data history, support the multirepresentation of these data, and represent temporal and spatial data with two and three dimensions features. The model must also allow the assignment of different types of constraints to relations and provide a complete orthogonality between dimensions and concepts. The More >

  • Open Access

    ARTICLE

    La genèse systémique d’empreinte pour une maîtrise de l’observation de la Terre

    Mireille Fargette1 , Maud Loireau2, Najet Raouani3 , Thérèse Libourel4

    Revue Internationale de Géomatique, Vol.31, No.1, pp. 135-197, 2022, DOI:10.3166/RIG31.135-197

    Abstract Ce travail s’intéresse à l’observation, à la connaissance scientifique construite à partir de ce qui est perçu (Lien de Sens) d’un monde systémique complexe. La démarche conduit à proposer le concept d’empreinte dans le cadre scientifique interdisciplinaire « Système - Réalité - Monde perçu - Modèle », à le mettre à l’épreuve des données, puis à proposer la démarche d’ontologie systémique. Celle-ci permet de déployer le Lien de Forme du domaine systémique au monde perçu, d’analyser et décrire la part pertinente de la donnée et de montrer en quoi l’ensemble de ce travail essentiellement symbolique More >

  • Open Access

    ARTICLE

    RESEARCH ON A NOVEL CONCEPT OF SELF-FORMING AIR COOLING BATTERY RACK

    Mingjie Zhanga , Kai Yanga, Le Qinb, Xiaole Yaob, Qian Liub, Xing Jub,*

    Frontiers in Heat and Mass Transfer, Vol.19, pp. 1-10, 2022, DOI:10.5098/hmt.19.13

    Abstract Lithium-ion batteries used for energy storage systems will release amount of heat during operation. It will cause serious consequences of thermal runaway if not dissipate in time. In this study, a self-forming air-cooled battery rack of the energy storage system is established based on the normal battery rack for energy storage and the shape of the energy storage battery itself. The frames of the battery rack acts as air ducts, which greatly reduce the system complexity. In this paper, the heat generation model is established based on the experiment, and the four battery rack forms… More >

  • Open Access

    ARTICLE

    Analysis of the Hydraulic Performances of a New Liquid Emitter Based on a Leaf Vein Concept

    Tianyu Xu, Zhouming Su, Yanru Su, Zonglei Li, Quanjie Chen, Shuteng Zhi, Ennan Zheng*, Kaili Meng

    FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.8, pp. 2147-2160, 2023, DOI:10.32604/fdmp.2023.025556

    Abstract The leaf-vein drip irrigation emitter is a new type of drip emitter based on a bionic structure able to support shunting, sharp turns, and increased dissipation. In the present work, the results of twenty-five tests executed in the framework of an orthogonal design strategy are presented in order to clarify the influence of the geometrical parameters of the flow channel on the hydraulic characteristics of such emitter. The corresponding flow index and head loss coefficient are determined through numerical simulations and model testing. The results show that the flow index of the flow channel is… More >

  • Open Access

    REVIEW

    Subspace Clustering in High-Dimensional Data Streams: A Systematic Literature Review

    Nur Laila Ab Ghani1,2,*, Izzatdin Abdul Aziz1,2, Said Jadid AbdulKadir1,2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4649-4668, 2023, DOI:10.32604/cmc.2023.035987

    Abstract Clustering high dimensional data is challenging as data dimensionality increases the distance between data points, resulting in sparse regions that degrade clustering performance. Subspace clustering is a common approach for processing high-dimensional data by finding relevant features for each cluster in the data space. Subspace clustering methods extend traditional clustering to account for the constraints imposed by data streams. Data streams are not only high-dimensional, but also unbounded and evolving. This necessitates the development of subspace clustering algorithms that can handle high dimensionality and adapt to the unique characteristics of data streams. Although many articles… More >

  • Open Access

    ARTICLE

    Concept Drift Analysis and Malware Attack Detection System Using Secure Adaptive Windowing

    Emad Alsuwat1,*, Suhare Solaiman1, Hatim Alsuwat2

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 3743-3759, 2023, DOI:10.32604/cmc.2023.035126

    Abstract Concept drift is a main security issue that has to be resolved since it presents a significant barrier to the deployment of machine learning (ML) models. Due to attackers’ (and/or benign equivalents’) dynamic behavior changes, testing data distribution frequently diverges from original training data over time, resulting in substantial model failures. Due to their dispersed and dynamic nature, distributed denial-of-service attacks pose a danger to cybersecurity, resulting in attacks with serious consequences for users and businesses. This paper proposes a novel design for concept drift analysis and detection of malware attacks like Distributed Denial of… More >

  • Open Access

    ARTICLE

    In vitro polymerization of the dopamine-borate melanin precursor: A proof-of-concept regarding boron neutron-capture therapy for melanoma

    JUAN C. STOCKERT1,2,*, SILVINA A. ROMERO1, MARCELO N. FELIX-POZZI3, ALFONSO BLÁZQUEZ-CASTRO4

    BIOCELL, Vol.47, No.4, pp. 919-928, 2023, DOI:10.32604/biocell.2023.026631

    Abstract

    The 10boron neutron-capture therapy (BNCT) is an emerging antitumoral method that shows increasing biomedical interest. BNCT is based on the selective accumulation of the 10boron isotope within the tumor, which is then irradiated with low-energy thermal neutrons, generating nuclear fission that produces 7lithium, 4helium, and γ rays. Simple catechol-borate esters have been rather overlooked as precursors of melanin biosynthesis, and therefore, a proof-of-concept approach for using dopamine-borate (DABO) as a suitable boron-containing candidate for potential BNCT is presented here. DABO can spontaneously oxidize and autopolymerize in vitro, giving a soluble, eumelanin-like brown-black poly-DABO product. Melanotic melanoma cell cultures treated

    More >

  • Open Access

    ARTICLE

    Combined Effect of Concept Drift and Class Imbalance on Model Performance During Stream Classification

    Abdul Sattar Palli1,6,*, Jafreezal Jaafar1,2, Manzoor Ahmed Hashmani1,3, Heitor Murilo Gomes4,5, Aeshah Alsughayyir7, Abdul Rehman Gilal1

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1827-1845, 2023, DOI:10.32604/cmc.2023.033934

    Abstract Every application in a smart city environment like the smart grid, health monitoring, security, and surveillance generates non-stationary data streams. Due to such nature, the statistical properties of data changes over time, leading to class imbalance and concept drift issues. Both these issues cause model performance degradation. Most of the current work has been focused on developing an ensemble strategy by training a new classifier on the latest data to resolve the issue. These techniques suffer while training the new classifier if the data is imbalanced. Also, the class imbalance ratio may change greatly from… More >

  • Open Access

    ARTICLE

    Drift Detection Method Using Distance Measures and Windowing Schemes for Sentiment Classification

    Idris Rabiu1,3,*, Naomie Salim2, Maged Nasser1,4, Aminu Da’u1, Taiseer Abdalla Elfadil Eisa5, Mhassen Elnour Elneel Dalam6

    CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 6001-6017, 2023, DOI:10.32604/cmc.2023.035221

    Abstract Textual data streams have been extensively used in practical applications where consumers of online products have expressed their views regarding online products. Due to changes in data distribution, commonly referred to as concept drift, mining this data stream is a challenging problem for researchers. The majority of the existing drift detection techniques are based on classification errors, which have higher probabilities of false-positive or missed detections. To improve classification accuracy, there is a need to develop more intuitive detection techniques that can identify a great number of drifts in the data streams. This paper presents… More >

  • Open Access

    ARTICLE

    Seismic Liquefaction Resistance Based on Strain Energy Concept Considering Fine Content Value Effect and Performance Parametric Sensitivity Analysis

    Nima Pirhadi1, Xusheng Wan1, Jianguo Lu1, Jilei Hu2,3,*, Mahmood Ahmad4,5, Farzaneh Tahmoorian6

    CMES-Computer Modeling in Engineering & Sciences, Vol.135, No.1, pp. 733-754, 2023, DOI:10.32604/cmes.2022.022207

    Abstract Liquefaction is one of the most destructive phenomena caused by earthquakes, which has been studied in the issues of potential, triggering and hazard analysis. The strain energy approach is a common method to investigate liquefaction potential. In this study, two Artificial Neural Network (ANN) models were developed to estimate the liquefaction resistance of sandy soil based on the capacity strain energy concept (W) by using laboratory test data. A large database was collected from the literature. One group of the dataset was utilized for validating the process in order to prevent overtraining the presented model. To… More >

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