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  • Open Access

    ARTICLE

    Efficient Intelligent E-Learning Behavior-Based Analytics of Student’s Performance Using Deep Forest Model

    Raed Alotaibi1, Omar Reyad2,3, Mohamed Esmail Karar4,*

    Computer Systems Science and Engineering, Vol.48, No.5, pp. 1133-1147, 2024, DOI:10.32604/csse.2024.053358

    Abstract E-learning behavior data indicates several students’ activities on the e-learning platform such as the number of accesses to a set of resources and number of participants in lectures. This article proposes a new analytics system to support academic evaluation for students via e-learning activities to overcome the challenges faced by traditional learning environments. The proposed e-learning analytics system includes a new deep forest model. It consists of multistage cascade random forests with minimal hyperparameters compared to traditional deep neural networks. The developed forest model can analyze each student’s activities during the use of an e-learning… More >

  • Open Access

    ARTICLE

    Analysis of System Value Evolution Trends of Energy Storage in Decarbonization Process

    Mo Zhou1, Jingming Zhao1, Zili Chen2,*, Qiushi Fang1, Hua Li1, Zhaoyuan Wu2

    Energy Engineering, Vol.121, No.10, pp. 3037-3053, 2024, DOI:10.32604/ee.2024.050842

    Abstract With the continuous expansion of the scale of renewable energy installation, the demand for energy storage has increased significantly. However, there are significant differences in the value of energy storage in different scenarios, and the phenomenon of diminishing marginal benefits of energy storage is becoming more apparent. Therefore, the multi-dimensional value evolution trend of energy storage has become a key issue. This study selects indicators from three dimensions of energy storage: low-carbon emission reduction, smoothing wind and solar power fluctuations, and saving generation costs, quantifying the economic, environmental, and technical values of energy storage. This… More >

  • Open Access

    ARTICLE

    Evaluation of Mechanical Properties and Surface Quality of Wood from Bosnia and Herzegovina Exposed to Outdoor Conditions

    Redžo Hasanagić1,*, Umejr Šljivo1, Leila Fathi2, Pallavi Gautam3, Mohsen Bahmani2,*, Miha Humar4

    Journal of Renewable Materials, Vol.12, No.8, pp. 1417-1431, 2024, DOI:10.32604/jrm.2024.052826

    Abstract This study investigated the mechanical properties of beech (Fagus sylvatica L.) and fir (Abies alba) wood from Bosnia and Herzegovina under outdoor exposure. Samples were exposed for 3-month exposure to assess bending strength, color changes, and surface quality. Results showed outdoor exposure negatively affected mechanical properties, particularly in samples with extended finger joints, causing significant surface cracks in uncoated samples. Beech wood exhibited notable color changes under exposure, with approximately 50% darkening without coating compared to 25% under covered conditions. Coated samples displayed minimal color changes, affirming the efficacy of surface treatment. Fir wood exhibited a roughness More > Graphic Abstract

    Evaluation of Mechanical Properties and Surface Quality of Wood from Bosnia and Herzegovina Exposed to Outdoor Conditions

  • Open Access

    ARTICLE

    Performance Evaluation of Machine Learning Algorithms in Reduced Dimensional Spaces

    Kaveh Heidary1,*, Venkata Atluri1, John Bland2

    Journal of Cyber Security, Vol.6, pp. 69-87, 2024, DOI:10.32604/jcs.2024.051196

    Abstract This paper investigates the impact of reducing feature-vector dimensionality on the performance of machine learning (ML) models. Dimensionality reduction and feature selection techniques can improve computational efficiency, accuracy, robustness, transparency, and interpretability of ML models. In high-dimensional data, where features outnumber training instances, redundant or irrelevant features introduce noise, hindering model generalization and accuracy. This study explores the effects of dimensionality reduction methods on binary classifier performance using network traffic data for cybersecurity applications. The paper examines how dimensionality reduction techniques influence classifier operation and performance across diverse performance metrics for seven ML models. Four… More >

  • Open Access

    EDITORIAL

    Introduction to the Special Issue on Computer-Aided Uncertainty Modeling and Reliability Evaluation for Complex Engineering Structures

    Debiao Meng1,*, Abílio Manuel Pinho de Jesus2, Zeng Meng3

    CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 1-5, 2024, DOI:10.32604/cmes.2024.056319

    Abstract This article has no abstract. More >

  • Open Access

    ARTICLE

    Enhancing Autonomy Capability in Regional Power Grids: A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

    Jie Ma1, Tong Zhao2, Yuanzhao Hao3, Wenwen Qin2, Haozheng Yu1, Mingxuan Du2, Yuanhong Liu4, Liang Zhang2, Shixia Mu5, Cuiping Li2, Junhui Li2,*

    Energy Engineering, Vol.121, No.9, pp. 2449-2477, 2024, DOI:10.32604/ee.2024.051244

    Abstract After the integration of large-scale Distributed Generation (DG) into the distribution network, the randomness and volatility of its output result in a reduction of spatiotemporal alignment between power generation and demand in the distribution network, exacerbating the phenomenon of wind and solar power wastage. As a novel power system model, the fundamental concept of Regional Autonomous Power Grids (RAPGs) is to achieve localized management and energy autonomy, thereby facilitating the effective consumption of DGs. Therefore, this paper proposes a distributed resource planning strategy that enhances the autonomy capabilities of regional power grids by considering multiple… More > Graphic Abstract

    Enhancing Autonomy Capability in Regional Power Grids: A Strategic Planning Approach with Multiple Autonomous Evaluation Indexes

  • Open Access

    ARTICLE

    Evaluation of Multi-Temporal-Spatial Scale Adjustment Capability and Cluster Optimization Operation Method for Distribution Networks with Distributed Photovoltaics

    Jiaxin Qiao1, Yuchen Hao2, Yingqi Liao3, Fang Liang3, Jing Bian1,*

    Energy Engineering, Vol.121, No.9, pp. 2655-2680, 2024, DOI:10.32604/ee.2024.049509

    Abstract The massive integration of high-proportioned distributed photovoltaics into distribution networks poses significant challenges to the flexible regulation capabilities of distribution stations. To accurately assess the flexible regulation capabilities of distribution stations, a multi-temporal and spatial scale regulation capability assessment technique is proposed for distribution station areas with distributed photovoltaics, considering different geographical locations, coverage areas, and response capabilities. Firstly, the multi-temporal scale regulation characteristics and response capabilities of different regulation resources in distribution station areas are analyzed, and a resource regulation capability model is established to quantify the adjustable range of different regulation resources. On… More >

  • Open Access

    ARTICLE

    PARE: Privacy-Preserving Data Reliability Evaluation for Spatial Crowdsourcing in Internet of Things

    Peicong He, Yang Xin*, Yixian Yang

    CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3067-3084, 2024, DOI:10.32604/cmc.2024.054777

    Abstract The proliferation of intelligent, connected Internet of Things (IoT) devices facilitates data collection. However, task workers may be reluctant to participate in data collection due to privacy concerns, and task requesters may be concerned about the validity of the collected data. Hence, it is vital to evaluate the quality of the data collected by the task workers while protecting privacy in spatial crowdsourcing (SC) data collection tasks with IoT. To this end, this paper proposes a privacy-preserving data reliability evaluation for SC in IoT, named PARE. First, we design a data uploading format using blockchain More >

  • Open Access

    ARTICLE

    Experimental and Numerical Evaluation of the Cavitation Performances of Self-Excited Oscillating Jets

    Yuanyuan Zhao1, Fujian Zhao2, Guohui Li3, Wei Xu4,*, Xiuli Wang2,*

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.8, pp. 1883-1901, 2024, DOI:10.32604/fdmp.2024.047298

    Abstract Self-excited oscillating jets (SOJ) are used in several practical applications. Their performances are significantly affected by structural parameters and the target distance. In this study, a geometric model of the SOJ nozzle accounting for multiple structural parameters is introduced, then the related cavitation performances and the optimal target distance are investigated using a Large-Eddy Simulation (LES) approach. Results are also provided about an experiment, which was conducted to validate the simulation results. By analyzing the evolution of the vapor volume fraction at the nozzle outlet, a discussion is presented about the effect of the aforementioned… More >

  • Open Access

    REVIEW

    Processus pour le développement d’une stratégie d’évaluation de la qualité de vie en cancer avancé pédiatrique

    Lye-Ann Robichaud1,2,3, Marianne Olivier-D’Avignon4, Julie Felipe1, Hermann Ferdinand Thomas Ehrenfeld1,2,3, Marc-Antoine Marquis5,6, Bruno Michon7,8, Émélie Rondeau2,3, Mathias Tyo-Gomez9, Michel Duval5,10, Serge Sultan1,2,3,5,10,*

    Psycho-Oncologie, Vol.18, No.2, pp. 127-135, 2024, DOI:10.32604/po.2024.046496

    Abstract En contexte de cancer avancé pédiatrique, c’est-à-dire quand les traitements visant le cancer ne sont pas efficaces, les soins offerts aux patients ont une visée palliative pour limiter les symptômes et optimiser la qualité de vie (QdV). Pour orienter ces soins, il est nécessaire de connaître et mesurer ce qui est important pour les jeunes dans cette situation. Malheureusement, il existe très peu d’outils disponibles. L’objectif de cet article est de décrire le processus de développement d’une nouvelle méthode d’évaluation de la QdV qui s’adresse spécifiquement au contexte de cancer avancé pédiatrique, le programme Advance… More >

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