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  • Open Access

    REVIEW

    Mitigating Urban Heat Island Effects: A Review of Innovative Pavement Technologies and Integrated Solutions

    S. F. Ismael1,2,*, A. H. Alias1, N. A. Haron1, B. B. Zaidan3, Abdulrahman M. Abdulghani4

    Structural Durability & Health Monitoring, Vol.18, No.5, pp. 525-551, 2024, DOI:10.32604/sdhm.2024.050088

    Abstract In this review paper, we present a thorough investigation into the role of pavement technologies in advancing urban sustainability. Our analysis traverses the historical evolution of these technologies, meticulously evaluating their socio-economic and environmental impacts, with a particular emphasis on their role in mitigating the urban heat island effect. The evaluation of pavement types and variables influencing pavement performance to be used in the multi-criteria decision-making (MCDM) framework to choose the optimal pavement application are at the heart of our research. Which serves to assess a spectrum of pavement options, revealing insights into the most More >

  • Open Access

    ARTICLE

    Study of a Hydraulic Jump in an Asymmetric Trapezoidal Channel with Different Sluice Gates

    Bouthaina Debabeche1,2,*, Sonia Cherhabil3

    FDMP-Fluid Dynamics & Materials Processing, Vol.20, No.7, pp. 1499-1516, 2024, DOI:10.32604/fdmp.2024.047403

    Abstract In this study, the main properties of the hydraulic jump in an asymmetric trapezoidal flume are analyzed experimentally, including the so-called sequent depths, characteristic lengths, and efficiency. In particular, an asymmetric trapezoidal flume with a length of 7 m and a width of 0.304 m is considered, with the bottom of the flume transversely inclined at an angle of m = 0.296 and vertical lateral sides. The corresponding inflow Froude number is allowed to range in the interval (1.40 < F1 < 6.11). The properties of this jump are compared to those of hydraulic jumps More >

  • Open Access

    ARTICLE

    Sentiment Analysis Using E-Commerce Review Keyword-Generated Image with a Hybrid Machine Learning-Based Model

    Jiawen Li1,2, Yuesheng Huang1, Yayi Lu1, Leijun Wang1,*, Yongqi Ren1, Rongjun Chen1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1581-1599, 2024, DOI:10.32604/cmc.2024.052666

    Abstract In the context of the accelerated pace of daily life and the development of e-commerce, online shopping is a mainstream way for consumers to access products and services. To understand their emotional expressions in facing different shopping experience scenarios, this paper presents a sentiment analysis method that combines the e-commerce review keyword-generated image with a hybrid machine learning-based model, in which the Word2Vec-TextRank is used to extract keywords that act as the inputs for generating the related images by generative Artificial Intelligence (AI). Subsequently, a hybrid Convolutional Neural Network and Support Vector Machine (CNN-SVM) model… More >

  • Open Access

    ARTICLE

    Ensemble Approach Combining Deep Residual Networks and BiGRU with Attention Mechanism for Classification of Heart Arrhythmias

    Batyrkhan Omarov1,2,*, Meirzhan Baikuvekov1, Daniyar Sultan1, Nurzhan Mukazhanov3, Madina Suleimenova2, Maigul Zhekambayeva3

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 341-359, 2024, DOI:10.32604/cmc.2024.052437

    Abstract This research introduces an innovative ensemble approach, combining Deep Residual Networks (ResNets) and Bidirectional Gated Recurrent Units (BiGRU), augmented with an Attention Mechanism, for the classification of heart arrhythmias. The escalating prevalence of cardiovascular diseases necessitates advanced diagnostic tools to enhance accuracy and efficiency. The model leverages the deep hierarchical feature extraction capabilities of ResNets, which are adept at identifying intricate patterns within electrocardiogram (ECG) data, while BiGRU layers capture the temporal dynamics essential for understanding the sequential nature of ECG signals. The integration of an Attention Mechanism refines the model’s focus on critical segments… More >

  • Open Access

    ARTICLE

    Detecting XSS with Random Forest and Multi-Channel Feature Extraction

    Qiurong Qin, Yueqin Li*, Yajie Mi, Jinhui Shen, Kexin Wu, Zhenzhao Wang

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 843-874, 2024, DOI:10.32604/cmc.2024.051769

    Abstract In the era of the Internet, widely used web applications have become the target of hacker attacks because they contain a large amount of personal information. Among these vulnerabilities, stealing private data through cross-site scripting (XSS) attacks is one of the most commonly used attacks by hackers. Currently, deep learning-based XSS attack detection methods have good application prospects; however, they suffer from problems such as being prone to overfitting, a high false alarm rate, and low accuracy. To address these issues, we propose a multi-stage feature extraction and fusion model for XSS detection based on… More >

  • Open Access

    ARTICLE

    Optimized Binary Neural Networks for Road Anomaly Detection: A TinyML Approach on Edge Devices

    Amna Khatoon1, Weixing Wang1,*, Asad Ullah2, Limin Li3,*, Mengfei Wang1

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 527-546, 2024, DOI:10.32604/cmc.2024.051147

    Abstract Integrating Tiny Machine Learning (TinyML) with edge computing in remotely sensed images enhances the capabilities of road anomaly detection on a broader level. Constrained devices efficiently implement a Binary Neural Network (BNN) for road feature extraction, utilizing quantization and compression through a pruning strategy. The modifications resulted in a 28-fold decrease in memory usage and a 25% enhancement in inference speed while only experiencing a 2.5% decrease in accuracy. It showcases its superiority over conventional detection algorithms in different road image scenarios. Although constrained by computer resources and training datasets, our results indicate opportunities for More >

  • Open Access

    ARTICLE

    An Improved Iterated Greedy Algorithm for Solving Rescue Robot Path Planning Problem with Limited Survival Time

    Xiaoqing Wang1, Peng Duan1,*, Leilei Meng1,*, Kaidong Yang2

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 931-947, 2024, DOI:10.32604/cmc.2024.050612

    Abstract Effective path planning is crucial for mobile robots to quickly reach rescue destination and complete rescue tasks in a post-disaster scenario. In this study, we investigated the post-disaster rescue path planning problem and modeled this problem as a variant of the travel salesman problem (TSP) with life-strength constraints. To address this problem, we proposed an improved iterated greedy (IIG) algorithm. First, a push-forward insertion heuristic (PFIH) strategy was employed to generate a high-quality initial solution. Second, a greedy-based insertion strategy was designed and used in the destruction-construction stage to increase the algorithm’s exploration ability. Furthermore,… More >

  • Open Access

    ARTICLE

    Classified VPN Network Traffic Flow Using Time Related to Artificial Neural Network

    Saad Abdalla Agaili Mohamed*, Sefer Kurnaz

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 819-841, 2024, DOI:10.32604/cmc.2024.050474

    Abstract VPNs are vital for safeguarding communication routes in the continually changing cybersecurity world. However, increasing network attack complexity and variety require increasingly advanced algorithms to recognize and categorize VPN network data. We present a novel VPN network traffic flow classification method utilizing Artificial Neural Networks (ANN). This paper aims to provide a reliable system that can identify a virtual private network (VPN) traffic from intrusion attempts, data exfiltration, and denial-of-service assaults. We compile a broad dataset of labeled VPN traffic flows from various apps and usage patterns. Next, we create an ANN architecture that can… More >

  • Open Access

    ARTICLE

    A Multi-Strategy-Improved Northern Goshawk Optimization Algorithm for Global Optimization and Engineering Design

    Liang Zeng1,2, Mai Hu1, Chenning Zhang1, Quan Yuan1, Shanshan Wang1,2,*

    CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1677-1709, 2024, DOI:10.32604/cmc.2024.049717

    Abstract Optimization algorithms play a pivotal role in enhancing the performance and efficiency of systems across various scientific and engineering disciplines. To enhance the performance and alleviate the limitations of the Northern Goshawk Optimization (NGO) algorithm, particularly its tendency towards premature convergence and entrapment in local optima during function optimization processes, this study introduces an advanced Improved Northern Goshawk Optimization (INGO) algorithm. This algorithm incorporates a multifaceted enhancement strategy to boost operational efficiency. Initially, a tent chaotic map is employed in the initialization phase to generate a diverse initial population, providing high-quality feasible solutions. Subsequently, after… More >

  • Open Access

    ABSTRACT

    Abstracts of the XLIII ANNUAL MEETING of ROSARIO SOCIETY OF BIOLOGY

    BIOCELL, Vol.48, Suppl.3, pp. 1-15, 2024

    Abstract This article has no abstract. More >

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