Farhad Mortezapour Shiri^1,*, Ehsan Ahmadi², Mohammadreza Rezaee¹, Thinagaran Perumal¹

Journal on Artificial Intelligence, Vol.6, pp. 85-103, 2024, DOI:10.32604/jai.2024.048911

Abstract Automatic detection of student engagement levels from videos, which is a spatio-temporal classification problem is crucial for enhancing the quality of online education. This paper addresses this challenge by proposing four novel hybrid end-to-end deep learning models designed for the automatic detection of student engagement levels in e-learning videos. The evaluation of these models utilizes the DAiSEE dataset, a public repository capturing student affective states in e-learning scenarios. The initial model integrates EfficientNetV2-L with Gated Recurrent Unit (GRU) and attains an accuracy of 61.45%. Subsequently, the second model combines EfficientNetV2-L with bidirectional GRU (Bi-GRU), yielding an accuracy of 61.56%. The… More >

Yiyi Cen^1,3, Wenzheng Jia², Wen Dai^3,*, Chun Wang⁴, He Wu¹

Revue Internationale de Géomatique, Vol.33, pp. 93-109, 2024, DOI:10.32604/rig.2024.050273

Abstract Color, as a significant element of village landscapes, serves various functions such as enhancing aesthetic appeal and attractiveness, conveying emotions and cultural values. To explore the three-dimensional spatial characteristics of color landscapes in beautiful villages, this study conducted a comparative experiment involving eight provincial-level beautiful villages and eight ordinary villages in Jinzhai County. Landscape pattern indices were used to analyze the color landscape patterns on the facades of these villages, complemented by a quantitative analysis of color attributes using the Munsell color system. The results indicate that (1) Natural landscape colors in beautiful villages are primarily concentrated in the yellow-red… More >

Xianwei Jiang¹, Yanqiong Zhang^1,*, Juan Lei¹, Yudong Zhang^2,3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.140, No.1, pp. 1-40, 2024, DOI:10.32604/cmes.2024.047649

Abstract Research on Chinese Sign Language (CSL) provides convenience and support for individuals with hearing impairments to communicate and integrate into society. This article reviews the relevant literature on Chinese Sign Language Recognition (CSLR) in the past 20 years. Hidden Markov Models (HMM), Support Vector Machines (SVM), and Dynamic Time Warping (DTW) were found to be the most commonly employed technologies among traditional identification methods. Benefiting from the rapid development of computer vision and artificial intelligence technology, Convolutional Neural Networks (CNN), 3D-CNN, YOLO, Capsule Network (CapsNet) and various deep neural networks have sprung up. Deep Neural Networks (DNNs) and their derived… More >

Mahmood A. Mahmood^1,2,*, Khalaf Alsalem¹

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3431-3448, 2024, DOI:10.32604/cmc.2024.047604

Abstract Olive trees are susceptible to a variety of diseases that can cause significant crop damage and economic losses. Early detection of these diseases is essential for effective management. We propose a novel transformed wavelet, feature-fused, pre-trained deep learning model for detecting olive leaf diseases. The proposed model combines wavelet transforms with pre-trained deep-learning models to extract discriminative features from olive leaf images. The model has four main phases: preprocessing using data augmentation, three-level wavelet transformation, learning using pre-trained deep learning models, and a fused deep learning model. In the preprocessing phase, the image dataset is augmented using techniques such as… More >

Zhaoliang Wu¹, Yuewei Wu^1,2, Xiaoli Feng¹, Jiajun Zou³, Fulian Yin^1,2,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3391-3412, 2024, DOI:10.32604/cmc.2024.047076

Abstract Aspect-Based Sentiment Analysis (ABSA) is a fundamental area of research in Natural Language Processing (NLP). Within ABSA, Aspect Sentiment Quad Prediction (ASQP) aims to accurately identify sentiment quadruplets in target sentences, including aspect terms, aspect categories, corresponding opinion terms, and sentiment polarity. However, most existing research has focused on English datasets. Consequently, while ASQP has seen significant progress in English, the Chinese ASQP task has remained relatively stagnant. Drawing inspiration from methods applied to English ASQP, we propose Chinese generation templates and employ prompt-based instruction learning to enhance the model’s understanding of the task, ultimately improving ASQP performance in the… More >

Xuelong Wu¹, Junsheng Wang^1,*, Zhongyao Li¹, Yisheng Miao¹, Chengpeng Xue¹, Yuling Lang², Decai Kong², Xiaoying Ma², Haibao Qiao²

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 3703-3720, 2024, DOI:10.32604/cmc.2024.047027

Abstract X-ray Computed Tomography (XCT) enables non-destructive acquisition of the internal structure of materials, and image segmentation plays a crucial role in analyzing material XCT images. This paper proposes an image segmentation method based on the Segment Anything model (SAM). We constructed a dataset of carbide in nickel-based single crystal superalloys XCT images and preprocessed the images using median filtering, histogram equalization, and gamma correction. Subsequently, SAM was fine-tuned to adapt to the task of material XCT image segmentation, resulting in Material-SAM. We compared the performance of threshold segmentation, SAM, U-Net model, and Material-SAM. Our method achieved 88.45% Class Pixel Accuracy… More >

Roba Tarek AbdelFatah^*, Irene S. Fahim, Mohamed Mahran Kasem

Frontiers in Heat and Mass Transfer, Vol.22, No.1, pp. 317-339, 2024, DOI:10.32604/fhmt.2023.044706

Abstract Parabolic trough solar collectors (PTCs) are among the most cost-efficient solar thermal technologies. They have several applications, such as feed heaters, boilers, steam generators, and electricity generators. A PTC is a concentrated solar power system that uses parabolic reflectors to focus sunlight onto a tube filled with heat-transfer fluid. PTCs performance can be investigated using optical and thermal mathematical models. These models calculate the amount of energy entering the receiver, the amount of usable collected energy, and the amount of heat loss due to convection and radiation. There are several methods and configurations that have been developed so far; however,… More > Graphic Abstract

LU ZHANG^*, JINGUO CHU^*, YUSHAN YU

Oncology Research, Vol.32, No.4, pp. 703-716, 2024, DOI:10.32604/or.2023.030988

Abstract Background: Limited research has been conducted on the influence of autophagy-associated long non-coding RNAs (ARLncRNAs) on the prognosis of hepatocellular carcinoma (HCC). Methods: We analyzed 371 HCC samples from TCGA, identifying expression networks of ARLncRNAs using autophagy-related genes. Screening for prognostically relevant ARLncRNAs involved univariate Cox regression, Lasso regression, and multivariate Cox regression. A Nomogram was further employed to assess the reliability of Riskscore, calculated from the signatures of screened ARLncRNAs, in predicting outcomes. Additionally, we compared drug sensitivities in patient groups with differing risk levels and investigated potential biological pathways through enrichment analysis, using consensus clustering to identify subgroups… More >

Seoyun Kim^1,#, Hyerim Yu^2,#, Jeewoo Yoon^1,3, Eunil Park^1,2,*

Computer Systems Science and Engineering, Vol.48, No.2, pp. 413-429, 2024, DOI:10.32604/csse.2023.041575

Abstract Given the increasing number of countries reporting degraded air quality, effective air quality monitoring has become a critical issue in today’s world. However, the current air quality observatory systems are often prohibitively expensive, resulting in a lack of observatories in many regions within a country. Consequently, a significant problem arises where not every region receives the same level of air quality information. This disparity occurs because some locations have to rely on information from observatories located far away from their regions, even if they may be the closest available options. To address this challenge, a novel approach that leverages machine… More >

Arvind Pattamatta^a,*, Ghanshyam Singh^b

Frontiers in Heat and Mass Transfer, Vol.3, No.2, pp. 1-11, 2012, DOI:10.5098/hmt.v3.2.3005

Abstract The present study deals with the assessment of different turbulence models for heated wall jet flow. The velocity field and thermal characteristics for isothermal and uniform heat flux surfaces in the presence of wall jet flow have been predicted using different turbulence models and the results are compared against the experimental data of Wygnanski et al. (1992), Schneider and Goldstein (1994), and AbdulNour et al. (2000). Thirteen different turbulence models are considered for validation, which include the Standard k-ε (SKE), Realizable k-ε (RKE), shear stress transport (SST), Sarkar & So (SSA), v ² -f, Reynolds stress Model (RSM), and Spalart… More >