Puja S. Prasad¹, Adepu Sree Lakshmi¹, Sandeep Kautish², Simar Preet Singh³, Rajesh Kumar Shrivastava³, Abdulaziz S. Almazyad⁴, Hossam M. Zawbaa⁵, Ali Wagdy Mohamed^6,7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 725-739, 2024, DOI:10.32604/cmes.2023.030640

Abstract Pupil dynamics are the important characteristics of face spoofing detection. The face recognition system is one of the most used biometrics for authenticating individual identity. The main threats to the facial recognition system are different types of presentation attacks like print attacks, 3D mask attacks, replay attacks, etc. The proposed model uses pupil characteristics for liveness detection during the authentication process. The pupillary light reflex is an involuntary reaction controlling the pupil’s diameter at different light intensities. The proposed framework consists of two-phase methodologies. In the first phase, the pupil’s diameter is calculated by applying stimulus (light) in one eye… More >

Haoliang Yang^*, Yonggang Dong, Zhifang Yang

Energy Engineering, Vol.120, No.12, pp. 2917-2931, 2023, DOI:10.32604/ee.2023.029167

Abstract Reducing the impact of power outages and maintaining the power supply duration must be considered in implementing emergency energy dispatching in micro-networks. This paper studies a new emergency energy treatment method based on the robust optimal method and the industrial park micro-network with the optical energy storage system. After controlling the load input, a control strategy of adjusting and removing is proposed. Rolling optimal theory is applied to emergency energy scheduling based on a robust optimal mathematical model. A weighting factor is introduced into the optimal model to balance the importance of reducing and retaining the power supply. Uncertainty is… More >

Shaik Mahaboob Basha^1,*, Victor Hugo C. de Albuquerque², Samia Allaoua Chelloug^3,*, Mohamed Abd Elaziz^4,5,6,7, Shaik Hashmitha Mohisin⁸, Suhail Parvaze Pathan⁹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.2, pp. 1981-2004, 2024, DOI:10.32604/cmes.2023.031425

Abstract Manual investigation of chest radiography (CXR) images by physicians is crucial for effective decision-making in COVID-19 diagnosis. However, the high demand during the pandemic necessitates auxiliary help through image analysis and machine learning techniques. This study presents a multi-threshold-based segmentation technique to probe high pixel intensity regions in CXR images of various pathologies, including normal cases. Texture information is extracted using gray co-occurrence matrix (GLCM)-based features, while vessel-like features are obtained using Frangi, Sato, and Meijering filters. Machine learning models employing Decision Tree (DT) and Random Forest (RF) approaches are designed to categorize CXR images into common lung infections, lung… More > Graphic Abstract

Harsh Mankodiya¹, Priyal Palkhiwala¹, Rajesh Gupta^1,*, Nilesh Kumar Jadav¹, Sudeep Tanwar¹, Osama Alfarraj², Amr Tolba², Maria Simona Raboaca^3,4,*, Verdes Marina⁵

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 1123-1142, 2023, DOI:10.32604/cmc.2023.038556

Abstract The amalgamation of artificial intelligence (AI) with various areas has been in the picture for the past few years. AI has enhanced the functioning of several services, such as accomplishing better budgets, automating multiple tasks, and data-driven decision-making. Conducting hassle-free polling has been one of them. However, at the onset of the coronavirus in 2020, almost all worldly affairs occurred online, and many sectors switched to digital mode. This allows attackers to find security loopholes in digital systems and exploit them for their lucrative business. This paper proposes a three-layered deep learning (DL)-based authentication framework to develop a secure online… More >

Peiyuan Jiang¹, Weijun Pan^1,*, Jian Zhang¹, Teng Wang¹, Junxiang Huang²

CMC-Computers, Materials & Continua, Vol.77, No.1, pp. 911-940, 2023, DOI:10.32604/cmc.2023.041772

Abstract

This study aims to address the deviation in downstream tasks caused by inaccurate recognition results when applying Automatic Speech Recognition (ASR) technology in the Air Traffic Control (ATC) field. This paper presents a novel cascaded model architecture, namely Conformer-CTC/Attention-T5 (CCAT), to build a highly accurate and robust ATC speech recognition model. To tackle the challenges posed by noise and fast speech rate in ATC, the Conformer model is employed to extract robust and discriminative speech representations from raw waveforms. On the decoding side, the Attention mechanism is integrated to facilitate precise alignment between input features and output characters. The Text-To-Text… More >

Feng Yang¹, Zhong Wu^2,*, Xiaoyan Teng¹

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.1, pp. 719-738, 2024, DOI:10.32604/cmes.2023.028699

Abstract The low efficiency and high cost of fresh agricultural product terminal distribution directly restrict the operation of the entire supply network. To reduce costs and optimize the distribution network, we construct a mixed integer programming model that comprehensively considers to minimize fixed, transportation, fresh-keeping, time, carbon emissions, and performance incentive costs. We analyzed the performance of traditional rider distribution and robot distribution modes in detail. In addition, the uncertainty of the actual market demand poses a huge threat to the stability of the terminal distribution network. In order to resist uncertain interference, we further extend the model to a robust… More > Graphic Abstract

Xuhang Lin¹, Haibo Chen^1,*

The International Conference on Computational & Experimental Engineering and Sciences, Vol.27, No.1, pp. 1-1, 2023, DOI:10.32604/icces.2023.09388

Abstract As an important and useful tool for reducing noise, the sound barrier is of practical significance. The sound barrier has different noise reduction effects for different sizes, shapes and properties of the sound absorbing material. Liu et al. [1] have performed shape optimization of sound barriers by using isogeometric boundary element method and method of moving asymptotes (MMA). However, in engineering practice, it is difficult to determine some parameters accurately such as material properties, geometries, external loads. Therefore, it is necessary to consider these uncertainty conditions in order to ensure the rationality of the numerical calculation of engineering problems. In… More >

Youngeun An, Jimin Lee, EunSang Bak^*, Sungbum Pan^*

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 1817-1832, 2023, DOI:10.32604/cmc.2023.039460

Abstract Emotion recognition based on facial expressions is one of the most critical elements of human-machine interfaces. Most conventional methods for emotion recognition using facial expressions use the entire facial image to extract features and then recognize specific emotions through a pre-trained model. In contrast, this paper proposes a novel feature vector extraction method using the Euclidean distance between the landmarks changing their positions according to facial expressions, especially around the eyes, eyebrows, nose, and mouth. Then, we apply a new classifier using an ensemble network to increase emotion recognition accuracy. The emotion recognition performance was compared with the conventional algorithms… More >

Zhaoyang Ma^1,*, Qingda Yang¹, Xingming Guo¹

The International Conference on Computational & Experimental Engineering and Sciences, Vol.26, No.2, pp. 1-1, 2023, DOI:10.32604/icces.2023.08941

Abstract P This paper presents and validates a new local to global (L2G) FEM approach that can analyze multiple, interactive fracture processes in 2D solids with improved numerical efficiency and robustness. The method features: 1) forming local problems for individual and interactive cracks; and 2) parallel solving local problems and returning local solutions as part of the trial solution for global iteration. It has been demonstrated analytically (through a simple 1D problem) and numerically (through several benchmarking examples) that, the proposed method can substantially improve the robustness of the global solution process and significantly reduce the costly global iteration for convergence.… More >

Weixin Jiang^1,*, Qing Yuan², Zongze Li³, Junhua Gong³, Bo Yu⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.25, No.4, pp. 1-2, 2023, DOI:10.32604/icces.2023.08861

Abstract The hydraulic and thermal simulation of crude oil pipeline transportation is greatly significant for the safe transportation and accurate regulation of pipelines. With reasonable basic parameters, the solution of the traditional partial differential equation (PDE) for the axial soil temperature field on the pipeline can obtain accurate simulation results, yet it brings about a low calculation efficiency problem. In order to overcome the low-efficiency problem, an efficient and robust hybrid solution model for soil temperature field coupling with Bayesian neural network and PDE is proposed, which considers the dynamic changes of boundary conditions. Four models, including the proposed hybrid model,… More >