Saba Awan^1,*, Zahid Mehmood^2,*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2535-2555, 2024, DOI:10.32604/cmc.2024.047337

Abstract Highway safety researchers focus on crash injury severity, utilizing deep learning—specifically, deep neural networks (DNN), deep convolutional neural networks (D-CNN), and deep recurrent neural networks (D-RNN)—as the preferred method for modeling accident severity. Deep learning’s strength lies in handling intricate relationships within extensive datasets, making it popular for accident severity level (ASL) prediction and classification. Despite prior success, there is a need for an efficient system recognizing ASL in diverse road conditions. To address this, we present an innovative Accident Severity Level Prediction Deep Learning (ASLP-DL) framework, incorporating DNN, D-CNN, and D-RNN models fine-tuned through iterative hyperparameter selection with Stochastic… More >

Bayi Xu¹, Lei Sun^2,*, Xiuqing Mao², Chengwei Liu³, Zhiyi Ding²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1995-2022, 2024, DOI:10.32604/cmc.2023.046478

Abstract In recent years, frequent network attacks have highlighted the importance of efficient detection methods for ensuring cyberspace security. This paper presents a novel intrusion detection system consisting of a data preprocessing stage and a deep learning model for accurately identifying network attacks. We have proposed four deep neural network models, which are constructed using architectures such as Convolutional Neural Networks (CNN), Bi-directional Long Short-Term Memory (BiLSTM), Bidirectional Gate Recurrent Unit (BiGRU), and Attention mechanism. These models have been evaluated for their detection performance on the NSL-KDD dataset.To enhance the compatibility between the data and the models, we apply various preprocessing… More >

Mohammad Javad SheikhMozafari^*

Sound & Vibration, Vol.58, pp. 81-100, 2024, DOI:10.32604/sv.2024.048897

Abstract Mitigating low-frequency noise poses a significant challenge for acoustic engineers, due to their long wavelength, with conventional porous sound absorbers showing limitations in attenuating such noise. An effective strategy involves combining porous materials with micro-perforated plates (MPP) to address this issue. Given the significant impact of structural variables like panel thickness, hole diameter, and air gap on the acoustic characteristics of MPP, achieving the optimal condition demands numerous sample iterations. The impedance tube’s considerable expense for sound absorption measurement and the substantial cost involved in fabricating each sample using a 3D printer underscore the advantage of utilizing simulation methods to… More > Graphic Abstract

Nilkanth Mukund Deshpande^1,2, Shilpa Gite^3,4,*, Biswajeet Pradhan^5,6, Abdullah Alamri⁷, Chang-Wook Lee^8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.1, pp. 593-631, 2024, DOI:10.32604/cmes.2023.030704

Abstract Infection of leukemia in humans causes many complications in its later stages. It impairs bone marrow’s ability to produce blood. Morphological diagnosis of human blood cells is a well-known and well-proven technique for diagnosis in this case. The binary classification is employed to distinguish between normal and leukemia-infected cells. In addition, various subtypes of leukemia require different treatments. These sub-classes must also be detected to obtain an accurate diagnosis of the type of leukemia. This entails using multi-class classification to determine the leukemia subtype. This is usually done using a microscopic examination of these blood cells. Due to the requirement… More > Graphic Abstract

Manjur Kolhar^*, Sultan Mesfer Aldossary

CMC-Computers, Materials & Continua, Vol.77, No.3, pp. 2857-2879, 2023, DOI:10.32604/cmc.2023.042726

Abstract In many commercial and public sectors, the Internet of Things (IoT) is deeply embedded. Cyber security threats aimed at compromising the security, reliability, or accessibility of data are a serious concern for the IoT. Due to the collection of data from several IoT devices, the IoT presents unique challenges for detecting anomalous behavior. It is the responsibility of an Intrusion Detection System (IDS) to ensure the security of a network by reporting any suspicious activity. By identifying failed and successful attacks, IDS provides a more comprehensive security capability. A reliable and efficient anomaly detection system is essential for IoT-driven decision-making.… More >

Ahmed Hassan Abdou^1,*, Omar Abdullah Alkhateeb², Hossam Eldin Hamed Mansour³, Hesham S. Ghazzawy⁴, Muayad Saud Albadrani⁵, Nadi Awad Al-harbi⁶, Wasimah B. Al-Shammari⁷, Khaled Abdelaal^8,*

Phyton-International Journal of Experimental Botany, Vol.92, No.12, pp. 3305-3321, 2023, DOI:10.32604/phyton.2023.044780

Abstract Plant growth-promoting bacteria (PGPB) play an important role in improving agricultural production under several abiotic stress factors. PGPB can be used to increase crop growth and development through hormonal balance and increase nutrient uptake. The positive effect of PGPB may be due to its pivotal role in morphophysiological and biochemical characteristics like leaf number, leaf area, and stem length. Furthermore, relative water content, chlorophyll content, carotenoids, antioxidant enzymes, and plant hormones were improved with PGPB treatment. Crop yield and yield components were also increased with PGPB treatment in numerous crops. The anatomical structure of plant organs was increased such as… More >

Refah Alotaibi¹, Mazen Nassar^2,3, Ahmed Elshahhat^4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2571-2596, 2024, DOI:10.32604/cmes.2023.030582

Abstract A novel extended Lindley lifetime model that exhibits unimodal or decreasing density shapes as well as increasing, bathtub or unimodal-then-bathtub failure rates, named the Marshall-Olkin-Lindley (MOL) model is studied. In this research, using a progressive Type-II censored, various inferences of the MOL model parameters of life are introduced. Utilizing the maximum likelihood method as a classical approach, the estimators of the model parameters and various reliability measures are investigated. Against both symmetric and asymmetric loss functions, the Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) technique with the assumption of independent gamma priors. From the Fisher information… More >

Qixin Lan¹, Binqiang Chen^1,*, Bin Yao¹, Wangpeng He²

CMES-Computer Modeling in Engineering & Sciences, Vol.138, No.3, pp. 2825-2844, 2024, DOI:10.32604/cmes.2023.030378

Abstract The wear of metal cutting tools will progressively rise as the cutting time goes on. Wearing heavily on the tool will generate significant noise and vibration, negatively impacting the accuracy of the forming and the surface integrity of the workpiece. Hence, during the cutting process, it is imperative to continually monitor the tool wear state and promptly replace any heavily worn tools to guarantee the quality of the cutting. The conventional tool wear monitoring models, which are based on machine learning, are specifically built for the intended cutting conditions. However, these models require retraining when the cutting conditions undergo any… More >

Husam Rashid Hudear^*, Saad Najeeb Shehab

Frontiers in Heat and Mass Transfer, Vol.21, pp. 367-383, 2023, DOI:10.32604/fhmt.2023.042639

Abstract This paper presents a numerical emulation study of heat transmission through tube banks in three-dimensions. Staggered configuration is displayed by fluid dynamics using computer programs (CFD) software (ANSYS fluent). The computer model is used to predict the values of the Nusselt number when changing the values of heat flux and longitudinal pitch. The longitudinal pitch (SL/D) of 1.3, 1.8, and 2.4 mm. The transverse pitch (ST/D) of 1.5 mm, and also considered Reynolds numbers 10000, 13000, 17000, and 190000. The staggered configuration of the tube bundle is demonstrated to investigate the impact of this arrangement on the heat transmission rate… More >

Mohammad Yaghoub Abdollahzadeh Jamalabadi, Jinxiang Xi^*

Frontiers in Heat and Mass Transfer, Vol.21, pp. 65-79, 2023, DOI:10.32604/fhmt.2023.042613

Abstract As a means of harvesting solar energy for water treatment, solar-driven vapor generation is becoming more appealing. Due to their entangled fibrous networks and high surface area, fibers can be used as building blocks to generate water vapor. In this paper, using a two-dimensional fiber bundle model, we studied the generation of solar vapor based on the fiber height, distance between fibers, and input sun radiation. The performance of solar absorption system was also evaluated by evaluating thermal and water management. Results showed a constant increase in solar vapor generation with an increasing fiber height and decreasing inter-fiber distance. However,… More > Graphic Abstract