Mekonnen S. Ayano^1,*, Thokozani N. Khumalo¹, Stephen T. Sikwila², Stanford Shateyi³

Frontiers in Heat and Mass Transfer, Vol.22, No.4, pp. 1153-1169, 2024, DOI:10.32604/fhmt.2024.048474

Abstract The present paper examines the temperature-dependent viscosity and thermal conductivity of a micropolar silver ()−Magnesium oxide () hybrid nanofluid made of silver and magnesium oxide over a rotating vertical cone, with the influence of transverse magnetic field and thermal radiation. The physical flow problem has been modeled with coupled partial differential equations. We apply similarity transformations to the non-dimensionalized equations, and the resulting nonlinear differential equations are solved using overlapping grid multidomain spectral quasilinearization method. The flow behavior for the fluid is scrutinized under the impact of diverse physical constraints, which are illustrated graphically. The More >

Farouq Zitouni^1,*, Saad Harous², Abdulaziz S. Almazyad³, Ali Wagdy Mohamed^4,5, Guojiang Xiong⁶, Fatima Zohra Khechiba¹, Khadidja Kherchouche¹

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.1, pp. 219-265, 2024, DOI:10.32604/cmes.2024.052001

Abstract Hybridizing metaheuristic algorithms involves synergistically combining different optimization techniques to effectively address complex and challenging optimization problems. This approach aims to leverage the strengths of multiple algorithms, enhancing solution quality, convergence speed, and robustness, thereby offering a more versatile and efficient means of solving intricate real-world optimization tasks. In this paper, we introduce a hybrid algorithm that amalgamates three distinct metaheuristics: the Beluga Whale Optimization (BWO), the Honey Badger Algorithm (HBA), and the Jellyfish Search (JS) optimizer. The proposed hybrid algorithm will be referred to as BHJO. Through this fusion, the BHJO algorithm aims to… More >

Mohammed Mohammed^1,2,*, Jawad K. Oleiwi³, Aeshah M. Mohammed⁴, Anwar Ja’afar Mohamad Jawad⁵, Azlin F. Osman^1,2, Tijjani Adam⁶, Bashir O. Betar⁷, Subash C. B. Gopinath^2,8,9

Journal of Renewable Materials, Vol.12, No.7, pp. 1237-1290, 2024, DOI:10.32604/jrm.2024.051201

Abstract Natural fibre (NFR) reinforced functional polymer composites are quickly becoming an indispensable sustainable material in the transportation industry because of their lightweight, lower cost in manufacture, and adaptability to a wide variety of goods. However, the major difficulties of using these fibres are their existing poor dimensional stability and the extreme hydrophilicity. In assessing the mechanical properties (MP) of composites, the interfacial bonding (IB) happening between the NFR and the polymer matrix (PM) plays an incredibly significant role. When compared to NFR/synthetic fibre hybrid composites, hybrid composites (HC) made up of two separate NFR are… More > Graphic Abstract

Wei Liu^*, Tengteng Ren

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2979-3000, 2024, DOI:10.32604/cmc.2024.053627

Abstract Feature Selection (FS) is a key pre-processing step in pattern recognition and data mining tasks, which can effectively avoid the impact of irrelevant and redundant features on the performance of classification models. In recent years, meta-heuristic algorithms have been widely used in FS problems, so a Hybrid Binary Chaotic Salp Swarm Dung Beetle Optimization (HBCSSDBO) algorithm is proposed in this paper to improve the effect of FS. In this hybrid algorithm, the original continuous optimization algorithm is converted into binary form by the S-type transfer function and applied to the FS problem. By combining the… More >

Tuğba Çelikten¹, Aytuğ Onan^2,*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 3351-3377, 2024, DOI:10.32604/cmc.2024.051574

Abstract The purpose of this study is to develop a reliable method for distinguishing between AI-generated, paraphrased, and human-written texts, which is crucial for maintaining the integrity of research and ensuring accurate information flow in critical fields such as healthcare. To achieve this, we propose HybridGAD, a novel hybrid model that combines Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), and Bidirectional Gated Recurrent Unit (Bi-GRU) architectures with an attention mechanism. Our methodology involves training this hybrid model on a dataset of radiology abstracts, encompassing texts generated by AI, paraphrased by AI, and written by humans. The… More >

Tajmal Hussain, Jungpyo Hong^*, Jongwon Seok^*

CMC-Computers, Materials & Continua, Vol.80, No.2, pp. 2099-2119, 2024, DOI:10.32604/cmc.2024.050884

Abstract Smart manufacturing is a process that optimizes factory performance and production quality by utilizing various technologies including the Internet of Things (IoT) and artificial intelligence (AI). Quality control is an important part of today’s smart manufacturing process, effectively reducing costs and enhancing operational efficiency. As technology in the industry becomes more advanced, identifying and classifying defects has become an essential element in ensuring the quality of products during the manufacturing process. In this study, we introduce a CNN model for classifying defects on hot-rolled steel strip surfaces using hybrid deep learning techniques, incorporating a global… More >

Sohail Muhammad¹, Muzammil Khan², Sarwar Shah Khan^2,3,*

Journal on Artificial Intelligence, Vol.6, pp. 193-209, 2024, DOI:10.32604/jai.2024.052099

Abstract Retrieving information from evolving digital data collection using a user’s query is always essential and needs efficient retrieval mechanisms that help reduce the required time from such massive collections. Large-scale time consumption is certain to scan and analyze to retrieve the most relevant textual data item from all the documents required a sophisticated technique for a query against the document collection. It is always challenging to retrieve a more accurate and fast retrieval from a large collection. Text summarization is a dominant research field in information retrieval and text processing to locate the most appropriate… More >

Song Lu¹, Jianjun Guo², Richard Ansah Herman¹, Xinyi Wu¹, Lin Ma¹, Guohua Wu^1,*

Journal of Renewable Materials, Vol.12, No.6, pp. 1043-1055, 2024, DOI:10.32604/jrm.2024.051767

Abstract Silk is widely used in the production of high-quality textiles. At the same time, the amount of silk textiles no longer in use and discarded is increasing, resulting in significant waste and pollution. This issue is of great concern in many countries where silk is used. Hydrogen peroxide as a naturally occurring compound is an important indicator of detection in both biology and the environment. This study aims to develop a composite fiber with hydrogen peroxide-sensing properties using discarded silk materials. To achieve this goal, firstly, polydopamine (PDA) was used to encapsulate the ZnFeO NPs… More > Graphic Abstract

Bingyi Ren^1,4, Juwei Zhang^2,3,4,*, Tong Wang^2,4

CMC-Computers, Materials & Continua, Vol.80, No.1, pp. 1425-1440, 2024, DOI:10.32604/cmc.2024.052667

Abstract Autonomous driving technology has entered a period of rapid development, and traffic sign detection is one of the important tasks. Existing target detection networks are difficult to adapt to scenarios where target sizes are seriously imbalanced, and traffic sign targets are small and have unclear features, which makes detection more difficult. Therefore, we propose a Hybrid Feature Fusion Traffic Sign detection algorithm based on YOLOv7 (HFFT-YOLO). First, a self-attention mechanism is incorporated at the end of the backbone network to calculate feature interactions within scales; Secondly, the cross-scale fusion part of the neck introduces a… More >

Jiawen Li^1,2, Yuesheng Huang¹, Yayi Lu¹, Leijun Wang^1,*, 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 >