Qazi Mazhar ul Haq¹, Fahim Arif^2,3, Khursheed Aurangzeb⁴, Noor ul Ain³, Javed Ali Khan⁵, Saddaf Rubab⁶, Muhammad Shahid Anwar^7,*

CMC-Computers, Materials & Continua, Vol.78, No.3, pp. 4379-4397, 2024, DOI:10.32604/cmc.2024.047172

Abstract Software project outcomes heavily depend on natural language requirements, often causing diverse interpretations and issues like ambiguities and incomplete or faulty requirements. Researchers are exploring machine learning to predict software bugs, but a more precise and general approach is needed. Accurate bug prediction is crucial for software evolution and user training, prompting an investigation into deep and ensemble learning methods. However, these studies are not generalized and efficient when extended to other datasets. Therefore, this paper proposed a hybrid approach combining multiple techniques to explore their effectiveness on bug identification problems. The methods involved feature selection, which is used to… More >

Haomiao Wang¹, Jinxi Wang², Qingmei Sui^2,*, Faye Zhang², Yibin Li¹, Mingshun Jiang², Phanasindh Paitekul³

Structural Durability & Health Monitoring, Vol.18, No.2, pp. 91-110, 2024, DOI:10.32604/sdhm.2023.041522

Abstract Due to their robust learning and expression ability for complex features, the deep learning (DL) model plays a vital role in bearing fault diagnosis. However, since there are fewer labeled samples in fault diagnosis, the depth of DL models in fault diagnosis is generally shallower than that of DL models in other fields, which limits the diagnostic performance. To solve this problem, a novel transfer residual Swin Transformer (RST) is proposed for rolling bearings in this paper. RST has 24 residual self-attention layers, which use the hierarchical design and the shifted window-based residual self-attention. Combined with transfer learning techniques, the… More >

Perez Joan¹, Fusco Giovanni¹, Sadahiro Yukio²

Revue Internationale de Géomatique, Vol.31, No.2, pp. 303-327, 2022, DOI:10.3166/RIG.31.303-327© 2022

Abstract This paper presents different methods implemented with the aim of studying urban dynamics at the building level. Building types are identified within a comprehensive vector-based building inventory, spanning over at least two time points. First, basic morphometric indicators are computed for each building: area, floor-area, number of neighbors, elongation, and convexity. Based on the availability of expert knowledge, different types of classification and clustering are performed: supervised tree-like classificatory model, expert-constrained k-means and combined SOM-HCA. A grid is superimposed on the test region of Osaka (Japan) and the number of building types per cell and for each period is computed,… More >

Nazik Alturki¹, Raed Alharthi², Muhammad Umer^3,*, Oumaima Saidani¹, Amal Alshardan¹, Reemah M. Alhebshi⁴, Shtwai Alsubai⁵, Ali Kashif Bashir^6,7,8,*

CMES-Computer Modeling in Engineering & Sciences, Vol.139, No.3, pp. 3387-3415, 2024, DOI:10.32604/cmes.2023.044700

Abstract The concept of smart houses has grown in prominence in recent years. Major challenges linked to smart homes are identification theft, data safety, automated decision-making for IoT-based devices, and the security of the device itself. Current home automation systems try to address these issues but there is still an urgent need for a dependable and secure smart home solution that includes automatic decision-making systems and methodical features. This paper proposes a smart home system based on ensemble learning of random forest (RF) and convolutional neural networks (CNN) for programmed decision-making tasks, such as categorizing gadgets as “OFF” or “ON” based… More >

Huixiang Xu^*

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 2309-2335, 2024, DOI:10.32604/cmc.2024.046253

Abstract The Internet of Things (IoT) has revolutionized how we interact with and gather data from our surrounding environment. IoT devices with various sensors and actuators generate vast amounts of data that can be harnessed to derive valuable insights. The rapid proliferation of Internet of Things (IoT) devices has ushered in an era of unprecedented data generation and connectivity. These IoT devices, equipped with many sensors and actuators, continuously produce vast volumes of data. However, the conventional approach of transmitting all this data to centralized cloud infrastructures for processing and analysis poses significant challenges. However, transmitting all this data to a… More >

Ali Hamid Farea^1,*, Omar H. Alhazmi¹, Kerem Kucuk²

CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1525-1545, 2024, DOI:10.32604/cmc.2023.045794

Abstract While emerging technologies such as the Internet of Things (IoT) have many benefits, they also pose considerable security challenges that require innovative solutions, including those based on artificial intelligence (AI), given that these techniques are increasingly being used by malicious actors to compromise IoT systems. Although an ample body of research focusing on conventional AI methods exists, there is a paucity of studies related to advanced statistical and optimization approaches aimed at enhancing security measures. To contribute to this nascent research stream, a novel AI-driven security system denoted as “AI2AI” is presented in this work. AI2AI employs AI techniques to… More >

Lei Zhu^1,#, Lihe Hou^1,3,#, Yu Zhang¹, Yang Jiang¹, Yi Wang^1,2, Meiping Zhang^1,2, Mingzhu Zhao^1,2,*, Kangyu Wang^1,2,*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 313-327, 2024, DOI:10.32604/phyton.2024.047938

Abstract Panax ginseng C. A. Mey. is an important plant species used in traditional Chinese medicine, whose primary active ingredient is a ginsenoside. Ginsenoside biosynthesis is not only regulated by transcription factors but also controlled by a variety of structural genes. Nonetheless, the molecular mechanism underlying ginsenoside biosynthesis has always been a topic in the discussion of ginseng secondary metabolites. Squalene epoxidase (SQE) is a key enzyme in the mevalonic acid pathway, which affects the biosynthesis of secondary metabolites such as terpenoid. Using ginseng transcriptome, expression, and ginsenoside content databases, this study employed bioinformatic methods to systematically analyze the genes encoding… More >

Mengyuan Li¹, Zhongye Gao^1,2, Lina Jiang¹, Leishan Chen^1,2,*, Jianhui Ma^1,*

Phyton-International Journal of Experimental Botany, Vol.93, No.2, pp. 329-342, 2024, DOI:10.32604/phyton.2024.046976

Abstract Abscisic acid (ABA), hydrogen peroxide (H₂O₂) and ascorbate (AsA)–glutathione (GSH) cycle are widely known for their participation in various stresses. However, the relationship between ABA and H₂O₂ levels and the AsA–GSH cycle under drought stress in wheat has not been studied. In this study, a hydroponic experiment was conducted in wheat seedlings subjected to 15% polyethylene glycol (PEG) 6000–induced dehydration. Drought stress caused the rapid accumulation of endogenous ABA and H₂O₂ and significantly decreased the number of root tips compared with the control. The application of ABA significantly increased the number of root tips, whereas the application of H₂O₂ markedly… More >

CHAO LIU^*

BIOCELL, Vol.48, No.2, pp. 339-351, 2024, DOI:10.32604/biocell.2023.047044

Abstract Introduction: Osteoarthritis (OA) is still an important health problem, and understanding its pathological mechanisms is essential for its diagnosis and treatment. There is evidence that autophagy may play a role in OA progression, but the exact mechanism remains unclear. Methods: In this study, we adopted a multi-prong approach to systematically identify the key autophagy-related genes (ARGs) associated with OA. Through weighted gene co-expression network analysis, we initially identified significant gene modules associated with OA. Subsequent differential gene analysis performed on normal and OA specimens. Further analysis later using the MCC algorithm highlighted hub ARGs. These genes were then incorporated into… More >

JINGLONG CAO^1,#, SHUMEI LI^2,#, TONG ZHANG^1,#, JIAN LIU¹, WENSHUANG HOU¹, ANQI WANG¹, CHANG WANG^3,4,*, CHENGHAO JIN^1,3,5,*

BIOCELL, Vol.48, No.2, pp. 313-325, 2024, DOI:10.32604/biocell.2023.043474

Abstract Background: Valtrate (Val) was extracted from the Valeriana jatamansi Jones plant, had good antitumor activity. However, its precise molecular mechanism in cancer cells was still unclear. This study investigated the effect of Val on gastric cancer (GC) cells and its potential molecular mechanism. Methods: Cell viability was examined by CCK-8 assay. Cell cycle, apoptosis, and Reactive oxygen species (ROS) level were analyzed by flow cytometry. The migration effect of Val on AGS cells was analyzed by transwell and wound-healing assay. The expression levels of proteins were analyzed by western blot. Results: The cell viability assay results demonstrated that Val significantly… More > Graphic Abstract