Wei Jiang^1,2,*, Zelin Cao^3,4

Structural Durability & Health Monitoring, Vol.17, No.1, pp. 37-54, 2023, DOI:10.32604/sdhm.2022.013444

Abstract The attenuation relationship of ground motion based on seismology has always been a front subject of engineering earthquake. Among them, the regional finite-fault source model is very important. In view of this point, the general characteristics of regional seism-tectonics, including the dip and depth of the fault plane, are emphasized. According to the statistics of regional seism-tectonics and focal mechanisms in Sichuan, China, and the sensitivity of estimated peak ground acceleration (PGA) attenuation is analyzed, and the dip angle is taken as an average of 70°. Based the statistics of the upper crustal structure and the focal depth of regional… More >

Ruaa H. Abbas¹, A. Kadhim^1,*, Azhar M. Haleem²

Journal of Renewable Materials, Vol.11, No.5, pp. 2109-2123, 2023, DOI:10.32604/jrm.2023.025112

Abstract Copper oxide nanoparticles (CuO NPs) were synthesised with laser ablation of a copper sheet immersed in deionized water (DW), cetrimonium bromide (CTAB), and sodium dodecyl sulphate (SDS), respectively. The target was irradiated with a pulsed Nd: YAG laser at 1064 nm, 600 mJ, a pulse duration of 10 ns, and a repetition rate of 5 Hz. The CuO NPs colloidal were analyzed using UV–Vis spectroscopy, the Fourier transform infrared (FTIR) spectrometer, zeta potential (ZP), X-ray diffraction (XRD), transmission electron microscope (TEM) and field emission scanning electron microscopy (FESEM). The absorption spectra of CuO NPs colloidal showed peaks at 214, 215… More >

Jun Lee¹, Hyun Kwon^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 2025-2042, 2023, DOI:10.32604/cmc.2023.036051

Abstract A concurrency control mechanism for collaborative work is a key element in a mixed reality environment. However, conventional locking mechanisms restrict potential tasks or the support of non-owners, thus increasing the working time because of waiting to avoid conflicts. Herein, we propose an adaptive concurrency control approach that can reduce conflicts and work time. We classify shared object manipulation in mixed reality into detailed goals and tasks. Then, we model the relationships among goal, task, and ownership. As the collaborative work progresses, the proposed system adapts the different concurrency control mechanisms of shared object manipulation according to the modeling of… More >

NaeJoung Kwak¹, DongJu Kim^2,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1671-1686, 2023, DOI:10.32604/cmc.2023.035762

Abstract This paper proposes a method for detecting a helmet for the safety of workers from risk factors and a mask worn indoors and verifying a worker’s identity while wearing a helmet and mask for security. The proposed method consists of a part for detecting the worker’s helmet and mask and a part for verifying the worker’s identity. An algorithm for helmet and mask detection is generated by transfer learning of Yolov5’s s-model and m-model. Both models are trained by changing the learning rate, batch size, and epoch. The model with the best performance is selected as the model for detecting… More >

Ghada Atteia¹, El-Sayed M. El-kenawy^2,3, Nagwan Abdel Samee^1,*, Mona M. Jamjoom⁴, Abdelhameed Ibrahim⁵, Abdelaziz A. Abdelhamid^6,7, Ahmad Taher Azar^8,9, Nima Khodadadi^10,11, Reham A. Ghanem¹², Mahmoud Y. Shams¹³

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1883-1900, 2023, DOI:10.32604/cmc.2023.031723

Abstract The rapid population growth results in a crucial problem in the early detection of diseases in medical research. Among all the cancers unveiled, breast cancer is considered the second most severe cancer. Consequently, an exponential rising in death cases incurred by breast cancer is expected due to the rapid population growth and the lack of resources required for performing medical diagnoses. Utilizing recent advances in machine learning could help medical staff in diagnosing diseases as they offer effective, reliable, and rapid responses, which could help in decreasing the death risk. In this paper, we propose a new algorithm for feature… More >

Lilia Oreto^1,*, Giuseppe Mandraffino², Paolo Ciliberti³, Teresa P. Santangelo⁴, Placido Romeo⁵, Antonio Celona⁵, Placido Gitto¹, Lorenzo Galletti³, Fiore S. Iorio³, Alfredo Di Pino¹, Aurelio Secinaro⁴, Paolo Guccione³, Robert H. Anderson⁶, Salvatore Agati¹

Congenital Heart Disease, Vol.18, No.1, pp. 97-111, 2023, DOI:10.32604/chd.2022.023619

Abstract Aims: Evidence is emerging that, in the setting of isomerism, the atrial and bronchial arrangement are not always concordant, nor are these patterns always harmonious with the arrangement of the abdominal organs. We aimed to evaluate the concordance between these features in a cohort of patients with cardiac malformations in the setting of known isomerism, seeking to determine whether it was feasible to assess complexity on this basis, in this regard taking note of the potential value of bronchial as opposed to appendage morphology. Methods and Results: We studied 78 patients known to have isomerism of the bronchuses, 43 with… More > Graphic Abstract

Noureen Talpur^1,*, Said Jadid Abdulkadir¹, Mohd Hilmi Hasan¹, Hitham Alhussian¹, Ayed Alwadain²

CMC-Computers, Materials & Continua, Vol.74, No.3, pp. 5799-5820, 2023, DOI:10.32604/cmc.2023.034025

Abstract Machine learning (ML) practices such as classification have played a very important role in classifying diseases in medical science. Since medical science is a sensitive field, the pre-processing of medical data requires careful handling to make quality clinical decisions. Generally, medical data is considered high-dimensional and complex data that contains many irrelevant and redundant features. These factors indirectly upset the disease prediction and classification accuracy of any ML model. To address this issue, various data pre-processing methods called Feature Selection (FS) techniques have been presented in the literature. However, the majority of such techniques frequently suffer from local minima issues… More >

SEHRISH ABBAS¹, BUSHRA UZAIR^1,*, MAISRA AZHAR BUTT¹, FARID MENAA², BARKAT A. KHAN^3,*

BIOCELL, Vol.47, No.2, pp. 245-260, 2023, DOI:10.32604/biocell.2023.025311

Abstract The association of gut microflora and human health is being increasingly recognized, and the impact of gut microflora on the host is well characterized, including the body’s energy metabolism and immune system maintenance. Several human diseases, including metabolic, autoimmune, obesity, hypothyroidism, and intestinal disorders, are closely associated with gut dysbiosis. Inorganic nanoparticles (NPs) are extensively utilized in numerous fields due to their distinctive, attractive physicochemical properties. Estimation of the potential impacts of NPs, with a high number of microorganisms inside the human body (microbiota) and its genomes (microbiome), represents one of the most important aspects of nano-toxicology. This review article… More > Graphic Abstract

Doaa Sami Khafaga¹, Amel Ali Alhussan^1,*, Abdelaziz A. Abdelhamid^2,3, Abdelhameed Ibrahim⁴, Mohamed Saber⁵, El-Sayed M. El-kenawy^6,7

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1469-1482, 2023, DOI:10.32604/csse.2023.031943

Abstract Arrhythmia has been classified using a variety of methods. Because of the dynamic nature of electrocardiogram (ECG) data, traditional handcrafted approaches are difficult to execute, making the machine learning (ML) solutions more appealing. Patients with cardiac arrhythmias can benefit from competent monitoring to save their lives. Cardiac arrhythmia classification and prediction have greatly improved in recent years. Arrhythmias are a category of conditions in which the heart's electrical activity is abnormally rapid or sluggish. Every year, it is one of the main reasons of mortality for both men and women, worldwide. For the classification of arrhythmias, this work proposes a… More >

B. Yasotha^1,*, T. Sasikala², M. Krishnamurthy³

Computer Systems Science and Engineering, Vol.45, No.2, pp. 1625-1640, 2023, DOI:10.32604/csse.2023.025669

Abstract The internet has become a part of every human life. Also, various devices that are connected through the internet are increasing. Nowadays, the Industrial Internet of things (IIoT) is an evolutionary technology interconnecting various industries in digital platforms to facilitate their development. Moreover, IIoT is being used in various industrial fields such as logistics, manufacturing, metals and mining, gas and oil, transportation, aviation, and energy utilities. It is mandatory that various industrial fields require highly reliable security and preventive measures against cyber-attacks. Intrusion detection is defined as the detection in the network of security threats targeting privacy information and sensitive… More >