Chaozhi Cai^*, Tiexin Xu, Jianhua Ren, Yingfang Xue

Structural Durability & Health Monitoring, Vol.19, No.1, pp. 125-144, 2025, DOI:10.32604/sdhm.2024.052813 - 15 November 2024

Abstract A bearing fault diagnosis method based on the Markov transition field (MTF) and SEnet (SE)-IShufflenetV2 model is proposed in this paper due to the problems of complex working conditions, low fault diagnosis accuracy, and poor generalization of rolling bearing. Firstly, MTF is used to encode one-dimensional time series vibration signals and convert them into time-dependent and unique two-dimensional feature images. Then, the generated two-dimensional dataset is fed into the SE-IShufflenetV2 model for training to achieve fault feature extraction and classification. This paper selects the bearing fault datasets from Case Western Reserve University and Paderborn University… More >

Shridhar C. Ghagane^1,3, Shadab Rangrez³, R.B. Nerli^2,3, Madhukar L. Thakur^4,6, Leonard G. Gomella^5,6

Canadian Journal of Urology, Vol.31, No.3, pp. 11892-11896, 2024

Abstract Introduction: Prostate cancer is the second most common malignancy in men worldwide. Genomic VPAC receptors are expressed on malignant prostate cancer cells and can be targeted and imaged optically by a peptide labeled fluorophore. The objective of our study was to assess the feasibility of detecting cancer of the prostate using a voided urine sample.
Materials and methods: Patients ≥ 40 years old, with lower urinary tract symptoms and serum PSA > 4 ng/ mL formed the study group. The first 50 mL of voided urine sample was collected and processed. The cells that were shed in… More >

Rafid Sagban^1,2,*, Haydar Abdulameer Marhoon^3,4, Saadaldeen Rashid Ahmed^5,6,*

Intelligent Automation & Soft Computing, Vol.39, No.6, pp. 1035-1051, 2024, DOI:10.32604/iasc.2024.058416 - 30 December 2024

Abstract Skin cancer is a highly frequent kind of cancer. Early identification of a phenomenon significantly improves outcomes and mitigates the risk of fatalities. Melanoma, basal, and squamous cell carcinomas are well-recognized cutaneous malignancies. Malignant We can differentiate Melanoma from non-pigmented carcinomas like basal and squamous cell carcinoma. The research on developing automated skin cancer detection systems has primarily focused on pigmented malignant type melanoma. The limited availability of datasets with a wide range of lesion categories has hindered in-depth exploration of non-pigmented malignant skin lesions. The present study investigates the feasibility of automated methods for… More >

S. Ramacharan^1,*, Martin Margala¹, Amjan Shaik², Prasun Chakrabarti³, Tulika Chakrabarti⁴

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 3731-3760, 2024, DOI:10.32604/cmc.2024.058488 - 19 December 2024

Abstract Breast cancer remains a significant global health concern, with early detection being crucial for effective treatment and improved survival rates. This study introduces HERA-Net (Hybrid Extraction and Recognition Architecture), an advanced hybrid model designed to enhance the diagnostic accuracy of breast cancer detection by leveraging both thermographic and ultrasound imaging modalities. The HERA-Net model integrates powerful deep learning architectures, including VGG19, U-Net, GRU (Gated Recurrent Units), and ResNet-50, to capture multi-dimensional features that support robust image segmentation, feature extraction, and temporal analysis. For thermographic imaging, a comprehensive dataset of 3534 infrared (IR) images from the… More >

Farah Mohammad^1,2,*, Khulood Mohammed Al Mansoor³

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4125-4147, 2024, DOI:10.32604/cmc.2024.056666 - 19 December 2024

Abstract Depression is a prevalent mental health issue affecting individuals of all age groups globally. Similar to other mental health disorders, diagnosing depression presents significant challenges for medical practitioners and clinical experts, primarily due to societal stigma and a lack of awareness and acceptance. Although medical interventions such as therapies, medications, and brain stimulation therapy provide hope for treatment, there is still a gap in the efficient detection of depression. Traditional methods, like in-person therapies, are both time-consuming and labor-intensive, emphasizing the necessity for technological assistance, especially through Artificial Intelligence. Alternative to this, in most cases… More >

Khushmeen Kaur Brar¹, Bhawna Goyal¹, Ayush Dogra², Sampangi Rama Reddy³, Ahmed Alkhayyat⁴, Rajesh Singh⁵, Manob Jyoti Saikia^6,7,*

CMC-Computers, Materials & Continua, Vol.81, No.3, pp. 4217-4263, 2024, DOI:10.32604/cmc.2024.052548 - 19 December 2024

Abstract Skin cancer has been recognized as one of the most lethal and complex types of cancer for over a decade. The diagnosis of skin cancer is of paramount importance, yet the process is intricate and challenging. The analysis and modeling of human skin pose significant difficulties due to its asymmetrical nature, the visibility of dense hair, and the presence of various substitute characteristics. The texture of the epidermis is notably different from that of normal skin, and these differences are often evident in cases of unhealthy skin. As a consequence, the development of an effective… More >

Xinwei Wang^1,2,*, Ming Li¹, Hankun Bing¹, Dongxing Zhang¹, Yuanshu Zhang¹

Energy Engineering, Vol.121, No.12, pp. 3875-3898, 2024, DOI:10.32604/ee.2024.056237 - 22 November 2024

Abstract After long-term operation, the performance of components in the GTCC system deteriorates and requires timely maintenance. Due to the inability to directly measure the degree of component malfunction, it is necessary to use advanced exergy analysis diagnosis methods to characterize the components’ health condition (degree of malfunction) through operation data of the GTCC system. The dissipative temperature is used to describe the degree of malfunction of different components in the GTCC system, and an advanced exergy analysis diagnostic method is used to establish a database of overall operating condition component malfunctions in the GTCC system.… More >

Kusum Yadav¹, Yasser Alharbi¹, Eissa Jaber Alreshidi¹, Abdulrahman Alreshidi¹, Anuj Kumar Jain², Anurag Jain³, Kamal Kumar⁴, Sachin Sharma⁵, Brij B. Gupta^6,7,8,*

CMC-Computers, Materials & Continua, Vol.81, No.2, pp. 2665-2683, 2024, DOI:10.32604/cmc.2024.053565 - 18 November 2024

Abstract In today’s world, image processing techniques play a crucial role in the prognosis and diagnosis of various diseases due to the development of several precise and accurate methods for medical images. Automated analysis of medical images is essential for doctors, as manual investigation often leads to inter-observer variability. This research aims to enhance healthcare by enabling the early detection of diabetic retinopathy through an efficient image processing framework. The proposed hybridized method combines Modified Inertia Weight Particle Swarm Optimization (MIWPSO) and Fuzzy C-Means clustering (FCM) algorithms. Traditional FCM does not incorporate spatial neighborhood features, making More >

Lei Wang^1,*, Blanca Rodriguez², Xiaoyu Luo³, Charles Augarde⁴

The International Conference on Computational & Experimental Engineering and Sciences, Vol.30, No.4, pp. 1-2, 2024, DOI:10.32604/icces.2024.013350

Abstract Cardiovascular disease is the leading cause of death worldwide. Disease-specific software, like FFRct from HeartFlow, and high-fidelity computational models within a general-purpose software, like Living Heart Project within Abaqus, are essential to revolutionise diagnosis and treatment of cardiovascular disease for clinicians and design of medical devices for industries. This talk presents our past researches on computational modelling of tear propagation in the aortic dissection [1-2] and of electromechanical coupling in the human heart with the finite element method [3], and our current exploration on high-fidelity and efficient computation and software development for diagnosis and treatment More >

Sumika Chauhan, Govind Vashishtha^*, Radoslaw Zimroz

CMES-Computer Modeling in Engineering & Sciences, Vol.141, No.3, pp. 1983-2020, 2024, DOI:10.32604/cmes.2024.055633 - 31 October 2024

Abstract Sensors, vital elements in data acquisition systems, play a crucial role in various industries. However, their exposure to harsh operating conditions makes them vulnerable to faults that can compromise system performance. Early fault detection is therefore critical for minimizing downtime and ensuring system reliability. This paper delves into the contemporary landscape of fault diagnosis techniques for sensors, offering valuable insights for researchers and academicians. The papers begin by exploring the different types and causes of sensor faults, followed by a discussion of the various fault diagnosis methods employed in industrial sectors. The advantages and limitations More >