José Escorcia-Gutierrez^1,4,*, Jordina Torrents-Barrena⁴, Margarita Gamarra², Natasha Madera¹, Pedro Romero-Aroca³, Aida Valls⁴, Domenec Puig⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2971-2989, 2022, DOI:10.32604/cmc.2022.020074 - 27 September 2021

Abstract Diabetic retinopathy (DR) is a complication of diabetes mellitus that appears in the retina. Clinitians use retina images to detect DR pathological signs related to the occlusion of tiny blood vessels. Such occlusion brings a degenerative cycle between the breaking off and the new generation of thinner and weaker blood vessels. This research aims to develop a suitable retinal vasculature segmentation method for improving retinal screening procedures by means of computer-aided diagnosis systems. The blood vessel segmentation methodology relies on an effective feature selection based on Sequential Forward Selection, using the error rate of a… More >

S. Sathiya Devi¹, S. Vidivelli^2,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3049-3066, 2022, DOI:10.32604/cmc.2022.019917 - 27 September 2021

Abstract Breast cancer is one of the common invasive cancers and stands at second position for death after lung cancer. The present research work is useful in image processing for characterizing shape and gray-scale complexity. The proposed Modified Differential Box Counting (MDBC) extract Fractal features such as Fractal Dimension (FD), Lacunarity, and Succolarity for shape characterization. In traditional DBC method, the unreasonable results obtained when FD is computed for tumour regions with the same roughness of intensity surface but different gray-levels. The problem is overcome by the proposed MDBC method that uses box over counting and… More >

Shahab Ul Islam¹, Saifullah Jan², Abdul Waheed^3,4,*, Gulzar Mehmood⁵, Mahdi Zareei⁶, Faisal Alanazi⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4123-4145, 2022, DOI:10.32604/cmc.2022.019226 - 27 September 2021

Abstract Spatial and temporal information on urban infrastructure is essential and requires various land-cover/land-use planning and management applications. Besides, a change in infrastructure has a direct impact on other land-cover and climatic conditions. This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature (LST) during the years 1996 and 2019. For this purpose, firstly, satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper) plus and OLI (Operational Land Imager) of 30 m resolution were taken. Secondly, for classification and image processing, remote sensing (RS) applications… More >

G. Jayandhi^1,*, J.S. Leena Jasmine², S. Mary Joans²

Computer Systems Science and Engineering, Vol.40, No.2, pp. 491-503, 2022, DOI:10.32604/csse.2022.016376 - 09 September 2021

Abstract The most common form of cancer for women is breast cancer. Recent advances in medical imaging technologies increase the use of digital mammograms to diagnose breast cancer. Thus, an automated computerized system with high accuracy is needed. In this study, an efficient Deep Learning Architecture (DLA) with a Support Vector Machine (SVM) is designed for breast cancer diagnosis. It combines the ideas from DLA with SVM. The state-of-the-art Visual Geometric Group (VGG) architecture with 16 layers is employed in this study as it uses the small size of 3 × 3 convolution filters that reduces… More >

R. Sujitha^*, B. Paramasivan

CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1557-1572, 2022, DOI:10.32604/cmc.2022.019323 - 07 September 2021

Abstract With the modernization of machine learning techniques in healthcare, different innovations including support vector machine (SVM) have predominantly played a major role in classifying lung cancer, predicting coronavirus disease 2019, and other diseases. In particular, our algorithm focuses on integrated datasets as compared with other existing works. In this study, parallel-based SVM (P-SVM) and multiclass-based multiple submodels (MMSM-SVM) were used to analyze the optimal classification of lung diseases. This analysis aimed to find the optimal classification of lung diseases with id and stages, such as key-value pairs in MapReduce combined with P-SVM and MMSVM for More >

Najlaa Hindi Alsaedi^*, Emad Sami Jaha

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 407-427, 2022, DOI:10.32604/iasc.2022.019538 - 03 September 2021

Abstract Accurate recognition of person identity is a critical task in civil society for various application and different needs. There are different well-established biometric modalities that can be used for recognition purposes such as face, voice, fingerprint, iris, etc. Recently, face images have been widely used for person recognition, since the human face is the most natural and user-friendly recognition method. However, in real-life applications, some factors may degrade the recognition performance, such as partial face occlusion, poses, illumination conditions, facial expressions, etc. In this paper, we propose two dynamic feature subset selection (DFSS) methods to… More >

Abdul Muiz Fayyaz¹, Kawther A. Al-Dhlan², Saeed Ur Rehman¹, Mudassar Raza¹, Waqar Mehmood³, Muhammad Shafiq⁴, Jin-Ghoo Choi^4,*

Intelligent Automation & Soft Computing, Vol.31, No.1, pp. 507-522, 2022, DOI:10.32604/iasc.2022.016392 - 03 September 2021

Abstract Crops are very important to the financial needs of a country. Due to various diseases caused by different pathogens, a large number of crops have been destroyed. As humanoids, our basic need is food for survival, and the most basic foundation of our food is agriculture. For many developing countries, it is mainly an important source of income. Bacterial diseases are one of the main diseases that cause improper production and a major economic crisis for the country. Therefore, it is necessary to detect the disease early. However, it is not easy for humans to… More >

Xiyang Li^1,2, Bin Cheng^1,2, Hui Zhang^1,2,*, Xianghan Zhang¹, Zhi Yun¹

Energy Engineering, Vol.118, No.6, pp. 1869-1886, 2021, DOI:10.32604/EE.2021.015542 - 10 September 2021

Abstract With the continuous increase in the proportional use of wind energy across the globe, the reduction of power generation efficiency and safety hazards caused by the icing on wind turbine blades have attracted more consideration for research. Therefore, it is crucial to accurately analyze the thickness of icing on wind turbine blades, which can serve as a basis for formulating corresponding control measures and ensure a safe and stable operation of wind turbines in winter times and/or in high altitude areas. This paper fully utilized the advantages of the support vector machine (SVM) and back-propagation More >

Shuai Zheng, An-Nan Jiang^*, Kai-Shuai Feng

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.1, pp. 149-166, 2021, DOI:10.32604/cmes.2021.016761 - 24 August 2021

Abstract The randomness of rock joint development is an important factor in the uncertainty of geotechnical engineering stability. In this study, a method is proposed to evaluate the reliability of intermittent jointed rock slope. The least squares support vector machine (LSSVM) evolved by a bacterial foraging optimization algorithm (BFOA) is used to establish a response surface model to express the mapping relationship between the intermittent joint parameters and the slope safety factor. The training samples are obtained from the numerical calculation based on the joint finite element method during this process. Considering the randomness of the… More >

Heming Jia^1,2,*, Yao Li², Kangjian Sun², Ning Cao¹, Helen Min Zhou³

Computer Systems Science and Engineering, Vol.39, No.3, pp. 321-335, 2021, DOI:10.32604/csse.2021.017536 - 12 August 2021

Abstract In this paper, a hybrid model based on sooty tern optimization algorithm (STOA) is proposed to optimize the parameters of the support vector machine (SVM) and identify the best feature sets simultaneously. Feature selection is an essential process of data preprocessing, and it aims to find the most relevant subset of features. In recent years, it has been applied in many practical domains of intelligent systems. The application of SVM in many fields has proved its effectiveness in classification tasks of various types. Its performance is mainly determined by the kernel type and its parameters.… More >