Nishant Behar^*, Manish Shrivastava

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 823-839, 2022, DOI:10.32604/cmes.2022.017030

Abstract Breast cancer is considered an immense threat and one of the leading causes of mortality in females. It is curable only when detected at an early stage. A standard cancer diagnosis approach involves detection of cancer-related anomalies in tumour histopathology images. Detection depends on the accurate identification of the landmarks in the visual artefacts present in the slide images. Researchers are continuously striving to develop automatic machine-learning algorithms for processing medical images to assist in tumour detection. Nowadays, computer-based automated systems play an important role in cancer image analysis and help healthcare experts make rapid and correct inferences about the… More >

Hassen Aydi^1,2,3, Ashish Verma⁴, Jihad Younis⁵, Jung Rye Lee^6,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 887-902, 2022, DOI:10.32604/cmes.2022.016924

Abstract Several (generalized) hypergeometric functions and a variety of their extensions have been presented and investigated in the literature by many authors. In the present paper, we investigate four new hypergeometric functions in four variables and then establish several recursion formulas for these new functions. Also, some interesting particular cases and consequences of our results are discussed. More >

Jung Rye Lee¹, Aftab Hussain², Asfand Fahad³, Ali Raza³, Muhammad Imran Qureshi^3,*, Abid Mahboob⁴, Choonkil Park⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 871-885, 2022, DOI:10.32604/cmes.2022.016836

Abstract In quantitative structure-property relationship (QSPR) and quantitative structure-activity relationship (QSAR) studies, computation of topological indices is a vital tool to predict biochemical and physio-chemical properties of chemical structures. Numerous topological indices have been inaugurated to describe different topological features. The ev and ve-degree are recently introduced novelties, having stronger prediction ability. In this article, we derive formulae of the ev-degree and ve-degree based topological indices for chemical structure of Si₂C₃ − I[a,b]. More >

Shouming Hou, Ji Han^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 855-869, 2022, DOI:10.32604/cmes.2022.016621

Abstract Many people around the world have lost their lives due to COVID-19. The symptoms of most COVID-19 patients are fever, tiredness and dry cough, and the disease can easily spread to those around them. If the infected people can be detected early, this will help local authorities control the speed of the virus, and the infected can also be treated in time. We proposed a six-layer convolutional neural network combined with max pooling, batch normalization and Adam algorithm to improve the detection effect of COVID-19 patients. In the 10-fold cross-validation methods, our method is superior to several state-of-the-art methods. In… More >

Jamel Nebhen^1,*, Pietro M. Ferreira^2,3

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 607-631, 2022, DOI:10.32604/cmes.2022.016086

Abstract This paper presents a proposed low-noise and high-sensitivity Internet of Thing (IoT) system based on an M&NEMS microphone. The IoT device consists of an M&NEMS resistive accelerometer associated with an electronic readout circuit, which is a silicon nanowire and a Continuous-Time (CT) Δ Σ ADC. The first integrator of the Δ Σ ADC is based on a positive feedback DC-gain enhancement two-stage amplifier due to its high linearity and low-noise operations. To mitigate both the offset and 1/f noise, a suggested delay-time chopper negative-R stabilization technique is applied around the first integrator. A 65-nm CMOS process implements the CT Δ… More >

Ritam Sharma¹, Janki Ballabh Sharma¹, Ranjan Maheshwari¹, Praveen Agarwal^2,3,4,5,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 923-947, 2022, DOI:10.32604/cmes.2022.016065

Abstract In this paper, a novel hybrid texture feature set and fractional derivative filter-based breast cancer detection model is introduced. This paper also introduces the application of a histogram of linear bipolar pattern features (HLBP) for breast thermogram classification. Initially, breast tissues are separated by masking operation and filtered by Grmwald–Letnikov fractional derivative-based Sobel mask to enhance the texture and rectify the noise. A novel hybrid feature set using HLBP and other statistical feature sets is derived and reduced by principal component analysis. Radial basis function kernel-based support vector machine is employed for detecting the abnormality in the thermogram. The performance… More >

Haolin Wang¹, Lihui Dong¹, Wei Song^1,2,3,*, Xiaobin Zhao^1,3, Jianxin Xia⁴, Tongmu Liu⁵

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1573-1586, 2022, DOI:10.32604/iasc.2022.023994

Abstract Autonomous underwater vehicle (AUV) has many intelligent optical system, which can collect underwater signal information to make the system decision. One of them is the intelligent vision system, and it can capture the images to analyze. The performance of the particle image segmentation plays an important role in the monitoring of underwater mineral resources. In order to improve the underwater mineral image segmentation performance, some novel segmentation algorithm architectures are proposed. In this paper, an improved mineral image segmentation is proposed based on the modified U-Net. The pyramid upsampling module and residual module are bring into the U-Net model, which… More >

Betania Hernández-Ocaña, Adrian García-López, José Hernández-Torruco, Oscar Chávez-Bosquez^*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1797-1813, 2022, DOI:10.32604/iasc.2022.023570

Abstract The Bacterial Foraging Algorithm (BFOA) is a well-known swarm collective intelligence algorithm used to solve a variety of constraint optimization problems with wide success. Despite its universality, implementing the BFOA may be complex due to the calibration of multiple parameters. Moreover, the Two-Swim Modified Bacterial Foraging Optimization Algorithm (TS-MBFOA) is a state-of-the-art modification of the BFOA which may lead to solutions close to the optimal but with more parameters than the original BFOA. That is why in this paper we present the design using the Unified Modeling Language (UML) and the implementation in the MATLAB platform of a front-end for… More >

K. Karnavel^1,*, G. Shanmugasundaram², Satish S. Salunkhe³, V. Kamatchi Sundari⁴, M. Shunmugathammal⁴, Bal Krishna Saraswat⁵

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1855-1865, 2022, DOI:10.32604/iasc.2022.023524

Abstract Soft robotics is a new field that uses actuators that are non-standard and compatible materials. Industrial robotics is high-throughput manufacturing devices that are quick and accurate. They are built on rigid-body mechanisms. The advancement of robotic production now depends on the inclusion of staff in manufacturing processes, allowing for the completion of activities that need cognitive abilities that are now beyond the scope of artificial networks. Hydrostatic pressure is used to achieve high deflections of structures that are based on the elastomeric in Fluid Actuators (FAs). Soft actuators based on the fluid are a popular choice safe for humans and… More >

Mahmoud Awad¹, Mohamed Abouhawwash^1,2,*, H. N. Agiza¹

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1893-1904, 2022, DOI:10.32604/iasc.2022.023510

Abstract To solve single and multi-objective optimization problems, evolutionary algorithms have been created. We use the non-dominated sorting genetic algorithm (NSGA-II) to find the Pareto front in a two-objective portfolio query, and its extended variant NSGA-III to find the Pareto front in a three-objective portfolio problem, in this article. Furthermore, in both portfolio problems, we quantify the Karush-Kuhn-Tucker Proximity Measure (KKTPM) for each generation to determine how far we are from the effective front and to provide knowledge about the Pareto optimal solution. In the portfolio problem, looking for the optimal set of stock or assets that maximizes the mean return… More >