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 >

Ahmed H. Almulihi¹, Fawaz Alassery², Asif Irshad Khan³, Sarita Shukla⁴, Bineet Kumar Gupta⁴, Rajeev Kumar^4,*

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1763-1779, 2022, DOI:10.32604/iasc.2022.023460

Abstract The contributions of the Internet of Medical Things (IoMT), cloud services, information systems, and smart devices are useful for the healthcare industry. With the help of digital healthcare, our lives have been made much more secure and effortless and provide more convenient and accessible treatment. In current, the modern healthcare sector has become more significant and convenient for the purpose of both external and internal threats. Big data breaches affect clients, stakeholders, organisations, and businesses, and they are a source of concern and complication for security professionals. This research examines the many types and categories of big data breaches that… More >

D. Palanikkumar¹, Kamal Upreti², S. Venkatraman^3,*, J. Roselin Suganthi⁴, Sridharan Kannan⁵, S. Srinivasan⁶

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1843-1854, 2022, DOI:10.32604/iasc.2022.023350

Abstract The Selection of the mining method for underground minerals extraction is the crucial task for the mining engineers. Underground minerals extraction is a multi-criteria decision making problem due to many criteria to be considered in the selection process. There are many studies on selection of underground mining method using Multi Criteria Decision Making (MCDM) techniques or approaches. Extracting minerals from the underground involves many geological characteristics also called as input parameters. The geological characteristics of any mineral deposit vary from one location to another location. Thus only one mineral extraction method is not suitable for different deposit characteristics. There are… More >

Fawaz Alassery¹, Ahmed Alzahrani², Asif Irshad Khan², Ashi Khan^3,*, Mohd Nadeem⁴, Md Tarique Jamal Ansari⁴

Intelligent Automation & Soft Computing, Vol.32, No.3, pp. 1701-1715, 2022, DOI:10.32604/iasc.2022.023314

Abstract A large number of people live in diabetes worldwide. Type-2 Diabetes (D2) accounts for 92% of patients with D2 and puts a huge burden on the healthcare industry. This multi-criterion medical research is based on the data collected from the hospitals of Uttar Pradesh, India. In recent times there is a need for a web-based electronic system to determine the impact of mental health in D2 patients. This study will examine the impact assessment in D2 patients. This paper used the integrated methodology of Fuzzy Analytic Hierarchy (FAHP) and Fuzzy Technique for Order Performance by Similarity to Ideal Solution (FTOPSIS).… More >