Jun Yan^1,2, Qianqian Sui¹, Zhirui Fan¹, Zunyi Duan^3,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 967-986, 2022, DOI:10.32604/cmes.2022.017708

Abstract This study establishes a multiscale and multi-material topology optimization model for thermoelastic lattice structures (TLSs) considering mechanical and thermal loading based on the Extended Multiscale Finite Element Method (EMsFEM). The corresponding multi-material and multiscale mathematical formulation have been established with minimizing strain energy and structural mass as the objective function and constraint, respectively. The Solid Isotropic Material with Penalization (SIMP) interpolation scheme has been adopted to realize micro-scale multi-material selection of truss microstructure. The modified volume preserving Heaviside function (VPHF) is utilized to obtain a clear 0/1 material of truss microstructure. Compared with the classic topology optimization of single-material TLSs,… More >

Zhongxiang Chen¹, Huijuan Zha¹, Zhiquan Shu², Juyi Ye³, Jiaji Pan^1,4,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 841-854, 2022, DOI:10.32604/cmes.2022.017574

Abstract This study aims to improve control schemes for COVID-19 by a numerical model with estimation of parameters. We established a multi-level and multi-objective nonlinear SEIDR model to simulate the virus transmission. The early spread in Japan was adopted as a case study. The first 96 days since the infection were divided into five stages with parameters estimated. Then, we analyzed the trend of the parameter value, age structure ratio, and the defined PCR test index (standardization of the scale of PCR tests). It was discovered that the self-healing rate and confirmed rate were linear with the age structure ratio and… More >

Jienan Chen, Chuang Zhang, Yu Yan, Yuan Liu^*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 949-966, 2022, DOI:10.32604/cmes.2022.017516

Abstract Online file management systems enable cooperatively editing and sharing. However, due to the cost of communication and storage infrastructures, traditional online file management services, e.g., Google Drive and OneDrive, usually provide limited storage space and relatively low download speed for free users. To achieve better performance, ordinary users have to purchase their expensive services. Moreover, these file management systems are based on centralized architecture and bear the privacy leakage risk, because users’ personal files are stored and controlled by their servers. To address the above problems, we propose a peer-to-peer (P2P) file management system based on IPFS and Hyperledger Fabric,… More >

Muhammad Zafar^1,#,*, Muhammad Saif Ullah^1,#, Tareq Manzoor², Muddassir Ali³, Kashif Nazar⁴, Shaukat Iqbal⁵, Habib Ullah Manzoor⁶, Rizwan Haider¹, Woo Young Kim^7,*

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.2, pp. 723-749, 2022, DOI:10.32604/cmes.2022.017257

Abstract In recent years, the emergence of nanotechnology experienced incredible development in the field of medical sciences. During the past decade, investigating the characteristics of nanoparticles during fluid flow has been one of the intriguing issues. Nanoparticle distribution and uniformity have emerged as substantial criteria in both medical and engineering applications. Adverse effects of chemotherapy on healthy tissues are known to be a significant concern during cancer therapy. A novel treatment method of magnetic drug targeting (MDT) has emerged as a promising topical cancer treatment along with some attractive advantages of improving efficacy, fewer side effects, and reduce drug dose. During… More >

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 >