R. Kanthavel^1,*, R. Dhaya², Kanagaraj Venusamy³

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5783-5798, 2022, DOI:10.32604/cmc.2022.023745

Abstract Knee Osteoarthritis (OA) is a joint disease that is commonly observed in people around the world. Osteoarthritis commonly affects patients who are obese and those above the age of 60. A valid knee image was generated by Computed Tomography (CT). In this work, efficient segmentation of CT images using Elephant Herding Optimization (EHO) optimization is implemented. The initial stage employs, the CT image normalization and the normalized image is incited to image enhancement through histogram correlation. Consequently, the enhanced image is segmented by utilizing Niblack and Bernsen algorithm. The (EHO) optimized outcome is evaluated in two steps. The initial step… More >

Hunmin Lee¹, Inseop Na², Kamoliddin Bultakov³, Youngchul Kim^3,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5413-5425, 2022, DOI:10.32604/cmc.2022.023172

Abstract In this paper, we propose a BPR-CNN (Biometric Pattern Recognition-Convolution Neural Network) classifier for hand motion classification as well as a dynamic threshold algorithm for motion signal detection and extraction by EF (Electric Field) sensors. Currently, an EF sensor or EPS (Electric Potential Sensor) system is attracting attention as a next-generation motion sensing technology due to low computation and price, high sensitivity and recognition speed compared to other sensor systems. However, it remains as a challenging problem to accurately detect and locate the authentic motion signal frame automatically in real-time when sensing body-motions such as hand motion, due to the… More >

Xiangquan Li^1,2, Zhengguang Xu^1,*, Cheng Han¹, Ning Li¹

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.3, pp. 1807-1825, 2022, DOI:10.32604/cmes.2022.017799

Abstract This paper addresses a modified auxiliary model stochastic gradient recursive parameter identification algorithm (M-AM-SGRPIA) for a class of single input single output (SISO) linear output error models with multi-threshold quantized observations. It proves the convergence of the designed algorithm. A pattern-moving-based system dynamics description method with hybrid metrics is proposed for a kind of practical single input multiple output (SIMO) or SISO nonlinear systems, and a SISO linear output error model with multi-threshold quantized observations is adopted to approximate the unknown system. The system input design is accomplished using the measurement technology of random repeatability test, and the probabilistic characteristic… More >

Supreet Singh^1,2, Nitin Mittal¹, Urvinder Singh², Rohit Salgotra², Atef Zaguia³, Dilbag Singh^4,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3445-3462, 2022, DOI:10.32604/cmc.2022.023004

Abstract This paper provides a new optimization algorithm named as tunicate swarm naked mole-rat algorithm (TSNMRA) which uses hybridization concept of tunicate swarm algorithm (TSA) and naked mole-rat algorithm (NMRA). This newly developed algorithm uses the characteristics of both algorithms (TSA and NMRA) and enhance the exploration abilities of NMRA. Apart from the hybridization concept, important parameter of NMRA such as mating factor is made to be self-adaptive with the help of simulated annealing mutation operator and there is no need to define its value manually. For evaluating the working capabilities of proposed TSNMRA, it is tested for 100-digit challenge (CEC… More >

Sonali Dash¹, Sahil Verma^2,*, Kavita², N. Z. Jhanjhi³, Mehedi Masud⁴, Mohammed Baz⁵

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2459-2476, 2022, DOI:10.32604/cmc.2022.020904

Abstract Segmentation of vessel in retinal fundus images is a primary step for the clinical identification for specific eye diseases. Effective diagnosis of vascular pathologies from angiographic images is thus a vital aspect and generally depends on segmentation of vascular structure. Although various approaches for retinal vessel segmentation are extensively utilized, however, the responses are lower at vessel's edges. The curvelet transform signifies edges better than wavelets, and hence convenient for multiscale edge enhancement. The bilateral filter is a nonlinear filter that is capable of providing effective smoothing while preserving strong edges. Fast bilateral filter is an advanced version of bilateral… More >

Qian Wang¹, Xiaolong Yang^2,*, Di Pu³, Yingying Fan⁴

CMES-Computer Modeling in Engineering & Sciences, Vol.130, No.1, pp. 269-286, 2022, DOI:10.32604/cmes.2022.016437

Abstract This paper proposes a new power grid investment prediction model based on the deep restricted Boltzmann machine (DRBM) optimized by the Lion algorithm (LA). Firstly, two factors including transmission and distribution price reform (TDPR) and 5G station construction were comprehensively incorporated into the consideration of influencing factors, and the fuzzy threshold method was used to screen out critical influencing factors. Then, the LA was used to optimize the parameters of the DRBM model to improve the model's prediction accuracy, and the model was trained with the selected influencing factors and investment. Finally, the LA-DRBM model was used to predict the… More >

Usman Ali, Muhammad Tariq Mahmood^*

CMC-Computers, Materials & Continua, Vol.71, No.1, pp. 1597-1611, 2022, DOI:10.32604/cmc.2022.022219

Abstract Enormous methods have been proposed for the detection and segmentation of blur and non-blur regions of the images. Due to the limited available information about blur type, scenario and the level of blurriness, detection and segmentation is a challenging task. Hence, the performance of the blur measure operator is an essential factor and needs improvement to attain perfection. In this paper, we propose an effective blur measure based on local binary pattern (LBP) with adaptive threshold for blur detection. The sharpness metric developed based on LBP used a fixed threshold irrespective of the type and level of blur, that may… More >

Muhammad Tariq Mahmood^*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4867-4882, 2022, DOI:10.32604/cmc.2022.019544

Abstract Detection and classification of the blurred and the non-blurred regions in images is a challenging task due to the limited available information about blur type, scenarios and level of blurriness. In this paper, we propose an effective method for blur detection and segmentation based on transfer learning concept. The proposed method consists of two separate steps. In the first step, genetic programming (GP) model is developed that quantify the amount of blur for each pixel in the image. The GP model method uses the multi-resolution features of the image and it provides an improved blur map. In the second phase,… More >

Junyu Chen¹, Yunwen Feng^1,*, Cheng Lu^1,2, Chengwei Fei²

CMES-Computer Modeling in Engineering & Sciences, Vol.129, No.2, pp. 1013-1027, 2021, DOI:10.32604/cmes.2021.016980

Abstract As the key component in aeroengine rotor systems, the health status of rolling bearings directly influences the reliability and safety of aeroengine rotor systems. In order to monitor rolling bearing conditions, a fusion fault diagnosis method, namely empirical mode decomposition (EMD)-Mahalanobis distance (E2MD) and improved wavelet threshold (IWT) (E2MD-IWT) for vibrational signals and acoustic emission (AE) signals is developed to improve the diagnostic accuracy of rolling bearings. The IWT method is proposed with a hard wavelet threshold and a soft wavelet threshold. Moreover, it is shown to be effective through numerical simulation. EMD is utilized to process the original AE… More >

Kanika¹, Jimmy Singla¹, Ali Kashif Bashir², Yunyoung Nam^3,*, Najam UI Hasan⁴, Usman Tariq⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2861-2877, 2022, DOI:10.32604/cmc.2022.019990

Abstract With the rise of internet facilities, a greater number of people have started doing online transactions at an exponential rate in recent years as the online transaction system has eliminated the need of going to the bank physically for every transaction. However, the fraud cases have also increased causing the loss of money to the consumers. Hence, an effective fraud detection system is the need of the hour which can detect fraudulent transactions automatically in real-time. Generally, the genuine transactions are large in number than the fraudulent transactions which leads to the class imbalance problem. In this research work, an… More >