He Gong^1,2,3, Zilian Wang^1,3, Zhiqiang Cheng⁴, Lin Chen^1,3, Haohong Pan^1,3, Daming Zhang², Tianli Hu^1,3,*, Thobela Louis Tyasi⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4971-4980, 2022, DOI:10.32604/cmc.2022.029433

Abstract Flexible strain sensor has attracted much attention because of its potential application in human motion detection. In this work, the prepared strain sensor was obtained by encapsulating electrospun carbonized sponge (CS) with room temperature vulcanized silicone rubber (RTVS). In this paper, the formation mechanism of conductive sponge was studied. Based on the combination of carbonized sponge and RTVS, the strain sensing mechanism and piezoresistive properties are discussed. After research and testing, the CS/RTVS flexible strain sensor has excellent fast response speed and stability, and the maximum strain coefficient of the sensor is 136.27. In this study, the self-developed CS/RTVS sensor… More >

Hai Long¹, Zhe Wang¹, Yidi Cui^2,3, Junhui Wang⁴, Bo Gao⁵, Chao Chen⁵, Yan Zhu^5,*, Heinrich Herre¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5197-5217, 2022, DOI:10.32604/cmc.2022.029365

Abstract Psoriasis is a chronic, non-communicable, painful, disfiguring and disabling disease for which there is no cure, with great negative impact on patients’ quality of life (QoL). Diagnosis and treatment with traditional Chinese medical technique based on syndrome differentiation has been used in practice for a long time and proven effective, though, up to now, there are only a few available studies about the use of semantic technologies and the knowledge systems that use Traditional Chinese Medicine (TCM)-syndrome differentiation for information retrieval and automated reasoning. In this paper we use semantic techniques based on ontologies to develop a prototypical system for… More >

Jinglin Liang^1,2, Qian Sun^1,2,*, Xiaoyi Wang^3,2, Jiping Xu^1,2, Huiyan Zhang^1,2, Li Wang^1,2, Jiabin Yu^1,2, Jing Li⁴, Ruichao Wang⁵

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5459-5471, 2022, DOI:10.32604/cmc.2022.029362

Abstract Underwater sensor networks have important application value in the fields of water environment data collection, marine environment monitoring and so on. It has some characteristics such as low available bandwidth, large propagation delays and limited energy, which bring new challenges to the current researches. The research on coverage control of underwater sensor networks is the basis of other related researches. A good sensor node coverage control method can effectively improve the quality of water environment monitoring. Aiming at the problem of high dynamics and uncertainty of monitoring targets, the random events level are divided into serious events and general events.… More >

Abdullah G. Alharbi¹, Jawad Mirza², Mehak Raza³, Salman Ghafoor^4,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5411-5422, 2022, DOI:10.32604/cmc.2022.029317

Abstract In this paper, we report a simulation study on the performance enhancement of Praseodymium doped silica fiber amplifiers (PDFAs) in O-band (1270–1350 nm) in terms of small signal gain, power conversion efficiency (PCE), and output optical power by employing bidirectional pumping. The PDFA performance is examined by optimizing the length of Praseodymium doped silica fiber (PDF), its mode-field diameter (MFD) and the concentration of Pr³⁺. A small-signal peak gain of 56.4 dB, power conversion efficiency (PCE) of 47%, and output optical power of around 1.6 W (32 dBm) is observed at optimized parameters for input signal wavelength of 1310 nm.… More >

Haykel Marouani^1,*, Fahad Awjah Almehmadi¹, Rihem Farkh², Habib Dhahri³

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4981-4994, 2022, DOI:10.32604/cmc.2022.029315

Abstract

In this work, the concepts of particle swarm optimization-based method, named non-Gaussian improved particle swarm optimization for minimizing the cost of energy (COE) of wind turbines (WTs) on high-altitude sites are introduced. Since the COE depends on site specification constants and initialized parameters of wind turbine, the focus was on the design optimization of rotor radius, hub height and rated power. Based on literature, the COE is converted to the Saudi Arabia context. Thus, the constrained wind turbine optimization problem is developed. Then, non-Gaussian improved particle swarm optimization is provided and compared with the conventional particle swarm optimization for solving… More >

Nithya Rekha Sivakumar^1,*, Sara Abdelwahab Ghorashi¹, Faten Khalid Karim¹, Eatedal Alabdulkreem¹, Amal Al-Rasheed²

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 6253-6267, 2022, DOI:10.32604/cmc.2022.029266

Abstract Mobile clouds are the most common medium for aggregating, storing, and analyzing data from the medical Internet of Things (MIoT). It is employed to monitor a patient’s essential health signs for earlier disease diagnosis and prediction. Among the various disease, skin cancer was the wide variety of cancer, as well as enhances the endurance rate. In recent years, many skin cancer classification systems using machine and deep learning models have been developed for classifying skin tumors, including malignant melanoma (MM) and other skin cancers. However, accurate cancer detection was not performed with minimum time consumption. In order to address these… More >

Nurbaity Sabri^1,2,*, Haza Nuzly Abdull Hamed¹, Zaidah Ibrahim³, Kamalnizat Ibrahim⁴, Mohd Adham Isa¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5559-5573, 2022, DOI:10.32604/cmc.2022.029221

Abstract Adolescent Idiopathic Scoliosis (AIS) is a deformity of the spine that affects teenagers. The current method for detecting AIS is based on radiographic images which may increase the risk of cancer growth due to radiation. Photogrammetry is another alternative used to identify AIS by distinguishing the curves of the spine from the surface of a human’s back. Currently, detecting the curve of the spine is manually performed, making it a time-consuming task. To overcome this issue, it is crucial to develop a better model that automatically detects the curve of the spine and classify the types of AIS. This research… More >

Sofiene Haboubi^1,*, Tawfik Guesmi², Badr M Alshammari², Khalid Alqunun², Ahmed S Alshammari², Haitham Alsaif², Hamid Amiri¹

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 5385-5397, 2022, DOI:10.32604/cmc.2022.029198

Abstract Handwriting recognition is a challenge that interests many researchers around the world. As an exception, handwritten Arabic script has many objectives that remain to be overcome, given its complex form, their number of forms which exceeds 100 and its cursive nature. Over the past few years, good results have been obtained, but with a high cost of memory and execution time. In this paper we propose to improve the capacity of bidirectional gated recurrent unit (BGRU) to recognize Arabic text. The advantages of using BGRUs is the execution time compared to other methods that can have a high success rate… More >

Deepak Sukheja¹, Javaid Ahmad Shah², G. Madhu³, K. Sandeep Kautish⁴, Fahad A. Alghamdi⁵, Ibrahim. S. Yahia^6,7,8, El-Sayed M. El-Kenawy^9,10, Ali Wagdy Mohamed^11,12,*

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4595-4609, 2022, DOI:10.32604/cmc.2022.029122

Abstract Efficient decision-making remains an open challenge in the research community, and many researchers are working to improve accuracy through the use of various computational techniques. In this case, the fuzzification and defuzzification processes can be very useful. Defuzzification is an effective process to get a single number from the output of a fuzzy set. Considering defuzzification as a center point of this research paper, to analyze and understand the effect of different types of vehicles according to their performance. In this paper, the multi-criteria decision-making (MCDM) process under uncertainty and defuzzification is discussed by using the center of the area… More >

Zia Ullah¹, Muhammad Ismail Mohmand¹, Sadaqat ur Rehman^2,*, Muhammad Zubair³, Maha Driss⁴, Wadii Boulila⁵, Rayan Sheikh², Ibrahim Alwawi⁶

CMC-Computers, Materials & Continua, Vol.73, No.3, pp. 4465-4487, 2022, DOI:10.32604/cmc.2022.029101

Abstract Facial expression recognition has been a hot topic for decades, but high intraclass variation makes it challenging. To overcome intraclass variation for visual recognition, we introduce a novel fusion methodology, in which the proposed model first extract features followed by feature fusion. Specifically, RestNet-50, VGG-19, and Inception-V3 is used to ensure feature learning followed by feature fusion. Finally, the three feature extraction models are utilized using Ensemble Learning techniques for final expression classification. The representation learnt by the proposed methodology is robust to occlusions and pose variations and offers promising accuracy. To evaluate the efficiency of the proposed model, we… More >