Rohit Srivastava¹, Ravi Tomar¹, Ashutosh Sharma², Gaurav Dhiman³, Naveen Chilamkurti⁴, Byung-Gyu Kim^5,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 1-19, 2021, DOI:10.32604/cmc.2021.015466

Abstract As multimedia data sharing increases, data security in mobile devices and its mechanism can be seen as critical. Biometrics combines the physiological and behavioral qualities of an individual to validate their character in real-time. Humans incorporate physiological attributes like a fingerprint, face, iris, palm print, finger knuckle print, Deoxyribonucleic Acid (DNA), and behavioral qualities like walk, voice, mark, or keystroke. The main goal of this paper is to design a robust framework for automatic face recognition. Scale Invariant Feature Transform (SIFT) and Speeded-up Robust Features (SURF) are employed for face recognition. Also, we propose a modified Gabor Wavelet Transform for… More >

Taher M. Ghazal^1,2, Marrium Anam³, Mohammad Kamrul Hasan¹, Muzammil Hussain^4,*, Muhammad Sajid Farooq⁵, Hafiz Muhammad Ammar Ali⁴, Munir Ahmad⁶, Tariq Rahim Soomro⁷

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 191-203, 2021, DOI:10.32604/cmc.2021.015436

Abstract Hepatitis C is a contagious blood-borne infection, and it is mostly asymptomatic during the initial stages. Therefore, it is difficult to diagnose and treat patients in the early stages of infection. The disease’s progression to its last stages makes diagnosis and treatment more difficult. In this study, an AI system based on machine learning algorithms is presented to help healthcare professionals with an early diagnosis of hepatitis C. The dataset used for our Hep-Pred model is based on a literature study, and includes the records of 1385 patients infected with the hepatitis C virus. Patients in this dataset received treatment… More >

Ayman Abdulhadi Althuwayb¹, Fazirulhisyam Hashim², Jiun Terng Liew², Imran Khan³, Jeong Woo Lee⁴, Emmanuel Ampoma Affum⁵, Abdeldjalil Ouahabi^6,7,*, Sébastien Jacques⁸

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 679-694, 2021, DOI:10.32604/cmc.2021.015421

Abstract With the rapid development of the mobile internet and the internet of things (IoT), the fifth generation (5G) mobile communication system is seeing explosive growth in data traffic. In addition, low-frequency spectrum resources are becoming increasingly scarce and there is now an urgent need to switch to higher frequency bands. Millimeter wave (mmWave) technology has several outstanding features—it is one of the most well-known 5G technologies and has the capacity to fulfil many of the requirements of future wireless networks. Importantly, it has an abundant resource spectrum, which can significantly increase the communication rate of a mobile communication system. As… More >

Javaria Amin¹, Muhammad Sharif², Muhammad Almas Anjum³, Ayesha Siddiqa¹, Seifedine Kadry⁴, Yunyoung Nam^5,*, Mudassar Raza²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 785-799, 2021, DOI:10.32604/cmc.2021.015249

Abstract White blood cells (WBCs) are a vital part of the immune system that protect the body from different types of bacteria and viruses. Abnormal cell growth destroys the body’s immune system, and computerized methods play a vital role in detecting abnormalities at the initial stage. In this research, a deep learning technique is proposed for the detection of leukemia. The proposed methodology consists of three phases. Phase I uses an open neural network exchange (ONNX) and YOLOv2 to localize WBCs. The localized images are passed to Phase II, in which 3D-segmentation is performed using deeplabv3 as a base network of… More >

Norhan Hesham, Osama Abu-Elnasr^*, Samir Elmougy

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 175-190, 2021, DOI:10.32604/cmc.2021.015168

Abstract Many previous research studies have demonstrated game strategies enabling virtual players to play and take actions mimicking humans. The Case-Based Reasoning (CBR) strategy tries to simulate human thinking regarding solving problems based on constructed knowledge. This paper suggests a new Action-Based Reasoning (ABR) strategy for a chess engine. This strategy mimics human experts’ approaches when playing chess, with the help of the CBR phases. This proposed engine consists of the following processes. Firstly, an action library compiled by parsing many grandmasters’ cases with their actions from different games is built. Secondly, this library reduces the search space by using two… More >

Dileep Kumar^1,*, Imtiaz Hussain Kalwar², Tanweer Hussain¹, Bhawani Shankar Chowdhry¹, Sanaullah Mehran Ujjan¹, Tayab Din Memon³

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 393-408, 2021, DOI:10.32604/cmc.2021.014941

Abstract Reliability of rotating machines is highly dependent on the smooth rolling of bearings. Thus, it is very essential for reliable operation of rotating machines to monitor the working condition of bearings using suitable fault diagnosis and condition monitoring approach. In the recent past, Deep Learning (DL) has become applicable in condition monitoring of rotating machines owing to its performance. This paper proposes a novel bearing fault diagnosis method based on the processing and analysis of the vibration images. The proposed method is the UNET model that is a recent development in DL models. The model is applied to the 2D… More >

Atta-ur-Rahman¹, Kiran Sultan³, Iftikhar Naseer⁴, Rizwan Majeed⁵, Dhiaa Musleh¹, Mohammed Abdul Salam Gollapalli², Sghaier Chabani², Nehad Ibrahim¹, Shahan Yamin Siddiqui^6,7, Muhammad Adnan Khan^8,*

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 21-34, 2021, DOI:10.32604/cmc.2021.013453

Abstract COVID-19 turned out to be an infectious and life-threatening viral disease, and its swift and overwhelming spread has become one of the greatest challenges for the world. As yet, no satisfactory vaccine or medication has been developed that could guarantee its mitigation, though several efforts and trials are underway. Countries around the globe are striving to overcome the COVID-19 spread and while they are finding out ways for early detection and timely treatment. In this regard, healthcare experts, researchers and scientists have delved into the investigation of existing as well as new technologies. The situation demands development of a clinical… More >

Naveen Kumar Seerangan^1,*, S. Vijayaragavan Shanmugam²

CMC-Computers, Materials & Continua, Vol.69, No.1, pp. 819-830, 2021, DOI:10.32604/cmc.2021.012135

Abstract Root-cause identification plays a vital role in business decision making by providing effective future directions for the organizations. Aspect extraction and sentiment extraction plays a vital role in identifying the root-causes. This paper proposes the Ensemble based temporal weighting and pareto ranking (ETP) model for Root-cause identification. Aspect extraction is performed based on rules and is followed by opinion identification using the proposed boosted ensemble model. The obtained aspects are validated and ranked using the proposed aspect weighing scheme. Pareto-rule based aspect selection is performed as the final selection mechanism and the results are presented for business decision making. Experiments… More >

Mario Bonagura, Lucio Nobile^*

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 125-137, 2021, DOI:10.32604/sdhm.2021.015644

Abstract The compressive strength of concrete is one of most important mechanical parameters in the performance assessment of existing reinforced concrete structures. According to various international codes, core samples are drilled and tested to obtain the concrete compressive strengths. Non-destructive testing is an important alternative when destructive testing is not feasible without damaging the structure. The commonly used non-destructive testing (NDT) methods to estimate the in-situ values include the Rebound hammer test and the Ultrasonic Pulse Velocity test. The poor reliability of these tests due to different aspects could be partially contrasted by using both methods together, as proposed.in the SonReb… More >

Yihua Wang¹, Zhenhuan Zhou¹, Hao Xu^1,*, Shuai Li², Zhanjun Wu¹

Structural Durability & Health Monitoring, Vol.15, No.2, pp. 85-101, 2021, DOI:10.32604/sdhm.2021.014256

Abstract For practical engineering structures, it is usually difficult to measure external load distribution in a direct manner, which makes inverse load identification important. Specifically, load identification is a typical inverse problem, for which the models (e.g., response matrix) are often ill-posed, resulting in degraded accuracy and impaired noise immunity of load identification. This study aims at identifying external loads in a stiffened plate structure, through comparing the effectiveness of different methods for parameter selection in regulation problems, including the Generalized Cross Validation (GCV) method, the Ordinary Cross Validation method and the truncated singular value decomposition method. With demonstrated high accuracy,… More >