Walid El-Shafai¹, Abeer D. Algarni^2,*, Ghada M. El Banby³, Fathi E. Abd El-Samie^1,2, Naglaa F. Soliman^2,4

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1561-1575, 2022, DOI:10.32604/iasc.2022.020386 - 09 October 2021

Abstract Automated diagnosis based on medical images is a very promising trend in modern healthcare services. For the task of automated diagnosis, there should be flexibility to deal with an enormous amount of data represented in the form of medical images. In addition, efficient algorithms that could be adapted according to the nature of images should be used. The importance of automated medical diagnosis has been maximized with the evolution of COVID-19 pandemic. COVID-19 first appeared in China, Wuhan, and then it has exploded in the whole world with a very bad impact on our daily… More >

P. Ramya¹, B. Padmapriya², S. Poornachandra³

Computer Systems Science and Engineering, Vol.41, No.1, pp. 187-196, 2022, DOI:10.32604/csse.2022.020185 - 08 October 2021

Abstract Arthritis is an acute systemic disease of a joint accompanied by pain. In developed countries, it mainly causes disability among people over 50 years of age. Rheumatoid Arthritis is a type of arthritis that occurs commonly among elders. The incidence of arthritis is higher in females than in males. There is no permanent diagnosis method for arthritis, but if it was identified in the early stages based on the foot pressure, it can be diagnosed before attaining the critical stage of Rheumatoid Arthritis. The analysis and study of arthritis patients were done using design thinking… More >

Yousef Asiri^*

Computer Systems Science and Engineering, Vol.41, No.1, pp. 35-50, 2022, DOI:10.32604/csse.2022.020100 - 08 October 2021

Abstract Most of the international accreditation bodies in engineering education (e.g., ABET) and outcome-based educational systems have based their assessments on learning outcomes and program educational objectives. However, mapping program educational objectives (PEOs) to student outcomes (SOs) is a challenging and time-consuming task, especially for a new program which is applying for ABET-EAC (American Board for Engineering and Technology the American Board for Engineering and Technology—Engineering Accreditation Commission) accreditation. In addition, ABET needs to automatically ensure that the mapping (classification) is reasonable and correct. The classification also plays a vital role in the assessment of students’… More >

M. Vedaraj^*, P. Ezhumalai

Computer Systems Science and Engineering, Vol.41, No.1, pp. 95-108, 2022, DOI:10.32604/csse.2022.019976 - 08 October 2021

Abstract The integration of the Internet of Things (IoT) and cloud computing is the most popular growing technology in the IT world. IoT integrated cloud computing technology can be used in smart cities, health care, smart homes, environmental monitoring, etc. In recent days, IoT integrated cloud can be used in the health care system for remote patient care, emergency care, disease prediction, pharmacy management, etc. but, still, security of patient data and disease prediction accuracy is a major concern. Numerous machine learning approaches were used for effective early disease prediction. However, machine learning takes more time… More >

Mukhtar Ghaleb^1,*, Yahya Almurtadha², Fahad Algarni³, Monir Abdullah³, Emad Felemban⁴, Ali M. Alsharafi³, Mohamed Othman⁵, Khaled Ghilan⁶

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2619-2638, 2022, DOI:10.32604/cmc.2022.020358 - 27 September 2021

Abstract People often communicate with auto-answering tools such as conversational agents due to their 24/7 availability and unbiased responses. However, chatbots are normally designed for specific purposes and areas of experience and cannot answer questions outside their scope. Chatbots employ Natural Language Understanding (NLU) to infer their responses. There is a need for a chatbot that can learn from inquiries and expand its area of experience with time. This chatbot must be able to build profiles representing intended topics in a similar way to the human brain for fast retrieval. This study proposes a methodology to… More >

Muhammad Junaid^1,*, Adnan Sohail¹, Monagi H. Alkinani², Adeel Ahmed³, Mehmood Ahmed³, Faisal Rehman⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 3985-4007, 2022, DOI:10.32604/cmc.2022.019962 - 27 September 2021

Abstract Metaheuristic approaches in cloud computing have shown significant results due to their multi-objective advantages. These approaches are now considering hybrid metaheuristics combining the relative optimized benefits of two or more algorithms resulting in the least tradeoffs among several factors. The critical factors such as execution time, throughput time, response time, energy consumption, SLA violations, communication overhead, makespan, and migration time need careful attention while designing such dynamic algorithms. To improve such factors, an optimized multi-objective hybrid algorithm is being proposed that combines the relative advantages of Cat Swarm Optimization (CSO) with machine learning classifiers such… More >

R. H. Aswathy^1,*, P. Suresh¹, Mohamed Yacin Sikkandar², S. Abdel-Khalek³, Hesham Alhumyani⁴, Rashid A. Saeed⁴, Romany F. Mansour⁵

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2097-2111, 2022, DOI:10.32604/cmc.2022.019790 - 27 September 2021

Abstract In recent times, Internet of Things (IoT) and Cloud Computing (CC) paradigms are commonly employed in different healthcare applications. IoT gadgets generate huge volumes of patient data in healthcare domain, which can be examined on cloud over the available storage and computation resources in mobile gadgets. Chronic Kidney Disease (CKD) is one of the deadliest diseases that has high mortality rate across the globe. The current research work presents a novel IoT and cloud-based CKD diagnosis model called Flower Pollination Algorithm (FPA)-based Deep Neural Network (DNN) model abbreviated as FPA-DNN. The steps involved in the… More >

Juan Pablo Villa-Pulgarin¹, Anderson Alberto Ruales-Torres^1,2, Daniel Arias-Garzón¹, Mario Alejandro Bravo-Ortiz¹, Harold Brayan Arteaga-Arteaga¹, Alejandro Mora-Rubio¹, Jesus Alejandro Alzate-Grisales¹, Esteban Mercado-Ruiz¹, M. Hassaballah³, Simon Orozco-Arias^4,5, Oscar Cardona-Morales¹, Reinel Tabares-Soto^1,*

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2131-2148, 2022, DOI:10.32604/cmc.2022.019529 - 27 September 2021

Abstract Skin cancer is one of the most severe diseases, and medical imaging is among the main tools for cancer diagnosis. The images provide information on the evolutionary stage, size, and location of tumor lesions. This paper focuses on the classification of skin lesion images considering a framework of four experiments to analyze the classification performance of Convolutional Neural Networks (CNNs) in distinguishing different skin lesions. The CNNs are based on transfer learning, taking advantage of ImageNet weights. Accordingly, in each experiment, different workflow stages are tested, including data augmentation and fine-tuning optimization. Three CNN models More >

Batyrkhan Omarov^1,2,*, Nurbek Saparkhojayev², Shyrynkyz Shekerbekova³, Oxana Akhmetova¹, Meruert Sakypbekova¹, Guldina Kamalova³, Zhanna Alimzhanova¹, Lyailya Tukenova³, Zhadyra Akanova⁴

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 2815-2833, 2022, DOI:10.32604/cmc.2022.019246 - 27 September 2021

Abstract Diseases of the cardiovascular system are one of the major causes of death worldwide. These diseases could be quickly detected by changes in the sound created by the action of the heart. This dynamic auscultations need extensive professional knowledge and emphasis on listening skills. There is also an unmet requirement for a compact cardiac condition early warning device. In this paper, we propose a prototype of a digital stethoscopic system for the diagnosis of cardiac abnormalities in real time using machine learning methods. This system consists of three subsystems that interact with each other (1)… More >

Shahab Ul Islam¹, Saifullah Jan², Abdul Waheed^3,4,*, Gulzar Mehmood⁵, Mahdi Zareei⁶, Faisal Alanazi⁷

CMC-Computers, Materials & Continua, Vol.70, No.2, pp. 4123-4145, 2022, DOI:10.32604/cmc.2022.019226 - 27 September 2021

Abstract Spatial and temporal information on urban infrastructure is essential and requires various land-cover/land-use planning and management applications. Besides, a change in infrastructure has a direct impact on other land-cover and climatic conditions. This study assessed changes in the rate and spatial distribution of Peshawar district’s infrastructure and its effects on Land Surface Temperature (LST) during the years 1996 and 2019. For this purpose, firstly, satellite images of bands7 and 8 ETM+(Enhanced Thematic Mapper) plus and OLI (Operational Land Imager) of 30 m resolution were taken. Secondly, for classification and image processing, remote sensing (RS) applications… More >