Mwaffaq Abu-Alhaija, Nidal M. Turab^*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 45-53, 2022, DOI:10.32604/iasc.2022.021426

Abstract Applying machine learning techniques on Internet of Things (IoT) data streams will help achieve better understanding, predict future perceptions, and make crucial decisions based on those analytics. The collaboration between IoT, Big Data and machine learning can be found in different domains such as Health care, Smart cities, and Telecommunications. The aim of this paper is to develop a method for automated learning of electrocardiogram (ECG) streaming data to detect any heart beat anomalies. A promising solution is to use medical sensors that transfer vital signs to medical care computer systems, combined with machine learning, such that clinicians can get… More >

R. Sujatha¹, B. Venkata Siva Krishna¹, Jyotir Moy Chatterjee², P. Rahul Naidu¹, NZ Jhanjhi^3,*, Challa Charita¹, Eza Nerin Mariya¹, Mohammed Baz⁴

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 525-541, 2022, DOI:10.32604/iasc.2022.021216

Abstract In the current times, COVID-19 has taken a handful of people’s lives. So, vaccination is crucial for everyone to avoid the spread of the disease. However, not every vaccine will be perfect or will get success for everyone. In the present work, we have analyzed the data from the Vaccine Adverse Event Reporting System and understood that the vaccines given to the people might or might not work considering certain demographic factors like age, gender, and multiple other variables like the state of living, etc. This variable is considered because it explains the unmentioned variables like their food habits and… More >

Hung-Hsiang Wang¹, Chih-Ping Chen^2,*

Intelligent Automation & Soft Computing, Vol.32, No.1, pp. 237-254, 2022, DOI:10.32604/iasc.2022.020665

Abstract Machine learning can classify the image clarity of low-cost nailfold capillaroscopy (NC) and can be applied to the design verification for other medical devices. The method can be beneficial for systems that require a large number of image datasets. This investigation covers the design, integration, image sharpness estimation, and deconvolution sharpening of the NC. The study applies this device to record two videos and extract 600 photos, including blurry and sharp images. It then uses the Laplace operator method for blur detection of the pictures. Statistics are recorded for each image’s Laplace score and the distribution of clear photos in… More >

B. Prabhu Shankar^1,*, S. Chitra²

Computer Systems Science and Engineering, Vol.41, No.2, pp. 661-676, 2022, DOI:10.32604/csse.2022.019507

Abstract Social networks (SNs) are sources with extreme number of users around the world who are all sharing data like images, audio, and video to their friends using IoT devices. This concept is the so-called Social Internet of Things (SIot). The evolving nature of edge-cloud computing has enabled storage of a large volume of data from various sources, and this task demands an efficient storage procedure. For this kind of large volume of data storage, the usage of data replication using edge with geo-distributed cloud service area is suited to fulfill the user’s expectations with low latency. The major issue is… More >

Ayesha Siddiqa¹, Syed Abbas Zilqurnain Naqvi¹, Muhammad Ahsan¹, Allah Ditta², Hani Alquhayz³, M. A. Khan⁴, Muhammad Adnan Khan^5,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5519-5536, 2022, DOI:10.32604/cmc.2022.021666

Abstract Due to unforeseen climate change, complicated chronic diseases, and mutation of viruses’ hospital administration’s top challenge is to know about the Length of stay (LOS) of different diseased patients in the hospitals. Hospital management does not exactly know when the existing patient leaves the hospital; this information could be crucial for hospital management. It could allow them to take more patients for admission. As a result, hospitals face many problems managing available resources and new patients in getting entries for their prompt treatment. Therefore, a robust model needs to be designed to help hospital administration predict patients’ LOS to resolve… More >

Jaiteg Singh¹, Gaurav Goyal¹, Farman Ali², Babar Shah³, Sangheon Pack^4,*

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6189-6204, 2022, DOI:10.32604/cmc.2022.021657

Abstract Airline industry has witnessed a tremendous growth in the recent past. Percentage of people choosing air travel as first choice to commute is continuously increasing. Highly demanding and congested air routes are resulting in inadvertent delays, additional fuel consumption and high emission of greenhouse gases. Trajectory planning involves creation identification of cost-effective flight plans for optimal utilization of fuel and time. This situation warrants the need of an intelligent system for dynamic planning of optimized flight trajectories with least human intervention required. In this paper, an algorithm for dynamic planning of optimized flight trajectories has been proposed. The proposed algorithm… More >

Anwer Mustafa Hilal¹, Hadeel Alsolai², Fahd N. Al-Wesabi³, Mohammed Abdullah Al-Hagery⁴, Manar Ahmed Hamza^1,*, Mesfer Al Duhayyim⁵

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 6289-6304, 2022, DOI:10.32604/cmc.2022.021522

Abstract In present digital era, data science techniques exploit artificial intelligence (AI) techniques who start and run small and medium-sized enterprises (SMEs) to have an impact and develop their businesses. Data science integrates the conventions of econometrics with the technological elements of data science. It make use of machine learning (ML), predictive and prescriptive analytics to effectively understand financial data and solve related problems. Smart technologies for SMEs enable allows the firm to get smarter with their processes and offers efficient operations. At the same time, it is needed to develop an effective tool which can assist small to medium sized… More >

Abdullah Ali Salamai^1,*, Ather Abdulrahman Ageeli¹, El-Sayed M. El-kenawy²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5091-5106, 2022, DOI:10.32604/cmc.2022.021268

Abstract E-commerce refers to a system that allows individuals to purchase and sell things online. The primary goal of e-commerce is to offer customers the convenience of not going to a physical store to make a purchase. They will purchase the item online and have it delivered to their home within a few days. The goal of this research was to develop machine learning algorithms that might predict e-commerce platform sales. A case study has been designed in this paper based on a proposed continuous Stochastic Fractal Search (SFS) based on a Guided Whale Optimization Algorithm (WOA) to optimize the parameter… More >

Fahd N. Al-Wesabi^1,2,*, Hadeel Alsolai³, Anwer Mustafa Hilal⁴, Manar Ahmed Hamza⁴, Mesfer Al Duhayyim⁵, Noha Negm^6,7

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5803-5820, 2022, DOI:10.32604/cmc.2022.021195

Abstract Corona Virus Disease-2019 (COVID-19) was reported at first in Wuhan city, China by December 2019. World Health Organization (WHO) declared COVID-19 as a pandemic i.e., global health crisis on March 11, 2020. The outbreak of COVID-19 pandemic and subsequent lockdowns to curb the spread, not only affected the economic status of a number of countries, but it also resulted in increased levels of Depression, Anxiety, and Stress (DAS) among people. Therefore, there is a need exists to comprehend the relationship among psycho-social factors in a country that is hypothetically affected by high levels of stress and fear; with tremendously-limiting measures… More >

Ashutosh Kumar Dubey^1,*, Umesh Gupta², Sonal Jain²

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4523-4543, 2022, DOI:10.32604/cmc.2022.021148

Abstract This study aims to empirically analyze teaching-learning-based optimization (TLBO) and machine learning algorithms using k-means and fuzzy c-means (FCM) algorithms for their individual performance evaluation in terms of clustering and classification. In the first phase, the clustering (k-means and FCM) algorithms were employed independently and the clustering accuracy was evaluated using different computational measures. During the second phase, the non-clustered data obtained from the first phase were preprocessed with TLBO. TLBO was performed using k-means (TLBO-KM) and FCM (TLBO-FCM) (TLBO-KM/FCM) algorithms. The objective function was determined by considering both minimization and maximization criteria. Non-clustered data obtained from the first phase… More >