Amit Sundas¹, Sumit Badotra^1,*, Youseef Alotaibi², Saleh Alghamdi³, Osamah Ibrahim Khalaf⁴

CMC-Computers, Materials & Continua, Vol.72, No.2, pp. 2877-2894, 2022, DOI:10.32604/cmc.2022.025658

Abstract All task scheduling applications need to ensure that resources are optimally used, performance is enhanced, and costs are minimized. The purpose of this paper is to discuss how to Fitness Calculate Values (FCVs) to provide application software with a reliable solution during the initial stages of load balancing. The cloud computing environment is the subject of this study. It consists of both physical and logical components (most notably cloud infrastructure and cloud storage) (in particular cloud services and cloud platforms). This intricate structure is interconnected to provide services to users and improve the overall system's performance. This case study is… More >

Wenbing Zhu^*

Molecular & Cellular Biomechanics, Vol.19, No.2, pp. 89-96, 2022, DOI:10.32604/mcb.2022.018522

Abstract This study aims to understand the influence of nutritional supplementation and sports training on the physical fitness of track and field athletes. Twenty track and field athletes from Chongqing Normal University were supplemented with nutrition and trained for eight weeks. Water, sugar, and vitamins were supplemented. They were trained three times a week, two hours each time. One hour was for special track and field training, and one hour was for physical training. Before and after the experiment, the body composition, sports quality, and functional movement screening (FMS) of the athletes were tested. Compared with before the experiment, the muscle… More >

Ayman Altameem¹, Sandeep Kumar², Ramesh Chandra Poonia³, Abdul Khader Jilani Saudagar^4,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 4719-4736, 2022, DOI:10.32604/cmc.2022.022177

Abstract Since the beginning of time, humans have relied on plants for food, energy, and medicine. Plants are recognized by leaf, flower, or fruit and linked to their suitable cluster. Classification methods are used to extract and select traits that are helpful in identifying a plant. In plant leaf image categorization, each plant is assigned a label according to its classification. The purpose of classifying plant leaf images is to enable farmers to recognize plants, leading to the management of plants in several aspects. This study aims to present a modified whale optimization algorithm and categorizes plant leaf images into classes.… More >

Aman Bhaskar¹, Chirag Sharma¹, Khalid Mohiuddin², Aman Singh^1,*, Osman A. Nasr², Mamdooh Alwetaishi³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3069-3089, 2022, DOI:10.32604/cmc.2022.019866

Abstract Advancement in multimedia technology has resulted in protection against distortion, modification, and piracy. For implementing such protection, we have an existing technique called watermarking but obtaining desired distortion level with sufficient robustness is a challenging task for watermarking in multimedia applications. In the paper, we proposed a smart technique for video watermarking associating meta-heuristic algorithms along with an embedding method to gain an optimized efficiency. The main aim of the optimization algorithm is to obtain solutions with maximum robustness, and which should not exceed the set threshold of quality. To represent the accuracy of the proposed scheme, we employ a… More >

Muhammad Ibrahim¹, Faisal Jamil², YunJung Lee¹, DoHyeun Kim^2,*

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 2599-2616, 2022, DOI:10.32604/cmc.2022.019534

Abstract In recent times, the evolution of blockchain technology has got huge attention from the research community due to its versatile applications and unique security features. The IoT has shown wide adoption in various applications including smart cities, healthcare, trade, business, etc. Among these applications, fitness applications have been widely considered for smart fitness systems. The users of the fitness system are increasing at a high rate thus the gym providers are constantly extending the fitness facilities. Thus, scheduling such a huge number of requests for fitness exercise is a big challenge. Secondly, the user fitness data is critical thus securing… More >

R. Dayana^1,*, G. Maria Kalavathy²

Intelligent Automation & Soft Computing, Vol.31, No.3, pp. 1511-1528, 2022, DOI:10.32604/iasc.2022.020551

Abstract Wireless Sensor Networks (WSNs) become an integral part of Internet of Things (IoT) and finds their applicability in several domains. As classical WSN faces several issues in service-based IoT applications, fog computing has been introduced in real-time, enabling local data processing and avoid raw data transmission to cloud servers. The Fog-based WSN generally involves advanced nodes, normal nodes, and some Fog Nodes (FN). Though the Fog-based WSN offers several benefits, there is a need to develop an effective trust-based secure routing protocol for data transmission among Cluster Heads (CHs) and FNs. In this view, this paper presents a Quantum Firefly… More >

Faisal Jamil¹, Faiza Qayyum¹, Soha Alhelaly², Farjeel Javed³, Ammar Muthanna^4,5,*

CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2513-2530, 2021, DOI:10.32604/cmc.2021.018809

Abstract Nowadays, the blockchain, Internet of Things, and artificial intelligence technology revolutionize the traditional way of data mining with the enhanced data preprocessing, and analytics approaches, including improved service platforms. Nevertheless, one of the main challenges is designing a combined approach that provides the analytics functionality for diverse data and sustains IoT applications with robust and modular blockchain-enabled services in a diverse environment. Improved data analytics model not only provides support insights in IoT data but also fosters process productivity. Designing a robust IoT-based secure analytic model is challenging for several purposes, such as data from diverse sources, increasing data size,… More >

Husam Ali Abdulmohsin^1,*, Hala Bahjat Abdul Wahab², Abdul Mohssen Jaber Abdul Hossen³

CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3997-4016, 2021, DOI:10.32604/cmc.2021.014840

Abstract

Feature selection (FS) (or feature dimensional reduction, or feature optimization) is an essential process in pattern recognition and machine learning because of its enhanced classification speed and accuracy and reduced system complexity. FS reduces the number of features extracted in the feature extraction phase by reducing highly correlated features, retaining features with high information gain, and removing features with no weights in classification. In this work, an FS filter-type statistical method is designed and implemented, utilizing a t-test to decrease the convergence between feature subsets by calculating the quality of performance value (QoPV). The approach utilizes the well-designed fitness function… More >

Prisca Eser^1,*, Thomas Gruber¹, Thimo Marcin¹, Claudia Boeni^1,2, Kerstin Wustmann³, Christina DeLuigi¹, Matthias Greutmann⁴, Daniel Tobler⁵, Markus Schwerzmann³, Matthias Wilhelm¹

Congenital Heart Disease, Vol.16, No.1, pp. 73-84, 2021, DOI:10.32604/CHD.2021.013051

Abstract Background: The purpose of this study was to investigate whether patients with adult congenital heart disease (ACHD) benefit from exercise-based cardiac rehabilitation (CR) short- and long-term with regard to improvement of cardiorespiratory fitness. Methods: Cardiopulmonary exercise tests (CPET) completed by ACHD patients between January 2000 and October 2019 were analysed retrospectively. Linear mixed models were performed for peak oxygen consumption (VO₂) with patients as random effect and age, sex, disease classification, preceding surgery (≤3 months) and preceding CR (≤4 weeks for short term and >4 weeks for long term) as fixed effects. Results: 1056 CPETs of 311 ACHD patients with… More >

Peng Tang^∗, Yu Wang, Ning Shen

Computer Systems Science and Engineering, Vol.35, No.4, pp. 237-246, 2020, DOI:10.32604/csse.2020.35.237

Abstract In today’s modern society, the physical fitness of college students is gradually declining. In this paper, a prediction model for college students’ physical fitness is established, in which support vector regression (SVR) and k-means clustering are combined together for the prediction of college students’ fitness. Firstly, the physical measurement data of college students are classified according to gender and class characteristics. Then, the k-means clustering method is used to classify the physical measurement data of college students. Next, the physical characteristics of college students are extracted by SVR to establish the prediction model of physical indicators, and the model for… More >