Abdulghani Ragaa Alharbi^*

CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.3, pp. 2193-2209, 2023, DOI:10.32604/cmes.2022.018445

Abstract The Riemann wave system has a fundamental role in describing waves in various nonlinear natural phenomena, for instance, tsunamis in the oceans. This paper focuses on executing the generalized exponential rational function approach and some numerical methods to obtain a distinct range of traveling wave structures and numerical results of the two-dimensional Riemann problems. The stability of obtained traveling wave solutions is analyzed by satisfying the constraint conditions of the Hamiltonian system. Numerical simulations are investigated via the finite difference method to verify the accuracy of the obtained results. To extract the approximation solutions to the underlying problem, some ODE… More >

S. Sadesh^1,*, Osamah Ibrahim Khalaf², Mohammad Shorfuzzaman³, Abdulmajeed Alsufyani³, K. Sangeetha⁴, Mueen Uddin⁵

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3365-3384, 2023, DOI:10.32604/iasc.2023.030751

Abstract Web usage mining, content mining, and structure mining comprise the web mining process. Web-Page Recommendation (WPR) development by incorporating Data Mining Techniques (DMT) did not include end-users with improved performance in the obtained filtering results. The cluster user profile-based clustering process is delayed when it has a low precision rate. Markov Chain Monte Carlo-Dynamic Clustering (MC²-DC) is based on the User Behavior Profile (UBP) model group’s similar user behavior on a dynamic update of UBP. The Reversible-Jump Concept (RJC) reviews the history with updated UBP and moves to appropriate clusters. Hamilton’s Filtering Framework (HFF) is designed to filter user data… More >

Suma Sekhar^1,*, Sakuntala S. Pillai², S. Santhosh Kumar³

Intelligent Automation & Soft Computing, Vol.35, No.3, pp. 3187-3197, 2023, DOI:10.32604/iasc.2023.028702

Abstract Worldwide Interoperability for Microwave Access (WiMAX) trusts Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) combination for the deployment of physical layer functions and for connecting the medium access control to the wireless media. Even though Orthogonal Frequency Division Multiplexing (OFDM) facilitates reliable digital broadband transmission in the fading wireless channels, the presence of synchronization errors in the form of Carrier Frequency Offset (CFO) and Time Offset (TO) adversely affect the performance of OFDM based physical layers. The objective of this work is to improve the accuracy of the frequency and the time offset estimation in the WiMAX physical layer.… More >

G. Uganya^*, Radhika Baskar

Computer Systems Science and Engineering, Vol.45, No.1, pp. 641-658, 2023, DOI:10.32604/csse.2023.028341

Abstract Internet of Things (IoT) is an emerging technology that moves the world in the direction of smart things. But, IoT security is the complex problem due to its centralized architecture, and limited capacity. So, blockchain technology has great attention due to its features of decentralized architecture, transparency, immutable records and cryptography hash functions when combining with IoT. Cryptography hash algorithms are very important in blockchain technology for secure transmission. It converts the variable size inputs to a fixed size hash output which is unchangeable. Existing cryptography hash algorithms with digital signature have issues of single node accessibility and accessed up… More >

Eatedal Alabdulkreem¹, Jaber S. Alzahrani², Majdy M. Eltahir³, Abdullah Mohamed⁴, Manar Ahmed Hamza^5,*, Abdelwahed Motwakel⁵, Mohamed I. Eldesouki⁶, Mohammed Rizwanullah⁵

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 3039-3055, 2022, DOI:10.32604/cmc.2022.029835

Abstract Big health data collection and storing for further analysis is a challenging task because this knowledge is big and has many features. Several cloud-based IoT health providers have been described in the literature previously. Furthermore, there are a number of issues related to time consumed and overall network performance when it comes to big data information. In the existing method, less performed optimization algorithms were used for optimizing the data. In the proposed method, the Chaotic Cuckoo Optimization algorithm was used for feature selection, and Convolutional Support Vector Machine (CSVM) was used. The research presents a method for analyzing healthcare… More >

Sarika R. Khope¹, Susan Elias^2,*

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2333-2350, 2022, DOI:10.32604/cmc.2022.029423

Abstract Machine learning has proven to be one of the efficient solutions for analyzing complex data to perform identification and classification. With a large number of learning tools and techniques, the health section has significantly benefited from solving the diagnosis problems. This paper has reviewed some of the recent scientific implementations on learning-based schemes to find that existing studies of learning have mainly focused on predictive analysis with less emphasis on preprocessing and more inclination towards adopting sophisticated learning schemes that offer higher accuracy at the cost of the higher computational burden. Therefore, the proposed method addresses the concern mentioned above… More >

Majida Kazmi^1,*, Hashim Raza Khan^1,2, Lubaba², Mohammad Hashir Bin Khalid², Saad Ahmed Qazi^1,2

CMC-Computers, Materials & Continua, Vol.73, No.2, pp. 2351-2370, 2022, DOI:10.32604/cmc.2022.026265

Abstract Energy management benefits both consumers and utility companies alike. Utility companies remain interested in identifying and reducing energy waste and theft, whereas consumers’ interest remain in lowering their energy expenses. A large supply-demand gap of over 6 GW exists in Pakistan as reported in 2018. Reducing this gap from the supply side is an expensive and complex task. However, efficient energy management and distribution on demand side has potential to reduce this gap economically. Electricity load forecasting models are increasingly used by energy managers in taking real-time tactical decisions to ensure efficient use of resources. Advancement in Machine-learning (ML) technology… More >

S. Sakthivel¹, V. Vivekanandhan^2,*, M. Manikandan²

Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 853-866, 2023, DOI:10.32604/iasc.2023.026289

Abstract Irrigation plays a significant role in various agricultural cropping methods deployed in semiarid and arid regions where valuable water applications and managing are considered crucial concerns. Multiple factors such as weather, soil, water, and crop data need to be considered for irrigation maintenance in an efficient besides uniform manner from multifaceted and different information-based systems. A Multi-Agent System (MAS) has been proposed recently based on diverse agent subsystems with definite objectives for attaining global MAS objective and is deployed on Cloud Computing paradigm capable of gathering information from Wireless Sensor Networks (WSNs) positioned in rice, cotton, cassava crops for knowledge… More >

Sankar Sennan¹, Digvijay Pandey^2,*, Youseef Alotaibi³, Saleh Alghamdi⁴

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 343-361, 2022, DOI:10.32604/cmc.2022.028334

Abstract In the present scenario, Deep Learning (DL) is one of the most popular research algorithms to increase the accuracy of data analysis. Due to intra-class differences and inter-class variation, image classification is one of the most difficult jobs in image processing. Plant or spinach recognition or classification is one of the deep learning applications through its leaf. Spinach is more critical for human skin, bone, and hair, etc. It provides vitamins, iron, minerals, and protein. It is beneficial for diet and is readily available in people's surroundings. Many researchers have proposed various machine learning and deep learning algorithms to classify… More >

Waleed El Nahal¹, Hatim G. Zaini², Raghad H. Zaini³, Sherif S. M. Ghoneim^4,*, Ashraf Mohamed Ali Hassan⁵

CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 33-50, 2022, DOI:10.32604/cmc.2022.028190

Abstract Recently, many researchers have tried to develop a robust, fast, and accurate algorithm. This algorithm is for eye-tracking and detecting pupil position in many applications such as head-mounted eye tracking, gaze-based human-computer interaction, medical applications (such as deaf and diabetes patients), and attention analysis. Many real-world conditions challenge the eye appearance, such as illumination, reflections, and occasions. On the other hand, individual differences in eye physiology and other sources of noise, such as contact lenses or make-up. The present work introduces a robust pupil detection algorithm with and higher accuracy than the previous attempts for real-time analytics applications. The proposed… More >