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T. Vu-Huu¹, C. Le-Thanh², H. Nguyen-Xuan^3,4, M. Abdel-Wahab^3,5,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4217-4239, 2022, DOI:10.32604/cmc.2022.020889 - 11 October 2021
Abstract This paper investigates a polygonal finite element (PFE) to solve a two-dimensional (2D) incompressible steady fluid problem in a cavity square. It is a well-known standard benchmark (i.e., lid-driven cavity flow)-to evaluate the numerical methods in solving fluid problems controlled by the Navier–Stokes (N–S) equation system. The approximation solutions provided in this research are based on our developed equal-order mixed PFE, called Pe₁Pe₁. It is an exciting development based on constructing the mixed scheme method of two equal-order discretisation spaces for both fluid pressure and velocity fields of flows and our proposed stabilisation technique. In this More >

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Abrar M. Alajlan^*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4241-4259, 2022, DOI:10.32604/cmc.2022.020585 - 11 October 2021
Abstract Detection of the wormhole attacks is a cumbersome process, particularly simplex and duplex over the wireless sensor networks (WSNs). Wormhole attacks are characterized as distributed passive attacks that can destabilize or disable WSNs. The distributed passive nature of these attacks makes them enormously challenging to detect. The main objective is to find all the possible ways in which how the wireless sensor network’s broadcasting character and transmission medium allows the attacker to interrupt network within the distributed environment. And further to detect the serious routing-disruption attack “Wormhole Attack” step by step through the different network More >

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S. Ranjithkumar^1,*, S. Chenthur Pandian²
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4261-4277, 2022, DOI:10.32604/cmc.2022.019031 - 11 October 2021
Abstract The growth of cloud in modern technology is drastic by provisioning services to various industries where data security is considered to be common issue that influences the intrusion detection system (IDS). IDS are considered as an essential factor to fulfill security requirements. Recently, there are diverse Machine Learning (ML) approaches that are used for modeling effectual IDS. Most IDS are based on ML techniques and categorized as supervised and unsupervised. However, IDS with supervised learning is based on labeled data. This is considered as a common drawback and it fails to identify the attack patterns.… More >

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Mohamed Yacin Sikkandar^1,*, S. Sabarunisha Begum², Abdulaziz A. Alkathiry³, Mashhor Shlwan N. Alotaibi¹, Md Dilsad Manzar⁴
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4279-4291, 2022, DOI:10.32604/cmc.2022.020571 - 11 October 2021
Abstract Knee Osteoarthritis (KOA) is a degenerative knee joint disease caused by ‘wear and tear’ of ligaments between the femur and tibial bones. Clinically, KOA is classified into four grades ranging from 1 to 4 based on the degradation of the ligament in between these two bones and causes suffering from impaired movement. Identifying this space between bones through the anterior view of a knee X-ray image is solely subjective and challenging. Automatic classification of this process helps in the selection of suitable treatment processes and customized knee implants. In this research, a new automatic classification More >

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Aamer Khan¹, Insaf Ullah^2,*, Fahad Algarni³, Muhammad Naeem¹, M. Irfan Uddin⁴, Muhammad Asghar Khan²
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4293-4306, 2022, DOI:10.32604/cmc.2022.017318 - 11 October 2021
（This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
Abstract Recent years have witnessed growing scientific research interest in the Internet of Things (IoT) technologies, which supports the development of a variety of applications such as health care, Industry 4.0, agriculture, ecological data management, and other various domains. IoT utilizes the Internet as a prime medium of communication for both single documents as well as multi-digital messages. However, due to the wide-open nature of the Internet, it is important to ensure the anonymity, untraceably, confidentiality, and unforgeability of communication with efficient computational complexity and low bandwidth. We designed a light weight and secure proxy blind More >

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Insaf Ullah^1,*, Hira Zahid² , Fahad Algarni³, Muhammad Asghar Khan¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4307-4321, 2022, DOI:10.32604/cmc.2022.017380 - 11 October 2021
（This article belongs to the Special Issue: Machine Learning for Data Analytics)
Abstract

When the Wireless Sensor Network (WSN) is combined with the Internet of Things (IoT), it can be employed in a wide range of applications, such as agriculture, industry 4.0, health care, smart homes, among others. Accessing the big data generated by these applications in Cloud Servers (CSs), requires higher levels of authenticity and confidentiality during communication conducted through the Internet. Signcryption is one of the most promising approaches nowadays for overcoming such obstacles, due to its combined nature, i.e., signature and encryption. A number of researchers have developed schemes to address issues related to access control

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Talha Ahmed Khan, Khizar Abbas, Afaq Muhammad, Wang-Cheol Song^*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4323-4340, 2022, DOI:10.32604/cmc.2022.017118 - 11 October 2021
（This article belongs to the Special Issue: Intelligent Software-defined Networking (SDN) Technologies for Future Generation Networks)
Abstract The scope of the 5G network is not only limited to the enhancements in the form of the quality of service (QoS), but it also includes a wide range of services with various requirements. Besides this, many approaches and platforms are under the umbrella of 5G to achieve the goals of end-to-end service provisioning. However, the management of multiple services over heterogeneous platforms is a complex task. Each platform and service have various requirements to be handled by domain experts. Still, if the next-generation network management is dependent on manual updates, it will become impossible… More >

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Abid. A. Memon¹, M. Asif Memon¹, Kaleemullah Bhatti¹, Kamsing Nonlaopon^2,*, Ilyas Khan³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4341-4355, 2022, DOI:10.32604/cmc.2022.019407 - 11 October 2021
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract This article is intended to examine the fluid flow patterns and heat transfer in a rectangular channel embedded with three semi-circular cylinders comprised of steel at the boundaries. Such an organization is used to generate the heat exchangers with tube and shell because of the production of more turbulence due to zigzag path which is in favor of rapid heat transformation. Because of little maintenance, the heat exchanger of such type is extensively used. Here, we generate simulation of flow and heat transfer using non-isothermal flow interface in the Comsol multiphysics 5.4 which executes the… More >

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Talha Saeed, Chu Kiong Loo^*, Muhammad Shahreeza Safiruz Kassim
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4357-4372, 2022, DOI:10.32604/cmc.2022.019076 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Deep Learning for Medical Image Analysis)
Abstract

Abnormalities of the gastrointestinal tract are widespread worldwide today. Generally, an effective way to diagnose these life-threatening diseases is based on endoscopy, which comprises a vast number of images. However, the main challenge in this area is that the process is time-consuming and fatiguing for a gastroenterologist to examine every image in the set. Thus, this led to the rise of studies on designing AI-based systems to assist physicians in the diagnosis. In several medical imaging tasks, deep learning methods, especially convolutional neural networks (CNNs), have contributed to the state-of-the-art outcomes, where the complicated nonlinear relation

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Walid El-Shafai^1,2,*, Amira A. Mahmoud¹, El-Sayed M. El-Rabaie¹, Taha E. Taha¹, Osama F. Zahran¹, Adel S. El-Fishawy¹, Mohammed Abd-Elnaby³, Fathi E. Abd El-Samie^1,4
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4373-4391, 2022, DOI:10.32604/cmc.2022.019354 - 11 October 2021
Abstract Coronavirus (COVID-19) infection was initially acknowledged as a global pandemic in Wuhan in China. World Health Organization (WHO) stated that the COVID-19 is an epidemic that causes a 3.4% death rate. Chest X-Ray (CXR) and Computerized Tomography (CT) screening of infected persons are essential in diagnosis applications. There are numerous ways to identify positive COVID-19 cases. One of the fundamental ways is radiology imaging through CXR, or CT images. The comparison of CT and CXR scans revealed that CT scans are more effective in the diagnosis process due to their high quality. Hence, automated classification… More >

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Abeer D. Algarni^1,*, Walid El-Shafai², Ghada M. El Banby³, Fathi E. Abd El-Samie^1,2, Naglaa F. Soliman^1,4
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4393-4410, 2022, DOI:10.32604/cmc.2022.020265 - 11 October 2021
Abstract COVID-19 remains to proliferate precipitously in the world. It has significantly influenced public health, the world economy, and the persons’ lives. Hence, there is a need to speed up the diagnosis and precautions to deal with COVID-19 patients. With this explosion of this pandemic, there is a need for automated diagnosis tools to help specialists based on medical images. This paper presents a hybrid Convolutional Neural Network (CNN)-based classification and segmentation approach for COVID-19 detection from Computed Tomography (CT) images. The proposed approach is employed to classify and segment the COVID-19, pneumonia, and normal CT… More >

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1370

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Nasir Mahmood^*, Muhammad Usman Ghani Khan
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4411-4428, 2022, DOI:10.32604/cmc.2022.013956 - 11 October 2021
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract This study proposes an architecture for the prediction of extremist human behaviour from projected suicide bombings. By linking ‘dots’ of police data comprising scattered information of people, groups, logistics, locations, communication, and spatiotemporal characters on different social media groups, the proposed architecture will spawn beneficial information. This useful information will, in turn, help the police both in predicting potential terrorist events and in investigating previous events. Furthermore, this architecture will aid in the identification of criminals and their associates and handlers. Terrorism is psychological warfare, which, in the broadest sense, can be defined as the… More >

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Zeinab Shahbazi, Yung-Cheol Byun^*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4429-4446, 2022, DOI:10.32604/cmc.2022.019755 - 11 October 2021
（This article belongs to the Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract One of the common transportation systems in Korea is calling taxis through online applications, which is more convenient for passengers and drivers in the modern area. However, the driver's passenger taxi request can be rejected based on the driver's location and distance. Therefore, there is a need to specify driver's acceptance and rejection of the received request. The security of this system is another main core to save the transaction information and safety of passengers and drivers. In this study, the origin and destination of the Jeju island South Korea were captured from T-map and More >

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Samar Nour^1,*, Sameh A. Salem^1,2, Shahira M. Habashy¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4447-4466, 2022, DOI:10.32604/cmc.2022.020775 - 11 October 2021
Abstract Recently, Multicore systems use Dynamic Voltage/Frequency Scaling (DV/FS) technology to allow the cores to operate with various voltage and/or frequencies than other cores to save power and enhance the performance. In this paper, an effective and reliable hybrid model to reduce the energy and makespan in multicore systems is proposed. The proposed hybrid model enhances and integrates the greedy approach with dynamic programming to achieve optimal Voltage/Frequency (Vmin/F) levels. Then, the allocation process is applied based on the available workloads. The hybrid model consists of three stages. The first stage gets the optimum safe voltage More >

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Nithya Rekha Sivakumar^1,*, Ahmed Zohair Ibrahim²
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4467-4483, 2022, DOI:10.32604/cmc.2022.019041 - 11 October 2021
Abstract

Tele health utilizes information and communication mechanisms to convey medical information for providing clinical and educational assistances. It makes an effort to get the better of issues of health service delivery involving time factor, space and laborious terrains, validating cost-efficiency and finer ingress in both developed and developing countries. Tele health has been categorized into either real-time electronic communication, or store-and-forward communication. In recent years, a third-class has been perceived as remote healthcare monitoring or tele health, presuming data obtained via Internet of Things (IOT). Although, tele health data analytics and machine learning have been researched

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Jin Wang^1,2, Chenchen Han¹, Xiaofeng Yu^3,*, Yongjun Ren⁴, R. Simon Sherratt⁵
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4485-4502, 2022, DOI:10.32604/cmc.2022.020648 - 11 October 2021
Abstract Distributed storage can store data in multiple devices or servers to improve data security. However, in today's explosive growth of network data, traditional distributed storage scheme is faced with some severe challenges such as insufficient performance, data tampering, and data lose. A distributed storage scheme based on blockchain has been proposed to improve security and efficiency of traditional distributed storage. Under this scheme, the following improvements have been made in this paper. This paper first analyzes the problems faced by distributed storage. Then proposed to build a new distributed storage blockchain scheme with sharding blockchain.… More >

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Shubha Sumesh¹, John Yearwood¹, Shamsul Huda¹ and Shafiq Ahmad^2,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4503-4521, 2022, DOI:10.32604/cmc.2022.015474 - 11 October 2021
（This article belongs to the Special Issue: Deep Learning and Parallel Computing for Intelligent and Efficient IoT)
Abstract

Clinical Study and automatic diagnosis of electrocardiogram (ECG) data always remain a challenge in diagnosing cardiovascular activities. The analysis of ECG data relies on various factors like morphological features, classification techniques, methods or models used to diagnose and its performance improvement. Another crucial factor in the methodology is how to train the model for each patient. Existing approaches use standard training model which faces challenges when training data has variation due to individual patient characteristics resulting in a lower detection accuracy. This paper proposes an adaptive approach to identify performance improvement in building a training model

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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 - 11 October 2021
（This article belongs to the Special Issue: Role of Machine Learning and Evolutionary Algorithms for Cancer Detection and Prediction)
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… More >

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Peng Gao^*, Marek Perkowski, Yiwei Li, Xiaoyu Song
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4545-4561, 2022, DOI:10.32604/cmc.2022.020483 - 11 October 2021
Abstract After Google reported its realization of quantum supremacy, Solving the classical problems with quantum computing is becoming a valuable research topic. Switching function minimization is an important problem in Electronic Design Automation (EDA) and logic synthesis, most of the solutions are based on heuristic algorithms with a classical computer, it is a good practice to solve this problem with a quantum processer. In this paper, we introduce a new hybrid classic quantum algorithm using Grover’s algorithm and symmetric functions to minimize small Disjoint Sum of Product (DSOP) and Sum of Product (SOP) for Boolean switching More >

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Sagheer Abbas¹, Yousef Alhwaiti², Areej Fatima³, Muhammad A. Khan⁴, Muhammad Adnan Khan^5,*, Taher M. Ghazal^6,7, Asma Kanwal^1,8, Munir Ahmad¹, Nouh Sabri Elmitwally^2,9
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4563-4581, 2022, DOI:10.32604/cmc.2022.021102 - 11 October 2021
Abstract This paper presents a handwritten document recognition system based on the convolutional neural network technique. In today’s world, handwritten document recognition is rapidly attaining the attention of researchers due to its promising behavior as assisting technology for visually impaired users. This technology is also helpful for the automatic data entry system. In the proposed system prepared a dataset of English language handwritten character images. The proposed system has been trained for the large set of sample data and tested on the sample images of user-defined handwritten documents. In this research, multiple experiments get very worthy… More >

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Allam Abumwais^1,*, Adil Amirjanov¹, Kaan Uyar¹, Mujahed Eleyat²
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4583-4597, 2022, DOI:10.32604/cmc.2022.020529 - 11 October 2021
（This article belongs to the Special Issue: Application of Big Data Analytics in the Management of Business)
Abstract Multicore systems oftentimes use multiple levels of cache to bridge the gap between processor and memory speed. This paper presents a new design of a dedicated pipeline cache memory for multicore processors called dual port content addressable memory (DPCAM). In addition, it proposes a new replacement algorithm based on hardware which is called a near-far access replacement algorithm (NFRA) to reduce the cost overhead of the cache controller and improve the cache access latency. The experimental results indicated that the latency for write and read operations are significantly less in comparison with a set-associative cache More >

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Mohd Anul Haq^1,*, Abdul Khadar Jilani¹, P. Prabu²
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4599-4617, 2022, DOI:10.32604/cmc.2022.020495 - 11 October 2021
Abstract The understanding of water resource changes and a proper projection of their future availability are necessary elements of sustainable water planning. Monitoring GWS change and future water resource availability are crucial, especially under changing climatic conditions. Traditional methods for in situ groundwater well measurement are a significant challenge due to data unavailability. The present investigation utilized the Long Short Term Memory (LSTM) networks to monitor and forecast Terrestrial Water Storage Change (TWSC) and Ground Water Storage Change (GWSC) based on Gravity Recovery and Climate Experiment (GRACE) datasets from 2003–2025 for five basins of Saudi Arabia. An… More >

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Saadullah Farooq Abbasi^1,2, Harun Jamil³, Wei Chen^2,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4619-4633, 2022, DOI:10.32604/cmc.2022.020318 - 11 October 2021
（This article belongs to the Special Issue: Advancements in Lightweight AI for Constrained Internet of Things Devices for Smart Cities)
Abstract Sleep stage classification can provide important information regarding neonatal brain development and maturation. Visual annotation, using polysomnography (PSG), is considered as a gold standard for neonatal sleep stage classification. However, visual annotation is time consuming and needs professional neurologists. For this reason, an internet of things and ensemble-based automatic sleep stage classification has been proposed in this study. 12 EEG features, from 9 bipolar channels, were used to train and test the base classifiers including convolutional neural network, support vector machine, and multilayer perceptron. Bagging and stacking ensembles are then used to combine the outputs More >

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Reza Khademi Zahedi¹, Naif Alajlan², Hooman Khademi Zahedi³, Timon Rabczuk^2,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4635-4655, 2022, DOI:10.32604/cmc.2022.017682 - 11 October 2021
Abstract The outstanding thermal, optical, electrical and mechanical properties of molybdenum disolphide (MoS₂) heterostructures make them exceptional candidates for an extensive area of applications. Nevertheless, despite considerable technological and academic interest, there is presently a few information regarding the mechanical properties of these novel two-dimensional (2D) materials in the presence of the defects. In this manuscript, we performed extensive molecular dynamics simulations on pre-cracked and pre-notched all-molybdenum disolphide (MoS₂) heterostructure systems using ReaxFF force field. Therefore, we study the influence of several central-crack lengths and notch diameters on the mechanical response of 2H phase, 1T phase and… More >

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Hesham Alhumyani^1,*, Ibrahim Alrube¹, Sameer Alsharif¹, Ashraf Afifi¹, Chokri Ben Amar¹, Hala S. El-Sayed², Osama S. Faragallah³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4657-4673, 2022, DOI:10.32604/cmc.2022.020338 - 11 October 2021
Abstract The rapid development in the information technology field has introduced digital watermark technologies as a solution to prevent unauthorized copying and redistribution of data. This article introduces a self-embedded image verification and integrity scheme. The images are firstly split into dedicated segments of the same block sizes. Then, different Analytic Beta-Wavelet (ABW) orthogonal filters are utilized for embedding a self-segment watermark for image segment using a predefined method. ABW orthogonal filter coefficients are estimated to improve image reconstruction under different block sizes. We conduct a comparative study comparing the watermarked images using three kinds of More >

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Muneeb Ur Rehman¹, Fawad Ahmed¹, Muhammad Attique Khan², Usman Tariq³, Faisal Abdulaziz Alfouzan⁴, Nouf M. Alzahrani⁵, Jawad Ahmad^6,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4675-4690, 2022, DOI:10.32604/cmc.2022.019586 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract Recognition of dynamic hand gestures in real-time is a difficult task because the system can never know when or from where the gesture starts and ends in a video stream. Many researchers have been working on vision-based gesture recognition due to its various applications. This paper proposes a deep learning architecture based on the combination of a 3D Convolutional Neural Network (3D-CNN) and a Long Short-Term Memory (LSTM) network. The proposed architecture extracts spatial-temporal information from video sequences input while avoiding extensive computation. The 3D-CNN is used for the extraction of spectral and spatial features More >

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Ibrahim M. Mehedi^1,2,*, Mohd Heidir Mohd Shah¹ , Soon Xin Ng³ , Abdulah Jeza Aljohani^1,2, Mohammed El-Hajjar³, Muhammad Moinuddin^1,2
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4691-4705, 2022, DOI:10.32604/cmc.2022.020954 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract

This paper presents the design and implementation of Adaptive Generalized Dynamic Inversion (AGDI) to track the position of a Linear Flexible Joint Cart (LFJC) system along with vibration suppression of the flexible joint. The proposed AGDI control law will be comprised of two control elements. The baseline (continuous) control law is based on principle of conventional GDI approach and is established by prescribing the constraint dynamics of controlled state variables that reflect the control objectives. The control law is realized by inverting the prescribed dynamics using dynamically scaled Moore-Penrose generalized inversion. To boost the robust attributes

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Anitha Velu^*, Menakadevi Thangavelu
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4707-4724, 2022, DOI:10.32604/cmc.2022.020095 - 11 October 2021
Abstract The drastic growth of coastal observation sensors results in copious data that provide weather information. The intricacies in sensor-generated big data are heterogeneity and interpretation, driving high-end Information Retrieval (IR) systems. The Semantic Web (SW) can solve this issue by integrating data into a single platform for information exchange and knowledge retrieval. This paper focuses on exploiting the SW base system to provide interoperability through ontologies by combining the data concepts with ontology classes. This paper presents a 4-phase weather data model: data processing, ontology creation, SW processing, and query engine. The developed Oceanographic Weather More >

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Jhonn Pablo Rodríguez^1,*, David Camilo Corrales^1,2, David Griol³, Zoraida Callejas³, Juan Carlos Corrales¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4725-4743, 2022, DOI:10.32604/cmc.2022.019135 - 11 October 2021
（This article belongs to the Special Issue: Artificial Intelligence based Smart precision agriculture with analytic pattern in sustainable environments using IoT)
Abstract Coffee plays a key role in the generation of rural employment in Colombia. More than 785,000 workers are directly employed in this activity, which represents the 26% of all jobs in the agricultural sector. Colombian coffee growers estimate the production of cherry coffee with the main aim of planning the required activities, and resources (number of workers, required infrastructures), anticipating negotiations, estimating, price, and foreseeing losses of coffee production in a specific territory. These important processes can be affected by several factors that are not easy to predict (e.g., weather variability, diseases, or plagues.). In… More >

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Olutomilayo Olayemi Petinrin¹, Faisal Saeed², Xiangtao Li¹, Fahad Ghabban², Ka-Chun Wong^1,3,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4745-4762, 2022, DOI:10.32604/cmc.2022.020523 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Bioactive compounds in plants, which can be synthesized using N-arylation methods such as the Buchwald-Hartwig reaction, are essential in drug discovery for their pharmacological effects. Important descriptors are necessary for the estimation of yields in these reactions. This study explores ten metaheuristic algorithms for descriptor selection and model a voting ensemble for evaluation. The algorithms were evaluated based on computational time and the number of selected descriptors. Analyses show that robust performance is obtained with more descriptors, compared to cases where fewer descriptors are selected. The essential descriptor was deduced based on the frequency of More >

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Abdulaziz Al-Besher¹, Kailash Kumar¹, M. Sangeetha^2,*, Tinashe Butsa³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4763-4780, 2022, DOI:10.32604/cmc.2022.021033 - 11 October 2021
Abstract Most of the questions from users lack the context needed to thoroughly understand the problem at hand, thus making the questions impossible to answer. Semantic Similarity Estimation is based on relating user’s questions to the context from previous Conversational Search Systems (CSS) to provide answers without requesting the user's context. It imposes constraints on the time needed to produce an answer for the user. The proposed model enables the use of contextual data associated with previous Conversational Searches (CS). While receiving a question in a new conversational search, the model determines the question that refers More >

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Azam Zaka¹, Riffat Jabeen^2,*, Kanwal Iqbal Khan³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4781-4802, 2022, DOI:10.32604/cmc.2022.020316 - 11 October 2021
（This article belongs to the Special Issue: Emerging Trends and Real-World Applications of Intelligent Computing Techniques)
Abstract The continuous monitoring of the machine is beneficial in improving its process reliability through reflected power function distribution. It is substantial for identifying and removing errors at the early stages of production that ultimately benefit the firms in cost-saving and quality improvement. The current study introduces control charts that help the manufacturing concerns to keep the production process in control. It presents an exponentially weighted moving average and extended exponentially weighted moving average and then compared their performance. The percentiles estimator and the modified maximum likelihood estimator are used to constructing the control charts. The More >

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R. Manjula Devi¹, M. Premkumar², Pradeep Jangir³, Mohamed Abdelghany Elkotb^4,5, Rajvikram Madurai Elavarasan⁶, Kottakkaran Sooppy Nisar^7,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4803-4827, 2022, DOI:10.32604/cmc.2022.020847 - 11 October 2021
Abstract Optimization is a key technique for maximizing or minimizing functions and achieving optimal cost, gains, energy, mass, and so on. In order to solve optimization problems, metaheuristic algorithms are essential. Most of these techniques are influenced by collective knowledge and natural foraging. There is no such thing as the best or worst algorithm; instead, there are more effective algorithms for certain problems. Therefore, in this paper, a new improved variant of a recently proposed metaphorless Runge-Kutta Optimization (RKO) algorithm, called Improved Runge-Kutta Optimization (IRKO) algorithm, is suggested for solving optimization problems. The IRKO is formulated… More >

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Mohammad Hadwan^1,2,3,*, Basheer M. Al-Maqaleh⁴ , Fuad N. Al-Badani⁵ , Rehan Ullah Khan^1,3, Mohammed A. Al-Hagery⁶
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4829-4845, 2022, DOI:10.32604/cmc.2022.017824 - 11 October 2021
Abstract

Time series forecasting plays a significant role in numerous applications, including but not limited to, industrial planning, water consumption, medical domains, exchange rates and consumer price index. The main problem is insufficient forecasting accuracy. The present study proposes a hybrid forecasting methods to address this need. The proposed method includes three models. The first model is based on the autoregressive integrated moving average (ARIMA) statistical model; the second model is a back propagation neural network (BPNN) with adaptive slope and momentum parameters; and the third model is a hybridization between ARIMA and BPNN (ARIMA/BPNN) and artificial

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1530

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Mohammad Al-Khatib^*, Wafaa Saif
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4847-4865, 2022, DOI:10.32604/cmc.2022.021483 - 11 October 2021
Abstract The last decade witnessed rapid increase in multimedia and other applications that require transmitting and protecting huge amount of data streams simultaneously. For such applications, a high-performance cryptosystem is compulsory to provide necessary security services. Elliptic curve cryptosystem (ECC) has been introduced as a considerable option. However, the usual sequential implementation of ECC and the standard elliptic curve (EC) form cannot achieve required performance level. Moreover, the widely used Hardware implementation of ECC is costly option and may be not affordable. This research aims to develop a high-performance parallel software implementation for ECC. To achieve… More >

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Muhammad Tariq Mahmood^*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4867-4882, 2022, DOI:10.32604/cmc.2022.019544 - 11 October 2021
（This article belongs to the Special Issue: Security and Privacy issues for various Emerging Technologies and Future Trends)
Abstract Detection and classification of the blurred and the non-blurred regions in images is a challenging task due to the limited available information about blur type, scenarios and level of blurriness. In this paper, we propose an effective method for blur detection and segmentation based on transfer learning concept. The proposed method consists of two separate steps. In the first step, genetic programming (GP) model is developed that quantify the amount of blur for each pixel in the image. The GP model method uses the multi-resolution features of the image and it provides an improved blur More >

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1323

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R. Gopi^1,*, P. Muthusamy², P. Suresh³, C. G. Gabriel Santhosh Kumar⁴, Irina V. Pustokhina⁵, Denis A. Pustokhin⁶, K. Shankar⁷
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4883-4896, 2022, DOI:10.32604/cmc.2022.019442 - 11 October 2021
Abstract Smart City Healthcare (SHC²) system is applied in monitoring the patient at home while it is also expected to react to their needs in a timely manner. The system also concedes the freedom of a patient. IoT is a part of this system and it helps in providing care to the patients. IoT-based healthcare devices are trustworthy since it almost certainly recognizes the potential intensifications at very early stage and alerts the patients and medical experts to such an extent that they are provided with immediate care. Existing methodologies exhibit few shortcomings in terms of computational… More >

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1452

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ARTICLE

Sana Ben Hamida^1,2, Hichem Mrabet^3,4, Sana Belguith^5,*, Adeeb Alhomoud⁶, Abderrazak Jemai⁷
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4897-4919, 2022, DOI:10.32604/cmc.2022.019709 - 11 October 2021
（This article belongs to the Special Issue: AI for Wearable Sensing--Smartphone / Smartwatch User Identification / Authentication)
Abstract From fraud detection to speech recognition, including price prediction, Machine Learning (ML) applications are manifold and can significantly improve different areas. Nevertheless, machine learning models are vulnerable and are exposed to different security and privacy attacks. Hence, these issues should be addressed while using ML models to preserve the security and privacy of the data used. There is a need to secure ML models, especially in the training phase to preserve the privacy of the training datasets and to minimise the information leakage. In this paper, we present an overview of ML threats and vulnerabilities,… More >

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1368

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Raniyah Wazirali¹, Rami Ahmad^2,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4922-4946, 2022, DOI:10.32604/cmc.2022.020044 - 11 October 2021
（This article belongs to the Special Issue: Advanced IoT Industrial Solutions and Cyber Security Threats in Communication Networks)
Abstract Energy and security remain the main two challenges in Wireless Sensor Networks (WSNs). Therefore, protecting these WSN networks from Denial of Service (DoS) and Distributed DoS (DDoS) is one of the WSN networks security tasks. Traditional packet deep scan systems that rely on open field inspection in transport layer security packets and the open field encryption trend are making machine learning-based systems the only viable choice for these types of attacks. This paper contributes to the evaluation of the use machine learning algorithms in WSN nodes traffic and their effect on WSN network life time.… More >

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1650

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ARTICLE

Nouh Sabri Elmitwally^1,2, Asma Kanwal^3,4, Sagheer Abbas³, Muhammad A. Khan⁵, Muhammad Adnan Khan^6,*, Munir Ahmad³, Saad Alanazi¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4947-4964, 2022, DOI:10.32604/cmc.2022.021104 - 11 October 2021
Abstract Detection of personality using emotions is a research domain in artificial intelligence. At present, some agents can keep the human’s profile for interaction and adapts themselves according to their preferences. However, the effective method for interaction is to detect the person’s personality by understanding the emotions and context of the subject. The idea behind adding personality in cognitive agents begins an attempt to maximize adaptability on the basis of behavior. In our daily life, humans socially interact with each other by analyzing the emotions and context of interaction from audio or visual input. This paper More >

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1208

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Khaled M. Fouad¹ , Basma M. Hassan^2,*, Omar M. Salim³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4965-4985, 2022, DOI:10.32604/cmc.2022.020926 - 11 October 2021
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract

Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks (WSNs) where the battery capacity and energy sources are very restricted. Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features. This paper suggests a Hybrid Sensor Selection (HSS) technique that combines filter-wrapper method to acquire a rich-informational subset of sensors in a reasonable time. HSS aims to increase the lifetime of WSNs by using the optimal number of sensors. At the same time, HSS

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1360

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Muhammad Aasim Qureshi^1,*, Muhammad Asif¹, Mohd Fadzil Hassan², Ghulam Mustafa¹, Muhammad Khurram Ehsan¹, Aasim Ali¹, Unaza Sajid¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4987-5004, 2022, DOI:10.32604/cmc.2022.020544 - 11 October 2021
（This article belongs to the Special Issue: Machine Learning Empowered Secure Computing for Intelligent Systems)
Abstract In machine learning, sentiment analysis is a technique to find and analyze the sentiments hidden in the text. For sentiment analysis, annotated data is a basic requirement. Generally, this data is manually annotated. Manual annotation is time consuming, costly and laborious process. To overcome these resource constraints this research has proposed a fully automated annotation technique for aspect level sentiment analysis. Dataset is created from the reviews of ten most popular songs on YouTube. Reviews of five aspects—voice, video, music, lyrics and song, are extracted. An N-Gram based technique is proposed. Complete dataset consists of… More >

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2175

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Taher M. Ghazal^1,2, Sagheer Abbas³, Sundus Munir^3,4, M. A. Khan⁵, Munir Ahmad³, Ghassan F. Issa², Syeda Binish Zahra⁴, Muhammad Adnan Khan^6,*, Mohammad Kamrul Hasan¹
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5005-5019, 2022, DOI:10.32604/cmc.2022.020866 - 11 October 2021
Abstract Alzheimer's disease is a severe neuron disease that damages brain cells which leads to permanent loss of memory also called dementia. Many people die due to this disease every year because this is not curable but early detection of this disease can help restrain the spread. Alzheimer's is most common in elderly people in the age bracket of 65 and above. An automated system is required for early detection of disease that can detect and classify the disease into multiple Alzheimer classes. Deep learning and machine learning techniques are used to solve many medical problems More >

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Open Access

ARTICLE

Sunil Kumar¹, Hanumat G. Sastry¹, Venkatadri Marriboyina², Hammam Alshazly^3,*, Sahar Ahmed Idris⁴, Madhushi Verma⁵, Manjit Kaur⁵
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5021-5038, 2022, DOI:10.32604/cmc.2022.021149 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract Information extraction plays a vital role in natural language processing, to extract named entities and events from unstructured data. Due to the exponential data growth in the agricultural sector, extracting significant information has become a challenging task. Though existing deep learning-based techniques have been applied in smart agriculture for crop cultivation, crop disease detection, weed removal, and yield production, still it is difficult to find the semantics between extracted information due to unswerving effects of weather, soil, pest, and fertilizer data. This paper consists of two parts. An initial phase, which proposes a data preprocessing More >

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ARTICLE

Khuram Nawaz Khayam¹, Zahid Mehmood^2,*, Hassan Nazeer Chaudhry³, Muhammad Usman Ashraf⁴, Usman Tariq⁵, Mohammed Nawaf Altouri⁶, Khalid Alsubhi⁷
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5039-5058, 2022, DOI:10.32604/cmc.2022.019975 - 11 October 2021
Abstract Face recognition is a big challenge in the research field with a lot of problems like misalignment, illumination changes, pose variations, occlusion, and expressions. Providing a single solution to solve all these problems at a time is a challenging task. We have put some effort to provide a solution to solving all these issues by introducing a face recognition model based on local tetra patterns and spatial pyramid matching. The technique is based on a procedure where the input image is passed through an algorithm that extracts local features by using spatial pyramid matching and More >

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1284

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ARTICLE

Hyun Kyu Shin¹, Ha Young Kim², Sang Hyo Lee^3,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5059-5071, 2022, DOI:10.32604/cmc.2022.017262 - 11 October 2021
Abstract The durability performance of reinforced concrete (RC) building structures is significantly affected by the corrosion of the steel reinforcement due to chloride penetration, thus, the chloride ion diffusion coefficient should be investigated through experiments or theoretical equations to assess the durability of an RC structure. This study aims to predict the chloride ion diffusion coefficient of concrete, a heterogeneous material. A convolutional neural network (CNN)-based regression model that learns the condition of the concrete surface through deep learning, is developed to efficiently obtain the chloride ion diffusion coefficient. For the model implementation to determine the More >

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2049

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1140

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ARTICLE

Sikander Hans¹, Smarajit Ghosh¹, Aman Kataria², Vinod Karar^2,*, Sarika Sharma³
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5073-5089, 2022, DOI:10.32604/cmc.2022.019971 - 11 October 2021
Abstract The current and future status of the internet is represented by the upcoming Internet of Things (IoT). The internet can connect the huge amount of data, which contains lot of processing operations and efforts to transfer the pieces of information. The emerging IoT technology in which the smart ecosystem is enabled by the physical object fixed with software electronics, sensors and network connectivity. Nowadays, there are two trending technologies that take the platform i.e., Software Defined Network (SDN) and IoT (SD-IoT). The main aim of the IoT network is to connect and organize different objects… More >

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ARTICLE

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 - 11 October 2021
（This article belongs to the Special Issue: Artificial Intelligence and Machine Learning Algorithms in Real-World Applications and Theories)
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… More >

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1517

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ARTICLE

Jung-Hwa Kim¹, Jin-Woo Jeong^2,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5107-5132, 2022, DOI:10.32604/cmc.2022.021107 - 11 October 2021
Abstract Gaze estimation is one of the most promising technologies for supporting indoor monitoring and interaction systems. However, previous gaze estimation techniques generally work only in a controlled laboratory environment because they require a number of high-resolution eye images. This makes them unsuitable for welfare and healthcare facilities with the following challenging characteristics: 1) users’ continuous movements, 2) various lighting conditions, and 3) a limited amount of available data. To address these issues, we introduce a multi-view multi-modal head-gaze estimation system that translates the user’s head orientation into the gaze direction. The proposed system captures the… More >

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ARTICLE

Ibrahim M. Mehedi^1,2,*, Rachid Mansouri³, Ubaid M. Al-Saggaf^1,2, Ahmed I. M. Iskanderani¹, Maamar Bettayeb⁴, Abdulah Jeza Aljohani^1,2, Thangam Palaniswamy¹, Shaikh Abdul Latif⁵, Abdul Latif⁶
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5133-5142, 2022, DOI:10.32604/cmc.2022.021018 - 11 October 2021
（This article belongs to the Special Issue: Recent Advances in Metaheuristic Techniques and Their Real-World Applications)
Abstract A linear flexible joint system using fractional order linear active disturbance rejection control is studied in this paper. With this control scheme, the performance against disturbances, uncertainties, and attenuation is enhanced. Linear active disturbance rejection control (LADRC) is mainly based on an extended state observer (ESO) technology. A fractional integral (FOI) action is combined with the LADRC technique which proposes a hybrid control scheme like FO-LADRC. Incorporating this FOI action improves the robustness of the standard LADRC. The set-point tracking of the proposed FO-LADRC scheme is designed by Bode's ideal transfer function (BITF) based robust More >

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