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Bilal Khan¹, Danish Shehzad¹, Numan Shafi¹, Ga-Young Kim^2,*, Muhammad Umar Aftab¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1671-1690, 2022, DOI:10.32604/cmc.2022.024918
Abstract Nowadays multiple wireless communication systems operate in industrial environments side by side. In such an environment performance of one wireless network can be degraded by the collocated hostile wireless network having higher transmission power or higher carrier sensing threshold. Unlike the previous research works which considered IEEE 802.15.4 for the Industrial Wireless communication systems (iWCS) this paper examines the coexistence of IEEE 802.11 based iWCS used for delay-stringent communication in process automation and gWLAN (general-purpose WLAN) used for non-real time communication. In this paper, we present a Markov chain-based performance model that described the transmission failure of iWCS due to… More >

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Mansour F. Yassen^1,2,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1691-1706, 2022, DOI:10.32604/cmc.2022.029701
Abstract Quantifying the tool–tissue interaction forces in surgery can be utilized in the training of inexperienced surgeons, assist them better use surgical tools and avoid applying excessive pressures. The voltages read from strain gauges are used to approximate the unknown values of implemented forces. To this objective, the force-voltage connection must be quantified in order to evaluate the interaction forces during surgery. The progress of appropriate statistical learning approaches to describe the link between the genuine force applied on the tissue and numerous outputs obtained from sensors installed on surgical equipment is a key problem. In this study, different probabilistic approaches… More >

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794

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Miao Xu¹, Bo Zhu^1,*, Chunmei Chen¹, Yuwei Wan²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1707-1722, 2022, DOI:10.32604/cmc.2022.027708
Abstract It is not uncommon that two or more related process quality characteristics are needed to be monitored simultaneously in production process for most of time. Meanwhile, the observations obtained online are often serially autocorrelated due to high sampling frequency and process dynamics. This goes against the statistical I.I.D assumption in using the multivariate control charts, which may lead to the performance of multivariate control charts collapse soon. Meanwhile, the process control method based on pattern recognition as a non-statistical approach is not confined by this limitation, and further provide more useful information for quality practitioners to locate the assignable causes… More >

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1002

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636

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Abdulaziz Aldaej^*, Tariq Ahamed Ahanger, Mohammed Yousuf Uddin, Imdad Ullah
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1723-1745, 2022, DOI:10.32604/cmc.2022.027487
Abstract Viral diseases transmitted by mosquitoes are emerging public health problems across the globe. Dengue is considered to be the most significant mosquito-oriented disease. Conspicuously, the present study provides an effective architecture for Dengue Virus Infection surveillance. The proposed system involves a 4-level architecture for the prediction and prevention of dengue infection outspread. The architectural levels including Dengue Information Acquisition level, Dengue Information Classification level, Dengue-Mining and Extraction level, and Dengue-Prediction and Decision Modeling level enable an individual to periodically monitor his/her probabilistic dengue fever measure. The prediction process is carried out so that proactive measures are taken beforehand. For predictive… More >

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591

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ARTICLE

Imran Ashraf¹, Muhammad Usman Ali², Soojung Hur¹, Gunzung Kim¹, Yongwan Park^1,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1747-1768, 2022, DOI:10.32604/cmc.2022.020610
Abstract Indoor positioning and localization have emerged as a potential research area during the last few years owing to the wide proliferation of smartphones and the inception of location-attached services for the consumer industry. Due to the importance of precise location information, several positioning technologies are adopted such as Wi-Fi, ultrawideband, infrared, radio frequency identification, Bluetooth beacons, pedestrian dead reckoning, and magnetic field, etc. Although Wi-Fi and magnetic field-based positioning are more attractive concerning the deployment of Wi-Fi access points and ubiquity of magnetic field data, the latter is preferred as it does not require any additional infrastructure as other approaches… More >

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862

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Xiaodong Yan^1,2, Yiqin Wang^1,2, Wei Song^1,2,*, Xiaobing Zhao^1,2, A. Run³, Yang Yanxing⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1769-1781, 2022, DOI:10.32604/cmc.2022.027301
Abstract Text summarization creates subset that represents the most important or relevant information in the original content, which effectively reduce information redundancy. Recently neural network method has achieved good results in the task of text summarization both in Chinese and English, but the research of text summarization in low-resource languages is still in the exploratory stage, especially in Tibetan. What’s more, there is no large-scale annotated corpus for text summarization. The lack of dataset severely limits the development of low-resource text summarization. In this case, unsupervised learning approaches are more appealing in low-resource languages as they do not require labeled data.… More >

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529

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Mahmoud Ragab^1,2,3,*, Adel A. Bahaddad⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1783-1797, 2022, DOI:10.32604/cmc.2022.028055
Abstract Due to drastic increase in the generation of data, it is tedious to examine and derive high level knowledge from the data. The rising trends of high dimension data gathering and problem representation necessitates feature selection process in several machine learning processes. The feature selection procedure establishes a generally encountered issue of global combinatorial optimization. The FS process can lessen the number of features by the removal of unwanted and repetitive data. In this aspect, this article introduces an improved harmony search based global optimization for feature selection with optimal deep learning (IHSFS-ODL) enabled classification model. The proposed IHSFS-ODL technique… More >

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493

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Muhammad Hamza Azam¹, Mohd Hilmi Hasan^1,*, Azlinda A Malik², Saima Hassan³, Said Jadid Abdulkadir¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1799-1815, 2022, DOI:10.32604/cmc.2022.028292
Abstract Electricity price forecasting is a subset of energy and power forecasting that focuses on projecting commercial electricity market present and future prices. Electricity price forecasting have been a critical input to energy corporations’ strategic decision-making systems over the last 15 years. Many strategies have been utilized for price forecasting in the past, however Artificial Intelligence Techniques (Fuzzy Logic and ANN) have proven to be more efficient than traditional techniques (Regression and Time Series). Fuzzy logic is an approach that uses membership functions (MF) and fuzzy inference model to forecast future electricity prices. Fuzzy c-means (FCM) is one of the popular… More >

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1018

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551

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ARTICLE

Yan Sun^1,2,*, Cun Zhu¹, Qi Cui³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1817-1825, 2022, DOI:10.32604/cmc.2022.029408
Abstract Research on the feature of speech and image signals are carried out from two perspectives, the time domain and the frequency domain. The speech and image signals are a non-stationary signal, so FT is not used for the non-stationary characteristics of the signal. When short-term stable speech is obtained by windowing and framing the subsequent processing of the signal is completed by the Discrete Fourier Transform (DFT). The Fast Discrete Fourier Transform is a commonly used analysis method for speech and image signal processing in frequency domain. It has the problem of adjusting window size to a for desired resolution.… More >

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1073

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510

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Jahangir Jabbar¹, Muzammil Hussain², Hassaan Malik^2,*, Abdullah Gani³, Ali Haider Khan², Muhammad Shiraz⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1827-1844, 2022, DOI:10.32604/cmc.2022.024965
Abstract Wrist cracks are the most common sort of cracks with an excessive occurrence rate. For the routine detection of wrist cracks, conventional radiography (X-ray medical imaging) is used but periodically issues are presented by crack depiction. Wrist cracks often appear in the human arbitrary bone due to accidental injuries such as slipping. Indeed, many hospitals lack experienced clinicians to diagnose wrist cracks. Therefore, an automated system is required to reduce the burden on clinicians and identify cracks. In this study, we have designed a novel residual network-based convolutional neural network (CNN) for the crack detection of the wrist. For the… More >

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534

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E. A. Alabdulkreem¹, Ahmed Sedik², Abeer D. Algarni^3,*, Ghada M. El Banby⁴, Fathi E. Abd El-Samie^3,5, Naglaa F. Soliman^3,6
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1845-1861, 2022, DOI:10.32604/cmc.2022.023905
Abstract Image fusion has become one of the interesting fields that attract researchers to integrate information from different image sources. It is involved in several applications. One of the recent applications is the robotic vision. This application necessitates image enhancement of both infrared (IR) and visible images. This paper presents a Robot Human Interaction System (RHIS) based on image fusion and deep learning. The basic objective of this system is to fuse visual and IR images for efficient feature extraction from the captured images. Then, an enhancement model is carried out on the fused image to increase its quality. Several image… More >

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1108

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901

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Qiuqin Yang¹, Linfang Li¹, Ming-Xing Luo^1,*, Xiaojun Wang²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1863-1877, 2022, DOI:10.32604/cmc.2022.027120
Abstract In real communication systems, secure and low-energy transmit scheme is very important. So far, most of schemes focus on secure transmit in special scenarios. In this paper, our goal is to propose a secure protocol in wireless networks involved various factors including artificial noise (AN), the imperfect receiver and imperfect channel state information (CSI) of eavesdropper, weight of beamforming (BF) vector, cooperative jammers (CJ), multiple receivers, and multiple eavesdroppers, and the analysis shows that the protocol can reduce the transmission power, and at the same time the safe reachability rate is greater than our pre-defined value, and the analysis results… More >

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987

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601

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ARTICLE

Sikandar Zulqarnain Khan^1,*, Sajjad Shaukat Jamal², Asher Sajid³, Muhammad Rashid⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1879-1894, 2022, DOI:10.32604/cmc.2022.028152
Abstract This paper presents an efficient crypto processor architecture for key agreement using ECDH (Elliptic-curve Diffie Hellman) protocol over . The composition of our key-agreement architecture is expressed in consisting of the following: (i) Elliptic-curve Point Multiplication architecture for public key generation (DESIGN-I) and (ii) integration of DESIGN-I with two additional routing multiplexers and a controller for shared key generation (DESIGN-II). The arithmetic operators used in DESIGN-I and DESIGN-II contain an adder, squarer, a multiplier and inversion. A simple shift and add multiplication method is employed to retain lower hardware resources. Moreover, an essential inversion operation is operated using the Itoh-Tsujii… More >

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760

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ARTICLE

Sandhya Venu Vasantha¹, Shirina Samreen^2,*, Yelganamoni Lakshmi Aparna³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1895-1914, 2022, DOI:10.32604/cmc.2022.028504
Abstract Hitherto, Rice (Oryza Sativa) has been one of the most demanding food crops in the world, cultivated in larger quantities, but loss in both quality and quantity of yield due to abiotic and biotic stresses has become a major concern. During cultivation, the crops are most prone to biotic stresses such as bacterial, viral, fungal diseases and pests. These stresses can drastically damage the crop. Lately and erroneously recognized crop diseases can increase fertilizers costs and major yield loss which results in high financial loss and adverse impact on nation’s economy. The proven methods of molecular biology can provide accurate… More >

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1126

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761

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Xin Yao¹, Junyu Zhu¹, Hong Zeng², Wenzheng Yu^1,*, Hanxiaoya Zhang³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1915-1926, 2022, DOI:10.32604/cmc.2022.026777
Abstract Accumulated temperature, which is now widely used in agronomy, is an important ecological factor to the growth of plants, but few relative studies have been found on the vegetation area of floodplain grasslands in Poyang Lake. This research used the classification and regression tree (CART) to classify normalized vegetation area index derived from MODIS LAI (Moderate Resolution Imaging Spectroradiometer Leaf Area Index) images from 2008 to 2014, according to different climate indexes, such as mean daily air temperature (n), accumulated temperature (jw), daily maximum temperature (g), daily minimum temperature (d), accumulative precipitation (j), water level (s) and average water level… More >

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550

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ARTICLE

Syed Ali Raza^1,2, Sagheer Abbas¹, Taher M. Ghazal^3,4, Muhammad Adnan Khan^5,6, Munir Ahmad¹, Hussam Al Hamadi^7,*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1927-1942, 2022, DOI:10.32604/cmc.2022.029400
Abstract In the world of big data, it's quite a task to organize different files based on their similarities. Dealing with heterogeneous data and keeping a record of every single file stored in any folder is one of the biggest problems encountered by almost every computer user. Much of file management related tasks will be solved if the files on any operating system are somehow categorized according to their similarities. Then, the browsing process can be performed quickly and easily. This research aims to design a system to automatically organize files based on their similarities in terms of content. The proposed… More >

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650

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Sunday Adeola Ajagbe¹, Mayowa O. Oyediran², Anand Nayyar^3,*, Jinmisayo A. Awokola⁴, Jehad F. Al-Amri⁵
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1943-1959, 2022, DOI:10.32604/cmc.2022.028331
Abstract Cloud computing is a collection of disparate resources or services, a web of massive infrastructures, which is aimed at achieving maximum utilization with higher availability at a minimized cost. One of the most attractive applications for cloud computing is the concept of distributed information processing. Security, privacy, energy saving, reliability and load balancing are the major challenges facing cloud computing and most information technology innovations. Load balancing is the process of redistributing workload among all nodes in a network; to improve resource utilization and job response time, while avoiding overloading some nodes when other nodes are underloaded or idle is… More >

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954

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494

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ARTICLE

Abed Saif Alghawli^*
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1961-1976, 2022, DOI:10.32604/cmc.2022.028990
Abstract In the period of Industries 4.0, cyber-physical systems (CPSs) were a major study area. Such systems frequently occur in manufacturing processes and people’s everyday lives, and they communicate intensely among physical elements and lead to inconsistency. Due to the magnitude and importance of the systems they support, the cyber quantum models must function effectively. In this paper, an image-processing-based anomalous mobility detecting approach is suggested that may be added to systems at any time. The expense of glitches, failures or destroyed products is decreased when anomalous activities are detected and unplanned scenarios are avoided. The presently offered techniques are not… More >

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520

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ARTICLE

Krishan Kumar^1,*, Mohamed Abouhawwash^2,3, Amit Kant Pandit¹, Shubham Mahajan¹, Mofreh A. Hogo⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1977-1993, 2022, DOI:10.32604/cmc.2022.027850
Abstract The high-efficiency video coder (HEVC) is one of the most advanced techniques used in growing real-time multimedia applications today. However, they require large bandwidth for transmission through bandwidth, and bandwidth varies with different video sequences/formats. This paper proposes an adaptive information-based variable quantization matrix (AI-VQM) developed for different video formats having variable energy levels. The quantization method is adapted based on video sequence using statistical analysis, improving bit budget, quality and complexity reduction. Further, to have precise control over bit rate and quality, a multi-constraint prune algorithm is proposed in the second stage of the AI-VQM technique for pre-calculating K… More >

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982

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570

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Jian Liu¹, Yipeng Du¹, Xiang Wang^1,*, Wuguang Yue², Jim Feng³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 1995-2011, 2022, DOI:10.32604/cmc.2022.029073
Abstract Epilepsy is a common neurological disease and severely affects the daily life of patients. The automatic detection and diagnosis system of epilepsy based on electroencephalogram (EEG) is of great significance to help patients with epilepsy return to normal life. With the development of deep learning technology and the increase in the amount of EEG data, the performance of deep learning based automatic detection algorithm for epilepsy EEG has gradually surpassed the traditional hand-crafted approaches. However, the neural architecture design for epilepsy EEG analysis is time-consuming and laborious, and the designed structure is difficult to adapt to the changing EEG collection… More >

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657

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R. Rajkamal^1,*, Anitha Karthi², Xiao-Zhi Gao³
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2013-2033, 2022, DOI:10.32604/cmc.2022.027142
Abstract Diabetes is increasing commonly in people’s daily life and represents an extraordinary threat to human well-being. Machine Learning (ML) in the healthcare industry has recently made headlines. Several ML models are developed around different datasets for diabetic prediction. It is essential for ML models to predict diabetes accurately. Highly informative features of the dataset are vital to determine the capability factors of the model in the prediction of diabetes. Feature engineering (FE) is the way of taking forward in yielding highly informative features. Pima Indian Diabetes Dataset (PIDD) is used in this work, and the impact of informative features in… More >

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Almas Temirbekov¹, Zhadra Zhaksylykova^2,*, Yerzhan Malgazhdarov³, Syrym Kasenov¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2035-2055, 2022, DOI:10.32604/cmc.2022.027830
Abstract To apply the fictitious domain method and conduct numerical experiments, a boundary value problem for an ordinary differential equation is considered. The results of numerical calculations for different values of the iterative parameter τ and the small parameter ε are presented. A study of the auxiliary problem of the fictitious domain method for Navier-Stokes equations with continuation into a fictitious subdomain by higher coefficients with a small parameter is carried out. A generalized solution of the auxiliary problem of the fictitious domain method with continuation by higher coefficients with a small parameter is determined. After all the above mathematical studies,… More >

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698

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Ali Abdullah Hassan^1,*, Salwani Abdullah¹, Kamal Z. Zamli², Rozilawati Razali¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2057-2077, 2022, DOI:10.32604/cmc.2022.026310
Abstract Much of our daily tasks have been computerized by machines and sensors communicating with each other in real-time. There is a reasonable risk that something could go wrong because there are a lot of sensors producing a lot of data. Combinatorial testing (CT) can be used in this case to reduce risks and ensure conformance to specifications. Numerous existing meta-heuristic-based solutions aim to assist the test suite generation for combinatorial testing, also known as t-way testing (where t indicates the interaction strength), viewed as an optimization problem. Much previous research, while helpful, only investigated a small number of interaction strengths… More >

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Daqing Wu^1,2, Ziwei Zhu¹, Dong Hu^3,*, Romany Fouad Mansour⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2079-2095, 2022, DOI:10.32604/cmc.2022.027794
Abstract With the rapid development of the fresh cold chain logistics distribution and the prevalence of low carbon concept, this paper proposed an optimization model of low carbon fresh cold chain logistics distribution route considering customer satisfaction, and combined with time, space, weight, distribution rules and other constraints to optimize the distribution model. At the same time, transportation cost, penalty cost, overloading cost, carbon tax cost and customer satisfaction were considered as the components of the objective function, and the thought of cost efficiency was taken into account, so as to establish a distribution model based on the ratio of minimum… More >

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954

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K. A. Fasila^*, Sheena Mathew
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2097-2114, 2022, DOI:10.32604/cmc.2022.029637
Abstract

Internet of Things (IoT) has become widely used nowadays and tremendous increase in the number of users raises its security requirements as well. The constraints on resources such as low computational capabilities and power requirements demand lightweight cryptosystems. Conventional algorithms are not applicable in IoT network communications because of the constraints mentioned above. In this work, a novel and efficient scheme for providing security in IoT applications is introduced. The scheme proposes how security can be enhanced in a distributed IoT application by providing multilevel protection and dynamic key generation in the data uploading and transfer phases. Existing works rely… More >

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Mohammad Saraireh^1,*, A. M. Maqableh², Manar Jaradat³, Omar A. Saraereh⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2115-2133, 2022, DOI:10.32604/cmc.2022.029978
Abstract The growing need for renewable energy and zero carbon dioxide emissions has fueled the development of thermoelectric generators with improved power generating capability. Along with the endeavor to develop thermoelectric materials with greater figures of merit, the geometrical and structural optimization of thermoelectric generators is equally critical for maximum power output and efficiency. Green energy strategies that are constantly updated are a viable option for addressing the global energy issue while also protecting the environment. There have been significant focuses on the development of thermoelectric modules for a range of solar, automotive, military, and aerospace applications in recent years due… More >

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Muhammad I. Masud^1,2,*, Nasir Shaikh-Husin², Iqbal A. Khan¹, Abu K. Bin A’Ain²
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2135-2149, 2022, DOI:10.32604/cmc.2022.026831
Abstract A new carbon nanotube field effect transistor (CNTFET) based grounded active inductor (GAI) circuit is presented in this work. The suggested GAI offers a tunable inductance with a very wide inductive bandwidth, high quality factor (QF) and low power dissipation. The tunability of the realized circuit is achieved through CNTFET based varactor. The proposed topology shows inductive behavior in the frequency range of 0.1–101 GHz and achieves to a maximum QF of 9125. The GAI operates at 0.7 V with 0.337 mW of power consumption. To demonstrate the performance of GAI, a broadband low noise amplifier (LNA) circuit is designed by utilizing… More >

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Lina Wang^1,2,*, Xilin Deng¹, Peng Ge¹, Changming Dong^2,3, Brandon J. Bethel³, Leqing Yang¹, Jinyue Xia⁴
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2151-2168, 2022, DOI:10.32604/cmc.2022.027415
Abstract Though numerical wave models have been applied widely to significant wave height prediction, they consume massive computing memory and their accuracy needs to be further improved. In this paper, a two-dimensional (2D) significant wave height (SWH) prediction model is established for the South and East China Seas. The proposed model is trained by Wave Watch III (WW3) reanalysis data based on a convolutional neural network, the bi-directional long short-term memory and the attention mechanism (CNN-BiLSTM-Attention). It adopts the convolutional neural network to extract spatial features of original wave height to reduce the redundant information input into the BiLSTM network. Meanwhile,… More >

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Anas Al-Ragehi¹, Said Jadid Abdulkadir^1,2,*, Amgad Muneer^1,2, Safwan Sadeq³, Qasem Al-Tashi^4,5
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2169-2186, 2022, DOI:10.32604/cmc.2022.027885
Abstract Generative Adversarial Networks (GANs) are neural networks that allow models to learn deep representations without requiring a large amount of training data. Semi-Supervised GAN Classifiers are a recent innovation in GANs, where GANs are used to classify generated images into real and fake and multiple classes, similar to a general multi-class classifier. However, GANs have a sophisticated design that can be challenging to train. This is because obtaining the proper set of parameters for all models-generator, discriminator, and classifier is complex. As a result, training a single GAN model for different datasets may not produce satisfactory results. Therefore, this study… More >

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Fauzi A. Bala^1,2,*, Osman N. Ucan¹, Oguz Bayat¹
CMC-Computers, Materials & Continua, Vol.73, No.1, pp. 2187-2204, 2022, DOI:10.32604/cmc.2022.024205
Abstract Designing an authentication system for securing the power plants are important to allow only specific staffs of the power plant to access the certain blocks so that they can be restricted from using high risk-oriented equipment. This authentication is also vital to prevent any security threats or risks like compromises of business server, release of confidential data etc. Though conventional works attempted to accomplish better authentication, they lacked with respect to accuracy. Hence, the study aims to enhance the recognition rate by introducing a voice recognition system as a personal authentication based on Deep Learning (DL) due to its ability… More >

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