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Sengul Bayrak^1,2,*, Eylem Yucel², Hidayet Takci³, Ruya Samli²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1427-1446, 2021, DOI:10.32604/cmc.2021.015524 - 21 July 2021
（This article belongs to the Special Issue: Intelligent Decision Support Systems for Complex Healthcare Applications)
Abstract Today, electroencephalography is used to measure brain activity by creating signals that are viewed on a monitor. These signals are frequently used to obtain information about brain neurons and may detect disorders that affect the brain, such as epilepsy. Electroencephalogram (EEG) signals are however prone to artefacts. These artefacts must be removed to obtain accurate and meaningful signals. Currently, computer-aided systems have been used for this purpose. These systems provide high computing power, problem-specific development, and other advantages. In this study, a new clinical decision support system was developed for individuals to detect epileptic seizures… More >

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2193

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Sundresan Perumal¹, Mujahid Tabassum¹, Ganthan Narayana², Suresh Ponnan^3,*, Chinmay Chakraborty⁴, Saju Mohanan⁵, Zeeshan Basit⁵, Mohammad Tabrez Quasim⁶
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1447-1462, 2021, DOI:10.32604/cmc.2021.014854 - 21 July 2021
（This article belongs to the Special Issue: Machine Learning for Data Analytics)
Abstract A wireless sensor network (WSN) consists of several tiny sensor nodes to monitor, collect, and transmit the physical information from an environment through the wireless channel. The node failure is considered as one of the main issues in the WSN which creates higher packet drop, delay, and energy consumption during the communication. Although the node failure occurred mostly due to persistent energy exhaustion during transmission of data packets. In this paper, Artificial Neural Network (ANN) based Node Failure Detection (NFD) is developed with cognitive radio for detecting the location of the node failure. The ad hoc… More >

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Hussein Abdel-Mawgoud¹, Salah Kamel¹, Hegazy Rezk^2,3, Tahir Khurshaid⁴, Sang-Bong Rhee^4,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1463-1481, 2021, DOI:10.32604/cmc.2021.017995 - 21 July 2021
Abstract Recently, implementation of Battery Energy Storage (BES) with photovoltaic (PV) array in distribution networks is becoming very popular in overall the world. Integrating PV alone in distribution networks generates variable output power during 24-hours as it depends on variable natural source. PV can be able to generate constant output power during 24-hours by installing BES with it. Therefore, this paper presents a new application of a recent metaheuristic algorithm, called Slime Mould Algorithm (SMA), to determine the best size, and location of photovoltaic alone or with battery energy storage in the radial distribution system (RDS).… More >

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1591

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Mohamed Eb-Saad¹, Yunyoung Nam^2,*, Hazem M. El-bakry¹, Samir Abdelrazek¹
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1483-1501, 2021, DOI:10.32604/cmc.2021.017783 - 21 July 2021
（This article belongs to the Special Issue: Blockchain Driven Secure Cyber-Physical Systems)
Abstract Web service (WS) presents a good solution to the interoperability of different types of systems that aims to reduce the overhead of high processing in a resource-limited environment. With the increasing demand for mobile WS (MWS), the WS discovery process has become a significant challenging point in the WS lifecycle that aims to identify the relevant MWSs that best match the service requests. This discovery process is a resource-consuming task that cannot be performed efficiently in a mobile computing environment due to the limitations of mobile devices. Meanwhile, a cloud computing can provide rich computing… More >

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Dengyong Zhang^1,2, Jiawei Hu^1,2, Feng Li^1,2,*, Xiangling Ding³, Arun Kumar Sangaiah⁴, Victor S. Sheng⁵
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1503-1517, 2021, DOI:10.32604/cmc.2021.017089 - 21 July 2021
Abstract In the past several years, remarkable achievements have been made in the field of object detection. Although performance is generally improving, the accuracy of small object detection remains low compared with that of large object detection. In addition, localization misalignment issues are common for small objects, as seen in GoogLeNets and residual networks (ResNets). To address this problem, we propose an improved region-based fully convolutional network (R-FCN). The presented technique improves detection accuracy and eliminates localization misalignment by replacing position-sensitive region of interest (PS-RoI) pooling with position-sensitive precise region of interest (PS-Pr-RoI) pooling, which avoids More >

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Fahd N. Al-Wesabi^1,2,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1519-1536, 2021, DOI:10.32604/cmc.2021.018202 - 21 July 2021
Abstract In this paper, the text analysis-based approach RTADZWA (Reliable Text Analysis and Digital Zero-Watermarking Approach) has been proposed for transferring and receiving authentic English text via the internet. Second level order of alphanumeric mechanism of hidden Markov model has been used in RTADZWA approach as a natural language processing to analyze the English text and extracts the features of the interrelationship between contexts of the text and utilizes the extracted features as watermark information and then validates it later with attacked English text to detect any tampering occurred on it. Text analysis and text zero-watermarking… More >

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2066

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1441

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Aswathy K. Cherian^*, E. Poovammal
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1537-1552, 2021, DOI:10.32604/cmc.2021.018213 - 21 July 2021
（This article belongs to the Special Issue: Computational Models for Pro-Smart Environments in Data Science Assisted IoT Systems)
Abstract Obtaining clear images of underwater scenes with descriptive details is an arduous task. Conventional imaging techniques fail to provide clear cut features and attributes that ultimately result in object recognition errors. Consequently, a need for a system that produces clear images for underwater image study has been necessitated. To overcome problems in resolution and to make better use of the Super-Resolution (SR) method, this paper introduces a novel method that has been derived from the Alpha Generative Adversarial Network (AlphaGAN) model, named Alpha Super Resolution Generative Adversarial Network (AlphaSRGAN). The model put forth in this… More >

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1632

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Mohanad Al-Ghobari¹, Amgad Muneer^2,*, Suliman Mohamed Fati³
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1553-1570, 2021, DOI:10.32604/cmc.2021.016348 - 21 July 2021
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract Many tourists who travel to explore different cultures and cities worldwide aim to find the best tourist sites, accommodation, and food according to their interests. This objective makes it harder for tourists to decide and plan where to go and what to do. Aside from hiring a local guide, an option which is beyond most travelers’ budgets, the majority of sojourners nowadays use mobile devices to search for or recommend interesting sites on the basis of user reviews. Therefore, this work utilizes the prevalent recommender systems and mobile app technologies to overcome this issue. Accordingly,… More >

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Naglaa F. Soliman^1,2, Abeer D. Algarni^1,*, Walid El-Shafai³, Fathi E. Abd El-Samie^1,3, Ghada M. El Banby⁴
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1571-1595, 2021, DOI:10.32604/cmc.2021.016980 - 21 July 2021
Abstract Cancelable biometrics are required in most remote access applications that need an authentication stage such as the cloud and Internet of Things (IoT) networks. The objective of using cancelable biometrics is to save the original ones from hacking attempts. A generalized algorithm to generate cancelable templates that is applicable on both single and multiple biometrics is proposed in this paper to be considered for cloud and IoT applications. The original biometric is blurred with two co-prime operators. Hence, it can be recovered as the Greatest Common Divisor (GCD) between its two blurred versions. Minimal changes… More >

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Liangbo Xie¹, Yan Ren¹, Mu Zhou¹, Xiaolong Yang^1,*, Zhengwen Huang²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1597-1609, 2021, DOI:10.32604/cmc.2021.018502 - 21 July 2021
Abstract This paper presents an energy efficient successive-approximation register (SAR) analog-to-digital converter (ADC) for low-power applications. To improve the overall energy-efficiency, a skipping-window technique is used to bypass corresponding conversion steps when the input falls in a window indicated by a time-domain comparator, which can provide not only the polarity of the input, but also the amount information of the input. The time-domain comparator, which is based on the edge pursing principle, consists of delay cells, two NAND gates, two D-flip-flop register-based phase detectors and a counter. The digital characteristic of the comparator makes the design… More >

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1500

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Jaegwang Lee, Jongsuk R. Lee, Sunil Ahn^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1611-1629, 2021, DOI:10.32604/cmc.2021.016803 - 21 July 2021
（This article belongs to the Special Issue: Deep Learning Trends in Intelligent Systems)
Abstract With the increase in research on AI (Artificial Intelligence), the importance of DL (Deep Learning) in various fields, such as materials, biotechnology, genomes, and new drugs, is increasing significantly, thereby increasing the number of deep-learning framework users. However, to design a deep neural network, a considerable understanding of the framework is required. To solve this problem, a GUI (Graphical User Interface)-based DNN (Deep Neural Network) design tool is being actively researched and developed. The GUI-based DNN design tool can design DNNs quickly and easily. However, the existing GUI-based DNN design tool has certain limitations such… More >

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1648

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Muhammad Waleed Pasha¹, Mir Yasir Umair¹, Alina Mirza^1,*, Faizan Rao¹, Abdul Wakeel¹, Safia Akram¹, Fazli Subhan², Wazir Zada Khan³
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1631-1652, 2021, DOI:10.32604/cmc.2021.018205 - 21 July 2021
（This article belongs to the Special Issue: Reinforcement Learning Based solutions for Next-Generation Wireless Networks Coexistence)
Abstract Due to the inability of the Global Positioning System (GPS) signals to penetrate through surfaces like roofs, walls, and other objects in indoor environments, numerous alternative methods for user positioning have been presented. Amongst those, the Wi-Fi fingerprinting method has gained considerable interest in Indoor Positioning Systems (IPS) as the need for line-of-sight measurements is minimal, and it achieves better efficiency in even complex indoor environments. Offline and online are the two phases of the fingerprinting method. Many researchers have highlighted the problems in the offline phase as it deals with huge datasets and validation… More >

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2201

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Keshav Thapa, Zubaer Md. Abdhulla AI, Yang Sung-Hyun^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1653-1670, 2021, DOI:10.32604/cmc.2021.015660 - 21 July 2021
Abstract In this era, deep learning methods offer a broad spectrum of efficient and original algorithms to recognize or predict an output when given a sequence of inputs. In current trends, deep learning methods using recent long short-term memory (LSTM) algorithms try to provide superior performance, but they still have limited effectiveness when detecting sequences of complex human activity. In this work, we adapted the LSTM algorithm into a synchronous algorithm (sync-LSTM), enabling the model to take multiple parallel input sequences to produce multiple parallel synchronized output sequences. The proposed method is implemented for simultaneous human… More >

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1524

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Bin Xu^1,2,3, Lu Zhang¹, Zipeng Xu¹, Yichuan Liu¹, Jinming Chai¹, Sichong Qin⁴, Yanfei Sun^1,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1671-1686, 2021, DOI:10.32604/cmc.2021.018395 - 21 July 2021
Abstract In the IoT (Internet of Things) system, the introduction of UAV (Unmanned Aerial Vehicle) as a new data collection platform can solve the problem that IoT devices are unable to transmit data over long distances due to the limitation of their battery energy. However, the unreasonable distribution of UAVs will still lead to the problem of the high total energy consumption of the system. In this work, to deal with the problem, a deployment model of a mobile edge computing (MEC) system based on multi-UAV is proposed. The goal of the model is to minimize… More >

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Farhan Amin¹, Jin-Ghoo Choi², Gyu Sang Choi^2,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1687-1707, 2021, DOI:10.32604/cmc.2021.017870 - 21 July 2021
（This article belongs to the Special Issue: Big Data Analytics and Artificial Intelligence Techniques for Complex Systems)
Abstract Community detection in social networks is a hard problem because of the size, and the need of a deep understanding of network structure and functions. While several methods with significant effort in this direction have been devised, an outstanding open problem is the unknown number of communities, it is generally believed that the role of influential nodes that are surrounded by neighbors is very important. In addition, the similarity among nodes inside the same cluster is greater than among nodes from other clusters. Lately, the global and local methods of community detection have been getting… More >

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Rohit Samkria¹, Mohammed Abd-Elnaby², Rajesh Singh³, Anita Gehlot³, Mamoon Rashid^4,*, Moustafa H. Aly⁵, Walid El-Shafai⁶
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1709-1723, 2021, DOI:10.32604/cmc.2021.018525 - 21 July 2021
（This article belongs to the Special Issue: Big Data Analytics and Artificial Intelligence Techniques for Complex Systems)
Abstract Fault detection of the photovoltaic (PV) grid is necessary to detect serious output power reduction to avoid PV modules’ damage. To identify the fault of the PV arrays, there is a necessity to implement an automatic system. In this IoT and LabVIEW-based automatic fault detection of 3 × 3 solar array, a PV system is proposed to control and monitor Internet connectivity remotely. Hardware component to automatically reconfigure the solar PV array from the series-parallel (SP) to the complete cross-linked array underneath partial shading conditions (PSC) is centered on the Atmega328 system to achieve maximum… More >

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Ajmal Khan¹, Mubashir Mukhtar¹, Farman Ullah¹, Muhammad Bilal², Kyung-Sup Kwak^3,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1725-1746, 2021, DOI:10.32604/cmc.2021.017952 - 21 July 2021
（This article belongs to the Special Issue: Green IoT Networks using Machine Learning, Deep Learning Models)
Abstract In post disaster scenarios such as war zones floods and earthquakes, the cellular communication infrastructure can be lost or severely damaged. In such emergency situations, remaining in contact with other rescue response teams in order to provide inputs for both headquarters and disaster survivors becomes very necessary. Therefore, in this research work, a design, implementation and evaluation of energy aware rapidly deployable system named EA-RDSP is proposed. The proposed research work assists the early rescue workers and victims to transmit their location information towards the remotely located servers. In EA-RDSP, two algorithms are proposed i.e.,… More >

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Yong-Woon Hwang, Im-Yeong Lee^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1747-1764, 2021, DOI:10.32604/cmc.2021.018549 - 21 July 2021
Abstract Recently, with the advancement of Information and Communications Technology (ICT), Internet of Things (IoT) has been connected to the cloud and used in industrial sectors, medical environments, and smart grids. However, if data is transmitted in plain text when collecting data in an IoT-cloud environment, it can be exposed to various security threats such as replay attacks and data forgery. Thus, digital signatures are required. Data integrity is ensured when a user (or a device) transmits data using a signature. In addition, the concept of data aggregation is important to efficiently collect data transmitted from… More >

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1360

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Lina Wang^1,2,*, Qixiang Zhang¹, Xiling Niu¹, Yongjun Ren³, Jinyue Xia⁴
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1765-1781, 2021, DOI:10.32604/cmc.2021.017516 - 21 July 2021
Abstract Outlier detection is a key research area in data mining technologies, as outlier detection can identify data inconsistent within a data set. Outlier detection aims to find an abnormal data size from a large data size and has been applied in many fields including fraud detection, network intrusion detection, disaster prediction, medical diagnosis, public security, and image processing. While outlier detection has been widely applied in real systems, its effectiveness is challenged by higher dimensions and redundant data attributes, leading to detection errors and complicated calculations. The prevalence of mixed data is a current issue… More >

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Abdullah Muhammad, Salwani Abdullah, Nor Samsiah Sani^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1783-1799, 2021, DOI:10.32604/cmc.2021.018593 - 21 July 2021
Abstract Feature selection and sentiment analysis are two common studies that are currently being conducted; consistent with the advancements in computing and growing the use of social media. High dimensional or large feature sets is a key issue in sentiment analysis as it can decrease the accuracy of sentiment classification and make it difficult to obtain the optimal subset of the features. Furthermore, most reviews from social media carry a lot of noise and irrelevant information. Therefore, this study proposes a new text-feature selection method that uses a combination of rough set theory (RST) and teaching-learning… More >

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Nahida Islam¹, Fahiba Farhin¹, Ishrat Sultana¹, M. Shamim Kaiser¹, Md. Sazzadur Rahman¹, Mufti Mahmud², A. S. M. Sanwar Hosen³, Gi Hwan Cho^3,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1801-1821, 2021, DOI:10.32604/cmc.2021.018466 - 21 July 2021
（This article belongs to the Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract The Internet of Things (IoT) integrates billions of self-organized and heterogeneous smart nodes that communicate with each other without human intervention. In recent years, IoT based systems have been used in improving the experience in many applications including healthcare, agriculture, supply chain, education, transportation and traffic monitoring, utility services etc. However, node heterogeneity raised security concern which is one of the most complicated issues on the IoT. Implementing security measures, including encryption, access control, and authentication for the IoT devices are ineffective in achieving security. In this paper, we identified various types of IoT threats… More >

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Merna Gamal¹, Hala M. Abbas², Nour Moustafa^3,*, Elena Sitnikova³, Rowayda A. Sadek¹
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1823-1837, 2021, DOI:10.32604/cmc.2021.012877 - 21 July 2021
（This article belongs to the Special Issue: Security and Computing in Internet of Things)
Abstract Intrusion Detection Systems (IDSs) have a great interest these days to discover complex attack events and protect the critical infrastructures of the Internet of Things (IoT) networks. Existing IDSs based on shallow and deep network architectures demand high computational resources and high volumes of data to establish an adaptive detection engine that discovers new families of attacks from the edge of IoT networks. However, attackers exploit network gateways at the edge using new attacking scenarios (i.e., zero-day attacks), such as ransomware and Distributed Denial of Service (DDoS) attacks. This paper proposes new IDS based on… More >

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Jinxing Niu^1,*, Yayun Fu¹, Qingsheng Hu¹, Shaojie Yang¹, Tao Zhang¹, Sunil Kumar Jha²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1839-1849, 2021, DOI:10.32604/cmc.2021.017797 - 21 July 2021
Abstract The binocular stereo vision system is often used to reconstruct 3D point clouds of an object. However, it is challenging to find effective matching points in two object images with similar color or less texture. This will lead to mismatching by using the stereo matching algorithm to calculate the disparity map. In this context, the object can’t be reconstructed precisely. As a countermeasure, this study proposes to combine the Gray code fringe projection with the binocular camera as well as to generate denser point clouds by projecting an active light source to increase the texture… More >

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Buddhadeva Sahoo^1,*, Sangram Keshari Routray², Pravat Kumar Rout², Mohammed M. Alhaider³
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1851-1875, 2021, DOI:10.32604/cmc.2021.018535 - 21 July 2021
Abstract This paper suggests a combined novel control strategy for DFIG based wind power systems (WPS) under both nonlinear and unbalanced load conditions. The combined control approach is designed by coordinating the machine side converter (MSC) and the load side converter (LSC) control approaches. The proposed MSC control approach is designed by using a model predictive control (MPC) approach to generate appropriate real and reactive power. The MSC controller selects an appropriate rotor voltage vector by using a minimized optimization cost function for the converter operation. It shows its superiority by eliminating the requirement of transformation,… More >

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Guimin Hou¹, Jiaohua Qin^1,*, Xuyu Xiang¹, Yun Tan¹, Neal N. Xiong²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1877-1891, 2021, DOI:10.32604/cmc.2021.017481 - 21 July 2021
Abstract Medical image segmentation is an important application field of computer vision in medical image processing. Due to the close location and high similarity of different organs in medical images, the current segmentation algorithms have problems with mis-segmentation and poor edge segmentation. To address these challenges, we propose a medical image segmentation network (AF-Net) based on attention mechanism and feature fusion, which can effectively capture global information while focusing the network on the object area. In this approach, we add dual attention blocks (DA-block) to the backbone network, which comprises parallel channels and spatial attention branches, More >

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Prince Waqas Khan, Yung-Cheol Byun^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1893-1913, 2021, DOI:10.32604/cmc.2021.018523 - 21 July 2021
（This article belongs to the Special Issue: Emerging Trends in Artificial Intelligence and Machine Learning)
Abstract Despite the advancement within the last decades in the field of smart grids, energy consumption forecasting utilizing the metrological features is still challenging. This paper proposes a genetic algorithm-based adaptive error curve learning ensemble (GA-ECLE) model. The proposed technique copes with the stochastic variations of improving energy consumption forecasting using a machine learning-based ensembled approach. A modified ensemble model based on a utilizing error of model as a feature is used to improve the forecast accuracy. This approach combines three models, namely CatBoost (CB), Gradient Boost (GB), and Multilayer Perceptron (MLP). The ensembled CB-GB-MLP model’s… More >

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Omar Almutiry¹, Muhammad Ayaz², Tariq Sadad³, Ikram Ullah Lali⁴, Awais Mahmood^1,*, Najam Ul Hassan⁵, Habib Dhahri¹
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1915-1926, 2021, DOI:10.32604/cmc.2021.017702 - 21 July 2021
（This article belongs to the Special Issue: Artificial Intelligence based Smart precision agriculture with analytic pattern in sustainable environments using IoT)
Abstract Guava is one of the most important fruits in Pakistan, and is gradually boosting the economy of Pakistan. Guava production can be interrupted due to different diseases, such as anthracnose, algal spot, fruit fly, styler end rot and canker. These diseases are usually detected and identified by visual observation, thus automatic detection is required to assist formers. In this research, a new technique was created to detect guava plant diseases using image processing techniques and computer vision. An automated system is developed to support farmers to identify major diseases in guava. We collected healthy and… More >

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Marriam Nawaz¹, Zahid Mehmood^2,*, Tahira Nazir¹, Momina Masood¹, Usman Tariq³, Asmaa Mahdi Munshi⁴, Awais Mehmood¹, Muhammad Rashid⁵
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1927-1944, 2021, DOI:10.32604/cmc.2021.018052 - 21 July 2021
Abstract Copy-move forgery is the most common type of digital image manipulation, in which the content from the same image is used to forge it. Such manipulations are performed to hide the desired information. Therefore, forgery detection methods are required to identify forged areas. We have introduced a novel method for features computation by employing a circular block-based method through local tetra pattern (LTrP) features to detect the single and multiple copy-move attacks from the images. The proposed method is applied over the circular blocks to efficiently and effectively deal with the post-processing operations. It also… More >

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Simon Crase^1,2, Benjamin Hall², Suresh N. Thennadil^3,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1945-1965, 2021, DOI:10.32604/cmc.2021.018517 - 21 July 2021
Abstract Supervised machine learning techniques have become well established in the study of spectroscopy data. However, the unsupervised learning technique of cluster analysis hasn’t reached the same level maturity in chemometric analysis. This paper surveys recent studies which apply cluster analysis to NIR and IR spectroscopy data. In addition, we summarize the current practices in cluster analysis of spectroscopy and contrast these with cluster analysis literature from the machine learning and pattern recognition domain. This includes practices in data pre-processing, feature extraction, clustering distance metrics, clustering algorithms and validation techniques. Special consideration is given to the More >

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Nidhi Kalra^1,*, Raman Kumar Goyal¹, Anshu Parashar¹, Jaskirat Singh¹, Gagan Singla²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1967-1978, 2021, DOI:10.32604/cmc.2021.018732 - 21 July 2021
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract Every 24 seconds, someone dies on the road due to road accidents and it is the 8th leading cause of death and the first among children aged 15–29 years. 1.35 million people globally die every year due to road traffic crashes. An additional 20–50 million suffer from non-fatal injuries, often resulting in long-term disabilities. This costs around 3% of Gross Domestic Product to most countries, and it is a considerable economic loss. The governments have taken various measures such as better road infrastructures and strict enforcement of motor-vehicle laws to reduce these accidents. However, there… More >

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Fahd N. Al-Wesabi^1,2,*, Murad A. A. Almekhlafi³, Huda G. Iskandar^2,4, Adnan Zain⁵, Saleh Alzahrani⁶, Mohammed Alamgeer⁶, Nadhem Nemri⁶, Sami Dhabi⁶, Mohammad Medani⁶, Ali. M. Al-Sharafi^2,7
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1979-1994, 2021, DOI:10.32604/cmc.2021.018390 - 21 July 2021
Abstract In recent years, there has been an increasing demand to improve cellular communication services in several aspects. The aspect that received the most attention is improving the quality of coverage through using smart antennas which consist of array antennas. this paper investigates the main characteristics and design of the three types of array antennas of the base station for better coverage through simulation (MATLAB) which provides field and strength patterns measured in polar and rectangular coordinates for a variety of conditions including broadsides, ordinary End-fire, and increasing directivity End-fire which is typically used in smart More >

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Fahd N. Al-Wesabi^1,2,*, Murad A. Almekhlafi³, Mohammed Abdullah Al-Hagery⁴, Mohammad Alamgeer⁵, Khalid Mahmood⁵, Majdy M. Eltahir⁵, Ali M. Al-Sharafi^2,6, Amin M. El-Kustaban⁷
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 1995-2011, 2021, DOI:10.32604/cmc.2021.018644 - 21 July 2021
Abstract Renewable energy is one of the essential elements of the social and economic development in any civilized country. The use of fossil fuels and the non-renewable form of energy has many adverse effects on the most of ecosystems. Given the high potential of renewable energy sources in Yemen and the absence of similar studies in the region, this study aimed to examine the wind energy potential of Hodeidah-Yemen Republic by analyzing wind characteristics and assessment, determining the available power density, and calculate the wind energy extracted at different heights. The average wind speed of Hodeidah… More >

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C. Rajinikanth¹, P. Selvaraj², Mohamed Yacin Sikkandar³, T. Jayasankar⁴, Seifedine Kadry⁵, Yunyoung Nam^6,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2013-2029, 2021, DOI:10.32604/cmc.2021.018719 - 21 July 2021
Abstract Internet of Things (IoT) has become a major technological development which offers smart infrastructure for the cloud-edge services by the interconnection of physical devices and virtual things among mobile applications and embedded devices. The e-healthcare application solely depends on the IoT and cloud computing environment, has provided several characteristics and applications. Prior research works reported that the energy consumption for transmission process is significantly higher compared to sensing and processing, which led to quick exhaustion of energy. In this view, this paper introduces a new energy efficient cluster enabled clinical decision support system (EEC-CDSS) for… More >

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K. Muthumayil¹, S. Manikandan², S. Srinivasan³, José Escorcia-Gutierrez^4,*, Margarita Gamarra⁵, Romany F. Mansour⁶
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2031-2044, 2021, DOI:10.32604/cmc.2021.017116 - 21 July 2021
Abstract White Blood Cell (WBC) cancer or leukemia is one of the serious cancers that threaten the existence of human beings. In spite of its prevalence and serious consequences, it is mostly diagnosed through manual practices. The risks of inappropriate, sub-standard and wrong or biased diagnosis are high in manual methods. So, there is a need exists for automatic diagnosis and classification method that can replace the manual process. Leukemia is mainly classified into acute and chronic types. The current research work proposed a computer-based application to classify the disease. In the feature extraction stage, we… More >

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1514

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Fang Liu^1,*, Zhenyuan Zhang², Zunfu Wang¹, Yuting Xing³
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2045-2060, 2021, DOI:10.32604/cmc.2021.018303 - 21 July 2021
Abstract Due to the explosion of network data traffic and IoT devices, edge servers are overloaded and slow to respond to the massive volume of online requests. A large number of studies have shown that edge caching can solve this problem effectively. This paper proposes a distributed edge collaborative caching mechanism for Internet online request services scenario. It solves the problem of large average access delay caused by unbalanced load of edge servers, meets users’ differentiated service demands and improves user experience. In particular, the edge cache node selection algorithm is optimized, and a novel edge More >

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K. K. Thyagharajan, I. Kiruba Raji^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2061-2076, 2021, DOI:10.32604/cmc.2021.017591 - 21 July 2021
Abstract This paper proposes an approach to detecting diseases in neem leaf that uses a Fuzzy-Higher Order Biologically Inspired Neuron Model (F-HOBINM) and adaptive neuro classifier (ANFIS). India exports USD 0.28-million worth of neem leaf to the UK, USA, UAE, and Europe in the form of dried leaves and powder, both of which help reduce diabetes-related issues, cardiovascular problems, and eye disorders. Diagnosing neem leaf disease is difficult through visual interpretation, owing to similarity in their color and texture patterns. The most common diseases include bacterial blight, Colletotrichum and Alternaria leaf spot, blight, damping-off, powdery mildew,… More >

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Mohamed Ezz^1,2,*, Murtada K. Elbashir^1,3, Hosameldeen Shabana^4,5
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2077-2092, 2021, DOI:10.32604/cmc.2021.018155 - 21 July 2021
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract It is important to determine early on which patients require ICU admissions in managing COVID-19 especially when medical resources are limited. Delay in ICU admissions is associated with negative outcomes such as mortality and cost. Therefore, early identification of patients with a high risk of respiratory failure can prevent complications, enhance risk stratification, and improve the outcomes of severely-ill hospitalized patients. In this paper, we develop a model that uses the characteristics and information collected at the time of patients’ admissions and during their early period of hospitalization to accurately predict whether they will need… More >

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Simy Mary Kurian¹, Sujitha Juliet Devaraj^1,*, Vinodh P. Vijayan²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2093-2109, 2021, DOI:10.32604/cmc.2021.018090 - 21 July 2021
（This article belongs to the Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract Magnetic resonance imaging (MRI) is an essential tool for detecting brain tumours. However, identification of brain tumours in the early stages is a very complex task since MRI images are susceptible to noise and other environmental obstructions. In order to overcome these problems, a Gamma MAP denoised Strömberg wavelet segmentation based on a maximum entropy classifier (GMDSWS-MEC) model is developed for efficient tumour detection with high accuracy and low time consumption. The GMDSWS-MEC model performs three steps, namely pre-processing, segmentation, and classification. Within the GMDSWS-MEC model, the Gamma MAP filter performs the pre-processing task and… More >

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Juan Huang¹, Bifang Zhou¹, Huajun Huang^2,*, Jianjiang Liu¹, Neal N. Xiong³
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2111-2121, 2021, DOI:10.32604/cmc.2021.016770 - 21 July 2021
Abstract To overcome the deficiency of traditional mathematical statistics methods, an adaptive Lasso grey model algorithm for regional FDI (foreign direct investment) prediction is proposed in this paper, and its validity is analyzed. Firstly, the characteristics of the FDI data in six provinces of Central China are generalized, and the mixture model's constituent variables of the Lasso grey problem as well as the grey model are defined. Next, based on the influencing factors of regional FDI statistics (mean values of regional FDI and median values of regional FDI), an adaptive Lasso grey model algorithm for regional… More >

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1276

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Zakir Ullah¹, Asif Umer¹, Mahdi Zaree², Jamil Ahmad¹, Faisal Alanazi^3,*, Noor Ul Amin¹, Arif Iqbal Umar¹, Ali Imran Jehangiri¹, Muhammad Adnan¹
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2123-2140, 2021, DOI:10.32604/cmc.2021.015445 - 21 July 2021
Abstract Cloud computing is a demanding business platform for services related to the field of IT. The goal of cloud customers is to access resources at a sustainable price, while the goal of cloud suppliers is to maximize their services utilization. Previously, the customers would bid for every single resource type, which was a limitation of cloud resources allocation. To solve these issues, researchers have focused on a combinatorial auction in which the resources are offered by the providers in bundles so that the user bids for their required bundle. Still, in this allocation mechanism, some… More >

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1353

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Anhao Xiang, Jun Zheng^*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2141-2158, 2021, DOI:10.32604/cmc.2021.018808 - 21 July 2021
Abstract Distribution feeder microgrid (DFM) built based on existing distributed feeder (DF), is a promising solution for modern microgrid. DFM contains a large number of heterogeneous devices that generate heavy network traffice and require a low data delivery latency. The information-centric networking (ICN) paradigm has shown a great potential to address the communication requirements of smart grid. However, the integration of advanced information and communication technologies with DFM make it vulnerable to cyber attacks. Adequate authentication of grid devices is essential for preventing unauthorized accesses to the grid network and defending against cyber attacks. In this… More >

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1440

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Raja Jarray¹, Mujahed Al-Dhaifallah^2,*, Hegazy Rezk^3,4, Soufiene Bouallègue^1,5
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2159-2180, 2021, DOI:10.32604/cmc.2021.018752 - 21 July 2021
Abstract Paths planning of Unmanned Aerial Vehicles (UAVs) in a dynamic environment is considered a challenging task in autonomous flight control design. In this work, an efficient method based on a Multi-Objective Multi-Verse Optimization (MOMVO) algorithm is proposed and successfully applied to solve the path planning problem of quadrotors with moving obstacles. Such a path planning task is formulated as a multicriteria optimization problem under operational constraints. The proposed MOMVO-based planning approach aims to lead the drone to traverse the shortest path from the starting point and the target without collision with moving obstacles. The vehicle… More >

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1649

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Marwan Albahar^*, Mohammed Thanoon, Monaj Alzilai, Alaa Alrehily, Munirah Alfaar, Maimoona Algamdi, Norah Alassaf
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2181-2202, 2021, DOI:10.32604/cmc.2021.018260 - 21 July 2021
Abstract Malicious Portable Document Format (PDF) files represent one of the largest threats in the computer security space. Significant research has been done using handwritten signatures and machine learning based on detection via manual feature extraction. These approaches are time consuming, require substantial prior knowledge, and the list of features must be updated with each newly discovered vulnerability individually. In this study, we propose two models for PDF malware detection. The first model is a convolutional neural network (CNN) integrated into a standard deviation based regularization model to detect malicious PDF documents. The second model is a More >

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1646

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Yang Wang¹, Ying Tian^1,*, Ou Tian²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2203-2216, 2021, DOI:10.32604/cmc.2021.018709 - 21 July 2021
Abstract As the use of facial attributes continues to expand, research into facial age estimation is also developing. Because face images are easily affected by factors including illumination and occlusion, the age estimation of faces is a challenging process. This paper proposes a face age estimation algorithm based on lightweight convolutional neural network in view of the complexity of the environment and the limitations of device computing ability. Improving face age estimation based on Soft Stagewise Regression Network (SSR-Net) and facial images, this paper employs the Center Symmetric Local Binary Pattern (CSLBP) method to obtain the More >

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Muzamil Ahmed^1,2, Muhammad Ramzan^3,4, Hikmat Ullah Khan², Saqib Iqbal⁵, Muhammad Attique Khan⁶, Jung-In Choi⁷, Yunyoung Nam^8,*, Seifedine Kadry⁹
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2217-2230, 2021, DOI:10.32604/cmc.2021.018103 - 21 July 2021
（This article belongs to the Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract Violence recognition is crucial because of its applications in activities related to security and law enforcement. Existing semi-automated systems have issues such as tedious manual surveillances, which causes human errors and makes these systems less effective. Several approaches have been proposed using trajectory-based, non-object-centric, and deep-learning-based methods. Previous studies have shown that deep learning techniques attain higher accuracy and lower error rates than those of other methods. However, the their performance must be improved. This study explores the state-of-the-art deep learning architecture of convolutional neural networks (CNNs) and inception V4 to detect and recognize violence… More >

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Faisal Mehmood¹, Shabir Ahmad^2,3, Israr Ullah¹, Faisal Jamil¹, DoHyeun Kim^1,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2231-2244, 2021, DOI:10.32604/cmc.2021.017528 - 21 July 2021
（This article belongs to the Special Issue: Intelligent Software-defined Networking (SDN) Technologies for Future Generation Networks)
Abstract The data being generated by the Internet of Things needs to be stored, monitored, and analyzed for maximum IoT resource utilization. Software Defined Networking has been extensively utilized to address issues such as heterogeneity and scalability. However, for small-scale IoT application, sometimes it is considered an inefficient approach. This paper proposes an alternate lightweight mechanism to the design and implementation of a dynamic virtual network based on user requirements. The key idea is to provide users a virtual interface that enables them to reconfigure the communication flow between the sensors and actuators at runtime. The More >

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1363

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R. Sowmyalakshmi^1,*, Mohamed Ibrahim Waly², Mohamed Yacin Sikkandar², T. Jayasankar¹, Sayed Sayeed Ahmad³, Rashmi Rani³, Suresh Chavhan^4,5
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2245-2260, 2021, DOI:10.32604/cmc.2021.018636 - 21 July 2021
Abstract In the recent years, microarray technology gained attention for concurrent monitoring of numerous microarray images. It remains a major challenge to process, store and transmit such huge volumes of microarray images. So, image compression techniques are used in the reduction of number of bits so that it can be stored and the images can be shared easily. Various techniques have been proposed in the past with applications in different domains. The current research paper presents a novel image compression technique i.e., optimized Linde–Buzo–Gray (OLBG) with Lempel Ziv Markov Algorithm (LZMA) coding technique called OLBG-LZMA for… More >

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Yuzhen Liu^1,3, Xiaoliang Wang^1,*, Xinghui She¹, Ming Yi¹, Yuelong Li¹, Frank Jiang²
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2261-2276, 2021, DOI:10.32604/cmc.2021.015501 - 21 July 2021
Abstract An intelligent mosquito net employing deep learning has been one of the hotspots in the field of Internet of Things as it can reduce significantly the spread of pathogens carried by mosquitoes, and help people live well in mosquito-infested areas. In this study, we propose an intelligent mosquito net that can produce and transmit data through the Internet of Medical Things. In our method, decision-making is controlled by a deep learning model, and the proposed method uses infrared sensors and an array of pressure sensors to collect data. Moreover the ZigBee protocol is used to… More >

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1235

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Mahmoud Ragab^1,2, Ali Algarni³, Adel A. Bahaddad⁴, Romany F. Mansour^5,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2277-2294, 2021, DOI:10.32604/cmc.2021.018000 - 21 July 2021
Abstract Physical health plays an important role in overall well-being of the human beings. It is the most observed dimension of health among others such as social, intellectual, emotional, spiritual and environmental dimensions. Due to exponential increase in the development of wireless communication techniques, Internet of Things (IoT) has effectively penetrated different aspects of human lives. Healthcare is one of the dynamic domains with ever-growing demands which can be met by IoT applications. IoT can be leveraged through several health service offerings such as remote health and monitoring services, aided living, personalized treatment, and so on.… More >

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2042

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1289

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Mohamed Esmail Karar^1,2, Omar Reyad^1,3, Mohammed Abd-Elnaby⁴, Abdel-Haleem Abdel-Aty^5,6, Marwa Ahmed Shouman^7,*
CMC-Computers, Materials & Continua, Vol.69, No.2, pp. 2295-2312, 2021, DOI:10.32604/cmc.2021.018671 - 21 July 2021
（This article belongs to the Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract Lightweight deep convolutional neural networks (CNNs) present a good solution to achieve fast and accurate image-guided diagnostic procedures of COVID-19 patients. Recently, advantages of portable Ultrasound (US) imaging such as simplicity and safe procedures have attracted many radiologists for scanning suspected COVID-19 cases. In this paper, a new framework of lightweight deep learning classifiers, namely COVID-LWNet is proposed to identify COVID-19 and pneumonia abnormalities in US images. Compared to traditional deep learning models, lightweight CNNs showed significant performance of real-time vision applications by using mobile devices with limited hardware resources. Four main lightweight deep learning… More >

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