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Yihuai Liang, Yan Li, Byeong-Seok Shin^*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2825-2842, 2021, DOI:10.32604/cmc.2021.016682
（This article belongs to this Special Issue: Advances of AI and Blockchain technologies for Future Smart City)
Abstract A centralized trusted execution environment (TEE) has been extensively studied to provide secure and trusted computing. However, a TEE might become a throughput bottleneck if it is used to evaluate data quality when collecting large-scale data in a crowdsourcing system. It may also have security problems compromised by attackers. Here, we propose a scheme, named dTEE, for building a platform for providing distributed trusted computing by leveraging TEEs. The platform is used as an infrastructure of trusted computations for blockchain-based crowdsourcing systems, especially to securely evaluate data quality and manage remuneration: these operations are handled by a TEE group. First,… More >

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Romany F. Mansour^1,*, Shaha Al-Otaibi², Amal Al-Rasheed², Hanan Aljuaid³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2843-2858, 2021, DOI:10.32604/cmc.2021.016626
Abstract Big data streams started becoming ubiquitous in recent years, thanks to rapid generation of massive volumes of data by different applications. It is challenging to apply existing data mining tools and techniques directly in these big data streams. At the same time, streaming data from several applications results in two major problems such as class imbalance and concept drift. The current research paper presents a new Multi-Objective Metaheuristic Optimization-based Big Data Analytics with Concept Drift Detection (MOMBD-CDD) method on High-Dimensional Streaming Data. The presented MOMBD-CDD model has different operational stages such as pre-processing, CDD, and classification. MOMBD-CDD model overcomes class… More >

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Rashad Bantan¹, Amal S. Hassan², Ehab Almetwally³, M. Elgarhy⁴, Farrukh Jamal⁵, Christophe Chesneau⁶, Mahmoud Elsehetry^7,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2859-2875, 2021, DOI:10.32604/cmc.2021.015422
Abstract Accelerated life testing has been widely used in product life testing experiments because it can quickly provide information on the lifetime distributions by testing products or materials at higher than basic conditional levels of stress, such as pressure, temperature, vibration, voltage, or load to induce early failures. In this paper, a step stress partially accelerated life test (SS-PALT) is regarded under the progressive type-II censored data with random removals. The removals from the test are considered to have the binomial distribution. The life times of the testing items are assumed to follow length-biased weighted Lomax distribution. The maximum likelihood method… More >

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D. Venugopal¹, T. Jayasankar², Mohamed Yacin Sikkandar³, Mohamed Ibrahim Waly³, Irina V. Pustokhina⁴, Denis A. Pustokhin⁵, K. Shankar^6,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2877-2893, 2021, DOI:10.32604/cmc.2021.015480
Abstract Data fusion is one of the challenging issues, the healthcare sector is facing in the recent years. Proper diagnosis from digital imagery and treatment are deemed to be the right solution. Intracerebral Haemorrhage (ICH), a condition characterized by injury of blood vessels in brain tissues, is one of the important reasons for stroke. Images generated by X-rays and Computed Tomography (CT) are widely used for estimating the size and location of hemorrhages. Radiologists use manual planimetry, a time-consuming process for segmenting CT scan images. Deep Learning (DL) is the most preferred method to increase the efficiency of diagnosing ICH. In… More >

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Fawaz Jaber Alsolami¹, Abdullah Saad Al-Malaise ALGhamdi², Asif Irshad Khan^1,*, Yoosef B. Abushark¹, Abdulmohsen Almalawi¹, Farrukh Saleem², Alka Agrawal³, Rajeev Kumar^3,4, Raees Ahmad Khan³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2895-2912, 2021, DOI:10.32604/cmc.2021.017469
（This article belongs to this Special Issue: Artificial Intelligence and Healthcare Analytics for COVID-19)
Abstract Ever since its outbreak in the Wuhan city of China, COVID-19 pandemic has engulfed more than 211 countries in the world, leaving a trail of unprecedented fatalities. Even more debilitating than the infection itself, were the restrictions like lockdowns and quarantine measures taken to contain the spread of Coronavirus. Such enforced alienation affected both the mental and social condition of people significantly. Social interactions and congregations are not only integral part of work life but also form the basis of human evolvement. However, COVID-19 brought all such communication to a grinding halt. Digital interactions have failed to enthuse the fervor… More >

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Thanh Thuong Huynh¹, Tien V. T. Nguyen^2,3, Quoc Manh Nguyen⁴, Trieu Khoa Nguyen^2,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2913-2923, 2021, DOI:10.32604/cmc.2021.016064
（This article belongs to this Special Issue: Application of Artificial Intelligence, Internet of Things, and Learning Approach for Learning Process in COVID-19/Industrial Revolution 4.0)
Abstract In this study, we investigated warpage and corner lifting minimization for three-dimensional printed parts generated by macro-size fused deposition modeling (FDM). First, the reasons for warpage were theoretically elucidated. This approach revealed that the thermal deformation and differential volumetric shrinkage of the extruded molten plastic resulted in warpage of FDM parts. In addition, low adhesion between the deposited model and the heated or non-heated printing bed may intensify warpage further. As a next step, initial small-size and medium-size models were used to identify parameters to manage and minimize warpage in a way that would reduce material consumption and running time.… More >

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Turki M. Alanazi¹, Ahmed Ben Atitallah^1,2,*, Imen Abid²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2925-2943, 2021, DOI:10.32604/cmc.2021.017575
Abstract In this paper, a software/hardware High-level Synthesis (HLS) design is proposed to compute the Adaptive Vector Median Filter (AVMF) in real-time. In fact, this filter is known by its excellent impulsive noise suppression and chromaticity conservation. The software (SW) study of this filter demonstrates that its implementation is too complex. The purpose of this work is to study the impact of using an HLS tool to design ideal floating-point and optimized fixed-point hardware (HW) architectures for the AVMF filter using square root function (ideal HW) and ROM memory (optimized HW), respectively, to select the best HLS architectures and to design… More >

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Jaeuk Moon, Seungwon Jung, Sungwoo Park, Eenjun Hwang^*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2945-2959, 2021, DOI:10.32604/cmc.2021.017435
（This article belongs to this Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract One popular strategy to reduce the enormous number of illnesses and deaths from a seasonal influenza pandemic is to obtain the influenza vaccine on time. Usually, vaccine production preparation must be done at least six months in advance, and accurate long-term influenza forecasting is essential for this. Although diverse machine learning models have been proposed for influenza forecasting, they focus on short-term forecasting, and their performance is too dependent on input variables. For a country’s long-term influenza forecasting, typical surveillance data are known to be more effective than diverse external data on the Internet. We propose a two-stage data selection… More >

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Mohamed Abdel-Basset¹, Reda Mohamed¹, Mohamed Abouhawwash^2,3, Ripon K. Chakrabortty⁴, Michael J. Ryan⁴, Yunyoung Nam^5,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2961-2977, 2021, DOI:10.32604/cmc.2021.016956
Abstract Image segmentation is vital when analyzing medical images, especially magnetic resonance (MR) images of the brain. Recently, several image segmentation techniques based on multilevel thresholding have been proposed for medical image segmentation; however, the algorithms become trapped in local minima and have low convergence speeds, particularly as the number of threshold levels increases. Consequently, in this paper, we develop a new multilevel thresholding image segmentation technique based on the jellyfish search algorithm (JSA) (an optimizer). We modify the JSA to prevent descents into local minima, and we accelerate convergence toward optimal solutions. The improvement is achieved by applying two novel… More >

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Shiqi Wang¹, Mingfang Jiang^2,*, Jiaohua Qin¹, Hengfu Yang², Zhichen Gao³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2979-2993, 2021, DOI:10.32604/cmc.2021.017094
Abstract In the era of big data, outsourcing massive data to a remote cloud server is a promising approach. Outsourcing storage and computation services can reduce storage costs and computational burdens. However, public cloud storage brings about new privacy and security concerns since the cloud servers can be shared by multiple users. Privacy-preserving feature extraction techniques are an effective solution to this issue. Because the Rotation Invariant Local Binary Pattern (RILBP) has been widely used in various image processing fields, we propose a new privacy-preserving outsourcing computation of RILBP over encrypted images in this paper (called PPRILBP). To protect image content,… More >

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M. S. Maharajan¹, T. Abirami², Irina V. Pustokhina³, Denis A. Pustokhin⁴, K. Shankar^5,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 2995-3013, 2021, DOI:10.32604/cmc.2021.016139
Abstract Wireless Sensor Networks (WSN) started gaining attention due to its wide application in the fields of data collection and information processing. The recent advancements in multimedia sensors demand the Quality of Service (QoS) be maintained up to certain standards. The restrictions and requirements in QoS management completely depend upon the nature of target application. Some of the major QoS parameters in WSN are energy efficiency, network lifetime, delay and throughput. In this scenario, clustering and routing are considered as the most effective techniques to meet the demands of QoS. Since they are treated as NP (Non-deterministic Polynomial-time) hard problem, Swarm… More >

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Shakir Ullah¹, Sadiq Ullah¹, Inzamam Ahmad¹, Wasi Ur Rehman Khan¹, Toufeeq Ahmad¹, Usman Habib², Mahmoud A. Albreem³, Mohammed H. Alsharif⁴, Peerapong Uthansakul^5,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3015-3027, 2021, DOI:10.32604/cmc.2021.015549
（This article belongs to this Special Issue: Advances in 5G Antenna Designs and Systems)
Abstract In this paper, the design and experimental evaluation of a hexagonal-shaped coplanar waveguide (CPW)-feed frequency reconfigurable antenna is presented using flame retardant (FR)-4 substrate with size of 37 × 35 × 1.6 mm³. The antenna is made tunable to three different modes through the status of two pin diodes to operate in four distinct frequency bands, i.e., 2.45 GHz wireless fidelity (Wi-Fi) in MODE 1, 3.3 GHz (5G sub-6 GHz band) in MODE 2, 2.1 GHz (3G Long Term Evolution (LTE)-advanced) and 3.50 GHz Worldwide Interoperability for Microwave Access (WiMAX) in MODE 3. The optimization through simulation modeling shows that… More >

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Shahid Bashir¹, Imran Khan², Fahd N. Al-Wesabi³, Nadhem Nemri³, Ammar Zahary⁴, Quang Ngoc Nguyen^5,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3029-3044, 2021, DOI:10.32604/cmc.2021.017015
Abstract The device-to-device (D2D) networking technology is extended to the conventional cellular network to boost the communication efficiency of the entire network, forming a heterogeneous 5G and beyond (B5G) communication network. D2D communication in a cellular cell will boost the efficiency of the spectrum, increase the ability of the device, and reduce the communication burden of base stations through the sharing of approved cell resources, causing serious interference as well. The device-to-device (D2D) networking technology is extended to the conventional cellular network to boost the communication efficiency of the entire network, forming a heterogeneous 5G communication network. D2D communication in a… More >

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Runsheng Wang¹, Hefei Ling^1,*, Ping Li¹, Yuxuan Shi¹, Lei Wu¹, Jialie Shen²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3045-3060, 2021, DOI:10.32604/cmc.2021.017275
Abstract Gait recognition is a biometric technique that captures human walking pattern using gait silhouettes as input and can be used for long-term recognition. Recently proposed video-based methods achieve high performance. However, gait covariates or walking conditions, i.e., bag carrying and clothing, make the recognition of intra-class gait samples hard. Advanced methods simply use triplet loss for metric learning, which does not take the gait covariates into account. For alleviating the adverse influence of gait covariates, we propose cross walking condition constraint to explicitly consider the gait covariates. Specifically, this approach designs center-based and pair-wise loss functions to decrease discrepancy of… More >

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Qura-Tul-Ain Khan¹, Sagheer Abbas¹, Muhammad Adnan Khan^2,*, Areej Fatima³, Saad Alanazi⁴, Nouh Sabri Elmitwally^4,5
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3061-3077, 2021, DOI:10.32604/cmc.2021.015441
Abstract In vehicular systems, driving is considered to be the most complex task, involving many aspects of external sensory skills as well as cognitive intelligence. External skills include the estimation of distance and speed, time perception, visual and auditory perception, attention, the capability to drive safely and action-reaction time. Cognitive intelligence works as an internal mechanism that manages and holds the overall driver’s intelligent system.These cognitive capacities constitute the frontiers for generating adaptive behaviour for dynamic environments. The parameters for understanding intelligent behaviour are knowledge, reasoning, decision making, habit and cognitive skill. Modelling intelligent behaviour reveals that many of these parameters… More >

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Shaheen Khatoon^1,*, Majed A. Alshamari¹, Amna Asif¹, Md Maruf Hasan¹, Sherif Abdou², Khaled Mostafa Elsayed³, Mohsen Rashwan⁴
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3079-3100, 2021, DOI:10.32604/cmc.2021.017371
（This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract Social media platforms have proven to be effective for information gathering during emergency events caused by natural or human-made disasters. Emergency response authorities, law enforcement agencies, and the public can use this information to gain situational awareness and improve disaster response. In case of emergencies, rapid responses are needed to address victims’ requests for help. The research community has developed many social media platforms and used them effectively for emergency response and coordination in the past. However, most of the present deployments of platforms in crisis management are not automated, and their operational success largely depends on experts who analyze… More >

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Rajalakshmi Shenbaga Moorthy^1,*, P. Pabitha²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3101-3119, 2021, DOI:10.32604/cmc.2021.016489
Abstract Parkinson’s disease is a neurogenerative disorder and it is difficult to diagnose as no therapies may slow down its progression. This paper contributes a novel analytic system for Parkinson’s Disease Prediction mechanism using Improved Radial Basis Function Neural Network (IRBFNN). Particle swarm optimization (PSO) with K-means is used to find the hidden neuron’s centers to improve the accuracy of IRBFNN. The performance of RBFNN is seriously affected by the centers of hidden neurons. Conventionally K-means was used to find the centers of hidden neurons. The problem of sensitiveness to the random initial centroid in K-means degrades the performance of RBFNN.… More >

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Tao Zhang^1,*, Jie Shen¹, Shaoen Wu²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3121-3131, 2021, DOI:10.32604/cmc.2021.016362
Abstract Nonlinear response is an important factor affecting the accuracy of three-dimensional image measurement based on the fringe structured light method. A phase compensation algorithm combined with a Hilbert transform is proposed to reduce the phase error caused by the nonlinear response of a digital projector in the three-dimensional measurement system of fringe structured light. According to the analysis of the influence of Gamma distortion on the phase calculation, the algorithm establishes the relationship model between phase error and harmonic coefficient, introduces phase shift to the signal, and keeps the signal amplitude constant while filtering out the DC component. The phase… More >

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Latif Jan¹, Mohammad Haseeb Zafar¹, Abdul Waheed², Mahdi Zareei³, Faisal Alanazi^4,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3133-3145, 2021, DOI:10.32604/cmc.2021.014857
Abstract Spatial diversity plays a significant role in wireless communication systems, including the Fourth Generation (4G) and Fifth Generation (5G) systems, and it is expected to be a fundamental part of the future wireless communication systems as well. The Multiple-Input Multiple-Output (MIMO) technology, which is included in the IEEE 802.16j standard, still holds the most crucial position in the 4G spectrum as it promises to improve the throughput, capacity, spectral, and energy efficiency of wireless communication systems in the 2020s. This makes MIMO a viable technology for delay constrained medical and health care facilities. This paper presents an approximate closed-form expression… More >

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Muhammad Reazul Haque¹, Saw Chin Tan¹, Zulfadzli Yusoff^2,*, Kashif Nisar^3,5,6, Lee Ching Kwang^2,7, Rizaludin Kaspin⁴, Bhawani Shankar Chowdhry⁵, Rajkumar Buyya⁸, Satya Prasad Majumder⁹, Manoj Gupta¹⁰, Shuaib Memon¹¹
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3147-3165, 2021, DOI:10.32604/cmc.2021.016591
（This article belongs to this Special Issue: Advanced 5G Communication System for Transforming Health Care)
Abstract In software-defined networks (SDNs), controller placement is a critical factor in the design and planning for the future Internet of Things (IoT), telecommunication, and satellite communication systems. Existing research has concentrated largely on factors such as reliability, latency, controller capacity, propagation delay, and energy consumption. However, SDNs are vulnerable to distributed denial of service (DDoS) attacks that interfere with legitimate use of the network. The ever-increasing frequency of DDoS attacks has made it necessary to consider them in network design, especially in critical applications such as military, health care, and financial services networks requiring high availability. We propose a mathematical… More >

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Osamah Ibrahim Khalaf¹, Munsif Sokiyna^2,*, Youseef Alotaibi³, Abdulmajeed Alsufyani⁴, Saleh Alghamdi⁵
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3167-3184, 2021, DOI:10.32604/cmc.2021.016099
Abstract A major issue while building web applications is proper input validation and sanitization. Attackers can quickly exploit errors and vulnerabilities that lead to malicious behavior in web application validation operations. Attackers are rapidly improving their capabilities and technologies and now focus on exploiting vulnerabilities in web applications and compromising confidentiality. Cross-site scripting (XSS) and SQL injection attack (SQLIA) are attacks in which a hacker sends malicious inputs (cheat codes) to confuse a web application, to access or disable the application’s back-end without user awareness. In this paper, we explore the problem of detecting and removing bugs from both client-side and… More >

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Rashid Jan¹, Hassan Khan^2,3, Poom Kumam^4,5,*, Fairouz Tchier⁶, Rasool Shah², Haifa Bin Jebreen⁶
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3185-3201, 2021, DOI:10.32604/cmc.2021.015252
（This article belongs to this Special Issue: Recent Advances in Fractional Calculus Applied to Complex Engineering Phenomena)
Abstract It is eminent that partial differential equations are extensively meaningful in physics, mathematics and engineering. Natural phenomena are formulated with partial differential equations and are solved analytically or numerically to interrogate the system’s dynamical behavior. In the present research, mathematical modeling is extended and the modeling solutions Helmholtz equations are discussed in the fractional view of derivatives. First, the Helmholtz equations are presented in Caputo’s fractional derivative. Then Natural transformation, along with the decomposition method, is used to attain the series form solutions of the suggested problems. For justification of the proposed technique, it is applied to several numerical examples.… More >

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Yuan Sun^1,2,*, Chaofan Chen^1,2, Andong Chen³, Xiaobing Zhao^1,2
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3203-3213, 2021, DOI:10.32604/cmc.2021.016517
Abstract As the dual task of question answering, question generation (QG) is a significant and challenging task that aims to generate valid and fluent questions from a given paragraph. The QG task is of great significance to question answering systems, conversational systems, and machine reading comprehension systems. Recent sequence to sequence neural models have achieved outstanding performance in English and Chinese QG tasks. However, the task of Tibetan QG is rarely mentioned. The key factor impeding its development is the lack of a public Tibetan QG dataset. Faced with this challenge, the present paper first collects 425 articles from the Tibetan… More >

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Reem K. Alkhodhairi¹, Shahad R. Aljalhami¹, Norah K. Rusayni¹, Jowharah F. Alshobaili¹, Amal A. Al-Shargabi^1,*, Abdulatif Alabdulatif²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3215-3233, 2021, DOI:10.32604/cmc.2021.016881
（This article belongs to this Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
Abstract Currently, Bitcoin is the world’s most popular cryptocurrency. The price of Bitcoin is extremely volatile, which can be described as high-benefit and high-risk. To minimize the risk involved, a means of more accurately predicting the Bitcoin price is required. Most of the existing studies of Bitcoin prediction are based on historical (i.e., benchmark) data, without considering the real-time (i.e., live) data. To mitigate the issue of price volatility and achieve more precise outcomes, this study suggests using historical and real-time data to predict the Bitcoin candlestick—or open, high, low, and close (OHLC)—prices. Seeking a better prediction model, the present study… More >

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Mohammed Mujib Alshahrani^*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3235-3254, 2021, DOI:10.32604/cmc.2021.015310
（This article belongs to this Special Issue: Security Issues in Industrial Internet of Things)
Abstract The term IoT refers to the interconnection and exchange of data among devices/sensors. IoT devices are often small, low cost, and have limited resources. The IoT issues and challenges are growing increasingly. Security and privacy issues are among the most important concerns in IoT applications, such as smart buildings. Remote cybersecurity attacks are the attacks which do not require physical access to the IoT networks, where the attacker can remotely access and communicate with the IoT devices through a wireless communication channel. Thus, remote cybersecurity attacks are a significant threat. Emerging applications in smart environments such as smart buildings require… More >

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Iskandar Waini^1,2, Anuar Ishak^2,*, Ioan Pop³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3255-3269, 2021, DOI:10.32604/cmc.2021.017643
Abstract This study examines the stagnation point flow over a stretching/shrinking sheet in a hybrid nanofluid with homogeneous-heterogeneous reactions. The hybrid nanofluid consists of copper (Cu) and alumina (Al₂O₃) nanoparticles which are added into water to form Cu-Al₂O₃/water hybrid nanofluid. The similarity equations are obtained using a similarity transformation. Then, the function bvp4c in MATLAB is utilised to obtain the numerical results. The dual solutions are found for limited values of the stretching/shrinking parameter. Also, the turning point arises in the shrinking region (λ < 0). Besides, the presence of hybrid nanoparticles enhances the heat transfer rate, skin friction coefficient, and… More >

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Thavavel Vaiyapuri^*, Adel Binbusayyis
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3271-3288, 2021, DOI:10.32604/cmc.2021.017665
（This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract In the era of Big data, learning discriminant feature representation from network traffic is identified has as an invariably essential task for improving the detection ability of an intrusion detection system (IDS). Owing to the lack of accurately labeled network traffic data, many unsupervised feature representation learning models have been proposed with state-of-the-art performance. Yet, these models fail to consider the classification error while learning the feature representation. Intuitively, the learnt feature representation may degrade the performance of the classification task. For the first time in the field of intrusion detection, this paper proposes an unsupervised IDS model leveraging the… More >

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Gun-Yoon Shin¹, Dong-Wook Kim¹, Sang-Soo Kim², Myung-Mook Han^3,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3289-3303, 2021, DOI:10.32604/cmc.2021.017502
Abstract Detection of unknown attacks like a zero-day attack is a research field that has long been studied. Recently, advances in Machine Learning (ML) and Artificial Intelligence (AI) have led to the emergence of many kinds of attack-generation tools developed using these technologies to evade detection skillfully. Anomaly detection and misuse detection are the most commonly used techniques for detecting intrusion by unknown attacks. Although anomaly detection is adequate for detecting unknown attacks, its disadvantage is the possibility of high false alarms. Misuse detection has low false alarms; its limitation is that it can detect only known attacks. To overcome such… More >

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Muhammad Shaheen^1,*, Umair Abdullah²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3305-3322, 2021, DOI:10.32604/cmc.2021.016766
Abstract This paper is aimed to develop an algorithm for extracting association rules, called Context-Based Association Rule Mining algorithm (CARM), which can be regarded as an extension of the Context-Based Positive and Negative Association Rule Mining algorithm (CBPNARM). CBPNARM was developed to extract positive and negative association rules from Spatio-temporal (space-time) data only, while the proposed algorithm can be applied to both spatial and non-spatial data. The proposed algorithm is applied to the energy dataset to classify a country’s energy development by uncovering the enthralling interdependencies between the set of variables to get positive and negative associations. Many association rules related… More >

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Youseef Alotaibi^1,*, Muhammad Noman Malik², Huma Hayat Khan³, Anab Batool², Saif ul Islam⁴, Abdulmajeed Alsufyani⁵, Saleh Alghamdi⁶
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3323-3338, 2021, DOI:10.32604/cmc.2021.016727
Abstract Social media data are rapidly increasing and constitute a source of user opinions and tips on a wide range of products and services. The increasing availability of such big data on biased reviews and blogs creates challenges for customers and businesses in reviewing all content in their decision-making process. To overcome this challenge, extracting suggestions from opinionated text is a possible solution. In this study, the characteristics of suggestions are analyzed and a suggestion mining extraction process is presented for classifying suggestive sentences from online customers’ reviews. A classification using a word-embedding approach is used via the XGBoost classifier. The… More >

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F. S. Bayones¹, A. M. Abd-Alla², A. M. Farhan^3,4,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3339-3352, 2021, DOI:10.32604/cmc.2021.016021
Abstract The present article deals with the investigation thermal stress of a magnetothermoelastic cylinder subjected to rotation, open or closed circuit, thermal and mechanical boundary conditions. The outer and inner surfaces of the cylinder are subjected to both mechanical and thermal boundary conditions. A The transient coupled thermoelasticity in an infinite cylinder with its base abruptly exposed to a heat flux of a decaying exponential function of time is devised solve by the finite-difference method. The fundamental equations’ system is solved by utilizing an implicit finite-difference method. This current method is a second-order accurate in time and space; it is also… More >

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Saleem Ibraheem Saleem^*, Adnan Mohsin Abdulazeez
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3353-3372, 2021, DOI:10.32604/cmc.2021.016342
（This article belongs to this Special Issue: AI, IoT, Blockchain Assisted Intelligent Solutions to Medical and Healthcare Systems)
Abstract Writer identification (WI) based on handwritten text structures is typically focused on digital characteristics, with letters/strokes representing the information acquired from the current research in the integration of individual writing habits/styles. Previous studies have indicated that a word’s attributes contribute to greater recognition than the attributes of a character or stroke. As a result of the complexity of Arabic handwriting, segmenting and separating letters and strokes from a script poses a challenge in addition to WI schemes. In this work, we propose new texture features for WI based on text. The histogram of oriented gradient (HOG) features are modified to… More >

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Ying Sun¹, Yanfei Sun^1,2,*, Jin Qi¹, Fei Wu¹, Xiao-Yuan Jing^1,3, Yu Xue⁴, Zixin Shen⁵
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3373-3389, 2021, DOI:10.32604/cmc.2021.016539
Abstract Cross-project defect prediction (CPDP) aims to predict the defects on target project by using a prediction model built on source projects. The main problem in CPDP is the huge distribution gap between the source project and the target project, which prevents the prediction model from performing well. Most existing methods overlook the class discrimination of the learned features. Seeking an effective transferable model from the source project to the target project for CPDP is challenging. In this paper, we propose an unsupervised domain adaptation based on the discriminative subspace learning (DSL) approach for CPDP. DSL treats the data from two… More >

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Ali Abdi Seyedkolaei¹, Seyed Amin Hosseini Seno^1,*, Rahmat Budiarto²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3391-3410, 2021, DOI:10.32604/cmc.2021.017313
（This article belongs to this Special Issue: Intelligent Software-defined Networking (SDN) Technologies for Future Generation Networks)
Abstract In software-defined networking (SDN) networks, unlike traditional networks, the control plane is located separately in a device or program. One of the most critical problems in these networks is a controller placement problem, which has a significant impact on the network’s overall performance. This paper attempts to provide a solution to this problem aiming to reduce the operational cost of the network and improve their survivability and load balancing. The researchers have proposed a suitable framework called kernel search introducing integer programming formulations to address the controller placement problem. It demonstrates through careful computational studies that the formulations can design… More >

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Usman Shahzad^1,2,*, Ishfaq Ahmad¹, Ibrahim Mufrah Almanjahie^3,4, Nadia H.Al –Noor⁵
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3411-3430, 2021, DOI:10.32604/cmc.2021.017046
Abstract Variance is one of the most vital measures of dispersion widely employed in practical aspects. A commonly used approach for variance estimation is the traditional method of moments that is strongly influenced by the presence of extreme values, and thus its results cannot be relied on. Finding momentum from Koyuncu’s recent work, the present paper focuses first on proposing two classes of variance estimators based on linear moments (L-moments), and then employing them with auxiliary data under double stratified sampling to introduce a new class of calibration variance estimators using important properties of L-moments (L-location, L-cv, L-variance). Three populations are… More >

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Zhenzhou Wang¹, Yinuo Ma¹, Pingping Yu^1,*, Ning Cao², Heiner Dintera³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3431-3446, 2021, DOI:10.32604/cmc.2021.017729
Abstract Predicting the blooming season of ornamental plants is significant for guiding adjustments in production decisions and providing viewing periods and routes. The current strategies for observation of ornamental plant booming periods are mainly based on manpower and experience, which have problems such as inaccurate recognition time, time-consuming and energy sapping. Therefore, this paper proposes a neural network-based method for predicting the flowering phase of pear tree. Firstly, based on the meteorological observation data of Shijiazhuang Meteorological Station from 2000 to 2019, three principal components (the temperature factor, weather factor, and humidity factor) with high correlation coefficient with the flowering phase… More >

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Chung-Il Kim¹, Jehyeok Rew², Yongjang Cho², Eenjun Hwang^2,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3447-3463, 2021, DOI:10.32604/cmc.2021.017633
（This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract Image inpainting is an interesting technique in computer vision and artificial intelligence for plausibly filling in blank areas of an image by referring to their surrounding areas. Although its performance has been improved significantly using diverse convolutional neural network (CNN)-based models, these models have difficulty filling in some erased areas due to the kernel size of the CNN. If the kernel size is too narrow for the blank area, the models cannot consider the entire surrounding area, only partial areas or none at all. This issue leads to typical problems of inpainting, such as pixel reconstruction failure and unintended filling.… More >

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Ghulfam Zahra¹, Muhammad Imran¹, Abdulrahman M. Qahtani^2,*, Abdulmajeed Alsufyani², Omar Almutiry³, Awais Mahmood³, Fayez Eid Alazemi⁴
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3465-3481, 2021, DOI:10.32604/cmc.2021.017454
（This article belongs to this Special Issue: Recent Advances in Deep Learning, Information Fusion, and Features Selection for Video Surveillance Application)
Abstract In recent years, video surveillance application played a significant role in our daily lives. Images taken during foggy and haze weather conditions for video surveillance application lose their authenticity and hence reduces the visibility. The reason behind visibility enhancement of foggy and haze images is to help numerous computer and machine vision applications such as satellite imagery, object detection, target killing, and surveillance. To remove fog and enhance visibility, a number of visibility enhancement algorithms and methods have been proposed in the past. However, these techniques suffer from several limitations that place strong obstacles to the real world outdoor computer… More >

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Khalil Khan¹, Rehan Ullah Khan², Jehad Ali³, Irfan Uddin⁴, Sahib Khan⁵, Byeong-hee Roh^3,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3483-3498, 2021, DOI:10.32604/cmc.2021.016535
Abstract Race classification is a long-standing challenge in the field of face image analysis. The investigation of salient facial features is an important task to avoid processing all face parts. Face segmentation strongly benefits several face analysis tasks, including ethnicity and race classification. We propose a race-classification algorithm using a prior face segmentation framework. A deep convolutional neural network (DCNN) was used to construct a face segmentation model. For training the DCNN, we label face images according to seven different classes, that is, nose, skin, hair, eyes, brows, back, and mouth. The DCNN model developed in the first phase was used… More >

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Hasan Sabah Hasan^1,*, Abdallah A. Abdallah², Imran Khan³, Hala Sadek Alosman⁴, Ayshan Kolemen⁵, Bilal Alhayani⁶
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3499-3511, 2021, DOI:10.32604/cmc.2021.015968
（This article belongs to this Special Issue: Wireless Sensors Networks Application in Healthcare and Medical Internet of Things (Miot) in Bio-Medical Sensors Networks)
Abstract True unilateral posterior crossbite in adults is a challenging malocclusion to treat, especially when we need to correct cross-arch segments with unwanted effects on non-cross segments. Conventional expansion methods are expected to have some shortcomings; the Unilateral dental expander appliance used to restore unilateral cross bite dental arch is an uncommon appliance; for this, a designed new device is needed. This paper aimed to invite a new unilateral dental expander appliance (UDEX) to treat unilateral dental posterior crossbite in adults using available dental material, easy to use and handle, well tolerated by the patient, and biocompatible with oral structure. It… More >

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Pushpendra Kumar^1,2,*, Ramjeevan Singh Thakur³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3513-3529, 2021, DOI:10.32604/cmc.2021.016957
（This article belongs to this Special Issue: Emerging Applications of Artificial Intelligence, Machine learning and Data Science)
Abstract The aim of this research is to develop a mechanism to help medical practitioners predict and diagnose liver disease. Several systems have been proposed to help medical experts by diminishing error and increasing accuracy in diagnosing and predicting diseases. Among many existing methods, a few have considered the class imbalance issues of liver disorder datasets. As all the samples of liver disorder datasets are not useful, they do not contribute to learning about classifiers. A few samples might be redundant, which can increase the computational cost and affect the performance of the classifier. In this paper, a model has been… More >

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Mohammad Aldossary^*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3531-3562, 2021, DOI:10.32604/cmc.2021.017477
Abstract With the striking rise in penetration of Cloud Computing, energy consumption is considered as one of the key cost factors that need to be managed within cloud providers’ infrastructures. Subsequently, recent approaches and strategies based on reactive and proactive methods have been developed for managing cloud computing resources, where the energy consumption and the operational costs are minimized. However, to make better cost decisions in these strategies, the performance and energy awareness should be supported at both Physical Machine (PM) and Virtual Machine (VM) levels. Therefore, in this paper, a novel hybrid approach is proposed, which jointly considered the prediction… More >

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Sara Saber¹, Uswah Khairuddin^2,*, Rubiyah Yusof², Ahmed Madani¹
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3563-3576, 2021, DOI:10.32604/cmc.2021.017769
Abstract The identification of DNA binding proteins (DNABPs) is considered a major challenge in genome annotation because they are linked to several important applied and research applications of cellular functions e.g., in the study of the biological, biophysical, and biochemical effects of antibiotics, drugs, and steroids on DNA. This paper presents an efficient approach for DNABPs identification based on deep transfer learning, named “DTLM-DBP.” Two transfer learning methods are used in the identification process. The first is based on the pre-trained deep learning model as a feature’s extractor and classifier. Two different pre-trained Convolutional Neural Networks (CNN), AlexNet 8 and VGG… More >

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1306

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Ajla Kulaglic^1,*, Burak Berk Ustundag²
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3577-3593, 2021, DOI:10.32604/cmc.2021.014768
Abstract Machine Learning (ML) algorithms have been widely used for financial time series prediction and trading through bots. In this work, we propose a Predictive Error Compensated Wavelet Neural Network (PEC-WNN) ML model that improves the prediction of next day closing prices. In the proposed model we use multiple neural networks where the first one uses the closing stock prices from multiple-scale time-domain inputs. An additional network is used for error estimation to compensate and reduce the prediction error of the main network instead of using recurrence. The performance of the proposed model is evaluated using six different stock data samples… More >

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S. Nanthini^1,*, S. Nithya Kalyani², Sudhakar Sengan³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3595-3614, 2021, DOI:10.32604/cmc.2021.015038
Abstract In this paper, the energy conservation in the ununiform clustered network field is proposed. The fundamental reason behind the methodology is that in the process of CH election, nodes Competition Radius (CR) task is based on not just the space between nodes and their Residual Energy (RE), which is utilized in Energy-Aware Distributed Unequal Clustering (EADUC) protocol but also a third-degree factor, i.e., the nearby multi-hop node count. In contrast, a third-factor nearby nodes count is also used. This surrounding data is taken into account in the clustering feature to increase the network’s life span. The proposed method, known as… More >

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Mohamed S. Mohamed^1,*, Sayed K. Elagan¹, Saad J. Almalki¹, Muteb R. Alharthi¹, Mohamed F. El-Badawy², Amr M. S. Mahdy¹
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3615-3628, 2021, DOI:10.32604/cmc.2021.017208
（This article belongs to this Special Issue: Artificial Intelligence and Healthcare Analytics for COVID-19)
Abstract In this article, we have shown that bacterial DNA could act like some coils which interact with coil-like DNA of host cells. By decreasing the separating distance between two bacterial cellular DNA, the interaction potential, entropy, and the number of microstates of the system grow. Moreover, the system gives its energy to the medium and the temperature of the host body grows. This could be seen as fever in diseases. By emitting some special waves and changing the temperature of the medium, the effects of bacterial waves could be reduced and bacterial diseases could be controlled. Many investigators have shown… More >

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1286

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Lukas Danys¹, Radek Martinek¹, Rene Jaros^1,*, Jan Baros¹, Petr Simonik², Vaclav Snasel³
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3629-3652, 2021, DOI:10.32604/cmc.2021.017333
Abstract This pilot study focuses on a real measurements and enhancements of a software defined radio-based system for vehicle-to everything visible light communication (SDR-V2X-VLC). The presented system is based on a novel adaptive optimization of the feed-forward software defined equalization (FFSDE) methods of the least mean squares (LMS), normalized LMS (NLMS) and QR decomposition-based recursive least squares (QR-RLS) algorithms. Individual parameters of adaptive equalizations are adjusted in real-time to reach the best possible results. Experiments were carried out on a conventional LED Octavia III taillight drafted directly from production line and universal software radio peripherals (USRP) from National Instruments. The transmitting/receiving… More >

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Daniyal Baig¹, Tahir Alyas¹, Muhammad Hamid², Muhammad Saleem³, Saadia Malik⁴, Nadia Tabassum^5,*, Natash Ali Mian⁶
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3653-3669, 2021, DOI:10.32604/cmc.2021.017948
Abstract The past two decades witnessed a broad-increase in web technology and on-line gaming. Enhancing the broadband confinements is viewed as one of the most significant variables that prompted new gaming technology. The immense utilization of web applications and games additionally prompted growth in the handled devices and moving the limited gaming experience from user devices to online cloud servers. As internet capabilities are enhanced new ways of gaming are being used to improve the gaming experience. In cloud-based video gaming, game engines are hosted in cloud gaming data centers, and compressed gaming scenes are rendered to the players over the… More >

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Daniel Godfrey¹, Beom-Su Kim¹, Haoran Miao¹, Babar Shah², Bashir Hayat³, Imran Khan⁴, Tae-Eung Sung⁵, Ki-Il Kim^1,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3671-3692, 2021, DOI:10.32604/cmc.2021.017475
（This article belongs to this Special Issue: Intelligent Software-defined Networking (SDN) Technologies for Future Generation Networks)
Abstract The end-to-end delay in a wired network is strongly dependent on congestion on intermediate nodes. Among lots of feasible approaches to avoid congestion efficiently, congestion-aware routing protocols tend to search for an uncongested path toward the destination through rule-based approaches in reactive/incident-driven and distributed methods. However, these previous approaches have a problem accommodating the changing network environments in autonomous and self-adaptive operations dynamically. To overcome this drawback, we present a new congestion-aware routing protocol based on a Q-learning algorithm in software-defined networks where logically centralized network operation enables intelligent control and management of network resources. In a proposed routing protocol,… More >

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Adarsh Anand¹, Jasmine Kaur¹, Ompal Singh¹, Omar H. Alhazmi^2,*
CMC-Computers, Materials & Continua, Vol.68, No.3, pp. 3693-3712, 2021, DOI:10.32604/cmc.2021.017461
Abstract A carefully planned software development process helps in maintaining the quality of the software. In today’s scenario the primitive software development models have been replaced by the Agile based models like SCRUM, KANBAN, LEAN, etc. Although, every framework has its own boon, the reason for widespread acceptance of the agile-based approach is its evolutionary nature that permits change in the path of software development. The development process occurs in iterative and incremental cycles called sprints. In SCRUM, which is one of the most widely used agile-based software development modeling framework; the sprint length is fixed throughout the process wherein; it… More >

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