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Farouq Mohammad A. Alam¹, Sharifah Alrajhi¹, Mazen Nassar^1,2, Ahmed Z. Afify^3,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2185-2202, 2021, DOI:10.32604/cmc.2021.015089
（This article belongs to this Special Issue: Artificial Intelligence and IoT based intelligent systems using high performance computing for Medical applications.)
Abstract The main objective of this paper is to discuss a general family of distributions generated from the symmetrical arcsine distribution. The considered family includes various asymmetrical and symmetrical probability distributions as special cases. A particular case of a symmetrical probability distribution from this family is the Arcsine–Gaussian distribution. Key statistical properties of this distribution including quantile, mean residual life, order statistics and moments are derived. The Arcsine–Gaussian parameters are estimated using two classical estimation methods called moments and maximum likelihood methods. A simulation study which provides asymptotic distribution of all considered point estimators, 90% and 95% asymptotic confidence intervals are… More >

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Ameen Banjar¹, Zohair Ahmed², Ali Daud¹, Rabeeh Ayaz Abbasi³, Hussain Dawood^4,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2203-2225, 2021, DOI:10.32604/cmc.2021.014226
（This article belongs to this Special Issue: Machine Learning-based Intelligent Systems: Theories, Algorithms, and Applications)
Abstract Most consumers read online reviews written by different users before making purchase decisions, where each opinion expresses some sentiment. Therefore, sentiment analysis is currently a hot topic of research. In particular, aspect-based sentiment analysis concerns the exploration of emotions, opinions and facts that are expressed by people, usually in the form of polarity. It is crucial to consider polarity calculations and not simply categorize reviews as positive, negative, or neutral. Currently, the available lexicon-based method accuracy is affected by limited coverage. Several of the available polarity estimation techniques are too general and may not reflect the aspect/topic in question if… More >

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M. Premkumar¹, R. Sowmya², Pradeep Jangir³, Kottakkaran Sooppy Nisar^4,*, Mujahed Aldhaifallah⁵
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2227-2242, 2021, DOI:10.32604/cmc.2021.015565
（This article belongs to this Special Issue: Role of Computer in Modelling & Solving Real-World Problems)
Abstract The Equilibrium Optimizer (EO), Grey Wolf Optimizer (GWO), and Whale Optimizer (WO) algorithms are being recently developed for engineering optimization problems. In this paper, the EO, GWO, and WO algorithms are applied individually for a brushless direct current (BLDC) design optimization problem. The EO algorithm is inspired by the models utilized to find the system’s dynamic state and equilibrium state. The GWO and WO algorithms are inspired by the hunting behavior of the wolf and the whale, respectively. The primary purpose of any optimization technique is to find the optimal configuration by maximizing motor efficiency and/or minimizing the total mass.… More >

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Amir Haider¹, MuhibUr Rahman², Hamza Ahmad³, Mahdi NaghshvarianJahromi⁴, Muhammad Tabish Niaz¹, Hyung Seok Kim^1,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2243-2254, 2021, DOI:10.32604/cmc.2021.015613
Abstract This paper introduces a compact dual notched UWB antenna with an independently controllable WLAN notched band integrated with fixed WiMAX band-notch. The proposed antenna utilizes a slot resonator placed in the main radiator of the antenna for fixed WiMAX band notch, while an inverted L-shaped resonator in the partial ground plane for achieving frequency agility within WLAN notched band. The inverted L-shaped resonator is also loaded with fixed and variable capacitors to control and adjust the WLAN notch. The WLAN notched band can be controlled independently with a wide range of tunability without disturbing the WiMAX band-notch performance. Step by… More >

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Muntaha Alzubade^1,*, Orkan Ozcan¹, Nebiye Musaoglu¹, Murat Türkeş²
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2255-2269, 2021, DOI:10.32604/cmc.2021.013565
Abstract Remote sensing analysis techniques have been investigated extensively, represented by a critical vision, and are used to advance our understanding of the impacts of climate change and variability on the environment. This study aims to find a means of analysis that relies on remote sensing techniques to demonstrate the effects of observed climate variability on Land Use and Land Cover (LULC) of the Mesopotamia region, defined as a historical region located in the Middle East. This study employed the combined analysis of the Normalized Difference Vegetation Index (NDVI), Land Surface Temperature (LST), and two statistical analysis methods (Pearson Correlation Analysis,… More >

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Hegazy Rezk^1,2,*, Ahmed Fathy^3,4, Mokhtar Aly^5,6, Mohamed N. Ibrahim^7,8,9
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2271-2281, 2021, DOI:10.32604/cmc.2021.014590
（This article belongs to this Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Hydrocarbons, carbon monoxide and other pollutants from the transportation sector harm human health in many ways. Fuel cell (FC) has been evolving rapidly over the past two decades due to its efficient mechanism to transform the chemical energy in hydrogen-rich compounds into electrical energy. The main drawback of the standalone FC is its slow dynamic response and its inability to supply rapid variations in the load demand. Therefore, adding energy storage systems is necessary. However, to manage and distribute the power-sharing among the hybrid proton exchange membrane (PEM) fuel cell (FC), battery storage (BS), and supercapacitor (SC), an energy management… More >

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Mokhtar Aly^1,2, Hegazy Rezk^3,4,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2283-2299, 2021, DOI:10.32604/cmc.2021.014786
Abstract Fuzzy logic control (FLC) systems have found wide utilization in several industrial applications. This paper proposes a fuzzy logic-based fault detection and identification method for open-circuit switch fault in grid-tied photovoltaic (PV) inverters. Large installations and ambitious plans have been recently achieved for PV systems as clean and renewable power generation sources due to their improved environmental impacts and availability everywhere. Power converters represent the main parts for the grid integration of PV systems. However, PV power converters contain several power switches that construct their circuits. The power switches in PV systems are highly subjected to high stresses due to… More >

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1182

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Rami Sihwail^*, Khairuddin Omar, Khairul Akram Zainol Ariffin
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2301-2320, 2021, DOI:10.32604/cmc.2021.014510
Abstract The study of malware behaviors, over the last years, has received tremendous attention from researchers for the purpose of reducing malware risks. Most of the investigating experiments are performed using either static analysis or behavior analysis. However, recent studies have shown that both analyses are vulnerable to modern malware files that use several techniques to avoid analysis and detection. Therefore, extracted features could be meaningless and a distraction for malware analysts. However, the volatile memory can expose useful information about malware behaviors and characteristics. In addition, memory analysis is capable of detecting unconventional malware, such as in-memory and fileless malware.… More >

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ARTICLE

Rajesh Kumar Sahoo¹, Morched Derbali^2,*, Houssem Jerbi³, Doan Van Thang⁴, P. Pavan Kumar⁵, Sipra Sahoo⁶
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2321-2336, 2021, DOI:10.32604/cmc.2021.013014
（This article belongs to this Special Issue: Emerging Computational Intelligence Technologies for Software Engineering: Paradigms, Principles and Applications)
Abstract Software testing has been attracting a lot of attention for effective software development. In model driven approach, Unified Modelling Language (UML) is a conceptual modelling approach for obligations and other features of the system in a model-driven methodology. Specialized tools interpret these models into other software artifacts such as code, test data and documentation. The generation of test cases permits the appropriate test data to be determined that have the aptitude to ascertain the requirements. This paper focuses on optimizing the test data obtained from UML activity and state chart diagrams by using Basic Genetic Algorithm (BGA). For generating the… More >

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Rabia Javed^1,2, Mohd Shafry Mohd Rahim¹, Tanzila Saba³, Suliman Mohamed Fati³, Amjad Rehman^3,*, Usman Tariq⁴
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2337-2352, 2021, DOI:10.32604/cmc.2021.014677
Abstract Most of the melanoma cases of skin cancer are the life-threatening form of cancer. It is prevalent among the Caucasian group of people due to their light skin tone. Melanoma is the second most common cancer that hits the age group of 15–29 years. The high number of cases has increased the importance of automated systems for diagnosing. The diagnosis should be fast and accurate for the early treatment of melanoma. It should remove the need for biopsies and provide stable diagnostic results. Automation requires large quantities of images. Skin lesion datasets contain various kinds of dermoscopic images for the… More >

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Sally M. Elghamrawy¹, Aboul Ella Hassnien^2,*, Vaclav Snasel³
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2353-2371, 2021, DOI:10.32604/cmc.2021.014767
Abstract Detecting COVID-19 cases as early as possible became a critical issue that must be addressed to avoid the pandemic’s additional spread and early provide the appropriate treatment to the affected patients. This study aimed to develop a COVID-19 diagnosis and prediction (AIMDP) model that could identify patients with COVID-19 and distinguish it from other viral pneumonia signs detected in chest computed tomography (CT) scans. The proposed system uses convolutional neural networks (CNNs) as a deep learning technology to process hundreds of CT chest scan images and speeds up COVID-19 case prediction to facilitate its containment. We employed the whale optimization… More >

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ARTICLE

Muhammad Wajeeh Uz Zaman¹, Yaser Hafeez¹, Shariq Hussain², Haris Anwaar³, Shunkun Yang^4,*, Sadia Ali¹, Aaqif Afzaal Abbasi², Oh-Young Song⁵
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2373-2391, 2021, DOI:10.32604/cmc.2021.015112
（This article belongs to this Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
Abstract The rapid growth in software demand incentivizes software development organizations to develop exclusive software for their customers worldwide. This problem is addressed by the software development industry by software product line (SPL) practices that employ feature models. However, optimal feature selection based on user requirements is a challenging task. Thus, there is a requirement to resolve the challenges of software development, to increase satisfaction and maintain high product quality, for massive customer needs within limited resources. In this work, we propose a recommender system for the development team and clients to increase productivity and quality by utilizing historical information and… More >

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J. Banumathi¹, A. Muthumari², S. Dhanasekaran³, S. Rajasekaran⁴, Irina V. Pustokhina⁵, Denis A. Pustokhin⁶, K. Shankar^7,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2393-2407, 2021, DOI:10.32604/cmc.2021.015605
Abstract Due to the advancements in remote sensing technologies, the generation of hyperspectral imagery (HSI) gets significantly increased. Accurate classification of HSI becomes a critical process in the domain of hyperspectral data analysis. The massive availability of spectral and spatial details of HSI has offered a great opportunity to efficiently illustrate and recognize ground materials. Presently, deep learning (DL) models particularly, convolutional neural networks (CNNs) become useful for HSI classification owing to the effective feature representation and high performance. In this view, this paper introduces a new DL based Xception model for HSI analysis and classification, called Xcep-HSIC model. Initially, the… More >

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1173

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A. S. Al-Waisy¹, Mazin Abed Mohammed¹, Shumoos Al-Fahdawi¹, M. S. Maashi², Begonya Garcia-Zapirain³, Karrar Hameed Abdulkareem⁴, S. A. Mostafa⁵, Nallapaneni Manoj Kumar⁶, Dac-Nhuong Le^7,8,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2409-2429, 2021, DOI:10.32604/cmc.2021.012955
（This article belongs to this Special Issue: Machine Learning and Computational Methods for COVID-19 Disease Detection and Prediction)
Abstract Coronavirus (COVID-19) epidemic outbreak has devastating effects on daily lives and healthcare systems worldwide. This newly recognized virus is highly transmissible, and no clinically approved vaccine or antiviral medicine is currently available. Early diagnosis of infected patients through effective screening is needed to control the rapid spread of this virus. Chest radiography imaging is an effective diagnosis tool for COVID-19 virus and follow-up. Here, a novel hybrid multimodal deep learning system for identifying COVID-19 virus in chest X-ray (CX-R) images is developed and termed as the COVID-DeepNet system to aid expert radiologists in rapid and accurate image interpretation. First, Contrast-Limited… More >

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ARTICLE

M. Jayalakshmi¹, Lalit Garg^2,*, K. Maharajan³, K. Jayakumar⁴, Kathiravan Srinivasan⁵, Ali Kashif Bashir⁶, K. Ramesh⁷
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2431-2447, 2021, DOI:10.32604/cmc.2021.015352
Abstract In several countries, the ageing population contour focuses on high healthcare costs and overloaded health care environments. Pervasive health care monitoring system can be a potential alternative, especially in the COVID-19 pandemic situation to help mitigate such problems by encouraging healthcare to transition from hospital-centred services to self-care, mobile care and home care. In this aspect, we propose a pervasive system to monitor the COVID’19 patient’s conditions within the hospital and outside by monitoring their medical and psychological situation. It facilitates better healthcare assistance, especially for COVID’19 patients and quarantined people. It identifies the patient’s medical and psychological condition based… More >

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ARTICLE

Nabeela Awan¹, Salman Khan², Mohammad Khalid Imam Rahmani³, Muhammad Tahir³, Nur Alam MD^4,*, Ryan Alturki⁵, Ihsan Ullah⁶
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2449-2462, 2021, DOI:10.32604/cmc.2021.014386
（This article belongs to this Special Issue: Machine Learning-based Secured and Privacy-preserved Smart City)
Abstract Recent advancements in hardware and communication technologies have enabled worldwide interconnection using the internet of things (IoT). The IoT is the backbone of smart city applications such as smart grids and green energy management. In smart cities, the IoT devices are used for linking power, price, energy, and demand information for smart homes and home energy management (HEM) in the smart grids. In complex smart grid-connected systems, power scheduling and secure dispatch of information are the main research challenge. These challenges can be resolved through various machine learning techniques and data analytics. In this paper, we have proposed a particle… More >

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ARTICLE

Yasir Shahzad^1,*, Huma Javed¹, Haleem Farman², Jamil Ahmad², Bilal Jan³, Abdelmohsen A. Nassani⁴
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2463-2480, 2021, DOI:10.32604/cmc.2021.014904
Abstract Smart healthcare integrates an advanced wave of information technology using smart devices to collect health-related medical science data. Such data usually exist in unstructured, noisy, incomplete, and heterogeneous forms. Annotating these limitations remains an open challenge in deep learning to classify health conditions. In this paper, a long short-term memory (LSTM) based health condition prediction framework is proposed to rectify imbalanced and noisy data and transform it into a useful form to predict accurate health conditions. The imbalanced and scarce data is normalized through coding to gain consistency for accurate results using synthetic minority oversampling technique. The proposed model is… More >

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ARTICLE

Muhammad Waqas Nadeem^1,2, Hock Guan Goh^1,*, Muhammad Adnan Khan³, Muzammil Hussain⁴, Muhammad Faheem Mushtaq⁵, Vasaki a/p Ponnusamy¹
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2481-2496, 2021, DOI:10.32604/cmc.2021.014649
Abstract The contemporary evolution in healthcare technologies plays a considerable and significant role to improve medical services and save human lives. Heart disease or cardiovascular disease is the most fatal and complex disease which it is hardly to be detected through our naked eyes, as numerous people have been suffering from this disease globally. Heart attacks occur when the ranges of vital signs such as blood pressure, pulse rate, and body temperature exceed their normal values. The efficient diagnosis of heart diseases could play a substantial role in the field of cardiology, while diagnostic time could be reduced. It has been… More >

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ARTICLE

Yussuf Ahmed^1,*, A.Taufiq Asyhari¹, Md Arafatur Rahman²
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2497-2513, 2021, DOI:10.32604/cmc.2021.014223
（This article belongs to this Special Issue: Machine Learning-based Secured and Privacy-preserved Smart City)
Abstract The number of cybersecurity incidents is on the rise despite significant investment in security measures. The existing conventional security approaches have demonstrated limited success against some of the more complex cyber-attacks. This is primarily due to the sophistication of the attacks and the availability of powerful tools. Interconnected devices such as the Internet of Things (IoT) are also increasing attack exposures due to the increase in vulnerabilities. Over the last few years, we have seen a trend moving towards embracing edge technologies to harness the power of IoT devices and 5G networks. Edge technology brings processing power closer to the… More >

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ARTICLE

A. M. Farhan^1,2,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2515-2525, 2021, DOI:10.32604/cmc.2021.014255
Abstract In this paper, we investigated the inuence of rotating half-space on the propagation of Rayleigh waves in a homogeneous isotropic, generalized thermo-elastic body, subject to the boundary conditions that the surface is traction free. In addition, it is subject to insulating thermal conduction. A general solution is obtained by using Lame’ potential’s and Hankel transform. The dispersion equations has been derived separately for two types of Rayleigh wave propagation properties by solving the equations of motion with appropriate boundary conditions. It is observed that the rotation, frequency and r exert some influence in the homogeneous isotropic medium due to propagation… More >

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ARTICLE

Shahzad Hameed¹, Qurratul-Ain Minhas¹, Sheeraz Ahmed², Shabana Habib⁴, Mohammad Kamrul Hasan³, Muhammad Islam⁵, Sheroz Khan^5,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2527-2546, 2021, DOI:10.32604/cmc.2021.013896
Abstract Flying ad hoc networks (FANETs) present a challenging environment due to the dynamic and highly mobile nature of the network. Dynamic network topology and uncertain node mobility structure of FANETs do not aim to consider only one path transmission. Several different techniques are adopted to address the issues arising in FANETs, from game theory to clustering to channel estimation and other statistical schemes. These approaches mostly employ traditional concepts for problem solutions. One of the novel approaches that provide simpler solutions to more complex problems is to use biologically inspired schemes. Several Nature-inspired schemes address cooperation and alliance which can… More >

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ARTICLE

Kangjik Kim¹, Hyunbin Kim¹, Junchul Chun¹, Mingoo Kang², Min Hong^3,*, Byungseok Min⁴
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2547-2568, 2021, DOI:10.32604/cmc.2021.014642
Abstract Physical contamination of food occurs when it comes into contact with foreign objects. Foreign objects can be introduced to food at any time during food delivery and packaging and can cause serious concerns such as broken teeth or choking. Therefore, a preventive method that can detect and remove foreign objects in advance is required. Several studies have attempted to detect defective products using deep learning networks. Because it is difficult to obtain foreign object-containing food data from industry, most studies on industrial anomaly detection have used unsupervised learning methods. This paper proposes a new method for real-time anomaly detection in… More >

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ARTICLE

Mazhar Javed Awan^1,2,*, Mohd Shafry Mohd Rahim², Haitham Nobanee^3,4,5, Ashna Munawar², Awais Yasin⁶, Azlan Mohd Zain ⁷
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2569-2583, 2021, DOI:10.32604/cmc.2021.014253
（This article belongs to this Special Issue: Artificial Intelligence and Big Data in Entrepreneurship)
Abstract Big data is the collection of large datasets from traditional and digital sources to identify trends and patterns. The quantity and variety of computer data are growing exponentially for many reasons. For example, retailers are building vast databases of customer sales activity. Organizations are working on logistics financial services, and public social media are sharing a vast quantity of sentiments related to sales price and products. Challenges of big data include volume and variety in both structured and unstructured data. In this paper, we implemented several machine learning models through Spark MLlib using PySpark, which is scalable, fast, easily integrated… More >

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ARTICLE

Gulzar Ahmad¹, Saad Alanazi², Madallah Alruwaili², Fahad Ahmad^3,6, Muhammad Adnan Khan^4,*, Sagheer Abbas¹, Nadia Tabassum⁵
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2585-2600, 2021, DOI:10.32604/cmc.2021.015080
Abstract Security is a significant issue for everyone due to new and creative ways to commit cybercrime. The Closed-Circuit Television (CCTV) systems are being installed in offices, houses, shopping malls, and on streets to protect lives. Operators monitor CCTV; however, it is difficult for a single person to monitor the actions of multiple people at one time. Consequently, there is a dire need for an automated monitoring system that detects a person with ammunition or any other harmful material Based on our research and findings of this study, we have designed a new Intelligent Ammunition Detection and Classification (IADC) system using… More >

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ARTICLE

Florin Valentin Leuciuc^1,2,*, Maria Daniela Craciun^1,2, Iulian Stefan Holubiac¹, Mazin Abed Mohammed³, Karrar Hameed Abdulkareem⁴, Gheorghe Pricop^1,2
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2601-2617, 2021, DOI:10.32604/cmc.2021.014863
（This article belongs to this Special Issue: Retrospective Big Data Analytics in Radiological Imaging for Precision Medicine)
Abstract Identifying patterns, recognition systems, prediction methods, and detection methods is a major challenge in solving different medical issues. Few categories of devices for personal and professional assessment of body composition are available. Bioelectrical impedance analyzer is a simple, safe, affordable, mobile, non-invasive, and less expensive alternative device for body composition assessment. Identifying the body composition pattern of different groups with varying age and gender is a major challenge in defining an optimal level because of the body shape, body mass, energy requirements, physical fitness, health status, and metabolic profile. Thus, this research aims to identify the statistical medical pattern recognition… More >

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Imtisal Qadeer^1,2, Muhammad Khurram Ehsan^3,*
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2619-2630, 2021, DOI:10.32604/cmc.2021.015641
（This article belongs to this Special Issue: Management of Security, Privacy and Trust of Multimedia Data in Mobile devices communication)
Abstract To secure the wireless connection between devices with low computational power has been a challenging problem due to heterogeneity in operating devices, device to device communication in Internet of Things (IoTs) and 5G wireless systems. Physical layer key generation (PLKG) tackles this secrecy problem by introducing private keys among two connecting devices through wireless medium. In this paper, relative calibration is used as a method to enhance channel reciprocity which in turn increases the performance of the key generation process. Channel reciprocity based key generation is emerged as better PLKG methodology to obtain secure wireless connection in IoTs and 5G… More >

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Rizwan Ali Naqvi¹, Muhammad Faheem Mushtaq², Natash Ali Mian³, Muhammad Adnan Khan^4,*, Atta-ur-Rahman⁵, Muhammad Ali Yousaf⁶, Muhammad Umair⁶, Rizwan Majeed⁷
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2631-2646, 2021, DOI:10.32604/cmc.2021.012167
Abstract Coronaviruses are a family of viruses that can be transmitted from one person to another. Earlier strains have only been mild viruses, but the current form, known as coronavirus disease 2019 (COVID-19), has become a deadly infection. The outbreak originated in Wuhan, China, and has since spread worldwide. The symptoms of COVID-19 include a dry cough, sore throat, fever, and nasal congestion. Antimicrobial drugs, pathogen–host interaction, and 2 weeks of isolation have been recommended for the treatment of the infection. Safe operating procedures, such as the use of face masks, hand sanitizer, handwashing with soap, and social distancing, are also… More >

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Sohan Kumar Pande¹, Sanjaya Kumar Panda², Satyabrata Das¹, Kshira Sagar Sahoo³, Ashish Kr. Luhach⁴, N. Z. Jhanjhi^5,*, Roobaea Alroobaea⁶, Sivakumar Sivanesan⁵
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2647-2663, 2021, DOI:10.32604/cmc.2021.015026
Abstract In recent years, vehicular cloud computing (VCC) has gained vast attention for providing a variety of services by creating virtual machines (VMs). These VMs use the resources that are present in modern smart vehicles. Many studies reported that some of these VMs hosted on the vehicles are overloaded, whereas others are underloaded. As a circumstance, the energy consumption of overloaded vehicles is drastically increased. On the other hand, underloaded vehicles are also drawing considerable energy in the underutilized situation. Therefore, minimizing the energy consumption of the VMs that are hosted by both overloaded and underloaded is a challenging issue in… More >

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REVIEW

Tauqeer ul Amin^1,*, Basit Shahzad¹, Fazal-e-Amin², Muhammad Shoaib²
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2665-2680, 2021, DOI:10.32604/cmc.2021.013263
（This article belongs to this Special Issue: COVID-19 impacts on Software Engineering industry and research community)
Abstract Requirements elicitation is a fundamental phase of software development in which an analyst discovers the needs of different stakeholders and transforms them into requirements. This phase is cost- and time-intensive, and a project may fail if there are excessive costs and schedule overruns. COVID-19 has affected the software industry by reducing interactions between developers and customers. Such a lack of interaction is a key reason for the failure of software projects. Projects can also fail when customers do not know precisely what they want. Furthermore, selecting the unsuitable elicitation technique can also cause project failure. The present study, therefore, aimed… More >

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Omar Fetitah¹, Ibrahim M. Almanjahie^2,3, Mohammed Kadi Attouch^1,*, Salah Khardani⁴
CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2681-2694, 2021, DOI:10.32604/cmc.2021.015469
Abstract The problem of predicting continuous scalar outcomes from functional predictors has received high levels of interest in recent years in many fields, especially in the food industry. The k-nearest neighbor (k-NN) method of Near-Infrared Reflectance (NIR) analysis is practical, relatively easy to implement, and becoming one of the most popular methods for conducting food quality based on NIR data. The k-NN is often named k nearest neighbor classifier when it is used for classifying categorical variables, while it is called k-nearest neighbor regression when it is applied for predicting noncategorical variables. The objective of this paper is to use the… More >

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