Jin Han¹, Cheng Wang², Jie Miao³, Mingxin Lu³, Yingchun Wang⁴, Jin Shi^3,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2645-2654, 2021, DOI:10.32604/cmc.2021.014371

Abstract With the development of information technology, cloud computing technology has brought many conveniences to all aspects of work and life. With the continuous promotion, popularization and vigorous development of e-government and e-commerce, the number of documents in electronic form is getting larger and larger. Electronic document is an indispensable main tool and real record of e-government and business activities. How to scientifically and effectively manage electronic documents? This is an important issue faced by governments and enterprises in improving management efficiency, protecting state secrets or business secrets, and reducing management costs. This paper discusses the application of cloud computing technology… More >

Muhammad Yahya Saeed¹, Muhammad Awais¹, Muhammad Younas¹, Muhammad Arif Shah^2,*, Atif Khan³, M. Irfan Uddin⁴, Marwan Mahmoud⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2409-2423, 2021, DOI:10.32604/cmc.2021.014330

Abstract Text Summarization is an essential area in text mining, which has procedures for text extraction. In natural language processing, text summarization maps the documents to a representative set of descriptive words. Therefore, the objective of text extraction is to attain reduced expressive contents from the text documents. Text summarization has two main areas such as abstractive, and extractive summarization. Extractive text summarization has further two approaches, in which the first approach applies the sentence score algorithm, and the second approach follows the word embedding principles. All such text extractions have limitations in providing the basic theme of the underlying documents.… More >

R. Alshenawy^1,2, Mohamed A. H. Sabry³, Ehab M. Almetwally^4,*, Hisham M. Elomngy²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2973-2995, 2021, DOI:10.32604/cmc.2021.014289

Abstract Maximum product spacing for stress–strength model based on progressive Type-II hybrid censored samples with different cases has been obtained. This paper deals with estimation of the stress strength reliability model R = P(Y < X) when the stress and strength are two independent exponentiated Gumbel distribution random variables with different shape parameters but having the same scale parameter. The stress–strength reliability model is estimated under progressive Type-II hybrid censoring samples. Two progressive Type-II hybrid censoring schemes were used, Case I: A sample size of stress is the equal sample size of strength, and same time of hybrid censoring, the product… More >

Sandeep Kumar¹, Teekam Singh^1,2, Kamaleldin Abodayeh³, Wasfi Shatanawi^3,4,5,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2343-2357, 2021, DOI:10.32604/cmc.2021.014224

Abstract This study presents an inventory model for imperfect products with depletion in ordering costs and constant lead time where the price discount in the backorder is permitted. The imperfect products are refused or modified or if they reached to the customer, returned and thus some extra costs are experienced. Lately some of the researchers explicitly present on the significant association between size of lot and quality imperfection. In practical situations, the unsatisfied demands increase the period of lead time and decrease the backorders. To control customers' problems and losses, the supplier provides a price discount in backorders during shortages. Also,… More >

Norah Saleh Alghamdi^1,*, Mohammad Ayoub Khan²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2509-2524, 2021, DOI:10.32604/cmc.2021.014180

Abstract Wireless sensor networks (WSNs) and Internet of Things (IoT) have gained more popularity in recent years as an underlying infrastructure for connected devices and sensors in smart cities. The data generated from these sensors are used by smart cities to strengthen their infrastructure, utilities, and public services. WSNs are suitable for long periods of data acquisition in smart cities. To make the networks of smart cities more reliable for sensitive information, the blockchain mechanism has been proposed. The key issues and challenges of WSNs in smart cities is efficiently scheduling the resources; leading to extending the network lifetime of sensors.… More >

Hyun Kyu Shin¹, Si Woon Lee², Goo Pyo Hong³, Lee Sael², Sang Hyo Lee⁴, Ha Young Kim^5,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2493-2507, 2021, DOI:10.32604/cmc.2021.014170

Abstract The demand for defect diagnoses is gradually gaining ground owing to the growing necessity to implement safe inspection methods to ensure the durability and quality of structures. However, conventional manpower-based inspection methods not only incur considerable cost and time, but also cause frequent disputes regarding defects owing to poor inspections. Therefore, the demand for an effective and efficient defect-diagnosis model for concrete structures is imminent, as the reduction in maintenance costs is significant from a long-term perspective. Thus, this paper proposes a deep learning-based image object-identification method to detect the defects of paint peeling, leakage peeling, and leakage traces that… More >

Sushil Kumar Singh¹, Yi Pan², Jong Hyuk Park^1,*

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2905-2922, 2021, DOI:10.32604/cmc.2021.014151

Abstract For the past few decades, the Internet of Things (IoT) has been one of the main pillars wielding significant impact on various advanced industrial applications, including smart energy, smart manufacturing, and others. These applications are related to industrial plants, automation, and e-healthcare fields. IoT applications have several issues related to developing, planning, and managing the system. Therefore, IoT is transforming into G-IoT (Green Internet of Things), which realizes energy efficiency. It provides high power efficiency, enhances communication and networking. Nonetheless, this paradigm did not resolve all smart applications’ challenges in edge infrastructure, such as communication bandwidth, centralization, security, and privacy.… More >

Saleh Albahli¹, Hafiz Tayyab Rauf^2,*, Muhammad Arif³, Md Tabrez Nafis⁴, Abdulelah Algosaibi⁵

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3139-3149, 2021, DOI:10.32604/cmc.2021.014134

Abstract With the increasing demand for doctors in chest related diseases, there is a 15% performance gap every five years. If this gap is not filled with effective chest disease detection automation, the healthcare industry may face unfavorable consequences. There are only several studies that targeted X-ray images of cardiothoracic diseases. Most of the studies only targeted a single disease, which is inadequate. Although some related studies have provided an identification framework for all classes, the results are not encouraging due to a lack of data and imbalanced data issues. This research provides a significant contribution to Generative Adversarial Network (GAN)… More >

Saleh Albahli¹, Anadil Alsaqabi¹, Fatimah Aldhubayi¹, Hafiz Tayyab Rauf^2,*, Muhammad Arif³, Mazin Abed Mohammed⁴

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2317-2341, 2021, DOI:10.32604/cmc.2021.014113

Abstract Crimes are expected to rise with an increase in population and the rising gap between society’s income levels. Crimes contribute to a significant portion of the socioeconomic loss to any society, not only through its indirect damage to the social fabric and peace but also the more direct negative impacts on the economy, social parameters, and reputation of a nation. Policing and other preventive resources are limited and have to be utilized. The conventional methods are being superseded by more modern approaches of machine learning algorithms capable of making predictions where the relationships between the features and the outcomes are… More >

Usman Shahzad^1,2,*, Ishfaq Ahmad¹, Ibrahim Mufrah Almanjahie^3,4, Nadia H. Al Noor⁵, Muhammad Hanif²

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 3013-3028, 2021, DOI:10.32604/cmc.2021.014101

Abstract Variance is one of the most important measures of descriptive statistics and commonly used for statistical analysis. The traditional second-order central moment based variance estimation is a widely utilized methodology. However, traditional variance estimator is highly affected in the presence of extreme values. So this paper initially, proposes two classes of calibration estimators based on an adaptation of the estimators recently proposed by Koyuncu and then presents a new class of L-Moments based calibration variance estimators utilizing L-Moments characteristics (L-location, L-scale, L-CV) and auxiliary information. It is demonstrated that the proposed L-Moments based calibration variance estimators are more efficient than… More >