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  • Open Access

    ARTICLE

    RFID Adaption in Healthcare Organizations: An Integrative Framework

    Ahed Abugabah1,*, Louis Sanzogni2, Luke Houghton2, Ahmad Ali AlZubi3, Alaa Abuqabbeh4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1335-1348, 2022, DOI:10.32604/cmc.2022.019097

    Abstract Radio frequency identification (RFID), also known as electronic label technology, is a non-contact automated identification technology that recognizes the target object and extracts relevant data and critical characteristics using radio frequency signals. Medical equipment information management is an important part of the construction of a modern hospital, as it is linked to the degree of diagnosis and care, as well as the hospital’s benefits and growth. The aim of this study is to create an integrated view of a theoretical framework to identify factors that influence RFID adoption in healthcare, as well as to conduct an empirical review of the… More >

  • Open Access

    ARTICLE

    Model Identification and Control of Evapotranspiration for Irrigation Water Optimization

    Wafa Difallah1,2,*, Fateh Bounaama2, Belkacem Draoui2, Khelifa Benahmed3, Abdelkader Laaboudi4

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1749-1767, 2022, DOI:10.32604/cmc.2022.019071

    Abstract Water conservation starts from rationalizing irrigation, as it is the largest consumer of this vital source. Following the critical and urgent nature of this issue, several works have been proposed. The idea of most researchers is to develop irrigation management systems to meet the water needs of plants with optimal use of this resource. In fact, irrigation water requirement is only the amount of water that must be applied to compensate the evapotranspiration loss. Penman-Monteith equation is the most common formula to evaluate reference evapotranspiration, but it requires many factors that cannot be available in many cases. This leads to… More >

  • Open Access

    ARTICLE

    Utilization of Machine Learning Methods in Modeling Specific Heat Capacity of Nanofluids

    Mamdouh El Haj Assad1, Ibrahim Mahariq2, Raymond Ghandour2, Mohammad Alhuyi Nazari3, Thabet Abdeljawad4,5,6,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 361-374, 2022, DOI:10.32604/cmc.2022.019048

    Abstract Nanofluids are extensively applied in various heat transfer mediums for improving their heat transfer characteristics and hence their performance. Specific heat capacity of nanofluids, as one of the thermophysical properties, performs principal role in heat transfer of thermal mediums utilizing nanofluids. In this regard, different studies have been carried out to investigate the influential factors on nanofluids specific heat. Moreover, several regression models based on correlations or artificial intelligence have been developed for forecasting this property of nanofluids. In the current review paper, influential parameters on the specific heat capacity of nanofluids are introduced. Afterwards, the proposed models for their… More >

  • Open Access

    ARTICLE

    Classification of Citrus Plant Diseases Using Deep Transfer Learning

    Muhammad Zia Ur Rehman1, Fawad Ahmed1, Muhammad Attique Khan2, Usman Tariq3, Sajjad Shaukat Jamal4, Jawad Ahmad5,*, Iqtadar Hussain6

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1401-1417, 2022, DOI:10.32604/cmc.2022.019046

    Abstract In recent years, the field of deep learning has played an important role towards automatic detection and classification of diseases in vegetables and fruits. This in turn has helped in improving the quality and production of vegetables and fruits. Citrus fruits are well known for their taste and nutritional values. They are one of the natural and well known sources of vitamin C and planted worldwide. There are several diseases which severely affect the quality and yield of citrus fruits. In this paper, a new deep learning based technique is proposed for citrus disease classification. Two different pre-trained deep learning… More >

  • Open Access

    ARTICLE

    An Eigenspace Method for Detecting Space-Time Disease Clusters with Unknown Population-Data

    Sami Ullah1,*, Nurul Hidayah Mohd Nor1, Hanita Daud1, Nooraini Zainuddin1, Hadi Fanaee-T2, Alamgir Khalil3

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1945-1953, 2022, DOI:10.32604/cmc.2022.019029

    Abstract Space-time disease cluster detection assists in conducting disease surveillance and implementing control strategies. The state-of-the-art method for this kind of problem is the Space-time Scan Statistics (SaTScan) which has limitations for non-traditional/non-clinical data sources due to its parametric model assumptions such as Poisson or Gaussian counts. Addressing this problem, an Eigenspace-based method called Multi-EigenSpot has recently been proposed as a nonparametric solution. However, it is based on the population counts data which are not always available in the least developed countries. In addition, the population counts are difficult to approximate for some surveillance data such as emergency department visits and… More >

  • Open Access

    ARTICLE

    A Modified Search and Rescue Optimization Based Node Localization Technique in WSN

    Suma Sira Jacob1,*, K. Muthumayil2, M. Kavitha3, Lijo Jacob Varghese4, M. Ilayaraja5, Irina V. Pustokhina6, Denis A. Pustokhin7

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1229-1245, 2022, DOI:10.32604/cmc.2022.019019

    Abstract Wireless sensor network (WSN) is an emerging technology which find useful in several application areas such as healthcare, environmental monitoring, border surveillance, etc. Several issues that exist in the designing of WSN are node localization, coverage, energy efficiency, security, and so on. In spite of the issues, node localization is considered an important issue, which intends to calculate the coordinate points of unknown nodes with the assistance of anchors. The efficiency of the WSN can be considerably influenced by the node localization accuracy. Therefore, this paper presents a modified search and rescue optimization based node localization technique (MSRO-NLT) for WSN.… More >

  • Open Access

    ARTICLE

    Enhancing the Robustness of Visual Object Tracking via Style Transfer

    Abdollah Amirkhani1,*, Amir Hossein Barshooi1, Amir Ebrahimi2

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 981-997, 2022, DOI:10.32604/cmc.2022.019001

    Abstract The performance and accuracy of computer vision systems are affected by noise in different forms. Although numerous solutions and algorithms have been presented for dealing with every type of noise, a comprehensive technique that can cover all the diverse noises and mitigate their damaging effects on the performance and precision of various systems is still missing. In this paper, we have focused on the stability and robustness of one computer vision branch (i.e., visual object tracking). We have demonstrated that, without imposing a heavy computational load on a model or changing its algorithms, the drop in the performance and accuracy… More >

  • Open Access

    ARTICLE

    An Ensemble Learning Based Approach for Detecting and Tracking COVID19 Rumors

    Sultan Noman Qasem1,2, Mohammed Al-Sarem3,4, Faisal Saeed3,*

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1721-1747, 2022, DOI:10.32604/cmc.2022.018972

    Abstract Rumors regarding epidemic diseases such as COVID 19, medicines and treatments, diagnostic methods and public emergencies can have harmful impacts on health and political, social and other aspects of people’s lives, especially during emergency situations and health crises. With huge amounts of content being posted to social media every second during these situations, it becomes very difficult to detect fake news (rumors) that poses threats to the stability and sustainability of the healthcare sector. A rumor is defined as a statement for which truthfulness has not been verified. During COVID 19, people found difficulty in obtaining the most truthful news… More >

  • Open Access

    ARTICLE

    Ambiguity Resolution in Direction of Arrival Estimation with Linear Antenna Arrays Using Differential Geometry

    Alamgir Safi1, Muhammad Asghar Khan2,*, Fahad Algarni3, Muhammad Adnan Aziz1, M. Irfan Uddin4, Insaf Ullah2, Tanweer Ahmad Cheema1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 581-599, 2022, DOI:10.32604/cmc.2022.018963

    Abstract Linear antenna arrays (LAs) can be used to accurately predict the direction of arrival (DOAs) of various targets of interest in a given area. However, under certain conditions, LA suffers from the problem of ambiguities among the angles of targets, which may result in misinterpretation of such targets. In order to cope up with such ambiguities, various techniques have been proposed. Unfortunately, none of them fully resolved such a problem because of rank deficiency and high computational cost. We aimed to resolve such a problem by proposing an algorithm using differential geometry. The proposed algorithm uses a specially designed doublet… More >

  • Open Access

    ARTICLE

    Network Analysis for Projects with High Risk Levels in Uncertain Environments

    Mohamed Abdel-Basset1, Asmaa Atef1, Mohamed Abouhawwash2,3, Yunyoung Nam4,*, Nabil M. AbdelAziz1

    CMC-Computers, Materials & Continua, Vol.70, No.1, pp. 1281-1296, 2022, DOI:10.32604/cmc.2022.018947

    Abstract The critical path method is one of the oldest and most important techniques used for planning and scheduling projects. The main objective of project management science is to determine the critical path through a network representation of projects. The critical path through a network can be determined by many algorithms and is useful for managing, monitoring, and controlling the time and cost of an entire project. The essential problem in this case is that activity durations are uncertain; time presents considerable uncertainty because the time of an activity is not always easily or accurately estimated. This issue increases the need… More >

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