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  • Open Access

    ARTICLE

    Adaptive Noise Detector and Partition Filter for Image Restoration

    Cong Lin1, Chenghao Qiu1, Can Wu1, Siling Feng1,*, Mengxing Huang1,2,*

    CMC-Computers, Materials & Continua, Vol.75, No.2, pp. 4317-4340, 2023, DOI:10.32604/cmc.2023.036249

    Abstract The random-value impulse noise (RVIN) detection approach in image denoising, which is dependent on manually defined detection thresholds or local window information, does not have strong generalization performance and cannot successfully cope with damaged pictures with high noise levels. The fusion of the K-means clustering approach in the noise detection stage is reviewed in this research, and the internal relationship between the flat region and the detail area of the damaged picture is thoroughly explored to suggest an unique two-stage method for gray image denoising. Based on the concept of pixel clustering and grouping, all pixels in the damaged picture… More >

  • Open Access

    ARTICLE

    Data Analytics on Unpredictable Pregnancy Data Records Using Ensemble Neuro-Fuzzy Techniques

    C. Vairavel1,*, N. S. Nithya2

    Computer Systems Science and Engineering, Vol.46, No.2, pp. 2159-2175, 2023, DOI:10.32604/csse.2023.036598

    Abstract The immune system goes through a profound transformation during pregnancy, and certain unexpected maternal complications have been correlated to this transition. The ability to correctly examine, diagnoses, and predict pregnancy-hastened diseases via the available big data is a delicate problem since the range of information continuously increases and is scalable. Many approaches for disease diagnosis/classification have been established with the use of data mining concepts. However, such methods do not provide an appropriate classification/diagnosis model. Furthermore, single learning approaches are used to create the bulk of these systems. Classification issues may be made more accurate by combining predictions from many… More >

  • Open Access

    ARTICLE

    End-to-End 2D Convolutional Neural Network Architecture for Lung Nodule Identification and Abnormal Detection in Cloud

    Safdar Ali1, Saad Asad1, Zeeshan Asghar1, Atif Ali1, Dohyeun Kim2,*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 461-475, 2023, DOI:10.32604/cmc.2023.035672

    Abstract The extent of the peril associated with cancer can be perceived from the lack of treatment, ineffective early diagnosis techniques, and most importantly its fatality rate. Globally, cancer is the second leading cause of death and among over a hundred types of cancer; lung cancer is the second most common type of cancer as well as the leading cause of cancer-related deaths. Anyhow, an accurate lung cancer diagnosis in a timely manner can elevate the likelihood of survival by a noticeable margin and medical imaging is a prevalent manner of cancer diagnosis since it is easily accessible to people around… More >

  • Open Access

    ARTICLE

    Detection of Abnormal Network Traffic Using Bidirectional Long Short-Term Memory

    Nga Nguyen Thi Thanh, Quang H. Nguyen*

    Computer Systems Science and Engineering, Vol.46, No.1, pp. 491-504, 2023, DOI:10.32604/csse.2023.032107

    Abstract Nowadays, web systems and servers are constantly at great risk from cyberattacks. This paper proposes a novel approach to detecting abnormal network traffic using a bidirectional long short-term memory (LSTM) network in combination with the ensemble learning technique. First, the binary classification module was used to detect the current abnormal flow. Then, the abnormal flows were fed into the multilayer classification module to identify the specific type of flow. In this research, a deep learning bidirectional LSTM model, in combination with the convolutional neural network and attention technique, was deployed to identify a specific attack. To solve the real-time intrusion-detecting… More >

  • Open Access

    ARTICLE

    Selection and Validation of Reference Genes for Normalization of RT-qPCR Analysis in Developing or Abiotic-Stressed Tissues of Loquat (Eriobotrya japonica)

    Shoukai Lin1,2,#, Shichang Xu1,#, Liyan Huang1, Fuxiang Qiu1, Yihong Zheng1, Qionghao Liu1, Shiwei Ma1,2, Bisha Wu1,2, Jincheng Wu1,2,*

    Phyton-International Journal of Experimental Botany, Vol.92, No.4, pp. 1185-1201, 2023, DOI:10.32604/phyton.2023.026752

    Abstract Loquat (Eriobotrya japonica Lindl.) is a subtropical evergreen fruit tree that produces fruits with abundant nutrients and medicinal components. Confirming suitable reference genes for a set of loquat samples before qRT-PCR experiments is essential for the accurate quantification of gene expression. In this study, eight candidate reference genes were selected from our previously published RNA-seq data, and primers for each candidate reference gene were designed and evaluated. The Cq values of the candidate reference genes were calculated by RT-qPCR in 31 different loquat samples, including 12 subgroups of developing or abiotic-stressed tissues. Different combinations of stable reference genes were screened… More >

  • Open Access

    REVIEW

    Current Perspectives on Umbilical Cord Abnormalities Including Blood Flow Parameters Based on Ultrasound Observations

    Xue Song1,2, Cun Liu2, Jingying Wang1,*, Xinglian Yang1, Mingrui Li1

    Molecular & Cellular Biomechanics, Vol.19, No.4, pp. 209-219, 2022, DOI:10.32604/mcb.2022.026082

    Abstract The umbilical cord is a vital structure between the fetus and placenta for the growth and well-being of the fetus. Although the umbilical cord may be the only organ that dies at the beginning of life, it is one of the most important parts of the feta-placental unit and plays a role in determining how life begins. In general, the prenatal examination of the umbilical cord is limited to the observation of the number of vessels and the evaluation of umbilical artery blood flow parameters. Pathologists have done more research on the morphological characteristics of the umbilical cord and linked… More >

  • Open Access

    ARTICLE

    (α, γ)-Anti-Multi-Fuzzy Subgroups and Some of Its Properties

    Memet Şahin1, Vakkas Uluçay2, S. A. Edalatpanah3,*, Fayza Abdel Aziz Elsebaee4, Hamiden Abd El-Wahed Khalifa5

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 3221-3229, 2023, DOI:10.32604/cmc.2023.033006

    Abstract Recently, fuzzy multi-sets have come to the forefront of scientists’ interest and have been used in algebraic structures such as multi-groups, multi-rings, anti-fuzzy multigroup and (α, γ)-anti-fuzzy subgroups. In this paper, we first summarize the knowledge about the algebraic structure of fuzzy multi-sets such as (α, γ)-anti-multi-fuzzy subgroups. In a way, the notion of anti-fuzzy multigroup is an application of anti-fuzzy multi sets to the theory of group. The concept of anti-fuzzy multigroup is a complement of an algebraic structure of a fuzzy multi set that generalizes both the theories of classical group and fuzzy group. The aim of this… More >

  • Open Access

    ARTICLE

    Developing a Secure Framework Using Feature Selection and Attack Detection Technique

    Mahima Dahiya*, Nitin Nitin

    CMC-Computers, Materials & Continua, Vol.74, No.2, pp. 4183-4201, 2023, DOI:10.32604/cmc.2023.032430

    Abstract Intrusion detection is critical to guaranteeing the safety of the data in the network. Even though, since Internet commerce has grown at a breakneck pace, network traffic kinds are rising daily, and network behavior characteristics are becoming increasingly complicated, posing significant hurdles to intrusion detection. The challenges in terms of false positives, false negatives, low detection accuracy, high running time, adversarial attacks, uncertain attacks, etc. lead to insecure Intrusion Detection System (IDS). To offset the existing challenge, the work has developed a secure Data Mining Intrusion detection system (DataMIDS) framework using Functional Perturbation (FP) feature selection and Bengio Nesterov Momentum-based… More >

  • Open Access

    ARTICLE

    Psychological Support for Public-Funded Normal Students Engaged in Teaching Profession

    Shize Zhi1,2,*

    International Journal of Mental Health Promotion, Vol.24, No.6, pp. 883-900, 2022, DOI:10.32604/ijmhp.2022.022536

    Abstract Among primary and secondary school teachers in China, 70% of teachers believe facing more significant occupational pressure. 63.8% of teachers clearly stated that occupational stress had caused a tremendous impact on them. And this has had adverse effects on them, such as mental, physical, and personal development. This paper studies the group of public-funded regular students from the perspective of psychological support. This paper uses the SCL-90 form to investigate the professional psychology of teachers for the psychological support of public-funded regular students engaged in the teaching profession. And it conducts a survey on the curriculum setting and satisfaction of… More >

  • Open Access

    ARTICLE

    GRU-based Buzzer Ensemble for Abnormal Detection in Industrial Control Systems

    Hyo-Seok Kim1, Chang-Gyoon Lim2, Sang-Joon Lee3, Yong-Min Kim4,*

    CMC-Computers, Materials & Continua, Vol.74, No.1, pp. 1749-1763, 2023, DOI:10.32604/cmc.2023.026708

    Abstract Recently, Industrial Control Systems (ICSs) have been changing from a closed environment to an open environment because of the expansion of digital transformation, smart factories, and Industrial Internet of Things (IIoT). Since security accidents that occur in ICSs can cause national confusion and human casualties, research on detecting abnormalities by using normal operation data learning is being actively conducted. The single technique proposed by existing studies does not detect abnormalities well or provide satisfactory results. In this paper, we propose a GRU-based Buzzer Ensemble for Abnormal Detection (GBE-AD) model for detecting anomalies in industrial control systems to ensure rapid response… More >

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