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  • Open Access

    ARTICLE

    MCMOD: The Multi-Category Large-Scale Dataset for Maritime Object Detection

    Zihao Sun1,*, Xiao Hu2, Yining Qi2, Yongfeng Huang2, Songbin Li3

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1657-1669, 2023, DOI:10.32604/cmc.2023.036558

    Abstract The marine environment is becoming increasingly complex due to the various marine vehicles, and the diversity of maritime objects poses a challenge to marine environmental governance. Maritime object detection technology plays an important role in this segment. In the field of computer vision, there is no sufficiently comprehensive public dataset for maritime objects in the contrast to the automotive application domain. The existing maritime datasets either have no bounding boxes (which are made for object classification) or cover limited varieties of maritime objects. To fulfil the vacancy, this paper proposed the Multi-Category Large-Scale Dataset for Maritime Object Detection (MCMOD) which… More >

  • Open Access

    ARTICLE

    An Efficient EMD-Based Reversible Data Hiding Technique Using Dual Stego Images

    Ahmad A. Mohammad*

    CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1139-1156, 2023, DOI:10.32604/cmc.2023.035964

    Abstract Exploiting modification direction (EMD) based data hiding techniques (DHTs) provide moderate data hiding capacity and high-quality stego images. The overflow problem and the cyclic nature of the extraction function essentially hinder their application in several fields in which reversibility is necessary. Thus far, the few EMD reversible DHTs are complex and numerically demanding. This paper presents a novel EMD-based reversible DHT using dual-image. Two novel 2 × 4 modification lookup tables are introduced, replacing the reference matrix used in similar techniques and eliminating the numerically demanding search step in similar techniques. In the embedding step, one of the modification tables modifies a… More >

  • Open Access

    ARTICLE

    Stage-Wise Categorization and Prediction of Diabetic Retinopathy Using Ensemble Learning and 2D-CNN

    N. M. Balamurugan1,*, K. Maithili2, T. K. S. Rathish Babu3, M. Adimoolam4

    Intelligent Automation & Soft Computing, Vol.36, No.1, pp. 499-514, 2023, DOI:10.32604/iasc.2023.031661

    Abstract Diabetic Eye Disease (DED) is a fundamental cause of blindness in human beings in the medical world. Different techniques are proposed to forecast and examine the stages in Prognostication of Diabetic Retinopathy (DR). The Machine Learning (ML) and the Deep Learning (DL) algorithms are the predominant techniques to project and explore the images of DR. Even though some solutions were adapted to challenge the cause of DR disease, still there should be an efficient and accurate DR prediction to be adapted to refine its performance. In this work, a hybrid technique was proposed for classification and prediction of DR. The… More >

  • Open Access

    ARTICLE

    The Effect of Sleep on Workplace Interpersonal Conflict: The Mediating Role of Ego Depletion

    Mei Chen, Haoran Dong, Yang Luo, Hui Meng*

    International Journal of Mental Health Promotion, Vol.24, No.6, pp. 901-916, 2022, DOI:10.32604/ijmhp.2022.020006

    Abstract This study aimed to investigate the relationship between sleep and workplace interpersonal conflict and the role of ego depletion as the mediating mechanism. A survey was conducted daily for two weeks using an experience sampling method. A sample of 79 employees from the East Coast of China was collected. A multilevel regression analysis was conducted to test the proposed hypotheses. Results indicated that higher sleep quantity was associated with lower daily ego depletion at noon and lower workplace interpersonal conflict. Moreover, ego depletion mediated the effects of sleep quantity on workplace interpersonal conflict. The findings identified the adverse effects of… More >

  • Open Access

    ARTICLE

    Refined Sparse Representation Based Similar Category Image Retrieval

    Xin Wang, Zhilin Zhu, Zhen Hua*

    CMES-Computer Modeling in Engineering & Sciences, Vol.134, No.2, pp. 893-908, 2023, DOI:10.32604/cmes.2022.021287

    Abstract Given one specific image, it would be quite significant if humanity could simply retrieve all those pictures that fall into a similar category of images. However, traditional methods are inclined to achieve high-quality retrieval by utilizing adequate learning instances, ignoring the extraction of the image’s essential information which leads to difficulty in the retrieval of similar category images just using one reference image. Aiming to solve this problem above, we proposed in this paper one refined sparse representation based similar category image retrieval model. On the one hand, saliency detection and multi-level decomposition could contribute to taking salient and spatial… More >

  • Open Access

    ARTICLE

    Reducing the Range of Cancer Risk on BI-RADS 4 Subcategories via Mathematical Modelling

    Nezihal Gokbulut1,2, Evren Hincal1,2,*, Hasan Besim3, Bilgen Kaymakamzade1,2

    CMES-Computer Modeling in Engineering & Sciences, Vol.133, No.1, pp. 93-109, 2022, DOI:10.32604/cmes.2022.019782

    Abstract Breast Imaging Reporting and Data System, also known as BI-RADS is a universal system used by radiologists and doctors. It constructs a comprehensive language for the diagnosis of breast cancer. BI-RADS 4 category has a wide range of cancer risk since it is divided into 3 categories. Mathematical models play an important role in the diagnosis and treatment of cancer. In this study, data of 42 BI-RADS 4 patients taken from the Center for Breast Health, Near East University Hospital is utilized. Regarding the analysis, a mathematical model is constructed by dividing the population into 4 compartments. Sensitivity analysis is… More >

  • Open Access

    ARTICLE

    Regorafenib-Induced Hand–Foot Skin Reaction Is More Severe on the Feet Than on the Hands

    Yuma Nonomiya*, Takashi Yokokawa, Kazuyoshi Kawakami, Kazuo Kobayashi, Takeshi Aoyama, Tomomi Takiguchi, Takahito Sugisaki, Kenichi Suzuki, Mitsukuni Suenaga, Takeru Wakatsuki, Kensei Yamaguchi, Yoshikazu Sugimoto*, Toshihiro Hama

    Oncology Research, Vol.27, No.5, pp. 551-556, 2019, DOI:10.3727/096504018X15291727589740

    Abstract Regorafenib is a multikinase inhibitor for the treatment of metastatic colorectal cancer. Regorafenib-induced hand–foot skin reaction (HFSR) is a common side effect during treatment. The reported frequency of HFSR was 80% (grade 3: 28%) in the Japanese subpopulation in the CORRECT trial; however, more detailed data regarding HFSR in terms of onset and sites of susceptibility are unclear. Additionally, the risk factors for regorafenib-induced severe HFSR are unknown. The aim of this study was to compare HFSR between the hands and feet and identify preexisting risk factors for severe HFSR in Japanese patients receiving regorafenib. We retrospectively examined the onset… More >

  • Open Access

    ARTICLE

    P-ROCK: A Sustainable Clustering Algorithm for Large Categorical Datasets

    Ayman Altameem1, Ramesh Chandra Poonia2, Ankit Kumar3, Linesh Raja4, Abdul Khader Jilani Saudagar5,*

    Intelligent Automation & Soft Computing, Vol.35, No.1, pp. 553-566, 2023, DOI:10.32604/iasc.2023.027579

    Abstract Data clustering is crucial when it comes to data processing and analytics. The new clustering method overcomes the challenge of evaluating and extracting data from big data. Numerical or categorical data can be grouped. Existing clustering methods favor numerical data clustering and ignore categorical data clustering. Until recently, the only way to cluster categorical data was to convert it to a numeric representation and then cluster it using current numeric clustering methods. However, these algorithms could not use the concept of categorical data for clustering. Following that, suggestions for expanding traditional categorical data processing methods were made. In addition to… More >

  • Open Access

    ARTICLE

    Fluid Analysis and Structure Optimization of Impeller Based on Surrogate Model

    Huanwei Xu*, Wenzhang Wei, Hanjin He, Xuerui Yang

    CMES-Computer Modeling in Engineering & Sciences, Vol.132, No.1, pp. 173-199, 2022, DOI:10.32604/cmes.2022.019424

    Abstract The surrogate model technology has a good performance in solving black-box optimization problems, which is widely used in multi-domain engineering optimization problems. The adaptive surrogate model is the mainstream research direction of surrogate model technology, which can realize model fitting and global optimization of engineering problems by infilling criteria. Based on the idea of the adaptive surrogate model, this paper proposes an efficient global optimization algorithm based on the local remodeling method (EGO-LR), which aims at improving the accuracy and optimization efficiency of the model. The proposed algorithm firstly constructs the expectation improvement (EI) function in the local area and… More >

  • Open Access

    ARTICLE

    Medical Image Demosaicing Based Design of Newton Gregory Interpolation Algorithm

    E. P. Kannan1,*, S. S. Vinsley2, T. V. Chithra3

    Intelligent Automation & Soft Computing, Vol.34, No.3, pp. 1675-1691, 2022, DOI:10.32604/iasc.2022.022707

    Abstract In this paper, Field-Programmable Gate Array (FPGA) implementation-based image demosaicing is carried out. The Newton Gregory interpolation algorithm is designed based on FPGA frame work. Interpolation is the method of assessing the value of a function for any in-between value of self-regulating variable, whereas the method of computing the value of the function outside the specified range is named extrapolation. The natural images are collected from Kodak image database and medical images are collected from UPOL (University of Phoenix Online) database. The proposed algorithm is executed on using Xilinx ISE (Integrated Synthesis Environment) Design Suite 14.2 and is confirmed on… More >

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