K. Kalyani¹, Sara A Althubiti², Mohammed Altaf Ahmed³, E. Laxmi Lydia⁴, Seifedine Kadry⁵, Neunggyu Han⁶, Yunyoung Nam^6,*

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 149-164, 2023, DOI:10.32604/cmc.2023.033005 - 06 February 2023

Abstract Melanoma is a skin disease with high mortality rate while early diagnoses of the disease can increase the survival chances of patients. It is challenging to automatically diagnose melanoma from dermoscopic skin samples. Computer-Aided Diagnostic (CAD) tool saves time and effort in diagnosing melanoma compared to existing medical approaches. In this background, there is a need exists to design an automated classification model for melanoma that can utilize deep and rich feature datasets of an image for disease classification. The current study develops an Intelligent Arithmetic Optimization with Ensemble Deep Transfer Learning Based Melanoma Classification… More >

Dong-Wook Kim¹, Gun-Yoon Shin¹, Myung-Mook Han^2,*

Computer Systems Science and Engineering, Vol.46, No.1, pp. 153-164, 2023, DOI:10.32604/csse.2023.034589 - 20 January 2023

Abstract Unlike external attacks, insider threats arise from legitimate users who belong to the organization. These individuals may be a potential threat for hostile behavior depending on their motives. For insider detection, many intrusion detection systems learn and prevent known scenarios, but because malicious behavior has similar patterns to normal behavior, in reality, these systems can be evaded. Furthermore, because insider threats share a feature space similar to normal behavior, identifying them by detecting anomalies has limitations. This study proposes an improved anomaly detection methodology for insider threats that occur in cybersecurity in which a discrete… More >

Lilia Oreto^1,*, Giuseppe Mandraffino², Paolo Ciliberti³, Teresa P. Santangelo⁴, Placido Romeo⁵, Antonio Celona⁵, Placido Gitto¹, Lorenzo Galletti³, Fiore S. Iorio³, Alfredo Di Pino¹, Aurelio Secinaro⁴, Paolo Guccione³, Robert H. Anderson⁶, Salvatore Agati¹

Congenital Heart Disease, Vol.18, No.1, pp. 97-111, 2023, DOI:10.32604/chd.2022.023619 - 09 January 2023

Abstract Aims: Evidence is emerging that, in the setting of isomerism, the atrial and bronchial arrangement are not always concordant, nor are these patterns always harmonious with the arrangement of the abdominal organs. We aimed to evaluate the concordance between these features in a cohort of patients with cardiac malformations in the setting of known isomerism, seeking to determine whether it was feasible to assess complexity on this basis, in this regard taking note of the potential value of bronchial as opposed to appendage morphology. Methods and Results: We studied 78 patients known to have isomerism of the… More > Graphic Abstract

Feilu Hang¹, Wei Guo¹, Hexiong Chen¹, Linjiang Xie¹, Chenghao Zhou^2,*, Yao Liu²

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 517-529, 2023, DOI:10.32604/cmes.2023.025774 - 05 January 2023

Abstract Modern large-scale enterprise systems produce large volumes of logs that record detailed system runtime status and key events at key points. These logs are valuable for analyzing performance issues and understanding the status of the system. Anomaly detection plays an important role in service management and system maintenance, and guarantees the reliability and security of online systems. Logs are universal semi-structured data, which causes difficulties for traditional manual detection and pattern-matching algorithms. While some deep learning algorithms utilize neural networks to detect anomalies, these approaches have an over-reliance on manually designed features, resulting in the… More >

Ziwei Liu¹, Xinwei Yue^1,*, Shuo Chen¹, Xuliang Liu², Yafei Wang¹, Wanwei Tang³

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 767-785, 2023, DOI:10.32604/cmes.2023.025300 - 05 January 2023

Abstract Hardware impairments (HI) are always present in low-cost wireless devices. This paper investigates the outage behaviors of intelligent reflecting surface (IRS) assisted non-orthogonal multiple access (NOMA) networks by taking into account the impact of HI. Specifically, we derive the approximate and asymptotic expressions of the outage probability for the IRS-NOMA-HI networks. Based on the asymptotic results, the diversity orders under perfect self-interference cancellation and imperfect self-interference cancellation scenarios are obtained to evaluate the performance of the considered network. In addition, the system throughput of IRS-NOMA-HI is discussed in delay-limited mode. The obtained results are provided More >

Yanwen Lu^1,#, Wenliang Ma^1,#, Xiang Dong^1,#, Mackenzie Brown², Tong Lu^3,*, Weidong Gan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 347-362, 2023, DOI:10.32604/cmes.2023.024909 - 05 January 2023

Abstract This study aims to apply ResNet-18 convolutional neural network (CNN) and XGBoost to preoperative computed tomography (CT) images and clinical data for distinguishing Xp11.2 translocation renal cell carcinoma (Xp11.2 tRCC) from common subtypes of renal cell carcinoma (RCC) in order to provide patients with individualized treatment plans. Data from 45 patients with Xp11.2 tRCC from January 2007 to December 2021 are collected. Clear cell RCC (ccRCC), papillary RCC (pRCC), or chromophobe RCC (chRCC) can be detected from each patient. CT images are acquired in the following three phases: unenhanced, corticomedullary, and nephrographic. A unified framework More >

Yanqiu Chen, Xiaopeng Ji^*

CMES-Computer Modeling in Engineering & Sciences, Vol.136, No.1, pp. 531-553, 2023, DOI:10.32604/cmes.2023.024531 - 05 January 2023

Abstract Non-orthogonal multiple access technology (NOMA), as a potentially promising technology in the 5G/B5G era, suffers from ubiquitous security threats due to the broadcast nature of the wireless medium. In this paper, we focus on artificial-signal-assisted and relay-assisted secure downlink transmission schemes against external eavesdropping in the context of physical layer security, respectively. To characterize the non-cooperative confrontation around the secrecy rate between the legitimate communication party and the eavesdropper, their interactions are modeled as a two-person zero-sum game. The existence of the Nash equilibrium of the proposed game models is proved, and the pure strategy More >

G. Murugesan^1,*, J. Jeyapriya², M. Hemalatha³, S. Rajeshkannan⁴

Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2099-2109, 2023, DOI:10.32604/iasc.2023.032068 - 05 January 2023

Abstract The diagnostic interpretation of dermoscopic images is a complex task as it is very difficult to identify the skin lesions from the normal. Thus the accurate detection of potential abnormalities is required for patient monitoring and effective treatment. In this work, a Two-Tier Segmentation (TTS) system is designed, which combines the unsupervised and supervised techniques for skin lesion segmentation. It comprises preprocessing by the median filter, TTS by Colour K-Means Clustering (CKMC) for initial segmentation and Faster Region based Convolutional Neural Network (FR-CNN) for refined segmentation. The CKMC approach is evaluated using the different number of… More >

HAOTONG SUN^1,2, HEYING WANG^1,3, XIN LI^1,2, YANJIE HAO^1,2, JUN LING^1,2, HUAN WANG^1,2, FEIMIAO WANG^1,2, FANG XU^1,2,*

BIOCELL, Vol.47, No.3, pp. 607-618, 2023, DOI:10.32604/biocell.2023.026445 - 03 January 2023

Abstract Background: Colon adenocarcinoma (COAD) is the second leading cause of cancer death worldwide thus, identification of COAD biomarkers is critical. Mitotic Arrest Deficient 2 Like 2 (MAD2L2) is a key factor in mammalian DNA damage repair and is highly expressed in many malignant tumors. This is a comprehensive study of MAD2L2 expression, its diagnostic value, prognostic analysis, potential biological function, and impact on the immune system of patients with COAD. Methods: Gene expression, clinical relevance, prognostic analysis, diagnostic value, GO/KEGG cluster analysis, data obtained from TCGA, and bioinformatics statistical analysis were performed using the R package. Immune… More >

ZEKUN XIN^1,#, YUDAN MA^2,#, WEIQIANG SONG³, HAO GAO³, LIJUN DONG³, BAO ZHANG^1,*, ZHILONG REN^3,*

BIOCELL, Vol.47, No.3, pp. 555-567, 2023, DOI:10.32604/biocell.2023.026254 - 03 January 2023

Abstract Background: Recently, researchers have been attracted in identifying the crucial genes related to cancer, which plays important role in cancer diagnosis and treatment. However, in performing the cancer molecular subtype classification task from cancer gene expression data, it is challenging to obtain those significant genes due to the high dimensionality and high noise of data. Moreover, the existing methods always suffer from some issues such as premature convergence. Methods: To address those problems, we propose a new ant colony optimization (ACO) algorithm called DACO to classify the cancer gene expression datasets, identifying the essential genes of… More >