Kangjik Kim¹, Hyunbin Kim¹, Junchul Chun¹, Mingoo Kang², Min Hong^3,*, Byungseok Min⁴

CMC-Computers, Materials & Continua, Vol.67, No.2, pp. 2547-2568, 2021, DOI:10.32604/cmc.2021.014642

Abstract Physical contamination of food occurs when it comes into contact with foreign objects. Foreign objects can be introduced to food at any time during food delivery and packaging and can cause serious concerns such as broken teeth or choking. Therefore, a preventive method that can detect and remove foreign objects in advance is required. Several studies have attempted to detect defective products using deep learning networks. Because it is difficult to obtain foreign object-containing food data from industry, most studies on industrial anomaly detection have used unsupervised learning methods. This paper proposes a new method for real-time anomaly detection in… More >

Hyeong Won Yu¹, Muhammad Afzal², Maqbool Hussain², Hyungju Kwon³, Young Joo Park⁴, June Young Choi^1,*, Kyu Eun Lee⁵

CMC-Computers, Materials & Continua, Vol.67, No.1, pp. 1241-1251, 2021, DOI:10.32604/cmc.2021.014910

Abstract Advances in technology are enabling gene mutations in papillary thyroid carcinoma (PTC) to be analyzed and clinical outcomes, such as recurrence, to be predicted. To date, the most common genetic mutation in PTC is in BRAF kinase (BRAF). However, whether mutations in other genes coincide with those in BRAF remains to be clarified. The aim of this study was to find mutations in other genes that co-exist with mutated BRAF, and to analyze their frequency and clinical relevance in PTC. Clinical and genetic data were collected from 213 PTC patients with a total of 36,572 mutation sites in 735 genes.… More >

Shumaila Shahzadi¹, Fahad Ahmad^1,*, Asma Basharat¹, Madallah Alruwaili², Saad Alanazi², Mamoona Humayun², Muhammad Rizwan¹, Shahid Naseem³

CMC-Computers, Materials & Continua, Vol.66, No.3, pp. 2723-2749, 2021, DOI:10.32604/cmc.2021.014594

Abstract With the rising demand for data access, network service providers face the challenge of growing their capital and operating costs while at the same time enhancing network capacity and meeting the increased demand for access. To increase efficacy of Software Defined Network (SDN) and Network Function Virtualization (NFV) framework, we need to eradicate network security configuration errors that may create vulnerabilities to affect overall efficiency, reduce network performance, and increase maintenance cost. The existing frameworks lack in security, and computer systems face few abnormalities, which prompts the need for different recognition and mitigation methods to keep the system in the… More >

Sophie Piperno-Neumann^1,*, Pascale Mariani², Vincent Servois³, Gaelle Pierron⁴, Livia LumbrosoRouic⁵, Alexandre Matet^5,6, Manuel Rodrigues¹, Nathalie Cassoux^5,6

Oncologie, Vol.22, No.4, pp. 203-212, 2020, DOI:10.32604/oncologie.2020.014102

Abstract Uveal melanoma is a rare subtype of melanoma, intrinsically different from cutaneous melanoma. Despite optimal therapeutic management allowing local control of the primary ocular tumor, 20 to 50% of patients develop metastases, mainly localized to the liver, with a poor prognosis and a 12-month median survival from the diagnosis of the metastatic disease. There is a lack of effective treatments in the metastatic setting, and dedicated strategies and trials for uveal melanoma patients are needed, based on identification of new targets and specific preclinical findings.


Résumé:
Le mélanome de l’uvée est un cancer rare, en tous points différent du mélanome… More >

Sophie Gardrat^*, Vincent Cockenpot

Oncologie, Vol.22, No.4, pp. 195-202, 2020, DOI:10.32604/oncologie.2020.013698

Abstract The pathological examination of ocular tumors has specificities in terms of macroscopic management, microscopic analysis, and molecular examinations requiring special attention. We discuss here the difficulties encountered in the reception in the pathological anatomy laboratory of conjunctival samples, enucleation and orbital exenteration pieces, then detail the diagnostic and theranostic, microscopic and molecular characteristics of ocular tumor pathologies. Conjunctival tumors (epithelial, melanocytic and lymphoid), choroidal tumors (including uveal melanoma) and retinoblastoma are treated. Because of their low frequency and their features, these tumors should be the subject of anatomo-clinical discussions.

Résumé:
L’examen anatomopathologique des tumeurs oculaires comporte des spécificités en termes… More >

Laurence Desjardins^*

Oncologie, Vol.22, No.4, pp. 189-194, 2020, DOI:10.32604/oncologie.2020.012377

Abstract We describe the most frequent malignant intraocular tumors, conjunctival tumors and some lids and orbital tumors. Primary intraocular malignant tumors are retinoblastoma in children and uveal melanoma in adults. For uveal melanoma, the liver is the most frequent site of metastasis and this is why it is justified to prescribe liver ultrasonography every 6 months to these patients. Metastatic tumors can occur in the uvea and more frequently in the posterior part called the choroid. They are more frequent after breast cancer and lung cancer. Conjunctival tumors can be epithelial (benign papillomas and epidermoid carcinomas) or melanocytic (benign naevi and… More >

Yang Yang^1,*, Qian Zhao¹, Linna Ruan², Zhipeng Gao¹, Yonghua Huo³, Xuesong Qiu¹

Intelligent Automation & Soft Computing, Vol.26, No.5, pp. 1139-1155, 2020, DOI:10.32604/iasc.2020.011705

Abstract In network anomaly detection, network traffic data are often imbalanced, that is, certain classes of network traffic data have a large sample data volume while other classes have few, resulting in reduced overall network traffic anomaly detection on a minority class of samples. For imbalanced data, researchers have proposed the use of oversampling techniques to balance data sets; in particular, an oversampling method called the SMOTE provides a simple and effective solution for balancing data sets. However, current oversampling methods suffer from the generation of noisy samples and poor information quality. Hence, this study proposes an oversampling method for imbalanced… More >

Ji Qian¹, Fang Liu^2,*, Donghui Li³, Xin Jin⁴, Feng Li⁴

Journal of Cyber Security, Vol.2, No.4, pp. 157-166, 2020, DOI:10.32604/jcs.2020.011169

Abstract Anomaly detection using KPI (Key Performance Indicator) is critical for Internet-based services to maintain high service availability. However, given the velocity, volume, and diversified nature of monitoring data, it is difficult to obtain enough labelled data to build an accurate anomaly detection model for using supervised machine leaning methods. In this paper, we propose an automatic and generic transfer learning strategy: Detecting anomalies on a new KPI by using pretrained model on existing selected labelled KPI. Our approach, called KADT (KPI Anomaly Detection based on Transfer Learning), integrates KPI clustering and model pretrained techniques. KPI clustering is used to obtain… More >

Lewis Nkenyereye¹, Bayu Adhi Tama², Sunghoon Lim^3,*

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 2217-2227, 2021, DOI:10.32604/cmc.2020.012432

Abstract An anomaly-based intrusion detection system (A-IDS) provides a critical aspect in a modern computing infrastructure since new types of attacks can be discovered. It prevalently utilizes several machine learning algorithms (ML) for detecting and classifying network traffic. To date, lots of algorithms have been proposed to improve the detection performance of A-IDS, either using individual or ensemble learners. In particular, ensemble learners have shown remarkable performance over individual learners in many applications, including in cybersecurity domain. However, most existing works still suffer from unsatisfactory results due to improper ensemble design. The aim of this study is to emphasize the effectiveness… More >

Adnan¹, Umar Khan², Naveed Ahmed³, Syed Tauseef Mohyud-Din⁴, Ilyas Khan^5,*, Dumitru Baleanu^6,7,8, Kottakkaran Sooppy Nisar⁹

CMC-Computers, Materials & Continua, Vol.66, No.2, pp. 1563-1576, 2021, DOI:10.32604/cmc.2020.012326

Abstract Thermal transport investigation in colloidal suspensions is taking a significant research direction. The applications of these fluids are found in various industries, engineering, aerodynamics, mechanical engineering and medical sciences etc. A huge amount of thermal transport is essential in the operation of various industrial production processes. It is a fact that conventional liquids have lower thermal transport characteristics as compared to colloidal suspensions. The colloidal suspensions have high thermal performance due to the thermophysical attributes of the nanoparticles and the host liquid. Therefore, researchers focused on the analysis of the heat transport in nanofluids under diverse circumstances. As such, the… More >