Sarah A. Scuderi^*, Marika Lanza^*, Giovanna Casili^*, Francesca Esposito^†, Cristina Colarossi^‡, Dario Giuffrida^‡, Paterniti Irene^*, Salvatore Cuzzocrea^*,* Emanuela Esposito^*, Michela Campolo^*

Oncology Research, Vol.28, No.7-8, pp. 779-790, 2020, DOI:10.3727/096504021X16161478258040

Abstract Glioma are common malignant brain tumors, among which glioblastoma multiforme (GBM) has the worst prognosis. Different studies of GBM revealed that targeting nuclear factor B (NF- B) induced an attenuation tumor proliferation and prolonged cell survival. TBK1 {TANK [TRAF (TNF (tumor-necrosis-factor) receptorassociated factor)-associated NF- B activator]-binding kinase 1} is a serine/threonine protein kinase, and it is a member of the I B kinase (IKK) family involved in NF- B pathway activation. The aim of this study was to investigate the potential effect of BX795, an inhibitor of TBK1, in an in vitro and ex vivo model of GBM. GBM cell… More >

Elias Hossain¹, Mohammed Alshehri², Sultan Almakdi^2,*, Hanan Halawani², Md. Mizanur Rahman³, Wahidur Rahman⁴, Sabila Al Jannat⁵, Nadim Kaysar⁶, Shishir Mia⁴

CMC-Computers, Materials & Continua, Vol.72, No.1, pp. 1713-1746, 2022, DOI:10.32604/cmc.2022.024822

Abstract Diabetes Mellitus is one of the most severe diseases, and many studies have been conducted to anticipate diabetes. This research aimed to develop an intelligent mobile application based on machine learning to determine the diabetic, pre-diabetic, or non-diabetic without the assistance of any physician or medical tests. This study's methodology was classified into two the Diabetes Prediction Approach and the Proposed System Architecture Design. The Diabetes Prediction Approach uses a novel approach, Light Gradient Boosting Machine (LightGBM), to ensure a faster diagnosis. The Proposed System Architecture Design has been combined into seven modules; the Answering Question Module is a natural… More >

Shuqiang Guo^{1, *}, Baohai Yue¹, Manyang Gao², Xinxin Zhou¹, Bo Wang³

CMC-Computers, Materials & Continua, Vol.64, No.1, pp. 233-251, 2020, DOI:10.32604/cmc.2020.010039

Abstract The recycling of glass bottles can reduce the consumption of resources and contribute to environmental protection. At present, the classification of recycled glass bottles is difficult due to the many differences in specifications and models. This paper proposes a classification algorithm for glass bottles that is divided into two stages, namely the extraction of candidate regions and the classification of classifiers. In the candidate region extraction stage, aiming at the problem of the large time overhead caused by the use of the SIFT (scale-invariant feature transform) descriptor in SS (selective search), an improved feature of HLSN (Haar-like based on SPP-Net)… More >

Yong Fang¹, Yunyun Zhang², Cheng Huang^1,*

CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 185-195, 2019, DOI:10.32604/cmc.2019.06144

Abstract In recent years, the rapid development of e-commerce exposes great vulnerabilities in online transactions for fraudsters to exploit. Credit card transactions take a salient role in nowadays’ online transactions for its obvious advantages including discounts and earning credit card points. So credit card fraudulence has become a target of concern. In order to deal with the situation, credit card fraud detection based on machine learning is been studied recently. Yet, it is difficult to detect fraudulent transactions due to data imbalance (normal and fraudulent transactions), for which Smote algorithm is proposed in order to resolve data imbalance. The assessment of… More >