Phenolic Content and Antioxidant and Antimicrobial Activities of Malva sylvestris L., Malva oxyloba Boiss., Malva parviflora L., and Malva aegyptia L.... by Khalid A. Shadid, Ashok K. Shakya, Rajashri R. Naik, Nidal Jaradat, Husni S. Farah, Naeem Shalan, Nooman A. Khalaf, Ghaleb A. Oriquat

“…The current investigation points towards the quantitative characterization of the phenolic contents among the four edible Malva plants species (Malva sylvestris L., Malva oxyloba Boiss., Malva parviflora L., and Malva aegyptia L.) and also towards assessing their antibacterial activity against one Gram-positive isolate (Staphylococcus aureus) and four Gram-negative strains Escherichia coli, Pseudomonas aeruginosa, Shigella sonnei, and Proteus vulgaris. …”
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Church and State Relations in the Constitution of Malta by Kevin Aquilina

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Influence of Removable Devices' Heterouse on the Propagation of Malware by Xie Han, Yi-Hong Li, Li-Ping Feng, Li-Peng Song

“…The effects of removable devices’ heterouse in different areas on the propagation of malware spreading via removable devices remain unclear. …”
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Malware Analysis Using Visualized Image Matrices by KyoungSoo Han, BooJoong Kang, Eul Gyu Im

“…This paper proposes a novel malware visual analysis method that contains not only a visualization method to convert binary files into images, but also a similarity calculation method between these images. …”
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Power Consumption Based Android Malware Detection by Hongyu Yang, Ruiwen Tang

“…In order to solve the problem that Android platform’s sand-box mechanism prevents security protection software from accessing effective information to detect malware, this paper proposes a malicious software detection method based on power consumption. …”
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Modeling and Analysis of the Spread of Malware with the Influence of User Awareness by Qingyi Zhu, Xuhang Luo, Yuhang Liu

“…By incorporating the security awareness of computer users into the susceptible-infected-susceptible (SIS) model, this study proposes a new malware propagation model, named the SID model, where D compartment denotes the group of nodes with user awareness. …”
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The Impact of COVID-19 on Hospitalised COPD Exacerbations in Malta by Yvette Farrugia, Bernard Paul Spiteri Meilak, Neil Grech, Rachelle Asciak, Liberato Camilleri, Stephen Montefort, Christopher Zammit

“…The first COVID-19 case in Malta was confirmed on the 7th of March 2020. This study is aimed at investigating a significant difference between the number of acute exacerbations of chronic obstructive pulmonary disease (AECOPD) admissions and their inpatient outcome at Mater Dei Hospital during the COVID-19 pandemic when compared to the same period in 2019. …”
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Las malas mujeres de la Biblia by Amalia Pérez Valiño

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Behavior Intention Derivation of Android Malware Using Ontology Inference by Jian Jiao, Qiyuan Liu, Xin Chen, Hongsheng Cao

“…Previous researches on Android malware mainly focus on malware detection, and malware’s evolution makes the process face certain hysteresis. …”
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A Data Mining Classification Approach for Behavioral Malware Detection by Monire Norouzi, Alireza Souri, Majid Samad Zamini

“…In this paper we present a data mining classification approach to detect malware behavior. We proposed different classification methods in order to detect malware based on the feature and behavior of each malware. …”
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A Malware Detection Scheme Based on Mining Format Information by Jinrong Bai, Junfeng Wang, Guozhong Zou

“…Malware has become one of the most serious threats to computer information system and the current malware detection technology still has very significant limitations. …”
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MALVADA: A framework for generating datasets of malware execution traces by Razvan Raducu, Alain Villagrasa-Labrador, Ricardo J. Rodríguez, Pedro Álvarez

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Malware recognition approach based on self‐similarity and an improved clustering algorithm by Jinfu Chen, Chi Zhang, Saihua Cai, Zufa Zhang, Lu Liu, Longxia Huang

“…Abstract The recognition of malware in network traffic is an important research problem. …”
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Malware Detection in Self-Driving Vehicles Using Machine Learning Algorithms by Seunghyun Park, Jin-Young Choi

“…In this study, we propose a machine learning-based data analysis method to accurately detect abnormal behaviors due to malware in large-scale network traffic in real time. …”
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Detecting Obfuscated Malware Infections on Windows Using Ensemble Learning Techniques by Yadigar Imamverdiyev, Elshan Baghirov, John Chukwu Ikechukwu

Subjects: “…malware detection…”
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MalSEIRS: Forecasting Malware Spread Based on Compartmental Models in Epidemiology by Isabella Martínez Martínez, Andrés Florián Quitián, Daniel Díaz-López, Pantaleone Nespoli, Félix Gómez Mármol

“…In this context, the paper at hand proposes MalSEIRS, a novel dynamic model, to predict malware distribution in a network based on the SEIRS epidemiological model. …”
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Integrating Information Gain and Chi-Square for Enhanced Malware Detection Performance by Fauzi Adi Rafrastara, Wildanil Ghozi, Ramadhan Rakhmat Sani, Lekso Budi Handoko, Abdussalam Abdussalam, Elkaf Rahmawan Pramudya, Faizal M. Abdollah

Subjects: “…Malware detection…”
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Linear SVM-Based Android Malware Detection for Reliable IoT Services by Hyo-Sik Ham, Hwan-Hee Kim, Myung-Sup Kim, Mi-Jung Choi

“…In this paper, we apply a linear support vector machine (SVM) to detect Android malware and compare the malware detection performance of SVM with that of other machine learning classifiers. …”
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The Effects of Different Representations on Static Structure Analysis of Computer Malware Signatures by Ajit Narayanan, Yi Chen, Shaoning Pang, Ban Tao

“…The aim of this paper is to evaluate a static structure approach to malware modelling using the growing malware signature databases now available. …”
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A novel feature selection technique: Detection and classification of Android malware by Sandeep Sharma, Prachi, Rita Chhikara, Kavita Khanna

Subjects: “…Android Malware…”
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