M
Mohammed Nasser
Researcher at University of A Coruña
Publications - 33
Citations - 565
Mohammed Nasser is an academic researcher from University of A Coruña. The author has contributed to research in topics: Regression analysis & Outlier. The author has an hindex of 12, co-authored 33 publications receiving 445 citations. Previous affiliations of Mohammed Nasser include University of Rajshahi & University of Malaya.
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Journal ArticleDOI
Support Vector Machine and Random Forest Modeling for Intrusion Detection System (IDS)
TL;DR: This work has built two models for the classification purpose, one is based on Support Vector Machines (SVM) and the other is Random Forests (RF), and Experimental results show that either classifier is effective.
Journal ArticleDOI
Feature Selection for Intrusion Detection Using Random Forest
TL;DR: Results show that the Random Forest based proposed approach can select most important and relevant features useful for classification, which reduces not only the number of input features and time but also increases the classification accuracy.
Journal ArticleDOI
Making Waves: Collaboration in the time of SARS-CoV-2 - rapid development of an international co-operation and wastewater surveillance database to support public health decision-making.
Lian Lundy,Despo Fatta-Kassinos,Jaroslav Slobodnik,Popi Karaolia,Lubos Cirka,Norbert Kreuzinger,Sara Castiglioni,Lubertus Bijlsma,Valeria Dulio,Genevieve Deviller,Foon Yin Lai,Nikiforos A. Alygizakis,Manuela Barneo,Jose Antonio Baz-Lomba,Frederic Been,Marianna Cichova,Kelly Conde-Pérez,Adrian Covaci,Erica Donner,Andrej Ficek,Francis Hassard,Annelie Hedström,Félix Hernández,Veronika Janska,Kristen L. Jellison,Jan Hofman,Kelly Hill,Pei-Ying Hong,Barbara Kasprzyk-Hordern,Stoimir Kolarević,Ján Krahulec,Dimitra A. Lambropoulou,Rosa de Llanos,Tomáš Mackuľak,Lorena Martinez-Garcia,Francisco Javier Escobar Martínez,Gertjan Medema,Adrienn Micsinai,Mette Myrmel,Mohammed Nasser,Harald Niederstätter,Leonor Nozal,Herbert Oberacher,Věra Očenášková,Leslie Ogorzaly,Dimitrios Papadopoulos,Beatriz Peinado,Tarja Pitkänen,Margarita Poza,Soraya Rumbo-Feal,Maria Blanca Sanchez,Anna J. Székely,Andrea Soltysova,Nikolaos S. Thomaidis,Juan A. Vallejo,Alexander L.N. van Nuijs,Vassie C. Ware,Maria Viklander +57 more
TL;DR: The NORMAN SCORE “SARS-CoV-2 in sewage” database provides a platform for rapid, open access data sharing, validated by the uploading of 276 data sets from nine countries to-date and is a resource for the development of recommendations on minimum data requirements for wastewater pathogen surveillance.
Posted ContentDOI
Predicting the number of people infected with SARS-COV-2 in a population using statistical models based on wastewater viral load
Juan A. Vallejo,Soraya Rumbo-Feal,Kelly Conde-Pérez,Ángel López-Oriona,Javier Tarrío-Saavedra,Rubén Reif,Susana Ladra,Bruno K. Rodiño-Janeiro,Mohammed Nasser,Ángeles Cid,María C. Veiga,Antón Acevedo,Carlos Lamora,Germán Bou,Ricardo Cao,Ricardo Cao,Margarita Poza +16 more
TL;DR: In this paper, statistical regression models from the viral load detected in the wastewater and the epidemiological data from A Coruna health system that allowed us to estimate the number of infected people, including symptomatic and asymptomatic individuals, with reliability close to 90%, were developed.
Journal ArticleDOI
Comparison of the finite mixture of ARMA-GARCH, back propagation neural networks and support-vector machines in forecasting financial returns
Altaf Hossain,Mohammed Nasser +1 more
TL;DR: The finite mixture of ARMA-GARCH model is applied instead of AR or ARMA models to compare with the standard BP and SVM in forecasting financial time series (daily stock market index returns and exchange rate returns) and shows that the SVM model shows long memory property in forecastingFinancial returns.