An Improved Computational Model for Adaptive Communication Channel Estimation

Channel estimation is an important and necessary function performed by modern wireless receivers. The goal of channel estimation is to measure the effects of the channel on known or partially known transmission. The usual practice in acquiring knowledge about a channel is to model the channel and then acquire the parameters involved in the model. This paper proposes a variable partial update model for adaptive communication channel estimation with a view to improving signal error at the receiver station. The proposed model is composed of finite impulse response transversal adaptive filter and least mean square adaptation algorithm. The performance of the proposed model was compared with the full update model. The evaluation results indicated that the proposed model performed better than the full update model in terms of computational complexity, memory load, and convergence rate

Demographic attributes of COVID-19 patients in an Infectious Disease Center of Nigeria

Background: As part of our contribution to the growing pool of knowledge on the prevention and control of the COVID-19 pandemic, this study describes the demographic features of patients with COVID-19 hospitalized at Infectious Disease Center (IDC), Olodo, Ibadan, Oyo State, Nigeria.Methodology: This was a descriptive cross-sectional study of COVID-19 patients whose data were collected during admission between April 27, 2020 and June 20, 2020. SARS-CoV-2 infection was diagnosed on nasopharyngeal specimen using a real-time reverse transcription–polymerase chain reaction (rRT-PCR) assay. Data were analysed using the Statistical Package for Social Sciences (SPSS Inc., USA) version 20.0Results: Among 131 patients, 58% were between age 18 and 35 years, 48.1% were employees of private establishments, and 64.1% were males. High proportion (84.3%) of the patients spent less than 14 days on admission. As at June 20, 2020, the overall COVID-19 mortality in the IDC was 0.0%.Conclusion: This study concluded that COVID-19 was common among male Nigerians, those working in private establishments, and those aged 18-35 years. Future researches on COVID-19 in Nigeria must put gender and age into consideration. Keywords: SARS-COV2; COVID-19; age; gender; occupation French Title: Attributs démographiques des patients atteints de COVID-19dans un centre de maladies infectieuses du Nigéria Contexte: Dans le cadre de notre contribution au pool croissant de connaissances sur la prévention et le contrôle de la pandémie COVID-19, cette étude décrit les caractéristiques démographiques des patients atteints de COVID19 hospitalisés au Centre des maladies infectieuses (IDC), Olodo, Ibadan, État d'Oyo, Nigéria. Méthodologie: Il s'agissait d'une étude transversale descriptive de patients atteints de COVID-19 dont lesdonnées ont été collectées lors de l'admission entre le 27 avril 2020 et le 20 juin 2020. L'infection par le  SRASCoV-2 a été diagnostiquée sur un échantillon nasopharyngé à l'aide d'une transcription inverse en temps réel–Test de réaction en chaîne par polymérase (rRT-PCR). Les données ont été analysées à l'aide du StatisticalPackage for Social Sciences (SPSS Inc., USA) version 20.0 Résultats: Parmi 131 patients, 58% avaient entre 18 et 35 ans, 48,1% étaient des employés d'établissementsprivés et 64,1% étaient des hommes. Une forte proportion (84,3%) des patients ont passé moins de 14 jours àl'admission. Au 20 juin 2020, la mortalité globale par COVID-19 dans l'IDC était de 0,0%. Conclusion: Cette étude a conclu que le COVID-19 était courant chez les hommes Nigérians, ceux travaillantdans des établissements privés et ceux âgés de 18 à 35 ans. Les futures recherches sur le COVID-19 au Nigériadoivent prendre en compte le sexe et l'âge. Mots clés: SRAS-COV2; COVID-19; âge; le sexe; occupatio