Rivers State University of Science and Technology

About: Rivers State University of Science and Technology is a education organization based out in Port Harcourt, Rivers, Nigeria. It is known for research contribution in the topics: Population & Threatened species. The organization has 1826 authors who have published 1833 publications receiving 15183 citations.

Social media, fake news and fake COVID-19 cures in Nigeria

Abstract: This study investigates the impact of social media fake news' and fake cures headlines on how Netizens viewed and responded to the COVID-19 pandemic in Nigeria. Using data from an online survey (N=254), this study reveals that social media was overwhelmingly the most used type of media for news consumption generally, and the most important source of news about the pandemic. Data further reveal that the impact of extensive exposure to fake news headlines about the pandemic was dangerous and could have a deleterious impact. Crucially, this study finds that recalling and believing fake news headlines and using social media as the main source of news, significantly decreases the likelihood of believing credible and real news stories. Finally, this study offers theoretical and empirical background to frame the debate about factors that influence the believability of fake news headlines by contributing and extending the theorization of the amplification hypothesis.

Deviant Learning Algorithm: Learning Sparse Mismatch Representations through Time and Space

Abstract: Predictive coding (PDC) has recently attracted attention in the neuroscience and computing community as a candidate unifying paradigm for neuronal studies and artificial neural network implementations particularly targeted at unsupervised learning systems. The Mismatch Negativity (MMN) has also recently been studied in relation to PC and found to be a useful ingredient in neural predictive coding systems. Backed by the behavior of living organisms, such networks are particularly useful in forming spatio-temporal transitions and invariant representations of the input world. However, most neural systems still do not account for large number of synapses even though this has been shown by a few machine learning researchers as an effective and very important component of any neural system if such a system is to behave properly. Our major point here is that PDC systems with the MMN effect in addition to a large number of synapses can greatly improve any neural learning system's performance and ability to make decisions in the machine world. In this paper, we propose a novel bio-mimetic computational intelligence algorithm – the Deviant Learning Algorithm, inspired by these key ideas and functional properties of recent brain-cognitive discoveries and theories. We also show by numerical experiments guided by theoretical insights, how our invented bio-mimetic algorithm can achieve competitive predictions even with very small problem specific data.

Leachate Characterization from Municipal Solid Waste Dump Site and Its Adverse Impacts on Surface Water Quality Downstream - Uyo Village Road, Akwa Ibom State - Nigeria

Abstract: The present investigation discusses the characteristic of leachate generated from municipal solid waste landfill and it adverse impacts on downstream water quality. Landfill leachate was collected from a hole dug 10 m away from the waste dump site and the appearance of the leachate sample looks black. Three downstream water samples were collected at 10 meters intervals each from each other and less than 100 meters from the boundary of the dumpsite. All the samples were examined for temperature, pH, TDS, TSS, BOD, COD, nitrate, ammonia, Cu, Ni, Pb, Cd, Cl, total phosphate, sulfate, EC, DO and turbidity. The aim was to compare physicochemical and heavy metal properties of leachate and downstream water quality with internationally accepted protocols. Original Research Article Nta et al.; JERR, 13(2): 11-19, 2020; Article no.JERR.57040 12 The Laboratory analysis exhibited prevalence of high value of pH (8.513 ± 0.09), temperature(29.0± 0.0°C), turbidity (14.0±0.41NTU), DO (0.167±0.05 mg/l), COD (68.0±0.33 mg/l), BOD5 (324.0±3.00 mg/l), EC (4463±15.53 s/cm), Total phosphate (62.358±0.01 mg/l), Pb (0.31±0.00 mg/l), Cd (0.06±0.00 mg/l), Ni (0.355±0.01 mg/l), and Cu (8.67±0.04 mg/l) in the leachate sample, which have exceeded their permissible limits. For downstream water samples, pH (7.76±0.07 to 7.507±0.09), temperature (29.0±0.00°C) for the three sampling points, DO (3.667 ± 0.15 to 3.233 ± 0.12 mg/l), total phosphate (8.225 ± 0.00 to 7.935 ± 0.02 mg/l), Pb (0.465±0.01 to 0.091±0.00 mg/l), Cd (0.04±0.00 to 0.023±0.00 mg/l), Ni and Cu (0.043±0.06 mg/l) and (1.062 ± 0.00 mg/l) respectively, also exceeded their respective permissible limit recommended by Nigerian Standard for Drinking Water Quality, World Health Organization in drinking water quality. From this study, there is evidence that there is an increase in risk to surface water that is reported near Uyo village road municipal solid waste dumping site. Therefore, the concerned authority should take appropriate intervention measures to protect surface water. Also, knowledge of leachate quality will be useful in planning and providing remedial measures to protect downstream water quality in the area.