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Showing posts with the label Risk assessment

Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria

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Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria DOI:  https://doi.org/10.30564/jees.v5i1.5060 Received: 12 September 2022 | Revised: 18 March 2023 | Accepted: 21 March 2023 | Published Online: 13 April 2023 Abstract In order to investigate the source, contamination, and risk of heavy metals such as Pb, Zn, Cu, Ni, Co, Fe, Mn, and Cr, twelve (12) stream sediments and ten (10) rock samples were collected from pegmatite mining sites at Olode and its environs inside Ibadan, Southwestern Nigeria. The average values and order of abundance obtained followed the pattern: Mn (595.09) > Ba (80) > Cr (50.82) > V (45.09) > Zn (29.73) > Cu (13.82) > Co (13.82) > Sr (10.46) > Ni (9.73) > Pb (9.09) > Fe (1.59). These were greater than the background values, indicating that mining has a negative impact on the study area, as indicated by the high coefficient of variation and ...

Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria

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Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria DOI:  https://doi.org/10.30564/jees.v5i1.5060 Received: 12 September 2022 | Revised: 18 March 2023 | Accepted: 21 March 2023 | Published Online: 13 April 2023 Abstract In order to investigate the source, contamination, and risk of heavy metals such as Pb, Zn, Cu, Ni, Co, Fe, Mn, and Cr, twelve (12) stream sediments and ten (10) rock samples were collected from pegmatite mining sites at Olode and its environs inside Ibadan, Southwestern Nigeria. The average values and order of abundance obtained followed the pattern: Mn (595.09) > Ba (80) > Cr (50.82) > V (45.09) > Zn (29.73) > Cu (13.82) > Co (13.82) > Sr (10.46) > Ni (9.73) > Pb (9.09) > Fe (1.59). These were greater than the background values, indicating that mining has a negative impact on the study area, as indicated by the high coefficient of variation and ...

Assessment of Geologic Controls of Flooding in Parts of OBIO/AKPOR L.G.A., Rivers State, Nigeria

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Assessment of Geologic Controls of Flooding in Parts of OBIO/AKPOR L.G.A., Rivers State, Nigeria DOI:  https://doi.org/10.30564/jgr.v3i2.2902 Abstract Flooding of Municipal areas is a frequent environmental occurrence in Rivers State that occurs when rainfall runoff meets land surfaces with low water absorbing capacity or when it overwhelms drainage channels. In order to assess the flood situation in the study area, an integrated method which involves field-measurement, geographic information system (GIS),laboratory analysis of soil samples and topographic studies were employed.Digital elevation model of the study area reveals that the flooded areas are situated in areas with elevations lower than its surrounding, thereby acting as a natural basin to retain flood waters after rainfall.Four holes were drilled to depth of 3 m to obtain soil samples at 1 m sampling interval, from which laboratory analysis was carried out to d...

Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria

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Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria DOI:  https://doi.org/10.30564/jees.v5i1.5060 Received: 12 September 2022 | Revised: 18 March 2023 | Accepted: 21 March 2023 | Published Online: 13 April 2023 Abstract In order to investigate the source, contamination, and risk of heavy metals such as Pb, Zn, Cu, Ni, Co, Fe, Mn, and Cr, twelve (12) stream sediments and ten (10) rock samples were collected from pegmatite mining sites at Olode and its environs inside Ibadan, Southwestern Nigeria. The average values and order of abundance obtained followed the pattern: Mn (595.09) > Ba (80) > Cr (50.82) > V (45.09) > Zn (29.73) > Cu (13.82) > Co (13.82) > Sr (10.46) > Ni (9.73) > Pb (9.09) > Fe (1.59). These were greater than the background values, indicating that mining has a negative impact on the study area, as indicated by the high coefficient of variation and ...

Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria

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Source, Contamination Assessment and Risk Evaluation of Heavy Metals in the Stream Sediments of Rivers around Olode Area SW, Nigeria DOI:  https://doi.org/10.30564/jees.v5i1.5060 Received: 12 September 2022 | Revised: 18 March 2023 | Accepted: 21 March 2023 | Published Online: 13 April 2023 Abstract In order to investigate the source, contamination, and risk of heavy metals such as Pb, Zn, Cu, Ni, Co, Fe, Mn, and Cr, twelve (12) stream sediments and ten (10) rock samples were collected from pegmatite mining sites at Olode and its environs inside Ibadan, Southwestern Nigeria. The average values and order of abundance obtained followed the pattern: Mn (595.09) > Ba (80) > Cr (50.82) > V (45.09) > Zn (29.73) > Cu (13.82) > Co (13.82) > Sr (10.46) > Ni (9.73) > Pb (9.09) > Fe (1.59). These were greater than the background values, indicating that mining has a negative impact on the study area, as indicated by the high coefficient of variation and ...

Mobile Software Assurance Informed through Knowledge Graph Construction: The OWASP Threat of Insecure Data Storage

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Mobile Software Assurance Informed through Knowledge Graph Construction: The OWASP Threat of Insecure Data Storage DOI:  https://doi.org/10.30564/jcsr.v2i2.1765 Abstract Many organizations, to save costs, are moving to the Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate. Our research examines software assurance methodologies specifically focusing on security analysis coverage of the program analysis for mobile malware detection, mitigation, and prevention. This research focuses on secure software development of Android applications by developing knowledge graphs for threats reported by the Open Web Application Security Project (OWASP). OWASP maintains lists of the top ten security threats to web and mobile applications. We develop knowledge graphs based on the two most recent top ten threat years and show how the knowledge graph relationships can be discovered in mobile application source code. We analyze 200+ heal...