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An Algorithm to Determine the Extent of an Epidemic Spread: A NetLogo Modeling Approach
Jerry John Kponyo,
Kenneth Coker,
Justice Owusu Agyemang,
Joyce Der
Issue:
Volume 4, Issue 4, August 2019
Pages:
74-78
Received:
11 January 2019
Accepted:
7 August 2019
Published:
23 August 2019
Abstract: The outbreaks of infectious diseases have had a huge impact on the human society. Researchers have developed models aimed at understanding how various infectious diseases spread in communities and also proposed control measures that can minimize or stop the spread of the diseases. Most researchers have developed stochastic mathematical models which are used in predicting the occurrence of an epidemic. Most of the proposed models do not employ the use of system dynamics hence making it difficult to adopt the same model in predicting the behavior of other epidemic diseases. This research work focuses on the use of system dynamics in predicting the extent of an epidemic spread so that effective preventive and quarantine measures can be put in place to curb that epidemic. The SIR model forms the basis of the model. The model was developed in NetLogo. Disease parameters and environmental conditions play a role in the spread of an epidemic. Due to this the parameters used in the model included initial population, infectiousness, fatality rate, days to recover, hygiene, vaccination, travel-openings and the number of doctors within the community. The efficiency of the developed model was tested using data from two disease outbreaks: Ebola and Influenza. The model proved itself to be efficient in predicting the infected and death cases which were very close to the real-life data.
Abstract: The outbreaks of infectious diseases have had a huge impact on the human society. Researchers have developed models aimed at understanding how various infectious diseases spread in communities and also proposed control measures that can minimize or stop the spread of the diseases. Most researchers have developed stochastic mathematical models which...
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Prioritisation of Crude Oil Contaminated Sites to Inform Risk Decision Making Using Soil Quality Index
Douglas Reward Kokah,
Reuben Nwomandah Okparanma,
Samuel l Tari Raphae
Issue:
Volume 4, Issue 4, August 2019
Pages:
79-83
Received:
30 July 2019
Accepted:
19 August 2019
Published:
17 September 2019
Abstract: Crude oil contaminated sites delineation by soil quality index (SQI) is presented. This study used SQI proposed by the Canadian Council of Ministers of the Environment (CCME) to delineate three genuinely petroleum-contaminated sites in the Niger Delta, Nigeria to prioritise sites to inform risk decision making and/or remediation. In assessing the potential impact on human health risks at the contaminated sites, soil screening levels (SL) and gas chromatography-mass spectrometry (GC-MS) reference concentrations of total petroleum hydrocarbon (TPH) fractions with higher exposure potential (nC10-nC16, nC16-nC35, nC35-nC40), and risk indicator compound (benzo[a]pyrene) were used in calculating the SQI scores. The sites were assessed by scoring them on a scale spanning from 0 to 100, where 0 indicates a very high level of human health risks and 100 indicates no action is required. The following results were obtained: (a) Site 1, SQI=36.9. This indicates high priority for remediation; (b) Site 2, SQI=49.1, which implies there is high priority for remediation and (c) Site 3 (SQI=45), which means site 3 requires high priority for remedial action. Thus, SQI method can be used to prioritse crude oil contaminated sites to enhance risk classification and decision-making and provide further insight to the contaminated land sector.
Abstract: Crude oil contaminated sites delineation by soil quality index (SQI) is presented. This study used SQI proposed by the Canadian Council of Ministers of the Environment (CCME) to delineate three genuinely petroleum-contaminated sites in the Niger Delta, Nigeria to prioritise sites to inform risk decision making and/or remediation. In assessing the p...
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Quantifying the Uncertainty of Identified Parameters of Prestressed Concrete Poles Using the Experimental Measurements and Different Optimization Methods
Issue:
Volume 4, Issue 4, August 2019
Pages:
84-92
Received:
15 August 2019
Accepted:
6 September 2019
Published:
20 September 2019
Abstract: Prestressed concrete poles nowadays are widely used in supporting the catenary cables of train systems. Compared to their importance to the functionality of the train system, this type of structures have not yet received adequate attention from researchers. We have started tracing the changes in the dynamic behavior of these poles caused by the train passing and the degradation of the materials over a long-time period. In this aim, we installed a structural monitoring system on three of them along one of the high-speed train tracks in Germany. The efficient analysis of the recorded measurements by this system requires a well-known data covering the real material properties of the given structures considering uncertainties of the different parameters. In this paper, we inversely identify the material properties of the poles using deterministic and probabilistic approaches based on the experimental measurements of a full-scale structure and Finite Elements Models. In the deterministic approach, the parameters are identified using the simplex optimization algorithm. Uncertainty of the identified parameters is quantified using a Markov Estimator. In the probabilistic approach, Bayesian inference is utilized for better estimation of the probability distribution of the parameters. Both approaches are suitable for the estimation of mean values of the parameters. The Bayesian method, even though computationally more demanding, is additionally suitable for determining the probability distributions and quantifying the uncertainties of the identified parameters and the correlations between each pair of them. The results show the efficiency of each approach to identify the parameters of the poles. For a rough estimation of the mean values, we recommend the deterministic approach as a simple tool. Conversely, the Bayesian approach is recommended for more detailed and accurate estimation.
Abstract: Prestressed concrete poles nowadays are widely used in supporting the catenary cables of train systems. Compared to their importance to the functionality of the train system, this type of structures have not yet received adequate attention from researchers. We have started tracing the changes in the dynamic behavior of these poles caused by the tra...
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