Search results for: risk prediction model

Authors: Najibullah M, Soumendra Nath Kuiry

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Dams and reservoirs are perceived for their estimable alms to irrigation, water supply, flood control, electricity generation, etc. which civilize the prosperity and wealth of society across the world. Meantime the dam breach could cause devastating flood that can threat to the human lives and properties. Failures of large dams remain fortunately very seldom events. Nevertheless, a number of occurrences have been recorded in the world, corresponding in an average to one to two failures worldwide every year. Some of those accidents have caused catastrophic consequences. So it is decisive to predict the dam break flow for emergency planning and preparedness, as it poses high risk to life and property. To mitigate the adverse impact of dam break, modeling is necessary to gain a good understanding of the temporal and spatial evolution of the dam-break floods. This study will mainly deal with one-dimensional (1D) dam break modeling. Less commonly used in the hydraulic research community, another possible option for modeling the rapidly varied dam-break flows is the extended Boussinesq equations (BEs), which can describe the dynamics of short waves with a reasonable accuracy. Unlike the Shallow Water Equations (SWEs), the BEs taken into account the wave dispersion and non-hydrostatic pressure distribution. To capture the dam-break oscillations accurately it is very much needed of at least fourth-order accurate numerical scheme to discretize the third-order dispersion terms present in the extended BEs. The scope of this work is therefore to develop an 1D fourth-order accurate in both space and time Boussinesq model for dam-break flow analysis by using finite-volume / finite difference scheme. The spatial discretization of the flux and dispersion terms achieved through a combination of finite-volume and finite difference approximations. The flux term, was solved using a finite-volume discretization whereas the bed source and dispersion term, were discretized using centered finite-difference scheme. Time integration achieved in two stages, namely the third-order Adams Basforth predictor stage and the fourth-order Adams Moulton corrector stage. Implementation of the 1D Boussinesq model done using PYTHON 2.7.5. Evaluation of the performance of the developed model predicted as compared with the volume of fluid (VOF) based commercial model ANSYS-CFX. The developed model is used to analyze the risk of cascading dam failures similar to the Panshet dam failure in 1961 that took place in Pune, India. Nevertheless, this model can be used to predict wave overtopping accurately compared to shallow water models for designing coastal protection structures.

Keywords: Boussinesq equation, Coastal protection, Dam-break flow, One-dimensional model

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Authors: Ghada Abo-Zaid

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The main objective of this study was to examine the association between the elevated level of CRP and incidence of hypertension before and after adjusting by age, BMI, gender, SES, smoking, diabetes, cholesterol LDL and cholesterol HDL and to determine whether the association were differ by race. Method: Cross sectional data for participations from age 17 to age 74 years who included in The National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010 were analysed. CRP level was classified into three categories ( > 3mg/L, between 1mg/LL and 3mg/L, and < 3 mg/L). Blood pressure categorization was done using JNC 7 algorithm Hypertension defined as either systolic blood pressure (SBP) of 140 mmHg or more and disystolic blood pressure (DBP) of 90mmHg or greater, otherwise a self-reported prior diagnosis by a physician. Pre-hypertension was defined as (139 > SBP > 120 or 89 > DPB > 80). Multinominal regression model was undertaken to measure the association between CRP level and hypertension. Results: In univariable models, CRP concentrations > 3 mg/L were associated with a 73% greater risk of incident hypertension compared with CRP concentrations < 1 mg/L (Hypertension: odds ratio [OR] = 1.73; 95% confidence interval [CI], 1.50-1.99). Ethnic comparisons showed that American Mexican had the highest risk of incident hypertension (odds ratio [OR] = 2.39; 95% confidence interval [CI], 2.21-2.58).This risk was statistically insignificant, however, either after controlling by other variables (Hypertension: OR = 0.75; 95% CI, 0.52-1.08,), or categorized by race [American Mexican: odds ratio [OR] = 1.58; 95% confidence interval [CI], 0,58-4.26, Other Hispanic: odds ratio [OR] = 0.87; 95% confidence interval [CI], 0.19-4.42, Non-Hispanic white: odds ratio [OR] = 0.90; 95% confidence interval [CI], 0.50-1.59, Non-Hispanic Black: odds ratio [OR] = 0.44; 95% confidence interval [CI], 0.22-0,87]. The same results were found for pre-hypertension, and the Non-Hispanic black showed the highest significant risk for Pre-Hypertension (odds ratio [OR] = 1.60; 95% confidence interval [CI], 1.26-2.03). When CRP concentrations were between 1.0-3.0 mg/L, in an unadjusted models prehypertension was associated with higher likelihood of elevated CRP (OR = 1.37; 95% CI, 1.15-1.62). The same relationship was maintained in Non-Hispanic white, Non-Hispanic black, and other race (Non-Hispanic white: OR = 1.24; 95% CI, 1.03-1.48, Non-Hispanic black: OR = 1.60; 95% CI, 1.27-2.03, other race: OR = 2.50; 95% CI, 1.32-4.74) while the association was insignificant with American Mexican and other Hispanic. In the adjusted model, the relationship between CRP and prehypertension were no longer available. In contrary, Hypertension was not independently associated with elevated CRP, and the results were the same after grouped by race or adjusted by the confounder variables. The same results were obtained when SBP or DBP were on a continuous measure. Conclusions: This study confirmed the existence of an association between hypertension, prehypertension and elevated level of CRP, however this association was no longer available after adjusting by other variables. Ethic group differences were statistically significant at the univariable models, while it disappeared after controlling by other variables.

Keywords: CRP, hypertension, ethnicity, NHANES, blood pressure

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Authors: Yazan Al-Kofahi, Jamal Alqawasmi.

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In this study, a comprehensive literature review (SLR) was conducted, with the main goal of assessing the existing literature about how artificial intelligence (AI), machine learning (ML), deep learning (DL) models are used in sustainable architecture applications and issues including thermal comfort satisfaction, energy efficiency, cost prediction and many others issues. For this reason, the search strategy was initiated by using different databases, including Scopus, Springer and Google Scholar. The inclusion criteria were used by two research strings related to DL, ML and sustainable architecture. Moreover, the timeframe for the inclusion of the papers was open, even though most of the papers were conducted in the previous four years. As a paper filtration strategy, conferences and books were excluded from database search results. Using these inclusion and exclusion criteria, the search was conducted, and a sample of 59 papers was selected as the final included papers in the analysis. The data extraction phase was basically to extract the needed data from these papers, which were analyzed and correlated. The results of this SLR showed that there are many applications of ML and DL in Sustainable buildings, and that this topic is currently trendy. It was found that most of the papers focused their discussions on addressing Environmental Sustainability issues and factors using machine learning predictive models, with a particular emphasis on the use of Decision Tree algorithms. Moreover, it was found that the Random Forest repressor demonstrates strong performance across all feature selection groups in terms of cost prediction of the building as a machine-learning predictive model.

Keywords: machine learning, deep learning, artificial intelligence, sustainable building

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Authors: Jatziri Y. Moreno-Martinez, Arturo Galvan, Xavier Chavez Cardenas, Hiram Arroyo

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Several methods have been utilized to study the prediction of cracking of concrete structural under loading. The finite element analysis is an alternative that shows good results. The aim of this work was the numerical study of the width crack in reinforced concrete beams with dapped ends, these are frequently found in bridge girders and precast concrete construction. Properly restricting cracking is an important aspect of the design in dapped ends, it has been observed that the cracks that exceed the allowable widths are unacceptable in an aggressive environment for reinforcing steel. For simulating the crack width, the discrete crack approach was considered by means of a Cohesive Zone (CZM) Model using a function to represent the crack opening. Two cases of dapped-end were constructed and tested in the laboratory of Structures and Materials of Engineering Institute of UNAM. The first case considers a reinforcement based on hangers as well as on vertical and horizontal ring, the second case considers 50% of the vertical stirrups in the dapped end to the main part of the beam were replaced by an equivalent area (vertically projected) of diagonal bars under. The loading protocol consisted on applying symmetrical loading to reach the service load. The models were performed using the software package ANSYS v. 16.2. The concrete structure was modeled using three-dimensional solid elements SOLID65 capable of cracking in tension and crushing in compression. Drucker-Prager yield surface was used to include the plastic deformations. The reinforcement was introduced with smeared approach. Interface delamination was modeled by traditional fracture mechanics methods such as the nodal release technique adopting softening relationships between tractions and the separations, which in turn introduce a critical fracture energy that is also the energy required to break apart the interface surfaces. This technique is called CZM. The interface surfaces of the materials are represented by a contact elements Surface-to-Surface (CONTA173) with bonded (initial contact). The Mode I dominated bilinear CZM model assumes that the separation of the material interface is dominated by the displacement jump normal to the interface. Furthermore, the opening crack was taken into consideration according to the maximum normal contact stress, the contact gap at the completion of debonding, and the maximum equivalent tangential contact stress. The contact elements were placed in the crack re-entrant corner. To validate the proposed approach, the results obtained with the previous procedure are compared with experimental test. A good correlation between the experimental and numerical Load-Displacement curves was presented, the numerical models also allowed to obtain the load-crack width curves. In these two cases, the proposed model confirms the capability of predicting the maximum crack width, with an error of ± 30 %. Finally, the orientation of the crack is a fundamental for the prediction of crack width. The results regarding the crack width can be considered as good from the practical point view. Load-Displacement curve of the test and the location of the crack were able to obtain favorable results.

Keywords: cohesive zone model, dapped-end beams, discrete crack approach, finite element analysis

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Authors: Mohammed Islam, Jungyong Wang, Dong Cheol Seo

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The Smoothed Particle Hydrodynamics (SPH) method is a novel, meshless, and Lagrangian technique based numerical method that has shown promises to accurately predict the hydrodynamics of water and structure interactions in violent flow conditions. The main goal of this study is to build confidence on the versatility of the Smoothed Particle Hydrodynamics (SPH) based tool, to use it as a complementary tool to the physical model testing capabilities and support research need for the performance evaluation of ships and offshore platforms exposed to an extreme and harsh environment. In the current endeavor, an open-sourced SPH-based tool was used and validated for modeling and predictions of the hydrodynamic interactions of a 6-DOF ship and bergy bits. The study involved the modeling of a modern generic drillship and simplified bergy bits in floating and towing scenarios and in regular and irregular wave conditions. The predictions were validated using the model-scale measurements on a moored ship towed at multiple oblique angles approaching a floating bergy bit in waves. Overall, this study results in a thorough comparison between the model scale measurements and the prediction outcomes from the SPH tool for performance and accuracy. The SPH predicted ship motions and forces were primarily within ±5% of the measurements. The velocity and pressure distribution and wave characteristics over the free surface depicts realistic interactions of the wave, ship, and the bergy bit. This work identifies and presents several challenges in preparing the input file, particularly while defining the mass properties of complex geometry, the computational requirements, and the post-processing of the outcomes.

Keywords: SPH, ship and bergy bit, hydrodynamic interactions, model validation, physical model testing

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Authors: Zane Turner, Kevin Labille, Susan Gauch

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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We present a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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Authors: Zane Turner, Kevin Labille, Susan Gauch

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Sentiment analysis is a broad and expanding field that aims to extract and classify opinions from textual data. Lexicon-based approaches are based on the use of a sentiment lexicon, i.e., a list of words each mapped to a sentiment score, to rate the sentiment of a text chunk. Our work focuses on predicting stock price change using a sentiment lexicon built from financial conference call logs. We introduce a method to generate a sentiment lexicon based upon an existing probabilistic approach. By using a domain-specific lexicon, we outperform traditional techniques and demonstrate that domain-specific sentiment lexicons provide higher accuracy than generic sentiment lexicons when predicting stock price change.

Keywords: computational finance, sentiment analysis, sentiment lexicon, stock movement prediction

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Authors: Alev Atak

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In this paper, we aim to create a financial sentiment index by investigating the company’s voluntary information disclosures. We retrieve structured content from BIST 100 companies’ financial reports for the period 1998-2018 and extract relevant financial information for sentiment analysis through Natural Language Processing. We measure strategy-related disclosures and their cross-sectional variation and classify report content into generic sections using synonym lists divided into four main categories according to their liquidity risk profile, risk positions, intra-annual information, and exposure to risk. We use Word Error Rate and Cosin Similarity for comparing and measuring text similarity and derivation in sets of texts. In addition to performing text extraction, we will provide a range of text analysis options, such as the readability metrics, word counts using pre-determined lists (e.g., forward-looking, uncertainty, tone, etc.), and comparison with reference corpus (word, parts of speech and semantic level). Therefore, we create an adequate analytical tool and a financial dictionary to depict the importance of granular financial disclosure for investors to identify correctly the risk-taking behavior and hence make the aggregated effects traceable.

Keywords: financial sentiment, machine learning, information disclosure, risk

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Authors: Tigabu Dagne Akal

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While advances in computer and communications technology have made the network ubiquitous, they have also rendered networked systems vulnerable to malicious attacks devised from a distance. These attacks or intrusions start with attackers infiltrating a network through a vulnerable host and then launching further attacks on the local network or Intranet. Nowadays, system administrators and network professionals can attempt to prevent such attacks by developing intrusion detection tools and systems using data mining technology. In this study, the experiments were conducted following the Knowledge Discovery in Database Process Model. The Knowledge Discovery in Database Process Model starts from selection of the datasets. The dataset used in this study has been taken from Massachusetts Institute of Technology Lincoln Laboratory. After taking the data, it has been pre-processed. The major pre-processing activities include fill in missed values, remove outliers; resolve inconsistencies, integration of data that contains both labelled and unlabelled datasets, dimensionality reduction, size reduction and data transformation activity like discretization tasks were done for this study. A total of 21,533 intrusion records are used for training the models. For validating the performance of the selected model a separate 3,397 records are used as a testing set. For building a predictive model for intrusion detection J48 decision tree and the Naïve Bayes algorithms have been tested as a classification approach for both with and without feature selection approaches. The model that was created using 10-fold cross validation using the J48 decision tree algorithm with the default parameter values showed the best classification accuracy. The model has a prediction accuracy of 96.11% on the training datasets and 93.2% on the test dataset to classify the new instances as normal, DOS, U2R, R2L and probe classes. The findings of this study have shown that the data mining methods generates interesting rules that are crucial for intrusion detection and prevention in the networking industry. Future research directions are forwarded to come up an applicable system in the area of the study.

Keywords: intrusion detection, data mining, computer science, data mining

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Authors: Dorota Witkowska, Paweł Gosek, Lukasz Swiecicki, Wojciech Jernajczyk, Bruce J. West, Miroslaw Latka

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In clinical practice, the selection of an antidepressant often degrades to lengthy trial-and-error. In this work we employ a normalized wavelet power of alpha waves as a biomarker of antidepressant treatment response. This novel EEG metric takes into account both non-stationarity and intersubject variability of alpha waves. We recorded resting, 19-channel EEG (closed eyes) in 22 inpatients suffering from unipolar (UD, n=10) or bipolar (BD, n=12) depression. The EEG measurement was done at the end of the short washout period which followed previously unsuccessful pharmacotherapy. The normalized alpha wavelet power of 11 responders was markedly different than that of 11 nonresponders at several, mostly temporoparietal sites. Using the prediction of treatment response based on the normalized alpha wavelet power, we achieved 81.8% sensitivity and 81.8% specificity for channel T4.

Keywords: alpha waves, antidepressant, treatment outcome, wavelet

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Authors: Sujoy Das, M. M. Ghosh

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The thermal conductivity of a fluid can be significantly enhanced by dispersing nano-sized particles in it, and the resultant fluid is termed as "nanofluid". A theoretical model for estimating the thermal conductivity of a nanofluid has been proposed here. It is based on the mechanism that evenly dispersed nanoparticles within a nanofluid undergo Brownian motion in course of which the nanoparticles repeatedly collide with the heat source. During each collision a rapid heat transfer occurs owing to the solid-solid contact. Molecular dynamics (MD) simulation of the collision of nanoparticles with the heat source has shown that there is a pulse-like pick up of heat by the nanoparticles within 20-100 ps, the extent of which depends not only on thermal conductivity of the nanoparticles, but also on the elastic and other physical properties of the nanoparticle. After the collision the nanoparticles undergo Brownian motion in the base fluid and release the excess heat to the surrounding base fluid within 2-10 ms. The Brownian motion and associated temperature variation of the nanoparticles have been modeled by stochastic analysis. Repeated occurrence of these events by the suspended nanoparticles significantly contributes to the characteristic thermal conductivity of the nanofluids, which has been estimated by the present model for a ethylene glycol based nanofluid containing Cu-nanoparticles of size ranging from 8 to 20 nm, with Gaussian size distribution. The prediction of the present model has shown a reasonable agreement with the experimental data available in literature.

Keywords: brownian dynamics, molecular dynamics, nanofluid, thermal conductivity

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Authors: Gavin Quibell, Martin Kleynhans, Margot Soler

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The Sendai Framework notes that disaster risk reduction is essential for sustainable development, and Disaster Risk Reduction is included in 3 of the Sustainable Development Goals (SDGs), and 4 of the SDG targets. However, apart from promoting better governance and resourcing of disaster management agencies, little guidance is given how low-income nations can balance investments across the SDGs to achieve sustainable development in an increasingly climate vulnerable world with increasing prevalence of flood and drought disasters. As one of the world’s poorest nations, Malawi must balance investments across all the SDGs. This paper explores how Malawi’s National Guidelines for Community-based Flood Risk Management integrate sustainable development and flood management objectives at different administrative levels. While Malawi periodically suffers from large, widespread flooding, the greatest impacts are felt through the smaller annual floods and flash floods. The Guidelines address this through principles that recognize that while the protection of human life is the most important priority for flood risk management, addressing the impacts of floods on the rural poor and the economy requires different approaches. The National Guidelines are therefore underpinned by the following; 1. In the short-term investments in flood risk management must focus on breaking the poverty – vulnerability cycle; 2. In the long-term investments in the other SDGs will have the greatest flood risk management benefits; 3. If measures are in place to prevent loss of life and protect strategic infrastructure, it is better to protect more people against small and medium size floods than fewer people against larger floods; 4. Flood prevention measures should focus on small (1:5 return period) floods; 5. Flood protection measures should focus on small and medium floods (1:20 return period) while minimizing the risk of failure in larger floods; 6. The impacts of larger floods ( > 1:50) must be addressed through improved preparedness; 7. The impacts of climate change on flood frequencies are best addressed by focusing on growth not overdesign; and 8. Manage floods and droughts conjunctively. The National Guidelines weave these principles into Malawi’s approach to flood risk management through recommendations for planning and implementing flood prevention, protection and preparedness measures at district, traditional authority and village levels.

Keywords: flood risk management in low-income countries, sustainable development, investments in prevention, protection and preparedness, community-based flood risk management, Malawi

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Authors: Mohammad Namazi, Mohammad Sadeghzadeh Maharluie

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Predicting earnings management is vital for the capital market participants, financial analysts and managers. The aim of this research is attempting to respond to this query: Is there a significant difference between the regression model and neural networks’ models in predicting earnings management, and which one leads to a superior prediction of it? In approaching this question, a Linear Regression (LR) model was compared with two neural networks including Multi-Layer Perceptron (MLP), and Generalized Regression Neural Network (GRNN). The population of this study includes 94 listed companies in Tehran Stock Exchange (TSE) market from 2003 to 2011. After the results of all models were acquired, ANOVA was exerted to test the hypotheses. In general, the summary of statistical results showed that the precision of GRNN did not exhibit a significant difference in comparison with MLP. In addition, the mean square error of the MLP and GRNN showed a significant difference with the multi variable LR model. These findings support the notion of nonlinear behavior of the earnings management. Therefore, it is more appropriate for capital market participants to analyze earnings management based upon neural networks techniques, and not to adopt linear regression models.

Keywords: earnings management, generalized linear regression, neural networks multi-layer perceptron, Tehran stock exchange

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Authors: Yuchao Yao

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As two of the main characteristics of Chinese demographic trends, increasing divorce rates and decreasing fertility rates both shaped the population structure in the recent decade. Figuring out to what extent can be having a child make a difference in the divorce rate of a couple will not only draw a picture of Chinese families but also bring about a new perspective to evaluate the Chinese child-breeding policies. Based on China Family Panel Studies (CFPS) Data 2010-2018, this paper provides a systematic evaluation of how children influence a couple’s marital stability through a series of empirical models. Using survival analysis and propensity score matching (PSM) model, this paper finds that the number and age of children that a couple has mattered in consolidating marital relationship, and these effects vary little over time; during the last decade, newly having children can in fact decrease the possibility of divorce for Chinese couples; the such decreasing effect is largely due to the birth of a second child. As this is an inclusive attempt to study and compare not only the effects but also the causality of children on divorce risk in the last decade, the results of this research will do a good summary of the status quo of divorce in China. Furthermore, this paper provides implications for further reforming the current marriage and child-breeding policies.

Keywords: divorce risk, fertility, China, survival analysis, propensity score matching

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Authors: Oussama Derdous, Lakhdar Djemili, Hamza Bouchahed

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The consequences of a dam breach can be devastating; both in terms of lives lost and damaged infrastructure and property. Hydraulic modeling provides a clear picture of the possible consequences of partial or complete failure of a dam, which is the key to carry out emergency planning and conduct reliable risk assessments. In this paper, the MIKE11 model developed by the Danish Hydrologic Institute (DHI) was used to simulate the flood wave propagation associated with a potential failure analysis failure of Zardezas dam located in the city of Skikda in the North East of Algeria. MIKE11 results including inundation maps and the representative channel/valley cross-sections depicting flow depth and maximal flow velocities showed that Zardezas reservoir presents a significant risk to downstream areas in the event of a dam failure. These results can be used as the basis of the development of an Emergency Action Plan (EAP).The main objective of this plan is to predict the appropriate steps to avoid or at least decrease the consequences of unexpected failure of Zardezas dam.

Keywords: MIKE11, dam break, inundation maps, emergency action plan

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Authors: C. Brandt, R. Christopher, N. Damons

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Background: Soccer is one of the most common sports in the world. It is associated with a significant chance of injury either during training or during the course of an actual match. Studies on the epidemiology of soccer injuries have been widely conducted, but methodological appraisal is lacking to make evidence-based decisions. Objectives: The purpose of this study was to conduct a systematic review of common injuries in soccer and their risk factors. Methods: A systematic review was performed based on the Joanna Briggs Institute procedure for conducting systematic reviews. Databases such as SPORT Discus, Cinahl, Medline, Science Direct, PubMed, and grey literature were searched. The quality of selected studies was rated, and data extracted and tabulated. Plot data analysis was done, and incidence rates and odds ratios were calculated, with their respective 95% confidence intervals. I² statistic was used to determine the proportion of variation across studies. Results: The search yielded 62 studies, of which 21 were screened for inclusion. A total of 16 studies were included for the analysis, ten for qualitative and six for quantitative analysis. The included studies had, on average, a low risk of bias and good methodological quality. The heterogeneity amongst the pooled studies was, however, statistically significant (χ²-p value < 0.001). The pooled results indicated a high incidence of soccer injuries at an incidence rate of 6.83 per 1000 hours of play. The pooled results also showed significant evidence of risk factors and the likelihood of injury occurrence in relation to these risk factors (OR=1.12 95% CI 1.07; 1.17). Conclusion: Although multiple studies are available on the epidemiology of soccer injuries and risk factors, only a limited number of studies were of sound methodology to be included in a review. There was also significant heterogeneity amongst the studies. The incidence rate of common soccer injuries was found to be 6.83 per 1000 hours of play. This incidence rate is lower than the values reported by the majority of previous studies on the occurrence of common soccer injuries. The types of common soccer injuries found by this review support the soccer injuries pattern reported in existing literature as muscle strain and ligament sprain of varying severity, especially in the lower limbs. The risk factors that emerged from this systematic review are predominantly intrinsic risk factors. The risk factors increase the risk of traumatic and overuse injuries of the lower extremities such as hamstrings and groin strains, knee and ankle sprains, and contusion.

Keywords: incidence, prevalence, risk factors, soccer injuries

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Authors: Dib Imane, Chettah Wahid, Khedidja Abdelhamid

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The plain of Gadaïne - Ain Yaghout, located in the wilaya of Batna (Eastern Algeria), experiences intensive human activities, particularly in agricultural practices which are accompanied by an increasing use of chemical fertilizers and manure. These activities lead to a degradation of the quality of water resources. In order to protect the quality of groundwater in this plain and formulate effective strategies to mitigate or avoid any contamination of groundwater, a risk assessment using the European method known as “COSTE Action 620” was applied to the mio-. plio-quaternary aquifer of this plain. Risk assessment requires the identification of existing dangers and their potential impact on groundwater by using a system of evaluation and weighting. In addition, it also requires the integration of the hydrogeological factors that influence the movement of contaminants by means of the intrinsic vulnerability maps of groundwater, which were produced according to the modified DRASTIC method. The overall danger on the plain ranges from very low to high. Farms containing stables, houses detached from the public sewer system, and sometimes manure piles were assigned a weighting factor expressing the highest degree of harmfulness; this created a medium to high danger index. Large areas for agricultural practice and grazing are characterized, successively, by low to very low danger. Therefore, the risks present at the study site are classified according to a range from medium to very high-risk intensity. These classes successively represent 3%, 49%, and 0.2% of the surface of the plain. Cultivated land and farms present a high to very high level of risk successively. In addition, with the exception of the salt mine, which presents a very high level of risk, the gas stations and cemeteries, as well as the railway line, represent a high level of risk.

Keywords: semi-arid, quality of water resources, risk assessment, vulnerability, contaminants

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Authors: R. H. Fattepur, Sameer R. Fattepur, D. K. Sreekantha

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Dairy Farming is one of the key industries in India. India is the leading producer and also the consumer of milk, milk-based products in the world. In this paper, we have attempted to the replace the human expert system and to develop an artificial expert system prototype to increase the speed and accuracy of decision making dairy farming credit risk evaluation. Fuzzy logic is used for dealing with uncertainty, vague and acquired knowledge, fuzzy rule base method is used for representing this knowledge for building an effective expert system.

Keywords: expert system, fuzzy logic, knowledge base, dairy farming, credit risk

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Authors: Muhammad Zaman Shakir, Mingfa Yao, Zohaib Iqbal

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This study proposed four Jet fuel surrogate (S1, S2 S3, and 4) with careful selection of seven large hydrocarbon fuel components, ranging from C₉-C₁₆ of higher molecular weight and higher boiling point, adapting the standard molecular distribution size of the actual jet fuel. The surrogate was composed of seven components, including n-propyl cyclohexane (C₉H₁₈), n- propylbenzene (C₉H₁₂), n-undecane (C₁₁H₂₄), n- dodecane (C₁₂H₂₆), n-tetradecane (C₁₄H₃₀), n-hexadecane (C₁₆H₃₄) and iso-cetane (iC₁₆H₃₄). The skeletal jet fuel surrogate reaction mechanism was developed by two approaches, firstly based on a decoupling methodology by describing the C₄ -C₁₆ skeletal mechanism for the oxidation of heavy hydrocarbons and a detailed H₂ /CO/C₁ mechanism for prediction of oxidation of small hydrocarbons. The combined skeletal jet fuel surrogate mechanism was compressed into 128 species, and 355 reactions and thereby can be used in computational fluid dynamics (CFD) simulation. The extensive validation was performed for individual single-component including ignition delay time, species concentrations profile and laminar flame speed based on various fundamental experiments under wide operating conditions, and for their blended mixture, among all the surrogate, S1 has been extensively validated against the experimental data in a shock tube, rapid compression machine, jet-stirred reactor, counterflow flame, and premixed laminar flame over wide ranges of temperature (700-1700 K), pressure (8-50 atm), and equivalence ratio (0.5-2.0) to capture the properties target fuel Jet-A, while the rest of three surrogate S2, S3 and S4 has been validated for Shock Tube ignition delay time only to capture the ignition characteristic of target fuel S-8 & GTL, IPK and RP-3 respectively. Based on the newly proposed HyChem model, another four surrogate with similar components and composition, was developed and parallel validations data was used as followed for previously developed surrogate but at high-temperature condition only. After testing the mechanism prediction performance of surrogates developed by the decoupling methodology, the comparison was done with the results of surrogates developed by the HyChem model. It was observed that all of four proposed surrogates in this study showed good agreement with the experimental measurements and the study comes to this conclusion that like the decoupling methodology HyChem model also has a great potential for the development of oxidation mechanism for heavy alkanes because of applicability, simplicity, and compactness.

Keywords: computational fluid dynamics, decoupling methodology Hychem, jet fuel, surrogate, skeletal mechanism

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Authors: Geng Xiangren, Liu Lei, Gui Ye-Wei, Tang Wei, Wang An-ling

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The malfunction of thermal protection system (TPS) caused by aerodynamic heating is a latent trouble to aircraft structure safety. Accurately predicting the structure temperature field is quite important for the TPS design of hypersonic vehicle. Since Thornton’s work in 1988, the coupled method of aerodynamic heating and heat transfer has developed rapidly. However, little attention has been paid to the influence of structural deformation on aerodynamic heating and structural temperature field. In the flight, especially the long-endurance flight, the structural deformation, caused by the aerodynamic heating and temperature rise, has a direct impact on the aerodynamic heating and structural temperature field. Thus, the coupled interaction cannot be neglected. In this paper, based on the method of static aero-thermo-elasticity, considering the influence of aero-thermo-elasticity deformation, the aerodynamic heating and heat transfer coupled results of hypersonic vehicle wing model were calculated. The results show that, for the low-curvature region, such as fuselage or center-section wing, structure deformation has little effect on temperature field. However, for the stagnation region with high curvature, the coupled effect is not negligible. Thus, it is quite important for the structure temperature prediction to take into account the effect of elastic deformation. This work has laid a solid foundation for improving the prediction accuracy of the temperature distribution of aircraft structures and the evaluation capacity of structural performance.

Keywords: aerothermoelasticity, elastic deformation, structural temperature, multi-field coupling

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Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba

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The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.

Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry

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Authors: Etienne Sugewe

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Purpose: The establishment of a positive HIV serologic status of an individual could have been an inhibitory factor to prevent risk behaviours in people living with HIV/AIDS. We conducted a cross-sectional study in order to assess the prevalence and predictors of risk behaviors among HIV-positive people in Douala-Cameroon. Methods: We used pre-checked questionnaires to systematically collect data from four HIV treatment centers in Douala. This was done to some of them during the distribution of drugs and to others during their classical rendezvous between the months of May and July 2012. The Chi-Square and Student t-test were used for cross tabulation of variables; multiple regression analysis was performed to identify predictors of risky sexual behaviours. Results: Of the 330 persons interviewed, sixty percent were reported to have had sexual intercourse after the diagnosis of HIV. We obtained 37% HIV-positive partners, and 63% had HIV- negative partners or partners with unknown status. Among our patients, 45% of the subjects with regular partners reported to have had anal or vaginal sex. Those whose score on the knowledge about HIV/AIDS was < 50% and where 90% of them were less susceptible to the condom during intercourse (p: 0.01). About 74% of patients on ARV were less susceptible to the use of condoms during sexual intercourse (p: 0.03). Conclusion: Risk sexual behaviours among people living with HIV/AIDS are common and potentially expose their partners. For HIV-positive partners, these habits pose a real risk of suprainfection by other strains of HIV. The need to increase awareness and education among people living with HIV is therefore highly recommended.

Keywords: HIV/AIDS, behaviours, HIV positive, Douala, 2012

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Authors: Souhir Chelly, Asma Ben Cheikh, Hela Ghali, Salwa Khefacha, Lamine Dhidah, Mohamed Ben Rejeb, Houyem Said Latiri

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The hospital risk management department is firstly involved in the methodological analysis of grade zero sterilization incidents. The system is based on a subsequent analysis process in compliance with the ongoing requirements of the Haute Autorité de santé (HAS) for a reactive approach to risk, allowing to identify failures and start the appropriate preventive and corrective measures. The use of the association of litigation and risk management (ALARM) method makes easier the grade zero analysis and brings to light the team or institutional, organizational, temporal, individual factors representative of undesirable effects. Two main factors come out again from this analysis, pre-disinfection step of the emergency block unsupervised instrumentalist intern was poorly done since she did not remove the battery from micro air motor. At the sterilization unit, the worker who was not supervised by the nurse did the conditioning of the motor without having checked it if it still contained the battery. The main cause is that the management of human resources was inadequate at both levels, the instrumental trainee in the block who was not supervised by his supervisor and the worker of the sterilization unit who was not supervised by the responsible nurse. There is a lack of research help, advice, and collaboration. The difficulties encountered during this type of analysis are multiple. The first is based on its necessary acceptance by the various actors of care involved, which should not perceive it as a tool leading to individual punishment, but rather as a means to improve their practices.

Keywords: ALARM (Association of Litigation and Risk Management Method), incident, risk management, sterilization

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Authors: Helene Thieblemont, Fariborz Haghighat

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Energy storage systems play a crucial role in decreasing building energy consumption during peak periods and expand the use of renewable energies in buildings. To provide a high building thermal performance, the energy storage system has to be properly controlled to insure a good energy performance while maintaining a satisfactory thermal comfort for building’s occupant. In the case of passive discharge storages, defining in advance the required amount of energy is required to avoid overheating in the building. Consequently, anticipatory supervisory control strategies have been developed forecasting future energy demand and production to coordinate systems. Anticipatory supervisory control strategies are based on some predictions, mainly of the weather forecast. However, if the forecasted hourly outdoor temperature may be found online with a high accuracy, solar radiations predictions are most of the time not available online. To estimate them, this paper proposes an advanced approach based on the forecast of weather conditions. Several methods to correlate hourly weather conditions forecast to real hourly solar radiations are compared. Results show that using weather conditions forecast allows estimating with an acceptable accuracy solar radiations of the next day. Moreover, this technique allows obtaining hourly data that may be used for building models. As a result, this solar radiation prediction model may help to implement model-based controller as Model Predictive Control.

Keywords: anticipatory control, model predictive control, solar radiation forecast, thermal storage

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Authors: Cai Qianyi

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In the midst of global digital revolution, the flow of data poses security threats that call China's existing legislative framework for protecting personal information into question. As a preliminary procedure for risk analysis and prevention, the risk assessment of personal data transmission lacks detailed guidelines for support. Existing provisions reveal unclear responsibilities for network operators and weakened rights for data subjects. Furthermore, the regulatory system's weak operability and a lack of industry self-regulation heighten data transmission hazards. This paper aims to compare the regulatory pathways for data information transmission risks between China and Europe from a legal framework and content perspective. It draws on the “Data Protection Impact Assessment Guidelines” to empower multiple stakeholders, including data processors, controllers, and subjects, while also defining obligations. In conclusion, this paper intends to solve China's digital security shortcomings by developing a more mature regulatory framework and industry self-regulation mechanisms, resulting in a win-win situation for personal data protection and the development of the digital economy.

Keywords: personal information data transmission, risk assessment, DPIA, internet service provider, personal information data transimission, risk assessment

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Afroditi Zamanidou, Dionysios Giannakopoulos, Konstantinos Manolitsis

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A notable amount of electrical energy demand in many countries worldwide is used to cover public energy demand for road, square and other public spaces’ lighting. Renewable energy can contribute in a significant way to the electrical energy demand coverage for public lighting. This paper focuses on the sizing and design of a hybrid energy system (HES) exploiting the solar-wind energy potential to meet the electrical energy needs of lighting roads, squares and other public spaces. Moreover, the proposed HES provides coverage of the electrical energy demand for a Wi-Fi hotspot and a charging hotspot for the end-users. Alongside the sizing of the energy production system of the proposed HES, in order to ensure a reliable supply without interruptions, a storage system is added and sized. Multiple scenarios of energy consumption are assumed and applied in order to optimize the sizing of the energy production system and the energy storage system. A database with meteorological prediction data for 51 areas in Greece is developed in order to assess the possible deployment of the proposed HES. Since there are detailed meteorological prediction data for all 51 areas under investigation, the use of these data is evaluated, comparing them to real meteorological data. The meteorological prediction data are exploited to form three hourly production profiles for each area for every month of the year; minimum, average and maximum energy production. The energy production profiles are combined with the energy consumption scenarios and the sizing results of the energy production system and the energy storage system are extracted and presented for every area. Finally, the economic performance of the proposed HES in terms of Levelized cost of energy is estimated by calculating and assessing construction, operation and maintenance costs.

Keywords: energy production system sizing, Greece’s deployment potential, meteorological prediction data, wind-solar hybrid energy system, levelized cost of energy

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Authors: Warda L. Panondi, Norihiro Izumi

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Sedimentation is a significant threat to the sustainability of reservoirs and their watershed. In the Philippines, the Pulangi watershed experienced a high sediment loss mainly due to land conversions and plantations that showed critical erosion rates beyond the tolerable limit of -10 ton/ha/yr in all of its sub-basin. From this event, the prediction of runoff volume and sediment yield is essential to examine using the country's soil conservation techniques realistically. In this research, the Pulangi watershed was modeled using the soil water assessment tool (SWAT) to predict its watershed basin's annual runoff and sediment yield. For the calibration and validation of the model, the SWAT-CUP was utilized. The model was calibrated with monthly discharge data for 1990-1993 and validated for 1994-1997. Simultaneously, the sediment yield was calibrated in 2014 and validated in 2015 because of limited observed datasets. Uncertainty analysis and calculation of efficiency indexes were accomplished through the SUFI-2 algorithm. According to the coefficient of determination (R2), Nash Sutcliffe efficiency (NSE), King-Gupta efficiency (KGE), and PBIAS, the calculation of streamflow indicates a good performance for both calibration and validation periods while the sediment yield resulted in a satisfactory performance for both calibration and validation. Therefore, this study was able to identify the most critical sub-basin and severe needs of soil conservation. Furthermore, this study will provide baseline information to prevent floods and landslides and serve as a useful reference for land-use policies and watershed management and sustainability in the Pulangi watershed.

Keywords: Pulangi watershed, sediment yield, streamflow, SWAT model

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Authors: Naser Kazemi Eilaki, Ilona Heldal, Carolyn Ahmer, Bjarne Christian Hagen

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Elderly people and people with disabilities are recognized as at-risk groups when it comes to egress and travel from hazard zone to a safe place. One's disability can negatively influence her or his escape time, and this becomes even more important when people from this target group live alone. While earlier studies have frequently addressed quantitative measurements regarding at-risk groups' physical characteristics (e.g., their speed of travel), this paper considers the influence of at-risk groups’ characteristics on their decision and determining better escape routes. Most of evacuation models are based on mapping people's movement and their behaviour to summation times for common activity types on a timeline. Usually, timeline models estimate required safe egress time (RSET) as a sum of four timespans: detection, alarm, premovement, and movement time, and compare this with the available safe egress time (ASET) to determine what is influencing the margin of safety.This paper presents a cross-sectional study for identifying the most critical items on RSET and people's decision-making and with possibilities to include safety knowledge regarding people with physical or cognitive functional impairments. The result will contribute to increased knowledge on considering at-risk groups and disabilities for designing and developing safe escape routes. The expected results can be an asset to predict the probabilistic behavioural pattern of at-risk groups and necessary components for defining a framework for understanding how stakeholders can consider various disabilities when determining the margin of safety for a safe escape route.

Keywords: fire safety, evacuation, decision-making, at-risk groups

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Authors: A. A. Adebayo, O. Osibanjo

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Informal electronic waste (e-waste) processing is a crude method of recycling, which is on the increase in Nigeria. The release of hazardous substances such as heavy metals (HMs) into the environment during informal e-waste processing has been a major concern. However, there is insufficient information on environmental contamination from e-waste recycling, associated ecological risk in Alaba International Market, a major electronic market in Lagos, Nigeria. The aims of this study were to determine the levels of HMs in soil, resulting from the e-waste recycling; and also assess associated ecological risks in Alaba international market. Samples of soils (334) were randomly collected seasonally for three years from fourteen selected e-waste activity points and two control sites. The samples were digested using standard methods and HMs analysed by inductive coupled plasma optical emission. Ecological risk was estimated using Ecological Risk index (ER), Potential Ecological Risk index (RI), Index of geoaccumulation (Igeo), Contamination factor (Cf) and degree of contamination factor (Cdeg). The concentrations range of HMs (mg/kg) in soil were: 16.7-11200.0 (Pb); 14.3-22600.0 (Cu); 1.90-6280.0 (Ni), 39.5-4570.0 (Zn); 0.79-12300.0 (Sn); 0.02-138.0 (Cd); 12.7-1710.0 (Ba); 0.18-131.0 (Cr); 0.07-28.0 (V), while As was below detection limit. Concentrations range in control soils were 1.36-9.70 (Pb), 2.06-7.60 (Cu), 1.25-5.11 (Ni), 3.62-15.9 (Zn), BDL-0.56 (Sn), BDL-0.01 (Cd), 14.6-47.6 (Ba), 0.21–12.2 (Cr) and 0.22-22.2 (V). The trend in ecological risk index was in the order Cu > Pb > Ni > Zn > Cr > Cd > Ba > V. The potential ecological risk index with respect to informal e-waste activities were: burning > dismantling > disposal > stockpiling. The index of geo accumulation indices revealed that soils were extremely polluted with Cd, Cu, Pb, Zn and Ni. The contamination factor indicated that 93% of the studied areas have very high contamination status for Pb, Cu, Ba, Sn and Co while Cr and Cd were in the moderately contaminated status. The degree of contamination decreased in the order of Sn > Cu > Pb >> Zn > Ba > Co > Ni > V > Cr > Cd. Heavy metal contamination of Alaba international market environment resulting from informal e-waste processing was established. Proper management of e-waste and remediation of the market environment are recommended to minimize the ecological risks.

Keywords: Alaba international market, ecological risk, electronic waste, heavy metal contamination

Procedia PDF Downloads 183