Search results for: credit risk estimation

Authors: Chloe E. Edwards, Yasaman Shahtaheri

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Risk management plays a fundamental role in project planning and delivery. The purpose of incorporating risk management into project management practices is to identify and address uncertainties related to key project-related activities. The uncertainties, known as risk events, can relate to project deliverables that are quantifiable and are often measured by impact to project schedule, cost, or environmental impact. Risk management should be incorporated as an iterative practice throughout the planning, execution, and commissioning phases of a project. This paper specifically examines how risk management contributes to effective project planning and delivery through a case study of a transportation project. This case study focused solely on impacts to project schedule regarding three milestones: readiness for delivery, readiness for testing and commissioning, and completion of the facility. The case study followed the ISO 31000: Risk Management – Guidelines. The key factors that are outlined by these guidelines include understanding the scope and context of the project, conducting a risk assessment including identification, analysis, and evaluation, and lastly, risk treatment through mitigation measures. This process requires continuous consultation with subject matter experts and monitoring to iteratively update the risks accordingly. The risk identification process led to a total of fourteen risks related to design, permitting, construction, and commissioning. The analysis involved running 1,000 Monte Carlo simulations through @RISK 8.0 Industrial software to determine potential milestone completion dates based on the project baseline schedule. These dates include the best case, most likely case, and worst case to provide an estimated delay for each milestone. Evaluation of these results provided insight into which risks were the highest contributors to the projected milestone completion dates. Based on the analysis results, the risk management team was able to provide recommendations for mitigation measures to reduce the likelihood of risks occurring. The risk management team also provided recommendations for managing the identified risks and project activities moving forward to meet the most likely or best-case milestone completion dates.

Keywords: construction management, monte carlo simulation, project delivery, risk assessment, transportation engineering

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Authors: Mustafa Dogru, Ruveyda Komurlu

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Companies and professionals in the construction sector face various risks in every project depending on the characteristics, size, complexity, the location of the projects and the techniques used. Some risks’ effects may increase as the project progresses whereas new risks may emerge. Because of the ever-changing nature of the risks, risk management is a cyclical process that needs to be repeated throughout the project. Since the risks threaten the success of the project, risk management is an important part of the entire project management process. The aims of this study are to emphasize the importance of risk management in construction projects, summarize the risk identification process, and introduce a number of methods for preventing risks such as alternative design, checklists, prototyping and test-analysis-correction technique etc. Following the literature review conducted to list the techniques for preventing risks, case studies has been performed to compare and evaluate the success of the techniques in a number of completed projects with the same typology, performed domestic and international. Findings of the study suggest that controlling and minimizing the level of the risks in construction projects, taking optimal precautions for different risks, and mitigating or eliminating the effects of risks are important in order to prevent additional costs for the project. Additionally, focusing on the risks that have highest impact is the most rational way to minimize the effects of the risks on projects.

Keywords: construction projects, construction management, project management, risk management

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Authors: Lesa A. Thompson, Yoshinori Ikenaka, Victor Wepener, Mayumi Ishizuka

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One method for controlling malaria in endemic regions is the killing of vector mosquitoes using pesticides such as DDT in indoor residual spraying (IRS). This study was carried out to investigate the presence of and human health risk due to DDT and its metabolites (collectively, DDTs) contaminating human food sources in areas where DDT is used for IRS. Free-range chicken products (meat and eggs) were collected from homesteads in KwaZulu-Natal Province in the northeast of South Africa, and fish meat samples from Maputo Bay in neighbouring Mozambique. Samples were analysed for DDTs (o,p’-DDT, p,p’-DDT, o,p’-DDD, p,p’-DDD, o,p’-DDE and p,p’-DDE) using a gas chromatograph with electron capture detector (GC-ECD). DDTs were detected in all food types, with the predominant congener being p,p’-DDE. The presence of p,p’-DDT confirmed recent release of DDT into the environment. By using concentration levels detected in foods and national consumption levels, the risk to human health through consumption of such food products was calculated. In order of risk level, these were: chicken eggs > chicken meat > fish meat. Human risk (carcinogenic) values greater than one suggest there is an increased health risk through consumption of these foods.

Keywords: DDT, food contamination, human health risk, Mozambique, South Africa

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Authors: A. B. Bolkhir, A. Elshafie, T. K. Yousif

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This paper highlights the methods of error estimation in finite element analysis (FEA) results. It indicates that the modeling error could be eliminated by performing finite element analysis with successively finer meshes or by extrapolating response predictions from an orderly sequence of relatively low degree of freedom analysis results. In addition, the paper eliminates the round-off error by running the code at a higher precision. The paper provides application in finite element analysis results. It draws a conclusion based on results of application of methods of error estimation.

Keywords: finite element analysis (FEA), discretization error, round-off error, mesh refinement, richardson extrapolation, monotonic convergence

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Authors: P. Serpytis, K. Azukaitis, U. Gargalskaite, R. Navickas, J. Badariene, V. Dzenkeviciute

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Purpose: Total longitudinal displacement (tLoD) of the common carotid artery (CCA) wall is a novel ultrasound marker of vascular function that can be evaluated using modified speckle tracking techniques. Decreased CCA tLoD has already been shown to be associated with diabetes and was shown to predict one year cardiovascular outcome in patients with suspected coronary artery disease (CAD) . The aim of our study was to evaluate if CCA tLoD differ between patients with moderate or high cardiovascular (CV) risk and patients after recent acute myocardial infarction (AMI). Methods: 49 patients (54±6 years) with moderate or high CV risk and 42 patients (58±7 years) after recent AMI were included. All patients were non-diabetic. CCA tLoD was evaluated using GE EchoPAC speckle tracking software and expressed as mean of both sides. Data on systolic blood pressure, total and high density lipoprotein (HDL) cholesterol levels, high sensitivity C-reactive protein (hsCRP) level, smoking status and family history of early CV events was evaluated and assessed for association with CCA tLoD. Results: tLoD of CCA did not differ between patients with moderate or high CV risk and patients with very high CV risk after MI (0.265±0.128 mm vs. 0.237±0.103 mm, p>0.05). Lower tLoD was associated with lower HDL cholesterol levels (r=0.211, p=0.04) and male sex (0.228±0.1 vs. 0.297±0.134, p=0.01). Conclusions: tLoD of CCA did not differ between patients with moderate or high CV risk and patients with very high CV risk after AMI. However, lower CCA tLoD was significantly associated with low HDL cholesterol levels and male sex.

Keywords: total longitudinal displacement, carotid artery, cardiovascular risk, acute myocardial infarction

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Authors: P. S. Hsi, Y. F. Wang, Y. F. Ho, P. C. Hung

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The aim of the present study was to explore the dermal exposure assessment model of chemicals that have been developed abroad and to evaluate the feasibility of chemical dermal exposure assessment model for manufacturing industry in Taiwan. We conducted and analyzed six semi-quantitative risk management tools, including UK - Control of substances hazardous to health ( COSHH ) Europe – Risk assessment of occupational dermal exposure ( RISKOFDERM ), Netherlands - Dose related effect assessment model ( DREAM ), Netherlands – Stoffenmanager ( STOFFEN ), Nicaragua-Dermal exposure ranking method ( DERM ) and USA / Canada - Public Health Engineering Department ( PHED ). Five types of manufacturing industry were selected to evaluate. The Monte Carlo simulation was used to analyze the sensitivity of each factor, and the correlation between the assessment results of each semi-quantitative model and the exposure factors used in the model was analyzed to understand the important evaluation indicators of the dermal exposure assessment model. To assess the effectiveness of the semi-quantitative assessment models, this study also conduct quantitative dermal exposure results using prediction model and verify the correlation via Pearson's test. Results show that COSHH was unable to determine the strength of its decision factor because the results evaluated at all industries belong to the same risk level. In the DERM model, it can be found that the transmission process, the exposed area, and the clothing protection factor are all positively correlated. In the STOFFEN model, the fugitive, operation, near-field concentrations, the far-field concentration, and the operating time and frequency have a positive correlation. There is a positive correlation between skin exposure, work relative time, and working environment in the DREAM model. In the RISKOFDERM model, the actual exposure situation and exposure time have a positive correlation. We also found high correlation with the DERM and RISKOFDERM models, with coefficient coefficients of 0.92 and 0.93 (p<0.05), respectively. The STOFFEN and DREAM models have poor correlation, the coefficients are 0.24 and 0.29 (p>0.05), respectively. According to the results, both the DERM and RISKOFDERM models are suitable for performance in these selected manufacturing industries. However, considering the small sample size evaluated in this study, more categories of industries should be evaluated to reduce its uncertainty and enhance its applicability in the future.

Keywords: dermal exposure, risk management, quantitative estimation, feasibility evaluation

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Authors: Bouba Oumarou Aboubakar, HongXia Li, Sardar Annes Farooq

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The Belt and Road Initiative’s success strongly depends on the safety of all the million workers on construction projects sites. As the new BRI is directed toward Africa and meets a completely different culture from the Chinese project managers, maintaining low risk for workers risks shall be closely related to cultural sharing and mutual understanding. This is why this work introduces a cultural-wise safety management framework for Chinese Construction projects in Africa. The theoretical contribution of this paper is an improved risk assessment framework that integrates language, culture and difficulty of controlling risk factors into one approach. Practically, this study provides not only a useful tool for project safety management practitioners but the full understanding of all risks that may arise in the BRI projects in Africa.

Keywords: cultural-wise, safety culture, risk assessment, Chinese construction, BRI projects, Africa

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Authors: Masahiro Miyaji

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When a driver happens to be involved in some traffic congestion or after traffic incidents, the driver may fall in a state of anger. State of anger may encounter decisive risk resulting in severer traffic accidents. Preventive safety function using driver’s psychosomatic state with regard to anger may be one of solutions which would avoid that kind of risks. Identifying driver’s anger state is important to create countermeasures to prevent the risk of traffic accidents. As a first step, this research figured out root cause of traffic incidents by means of using Internet survey. From statistical analysis of the survey, dominant psychosomatic states immediately before traffic incidents were haste, distraction, drowsiness and anger. Then, we replicated anger state of a driver while driving, and then, replicated it by means of using driving simulator on bench test basis. Six types of facial expressions including anger were introduced as alternative characteristics. Kohonen neural network was adopted to classify anger state. Then, we created a methodology to detect anger state of a driver in high accuracy. We presented a driving support safety function. The function adapts driver’s anger state in cooperation with an autonomous driving unit to reduce the number of traffic accidents. Consequently, e evaluated reduction rate of driver’s anger in the traffic accident. To validate the estimation results, we referred the reduction rate of Advanced Safety Vehicle (ASV) as well as Intelligent Transportation Systems (ITS).

Keywords: Kohonen neural network, driver’s anger state, reduction of traffic accidents, driver’s state adaptive driving support safety

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Authors: Peng Li, Luan Wang, Haifeng Fei, Renhong Xie, Yibin Rui, Shanhong Guo

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The applications of satellite-based automatic identification system (S-AIS) pave the road for wide-range maritime traffic monitoring and management. But the coverage of satellite’s view includes multiple AIS self-organizing networks, which leads to the collision of AIS signals from different cells. The contribution of this work is to propose an improved multi-channel blind source separation algorithm based on Artificial Bee Colony (ABC) and advanced stochastic optimization to perform separation of the mixed AIS signals. The proposed approach adopts modified ABC algorithm to get an optimized initial separating matrix, which can expedite the initialization bias correction, and utilizes the Adaptive Moment Estimation (Adam) to update the separating matrix by adjusting the learning rate for each parameter dynamically. Simulation results show that the algorithm can speed up convergence and lead to better performance in separation accuracy.

Keywords: satellite-based automatic identification system, blind source separation, artificial bee colony, adaptive moment estimation

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Authors: Gebrehiwot H., Giorgis Bahita

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Firms in Africa experience less financial market in comparison to other emerging and developed countries, thus lagging behind the rest of the world in terms of innovation and growth. Though there are different factors to be considered, underdeveloped financial systems take the lion's share in hindering firm innovation and growth in Africa. Insufficient capacity to innovate is one of the problems facing African businesses. Moreover, a critical challenge faced by firms in Africa is access to finance and the inability of financially constrained firms to grow. Only little is known about how different sources of finance affect firm innovation and growth in Africa, specifically the formal and informal finance effect on firm innovation and growth. This study's aim is to address this gap by using formal and informal finance for working capital and fixed capital and its role in firm innovation and firm growth using firm-level data from the World Bank enterprise survey 2006-2019 with a total of 5661 sample firms from 14 countries based on available data on the selected variables. Additionally, this study examines factors for accessing credit from a formal financial institution. The logit model is used to examine the effect of finance on a firm’s innovation and factors to access formal finance, while the Ordinary List Square (OLS) regression mode is used to investigate the effect of finance on firm growth. 2SLS instrumental variables are used to address the possible endogeneity problem in firm growth and finance-innovation relationships. A result from the logistic regression indicates that both formal and informal finance used for working capital and investment in fixed capital was found to have a significant positive association with product and process innovation. In the case of finance and growth, finding show that positive association of both formal and informal financing to working capital and new investment in fixed capital though the informal has positive relations to firm growth as measured by sale growth but no significant association as measured by employment growth. Formal finance shows more magnitude of effect on innovation and growth when firms use formal finance to finance investment in fixed capital, while informal finance show less compared to formal finance and this confirms previous studies as informal is mainly used for working capital in underdeveloped economies like Africa. The factors that determine credit access: Age, firm size, managerial experience, exporting, gender, and foreign ownership are found to have significant determinant factors in accessing credit from formal and informal sources among the selected sample countries.

Keywords: formal finance, informal finance, innovation, growth

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Authors: Serge B. Provost

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Numerous statistical inference and modeling methodologies are based on sample moments rather than the actual observations. A result justifying the validity of this approach is introduced. More specifically, it will be established that given the first n moments of a sample of size n, one can recover the original n sample points. This implies that a sample of size n and its first associated n moments contain precisely the same amount of information. However, it is efficient to make use of a limited number of initial moments as most of the relevant distributional information is included in them. Two types of density estimation techniques that rely on such moments will be discussed. The first one expresses a density estimate as the product of a suitable base density and a polynomial adjustment whose coefficients are determined by equating the moments of the density estimate to the sample moments. The second one assumes that the derivative of the logarithm of a density function can be represented as a rational function. This gives rise to a system of linear equations involving sample moments, the density estimate is then obtained by solving a differential equation. Unlike kernel density estimation, these methodologies are ideally suited to model ‘big data’ as they only require a limited number of moments, irrespective of the sample size. What is more, they produce simple closed form expressions that are amenable to algebraic manipulations. They also turn out to be more accurate as will be shown in several illustrative examples.

Keywords: density estimation, log-density, polynomial adjustments, sample moments

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Authors: Ali Jahanfar, Brajesh Dubey, Bahram Gharabaghi, Saber Bayat Movahed

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Ever increasing population growth of major urban centers and environmental challenges in siting new landfills have resulted in a growing trend in design of mega-landfills some with extraordinary heights and dangerously steep slopes. Landfill failure mobility risk analysis is one of the most uncertain types of dynamic rheology models due to very large inherent variabilities in the heterogeneous solid waste material shear strength properties. The waste flow of three historic dumpsite and two landfill failures were back-analyzed using run-out modeling with DAN-W model. The travel distances of the waste flow during landfill failures were calculated approach by taking into account variability in material shear strength properties. The probability distribution function for shear strength properties of the waste material were grouped into four major classed based on waste material compaction (landfills versus dumpsites) and composition (high versus low quantity) of high shear strength waste materials such as wood, metal, plastic, paper and cardboard in the waste. This paper presents a probabilistic method for estimation of the spatial extent of waste avalanches, after a potential landfill failure, to create maps of vulnerability scores to inform property owners and residents of the level of the risk.

Keywords: landfill failure, waste flow, Voellmy rheology, friction coefficient, waste compaction and type

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Authors: Nabil Mekaoui, Nacer Jabour, Abdelhamid Allaoui, Abderahim Oulidi

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The reliability of several insurance indexes of the seismic risk is evaluated and compared for an efficient seismic risk coverage of buildings in Morocco, thus, reducing the basic risk. A large database of earthquake ground motions is established from recent seismic events in Morocco and synthetic ground motions compatible with the design spectrum in order to conduct nonlinear time history analyses on three building models representative of the building stock in Morocco. The uninhabitability index is evaluated based on the simulated damage index, then correlated with preselected insurance indexes. Interestingly, the commonly used peak ground acceleration index showed poor correlation when compared with other indexes, such as spectral accelerations at low periods. Recommendations on the choice of suitable insurance indexes are formulated for efficient seismic risk coverage in Morocco.

Keywords: catastrophe modeling, damage, earthquake, reinsurance, seismic hazard, trigger index, vulnerability

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Authors: Xiaodong Li, Peng Gao, Chao-Jung Huang, Shiying Hao, Xuefeng B. Ling, Yongxia Han, Yaqi Zhang, Le Zheng, Chengyin Ye, Modi Liu, Minjie Xia, Changlin Fu, Bo Jin, Karl G. Sylvester, Eric Widen

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Predicting the risk of Pancreatic Adenocarcinoma (PA) in advance can benefit the quality of care and potentially reduce population mortality and morbidity. The aim of this study was to develop and prospectively validate a risk prediction model to identify patients at risk of new incident PA as early as 3 months before the onset of PA in a statewide, general population in Maine. The PA prediction model was developed using Deep Neural Networks, a deep learning algorithm, with a 2-year electronic-health-record (EHR) cohort. Prospective results showed that our model identified 54.35% of all inpatient episodes of PA, and 91.20% of all PA that required subsequent chemoradiotherapy, with a lead-time of up to 3 months and a true alert of 67.62%. The risk assessment tool has attained an improved discriminative ability. It can be immediately deployed to the health system to provide automatic early warnings to adults at risk of PA. It has potential to identify personalized risk factors to facilitate customized PA interventions.

Keywords: cancer prediction, deep learning, electronic health records, pancreatic adenocarcinoma

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Authors: Rania Mousa, Peterson Ozili

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A key agenda of policymakers in developed and developing countries is to increase the level of financial inclusion. Microlending institutions have been recognized as important agents of financial inclusion, which have the potential to achieve this objective and help move toward a more accessible, inclusive, and equitable path to financial sustainability. In that respect, this case study attempts to identify and assess the key initiatives undertaken by Grameen America as it responded to the COVID-19 pandemic within the framework of selected United Nations’ Sustainability Development Goals (UN’s SD Goals). This study goes beyond the stated objective by using the vulnerable group theory and special agent theory of financial inclusion to support the analysis of financial and non-financial information collected from Grameen America’s Annual Reports and audited financial statements. The study follows a qualitative content analysis method to precisely gauge the shift in Grameen’s strategy and focus, as well as to assess the impact of its initiatives on the small business community before and after the pandemic. The findings showcase that Grameen’s longstanding mission to alleviate poverty is in line with the UN’s Sustainability Development Goal 1. Furthermore, Grameen’s commitment to creating partnerships with external organizations to offer credit and non-credit services and support is consistent with UN’s Sustainability Development Goal 17. The study suggests that policymakers should foster the creation of more member-based financial and non-financial institutions which are ethically and morally responsible to their members in both good and bad times.

Keywords: COVID-19, financial inclusion, microfinance, sustainable development, microlending

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Authors: Jun Su Park, Byung Kwan Oh, Jin Woo Hwang, Yousok Kim, Hyo Seon Park

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For the structural safety, the maximum stress calculated from the stress distribution of a structure is widely used. The stress distribution can be estimated by deformed shape of the structure obtained from measurement. Although the estimation of stress is strongly affected by the location and number of sensing points, most studies have conducted the stress estimation without reasonable basis on sensing plan such as the location and number of sensors. In this paper, an optimal sensing technique for estimating the stress distribution is proposed. This technique proposes the optimal location and number of sensing points for a 2-D frame structure while minimizing the error of stress distribution between analytical model and estimation by cubic smoothing splines using genetic algorithm. To verify the proposed method, the optimal sensor measurement technique is applied to simulation tests on 2-D steel frame structure. The simulation tests are performed under various loading scenarios. Through those tests, the optimal sensing plan for the structure is suggested and verified.

Keywords: genetic algorithm, optimal sensing, optimizing sensor placements, steel frame structure

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Authors: Mani Venkatesh, Catarina Delgado, Purvishkumar Patel

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The sustainable supply chain is gaining popularity among practitioners because of increased environmental degradation and stakeholder awareness. On the other hand supply chain, risk management is very crucial for the practitioners as it potentially disrupts supply chain operations. Prediction and addressing the risk caused by social issues in the supply chain is paramount importance to the sustainable enterprise. More recently, the usage of Big data analytics for forecasting business trends has been gaining momentum among professionals. The aim of the research is to explore the application of big data, predictive analytics in successfully mitigating supply chain social risk and demonstrate how such mitigation can help in achieving sustainability (environmental, economic & social). The method involves the identification and validation of social issues in the supply chain by an expert panel and survey. Later, we used a case study to illustrate the application of big data in the successful identification and mitigation of social issues in the supply chain. Our result shows that the company can predict various social issues through big data, predictive analytics and mitigate the social risk. We also discuss the implication of this research to the body of knowledge and practice.

Keywords: big data, sustainability, supply chain social sustainability, social risk, case study

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Authors: U. S. Babuga, A. H. Danwanka, A. Garba

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The research was carried out to compare the yield of respondents before and after access to extension services on crop production technologies in the study area. Data were collected from the study area through questionnaires administered to seventy-five randomly selected respondents. Data were analyzed using descriptive statistics, t-test and regression models. The result disclosed that majority (97%) of the respondent attended one form of school or the other. The majority (78.67%) of the respondents had farm size ranging between 1-3 hectares. The majority of the respondent adopt improved variety of crops, plant spacing, herbicide, fertilizer application, land preparation, crop protection, crop processing and storage of farm produce. The result of the t-test between the yield of respondents before and after access to extension services shows that there was a significant (p<0.001) difference in yield before and after access to extension. It also indicated that farm size was significant (p<0.001) while household size, years of farming experience and extension contact were significant at (p<0.005). The major constraint to adoption of crop production technologies were shortage of extension agents, high cost of technology and lack of access to credit facility. The major pre-requisite for the improvement of extension service are employment of more extension agents or workers and adequate training. Adequate agricultural credit to farmers at low interest rates will enhance their adoption of crop production technologies.

Keywords: comparative, analysis, yield, access, extension

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Authors: Citra Pertiwi, Muhammad Fikruzzaman Rahawarin

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Government of Indonesia had committed to increasing its national defense the budget up to 1,5 percent of GDP. However, the budget increase does not necessarily allocate efficiently and effectively. Using Data Envelopment Analysis (DEA), the operational units of Indonesian Armed Forces are considered as a proxy to measure those two aspects. The bootstrap technique is being used as well to reduce uncertainty in the estimation. Additionally, technological change is being measured as a nonstationary component. Nearly half of the units are being estimated as fully efficient, with less than a third is considered as effective. Longer and larger sets of data might increase the robustness of the estimation in the future.

Keywords: bootstrap, effectiveness, efficiency, DEA, military, Malmquist, technological change

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Authors: Bismina Akbar, Smitha M. V.

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Flooding is a global phenomenon that causes widespread devastation, economic damage, and loss of human lives. In the past twenty years, the number of reported flood events has increased significantly. Millions of people around the globe are at risk of flooding from coastal, dam breaks, groundwater, and urban surface water and wastewater sources. Climate change is one of the important causes for them since it affects, directly and indirectly, the river network. Although the contribution of climate change is undeniable, human contributions are there to increase the frequency of floods. There are different types of floods, such as Flash floods, Coastal floods, Urban floods, River (or fluvial) floods, and Ponding (or pluvial flooding). This study focuses on formulating mitigation strategies for urban flood risk reduction through analysis of different best practice case studies, including China, Japan, Indonesia, and Brazil. The mitigation measures suggest that apart from the structural and non-structural measures, environmental considerations like blue-green solutions are beneficial for flood risk reduction. And also, Risk-Informed Master plans are essential nowadays to take risk-based decision processes that enable more sustainability and resilience.

Keywords: hazard, mitigation, risk reduction, urban flood

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Authors: Sri Yusnita Irda Sari, Deni Kurniadi Sunjaya, Ardini Saptaningsih Raksanagara

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Water is one of the fundamental basic needs for human life, particularly drinking water sources. Although water quality is getting better, fecal-contamination of water is still found around the world, especially in the slum area of mid-low income countries. Drinking water source contamination in urban slum dwellers increases the risk of water borne diseases. Low level of sanitation and poor drinking water supply known as risk factors for diarrhea, moreover bacteria-contaminated drinking water source is the main cause of diarrhea in developing countries. This study aimed to assess risk infection due to Fecal Coliform contamination in various drinking water sources in urban area by applying Quantitative Microbiological Risk Assessment (QMRA). A Cross-sectional survey was conducted in a period of August to October 2015. Water samples were taken by simple random sampling from households in Cikapundung river basin which was one of urban slum area in the center of Bandung city, Indonesia. About 379 water samples from 199 households and 15 common wells were tested. Half of the households used treated drinking water from water gallon mostly refill water gallon which was produced in drinking water refill station. Others used raw water sources which need treatment before consume as drinking water such as tap water, borehole, dug well and spring water source. Annual risk to get infection due to Fecal Coliform contamination from highest to lowest risk was dug well (1127.9 x 10-5), spring water (49.7 x 10-5), borehole (1.383 x 10-5) and tap water (1.121 x 10-5). Annual risk infection of refill drinking water was 1.577 x 10-5 which is comparable to borehole and tap water. Household water treatment and storage to make raw water sources drinkable is essential to prevent risk of water borne diseases. Strong regulation and intense monitoring of refill water gallon quality should be prioritized by the government; moreover, distribution of tap water should be more accessible and affordable especially in urban slum area.

Keywords: drinking water, quantitative microbiological risk assessment, slum, urban

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Authors: Mariam Ismail, Kazeem Rufai, Jeremiah Balogun

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A study was conducted to apply fuzzy logic to the development of a monitoring model for child pornography based on associated risk factors, which can be used by forensic experts or integrated into forensic systems for the early detection of child pornographic activities. A number of methods were adopted in the study, which includes an extensive review of related works was done in order to identify the factors that are associated with child pornography following which they were validated by an expert sex psychologist and guidance counselor, and relevant data was collected. Fuzzy membership functions were used to fuzzify the associated variables identified alongside the risk of the occurrence of child pornography based on the inference rules that were provided by the experts consulted, and the fuzzy logic expert system was simulated using the Fuzzy Logic Toolbox available in the MATLAB Software Release 2016. The results of the study showed that there were 4 categories of risk factors required for assessing the risk of a suspect committing child pornography offenses. The results of the study showed that 2 and 3 triangular membership functions were used to formulate the risk factors based on the 2 and 3 number of labels assigned, respectively. The results of the study showed that 5 fuzzy logic models were formulated such that the first 4 was used to assess the impact of each category on child pornography while the last one takes the 4 outputs from the 4 fuzzy logic models as inputs required for assessing the risk of child pornography. The following conclusion was made; there were factors that were related to personal traits, social traits, history of child pornography crimes, and self-regulatory deficiency traits by the suspects required for the assessment of the risk of child pornography crimes committed by a suspect. Using the values of the identified risk factors selected for this study, the risk of child pornography can be easily assessed from their values in order to determine the likelihood of a suspect perpetuating the crime.

Keywords: fuzzy, membership functions, pornography, risk factors

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Authors: Yukinori Fuse, Masato Kawaguchi

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A quantitative risk assessment method was developed for fiber emissions from sprayed asbestos-containing materials (ACMs). In Japan, instead of being quantitative, these risk assessments have relied on the subjective judgment of skilled engineers, which may vary from one person to another. Therefore, this closed sampling method aims at avoiding any potential variability between assessments. This method was used to assess emissions from ACM sprayed in eleven buildings and the obtained results were compared with the subjective judgments of a skilled engineer. An approximate correlation tendency was found between both approaches. In spite of existing uncertainties, the closed sampling method is useful for public health protection. We firmly believe that this method may find application in the management and renovation decisions of buildings using friable and sprayed ACM.

Keywords: asbestos, renovation, risk assessment, maintenance

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Authors: Diana López-Soto, Soumaya Yacout, Francisco Ángel-Bello

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Although inventories are considered as stocks of money sitting on shelve, they are needed in order to secure a constant and continuous production. Therefore, companies need to have control over the amount of inventory in order to find the balance between excessive and shortage of inventory. The classification of items according to certain criteria such as the price, the usage rate and the lead time before arrival allows any company to concentrate its investment in inventory according to certain ranking or priority of items. This makes the decision making process for inventory management easier and more justifiable. The purpose of this paper is to present a new approach for the classification of new items based on the already existing criteria. This approach is called the Logical Analysis of Data (LAD). It is used in this paper to assist the process of ABC items classification based on multiple criteria. LAD is a data mining technique based on Boolean theory that is used for pattern recognition. This technique has been tested in medicine, industry, credit risk analysis, and engineering with remarkable results. An application on ABC inventory classification is presented for the first time, and the results are compared with those obtained when using the well-known AHP technique and the ANN technique. The results show that LAD presented very good classification accuracy.

Keywords: ABC multi-criteria inventory classification, inventory management, multi-class LAD model, multi-criteria classification

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Authors: Abdullah Alsayeqh

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The burden of foodborne diseases in Saudi Arabia is currently unknown. The objective of this study was to identify risk factors associated with these diseases among women in Riyadh. A cross-sectional study was carried out from March to July, 2013 where participants’ responses indicated that they were at risk of these diseases through improper food-holding temperature (45.28%), inadequate cooking (35.47%), cross-contamination (32.23%), and food from unsafe sources (22.39%). The claimed food safety knowledge by 22.04% of participants was not evidenced by their reported behaviors (p > 0.05). This is the first study to identify the gap in food safety knowledge among women in Riyadh which needs to be addressed by the concerned authorities in the country by engaging women more effectively in food safety educational campaigns.

Keywords: foodborne diseases, risk factors, knowledge, women, Saudi Arabia

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Authors: C. V. Pietreanu, S. E. Zaharia, C. Dinu

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Hazard assessment and risks quantification are key components for estimating the impact of existing regulations. But since regulatory compliance cannot cover all risks in aviation, the authors point out that by studying causal factors and eliminating uncertainty, an accurate analysis can be outlined. The research debuts by making delimitations on notions, as confusion on the terms over time has reflected in less rigorous analysis. Throughout this paper, it will be emphasized the fact that the variation in human performance and organizational factors represent the biggest threat from an operational perspective. Therefore, advanced risk assessment methods analyzed by the authors aim to understand vulnerabilities of the system given by a nonlinear behavior. Ultimately, the mathematical modeling of existing hazards and risks by eliminating uncertainty implies establishing an optimal solution (i.e. risk minimization).

Keywords: control, human factor, optimization, risk management, uncertainty

Procedia PDF Downloads 245

Authors: S. Alyami, S. Mohammad

Abstract:

These Risk management practices have a significant impact on construction SMEs. The effective utilisation of these practices depends on culture change in order to optimise decision making for critical activities within construction projects. Thus, successful implementation of empowerment strategies would enhance operational employees to participate in effective decision making. However, there remain many barriers to individuals and organisations within empowerment strategies that require empirical investigation before the industry can benefit from their implementation. Gaps in understanding the relationship between employee empowerment and risk management practices still exist. This research paper aims to examine the impact of the structural empowerment on risk management practices in construction SMEs. The questionnaire has been distributed to participants (162 employees) that involve projects and civil engineers within a case study from Saudi construction SMEs. Partial least squares based structural equation modeling (PLS-SEM) was utilised to perform analysis. The results reveal a positive relationship between empowerment and risk management practices. The study shows how structural empowerment contributes to operational employees in risk management practices through involving activities such as decision making, self-efficiency, and autonomy. The findings of this study will contribute to close the current gaps in the construction SMEs context.

Keywords: construction SMEs, culture, decision making, empowerment, risk management

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Authors: Sareh Rajabi, Salwa Bheiry

Abstract:

In general, Covid-19 created many financial and non-financial damages to the economy and community. Level and severity of covid-19 as pandemic case varies over the region and due to different types of the projects. Covid-19 virus emerged as one of the most imperative risk management factors word-wide recently. Therefore, as part of portfolio management assessment, it is essential to evaluate severity of such risk on the project and program in portfolio management level to avoid any risky portfolio. Covid-19 appeared very effectively in South America, part of Europe and Middle East. Such pandemic infection affected the whole universe, due to lock down, interruption in supply chain management, health and safety requirements, transportations and commercial impacts. Therefore, this research proposes Analytical Hierarchy Process (AHP) to analyze and assess such pandemic case like Covid-19 and its impacts on the construction projects. The AHP technique uses four sub-criteria: Health and safety, commercial risk, completion risk and contractual risk to evaluate the project and program. The result will provide the decision makers with information which project has higher or lower risk in case of Covid-19 and pandemic scenario. Therefore, the decision makers can have most feasible solution based on effective weighted criteria for project selection within their portfolio to match with the organization’s strategies.

Keywords: portfolio management, risk management, COVID-19, analytical hierarchy process technique

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Authors: Lo Kar Yin, Law Ka Mei

Abstract:

Architectural, engineering, construction and operations (AECO) industry practitioners have been well adapting to the dynamic construction market from the fundamental training of its discipline. As further triggered by the pandemic since 2019, great steps are taken in virtual environment and the best collaboration is strived with project teams without boundaries. With adoption of Building Information Modeling-based approach and qualitative analysis, this paper is to review quantity take-off and cost estimation process through modeling techniques in liaison with suppliers, fabricators, subcontractors, contractors, designers, consultants and services providers in the construction industry value chain for automatic project cost budgeting, project cost control and cost evaluation on design options of in-situ reinforced-concrete construction and Modular Integrated Construction (MiC) at design stage, variation of works and cash flow/spending analysis at construction stage as far as practicable, with a view to sharing the findings for enhancing mutual trust and co-operation among AECO industry practitioners. It is to foster development through a common prototype of design and build project delivery method in NEC Engineering and Construction Contract (ECC) Options A and C.

Keywords: building information modeling, cost estimation, quantity take-off, modeling techniques

Procedia PDF Downloads 179

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA

Procedia PDF Downloads 547