Search results for: operational risk

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: 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: Paul Dallyn, Ashraf El-Hamalawi, Alessandro Palmeri, Bob Knight

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In order to better understand the long term implications of the grout wear failure mode in large-diameter plain-sided grouted connections, a numerical model has been developed and calibrated that can take advantage of existing operational plant data to predict the wear accumulation for the actual load conditions experienced over a given period, thus limiting the need for expensive monitoring systems. This model has been derived and calibrated based on site structural condition monitoring (SCM) data and supervisory control and data acquisition systems (SCADA) data for two operational wind turbine generator substructures afflicted with this challenge, along with experimentally derived wear rates.

Keywords: grouted connection, numerical model, offshore structure, wear, wind energy

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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: 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: Sachin Kumar

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Fuzzy fractional diffusion equation is widely useful to depict different physical processes arising in physics, biology, and hydrology. The motive of this article is to deal with the fuzzy fractional diffusion equation. We study a mathematical model of fuzzy space-time fractional diffusion equation in which unknown function, coefficients, and initial-boundary conditions are fuzzy numbers. First, we find out a fuzzy operational matrix of Legendre polynomial of Caputo type fuzzy fractional derivative having a non-singular Mittag-Leffler kernel. The main advantages of this method are that it reduces the fuzzy fractional partial differential equation (FFPDE) to a system of fuzzy algebraic equations from which we can find the solution of the problem. The feasibility of our approach is shown by some numerical examples. Hence, our method is suitable to deal with FFPDE and has good accuracy.

Keywords: fractional PDE, fuzzy valued function, diffusion equation, Legendre polynomial, spectral method

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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: Victor Bodell, Lukas Ekstrom, Somayeh Aghanavesi

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Fuel consumption (FC) is one of the key factors in determining expenses of operating a heavy-duty vehicle. A customer may therefore request an estimate of the FC of a desired vehicle. The modular design of heavy-duty vehicles allows their construction by specifying the building blocks, such as gear box, engine and chassis type. If the combination of building blocks is unprecedented, it is unfeasible to measure the FC, since this would first r equire the construction of the vehicle. This paper proposes a machine learning approach to predict FC. This study uses around 40,000 vehicles specific and o perational e nvironmental c onditions i nformation, such as road slopes and driver profiles. A ll v ehicles h ave d iesel engines and a mileage of more than 20,000 km. The data is used to investigate the accuracy of machine learning algorithms Linear regression (LR), K-nearest neighbor (KNN) and Artificial n eural n etworks (ANN) in predicting fuel consumption for heavy-duty vehicles. Performance of the algorithms is evaluated by reporting the prediction error on both simulated data and operational measurements. The performance of the algorithms is compared using nested cross-validation and statistical hypothesis testing. The statistical evaluation procedure finds that ANNs have the lowest prediction error compared to LR and KNN in estimating fuel consumption on both simulated and operational data. The models have a mean relative prediction error of 0.3% on simulated data, and 4.2% on operational data.

Keywords: artificial neural networks, fuel consumption, friedman test, machine learning, statistical hypothesis testing

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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: Sareh Rajabi, Salwa Bheiry

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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: Chris Nelson

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Quality and excellence are qualitative topics that are usually addressed based on knowledge and past experience from leadership and those in charge of the organization. The significance of this study is to highlight the differences and similarities between these two mindsets and how an operational staff can most appropriately use them in the workplace. Quality and excellence are two words that are talked about a lot in the manufacturing world. Buzzwords such as operational excellence, quality controls, and efficiencies are discussed in the boardroom as well on the shop floor. These terms are used quite frequently and with good reasons. When a person visits their favorite local restaurant, They go because 1) they like the food and 2) the people are some of the greatest individuals to be around. With that in mind, they know they always put out quality food. They do not always go because the quality of the food is far superior than other restaurants. But the quality of ingredients always meets their expectations. When they compare them to the term excellence, they are disappointed. The food never looks like the pictures on the menu. But when have you ever been to a restaurant where the food looks the same as on the menu? For them, when evaluating which buzzword to use as a guiding star, its simple: excellence. The corporation can accomplish these goals by operating at a standard that far exceeds customer’s wants and needs.

Keywords: industrial engineering, innovation, management and technology, logistics and scheduling, six sigma

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Authors: Ummu Salma Al Azizah, Herri Mulyono, Anisa Mauliata Suryana

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The significance of corporate governance regarding to the agency problem have been transparent. This study examine the impact of corporate governance on the performance of Islamic banking in Indonesia. By using fixed effect model and added some control variable, the current study try to explore the correlation between the theoretical framework on corporate governance, such as agency theory and risk management theory. The bank performance (Return on Asset and Return on Equity) which are operational performance and financial performance. And Corporate governance based on Board size, CEO duality, Audit committee and Shariah supervisory board. The limitation of this study only focus on the Islamic banks performance from year 2015 to 2020. The study fill the gap in the literature by addressing the issue of corporate governance on Islamic banks performance in Indonesia.

Keywords: corporate governance, financial performance, islamic banks, listed companies, Indonesia

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

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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

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Authors: A. Fathianpour, M. B. Jelodar, S. Wilkinson

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This paper outlines the approaches taken to assess multi-hazard assessments. There is currently confusion in assessing multi-hazard impacts, and so this study aims to determine which of the available options are the most useful. The paper uses an international literature search, and analysis of current multi-hazard assessments and a case study to illustrate the effectiveness of the chosen method. Findings from this study will help those wanting to assess multi-hazards to undertake a straightforward approach. The paper is significant as it helps to interpret the various approaches and concludes with the preferred method. Many people in the world live in hazardous environments and are susceptible to disasters. Unfortunately, when a disaster strikes it is often compounded by additional cascading hazards, thus people would confront more than one hazard simultaneously. Hazards include natural hazards (earthquakes, floods, etc.) or cascading human-made hazards (for example, Natural Hazard Triggering Technological disasters (Natech) such as fire, explosion, toxic release). Multi-hazards have a more destructive impact on urban areas than one hazard alone. In addition, climate change is creating links between different disasters such as causing landslide dams and debris flows leading to more destructive incidents. Much of the prevailing literature deals with only one hazard at a time. However, recently sophisticated multi-hazard assessments have started to appear. Given that multi-hazards occur, it is essential to take multi-hazard risk assessment under consideration. This paper aims to review the multi-hazard assessment methods through articles published to date and categorize the strengths and disadvantages of using these methods in risk assessment. Napier City is selected as a case study to demonstrate the necessity of using multi-hazard risk assessments. In order to assess multi-hazard risk assessments, first, the current multi-hazard risk assessment methods were described. Next, the drawbacks of these multi-hazard risk assessments were outlined. Finally, the improvements to current multi-hazard risk assessments to date were summarised. Generally, the main problem of multi-hazard risk assessment is to make a valid assumption of risk from the interactions of different hazards. Currently, risk assessment studies have started to assess multi-hazard situations, but drawbacks such as uncertainty and lack of data show the necessity for more precise risk assessment. It should be noted that ignoring or partial considering multi-hazards in risk assessment will lead to an overestimate or overlook in resilient and recovery action managements.

Keywords: cascading hazards, disaster assessment, mullti-hazards, risk assessment

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Authors: Fei Gao, Rodolfo C. Raga Jr.

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This research proposal will ascertain the major risk factors for diabetes and to design a predictive model for risk assessment. The project aims to improve diabetes early detection and management by utilizing data science techniques, which may improve patient outcomes and healthcare efficiency. The phase relation values of each attribute were used to analyze and choose the attributes that might influence the examiner's survival probability using Diabetes Health Indicators Dataset from Kaggle’s data as the research data. We compare and evaluate eight machine learning algorithms. Our investigation begins with comprehensive data preprocessing, including feature engineering and dimensionality reduction, aimed at enhancing data quality. The dataset, comprising health indicators and medical data, serves as a foundation for training and testing these algorithms. A rigorous cross-validation process is applied, and we assess their performance using five key metrics like accuracy, precision, recall, F1-score, and area under the receiver operating characteristic curve (AUC-ROC). After analyzing the data characteristics, investigate their impact on the likelihood of diabetes and develop corresponding risk indicators.

Keywords: diabetes, risk factors, predictive model, risk assessment, data science techniques, early detection, data analysis, Kaggle

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Authors: David Ahiamadia, Ramilan Thiagarajah, Peter Tozer

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In Sub Saharan Africa, farm typologies have been used as a practical way to address heterogeneity among farming systems which is mostly done by grouping farms into subsets with similar characteristics. Due to the complexity in farming systems among farm households, it is not possible to formulate policy recommendations for individual farmers. As a result, this study employs a multivariate statistical approach using Principal Component Analysis (PCA) coupled with cluster analysis to reduce heterogeneity in a 615-household data set from the Africa Rising Baseline Evaluation Survey for 25 farming communities in Northern Ghana. Variables selected for the study were mostly socio-economic, production potential, production intensity, production orientation, crop diversity, food security, resource endowments, and climate risk variables. To avoid making some individuals in the subpopulation worse off when aclimate risk intervention is broadly implemented, the findings of the study also account for diversity in climate risk perception among the different farm types identified and their response strategies towards climate risk. The climate risk variables used in this study involve the most severeclimate shock types perceived by the household, household response to climate shock type, and reason for crop failure (i.e., maize, rice, and groundnut). Eventually, four farm types, each with an adequate level of homogeneity in climate risk perception and response strategies, were identified. Farm type 1 and 3 were wealthy with a lower degree of climate risk perception compared to farm type 2 and 4. Also, relatively wealthy farmers used asset liquidation as a climate risk management strategy, whereas poor farmers resorted to engaging in spiritual activities such as prayers, sacrifices, and divine consultations.

Keywords: smallholder, households, climate risk, variables, typologies

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Authors: A. Badran, M. Hollocks, H. Markus

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Background: Common risk factors for cardiovascular disease are associated with age-related cognitive decline. There has been much interest in treating modifiable cardiovascular risk factors in the hope of reducing cognitive decline. However, there is currently no validated neuropsychological test to assess the subclinical cognitive effects of vascular risk. The Brief Memory and Executive Test (BMET) is a clinical screening tool, which was originally designed to be sensitive and specific to Vascular Cognitive Impairment (VCI), an impairment characterised by decline in frontally-mediated cognitive functions (e.g. Executive Function and Processing Speed). Objective: To cross-sectionally assess the validity of the BMET as a measure of the subclinical effects of vascular risk on cognition, in an otherwise healthy elderly cohort. Methods: Data from 346 participants (57 ± 10 years) without major neurological or psychiatric disorders were included in this study, gathered as part of a previous multicentre validation study for the BMET. Framingham Vascular Age was used as a surrogate measure of vascular risk, incorporating several established risk factors. Principal Components Analysis of the subtests was used to produce common constructs: an index for Memory and another for Executive Function/Processing Speed. Univariate General Linear models were used to relate Vascular Age to performance on Executive Function/Processing Speed and Memory subtests of the BMET, adjusting for Age, Premorbid Intelligence and Ethnicity. Results: Adverse vascular risk was associated with poorer performance on both the Memory and Executive Function/Processing Speed indices, adjusted for Age, Premorbid Intelligence and Ethnicity (p=0.011 and p<0.001, respectively). Conclusions: Performance on the BMET reflects the subclinical effects of vascular risk on cognition, in age-related cognitive decline. Vascular risk is associated with decline in both Executive Function/Processing Speed and Memory groups of subtests. Future studies are needed to explore whether treating vascular risk factors can effectively reduce age-related cognitive decline.

Keywords: age-related cognitive decline, vascular cognitive impairment, subclinical cerebrovascular disease, cognitive aging

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Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

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Authors: Yi-Hsien Wang, Fu-Ju Yang, Hwa-Rong Shen, Rui-Lin Tseng

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The business is notably related to the market risk according to the increase of liberalization of financial markets. Hence, the company usually utilized high financial leverage of derivatives to hedge the risk. When the company choose different hedging instruments to face a variety of exchange rate risk, we employ the Multinomial Logistic-AHP to analyze the impact of various derivatives. Hence, the research summarized the literature on relevant factors affecting managers selected exchange rate hedging instruments, using Multinomial Logistic Model and and further integrate AHP. Using Experts’ Questionnaires can test multi-level selection and hedging effect of different hedging instruments in order to calculate the hedging instruments and the multi-level factors of weights to understand the gap between the empirical results and practical operation. Finally, the Multinomial Logistic-AHP Model will sort the weights to analyze. The research findings can be a basis reference for investors in decision-making.

Keywords: exchange rate risk, derivatives, hedge, multinomial logistic-AHP

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Authors: Peifang Hsieh

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The prevention of child abuse has aroused serious concerns in Taiwan because of the disparity between the increasing amount of reported child abuse cases that doubled over the past decade and the scarcity of social workers. New Taipei city, with the most population in Taiwan and over 70% of its 4 million citizens are migrant families in which the needs of children can be easily neglected due to insufficient support from relatives and communities, sees urgency for a social support system, by preemptively identifying and outreaching high-risk families of child abuse, so as to offer timely assistance and preventive measure to safeguard the welfare of the children. Big data analysis is the inspiration. As it was clear that high-risk families of child abuse have certain characteristics in common, New Taipei city decides to consolidate detailed background information data from departments of social affairs, education, labor, and health (for example considering status of parents’ employment, health, and if they are imprisoned, fugitives or under substance abuse), to cross-reference for accurate and prompt identification of the high-risk families in need. 'The Service Center for High-Risk Families' (SCHF) was established to integrate data cross-departmentally. By utilizing the machine learning 'random forest method' to build a risk prediction model which can early detect families that may very likely to have child abuse occurrence, the SCHF marks high-risk families red, yellow, or green to indicate the urgency for intervention, so as to those families concerned can be provided timely services. The accuracy and recall rates of the above model were 80% and 65%. This prediction model can not only improve the child abuse prevention process by helping social workers differentiate the risk level of newly reported cases, which may further reduce their major workload significantly but also can be referenced for future policy-making.

Keywords: child abuse, high-risk families, big data analysis, risk prediction model

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Authors: Alexander Babin, Leonid Savin

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In the present paper, increasing of energy efficiency of a thrust hybrid bearing with a central feeding chamber is considered. The mathematical model was developed to determine the pressure distribution and the reaction forces, based on the Reynolds equation and static characteristics’ equations. The boundary problem of pressure distribution calculation was solved using the method of finite differences. For various types of lubricants, geometry and operational characteristics, axial gaps can be determined, where the minimal friction coefficient is provided. The next part of the study considers the application of servovalves in order to maintain the desired position of the rotor. The report features the calculation results and the analysis of the influence of the operational and geometric parameters on the energy efficiency of mechatronic fluid-film bearings.

Keywords: active bearings, energy efficiency, mathematical model, mechatronics, thrust multipad bearing

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Authors: Korbi Fakhri

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The management of assets and liability is a vital task for every bank as far as a good direction allows its stability; however, a bad running forewarns its disappearance. Equity of a bank is among the most important rubrics in the liability side because, actually, these funds ensure three notably primordial functions for the survival of the bank. From one hand, equity is useful to bankroll the investments and cover the unexpected losses. From another hand, they attract the fund lessors since they inspire trust. So we are going to tackle some points including whether equity of the Islamic banks are oversized. In spite of the efforts made on the subject, the relationship between the capital and the deficiency probability has not been defined with certainty. In this article, we have elaborated a study over the nature of financial intermediation in Islamic banks by comparison to those of conventional ones. We have found a striking difference between two kinds of intermediation. We tried, from another side, to study the relationship between the capital level and deficiency risk relying on econometric model, and we have obtained a positive and significant relation between the capital and the deficiency risk for the conventional banks. This means that when the capital of these banks increases, the deficiency risk increases as well. In return, since the Islamic banks are constrained to respect the Sharia Committee as well as customers’ demands who may, in certain contracts, choose to invest their capitals in projects they are interested in. These constraints have as effects to reduce the deficiency risk even when the capital increases.

Keywords: Islamic bank, conventional bank, deficiency risk, financial intermediation

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Authors: Wan Noorul Hafilah Binti Wan Ariffin

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Dam safety management is the crucial infrastructure as dam failure has a catastrophic effect on the community. Dam safety management is the effective framework of key actions and activities for the dam owner to manage the safety of the dam for its entire life cycle. However, maintaining dam safety is a challenging task as there are changes in current dam states. These changes introduce new risks to the dam's safety, which had not been considered when the dam was designed. A new framework has to be developed to adapt to the changes in the dam risk and make the dams resilient. This study proposes a risk-based decision-making adaptation framework for dam safety management. The research focuses on climate change's impact on hydrological situations as it causes floods and damages the dam structure. The risk analysis framework is adopted to improve the dam management strategies. The proposed study encompasses four phases. To start with, measuring the effect by assessing the impact of climate change on embankment dam, the second phase is to analyze the potential embankment dam failures. The third is analyzing the different components of risks related to the dam and, finally, developing a robust decision-making framework.

Keywords: climate change, embankment dam, failure, risk-informed decision making

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Authors: Aline M. Dantas, Alexander T. Sack, Elisabeth Bruggen, Peiran Jiao, Teresa Schuhmann

Abstract:

Risk-taking behavior has been associated with the activity of specific prefrontal regions of the brain, namely the right dorsolateral prefrontal cortex (DLPFC) and the ventromedial prefrontal cortex (VMPFC). While the deactivation of the rDLPFC has been shown to lead to increased risk-taking behavior, the functional relationship between VMPFC activity and risk-taking behavior is yet to be clarified. Correlational evidence suggests that the VMPFC is involved in valuation processes that involve risky choices, but evidence on the functional relationship is lacking. Therefore, this study uses brain stimulation to investigate the role of the VMPFC during risk-taking behavior and replicate the current findings regarding the role of the rDLPFC in this same phenomenon. We used continuous theta-burst stimulation (cTBS) to inhibit either the VMPFC or DLPFC during the execution of the computerized Maastricht Gambling Task (MGT) in a within-subject design with 30 participants. We analyzed the effects of such stimulation on risk-taking behavior, participants’ choices of probabilities and average values, and response time. We hypothesized that, compared to sham stimulation, VMPFC inhibition leads to a reduction in risk-taking behavior by reducing the appeal to higher-value options and, consequently, the attractiveness of riskier options. Right DLPFC (rDLPFC) inhibition, on the other hand, should lead to an increase in risk-taking due to a reduction in cognitive control, confirming existent findings. Stimulation of both the rDLPFC and the VMPFC led to an increase in risk-taking behavior and an increase in the average value chosen after both rDLPFC and VMPFC stimulation compared to sham. No significant effect on chosen probabilities was found. A significant increase in response time was observed exclusively after rDLPFC stimulation. Our results indicate that inhibiting DLPFC and VMPFC separately leads to similar effects, increasing both risk-taking behavior and average value choices, which is likely due to the strong anatomical and functional interconnection of the VMPFC and rDLPFC.

Keywords: decision-making, risk-taking behavior, brain stimulation, TMS

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Authors: Iris W. A. Boot, Anke Wesselius, Maurice P. Zeegers

Abstract:

Diet may play an essential role in the aetiology of bladder cancer (BC). Vitamin D is involved in various biological functions which have the potential to prevent BC development. Besides, vitamin D also influences the uptake of calcium and phosphorus , thereby possibly indirectly influencing the risk of BC. The aim of the present study was to investigate the relation between vitamin D intake and BC risk. Individual dietary data were pooled from three cohort studies. Food item intake was converted to daily intakes of vitamin D, calcium and phosphorus. Pooled multivariate hazard ratios (HRs), with corresponding 95% confidence intervals (CIs) were obtained using Cox-regression models. Analyses were adjusted for gender, age and smoking status (Model 1), and additionally for the food groups fruit, vegetables and meat (Model 2). Dose–response relationships (Model 1) were examined using a nonparametric test for trend. In total, 2,871 cases and 522,364 non-cases were included in the analyses. The present study showed an overall increased BC risk for high dietary vitamin D intake (HR: 1.14, 95% CI: 1.03-1.26). A similar increase BC risk with high vitamin D intake was observed among women and for the non-muscle invasive BC subtype, (HR: 1.41, 95% CI: 1.15-1.72, HR: 1.13, 95% CI: 1.01-1.27, respectively). High calcium intake decreased the BC risk among women (HR: 0.81, 95% CI: 0.67-0.97). A combined inverse effect on BC risk was observed for low vitamin D intake and high calcium intake (HR: 0.67, 95% CI: 0.48-0.93), while a positive effect was observed for high vitamin D intake in combination with low, moderate and high phosphorus (HR: 1.31, 95% CI: 1.09-1.59, HR: 1.17, 95% CI: 1.01-1.36, HR: 1.16, 95% CI: 1.03-1.31, respectively). Combining all nutrients showed a decreased BC risk for low vitamin D intake, high calcium and moderate phosphor intake (HR: 0.37, 95% CI: 0.18-0.75), and an increased BC risk for moderate intake of all the nutrients (HR: 1.18, 95% CI: 1.02-1.38), for high vitamin D and low calcium and phosphor intake (HR: 1.28, 95% CI: 1.01-1.62), and for moderate vitamin D and calcium and high phosphorus intake (HR: 1.27, 95% CI: 1.01-1.59). No significant dose-response analyses were observed. The findings of this study show an increased BC risk for high dietary vitamin D intake and a decreased risk for high calcium intake. Besides, the study highlights the importance of examining the effect of a nutrient in combination with complementary nutrients for risk assessment. Future research should focus on nutrients in a wider context and in nutritional patterns.

Keywords: bladder cancer, nutritional oncology, pooled cohort analysis, vitamin D

Procedia PDF Downloads 84

Authors: Zohre Soleymani, Meisam Amirzadeh

Abstract:

Many products are safety critical, so proactive analysis techniques are vital for them because these techniques try to identify potential failures before the products are produced. Failure Mode and Effective Analysis (FMEA) is an effective tool in identifying probable problems of product or process and prioritizing them and planning for its elimination. The paper shows the implementation of FMEA process to identify and remove potential troubles of aero fuel pumps manufacturing process and improve the reliability of subsystems. So the different possible causes of failure and its effects along with the recommended actions are discussed. FMEA uses Risk Priority Number (RPN) to determine the risk level. RPN value is depending on Severity(S), Occurrence (O) and Detection (D) parameters, so these parameters need to be determined. After calculating the RPN for identified potential failure modes, the corrective actions are defined to reduce risk level according to assessment strategy and determined acceptable risk level. Then FMEA process is performed again and RPN revised is calculated. The represented results are applied in the format of a case study. These results show the improvement in manufacturing process and considerable reduction in aero fuel pump production risk level.

Keywords: FMEA, risk priority number, aero pump, corrective action

Procedia PDF Downloads 285

Authors: Arundhati Devi Maibam, K. Ingocha Singh

Abstract:

Cervical cancer is preventable if detected early. Determination of risk factors is essential to plan screening programmes to prevent the disease. To study the demographic risk factors of cervical cancer among Manipuri women, information on age, marital status, educational level, monthly family income and socioeconomic status were collected through a pre-tested interview schedule. In this study, 64 incident cases registered at the RT Dept, RIMS (Regional Institute of Medical Sciences), Imphal, Manipur, India during 2008-09 participated. Data were entered in Microsoft Excel and the results were expressed in percentages. Among the 64 patients with cervical cancer, 56 (88.9%) were in the age group of 40+ years. The majority of the patients were from rural areas (68.75%) and 31.25% were from urban areas. The majority of the patients were Hindus (73%), 55(85.9%) were of low educational level, 43(67.2%) were married, and 36 (56.25%) belonged to Class IV socioeconomic status. In conclusion, if detected early, cervical cancer is preventable and curable. The potential risk factors need to be identified and women in the risk group need to be motivated for screening. Affordable screening programmes and health care resources will help in lessening the burden of the disease.

Keywords: cervical cancer, Manipuri women, RIIMS, socio-demographic risk factors

Procedia PDF Downloads 276