Search results for: Reynolds stress model

Authors: Longqing Li

Abstract:

The paper addresses the inefficiency of the classical model in measuring the Value-at-Risk (VaR) using a normal distribution or a Student’s t distribution. Specifically, the paper focuses on the one day ahead Value-at-Risk (VaR) of major stock market’s daily returns in US, UK, China and Hong Kong in the most recent ten years under 95% confidence level. To improve the predictable power and search for the best performing model, the paper proposes using two leading alternatives, Extreme Value Theory (EVT) and a family of GARCH models, and compares the relative performance. The main contribution could be summarized in two aspects. First, the paper extends the GARCH family model by incorporating EGARCH and TGARCH to shed light on the difference between each in estimating one day ahead Value-at-Risk (VaR). Second, to account for the non-normality in the distribution of financial markets, the paper applies Generalized Error Distribution (GED), instead of the normal distribution, to govern the innovation term. A dynamic back-testing procedure is employed to assess the performance of each model, a family of GARCH and the conditional EVT. The conclusion is that Exponential GARCH yields the best estimate in out-of-sample one day ahead Value-at-Risk (VaR) forecasting. Moreover, the discrepancy of performance between the GARCH and the conditional EVT is indistinguishable.

Keywords: Value-at-Risk, Extreme Value Theory, conditional EVT, backtesting

Procedia PDF Downloads 326

Authors: Bo Hu, Shibo Wang, Haoyang Zhang, Jie Shi

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With the development of sonar detection technology, the acoustic stealth technology of underwater vehicles is facing severe challenges. The underwater acoustic coating is developing towards the direction of low-frequency absorption capability and broad absorption frequency bandwidth. In this paper, an acoustic model of underwater acoustic coating of composite material embedded with periodical steel structure is presented. The model has multiple high absorption peaks in the frequency range of 1kHz-8kHz, where achieves high sound absorption and broad bandwidth performance. It is found that the frequencies of the absorption peaks are related to the classic half-wavelength transmission principle. The sound absorption performance of the acoustic model is investigated by the finite element method using COMSOL software. The sound absorption mechanism of the proposed model is explained by the distributions of the displacement vector field. The influence of geometric parameters of periodical steel structure, including thickness and distance, on the sound absorption ability of the proposed model are further discussed. The acoustic model proposed in this study provides an idea for the design of underwater low-frequency broadband acoustic coating, and the results shows the possibility and feasibility for practical underwater application.

Keywords: acoustic coating, composite material, broad frequency bandwidth, sound absorption performance

Procedia PDF Downloads 178

Authors: Zhou Xiong, Kang Shao Bo, Yang Bo

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To date, high-performance structural steel has been widely used for columns in construction practices due to its significant advantages over conventional steel. However, the same design approach with conventional steel columns is still adopted in the design of high-performance steel columns. As a result, its superior properties cannot be fully considered in design. This paper conducts a test and finite element analysis on the overall stability behaviour of welded Q460GJ steel box columns. In the test, four steel columns with different slenderness and width-to-thickness ratio were compressed under an axial compression testing machine. And finite element models were established in which material nonlinearity and residual stress distributions of test columns were included. Then, comparisons were made between test results and finite element result, it showed that finite element analysis results are agree well with the test result. It means that the test and finite element model are reliable. Then, we compared the test result with the design value calculated by current code, the result showed that Q460GJ steel box columns have the higher overall buckling capacity than the design value. It is necessary to update the design curves for Q460GJ steel columns so that the overall stability capacity of Q460GJ box columns can be designed appropriately.

Keywords: axial compression, box columns, global buckling, numerical simulations, Q460GJ steel

Procedia PDF Downloads 409

Authors: Sajeeha Ansar, Asad Ali Safi, Sheikh Ziauddin, Ahmad R. Shahid, Faraz Ahsan

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The most aggressive form of brain tumor is called glioma. Glioma is kind of tumor that arises from glial tissue of the brain and occurs quite often. A fully automatic 2D-CNN model for brain tumor segmentation is presented in this paper. We performed pre-processing steps to remove noise and intensity variances using N4ITK and standard intensity correction, respectively. We used Keras open-source library with Theano as backend for fast implementation of CNN model. In addition, we used BRATS 2015 MRI dataset to evaluate our proposed model. Furthermore, we have used SimpleITK open-source library in our proposed model to analyze images. Moreover, we have extracted random 2D patches for proposed 2D-CNN model for efficient brain segmentation. Extracting 2D patched instead of 3D due to less dimensional information present in 2D which helps us in reducing computational time. Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.77 for complete, 0.76 for core, 0.77 for enhanced tumor regions. However, these results are comparable with methods already implemented 2D CNN architecture.

Keywords: brain tumor segmentation, convolutional neural networks, deep learning, LGG

Procedia PDF Downloads 188

Authors: Rameshwar Singh Seema

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In today’s world where diabetes has become an epidemic, our aim was to potentiate the effect of probiotics by integrating probiotics with cereals to formulate composite foods using Lactobacillus rhamnosus GG (LGG) and Lactobacillus casei NCDC19 against type 2 diabetes. After optimizing the product by Response Surface Methodology, it was studied for their effect on induction and progression of type 2 diabetes in HFD-fed Wistar rats. After 9 weeks study, best results were shown by the group fed with oat and milk based product fermented with LGG and L. casei NCDC19 which resulted in a significant decrease in blood glucose, HBA1c, improved OGTT, oxidative stress, cholesterol and triglycerides level during progression study of type 2 diabetes. During induction study also, there was significant reduction in blood glucose level, oxidative stress, cholesterol level and triglycerides level but slightly less as compared to progression study. Real time PCR gene expression studies were done for 5 genes (GLUT-4, IRS-2, ppar-γ, TNF-α, IL-6) whose expression is directly related to type 2 diabetes. The relative fold change expression was increased in case of GLUT-4, IRS-2, ppar-γ and decreased in case of TNF-α and IL-6 during both induction and progression study of diabetes but more significantly during progression study. Hence it was concluded that oat and milk based probiotic fermented product showed the synergistic effect of probiotics and oats especially in case of progression of type 2 diabetes. The benefits of these probiotic formulations may be further validated by clinical trials.

Keywords: type 2 diabetes, LGG, L.casei NCDC19, food science

Procedia PDF Downloads 420

Authors: Alyaa M. Younes, Nermine Harraz, Mohammad H. Elwany

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Lithium ion batteries are currently used for many applications including satellites, electric vehicles and mobile electronics. Their ability to store relatively large amount of energy in a limited space make them most appropriate for critical applications. Evaluation of the life of these batteries and their reliability becomes crucial to the systems they support. Reliability of Li-Ion batteries has been mainly considered based on its lifetime. However, another important factor that can be considered critical in many applications such as in electric vehicles is the cycle duration. The present work presents the results of an experimental investigation on the degradation behavior of a Laptop Li-ion battery (type TKV2V) and the effect of applied load on the battery cycle time. The reliability was evaluated using an accelerated life test. Least squares linear regression with median rank estimation was used to estimate the Weibull distribution parameters needed for the reliability functions estimation. The probability density function, failure rate and reliability function under each of the applied loads were evaluated and compared. An inverse power model is introduced that can predict cycle time at any stress level given.

Keywords: accelerated life test, inverse power law, lithium-ion battery, reliability evaluation, Weibull distribution

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Authors: Neerav Kumar, Naumaan Nayyar, Sharath Kashyap

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Most companies see an increase in the adoption of machine learning (ML) applications across internal and external-facing use cases. ML applications vend output either in batch or real-time patterns. A complete batch ML pipeline architecture comprises data sourcing, feature engineering, model training, model deployment, model output vending into a data store for downstream application. Due to unclear role expectations, we have observed that scientists specializing in building and optimizing models are investing significant efforts into building the other components of the architecture, which we do not believe is the best use of scientists’ bandwidth. We propose a system architecture created using AWS services that bring industry best practices to managing the workflow and simplifies the process of model deployment and end-to-end data integration for an ML application. This narrows down the scope of scientists’ work to model building and refinement while specialized data engineers take over the deployment, pipeline orchestration, data quality, data permission system, etc. The pipeline infrastructure is built and deployed as code (using terraform, cdk, cloudformation, etc.) which makes it easy to replicate and/or extend the architecture to other models that are used in an organization.

Keywords: data pipeline, machine learning, AWS, architecture, batch machine learning

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Authors: Blair Arthur Agero Jr., Lucia Garcia Heras

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The triangular fibrocartilage complex (TFCC) is one of the crucial stabilizing ligaments of the wrist. The TFCC is also subject to excessive stress amongst performance athletes and enthusiasts. The excessive loading of the TFCC may lead to a partial or complete rupture that requires surgery. The recovery from an open TFCC surgical repair may take several months. Immobilization of the repaired wrist for a given period is part of all the current protocols in the post-surgical treatment. The immobilization to prevent the rotation of the forearm can last from six weeks to eight weeks with the wrist held in a neutral position. In all protocols reviewed, the pronosupination is only initiated between the 6th week and 8th week or even later after the cast is removed. The prolonged immobilization can cause stiffness of the wrist and hand. Furthermore, the entire period of post-surgical hand therapy has its economic impact, especially for performing athletes. However, delayed mobilization, specifically rotation of the wrist, is necessary to allow ligament healing. This study aims to report the effects of early mobilization of the wrist in athletes who had an open surgical repair of the TFCC. The surgery was done by the co-author, and the hand therapy was implemented by the main author. The cases documented spans from 2014 to 2019 and were all performed in Dubai, United Arab Emirates. All selected participants in this case study were provided with a follow-up questionnaire to ascertain their current condition since their surgery. The respondents reported high satisfaction in the results of their treatment and have verified zero re-rupture of their TFCC despite mobilizing and rotating the wrist at the third-week post-surgery during their hand therapy. There is also a negligible number of respondents who reported a limitation in their ranges of pronosupination. This case study suggests that early mobilization of the wrist after an open TFCC surgical repair can be more beneficial to the patient as opposed to the traditional treatment of prolonged immobilization. However, it should be considered that the patients selected in this case study are professional performance athletes and advanced fitness enthusiasts. Athletes are known to withstand vigorous physical stress in their training that may correlate to their ability to better cope with the progressive stress that was implemented during their hand therapy. Nevertheless, this approach has its merits, and application of it may be adjusted for patients with a similar injury and surgical procedure.

Keywords: hand therapy, performance athlete, TFCC repair, wrist ligament

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Authors: Kannapha Amaruchkul

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We formulate a dynamic overbooking model for a tour operator, in which most reservations contain at least two people. The cancellation rate and the timing of the cancellation may depend on the group size. We propose two overbooking policies, namely economic- and service-based. In an economic-based policy, we want to minimize the expected oversold and underused cost, whereas, in a service-based policy, we ensure that the probability of an oversold situation does not exceed the pre-specified threshold. To illustrate the applicability of our approach, we use tour package data in 2016-2018 from a tour operator in Thailand to build a data-driven robust optimization model, and we tested the proposed overbooking policy in 2019. We also compare the data-driven approach to the conventional approach of fitting data into a probability distribution.

Keywords: applied stochastic model, data-driven robust optimization, overbooking, revenue management, tour operator

Procedia PDF Downloads 138

Authors: Moustafa Osman Mohammed

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This paper is mapping air quality model to engineering the industrial system that ultimately utilized in extensive range of energy systems, distribution resources, and end-user technologies. The model is determining long-range transport patterns contribution as area source can either traced from 48 hrs backward trajectory model or remotely described from background measurements data in those days. The trajectory model will be run within stable conditions and quite constant parameters of the atmospheric pressure at the most time of the year. Air parcel trajectory is necessary for estimating the long-range transport of pollutants and other chemical species. It provides a better understanding of airflow patterns. Since a large amount of meteorological data and a great number of calculations are required to drive trajectory, it will be very useful to apply HYPSLIT model to locate areas and boundaries influence air quality at regional location of Windsor. 2–days backward trajectories model at high and low concentration measurements below and upward the benchmark which was areas influence air quality measurement levels. The benchmark level will be considered as 30 (μg/m3) as the moderate level for Ontario region. Thereby, air quality model is incorporating a midpoint concept between biotic and abiotic components to broaden the scope of quantification impact. The later outcomes’ theories of environmental obligation suggest either a recommendation or a decision of what is a legislative should be achieved in mitigation measures of air emission impact ultimately.

Keywords: air quality, management systems, environmental impact assessment, industrial ecology, climate change

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Authors: Okolie Chukwulozie Paul, Iwenofu Chinwe Onyedika, Sinebe Jude Ebieladoh, M. C. Nwosu

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The research work is based on the statistical analysis of the processing data. The essence is to analyze the data statistically and to generate a design model for the production mix of soap manufacturing products in Bejoy manufacturing company Nkpologwu, Aguata Local Government Area, Anambra state, Nigeria. The statistical analysis shows the statistical analysis and the correlation of the data. T test, Partial correlation and bi-variate correlation were used to understand what the data portrays. The design model developed was used to model the data production yield and the correlation of the variables show that the R2 is 98.7%. However, the results confirm that the data is fit for further analysis and modeling. This was proved by the correlation and the R-squared.

Keywords: General Linear Model, correlation, variables, pearson, significance, T-test, soap, production mix and statistic

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Authors: Khizar Hayat Bhatti, Fiza Javed, Misbah Zafar

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Oat (Avena sativa L.) is a major cereal plant belonging to the family Poaceae. It is a very important source of carbohydrates, starch, minerals, vitamins and proteins that are beneficial for general health. Plants grow in the heavy metals contaminated soils that results in decline in growth. Glycine betaine application may improve plant growth, survival and resistance to metabolic disturbances due to stresses. Heavy metals, like nickels, have been accumulated for a long time in the soil because of industrial waste and sewage. The experiment was intended to alleviate the detrimental effects of heavy metal nickel stress on two oat varieties ‘Sgd-2011 and Hay’ using Glycine betain. Nickel was induced through soil application while GB was applied as foliar spray. After 10 days of nickel treatment, an exogenous spray of glycine betaine on the intact plant leaves. Data analysis was carried out using a Completely Randomized Design (CRD) with three replications in this study. For the analysis of all the data of the current research, Mini-Tab 19 software was used to compare the mean value of all treatments and Microsoft Excel software for generating the bars graphs. Significant accelerated plant growth was recorded when Ni exposed plants were treated with GB. Based on data findings, 3mM GB caused significant recovery from Ni stress doses. Overall results also demonstrated that the sgd-2011 variety of oats had the greatest outcomes for all parameters.

Keywords: CRD, foliar spray method, glycine betaine, heavy metals, nickel, ROS

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Authors: Chandra Prayaga, Aaron Wade, Lakshmi Prayaga, Gopi Shankar Mallu

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This paper presents the use of machine learning algorithms to predict the success of students in an introductory physics course. Data having 140 rows pertaining to the performance of two batches of students was used. The lack of sufficient data to train robust machine learning models was compensated for by generating synthetic data similar to the real data. CTGAN and CTGAN with Gaussian Copula (Gaussian) were used to generate synthetic data, with the real data as input. To check the similarity between the real data and each synthetic dataset, pair plots were made. The synthetic data was used to train machine learning models using the PyCaret package. For the CTGAN data, the Ada Boost Classifier (ADA) was found to be the ML model with the best fit, whereas the CTGAN with Gaussian Copula yielded Logistic Regression (LR) as the best model. Both models were then tested for accuracy with the real data. ROC-AUC analysis was performed for all the ten classes of the target variable (Grades A, A-, B+, B, B-, C+, C, C-, D, F). The ADA model with CTGAN data showed a mean AUC score of 0.4377, but the LR model with the Gaussian data showed a mean AUC score of 0.6149. ROC-AUC plots were obtained for each Grade value separately. The LR model with Gaussian data showed consistently better AUC scores compared to the ADA model with CTGAN data, except in two cases of the Grade value, C- and A-.

Keywords: machine learning, student success, physics course, grades, synthetic data, CTGAN, gaussian copula CTGAN

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Authors: Jatuphum Ketchatturat

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Value-added assessment has been used for developing the model of monitoring and evaluation of student's learning achievement. The steps of model development consist of 1) study and analyisis of the school and the district report system of student achievement and progress, 2) collecting the data of student achievement to develop the value added indicator, 3) developing the system of value-added assessment by participatory action research approach, 4) putting the system of value-added assessment into the educational district of secondary school, 5) determining the quality of the developed system of value-added assessment. The components of the developed model consist of 1) the database of value-added assessment of student's learning achievement, 2) the process of monitoring and evaluation the student's learning achievement, and 3) the reporting system of value-added assessment of student's learning achievement.

Keywords: learning achievement, monitoring and evaluation, value-added assessment

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Authors: Turuganti Venkateswarlu, Jagadeesh Anmala

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Excessive runoffs from various non-point source land uses, and other point sources are rapidly contaminating the water quality of streams in the Upper Green River watershed, Kentucky, USA. It is essential to maintain the stream water quality as the river basin is one of the major freshwater sources in this province. It is also important to understand the water quality parameters (WQPs) quantitatively and qualitatively along with their important features as stream water is sensitive to climatic events and land-use practices. In this paper, a model was developed for predicting one of the significant WQPs, Fecal Coliform (FC) from precipitation, temperature, urban land use factor (ULUF), agricultural land use factor (ALUF), and forest land-use factor (FLUF) using Random Forest (RF) algorithm. The RF model, a novel ensemble learning algorithm, can even find out advanced feature importance characteristics from the given model inputs for different combinations. This model’s outcomes showed a good correlation between FC and climate events and land use factors (R2 = 0.94) and precipitation and temperature are the primary influencing factors for FC.

Keywords: water quality, land use factors, random forest, fecal coliform

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Authors: Xiongxiong You, Zhanwen Niu

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Choosing an appropriate surrogate model plays an important role in surrogates-assisted evolutionary algorithms (SAEAs) since there are many types and different kernel functions in the surrogate model. In this paper, an adaptive selection of the best suitable surrogate model method is proposed to solve different kinds of expensive optimization problems. Firstly, according to the prediction residual error sum of square (PRESS) and different model selection strategies, the excellent individual surrogate models are integrated into multiple ensemble models in each generation. Then, based on the minimum root of mean square error (RMSE), the best suitable surrogate model is selected dynamically. Secondly, two methods with dynamic number of models and selection strategies are designed, which are used to show the influence of the number of individual models and selection strategy. Finally, some compared studies are made to deal with several commonly used benchmark problems, as well as a rotor system optimization problem. The results demonstrate the accuracy and robustness of the proposed method.

Keywords: adaptive selection, expensive optimization, rotor system, surrogates assisted evolutionary algorithms

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Authors: Foo Kok, Varun Thangamani

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Rectangular cavities with a full-span or finite-width configuration have been the basis of much previous research on cavity flows. However, much less attention has been given to the influence of sidewalls, in particular, on low-speed cavity flows. In this study, the flow characteristics of two separate low-speed finite-width cavities with a Reynolds number of 𝑅𝑒𝐷 = 10⁴ are examined using large eddy simulations. Two different lateral boundary conditions are used to investigate the influence of sidewalls on the self-sustaining oscillations and the three-dimensional flow fields inside the cavities. The results show that the full-span finite width cavities are less sensitive to the sidewall effect at a low length-to-width ratio 𝐿/𝐷. The increase in 𝐿/𝐷 leads to a departure from two-dimensional instability and results in the loss of spanwise homogeneity. The analysis of the spanwise flow structures shows that these effects correspond closely to the declination of the centrifugal force from the primary recirculation zone. Such effects are also reflected in the distinct modulation of the secondary vortices in the primary recirculation zone, which suggests that the instabilities observed in the full-span finite-width cavity flows are predominantly dependent on the secondary motion from the primary recirculation zone.

Keywords: LES, cavity flows, unsteady shear layer, instability modes, secondary flow

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Authors: E. Benga, T. Tengen, A. Alugongo

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Periodic and continuous inventory models are the two classical management tools used to handle inventories. These models have advantages and disadvantages. The implementation of both continuous (r,Q) inventory and periodic (R, S) inventory models in most manufacturing plants comes with higher cost. Such high inventory costs are due to the fact that most manufacturing plants are not flexible enough. Since demand and lead-time are two important variables of every inventory models, their effect on the flexibility of the manufacturing plant matter most. Unfortunately, these effects are not clearly understood by managers. The reason is that the decision parameters of the continuous (r, Q) inventory and periodic (R, S) inventory models are not designed to effectively deal with the issues of uncertainties such as poor manufacturing performances, delivery performance supplies performances. There is, therefore, a need to come up with a predictive and hybrid inventory model that can combine in some sense the feature of the aforementioned inventory models. A linear combination technique is used to hybridize both continuous (r, Q) inventory and periodic (R, S) inventory models. The behavior of such hybrid inventory model is described by a differential equation and then optimized. From the results obtained after simulation, the continuous (r, Q) inventory model is more effective than the periodic (R, S) inventory models in the short run, but this difference changes as time goes by. Because the hybrid inventory model is more cost effective than the continuous (r,Q) inventory and periodic (R, S) inventory models in long run, it should be implemented for strategic decisions.

Keywords: periodic inventory, continuous inventory, hybrid inventory, optimization, manufacturing plant

Procedia PDF Downloads 385

Authors: Duplan Yves Jamont Junior

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The Diamond-Mortensen-Pissarides model widely used in labor economics is tailored to fishery. By this way, a fishing function is defined to depict the fishing technology, and Bellman equations are established to describe the behaviors of fishermen and conservationists. On this basis, a negotiation takes place as a Nash-bargaining over the upper limit of the fishing pressure between both political representative groups of fishermen and conservationists. The existence and uniqueness conditions of the Nash-bargained fishing pressure are established. Given the biomass evolution equation, the dynamics of the model variables (fishing pressure, biomass, fish need) is studied.

Keywords: conservation, fishery, fishing, Nash bargaining

Procedia PDF Downloads 262

Authors: Kingsley Oturu, Winifred Ijomah, Wale Coker, Chibueze Achi

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With the impact of BREXIT and the need for cross-border collaboration, this international research investigated the use of a conceptual model for remanufacturing medical equipment (with a focus on anesthetic machines and baby incubators). Early findings of the research suggest that contextual factors need to be taken into consideration, as well as an emphasis on cleaning (e.g., sterilization) during the process of remanufacturing medical equipment. For example, copper tubings may be more important in the remanufacturing of anesthetic equipment in tropical climates than in cold climates.

Keywords: medical equipment remanufacture, sustainability, circular business models, remanufacture process model

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Authors: Farokh Alipour, Ali Falavand, Neda Beit Saeid

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The calculation of the effect of accidental releases of flammable materials such as LNG requires the use of a suitable consequence model. This study is due to providing a planning advice for developments in the vicinity of LNG sites and other sites handling flammable materials. In this paper, an applicable algorithm that is able to model pool fires on water is presented and applied to estimate pool fire damage zone. This procedure can be used to model pool fires on land and could be helpful in consequence modeling and domino effect zone measurements of flammable materials which is needed in site selection and plant layout.

Keywords: LNG, pool fire, spill, radiation

Procedia PDF Downloads 409

Authors: Linda Frost, Lindsay Anderson, Jana Borras, Ariel Dysangco, Vimabayi Makwaira

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The academic environment in which nursing students are immersed in comes with many demands and expectations. Course load, clinical placements, and financial expenses are examples of the pressures facing students each semester. These pressures contribute to student stress and impact their overall well-being and mental fitness. Students' ability to cope with stress and bounce back from adversity is enhanced when we build their mental fitness. Building mental fitness has the benefit of improving physical health, relationships, self-esteem, resilience, work productivity, and overall contentment, happiness and life satisfaction. While self-care is encouraged to avoid burnout, there is a gap in literature on programs to help build nursing students’ mental health and ability to engage in self-care. There is an opportunity and a need to design programs and implement actions aimed at reducing stress and its adverse effects on nursing students. Nursing students require the support of people who understand the complexities of the nursing profession, multifaceted work environments in which they operate, and the impact these environments have on their mental fitness. Nursing academia is in the best position to ensure that tools are in place to support the next generation of nurses who face a career with significant emotional and physical demands. This is a mixed-method study using an embedded design. We utilized a pretest-posttest design to compare the difference in psychological capital (PsyCap) and burnout in students who have received the Mastering My Mental Fitness-Nurses™ (MMMF-N™) workshops (n=8) and the control group (n=9) who have not. Semi structured interviews were conducted with the eight nursing students in the intervention group, along with data from feedback forms to explore the impact of the workshops on student’s burnout and PsyCap and determine how to improve the workshops for future students. The quantitative and qualitative data will be merged using a side-by-side comparison. This will be in a discussion format that allows for the comparison of the results from both phases. The findings will be available January 2025. We anticipate that students in the control and intervention group will report similar levels of burnout. As well, students in the intervention group will indicate the benefits of the MMMF-N™ workshops through qualitative interviews and workshop feedback forms.

Keywords: burnout, mental fitness, nursing students, psychological capital

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Authors: Heidar Jafarizadeh, Hossein Keshtkar, Ahmad Sohankar

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Heat transfer and turbulent flow structure have been studied in a divergent ribbed duct with a varying duct geometry with Reynolds numbers of 7000 to 90000 using numerical methods. In this study, we confirmed our numerical results of a ribbed duct with an Initial slope of zero to 3 degree by comparing them to experimental data we had and investigated the impact of the ducts divergence on heat transfer and flow pattern in the 2-dimensional flow. Then we investigated the effect of tilting the ribs, on heat transfer and flow behavior. We achieved this by changing the ribs angles from a range of 40 to 75 degrees in a divergent duct and simulated the flow in 3-dimensions. Our results show that with an increase in duct divergence, heat transfer increases linearly and the coefficient of friction increases exponentially. As the results show, a duct with a divergence angle of 1.5 degree presents better thermal performance in comparison with all the angle range’s we studied. Besides, a ribbed duct with 40 degree rib orientation had the best thermal performance considering the simultaneous effects of pressure drop and heat transfer which were imposed on it.

Keywords: divergent ribbed duct, heat transfer, thermal performance, turbulent flow structure

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Authors: Fredrick Etyang

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This paper presents a Rapid Industrialization Model (RIM) designed to support existing industrialization policies, strategies and industrial development plans at National, Regional and Constituent level in Africa. The model will reinforce efforts to attainment of inclusive and sustainable industrialization of Africa by state and non-state actors. The overall objective of this model is to serve as a framework for rapid industrialization in developing economies and the specific objectives range from supporting rapid industrialization development to promoting a structural change in the economy, a balanced regional industrial growth, achievement of local, regional and international competitiveness in areas of clear comparative advantage in industrial exports and ultimately, the RIM will serve as a step-by-step guideline for the industrialization of African Economies. This model is a product of a scientific research process underpinned by desk research through the review of African countries development plans, strategies, datasets, industrialization efforts and consultation with key informants. The rigorous research process unearthed multi-directional and renewed efforts towards industrialization of Africa premised on collective commitment of individual states, regional economic communities and the African union commission among other strategic stakeholders. It was further, established that the inputs into industrialization of Africa outshine the levels of industrial development on the continent. The RIM comes in handy to serve as step-by-step framework for African countries to follow in their industrial development efforts of transforming inputs into tangible outputs and outcomes in the short, intermediate and long-run. This model postulates three stages of industrialization and three phases toward rapid industrialization of African economies, the model is simple to understand, easily implementable and contextualizable with high return on investment for each unit invested into industrialization supported by the model. Therefore, effective implementation of the model will result into inclusive and sustainable rapid industrialization of Africa.

Keywords: economic development, industrialization, economic efficiency, exports and imports

Procedia PDF Downloads 89

Authors: Samindi Samarakoon, Ørjan Sletbakk Vie, Remi Kleiven Fjelldal

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White concrete facade elements are widely used in construction industry. It is challenging to achieve the desired workability in casting of white concrete elements. Particle Matrix model was used for proportioning the self-compacting white concrete (SCWC) to control segregation and bleeding and to improve workability. The paper presents how to reach the target slump flow while controlling bleeding and segregation in SCWC. The amount of aggregates, binders and mixing water, as well as type and dosage of superplasticizer (SP) to be used are the major factors influencing the properties of SCWC. Slump flow and compressive strength tests were carried out to examine the performance of SCWC, and the results indicate that the particle matrix model could produce successfully SCWC controlling segregation and bleeding.

Keywords: white concrete, particle matrix model, mix design, construction industry

Procedia PDF Downloads 271

Authors: Ferry Kurniawan

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In this paper, we nowcast quarterly output growth in Indonesia by exploiting higher frequency data (monthly indicators) using a mixed-frequency factor model and exploiting both quarterly and monthly data. Nowcasting quarterly GDP in Indonesia is particularly relevant for the central bank of Indonesia which set the policy rate in the monthly Board of Governors Meeting; whereby one of the important step is the assessment of the current state of the economy. Thus, having an accurate and up-to-date quarterly GDP nowcast every time new monthly information becomes available would clearly be of interest for central bank of Indonesia, for example, as the initial assessment of the current state of the economy -including nowcast- will be used as input for longer term forecast. We consider a small scale mixed-frequency factor model to produce nowcasts. In particular, we specify variables as year-on-year growth rates thus the relation between quarterly and monthly data is expressed in year-on-year growth rates. To assess the performance of the model, we compare the nowcasts with two other approaches: autoregressive model –which is often difficult when forecasting output growth- and Mixed Data Sampling (MIDAS) regression. In particular, both mixed frequency factor model and MIDAS nowcasts are produced by exploiting the same set of monthly indicators. Hence, we compare the nowcasts performance of the two approaches directly. To preview the results, we find that by exploiting monthly indicators using mixed-frequency factor model and MIDAS regression we improve the nowcast accuracy over a benchmark simple autoregressive model that uses only quarterly frequency data. However, it is not clear whether the MIDAS or mixed-frequency factor model is better. Neither set of nowcasts encompasses the other; suggesting that both nowcasts are valuable in nowcasting GDP but neither is sufficient. By combining the two individual nowcasts, we find that the nowcast combination not only increases the accuracy - relative to individual nowcasts- but also lowers the risk of the worst performance of the individual nowcasts.

Keywords: nowcasting, mixed-frequency data, factor model, nowcasts combination

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Authors: Lela Mirtskhulava, Mariam Khunjgurua, Nino Lomineishvili, Koba Bakuria

Abstract:

Software reliability prediction gives a great opportunity to measure the software failure rate at any point throughout system test. A software reliability prediction model provides with the technique for improving reliability. Software reliability is very important factor for estimating overall system reliability, which depends on the individual component reliabilities. It differs from hardware reliability in that it reflects the design perfection. Main reason of software reliability problems is high complexity of software. Various approaches can be used to improve the reliability of software. We focus on software reliability model in this article, assuming that there is a time redundancy, the value of which (the number of repeated transmission of basic blocks) can be an optimization parameter. We consider given mathematical model in the assumption that in the system may occur not only irreversible failures, but also a failure that can be taken as self-repairing failures that significantly affect the reliability and accuracy of information transfer. Main task of the given paper is to find a time distribution function (DF) of instructions sequence transmission, which consists of random number of basic blocks. We consider the system software unreliable; the time between adjacent failures has exponential distribution.

Keywords: exponential distribution, conditional mean time to failure, distribution function, mathematical model, software reliability

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Authors: Asmaa F. Hamouda, Randa M Shrourou

Abstract:

Cabbage (Brassica oleracea) and Ginger (Zingiber officinale) constitute apportion of regular human diet. The effect of Cabbage(CE) and Ginger extracts(GE) separately on liver nitric oxide (NO), malondialdehyde (MDA), as well as serum aspartate aminotransferase (AST), alanine aminotransferase (ALT), total bilirubin, total cholesterol(TC), triglyceride(T.G), high density lipoprotein(HDL cholesterol), low density lipoprotein (LDL cholesterol), thyroid-stimulating hormone (TSH), Triiodothyronine (T3), Thyroxine (T4) in rats treated and untreated with carbon tetrachloride (CCl4) was studied. The levels of NO, MDA, as well as serum AST, ALT, total bilirubin, TC, T.G, LDLand TSH showed an elevation and decline in HDL, T3, and T4 in rats treated with CCl4 as compared to control. Treatment of rats with GE pre, during, and post CCl4 administration improved NO, MDA, as well as serum AST, ALT, total bilirubin, TC, T.G, HDL, LDL, TSH, T3, T4 as compared to CCl4, indicates that GE improve thyroid function and reduced oxidative stress as well as injuries induced by CCl4. Treatment of rats with CE pre, during, and post CCl4 administration did not improved in the thyroid hormones and lipid profile levels as compared to CCl4. These findings suggest that ginger treatment exerts a protective effect on metabolic disorders by decreasing oxidative stress.

Keywords: liver injuries, carbon tetrachloride (CCl4), cabbage (Brassica oleracea), ginger (Zingiber officinale), thyroid function

Procedia PDF Downloads 267

Authors: Noora Al-Shanfari, M. Mazharul Islam

Abstract:

The cumulative incidence function (CIF) is a fundamental approach for analyzing survival data in the presence of competing risks, which estimates the marginal probability for each competing event. Parametric modeling of CIF has the advantage of fitting various shapes of CIF and estimates the impact of covariates with maximum efficiency. To calculate the total CIF's covariate influence using a parametric model., it is essential to parametrize the baseline of the CIF. As the CIF is an improper function by nature, it is necessary to utilize an improper distribution when applying parametric models. The Gompertz distribution, which is an improper distribution, is limited in its applicability as it only accounts for monotone hazard shapes. The generalized Gompertz distribution, however, can adapt to a wider range of hazard shapes, including unimodal, bathtub, and monotonic increasing or decreasing hazard shapes. In this paper, the generalized Gompertz distribution is used to parametrize the baseline of the CIF, and the parameters of the proposed model are estimated using the maximum likelihood approach. The proposed model is compared with the existing Gompertz model using the Akaike information criterion. Appropriate statistical test procedures and model-fitting criteria will be used to test the adequacy of the model. Both models are applied to the ‘colon’ dataset, which is available in the “biostat3” package in R.

Keywords: competing risks, cumulative incidence function, improper distribution, parametric modeling, survival analysis

Procedia PDF Downloads 111

Authors: Emir H. Pernet, Jeimy J. Cano

Abstract:

Maturity models, used descriptively to explain changes in reality or normatively to guide managers to make interventions to make organizations more effective and efficient, are based on the principles of statistical quality control promulgated by Shewhart in the years 30, and on the principles of PDCA continuous improvement (Plan, Do, Check, Act) developed by Deming and Juran. Some frameworks developed over the concept of maturity models includes COBIT, CMM, and ITIL. This paper presents some limitations of traditional maturity models, most of them based on points of reflection and analysis done by some authors. Almost all limitations are related to the mechanistic and reductionist approach of the principles over those models are built. As Systems Theory helps the understanding of the dynamics of organizations and organizational change, the development of a systemic maturity model can help to overcome some of those limitations. This document proposes a systemic maturity model, based on a systemic conceptualization of organizations, focused on the study of the functioning of the parties, the relationships among them, and their behavior as a whole. The concept of maturity from the system theory perspective is conceptually defined as an emergent property of the organization, which arises from as a result of the degree of alignment and integration of their processes. This concept is operationalized through a systemic function that measures the maturity of an organization, and finally validated by the measuring of maturity in organizations. For its operationalization and validation, the model was applied to measure the maturity of organizational Governance, Risk and Compliance (GRC) processes.

Keywords: GRC, maturity model, systems theory, viable system model

Procedia PDF Downloads 316