Search results for: inventory theoretic model

Authors: K. Boumediene, S. E. Belhenniche

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This article presents a numerical analysis of a turbulent flow past DTMB 4119 marine propeller by the means of RANS approach; the propeller designed at David Taylor Model Basin in USA. The purpose of this study is to predict the hydrodynamic performance of the marine propeller, it aims also to compare the results obtained with the experiment carried out in open water tests; a periodical computational domain was created to reduce the unstructured mesh size generated. The standard kw turbulence model for the simulation is selected; the results were in a good agreement. Therefore, the errors were estimated respectively to 1.3% and 5.9% for KT and KQ.

Keywords: propeller flow, CFD simulation, RANS, hydrodynamic performance

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Authors: Najibullah M, Soumendra Nath Kuiry

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

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

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Authors: Anand Malik

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The Himalayas with high tectonic activities poses a great threat to human life and property. Climate change is another reason which triggering extreme events multiple fold effect on high mountain glacial environment, rock falls, landslides, debris flows, flash flood and snow avalanches. One such extreme event of cloud burst along with breach of moraine dammed Chorabri Lake occurred from June 14 to June 17, 2013, triggered flooding of Saraswati and Mandakini rivers in the Kedarnath Valley of Rudraprayag district of Uttrakhand state of India. As a result, huge volume of water with its high velocity created a catastrophe of the century, which resulted into loss of large number of human/animals, pilgrimage, tourism, agriculture and property. Thus a comprehensive assessment of debris flow hazards requires GIS-based modeling using numerical methods. The aim of present study is to focus on analysis and mapping of debris flow movements using geospatial data with flow-r (developed by team at IGAR, University of Lausanne). The model is based on combined probabilistic and energetic algorithms for the assessment of spreading of flow with maximum run out distances. Aster Digital Elevation Model (DEM) with 30m x 30m cell size (resolution) is used as main geospatial data for preparing the run out assessment, while Landsat data is used to analyze land use land cover change in the study area. The results of the study area show that model can be applied with great accuracy as the model is very useful in determining debris flow areas. The results are compared with existing available landslides/debris flow maps. ArcGIS software is used in preparing run out susceptibility maps which can be used in debris flow mitigation and future land use planning.

Keywords: debris flow, geospatial data, GIS based modeling, flow-R

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Authors: Gunay Imanguliyeva

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Burnout is one of the concerning issues in education. The present paper aimed to explore the concept of burnout among program directors and faculty working in three higher education institutions (HEIs) in Azerbaijan and identify the factors contributing to burnout and the possible consequences of this syndrome on research participants’ professional and personal life. The researcher believed that if the concept of burnout was defined precisely and explored among more faculty, administration, and educational institutions, university leadership may have looked for the ways to support program directors and faculty, which would increase job satisfaction and decrease turnover. An exploratory qualitative research design was chosen for this study. The conceptual framework of this study was based on the Maslach Burnout Inventory. The instruments of the research were semi-structured interviews, observation, and document review. Three EFL (Teaching English as a Foreign Language) instructors and three program directors of the English Language Department working in three higher educational institutions in Azerbaijan participated in this study. The major findings of this study showed that both program directors and faculty suffered from burnout. Though they were aware of the factors that caused burnout, they did not know how to deal with this feeling. While research participants had high feeling of Emotional Exhaustion and Depersonalization, they had a low feeling of Personal Accomplishment. The researcher suggests that further research is important to measure the level of burnout and to enable HEIs to increase the productivity of program directors’ and faculty’s work as well as decrease the rate of retention in future. Also, in order to help program directors and faculty to cope with burnout, the research recommends the university leadership to meet their psycho-social needs, emotional-physical needs, and personal-intellectual needs. Keywords: burnout, emotional exhaustion, factors, well-being, higher education

Keywords: burnout, well-being, higher education, factors

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Authors: Noha A. Alowedi

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This paper proposes a Translator Career Path (TCP) which is based on the Dreyfus Model of Skills Acquisition as the conceptual framework. In this qualitative study, the methodology to collect and analyze the data takes an inductive approach that draws upon the literature to form the criteria for the different steps in the TCP. This path is based on descriptors of expert translator performance and best employees’ practice documented in the literature. Each translator skill will be graded as novice, advanced beginner, competent, proficient, and expert. Consequently, five levels of translator performance are identified in the TCP as five ranks. The first rank is the intern translator, which is equivalent to the novice level; the second rank is the assistant translator, which is equivalent to the advanced beginner level; the third rank is the associate translator, which is equivalent to the competent level; the fourth rank is the translator, which is equivalent to the proficient level; finally, the fifth rank is the expert translator, which is equivalent to the expert level. The main function of this career path is to guide the processes of translator development in translation organizations. Although it is designed primarily for the need of in-house translators’ supervisors, the TCP can be used in academic settings for translation trainers and teachers.

Keywords: Dreyfus model, translation organization, translator career path, translator development, translator evaluation, translator promotion

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Authors: Sungjun Hong, Yanghon Chung, Nyunbae Park, Sangyong Park

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South Korea, as the 7th largest greenhouse gas emitting country in 2011, announced that the national reduction target of greenhouse gas emissions was 30% based on BAU (Business As Usual) by 2020. And the reduction rate of the transport sector is 34.3% which is the highest figure among all sectors. This paper attempts to analyze the environmental effect on deploying the green cars in Korean road transport sector. In order to calculate the greenhouse gas emissions, the LEAP model is applied in this study.

Keywords: green car, greenhouse gas, LEAP model, road transport sector

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Authors: Ritesh Kumar, Rajendra Pamula

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In this paper, we present our contribution for book recommendation. In our experiment, we combine the results of Sequential Dependence Model (SDM) and exploitation of book information such as reviews, tags and ratings. This social information is assigned by users. For this, we used CLEF-2016 Social Book Search Track Suggestion task. Finally, our proposed method extensively evaluated on CLEF -2015 Social Book Search datasets, and has better performance (nDCG@10) compared to other state-of-the-art systems. Recently we got the good performance in CLEF-2016.

Keywords: sequential dependence model, social information, social book search, query expansion

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Authors: Rakesh Kumar, A. K. Ghosh

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The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Eda Yakit Ak, Ergül Aslan

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The study was conducted using the quasi-experimental design to determine the influence of the nursing support program prepared according to the Health Belief Model on reproductive health behaviors of orthopedically disabled women in the physical therapy and rehabilitation clinic at a university hospital between August 2019-October, 2020. The research sample included 50 women (35 in the control group and 15 in the experimental group with orthopedic disability). A 3-week nursing support program was applied to the experimental group of women. To collect the data, Introductory Information Form and Scale for Determining the Protective Attitudes of Married Women towards Reproductive Health (SDPAMW) were applied. The evaluation was made with a follow-up form for four months. In the first evaluation, the total SDPAMW scores were 119.93±20.59 for the experimental group and 122.20±16.71 for the control group. In the final evaluation, the total SDPAMW scores were 144.27±11.95 for the experimental group and 118.00±16.43 for the control group. The difference between the groups regarding the first and final evaluations for the total SDPAMW scores was statistically significant (p<0.01). In the experimental group, between the first and final evaluations regarding the sub-dimensions of SDPAMW, an increase was found in the behavior of seeing the doctor on reproductive health issues, protection from reproductive organ and breast cancer, general health behaviors to protect reproductive health, and protection from genital tract infections (p<0.05). Consequently, the nursing support program based on the Health Belief Model applied to orthopedically disabled women positively affected reproductive health behaviors.

Keywords: orthopedically disabled, woman, reproductive health, nursing support program, health belief model

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Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Yuanhao Gao, Pin Lin, Kees Weijer

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In this paper, we will determine the external body force distribution with analysis of stokes fluid motion using mathematical modelling and numerical approaching. The body force distribution is regarded as the unknown variable and could be determined by the idea of optimal control theory. The Stokes flow motion and its velocity are generated by given forces in a unit square domain. A regularized objective functional is built to match the numerical result of flow velocity with the generated velocity data. So that the force distribution could be determined by minimizing the value of objective functional, which is also the difference between the numerical and experimental velocity. Then after utilizing the Lagrange multiplier method, some partial differential equations are formulated consisting the optimal control system to solve. Finite element method and conjugate gradient method are used to discretize equations and deduce the iterative expression of target body force to compute the velocity numerically and body force distribution. Programming environment FreeFEM++ supports the implementation of this model.

Keywords: optimal control model, Stokes equation, finite element method, conjugate gradient method

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Authors: M. Osman Gani, M. Ferdows, Toshiyuki Ogawa

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In this work, we proposed a modified FHN-type reaction-diffusion system for a bistable excitable system by adding a scaled function obtained from a given function. We study the existence and the stability of the periodic traveling waves (or wavetrains) for the FitzHugh-Nagumo (FHN) system and the modified one and compare the results. The stability results of the periodic traveling waves (PTWs) indicate that most of the solutions in the fast family of the PTWs are stable for the FitzHugh-Nagumo equations. The instability occurs only in the waves having smaller periods. However, the smaller period waves are always unstable. The fast family with sufficiently large periods is always stable in FHN model. We find that the oscillation of pulse widths is absent in the standard FHN model. That motivates us to study the PTWs in the proposed FHN-type reaction-diffusion system for the bistable excitable media. A good agreement is found between the solutions of the traveling wave ODEs and the corresponding whole PDE simulation.

Keywords: bistable system, Eckhaus bifurcation, excitable media, FitzHugh-Nagumo model, periodic traveling waves

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Authors: Rebecca Angeles

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This case study features the Kuehne + Nagel PharmaChain solution for ‘cold chain’ pharmaceutical and biologic product shipments with IOT-enabled features for shipment temperature and location tracking. Using the case study method and content analysis, this research project investigates the application of the structurational model of technology theory introduced by Orlikowski in order to interpret the firm’s entry and participation in the IOT-impelled marketplace.

Keywords: Internet of Things (IOT), radio frequency identification (RFID), structurational model of technology (Orlikowski), supply chain management

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Authors: M. Khoshab, M. J. Sedigh

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Dynamic systems, which in mathematical point of view are those governed by differential equations, are much more difficult to study and to predict their behavior in comparison with static systems which are governed by algebraic equations. Economical systems such as market are among complicated dynamic systems. This paper tries to adopt a very simple mathematical model for market and to study effect of supply and demand function on behavior of the market while the supply side experiences a lag due to production restrictions.

Keywords: dynamic system, lag on supply demand, market stability, supply demand model

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Authors: Mona Heydari, Ehsan Motamedian, Seyed Abbas Shojaosadati

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Prediction of perturbations after genetic manipulation (especially gene knockout) is one of the important challenges in systems biology. In this paper, a new algorithm is introduced that integrates microarray data into the metabolic model. The algorithm was used to study the change in the cell phenotype after knockout of Gss gene in Escherichia coli BW25113. Algorithm implementation indicated that gene deletion resulted in more activation of the metabolic network. Growth yield was more and less regulating gene were identified for mutant in comparison with the wild-type strain.

Keywords: metabolic network, gene knockout, flux balance analysis, microarray data, integration

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Authors: Seyedeh Mersedeh Banijamali, Ali Rajabzadeh

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Industrial development in recent centuries has been replaced by a sustainable development. The industry executives, particularly in the development countries are looking for procedures to protect the environment, improve their organization's performance. One of these approaches is the green supply chain management. Green supply chain management approach as a comprehensive approach to environmental management that contains all flows from suppliers to producers and ultimately to consumers, in many industries, particularly in the Steel industry, which has a strategic role in the country's industrial and economic development, has been receiving significant attention. The purpose of this study is examining the impact of green supply chain on chain operational performance in the Steel industry and formulating model for it. In this way, first the components of green supply chain (in 5 dimensions, planning, sourcing, making, delivery and return) have been prioritized through TOPSIS decision technique and then impact of these components on operational performance has been modeled with model dynamic systems and Vensim software. This research shows that green supply chain has a positive impact on operational performance and improve it.

Keywords: green supply chain, the dimensions of the green supply chain, operational performance, steel industry, dynamical systems

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Authors: Juyeon Lee, Sungeun You

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Experiential avoidance is one’s tendency to avoid painful internal experience, unwanted adverse thoughts, emotions, and physical sensations. The Multidimensional Experiential Avoidance Questionnaire (MEAQ) is a measure of experiential avoidance, and the original scale consisted of 62 items with six subfactors including behavioral avoidance, distress aversion, procrastination, distraction/suppression, repression/denial, and distress endurance. The purpose of this study was to examine the factor structure of the MEAQ in a Korean sample. Three hundred community adults and university students aged 18 to 35 participated in an online survey assessing experiential avoidance (MEAQ and Acceptance and Action Questionnaire-II; AAQ-II), depression (Patient Health Questionnaire-9; PHQ-9), anxiety (Generalized Anxiety Disoder-7; GAD-7), negative affect (Positive and Negative Affect Scale; PANAS), neuroticism (Big Five Inventory; BFI), and quality of life (Satisfaction with Life Scale; SWLS). Factor analysis with principal axis with direct oblimin rotation was conducted to examine subfactors of the MEAQ. Results indicated that the six-factor structure of the original scale was adequate. Eight items out of 62 items were removed due to insufficient factor loading. These items included 3 items of behavior avoidance (e.g., “When I am hurting, I would do anything to feel better”), 2 items of repression/denial (e.g., “I work hard to keep out upsetting feelings”), and 3 items of distress aversion (e.g., “I prefer to stick to what I am comfortable with, rather than try new activities”). The MEAQ was positively associated with the AAQ-II (r = .47, p < .001), PHQ-9 (r = .37, p < .001), GAD-7 (r = .34, p < .001), PANAS (r = .35, p < .001), and neuroticism (r = .24, p < .001), and negatively correlated with the SWLS (r = -.38, p < .001). Internal consistency was good for the MEAQ total (Cronbach’s α = .90) as well as all six subfactors (Cronbach’s α = .83 to .87). The findings of the study support the multidimensional feature of experiential avoidance and validity of the MEAQ in a sample of Korean adults.

Keywords: avoidance, experiential avoidance, factor structure, MEAQ

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Authors: Javier Navarro Garcia, Narciso Vazquez Carretero

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Eurocode 1, part 1-4, wind actions, includes in its article 1.5 the possibility of using numerical calculation methods to obtain information on the loads acting on a building. On the other hand, the analysis using computational fluids dynamics (CFD) in aerospace, aeronautical, and industrial applications is already in widespread use. The application of techniques based on CFD analysis on the building to study its aerodynamic behavior now opens a whole alternative field of possibilities for civil engineering and architecture; optimization of the results with respect to those obtained by applying the regulations, the possibility of obtaining information on pressures, speeds at any point of the model for each moment, the analysis of turbulence and the possibility of modeling any geometry or configuration. The present work compares the results obtained on a building, with respect to its aerodynamic behavior, from a mathematical model based on the analysis by CFD with the results obtained by applying Eurocode1, part1-4, wind actions. It is verified that the results obtained by CFD techniques suppose an optimization of the wind action that acts on the building with respect to the wind action obtained by applying the Eurocode1, part 1-4, wind actions. In order to carry out this verification, a 45m high square base truncated pyramid building has been taken. The mathematical model on CFD, based on finite volumes, has been calculated using the FLUENT commercial computer application using a scale-resolving simulation (SRS) type large eddy simulation (LES) turbulence model for an atmospheric boundary layer wind with turbulent component in the direction of the flow.

Keywords: aerodynamic, CFD, computacional fluids dynamics, computational mechanics

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Authors: Sidrah Ahmed

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The river and lakes flows are modeled mathematically by shallow water equations that are depth-averaged Reynolds Averaged Navier-Stokes equations under Boussinesq approximation. The temperature stratification dynamics influence the water quality and mixing characteristics. It is mainly due to the atmospheric conditions including air temperature, wind velocity, and radiative forcing. The experimental observations are commonly taken along vertical scales and are not sufficient to estimate small turbulence effects of temperature variations induced characteristics of shallow flows. Wind shear stress over the water surface influence flow patterns, heat fluxes and thermodynamics of water bodies as well. Hence it is crucial to couple temperature gradients with shallow water model to estimate the atmospheric effects on flow patterns. The Ripa system has been introduced to study ocean currents as a variant of shallow water equations with addition of temperature variations within the flow. Ripa model is a hyperbolic system of partial differential equations because all the eigenvalues of the system’s Jacobian matrix are real and distinct. The time steps of a numerical scheme are estimated with the eigenvalues of the system. The solution to Riemann problem of the Ripa model is composed of shocks, contact and rarefaction waves. Solving Ripa model with Riemann initial data with the central schemes is difficult due to the eigen structure of the system.This works presents the comparison of four different finite difference schemes for the numerical solution of Riemann problem for Ripa model. These schemes include Lax-Friedrichs, Lax-Wendroff, MacCormack scheme and a higher order finite difference scheme with WENO method. The numerical flux functions in both dimensions are approximated according to these methods. The temporal accuracy is achieved by employing TVD Runge Kutta method. The numerical tests are presented to examine the accuracy and robustness of the applied methods. It is revealed that Lax-Freidrichs scheme produces results with oscillations while Lax-Wendroff and higher order difference scheme produce quite better results.

Keywords: finite difference schemes, Riemann problem, shallow water equations, temperature gradients

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Authors: Gebremedhin Kiros, Amba Shetty, Lakshman Nandagiri

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Soil erosion is a major threat to the sustainability of land and water resources in the catchment and there is a need to identify critical areas of erosion so that suitable conservation measures may be adopted. The present study was taken up to understand the temporal and spatial distribution of soil erosion and daily sediment yield in Geba catchment (5137 km2) located in the Northern Highlands of Ethiopia. Soil and Water Assessment Tool (SWAT) was applied to the Geba catchment using data pertaining to rainfall, climate, soils, topography and land use/land cover (LU/LC) for the historical period 2000-2013. LU/LC distribution in the catchment was characterized using LANDSAT satellite imagery and the GIS-based ArcSWAT version of the model. The model was calibrated and validated using sediment concentration measurements made at the catchment outlet. The catchment was divided into 13 sub-basins and based on estimated soil erosion, these were prioritized on the basis of susceptibility to soil erosion. Model results indicated that the average sediment yield estimated of the catchment was 12.23 tons/ha/yr. The generated soil loss map indicated that a large portion of the catchment has high erosion rates resulting in significantly large sediment yield at the outlet. Steep and unstable terrain, the occurrence of highly erodible soils and low vegetation cover appeared to favor high soil erosion. Results obtained from this study prove useful in adopting in targeted soil and water conservation measures and promote sustainable management of natural resources in the Geba and similar catchments in the region.

Keywords: Ethiopia, Geba catchment, MUSLE, sediment yield, SWAT Model

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

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Gliomas are most challenging and aggressive type of tumors which appear in different sizes, locations, and scattered boundaries. CNN is most efficient deep learning approach with outstanding capability of solving image analysis problems. A fully automatic deep learning based 2D-CNN model for brain tumor segmentation is presented in this paper. We used small convolution filters (3 x 3) to make architecture deeper. We increased convolutional layers for efficient learning of complex features from large dataset. We achieved better results by pushing convolutional layers up to 16 layers for HGG model. We achieved reliable and accurate results through fine-tuning among dataset and hyper-parameters. Pre-processing of this model includes generation of brain pipeline, intensity normalization, bias correction and data augmentation. We used the BRATS-2015, and Dice Similarity Coefficient (DSC) is used as performance measure for the evaluation of the proposed method. Our method achieved DSC score of 0.81 for complete, 0.79 for core, 0.80 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, HGG

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Authors: Bekmurza H. Aitchanov, Sholpan K. Aitchanova, Olimzhon A. Baimuratov, Aitkul N. Aldibekova

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This work considers the automated control system (ACS) of milk quality during its magnetic field processing. For achieving high level of quality control methods were applied transformation of complex nonlinear systems in a linearized system with a less complex structure. Presented ACS is adjustable by seven parameters: mass fraction of fat, mass fraction of dry skim milk residues (DSMR), density, mass fraction of added water, temperature, mass fraction of protein, acidity.

Keywords: fluids magnetization, nuclear magnetic resonance, automated control system, dynamic pulse-frequency modulator, PFM, nonlinear systems, structural model

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Authors: Daniel Nkrumah

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The Magic Bullet theory was a popular media effect theory that defined the power of the mass media in altering beliefs and perceptions of its audiences. However, following the People's Choice study, the theory was said to have been disproved and was supplanted by the Two-Step Flow Theory. This paper examines the relevance of the Magic Bullet theory in Africa and establishes whether it is still relevant in Africa's media spaces and societies. Using selected cases on the continent, it adopts a grounded theory approach and explores a new theoretical model that attempts to enforce an argument that the Two-Step Flow theory though important and valid, was ill-conceived as a direct replacement to the Magic Bullet theory.

Keywords: magic bullet theory, two-step flow theory, media effects, african media

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Authors: Pedro A. Marques, Francisco Monteiro, Alessandra Zumbo, Alessia Simonini, Miguel A. Mendez

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Cryogenic fuels such as Liquid Hydrogen (LH₂) must be transported and stored at extremely low temperatures. Without expensive active cooling solutions, preventing fuel boil-off over time is impossible. Hence, one must resort to venting systems at the cost of significant energy and fuel mass loss. These losses increase significantly in propellant tanks installed on vehicles, as the presence of external accelerations induces sloshing. Sloshing increases heat and mass transfer rates and leads to significant pressure oscillations, which might further trigger propellant venting. To make LH₂ economically viable, it is essential to minimize these factors by using advanced control techniques. However, these require accurate modelling and a full understanding of the tank's thermodynamics. The present research aims to implement a simple thermodynamic model capable of predicting the state of a cryogenic fuel tank under different operating conditions (i.e., filling, pressurization, fuel extraction, long-term storage, and sloshing). Since this model relies on a set of closure parameters to drive the system's transient response, it must be calibrated using experimental or numerical data. This work focuses on the former approach, wherein the model is calibrated through an experimental campaign carried out on a reduced-scale model of a cryogenic tank. The thermodynamic model of the system is composed of three control volumes: the ullage, the liquid, and the insulating walls. Under this lumped formulation, the governing equations are derived from energy and mass balances in each region, with mass-averaged properties assigned to each of them. The gas-liquid interface is treated as an infinitesimally thin region across which both phases can exchange mass and heat. This results in a coupled system of ordinary differential equations, which must be closed with heat and mass transfer coefficients between each control volume. These parameters are linked to the system evolution via empirical relations derived from different operating regimes of the tank. The derivation of these relations is carried out using an inverse method to find the optimal relations that allow the model to reproduce the available data. This approach extends classic system identification methods beyond linear dynamical systems via a nonlinear optimization step. Thanks to the data-driven assimilation of the closure problem, the resulting model accurately predicts the evolution of the tank's thermodynamics at a negligible computational cost. The lumped model can thus be easily integrated with other submodels to perform complete system simulations in real time. Moreover, by setting the model in a dimensionless form, a scaling analysis allowed us to relate the tested configurations to a representative full-size tank for naval applications. It was thus possible to compare the relative importance of different transport phenomena between the laboratory model and the full-size prototype among the different operating regimes.

Keywords: destratification, hydrogen, modeling, pressure-drop, pressurization, sloshing, thermodynamics

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Authors: Aawag Mohsen Al-Awag, Wesam Salah Alaloul, M. S. Liew

Abstract:

Industrialized building system (IBS) is a method of construction with concentrated practices consisting of techniques, products, and a set of linked elements which operate collectively to accomplish objectives. The Industrialised Building System (IBS) has been recognised as a viable method for improving overall construction performance in terms of quality, cost, safety and health, waste reduction, and productivity. The Malaysian construction industry is considered one of the contributors to the development of the country. The acceptance level of IBS is still below government expectations. Thus, the Malaysian government has been continuously encouraging the industry to use and implement IBS. Conventional systems have several drawbacks, including project delays, low economic efficiency, excess inventory, and poor product quality. When it comes to implementing IBS, construction companies still face several obstacles and problems, notably in terms of contractual and procurement concerns, which leads to the low adoption of IBS in Malaysia. There are barriers to the acceptance of IBS technology, focused on awareness of historical failure and risks connected to IBS practices to provide enhanced performance. Therefore, the transformation from the existing conventional building systems to the industrialized building systems (IBS) is needed more than ever. The flexibility of IBS in Malaysia’s construction industry is very low due to numerous shortcomings and obstacles. Due to its environmental, economic, and social benefits, IBS could play a significant role in the Malaysian construction industry in the future. This paper concentrates on the potential role of IBS in sustainable construction practices in Malaysia. It also highlights the awareness, barriers, advantages, and disadvantages of IBS in the construction sector. The study concludes with recommendations for Malaysian construction stakeholders to encourage and increase the utilization of industrialised building systems.

Keywords: construction industry, industrialized building system, barriers, advantages and disadvantages, construction, sustainability, Malaysia

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Authors: Khawlh A. Alzubaidi, Khadijah B. Alziyadi, Amor M. Alsayari

Abstract:

The discovery of a dilute magnetic semiconductor (DMS) in which ferromagnetism is carrier-mediated and persists above room temperature is a major step toward the implementation of spintronic devices for processing, transferring, and storing of information. Among the many types of DMS materials which have been investigated, Mn-doped GaAs has become one of the best candidates for technological application. However, despite major developments over the last few decades, the maximum Curie temperature (~200 K) remains well below room temperature. In this work, we have studied the effect of Mn content and strain on the GaMnAs effective masses of electron, heavy and light holes calculated in the different crystallographic direction. Also, the Curie temperature in the DMS GaMnAs alloy is determined. Compilation of GaMnAs band parameters have been carried out using the 8-band k.p model based on Lowdin perturbation theory where spin orbit, sp-d exchange interaction, and biaxial strain are taken into account. Our results show that effective masses, calculated along the different crystallographic directions, have a strong dependence on strain, ranging from -2% (tensile strain) to 2% (compressive strain), and Mn content increased from 1 to 5%. The Curie temperature is determined within the mean-field approach based on the Zener model.

Keywords: diluted magnetic semiconductors, k.p method, effective masses, curie temperature, strain

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Authors: Moataz Medhat, Essam E. Khalil, Hatem Haridy

Abstract:

In the present study, a numerical simulation study is used to 3-D model the steady-state combustion of a staged natural gas flame in a 300 kW swirl-stabilized burner, using ANSYS solver to find the highest combustion efficiency by changing the inlet air swirl number and burner quarl angle in a furnace and showing the effect of flue gas recirculation, type of fuel and staging. The combustion chamber of the gas turbine is a cylinder of diameter 1006.8 mm, and a height of 1651mm ending with a hood until the exhaust cylinder has been reached, where the exit of combustion products which have a diameter of 300 mm, with a height of 751mm. The model was studied by 15 degree of the circumference due to axisymmetric of the geometry and divided into a mesh of about 1.1 million cells. The numerical simulations were performed by solving the governing equations in a three-dimensional model using realizable K-epsilon equations to express the turbulence and non-premixed flamelet combustion model taking into consideration radiation effect. The validation of the results was done by comparing it with other experimental data to ensure the agreement of the results. The study showed two zones of recirculation. The primary one is at the center of the furnace, and the location of the secondary one varies by changing the quarl angle of the burner. It is found that the increase in temperature in the external recirculation zone is a result of increasing the swirl number of the inlet air stream. Also it was found that recirculating part of the combustion products back to the combustion zone decreases pollutants formation especially nitrogen monoxide.

Keywords: burner selection, natural gas, analysis, recirculation

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Authors: Heval Serhat Uluk, Sam M. Dakka, Kuldeep Singh, Richard Jefferson-Loveday

Abstract:

The carbon footprint of the aviation sector in total measured 3.8% in 2017, and it is expected to triple by 2050. New combustion approaches and fuel types are necessary to prevent this. This paper will focus on using propane, methane, and hydrogen as fuel replacements for kerosene and implement a trapped vortex combustor design to increase efficiency. Reacting simulations were conducted for axisymmetric trapped vortex combustor to investigate the static pressure drop, combustion efficiency and pattern factor for various cavity aspect ratios for 0.3, 0.6 and 1 and air mass flow rates for 14 m/s, 28 m/s and 42 m/s. Propane, methane and hydrogen are used as alternative fuels. The combustion model was anchored based on swirl flame configuration with an emphasis on high fidelity of boundary conditions with favorable results of eddy dissipation model implementation. Reynolds Averaged Navier Stokes (RANS) k-ε model turbulence model for the validation effort was used for turbulence modelling. A grid independence study was conducted for the three-dimensional model to reduce computational time. Preliminary results for 24 m/s air mass flow rate provided a close temperature profile inside the cavity relative to the experimental study. The investigation will be carried out on the effect of air mass flow rates and cavity aspect ratio on the combustion efficiency, pattern factor and static pressure drop in the combustor. A comparison study among pure methane, propane and hydrogen will be conducted to investigate their suitability for trapped vortex combustors and conclude their advantages and disadvantages as a fuel replacement. Therefore, the study will be one of the milestones to achieving 2050 zero carbon emissions or reducing carbon emissions.

Keywords: computational fluid dynamics, aerodynamic, aerospace, propulsion, trapped vortex combustor

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Authors: Azam Abkhiz, Abolghasem Nasir

Abstract:

To achieve sustainable competitive advantage in the market, it is necessary to provide and improve customer satisfaction and Loyalty. To reach this objective, companies need to identify and analyze their customers. Thus, it is critical to measure the level of customer satisfaction and Loyalty very carefully. This study attempts to build a conceptual model to provide clear insights of customer loyalty. Using Bayesian networks (BNs), a model is proposed to evaluate customer loyalty and its consequences, such as repurchase and positive word-of-mouth. BN is a probabilistic approach that predicts the behavior of a system based on observed stochastic events. The most relevant determinants of customer loyalty are identified by the literature review. Perceived value, service quality, trust, corporate image, satisfaction, and switching costs are the most important variables that explain customer loyalty. The data are collected by use of a questionnaire-based survey from 1430 customers of a home appliances manufacturer in Iran. Four scenarios and sensitivity analyses are performed to run and analyze the impact of different determinants on customer loyalty. The proposed model allows businesses to not only set their targets but proactively manage their customer behaviors as well.

Keywords: customer satisfaction, customer loyalty, Bayesian networks, home appliances industry

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Authors: Teng lin, Li Yuxing, Han Hui, Zhao Pengfei, Zhang Datong

Abstract:

With the development of carbon capture and storage (CCS), the flow assurance of CO2 transportation becomes more important, particularly for supercritical CO2 pipelines. The relieving system using the choke valve is applied to control the pressure in CO2 pipeline. However, the temperature of fluid would drop rapidly because of Joule-Thomson cooling (JTC), which may cause solid CO2 form and block the pipe. In this paper, a Computational Fluid Dynamic (CFD) model, using the modified Lagrangian method, Reynold's Stress Transport model (RSM) for turbulence and stochastic tracking model (STM) for particle trajectory, was developed to predict the deposition characteristic of solid carbon dioxide. The model predictions were in good agreement with the experiment data published in the literature. It can be observed that the particle distribution affected the deposition behavior. In the region of the sudden expansion, the smaller particles accumulated tightly on the wall were dominant for pipe blockage. On the contrary, the size of solid CO2 particles deposited near the outlet usually was bigger and the stacked structure was looser. According to the calculation results, the movement of the particles can be regarded as the main four types: turbulent motion close to the sudden expansion structure, balanced motion at sudden expansion-middle region, inertial motion near the outlet and the escape. Furthermore the particle deposits accumulated primarily in the sudden expansion region, reattachment region and outlet region because of the four type of motion. Also the Stokes number had an effect on the deposition ratio and it is recommended for Stokes number to avoid 3-8St.

Keywords: carbon capture and storage, carbon dioxide pipeline, gas-particle flow, deposition

Procedia PDF Downloads 353