Search results for: performance prism model

Authors: Avatharam Ganivada, Krishna Shah

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The Mask R-CNN is recently introduced by the team of Facebook AI Research (FAIR), which is mainly concerned with instance segmentation in images. Here, the Mask R-CNN is based on ResNet and feature pyramid network (FPN), where a single dropout method is employed. This paper provides a modified Mask R-CNN by adding multiple dropout methods into the Mask R-CNN. The proposed model has also utilized the concepts of Resnet and FPN to extract stage-wise network feature maps, wherein a top-down network path having lateral connections is used to obtain semantically strong features. The proposed model produces three outputs for each object in the image: class label, bounding box coordinates, and object mask. The performance of the proposed network is evaluated in the segmentation of every instance in images using COCO and cityscape datasets. The proposed model achieves better performance than the state-of-the-networks for the datasets.

Keywords: instance segmentation, object detection, convolutional neural networks, deep learning, computer vision

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Authors: Enyia James Diwa, Dodeye Ina Igbong, Archibong Eso Archibong

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The creep life of an industrial gas turbine is determined through a physics-based model used to investigate the high pressure temperature (HPT) of the blade in use. A performance model was carried out via the Cranfield University TURBOMATCH simulation software to size the blade and to determine the corresponding stress. Various effects such as radial temperature distortion factor, turbine entry temperature, ambient temperature, blade metal temperature, and compressor degradation on the blade creep life were investigated. The output results show the difference in creep life and the location of failure along the span of the blade enabling better-informed advice for the gas turbine operator.

Keywords: creep, living, performance, degradation

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Authors: Emmanuel Osaze Oshoiribhor, Adetokunbo MacGregor John-Otumu

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There has been a need in recent years to predict student academic achievement prior to graduation. This is to assist them in improving their grades, especially for those who have struggled in the past. The purpose of this research is to use supervised learning techniques to create a model that predicts student academic progress. Many scholars have developed models that predict student academic achievement based on characteristics including smoking, demography, culture, social media, parent educational background, parent finances, and family background, to mention a few. This element, as well as the model used, could have misclassified the kids in terms of their academic achievement. As a prerequisite to predicting if the student will perform well in the future on related courses, this model is built using a logistic regression classifier with basic features such as the previous semester's course score, attendance to class, class participation, and the total number of course materials or resources the student is able to cover per semester. With a 96.7 percent accuracy, the model outperformed other classifiers such as Naive bayes, Support vector machine (SVM), Decision Tree, Random forest, and Adaboost. This model is offered as a desktop application with user-friendly interfaces for forecasting student academic progress for both teachers and students. As a result, both students and professors are encouraged to use this technique to predict outcomes better.

Keywords: artificial intelligence, ML, logistic regression, performance, prediction

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Authors: Cheng-Hao Jiang, Mu-Xuan Tao

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The rigid diaphragm model may cause errors in the calculation of internal forces due to neglecting the in-plane deformation of the diaphragm. This paper thus studies the effects of different diaphragm in-plane models (including in-plane rigid model and in-plane flexible model) on the seismic performance of structures. Taking an actual industrial plant as an example, the seismic performance of the structure is predicted using different floor diaphragm models, and the analysis errors caused by different diaphragm in-plane models including deformation error and internal force error are calculated. Furthermore, the influence of the aspect ratio on the analysis errors is investigated. Finally, the code rationality is evaluated by assessing the analysis errors of the structure models whose floors were determined as rigid according to the code’s criterion. It is found that different floor models may cause great differences in the distribution of structural internal forces, and the current code may underestimate the influence of the floor in-plane effect.

Keywords: industrial plant, diaphragm, calculating error, code rationality

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Authors: Entisar A. Elgmati

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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

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Authors: Sasiwimol Auepong, Raywat Tanadkithirun

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In this work, the problem that squirrels ruin durian, which is an economical fruit in Thailand, is considered. We seek the strategy for the durian farmers to eliminate the squirrels under the consideration that squirrels also provide ecosystem service. The population dynamics of squirrels are constructed to have carrying capacity since we consider the population in a confined area. A performance index indicating the total benefit of a given elimination strategy is provided. It comprises the cost of countermeasures, the loss of resources, and the ecosystem service provided by squirrels. The optimal performance index is numerically solved through the variational inequality using the finite difference method. The optimal strategy to control the squirrel population is also given numerically.

Keywords: controlled stochastic differential equation, durian, finite difference method, performance index, singular stochastic control model, squirrel

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Authors: David Tena-Gago, Jose M. Alcaraz Calero, Qi Wang

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The evolution and integration of automated vehicles have become more and more tangible in recent years. State-of-the-art technological advances in the field of camera-based Artificial Intelligence (AI) and computer vision greatly favor the performance and reliability of the Advanced Driver Assistance System (ADAS), leading to a greater knowledge of vehicular operation and resembling human behavior. However, the exclusive use of this technology still seems insufficient to control vehicular operation at 100%. To reveal the degree of accuracy of the current camera-based automated driving AI modules, this paper studies the structure and behavior of one of the main solutions in a controlled testing environment. The results obtained clearly outline the lack of reliability when using exclusively the AI model in the perception stage, thereby entailing using additional complementary sensors to improve its safety and performance.

Keywords: accuracy assessment, AI-driven mobility, artificial intelligence, automated vehicles

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Authors: Ehsan Mehryaar

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The rate of penetration is (RoP) one of the vital factors in the cost and time of tunnel boring projects; therefore, predicting it can lead to a substantial increase in the efficiency of the project. RoP is heavily dependent geological properties of the project site and TBM properties. In this study, 151-point data from Queen’s water tunnel is collected, which includes unconfined compression strength, peak slope index, angle with weak planes, and distance between planes of weaknesses. Since the size of the data is small, it was observed that it is imbalanced. To solve that problem synthetic minority oversampling technique is utilized. The model based on the model tree is proposed, where each leaf consists of a support vector machine model. Proposed model performance is then compared to existing empirical equations in the literature.

Keywords: Model tree, SMOTE, rate of penetration, TBM(tunnel boring machine), SVM

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Authors: Belkheir Noura, Rabah Kerfah, Boumehani Abdellah

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The influence of solidity variations on the aerodynamic performance of H type vertical axis wind turbine is studied in this paper. The wind turbine model used in this paper is the three-blade wind turbine with the symmetrical airfoil, NACA0021. The length of the chord is 0.265m. Numerical investigations were implemented for the different solidity by changing the radius and blade number. A two-dimensional model of the wind turbine is employed. The approach a Reynolds-Averaged Navier–Stokes equations, completed by the K- ώ SST turbulence model, is used. Motion mesh model capability of a computational fluid dynamics (CFD) solver is used. For each value of the solidity, the aerodynamics performances and the characteristics of the flow field are studied at several values of the tip speed ratio, λ = 0.5 to λ = 3, with an incoming wind speed of 8 m/s. The results show that increasing the number of blades will reduce the maximum value of the power coefficient of the wind turbine. Also, for the VAWT with a lower solidity can obtain the maximum Cp at a high tip speed ratio. The effects of changing the radius and blade number on aerodynamic performance are almost the same. Finally, for the validation, experimental data from the literature and computational results were compared. In conclusion, to study the influence of the solidity in the performances of the wind turbine is to provide the reference for the design of H type vertical axis wind turbines.

Keywords: wind energy, darrieus h type vertical axis wind turbine, computational fluid dynamic, solidity

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Authors: Atiqa Marium

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In 2015, all 193 UN Member countries adopted the 2030 Agenda for Sustainable Development, which is an ambitious 15- year plan to address some of the most pressing issues the world faces. Goal 4 is about Quality Education which highlights the importance of inclusive and quality education for sustainable development. Sustainable Development Goal 10 focuses on reducing inequalities within and among countries. In June 2019, Federal Government in Canada released “Towards Canada’s 2030 Agenda National Strategy”, which was an important step to move the 2030 Agenda forward. In April 2019, the Ontario government announced the performance-based funding model for publically assisted colleges and universities in Ontario, which is now part of the universities’ budget 2024-2025. The literature review has shown that the funding model has been implemented by different governments to achieve objectives. However, this model has also resulted in conflicting consequences like reducing university autonomy, education quality/ academic standards, and increased equity concerns. The primary focus of this paper will be to analyze the tensions and coherence between the proposed funding model for education for sustainable development goals and targets set by Canada’s 2030 Agenda National Strategy. Considering that the literature review has provided evidence that the performance-based funding model has resulted in reducing quality of education and increased equity issues in other countries, it will be interesting to see how this proposed funding will align with the SDGs of “Quality Education” and “Reduced Inequalities”. This paper will be well-suited for Volume 4, with the theme of re-visioning institutional impact and sustainability. This paper will underscore the importance of policy coherence between federal and provincial policies for higher education institutions in Ontario for better institutional impact and helping universities in the attainment of goals set in 2030 Agenda towards education for sustainable development.

Keywords: performance-based funding model, education for sustainable development, policy coherence, sustainable development gaols

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Authors: Mohamed Gar Alalm

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This study aims to investigate various operating conditions that affect the performance of the electro-Fenton process for degradation of pesticides. Stainless steel electrodes were utilized in the electro-Fenton cell due to their relatively low cost. The favored conditions of current intensity, pH, iron loading, and pesticide concentration were deeply discussed. Complete removal of pesticide was attained at the optimum conditions. The degradation kinetics were described by pseudo- first-order pattern. In addition, a response surface model was developed to describe the performance of electro-Fenton process under different operational conditions. The model indicated that the coefficient of determination was (R² = 0.995).

Keywords: electro-Fenton, stainless steel, pesticide, wastewater

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Authors: Yi-Guang Li, Suresh Sampath

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Gas turbine performance degrades over time, and the degradation is greatly affected by environmental, ambient, and operating conditions. The engines may degrade slowly under favorable conditions and result in a waste of engine life if a scheduled maintenance scheme is followed. They may also degrade fast and fail before a scheduled overhaul if the conditions are unfavorable, resulting in serious secondary damage, loss of engine availability, and increased maintenance costs. To overcome these problems, gas turbine owners are gradually moving from scheduled maintenance to condition-based maintenance, where condition monitoring is one of the key supporting technologies. This paper presents an integrated adaptive GPA diagnostics and performance monitoring system developed at Cranfield University for gas turbine gas path condition monitoring. It has the capability to predict the performance degradation of major gas path components of gas turbine engines, such as compressors, combustors, and turbines, using gas path measurement data. It is also able to predict engine key performance parameters for condition monitoring, such as turbine entry temperature that cannot be directly measured. The developed technology has been implemented into digital twin computer Software, Pythia, to support the condition monitoring of gas turbine engines. The capabilities of the integrated GPA condition monitoring system are demonstrated in three test cases using a model gas turbine engine similar to the GE aero-derivative LM2500 engine widely used in power generation and marine propulsion. It shows that when the compressor of the model engine degrades, the Adaptive GPA is able to predict the degradation and the changing engine performance accurately using gas path measurements. Such a presented technology and software are generic, can be applied to different types of gas turbine engines, and provide crucial engine health and performance parameters to support condition monitoring and condition-based maintenance.

Keywords: gas turbine, adaptive GPA, performance, diagnostics, condition monitoring

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Authors: Praveena Sinha

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Context: Diabetes is a global public health burden, particularly affecting postmenopausal women. Insulin resistance (IR) is prevalent in this population, and it is associated with an increased risk of developing type 2 diabetes. Yoga therapy is gaining attention as a complementary intervention for diabetes due to its potential to address stress psychophysiology. This study focuses on the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Research Aim: The aim of this research is to investigate the effect of a 3-month long yoga practice on insulin resistance in early postmenopausal women. Methodology: The study conducted a prospective longitudinal design with 67 women within five years of menopause. Participants were divided into two groups based on their willingness to join yoga. The Yoga group (n = 37) received routine gynecological management along with an integrated yoga module, while the Non-Yoga group (n = 30) received only routine management. Insulin resistance was measured using the homeostasis model assessment of insulin resistance (HOMA-IR) method before and after the intervention. Statistical analysis was performed using GraphPad Prism Version 5 software, with statistical significance set at P < 0.05. Findings: The results indicate a significant decrease in serum fasting insulin levels and HOMA-IR measurements in the Yoga group, although the decrease did not reach statistical significance. In contrast, the Non-Yoga group showed a significant rise in serum fasting insulin levels and HOMA-IR measurements after 3 months, suggesting a detrimental effect on insulin resistance in these postmenopausal women. Theoretical Importance: This study provides evidence that a 12-week yoga practice can attenuate the increase in insulin resistance in early postmenopausal women. It highlights the potential of yoga as a preventive measure against the early onset of insulin resistance and the development of type 2 diabetes mellitus. Regular yoga practice can be a valuable tool in addressing hormonal imbalances associated with early postmenopause, leading to a decrease in morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in this population. Data Collection and Analysis Procedures: Data collection involved measuring serum fasting insulin levels and calculating HOMA-IR. Statistical analysis was performed using GraphPad Prism Version 5 software, and mean values with standard error of the mean were reported. The significance level was set at P < 0.05. Question Addressed: The study aimed to address whether a 3-month long yoga practice could attenuate insulin resistance in early postmenopausal women. Conclusion: The research findings support the efficacy of a 12-week yoga practice in attenuating insulin resistance in early postmenopausal women. Regular yoga practice has the potential to prevent the early onset of insulin resistance and the development of type 2 diabetes mellitus in this population. By addressing the hormonal imbalances associated with early post menopause, yoga could significantly decrease morbidity and mortality related to insulin resistance and type 2 diabetes mellitus in these subjects.

Keywords: post menopause, insulin resistance, HOMA-IR, yoga, type 2 diabetes mellitus

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Authors: Gulshan Sachdeva, Vaibhav Jain, S. S. Kachhwaha

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Cascade refrigeration systems employ series of single stage vapor compression units which are thermally coupled with evaporator/condenser cascades. Different refrigerants are used in each of the circuit depending on the optimum characteristics shown by the refrigerant for a particular application. In the present research study, a steady state thermodynamic model is developed which simulates the working of an actual cascade system. The model provides COP and all other system parameters like total compressor work, temperature, pressure, enthalpy and entropy at different state points. The working fluid in Low Temperature Circuit (LTC) is CO2 (R744) while ammonia (R717), propane (R290), propylene (R1270), R404A and R12 are the refrigerants in High Temperature Circuit (HTC). The performance curves of ammonia, propane, propylene, and R404A are compared with R12 to find its nearest substitute. Results show that ammonia is the best substitute of R12.

Keywords: cascade system, refrigerants, thermodynamic model, production engineering

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Authors: Luciana Abednego, Cecilia Nugraheni

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There are many approaches proposed for solving Sudoku puzzles. One of them is by modelling the puzzles as block world problems. There have been three model for Sudoku solvers based on this approach. Each model expresses Sudoku solver as a parameterized multi agent systems. In this work, we propose a new model which is an improvement over the existing models. This paper presents the development of a Sudoku solver that implements all the proposed models. Some experiments have been conducted to determine the performance of each model.

Keywords: Sudoku puzzle, Sudoku solver, block world problem, parameterized multi agent systems

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Authors: Duvert A. Puentes T., Javier A. Maldonado E., Ivan Quintero., Diego F. Villegas

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Mechanical Computation is a great tool to study the performance of complex models. An example of it is the study of the human body structure. This paper took advantage of different types of software to make a 3D model of the glenohumeral joint and apply a finite element analysis. The main objective was to study the change in the biomechanical properties of the joint when it presents an injury. Specifically, a BANKART lesion, which consists in the detachment of the anteroinferior labrum from the glenoid. Stress and strain distribution of the soft tissues were the focus of this study. First, a 3D model was made of a joint without any pathology, as a control sample, using segmentation software for the bones with the support of medical imagery and a cadaveric model to represent the soft tissue. The joint was built to simulate a compression and external rotation test using CAD to prepare the model in the adequate position. When the healthy model was finished, it was submitted to a finite element analysis and the results were validated with experimental model data. With the validated model, it was sensitized to obtain the best mesh measurement. Finally, the geometry of the 3D model was changed to imitate a BANKART lesion. Then, the contact zone of the glenoid with the labrum was slightly separated simulating a tissue detachment. With this new geometry, the finite element analysis was applied again, and the results were compared with the control sample created initially. With the data gathered, this study can be used to improve understanding of the labrum tears. Nevertheless, it is important to remember that the computational analysis are approximations and the initial data was taken from an in vitro assay.

Keywords: biomechanics, computational model, finite elements, glenohumeral joint, bankart lesion, labrum

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Solomon Weldegebriel Gebrelibanos

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Water is one of the most important substances in human life that can give a human liberality with its cost and availability. Water comes from rainfall and runoff and reaches the ground as runoff that is stored in a river, ponds, and big water bodies, including sea and ocean and the remaining water portion is infiltrated into the ground to store in the aquifer. Water can serve human beings in various ways, including irrigation, water supply, hydropower and soon. Water supply is the main pillar of the water service to the human being. Water supply distribution in Addis Ababa arises from Legedadi, Akakai, and Gefersa. The objective of the study is to measure the performance of the water supply distribution in Addis Ababa city. The water supply distribution model is developed by computer-aided design software. The model can analyze the operational change, loss of water, and performance of the network. The two design criteria that have been employed to analyze the network system are velocity and pressure. The result shows that the customers are using the water at high pressure with low demand. The water distribution system is older than the expected service life with more leakage. Hence the study recommended that fixing Pressure valves and new distribution facilities can resolve the performance of the water supply system

Keywords: distribution, model, pressure, velocity

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Authors: Dahmani Aziz, Mekdad Yousra

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The intellectual capital is an important source of profitability and the main supporter of the competitive where this study examines the contribution of expenditure on intellectual capital in the performance of industrial enterprises Algerian, and through a case study Sonatrach as the most important industrial enterprises in Algeria and the driving force of the Algerian economy. It has been the use of value-added intellectual coefficient (VAIC) in measuring the contribution of intellectual capital and analyzing data Sonatrach during the period from the year 2001 until the year 2012, and test the validity of hypotheses using Stepwise Regression model through the SPSS statistical software, and the study has proved the existence of a positive relationship between spending on human capital and financial performance and a stronger degree relationship between the structural capital and economic performance.

Keywords: industrial enterprise, intellectual capital, performance, economy of Algeria, spending

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Authors: Binoy Chandra Sarma, S. K. Deb

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Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study. Over 85% of industrial dryers are of the convective type with hot air or direct flue gases as the drying medium. Over 99% of the applications involve removal of water. In this study, the performance of a solar air heater with the recovery of the absorbed heat by the metallic concentrator sheet itself besides the normal heat accumulated by the receiver at the focus of the concentrator for generating drying air by convection at a low to medium temperature range is discussed. The system performance through thermal analysis & the performance of a model achieving the required temperature range is also investigate in this study.

Keywords: dryer, polygeneration, moisture, equilibrium, humidity

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Authors: Gleb Fomin, Kairat Tabynov, Nurkeldy Turebekov, Dinara Turegeldiyeva, Rinat Islamov

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The level of major cytokines in the blood of patients with COVID-19 varies greatly depending on age, gender, duration and severity of infection, and comorbidity. There are two clinically significant cytokines, IL-6 and TNF-α, which increase in levels in patients with severe COVID-19. However, in a model of COVID-19 in hamsters, TNF-α levels are unchanged or reduced, while the expression of other cytokines reflects the profile of cytokines found in patients’ plasma. The aim of our study was to evaluate the relationship between the level of cytokines in the blood, lungs, and lung damage in the model of the Syrian hamster (Mesocricetus auratus) infected with the SARS-CoV-2 strain. The study used outbred female and male Syrian hamsters (n=36, 4 groups) weighing 80-110 g and 5 months old (protocol IACUC, #4, 09/22/2020). Animals were infected intranasally with the hCoV-19/Kazakhstan/KazNAU-NSCEDI-481/2020 strain and euthanized at 3 d.p.i. The level of cytokines IL-6, TNF-α, IFN-α, and IFN-γ was determined by ELISA MyBioSourse (USA) for hamsters. Lung samples were subjected to histological processing. The presence of pathological changes in histological preparations was assessed on a 3-point scale. The work was carried out in the ABSL-3 laboratory. The data were analyzed in GraphPad Prism 6.00 (GraphPad Software, La Jolla, California, USA). The work was supported by the MES RK grant (AP09259865). In the blood, the level of TNF-α increased in males (p=0.0012) and IFN-γ in males and females (p=0.0001). On the contrary, IFN-α production decreased (p=0.0006). Only TNF-α level increased in lung tissues (p=0.0011). Correlation analysis showed a negative relationship between the level of IL-6 in the blood and lung damage in males (r -0.71, p=0.0001) and females (r-0.57, p=0.025). On the contrary, in males, the level of IL-6 in the lungs and score is positively correlated (r 0.80, p=0.01). The level of IFN-γ in the blood (r -0.64, p=0.035) and lungs (r-0.72, p=0.017) in males has a negative correlation with lung damage. No links were found for TNF-α and IFN-α. The study showed a positive association between lung injury and tissue levels of IL-6 in male hamsters. It is known that in humans, high concentrations of IL-6 in the lungs are associated with suppression of cellular immunity and, as a result, with an increase in the severity of COVID-19. TNF-α and IFN-γ play a key role in the pathogenesis of COVID-19 in hamsters. However, the mechanisms of their activity require more detailed study. IFN-α plays a lesser role in direct lung injury in a Syrian hamster model. We have shown the significance of tissue IL-6 and IFN-γ as predictors of the severity of lung damage in COVID-19 in the Syrian hamster model. Changes in the level of cytokines in the blood may not always reflect pathological processes in the lungs with COVID-19.

Keywords: syrian hamster, COVID-19, cytokines, biological model

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Authors: Alshehri Sultan

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Organizational change has remained an important subject for many researchers in the field of organizations theory. We propose the importance of organizational liability of renewal through a model that examines how an organization can overcome potential rigidities in organizational capabilities from learning by changing capabilities. We examine whether an established organization can overcome liability of renewal by changes in organizational capabilities and how the organizational renewal process reflect on the balance between the dynamic aspect of organizational learning as demonstrated by changes in capabilities and the stabilizing aspects of organizational inertia. We found both positive relationship between organizational learning and performance, and between legitimacy and performance. Performance and legitimacy have, however, a negative relationship on the pressure for change.

Keywords: organizational capabilities, organizational liability, liability of renewal, pressure for change

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Authors: Zhidong Zhang

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This study established a mixed method model in assessing statistics learning with Bayesian network models. There are three variants in exploratory sequential designs. There are three linked steps in one of the designs: qualitative data collection and analysis, quantitative measure, instrument, intervention, and quantitative data collection analysis. The study used a scoring model of analysis of variance (ANOVA) as a content domain. The research study is to examine students’ learning in both semantic and performance aspects at fine grain level. The ANOVA score model, y = α+ βx1 + γx1+ ε, as a cognitive task to collect data during the student learning process. When the learning processes were decomposed into multiple steps in both semantic and performance aspects, a hierarchical Bayesian network was established. This is a theory-driven process. The hierarchical structure was gained based on qualitative cognitive analysis. The data from students’ ANOVA score model learning was used to give evidence to the hierarchical Bayesian network model from the evidential variables. Finally, the assessment results of students’ ANOVA score model learning were reported. Briefly, this was a mixed method research design applied to statistics learning assessment. The mixed methods designs expanded more possibilities for researchers to establish advanced quantitative models initially with a theory-driven qualitative mode.

Keywords: exploratory sequential design, ANOVA score model, Bayesian network model, mixed methods research design, cognitive analysis

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Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

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This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

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Authors: Hao-Hsi Tseng, Hsin-Yun Lee

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In the process of building design, the designers have to complete the spatial design and consider the evacuation performance at the same time. It is usually difficult to combine the two planning processes and it results in the gap between spatial design and evacuation performance. Then the designers cannot complete an integrated optimal design solution. In addition, the evacuation routing models proposed by previous researchers is different from the practical evacuation decisions in the real field. On the other hand, more and more building design projects are executed by Building Information Modeling (BIM) in which the design content is formed by the object-oriented framework. Thus, the integration of BIM and evacuation simulation can make a significant contribution for designers. Therefore, this research plan will establish a model that integrates spatial design and evacuation planning. The proposed model will provide the support for the spatial design modifications and optimize the evacuation planning. The designers can complete the integrated design solution in BIM. Besides, this research plan improves the evacuation routing method to make the simulation results more practical. The proposed model will be applied in a building design project for evaluation and validation when it will provide the near-optimal design suggestion. By applying the proposed model, the integration and efficiency of the design process are improved and the evacuation plan is more useful. The quality of building spatial design will be better.

Keywords: building information modeling, evacuation, design, floor plan

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Authors: Bin Wang, Hengyu Ji, Zhifeng Ye

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Fuel Metering Unit (FMU) in fuel system of an aeroengine sometimes has direct influence on the engine performance, which is neglected for the sake of easy access to mathematical model of the engine in most cases. In order to verify the influence of FMU on an engine model, this paper presents a co-simulation of a stepping motor driven FMU (digital FMU) in a turboshaft aeroengine, using AMESim and MATLAB to obtain the steady and dynamic characteristics of the FMU. For this method, mechanical and hydraulic section of the unit is modeled through AMESim, while the stepping motor is mathematically modeled through MATLAB/Simulink. Combining these two sub-models yields an AMESim/MATLAB co-model of the FMU. A simplified component level model for the turboshaft engine is established and connected with the FMU model. Simulation results on the full model show that the engine model considering FMU characteristics describes the engine more precisely especially in its transition state. An FMU dynamics will cut down the rotation speed of the high pressure shaft and the inlet pressure of the combustor during the step response. The work in this paper reveals the impact of FMU on engine operation characteristics and provides a reference to an engine model for ground tests.

Keywords: fuel metering unit, stepping motor, AMESim/Matlab, full digital simulation

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Authors: Fally Titikpina, Abderafi Charki, Antoine Caucheteux, David Bigaud

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The building sector is one of the largest energy consumer with about 40% of the final energy consumption in the European Union. Ensuring building energy performance is of scientific, technological and sociological matter. To assess a building energy performance, the consumption being predicted or estimated during the design stage is compared with the measured consumption when the building is operational. When valuing this performance, many buildings show significant differences between the calculated and measured consumption. In order to assess the performance accurately and ensure the thermal efficiency of the building, it is necessary to evaluate the uncertainties involved not only in measurement but also those induced by the propagation of dynamic and static input data in the model being used. The evaluation of measurement uncertainty is based on both the knowledge about the measurement process and the input quantities which influence the result of measurement. Measurement uncertainty can be evaluated within the framework of conventional statistics presented in the \textit{Guide to the Expression of Measurement Uncertainty (GUM)} as well as by Bayesian Statistical Theory (BST). Another choice is the use of numerical methods like Monte Carlo Simulation (MCS). In this paper, we proposed to evaluate the uncertainty associated to the use of a simplified model for the estimation of the energy consumption of a given building. A detailed review and discussion of these three approaches (GUM, MCS and BST) is given. Therefore, an office building has been monitored and multiple sensors have been mounted on candidate locations to get required data. The monitored zone is composed of six offices and has an overall surface of 102 $m^2$. Temperature data, electrical and heating consumption, windows opening and occupancy rate are the features for our research work.

Keywords: building energy performance, uncertainty evaluation, GUM, bayesian approach, monte carlo method

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Authors: Chae Hoon Park, Jong Kang Park, Jong Tae Kim

Abstract:

Electrical characteristics of capacitive touchscreen need to be accurately analyzed to result in better performance for multi-channel capacitance sensing. In this paper, we extracted the panel resistances and capacitances of the touchscreen by comparing measurement data and model data. By employing a lumped RC model for driver-to-receiver paths in touchscreen, we estimated resistance and capacitance values according to the physical lengths of channel paths which are proportional to the RC model. As a result, we obtained the model having 95.54% accuracy of the measurement data.

Keywords: electrical characteristics of capacitive touchscreen, iterative extraction, lumped RC model, physical lengths of channel paths

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Authors: Vikram Saini, Lillie Dewan

Abstract:

This paper presents the iterative schemes based on Least square, Hierarchical Least Square and Stochastic Approximation Gradient method for the Identification of Wiener model with parametric structure. A gradient method is presented for the parameter estimation of wiener model with noise conditions based on the stochastic approximation. Simulation results are presented for the Wiener model structure with different static non-linear elements in the presence of colored noise to show the comparative analysis of the iterative methods. The stochastic gradient method shows improvement in the estimation performance and provides fast convergence of the parameters estimates.

Keywords: hard non-linearity, least square, parameter estimation, stochastic approximation gradient, Wiener model

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Authors: Zouhair Issa Ahmed, Ahmed Abdulrasool Ahmed, Falah Hassan Abdulsada

Abstract:

This paper presents a layout of a factory using Pro-Model simulation by choosing the best layout that gives the highest productivity and least work in process. The general problem is to find the best sequence in which jobs pass between the machines which are compatible with the technological constraints and optimal with respect to some performance criteria. The best simulation with Pro-Model program increased productivity and reduced work in process by balancing lines of production compared with the current layout of factory when productivity increased from 45 products to 180 products through 720 hours.

Keywords: scheduling, Pro-Model, simulation, balancing lines of production, layout planning, WIP

Procedia PDF Downloads 609