Search results for: scientific models

Authors: Sevde Altuntas, Fatih Buyukserin

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Alzheimer’s disease is responsible for irreversible neural damage of brain parts. One of the disease markers is Amyloid-β 1-42 protein that accumulates in the brain in the form plaques. The basic problem for detection of the protein is the low amount of protein that cannot be detected properly in body liquids such as blood, saliva or urine. To solve this problem, tests like ELISA or PCR are proposed which are expensive, require specialized personnel and can contain complex protocols. Therefore, Surface-enhanced Raman Spectroscopy (SERS) a good candidate for detection of Amyloid-β 1-42 protein. Because the spectroscopic technique can potentially allow even single molecule detection from liquid and solid surfaces. Besides SERS signal can be improved by using nanopattern surface and also is specific to molecules. In this context, our study proposes to fabricate diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin - T to detect low concentrations of Amyloid-β 1-42 protein in water and artificial saliva medium by the enhancement of protein SERS signal. The nanopatterned PC surface that was used to enhance SERS signal was fabricated by using Anodic Alumina Membranes (AAM) as a template. It is possible to produce AAMs with different column structures and varying thicknesses depending on voltage and anodization time. After fabrication process, the pore diameter of AAMs can be arranged with dilute acid solution treatment. In this study, two different columns structures were prepared. After a surface modification to decrease their surface energy, AAMs were treated with PC solution. Following the solvent evaporation, nanopatterned PC films with tunable pillared structures were peeled off from the membrane surface. The PC film was then modified with Au and Thioflavin-T for the detection of Amyloid-β 1-42 protein. The protein detection studies were conducted first in water via this biosensor platform. Same measurements were conducted in artificial saliva to detect the presence of Amyloid Amyloid-β 1-42 protein. SEM, SERS and contact angle measurements were carried out for the characterization of different surfaces and further demonstration of the protein attachment. SERS enhancement factor calculations were also completed via experimental results. As a result, our research group fabricated diagnostic test models that utilize Au-coated nanopatterned polycarbonate (PC) surfaces modified with Thioflavin-T to detect low concentrations of Alzheimer’s Amiloid – β protein in water and artificial saliva medium. This work was supported by The Scientific and Technological Research Council of Turkey (TUBITAK) Grant No: 214Z167.

Keywords: alzheimer, anodic aluminum oxide, nanotopography, surface enhanced Raman spectroscopy

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Authors: Olga Colbert

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The present work examines the representation of dreaming in Charles Dickens’ novels, particularly Oliver Twist. Dickens showed great interest in the science of dreaming and had ample knowledge of the latest dream theories in the Victorian era, as can be seen in his personal correspondence, most notably in his famous letter to Dr. Thomas Stone on 2/2/1851. This essay places Dickens’ personal writings side by side with his novels to elucidate whether the scientific paradigm about dreaming included in the novel is consistent with the current (in Dickens’ time) scientific knowledge, or whether it is anachronistic or visionary (ahead of his time). Oliver Twist is particularly useful because it contains entire passages pondering on the nature of dreaming, enumerating types of common dreams, and taking a stand on the interference of sensory perception during the dreaming state. The author is particularly intrigued by Dickens’ assumption of the commonality and universality of lucid dreaming as revealed in these passages. This essay places popular Victorian dream theories, such as those contained in Robert Macnish’s The Philosophy of Sleep, side by side with recent dream theory, particularly psychophysiologist Stephen LaBerge’s numerous articles and books on the topic of lucid dreaming to see if Dickens deviated in any way from the reigning paradigm of the Victorian era in his representation of dreaming in his novels. While Dickens puts to great narrative use many of the characteristics of dreaming described by leading Victorian theorists, the author of this study argues, however, that Dickens’ most visionary statements derive from his acute observations of his own dreaming experiences.

Keywords: consciousness, Dickens, dreaming, lucid dreaming, Victorian

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Authors: Li Chen

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For an aerofoil or hydrofoil in high Reynolds number flows, broadband noise is generated efficiently as the result of the turbulence convecting over the trailing edge. This noise can be related to the surface pressure fluctuations, which can be predicted by either CFD or empirical models. However, in reality, the aerofoil or hydrofoil often operates at an angle of attack. Under this situation, the flow is subjected to an Adverse-Pressure-Gradient (APG), and as a result, a flow separation may occur. This study is to assess trailing-edge noise models for such flows. In the present work, the trailing-edge noise from a 2D airfoil at 6 degree of angle of attach is investigated. Under this condition, the flow is experiencing a strong APG, and the flow separation occurs. The flow over the airfoil with a chord of 300 mm, equivalent to a Reynold Number 4x10⁵, is simulated using RANS with the SST k-ɛ turbulent model. The predicted surface pressure fluctuations are compared with the published experimental data and empirical models, and show a good agreement with the experimental data. The effect of the APG on the trailing edge noise is discussed, and the associated trailing edge noise is calculated.

Keywords: aero-acoustics, adverse-pressure gradient, computational fluid dynamics, trailing-edge noise

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Authors: Samir K. Safi

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The purpose of this study was to compare the performance of two types of models, namely MIDAS and MIDAS-GARCH, in predicting the volatility of crude oil returns based on gold price returns and the COVID-19 pandemic. The study aimed to identify which model would provide more accurate short-term and long-term predictions and which model would perform better in handling the increased volatility caused by the pandemic. The findings of the study revealed that the MIDAS model performed better in predicting short-term and long-term volatility before the pandemic, while the MIDAS-GARCH model performed significantly better in handling the increased volatility caused by the pandemic. The study highlights the importance of selecting appropriate models to handle the complexities of real-world data and shows that the choice of model can significantly impact the accuracy of predictions. The practical implications of model selection and exploring potential methodological adjustments for future research will be highlighted and discussed.

Keywords: GARCH-MIDAS, MIDAS, crude oil, gold, COVID-19, volatility

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Authors: Maria Inês Pinho

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Recent literature on issues of Cultural Management (also called Strategic Management for cultural organizations) systematically seeks for models that allow such equipment to adapt to the constant change that occurs in contemporary societies. In the last decade, the world, and in particular Europe has experienced a serious financial problem that has triggered defensive mechanisms, both in the direction of promoting the balance of public accounts and in the sense of the anonymous loss of the democratic and cultural values of each nation. If in the first case emerged the Troika that led to strong cuts in funding for Culture, deeply affecting those organizations; in the second case, the commonplace citizen is seen fighting for the non-closure of cultural equipment. Despite this, the cultural manager argues that there is no single formula capable of solving the need to adapt to change. In another way, it is up to this agent to know the existing scientific models and to adapt them in the best way to the reality of the institution he coordinates. These actions, as a rule, are concerned with the best performance vis-à-vis external audiences or with the financial sustainability of cultural organizations. They forget, therefore, that all this mechanics cannot function without its internal public, without its Human Resources. The employees of the cultural organization must then have an entrepreneurial posture - must be intrapreneurial. This paper intends to break this form of action and lead the cultural manager to understand that his role should be in the sense of creating value for society, through a good organizational performance. This is only possible with a posture of strategic entrepreneurship. In other words, with a link between: Cultural Management, Cultural Entrepreneurship and Cultural Intrapreneurship. In order to prove this assumption, the case study methodology was used with the symbol of the European Capital of Culture (Casa da Música) as well as qualitative and quantitative techniques. The qualitative techniques included the procedure of in-depth interviews to managers, founders and patrons and focus groups to public with and without experience in managing cultural facilities. The quantitative techniques involved the application of a questionnaire to middle management and employees of Casa da Música. After the triangulation of the data, it was proved that contemporary management of cultural organizations must implement among its practices, the concept of Strategic Entrepreneurship and its variables. Also, the topics which characterize the Cultural Intrapreneurship notion (job satisfaction, the quality in organizational performance, the leadership and the employee engagement and autonomy) emerged. The findings show then that to be sustainable, a cultural organization should meet the concerns of both external and internal forum. In other words, it should have an attitude of citizenship to the communities, visible on a social responsibility and a participatory management, only possible with the implementation of the concept of Strategic Entrepreneurship and its variable of Cultural Intrapreneurship.

Keywords: cultural entrepreneurship, cultural intrapreneurship, cultural organizations, strategic management

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Authors: Jérémy Philippe, Lucien Baldas, Batoul Attar, Jean-Charles Mare

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The proposed communication deals with the research and development of a rotary direct-drive servo valve for aerospace applications. A key challenge of the project is to downsize the electromagnetic torque motor by reducing the torque required to drive the rotary spool. It is intended to optimize the spool and the sleeve geometries by combining a Computational Fluid Dynamics (CFD) approach with commercial optimization software. The present communication addresses an important phase of the project, which consists firstly of gaining confidence in the simulation results. It is well known that the force needed to pilot a sliding spool valve comes from several physical effects: hydraulic forces, friction and inertia/mass of the moving assembly. Among them, the flow force is usually a major contributor to the steady-state (or Root Mean Square) driving torque. In recent decades, CFD has gradually become a standard simulation tool for studying fluid-structure interactions. However, in the particular case of high-pressure valve design, the authors have experienced that the calculated overall hydraulic force depends on the parameterization and options used to build and run the CFD model. To solve this issue, the authors have selected the standard case of the linear spool valve, which is addressed in detail in numerous scientific references (analytical models, experiments, CFD simulations). The first CFD simulations run by the authors have shown that the evolution of the equivalent discharge coefficient vs. Reynolds number at the metering orifice corresponds well to the values that can be predicted by the classical analytical models. Oppositely, the simulated flow force was found to be quite different from the value calculated analytically. This drove the authors to investigate minutely the influence of the studied domain and the setting of the CFD simulation. It was firstly shown that the flow recirculates in the inlet and outlet channels if their length is not sufficient regarding their hydraulic diameter. The dead volume on the uncontrolled orifice side also plays a significant role. These examples highlight the influence of the geometry of the fluid domain considered. The second action was to investigate the influence of the type of mesh, the turbulence models and near-wall approaches, and the numerical solver and discretization scheme order. Two approaches were used to determine the overall hydraulic force acting on the moving spool. First, the force was deduced from the momentum balance on a control domain delimited by the valve inlet and outlet and the spool walls. Second, the overall hydraulic force was calculated from the integral of pressure and shear forces acting at the boundaries of the fluid domain. This underlined the significant contribution of the viscous forces acting on the spool between the inlet and outlet orifices, which are generally not considered in the literature. This also emphasized the influence of the choices made for the implementation of CFD calculation and results analysis. With the step-by-step process adopted to increase confidence in the CFD simulations, the authors propose a set of best practices and recommendations for the efficient use of CFD to design high-pressure spool valves.

Keywords: computational fluid dynamics, hydraulic forces, servovalve, rotary servovalve

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Authors: A. Kahil, A. Nekmouche, N. Khelil, I. Hamadou, M. Hamizi, Ne. Hannachi

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The objective of this work is to study the influence of the nonlinear behavior models of the concrete (concrete_BAEL and concrete_UNI) as well as the confinement brought by the transverse reinforcement on the seismic response of reinforced concrete frame (RC/frame). These models as well as the confinement are integrated in the Cast3m finite element calculation code. The consideration of confinement (TAC, taking into account the confinement) provided by the transverse reinforcement and the non-consideration of confinement (without consideration of containment, WCC) in the presence and absence of a vertical load is studied. The application was made on a reinforced concrete frame (RC/frame) with 3 levels and 2 spans. The results show that on the one hand, the concrete_BAEL model slightly underestimates the resistance of the RC/frame in the plastic field, whereas the concrete_uni model presents the best results compared to the simplified model "concrete_BAEL", on the other hand, for the concrete-uni model, taking into account the confinement has no influence on the behavior of the RC/frame under imposed displacement up to a vertical load of 500 KN.

Keywords: reinforced concrete, nonlinear calculation, behavior laws, fiber model confinement, numerical simulation

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Authors: M. A. Wanzala, L. A. Ogallo, F. J. Opijah, J. N. Mutemi

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The usefulness and limitations in climate information are due to uncertainty inherent in the climate system. For any given region to have sustainable development it is important to apply climate information into its socio-economic strategic plans. The overall objective of the study was to assess the performance of the Coupled Model Inter-comparison Project (CMIP5) over the Lake Victoria Basin. The datasets used included the observed point station data, gridded rainfall data from Climate Research Unit (CRU) and hindcast data from eight CMIP5. The methodology included trend analysis, spatial analysis, correlation analysis, Principal Component Analysis (PCA) regression analysis, and categorical statistical skill score. Analysis of the trends in the observed rainfall records indicated an increase in rainfall variability both in space and time for all the seasons. The spatial patterns of the individual models output from the models of MPI, MIROC, EC-EARTH and CNRM were closest to the observed rainfall patterns.

Keywords: categorical statistics, coupled model inter-comparison project, principal component analysis, statistical downscaling

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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: M. Ahmadi, Sh. Damanabi, F. Sadoughi

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National Health Information System plays an important role in ensuring timely and reliable access to Health information which is essential for strategic and operational decisions that improve health, quality and effectiveness of health care. In other words, by using the National Health information system you can improve the quality of health data, information and knowledge used to support decision making at all levels and areas of the health sector. Since full identification of the components of this system for better planning and management influential factors of performance seems necessary, therefore, in this study, different attitudes towards components of this system are explored comparatively. Methods: This is a descriptive and comparative kind of study. The society includes printed and electronic documents containing components of the national health information system in three parts: input, process, and output. In this context, search for information using library resources and internet search were conducted and data analysis was expressed using comparative tables and qualitative data. Results: The findings showed that there are three different perspectives presenting the components of national health information system, Lippeveld, Sauerborn, and Bodart Model in 2000, Health Metrics Network (HMN) model from World Health Organization in 2008 and Gattini’s 2009 model. All three models outlined above in the input (resources and structure) require components of management and leadership, planning and design programs, supply of staff, software and hardware facilities, and equipment. In addition, in the ‘process’ section from three models, we pointed up the actions ensuring the quality of health information system and in output section, except Lippeveld Model, two other models consider information products, usage and distribution of information as components of the national health information system. Conclusion: The results showed that all the three models have had a brief discussion about the components of health information in input section. However, Lippeveld model has overlooked the components of national health information in process and output sections. Therefore, it seems that the health measurement model of network has a comprehensive presentation for the components of health system in all three sections-input, process, and output.

Keywords: National Health Information System, components of the NHIS, Lippeveld Model

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Authors: Ahmed R. Abdelaziz, Zaki M. I. Osha

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Solar radiation data are of great significance for solar energy system design. This study aims at developing and calibrating new empirical models for estimating monthly mean daily global solar radiation on a horizontal surface in Alexandria, Egypt. Day length hours, sun height, day number, and declination angle calculated data are used for this purpose. A comparison between measured and calculated values of solar radiation is carried out. It is shown that all the proposed correlations are able to predict the global solar radiation with excellent accuracy in Alexandria.

Keywords: solar energy, global solar radiation, model, regression coefficient

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Authors: Liang-Hsuan Chen, Sheng-Shing Nien

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This study aims to develop approaches to formulate intuitionistic fuzzy regression (IFR) models for many decision-making applications in the fuzzy environments using intuitionistic fuzzy observations. Intuitionistic fuzzy numbers (IFNs) are used to characterize the fuzzy input and output variables in the IFR formulation processes. A mathematical programming problem (MPP) is built up to optimally determine the IFR parameters. Each parameter in the MPP is defined as a couple of alternative numerical variables with opposite signs, and an intuitionistic fuzzy error term is added to the MPP to characterize the uncertainty of the model. The IFR model is formulated based on the distance measure to minimize the total distance errors between estimated and observed intuitionistic fuzzy responses in the MPP resolution processes. The proposed approaches are simple/efficient in the formulation/resolution processes, in which the sign of parameters can be determined so that the problem to predetermine the sign of parameters is avoided. Furthermore, the proposed approach has the advantage that the spread of the predicted IFN response will not be over-increased, since the parameters in the established IFR model are crisp. The performance of the obtained models is evaluated and compared with the existing approaches.

Keywords: fuzzy sets, intuitionistic fuzzy number, intuitionistic fuzzy regression, mathematical programming method

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Authors: Rebecca Owusu Coffie, Atakelty Hailu

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Variants of production frontier models have emerged, however, only a limited number of them are applied in empirical research. Hence the effects of these alternative frontier models are not well understood, particularly within sub-Saharan Africa. In this paper, we apply recent advances in the production frontier to examine levels of technical efficiency and efficiency drivers. Specifically, we compare the heteroscedastic parametric and the semiparametric stochastic smooth coefficient (SPSC) models. Using rice production data from Ghana, our empirical estimates reveal that alternative specification of efficiency estimators results in either downward or upward bias in the technical efficiency estimates. Methodologically, we find that the SPSC model is more suitable and generates high-efficiency estimates. Within the parametric framework, we find that parameterization of both the mean and variance of the pre-truncated function is the best model. For the drivers of technical efficiency, we observed that longer farm distances increase inefficiency through a reduction in labor productivity. High soil quality, however, increases productivity through increased land productivity.

Keywords: pre-truncated, rice production, smooth coefficient, technical efficiency

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Authors: Jiahe Liu, Hongyang Yu, Feng Qian, Miao Luo

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SMPL-X was a powerful parametric human body model that included male, neutral, and female models, with significant gender differences between these three models. During the process of 3D human body reconstruction, the correct selection of standard templates was crucial for obtaining accurate results. To address this issue, we developed an efficient gender classification algorithm to automatically select the appropriate template for 3D human body reconstruction. The key to this gender classification algorithm was the precise analysis of human body features. By using the SMPL-X model, the algorithm could detect and identify gender features of the human body, thereby determining which standard template should be used. The accuracy of this algorithm made the 3D reconstruction process more accurate and reliable, as it could adjust model parameters based on individual gender differences. SMPL-X and the related gender classification algorithm have brought important advancements to the field of 3D human body reconstruction. By accurately selecting standard templates, they have improved the accuracy of reconstruction and have broad potential in various application fields. These technologies continue to drive the development of the 3D reconstruction field, providing us with more realistic and accurate human body models.

Keywords: gender classification, joint detection, SMPL-X, 3D reconstruction

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Authors: Haidy S. Ghali, Engy Serag, A. Samer Ezeldin

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Copper is an essential raw material used in the construction industry. During the year 2021 and the first half of 2022, the global market suffered from a significant fluctuation in copper raw material prices due to the aftermath of both the COVID-19 pandemic and the Russia-Ukraine war, which exposed its consumers to an unexpected financial risk. Thereto, this paper aims to develop two ANN-LSTM price prediction models, using Python, that can forecast the average monthly copper prices traded in the London Metal Exchange; the first model is a multivariate model that forecasts the copper price of the next 1-month and the second is a univariate model that predicts the copper prices of the upcoming three months. Historical data of average monthly London Metal Exchange copper prices are collected from January 2009 till July 2022, and potential external factors are identified and employed in the multivariate model. These factors lie under three main categories: energy prices and economic indicators of the three major exporting countries of copper, depending on the data availability. Before developing the LSTM models, the collected external parameters are analyzed with respect to the copper prices using correlation and multicollinearity tests in R software; then, the parameters are further screened to select the parameters that influence the copper prices. Then, the two LSTM models are developed, and the dataset is divided into training, validation, and testing sets. The results show that the performance of the 3-Month prediction model is better than the 1-Month prediction model, but still, both models can act as predicting tools for diverse economic situations.

Keywords: copper prices, prediction model, neural network, time series forecasting

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Authors: Ghada Elshafei, A. Elazim Negm

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Recently, Green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives are green buildings should be designed to minimize the overall impact of the built environment on ecosystems in general and particularly on human health and on the natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state of art review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: green architecture/building, technologies, optimization, strategies, fuzzy techniques, models

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Authors: Yonas Masresha Aymeku

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The purpose of capacity modelling at U-turns is to develop a relationship between capacity and its geometric characteristics. In fact, the few models available for the estimation of capacity at different transportation facilities do not provide specific guidelines for median openings. For this reason, an effort is made to estimate the capacity by collecting the data sets from median openings at different lane roads in Hyderabad City, India. Wide difference (43% -59%) among the capacity values estimated by the existing models shows the limitation to consider for mixed traffic situations. Thus, a distinct model is proposed for the estimation of the capacity of U-turn vehicles at median openings considering mixed traffic conditions, which would further prompt to investigate the effect of different factors that might affect the capacity.

Keywords: geometric, guiddelines, median, vehicles

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Authors: L. Yettou

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In this study, the calculations of proton emission spectra produced by ⁶³Cu(n,xp) and ⁶⁵Cu(n,xp) reactions are used in the framework of preequilibrium models using the EMPIRE code and TALYS code. Exciton Model predidtions combined with the Kalbach angular distribution systematics and the Hybrid Monte Carlo Simulation (HMS) were used. The effects of levels densities and those of a-parameter have been investigated for our calculations. The comparison with experimental data shows clear improvement over the Exciton Model and HMS calculations.

Keywords: Preequilibrium models , level density, level density a-parameter., Empire code, Talys code.

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Authors: Denys Osipenko, Jonathan Crook

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Because of the variety of the card holders’ behaviour types and income sources each consumer account can be transferred to a variety of states. Each consumer account can be inactive, transactor, revolver, delinquent, defaulted and requires an individual model for the income prediction. The estimation of transition probabilities between statuses at the account level helps to avoid the memorylessness of the Markov Chains approach. This paper investigates the transition probabilities estimation approaches to credit cards income prediction at the account level. The key question of empirical research is which approach gives more accurate results: multinomial logistic regression or multistage conditional logistic regression with binary target. Both models have shown moderate predictive power. Prediction accuracy for conditional logistic regression depends on the order of stages for the conditional binary logistic regression. On the other hand, multinomial logistic regression is easier for usage and gives integrate estimations for all states without priorities. Thus further investigations can be concentrated on alternative modeling approaches such as discrete choice models.

Keywords: multinomial regression, conditional logistic regression, credit account state, transition probability

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Authors: Ikram Metalsi

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English as a Medium of Instruction known as (EMI) is expanding rapidly in the world. A growing volume of research has been dedicated to investigating its implementation. However, considerably less attention has been given to understanding EMI in a context where its implementation has been discussed but not yet put into practice. One such context is Algeria, where talks about a possible implementation of EMI have been going on for some time. The present study examines the current discourses and university lecturers’ attitudes towards the potential implementation of EMI as well as investigating the current implicit and explicit language policies in scientific courses in Algerian state universities. The focus is specifically on Engineering departments, as this field has gained worldwide importance in EMI research (Macaro et al. 2018), and, traditionally, French has been the MOI for Engineering in Algerian universities. Using the ROADMAPPING framework (Dafouz and Smit 2016) and the mixed method research approach, the present work explores the language in education policy (LEP) and planning situation in Algeria, the current media of instruction as well as the status and use of the English language in the scientific courses of the tertiary sector. Finally, the current study explores the perceived challenges and benefits of the implementation of EMI programmes from teachers’ perspectives with a particular focus on agency and how this potential policy implementation and teachers’ perceptions of agency around it may reflexively influence their professional identity.

Keywords: media of instruction, language in education policy, lecturers attitudes, teacher agency, professional identity

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Authors: Ramzi Rihane, Yassine Benayed

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Epilepsy is a chronic neurological disorder characterized by recurrent, unprovoked seizures resulting from abnormal electrical activity in the brain. Timely and accurate detection of these seizures is essential for improving patient care. In this study, we leverage the UK Bonn University open-source EEG dataset and employ advanced deep-learning techniques to automate the detection of epileptic seizures. By extracting key features from both time and frequency domains, as well as Spectrogram features, we enhance the performance of various deep learning models. Our investigation includes architectures such as Long Short-Term Memory (LSTM), Bidirectional LSTM (Bi-LSTM), 1D Convolutional Neural Networks (1D-CNN), and hybrid CNN-LSTM and CNN-BiLSTM models. The models achieved impressive accuracies: LSTM (98.52%), Bi-LSTM (98.61%), CNN-LSTM (98.91%), CNN-BiLSTM (98.83%), and CNN (98.73%). Additionally, we utilized a data augmentation technique called SMOTE, which yielded the following results: CNN (97.36%), LSTM (97.01%), Bi-LSTM (97.23%), CNN-LSTM (97.45%), and CNN-BiLSTM (97.34%). These findings demonstrate the effectiveness of deep learning in capturing complex patterns in EEG signals, providing a reliable and scalable solution for real-time seizure detection in clinical environments.

Keywords: electroencephalogram, epileptic seizure, deep learning, LSTM, CNN, BI-LSTM, seizure detection

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Authors: Prashansa Singh, Rohit Bajaj, Manjot Kaur

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In the modern agricultural landscape, precision farming has emerged as a pivotal strategy for enhancing crop yield and optimizing resource utilization. This paper introduces an innovative Crop Recommendation System (CRS) that leverages the Internet of Things (IoT) technology and the Message Queuing Telemetry Transport (MQTT) protocol to collect critical environmental and soil data via sensors deployed across agricultural fields. The system is designed to address the challenges of real-time data acquisition, efficient data transmission, and dynamic crop recommendation through the application of advanced Artificial Intelligence (AI) and Machine Learning (ML) models. The CRS architecture encompasses a network of sensors that continuously monitor environmental parameters such as temperature, humidity, soil moisture, and nutrient levels. This sensor data is then transmitted to a central MQTT server, ensuring reliable and low-latency communication even in bandwidth-constrained scenarios typical of rural agricultural settings. Upon reaching the server, the data is processed and analyzed by AI/ML models trained to correlate specific environmental conditions with optimal crop choices and cultivation practices. These models consider historical crop performance data, current agricultural research, and real-time field conditions to generate tailored crop recommendations. This implementation gets 99% accuracy.

Keywords: Iot, MQTT protocol, machine learning, sensor, publish, subscriber, agriculture, humidity

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Authors: Abderrazek Ben Maatoug, Ibrahim Fatnassi, Wassim Ben Ayed

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In this paper we investigate the issue of market risk quantification for Middle East and North Africa (MENA) Islamic market equity. We use Value-at-Risk (VaR) as a measure of potential risk in Islamic stock market, for long and short position, based on Riskmetrics model and the conditional parametric ARCH class model volatility with normal, student and skewed student distribution. The sample consist of daily data for the 2006-2014 of 11 Islamic stock markets indices. We conduct Kupiec and Engle and Manganelli tests to evaluate the performance for each model. The main finding of our empirical results show that (i) the superior performance of VaR models based on the Student and skewed Student distribution, for the significance level of α=1% , for all Islamic stock market indices, and for both long and short trading positions (ii) Risk Metrics model, and VaR model based on conditional volatility with normal distribution provides the best accurate VaR estimations for both long and short trading positions for a significance level of α=5%.

Keywords: value-at-risk, risk management, islamic finance, GARCH models

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Authors: Fares Laouacheria, Said Kechida, Moncef Chabi

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The objective of the study was based on the hydrological routing modelling for the continuous monitoring of the hydrological situation in the Moudjar river catchment, especially during floods with Hydrologic Engineering Center–Hydrologic Modelling Systems (HEC-HMS). The HEC-GeoHMS was used to transform data from geographic information system (GIS) to HEC-HMS for delineating and modelling the catchment river in order to estimate the runoff volume, which is used as inputs to the hydrological routing model. Two hydrological routing models were used, namely Muskingum and Muskingum routing models, for conducting this study. In this study, a comparison between the parameters of the Muskingum and Muskingum-Cunge routing models in HEC-HMS was used for modelling flood routing in the Moudjar river catchment and determining the relationship between these parameters and the physical characteristics of the river. The results indicate that the effects of input parameters such as the weighting factor "X" and travel time "K" on the output results are more significant, where the Muskingum routing model was more sensitive to input parameters than the Muskingum-Cunge routing model. This study can contribute to understand and improve the knowledge of the mechanisms of river floods, especially in ungauged river catchments.

Keywords: HEC-HMS, hydrological modelling, Muskingum routing model, Muskingum-Cunge routing model

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Authors: Lidija R. Jevrić, Sanja O. Podunavac-Kuzmanović, Strahinja Z. Kovačević

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In this paper, quantitative structure-retention relationships (QSRR) analysis was applied in order to correlate in silico biological and lipophilicity molecular descriptors with retention values for the set of selected s-triazine herbicides. In silico generated biological and lipophilicity descriptors were discriminated using generalized pair correlation method (GPCM). According to this method, the significant difference between independent variables can be noticed regardless almost equal correlation with dependent variable. Using established multiple linear regression (MLR) models some biological characteristics could be predicted. Established MLR models were evaluated statistically and the most suitable models were selected and ranked using sum of ranking differences (SRD) method. In this method, as reference values, average experimentally obtained values are used. Additionally, using SRD method, similarities among investigated s-triazine herbicides can be noticed. These analysis were conducted in order to characterize selected s-triazine herbicides for future investigations regarding their biodegradability. This study is financially supported by COST action TD1305.

Keywords: descriptors, generalized pair correlation method, pesticides, sum of ranking differences

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Authors: Payam Haghparast, Mikhail V. Sorin, Hakim Nesreddine

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The complex oblique shock phenomenon can be simply assumed as a normal shock at the constant area section to simulate a sharp pressure increase and velocity decrease in 1-D thermodynamic models. The assumed normal shock location is one of the greatest sources of error in ejector thermodynamic models. Most researchers consider an arbitrary location without justifying it. Our study compares the effect of normal shock place on ejector dimensions in 1-D models. To this aim, two different ejector experimental test benches, a constant area-mixing ejector (CAM) and a constant pressure-mixing (CPM) are considered, with different known geometries, operating conditions and working fluids (R245fa, R141b). In the first step, in order to evaluate the real value of the efficiencies in the different ejector parts and critical back pressure, a CFD model was built and validated by experimental data for two types of ejectors. These reference data are then used as input to the 1D model to calculate the lengths and the diameters of the ejectors. Afterwards, the design output geometry calculated by the 1D model is compared directly with the corresponding experimental geometry. It was found that there is a good agreement between the ejector dimensions obtained by the 1D model, for both CAM and CPM, with experimental ejector data. Furthermore, it is shown that normal shock place affects only the constant area length as it is proven that the inlet normal shock assumption results in more accurate length. Taking into account previous 1D models, the results suggest the use of the assumed normal shock location at the inlet of the constant area duct to design the supersonic ejectors.

Keywords: 1D model, constant area-mixing, constant pressure-mixing, normal shock location, ejector dimensions

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Authors: Mara Balestrieri

Abstract:

Climate change has long been the focus of attention for the growing impact of extreme weather events and global warming in many areas of the planet and the evidence of economic, social, and environmental damage caused by global warming. Nowadays, climate change is recognized as a critical global problem. Several initiatives have been undertaken over time to enhance the long theoretical debate and field experience in order to reduce Co2 emissions and contain climate alteration. However, the awareness that climate change is already taking place has led to a growing demand for adaptation. It is certainly a matter of anticipating the negative effects of climate change but, at the same time, implementing appropriate actions to prevent climate change-related damage, minimize the problems that may result, and also seize any opportunities that may arise. Consequently, adaptation has become a core element of climate policy and research. However, the attention to this issue has not developed in a uniform manner across countries. Some countries are further ahead than others. This paper examines the literature on climate change adaptation developed until 2018 in Italy, considering the urban dimension, to provide a framework for it, and to identify main topics and features. The papers were selected from Scopus and were analyzed through a matrix that we propose. Results demonstrate that adaptation to climate change studies attracted increasing attention from Italian scientific communities in the last years, although Italian scientific production is still quantitatively lower than in other countries and describes strengths and weaknesses in line with international panorama with respect to objectives, sectors, and problems.

Keywords: adaptation, bibliometric literature, climate change, urban studies

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Authors: Arifuzzaman Nayeem, Tafannum Torsha, Tanvir Manzur, Shaurav Alam

Abstract:

Performance evaluation of reinforced concrete (RC) beams subjected to accidental fire is significant for post-fire capacity measurement. Mechanical properties of any RC beam degrade due to heating since the strength and modulus of concrete and reinforcement suffer considerable reduction under elevated temperatures. Moreover, fire-induced thermal dilation and shrinkage cause internal stresses within the concrete and eventually result in cracking, spalling, and loss of stiffness, which ultimately leads to lower service life. However, conducting full-scale comprehensive experimental investigation for RC beams exposed to fire is difficult and cost-intensive, where the finite element (FE) based numerical study can provide an economical alternative for evaluating the post-fire capacity of RC beams. In this study, an attempt has been made to study the fire behavior of RC beams using FE software package ABAQUS under different durations of fire. The damaged plasticity model of concrete in ABAQUS was used to simulate behavior RC beams. The effect of temperature on strength and modulus of concrete and steel was simulated following relevant Eurocodes. Initially, the result of FE models was validated using several experimental results from available scholarly articles. It was found that the response of the developed FE models matched quite well with the experimental outcome for beams without heat. The FE analysis of beams subjected to fire showed some deviation from the experimental results, particularly in terms of stiffness degradation. However, the ultimate strength and deflection of FE models were similar to that of experimental values. The developed FE models, thus, exhibited the good potential to predict the fire behavior of RC beams. Once validated, FE models were then used to analyze several RC beams having different strengths (ranged between 20 MPa and 50 MPa) exposed to the standard fire curve (ASTM E119) for different durations. The post-fire performance of RC beams was investigated in terms of load-deflection behavior, flexural strength, and deflection characteristics.

Keywords: fire durations, flexural strength, post fire capacity, reinforced concrete beam, standard fire

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Authors: Chau-Kuang Chen, John Hughes, Jr., A. Dexter Samuels

Abstract:

The prediction models for the United States Medical Licensure Examination (USMLE) Steps 1 and 2 performances were constructed by the Monte Carlo simulation modeling approach via linear regression. The purpose of this study was to build robust simulation models to accurately identify the most important predictors and yield the valid range estimations of the Steps 1 and 2 scores. The application of simulation modeling approach was deemed an effective way in predicting student performances on licensure examinations. Also, sensitivity analysis (a/k/a what-if analysis) in the simulation models was used to predict the magnitudes of Steps 1 and 2 affected by changes in the National Board of Medical Examiners (NBME) Basic Science Subject Board scores. In addition, the study results indicated that the Medical College Admission Test (MCAT) Verbal Reasoning score and Step 1 score were significant predictors of the Step 2 performance. Hence, institutions could screen qualified student applicants for interviews and document the effectiveness of basic science education program based on the simulation results.

Keywords: prediction model, sensitivity analysis, simulation method, USMLE

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Authors: Mary Kay Bacallao

Abstract:

New research on the human genome has revealed secrets to the variation in skin pigmentation found in all human populations. Application of this research to multicultural education has a profound effect on students from all backgrounds. This paper identifies the four locations in the human genome that code for variation in skin pigmentation worldwide. The research makes this new knowledge accessible to students of all ages as they participate in an art project that brings these scientific multicultural concepts to life. Students participate in the application of breakthrough scientific principles through hands-on art activities where they simulate the work of the DNA coding to create their own skin tone using the colors expressed to varying degrees in every people group. As students create their own artwork handprint from the pallet of colors, they realize that each color on the pallet is essential to creating every tone of skin. This research project serves to bring people together and appreciate the variety and diversity in skin tones. As students explore the variations, they create pigmentation with the use of the eumelanins, which are the black-brown sources of pigmentation, and the pheomelanins, which are the yellow-reddish-brown sources of pigmentation. The research project dispels myths about skin tones that have divided people in the past. As a group project, this research leads to greater appreciation and understanding of the diverse family groups.

Keywords: diversity, multicultural, skin pigmentation, eumelanins, pheomelanins, handprint, artwork, science, genome, human

Procedia PDF Downloads 67