Search results for: cluster model approach

Authors: Bruno Vilić Belina, Jadranko Matuško

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The rapid development of cyber-physical systems significantly influences modern control systems introducing a whole new range of applications of control systems but also putting them under new challenges to ensure their resiliency to possible cyber attacks, either in the form of data integrity attacks or deception attacks. This paper presents a model predictive approach to the control of cyber-physical systems robust to cyber attacks. We assume that a cyber attack can be modelled as an additive disturbance that acts in the measuring channel. For such a system, we designed a tube-based predictive controller based. The performance of the designed controller has been verified in Matlab/Simulink environment.

Keywords: control systems, cyber attacks, resiliency, robustness, tube based model predictive control

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Authors: Elaine Yee Sing Wong, Jonine Jancey, Andy H. Lee, Anthony P. James

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Singapore has a rapidly aging population, where the majority of older women aged 50 years and above, are physically inactive and have unhealthy dietary habits, placing them at ‘high risk’ of non-communicable diseases. Given the multiplicity of less than optimal dietary habits and high levels of physical inactivity among Singaporean women, it is imperative to develop appropriate lifestyle interventions at recreational centres to enhance both their physical and nutritional knowledge, as well as provide them with the opportunity to develop skills to support behaviour change. To the best of our knowledge, this proposed study is the first physical activity and nutrition cluster randomised controlled trial conducted in Singapore for older women. Findings from this study may provide insights and recommendations for policy makers and key stakeholders to create new healthy living, recreational centres with supportive environments. This 6-month community-based cluster randomised controlled trial will involve the implementation and evaluation of physical activity and nutrition program for community dwelling Singaporean women, who currently attend recreational centres to promote social leisure activities in their local neighbourhood. The intervention will include dietary education and counselling sessions, physical activity classes, and telephone contact by certified fitness instructors and qualified nutritionists. Social Cognitive Theory with Motivational Interviewing will inform the development of strategies to support health behaviour change. Sixty recreational centres located in Singapore will be randomly selected from five major geographical districts and randomly allocated to the intervention (n=30) or control (n=30) cluster. A sample of 600 (intervention n=300; control n=300) women aged 50 years and above will then be recruited from these recreational centres. The control clusters will only undergo pre and post data collection and will not receive the intervention. It is hypothesised that by the end of the intervention, the intervention group participants (n = 300) compared to the control group (n = 300), will show significant improvements in the following variables: lipid profile, body mass index, physical activity and dietary behaviour, anthropometry, mental and physical health. Data collection will be examined and compared via the Statistical Package for the Social Science version 23. Descriptive and summary statistics will be used to quantify participants’ characteristics and outcome variables. Multi-variable mixed regression analyses will be used to confirm the effects of the proposed health intervention, taking into account the repeated measures and the clustering of the observations. The research protocol was approved by the Curtin University Human Research Ethics Committee (approval number: HRE2016-0366). The study has been registered with the Australian and New Zealand Clinical Trial Registry (12617001022358).

Keywords: community based, healthy aging, intervention, nutrition, older women, physical activity

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Authors: Saowaluck Ukrisdawithid

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The thermal conductivity of thermal insulation materials are measured by Heat Flow Meter (HFM) apparatus. The components of uncertainty are complex and difficult on routine measurement by modelling approach. In this study, uncertainty of thermal conductivity measurement was estimated by single laboratory validation approach. The within-laboratory reproducibility was 1.1%. The standard uncertainty of method and laboratory bias by using SRM1453 expanded polystyrene board was dominant at 1.4%. However, it was assessed that there was no significant bias. For sample measurement, the sources of uncertainty were repeatability, density of sample and thermal conductivity resolution of HFM. From this approach to sample measurements, the combined uncertainty was calculated. In summary, the thermal conductivity of sample, polystyrene foam, was reported as 0.03367 W/m·K ± 3.5% (k = 2) at mean temperature 23.5 °C. The single laboratory validation approach is simple key of routine testing laboratory for estimation uncertainty of thermal conductivity measurement by using HFM, according to ISO/IEC 17025-2017 requirements. These are meaningful for laboratory competent improvement, quality control on products, and conformity assessment.

Keywords: single laboratory validation approach, within-laboratory reproducibility, method and laboratory bias, certified reference material

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Authors: Sai Maniveer Adapa, Sai Guptha Perla, Adithya Reddy P.

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Thyroid nodules can often be diagnosed with ultrasound imaging, although differentiating between benign and malignant nodules can be challenging for medical professionals. This work suggests a novel approach to increase the precision of thyroid nodule identification by combining machine learning and deep learning. The new approach first extracts information from the ultrasound pictures using a deep learning method known as a convolutional autoencoder. A support vector machine, a type of machine learning model, is then trained using these features. With an accuracy of 92.52%, the support vector machine can differentiate between benign and malignant nodules. This innovative technique may decrease the need for pointless biopsies and increase the accuracy of thyroid nodule detection.

Keywords: thyroid tumor diagnosis, ultrasound images, deep learning, machine learning, convolutional auto-encoder, support vector machine

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Authors: Alaa El-Din Rezk

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For organic xenobiotics, sorption to Aldrich humic acid is a key process controlling their mobility, bioavailability, toxicity and fate in the soil. Hydrophobic organic compounds possessing either acid or basic groups can be partially ionized (deprotonated or protonated) within the range of natural soil pH. For neutral and ionogenicxenobiotics including (neutral, acids and bases) sorption coefficients normalized to organic carbon content, Koc, have measured at different pH values. To this end, the batch equilibrium technique has been used, employing SPME combined with GC-MSD as an analytical tool. For most ionogenic compounds, sorption has been affected by both pH and pKa and can be explained through Henderson-Hasselbalch equation. The results demonstrate that when assessing the environmental fate of ionogenic compounds, their pKa and speciation under natural conditions should be taken into account. A new model has developed to predict the relationship between log Koc and pH with full statistical evaluation against other existing predictive models. Neutral solutes have displayed a good fit with the classical model using log Kow as log Koc predictor, whereas acidic and basic compounds have displayed a good fit with the LSER approach and the new proposed model. Measurement limitations of the Batch technique and SPME-GC-MSD have been found with ionic compounds.

Keywords: humic acid, log Koc, pH, pKa, SPME-GCMSD

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Authors: Muhsin Kizhisseri, Jorg Schluter, Saleh Gharie

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Atherosclerosis is the main reason of stroke, which is one of the deadliest diseases in the world. The carotid artery in the brain is the prominent location for atherosclerotic progression, which hinders the blood flow into the brain. The inclusion of computational fluid dynamics (CFD) into the diagnosis cycle to understand the hemodynamics of the patient-specific carotid artery can give insights into stroke prediction. Realistic outlet boundary conditions are an inevitable part of the numerical simulations, which is one of the major factors in determining the accuracy of the CFD results. The Windkessel model-based outlet boundary conditions can give more realistic characteristics of the distal vascular branches of the carotid artery, such as the resistance to the blood flow and compliance of the distal arterial walls. This study aims to find the most influential distal branches of the carotid artery by using the Windkessel model parameters in the outlet boundary conditions. The parametric study approach to Windkessel model parameters can include the geometrical features of the distal branches, such as radius and length. The incorporation of the variations of the geometrical features of the major distal branches such as the middle cerebral artery, anterior cerebral artery, and ophthalmic artery through the Windkessel model can aid in identifying the most influential distal branch in the carotid artery. The results from this study can help physicians and stroke neurologists to have a more detailed and accurate judgment of the patient's condition.

Keywords: stroke, carotid artery, computational fluid dynamics, patient-specific, Windkessel model, distal vascular branches

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Authors: Ashna Babu, Deepshikha Jaiswal Nagar

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Cuprate high-temperature superconductors (HTSCs) have been immensely studied during the past few decades because of their structure which is described as a superlattice of superconducting CuO₂ layers. In particular, YBa₂Cu₃O₆₊δ (YBCO), with its critical temperature of 93 K, has received the most attention due to its well-defined metal stoichiometry and variable oxygen content that determines the carrier doping level. Substitution of metal ions at the Cu site is known to increase the critical current density without destroying superconductivity in YBCO. The construction of vortex phase diagrams is very important for such doped YBCO materials both from a fundamental perspective as well as from a technological perspective. By measuring field-dependent magnetization on annealed single crystals of Al-doped YBCO, YBa₂Cu₃₋ₓAlₓO₆₊δ (Al-YBCO), we were able to observe a second magnetization peak anomaly (SMP) in a very large part of the phase diagram. We were also able to observe the SMP anomaly in temperature-dependent magnetization measurements, the first observation to our knowledge. Critical current densities were calculated using Bean’s critical state model, flux jumps associated with symmetry reorientation of vortex lattice were studied, the oxygen cluster distribution was also analysed, and by incorporating all observations, we made a vortex phase diagram for oxygenated Al-YBCO single crystal.

Keywords: oxygen deficient clusters, second magnetization peak anomaly, flux jumps, vortex phase diagram

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Authors: Rose Branch-Allen, John Jayachandran

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Background and purpose: Canada is a pluralistic, multicultural society with an ethno-cultural composition that has been shaped over time by immigrants and their descendants. Although Canada welcomes these immigrants, many will endure hardship and assimilation difficulties. Despite these life hurdles, surveys consistently disclose high life satisfaction for all Canadians. Most research studies on Life Satisfaction/ Subjective Wellbeing (SWB) have focused on one main determinant and a variety of social demographic variables to delineate the determinants of life satisfaction. However, very few research studies examine life satisfaction from a holistic approach. In addition, we need to understand the causal pathways leading to life satisfaction, and develop theories that explain why certain variables differentially influence the different components of SWB. The aim this study was to utilize a holistic approach to construct a causal model and identify major determinants of life satisfaction. Data and measures: This study utilized data from the General Social Survey, with a sample size of 19, 597. The exogenous concepts included age, gender, marital status, household size, socioeconomic status, ethnicity, location, immigration status, religiosity, and neighborhood. The intervening concepts included health, social contact, leisure, enjoyment, work-family balance, quality time, domestic labor, and sense of belonging. The endogenous concept life satisfaction was measured by multiple indicators (Cronbach’s alpha = .83). Analysis: Several multiple regression models were run sequentially to estimate path coefficients for the causal model. Results: Overall, above average satisfaction with life was reported for respondents with specific socio-economic, demographic and lifestyle characteristics. With regard to exogenous factors, respondents who were female, younger, married, from high socioeconomic status background, born in Canada, very religious, and demonstrated high level of neighborhood interaction had greater satisfaction with life. Similarly, intervening concepts suggested respondents had greater life satisfaction if they had better health, more social contact, less time on passive leisure activities and more time on active leisure activities, more time with family and friends, more enjoyment with volunteer activities, less time on domestic labor and a greater sense of belonging to the community. Conclusions and Implications: Our results suggest that a holistic approach is necessary for establishing determinants of life satisfaction, and that life satisfaction is not merely comprised of positive or negative affect rather understanding the causal process of life satisfaction. Even though, most of our findings are consistent with previous studies, a significant number of causal connections contradict some of the findings in literature today. We have provided possible explanation for these anomalies researchers encounter in studying life satisfaction and policy implications.

Keywords: causal model, holistic approach, life satisfaction, socio-demographic variables, subjective well-being

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Authors: S. Bouhouche, R. Drai, J. Bast

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This paper is concerned with a method for uncertainty evaluation of steel sample content using X-Ray Fluorescence method. The considered method of analysis is a comparative technique based on the X-Ray Fluorescence; the calibration step assumes the adequate chemical composition of metallic analyzed sample. It is proposed in this work a new combined approach using the Kalman Filter and Markov Chain Monte Carlo (MCMC) for uncertainty estimation of steel content analysis. The Kalman filter algorithm is extended to the model identification of the chemical analysis process using the main factors affecting the analysis results; in this case, the estimated states are reduced to the model parameters. The MCMC is a stochastic method that computes the statistical properties of the considered states such as the probability distribution function (PDF) according to the initial state and the target distribution using Monte Carlo simulation algorithm. Conventional approach is based on the linear correlation, the uncertainty budget is established for steel Mn(wt%), Cr(wt%), Ni(wt%) and Mo(wt%) content respectively. A comparative study between the conventional procedure and the proposed method is given. This kind of approaches is applied for constructing an accurate computing procedure of uncertainty measurement.

Keywords: Kalman filter, Markov chain Monte Carlo, x-ray fluorescence calibration and testing, steel content measurement, uncertainty measurement

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Authors: Sendy Ghirardi, Pau Rausell Köster

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The European Commission increasingly pushes cultural policies towards social outcomes and local and regional authorities also call for culture-driven strategies for local development and prosperity and therefore, the measurement of cultural participation becomes increasingly more significant for evidence-based policy-making processes. Cultural participation involves various kinds of social and economic spillovers that combine social and economic objectives of value creation, including social sustainability and respect for human values. Traditionally, from the economic perspective, cultural consumption is measured by the value of financial transactions in purchasing, subscribing to, or renting cultural equipment and content, addressing the market value of cultural products and services. The main sources of data are the household spending survey and merchandise trade survey, among others. However, what characterizes the cultural consumption is that it is linked with the hedonistic and affective dimension rather than the utilitarian one. In fact, nowadays, more and more attention is being paid to the social and psychological dimensions of culture. The aim of this work is to present a comprehensive approach to measure the impacts of cultural participation and cultural users’ behaviour, combining both socio-psychological and economic approaches. The model combines contingent evaluation techniques with the individual characteristic and perception analysis of the cultural experiences to evaluate the cognitive, aesthetic, emotive and social impacts of cultural participation. To investigate the comprehensive approach to measure the impact of the cultural events on individuals, the research has been designed on the basis of prior theoretical development. A deep literature methodology has been done to develop the theoretical model applied to the web platform to measure the impacts of cultural experience on individuals. The developed framework aims to become a democratic tool for evaluating the services that cultural or policy institutions can adopt through the use of an interacting platform that produces big data benefiting academia, cultural management and policies. The Au Culture is a prototype based on an application that can be used on mobile phones or any other digital platform. The development of the AU Culture Platform has been funded by the Valencian Innovation Agency (Government of the Region of Valencia) and it is part of the Horizon 2020 project MESOC.

Keywords: comprehensive approach, cultural participation, economic dimension, socio-psychological dimension

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Authors: Thien X. Dinh, Peter Witt

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A one-dimensional model for the simulation of condensation and solidification of a metallurgical vapor in the mixture of gas during supersonic expansion is presented. In the model, condensation is based on critical nucleation and drop-growth theory. When the temperature falls below the supercooling point, all the formed liquid droplets in the condensation phase are assumed to solidify at an infinite rate. The model was verified with a Computational Fluid Dynamics simulation of magnesium vapor condensation and solidification. The obtained results are in reasonable agreement with CFD data. Therefore, the model is a promising, efficient tool for use in the design process for supersonic nozzles applied in mineral processes since it is faster than the CFD counterpart by an order of magnitude.

Keywords: condensation, metallurgical flow, solidification, supersonic expansion

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Authors: Mohammad Zaid, Md. Rehan Sadique

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Underground structures are an integral part of urban infrastructures. Tunnels are being used for the transportation of humans and goods from distance to distance. Terrorist attacks on underground structures such as tunnels have resulted in the improvement of design methodologies of tunnels. The design of underground tunnels must include anti-terror design parameters. The study has been carried out to analyse the rock tunnel when subjected to internal blast loading. The finite element analysis has been carried out for 30m by 30m of the cross-section of the tunnel and 35m length of extrusion of the rock tunnel model. The effect of tunnel diameter and overburden depth of tunnel has been studied under internal blast loading. Four different diameters of tunnel considered are 5m, 6m, 7m, and 8m, and four different overburden depth of tunnel considered are 5m, 7.5m, 10m, and 12.5m. The mohr-coulomb constitutive material model has been considered for the Quartzite rock. A concrete damage plasticity model has been adopted for concrete tunnel lining. For the trinitrotoluene (TNT) Jones-Wilkens-Lee (JWL) material model has been considered. Coupled-Eulerian-Lagrangian (CEL) approach for blast analysis has been considered in the present study. The present study concludes that a shallow tunnel having smaller diameter needs more attention in comparison to blast resistant design of deep tunnel having a larger diameter. Further, in the case of shallow tunnels, more bulging has been observed, and a more substantial zone of rock has been affected by internal blast loading.

Keywords: finite element method, blast, rock, tunnel, CEL, JWL

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Authors: Malte Schilling, Mahmoud M. Rabah, Sven Liebisch

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Wave run-up and overtopping are the relevant parameters for the dimensioning of the crest height of dikes. Various experimental as well as numerical studies have investigated these parameters under different boundary conditions (e.g. wave conditions, structure type). Particularly for the dike design in Europe, a common approach is formulated where wave and structure properties are parameterized. However, this approach assumes equal run-up heights and overtopping discharges along the longitudinal axis. However, convex dikes have a heterogeneous crest by definition. Hence, local differences in a convex dike line are expected to cause wave-structure interactions different to a straight dike. This study aims to assess both run-up and overtopping at convexly curved dikes. To cast light on the relevance of curved dikes for the design approach mentioned above, physical model tests were conducted in a 3D wave basin of the Ludwig-Franzius-Institute Hannover. A dike of a slope of 1:6 (height over length) was tested under both regular waves and TMA wave spectra. Significant wave heights ranged from 7 to 10 cm and peak periods from 1.06 to 1.79 s. Both run-up and overtopping was assessed behind the curved and straight sections of the dike. Both measurements were compared to a dike with a straight line. It was observed that convex curvatures in the longitudinal dike line cause a redirection of incident waves leading to a concentration around the center point. Measurements prove that both run-up heights and overtopping rates are higher than on the straight dike. It can be concluded that deviations from a straight longitudinal dike line have an impact on design parameters and imply uncertainties within the design approach in force. Therefore, it is recommended to consider these influencing factors for such cases.

Keywords: convex dike, longitudinal curvature, overtopping, run-up

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Authors: Jiameng Wang, Yunfei Yin, Xiyu Deng

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Parallel optimization is one of the important research topics of data mining at this stage. Taking Classification and Regression Tree (CART) parallelization as an example, this paper proposes a parallel data mining algorithm based on SSP-OGini-PCCP. Aiming at the problem of choosing the best CART segmentation point, this paper designs an S-SP model without data association; and in order to calculate the Gini index efficiently, a parallel OGini calculation method is designed. In addition, in order to improve the efficiency of the pruning algorithm, a synchronous PCCP pruning strategy is proposed in this paper. In this paper, the optimal segmentation calculation, Gini index calculation, and pruning algorithm are studied in depth. These are important components of parallel data mining. By constructing a distributed cluster simulation system based on SPARK, data mining methods based on SSP-OGini-PCCP are tested. Experimental results show that this method can increase the search efficiency of the best segmentation point by an average of 89%, increase the search efficiency of the Gini segmentation index by 3853%, and increase the pruning efficiency by 146% on average; and as the size of the data set increases, the performance of the algorithm remains stable, which meets the requirements of contemporary massive data processing.

Keywords: classification, Gini index, parallel data mining, pruning ahead

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Authors: Murat Avci, Fatih Kosar, Ismail Yilmaz

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In this study, structure-flow interaction for water brake mechanism is studied with Abaqus CEL approach. The water brake mechanism is used for dynamic systems such as sled system on rail. For the achievement of these system tests, structure-flow interaction should be investigated in detail. This study is about a sled test of an aircraft subsystem which rises to supersonic speeds thanks to rocket engines. To decrease or to stop the thrusting rocket sleds, water brake mechanisms are used. Water brake mechanism provides the deceleration of the structures that have supersonic speeds. Therefore, structure-flow interaction may cause damage to the water brake mechanism. To verify all design revisions with system tests are so costly so that some decisions are taken in accordance with numerical methods. In this study, structure-flow interaction that belongs to water brake mechanism is solved with Abaqus CEL approach. Fluid and deformation on the structure behaviors are modeled at the same time thanks to CEL approach. Provided analysis results are corrected with the dynamic tests. Deformation zones seen in numerical analysis are also observed in dynamic tests. Finally, Johnson-Cook material model parameters used for this analysis are proven, and it is understood that these parameters can be used for dynamic analysis like water brake mechanism.

Keywords: aircraft, rocket, structure-flow, supersonic

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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: Arup Kumar Sarma, Rohan Kar

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The development of physical model of River like Brahmaputra, which finds its origin in the Chema Yundung glacier of Tibet and flows through India and Bangladesh, is always expensive and very much time consuming. With the advancement of computational technique, mathematical modeling has found wide application. MIKE 21C is one such commercial software, developed by Danish Hydraulic Institute (DHI), with the depth-averaged approach and a two-dimensional curvilinear finite-difference model, which is capable of modeling hydrodynamic and morphological processes with some limitations. The main purpose of this study are to generate bathymetry of the River Brahmaputra starting from “Sadia” at upstream to “Dhubri,” at downstream stretching a distance of approximately 695 km, for four different years: 1957, 1971, 1977, and 1981 over the grid generated in the MIKE 21C and to carry out the hydrodynamic simulation for these years to analyze the effect of bathymetry change on the surface water elevation. The study has established that bathymetric change can influence the flood level significantly in some of the river reaches and therefore the modification or updating of regular bathymetry is very much essential for the reliable flood routing in alluvial rivers.

Keywords: bathymetry, brahmaputra river, hydrodynamic model, surface water elevation

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Authors: Asaiel Alohaly

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A theoretical framework for corporate governance is needed to bridge the gap between the corporate governance of private companies and State-owned Enterprises (SOEs). The two dominant models, being shareholder and stakeholder, do not always address the specific requirements and challenges posed by ‘hybrid’ companies; namely, previously national bodies that have been privatised bffu t where the government retains significant control or holds a majority of shareholders. Thus, an exploratory theoretical study is needed to identify how ‘hybrid’ companies should be defined and why the state model should be acknowledged since it is the less conspicuous model in comparison with the shareholder and stakeholder models. This research focuses on ‘the state model of corporate governance to understand the complex ownership, control pattern, goals, and corporate governance of these hybrid companies. The significance of this research lies in the fact that there is a limited available publication on the state model. The outcomes of this research are as follows. It became evident that the state model exists in the ecosystem. However, corporate governance theories have not extensively covered this model. Though, there is a lot being said about it by OECD and the World Bank. In response to this gap between theories and industry practice, this research argues for the state model, which proceeds from an understanding of the institutionally embedded character of hybrid companies where the government is either a majority of the total shares or a controlling shareholder.

Keywords: corporate governance, control, shareholders, state model

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Authors: Krishna Mohan Bathula, Fatou Bintou Loucoubar, FNU Kaleemunnisa, Christelle Scharff, Mark Anthony De Castro

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Voice recognition algorithms such as automatic speech recognition and text-to-speech systems with African languages can play an important role in bridging the digital divide of Artificial Intelligence in Africa, contributing to the establishment of a fully inclusive information society. This paper proposes a Deep Learning model that can classify the user responses as inputs for an interactive voice response system. A dataset with Wolof language words ‘yes’ and ‘no’ is collected as audio recordings. A two stage Data Augmentation approach is adopted for enhancing the dataset size required by the deep neural network. Data preprocessing and feature engineering with Mel-Frequency Cepstral Coefficients are implemented. Convolutional Neural Networks (CNNs) have proven to be very powerful in image classification and are promising for audio processing when sounds are transformed into spectra. For performing voice response classification, the recordings are transformed into sound frequency feature spectra and then applied image classification methodology using a deep CNN model. The inference model of this trained and reusable Wolof voice response recognition system can be integrated with many applications associated with both web and mobile platforms.

Keywords: automatic speech recognition, interactive voice response, voice response recognition, wolof word classification

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Authors: Nabil Hameed Al-Farsi

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This study’s main goal is to develop a model and a maintenance strategy for a cement factory called Arabian Cement Company, Rabigh Plant. The proposed work here depends on Reliability centric maintenance approach to develop a strategy and maintenance schedule that ensures increasing the reliability of the production system components, thus ensuring continuous productivity. The cost-effective maintenance of the plant’s dependability performance is the key goal of durability-based maintenance is. The cement plant consists of 7 important steps, so, developing a maintenance plan based on Reliability centric maintenance (RCM) method is made up of 10 steps accordingly starting from selecting units and data until performing and updating the model. The processing unit chosen for the analysis of this case is the calcinatory unit regarding model’s validation and the Travancore Titanium Products Ltd (TTP) using the claimed data history acquired from the maintenance department maintenance from the mentioned company. After applying the proposed model, the results of the maintenance simulation justified the plant's existing scheduled maintenance policy being reconsidered. Results represent the need for preventive maintenance for all Class A criticality equipment instead of the planned maintenance and the breakdown one for all other equipment depends on its criticality and an FMEA report. Consequently, the additional cost of preventive maintenance would be offset by the cost savings from breakdown maintenance for the remaining equipment.

Keywords: engineering, reliability, strategy, maintenance, failure modes, effects and criticality analysis (FMEA)

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Authors: Anjalika Fernando, Banuka Athuraliya

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This paper presents a comprehensive approach for converting Sinhala Sign Language (SSL) into grammatically correct sentences using Natural Language Processing (NLP) techniques in real-time. While previous studies have explored various aspects of SSL translation, the research gap lies in the absence of grammar checking for SSL. This work aims to bridge this gap by proposing a two-stage methodology that leverages deep learning models to detect signs and translate them into coherent sentences, ensuring grammatical accuracy. The first stage of the approach involves the utilization of a Long Short-Term Memory (LSTM) deep learning model to recognize and interpret SSL signs. By training the LSTM model on a dataset of SSL gestures, it learns to accurately classify and translate these signs into textual representations. The LSTM model achieves a commendable accuracy rate of 94%, demonstrating its effectiveness in accurately recognizing and translating SSL gestures. Building upon the successful recognition and translation of SSL signs, the second stage of the methodology focuses on improving the grammatical correctness of the translated sentences. The project employs a Neural Machine Translation (NMT) architecture, consisting of an encoder and decoder with LSTM components, to enhance the syntactical structure of the generated sentences. By training the NMT model on a parallel corpus of Sinhala wrong sentences and their corresponding grammatically correct translations, it learns to generate coherent and grammatically accurate sentences. The NMT model achieves an impressive accuracy rate of 98%, affirming its capability to produce linguistically sound translations. The proposed approach offers significant contributions to the field of SSL translation and grammar correction. Addressing the critical issue of grammar checking, it enhances the usability and reliability of SSL translation systems, facilitating effective communication between hearing-impaired and non-sign language users. Furthermore, the integration of deep learning techniques, such as LSTM and NMT, ensures the accuracy and robustness of the translation process. This research holds great potential for practical applications, including educational platforms, accessibility tools, and communication aids for the hearing-impaired. Furthermore, it lays the foundation for future advancements in SSL translation systems, fostering inclusive and equal opportunities for the deaf community. Future work includes expanding the existing datasets to further improve the accuracy and generalization of the SSL translation system. Additionally, the development of a dedicated mobile application would enhance the accessibility and convenience of SSL translation on handheld devices. Furthermore, efforts will be made to enhance the current application for educational purposes, enabling individuals to learn and practice SSL more effectively. Another area of future exploration involves enabling two-way communication, allowing seamless interaction between sign-language users and non-sign-language users.In conclusion, this paper presents a novel approach for converting Sinhala Sign Language gestures into grammatically correct sentences using NLP techniques in real time. The two-stage methodology, comprising an LSTM model for sign detection and translation and an NMT model for grammar correction, achieves high accuracy rates of 94% and 98%, respectively. By addressing the lack of grammar checking in existing SSL translation research, this work contributes significantly to the development of more accurate and reliable SSL translation systems, thereby fostering effective communication and inclusivity for the hearing-impaired community

Keywords: Sinhala sign language, sign Language, NLP, LSTM, NMT

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Authors: Ali Rahnamoun, Adri van Duin

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The concept of high velocity particle impact on the spacecraft surface materials has been one of the important issues in the design of such materials. Among these particles, water clusters might be the most abundant and the most important particles to be studied. The importance of water clusters is that upon impact on the surface of the materials, they can cause damage to the material and also if they are sub-cooled water clusters, they can attach to the surface of the materials and cause ice accumulation on the surface which is very problematic in spacecraft and also aircraft operations. The dynamics of the collisions between amorphous silica structures and water clusters with impact velocities of 1 km/s to 10 km/s are studied using the ReaxFF reactive molecular dynamics simulation method. The initial water clusters include 150 water molecules and the water clusters are collided on the surface of amorphous fully oxidized and suboxide silica structures. These simulations show that the most abundant molecules observed on the silica surfaces, other than reflecting water molecules, are H3O+ and OH- for the water cluster impacts on suboxide and fully oxidized silica structures, respectively. The effect of impact velocity on the change of silica mass is studied. At high impact velocities the water molecules attach to the silica surface through a chemisorption process meaning that water molecule dissociates through the interaction with silica surface. However, at low impact velocities, physisorbed water molecules are also observed, which means water molecule attaches and accumulates on the silica surface. The amount of physisorbed waters molecules at low velocities is higher on the suboxide silica surfaces. The evolution of the temperatures of the water clusters during the collisions indicates that the possibility of electron excitement at impact velocities less than 10 km/s is minimal and ReaxFF reactive molecular dynamics simulation can predict the chemistry of these hypervelocity impacts. However, at impact velocities close to 10 km/s the average temperature of the impacting water clusters increase to about 2000K, with individual molecules oocasionally reaching temperatures of over 8000K and thus will be prudent to consider the concept of electron excitation at these higher impact velocities which goes beyond the current ReaxFF ability.

Keywords: spacecraft materials, hypervelocity impact, reactive molecular dynamics simulation, amorphous silica

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Authors: Khalid Kaddoura, Tarek Zayed

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Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

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Authors: Ciro Cursio, Giulia Cursio, Pio Luigi Cursio, Luigi Cursio

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Communication between practitioner and patient is of the utmost importance in aesthetic medicine: as of today, images of previous treatments are the most common tool used by doctors to describe and anticipate future results for their patients. However, using photos of other people often reduces the engagement of the prospective patient and is further limited by the number and quality of pictures available to the practitioner. Pre-existing work solves this issue in two ways: 3D scanning of the area with manual editing of the 3D model by the doctor or automatic prediction of the treatment by warping the image with hand-written parameters. The first approach requires the manual intervention of the doctor, while the second approach always generates results that aren’t always realistic. Thus, in one case, there is significant manual work required by the doctor, and in the other case, the prediction looks artificial. We propose an AI-based algorithm that autonomously generates a realistic prediction of treatment results. For the purpose of this study, we focus on hyaluronic acid treatments in the facial area. Our approach takes into account the individual characteristics of each face, and furthermore, the prediction system allows the patient to decide which area of the face she wants to modify. We show that the predictions generated by our system are realistic: first, the quality of the generated images is on par with real images; second, the prediction matches the actual results obtained after the treatment is completed. In conclusion, the proposed approach provides a valid tool for doctors to show patients what they will look like before deciding on the treatment.

Keywords: prediction, hyaluronic acid, treatment, artificial intelligence

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Authors: Labane Chrif

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A nonlinear approach to the automatic pitch attitude control problem for aircraft transportation is presented. A nonlinear model describing the longitudinal equations of motion in strict feedback form is derived. Backstepping is utilized for the construction of a globally stabilizing controller with a number of free design parameters. The controller is evaluated using the aircraft transportation. The adaptation scheme proposed allowed us to design an explicit controller with a minimal knowledge of the aircraft aerodynamics. Finally, the simulation results will show that backstepping controller have better dynamic performance, simpler design, higher precision, easier implement, etc. At the same time, the control effect will be significantly improved. In addition, backstepping control is superior in short transition, good stability, anti-disturbance and good control.

Keywords: nonlinear control, backstepping, aircraft control, Lyapunov function, longitudinal model

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Authors: Khalil Aryanfar, Shahrzad Sanjari, Pariya Gholipor, Elmira Hafez

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The present study aimed to investigate and compare the characteristics of entrepreneurship among students in senior secondary schools in the academic year 2008-2009 in Tabriz city. Research employed survey method respectively. The study population consisted of all students in the senior branch of theoretical, technical, professional and vocational (1033 patients) were included. Sample size of 493 was calculated according to Morgan table. Sampling method was random cluster and stratified sampling. Data collected by researcher made questionnaire based on the theory of MC clleland (1963) and Brvkhavs (1980). These tools would indicators be for achievement, Independence, disposition, creativity, risk-taking, self-control, tolerance for ambiguity, team work approach in the future. To determine the psychometric properties of the questionnaire, content validity of the survey was approved by relevant experts. In addition, to estimate the internal consistency of Cronbach's alpha coefficient was calculated for 84% of total inventory. Collected data Using mean, standard deviation and were analyzed by ANOVA. The results showed that there is a significant difference between students' entrepreneurial potential fields of theoretical, technical, professional and vocational level (0/01).

Keywords: entrepreneurship, achievement motivation, risk taking, creativity, self-control, independence, tolerance of ambiguity, foresight

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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: James Beauchemin

Abstract:

Research indicates that college students are experiencing mental health challenges of greater severity, and an increased number of students are seeking help. Contributing to the compromised wellness of the college student population are the prevalence of unhealthy lifestyle habits and behaviors such as alcohol consumption, tobacco use, dietary concerns, risky sexual behaviors, and lack of physical activity. Alternative approaches are needed for this population that emphasize prevention and holistic lifestyle change that mitigate mental health and wellness challenges and alleviate strain on campus resources. This presentation will introduce a Solution-Focused Wellness (SFW) intervention model and examine wellness domains solution-focused strategies to promote personal well-being, and provide supporting research from multiple studies that illustrate intervention effectiveness with a collegiate population. Given the subjective and personal nature of wellness, a therapeutic approach that provides the opportunity for individuals to conceptualize and operationalize wellness themselves is critical to facilitating lasting wellness-based change. Solution-Focused Brief Therapy (SFBT) is a strength-based modality defined by its emphasis on constructing solutions rather than focusing on problems and the assumption that clients have the resources and capacity to change. SFBT has demonstrated effectiveness as a brief therapeutic intervention with the college population in groups and related to health and wellness. By integrating SFBT strategies with personal wellness, a brief intervention was developed to support college students in establishing lifestyles trends consistent with their conceptualizations of wellness. Research supports the effectiveness of a SFW model in improving college student wellness in both face-to-face and web-based formats. Outcomes of controlled and longitudinal studies will be presented, demonstrating significant improvements in perceptions of stress, life satisfaction, happiness, mental health, well-being, and resilience. Overall, there is compelling evidence that utilization of a Solution-Focused Brief Therapy approach with college students can help to improve personal wellness and establish healthy lifestyle trends, providing an effective prevention-focused strategy for college counseling centers and wellness centers to employ. Primary research objectives include: 1)establish an evidence-based approach to facilitating wellness pro motion among the college student population, 2) examine the effectiveness of a Solution-Focused Wellness (SFW) intervention model in decreasing stress, improving personal wellness, mental health, life satisfaction, and resiliency,3) investigate intervention impacts over time (e.g. 6-week post-intervention), and 4) demonstrate SFW intervention utility in wellness promotion and associated outcomes when compared with no-treatment control, and alternative intervention approaches.

Keywords: wellness, college students, solution-focused, prevention

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Authors: Suegnet Smit

Abstract:

Prior to 1994, special education in South Africa was marginalized and fragmented. Moving away from a Medical model approach to special education, the Government, after 1994, promoted an Inclusive approach, as a means to transform education in general, and special education in particular. This transformation, however, is moving at too a slow pace for learners with barriers to learning and development to benefit fully from their education. The goal of the Department of Basic Education is to minimize, remove, and prevent barriers to learning and development in the educational setting, by attending to the unique needs of the individual learner. However, the implementation of Inclusive education is problematic, and general education remains poor. This paper highlights the historical development of special education in South Africa, underpinned by a bio-ecological perspective. Problematic areas within the systemic levels of the education system are highlighted in order to indicate how the interactive processes within the systemic levels affect special needs learners on the personal dimension of the bio-ecological approach. As part of the methodology, thorough document analysis was conducted on information collected from a large body of research literature, which included academic articles, reports, policies, and policy reviews. Through a qualitative analysis, data were grouped and categorized according to the bio-ecological model systems, which revealed various successes and challenges within the education system. The challenges inhibit change, growth, and development for the child, who experience barriers to learning. From these findings, it is established that special education in South Africa has been, and still is, on a bumpy road. Sadly, the transformation process of change, envisaged by implementing Inclusive education, is still yet a dream, not fully realized. Special education seems to be stuck at what is, and the education system has not moved forward significantly enough to reach what special education should and could be. The gap that exists between a vision of Inclusive quality education for all, and the current reality, is still too wide. Problems encountered in all the education system levels, causes a funnel-effect downward to learners with special educational needs, with negative effects for the development of these learners.

Keywords: bio-ecological perspective, education systems, inclusive education, special education

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Authors: Nusrat T. Chowdhury

Abstract:

Green Supply Chain Management (GSCM) is becoming a key to success for profitable businesses. The various activities contributing to carbon emissions in a supply chain are transportation, ordering and holding of inventory. This research work develops a mixed-integer nonlinear programming (MINLP) model that considers the scenario of a supply chain with multiple periods, multiple products and multiple suppliers. The model assumes that the demand is deterministic, the buyer has a limited storage space in each period, the buyer is responsible for the transportation cost, a supplier-dependent ordering cost applies for each period in which an order is placed on a supplier and inventory shortage is permissible. The model provides an optimal decision regarding what products to order, in what quantities, with which suppliers, and in which periods in order to maximize the profit. For the purpose of evaluating the carbon emissions, three different carbon regulating policies i.e., carbon cap-and-trade, the strict cap on carbon emission and carbon tax on emissions, have been considered. The proposed MINLP has been validated using a randomly generated data set.

Keywords: green supply chain, carbon emission, mixed integer non-linear program, inventory shortage, carbon cap-and-trade

Procedia PDF Downloads 239