Search results for: educational models

Authors: Shamm Kidane, Ibrahim Abdella, Fitsum Gaim, Simon Mulugeta, Sirak Asmerom, Natnael Ambasager, Yoel Ghebrihiwot

Abstract:

The call for natural language processing (NLP) systems for low-resource languages has become more apparent than ever in the past few years, with the arduous challenges still present in preparing such systems. This paper presents an improved dataset version of the Nagaoka Tigrinya Corpus for Parts-of-Speech (POS) classification system in the Tigrinya language. The size of the initial Nagaoka dataset was incremented, totaling the new tagged corpus to 118K tokens, which comprised the 12 basic POS annotations used previously. The additional content was also annotated manually in a stringent manner, followed similar rules to the former dataset and was formatted in CONLL format. The system made use of the novel approach in NLP tasks and use of the monolingually pre-trained TiELECTRA, TiBERT and TiRoBERTa transformer models. The highest achieved score is an impressive weighted F1-score of 94.2%, which surpassed the previous systems by a significant measure. The system will prove useful in the progress of NLP-related tasks for Tigrinya and similarly related low-resource languages with room for cross-referencing higher-resource languages.

Keywords: Tigrinya POS corpus, TiBERT, TiRoBERTa, conditional random fields

Procedia PDF Downloads 103

Authors: C. Bateira, J. Fernandes, A. Costa

Abstract:

The Douro Demarked Region (DDR) is a production Porto wine region. On the NE of Portugal, the strong incision of the Douro valley developed very steep slopes, organized with agriculture terraces, have experienced an intense and deep transformation in order to implement the mechanization of the work. The old terrace system, based on stone vertical wall support structure, replaced by terraces with earth embankments experienced a huge terrace instability. This terrace instability has important economic and financial consequences on the agriculture enterprises. This paper presents and develops cartographic tools to access the embankment instability and identify the area prone to instability. The priority on this evaluation is related to the use of physically based mathematical models and develop a validation process based on an inventory of the past embankment instability. We used the shallow landslide stability model (SHALSTAB) based on physical parameters such us cohesion (c’), friction angle(ф), hydraulic conductivity, soil depth, soil specific weight (ϱ), slope angle (α) and contributing areas by Multiple Flow Direction Method (MFD). A terraced area can be analysed by this models unless we have very detailed information representative of the terrain morphology. The slope angle and the contributing areas depend on that. We can achieve that propose using digital elevation models (DEM) with great resolution (pixel with 40cm side), resulting from a set of photographs taken by a flight at 100m high with pixel resolution of 12cm. The slope angle results from this DEM. In the other hand, the MFD contributing area models the internal flow and is an important element to define the spatial variation of the soil saturation. That internal flow is based on the DEM. That is supported by the statement that the interflow, although not coincident with the superficial flow, have important similitude with it. Electrical resistivity monitoring values which related with the MFD contributing areas build from a DEM of 1m resolution and revealed a consistent correlation. That analysis, performed on the area, showed a good correlation with R2 of 0,72 and 0,76 at 1,5m and 2m depth, respectively. Considering that, a DEM with 1m resolution was the base to model the real internal flow. Thus, we assumed that the contributing area of 1m resolution modelled by MFD is representative of the internal flow of the area. In order to solve this problem we used a set of generalized DEMs to build the contributing areas used in the SHALSTAB. Those DEMs, with several resolutions (1m and 5m), were built from a set of photographs with 50cm resolution taken by a flight with 5km high. Using this maps combination, we modelled several final maps of terrace instability and performed a validation process with the contingency matrix. The best final instability map resembles the slope map from a DEM of 40cm resolution and a MFD map from a DEM of 1m resolution with a True Positive Rate (TPR) of 0,97, a False Positive Rate of 0,47, Accuracy (ACC) of 0,53, Precision (PVC) of 0,0004 and a TPR/FPR ratio of 2,06.

Keywords: agricultural terraces, cartography, landslides, SHALSTAB, vineyards

Procedia PDF Downloads 177

Authors: G. Salavwa, P. Erhijakpor Jr., H. Ukwu

Abstract:

This study will explore child labour issues in Nigeria because it is capable of affecting the physical and general well-being of children who perform hazardous work. This feat will be achieved through qualitative research methodology. Data collection shall be elicited by oral interviews and documental content analysis to delve on the application of the Convention on the Rights of the Child (CRC), International Labour Organization ILO and Geneva Convention relating to child labour practices in Nigeria. This will include the relevance of present domestic laws relating to child labour as implemented in Nigeria, together with factors that contribute to the practice of child labour in the country. The oral interview data analysis will be performed by breaking the interview data into significant statements and themes. This shall be done by comparing and determining the commonalities that are prevalent in the participants’ views regarding child labour menace in Nigeria. Presumably, findings from this study shall unveil that a poor educational policy, a widespread poverty level which is mostly prevalent amongst families in the rural areas of the country, a lack of employment for adults, have led to the ineffectiveness of the local child labour laws in Nigeria. These has in turn culminated into a somewhat non-implementation of the international laws of the CRC, ILO and Geneva Declaration on child labour to which the Nigerian government is a signatory. Based on the finding, this study will calls on the government of Nigeria to extend its free educational policy from the elementary, secondary to tertiary educations. The government also has to ensure that offenders of children’s rights should face a severe punishment.

Keywords: commonalities, tertiary, constitution, qualitative

Procedia PDF Downloads 212

Authors: Hadia Abdel Aziz, Raghda El Ebrashi

Abstract:

Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

Procedia PDF Downloads 372

Authors: Kayode E. Oyetade, Seraphin D. Eyono Obono

Abstract:

Age ratings are very helpful in providing parents with relevant information for the purchase and use of digital technologies by the children; this is why the non-definition of age ratings for the use of ICT's by children in schools is a major concern; and this problem serves as a motivation for this study whose aim is to examine the factors affecting the perceptions of educators on the learners’ youngest age for the introduction of ICT's in schools. This aim is achieved through two types of research objectives: the identification and design of theories and models on age ratings, and the empirical testing of such theories and models in a survey of educators from the Camperdown district of the South African KwaZulu-Natal province. A questionnaire is used for the collection of the data of this survey whose validity and reliability is checked in SPSS prior to its descriptive and correlative quantitative analysis. The main hypothesis supporting this research is the association between the demographics of educators, their personality, and their perceptions on the learners’ youngest age for the introduction of ICT's in schools; as claimed by existing research; except that the present study looks at personality from three dimensions: self-actualized personalities, fully functioning personalities, and healthy personalities. This hypothesis was fully confirmed by the empirical study conducted by this research except for the demographic factor where only the educators’ grade or class was found to be associated with the personality of educators.

Keywords: age ratings, educators, e-learning, personality theories

Procedia PDF Downloads 237

Authors: Mustafa Tufekci, Caner Guven

Abstract:

In Automotive Industry, sliding door systems that are also used as body closures, are safety members. Extreme product tests are realized to prevent failures in a design process, but these tests realized experimentally result in high costs. Finite element analysis is an effective tool used for the design process. These analyses are used before production of a prototype for validation of design according to customer requirement. In result of this, the substantial amount of time and cost is saved. Finite element model is created for geometries that are designed in 3D CAD programs. Different element types as bar, shell and solid, can be used for creating mesh model. The cheaper model can be created by the selection of element type, but combination of element type that was used in model, number and geometry of element and degrees of freedom affects the analysis result. Sliding door system is a good example which used these methods for this study. Structural analysis was realized for sliding door mechanism by using FE models. As well, physical tests that have same boundary conditions with FE models were realized. Comparison study for these element types, were done regarding test and analyses results then the optimum combination was achieved.

Keywords: finite element analysis, sliding door mechanism, element type, structural analysis

Procedia PDF Downloads 329

Authors: Ahmed Mousa, Huda Mazeed

Abstract:

The research aims to determine the appropriate songs and artistic indications for the kindergarten child. In addition, it aims to use the songs of folk to develop expressive visual drawings with artistic connotations for the kindergarten child. The current research used a one group semi-experimental approach to identify the impact of songs on expressive children's drawings. The research community is represented in the educational administration in Giza Governorate for the academic year (2018 - 2019). The sample was taken from the kindergarten of Gamal Abdel Nasser School of Dokki Educational Administration in Giza Governorate. The study was applied to the second level children sample (5-6 years), where they numbered 20 children, males and females. The research results show that there are statistically significant differences between the average scores of the children of the experimental group in the pre and post-measurements on the observation card for children after hearing the songs of social and national folk in favor of post measurement. Moreover, the results demonstrate that there are no statistically significant differences between the average scores of children in the experimental group in the measurements, the post and follow-up, on the observation card of children's drawings for social and national folk.

Keywords: folk songs, visual expressive, artistic connotations, early childhood

Procedia PDF Downloads 176

Authors: C. S. Subhashini, H. L. Premaratne

Abstract:

Landslides are the most recurrent and prominent disaster in Sri Lanka. Sri Lanka has been subjected to a number of extreme landslide disasters that resulted in a significant loss of life, material damage, and distress. It is required to explore a solution towards preparedness and mitigation to reduce recurrent losses associated with landslides. Artificial Neural Networks (ANNs) and Hidden Markov Model (HMMs) are now widely used in many computer applications spanning multiple domains. This research examines the effectiveness of using Artificial Neural Networks and Hidden Markov Model in landslides predictions and the possibility of applying the modern technology to predict landslides in a prominent geographical area in Sri Lanka. A thorough survey was conducted with the participation of resource persons from several national universities in Sri Lanka to identify and rank the influencing factors for landslides. A landslide database was created using existing topographic; soil, drainage, land cover maps and historical data. The landslide related factors which include external factors (Rainfall and Number of Previous Occurrences) and internal factors (Soil Material, Geology, Land Use, Curvature, Soil Texture, Slope, Aspect, Soil Drainage, and Soil Effective Thickness) are extracted from the landslide database. These factors are used to recognize the possibility to occur landslides by using an ANN and HMM. The model acquires the relationship between the factors of landslide and its hazard index during the training session. These models with landslide related factors as the inputs will be trained to predict three classes namely, ‘landslide occurs’, ‘landslide does not occur’ and ‘landslide likely to occur’. Once trained, the models will be able to predict the most likely class for the prevailing data. Finally compared two models with regards to prediction accuracy, False Acceptance Rates and False Rejection rates and This research indicates that the Artificial Neural Network could be used as a strong decision support system to predict landslides efficiently and effectively than Hidden Markov Model.

Keywords: landslides, influencing factors, neural network model, hidden markov model

Procedia PDF Downloads 384

Authors: Djallel Bouamama, Yasser R. Haddadi

Abstract:

Accurate brain tumor segmentation is crucial for diagnosis and treatment planning, yet it remains a challenging task due to the variability in tumor shapes and intensities. This paper introduces a distinct approach to brain tumor image segmentation by leveraging an advanced architecture known as Mamba-Unet. Building on the well-established U-Net framework, Mamba-Unet incorporates distinct design enhancements to improve segmentation performance. Our proposed method integrates a multi-scale attention mechanism and a hybrid loss function to effectively capture fine-grained details and contextual information in brain MRI scans. We demonstrate that Mamba-Unet significantly enhances segmentation accuracy compared to conventional U-Net models by utilizing a comprehensive dataset of annotated brain MRI scans. Quantitative evaluations reveal that Mamba-Unet surpasses traditional U-Net architectures and other contemporary segmentation models regarding Dice coefficient, sensitivity, and specificity. The improvements are attributed to the method's ability to manage class imbalance better and resolve complex tumor boundaries. This work advances the state-of-the-art in brain tumor segmentation and holds promise for improving clinical workflows and patient outcomes through more precise and reliable tumor detection.

Keywords: brain tumor classification, image segmentation, CNN, U-NET

Procedia PDF Downloads 34

Authors: Musthaya Patchanee

Abstract:

The aim of this research is to study potential factors relating to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province by conducting a random sampling of 400 people aged between 15-59 who migrated from Myanmar. The information collected through interviews was analyzed to find a percentage and mean using the Stepwise Multiple Regression Analysis. The results have shown that 33.25% of Myanmar migrant workers want to return to their home country within the next 1-5 years, 46.25%, in 6-10 years and the rest, in over 10 years. The factors relating to such decision can be concluded that the scale of the decision of return migration has a positive relationship with a statistical significance at 0.05 with a conformity with friends and relatives (r=0.886), a relationship with family and community (r=0.782), possession of land in hometown (r=0.756) and educational level (r=0.699). However, the factor of property possession in Prachuap Khiri Khan is the only factor with a high negative relationship (r=0.-537). From the Stepwise Multiple Regression Analysis, the results have shown that the conformity with friends and relatives and educational level factors are influential to the decision of return migration of Myanmar migrant workers in Prachuap Khiri Khan Province, which can predict the decision at 86.60% and the multiple regression equation from the analysis is Y= 6.744+1.198 conformity + 0.647 education.

Keywords: decision of return migration, factors of return migration, Myanmar migrant workers, Prachuap Khiri Khan Province

Procedia PDF Downloads 541

Authors: Yang Yang, Dan Liu

Abstract:

Anomaly detection models for network flow based on machine learning have poor detection performance under extremely unbalanced training data conditions and also have slow detection speed and large resource consumption when deploying on network edge devices. Embedding multi-teacher knowledge distillation (mKD) in anomaly detection can transfer knowledge from multiple teacher models to a single model. Inspired by this, we proposed a state-of-the-art model, mKDNAD, to improve detection performance. mKDNAD mine and integrate the knowledge of one-dimensional sequence and two-dimensional image implicit in network flow to improve the detection accuracy of small sample classes. The multi-teacher knowledge distillation method guides the train of the student model, thus speeding up the model's detection speed and reducing the number of model parameters. Experiments in the CICIDS2017 dataset verify the improvements of our method in the detection speed and the detection accuracy in dealing with the small sample classes.

Keywords: network flow anomaly detection (NAD), multi-teacher knowledge distillation, machine learning, deep learning

Procedia PDF Downloads 122

Authors: Hilal Karakuş, Berrin Akman

Abstract:

Preschool years are considered as critical years because of shaping the future lives of individuals. All of the knowledge, skills, and concepts are acquired during this period. Also, basis of academic skills is based on this period. As all of the developmental areas are the fastest in that period, the basis of mathematics education should be given in this period, too. Mathematics is seen as a difficult and abstract course by the most people. Therefore, the enjoyable side of mathematics should be presented in a concrete way in this period to avoid any bias of children for mathematics. This study is conducted to examine mathematics concept acquisition of children in terms of different variables. Screening model is used in this study which is carried out in a quantity way. The study group of this research consists of total 300 children, selected from each class randomly in groups of five, who are from public and private preschools in Çankaya, which is district of Ankara, in 2014-2015 academic year and attending children in the nursery classes and preschool institutions are connected to the Ministry of National Education. The study group of the research was determined by stage sampling method. The schools, which formed study group, are chosen by easy sampling method and the children are chosen by simple random method. Research data were collected with Bracken Basic Concept Scale–Revised Form and Child’s Personal Information Form generated by the researcher in order to get information about children and their families. Bracken Basic Concept Scale-Revised Form consists of 11 sub-dimensions (color, letter, number, size, shape, comparison, direction-location, and quantity, individual and social awareness, building- material) and 307 items. Subtests related to the mathematics were used in this research. In the “Child Individual Information Form” there are items containing demographic information as followings: age of children, gender of children, attending preschools educational intuitions for children, school attendance, mother’s and father’s education levels. At the result of the study, while it was found that children’s mathematics skills differ from age, state of attending any preschool educational intuitions , time of attending any preschool educational intuitions, level of education of their mothers and their fathers; it was found that it does not differ by the gender and type of school they attend.

Keywords: preschool education, preschool period children, mathematics education, mathematics concept acquisitions

Procedia PDF Downloads 350

Authors: Muhammad Rizwan, Naveed Ahmad, Akhtar Naeem Khan

Abstract:

Seismic behavior factors are evaluated for the performance assessment of low rise reinforced concrete RC frame structures based on experimental study of unidirectional dynamic shake table testing of two 1/3rd reduced scaled two storey frames, with a code confirming special moment resisting frame (SMRF) model and a noncompliant model of similar characteristics but built in low strength concrete .The models were subjected to a scaled accelerogram record of 1994 Northridge earthquake to deformed the test models to final collapse stage in order to obtain the structural response parameters. The fully compliant model was observed with more stable beam-sway response, experiencing beam flexure yielding and ground-storey column base yielding upon subjecting to 100% of the record. The response modification factor - R factor obtained for the code complaint and deficient prototype structures were 7.5 and 4.5 respectively, which is about 10% and 40% less than the UBC-97 specified value for special moment resisting reinforced concrete frame structures.

Keywords: Northridge 1994 earthquake, reinforced concrete frame, response modification factor, shake table testing

Procedia PDF Downloads 173

Authors: Melissa Ramirez, Mohammad Awal

Abstract:

The Inflow Performance Relationship (IPR) of a well is a relation between the oil production rate and flowing bottom-hole pressure. This relationship is an important tool for petroleum engineers to understand and predict the well performance. In the petroleum industry, IPR correlations are used to design and evaluate well completion, optimizing well production, and designing artificial lift. The most commonly used IPR correlations models are Vogel and Wiggins, these models are applicable to homogeneous and isotropic reservoir data. In this work, a new IPR model is developed to determine inflow performance relationship of oil wells in a naturally fracture reservoir. A 3D black-oil reservoir simulator is used to develop the oil mobility function for the studied reservoir. Based on simulation runs, four flow rates are run to record the oil saturation and calculate the relative permeability for a naturally fractured reservoir. The new method uses the result of a well test analysis along with permeability and pressure-volume-temperature data in the fluid flow equations to obtain the oil mobility function. Comparisons between the new method and two popular correlations for non-fractured reservoirs indicate the necessity for developing and using an IPR correlation specifically developed for a fractured reservoir.

Keywords: inflow performance relationship, mobility function, naturally fractured reservoir, well test analysis

Procedia PDF Downloads 283

Authors: Oluwlola Felicia Kikelomo

Abstract:

This study examined the influence of Tertiary Education Trust Fund (TETF) intervention projects and resource utilization in universities in South Western State of Nigeria. The study was a descriptive design of the correlation type. Purposive sampling technique was used to select six out of 14 beneficiary universities in the States. Instruments used to collect data were TETF Intervention Projects Checklist (TETFIPC), Educational Facilities Checklists (EFC) and Resources Utilization Checklists (RUC). The research questions raised were answered using percentage and utilization rates, while Pearson product-moment correlation statistic was used to test the hypotheses formulated to guide the study 0.05 level of significance. Findings of the study indicated that building construction had the highest TETF allocation (64.5%), while staff development opportunities had the least (1.1%) in the sampled universities. Significant and positive relationship existed between time and space utilization rates and student academic performance in the universities (r (1,800) = 0.63 and r (1,800) = 0.59, p ≤ 0.05 respectively). Based, on these findings, it was recommended that there should be periodic evaluation of completed TETF projects and utilization to ensure that TETF funds are properly used for the approved projects; and that TETF should improve on the provision of educational facilities to universities for staff and students’ use through increase in education tax from 2% to 4% with collaboration with the world bank and other funding agencies as being practiced in other countries of the world such as Norway, Spain, and United Kingdom.

Keywords: tertiary education trust fund, intervention, education, human development

Procedia PDF Downloads 381

Authors: Mohammad Rawashdeh, Mark McEntee, Maha Zaitoun, Mostafa Abdelrahman, Patrick Brennan, Haytham Alewaidat, Sarah Lewis, Charbel Saade

Abstract:

Despite the tremendous advancements that have been generated by Computed Tomography (CT) in the field of diagnosis, concerns have been raised about the potential cancer induction risk from CT because of the exponentially increased use of it in medicine. This study aims at investigating the application and knowledge of practicing radiographers in Jordan about CT radiation. In order to collect the primary data of this study, a questionnaire was designed and distributed by social media using a snow-balling sampling method. The respondents (n=54) have answered 36 questions including the questions about their demographic information, knowledge about Diagnostic Reference Levels (DRLs), CT exposure and adaptation of pediatric patients exposure. The educational level of the respondents was either at a diploma degree (35.2%) or bachelor (64.8%). The results of this study have indicated a good level of general knowledge between radiographers about the relationship between image quality, exposure parameters, and patient dose. The level of knowledge related to DRL was poor where less than 7.4 percent of the sample members were able to give specific values for a number of common anatomical fields, including abdomen, brain, and chest. Overall, Jordanian radiographers need to gain more knowledge about the expected levels of the dose when applying good practice. Additional education on DRL or DRL inclusion in educational programs is highlighted.

Keywords: computed tomography, CT scan, DRLs, exposure parameters, image quality, radiation dose

Procedia PDF Downloads 144

Authors: Andreas Stollwitzer, Lara Bettinelli, Josef Fink

Abstract:

The expansion of the high-speed rail network over the past decades has resulted in new challenges for engineers, including traffic-induced resonance vibrations of railway bridges. Excessive resonance-induced speed-dependent accelerations of railway bridges during high-speed traffic can lead to negative consequences such as fatigue symptoms, distortion of the track, destabilisation of the ballast bed, and potentially even derailment. A realistic prognosis of bridge vibrations during high-speed traffic must not only rely on the right choice of an adequate calculation model for both bridge and train but first and foremost on the use of dynamic model parameters which reflect reality appropriately. However, comparisons between measured and calculated bridge vibrations are often characterised by considerable discrepancies, whereas dynamic calculations overestimate the actual responses and therefore lead to uneconomical results. This gap between measurement and calculation constitutes a complex research issue and can be traced to several causes. One major cause is found in the dynamic properties of the ballasted track, more specifically in the persisting, substantial uncertainties regarding the consideration of the ballasted track (mechanical model and input parameters) in dynamic calculations. Furthermore, the discrepancy is particularly pronounced concerning the damping values of the bridge, as conservative values have to be used in the calculations due to normative specifications and lack of knowledge. By using a large-scale test facility, the analysis of the dynamic behaviour of ballasted track has been a major research topic at the Institute of Structural Engineering/Steel Construction at TU Wien in recent years. This highly specialised test facility is designed for isolated research of the ballasted track's dynamic stiffness and damping properties – independent of the bearing structure. Several mechanical models for the ballasted track consisting of one or more continuous spring-damper elements were developed based on the knowledge gained. These mechanical models can subsequently be integrated into bridge models for dynamic calculations. Furthermore, based on measurements at the test facility, model-dependent stiffness and damping parameters were determined for these mechanical models. As a result, realistic mechanical models of the railway bridge with different levels of detail and sufficiently precise characteristic values are available for bridge engineers. Besides that, this contribution also presents another practical application of such a bridge model: Based on the bridge model, determination equations for the damping factor (as Lehr's damping factor) can be derived. This approach constitutes a first-time method that makes the damping factor of a railway bridge calculable. A comparison of this mathematical approach with measured dynamic parameters of existing railway bridges illustrates, on the one hand, the apparent deviation between normatively prescribed and in-situ measured damping factors. On the other hand, it is also shown that a new approach, which makes it possible to calculate the damping factor, provides results that are close to reality and thus raises potentials for minimising the discrepancy between measurement and calculation.

Keywords: ballasted track, bridge dynamics, damping, model design, railway bridges

Procedia PDF Downloads 164

Authors: Smita Singh

Abstract:

Objective: The Faculty of Chemistry Education at Humboldt University has developed ‘Studium’, a web application designed to enhance long-term self-regulated learning (SRL) and academic achievement. Leveraging advanced generative AI, ‘Studium’ offers a dynamic and adaptive educational experience tailored to individual learning preferences and languages. The application includes evolving tools for personalized notetaking from preferred sources, customizable presentation capabilities, and AI-assisted guidance from academic documents or textbooks. It also features workflow automation and seamless integration with collaborative platforms like Miro, powered by AI. This study aims to propose a model that combines generative AI with traditional features and customization options, empowering students to create personalized learning environments that effectively address the challenges of SRL. Method: To achieve this, the study included graduate and undergraduate students from diverse subject streams, with 15 participants each from Germany and India, ensuring a diverse educational background. An exploratory design was employed using a speed dating method with enactment, where different scenario sessions were created to allow participants to experience various features of ‘Studium’. The session lasted for 50 minutes, providing an in-depth exploration of the platform's capabilities. Participants interacted with Studium’s features via Zoom conferencing and were then engaged in semi-structured interviews lasting 10-15 minutes to gain deeper insights into the effectiveness of ‘Studium’. Additionally, online questionnaire surveys were conducted before and after the session to gather feedback and evaluate satisfaction with self-regulated learning (SRL) after using ‘Studium’. The response rate of this survey was 100%. Results: The findings of this study indicate that students widely acknowledged the positive impact of ‘Studium’ on their learning experience, particularly its adaptability and intuitive design. They expressed a desire for more tools like ‘Studium’ to support self-regulated learning in the future. The application significantly fostered students' independence in organizing information and planning study workflows, which in turn enhanced their confidence in mastering complex concepts. Additionally, ‘Studium’ promoted strategic decision-making and helped students overcome various learning challenges, reinforcing their self-regulation, organization, and motivation skills. Conclusion: This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like “Studium” can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners. This proposed model emphasizes the need for effective integration of personalized AI tools into active learning and SRL environments. By addressing key research questions, our framework aims to demonstrate how AI-assisted platforms like ‘Studium’ can facilitate deeper understanding, maintain student motivation, and support the achievement of academic goals. Thus, our ideal model for AI-assisted educational platforms provides a strategic approach to enhance student's learning experiences and promote their development as self-regulated learners.

Keywords: self-regulated learning (SRL), generative AI, AI-assisted educational platforms

Procedia PDF Downloads 29

Authors: Yung C. Lin, Kung D. Wu, Wei C. Shih, Jui P. Hung

Abstract:

High speed and high precision machining have become the most important technology in manufacturing industry. The surface roughness of high precision components is regarded as the important characteristics of the product quality. However, machining chatter could damage the machined surface and restricts the process efficiency. Therefore, selection of the appropriate cutting conditions is of importance to prevent the occurrence of chatter. In addition, vibration of the spindle tool also affects the surface quality, which implies the surface precision can be controlled by monitoring the vibration of the spindle tool. Based on this concept, this study was aimed to investigate the influence of the machining conditions on the surface roughness and the vibration of the spindle tool. To this end, a series of machining tests were conducted on aluminum alloy. In tests, the vibration of the spindle tool was measured by using the acceleration sensors. The surface roughness of the machined parts was examined using white light interferometer. The response surface methodology (RSM) was employed to establish the mathematical models for predicting surface finish and tool vibration, respectively. The correlation between the surface roughness and spindle tool vibration was also analyzed by ANOVA analysis. According to the machining tests, machined surface with or without chattering was marked on the lobes diagram as the verification of the machining conditions. Using multivariable regression analysis, the mathematical models for predicting the surface roughness and tool vibrations were developed based on the machining parameters, cutting depth (a), feed rate (f) and spindle speed (s). The predicted roughness is shown to agree well with the measured roughness, an average percentage of errors of 10%. The average percentage of errors of the tool vibrations between the measurements and the predictions of mathematical model is about 7.39%. In addition, the tool vibration under various machining conditions has been found to have a positive influence on the surface roughness (r=0.78). As a conclusion from current results, the mathematical models were successfully developed for the predictions of the surface roughness and vibration level of the spindle tool under different cutting condition, which can help to select appropriate cutting parameters and to monitor the machining conditions to achieve high surface quality in milling operation.

Keywords: machining parameters, machining stability, regression analysis, surface roughness

Procedia PDF Downloads 231

Authors: Zeyad Suleiman Bataineh

Abstract:

Introduction: civilian wars are associated with severe humanitarian effects that include loss of individuals and properties. Psychological dimensions are also included depression. Objectives: the main objectives of the present study were to investigate the depression level among Syrian patients who visited internal medicine clinics and other related variables. Methods and subjects: this study was conducted based on cross sectional study design. A total of 175 patients were involved. Patients were asked to fill a questionnaire to assess the level of depression that include demographic variables such as gender, age, educational level, and social status. Beck Aaron scale for depression was used. Participation in this study was voluntary, and all patients were informed about their rights to withdraw from the study without being negatively affected. Data were entered into excel spreading sheet for all participants. SPSS version 21 was used to analyze data. Data were described as means, the standard deviation for linear variables, frequencies, and percentages for categorical variables. The relationships between variables were evaluated using independent t test and One Way ANOVA test. Significance was considered at α≤0.05. Results: Depression was found in 152 (87%) of participants. The majority of participants with depression had moderate to severe depression. Depression was significantly associated gender, age, educational level, and social status (p<0.05). Conclusion: psychological rehabilitation is required for patients who experienced civilian wars.

Keywords: mental health, deprssion, health system, psychological dimension

Procedia PDF Downloads 128

Authors: Omar Qaftan

Abstract:

Earthquakes can cause tremendous loss of human life and can result in severe damage to a several of civil engineering structures especially the tall buildings. The response of a multistory structure subjected to earthquake loading is a complex task, and it requires to be studied by physical and numerical modelling. For many circumstances, the scale models on shaking table may be a more economical option than the similar full-scale tests. A shaking table apparatus is a powerful tool that offers a possibility of understanding the actual behaviour of structural systems under earthquake loading. It is required to use a set of scaling relations to predict the behaviour of the full-scale structure. Selecting the scale factors is the most important steps in the simulation of the prototype into the scaled model. In this paper, the principles of scaling modelling procedure are explained in details, and the simulation of scaled multi-storey concrete structure for dynamic studies is investigated. A procedure for a complete dynamic simulation analysis is investigated experimentally and numerically with a scale factor of 1/50. The frequency domain accounting and lateral displacement for both numerical and experimental scaled models are determined. The procedure allows accounting for the actual dynamic behave of actual size porotype structure and scaled model. The procedure is adapted to determine the effects of the tall multi-storey structure on a raft foundation. Four generated accelerograms were used as inputs for the time history motions which are in complying with EC8. The output results of experimental works expressed regarding displacements and accelerations are compared with those obtained from a conventional fixed-base numerical model. Four-time history was applied in both experimental and numerical models, and they concluded that the experimental has an acceptable output accuracy in compare with the numerical model output. Therefore this modelling methodology is valid and qualified for different shaking table experiments tests.

Keywords: structure, raft, soil, interaction

Procedia PDF Downloads 136

Authors: Chun-Lang Chang, Chun-Kai Liu

Abstract:

In this study, the patients that have undergone total knee replacement surgery from the 2010 National Health Insurance database were adopted as the study participants. The important factors were screened and selected through literature collection and interviews with physicians. Through the Cross Entropy Method (CE), Genetic Algorithm Logistic Regression (GALR), and Particle Swarm Optimization (PSO), the weights of the factors were obtained. In addition, the weights of the respective algorithms, coupled with the Excel VBA were adopted to construct the Case Based Reasoning (CBR) system. The results through statistical tests show that the GALR and PSO produced no significant differences, and the accuracy of both models were above 97%. Moreover, the area under the curve of ROC for these two models also exceeded 0.87. This study shall serve as a reference for medical staff as an assistance for clinical assessment of infections in order to effectively enhance medical service quality and efficiency, avoid unnecessary medical waste, and substantially contribute to resource allocations in medical institutions.

Keywords: Case Based Reasoning, Cross Entropy Method, Genetic Algorithm Logistic Regression, Particle Swarm Optimization, Total Knee Replacement Surgery

Procedia PDF Downloads 322

Authors: Syazreen N. Shair, Saiful A. Ishak, Aida Y. Yusof, Azizah Murad

Abstract:

In this paper, we forecast age-specific Malaysian mortality rates and life expectancy at births by gender and ethnic groups including Malay, Chinese and Indian. Two mortality forecasting models are adopted the original Lee-Carter model and its recent modified version, the product ratio coherent model. While the first forecasts the mortality rates for each subpopulation independently, the latter accounts for the relationship between sub-populations. The evaluation of both models is performed using the out-of-sample forecast errors which are mean absolute percentage errors (MAPE) for mortality rates and mean forecast errors (MFE) for life expectancy at births. The best model is then used to perform the long-term forecasts up to the year 2030, the year when Malaysia is expected to become an aged nation. Results suggest that in terms of overall accuracy, the product ratio model performs better than the original Lee-Carter model. The association of lower mortality group (Chinese) in the subpopulation model can improve the forecasts of high mortality groups (Malay and Indian).

Keywords: coherent forecasts, life expectancy at births, Lee-Carter model, product-ratio model, mortality rates

Procedia PDF Downloads 219

Authors: Karim Hamidi Machekposhti, Hossein Sedghi

Abstract:

This study was designed to find the best stochastic model (using of time series analysis) for annual extreme streamflow (peak and maximum streamflow) of Karkheh River at Iran. The Auto-regressive Integrated Moving Average (ARIMA) model used to simulate these series and forecast those in future. For the analysis, annual extreme streamflow data of Jelogir Majin station (above of Karkheh dam reservoir) for the years 1958–2005 were used. A visual inspection of the time plot gives a little increasing trend; therefore, series is not stationary. The stationarity observed in Auto-Correlation Function (ACF) and Partial Auto-Correlation Function (PACF) plots of annual extreme streamflow was removed using first order differencing (d=1) in order to the development of the ARIMA model. Interestingly, the ARIMA(4,1,1) model developed was found to be most suitable for simulating annual extreme streamflow for Karkheh River. The model was found to be appropriate to forecast ten years of annual extreme streamflow and assist decision makers to establish priorities for water demand. The Statistical Analysis System (SAS) and Statistical Package for the Social Sciences (SPSS) codes were used to determinate of the best model for this series.

Keywords: stochastic models, ARIMA, extreme streamflow, Karkheh river

Procedia PDF Downloads 148

Authors: Ozgul Kartal, Wade Tillett, Lyn D. English

Abstract:

Despite its global significance in curricula, mathematical modeling encounters persistent disparities in recognition and emphasis within regular mathematics classrooms and teacher education across countries with diverse educational and cultural traditions, including variations in the perceived role of mathematical modeling. Over the past two decades, increased attention has been given to the integration of mathematical modeling into national curriculum standards in the U.S. and other countries. Therefore, the mathematics education research community has dedicated significant efforts to investigate various aspects associated with the teaching and learning of mathematical modeling, primarily focusing on exploring the applicability of modeling in schools and assessing students', teachers', and preservice teachers' (PTs) competencies and engagement in modeling cycles and processes. However, limited attention has been directed toward examining potential resistance hindering teachers and PTs from effectively implementing mathematical modeling. This study focuses on how PTs, without prior modeling experience, resist and/or embrace mathematical modeling and its pedagogy as they learn about models and modeling perspectives, navigate the modeling process, design and implement their modeling activities and lesson plans, and experience the pedagogy enabling modeling. Model eliciting activities (MEAs) were employed due to their high potential to support the development of mathematical modeling pedagogy. The mathematical modeling module was integrated into a mathematics methods course to explore how PTs embraced or resisted mathematical modeling and its pedagogy. The module design included reading, reflecting, engaging in modeling, assessing models, creating a modeling task (MEA), and designing a modeling lesson employing an MEA. Twelve senior undergraduate students participated, and data collection involved video recordings, written prompts, lesson plans, and reflections. An open coding analysis revealed acceptance and resistance toward teaching mathematical modeling. The study identified four overarching themes, including both acceptance and resistance: pedagogy, affordance of modeling (tasks), modeling actions, and adjusting modeling. In the category of pedagogy, PTs displayed acceptance based on potential pedagogical benefits and resistance due to various concerns. The affordance of modeling (tasks) category emerged from instances when PTs showed acceptance or resistance while discussing the nature and quality of modeling tasks, often debating whether modeling is considered mathematics. PTs demonstrated both acceptance and resistance in their modeling actions, engaging in modeling cycles as students and designing/implementing MEAs as teachers. The adjusting modeling category captured instances where PTs accepted or resisted maintaining the qualities and nature of the modeling experience or converted modeling into a typical structured mathematics experience for students. While PTs displayed a mix of acceptance and resistance in their modeling actions, limitations were observed in embracing complexity and adhering to model principles. The study provides valuable insights into the challenges and opportunities of integrating mathematical modeling into teacher education, emphasizing the importance of addressing pedagogical concerns and providing support for effective implementation. In conclusion, this research offers a comprehensive understanding of PTs' engagement with modeling, advocating for a more focused discussion on the distinct nature and significance of mathematical modeling in the broader curriculum to establish a foundation for effective teacher education programs.

Keywords: mathematical modeling, model eliciting activities, modeling pedagogy, secondary teacher education

Procedia PDF Downloads 65

Authors: Mehdi Behbahani, Sebastian Rible, Charles Moulinec, Yvan Fournier, Mike Nicolai, Paolo Crosetto

Abstract:

Computational Fluid Dynamics blood-flow simulations are increasingly used to develop and validate blood-contacting medical devices. This study shows that numerical simulations can provide additional and accurate estimates of relevant hemodynamic indicators (e.g., recirculation zones or wall shear stresses), which may be difficult and expensive to obtain from in-vivo or in-vitro experiments. The most recent FDA (Food and Drug Administration) benchmark consisted of a simplified centrifugal blood pump model that contains fluid flow features as they are commonly found in these devices with a clear focus on highly turbulent phenomena. The FDA centrifugal blood pump study is composed of six test cases with different volumetric flow rates ranging from 2.5 to 7.0 liters per minute, pump speeds, and Reynolds numbers ranging from 210,000 to 293,000. Within the frame of this study different turbulence models were tested including RANS models, e.g. k-omega, k-epsilon and a Reynolds Stress Model (RSM) and, LES. The partitioners Hilbert, METIS, ParMETIS and SCOTCH were used to create an unstructured mesh of 76 million elements and compared in their efficiency. Computations were performed on the JUQUEEN BG/Q architecture applying the highly parallel flow solver Code SATURNE and typically using 32768 or more processors in parallel. Visualisations were performed by means of PARAVIEW. Different turbulence models including all six flow situations could be successfully analysed and validated against analytical considerations and from comparison to other data-bases. It showed that an RSM represents an appropriate choice with respect to modeling high-Reynolds number flow cases. Especially, the Rij-SSG (Speziale, Sarkar, Gatzki) variant turned out to be a good approach. Visualisation of complex flow features could be obtained and the flow situation inside the pump could be characterized.

Keywords: blood flow, centrifugal blood pump, high performance computing, scalability, turbulence

Procedia PDF Downloads 382

Authors: Daniel Rosero, Johan S. Arana, Sebastian Arango, Alejandro Cruz, Isabel Gomez-Gutierrez, Peter Thomson

Abstract:

Santiago de Cali is located in the southwestern Colombia in a high seismic hazard zone. About 50% of the city is on the banks of the Cauca River, which is the second most important hydric affluent in the country and whose alluvial deposits contain potentially liquefiable sands. Among the methods used to study a site's liquefaction potential is the finite elements method which use constitutive models to simulate the soil response for different load types. Among the different constitutive models, the Modified UBCSand stands out to study the seismic behavior of sands, and especially the liquefaction phenomenon. In this paper, the dynamic behavior of a potentially liquefiable sand of Santiago de Cali is studied by cyclic triaxial and CPTu tests. Subsequently, the behavior of the sand is simulated using the Modified UBCSand constitutive model, whose parameters are calibrated using the results of cyclic triaxial and CPTu tests. The above with the aim of analyze the constitutive model applicability for studying the geotechnical problems associated to liquefaction in the city.

Keywords: constitutive model, cyclic triaxial test, dynamic behavior, liquefiable sand, modified ubcsand

Procedia PDF Downloads 272

Authors: Joseph Mouallem, Seyed Reza Amini Niaki, Norman Chavez-Cussy, Christian Costa Milioli, Fernando Eduardo Milioli

Abstract:

Sub-grid closures for filtered two-fluid models (fTFM) useful in large scale simulations (LSS) of riser flows can be derived from highly resolved simulations (HRS) with microscopic two-fluid modeling (mTFM). Accurate sub-grid closures require accurate mTFM formulations as well as accurate correlation of relevant filtered parameters to suitable independent variables. This article deals with both of those issues. The accuracy of mTFM is touched by assessing the impact of gas sub-grid turbulence over HRS filtered predictions. A gas turbulence alike effect is artificially inserted by means of a stochastic forcing procedure implemented in the physical space over the momentum conservation equation of the gas phase. The correlation issue is touched by introducing a three-filtered variable correlation analysis (three-marker analysis) performed under a variety of different macro-scale conditions typical or risers. While the more elaborated correlation procedure clearly improved accuracy, accounting for gas sub-grid turbulence had no significant impact over predictions.

Keywords: fluidization, gas-particle flow, two-fluid model, sub-grid models, filtered closures

Procedia PDF Downloads 124

Authors: Taras Agryzkov, Jose L. Oliver, Leandro Tortosa, Jose Vicent

Abstract:

This paper aims to demonstrate how network models can be used to understand and to deal with some aspects of urban complexity. As it is well known, the Theory of Architecture and Urbanism has been using for decades’ intellectual tools based on the ‘sciences of complexity’ as a strategy to propose theoretical approaches about cities and about architecture. In this sense, it is possible to find a vast literature in which for instance network theory is used as an instrument to understand very diverse questions about cities: from their commercial activity to their heritage condition. The contribution of this research consists in adding one step of complexity to this process: instead of working with one single primal graph as it is usually done, we will show how new network models arise from the consideration of two different primal graphs interacting in two layers. When we model an urban network through a mathematical structure like a graph, the city is usually represented by a set of nodes and edges that reproduce its topology, with the data generated or extracted from the city embedded in it. All this information is normally displayed in a single layer. Here, we propose to separate the information in two layers so that we can evaluate the interaction between them. Besides, both layers may be composed of structures that do not have to coincide: from this bi-layer system, groups of interactions emerge, suggesting reflections and in consequence, possible actions.

Keywords: graphs, mathematics, networks, urban studies

Procedia PDF Downloads 180

Authors: A. F. Suleimanov, A. B. Saduakassova, V. S. Pokrovsky, D. V. Vinnikov

Abstract:

Relevance: Epithelial ovarian cancer (EOC) is the most lethal gynecological malignancy, with relapse occurring in about 70% of advanced cases with poor prognoses. The aim of the study was to evaluate functional visceral fat activity (VAT) evaluated by ¹⁸F-fluorodeoxyglucose (¹⁸F-FDG) positron emission tomography/computed tomography (PET/CT) as a predictor of metastases in epithelial ovarian cancer (EOC). Materials and methods: We assessed 53 patients with histologically confirmed EOC who underwent ¹⁸F-FDG PET/CT after a surgical treatment and courses of chemotherapy. Age, histology, stage, and tumor grade were recorded. Functional VAT activity was measured by maximum standardized uptake value (SUVₘₐₓ) using ¹⁸F-FDG PET/CT and tested as a predictor of later metastases in eight abdominal locations (RE – Epigastric Region, RLH – Left Hypochondriac Region, RRL – Right Lumbar Region, RU – Umbilical Region, RLL – Left Lumbar Region, RRI – Right Inguinal Region, RP – Hypogastric (Pubic) Region, RLI – Left Inguinal Region) and pelvic cavity (P) in the adjusted regression models. We also identified the best areas under the curve (AUC) for SUVₘₐₓ with the corresponding sensitivity (Se) and specificity (Sp). Results: In both adjusted-for regression models and ROC analysis, ¹⁸F-FDG accumulation in RE (cut-off SUVₘₐₓ 1.18; Se 64%; Sp 64%; AUC 0.669; p = 0.035) could predict later metastases in EOC patients, as opposed to age, sex, primary tumor location, tumor grade, and histology. Conclusions: VAT SUVₘₐₓ is significantly associated with later metastases in EOC patients and can be used as their predictor.

Keywords: ¹⁸F-FDG, PET/CT, EOC, predictive value

Procedia PDF Downloads 64