Search results for: curriculum models

Authors: Mostafa ‘Neo’ Mohsenvand, Mohammad Rasool Izadi, Pattie Maes

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EEG-based biometrics (user identification) has been explored on small datasets of no more than 157 subjects. Here we show that the accuracy of modern supervised methods falls rapidly as the number of users increases to a few thousand. Moreover, supervised methods require a large amount of labeled data for training which limits their applications in real-world scenarios where acquiring data for training should not take more than a few minutes. We show that using contrastive learning for pre-training, it is possible to maintain high accuracy on a dataset of 2130 subjects while only using a fraction of labels. We compare 5 different self-supervised tasks for pre-training of the encoder where our proposed method achieves the accuracy of 96.4%, improving the baseline supervised models by 22.75% and the competing self-supervised model by 3.93%. We also study the effects of the length of the signal and the number of channels on the accuracy of the user-identification models. Our results reveal that signals from temporal and frontal channels contain more identifying features compared to other channels.

Keywords: brainprint, contrastive learning, electroencephalo-gram, self-supervised learning, user identification

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Authors: N. Paparisteidi, D. Rodamitou

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This article focuses on the skills development and path planning of students studying computer science in EPITECH: french private institute of Higher Education. The researchers examine students’ points of view and experience in a blended learning model based on a skills development curriculum. The study is based on the collection of four main categories of data: semi-participant observation, distribution of questionnaires, interviews, and analysis of internal school databases. The findings seem to indicate that a skills-based program on active learning enables students to develop their learning strategies as well as their personal skills and to actively engage in the creation of their career path and contribute to providing additional information to curricula planners and decision-makers about learning design in higher education.

Keywords: active learning, blended learning, higher education, skills development

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Authors: Ting Ye, Nhan Phan-Thien, Chwee Teck Lim, Lina Peng, Huixin Shi

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In biofluid flow systems, often the flow problems of fluids of complex structures, such as the flow of red blood cells (RBCs) through complex capillary vessels, need to be considered. In this paper, we aim to apply a particle-based method, Smoothed Dissipative Particle Dynamics (SDPD), to simulate the motion and deformation of RBCs in complex micro-tubes. We first present the theoretical models, including SDPD model, RBC-fluid interaction model, RBC deformation model, RBC aggregation model, and boundary treatment model. After that, we show the verification and validation of these models, by comparing our numerical results with the theoretical, experimental and previously-published numerical results. Finally, we provide some simulation cases, such as the motion and deformation of RBCs in rectangular, cylinder, curved, bifurcated, and constricted micro-tubes, respectively.

Keywords: aggregation, deformation, red blood cell, smoothed dissipative particle dynamics

Procedia PDF Downloads 174

Authors: Md Al Masum Bhuiyan, Maria C. Mariani, Osei K. Tweneboah

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In the present work, we develop a technique for estimating the volatility of financial time series by using stochastic differential equation. Taking the daily closing prices from developed and emergent stock markets as the basis, we argue that the incorporation of stochastic volatility into the time-varying parameter estimation significantly improves the forecasting performance via Maximum Likelihood Estimation. While using the technique, we see the long-memory behavior of data sets and one-step-ahead-predicted log-volatility with ±2 standard errors despite the variation of the observed noise from a Normal mixture distribution, because the financial data studied is not fully Gaussian. Also, the Ornstein-Uhlenbeck process followed in this work simulates well the financial time series, which aligns our estimation algorithm with large data sets due to the fact that this algorithm has good convergence properties.

Keywords: financial time series, maximum likelihood estimation, Ornstein-Uhlenbeck type models, stochastic volatility model

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Authors: Florian Pfeffel, Valentin Nickolai, Christian Louis Kühner

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Digitalization has disrupted the traditional workplace environment by allowing many employees to work from anywhere at any time. This trend of working from home was further accelerated due to the COVID-19 crisis, which forced companies to rethink their workplace models. While in many companies, this shift happened out of pure necessity; many employees were left more satisfied with their job due to the opportunity to work from home. This study focuses on employees’ job satisfaction in the service sector in dependence on the different work models, which are defined as a “work from home” model, the traditional “work in office” model, and a hybrid model. Using structural equation modeling (SEM), these three work models have been analyzed based on 13 influencing factors on job satisfaction that have been further summarized in the three groups “classic influencing factors”, “influencing factors changed by remote working”, and “new remote working influencing factors”. Based on the influencing factors on job satisfaction, a survey has been conducted with n = 684 employees in the service sector. Cronbach’s alpha of the individual constructs was shown to be suitable. Furthermore, the construct validity of the constructs was confirmed by face validity, content validity, convergent validity (AVE > 0.5: CR > 0.7), and discriminant validity. Additionally, confirmatory factor analysis (CFA) confirmed the model fit for the investigated sample (CMIN/DF: 2.567; CFI: 0.927; RMSEA: 0.048). The SEM-analysis has shown that the most significant influencing factor on job satisfaction is “identification with the work” with β = 0.540, followed by “Appreciation” (β = 0.151), “Compensation” (β = 0.124), “Work-Life-Balance” (β = 0.116), and “Communication and Exchange of Information” (β = 0.105). While the significance of each factor can vary depending on the work model, the SEM-analysis shows that the identification with the work is the most significant factor in all three work models and, in the case of the traditional office work model, it is the only significant influencing factor. The study shows that employees who work entirely remotely or have a hybrid work model are significantly more satisfied with their job, with a job satisfaction score of 5.0 respectively on a scale from 1 (very dissatisfied) to 7 (very satisfied), than employees do not have the option to work from home with a score of 4.6. This comes as a result of the lower identification with the work in the model without any remote working. Furthermore, the responses indicate that it is important to consider the individual preferences of each employee when it comes to the work model to achieve overall higher job satisfaction. Thus, it can be argued that companies can profit off of more motivation and higher productivity by considering the individual work model preferences, therefore, increasing the identification with the respective work.

Keywords: home-office, identification with work, job satisfaction, new work, remote work, structural equation modeling

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Authors: José Leandro Melgar Néris, Claudinéia Brazil, Luciane Teresa Salvi, Isabel Cristina Damin

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The impact the climate change is not recent, the main variable in the hydrological cycle is the sequence and shortage of a drought, which has a significant impact on the socioeconomic, agricultural and environmental spheres. This study aims to characterize and quantify, based on precipitation climatic projections, the rainy and dry events in the region of the Uruguay River Basin, through the Standardized Precipitation Index (SPI). The database is the image that is part of the Intercomparison of Model Models, Phase 5 (CMIP5), which provides condition prediction models, organized according to the Representative Routes of Concentration (CPR). Compared to the normal set of climates in the Uruguay River Watershed through precipitation projections, seasonal precipitation increases for all proposed scenarios, with a low climate trend. From the data of this research, the idea is that this article can be used to support research and the responsible bodies can use it as a subsidy for mitigation measures in other hydrographic basins.

Keywords: climate change, climatic model, dry events, precipitation projections

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Authors: Chantana Insra

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The research objective focuses on creating a prototype media of the tactile texture of muscles for educational institutes to help visually impaired students learn massage extra learning materials further than the ordinary curriculum. This media is designed as an extra learning material. The population in this study was 30 blinded students between 4th - 6th grades who were able to read Braille language. The research was conducted during the second semester in 2012 at The Bangkok School for the Blind. The method in choosing the population in the study was purposive sampling. The methodology of the research includes collecting data related to visually impaired people, the production of the tactile texture media, human anatomy and Thai traditional massage from literature reviews and field studies. This information was used for analyzing and designing 14 tactile texture pictures presented to experts to evaluate and test the media.

Keywords: blind, tactile texture, muscle, visual arts and design

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Authors: O. Akinola, R. Mustapha

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Obesity is the most serious long-term health problem currently facing adolescents and its prevalence increasing worldwide including developing countries. A cross-sectional study was carried out among age 11-19 years in both public and private school in the urban area of the state. The data was collected using pretest self-administered questionnaire; Anthropometric measurement was also used to examine their nutritional status. Obesity status were determined using BMI cut off point, the overweight was found to be 3.06% among female and 0.6% among male whereas the prevalence of obesity was 0.46% in female and non among male. 62.6% snack daily, fruit consumption pattern was low 0.6%, and 43.7% spend between 4-5 hours watching television daily after school. A positive association exists between the lifestyle and nutritional status of the respondents. Education effort to improve nutrition knowledge can be incorporated into course curriculum and focus on various components within the system when implementing preventive measure on obesity.

Keywords: adolescent, obesity, overweight, prevalence

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Authors: Zhihua Cao, Hongfei Zhao, Zhongneng Wu

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The development of polar-based agroforestry was necessary due to the influence of the timber market environment in China, which can promote the coordinated development of forestry and agriculture, and gain remarkable ecological, economic and social benefits. The main agroforestry models of the main poplar planting area in Huaibei plain and along the Yangtze River plain were carried out. 11 typical management models of poplar were selected to sum up: pure poplar forest, poplar-rape-soybean, poplar-wheat-soybean, poplar-rape-cotton, poplar-wheat, poplar-chicken, poplar-duck, poplar-sheep, poplar-Agaricus blazei, poplar-oil peony, poplar-fish, represented by M0-M10, respectively. 12 indexes related with economic, ecological and social benefits (annual average cost, net income, ratio of output to investment, payback period of investment, land utilization ratio, utilization ratio of light energy, improvement and system stability of ecological and production environment, product richness, labor capacity, cultural quality of labor force, sustainability) were screened out to carry on the comprehensive evaluation and analysis to 11 kinds of typical agroforestry models based on analytic hierarchy process (AHP). The results showed that the economic benefit of each agroforestry model was in the order of: M8 > M6 > M9 > M7 > M5 > M10 > M4 > M1 > M2 > M3 > M0. The economic benefit of poplar-A. blazei model was the highest (332, 800 RMB / hm²), followed by poplar-duck and poplar-oil peony model (109, 820RMB /hm², 5, 7226 RMB /hm²). The order of comprehensive benefit was: M8 > M4 > M9 > M6 > M1 > M2 > M3 > M7 > M5 > M10 > M0. The economic benefit and comprehensive benefit of each agroforestry model were higher than that of pure poplar forest. The comprehensive benefit of poplar-A. blazei model was the highest, and that of poplar-wheat model ranked second, while its economic benefit was not high. Next were poplar-oil peony and poplar-duck models. It was suggested that the model of poplar-wheat should be adopted in the plain along the Yangtze River, and the whole cycle mode of poplar-grain, popalr-A. blazei, or poplar-oil peony should be adopted in Huaibei plain, northern Anhui. Furthermore, wheat, rape, and soybean are the main crops before the stand was closed; the agroforestry model of edible fungus or Chinese herbal medicine can be carried out when the stand was closed in order to maximize the comprehensive benefit. The purpose of this paper is to provide a reference for forest farmers in the selection of poplar agroforestry model in the future and to provide the basic data for the sustainable and efficient study of poplar agroforestry in Anhui province, eastern China.

Keywords: agroforestry, analytic hierarchy process (AHP), comprehensive benefit, model, poplar

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Authors: Natacha Fery, Guilherme L. Dalledonne, Xiangyang Zheng, Cheng Tang, Roberto Mayerle

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A Decision Support System (DSS) for supporting decision makers in the management of the Shandong Peninsula has been developed. Emphasis has been given to coastal protection, coastal cage aquaculture and harbors. The investigations were done in the framework of a joint research project funded by the German Ministry of Education and Research (BMBF) and the Chinese Academy of Sciences (CAS). In this paper, a description of the DSS, the development of its components, and results of its application are presented. The system integrates in-situ measurements, process-based models, and a database management system. Numerical models for the simulation of flow, waves, sediment transport and morphodynamics covering the entire Bohai Sea are set up based on the Delft3D modelling suite (Deltares). Calibration and validation of the models were realized based on the measurements of moored Acoustic Doppler Current Profilers (ADCP) and High Frequency (HF) radars. In order to enable cost-effective and scalable applications, a database management system was developed. It enhances information processing, data evaluation, and supports the generation of data products. Results of the application of the DSS to the management of coastal protection, coastal cage aquaculture and harbors are presented here. Model simulations covering the most severe storms observed during the last decades were carried out leading to an improved understanding of hydrodynamics and morphodynamics. Results helped in the identification of coastal stretches subjected to higher levels of energy and improved support for coastal protection measures.

Keywords: coastal protection, decision support system, in-situ measurements, numerical modelling

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Authors: Mohd Asrul Affendi Bin Abdullah

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Sample size calculation is especially important for zero inflated models because a large sample size is required to detect a significant effect with this model. This paper verify how to present percentage of power approximation for categorical and then extended to zero inflated models. Wald test was chosen to determine power sample size of AIDS death rate because it is frequently used due to its approachability and its natural for several major recent contribution in sample size calculation for this test. Power calculation can be conducted when covariates are used in the modeling ‘excessing zero’ data and assist categorical covariate. Analysis of AIDS death rate study is used for this paper. Aims of this study to determine the power of sample size (N = 945) categorical death rate based on parameter estimate in the simulation of the study.

Keywords: power sample size, Wald test, standardize rate, ZINBDR

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Authors: Ajay Kumar, Shamily Jaggi

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In developing countries like India development of modern technologies has been a key determinant in accelerating industrialization and urbanization. But in the pursuit of rapid economic growth, development is considered a top priority, while environmental protection is not given the same importance. Thus, a number of industries sited haphazardly have been established, leading to a deterioration of natural resources like water, soil and air. As a result, environmental pollution is tremendously increasing due to industrialization and mechanization that are serving to fulfill the demands of the population. With the increasing population, demand for bricks for construction work is also increasing, establishing the brick industry as a growing industry. Brick production requires two main resources; water as a source of life, and soil, as a living environment. Water and soil conservation is a critical issue in areas facing scarcity of water and soil resources. The purpose of this review paper is to provide a brief overview of the theoretical frameworks used in the analysis of the adoption and/or acceptance of soil and water conservation practices in the brick industry. Different frameworks and models have been used in the analysis of the adoption and/or acceptance of new technologies and practices; these include the technology acceptance model, motivational model, theory of reasoned action, innovation diffusion theory, theory of planned behavior, and the unified theory of acceptance and use of technology. However, every model has some limitations, such as not considering environmental/contextual and economic factors that may affect the individual’s intention to perform a behavior. The paper concludes that in comparing other models, the UTAUT seems a better model for understanding the dynamics of acceptance and adoption of water and soil conservation practices.

Keywords: brick kiln, water conservation, soil conservation, unified theory of acceptance and use of technology, technology adoption

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Authors: Armineh Nourbakhsh, Sameena Shah, Carolyn Rose

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Layout-aware language models have been used to create multimodal representations for documents that are in image form, achieving relatively high accuracy in document understanding tasks. However, the large number of parameters in the resulting models makes building and using them prohibitive without access to high-performing processing units with large memory capacity. We propose an alternative approach that can create efficient representations without the need for a neural visual backbone. This leads to an 80% reduction in the number of parameters compared to the smallest SOTA model, widely expanding applicability. In addition, our layout embeddings are pre-trained on spatial and visual cues alone and only fused with text embeddings in downstream tasks, which can facilitate applicability to low-resource of multi-lingual domains. Despite using 2.5% of training data, we show competitive performance on two form understanding tasks: semantic labeling and link prediction.

Keywords: layout understanding, form understanding, multimodal document understanding, bias-augmented attention

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Authors: Yepeng Cheng, Yasuhiko Morimoto

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Customer relationship analysis is vital for retail stores, especially for supermarkets. The point of sale (POS) systems make it possible to record the daily purchasing behaviors of customers as an identification point of sale (ID-POS) database, which can be used to analyze customer behaviors of a supermarket. The customer value is an indicator based on ID-POS database for detecting the customer loyalty of a store. In general, there are many supermarkets in a city, and other nearby competitor supermarkets significantly affect the customer value of customers of a supermarket. However, it is impossible to get detailed ID-POS databases of competitor supermarkets. This study firstly focused on the customer value and distance between a customer's home and supermarkets in a city, and then constructed the models based on logistic regression analysis to analyze correlations between distance and purchasing behaviors only from a POS database of a supermarket chain. During the modeling process, there are three primary problems existed, including the incomparable problem of customer values, the multicollinearity problem among customer value and distance data, and the number of valid partial regression coefficients. The improved customer value, Huff’s gravity model, and inverse attractiveness frequency are considered to solve these problems. This paper presents three types of models based on these three methods for loyal customer classification and competitors’ influence analysis. In numerical experiments, all types of models are useful for loyal customer classification. The type of model, including all three methods, is the most superior one for evaluating the influence of the other nearby supermarkets on customers' purchasing of a supermarket chain from the viewpoint of valid partial regression coefficients and accuracy.

Keywords: customer value, Huff's Gravity Model, POS, Retailer

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Authors: Nasim Eslamirad, Mahdi Rasoulinezhad, Francesco De Luca, Sadok Ben Yahia, Kimmo Sakari Lylykangas, Francesco Pilla

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With the ongoing urbanization, cities face increasing environmental challenges impacting human well-being. To tackle these issues, data-driven approaches in urban analysis have gained prominence, leveraging urban data to promote sustainability. Integrating Machine Learning techniques enables researchers to analyze and predict complex environmental phenomena like Urban Heat Island occurrences in urban areas. This paper demonstrates the implementation of data-driven approach and interpretable Machine Learning algorithms with interpretability techniques to conduct comprehensive data analyses for sustainable urban design. The developed framework and algorithms are demonstrated for Tallinn, Estonia to develop sustainable urban strategies to mitigate urban heat waves. Geospatial data, preprocessed and labeled with UHI levels, are used to train various ML models, with Logistic Regression emerging as the best-performing model based on evaluation metrics to derive a mathematical equation representing the area with UHI or without UHI effects, providing insights into UHI occurrences based on buildings and urban features. The derived formula highlights the importance of building volume, height, area, and shape length to create an urban environment with UHI impact. The data-driven approach and derived equation inform mitigation strategies and sustainable urban development in Tallinn and offer valuable guidance for other locations with varying climates.

Keywords: data-driven approach, machine learning transparent models, interpretable machine learning models, urban heat island effect

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Authors: Mais Khader, Xingjie Wei

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This research sheds light on female entrepreneurs by providing new insights on the survival predictions of companies led by females in the UK. This study aims to build a predictive machine learning model of the survival of female-led & co-led small & medium enterprises (SMEs) in the UK over the period 2000-2020. The predictive model built utilised a combination of financial and non-financial features related to both companies and their directors to predict SMEs' survival. These features were studied in terms of their contribution to the resultant predictive model. Five machine learning models are used in the modelling: Decision tree, AdaBoost, Naïve Bayes, Logistic regression and SVM. The AdaBoost model had the highest performance of the five models, with an accuracy of 73% and an AUC of 80%. The results show high feature importance in predicting companies' survival for company size, management experience, financial performance, industry, region, and females' percentage in management.

Keywords: company survival, entrepreneurship, females, machine learning, SMEs

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Authors: Aisha Alshdefat, Lina Shakman

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Objective: With environmental sustainability (ES) emerging as a critical concern due to its global impact, higher education institutions play a vital role in promoting ES through curricula and campus operations. This study examines the perceptions, attitudes, and behaviors related to ES among students at Sultan Qaboos University, aiming to identify areas for improved integration of sustainability practices in higher education. Design: A descriptive cross-sectional study, conducted via an online questionnaire, examines perceptions and attitudes toward environmental sustainability among students at Sultan Qaboos University, Muscat, Oman. The survey instrument employs a 5-point Likert scale to assess six key areas: awareness, concern, attitude, willingness to participate, current behaviors, and recommendations for enhancing campus sustainability initiatives. A convenience sample of 200 students was initially targeted, with 157 students ultimately responding between September and November 2024. Eligible participants included Undergraduate and graduate students who consented after being fully informed of the study objectives and design were included, while those who withdrew or refused participation were excluded. Following ethical approval, data collection was carried out through Google Forms. SPSS Version 23 was used for descriptive and inferential analyses, including Pearson’s correlation, chi-square, and Fisher's exact test, to explore associations among key variables. Findings: Preliminary analysis indicates that 68% of participants are familiar with core environmental sustainability (ES) concepts, including the Sustainable Development Goals (SDGs), and express high concern regarding environmental issues. However, only 47% report active involvement in campus-led ES initiatives, underscoring an engagement gap. Over 70% of respondents believe that sustainability should be prioritized as a university policy, and 62% expressed willingness to participate in additional ES-related programs. Despite this interest, 58% advocated for more sustainability-focused courses in their curriculum, suggesting current offerings are insufficient. Statistical analysis revealed a significant positive correlation between ES awareness and willingness to engage in sustainable practices (p < 0.05). These findings highlight the need for expanded institutional efforts, including targeted programs and curriculum integration, to cultivate a more sustainability-centered culture among students. Conclusion: The results emphasize that while students demonstrate a strong foundational awareness of ES, greater institutional support is essential to transform this awareness into active engagement. More comprehensive integration of sustainability within academic programs and campus life could substantially enhance students’ involvement and commitment to environmental stewardship.

Keywords: environmental sustainability, higher education, students, perceptions, Sultan Qaboos University.

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Authors: Ya-Li Tsai

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Nitrogen is a vital element crucial for crop growth, significantly influencing crop yield. In rice cultivation, farmers often apply substantial nitrogen fertilizer to maximize yields. However, excessive nitrogen application increases the risk of lodging and pest infestation, leading to yield losses. Additionally, conventional flooded irrigation methods consume significant water resources, necessitating precise agricultural and intelligent water management systems. In this study, it leveraged physiological data and field images captured by unmanned aerial vehicles, considering fertilizer treatment and irrigation as key factors. Statistical models incorporating rice physiological data, yield, and vegetation indices from image data were developed. Missing physiological data were addressed using multiple imputation and regression methods, and regression models were established using principal component analysis and stepwise regression. Target nitrogen accumulation at key growth stages was identified to optimize fertilizer application, with the difference between actual and target nitrogen accumulation guiding recommendations for ear dressing dosage. Field experiments conducted in 2022 validated the recommended ear dressing dosage, demonstrating no significant difference in final yield compared to traditional fertilizer levels under alternate wetting and drying irrigation. These findings highlight the efficacy of applying recommended dosages based on fertilizer decision models, offering the potential for reduced fertilizer use while maintaining yield in rice cultivation.

Keywords: intelligent fertilizer management, nitrogen top and ear dressing fertilizer, rice, yield optimization

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Authors: Amro Issam Hamed Attia Ramadan, Marco Zappatore, Pasquale Balena, Antonella Longo

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Considering the energetic crisis that is hitting Europe, it becomes more and more necessary to change the energy policies to depend less on fossil fuels and replace them with energy from renewable sources. This has triggered the urge to use clean energy not only to satisfy energy needs and fulfill the required consumption but also to decrease the danger of climatic changes due to harmful emissions. Many countries have already started creating energetic communities based on renewable energy sources. The first step to understanding energy needs in any place is to perfectly know the consumption. In this work, we aim to estimate electricity consumption for a municipality that makes up part of a rural area located in southern Italy using forecast models that allow for the estimation of electricity consumption for the next ten years, and we then apply the same model to the province where the municipality is located and estimate the future consumption for the same period to examine whether it is possible to start from the municipality level to reach the province level when creating energy communities.

Keywords: ARIMA, electricity consumption, forecasting models, time series

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Authors: Farha Sattar, Laurence Tamatea, Muhammad Nawaz

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Drones, the Unmanned Aerial Vehicles are playing an important role in real-world problem-solving. With the new advancements in technology, drones are becoming available, affordable and user- friendly. Use of drones in education is opening new trends in teaching and learning practices in an innovative and engaging way. Drones vary in types and sizes and possess various characteristics and capabilities which enhance their potential to be used in education from basic to advanced and challenging learning activities which are suitable for primary, middle and high school level. This research aims to provide an insight to explore different types of drones and their compatibility to be used in teaching different subjects at various levels. Research focuses on integrating the drone technology along with Australian curriculum content knowledge to reinforce the understanding of the fundamental concepts and helps to develop the critical thinking and reasoning in the learning process.

Keywords: critical thinking, drone technology, drone types, innovative learning

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Authors: Martin Cermak, Tomas Karasek, Jaroslav Rojicek

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The key role in phenomenological modelling of cyclic plasticity is good understanding of stress-strain behaviour of given material. There are many models describing behaviour of materials using numerous parameters and constants. Combination of individual parameters in those material models significantly determines whether observed and predicted results are in compliance. Parameter identification techniques such as random gradient, genetic algorithm, and sensitivity analysis are used for identification of parameters using numerical modelling and simulation. In this paper genetic algorithm and sensitivity analysis are used to study effect of 4 parameters of modified AbdelKarim-Ohno cyclic plasticity model. Results predicted by Finite Element (FE) simulation are compared with experimental data from biaxial ratcheting test with semi-elliptical loading path.

Keywords: genetic algorithm, sensitivity analysis, inverse approach, finite element method, cyclic plasticity, ratcheting

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Authors: Nitin Joseph

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Objectives: This study was done to assess emotional intelligence levels and to find out its association with socio demographic variables and perceived stress among medical students. Material and Methods: This study was done among first and second year medical students. Data was collected using a self-administered questionnaire. Results: Emotional intelligence scores was found to significantly increase with age of the participants (F=2.377, P < 0.05). Perceived stress was found to be significantly more among first year (t=1.997, P=0.05). Perceived stress was found to significantly decrease with increasing emotional intelligence scores (r = – 0.226, P < 0.001). Conclusion: First year students were found to be more vulnerable to stress than their seniors probably due to lesser emotional intelligence. As both these parameters are related, ample measures to improve emotional intelligence needs to be supported in the training curriculum of beginners so as to make them more stress free during early student life.

Keywords: emotional intelligence, medical students, perceived stress, socio demographic variables

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Authors: Alejandra Sierra, Gloria Valadez, Adriana Dávalos, Mirliana Ramírez

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For years, the Pan American Health Organization/World Health Organization and other organizations have made efforts to the improve access and the quality of prenatal care as part of comprehensive programs for maternal and neonatal health, the standards of care have been renewed in order to migrate from a medical perspective to a holistic perspective. However, despite the efforts currently antenatal care models have not been verified by a scientific evaluation in order to determine their effectiveness. The teenage pregnancy is considered as a very important phenomenon since it has been strongly associated with inequalities, poverty and the lack of gender quality; therefore it is important to analyze the antenatal care that’s been given, including not only the clinical intervention but also the activities surrounding the advertising and the health education. In this study, the objective was to describe if the previously established activities (on the prenatal care models) are being performed in the care of pregnant teenagers attending prenatal care in health institutions in two cities in México and Chile during 2013. Methods: Observational and descriptive study, of a transversal cohort. 170 pregnant women (13-19 years) were included in prenatal care in two health institutions (100 women from León-Mexico and 70 from Chile-Coquimbo). Data collection: direct survey, perinatal clinical record card which was used as checklists: WHO antenatal care model WHO-2003, Official Mexican Standard NOM-007-SSA2-1993 and Personalized Service Manual on Reproductive Process- Chile Crece Contigo; for data analysis descriptive statistics were used. The project was approved by the relevant ethics committees. Results: Regarding the fulfillment of interventions focused on physical, gynecological exam, immunizations, monitoring signs and biochemical parameters in both groups was met by more than 84%; the activities of guidance and counseling pregnant teenagers in Leon compliance rates were below 50%, on the other hand, although pregnant women in Coquimbo had a higher percentage of compliance, no one reached 100%. The topics that less was oriented were: family planning, signs and symptoms of complications and labor. Conclusions: Although the coverage of the interventions indicated in the prenatal care models was high, there were still shortcomings in the fulfillment of activities to orientation, education and health promotion. Deficiencies in adherence to prenatal care guidelines could be due to different circumstances such as lack of registration or incomplete filling of medical records, lack of medical supplies or health personnel, absences of people at prenatal check-up appointments, among many others. Therefore, studies are required to evaluate the quality of prenatal care and the effectiveness of existing models, considering the role of the different actors (pregnant women, professionals and health institutions) involved in the functionality and quality of prenatal care models, in order to create strategies to design or improve the application of a complete process of promotion and prevention of maternal and child health as well as sexual and reproductive health in general.

Keywords: adolescent health, health systems, maternal health, primary health care

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Authors: Owamah Hilary, O. C. Izinyon

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Many existing biogas kinetic models are difficult to apply to substrates they were not developed for, as they are substrate specific. Biodegradability kinetic (BIK) model and maximum biogas production potential and stability assessment (MBPPSA) model were therefore developed in this study for the anaerobic co-digestion of food waste and maize husk. Biodegradability constant (k) was estimated as 0.11d-1 using the BIK model. The results of maximum biogas production potential (A) obtained using the MBPPSA model corresponded well with the results obtained using the popular but complex modified Gompertz model for digesters B-1, B-2, B-3, B-4, and B-5. The (If) value of MBPPSA model also showed that digesters B-3, B-4, and B-5 were stable, while B-1 and B-2 were unstable. Similar stability observation was also obtained using the modified Gompertz model. The MBPPSA model can therefore be used as alternative model for anaerobic digestion feasibility studies and plant design.

Keywords: biogas, inoculum, model development, stability assessment

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Authors: Buddhi Arachchige, Hessam Ghasemnejad

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In this study, the post impact behavior of curved composite plates subjected to low velocity impact was studied analytically and numerically. Approaches to damage modelling are proposed through the degradation of stiffness in the damaged region by reduction of thickness in the damage region. Spring-mass models were used to model the impact response of the plate and impactor. The study involved designing two damage models to compare and contrast the model best fitted with the numerical results. The theoretical force-time responses were compared with the numerical results obtained through a detailed study carried out in LS-DYNA. The modified damage model established a good prediction with the analytical force-time response for different layups and geometry. This study provides a gateway in selecting the most effective layups for variable stiffness curved composite panels able to withstand a higher impact damage.

Keywords: analytical modelling, composite damage, impact, variable stiffness

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Authors: H. J. Joshi, Satyajeet Patil, Parth Dandavate, Mihir Kulkarni, Harshita Agrawal

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As the world looks towards a sustainable future, electric vehicles have become increasingly popular. Millions worldwide are looking to switch to Electric cars over the previously favored combustion engine-powered cars. This demand has seen an increase in Electric Vehicle Charging Stations. The big challenge is that the randomness of electrical energy makes it tough for these charging stations to provide an adequate amount of energy over a specific amount of time. Thus, it has become increasingly crucial to model these patterns and forecast the energy needs of power stations. This paper aims to analyze how different machine learning models perform on Electric Vehicle charging time-series data. The data set consists of authentic Electric Vehicle Data from the Netherlands. It has an overview of ten thousand transactions from public stations operated by EVnetNL.

Keywords: forecasting, smart grid, electric vehicle load forecasting, machine learning, time series forecasting

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Authors: Felipe M. de Freitas, Icaro V. Soares, Lucas L. L. Fortes, Sandro T. M. Gonçalves, Úrsula D. C. Resende

Abstract:

The SPICE-based simulators are quite robust and widely used for simulation of electronic circuits, their algorithms support linear and non-linear lumped components and they can manipulate an expressive amount of encapsulated elements. Despite the great potential of these simulators based on SPICE in the analysis of quasi-static electromagnetic field interaction, that is, at low frequency, these simulators are limited when applied to microwave hybrid circuits in which there are both lumped and distributed elements. Usually the spatial discretization of the FDTD (Finite-Difference Time-Domain) method is done according to the actual size of the element under analysis. After spatial discretization, the Courant Stability Criterion calculates the maximum temporal discretization accepted for such spatial discretization and for the propagation velocity of the wave. This criterion guarantees the stability conditions for the leapfrogging of the Yee algorithm; however, it is known that for the field update, the stability of the complete FDTD procedure depends on factors other than just the stability of the Yee algorithm, because the FDTD program needs other algorithms in order to be useful in engineering problems. Examples of these algorithms are Absorbent Boundary Conditions (ABCs), excitation sources, subcellular techniques, grouped elements, and non-uniform or non-orthogonal meshes. In this work, the influence of the stability of the FDTD method in the modeling of concentrated elements such as resistive sources, resistors, capacitors, inductors and diode will be evaluated. In this paper is proposed, therefore, the electromagnetic modeling of electronic components in order to create models that satisfy the needs for simulations of circuits in ultra-wide frequencies. The models of the resistive source, the resistor, the capacitor, the inductor, and the diode will be evaluated, among the mathematical models for lumped components in the LE-FDTD method (Lumped-Element Finite-Difference Time-Domain), through the parametric analysis of Yee cells size which discretizes the lumped components. In this way, it is sought to find an ideal cell size so that the analysis in FDTD environment is in greater agreement with the expected circuit behavior, maintaining the stability conditions of this method. Based on the mathematical models and the theoretical basis of the required extensions of the FDTD method, the computational implementation of the models in Matlab® environment is carried out. The boundary condition Mur is used as the absorbing boundary of the FDTD method. The validation of the model is done through the comparison between the obtained results by the FDTD method through the electric field values and the currents in the components, and the analytical results using circuit parameters.

Keywords: hybrid circuits, LE-FDTD, lumped element, parametric analysis

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Authors: Tin Thongthammachart, Wanida Jinsart

Abstract:

Atmospheric particulate matter particles with a diameter less than 10 microns (PM₁₀) and less than 2.5 microns (PM₂.₅) have adverse health effect. The impact from PM was studied from both health and regulatory perspective. Ambient PM data was collected over ten years in Bangkok and vicinity areas of Thailand from 2007 to 2017. Statistical models were used to forecast PM concentrations from 2018 to 2020. Monitoring monthly data averaged concentration of PM₁₀ and PM₂.₅ were used as input to forecast the monthly average concentration of PM. The forecasting results were validated by root means square error (RMSE). The predicted results were used to determine hazard risk for the carcinogenic disease. The health risk values were interpolated with GIS with ordinary kriging technique to create hazard maps in Bangkok and vicinity area. GIS-based maps illustrated the variability of PM distribution and high-risk locations. These evaluated results could support national policy for the sake of human health.

Keywords: PM₁₀, PM₂.₅, statistical models, atmospheric particulate matter

Procedia PDF Downloads 159

Authors: Dino Carpentras, Paul Maher, Caoimhe O'Reilly, Michael Quayle

Abstract:

Opinion dynamics is dedicated to modeling the dynamic evolution of people's opinions. Models in this field are based on a micro-dynamic rule, which determines how people update their opinion when interacting. Despite the high number of new models (many of them based on new rules), little research has been dedicated to experimentally validate the rule. A few studies started bridging this literature gap by experimentally testing the rule. However, in these studies, participants are forced to express their opinion as a number instead of using natural language. Furthermore, some of these studies average data from experimental questions, without testing if differences existed between them. Indeed, it is possible that different topics could show different dynamics. For example, people may be more prone to accepting someone's else opinion regarding less polarized topics. In this work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions using natural language ('agree' or 'disagree') and the certainty of their answer, expressed as a number between 1 and 10. To keep the interaction based on natural language, certainty was not shown to other participants. We then showed to the participant someone else's opinion on the same topic and, after a distraction task, we repeated the measurement. To produce data compatible with standard opinion dynamics models, we multiplied the opinion (encoded as agree=1 and disagree=-1) with the certainty to obtain a single 'continuous opinion' ranging from -10 to 10. By analyzing the topics independently, we observed that each one shows a different initial distribution. However, the dynamics (i.e., the properties of the opinion change) appear to be similar between all topics. This suggested that the same micro-dynamic rule could be applied to unpolarized topics. Another important result is that participants that change opinion tend to maintain similar levels of certainty. This is in contrast with typical micro-dynamics rules, where agents move to an average point instead of directly jumping to the opposite continuous opinion. As expected, in the data, we also observed the effect of social influence. This means that exposing someone with 'agree' or 'disagree' influenced participants to respectively higher or lower values of the continuous opinion. However, we also observed random variations whose effect was stronger than the social influence’s one. We even observed cases of people that changed from 'agree' to 'disagree,' even if they were exposed to 'agree.' This phenomenon is surprising, as, in the standard literature, the strength of the noise is usually smaller than the strength of social influence. Finally, we also built an opinion dynamics model from the data. The model was able to explain more than 80% of the data variance. Furthermore, by iterating the model, we were able to produce polarized states even starting from an unpolarized population. This experimental approach offers a way to test the micro-dynamic rule. This also allows us to build models which are directly grounded on experimental results.

Keywords: experimental validation, micro-dynamic rule, opinion dynamics, update rule

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Authors: Wendu Pang, Yaxin Luo, Junhong Li, Yu Zhao, Danni Cheng, Yufang Rao, Minzi Mao, Ke Qiu, Yijun Dong, Fei Chen, Jun Liu, Jian Zou, Haiyang Wang, Wei Xu, Jianjun Ren

Abstract:

We aimed to compare the prognostic prediction value of positive lymph node number (PLNN) to the American Joint Committee on Cancer (AJCC) tumor, lymph node, and metastasis (TNM) staging system for patients with hypopharyngeal squamous cell carcinoma (HPSCC). A total of 826 patients with HPSCC from the Surveillance, Epidemiology, and End Results database (2004–2015) were identified and split into two independent cohorts: training (n=461) and validation (n=365). Univariate and multivariate Cox regression analyses were used to evaluate the prognostic effects of PLNN in patients with HPSCC. We further applied six Cox regression models to compare the survival predictive values of the PLNN and AJCC TNM staging system. PLNN showed a significant association with overall survival (OS) and cancer-specific survival (CSS) (P < 0.001) in both univariate and multivariable analyses, and was divided into three groups (PLNN 0, PLNN 1-5, and PLNN>5). In the training cohort, multivariate analysis revealed that the increased PLNN of HPSCC gave rise to significantly poor OS and CSS after adjusting for age, sex, tumor size, and cancer stage; this trend was also verified by the validation cohort. Additionally, the survival model incorporating a composite of PLNN and TNM classification (C-index, 0.705, 0.734) performed better than the PLNN and AJCC TNM models. PLNN can serve as a powerful survival predictor for patients with HPSCC and is a surrogate supplement for cancer staging systems.

Keywords: hypopharyngeal squamous cell carcinoma, positive lymph nodes number, prognosis, prediction models, survival predictive values

Procedia PDF Downloads 154