Search results for: prophetic holistic model

Authors: Mário Ernesto Sitoe, Orlando Zacarias

Abstract:

University education is influenced by several factors that range from the adoption of strategies to strengthen the whole process to the academic performance improvement of the students themselves. This work uses data mining techniques to develop a predictive model to identify students with a tendency to evasion and retention. To this end, a database of real students’ data from the Department of University Admission (DAU) and the Department of Mathematics and Informatics (DMI) was used. The data comprised 388 undergraduate students admitted in the years 2009 to 2014. The Weka tool was used for model building, using three different techniques, namely: K-nearest neighbor, random forest, and logistic regression. To allow for training on multiple train-test splits, a cross-validation approach was employed with a varying number of folds. To reduce bias variance and improve the performance of the models, ensemble methods of Bagging and Stacking were used. After comparing the results obtained by the three classifiers, Logistic Regression using Bagging with seven folds obtained the best performance, showing results above 90% in all evaluated metrics: accuracy, rate of true positives, and precision. Retention is the most common tendency.

Keywords: evasion and retention, cross-validation, bagging, stacking

Procedia PDF Downloads 71

Authors: Susanna Graziano, Lydia Krstic Ward

Abstract:

The purpose of this presentation is to demonstrate the steps of using multimedia and collaborative platforms in project-based learning. The presentation will demonstrate the stages of the learning project with various components of independent and collaborative learning, where students research the topic, share information, prepare a survey, use social media (Facebook, Instagram, WhasApp) and collaborative platforms (wikispaces.com and Google docs) to collect, analyze and process data, then produce reports and logos to be displayed as a final product. At the beginning of the presentation participants will answer a questionnaire about project based learning and share their experience on using social media, real–world project work and collaborative learning. Using a PPP, the presentation will walk participants through the steps of a completed project where tertiary education students are involved in putting together a multimedia campaign for safe driving in Kuwait. The research component of the project entails taking a holistic view on the problem of the high death rate in traffic accidents. The final goal of the project is to lead students to raise public awareness about the importance of safe driving. The project steps involve using the social media and collaborative platforms for collecting data and sharing the required materials to be used in the final product – a display of written reports, slogans and videos, as well as oral presentations. The same structure can be used to organize a multimedia campaign focusing on other issues, whilst scaffolding on students’ ability to brainstorm, retrieve information, organize it and engage in collaborative/ cooperative learning whilst being immersed in content-based learning as well as in authentic tasks. More specifically, the project we carried out at Box Hill College was a real-world one and involved a multimedia Campaign for Safe Driving since reckless driving is one of the major problems in the country. The idea for the whole project started by a presentation given by a board member of the Kuwaiti Society for Traffic Safety who was invited to college and spoke about: • Driving laws in the country, • What causes car accidents, • Driving safety tips. The principal goal of this project was to let students consider problems of traffic in Kuwait from different points of view. They also had to address the number and causes of accidents, evaluate the effectiveness of the local traffic law in order to send a warning about the importance of safe driving and, finally, suggest ways of its improvement. Benefits included: • Engagement, • Autonomy, • Motivation, • Content knowledge, • Language mastery, • Enhanced critical thinking, • Increased metacognitive awareness, • Improved social skills, • Authentic experience.

Keywords: social media, online learning platforms, collaborative platforms, project based learning

Procedia PDF Downloads 415

Authors: Jennifer De Paola

Abstract:

Objectives: The literature is saturated with figures and hard data on happiness and its rates, causes and effects at a large scale, whereas very little is known about the way specific groups of people within societies understand and talk about happiness in their everyday life. The present study contributes to fill this gap in the happiness research by analyzing social representations of happiness among young women through the theoretical frame provided by Moscovici’s Social Representation Theory. Methods: Participants were (N= 351) female students (16-18 year olds) from Finnish, Swedish and English speaking high schools in the Helsinki region, Finland. Main source of data collection were word associations using the stimulus word ‘happiness’ and word associations using as stimulus the term that in the participants’ opinion represents the opposite of happiness. The allowed number of associations was five per stimulus word (10 associations per participant). In total, the 351 participants produced 6973 associations with the two stimulus words given: 3500 (50,19%) associations with ‘happiness’ and 3473 (49,81%) associations with ‘opposite of happiness’. The associations produced were analyzed qualitatively to identify associations with similar meaning and then coded combining similar associations in larger categories. Results: In total, 33 categories were identified respectively for the stimulus word ‘happiness’ and for the stimulus word ‘opposite of happiness’. In general terms, the 33 categories identified for ‘happiness’ included associations regarding relationships with key people considered important, such as ‘family’, abstract concepts such as meaningful life, success and moral values as well as more mundane and hedonic elements like food, pleasure and fun. Similarly, the 33 categories emerged for ‘opposite of happiness’ included relationship problems and arguments, negative feelings such as sadness, depression, stress as well as more concrete issues such as financial problems. Participants were also asked to rate their own level of happiness on a scale from 1 to 10. Results indicated the mean of the self-rated level of happiness was 7,93 (the range varied from 1 to 10; SD = 1, 50). Participants’ responses were further divided into three different groups according to the self-rated level of happiness: group 1 (level 10-9), group 2 (level 8-6), and group 3 (level 5 and lower) in order to investigate the way the categories mentioned above were distributed among the different groups. Preliminary results show that the category ‘family’ is associated with higher level of happiness, whereas its presence gradually decreases among the participants with a lower level of happiness. Moreover, the category ‘depression’ seems to be mainly present among participants in group 3, whereas the category ‘sadness’ is mainly present among participants with higher level of happiness. Conclusion: In conclusion, this study indicates the prevalent ways of thinking about happiness and its opposite among young female students, suggesting that representations varied to some extent depending on the happiness level of the participants. This study contributes to bringing new knowledge as it considers happiness as a holistic state, thus going beyond the literature that so far has too often viewed happiness as a mere unidimensional spectrum.

Keywords: female, happiness, social representations, unhappiness

Procedia PDF Downloads 217

Authors: Rehan Ali Shah, A. M. Siddiqui, T. Haroon

Abstract:

Slip boundary value problem in wire coating analysis with heat transfer is examined. The fluid is assumed to be viscoelastic PTT (Phan-Thien and Tanner). The rheological constitutive equation of PTT fluid model simulates various polymer melts. Therefore, the current consequences are valuable in a number of realistic situations. Effects of slip parameter γ as well as εDec^2 (viscoelastic index) on the axial velocity, shear stress, normal stress, average velocity, volume flux, thickness of coated wire, shear stress, force on the total wire and temperature distribution profiles have been investigated. A new direction is explored to analyze the flow with the slip parameter. The slippage at the boundaries plays an important role in thickness of coated wire. It is noted that as the slip parameter increases the flow rate and thickness of coated wire increases while, temperature distribution decreases. The results reduce to no slip when the slip parameter is vanished. Furthermore, we can obtain the results for Maxwell and viscous model by setting ε and λ equal to zero respectively.

Keywords: wire coating, straight annular die, PTT fluid, heat transfer, slip boundary conditions

Procedia PDF Downloads 355

Authors: Tzong-Shing Cheng, Chen Pei Chen, Shu-Wei Chen

Abstract:

The purpose of this research is to apply Unified Theory of Acceptance and Use of Technology (UTAUT) model to investigate the factors that influence elementary school teacher’s behavior of using e-books. Based on the literature review, a questionnaire was modified and used to test the elementary school teachers in Changhua. A total of 420 questionnaires were administered and 364 of them were returned, including 328 valid and 36 invalid questionnaires. The effective response rate is 78%. The methods of data analysis include descriptive statistics, factor analysis, Pearson’s correlation coefficient, one way analysis of variance (ANOVA) and simple regression analysis. The results show that: 1. There were significant difference in the Elementary school teachers’ “Performance Expectancy”, “Effort Expectancy”, “Social Influence”, and “Facilitating Conditions” depending on their different “Demographic Variables”. 2. “Performance Expectancy” and “Behavioral Intention to Use” are positively correlated. 3. “Effort Expectancy” and “Behavioral Intention to Use” are positively correlated. 4. There was no significant relationship between “Social Influence” and “Behavioral Intention to Use”. 5. There was significant relationship between “Facilitating Conditions” and “Use Behavior”.

Keywords: e-books, UTAUT, elementary school teacher, behavioral intention to use

Procedia PDF Downloads 600

Authors: S. Nandagopalan, N. Pradeep

Abstract:

The aim of this paper is to propose a general framework for storing, analyzing, and extracting knowledge from two-dimensional echocardiographic images, color Doppler images, non-medical images, and general data sets. A number of high performance data mining algorithms have been used to carry out this task. Our framework encompasses four layers namely physical storage, object identification, knowledge discovery, user level. Techniques such as active contour model to identify the cardiac chambers, pixel classification to segment the color Doppler echo image, universal model for image retrieval, Bayesian method for classification, parallel algorithms for image segmentation, etc., were employed. Using the feature vector database that have been efficiently constructed, one can perform various data mining tasks like clustering, classification, etc. with efficient algorithms along with image mining given a query image. All these facilities are included in the framework that is supported by state-of-the-art user interface (UI). The algorithms were tested with actual patient data and Coral image database and the results show that their performance is better than the results reported already.

Keywords: active contour, bayesian, echocardiographic image, feature vector

Procedia PDF Downloads 410

Authors: Aliya Grig, Konstantin Sokolov, Igor Shatalin

Abstract:

The report describes the methodology for collecting data and building an ML model for determining the personality psychotype using profiling and personality traits methods based on several short messages of a user communicating on an arbitrary topic with a chitchat bot. In the course of the experiments, the minimum amount of text was revealed to confidently determine aspects of personality. Model accuracy - 85%. Users' language of communication is English. AI for a personalized communication with a user based on his mood, personality, and current emotional state. Features investigated during the research: personalized communication; providing empathy; adaptation to a user; predictive analytics. In the report, we describe the processes that captures both structured and unstructured data pertaining to a user in large quantities and diverse forms. This data is then effectively processed through ML tools to construct a knowledge graph and draw inferences regarding users of text messages in a comprehensive manner. Specifically, the system analyzes users' behavioral patterns and predicts future scenarios based on this analysis. As a result of the experiments, we provide for further research on training AI models to be empathetic, creating personalized communication for a user

Keywords: AI, empathetic, chatbot, AI models

Procedia PDF Downloads 80

Authors: Omar Al Denali, Abdelaziz Badi

Abstract:

The ASTM A516 Grade 70 steel is a suitable material used for the fabrication of boiler pressure vessels working in moderate and lower temperature services, and it has good weldability and excellent notch toughness. The post-weld heat treatment (PWHT) or stress-relieving heat treatment has significant effects on avoiding the martensite transformation and resulting in high hardness, which can lead to cracking in the heat-affected zone (HAZ). An adaptive neuro-fuzzy inference system (ANFIS) was implemented to predict the material tensile strength of post-weld heat treatment (PWHT) experiments. The ANFIS models presented excellent predictions, and the comparison was carried out based on the mean absolute percentage error between the predicted values and the experimental values. The ANFIS model gave a Mean Absolute Percentage Error of 0.556 %, which confirms the high accuracy of the model.

Keywords: prediction, post-weld heat treatment, adaptive neuro-fuzzy inference system, mean absolute percentage error

Procedia PDF Downloads 145

Authors: Victor William Harris

Abstract:

This research is a validation study of the Social Emotional Ability Inventory (SEAI), a multi-dimensional self-report instrument informed by positive psychology, emotional intelligence, social intelligence, and sociocultural learning theory. Designed for use in tandem with the Social Emotional Development (SEAD) theoretical model, the SEAI provides diagnostic-level guidance for professionals and individuals interested in investigating, identifying, and understanding social, emotional strengths, as well as remediating specific social competency deficiencies. The SEAI was shown to be psychometrically sound, exhibited strong internal reliability, and supported the a priori hypotheses of the SEAD. Additionally, confirmatory factor analysis provided evidence of goodness of fit, convergent and divergent validity, and supported a theoretical model that reflected SEAD expectations. The SEAI and SEAD hold potentially far-reaching and important practical implications for theoretical guidance and diagnostic-level measurement of social, emotional competency across a wide range of domains. Strategies researchers, practitioners, educators, and individuals might use to deploy SEAI in order to improve quality of life outcomes are discussed.

Keywords: emotion, emotional ability, positive psychology-social emotional ability, social emotional ability, social emotional ability instrument

Procedia PDF Downloads 230

Authors: Anders Troedsson

Abstract:

For us humans, risks are intimately linked to human vulnerabilities - where there is vulnerability, there is potentially insecurity, and risk. Reducing vulnerability through compensatory measures means increasing security and decreasing risk. The paper suggests that a meaningful way to approach the study of risks (including threats, assaults, crisis etc.), is to understand the vulnerabilities these external phenomena evoke in humans. As is argued, the basis of risk evaluation, as well as responses, is the more or less subjective perception by the individual person, or a group of persons, exposed to the external event or phenomena in question. This will be determined primarily by the vulnerability or vulnerabilities that the external factor are perceived to evoke. In this way, risk perception is primarily an inward dynamic, rather than an outward one. Therefore, a route towards an understanding of the perception of risks, is a closer scrutiny of the vulnerabilities which they can evoke, thereby approaching an understanding of what in the paper is called the essence of risk (including threat, assault etc.), or that which a certain perceived risk means to an individual or group of individuals. As a necessary basis for gauging the wide spectrum of potential risks and their meaning, the paper proposes a model of human vulnerabilities, drawing from i.a. a long tradition of needs theory. In order to account for the subjectivity factor, which mediates between the innate vulnerabilities on the one hand, and the event or phenomenon out there on the other hand, an ensuing ontological discussion about the timespace characteristics of risk/threat/assault as perceived by humans leads to the positing of two dimensions. These two dimensions are applied on the vulnerabilities, resulting in a modelling effort featuring four realms of vulnerabilities which are related to each other and together represent a dynamic whole. In approaching the problem of risk perception, the paper thus defines the relevant realms of vulnerabilities, depicting them as a dynamic whole. With reference to a substantial body of literature and a growing international policy trend since the 1990s, this model is put in the language of human security - a concept relevant not only for international security studies and policy, but also for other academic disciplines and spheres of human endeavor.

Keywords: human security, timespace, vulnerabilities, risk perception

Procedia PDF Downloads 324

Authors: Givi Kupatadze

Abstract:

Backward economies are facing a challenge of achieving sustainable high economic growth rate. Dominant growth models represent a roadmap in framing economic development strategy. This paper examines a relevance of the dominant growth models for backward economies. Cobb-Douglas production function, the Harrod-Domar model of economic growth, the Solow growth model and general formula of gross domestic product are examined to undertake a comprehensive study of the dominant growth models. Deductive research method allows to uncover major weaknesses of the dominant growth models and to come up with practical implications for economic development strategy. The key finding of the paper shows, contrary to what used to be taught by textbooks of economics, that constant returns to scale property of the dominant growth models are a mere coincidence and its generalization over space and time can be regarded as one of the most unfortunate mistakes in the whole field of political economy. The major suggestion of the paper for backward economies is that understanding and considering taxonomy of economic activities based on increasing and diminishing returns to scale represent a cornerstone of successful economic development strategy.

Keywords: backward economies, constant returns to scale, dominant growth models, taxonomy of economic activities

Procedia PDF Downloads 362

Authors: Yosr Ghozzi

Abstract:

The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

Procedia PDF Downloads 90

Authors: Mohamed Bualhamam

Abstract:

Due to the complex nature of tourism resources of the Northern part of the United Arab Emirates (UAE), the potential of Geographical Information Systems (GIS) and Remote Sensing (RS) in resolving these issues was used. The study was an attempt to use existing GIS data layers to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth and give some specific recommendations to protect the area. By identifying sensitive natural environment and archaeological heritage resources, public agencies and citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas. The paper concludes that applications of GIS and RS in study of urban growth impact in tourism resources are a strong and effective tool that can aid in tourism planning and decision-making. The study area is one of the fastest growing regions in the country. The increase in population along the region, as well as rapid growth of towns, has increased the threat to natural resources and archeological sites. Satellite remote sensing data have been proven useful in assessing the natural resources and in monitoring the changes. The study used GIS and RS to identify sensitive natural environment and archaeological heritage resources that may be threatened by increased urban growth. The result of GIS analyses shows that the Northern part of the UAE has variety for tourism resources, which can use for future tourism development. Rapid urban development in the form of small towns and different economic activities are showing in different places in the study area. The urban development extended out of old towns and have negative affected of sensitive tourism resources in some areas. Tourism resources for the Northern part of the UAE is a highly complex resources, and thus requires tools that aid in effective decision making to come to terms with the competing economic, social, and environmental demands of sustainable development. The UAE government should prepare a tourism databases and a GIS system, so that planners can be accessed for archaeological heritage information as part of development planning processes. Applications of GIS in urban planning, tourism and recreation planning illustrate that GIS is a strong and effective tool that can aid in tourism planning and decision- making. The power of GIS lies not only in the ability to visualize spatial relationships, but also beyond the space to a holistic view of the world with its many interconnected components and complex relationships. The worst of the damage could have been avoided by recognizing suitable limits and adhering to some simple environmental guidelines and standards will successfully develop tourism in sustainable manner. By identifying sensitive natural environment and archaeological heritage resources of the Northern part of the UAE, public agencies and private citizens are in a better position to successfully protect important natural lands and direct growth away from environmentally sensitive areas.

Keywords: GIS, natural environment, UAE, urban growth

Procedia PDF Downloads 252

Authors: Ritika Chaturvedi

Abstract:

Introduction: Sexual objectification, characterized by the reduction of an individual to a mere object of sexual desire, remains a pervasive societal issue with profound repercussions on individual well-being. Such experiences, often rooted in systemic and cultural norms, have long-lasting implications for mental and emotional health. This study aims to explore the intricate relationship between experiences of sexual objectification and insidious trauma, further investigating the potential moderating effects of overexcitabilities as proposed by Dabrowski's theory of positive disintegration. Methodology: The research involved a comprehensive cohort of 204 women, spanning ages from 18 to 65 years. Participants were tasked with completing self-administered questionnaires designed to capture their experiences with sexual objectification. Additionally, the questionnaire assessed symptoms indicative of insidious trauma and explored overexcitabilities across five distinct domains: emotional, intellectual, psychomotor, sensory, and imaginational. Employing advanced statistical techniques, including multiple regression and moderation analysis, the study sought to decipher the intricate interplay among these variables. Findings: The study's results revealed a compelling positive correlation between experiences of sexual objectification and the onset of symptoms indicative of insidious trauma. This correlation underscores the profound and detrimental effects of sexual objectification on an individual's psychological well-being. Interestingly, the moderation analyses introduced a nuanced understanding, highlighting the differential roles of various overexcitabilities. Specifically, emotional, intellectual, and sensual overexcitabilities were found to exacerbate trauma symptomatology. In contrast, psychomotor overexcitability emerged as a protective factor, demonstrating a mitigating influence on the relationship between sexual objectification and trauma. Implications: The study's findings hold significant implications for a diverse array of stakeholders, encompassing mental health practitioners, educators, policymakers, and advocacy groups. The identified moderating effects of overexcitabilities emphasize the need for tailored interventions that consider individual differences in coping and resilience mechanisms. By recognizing the pivotal role of overexcitabilities in modulating the traumatic consequences of sexual objectification, this research advocates for the development of more nuanced and targeted support frameworks. Moreover, the study underscores the importance of continued research endeavors to unravel the intricate mechanisms and dynamics underpinning these relationships. Such endeavors are crucial for fostering the evolution of informed, evidence-based interventions and strategies aimed at mitigating the adverse effects of sexual objectification and promoting holistic well-being.

Keywords: sexual objectification, insidious trauma, emotional overexcitability, intellectual overexcitability, sensual overexcitability, psychomotor overexcitability, imaginational overexcitability

Procedia PDF Downloads 37

Authors: Sarantos Psycharis

Abstract:

Physical Computing, as an instructional model, is applied in the framework of the Engineering Pedagogy to teach “transversal/cross-cutting ideas” in a STEM content approach. Labview and Arduino were used in order to connect the physical world with real data in the framework of the so called Computational Experiment. Tertiary prospective engineering educators were engaged during their course and Computational Thinking (CT) concepts were registered before and after the intervention across didactic activities using validated questionnaires for the relationship between self-efficacy, computer programming, and CT concepts when STEM content epistemology is implemented in alignment with the Computational Pedagogy model. Results show a significant change in students’ responses for self-efficacy for CT before and after the instruction. Results also indicate a significant relation between the responses in the different CT concepts/practices. According to the findings, STEM content epistemology combined with Physical Computing should be a good candidate as a learning and teaching approach in university settings that enhances students’ engagement in CT concepts/practices.

Keywords: arduino, computational thinking, computer programming, Labview, self-efficacy, STEM

Procedia PDF Downloads 108

Authors: Rosdyana Mangir Irawan Kusuma, Wei-Chun Kao, Ho-Thi Trang, Yu-Yen Ou, Kai-Lung Hua

Abstract:

Stock market prediction is still a challenging problem because there are many factors that affect the stock market price such as company news and performance, industry performance, investor sentiment, social media sentiment, and economic factors. This work explores the predictability in the stock market using deep convolutional network and candlestick charts. The outcome is utilized to design a decision support framework that can be used by traders to provide suggested indications of future stock price direction. We perform this work using various types of neural networks like convolutional neural network, residual network and visual geometry group network. From stock market historical data, we converted it to candlestick charts. Finally, these candlestick charts will be feed as input for training a convolutional neural network model. This convolutional neural network model will help us to analyze the patterns inside the candlestick chart and predict the future movements of the stock market. The effectiveness of our method is evaluated in stock market prediction with promising results; 92.2% and 92.1 % accuracy for Taiwan and Indonesian stock market dataset respectively.

Keywords: candlestick chart, deep learning, neural network, stock market prediction

Procedia PDF Downloads 429

Authors: N. Borjalilu, P. Rabiei, A. Enjoo

Abstract:

Flight Data Monitoring (FDM) program assists an operator in aviation industries to identify, quantify, assess and address operational safety risks, in order to improve safety of flight operations. FDM is a powerful tool for an aircraft operator integrated into the operator’s Safety Management System (SMS), allowing to detect, confirm, and assess safety issues and to check the effectiveness of corrective actions, associated with human errors. This article proposes a model for safety risk assessment level of flight data in a different aspect of event focus based on fuzzy set values. It permits to evaluate the operational safety level from the point of view of flight activities. The main advantages of this method are proposed qualitative safety analysis of flight data. This research applies the opinions of the aviation experts through a number of questionnaires Related to flight data in four categories of occurrence that can take place during an accident or an incident such as: Runway Excursions (RE), Controlled Flight Into Terrain (CFIT), Mid-Air Collision (MAC), Loss of Control in Flight (LOC-I). By weighting each one (by F-TOPSIS) and applying it to the number of risks of the event, the safety risk of each related events can be obtained.

Keywords: F-topsis, fuzzy set, flight data monitoring (FDM), flight safety

Procedia PDF Downloads 157

Authors: Henry Gonzalo Acurio Flores, Alvaro Nicolas Corral Naveda, Juan Francisco Fonseca Palacios

Abstract:

In Ecuador, subventions on fossil fuels for the road transportation sector have always been part of its economy throughout time, mainly because of demagogy and populism from political leaders. It is clearly seen that the government cannot maintain the subsidies anymore due to its commercial balance and its general state budget; subsidies are a key barrier to implementing the use of cleaner technologies. However, during the last few months, the elimination of subsidies has been done gradually with the purpose of reaching international prices. It is expected that with this measure, the population will opt for other means of transportation, and in a certain way, it will promote the use of private electric vehicles and public, e.g., taxis and buses (urban transport). Considering the three main elements of sustainable development, an analysis of the social, economic, and environmental impacts of eliminating subsidies will be generated at the country level. To achieve this, four scenarios will be developed in order to determine how the subsidies will contribute to the promotion of electro-mobility. 1) A Business as Usual BAU scenario; 2) the introduction of 10 000 electric vehicles by 2025; 3) the introduction of 100 000 electric vehicles by 2030; 4) the introduction of 750 000 electric vehicles by 2040 (for all the scenarios buses, taxis, lightweight duty vehicles, and private vehicles will be introduced, as it is established in the National Electro Mobility Strategy for Ecuador). The Low Emissions Analysis Platform (LEAP) will be used, and it will be suitable to determine the cost for the government in terms of importing derivatives for fossil fuels and the cost of electricity to power the electric fleet that can be changed. The elimination of subventions generates fiscal resources for the state that can be used to develop other kinds of projects that will benefit Ecuadorian society. It will definitely change the energy matrix, and it will provide energy security for the country; it will be an opportunity for the government to incentivize a greater introduction of renewable energies, e.g., solar, wind, and geothermal. At the same time, it will also reduce greenhouse gas emissions (GHG) from the transportation sector, considering its mitigation potential, which as a result, will ameliorate the inhabitant quality of life by improving the quality of air, therefore reducing respiratory diseases associated with exhaust emissions, consequently, achieving sustainability, the Sustainable Development Goals (SDGs), and complying with the agreements established in the Paris Agreement COP 21 in 2015. Electro mobility in Latin America and the Caribbean can only be achieved by the implementation of the right policies at the central government, which need to be accompanied by a National Urban Mobility Policy (NUMP) and can encompass a greater vision to develop holistic, sustainable transport systems at local governments.

Keywords: electro mobility, energy, policy, sustainable transportation

Procedia PDF Downloads 77

Authors: Hsin-Yang Wang, K. M. A. Salam, Ying-Jia Lin, Daniel Tan, Tzu-Hsuan Chou, Hung-Yu Kao

Abstract:

Detecting user intent from natural language expression has a wide variety of use cases in different natural language processing applications. Recently few-shot training has a spike of usage on commercial domains. Due to the lack of significant sample features, the downstream task performance has been limited or leads to an unstable result across different domains. As a state-of-the-art method, the pre-trained BERT model gathering the sentence-level information from a large text corpus shows improvement on several NLP benchmarks. In this research, we are proposing a method to change multi-class classification tasks into binary classification tasks, then use the confidence score to rank the results. As a language model, BERT performs well on sequence data. In our experiment, we change the objective from predicting labels into finding the relations between words in sequence data. Our proposed method achieved 71.0% accuracy in the internal intent detection dataset and 63.9% accuracy in the HuffPost dataset. Acknowledgment: This work was supported by NCKU-B109-K003, which is the collaboration between National Cheng Kung University, Taiwan, and SoftBank Corp., Tokyo.

Keywords: OSML, BERT, text classification, one shot

Procedia PDF Downloads 90

Authors: Saahith M. S., Sivakami R.

Abstract:

In the realm of football analytics, particularly focusing on predicting football player performance, the ability to forecast player success accurately is of paramount importance for teams, managers, and fans. This study introduces an elaborate examination of predicting football player performance through the integration of data visualization methods and machine learning algorithms. The research entails the compilation of an extensive dataset comprising player attributes, conducting data preprocessing, feature selection, model selection, and model training to construct predictive models. The analysis within this study will involve delving into feature significance using methodologies like Select Best and Recursive Feature Elimination (RFE) to pinpoint pertinent attributes for predicting player performance. Various machine learning algorithms, including Random Forest, Decision Tree, Linear Regression, Support Vector Regression (SVR), and Artificial Neural Networks (ANN), will be explored to develop predictive models. The evaluation of each model's performance utilizing metrics such as Mean Squared Error (MSE) and R-squared will be executed to gauge their efficacy in predicting player performance. Furthermore, this investigation will encompass a top player analysis to recognize the top-performing players based on the anticipated overall performance scores. Nationality analysis will entail scrutinizing the player distribution based on nationality and investigating potential correlations between nationality and player performance. Positional analysis will concentrate on examining the player distribution across various positions and assessing the average performance of players in each position. Age analysis will evaluate the influence of age on player performance and identify any discernible trends or patterns associated with player age groups. The primary objective is to predict a football player's overall performance accurately based on their individual attributes, leveraging data-driven insights to enrich the comprehension of player success on the field. By amalgamating data visualization and machine learning methodologies, the aim is to furnish valuable tools for teams, managers, and fans to effectively analyze and forecast player performance. This research contributes to the progression of sports analytics by showcasing the potential of machine learning in predicting football player performance and offering actionable insights for diverse stakeholders in the football industry.

Keywords: football analytics, player performance prediction, data visualization, machine learning algorithms, random forest, decision tree, linear regression, support vector regression, artificial neural networks, model evaluation, top player analysis, nationality analysis, positional analysis

Procedia PDF Downloads 29

Authors: Li Long, Thomas Ortlepp

Abstract:

A theoretical model for the optimization of thermopile sensor performance is developed for thermoelectric-based infrared radiation detection. It is shown that the performance of polycrystalline silicon film thermopile sensor can be optimized according to the thermoelectric quality factor, sensor layer structure factor, and sensor layout geometrical form factor. Based on the properties of electrons, phonons, grain boundaries, and their interactions, the thermoelectric quality factor of polycrystalline silicon is analyzed with the relaxation time approximation of the Boltzmann transport equation. The model includes the effect of grain structure, grain boundary trap properties, and doping concentration. The layer structure factor is analyzed with respect to the infrared absorption coefficient. The optimization of layout design is characterized by the form factor, which is calculated for different sensor designs. A double-layer polycrystalline silicon thermopile infrared sensor on a suspended membrane has been designed and fabricated with a CMOS-compatible process. The theoretical approach is confirmed by measurement results.

Keywords: polycrystalline silicon, relaxation time approximation, specific detectivity, thermal conductivity, thermopile infrared sensor

Procedia PDF Downloads 122

Authors: Abhishek Soni, A. Kumaraswamy, M. S. Mahesh

Abstract:

Bullet penetration in steel plate is investigated with the help of three-dimensional, non-linear, transient, dynamic, finite elements analysis using explicit time integration code LSDYNA. The effect of large strain, strain-rate and temperature at very high velocity regime was studied from number of simulations of semi-spherical nose shape bullet penetration through single layered circular plate with 2 mm thickness at impact velocities of 500, 1000, and 1500 m/s with the help of Johnson Cook material model. Mie-Gruneisen equation of state is used in conjunction with Johnson Cook material model to determine pressure-volume relationship at various points of interests. Two material models viz. Plastic-Kinematic and Johnson- Cook resulted in different deformation patterns in steel plate. It is observed from the simulation results that the velocity drop and loss of kinetic energy occurred very quickly up to perforation of plate, after that the change in velocity and changes in kinetic energy are negligibly small. The physics behind this kind of behaviour is presented in the paper.

Keywords: AISI 4340 steel, ballistic impact simulation, bullet penetration, non-linear FEM

Procedia PDF Downloads 198

Authors: Aamna Lawrence, Ashutosh Mishra

Abstract:

Tremors occur in 60% of the patients who have Multiple Sclerosis (MS), the most common demyelinating disease that affects the central and peripheral nervous system, and are the primary cause of disability in young adults. While pharmacological agents provide minimal benefits, surgical interventions like Deep Brain Stimulation and Thalamotomy are riddled with dangerous complications which make non-invasive electrical stimulation an appealing treatment of choice for dealing with tremors. Hence, we hypothesized that if the non-invasive electrical stimulation parameters (mainly frequency) can be computed by mathematically modeling the nerve fibre to take into consideration the minutest details of the axon morphologies, tremors due to demyelination can be optimally alleviated. In this computational study, we have modeled the random demyelination pattern in a nerve fibre that typically manifests in MS using the High-Density Hodgkin-Huxley model with suitable modifications to account for the myelin. The internode of the nerve fibre in our model could have up to ten demyelinated regions each having random length and myelin thickness. The arrival time of action potentials traveling the demyelinated and the normally myelinated nerve fibre between two fixed points in space was noted, and its relationship with the nerve fibre radius ranging from 5µm to 12µm was analyzed. It was interesting to note that there were no overlaps between the arrival time for action potentials traversing the demyelinated and normally myelinated nerve fibres even when a single internode of the nerve fibre was demyelinated. The study gave us an opportunity to design DC pulses whose frequency of application would be a function of the random demyelination pattern to block only the delayed tremor-causing action potentials. The DC pulses could be delivered to the peripheral nervous system non-invasively by an electrode bracelet that would suppress any shakiness beyond it thus paving the way for wearable neuro-rehabilitative technologies.

Keywords: demyelination, Hodgkin-Huxley model, non-invasive electrical stimulation, tremor

Procedia PDF Downloads 116

Authors: Reza Safdari, Goli Arji, Robab Abdolkhani Maryam zahmatkeshan

Abstract:

Background and purpose: Cardiovascular diseases are among the most common diseases in all societies. The most important step in minimizing myocardial infarction and its complications is to minimize its risk factors. The amount of medical data is increasingly growing. Medical data mining has a great potential for transforming these data into information. Using data mining techniques to generate predictive models for identifying those at risk for reducing the effects of the disease is very helpful. The present study aimed to collect data related to risk factors of heart infarction from patients’ medical record and developed predicting models using data mining algorithm. Methods: The present work was an analytical study conducted on a database containing 350 records. Data were related to patients admitted to Shahid Rajaei specialized cardiovascular hospital, Iran, in 2011. Data were collected using a four-sectioned data collection form. Data analysis was performed using SPSS and Clementine version 12. Seven predictive algorithms and one algorithm-based model for predicting association rules were applied to the data. Accuracy, precision, sensitivity, specificity, as well as positive and negative predictive values were determined and the final model was obtained. Results: five parameters, including hypertension, DLP, tobacco smoking, diabetes, and A+ blood group, were the most critical risk factors of myocardial infarction. Among the models, the neural network model was found to have the highest sensitivity, indicating its ability to successfully diagnose the disease. Conclusion: Risk prediction models have great potentials in facilitating the management of a patient with a specific disease. Therefore, health interventions or change in their life style can be conducted based on these models for improving the health conditions of the individuals at risk.

Keywords: decision trees, neural network, myocardial infarction, Data Mining

Procedia PDF Downloads 419

Authors: Hesam Sedaghat Nejad, Navid Hosseini, Arash Nikvar Hassani

Abstract:

Determination of the optimum block size with high profitability is one of the significant parameters in designation of the building stone mines. The aim of this study was to determine the optimum dimensions of building stone blocks in Delichai travertine mine of Damavand in Tehran province through combining the effective parameters proven in determination of the optimum dimensions in building stones such as the spacing of joints and gaps, extraction tools constraints with the help of modeling by Gemcom software. To this end, following simulation of the topography of the mine, the block model was prepared and then in order to use spacing joints and discontinuities as a limiting factor, the existing joints set was added to the model. Since only one almost horizontal joint set with a slope of 5 degrees was available, this factor was effective only in determining the optimum height of the block, and thus to determine the longitudinal and transverse optimum dimensions of the extracted block, the power of available loader in the mine was considered as the secondary limiting factor. According to the aforementioned factors, the optimal block size in this mine was measured as 3.4×4×7 meter.

Keywords: building stone, optimum block size, Delichay travertine mine, loader power

Procedia PDF Downloads 352

Authors: Hussain Ali Bekhet, Tuan Ab. Rashid Bin Tuan Abdullah, Tahira Yasmin

Abstract:

The strong relationship between energy consumption and economic growth is widely recognised. Most countries’ energy demand declined during the economic depression known as the Global Financial Crisis (GFC) of 2008–2009. The objective of the current study is to investigate the energy consumption and performance of Malaysia’s manufacturing sectors during the GFC. We applied the output multiplier approach, which is based on the input-output model. Two input-output tables of Malaysia covering 2005 and 2010 were used. The results indicate significant changes in the output multipliers of the manufacturing sectors between 2005 and 2010. Moreover, the energy-to-manufacturing sectors’ output multipliers also decreased during the GFC due to a decline in export-oriented industries during the crisis. The increasing importance of the manufacturing sector to the development of Malaysian trade resulted in a noticeable decrease in the consumption of each energy sector’s output, especially the electricity and gas sector. Based on the research findings, the Malaysian government released several policy implementations in the form of stimulus packages to enhance these sectors’ performance and generally improve the Malaysian economy.

Keywords: global financial crisis, input-output model, manufacturing, output multipliers, energy, Malaysia

Procedia PDF Downloads 719

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

Procedia PDF Downloads 329

Authors: Nirere Martine

Abstract:

Purpose –The purpose of this study aims to understand the intention of customers to adopt sustainable packaging and the impact of sustainable packaging on customers’ willingness to buy a product using sustainable packaging. Design/methodology/approach – A new research model based on the technology acceptance model (TAM) and structural equation modeling are used to examine causality and test relationship based on the data collected from 251 Rwanda samples. Findings – The findings indicated that perceived ease of use positively affects perceived usefulness. However, perceived usefulness and perceived ease of use positively affect the intention to adopt sustainable packaging. However, perceived risk and perceived cost negatively affect the intention to adopt sustainable packaging. The intention to adopt sustainable packaging positively affects the willingness to buy a product using sustainable packaging. Originality/value – Many researchers have investigated the issue of a consumers’ behavior to purchase a product. In particular, they have examined whether customers are willing to pay extra for a packaging product. There has been no study that has examined the impact of sustainable packaging on customers’ willingness to buy. The results of this study can help manufacturers form a better understanding of customers’ willingness to purchase a product using sustainable packaging.

Keywords: consumers’ behavioral, sustainable packaging, TAM, Rwanda

Procedia PDF Downloads 177

Authors: Thi Thanh Nga Pham, Damien Philippon, Alexis Drogoul, Thi Thu Thuy Nguyen, Tien Cong Nguyen

Abstract:

Mekong River Delta region of Vietnam is recognized as one of the most vulnerable to climate change due to flooding and seawater rise and therefore an increased burden of climate change-related diseases. Changes in temperature and precipitation are likely to alter the incidence and distribution of vector-borne diseases such as dengue fever. In this region, the peak of the dengue epidemic period is around July to September during the rainy season. It is believed that climate is an important factor for dengue transmission. This study aims to enhance the capacity of dengue prediction by the relationship of dengue incidences with climate and environmental variables for Mekong River Delta of Vietnam during 2005-2015. Mathematical models for vector-host infectious disease, including larva, mosquito, and human being were used to calculate the impacts of climate to the dengue transmission with incorporating geospatial data for model input. Monthly dengue incidence data were collected at provincial level. Precipitation data were extracted from satellite observations of GSMaP (Global Satellite Mapping of Precipitation), land surface temperature and land cover data were from MODIS. The value of seasonal reproduction number was estimated to evaluate the potential, severity and persistence of dengue infection, while the final infected number was derived to check the outbreak of dengue. The result shows that the dengue infection depends on the seasonal variation of climate variables with the peak during the rainy season and predicted dengue incidence follows well with this dynamic for the whole studied region. However, the highest outbreak of 2007 dengue was not captured by the model reflecting nonlinear dependences of transmission on climate. Other possible effects will be discussed to address the limitation of the model. This suggested the need of considering of both climate variables and another variability across temporal and spatial scales.

Keywords: infectious disease, dengue, geospatial data, climate

Procedia PDF Downloads 374

Authors: Chutikarn Sriviboon, Witthaya Mekhum

Abstract:

The purposes of this research were to analyze and evaluate successful factors in OTOP production process for the developing of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The research has been designed as a qualitative study to gather information from 30 OTOP producers in Bangkontee District, Samudsongkram Province. They were all interviewed on 3 main parts. Part 1 was about the production process including 1) production 2) product development 3) the community strength 4) marketing possibility and 5) product quality. Part 2 evaluated appropriate successful factors including 1) the analysis of the successful factors 2) evaluate the strategy based on Sufficiency Economic Philosophy and 3) the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality. The results showed that the production did not affect the environment with potential in continuing standard quality production. They used the raw materials in the country. On the aspect of product and community strength in the past 1 year, it was found that there was no appropriate packaging showing product identity according to global market standard. They needed the training on packaging especially for food and drink products. On the aspect of product quality and product specification, it was found that the products were certified by the local OTOP standard. There should be a responsible organization to help the uncertified producers pass the standard. However, there was a problem on food contamination which was hazardous to the consumers. The producers should cooperate with the government sector or educational institutes involving with food processing to reach FDA standard. The results from small group discussion showed that the community expected high education and better standard living. Some problems reported by the community included informal debt and drugs in the community. There were 8 steps in developing the model of learning center on OTOP production process based on Sufficiency Economic Philosophy for sustainable life quality.

Keywords: production process, OTOP, sufficiency economic philosophy, learning center

Procedia PDF Downloads 363