Search results for: teaching and learning effectiveness

Authors: Vaidehi Murarka, Sneha Mehta, Dishant Upadhyay

Abstract:

Our project topic is “Alphabet Recognition using pixel probability distribution”. The project uses techniques of Image Processing and Machine Learning in Computer Vision. Alphabet recognition is the mechanical or electronic translation of scanned images of handwritten, typewritten or printed text into machine-encoded text. It is widely used to convert books and documents into electronic files etc. Alphabet Recognition based OCR application is sometimes used in signature recognition which is used in bank and other high security buildings. One of the popular mobile applications includes reading a visiting card and directly storing it to the contacts. OCR's are known to be used in radar systems for reading speeders license plates and lots of other things. The implementation of our project has been done using Visual Studio and Open CV (Open Source Computer Vision). Our algorithm is based on Neural Networks (machine learning). The project was implemented in three modules: (1) Training: This module aims “Database Generation”. Database was generated using two methods: (a) Run-time generation included database generation at compilation time using inbuilt fonts of OpenCV library. Human intervention is not necessary for generating this database. (b) Contour–detection: ‘jpeg’ template containing different fonts of an alphabet is converted to the weighted matrix using specialized functions (contour detection and blob detection) of OpenCV. The main advantage of this type of database generation is that the algorithm becomes self-learning and the final database requires little memory to be stored (119kb precisely). (2) Preprocessing: Input image is pre-processed using image processing concepts such as adaptive thresholding, binarizing, dilating etc. and is made ready for segmentation. “Segmentation” includes extraction of lines, words, and letters from the processed text image. (3) Testing and prediction: The extracted letters are classified and predicted using the neural networks algorithm. The algorithm recognizes an alphabet based on certain mathematical parameters calculated using the database and weight matrix of the segmented image.

Keywords: contour-detection, neural networks, pre-processing, recognition coefficient, runtime-template generation, segmentation, weight matrix

Procedia PDF Downloads 377

Authors: Eva Maged Hosni Sadek

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 48

Authors: Sam Teek Ling, Norhashidah Hj. Mohd. Ali

Abstract:

We investigate the formulation and implementation of new explicit group iterative methods in solving the two-dimensional Poisson equation with Dirichlet boundary conditions. The methods are derived from a fourth order compact nine point finite difference discretization. The methods are compared with the existing second order standard five point formula to show the dramatic improvement in computed accuracy. Numerical experiments are presented to illustrate the effectiveness of the proposed methods.

Keywords: explicit group iterative method, finite difference, fourth order compact, Poisson equation

Procedia PDF Downloads 424

Authors: Xinghang Lv, Tao Peng, Jia Chen, Junping Liu, Xinrong Hu, Ruhan He, Minghua Jiang, Wenli Cao

Abstract:

As one of the most dangerous vulnerabilities, effective detection of buffer overflow vulnerabilities is extremely necessary. Traditional detection methods are not accurate enough and consume more resources to meet complex and enormous code environment at present. In order to resolve the above problems, we propose the method for Buffer overflow detection based on Abstract syntax tree, Control flow graph, and Data dependency graph (BodeACD) in C/C++ programs with source code. Firstly, BodeACD constructs the function samples of buffer overflow that are available on Github, then represents them as code representation sequences, which fuse control flow, data dependency, and syntax structure of source code to reduce information loss during code representation. Finally, BodeACD learns vulnerability patterns for vulnerability detection through deep learning. The results of the experiments show that BodeACD has increased the precision and recall by 6.3% and 8.5% respectively compared with the latest methods, which can effectively improve vulnerability detection and reduce False-positive rate and False-negative rate.

Keywords: vulnerability detection, abstract syntax tree, control flow graph, data dependency graph, code representation, deep learning

Procedia PDF Downloads 161

Authors: Karima Megdouli

Abstract:

The ejector, a central element within the CO₂ transcritical ejection refrigeration system, holds significant importance in enhancing refrigeration capacity and minimizing compressor power usage. This study's objective is to introduce a technique for enhancing the effectiveness of the CO₂ transcritical two-phase ejector, utilizing Taguchi and ANOVA analysis. The investigation delves into the impact of geometric parameters, secondary flow temperature, and primary flow pressure on the efficiency of the ejector. Results indicate that employing a combination of Taguchi and ANOVA offers increased reliability and superior performance when optimizing the design of the CO₂ two-phase ejector.

Keywords: ejector, supersonic, Taguchi, ANOVA, optimization

Procedia PDF Downloads 67

Authors: T. S. Terence Ma, Irene T. Ho

Abstract:

Conducting adequate assessment of the challenges students with ASD (Autism Spectrum Disorder) face and the support they need is imperative for promoting their school adjustment. Students with ASD often show deficits in communication, social interaction, emotional regulation, and self-management in learning. While targeting these areas in intervention is often helpful, we argue that not enough attention has been paid to weak self-regulation being a key factor underlying their manifest difficulty in all these areas. Self-regulation refers to one’s ability to moderate their behavioral or affective responses without assistance from others. Especially for students with high functioning autism, who often show problems not so much in acquiring the needed skills but rather in applying those skills appropriately in everyday problem-solving, self-regulation becomes a key to successful adjustment in daily life. Therefore, a greater understanding of the construct of self-regulation, its relationship with other daily skills, and its role in school functioning for students with ASD would generate insights on how students’ school adjustment could be promoted more effectively. There were two focuses in this study. Firstly, we examined the extent to which self-regulation is a distinct construct that is differentiable from other daily skills and the most salient indicators of this construct. Then we tested a model of relationships between self-regulation and other daily school skills as well as their relative and combined effects on school adjustment. A total of 1,345 Grade1 to Grade 6 students with ASD attending mainstream schools in Hong Kong participated in the research. In the first stage of the study, teachers filled out a questionnaire consisting of 136 items assessing a wide range of student skills in social, emotional and learning areas. Results from exploratory factor analysis (EFA) with 673 participants and subsequent confirmatory factor analysis (CFA) with another group of 672 participants showed that there were five distinct factors of school skills, namely (1) communication skills, (2) pro-social behavior, (3) emotional skills, (4) learning management, and (5) self-regulation. Five scales representing these skill dimensions were generated. In the second stage of the study, a model postulating the mediating role of self-regulation for the effects of the other four types of skills on school adjustment was tested with structural equation modeling (SEM). School adjustment was defined in terms of the extent to which the student is accepted well in school, with high engagement in school life and self-esteem as well as good interpersonal relationships. A 5-item scale was used to assess these aspects of school adjustment. Results showed that communication skills, pro-social behavior, emotional skills and learning management had significant effects on school adjustment only indirectly through self-regulation, and their total effects were found to be not high. The results indicate that support rendered to students with ASD focusing only on the training of well-defined skills is not adequate for promoting their inclusion in school. More attention should be paid to the training of self-management with an emphasis on the application of skills backed by self-regulation. Also, other non-skill factors are important in promoting inclusive education.

Keywords: autism, assessment, factor analysis, self-regulation, school adjustment

Procedia PDF Downloads 98

Authors: Boonyarat Chaleephay

Abstract:

The purpose of this research paper was to describe the relationship of acupressure points on the anterior surface of the upper limb in accordance with Applied Thai Traditional Massage (ATTM) and the deep structures located at those acupressure points. There were 2 population groups; normal subjects and cadaver specimens. Eighteen males with age ranging from 20-40 years old and seventeen females with ages ranging from 30-97 years old were studies. This study was able to obtain a fundamental knowledge concerning acupressure point and the deep structures that related to those acupressure points. It might be used as the basic knowledge for clinically applying and planning treatment as well as teaching in ATTM.

Keywords: acupressure point (AP), applie Thai traditional medicine (ATTM), paresthesia, numbness

Procedia PDF Downloads 237

Authors: Wing Chi Wong

Abstract:

Globally, studying parents caring for children with attention deficit/ hyperactivity disorder (ADHD) is valuable in order to design measures in supporting those parents by health care providers and government. Such parents in Hong Kong seem to encounter detrimental stress and enormous difficulties which are exacerbated by the traditional Chinese culture, exclusion from social members and fiercely competitive educational system. However, seldom studies scrutinize this issue in Hong Kong. This article aims to review the literature regarding parents caring offsprings with ADHD in Hong Kong. Criteria were set for searching among published studies listed in various databases, including MEDLINE, CINCAHL, PsycINFO, ProQuest, Embase, Cochrane Library and Springer Link. Articles with words 'Attention Deficit Hyperactivity Disorder', 'parenting', 'parent', 'family', 'father', 'mother', 'care' in titles and abstracts were identified. Articles with all types of research designs and methods, regardless in English or Chinese, were included. They were limited to years between January 2008 and September 2018. Four relevant studies have resulted. Of them, two were exploratory studies, one was a qualitative study, and one was a survey. Samples were recruited from child psychiatric clinic, Child and Adolescent Mental Health Unit, or multiple family group therapy centres. Authors proclaimed that quality of life of those parents was usually low; particularly mothers perceived a higher stress than fathers; parenting barriers existed; conflicts were commonly raised in parent-child relationship resulting in probable maltreatment to children. Previous studies generally suggested the potential negative outcomes of parents caring children with ADHD. The types and effectiveness of interventions to those parents on relieving their tortures under Hong Kong context had not been explored and systematically evaluated. The scanty studies and existing understanding could not give a promising conclusion pertaining to the appropriate family intervention to parents living with children with ADHD. A stringent research design is necessary to establish evidence on the effectiveness of interventions for those families.

Keywords: attention deficit/ hyperactivity disorder, Hong Kong, parents, interventions

Procedia PDF Downloads 150

Authors: Mathieu Audet, Monica Soliman, Emilie Eve Gravel, Rebecca Friesdorf

Abstract:

Access to higher education is critical for reducing social inequalities. The Canada Learning Bond (CLB) is a government savings incentive aimed at increasing higher education access for children of low income families by providing money toward a Registered Education Savings Plan. To better understand the educational and financial decision-making of low income families, Employment Social Development Canada conducted qualitative fieldwork with eligible parents and children, teachers, and community organizations promoting the Bond. Insights from this fieldwork were then used to develop letters to better target the needs and experiences of eligible families. In the present study, we conducted a randomized controlled trial with children ages 12 to 13, the oldest cohort of eligible children, to test the effectiveness of the new letters. Parents or caregivers of 150,088 eligible children were assigned to one of five letter conditions promoting the Bond or to a control condition that did not receive a letter. The letter conditions were: (a) the standard letter from past outreach, (b) a letter presenting the exact amount the child was eligible to receive, enhancing the salience of benefits, (c) a letter with a social norm, (d) a letter with an image emphasizing the feasibility of higher education by presenting the diversity of options (i.e., college, trade schools, apprenticeships) – many participants interviewed viewed that university was unfeasible, and (e) a letter minimizing references to 'saving' (i.e., not framing the Bond explicitly as a savings incentive) – a concept that did not resonate with low income families who felt they could not afford to save. The exact amount was also presented in letters (c) through (e). The letter minimizing references to 'saving' and presenting the exact amount had the highest net take-up rate at 6.6%, compared to 3.5% for the standard letter group. Furthermore, this trial’s BI-informed letters showed the largest impact on take-up so far, with a net take-up of 5.7% compared to 3.0% and 3.9% in the first two trials. This research highlights the value of mixed-method approaches combining qualitative and behavioural insights methods for developing context-sensitive interventions for social programs. By gaining a deeper understanding of the needs and experiences of program users through qualitative fieldwork, and then integrating these insights into behaviourally informed communications, we were able to increase take-up of an education savings program, which may ultimately improve access to higher education in children of low income families.

Keywords: access to higher education, behavioral insights, government, innovation, mixed-methods, social programs

Procedia PDF Downloads 116

Authors: Lorna Martha Dreyer

Abstract:

Consistent with the changing paradigm on the rights of people with disabilities and in pursuit of social justice, there is internationally an increase in students with disabilities enrolling at Higher Education Institutions (HEIs). This trend challenges HEI’s to transform and attain Education for All (EFA) as a global imperative. However, while physical and sensory disabilities are observable, students with specific learning disabilities (SLD) do not present with any visible indications and are often referred to as “hidden” or “invisible” disabilities. This qualitative case study aimed to illuminate the experiences of students with SLDs at a South African university. The research was, therefore, guided by Vygotsky’s social-cultural theory (SCT). This research was conducted within a basic qualitative research methodology embedded in an interpretive paradigm. Data was collected through an online background survey and semi-structured interviews. Thematic qualitative content analysis was used to analyse the collected data systematically. From a social justice perspective, the major findings suggest that there are several factors that impede equal education for students with SLDs at university. Most participants in this small-scale study experienced a lack of acknowledgment and support from lecturers. They reported valuing the support of family and friends more than that of lecturers. It is concluded that lecturers need to be reflective of their pedagogical practices if authentic inclusion is to be realised.

Keywords: higher education, inclusive education, pedagogy, social-cultural theory, specific learning disabilities

Procedia PDF Downloads 136

Authors: Rania Melad Kamel Hakim

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. These have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these ‘syndrome’ forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or ‘non-syndrome’ autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way to improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co-morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties (‘sticky attention’), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 45

Authors: John Hardy

Abstract:

Over the last decade, the increasing utility of extremist narratives to the operational effectiveness of terrorist organizations has been evidenced by the proliferation of inspired or affiliated attacks across the world. Famous examples such as regional al-Qaeda affiliates and the self-styled “Islamic State” demonstrate the effectiveness of leveraging communication technologies to disseminate propaganda, recruit members, and orchestrate attacks. Terrorist organizations with the capacity to harness the communicative power offered by digital communication technologies and effective political narratives have held an advantage over their targets in recent years. Terrorists have leveraged the perceived legitimacy of grass-roots actors to appeal to a global audience of potential supporters and enemies alike, and have wielded a proficiency in profile-raising which remains unmatched by counter terrorism narratives around the world. In contrast, many attempts at propagating official counter-narratives have been received by target audiences as illegitimate, top-down and impersonally bureaucratic. However, the benefits provided by widespread communication and extremist narratives have come at an operational cost. Terrorist organizations now face a significant challenge in protecting their access to communications technologies and authority over the content they create and endorse. The dissemination of effective narratives has emerged as a core function of terrorist organizations with international reach via inspired or affiliated attacks. As such, it has become a critical function which can be targeted by intelligence and security forces. This study applies network targeting principles which have been used by coalition forces against a range of non-state actors in the Middle East and South Asia to the communicative function of terrorist organizations. This illustrates both a conceptual link between functional targeting and operational disruption in the abstract and a tangible impact on the operational effectiveness of terrorists by degrading communicative ability and legitimacy. Two case studies highlight the utility of applying functional targeting against terrorist organizations. The first case is the targeted killing of Anwar al-Awlaki, an al-Qaeda propagandist who crafted a permissive narrative and effective propaganda videos to attract recruits who committed inspired terrorist attacks in the US and overseas. The second is a series of operations against Islamic State propagandists in Syria, including the capture or deaths of a cadre of high profile Islamic State members, including Junaid Hussain, Abu Mohammad al-Adnani, Neil Prakash, and Rachid Kassim. The group of Islamic State propagandists were linked to a significant rise in affiliated and enabled terrorist attacks and were subsequently targeted by law enforcement and military agencies. In both cases, the disruption of communication between the terrorist organization and recruits degraded both communicative and operational functions. Effective functional targeting on member recruitment and operational tempo suggests that narratives are a critical function which can be leveraged against terrorist organizations. Further application of network targeting methods to terrorist narratives may enhance the efficacy of a range of counter terrorism techniques employed by security and intelligence agencies.

Keywords: countering violent extremism, counter terrorism, intelligence, terrorism, violent extremism

Procedia PDF Downloads 284

Authors: Sharifah Mousli, Sona Taheri, Jiayuan He

Abstract:

Autism spectrum disorder (ASD) is a complex developmental condition involving persistent difficulties with social communication, restricted interests, and repetitive behavior. The challenges associated with ASD can interfere with an affected individual’s ability to function in social, academic, and employment settings. Although there is no effective medication known to treat ASD, to our best knowledge, early intervention can significantly improve an affected individual’s overall development. Hence, an accurate diagnosis of ASD at an early phase is essential. The use of machine learning approaches improves and speeds up the diagnosis of ASD. In this paper, we focus on the application of unsupervised clustering methods in ASD as a large volume of ASD data generated through hospitals, therapy centers, and mobile applications has no pre-existing labels. We conduct a comparative analysis using seven clustering approaches such as K-means, agglomerative hierarchical, model-based, fuzzy-C-means, affinity propagation, self organizing maps, linear vector quantisation – as well as the recently developed optimization-based clustering (COMSEP-Clust) approach. We evaluate the performances of the clustering methods extensively on real-world ASD datasets encompassing different age groups: toddlers, children, adolescents, and adults. Our experimental results suggest that the COMSEP-Clust approach outperforms the other seven methods in recognizing ASD with well-separated clusters.

Keywords: autism spectrum disorder, clustering, optimization, unsupervised machine learning

Procedia PDF Downloads 104

Authors: Rashmi Motwani, Ritu Raj

Abstract:

The emergence of online educational environments has changed the way adolescents learn, which has benefits and drawbacks for their development. This review has as its goal the examination of how personality traits and adolescents’ well-being are associated in the setting of online education. This review analyses the effects of a variety of personality traits on the mental, emotional, and social health of online school-going adolescents by looking at a wide range of previous research. This research explores the mechanisms that mediate or regulate the connection between one's personality traits and well-being in an online educational environment. The elements can be broken down into two categories: technological, like internet availability and digital literacy, and social, including social support, peer interaction, and teacher-student connections. To improve the well-being of adolescents in online learning environments, it is essential to understand factors that moderate the effects of interventions and support systems. This review concludes by emphasising the complex nature of the association between individual differences in personality and the success of online students aged 13 to 18. This review contributes to the development of evidence-based strategies for promoting positive mental health and overall well-being among adolescents engaged in online educational settings by shedding light on the impact of personality traits on various dimensions of well-being and by identifying the mediating or moderating factors. Educators, governments, and parents can use the findings of this review to create an online learning environment that is safe and well-being for adolescents.

Keywords: personality traits, adolescent, wellbeing, online education

Procedia PDF Downloads 43

Authors: Wesam Jasim, Dongbing Gu

Abstract:

This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotors path tracking. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR to stabilize the quadrotor and successfully track different paths. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.

Keywords: iLQR controller, optimal control, path tracking, quadrotor UAVs

Procedia PDF Downloads 432

Authors: Sue S. Feldman

Abstract:

As clinical and nursing informatics mature, an area that has gotten a lot of attention is the value capstone projects. Capstones are meant to address authentic and complex domain-specific problems. While capstone projects have not always been essential in graduate clinical and nursing informatics education, employers are wanting to see evidence of the prospective employee's knowledge and skills as an indication of employability. Capstones can be organized in many ways: a single course over a single semester, multiple courses over multiple semesters, as a targeted demonstration of skills, as a synthesis of prior knowledge and skills, mentored by one single person or mentored by various people, submitted as an assignment or presented in front of a panel. Because of the potential for capstones to enhance the educational experience, and as a mechanism for application of knowledge and demonstration of skills, a rigorous capstone can accelerate a graduate's potential in the workforce. In 2016, the capstone at the University of Alabama at Birmingham (UAB) could feel the external forces of a maturing Clinical and Nursing Informatics discipline. While the program had a capstone course for many years, it was lacking the depth of knowledge and demonstration of skills being asked for by those hiring in a maturing Informatics field. Since the program is online, all capstones were always in the online environment. While this modality did not change, other contributors to instruction modality changed. Pre-2016, the instruction modality was self-guided. Students checked in with a single instructor, and that instructor monitored progress across all capstones toward a PowerPoint and written paper deliverable. At the time, the enrollment was few, and the maturity had not yet pushed hard enough. By 2017, doubling enrollment and the increased demand of a more rigorously trained workforce led to restructuring the capstone so that graduates would have and retain the skills learned in the capstone process. There were three major changes: the capstone was broken up into a 3-course sequence (meaning it lasted about 10 months instead of 14 weeks), there were many chunks of deliverables, and each faculty had a cadre of about 5 students to advise through the capstone process. Literature suggests that the chunking, breaking up complex projects (i.e., the capstone in one summer) into smaller, more manageable chunks (i.e., chunks of the capstone across 3 semesters), can increase and sustain learning while allowing for increased rigor. By doing this, the teaching responsibility was shared across faculty with each semester course being taught by a different faculty member. This change facilitated delving much deeper in instruction and produced a significantly more rigorous final deliverable. Having students advised across the faculty seemed like the right thing to do. It not only shared the load, but also shared the success of students. Furthermore, it meant that students could be placed with an academic advisor who had expertise in their capstone area, further increasing the rigor of the entire capstone process and project and increasing student knowledge and skills.

Keywords: capstones, clinical informatics, health informatics, informatics

Procedia PDF Downloads 120

Authors: Beatriz Garcia-Juan, Ana B. Escrig-Tena, Vicente Roca-Puig

Abstract:

The aim of this article is to conduct a theoretical and empirical study in order to examine how the goal orientation (GO) of public employees affects the relationship between the structural and psychological empowerment that they experience at their workplaces. In doing so, we follow structural empowerment (SE) and psychological empowerment (PE) conceptualizations, and relate them to the public administration framework. Moreover, we review arguments from GO theories, and previous related contributions. Empowerment has emerged as an important issue in the public sector organization setting in the wake of mainstream New Public Management (NPM), the new orientation in the public sector that aims to provide a better service for citizens. It is closely linked to the drive to improve organizational effectiveness through the wise use of human resources. Nevertheless, it is necessary to combine structural (managerial) and psychological (individual) approaches in an integrative study of empowerment. SE refers to a set of initiatives that aim the transference of power from managerial positions to the rest of employees. PE is defined as psychological state of competence, self-determination, impact, and meaning that an employee feels at work. Linking these two perspectives will lead to arrive at a broader understanding of the empowerment process. Specifically in the public sector, empirical contributions on this relationship are therefore important, particularly as empowerment is a very useful tool with which to face the challenges of the new public context. There is also a need to examine the moderating variables involved in this relationship, as well as to extend research on work motivation in public management. It is proposed the study of the effect of individual orientations, such as GO. GO concept refers to the individual disposition toward developing or confirming one’s capacity in achievement situations. Employees’ GO may be a key factor at work and in workforce selection processes, since it explains the differences in personal work interests, and in receptiveness to and interpretations of professional development activities. SE practices could affect PE feelings in different ways, depending on employees’ GO, since they perceive and respond differently to such practices, which is likely to yield distinct PE results. The model is tested on a sample of 521 Spanish local authority employees. Hierarchical regression analysis was conducted to test the research hypotheses using SPSS 22 computer software. The results do not confirm the direct link between SE and PE, but show that learning goal orientation has considerable moderating power in this relationship, and its interaction with SE affects employees’ PE levels. Therefore, the combination of SE practices and employees’ high levels of LGO are important factors for creating psychologically empowered staff in public organizations.

Keywords: goal orientation, moderating effect, psychological empowerment, structural empowerment

Procedia PDF Downloads 271

Authors: Sara Asham Mahrous Kamel

Abstract:

A descriptive statistical analysis of the data showed that the most important factor evoking negative attitudes among teachers is student behavior. have been presented as useful models for understanding the risk factors and protective factors associated with the emergence of autistic traits. Although these "syndrome" forms of autism reach clinical thresholds, they appear to be distinctly different from the idiopathic or "non-syndrome" autism phenotype. Most teachers reported that kindergartens did not prepare them for the educational needs of children with autism, particularly in relation to non-verbal skills. The study is important and points the way for improving teacher inclusion education in Thailand. Inclusive education for students with autism is still in its infancy in Thailand. Although the number of autistic children in schools has increased significantly since the Thai government introduced the Education Regulations for Persons with Disabilities Act in 2008, there is a general lack of services for autistic students and their families. This quantitative study used the Teaching Skills and Readiness Scale for Students with Autism (APTSAS) to test the attitudes and readiness of 110 elementary school teachers when teaching students with autism in general education classrooms. To uncover the true nature of these co morbidities, it is necessary to expand the definition of autism to include the cognitive features of the disorder, and then apply this expanded conceptualization to examine patterns of autistic syndromes. This study used various established eye-tracking paradigms to assess the visual and attention performance of children with DS and FXS who meet the autism thresholds defined in the Social Communication Questionnaire. To study whether the autistic profiles of these children are associated with visual orientation difficulties ("sticky attention"), decreased social attention, and increased visual search performance, all of which are hallmarks of the idiopathic autistic child phenotype. Data will be collected from children with DS and FXS, aged 6 to 10 years, and two control groups matched for age and intellectual ability (i.e., children with idiopathic autism).In order to enable a comparison of visual attention profiles, cross-sectional analyzes of developmental trajectories are carried out. Significant differences in the visual-attentive processes underlying the presentation of autism in children with FXS and DS have been suggested, supporting the concept of syndrome specificity. The study provides insights into the complex heterogeneity associated with autism syndrome symptoms and autism itself, with clinical implications for the utility of autism intervention programs in DS and FXS populations.

Keywords: attitude, autism, teachers, sports activities, movement skills, motor skills

Procedia PDF Downloads 39

Authors: Jummalla Aashrith, N. L. Shiva Sai, K. Bhavya Sri

Abstract:

The swift progress of web technology has not only amassed a vast reservoir of internet data but also triggered a substantial surge in data generation. The internet has metamorphosed into one of the dynamic hubs for online education, idea dissemination, as well as opinion-sharing. Notably, the widely utilized social networking platform Twitter is experiencing considerable expansion, providing users with the ability to share viewpoints, participate in discussions spanning diverse communities, and broadcast messages on a global scale. The upswing in online engagement has sparked a significant curiosity in subjective analysis, particularly when it comes to Twitter data. This research is committed to delving into sentiment analysis, focusing specifically on the realm of Twitter. It aims to offer valuable insights into deciphering information within tweets, where opinions manifest in a highly unstructured and diverse manner, spanning a spectrum from positivity to negativity, occasionally punctuated by neutrality expressions. Within this document, we offer a comprehensive exploration and comparative assessment of modern approaches to opinion mining. Employing a range of machine learning algorithms such as Naive Bayes and Logistic Regression, our investigation plunges into the domain of Twitter data streams. We delve into overarching challenges and applications inherent in the realm of subjectivity analysis over Twitter.

Keywords: machine learning, sentiment analysis, visualisation, python

Procedia PDF Downloads 43

Authors: Oktawia Braniewicz

Abstract:

The phenomenon of emigration and migration increasingly affects Poland's borders as well. For this reason, it is necessary to examine the level of protection of Human Rights in Polish Centres for Foreigners. The field study covered 11 centers for Foreigners in the provinces Kujawsko-Pomorskie Region, Lubelskie Region, Lodzkie Region, Mazowieckie Region and Podlaskie Region. Photographic documentation of living and social conditions, conversations with center employees and refugees allow to show a comprehensive picture of the situation prevailing in Centres for Foreigners. The object of reflection will be, in particular, the standards resulting from art. 8 and 13 of the Convention for the Protection of Human Rights and Fundamental Freedoms and article 2 of Protocol No. 1 to the Convention for the Protection of Human Rights and Fundamental Freedoms. The degree of realization of the right to education and the right to respect for family and private life will be shown. Issues related to learning the Polish language, access to a professional translator and psychological help will also be approximated. Learning Polish is not obligatory, which causes problems with assimilation and integration with other members of the new community. In centers for foreigners, there are no translators - a translator from an external company is rented if necessary. The waiting time for an interpreter makes the refugees feel anxious, unable to communicate with the employees of the centers (this is a situation in which the refugees do not know either English, Polish or Russian). Psychologist's help is available on designated days of the week. There is no separate specialist in child psychology, which is a serious problem.

Keywords: human rights, Polish centres, foreigners, fundamental freedoms

Procedia PDF Downloads 123

Authors: Vathsala Kaluarachchi, Oshani Wimalarathna, Charith Vandebona, Gayani Chandrarathna, Lakmal Rupasinghe, Windhya Rankothge

Abstract:

It is the fundamental function of a monitoring system to allow users to collect and process data. A worldwide threat, the corona outbreak has wreaked havoc in Sri Lanka, and the situation has gotten out of hand. Since the epidemic, the Sri Lankan government has been unable to establish a systematic system for monitoring corona patients and providing emergency care in the event of an outbreak. Most patients have been held at home because of the high number of patients reported in the nation, but they do not yet have access to a functioning medical system. It has resulted in an increase in the number of patients who have been left untreated because of a lack of medical care. The absence of competent medical monitoring is the biggest cause of mortality for many people nowadays, according to our survey. As a result, a smartphone app for analyzing the patient's state and determining whether they should be hospitalized will be developed. Using the data supplied, we are aiming to send an alarm letter or SMS to the hospital once the system recognizes them. Since we know what those patients need and when they need it, we will put up a desktop program at the hospital to monitor their progress. Deep learning, image processing and application development, natural language processing, and blockchain management are some of the components of the research solution. The purpose of this research paper is to introduce a mechanism to connect hospitals and patients even when they are physically apart. Further data security and user-friendliness are enhanced through blockchain and NLP.

Keywords: blockchain, deep learning, NLP, monitoring system

Procedia PDF Downloads 128

Authors: Yunseok Noh, Chang-Uk Kwak, Sun-Joong Kim, Seong-Bae Park

Abstract:

Scripts are one of the basic text resources to understand broadcasting contents. Since broadcast media wields lots of influence over the public, tools for understanding broadcasting contents are more required. Topic modeling is the method to get the summary of the broadcasting contents from its scripts. Generally, scripts represent contents descriptively with directions and speeches. Scripts also provide scene segments that can be seen as semantic units. Therefore, a script can be topic modeled by treating a scene segment as a document. Because scripts consist of speeches mainly, however, relatively small co-occurrences among words in the scene segments are observed. This causes inevitably the bad quality of topics based on statistical learning method. To tackle this problem, we propose a method of learning with additional word co-occurrence information obtained using scene similarities. The main idea of improving topic quality is that the information that two or more texts are topically related can be useful to learn high quality of topics. In addition, by using high quality of topics, we can get information more accurate whether two texts are related or not. In this paper, we regard two scene segments are related if their topical similarity is high enough. We also consider that words are co-occurred if they are in topically related scene segments together. In the experiments, we showed the proposed method generates a higher quality of topics from Korean drama scripts than the baselines.

Keywords: broadcasting contents, scripts, text similarity, topic model

Procedia PDF Downloads 309

Authors: Harvey Sanchez-Restrepo, Jorge Louca

Abstract:

Equity and education are major focus of government policies around the world due to its relevance for addressing the sustainable development goals launched by Unesco. In this research, we developed a primary analysis of a data set of more than one hundred educational and non-educational factors associated with learning, coming from a census-based large-scale assessment carried on in Ecuador for 1.038.328 students, their families, teachers, and school directors, throughout 2014-2018. Each participating student was assessed by a standardized computer-based test. Learning outcomes were calibrated through item response theory with two-parameters logistic model for getting raw scores that were re-scaled and synthetized by a learning index (LI). Our objective was to develop a network for modelling educational deprivation and analyze the structure of inequality gaps, as well as their relationship with socioeconomic status, school financing, and student's ethnicity. Results from the model show that 348 270 students did not develop the minimum skills (prevalence rate=0.215) and that Afro-Ecuadorian, Montuvios and Indigenous students exhibited the highest prevalence with 0.312, 0.278 and 0.226, respectively. Regarding the socioeconomic status of students (SES), modularity class shows clearly that the system is out of equilibrium: the first decile (the poorest) exhibits a prevalence rate of 0.386 while rate for decile ten (the richest) is 0.080, showing an intense negative relationship between learning and SES given by R= –0.58 (p < 0.001). Another interesting and unexpected result is the average-weighted degree (426.9) for both private and public schools attending Afro-Ecuadorian students, groups that got the highest PageRank (0.426) and pointing out that they suffer the highest educational deprivation due to discrimination, even belonging to the richest decile. The model also found the factors which explain deprivation through the highest PageRank and the greatest degree of connectivity for the first decile, they are: financial bonus for attending school, computer access, internet access, number of children, living with at least one parent, books access, read books, phone access, time for homework, teachers arriving late, paid work, positive expectations about schooling, and mother education. These results provide very accurate and clear knowledge about the variables affecting poorest students and the inequalities that it produces, from which it might be defined needs profiles, as well as actions on the factors in which it is possible to influence. Finally, these results confirm that network analysis is fundamental for educational policy, especially linking reliable microdata with social macro-parameters because it allows us to infer how gaps in educational achievements are driven by students’ context at the time of assigning resources.

Keywords: complex network, educational deprivation, evidence-based policy, large-scale assessments, policy informatics

Procedia PDF Downloads 112

Authors: Chih-Chiang Hua, Yi-Hsiung Fang, Cyuan-Jyun Wong

Abstract:

An improved PV balancer for photovoltaic applications is proposed in this paper. The proposed PV balancer senses the voltage and current of PV module and adjusts the output voltage of converter. Thus, the PV system can implement maximum power point tracking (MPPT) independently for each module whether it is under shading, different irradiation or degradation of PV cell. In addition, the cost of PV balancer can be reduced due to the low power rating of converter. To assess the effectiveness of the proposed system, two PV balancers are designed and verified through simulation under different shading conditions. The proposed PV balancers can provide more energy than the traditional PV balancer.

Keywords: MPPT, partial shading, PV System, converter

Procedia PDF Downloads 283

Authors: J. Otegui, M. Agirre, M. A. Cestau, H. Erauskin

Abstract:

The increasing accessibility of mid-priced additive manufacturing (AM) systems offers a chance to incorporate this technology into engineering instruction. Furthermore, AM facilitates the creation of manufacturing designs, enhancing the efficiency of various machines. One example of these machines is the Stirling cycle engine. It encompasses complex thermodynamic machinery, revealing various aspects of mechanical engineering expertise upon closer inspection. In this publication, the application of Stirling Engines fabricated via additive manufacturing techniques will be showcased for the purpose of instructive design and product enhancement. The performance of a Stirling engine's conventional displacer and piston is contrasted. The outcomes of utilizing this instructional tool in teaching are demonstrated.

Keywords: 3D printing, additive manufacturing, mechanical design, stirling engine.

Procedia PDF Downloads 39

Authors: Gizem Yilmazel

Abstract:

Turkiye has been facing failure in English language teaching despite long years of English studies during mandatory education. A body of research studying the reasons of the failure in the literature exists yet the problem has not been solved and English language education is still a phenomenon in Turkiye. The failure is mostly attributed to the methods used in English education (Grammar Translation Method), lack of exposure to the language, inability to practice the language, financial difficulties, the belief of abroad experience necessity, national examinations, and conservative institutional policies. The findings are evident and tangible yet the problem persists. This paper aims to bring the issue a critical perspective and discuss the reasons of the failure.

Keywords: EFL, failure, critical perspective, language education

Procedia PDF Downloads 41

Authors: Bastien Batardière, Joon Kwon

Abstract:

For finite-sum optimization, variance-reduced gradient methods (VR) compute at each iteration the gradient of a single function (or of a mini-batch), and yet achieve faster convergence than SGD thanks to a carefully crafted lower-variance stochastic gradient estimator that reuses past gradients. Another important line of research of the past decade in continuous optimization is the adaptive algorithms such as AdaGrad, that dynamically adjust the (possibly coordinate-wise) learning rate to past gradients and thereby adapt to the geometry of the objective function. Variants such as RMSprop and Adam demonstrate outstanding practical performance that have contributed to the success of deep learning. In this work, we present AdaLVR, which combines the AdaGrad algorithm with loopless variance-reduced gradient estimators such as SAGA or L-SVRG that benefits from a straightforward construction and a streamlined analysis. We assess that AdaLVR inherits both good convergence properties from VR methods and the adaptive nature of AdaGrad: in the case of L-smooth convex functions we establish a gradient complexity of O(n + (L + √ nL)/ε) without prior knowledge of L. Numerical experiments demonstrate the superiority of AdaLVR over state-of-the-art methods. Moreover, we empirically show that the RMSprop and Adam algorithm combined with variance-reduced gradients estimators achieve even faster convergence.

Keywords: convex optimization, variance reduction, adaptive algorithms, loopless

Procedia PDF Downloads 57

Authors: J. Fernandez de Canete, P. Del Saz Orozco, I. Garcia-Moral, A. Akhrymenka

Abstract:

Object-oriented modeling is spreading in current simulation of wastewater treatments plants through the use of the individual components of the process and its relations to define the underlying dynamic equations. In this paper, we describe the use of the free-software OpenModelica simulation environment for the object-oriented modeling of an activated sludge process under feedback control. The performance of the controlled system was analyzed both under normal conditions and in the presence of disturbances. The object-oriented described approach represents a valuable tool in teaching provides a practical insight in wastewater process control field.

Keywords: object-oriented programming, activated sludge process, OpenModelica, feedback control

Procedia PDF Downloads 377

Authors: Jui-Chien Hsieh

Abstract:

Background:12-lead electrocardiography(ECG) is one of frequently-used tools to detect atrial fibrillation (AF), which might degenerate into life-threaten stroke, in clinical Practice. Based on this study, the AF detection by the clinically-used 12-lead ECG device has only 0.73~0.77 positive predictive value (ppv). Objective: It is on great demand to develop a new algorithm to improve the precision of AF detection using 12-lead ECG. Due to the progress on artificial intelligence (AI), we develop an ECG deep model that has the ability to recognize AF patterns and reduce false-positive errors. Methods: In this study, (1) 570-sample 12-lead ECG reports whose computer interpretation by the ECG device was AF were collected as the training dataset. The ECG reports were interpreted by 2 senior cardiologists, and confirmed that the precision of AF detection by the ECG device is 0.73.; (2) 88 12-lead ECG reports whose computer interpretation generated by the ECG device was AF were used as test dataset. Cardiologist confirmed that 68 cases of 88 reports were AF, and others were not AF. The precision of AF detection by ECG device is about 0.77; (3) A parallel 4-layer 1 dimensional convolutional neural network (CNN) was developed to identify AF based on limb-lead ECGs and chest-lead ECGs. Results: The results indicated that this model has better performance on AF detection than traditional computer interpretation of the ECG device in 88 test samples with 0.94 ppv, 0.98 sensitivity, 0.80 specificity. Conclusions: As compared to the clinical ECG device, this AI ECG model promotes the precision of AF detection from 0.77 to 0.94, and can generate impacts on clinical applications.

Keywords: 12-lead ECG, atrial fibrillation, deep learning, convolutional neural network

Procedia PDF Downloads 109

Authors: Nutcha Taneepanichskul, Helen C. Hailes, Mark Miodownik

Abstract:

Plastic waste has emerged as a critical global environmental challenge, primarily driven by the prevalent use of conventional plastics derived from petrochemical refining and manufacturing processes in modern packaging. While these plastics serve vital functions, their persistence in the environment post-disposal poses significant threats to ecosystems. Addressing this issue necessitates approaches, one of which involves the development of biodegradable plastics designed to degrade under controlled conditions, such as industrial composting facilities. It is imperative to note that compostable plastics are engineered for degradation within specific environments and are not suited for uncontrolled settings, including natural landscapes and aquatic ecosystems. The full benefits of compostable packaging are realized when subjected to industrial composting, preventing environmental contamination and waste stream pollution. Therefore, effective sorting technologies are essential to enhance composting rates for these materials and diminish the risk of contaminating recycling streams. In this study, it leverage hyperspectral imaging technology (HSI) coupled with advanced machine learning algorithms to accurately identify various types of plastics, encompassing conventional variants like Polyethylene terephthalate (PET), Polypropylene (PP), Low density polyethylene (LDPE), High density polyethylene (HDPE) and biodegradable alternatives such as Polybutylene adipate terephthalate (PBAT), Polylactic acid (PLA), and Polyhydroxyalkanoates (PHA). The dataset is partitioned into three subsets: a training dataset comprising uncontaminated conventional and biodegradable plastics, a validation dataset encompassing contaminated plastics of both types, and a testing dataset featuring real-world packaging items in both pristine and contaminated states. Five distinct machine learning algorithms, namely Partial Least Squares Discriminant Analysis (PLS-DA), Support Vector Machine (SVM), Convolutional Neural Network (CNN), Logistic Regression, and Decision Tree Algorithm, were developed and evaluated for their classification performance. Remarkably, the Logistic Regression and CNN model exhibited the most promising outcomes, achieving a perfect accuracy rate of 100% for the training and validation datasets. Notably, the testing dataset yielded an accuracy exceeding 80%. The successful implementation of this sorting technology within recycling and composting facilities holds the potential to significantly elevate recycling and composting rates. As a result, the envisioned circular economy for plastics can be established, thereby offering a viable solution to mitigate plastic pollution.

Keywords: biodegradable plastics, sorting technology, hyperspectral imaging technology, machine learning algorithms

Procedia PDF Downloads 68