Search results for: grief education and training

Authors: Garry Gorman, Nigel McKelvey, James Connolly

Abstract:

This study will evaluate a growth mindset intervention with Junior Cycle Coding and Senior Cycle Computer Science students in Ireland, where gamification will be used to incentivise growth mindset behaviour. An artificial intelligence (AI) driven personalised learning system will be developed to present computer programming learning tasks in a manner that is best suited to the individuals’ own learning preferences while incentivising and rewarding growth mindset behaviour of persistence, mastery response to challenge, and challenge seeking. This research endeavours to measure mindset with before and after surveys (conducted nationally) and by recording growth mindset behaviour whilst playing a digital game. This study will harness the capabilities of AI and aims to determine how a personalised learning (PL) experience can impact the mindset of a broad range of students. The focus of this study will be to determine how personalising the learning experience influences female and disadvantaged students' sense of belonging in the computer science classroom when tasks are presented in a manner that is best suited to the individual. Whole Brain Learning will underpin this research and will be used as a framework to guide the research in identifying key areas such as thinking and learning styles, cognitive potential, motivators and fears, and emotional intelligence. This research will be conducted in multiple school types over one academic year. Digital games will be played multiple times over this period, and the data gathered will be used to inform the AI algorithm. The three data sets are described as follows: (i) Before and after survey data to determine the grit scores and mindsets of the participants, (ii) The Growth Mind-Set data from the game, which will measure multiple growth mindset behaviours, such as persistence, response to challenge and use of strategy, (iii) The AI data to guide PL. This study will highlight the effectiveness of an AI-driven personalised learning experience. The data will position AI within the Irish educational landscape, with a specific focus on the teaching of CS. These findings will benefit coding and computer science teachers by providing a clear pedagogy for the effective delivery of personalised learning strategies for computer science education. This pedagogy will help prevent students from developing a fixed mindset while helping pupils to exhibit persistence of effort, use of strategy, and a mastery response to challenges.

Keywords: computer science education, artificial intelligence, growth mindset, pedagogy

Procedia PDF Downloads 87

Authors: Daisy Owomugasho Ndikuno

Abstract:

The paper explores the extent to which mindset change has been critical in the community rural development in Uganda. It is descriptive research with The Parish Development Model as a case study. The results show that rural community development is possible and its success largely depends on harnessing local resources and knowledge; leveraging education, empowerment and awareness; creating sustainable livelihoods and encouraging entrepreneurship and innovation; access to financial resources; and building collaborative networks and partnerships. In all these, the role of mindset change is critical. By instilling a positive, collaborative and innovative mindset, rural communities can overcome challenges and chat a path towards sustainable development.

Keywords: community, development, mindset, change

Procedia PDF Downloads 93

Authors: Smita Mathur

Abstract:

Play is an innate, player-centric, joyful, fundamental activity of early childhood development that significantly contributes to social, emotional, and academic learning. Leveraging the power of play can enhance these domains by creating engaging, interactive, and developmentally appropriate learning experiences for young children. This research aimed to systematically examine young children’s play behaviors with a focus on four primary objectives: (1) the frequency and duration of on-task behaviors, (2) social interactions and emotional expressions during play, (3) the correlation between academic skills and play, and (4) identifying best practices for integrating play-based curricula. To achieve these objectives, a mixed-method study was conducted among young preschool-aged children in low socio-economic populations in the United States. The children were identified using purposive sampling. The children were observed during structured play in classrooms and unstructured play during outdoor playtime and in their home environments. The study sampled 97 preschool-aged children. A total of 3970 minutes of observations were coded to address the research questions. Thirty-seven percent of children lived in linguistically isolated families, and 76% lived in basic budget poverty. Children lived in overcrowded housing situations (67%), and most families had mixed citizenship status (66%). The observational study was conducted using the observation protocol during the Oxford Study Project. On-task behaviors were measured by tracking the frequency and duration of activities where children maintained focus and engagement. In examining social interactions and emotional expressions, the study recorded social interactions, emotional responses, and teacher involvement during play. The study aimed to identify best practices for integrating play-based curricula into early childhood education. By analyzing the effectiveness of different play-based strategies and their impact on on-task behaviors, social-emotional development, and academic skills, the research sought to provide actionable recommendations for educators and caregivers. The findings from study 1. Highlight play behaviors that increase on-task behaviors and academic, & social skills in young children. 2. Offers insights into teacher preparation and designing play-based curriculum 3. Research critiques observation as a data collection technique.

Keywords: play, early childhood education, social-emotional development, academic development

Procedia PDF Downloads 27

Authors: Omid Kalatpour, Mohammadreza Ajdari

Abstract:

This article studied the possible causes of human error-induced incidents in the petrochemical industry maintenance activities by using Human Factors Analysis and Classification System (HFACS). The purpose of the study was anticipating and identifying these causes and proposing corrective and preventive actions. Maintenance department in a petrochemical company was selected for research. A checklist of human error-induced incidents was developed based on four HFACS main levels and nineteen sub-groups. Hierarchical task analysis (HTA) technique was used to identify maintenance activities and tasks. The main causes of possible incidents were identified by checklist and recorded. Corrective and preventive actions were defined depending on priority. Analyzing the worksheets of 444 activities in four levels of HFACS showed 37.6% of the causes were at the level of unsafe actions, 27.5% at the level of unsafe supervision, 20.9% at the level of preconditions for unsafe acts and 14% of the causes were at the level of organizational effects. The HFACS sub-groups showed errors (24.36%) inadequate supervision (14.89%) and violations (13.26%) with the most frequency. According to findings of this study, increasing the training effectiveness of operators and supervision improvement respectively are the most important measures in decreasing the human error-induced incidents in petrochemical industry maintenance.

Keywords: human error, petrochemical industry, maintenance, HFACS

Procedia PDF Downloads 242

Authors: Aragorn Joaquin Pineda Dela Cruz

Abstract:

Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

Procedia PDF Downloads 102

Authors: Xinyi Le

Abstract:

In this paper, 3D printing orientations were determined through our perceptual model. Some FDM (Fused Deposition Modeling) 3D printers, which are widely used in universities and industries, often require support structures during the additive manufacturing. After removing the residual material, some surface artifacts remain at the contact points. These artifacts will damage the function and visual effect of the model. To prevent the impact of these artifacts, we present a fuzzy extreme learning machine approach to find printing directions that avoid placing supports in perceptually significant regions. The proposed approach is able to solve the evaluation problem by combing both the subjective knowledge and objective information. Our method combines the advantages of fuzzy theory, auto-encoders, and extreme learning machine. Fuzzy set theory is applied for dealing with subjective preference information, and auto-encoder step is used to extract good features without supervised labels before extreme learning machine. An extreme learning machine method is then developed successfully for training and learning perceptual models. The performance of this perceptual model will be demonstrated on both natural and man-made objects. It is a good human-computer interaction practice which draws from supporting knowledge on both the machine side and the human side.

Keywords: 3d printing, perceptual model, fuzzy evaluation, data-driven approach

Procedia PDF Downloads 438

Authors: Nivedita Ghosh

Abstract:

In his critique of Lefebvre’s view that ‘technological capacities’ are class-dependent, Francois Hetman argues that technology today is participatory, allowing the entry of individuals from different levels of social stratification. As a result, we are entering into an era of technology operators or ‘clerks’ who become the new decision-makers because of the knowledge they possess of the use of technologies. In response to Hetman’s thesis, this paper argues that knowledge of technology, while indeed providing a momentary space for decision-making, does not necessarily restructure social hierarchies. Through case studies presented from the world of Indian documentary filmmaking, this paper puts forth the view that Hetman’s clerks, despite being technologically advanced, do not break into the filmmaking hierarchical order. This remains true even for a situation where technical knowledge rests most with those in the lowest rungs of the filmmaking ladder. Instead, technological knowledge provides the space for other kinds of relationships to evolve, such as those of ‘trusting the technician’ or ‘admiration for the technician’s work’. Furthermore, what continues to define documentary filmmaking hierarchy is conceptualization capacities of the practitioners, which are influenced by a similarity in socio-cultural backgrounds and film school training accessible primarily to the filmmakers instead of the technicians. Accordingly, the paper concludes with the argument that more than ‘technological-capacities’, it is ‘conceptualization capacities’ which are class-dependent, especially when we study the field of documentary filmmaking.

Keywords: documentary filmmaking, India, technology, knowledge, hierarchy

Procedia PDF Downloads 262

Authors: Sozan H. Omar, Lina L. Al-Rewaili

Abstract:

The current study aimed to measure the fifth Grade student skills of reading illustrates in physical and chemical chapter included in science textbook, as well as identity the tasks the dispersants related to designing these illustrates which obstruct the students to read them properly. The researcher applied the test instrument of open discuss questions to measure the skill of: recognizing, description, interpretation and assessment for a sample of this research consisted of (269) students who read three illustrates, and conduct an interview with sample of them (27) students to recognize the dispersants related to designing of these illustrates. The study results showed that there are poor levels in illustrated drawing reading skills: description, interpretation, and assessment. The most important dispersants which obstruct the students to read theses illustrates properly representing: Art impacts of these illustrates, there are some elements which don’t serve these illustrates. In the light of the above results, the researcher provided some recommendations such as training the students on using the images and illustrates properly in science textbooks, as well as create simple designs of illustrates and they should be free of crowded elements and impacts which don’t serve the illustrates.

Keywords: reading illustrated drawings skills, fifth grade science, physical and chemical changes

Procedia PDF Downloads 374

Authors: Mengyu Lu, Yongsheng Guo

Abstract:

This study investigates how employee incentives affect employee performance in financing from customers. This study followed a grounded theory approach where data were collected through 29 interviews. Main themes and categories were identified through the coding processes. This study found that casual conditions, including financial barriers, informal finance, business location, customer base and customer relationship, influenced the adoption of customer finance in the case of SMEs. The SMEs build and maintain long-term relationships with customers through personal communications. The SMEs engage and motivate employees in customer communications and business financing strategy through financial incentives programs, including bonuses, salary rises, rewards and non-financial incentives, including training opportunities, extra holiday leave, and flexible working hours. Employee performance was measured through financing contribution and job contribution. As a consequence, customers will be well served by employees and get a better customer experience. SMEs can get benefits such as employee engagement, employee satisfaction and sustainable financing sources. This study gets in sight of employee incentives in improving employee performance in customer finance and makes implications to human capital theories. Suggestions are provided to the decision-makers in businesses as incentive programs improve employee performance that, eventually contributes to overall business performance.

Keywords: SMEs, financing from customers, employee incentives, performance-based measurement

Procedia PDF Downloads 56

Authors: Rajasekhar Mamilla, G. Janardhana, G. Anjan Babu

Abstract:

The present research studies analyses the students’ satisfaction with university performance regarding the reliability dimension, ability of professors and staff to perform the promised services with quality to students in the post-graduate courses offered by Sri Venkateswara University in India. The research is done with the notion that the student compares the perceived performance with prior expectations. Customer satisfaction is seen as the outcome of this comparison. The sample respondents were administered with the schedule based on the stratified random technique for this study. Statistical techniques such as factor analysis, t-test and correlation analysis were used to accomplish the respective objectives of the study.

Keywords: satisfaction, reliability, service quality, customer

Procedia PDF Downloads 549

Authors: Zhiyan Meng, Dan Liu, Jintao Meng

Abstract:

Dependable encrypted traffic classification is crucial for improving cybersecurity and handling the growing amount of data. Large language models have shown that learning from large datasets can be effective, making pre-trained methods for encrypted traffic classification popular. However, attention-based pre-trained methods face two main issues: their large neural parameters are not suitable for low-computation environments like mobile devices and real-time applications, and they often overfit by getting stuck in local minima. To address these issues, we developed a lightweight transformer model, which reduces the computational parameters through lightweight vocabulary construction and Squeeze-and-Excitation Block. We use sharpness-aware optimization to avoid local minima during pre-training and capture temporal features with relative positional embeddings. Our approach keeps the model's classification accuracy high for downstream tasks. We conducted experiments on four datasets -USTC-TFC2016, VPN 2016, Tor 2016, and CICIOT 2022. Even with fewer than 18 million parameters, our method achieves classification results similar to methods with ten times as many parameters.

Keywords: sharpness-aware optimization, encrypted traffic classification, squeeze-and-excitation block, pretrained model

Procedia PDF Downloads 30

Authors: Kh. Alaa, Sh. Sarah, J. Khowlah, S. Liyakathunsia

Abstract:

Education has become very important nowadays and with the rapidly increasing number of student, taking the attendance manually is getting very difficult and time wasting. In order to solve this problem, an automated solution is required. An effective automated system can be implemented to manage student attendance in different ways. This research will discuss a unique class attendance system which integrates both Face Recognition and RFID technique. This system focuses on reducing the time spent on submitting of the lecture and the wastage of time on submitting and getting approval for the absence excuse and sick leaves. As a result, the suggested solution will enhance not only the time, also it will also be helpful in eliminating fake attendance.

Keywords: attendance system, face recognition, RFID, process model, cost, time

Procedia PDF Downloads 375

Authors: Mitra Savabi-Esfahani, Fariba Taleghani, Mahnaz Noroozi, Maryam Tabatabaeian, Elsebeth Lynge

Abstract:

Breast cancer is a health concern in worldwide. All women have not adequate information about breast cancer, resulting in undetected some tumors until advanced stages. Therefore awareness of people was recommended as a strategy to control that. The aim of this study was to assess the effect of an educational intervention on women's knowledge and attitude about breast cancer and screening. This study was conducted in 2016 on 191 women. All women living in one of big cities were invited to enroll in training classes. Inclusion criteria consisted women who were 20 - 69 years and not participated in any educational intervention. The lecture with group discussion was used as educational methods. Data collection tool was a structured questionnaire which filled out before and after intervention. The reliability of the questionnaire was determined by Cronbach's alpha. The data were analyzed using SPSS software. The average age was 44/4 ± 11.5 and 42.6% of the women had obtained high school. Of the 191 women, 70(36.6%) and 76(39.8%) had low and medium level of knowledge respectively and half of them, 95(50%) had medium level of attitude in before intervention. There was significant difference between mean scores of knowledge and attitude before and after the intervention by Paired T test (p < 0/001). It seems applying effective educational interventions can increase knowledge and attitude women about breast cancer particularly in community that they have insufficient levels. Moreover, the lecture method along with group discussion can be proposed as effective and conventional methods for this purpose.

Keywords: attitude, breast cancer, educational intervention, knowledge

Procedia PDF Downloads 309

Authors: Gae Hee Song

Abstract:

This paper aims to address the evolution of public-private partnerships for mainstreaming an evaluation approach in the community-based education project. It examines the distinctive features of Save the Children’s School Me project in terms of empowerment evaluation principles introduced by David M. Fetterman, especially community ownership, capacity building, and organizational learning. School Me is a Save the Children Korea funded-project, having been implemented in Cote d’Ivoire and Sierra Leone since 2016. The objective of this project is to reduce gender-based disparities in school completion and learning outcomes by creating an empowering learning environment for girls and boys. Both quasi-experimental and experimental methods for impact evaluation have been used to explore changes in learning outcomes, gender attitudes, and learning environments. To locate School Me in the public-private partnership framework for community empowerment and sustainability, the data have been collected from School Me progress/final reports, baseline, and endline reports, fieldwork observations, inter-rater reliability of baseline and endline data collected from a total of 75 schools in Cote d’Ivoire and Sierra Leone. The findings of this study show that School Me project has a significant evaluation component, including qualitative exploratory research, participatory monitoring, and impact evaluation. It strongly encourages key actors, girls, boys, parents, teachers, community leaders, and local education authorities, to participate in the collection and interpretation of data. For example, 45 community volunteers collected baseline data in Cote d’Ivoire; on the other hand, three local government officers and fourteen enumerators participated in the follow-up data collection of Sierra Leone. Not only does this public-private partnership improve local government and community members’ knowledge and skills of monitoring and evaluation, but the evaluative findings also help them find their own problems and solutions with a strong sense of community ownership. Such community empowerment enables Save the Children country offices and member offices to gain invaluable experiences and lessons learned. As a result, empowerment evaluation leads to community-oriented governance and the sustainability of the School Me project.

Keywords: community empowerment, Cote d’Ivoire, empowerment evaluation, public-private partnership, save the children, school me, Sierra Leone, sustainability

Procedia PDF Downloads 125

Authors: Moshe Leiba, Doron Zohar

Abstract:

Computer Science (CS) and programming is still considered a boy’s club and is a male-dominated profession. This is also the case in high schools and higher education. In Israel, not different from the rest of the world, there are less than 35% of female students in CS studies that take the matriculation exams. The Israeli matriculation exams are written in a masculine form language. Gender-fair language (GFL) aims at reducing gender stereotyping and discrimination. There are several strategies that can be employed to make languages gender-fair and to treat women and men symmetrically (especially in languages with grammatical gender, among them neutralization and using the plural form. This research aims at exploring computer science teachers’ beliefs regarding the use of gender-fair language in exams. An exploratory quantitative research methodology was employed to collect the data. A questionnaire was administered to 353 computer science teachers. 58% female and 42% male. 86% are teaching for at least 3 years, with 59% of them have a teaching experience of 7 years. 71% of the teachers teach in high school, and 82% of them are preparing students for the matriculation exam in computer science. The questionnaire contained 2 matriculation exam questions from previous years and open-ended questions. Teachers were asked which form they think is more suited: (a) the existing form (mescaline), (b) using both gender full forms (e.g., he/she), (c) using both gender short forms, (d) plural form, (e) natural form, and (f) female form. 84% of the teachers recognized the need to change the existing mescaline form in the matriculation exams. About 50% of them thought that using the plural form was the best-suited option. When examining the teachers who are pro-change and those who are against, no gender differences or teaching experience were found. The teachers who are pro gender-fair language justified it as making it more personal and motivating for the female students. Those who thought that the mescaline form should remain argued that the female students do not complain and the change in form will not influence or affect the female students to choose to study computer science. Some even argued that the change will not affect the students but can only improve their sense of identity or feeling toward the profession (which seems like a misconception). This research suggests that the teachers are pro-change and believe that re-formulating the matriculation exams is the right step towards encouraging more female students to choose to study computer science as their major study track and to bridge the gap for gender equality. This should indicate a bottom-up approach, as not long after this research was conducted, the Israeli ministry of education decided to change the matriculation exams to gender-fair language using the plural form. In the coming years, with the transition to web-based examination, it is suggested to use personalization and adjust the language form in accordance with the student's gender.

Keywords: compter science, gender-fair language, teachers, national exams

Procedia PDF Downloads 112

Authors: Nur Sofi Hidayah, Ratih Tri Purwatiningsih

Abstract:

Learning is a process attempts person to obtain a new behavior changes as a whole, as a result of his own experience in the interaction with the environment. Learning involves our brain to think, while the ability of the brain to each student's performance is different. To obtain optimal learning results then need time to learn the exact hour that the brain's performance is not too heavy. Referring to the learning system in Finland which apply 45 minutes to learn and a 15-minute break is expected to be the brain work better, with the rest of the brain, the brain will be more focused and lessons can be absorbed well. It can be concluded that learning in this way students learn with brain always fresh and the best possible use of the time, but it can make students not saturated in a lesson.

Keywords: learning, working hours brain, time efficient learning, working hours in the brain receive stimulus.

Procedia PDF Downloads 397

Authors: Sean Sloan

Abstract:

Probability Risk Assessments (PRA) can be a difficult concept for students to grasp. So in searching for different ways to describe PRA to relate it to their lives; COVID-19 came up. The parallels are amazing. Soon students began analyzing acceptable risk with the virus. This helped them to quantify just how dangerous is dangerous. The original lesson was dismissed and for the remainder of the period, the probability of risk, and the lethality of risk became the topic. Spreading events such as a COVID carrier on an airline became analogous to single fault casualties such as a Tsunami. Odds of spreading became odds of backup-diesel-generator failure – like with Fukashima Daiichi. Fatalities of the disease became expected fatalities due to radiation spread. Quantification from this discussion took it from hyperbole and emotion into one where we could rationally base guidelines. It has been one of the most effective educational devices observed.

Keywords: COVID, education, probability, risk

Procedia PDF Downloads 152

Authors: Arpan Upadhyaya, Sunaina Kuknor

Abstract:

The paper examines the succession management strategies and the preparation level of heirs in the context of family-owned educational institutions in Nepal. Sixteen in-depth, semi-structured interviews with the institution's leader were conducted. The study's findings show the lack of awareness about the importance of succession planning among the institution owners due to the availability of limited resources. The paper also provides some insights into how family ownership and management are done and the lack of formal processes in succession management strategies. It will aid researchers in considering the societal perspective of the successor, which is also a significant worry.

Keywords: effective plans, family business, interest, leadership, successor

Procedia PDF Downloads 112

Authors: Glenn Guira

Abstract:

Domestic violence is an international pandemic that has affected women from all walks of life. The World Health Organization (2016), announced that recent global prevalence of violence against women indicates that 1 in 3 (35 %) women worldwide have experienced either physical and/or sexual intimate partner violence or non-partner violence in their lifetime. It further said that violence against women is a major public health problem and violations of women’s human rights. Furthermore, the agency said that the factors associated in an increased risk of experiencing intimate partner and sexual violence include low education, child maltreatment or exposure to violence between parents, abuse during childhood, attitudes accepting violence and gender inequality. This is an integrative review of domestic violence focusing on four themes namely types of domestic violence against women, predictors of domestic violence against women, effects of domestic violence against women and strategies in addressing domestic violence against women. This integrative research study was conducted to identify relevant themes on domestic violence that was conducted and published. This study is geared toward understanding further domestic violence as a public health concern. Using the keywords domestic violence, Google Scholar, MEDLINE PLUS, and Ingenta Connect were searched to identify relevant studies. This resulted in 3,467 studies that fall within the copyright year 2006 – 2016. The studies were delimited to domestic violence against women because there are other types of violence that can be committed such as senior citizens abuse, child abuse, violence against males and gay/lesbian abuse. The significant findings of the research study are the following: the forms of domestic violence against women include physical, sexual, psychological, emotional, economic, spiritual and conflict-related violence against, the predictors of domestic violence against women include demographic, health-related, psychological, behavioral, partner-related and social-stress factors, the effects of domestic violence against women include victim-related factors and child-related factors and the strategies addressing domestic violence against women include personal-related strategies, education-related strategies, health-related strategies, legal-related strategies and judicial-related strategies. Consequent to the foregoing findings, the following conclusions are drawn by the researcher that there are published researches that presented different forms, predictors, effects and strategies addressing domestic violence committed by perpetrators against women. The researcher recommended that the summarized comprehensive data should be use to educate people who are potential victims of domestic violence and that future researchers should continue to conduct research for the development of pragmatic programs aimed at reducing domestic violence.

Keywords: domestic violence, physical abuse, intimate partner violence, sexual violence

Procedia PDF Downloads 267

Authors: Amir Hossein Hejazi, Nima Amjady

Abstract:

In recent years, due to environmental issues traditional energy sources had been replaced by renewable ones. Wind energy as the fastest growing renewable energy shares a considerable percent of energy in power electricity markets. With this fast growth of wind energy worldwide, owners and operators of wind farms, transmission system operators, and energy traders need reliable and secure forecasts of wind energy production. In this paper, a new forecasting strategy is proposed for short-term wind power prediction based on Echo State Networks (ESN). The forecast engine utilizes state-of-the-art training process including dynamical reservoir with high capability to learn complex dynamics of wind power or wind vector signals. The study becomes more interesting by incorporating prediction of wind direction into forecast strategy. The Big Bang-Big Crunch (BB-BC) evolutionary optimization algorithm is adopted for adjusting free parameters of ESN-based forecaster. The proposed method is tested by real-world hourly data to show the efficiency of the forecasting engine for prediction of both wind vector and wind power output of aggregated wind power production.

Keywords: wind power forecasting, echo state network, big bang-big crunch, evolutionary optimization algorithm

Procedia PDF Downloads 572

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 51

Authors: YingWei Tan, XueFeng Ding

Abstract:

Attention-based voice activity detection models have gained significant attention in recent years due to their fast training speed and ability to capture a wide contextual range. The inclusion of multi-head style and position embedding in the attention architecture are crucial. Having multiple attention heads allows for differential focus on different parts of the sequence, while position embedding provides guidance for modeling dependencies between elements at various positions in the input sequence. In this work, we propose an approach by considering each head as a node, enabling the application of graph neural networks (GNN) to identify correlations among the different nodes. In addition, we adopt an implementation named rotary position embedding (RoPE), which encodes absolute positional information into the input sequence by a rotation matrix, and naturally incorporates explicit relative position information into a self-attention module. We evaluate the effectiveness of our method on a synthetic dataset, and the results demonstrate its superiority over the baseline CRNN in scenarios with low signal-to-noise ratio and noise, while also exhibiting robustness across different noise types. In summary, our proposed framework effectively combines the strengths of CNN and RNN (LSTM), and further enhances detection performance through the integration of graph neural networks and rotary position embedding.

Keywords: voice activity detection, CRNN, graph neural networks, rotary position embedding

Procedia PDF Downloads 71

Authors: Zahra Alipour, Amirreza Moheb Afzali

Abstract:

In the field of human-computer interaction (HCI), hand gestures play a crucial role in facilitating communication by expressing emotions and intentions. The precise tracking of the index finger and the estimation of joint positions are essential for developing effective gesture recognition systems. However, various challenges, such as anatomical variations, occlusions, and environmental influences, hinder optimal functionality. This study investigates the performance of the YOLOv8m model for hand detection using the EgoHands dataset, which comprises diverse hand gesture images captured in various environments. Over three training processes, the model demonstrated significant improvements in precision (from 88.8% to 96.1%) and recall (from 83.5% to 93.5%), achieving a mean average precision (mAP) of 97.3% at an IoU threshold of 0.7. We also compared YOLOv8m with MediaPipe and an integrated YOLOv8 + MediaPipe approach. The combined method outperformed the individual models, achieving an accuracy of 99% and a recall of 99%. These findings underscore the benefits of model integration in enhancing gesture recognition accuracy and localization for real-time applications. The results suggest promising avenues for future research in HCI, particularly in augmented reality and assistive technologies, where improved gesture recognition can significantly enhance user experience.

Keywords: YOLOv8, mediapipe, finger tracking, joint estimation, human-computer interaction (HCI)

Procedia PDF Downloads 5

Authors: Henry Wilde, Thiravat Hemachudha

Abstract:

Human rabies deaths are underreported worldwide at 55,000 annual cases; more than of dengue and Japanese encephalitis. Almost half are children. A recent study from the Philippines of nearly 2,000 rabies deaths revealed that none of had received incomplete or no post exposure prophylaxis. Coming from a canine rabies endemic country, this is not unique. There are two major barriers to reducing human rabies deaths: 1) the large number of unvaccinated dogs and 2) post-exposure prophylaxis (PEP) that is not available, incomplete, not affordable, or not within reach for bite victims travel means. Only the first barrier, inadequate vaccination of dogs, is now being seriously addressed. It is also often not done effectively or sustainably. Rabies PEP has evolved as a complex, prolonged process, usually delegated to centers in larger cities. It is virtually unavailable in villages or small communities where most dog bites occur, victims are poor and usually unable to travel a long distance multiple times to receive PEP. Reseacrh that led to better understanding of the pathophysiology of rabies and immune responses to potent vaccines and immunoglobulin have allowed shortening and making PEP more evidence based. This knowledge needs to be adopted and applied so that PEP can be rendered safely and affordably where needed the most: by village health care workers who have long performed more complex services after appropriate training. Recent research makes this an important and long neglected goal that is now within our means to implement.

Keywords: rabies, post-exposure prophylaxis, availability, immunoglobulin

Procedia PDF Downloads 264

Authors: Paulo Sérgio Ribeiro de Araújo Bogas

Abstract:

Although several studies have assumed (at least implicitly) that learners' approaches to learning develop into deeper approaches to higher education, there appears to be no clear theoretical basis for this assumption and no empirical evidence. As a scientific contribution to this discussion, a pedagogical intervention of a quasi-experimental nature was developed, with a mixed methodology, evaluating the intervention within a single curricular unit of Marketing, using cases based on real challenges of brands, business simulation, and customer projects. Primary and secondary experiences were incorporated in the intervention: the primary experiences are the experiential activities themselves; the secondary experiences result from the primary experience, such as reflection and discussion in work teams. A diversified learning relationship was encouraged through the various connections between the different members of the learning community. The present study concludes that in the same context, the student's responses can be described as students who reinforce the initial deep approach, students who maintain the initial deep approach level, and others who change from an emphasis on the deep approach to one closer to superficial. This typology did not always confirm studies reported in the literature, namely, whether the initial level of deep processing would influence the superficial and the opposite. The result of this investigation points to the inclusion of pedagogical and didactic activities that integrate different motivations and initial strategies, leading to the possible adoption of deep approaches to learning since it revealed statistically significant differences in the difference in the scores of the deep/superficial approach and the experiential level. In the case of real challenges, the categories of “attribution of meaning and meaning of studied” and the possibility of “contact with an aspirational context” for their future professional stand out. In this category, the dimensions of autonomy that will be required of them were also revealed when comparing the classroom context of real cases and the future professional context and the impact they may have on the world. Regarding the simulated practice, two categories of response stand out: on the one hand, the motivation associated with the possibility of measuring the results of the decisions taken, an awareness of oneself, and, on the other hand, the additional effort that this practice required for some of the students.

Keywords: experiential learning, higher education, mixed methods, reflective learning, marketing

Procedia PDF Downloads 83

Authors: M. J. Ponnambalam

Abstract:

Physics Outreach in Jamaica has nearly tripled the number of students doing Introductory Calculus-based Physics at the University of the West Indies (UWI, Mona) within 5 years, and thus has shown the importance of Physics Teaching & Learning in Informal Settings. In 1899, the first president of the American Physical Society called Physics, “the science above all sciences.” Sure enough, exactly one hundred years later, Time magazine proclaims Albert Einstein, “Person of the Century.” Unfortunately, Physics seems to be losing that glow in this century. Many countries, big and small, are finding it difficult to attract bright young minds to pursue Physics. At UWI, Mona, the number of students in first year Physics dropped to an all-time low of 81 in 2006, from more than 200 in the nineteen eighties, spelling disaster for the Physics Department! The author of this paper launched an aggressive Physics Outreach that same year, aimed at conveying to the students and the general public the following messages: i) Physics is an exciting intellectual enterprise, full of fun and delight. ii) Physics is very helpful in understanding how things like TV, CD player, car, computer, X-ray, CT scan, MRI, etc. work. iii) The critical and analytical thinking developed in the study of Physics is of inestimable value in almost any field. iv) Physics is the core subject for Science and Technology, and hence of national development. Science Literacy is a ‘must’ for any nation in the 21st century. Hence, the Physics Outreach aims at reaching out to every person, through every possible means. The Outreach work is split into the following target groups: i) Universities, ii) High Schools iii) Middle Schools, iv) Primary Schools, v) General Public, and vi) Physics teachers in High Schools. The programmes, tools and best practices are adjusted to suit each target group. The feedback from each group is highly positive. e.g. In February 2014, the author conducted in 3 Primary Schools the Interactive Show on ‘Science Is Fun’ to stimulate 290 students’ interest in Science – with lively and interesting demonstrations and experiments in a highly interactive way, using dramatization, story-telling and dancing. The feedback: 47% found the Show ‘Exciting’ and 51% found it ‘Interesting’ – totaling an impressive 98%. When asked to describe the Show in their own words, the leading 4 responses were: ‘Fun’ (26%), ‘Interesting’ (20%), ‘Exciting’ (14%) and ‘Educational’ (10%) – confirming that ‘fun’ & ‘education’ can go together. The success of Physics Outreach in Jamaica verifies the following words of Chodos, Associate Executive Officer of the American Physical Society: “If we could get members to go to K-12 schools and levitate a magnet or something, we really think these efforts would bring great rewards.”

Keywords: physics education, physics popularization, UWI, Jamaica

Procedia PDF Downloads 407

Authors: Faris Algahtani

Abstract:

The COVID 19 pandemic and associated public health measures have disrupted the lives of peoplearound the world, including children. There is little knowledge about how pandemic measures have affected children in the Kingdom of Saudi Arabia (KSA). The aim and objectives of this qualitative study was to learn about the outcomes and impacts of the pandemic on children ages 0-8 in KSA. The study was based on 40 in-depth interviews that were conducted with experts in health, social protection, education, and early learning, children with special needs, and economics, including decision makers as well as specialists in service provision. The interviews were recorded and translated from Arabic to English into summary notes. The narrative was coded and analyzed following a thematic analysis.

Keywords: disabilities, COVID-19, families, children

Procedia PDF Downloads 211

Authors: Mehdi Montakhabrazlighi, Ercan Balikci

Abstract:

The neural network (NN) method is applied to alloy development of single crystal Ni-base Superalloys with low density and improved mechanical strength. A set of 1200 dataset which includes chemical composition of the alloys, applied stress and temperature as inputs and density and time to rupture as outputs is used for training and testing the network. Thermodynamic phase diagram modeling of the screened alloys is performed with Thermocalc software to model the equilibrium phases and also microsegregation in solidification processing. The model is first trained by 80% of the data and the 20% rest is used to test it. Comparing the predicted values and the experimental ones showed that a well-trained network is capable of accurately predicting the density and time to rupture strength of the Ni-base superalloys. Modeling results is used to determine the effect of alloying elements, stress, temperature and gamma-prime phase volume fraction on rupture strength of the Ni-base superalloys. This approach is in line with the materials genome initiative and integrated computed materials engineering approaches promoted recently with the aim of reducing the cost and time for development of new alloys for critical aerospace components. This work has been funded by TUBITAK under grant number 112M783.

Keywords: neural network, rupture strength, superalloy, thermocalc

Procedia PDF Downloads 313

Authors: Maneesha Pahlani, Najmin Sultana

Abstract:

A hospital is one of the most suitable places for acquiring an infection because it harbors a high population of virulent strains of microorganisms that may be resistant to antibiotics, especially the prevalence of Methicillin-Resistant Staphylococcus Aureus (MRSA) infections. The hospital-acquired infection has become a global challenge. In developed countries, healthcare-associated infections occur in 5-15% of hospitalized clients, affecting 9-37% of those admitted to intensive care units (ICU). A non-experimental descriptive study was conducted among 50 nursing officers working in a selected hospital in Bangalore to assess the nursing officers’ level of knowledge regarding the prevention and management of MRSA infections and to associate the pre-test knowledge mean scores of nursing officers with selected socio-demographic variables. Data was collected using a structured questionnaire consisting of socio-demographic data and a structured questionnaire on knowledge regarding the prevention and management of MRSA infections. The data was analyzed in terms of frequencies and percentages for the analysis of demographic variables and computing chi-square to determine the association between knowledge means scores and selected demographic variables. The study findings revealed that the nursing officer had an overall good level of knowledge (63.05%) regarding the prevention and management of MRSA infections, and there is no significant association found between the level of knowledge mean scores for prevention and management of MRSA infection with the selected socio-demographic variables. However, the categorization of knowledge items showed that the nursing officer must thoroughly receive education on correct guidance and information regarding MRSA infection control policy, including measures and practices on hygiene precautions and information regarding antibiotic resistance for effective nursing care to patients with MRSA infections. The conclusions drawn from the study findings showed that it is necessary that the nursing officer thoroughly receive education on correct guidance and information regarding MRSA infection control policy, including measures and practices on hygiene precautions and information regarding antibiotic resistance to provide effective nursing care to patients with MRSA infection as they constantly care for the patient who can be at risk for multi-drug resistance organisms to reduce the risk of MRSA infection in hospital care settings as well community settings.

Keywords: MRSA, nursing officers, knowledge, preventive and management

Procedia PDF Downloads 69

Authors: Shalini Tripathi, Pardeep Kumar

Abstract:

The method of translating observed symptoms into disease names is known as disease diagnosis. The ability to solve clinical problems in a complex manner is critical to a doctor's effectiveness in providing health care. The accuracy of his or her expertise is crucial to the survival and well-being of his or her patients. Artificial Intelligence (AI) has a huge economic influence depending on how well it is applied. In the medical sector, human brain-simulated intellect can help not only with classification accuracy, but also with reducing diagnostic time, cost and pain associated with pathologies tests. In light of AI's present and prospective applications in the biomedical, we will identify them in the paper based on potential benefits and risks, social and ethical consequences and issues that might be contentious but have not been thoroughly discussed in publications and literature. Current apps, personal tracking tools, genetic tests and editing programmes, customizable models, web environments, virtual reality (VR) technologies and surgical robotics will all be investigated in this study. While AI holds a lot of potential in medical diagnostics, it is still a very new method, and many clinicians are uncertain about its reliability, specificity and how it can be integrated into clinical practice without jeopardising clinical expertise. To validate their effectiveness, more systemic refinement of these implementations, as well as training of physicians and healthcare facilities on how to effectively incorporate these strategies into clinical practice, will be needed.

Keywords: Artificial Intelligence, medical diagnosis, virtual reality, healthcare ethical implications 

Procedia PDF Downloads 132