Search results for: teaching and learning

Authors: Shriya Shukla, Lachin Fernando

Abstract:

Pneumonia, a leading cause of mortality in young children globally, presents significant diagnostic challenges, particularly in resource-limited settings. This study presents an approach to diagnosing pediatric pneumonia using Chest X-Ray (CXR) images, employing a lightweight MobileNetV2 model enhanced with synthetic data augmentation. Addressing the challenge of dataset scarcity and imbalance, the study used a Variational Autoencoder-Generative Adversarial Network (VAE-GAN) to generate synthetic CXR images, improving the representation of normal cases in the pediatric dataset. This approach not only addresses the issues of data imbalance and scarcity prevalent in medical imaging but also provides a more accessible and reliable diagnostic tool for early pneumonia detection. The augmented data improved the model’s accuracy and generalization, achieving an overall accuracy of 95% in pneumonia detection. These findings highlight the efficacy of the MobileNetV2 model, offering a computationally efficient yet robust solution well-suited for resource-constrained environments such as mobile health applications. This study demonstrates the potential of synthetic data augmentation in enhancing medical image analysis for critical conditions like pediatric pneumonia.

Keywords: pneumonia, MobileNetV2, image classification, GAN, VAE, deep learning

Procedia PDF Downloads 136

Authors: K. Shaloom Mbambu, M. Pascal Tshimbalanga, K. Ruth Mutala, K. Roger Kabuya, N. Dieudonné Kabeya, Y. L. Kabeya Mukeba

Abstract:

In this article, the authors examine the even more worrying situation of girls in sub-Saharan Africa. Two-girls on five are private of Global Education, which represents a real loss to the development of communities and countries. Cultural traditions, poverty, violence, early and forced marriages, early pregnancies, and many other gender inequalities were the causes of this cancer development. Namely, "it is no more efficient development tool that is educating girls." The non-schooling of girls and their lack of supervision by liberal professions have serious consequences for the life of each of them. To improve the conditions of their inferior status, girls to men introduce poverty and health risks. Raising awareness among parents and communities on the importance of girls' education, improving children's access to school, girl-boy equality with their rights, creating income, and generating activities for girls, girls, and girls learning of liberal trades to make them self-sufficient. Organizations such as the United Nations Organization can save the children. ASEAD and the AEDA group are predicting the impact of this cancer on the development of a nation's future generation must be preserved.

Keywords: young girl, Sub-Saharan Africa, higher and vocational education, development, society, environment

Procedia PDF Downloads 263

Authors: Beverly Komen

Abstract:

Online crimes have been on the rise in the recent days, especially with the hit of the covid-19 pandemic. The coronavirus pandemic has led to an unprecedented rise in screen time, this means more families are relying on technology and digital solutions to keep children learning, spending more time on the virtual platforms can leave children vulnerable to online abuse and exploitation. With ease access of affordable phones, internet, and increased online activities, all children are at risk of being abused online hence making the digital space unsafe for children. With these increased use of technology and its accessibility, children are at risk of facing challenges such as access to inappropriate content, online grooming, identity theft, cyber bullying, among other risks. The big question is; as we enjoy the benefits brought in by technology, how do we ensure that our children are save in this digital space? With the analysis of the current trends, there is a gap in knowledge on people’s understanding on child online protection and safety measures when using the digital space. A survey conducted among 50 parents in Nairobi in Kenya indicated that there is a gap in knowledge on online protection of children and over 50 % of the participants shared that for sure they have no idea on how to protect children online. This paper seeks to address the concept of child protection in the digital space and come up with viable solutions in protecting children from online vices.

Keywords: child protection, digital space, online risks, online grooming, cyber bulying, online child sexual exploitation, and abuse

Procedia PDF Downloads 191

Authors: Kelly Jo Hollingsworth

Abstract:

Conversational Solfege, a research-based, 12-step music literacy instructional method using the sound-before-sight approach, was used to teach rhythm-reading to 128-second grade students at a public school in the southeastern United States. For each step, multiple scripted techniques are supplied to teach each skill. Unit one was the focus of this study, which is quarter note and barred eighth note rhythms. During regular weekly music instruction, students completed method steps one through five, which includes aural discrimination, decoding familiar and unfamiliar rhythm patterns, and improvising rhythmic phrases using quarter notes and barred eighth notes. Intact classes were randomly assigned to two treatment groups for teaching steps six through eight, which was the visual presentation and identification of quarter notes and barred eighth notes, visually presenting and decoding familiar patterns, and visually presenting and decoding unfamiliar patterns using said notation. For three weeks, students practiced steps six through eight during regular weekly music class. One group spent five-minutes of class time on steps six through eight technique work, while the other group spends ten-minutes of class time practicing the same techniques. A pretest and posttest were administered, and ANOVA results reveal both the five-minute (p < .001) and ten-minute group (p < .001) reached statistical significance suggesting Conversational Solfege is an efficient, effective approach to teach rhythm-reading to second grade students. After two weeks of no instruction, students were retested to measure retention. Using a repeated-measures ANOVA, both groups reached statistical significance (p < .001) on the second posttest, suggesting both the five-minute and ten-minute group retained rhythm-reading skill after two weeks of no instruction. Statistical significance was not reached between groups (p=.252), suggesting five-minutes is equally as effective as ten-minutes of rhythm-reading practice using Conversational Solfege techniques. Future research includes replicating the study with other grades and units in the text.

Keywords: conversational solfege, length of instructional time, rhythm-reading, rhythm instruction

Procedia PDF Downloads 163

Authors: Libing Zhu, Waichung Chen, Kwaicing Lo, Lei Li

Abstract:

Background: Tian Jiu Therapy (a medicinal vesiculation therapy according to traditional Chinese medicine theory) in San Fu Days (the three hottest days in a year is calculated by the Chinese ancient calendar) is widely used by patients with chronic asthma in China although from modern medicine perspective there is insufficient evidence of its effectiveness and safety issues. We investigated the efficacy and safety of Tian Jiu Therapy compared with placebo in patients with chronic asthma. Methods: Patients with chronic asthma were randomly assigned to Tian Jiu treatment group (n=165), placebo control group (n=158). Registered Chinese Medicine practitioners, in Orthopedics-Traumatology, Acupuncture, and Tui-na Clinical Centre for Teaching and Research, School of Chinese Medicine, The University of Hong Kong, administered Tian Jiu Therapy and placebo treatment in 3 times over 2 months. Patients completed questionnaires and lung function test before treatment and after treatment, 3, 6, 9, and 11 months, respectively. The primary outcome was the no of asthma-related sub-healthy symptoms and the percentage of patients with twenty-three symptoms. Results: 451 patients were recruited totally, 111 patients refused or did not participate according the appointment time and 17 did not meet the inclusion criteria. Consequently, 323 of eligible patients were enrolled. There was nothing difference between Tian Jiu Therapy group and placebo control group at the end of all treatments neither primary nor secondary outcomes. While Tian Jiu Therapy as compared with placebo significantly reduced the percentage of participants who are susceptible waken up by asthma symptoms from 27% to 14% at 2nd follow-up (P < 0.05). Similarly, Tian Jiu Therapy significantly reduced the proportion of participants who had the symptom of running nose and sneezing before onset from 18% to 8% at 2nd follow-up (P < 0.05). Additionally, Tian Jiu Therapy significantly reduced the level of asthma, the proportion of participants who don’t need to processed during asthma attack increased from 6% to 15% at 1st follow-up and 0% to 7% at 3rd follow-up (P < 0.05). Improvements also occurred with Tian Jiu Therapy group, it reduced the proportion of participants who were spontaneously sweating at 3rd follow up and diarrhea after intake of oily food at 4th follow-up (P < 0.05). Conclusion: When added to a regimen of foundational therapy for chronic asthma participants, Tian Jiu Therapy further reduced the need for medications to control asthma, improved the quality of participants’ life, and significantly reduced the level of asthma. What is more, this benefit seems to have an accumulative effect over time was in accordance with the TCM theory of 'winter disease is being cured in summer'.

Keywords: asthma, Tian Jiu Therapy, San Fu Days, triaditional Chinese medicine, clinical trial

Procedia PDF Downloads 317

Authors: Ibrahima Diallo

Abstract:

The literature on teacher education foregrounds reflection as an important aspect of professional practice. Reflection for a teacher consists in critically analysing and evaluating retrospectively a lesson to see what worked, what did not work, and how to improve it for the future. Now, many teacher education programmes worldwide consider the ability to reflect as one of the hallmarks of an effective educator. However, in some context like Senegal, reflection has not been given due consideration in teacher education programmes. In contexts where it has been in the education landscape for some time now, reflection is mostly depicted as an individual written activity and many teacher trainees have become disenchanted by the repeated enactments of this task that is solely intended to satisfy course requirements. This has resulted in whitewashing weaknesses or even ‘faking’ reflection. Besides, the “one-size-fits-all” approach of reflection could not flourish because how reflection impacts on practice is still unproven. Therefore, reflective practice needs to be contextualised and made more thought-provoking through dialogue and by using classroom data. There is also a need to highlight change brought in teachers’ practice through reflection. So, this study introduces reflection in a new context and aims to show evidenced change in novice EFL teachers’ practice through dialogic data-led reflection. The purpose of this study is also to contribute to the scarce literature on reflection in sub-Saharan Africa by bringing new perspectives on contextualised teacher-led reflection. Eight novice EFL teachers participated in this qualitative longitudinal study, and data have been gathered online through post-lesson reflection recordings and lesson videos for a period of four months. Then, the data have been thematically analysed using NVivo to systematically organize and manage the large amount of data. The analysis followed the six steps approach to thematic analysis. Major themes related to teachers’ classroom practice and their conception of reflection emerged from the analysis of the data. The results showed that post-lesson reflection with a peer can help novice EFL teachers gained more awareness on their classroom practice. Dialogic reflection also helped them evaluate their lessons and seek for improvement. The analysis of the data also gave insight on teachers’ conception of reflection in an EFL context. It was found that teachers were more engaged in reflection when using their lesson video recordings. Change in teaching behaviour as a result of reflection was evidenced by the analysis of the lesson video recordings. This study has shown that video-stimulated reflection is practical form of professional development that can be embedded in teachers’ professional life.

Keywords: novice EFL teachers, practice, professional development, video-stimulated reflection

Procedia PDF Downloads 101

Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

Abstract:

Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

Procedia PDF Downloads 200

Authors: Sarah Rietze, Hannes Zacher

Abstract:

Daily stand-up meetings are the most commonly used method in agile teams. In daily stand-ups, team members gather to coordinate and align their efforts, typically for a predefined period of no more than 15 minutes. The primary purpose is to ask and answer the following three questions: What was accomplished yesterday? What will be done today? What obstacles are impeding my progress? Daily stand-ups aim to enhance communication, mutual understanding, and support within the team, as well as promote collective learning from mistakes through daily synchronization and transparency. The use of daily stand-ups is intended to positively influence psychological safety within teams, which is the belief that it is safe to show oneself and take personal risks. Two studies will be presented, which explore the relationships between daily stand-ups, psychological safety, and psychological well-being. In a first study, based on survey results (n = 318), we demonstrated that daily stand-ups have a positive indirect effect on job satisfaction and a negative indirect effect on turnover intention through their impact on psychological safety. In a second study, we investigate, using an experimental design, how the use of daily stand-ups in teams enhances psychological safety and well-being compared to a control group that does not use daily stand-ups. Psychological safety is considered one of the most crucial cultural factors for a sustainable, agile organization. Agile approaches, such as daily stand-ups, are a critical part of the evolving work environment and offer a proactive means to shape and foster psychological safety within teams.

Keywords: occupational wellbeing, agile work practices, psychological safety, daily stand-ups

Procedia PDF Downloads 70

Authors: Hosein Hamisheh Bahar, Mohammad Hossein Fazel Zarandi, Akbar Esfahanipour

Abstract:

In this paper, a hybrid expert system is developed by using fuzzy genetic network programming with reinforcement learning (GNP-RL). In this system, the frame-based structure of the system uses the trading rules extracted by GNP. These rules are extracted by using technical indices of the stock prices in the training time period. For developing this system, we applied fuzzy node transition and decision making in both processing and judgment nodes of GNP-RL. Consequently, using these method not only did increase the accuracy of node transition and decision making in GNP's nodes, but also extended the GNP's binary signals to ternary trading signals. In the other words, in our proposed Fuzzy GNP-RL model, a No Trade signal is added to conventional Buy or Sell signals. Finally, the obtained rules are used in a frame-based system implemented in Kappa-PC software. This developed trading system has been used to generate trading signals for ten companies listed in Tehran Stock Exchange (TSE). The simulation results in the testing time period shows that the developed system has more favorable performance in comparison with the Buy and Hold strategy.

Keywords: fuzzy genetic network programming, hybrid expert system, technical trading signal, Tehran stock exchange

Procedia PDF Downloads 335

Authors: Adrian-Gabriel Chifu, Sebastien Fournier

Abstract:

One of the challenges of natural language understanding is to deal with the subjectivity of sentences, which may express opinions and emotions that add layers of complexity and nuance. Sentiment analysis is a field that aims to extract and analyze these subjective elements from text, and it can be applied at different levels of granularity, such as document, paragraph, sentence, or aspect. Aspect-based sentiment analysis is a well-studied topic with many available data sets and models. However, there is no clear definition of what makes a sentence difficult for aspect-based sentiment analysis. In this paper, we explore this question by conducting an experiment with three data sets: ”Laptops”, ”Restaurants”, and ”MTSC” (Multi-Target-dependent Sentiment Classification), and a merged version of these three datasets. We study the impact of domain diversity and syntactic diversity on difficulty. We use a combination of classifiers to identify the most difficult sentences and analyze their characteristics. We employ two ways of defining sentence difficulty. The first one is binary and labels a sentence as difficult if the classifiers fail to correctly predict the sentiment polarity. The second one is a six-level scale based on how many of the top five best-performing classifiers can correctly predict the sentiment polarity. We also define 9 linguistic features that, combined, aim at estimating the difficulty at sentence level.

Keywords: sentiment analysis, difficulty, classification, machine learning

Procedia PDF Downloads 95

Authors: Saeyoung Lee

Abstract:

As the enthusiasm for education in Korea is too much high, it is well known by others that children in Korea get good scores in Mathematics. However, behind of this good reputation, children in Korea are easy to get lose self-confidence, tend to complaint and rarely participate in the class because of too much competition which leads to lack of competences. In this regard, the main goals of this paper are, by applying the programme based on peer-communication on Mathematics education field, it would like to improve self-managemental competence to make children gain self-confidence, communicative competence to make them deal with complaint and communitive competence to make them participated in the class for the age of 10 children to solve this problem. 14 children the age of 10 in one primary school in Gangnam, Seoul, Korea had participated in the research from March 2018 to October 2018. They were under the programme based on peer-communication during the period. Every Mathematics class maintained the same way. Firstly a problem was given to children. Secondly, children were asked to find many ways to solve the problem as much as they could by themselves. Thirdly all ways to solve the problem by children were posted on the board and three of the children made a group to distinguish the ways from valid to invalid. Lastly, all children made a discuss to find one way which is the most efficient among valid ways. Pre-test was carried out by the questionnaire based on Likert scale before applying the programme. The result of the pre-test was 3.89 for self-managemental competence, 3.91 for communicative competence and 4.19 for communitive competence. Post-test was carried out by the same questionnaire after applying the programme. The result of the post-test was 3.93 for self-managemental competence, 4.23 for communicative competence and 4.20 for communitive competence. That means by applying the programme based on peer-communication on Mathematics education field, the age of 10 children in Korea could improve self-managemental, communicative and communitive competence. Especially it works very well on communicative competence by increasing 0.32 points as it marked. Considering this research, Korean Mathematics education based on competition which leads to lack of competences should be changed to cooperative structure to make students more competent rather than just getting good scores. In conclusion, innovative teaching methods which are focused on improving competences such as the programme based on peer-communication which was applied in this research are strongly required to be studied and widely used.

Keywords: competences, mathematics education, peer-communication, primary education

Procedia PDF Downloads 138

Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

Abstract:

Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

Procedia PDF Downloads 143

Authors: Kwame Amoah

Abstract:

Artificial intelligence (AI) has the prospect of transforming project management, significantly improving efficiency and accuracy. By automating specific tasks with defined guidelines, AI can assist project managers in making better decisions and allocating resources efficiently, with possible risk mitigation. This study explores how AI is already impacting project management and likely future AI's impact on the field. The AI's reaction has been a divided opinion; while others picture it as a destroyer of jobs, some welcome it as an innovation advocate. Both sides agree that AI will be disruptive and revolutionize PM's functions. If current research is to go by, AI or some form will replace one-third of all learning graduate PM jobs by as early as 2030. A recent survey indicates AI spending will reach $97.9 billion by the end of 2023. Considering such a profound impact, the project management profession will also see a paradigm shift driven by AI. The study examines what the project management profession will look like in the next 5-10 years after this technological disruption. The research methods incorporate existing literature, develop trend analysis, and conduct structured interviews with project management stakeholders from North America to gauge the trend. PM professionals can harness the power of AI, ensuring a smooth transition and positive outcomes. AI adoption will maximize benefits, minimize adverse consequences, and uphold ethical standards, leading to improved project performance.

Keywords: project management, disruptive teacnologies, project management function, AL applications, artificial intelligence

Procedia PDF Downloads 90

Authors: Dalin Si, Azizan Aziz, Bertrand Lasternas

Abstract:

To encourage building owners to purchase electricity at the wholesale market and reduce building peak demand, this study aims to develop models that predict day-ahead hourly electricity consumption and demand using artificial neural network (ANN) and support vector machine (SVM). All prediction models are built in Python, with tool Scikit-learn and Pybrain. The input data for both consumption and demand prediction are time stamp, outdoor dry bulb temperature, relative humidity, air handling unit (AHU), supply air temperature and solar radiation. Solar radiation, which is unavailable a day-ahead, is predicted at first, and then this estimation is used as an input to predict consumption and demand. Models to predict consumption and demand are trained in both SVM and ANN, and depend on cooling or heating, weekdays or weekends. The results show that ANN is the better option for both consumption and demand prediction. It can achieve 15.50% to 20.03% coefficient of variance of root mean square error (CVRMSE) for consumption prediction and 22.89% to 32.42% CVRMSE for demand prediction, respectively. To conclude, the presented models have potential to help building owners to purchase electricity at the wholesale market, but they are not robust when used in demand response control.

Keywords: building energy prediction, data mining, demand response, electricity market

Procedia PDF Downloads 320

Authors: Paul Essel, Eric T. Glover, Gustav Gbeddy, Yaw Adjei-Kyereme, Abdallah M. A. Dawood, Evans M. Ameho, Emmanuel A. Aberikae

Abstract:

Radioactive materials mainly in the form of Sealed Radioactive Sources are being used in various sectors (medicine, agriculture, industry, research, and teaching) for the socio-economic development of Ghana. The use of these beneficial radioactive materials has resulted in an inventory of Disused Sealed Radioactive Sources (DSRS) in storage. Most of the DSRS are legacy/historic sources which cannot be returned to their manufacturer or country of origin. Though small in volume, DSRS can be intensively radioactive and create a significant safety and security liability. They need to be managed in a safe and secure manner in accordance with the fundamental safety objective. The Radioactive Waste Management Center (RWMC) of the Ghana Atomic Energy Commission (GAEC) is currently storing a significant volume of DSRS. The initial activities of the DSRS range from 7.4E+5 Bq to 6.85E+14 Bq. If not managed properly, such DSRS can represent a potential hazard to human health and the environment. Storage is an important interim step, especially for DSRS containing very short-lived radionuclides, which can decay to exemption levels within a few years. Long-term storage, however, is considered an unsustainable option for DSRS with long half-lives hence the need for a disposal facility. The GAEC intends to use the International Atomic Energy Agency’s (IAEA’s) Borehole Disposal System (BDS) to provide a safe, secure, and cost-effective disposal option to dispose of its DSRS in storage. The proposed site for implementation of the BDS is on the GAEC premises at Kwabenya. The site has been characterized to gain a general understanding in terms of its regional setting, its past evolution and likely future natural evolution over the assessment time frame. Due to the long half-lives of some of the radionuclides to be disposed of (Ra-226 with half-life of 1600 years), the engineered barriers of the system must be robust to contain these radionuclides for this long period before they decay to harmless levels. There is the need to assess the safety related functions of the engineered barriers of this disposal system.

Keywords: radionuclides, disposal, radioactive waste, engineered barrier

Procedia PDF Downloads 86

Authors: Wafaa Salah, Mostafa A. Salama, Jane Doe

Abstract:

Recently, the corporate social performance (CSP) is not less important than the corporate financial performance (CFP). Debate still exists about the nature of the relationship between the CSP and CFP, whether it is a positive, negative or a neutral correlation. The objective of this study is to explore the relationship between corporate social responsibility (CSR) reports and CFP. The study uses the accounting-based and market-based quantitative measures to quantify the financial performance of seven organizations listed on the Egyptian Stock Exchange in 2007-2014. Then uses the information retrieval technologies to quantify the contribution of each of the three dimensions of the corporate social responsibility report (environmental, social and economic). Finally, the correlation between these two sets of variables is viewed together in a model to detect the correlations between them. This model is applied on seven firms that generate social responsibility reports. The results show a positive correlation between the Earnings per share (market based measure) and the economical dimension in the CSR report. On the other hand, total assets and property, plant and equipment (accounting-based measure) are positively correlated to the environmental and social dimensions of the CSR reports. While there is not any significant relationship between ROA, ROE, Operating income and corporate social responsibility. This study contributes to the literature by providing more clarification of the relationship between CFP and the isolated CSR activities in a developing country.

Keywords: financial, social, machine learning, corporate social performance, corporate social responsibility

Procedia PDF Downloads 315

Authors: Rafi Ullah, Shah Muhammad Emaduddin, Taha Jilani

Abstract:

Vehicle Adhoc Networks (VANET) belongs to a special class of Mobile Adhoc Network (MANET) with high mobility. Network is created by road side vehicles equipped with communication devices like GPS and Wifi etc. Since the environment is highly dynamic due to difference in speed and high mobility of vehicles and weak stability of the network connection, it is a challenging task to design an efficient routing protocol for such an unstable environment. Our proposed algorithm uses heuristic for the calculation of optimal path for routing the packet efficiently in collaboration with several other parameters like geographical location, speed, priority, the distance among the vehicles, communication range, and networks congestion. We have incorporated probabilistic, heuristic and machine learning based approach inconsistency with the relay function of the memory buffer to keep the packet moving towards the destination. These parameters when used in collaboration provide us a very strong and admissible heuristics. We have mathematically proved that the proposed technique is efficient for the routing of packets, especially in a medical emergency situation. These networks can be used for medical emergency, security, entertainment and routing purposes.

Keywords: heuristics routing, intelligent routing, VANET, route optimization

Procedia PDF Downloads 186

Authors: Antonia Tsaknaki

Abstract:

There are many and divergent views on how the science of translation should be taught in academic institutions or colleges, meaning as an independent study area or as part of Linguistics, Literature or Foreign Languages Departments. A much more debated issue refers to the question of whether translation theory should be included in syllabuses and study programs or the focus should be solely on practicing the profession, that is translating texts. This dissertation examines prevailing views on the significance of translation theory in translation studies in order to design an open course on moodle. Taking into account that there is a remarkable percentage of translation professionals who are self-taught without having any specific studies, the course aims at helping either translation students or professional translators familiarize with concepts, methods and problem-solving strategies that are considered necessary during the process. It is organized in four modules where the learner is guided through a series of topics (register, equivalence, decision-making, level of naturalness, Skopos theory etc); after completing these topics, they are given assignments (further reading) and texts to work on in order to practice the skills obtained. The course does not focus on a specific language pair and therefore is suitable for every individual who needs a theoretical background to boost their performance or for institutions seeking to save classroom time but not at the expense of learners’ skills.

Keywords: MOOCs, moodle, online learning, open courses, translation, translation theory

Procedia PDF Downloads 151

Authors: Stephanie Yun Yu Law

Abstract:

Background: This study aims to investigate into communication between trainee doctors and patients, especially how doctor’s reaction to patient’s emotional issues expressed in the consultation affect patient’s satisfaction. Objectives: Thus, there are three aims in this study, 1.) how do trainee doctors react to patients emotional cues in OSCE station? 2.) Any differences in the respond type to emotional cues between first year students and third year students? 3.) Is response type (reducing space) related to OSCE outcome (patient satisfaction and expert rating)? Methods: Fifteen OSCE stations was videotaped, in which 9 were stations with first-year students and 6 were with third-year students. OSCE outcomes were measured by Communication Assessment Tool and Examiners Checklist. Analyses: All patient’s cues/concerns and student’s reaction were coded by Verona Coding Definitions of Emotional Sequence. Descriptive data was gathered from Observer XT and logistic regression (two-level) was carried out to see if occurrence of reducing space response can be predicted by OSCE outcomes. Results: Reducing space responses from all students were slightly less than a half in total responses to patient’s cues. The mean percentage of reducing space behaviours was lower among first year students when compared to third year students. Patient’s satisfaction significantly (p<0.05) and negatively predicted reducing space behaviours. Conclusions: Most of the medical students, to some extent, did not provide adequate responses for patient’s emotional cues. But first year students did provide more space for patients to talk about their emotional issues when compared to third year students. Lastly, patients would feel less satisfied if trainee doctors use more reducing space responses in reaction to patient’s expressed emotional cues/concerns. Practical implications: Firstly, medical training programme can be tailored on teaching students how to detect and respond appropriately to emotional cues in order to improve underperformed student’s communication skills in healthcare setting. Furthermore, trainee doctor’s relationship with patients in clinical practice can also be improved by reacting appropriately to patient’s emotive cues in consultations (such as limit the use of reducing space behaviours).

Keywords: doctors-patients communication, applied clinical psychology, health psychology, healthcare professionals

Procedia PDF Downloads 220

Authors: Yen Ling Liu, Shu-Fen Wu, Chen-Fuh Lam, I-Ling Tsai, Chia-Yu Chen

Abstract:

Purpose: Nurse anesthetists are confronting extraordinarily high job stress in their daily practice, deriving from the fast-track anesthesia care, risk of perioperative complications, routine rotating shifts, teaching programs and interactions with the surgical team in the operating room. This study investigated the influence of work stress on the burnout and turnover intention of nurse anesthetists in a regional general hospital in Southern Taiwan. Methods: This was a descriptive correlational study carried out in 66 full-time nurse anesthetists. Data was collected from March 2017 to June 2017 by in-person interview, and a self-administered structured questionnaire was completed by the interviewee. Outcome measurements included the Practice Environment Scale of the Nursing Work Index (PES-NWI), Maslach Burnout Inventory (MBI) and nursing staff turnover intention. Numerical data were analyzed by descriptive statistics, independent t test, or one-way ANOVA. Categorical data were compared using the chi-square test (x²). Datasets were computed with Pearson product-moment correlation and linear regression. Data were analyzed by using SPSS 20.0 software. Results: The average score for job burnout was 68.7916.67 (out of 100). The three major components of burnout, including emotional depletion (mean score of 26.32), depersonalization (mean score of 13.65), and personal(mean score of 24.48). These average scores suggested that these nurse anesthetists were at high risk of burnout and inversely correlated with turnover intention (t = -4.048, P < 0.05). Using linear regression model, emotional exhaustion and depersonalization were the two independent factors that predicted turnover intention in the nurse anesthetists (19.1% in total variance). Conclusion/Implications for Practice: The study identifies that the high risk of job burnout in the nurse anesthetists is not simply derived from physical overload, but most likely resulted from the additional emotional and psychological stress. The occurrence of job burnout may affect the quality of nursing work, and also influence family harmony, in turn, may increase the turnover rate. Multimodal approach is warranted to reduce work stress and job burnout in nurse anesthetists to enhance their willingness to contribute in anesthesia care.

Keywords: anesthesia nurses, burnout, job, turnover intention

Procedia PDF Downloads 300

Authors: Vimala Rani P, Narasimha Malikarjunan, Mercy Shalinie S

Abstract:

Data Networking was brought forth as an instantiation of information-centric networking. The attackers can send a colossal number of spoofs to take hold of the Pending Interest Table (PIT) named an Interest Flooding attack (IFA) since the in- interests are recorded in the PITs of the intermediate routers until they receive corresponding Data Packets are go beyond the time limit. These attacks can be detrimental to network performance. PIT expiration rate or the Interest satisfaction rate, which cannot differentiate the IFA from attacks, is the criterion Traditional IFA detection techniques are concerned with. Threshold values can casually affect Threshold-based traditional methods. This article proposes an accurate IFA detection mechanism based on a Multiple Feature-based Extreme Learning Machine (MF-ELM). Accuracy of the attack detection can be increased by presenting the entropy of Internet names, Interest satisfaction rate and PIT usage as features extracted in the MF-ELM classifier. Furthermore, we deploy a queue-based hostile Interest prefix mitigation mechanism. The inference of this real-time test bed is that the mechanism can help the network to resist IFA with higher accuracy and efficiency.

Keywords: information-centric network, pending interest table, interest flooding attack, MF-ELM classifier, queue-based mitigation strategy

Procedia PDF Downloads 211

Authors: Pranjali Avinash Yadav-Deshmukh

Abstract:

Remarkable development of the Internet along with the new technological innovation, such as high-speed systems and affordable large storage space have led to a tremendous increase in the amount and accessibility to digital records. For any person, studying of all these data is tremendously time intensive, so there is a great need to access effective multi-document summarization (MDS) systems, which can successfully reduce details found in several records into a short, understandable summary or conclusion. For semantic representation of textual details in ontology area, as a theoretical design, our system provides a significant structure. The stability of using the ontology in fixing multi-document summarization problems in the sector of catastrophe control is finding its recommended design. Saliency ranking is usually allocated to each phrase and phrases are rated according to the ranking, then the top rated phrases are chosen as the conclusion. With regards to the conclusion quality, wide tests on a selection of media announcements are appropriate for “Jammu Kashmir Overflow in 2014” records. Ontology centered multi-document summarization methods using “NLP centered extraction” outshine other baselines. Our participation in recommended component is to implement the details removal methods (NLP) to enhance the results.

Keywords: disaster management, extraction technique, k-means, multi-document summarization, NLP, ontology, sentence extraction

Procedia PDF Downloads 390

Authors: Araba A. Z. Osei-Tutu, Ebenezer Odame, Joseph Bawa, Samuel Amponsah

Abstract:

Education is recognized as a fundamental human right and a catalyst for development. Despite progress in the provision of higher education on the African continent, there persist challenges with the tripartite areas of access, equity and quality. Therefore, this systematic review aimed at providing a comprehensive overview of conversations and voices of scholars on these three concepts in HE in Africa. The systematic review employed a thematic analysis approach, synthesizing findings from 38 selected sources. After a critical analysis of the sources included in the systematic review, deficits in access, quality, and equity were outlined, focusing on infrastructure, regional disparities, and privatization challenges. The review also revealed the weak enforcement of quality assurance measures. Strategies for improvement, proffered by the study, include expanding public sector HE, deregulating the educational sector, promoting open and distance learning, implementing preferential admission policies, and enhancing financial aid. This research contributes valuable insights for policymakers, educators, and stakeholders, fostering a collaborative approach to address challenges and promote holistic development in African higher education.

Keywords: access, equity, quality, higher education, Africa, systematic review, strategies

Procedia PDF Downloads 81

Authors: Cleiton Pons Ferreira, Diana Francisca Adamatti

Abstract:

Advancements in computers technology have allowed to obtain information for research in biology and neuroscience. In order to transform the data from these surveys, networks have long been used to represent important biological processes, changing the use of this tools from purely illustrative and didactic to more analytic, even including interaction analysis and hypothesis formulation. Many studies have involved this application, but not directly for interpretation of data obtained from brain functions, asking for new perspectives of development in neuroinformatics using existent models of tools already disseminated by the bioinformatics. This study includes an analysis of neurological data through electroencephalogram (EEG) signals, using the Cytoscape, an open source software tool for visualizing complex networks in biological databases. The data were obtained from a comparative case study developed in a research from the University of Rio Grande (FURG), using the EEG signals from a Brain Computer Interface (BCI) with 32 eletrodes prepared in the brain of a blind and a sighted individuals during the execution of an activity that stimulated the spatial ability. This study intends to present results that lead to better ways for use and adapt techniques that support the data treatment of brain signals for elevate the understanding and learning in neuroscience.

Keywords: neuroinformatics, bioinformatics, network tools, brain mapping

Procedia PDF Downloads 188

Authors: Girish J. Showkatramani, Arthi M. Krishna, Sashi Nareddi, Naresh Nula, Aaron Pepe, Glen Brown, Greg Gabel, Chris Doninger

Abstract:

Trademark examination and approval is a complex process that involves analysis and review of the design components of the marks such as the visual representation as well as the textual data associated with marks such as marks' description. Currently, the process of identifying marks with similar visual representation is done manually in United States Patent and Trademark Office (USPTO) and takes a considerable amount of time. Moreover, the accuracy of these searches depends heavily on the experts determining the trademark design codes used to catalog the visual design codes in the mark. In this study, we explore several methods to automate trademark design code classification. Based on recent successes of convolutional neural networks in image classification, we have used several different convolutional neural networks such as Google’s Inception v3, Inception-ResNet-v2, and Xception net. The study also looks into other techniques to augment the results from CNNs such as using Open Source Computer Vision Library (OpenCV) to pre-process the images. This paper reports the results of the various models trained on year of annotated trademark images.

Keywords: trademark design code, convolutional neural networks, trademark image classification, trademark image search, Inception-ResNet-v2

Procedia PDF Downloads 235

Authors: Binod Duwadi

Abstract:

This article examines the language and literacy practices of English Code-mixing in Nepalese Classroom. Situating the study within an ecological framework, a systematic functional linguistic (SFL) approach was used to analyze students writing in two Neplease schools. Data collection included interviews with teachers, classroom observations, instructional materials, and focal students’ writing samples. Data analyses revealed vastly different language ecologies between the schools owing to sharp socioeconomic stratification, the structural organization of schools, and the pervasiveness of standard language ideology, with stigmatizes English code mixing (ECM) and privileges Standard English in schools. Functional analysis of students’ writing showed that the nature of the writing tasks at the schools created different affordances for exploiting lexicogrammatically choices for meaning making-enhancing them in the case of one school but severely restricting them in the case of another- perpetuating the academic disadvantage for code mixing speakers. Recommendations for structural and attitudinal changes through teacher training and implementation of approaches that engage students’ bidialectal competence for learning are made as important first steps towards addressing educational inequities in Nepalese schools.

Keywords: code-mixing, ecological perspective, systematic functional approach, language and identity

Procedia PDF Downloads 127

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching, including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders, including Ghana Football Association (GFA), to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 75

Authors: Fiona Soraya Addai-Sundiata, Ernest Yeboah Acheampong, Ralph Frimpong

Abstract:

The rationale of this study is to examine the career experiences of elite female football coaches in Ghana. More importantly, it focus on their motives, the challenges of football coaching and their experiences along their career paths. The study draws from literature on female coaches in football to understand their experiences and reflections in their chosen careers. The findings of the study relied on in-depth semi-structured interviews with five elite female football coaches aged between 28 and 50 years. Participants’ responses reveal that both intrinsic and extrinsic motives drive them into football coaching including learning experiences from abroad, a strong desire to break the gendered hegemony of coaching in Ghana, serving as role models, enjoyment, satisfaction and passion for their chosen careers. Results indicate that they encountered sociocultural, organisational, personal and interpersonal challenges. Also, they experience gender stereotyping, limited career mobility, sexism and marginalisation, which prevent them from becoming elite coaches. The study provides useful data for stakeholders including Ghana Football Association (GFA) to use effective strategies (e.g., special incentives for women coaches) to attract and retain women in the football coaching space.

Keywords: elite female football coaches, career experiences, gender, motives, trajectories

Procedia PDF Downloads 65

Authors: Taylor Kolody, Farkhund Iqbal, Rabia Batool, Benjamin Fung, Mohammed Hussaeni, Saiqa Aleem

Abstract:

The rising threat of climate change has led to an increase in public awareness and care about our collective and individual environmental impact. A key component of this impact is our use of cars and other polluting forms of transportation, but it is often difficult for an individual to know how severe this impact is. While there are applications that offer this feedback, they require manual entry of what transportation mode was used for a given trip, which can be burdensome. In order to alleviate this shortcoming, a data from the 2016 TRIPlab datasets has been used to train a variety of machine learning models to automatically recognize the mode of transportation. The accuracy of 89.6% is achieved using single deep neural network model with Gated Recurrent Unit (GRU) architecture applied directly to trip data points over 4 primary classes, namely walking, public transit, car, and bike. These results are comparable in accuracy to results achieved by others using ensemble methods and require far less computation when classifying new trips. The lack of trip context data, e.g., bus routes, bike paths, etc., and the need for only a single set of weights make this an appropriate methodology for applications hoping to reach a broad demographic and have responsive feedback.

Keywords: classification, gated recurrent unit, recurrent neural network, transportation

Procedia PDF Downloads 141

Authors: Zainab Yahaya Suleiman

Abstract:

Physical fitness, as one of the most important keys to a healthy wellbeing, is the basis of dynamic and creative intellectual activity. As a result, the fitness world is expanding every day. It is believed that a fitness centre is a place of healing and also the natural environment is vital to speedy recovery. The aim of this paper is to propose and designs a suitable location for a fitness centre in Batagarawa metropolis. Batagarawa city is enriched with four tertiary institutions with diverse commerce and culture but lacks the facility of a well-equipped fitness centre. The proposed fitness centre intends to be an organically sound centre that will make use of principles of organic architecture to create a new pleasant environment between man and his environments. Organic architecture is the science of designing a building within pleasant natural resources and features surrounding the environment. It is regarded as visual poetry and reinterpretation of nature’s principles; as well as embodies a settlement of person, place, and materials. Using organic architecture, the design was interlaced with the dynamic, organic and monumental features surrounding the environment. The city has inadequate/no facility that is considered organic where one can keep fit in a friendly, conducive and adequate location. Thus, the need for establishing a fitness centre to cater for this need cannot be over-emphasised. Conclusively, a fitness centre will be an added advantage to this fast growing centre of learning.

Keywords: organic architecture, fitness center, environment, natural resources, natural features, building design

Procedia PDF Downloads 414