Search results for: online grooming

Authors: Jacqueline Mary Jepson

Abstract:

This article provides a case study centred on the development of 13 video episodes which have been created to enhance student engagement with a post graduate online course in Project Management. The student group was unique as their online course needed to provide for asynchronistic learning and an adult learning pedagogy. In addition, students had come from a wide range professional backgrounds, with some having no Project Management experience, while others had 20 years or more. Students had to gain an understanding of an advanced body of knowledge and the course needed to achieve the academic requirements to qualify individuals to apply their learning in a range of contexts for professional practice and scholarship. To achieve this, a 13 episode case study was developed along with supportive learning materials based on the relocation of a zoo. This unique project provided a learning environment where the project could evolve over each video episode demonstrating the application of Project Management methodology which was then tied into the learning outcomes for the course and the assessment tasks. Discussion forums provided a way for students to converse and demonstrate their own understanding of content and how Project Management methodology can be applied.

Keywords: project management, adult learning, video case study, asynchronistic education

Procedia PDF Downloads 338

Authors: Ruwan Gunawardane

Abstract:

Second language teaching and learning is a complex process in which various factors are identified as having a negative impact on the competency in English among undergraduates of Sri Lanka. One such issue is the lack of intrinsic motivation among them to learn English despite the fact that they all know the importance of English. This study attempted to ascertain how the intrinsic motivation of undergraduates to learn English can be improved through reading out of curiosity. Humans are curious by nature, and cognitive psychology says that curiosity facilitates learning, memory, and motivation. The researcher carried out this study during the closure of universities due to the outbreak of the coronavirus through ‘Online Reading Café’, an online reading programme introduced by himself. He invited 1166 students of the Faculty of Science, University of Ruhuna, to read 50 articles taken from CNN and the BBC and posted at least two to three articles on the LMS of the faculty almost every day over a period of 23 days. The themes of the articles were based on the universe, exploration of planets, scientific experiments, evolution, etc., and the students were encouraged to collect as many words, phrases, and sentence structures as possible while reading and to form meaningful sentences using them. The data obtained through the students’ feedback was qualitatively analyzed. It was found that these undergraduates were interested in reading something out of curiosity, due to which intrinsic motivation is enhanced, and it facilitates competence in L2.

Keywords: English, competence, reading, curiosity

Procedia PDF Downloads 138

Authors: Shaun G. Abbott, Rebecca C. Reynolds, John B. F. de Wit

Abstract:

Low physical activity (PA) levels are a major public health concern in Australia. There is some evidence that PA interventions can increase PA levels via various methods, including online delivery. Low Socioeconomic Status (SES) people participate in less PA than the rest of the population, partly due to poor self-regulation behaviors associated with socioeconomic characteristics. Interventions that involve a particular method of self-regulation, Mental Contrasting with Implementation Intentions (MCII), has regularly achieved healthy behavior change, but few studies focus on PA behavior outcomes and no studies examining the effect of MCII on the PA behaviors of low SES people has been done. In this study, a pilot randomized controlled trial (RCT) will deliver MCII for PA behavior change to individuals of relative disadvantage for the first time. The current pilot study will predict sample size for a future full RCT and test the hypothesis that sedentary participants from areas of relative socioeconomic disadvantage of Sydney, who learn the MCII technique will be more physically active, have improved anthropometry and psychological indicators at the completion of a 12-week intervention compared to baseline and control. Eligible participants of relative socioeconomic disadvantage will be randomly assigned to either the ‘PA Information Plus MCII Intervention Group’ or a ‘PA Information-Only Control Group’. Both groups will attend a baseline and 12-week face-to-face consultation; where PA, anthropometric and psychological data will be gathered. The intervention group will be guided through an MCII session at the baseline appointment to establish a PA goal to aim to achieve over 12 weeks. Other than these baseline and 12-week consultations, all participant interaction will occur online. All participants will receive a ‘Fitbit’ accelerometer to record objectively. PA as a daily step count, along with a PA diary for the duration of the study. PA data will be recorded on a personalized online spreadsheet. Both groups will receive a standard PA information email at weeks 2, 4, and 8. The intervention group will also receive scripted follow-up online appointments to discuss goal progress. The current pilot study is in recruitment stage with findings to be presented at the conference in December if selected.

Keywords: implementation intentions, mental contrasting, motivation, pedometer, physical activity, socioeconomic

Procedia PDF Downloads 306

Authors: Abdulaziz Fageeh

Abstract:

In the bustling digital landscape of Saudi Arabia, a chilling wave of cybercrime has swept across the nation. Among the most nefarious acts are financial blackmail schemes, perpetrated by anonymous actors lurking within the shadows of social media platforms. This chilling reality necessitates the utilization of forensic linguistic techniques to unravel the identities of these virtual villains. This research delves into the complex world of authorship profiling, investigating the effectiveness of various linguistic features in identifying the perpetrators of malicious messages within the Saudi social media environment. By meticulously analyzing patterns of language, vocabulary choice, and stylistic nuances, the study endeavors to uncover the hidden characteristics of the individuals responsible for these heinous acts. Through this linguistic detective work, the research aims to provide valuable insights to investigators and policymakers in the ongoing battle against cybercrime and to shed light on the evolution of malicious online behavior within the Saudi context.

Keywords: authorship profiling, arabic linguistics, saudi social media, cybercrime, financial blackmail, linguistic features, forensic linguistics, online threats

Procedia PDF Downloads 11

Authors: Atefeh Heydari, Mohammadali Tavakoli, Zuriati Ismail, Naomie Salim

Abstract:

Seeking and sharing knowledge on online forums have made them popular in recent years. Although online forums are valuable sources of information, due to variety of sources of messages, retrieving reliable threads with high quality content is an issue. Majority of the existing information retrieval systems ignore the quality of retrieved documents, particularly, in the field of thread retrieval. In this research, we present an approach that employs various quality features in order to investigate the quality of retrieved threads. Different aspects of content quality, including completeness, comprehensiveness, and politeness, are assessed using these features, which lead to finding not only textual, but also conceptual relevant threads for a user query within a forum. To analyse the influence of the features, we used an adopted version of voting model thread search as a retrieval system. We equipped it with each feature solely and also various combinations of features in turn during multiple runs. The results show that incorporating the quality features enhances the effectiveness of the utilised retrieval system significantly.

Keywords: content quality, forum search, thread retrieval, voting techniques

Procedia PDF Downloads 213

Authors: Aman Berhe, Camille Guinaudeau, Claude Barras

Abstract:

In order to facilitate information seeking in large collections of multimedia documents with long and progressive content (such as broadcast news or TV series), one can extract the semantic links that exist between semantically coherent parts of documents, i.e., scenes. The links can then create a coherent collection of scenes from which it is easier to perform content analysis, topic extraction, or information retrieval. In this paper, we focus on TV series structuring and propose two approaches for scene linking at different levels of granularity (episode and season): a fuzzy online clustering technique and a graph-based community detection algorithm. When evaluated on the two first seasons of the TV series Game of Thrones, we found that the fuzzy online clustering approach performed better compared to graph-based community detection at the episode level, while graph-based approaches show better performance at the season level.

Keywords: multimedia collection structuring, progressive content, scene linking, fuzzy clustering, community detection

Procedia PDF Downloads 99

Authors: Helmi Baazaoui, Mounir Zrigui

Abstract:

This study addresses the challenge of hate speech detection in Tunisian Arabic text, a critical issue for online safety and moderation. Leveraging the strengths of the AraBERT model, we fine-tuned and evaluated its performance against the Bi-LSTM model across four distinct datasets: T-HSAB, TNHS, TUNIZI-Dataset, and a newly compiled dataset with diverse labels such as Offensive Language, Racism, and Religious Intolerance. Our experimental results demonstrate that AraBERT significantly outperforms Bi-LSTM in terms of Recall, Precision, F1-Score, and Accuracy across all datasets. The findings underline the robustness of AraBERT in capturing the nuanced features of Tunisian Arabic and its superior capability in classification tasks. This research not only advances the technology for hate speech detection but also provides practical implications for social media moderation and policy-making in Tunisia. Future work will focus on expanding the datasets and exploring more sophisticated architectures to further enhance detection accuracy, thus promoting safer online interactions.

Keywords: hate speech detection, Tunisian Arabic, AraBERT, Bi-LSTM, Gemini annotation tool, social media moderation

Procedia PDF Downloads 11

Authors: Nancy Di Tunnariello, Jenna L. Currie-Mueller

Abstract:

Totalistic organizations include organizations that operate by playing a prominent role in the life of its members through embedding values and practices. The Church of Scientology (CoS) is an example of a religious totalistic organization and has recently garnered attention because of the questionable treatment of members by those with authority, particularly when members try to leave the Church. The purpose of this study was to analyze exit communication and evaluate the task and relational messages discussed on online discussion boards for individuals with a previous or current connection to the totalistic CoS. Using organizational exit phases and interaction process analysis (IPA), researchers coded 30 boards consisting of 14,179 thought units from the Exscn.net website. Findings report all stages of exit were present, and post-exit surfaced most often. Posts indicated more tasks than relational messages, where individuals mainly provided orientation/information. After a discussion of the study’s contributions, limitations and directions for future research are explained.

Keywords: Bales' IPA, organizational exit, relational messages, scientology, task messages, totalistic organizations

Procedia PDF Downloads 129

Authors: Eid Alharbi, Yaser Miaji

Abstract:

The quality level for fresh fruits is very important for the fruit industries. In presents study, an automatic online sorting system according to the internal disorder for fresh apple fruit has developed by using near infrared (NIR) spectroscopic technology. The automatic conveyer belts system along with sorting mechanism was constructed. To check the internal quality of the apple fruit, apple was exposed to the NIR radiations in the range 650-1300nm and the data were collected in form of absorption spectra. The collected data were compared to the reference (data of known sample) analyzed and an electronic signal was pass to the sorting system. The sorting system was separate the apple fruit samples according to electronic signal passed to the system. It is found that absorption of NIR radiation in the range 930-950nm was higher in the internally defected samples as compared to healthy samples. On the base of this high absorption of NIR radiation in 930-950nm region the online sorting system was constructed.

Keywords: mechatronics, NIR, fruit quality, spectroscopic technology, mechatronic design

Procedia PDF Downloads 390

Authors: Melissa Houston

Abstract:

Political pressures, financial restraints, and recent legislation has led to administrators’ at academic institutions to rely upon online education as a viable means for delivering education to students anytime and anywhere. Administrators at academic institutions have utilized online education as a way to ensure that academic continuity takes place while campuses are physically closed or are recovering from damages during and after disaster. There is a gap in the research as to how to best train faculty for academic continuity during and after disasters occur. The lack of available research regarding how faculty members at academic institutions prepared themselves prior to a disaster served as a major rationale for this study. The problem that was addressed in this phenomenological study was to identify the training needed by faculty to provide academic continuity during and after times of disaster. The purpose of the phenomenological study was to provide further knowledge and understanding of the training needed by faculty to provide academic continuity after a disaster. Data collection from this study will help human resource professionals as well as administrators of academic institutions to better prepare faculty to provide academic continuity in the future. Participants were recruited on LinkedIn and were qualified as having been faculty who taught traditional courses during or after a disaster. Faculty members were asked a series of open-ended questions to gain understanding of their experiences of how they acquired training for themselves for academic continuity during and after a disaster. The findings from this study showed that faculty members identified assistance needed including professional development in the form of training and support, communication, and technological resources in order to provide academic continuity. The first conclusion from this study was that academic institutions need to support their students, staff and faculty with disaster training and the resources needed to provide academic continuity during and after disasters. The second conclusion from this study is that while disasters and other academic institution incidents are occurring more frequently, limited funding and the push for online education has created limited resources for academic institutions. The need to create partnerships and consortiums with other academic institutions and communities is crucial for the success and sustainability of academic institutions. Through these partnerships and consortiums academic institutions can share resources, knowledge, and training.

Keywords: training, faculty, disaster, academic continuity

Procedia PDF Downloads 189

Authors: Dragana Calic

Abstract:

The openness, availability and the sheer volume of big data have provided, what some regard as, an invaluable and rich dataset. Researchers, businesses, advertising agencies, medical institutions, to name only a few, collect, share, and analyze this data to enable their processes and decision making. However, there are important ethical considerations associated with the use of big data. The rapidly evolving nature of online technologies has overtaken the many legislative, privacy, and ethical frameworks and principles that exist. For example, should we obtain consent to use people’s online data, and under what circumstances can privacy considerations be overridden? Current guidance on how to appropriately and ethically handle big data is inconsistent. Consequently, this paper focuses on two quite distinct but related ethical considerations that are at the core of the use of big data for research purposes. They include empowering the producers of data and empowering researchers who want to study big data. The first consideration focuses on informed consent which is at the core of empowering producers of data. In this paper, we discuss some of the complexities associated with informed consent and consider studies of producers’ perceptions to inform research ethics guidelines and practice. The second consideration focuses on the researcher. Similarly, we explore studies that focus on researchers’ perceptions and experiences.

Keywords: big data, ethics, producers’ perceptions, researchers’ perceptions

Procedia PDF Downloads 284

Authors: Wanyi Zhu, Xia Ming, Huafeng Wang, Junda Chen, Lu Liu, Jiangwei Jiang, Guohua Liu

Abstract:

Anomaly detection is a first and imperative step needed to respond to unexpected problems and to assure high performance and security in large data center management. This paper presents an online anomaly detection system through an innovative approach of ensemble machine learning and adaptive differentiation algorithms, and applies them to performance data collected from a continuous monitoring system for multi-tier web applications running in Alibaba data centers. We evaluate the effectiveness and efficiency of this algorithm with production traffic data and compare with the traditional anomaly detection approaches such as a static threshold and other deviation-based detection techniques. The experiment results show that our algorithm correctly identifies the unexpected performance variances of any running application, with an acceptable false positive rate. This proposed approach has already been deployed in real-time production environments to enhance the efficiency and stability in daily data center operations.

Keywords: Alibaba data centers, anomaly detection, big data computation, dynamic ensemble learning

Procedia PDF Downloads 200

Authors: Liwen Hou

Abstract:

The booming mobile business has been penetrating the taxi industry worldwide with P2P (peer to peer) taxi services, as an emerging business model, transforming the industry. Parallel with other mobile businesses, member recommendations and online reviews are believed to be very effective with regard to acquiring new users for P2P taxi services. Based on an empirical dataset of the taxi industry in China, this study aims to reveal which factors influence users’ recommendations and review-writing behaviors. Differing from the existing literature, this paper takes the taxi driver’s perspective into consideration and hence selects a group of variables related to the drivers. We built two models to reflect the factors that influence the number of recommendations and reviews posted on the platform (i.e., the app). Our models show that all factors, except the driver’s score, significantly influence the recommendation behavior. Likewise, only one factor, passengers’ bad reviews, is insignificant in generating more drivers’ reviews. In the conclusion, we summarize the findings and limitations of the research.

Keywords: online recommendation, P2P taxi service, review-writing, word of mouth

Procedia PDF Downloads 306

Authors: Miguel Llorens-Marin, Adolfo Hernandez, Maria Puelles-Gallo

Abstract:

The increasing influence of Online Travel Agencies (OTAs) on hotel bookings and the electronic word-of-mouth (eWOM) contained in them has been featured by many scientific studies as a major factor in the booking decision. The main reason is that nowadays, in the hotel sector, consumers first come into contact with the offer through the web and the online environment. Due to the nature of the hotel product and the fact that it is booked in advance to actually seeing it, there is a lack of knowledge about its actual features. This makes eWOM a major channel to help consumers to reduce their perception of risk when making their booking decisions. This research studies the relationship between aspects of customer influenceability by reading eWOM communications, at the time of booking a hotel, with the propensity to write a review. In other words, to test relationships between the reading and the writing of eWOM. Also investigates the importance of different underlying motivations for writing eWOM. Online surveys were used to obtain the data from a sample of hotel customers, with 739 valid questionnaires. A measurement model and Path analysis were carried out to analyze the chain of relationships among the independent variable (influenceability from reading reviews) and the dependent variable (propensity to write a review) with the mediating effects of additional variables, which help to explain the relationship. The authors also tested the moderating effects of age and gender in the model. The study considered three different underlying motivations for writing a review on a hotel experience, namely hedonic, altruistic and conflicted. Results indicate that the level of influenceability by reading reviews has a positive effect on the propensity to write reviews; therefore, we manage to link the reading and the writing of reviews. Authors also discover that the main underlying motivation to write a hotel review is the altruistic motivation, being the one with the higher Standard regression coefficient above the hedonic motivation. The authors suggest that the propensity to write reviews is not related to sociodemographic factors (age and gender) but to attitudinal factors such as ‘the most influential factor when reading’ and ‘underlying motivations to write. This gives light on the customer engagement motivations to write reviews. The implications are that managers should encourage their customers to write eWOM reviews on altruistic grounds to help other customers to make a decision. The most important contribution of this work is to link the effect of reading hotel reviews with the propensity to write reviews.

Keywords: hotel reviews, electronic word-of-mouth (eWOM), online consumer reviews, digital marketing, social media

Procedia PDF Downloads 100

Authors: Ekaterina Malova

Abstract:

Type 1 diabetes (T1D) is a chronic illness requiring immense lifestyle changes to reduce the chance of life-threatening complications. Moving to a college may be the first time for a young adult with T1D to take responsibility for all the aspects of their diabetes care. In addition, people with T1D constantly face stigmatization and discrimination as a result of their health condition, which puts additional pressure on young adults with T1D. Hence, omissions in diabetes self-care often occur during the time of transition to college when both the social and physical environment of young adults changes drastically and contribute to the fact that emerging young adults remain one of the age groups with the highest hemoglobin levels and poorest diabetes control. However, despite potential severe health risks caused by a lack of proper diabetes self-care, little is known about the experiences of emerging adults embarking on a higher education journey as this population. Thus, young adults with type 1 diabetes are a 'forgotten group,' meaning that their experiences are rarely addressed by researchers. Given that self-disclosure and information-seeking can be challenging for individuals with stigmatized illnesses, online platforms like YouTube have become a popular medium of self-disclosure and information-seeking for people living with T1D. Thus, this study aims to provide an analysis of experiences that college students with T1D choose to share with the general public online and explore the nature of information being communicated by college students with T1D to the online community in personal narratives posted on YouTube. A systematic approach was used to retrieve a video sample by searching YouTube with keywords 'type 1 diabetes' and 'college,' with results ordered by relevance. A total of 18 videos were saved. Video lengths ranged from 2 to 28 minutes. The data were coded using NVivo. Video transcripts were coded and analyzed utilizing the thematic analysis method. Three key themes emerged from thematic analysis: 1) Advice, 2) Personal experience, and 3) Things I wish everyone knew about T1D. In addition, Theme 1 was divided into subtopics to differentiate between the most common types of advice: 1) Overcoming stigma and b) Seeking social support. The identified themes indicate that two groups of the population can potentially benefit from watching students’ video testimonies: 1) lay public and 2) other students with T1D. Given that students in the videos reported a lack of T1D education in the lay public, such video narratives can serve important educational purposes and reduce health stigma, while perceived similarity and identification with students in the videos may facilitate the transition of health information to other individuals with T1D and positively affect their diabetes routine. Thus, online video narratives can potentially serve both educational and persuasive purposes, empowering students with T1D to stay in control of T1D while succeeding academically.

Keywords: type 1 diabetes, college students, health communication, transition period

Procedia PDF Downloads 153

Authors: Naman Solanki, Souraj Mondal

Abstract:

With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

Procedia PDF Downloads 114

Authors: Lauren Kathryn Stretch

Abstract:

A study was conducted in the underprivileged setting of Nelson Mandela Bay, South Africa in order to monitor the progress of learners whose teachers receive training through the Early Inspiration Training Programme. Through tracking children’s growth & development, the effectiveness of the practitioner-training programme, which focuses on empowering women from underprivileged communities in South Africa, was analyzed. The aim was to identify impact & reach and to assess the effectiveness of this intervention programme through identifying impact on children’s growth and development. A Pre- and Post-Test was administered on about 850 young children in Pre-Grade R and Grade R classes in order to understand children’s ability level & the growth that would be evident as a result of effective teacher training. A pre-test evaluated the level of each child’s abilities, including physical-motor development, language, and speech development, cognitive development including visual perceptual skills, social-emotional development & play development. This was followed by a random selection of the classes of children into experimental and control groups. The experimental group’s teachers (practitioners) received 8-months of training & intervention, as well as mentorship & support. After the 8-month training programme, children from the experimental & control groups underwent post-assessment. The results indicate that the impact of effective practitioner training and enhancing a deep understanding of stimulation on young children, that this understanding is implemented in the classroom, highlighting the areas of growth & development in the children whose teachers received additional training & support, as compared to those who did not receive additional training. Monitoring & Evaluation systems not only track children’s ability levels, but also have a core focus on reporting systems, mentorship and providing ongoing support. As a result of the study, an Online Application (for Apple or Android Devices) was developed which is used to track children’s growth via age-appropriate assessments. The data is then statistically analysed to provide direction for relevant & impactful intervention. The App also focuses on effective reporting strategies, structures, and implementation to support organizations working with young children & maximize on outcomes.

Keywords: early childhood development, developmental child assessments, online application, monitoring and evaluating online

Procedia PDF Downloads 195

Authors: Charléa M. Smith, Raiden L. Schodowski, Arletty Pinel

Abstract:

Due to the COVID-19 pandemic, the Faculty of Medical Sciences of The University of the West Indies (UWI) Mona in Kingston, Jamaica, had to rapidly migrate to digital and blended learning. Students in the preclinical stage of the program transitioned to full-time online learning, while students in the clinical stage experienced decreased daily patient contact and the implementation of a blend of online lectures and virtual clinical practice. Such sudden changes were coupled with the institutional pressure of the need to introduce a novel approach to education without much time for preparation, as well as additional strain endured by the faculty, who were overwhelmed by serving as frontline workers. During the period July 20 to August 23, 2021, this study surveyed preclinical and clinical students to capture their experiences with these changes and their recommendations for future use of digital modalities of learning to enhance medical education. It was conducted with a fellow student of the 2021 cohort of the MultiPod mentoring program. A questionnaire was developed and distributed digitally via WhatsApp to all medical students of the UWI Mona campus to assess students’ experiences and perceptions of the advantages, challenges, and impact on individual knowledge proficiencies brought about by the transition to predominantly digital learning environments. 108 students replied, 53.7% preclinical and 46.3% clinical. 67.6% of the total were female and 30.6 % were male; 1.8% did not identify themselves by gender. 67.2% of preclinical students preferred blended learning and 60.3% considered that the content presented did not prepare them for clinical work. Only 31% considered that the online classes were interactive and encouraged student participation. 84.5% missed socialization with classmates and friends and 79.3% missed a focused environment for learning. 80% of the clinical students felt that they had not learned all that they expected and only 34% had virtual interaction with patients, mostly by telephone and video calls. Observing direct consultations was considered the most useful, yet this was the least-used modality. 96% of the preclinical students and 100% of the clinical ones supplemented their learning with additional online tools. The main recommendations from the survey are the use of interactive teaching strategies, more discussion time with lecturers, and increased virtual interactions with patients. Universities are returning to face-to-face learning, yet it is unlikely that blended education will disappear. This study demonstrates that students’ perceptions of their experience during mobility restrictions must be taken into consideration in creating more effective, inclusive, and efficient blended learning opportunities.

Keywords: blended learning, digital learning, medical education, student perceptions

Procedia PDF Downloads 166

Authors: Norhayati Mat Wajid, Abdul Murad Zainal Abidin, Faiz Fadzil, Mohd Yusof Aizad Mukhtar

Abstract:

One of the areas that present an opportunity to reduce the national carbon emission is the energy management of public buildings. To our present knowledge, there is no easy-to-use and centralized mechanism that enables the government to monitor the overall energy performance, as well as the carbon footprint, of Malaysia’s public buildings. Therefore, the Public Works Department Malaysia, or PWD, has developed a web-based energy performance reporting tool called JENOSYS (JKR Energy Online System), which incorporates a database of utility account numbers acquired from the utility service provider for analysis and reporting. For test case purposes, 23 buildings under PWD were selected and monitored for their monthly energy performance (in kWh), carbon emission reduction (in tCO₂eq) and utility cost (in MYR), against the baseline. This paper demonstrates the simplicity with which buildings without energy metering can be monitored centrally and the benefits that can be accrued by the government in terms of building energy disclosure and concludes with the recommendation of expanding the system to all the public buildings in Malaysia.

Keywords: energy-efficient buildings, energy management systems, government buildings, JENOSYS

Procedia PDF Downloads 174

Authors: Venkata Narayana Chejarla, Nafisa Parvez Shaik, Gopi Vara Prasad Marabathula, Deva Kumar Bejjam

Abstract:

Yoga is an advanced, well-recognized method with roots in Indian philosophy. Yoga benefits both the body and the psyche. Yoga is a regular exercise that helps people relax and sleep better while also enhancing their balance, endurance, and concentration. Yoga can be learned in a variety of settings, including at home with the aid of books and the internet as well as in yoga studios with the guidance of an instructor. Self-learning does not teach the proper yoga poses, and doing them without the right instruction could result in significant injuries. We developed "Online Yoga Asana Trainer using Deep Learning" so that people could practice yoga without a teacher. Our project is developed using Tensorflow, Movenet, and Keras models. The system makes use of data from Kaggle that includes 25 different yoga poses. The first part of the process involves applying the movement model for extracting the 17 key points of the body from the dataset, and the next part involves preprocessing, which includes building a pose classification model using neural networks. The system scores a 98.3% accuracy rate. The system is developed to work with live videos.

Keywords: yoga, deep learning, movenet, tensorflow, keras, CNN

Procedia PDF Downloads 240

Authors: W. S. Barber, S. L. King

Abstract:

This paper is a qualitative case study analysis of the development of a fully online learning community of graduate students through arts-based community building activities. With increasing numbers and types of online learning spaces, it is incumbent upon educators to continue to push the edge of what best practices look like in digital learning environments. In digital learning spaces, instructors can no longer be seen as purveyors of content knowledge to be examined at the end of a set course by a final test or exam. The rapid and fluid dissemination of information via Web 3.0 demands that we reshape our approach to teaching and learning, from one that is content-focused to one that is process-driven. Rather than having instructors as formal leaders, today’s digital learning environments require us to share expertise, as it is the collective experiences and knowledge of all students together with the instructors that help to create a very different kind of learning community. This paper focuses on innovations pursued in a 36 hour 12 week graduate course in higher education entitled “Critical and Reflective Practice”. The authors chronicle their journey to developing a fully online learning community (FOLC) by emphasizing the elements of social, cognitive, emotional and digital spaces that form a moving interplay through the community. In this way, students embrace anywhere anytime learning and often take the learning, as well as the relationships they build and skills they acquire, beyond the digital class into real world situations. We argue that in order to increase student online engagement, pedagogical approaches need to stem from two primary elements, both creativity and critical reflection, that are essential pillars upon which instructors can co-design learning environments with students. The theoretical framework for the paper is based on the interaction and interdependence of Creativity, Intuition, Critical Reflection, Social Constructivism and FOLCs. By leveraging students’ embedded familiarity with a wide variety of technologies, this case study of a graduate level course on critical reflection in education, examines how relationships, quality of work produced, and student engagement can improve by using creative and imaginative pedagogical strategies. The authors examine their professional pedagogical strategies through the lens that the teacher acts as facilitator, guide and co-designer. In a world where students can easily search for and organize information as self-directed processes, creativity and connection can at times be lost in the digitized course environment. The paper concludes by posing further questions as to how institutions of higher education may be challenged to restructure their credit granting courses into more flexible modules, and how students need to be considered an important part of assessment and evaluation strategies. By introducing creativity and critical reflection as central features of the digital learning spaces, notions of best practices in digital teaching and learning emerge.

Keywords: online, pedagogy, learning, communities

Procedia PDF Downloads 404

Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

Abstract:

Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

Procedia PDF Downloads 177

Authors: Ahmed Hariri

Abstract:

E-Learning has become a necessity in the advanced education. It is easier for the student and teacher communication also it speed up the process with less time and less effort. With the progress and the enormous development of distance education must keep up with this age of making a website that allows students and teachers to take all the advantages of advanced education. In this regards, we developed University Short courses web application which is specially designed for Faculty of computing and information technology, Rabigh, Kingdom of Saudi Arabia. After an elaborate review of the current state-of-the-art methods of teaching and learning, we found that instructors deliver extra short courses and workshop to students to enhance the knowledge of students. Moreover, this process is completely manual. The prevailing methods of teaching and learning consume a lot of time; therefore in this context, University Short courses web application will help to make process easy and user friendly. The site allows for students can view and register short courses online conducted by instructor also they can see courses starting dates, finishing date and locations. It also allows the instructor to put things on his courses on the site and see the students enrolled in the study material. Finally, student can print the certificate after finished the course online. ASP.NET, SQLSERVER, JavaScript SQL SERVER Database will use to develop the University Short Courses web application.

Keywords: e-learning, short courses, ASP.NET, SQL SERVER

Procedia PDF Downloads 134

Authors: Enyia James Diwa, Isaiah Thank-God Ebi, Dodeye Ina Igbong

Abstract:

The privatization of utilities has brought about very strong competition in industries such as petrochemical and gas distribution among others, considering the continuous increase in cost of fuel. This has brought about the intense reason for gas turbine owners and operators to reduce and control performance degradation of the engine in other to minimize cost. The most common and very crucial problem of the gas turbine is the fouling of compressor, which is mostly caused by a reduction in flow capacity, compressor efficiency, and pressure ratio, this, in turn, lead to the engine compressor re-matching and output power and thermal efficiency reduction. The content of this paper encompasses a detailed presentation of the major causes, effects and control mechanism of fouling. The major emphasis is on compressor water washing to enable power augmentation. A modelled gas turbine similar to that of GE LM6000 is modelled for the current study, based on TURBOMATCH which is a Cranfield University software specifically made for gas turbine performance simulation and fouling detection. The compounded and intricate challenges of compressor online water washing of large output gas turbine are carried out. The treatment is applied to axial compressor used in the petrochemical and hydrocarbon industry.

Keywords: gas turbine, fouling, degradation, compressor washing

Procedia PDF Downloads 348

Authors: Elizabeth Mahenge

Abstract:

Unemployment is a problem that face many graduates all over the world. Every year universities in many parts of the world produce graduates who are looking for an employment. Swahili, a Bantu language originated in East African coast, can be used as an avenue for youth’s employment in South Africa. This paper helps youth to know about job opportunities available through teaching Swahili language. The objective of this paper is capacity building to youths to be teachers of Swahili and be ready to compete in the marketplace. The methodology was through two weeks online training on how to teach Swahili as a foreign language. The communicative approach and task-based approach were used.  Participants to this training were collected through a WhatsApp group advertisement about “short training for Swahili teachers for foreigners”. A total number of 30 participants registered but only 11 attended the training. Training was online via zoom. The contribution of this paper is that by being fluent in Swahili one would benefit with teaching job opportunities anywhere in the world. Hence the problem of unemployment among the youths would be reduced as they can employ themselves or being employed in academic institutions anywhere in the world. The paper calls for youths in South Africa to opt for Swahili language courses to be trained and become experts in the teaching Swahili as a foreign language.

Keywords: foreign language, linguistic market, Swahili, employment

Procedia PDF Downloads 76

Authors: Mustafa Tevfik Hebebci, Ismail Sahin, Sirin Kucuk, Ismail Celik, Ahmet Oguz Akturk

Abstract:

ADDIE is an instructional design model which has the five core elements: analyze, design, develop, implement, and evaluate. The ADDIE approach provides a systematic process for the analysis of instructional needs, the design and development of instructional programs and materials, implementation of a program, and the evaluation of the effectiveness of an instruction. The case-based study is an instructional design model that is a variant of project-oriented learning. Collecting and analyzing stories can be used in two primary ways -perform task analysis and as a learning support during instruction- by instructional designers. Besides, teachers use technology to develop students’ thinking, enriching the learning environment and providing permanent learning. The purpose of this paper is to introduce an interactive online case-study library website developed in a national project. The design goal of the website is to provide interactive, enhanced, case-based and online educational resource for educators through the purpose and within the scope of a national project. The ADDIE instructional design model was used in the development of the website for the interactive case-based library. This web-based library contains the navigation menus as the follows: “Homepage”, "Registration", "Branches", "Aim of The Research", "About TPACK", "National Project", "Contact Us", etc. This library is developed on a web-based platform, which is important in terms of manageability, accessibility, and updateability of data. Users are able to sort the displayed case-studies by their titles, dates, ratings, view counts, etc. In addition, they encouraged to rate and comment on the case-studies. The usability test is used and the expert opinion is taken for the evaluation of the website. This website is a tool to integrate technology in education. It is believed that this website will be beneficial for pre-service and in-service teachers in terms of their professional developments.

Keywords: design, ADDIE, case based library, technology integration

Procedia PDF Downloads 479

Authors: Rajeev Kumar Bedi, Jaswinder Singh, Sunil Kumar Gupta

Abstract:

Cloud storage is a model of online data storage where data is stored in virtualized pool of servers hosted by third parties (CSPs) and located in different geographical locations. Cloud storage revolutionized the way how users access their data online anywhere, anytime and using any device as a tablet, mobile, laptop, etc. A lot of issues as vendor lock-in, frequent service outage, data loss and performance related issues exist in single cloud storage systems. So to evade these issues, the concept of multi cloud storage introduced. There are a lot of multi cloud storage systems exists in the market for mobile devices. In this article, we are providing comparison of four multi cloud storage systems for mobile devices Otixo, Unclouded, Cloud Fuze, and Clouds and evaluate their performance on the basis of CPU usage, battery consumption, time consumption and data usage parameters on three mobile phones Nexus 5, Moto G and Nexus 7 tablet and using Wi-Fi network. Finally, open research challenges and future scope are discussed.

Keywords: cloud storage, multi cloud storage, vendor lock-in, mobile devices, mobile cloud computing

Procedia PDF Downloads 407

Authors: Shivalaxmi Arumugham

Abstract:

Child sexual abuse (CSA) has taken several forms, particularly with the advent of internet technologies that provide pedophiles access to their targets anonymously at an affordable rate. To combat CSA which has far-reaching consequences on the physical and psychological health of the victims, a special act, the Protection of Children from Sexual Offences (POCSO) Act, was formulated amongst the existing laws. With its latest amendment criminalizing various online activities about child pornography also known as child sexual abuse materials in 2019, tremendous pressure is speculated on law enforcement to identify offenders online. Effective investigations of CSA cases help in not only to detect perpetrators but also in preventing the re-victimization of children. Understanding the vulnerability of the child population and that the offenders continue to develop stealthier strategies to operate, it is high time that traditional investigation, where the focus is on apprehending and prosecuting the offender, must make a paradigm shift to proactively investigate to prevent victimization at the first place. One of the proactive policing techniques involves understanding the psychology of the offenders and children and operating undercover to catch the criminals before a real child is victimized. With the fundamental descriptive approach to research, the article attempts to identify the multitude of issues associated with the investigation of child sexual abuse cases currently in practice in India. Then, the article contextualizes the various covert operations carried out by numerous law enforcement agencies across the globe. To provide this comprehensive overview, the paper examines various reports, websites, guidelines, protocols, judicial pronouncements, and research articles. Finally, the paper presents the challenges and ethical issues that are to be considered before getting into undercover operations either in the guise of a pedophile or as a child. The research hopes to contribute to the making of standard operating protocols for investigation officers and other relevant policymakers in this regard.

Keywords: child sexual abuse, cybercrime against children, covert police operations, investigation of CSA

Procedia PDF Downloads 97

Authors: Xueyang Li

Abstract:

This thesis investigates the impact of self-viewing on team creativity in virtual teamwork and examines the role of objective self-awareness and psychological safety in this context. The study uses a quantitative research approach and collects data from 304 participants working in virtual teams. We hypothesized that observing oneself in online meetings would lead to a heightened sense of objective self and thus lower team creativity and that psychological safety would moderate their relationship. We tested these hypotheses in a laboratory experiment manipulating whether participants were able to observe themselves during the completion of an online team creativity task and manipulating whether participants were subjected to a psychological safety intervention. The results indicate that self-observation has a negative effect on team creativity in virtual teamwork, while objective self-awareness mediates this relationship, and psychological safety plays a moderating role. We discuss several aspects of the theoretical explanation of the findings. This study contributes to the existing literature by highlighting the importance of self-observation in virtual teamwork and provides practical implications for managers and team leaders to promote creativity in virtual teams.

Keywords: objective self-awareness, psychological safety, self-viewing, team creativity, virtual teamwork

Procedia PDF Downloads 100

Authors: Shady Adib, Vladimir Vinogradov, Peter Gosling

Abstract:

Digital Twin (DT) technology is a new technology that appeared in the early 21st century. The DT is defined as the digital representation of living and non-living physical assets. By connecting the physical and virtual assets, data are transmitted smoothly, allowing the virtual asset to fully represent the physical asset. Although there are lots of studies conducted on the DT concept, there is still limited information about the ability of the DT models for monitoring and detecting unexpected changes in structural behaviour in real time. This is due to the large computational efforts required for the analysis and an excessively large amount of data transferred from sensors. This paper aims to develop the DT concept to be able to detect the abnormal changes in structural behaviour in real time using advanced modelling techniques, deep learning algorithms, and data acquisition systems, taking into consideration model uncertainties. finite element (FE) models were first developed offline to be used with a reduced basis (RB) model order reduction technique for the construction of low-dimensional space to speed the analysis during the online stage. The RB model was validated against experimental test results for the establishment of a DT model of a two-dimensional truss. The established DT model and deep learning algorithms were used to identify the location of damage once it has appeared during the online stage. Finally, the RB model was used again to identify the damage severity. It was found that using the RB model, constructed offline, speeds the FE analysis during the online stage. The constructed RB model showed higher accuracy for predicting the damage severity, while deep learning algorithms were found to be useful for estimating the location of damage with small severity.

Keywords: data acquisition system, deep learning, digital twin, model uncertainties, reduced basis, reduced order model

Procedia PDF Downloads 99