Search results for: video lectures

Authors: Jimmy K. C. Lam, Carrie Wong

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One of the key goals on Learning and Teaching as documented in the University strategic plan 2012/13 – 2017/18 is to encourage active learning, the use of innovative teaching approaches and technology, and promoting the adoption of flexible and varied teaching delivery methods. This research reported the recent visited to Prof Eric Mazur at Harvard University on Peer Instruction: Collaborative learning in large class and innovative use of technology to enable new mode of learning. Peer Instruction is a research-based, interactive teaching method developed by Prof. Eric Mazur at Harvard University in the 1990s. It has been adopted across the disciplines, institutional type and throughout the world. One problem with conventional teaching lies in the presentation of the material. Frequently, it comes straight out of textbook/notes, giving students little incentive to attend class. This traditional presentation is always delivered as monologue in front of passive audience. Only exceptional lecturers are capable of holding students’ attention for an entire lecture period. Consequently, lectures simply reinforce students’ feelings that the most important step in mastering the material is memorizing a zoo of unrelated examples. In order to address these misconceptions about learning, Prof Mazur’s Team developed “Peer Instruction”, a method which involves students in their own learning during lectures and focuses their attention on underling concepts. Lectures are interspersed with conceptual questions called Concept Tests, designed to expose common difficulties in understanding the material. The students are given one or two minutes to think about the question and formulate their own answers; they then spend two or three minutes discussing their answers in a group of three or four, attempting to reach consensus on the correct answer. This process forces the students to think through the arguments being developed, and enable them to assess their understanding concepts before they leave the classroom. The findings from Peer Instruction and innovative use of technology on teaching at Harvard University were applied to the first year Textiles and Fashion students in Hong Kong. Survey conducted from 100 students showed that over 80% students enjoyed the flexibility of peer instruction and 70% of them enjoyed the instant feedback from the Clicker system (Student Response System used at Harvard University). Further work will continue to explore the possibility of peer instruction to art and fashion students.

Keywords: peer instruction, education, technology, fashion

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Authors: Tom O'Mahony

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This article considers the design of a student-centered learning environment in engineering education. The learning environment integrates a number of components, including project-based learning, collaborative learning, two-stage assignments, active learning lectures, and a flipped-classroom. Together these elements place the individual learner and their learning at the center of the environment by focusing on understanding, enhancing relevance, applying learning, obtaining rich feedback, making choices, and taking responsibility. The evolution of this environment from 2014 to the present day is outlined. The impact of this environment on learners and their learning is evaluated via student questionnaires that consist of both open and closed-ended questions. The closed questions indicate that students found the learning environment to be really interesting and enjoyable (rated as 4.7 on a 5 point scale) and encouraged students to adopt a deep approach towards studying the course materials (rated as 4.0 on a 5 point scale). A content analysis of the open-ended questions provides evidence that the project, active learning lectures, and flipped classroom all contribute to the success of this environment. Furthermore, this analysis indicates that the two-stage assessment process, in which feedback is provided between a draft and final assignment, is the key component and the dominant theme. A limitation of the study is the small class size (less than 20 learners per year), but, to some degree, this is compensated for by the longitudinal nature of the study.

Keywords: deep approaches, formative assessment, project-based learning, student-centered learning

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Authors: Ahemd Sameer, Braj Bhushan

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The objective of our study was to compare wayfinding strategies to remember route while navigation in an unfamiliar homogenous environment. Two videos developed using free ware Trimble Sketchup© each having nine identical turns (3 right, 3 left, 3 straight) with no distinguishing feature at any turn. Thirt-two male post-graduate students of IIT Kanpur participated in the study. The experiment was conducted in three phases. In the first phase participant generated a list of personally known items to be used as landmarks. In the second phase participant saw the first video and was required to remember the sequence of turns. In the second video participant was required to imagine a landmark from the list generated in the first phase at each turn and associate the turn with it. In both the task the participant was asked to recall the sequence of turns as it appeared in the video. In the third phase, which was 20 minutes after the second phase, participants again recalled the sequence of turns. Results showed that performance in the first condition i.e. without use of landmarks was better than imaginary landmark condition. The difference, however, became significant when the participant were tested again about 30 minutes later though performance was still better in no-landmark condition. The finding is surprising given the past research in memory and is explained in terms of cognitive factors such as mental workload.

Keywords: Wayfinding, Landmark, Homogenous Environment, Memory

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Authors: Danielle Morin, Jennifer D. E. Thomas, Raafat G. Saade, Daniela Petrachi

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Over the past few decades, more and more students choose to enroll in online classes instead of attending in-class lectures. While past studies consider students’ attitudes towards online education and how their grades differed from in-class lectures, the profile of the online student remains a blur. To shed light on this, an online survey was administered to about 1,500 students enrolled in an undergraduate Fundamental Business Technology course at a Canadian University. The survey was comprised of questions on students’ demographics, their reasons for choosing online courses, their expectations towards the course, the communication channels they use for the course with fellow students and with the instructor. This paper focused on the research question: Do the perspectives of online students concerning the online experience, in general, and in the course in particular, differ according to age profile? After several statistical analyses, it was found that age does have an impact on the reasons why students select online classes instead of in-class. For example, it was found that the perception that an online course might be easier than in-class delivery was a more important reason for younger students than for older ones. Similarly, the influence of friends is much more important for younger students, than for older students. Similar results were found when analyzing students’ expectation about the online course and their use of communication tools. Overall, the age profile of online users had an impact on reasons, expectations and means of communication in an undergraduate Fundamental Business Technology course. It is left to be seen if this holds true across other courses, graduate and undergraduate.

Keywords: communication channels, fundamentals of business technology, online classes, pedagogy, user age profile, user perspectives

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Authors: Eva Nolan, Timothy Mcnichols

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Gamers spend over 3 billion hours collectively playing video games a week, which is arguably not nearly enough time to indulge in the many benefits gaming has to offer. Much of the previous research on video gaming is centered on the effects of playing violent video games and the negative impacts they have on the individual. However, there is a dearth of research in the area of non-violent video games, specifically the emotional and cognitive benefits playing non-violent games can offer individuals. Current research in the area of video game play suggests there are many benefits to playing for an individual, such as decreasing symptoms of depression, decreasing stress, increasing positive emotions, inducing relaxation, decreasing anxiety, and particularly improving mood. One suggestion as to why video games may offer such benefits is that they possess ideal characteristics to create and maintain flow experiences, which in turn, is the subjective experience where an individual obtains a heightened and improved state of mind while they are engaged in a task where a balance of challenge and skill is found. Many video games offer a platform for collaborative gameplay, which can enhance the emotional experience of gaming through the feeling of social support and social inclusion. The present study was designed to examine the effects of collaborative gameplay and flow experience on participants’ perceived mood. To investigate this phenomenon, an in-between subjects design involving forty participants were randomly divided into two groups where they engaged in solo or collaborative gameplay. Each group represented an even number of frequent gamers and non-frequent gamers. Each participant played ‘The Lego Movie Videogame’ on the Playstation 4 console. The participant’s levels of flow experience and perceived mood were measured by the Flow State Scale (FSS) and the Positive and Negative Affect Schedule (PANAS). The following research hypotheses were investigated: (i.) participants in the collaborative gameplay condition will experience higher levels of flow experience and higher levels of mood than those in the solo gameplay condition; (ii.) participants who are frequent gamers will experience higher levels of flow experience and higher levels of mood than non-frequent gamers; and (iii.) there will be a significant positive relationship between flow experience and mood. If the estimated findings are supported, this suggests that engaging in collaborative gameplay can be beneficial for an individual’s mood and that experiencing a state of flow can also enhance an individual’s mood. Hence, collaborative gaming can be beneficial to promote positive emotions (higher levels of mood) through engaging an individual’s flow state.

Keywords: collaborative gameplay, flow experience, mood, games, positive emotions

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Authors: Begona del Pino, Beatriz Prieto, Alberto Prieto

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Two opposite approaches to teaching can be considered: in-class learning (teacher-oriented) versus virtual learning (student-oriented). The most known example of the latter is Massive Online Open Courses (MOOCs). Both methodologies have pros and cons. Nowadays there is an increasing trend towards combining both of them. Blending learning is considered a valuable tool for improving learning since it combines student-centred interactive e-learning and face to face instruction. The aim of this contribution is to exchange and share the experience and research results of a blended-learning project that took place in the University of Granada (Spain). The research objective was to prove how combining didactic resources of a MOOC with in-class teaching, interacting directly with students, can substantially improve academic results, as well as student acceptance. The proposed methodology is based on the use of flipped learning technics applied to the subject ‘Fundamentals of Computer Science’ of the first course of two degrees: Telecommunications Engineering, and Industrial Electronics. In this proposal, students acquire the theoretical knowledges at home through a MOOC platform, where they watch video-lectures, do self-evaluation tests, and use other academic multimedia online resources. Afterwards, they have to attend to in-class teaching where they do other activities in order to interact with teachers and the rest of students (discussing of the videos, solving of doubts and practical exercises, etc.), trying to overcome the disadvantages of self-regulated learning. The results are obtained through the grades of the students and their assessment of the blended experience, based on an opinion survey conducted at the end of the course. The major findings of the study are the following: The percentage of students passing the subject has grown from 53% (average from 2011 to 2014 using traditional learning methodology) to 76% (average from 2015 to 2018 using blended methodology). The average grade has improved from 5.20±1.99 to 6.38±1.66. The results of the opinion survey indicate that most students preferred blended methodology to traditional approaches, and positively valued both courses. In fact, 69% of students felt ‘quite’ or ‘very’ satisfied with the classroom activities; 65% of students preferred the flipped classroom methodology to traditional in-class lectures, and finally, 79% said they were ‘quite’ or ‘very’ satisfied with the course in general. The main conclusions of the experience are the improvement in academic results, as well as the highly satisfactory assessments obtained in the opinion surveys. The results confirm the huge potential of combining MOOCs in formal undergraduate studies with on-campus learning activities. Nevertheless, the results in terms of students’ participation and follow-up have a wide margin for improvement. The method is highly demanding for both students and teachers. As a recommendation, students must perform the assigned tasks with perseverance, every week, in order to take advantage of the face-to-face classes. This perseverance is precisely what needs to be promoted among students because it clearly brings about an improvement in learning.

Keywords: blended learning, educational paradigm, flipped classroom, flipped learning technologies, lessons learned, massive online open course, MOOC, teacher roles through technology

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Authors: V. Miller, T. Jariel, C. Cooper-Chadwick

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Early treatment of stroke leads to higher survival and lower disability rates. Increasing knowledge to activate the emergency medical system for signs of stroke can improve outcomes for patients with stroke and decrease morbidity and mortality. Even though patients who get discharged from the hospital receive standard verbal and printed education, nearly 20% of them answer the question incorrectly when asked, “What will you do if you or someone you know have signs of stroke?” The main goal of this evidence-based project was to improve patients’ knowledge of what to do if they have signs of stroke. Evidence suggests that using video education in conjunction with verbal and printed education improves patient comprehension and retention. The percentage of patients who noted that they needed to call 911 for stroke symptoms increased from 80% to 87% in six months after project implementation. The results of this project demonstrate significant improvement in patients’ knowledge about the necessity of activation of emergency medical systems for stroke symptoms.

Keywords: emergency medical systems activation, evidence-based practice nursing, stroke education, video education

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Authors: Tomas Berhanu Bekele

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Traffic congestion is one of the main problems related to transportation in developed as well as developing countries. Traffic control systems are based on the idea of avoiding traffic instabilities and homogenizing traffic flow in such a way that the risk of accidents is minimized and traffic flow is maximized. Lately, Intelligent Transport Systems (ITS) has become an important area of research to solve such road traffic-related issues for making smart decisions. It links people, roads and vehicles together using communication technologies to increase safety and mobility. Moreover, accurate prediction of road traffic is important to manage traffic congestion. The aim of this study is to develop an ANN model for the prediction of traffic flow and to compare the ANN model with the linear regression model of traffic flow predictions. Data extraction was carried out in intervals of 15 minutes from the video player. Video of mixed traffic flow was taken and then counted during office work in order to determine the traffic volume. Vehicles were classified into six categories, namely Car, Motorcycle, Minibus, mid-bus, Bus, and Truck vehicles. The average time taken by each vehicle type to travel the trap length was measured by time displayed on a video screen.

Keywords: intelligent transport system (ITS), traffic flow prediction, artificial neural network (ANN), linear regression

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Authors: Kazumoto Tanaka

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It is well known that sport skill learning is facilitated by video observation of players’ actions in sports. The optimal viewpoint for the observation of actions depends on sport scenes. On the other hand, it is impossible to change viewpoint for the observation in general, because most videos are filmed from fixed points. The study has tackled the problem and focused on karate match as a first step. The study developed a method for observing karate player’s actions from any point of view by using 3D-CG model (i.e. virtual player) obtained from video images, and verified the effectiveness of the method on karate match.

Keywords: computer graphics, karate training, learning by observation, motion capture, virtual player

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Authors: Eleni Ioanna Levantinou

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Gestures play a major role in comprehension and memory recall due to the fact that aid the efficient channel of the meaning and support listeners’ comprehension and memory. In the present study, the assistance of two kinds of gestures (iconic and beat gestures) is tested in regards to memory and recall. The hypothesis investigated here is whether or not iconic and beat gestures provide assistance in memory and recall in Greek and in Greek speakers’ second language. Two groups of participants were formed, one comprising Greeks that reside in Athens and one with Greeks that reside in Copenhagen. Three kinds of stimuli were used: A video with words accompanied with iconic gestures, a video with words accompanied with beat gestures and a video with words alone. The languages used are Greek and English. The words in the English videos were spoken by a native English speaker and by a Greek speaker talking English. The reason for this is that when it comes to beat gestures that serve a meta-cognitive function and are generated according to the intonation of a language, prosody plays a major role. Thus, participants that have different influences in prosody may generate different results from rhythmic gestures. Memory recall was assessed by asking the participants to try to remember as many words as they could after viewing each video. Results show that iconic gestures provide significant assistance in memory and recall in Greek and in English whether they are produced by a native or a second language speaker. In the case of beat gestures though, the findings indicate that beat gestures may not play such a significant role in Greek language. As far as intonation is concerned, a significant difference was not found in the case of beat gestures produced by a native English speaker and by a Greek speaker talking English.

Keywords: first language, gestures, memory, second language acquisition

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Authors: Lata Kiran Dey, Rajendra Kumar, Biren Karmakar

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Web Real Time Communications is a collection of standards, protocols, which provides real-time communications capabilities between web browsers and devices. This paper outlines the design and further implementation of web real-time communications on secure web applications having audio and video call capabilities. This proposed application may put up a system that will be able to work over both desktops as well as the mobile browser. Though, WebRTC also gives a set of JavaScript standard RTC APIs, which primarily works over the real-time communication framework. This helps to build a suitable communication application, which enables the audio, video, and message transfer in between the today’s modern browsers having WebRTC support.

Keywords: WebRTC, SIP, RTC, JavaScript, SRTP, secure web sockets, browser

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Authors: Pratik Dhabal Deo, Manoj P.

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With the increasing number of social media users, the amount of video content available has also significantly increased. Currently, the number of smartphone users is at its peak, and many are increasingly using their smartphones as their main photography and recording devices. There have been a lot of developments in the field of Video Quality Assessment (VQA) and metrics like VMAF, SSIM etc. are said to be some of the best performing metrics, but the evaluation of these metrics is dominantly done on professionally taken video contents using professional tools, lighting conditions etc. No study particularly pinpointing the performance of the metrics on the contents taken by users on very commonly available devices has been done. Datasets that contain a huge number of videos from different high-end devices make it difficult to analyze the performance of the metrics on the content from most used devices even if they contain contents taken in poor lighting conditions using lower-end devices. These devices face a lot of distortions due to various factors since the spectrum of contents recorded on these devices is huge. In this paper, we have presented an analysis of the objective VQA metrics on contents taken only from most used devices and their performance on them, focusing on full-reference metrics. To carry out this research, we created a custom dataset containing a total of 90 videos that have been taken from three most commonly used devices, and android smartphone, an IOS smartphone and a DSLR. On the videos taken on each of these devices, the six most common types of distortions that users face have been applied on addition to already existing H.264 compression based on four reference videos. These six applied distortions have three levels of degradation each. A total of the five most popular VQA metrics have been evaluated on this dataset and the highest values and the lowest values of each of the metrics on the distortions have been recorded. Finally, it is found that blur is the artifact on which most of the metrics didn’t perform well. Thus, in order to understand the results better the amount of blur in the data set has been calculated and an additional evaluation of the metrics was done using HEVC codec, which is the next version of H.264 compression, on the camera that proved to be the sharpest among the devices. The results have shown that as the resolution increases, the performance of the metrics tends to become more accurate and the best performing metric among them is VQM with very few inconsistencies and inaccurate results when the compression applied is H.264, but when the compression is applied is HEVC, SSIM and VMAF have performed significantly better.

Keywords: distortion, metrics, performance, resolution, video quality assessment

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Authors: Abe Degale D., Cheng Jian

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When creating automated video surveillance systems, violent action recognition is crucial. In recent years, hand-crafted feature detectors have been the primary method for achieving violence detection, such as the recognition of fighting activity. Researchers have also looked into learning-based representational models. On benchmark datasets created especially for the detection of violent sequences in sports and movies, these methods produced good accuracy results. The Hockey dataset's videos with surveillance camera motion present challenges for these algorithms for learning discriminating features. Image recognition and human activity detection challenges have shown success with deep representation-based methods. For the purpose of detecting violent images and identifying aggressive human behaviours, this research suggested a deep representation-based model using the transfer learning idea. The results show that the suggested approach outperforms state-of-the-art accuracy levels by learning the most discriminating features, attaining 99.34% and 99.98% accuracy levels on the Hockey and Movies datasets, respectively.

Keywords: violence detection, faster RCNN, transfer learning and, surveillance video

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Authors: Balaji Ganesh Rajagopal, Subramanian Appavu alias Balamurugan, Ayyalraj Midhun Kumar, Krishnan Nallaperumal

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Intelligent Transportation System is an Emerging area to solve multiple transportation problems. Several forms of inputs are needed in order to solve ITS problems. Advanced Traveler Information System (ATIS) is a core and important ITS area of this modern era. This involves travel time forecasting, efficient road map analysis and cost based path selection, Detection of the vehicle in the dynamic conditions and Traffic congestion state forecasting. This Article designs and provides an algorithm for traffic data generation which can be used for the above said ATIS application. By inputting the real world traffic situation in the form of video sequences, the algorithm determines the Traffic density in terms of congestion, number of vehicles in a given path which can be fed for various ATIS applications. The Algorithm deduces the key frame from the video sequences and follows the Blob detection, Identification and Tracking using connected components algorithm to determine the correlation between the vehicles moving in the real road scene.

Keywords: traffic transportation, traffic density estimation, blob identification and tracking, relative velocity of vehicles, correlation between vehicles

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Authors: Adina Dudau, Georgios Kominis, Melinda Szocs

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This paper links distinct bodies of literature around innovation and public services by examining a case of perceived innovation failure. Through a mixed methodology investigating student attitudes to, and behaviour around, technological innovation in higher education, the paper makes a contribution to the public service innovation literature by focusing on the duality of innovation outcomes, suggestive of an innovation typology in public services. The study was conducted in a UK Russell Group university and it focused on a technological process innovation. The innovation consisted of the provision of feedback to students in the form of a digital video (mp4), tailored to each individual submission, with extended voice-over commentary from the course coordinator and visual cues intended to help students see the relevance of comments to their submissions. The sample of the study consisted of a class of 79 undergraduate students. To investigate student attainment, we designed a field (also known as quasi or natural) experiment, essentially a manipulation of a social setting (in this case, the form of feedback given to students), but as part of a naturally occurring social arrangement (a real course which students attend and in which they are assessed). A two group control group design (see figure 3) was utilised to examine the effectiveness of the feedback innovation (video feedback). Two outcome variables of the service innovation were measured: student satisfaction and student attainment. In other words, the study examined not only students’ perceptions of whether VF was deemed to be beneficial towards their subsequent assignments; but also evidence of actual incremental benefits in students’ performance from one assignment to the next after VF was provided. The results were baffling and indicating competing agendas in higher education.

Keywords: higher education, audio-video, feedback, innovation

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Authors: Belkacem Soundes, Guezouli Larbi

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This paper presents a robust and accurate method for text detection and localization over lecture videos. Frame regions are classified into text or background based on visual feature analysis. However, lecture video shows significant degradation mainly related to acquisition conditions, camera motion and environmental changes resulting in low quality videos. Hence, affecting feature extraction and description efficiency. Moreover, traditional text detection methods cannot be directly applied to lecture videos. Therefore, robust feature extraction methods dedicated to this specific video genre are required for robust and accurate text detection and extraction. Method consists of a three-step process: Slide region detection and segmentation; Feature extraction and non-text filtering. For robust and effective features extraction moment functions are used. Two distinct types of moments are used: orthogonal and non-orthogonal. For orthogonal Zernike Moments, both Pseudo Zernike moments are used, whereas for non-orthogonal ones Hu moments are used. Expressivity and description efficiency are given and discussed. Proposed approach shows that in general, orthogonal moments show high accuracy in comparison to the non-orthogonal one. Pseudo Zernike moments are more effective than Zernike with better computation time.

Keywords: text detection, text localization, lecture videos, pseudo zernike moments

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Authors: J. Chow

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In laboratory settings, this study measured and reported the effects of undergraduate students watching animated videos on learning microeconomics as compared with the effectiveness of reading written texts. The study described an experiment on learning microeconomics in higher education using two different types of learning materials. It reported the effectiveness on microeconomics learning of watching animated videos and reading written texts. Undergraduate students in the university were randomly assigned to either a ‘video group’ or a ‘text group’ in the experiment. Previously-validated multiple-choice questions on fundamental concepts of microeconomics were administered. Both groups showed improvement between the pre-test and post-test. The experience of learning using text and video materials was also assessed. After controlling the student characteristics variables, the analyses showed that both types of materials showed comparable level of perceived learning experience. The effect size and statistical significance of these results supported the hypothesis that animated video is an effective alternative to text materials as a learning tool for students. The findings suggest that such animated videos may support teaching microeconomics in higher education.

Keywords: animated videos for education, laboratory experiment, microeconomics education, undergraduate economics education

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Authors: Derlis Gregor, Kevin Cikel, Mario Arzamendia, Raúl Gregor

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This paper presents a self-sustaining mobile system for counting and classification of vehicles through processing video. It proposes a counting and classification algorithm divided in four steps that can be executed multiple times in parallel in a SBC (Single Board Computer), like the Raspberry Pi 2, in such a way that it can be implemented in real time. The first step of the proposed algorithm limits the zone of the image that it will be processed. The second step performs the detection of the mobile objects using a BGS (Background Subtraction) algorithm based on the GMM (Gaussian Mixture Model), as well as a shadow removal algorithm using physical-based features, followed by morphological operations. In the first step the vehicle detection will be performed by using edge detection algorithms and the vehicle following through Kalman filters. The last step of the proposed algorithm registers the vehicle passing and performs their classification according to their areas. An auto-sustainable system is proposed, powered by batteries and photovoltaic solar panels, and the data transmission is done through GPRS (General Packet Radio Service)eliminating the need of using external cable, which will facilitate it deployment and translation to any location where it could operate. The self-sustaining trailer will allow the counting and classification of vehicles in specific zones with difficult access.

Keywords: intelligent transportation system, object detection, vehicle couting, vehicle classification, video processing

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Authors: Ceren Kaya, Okan Erkaymaz, Orhan Ayar, Mahmut Özer

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Diabetes Mellitus (Diabetes) is a disease based on insulin hormone disorders and causes high blood glucose. Clinical findings determine that diabetes can be diagnosed by electrophysiological signals obtained from the vital organs. 'Diabetic Retinopathy' is one of the most common eye diseases resulting on diabetes and it is the leading cause of vision loss due to structural alteration of the retinal layer vessels. In this study, features of horizontal and vertical Video-Oculography (VOG) signals have been used to classify non-proliferative and proliferative diabetic retinopathy disease. Twenty-five features are acquired by using discrete wavelet transform with VOG signals which are taken from 21 subjects. Two models, based on multi-layer perceptron and radial basis function, are recommended in the diagnosis of Diabetic Retinopathy. The proposed models also can detect level of the disease. We show comparative classification performance of the proposed models. Our results show that proposed the RBF model (100%) results in better classification performance than the MLP model (94%).

Keywords: diabetic retinopathy, discrete wavelet transform, multi-layer perceptron, radial basis function, video-oculography (VOG)

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Authors: James G. Matthew, Seonmin Huh, Frank X. Bennett

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English for Specific Purposes, ESP, aims to equip learners with necessary English language skills. Many ESP programs address language skills for job performance, including reading job related documents and oral proficiency. Within ESP is English for occupational purposes, EOP, which centers around developing communicative competence for the globalized workplace. Many ESP and EOP courses lack the content needed to assist students to progress at work, resulting in the need to create lexical compilation for different professions. It is important to teach communicative competence and soft skills for real job-related problem situations and address the complexities of the real world to help students to be successful in their professions. ESP and EOP research is therefore trying to balance both profession-specific educational contents as well as international multi-disciplinary language skills for the globalized workforce. The current study will build upon the existing discussion by developing pedagogy to assist students in their career through developing a strong practical command of relevant English vocabulary. Our research question focuses on the pedagogy two professors incorporated in their English for employment courses. The current study is a qualitative case study on the modes of teaching delivery for EOP in South Korea. Two foreign professors teaching at two different universities in South Korea volunteered for the study to explore their teaching practices. Both professors’ curriculums included the components of employment-related concept vocabulary, business presentations, CV/resume and cover letter preparation, and job interview preparation. All the pre-made recorded video lectures, live online class sessions with students, teachers’ lesson plans, teachers’ class materials, students’ assignments, and midterm and finals video conferences were collected for data analysis. The study then focused on unpacking representative patterns in their teaching methods. The professors used their strengths as native speakers to extend the class discussion from narrow and restricted conversations to giving students broader opportunities to practice authentic English conversation. The methods of teaching utilized three main steps to extend the conversation. Firstly, students were taught concept vocabulary. Secondly, the vocabulary was then combined in speaking activities where students had to solve scenarios, and the students were required to expand on the given forms of words and language expressions. Lastly, the students had conversations in English, using the language learnt. The conversations observed in both classes were those of authentic, expanded English communication and this way of expanding concept vocabulary lessons into extended conversation is one representative pedagogical approach that both professors took. Extended English conversation, therefore, is crucial for EOP education.

Keywords: concept vocabulary, english as a foreign language, english for employment, extended conversation

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Authors: Boukerch Haroun, Luo Qing Sheng, Li Hua Shi, Boukraa Sebti

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In this paper we present the design and the implementation of a target tracking system where the target is set to be a moving person in a video sequence. The system can be applied easily as a vision system for mobile robot. The system is composed of two major parts the first is the detection of the person in the video frame using the SVM learning machine based on the “HOG” descriptors. The second part is the tracking of a moving person it’s done by using a combination of the Kalman filter and a modified version of the Camshift tracking algorithm by adding the target motion feature to the color feature, the experimental results had shown that the new algorithm had overcame the traditional Camshift algorithm in robustness and in case of occlusion.

Keywords: camshift algorithm, computer vision, Kalman filter, object tracking

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Authors: Megan Glyde, Louise Dye, David Keane, Ed Sutherland

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Background: Typically patient education is provided either verbally, in the form of written material, or with a multimedia-based tool such as videos, CD-ROMs, DVDs, or via the internet. By providing patients with effective educational tools, this can help to meet their information needs and subsequently empower these patients and allow them to participate within medical-decision making. Video education may have some distinct advantages compared to other modalities. For instance, whilst eHealth is emerging as a promising modality of patient education, an individual’s ability to access, read, and navigate through websites or online modules varies dramatically in relation to health literacy levels. Literacy levels may also limit patients’ ability to understand written education, whereas video education can be watched passively by patients and does not require high literacy skills. Other benefits of video education include that the same information is provided consistently to each patient, it can be a cost-effective method after the initial cost of producing the video, patients can choose to watch the videos by themselves or in the presence of others, and they can pause and re-watch videos to suit their needs. Health information videos are not only viewed by patients in formal educational sessions, but are increasingly being viewed on websites such as YouTube. Whilst there is a lot of anecdotal and sometimes misleading information on YouTube, videos from government organisations and professional associations contain trustworthy and high-quality information and could enable YouTube to become a powerful information dissemination platform for patients and carers. This systematic review will examine the efficacy of video education to improve treatment or illness-related knowledge in patients with various long-term conditions, in comparison to other modalities of education. Methods: Only studies which match the following criteria will be included: participants will have a long-term physical health condition, video education will aim to improve treatment or illness related knowledge and will be tested in isolation, and the study must be a randomised controlled trial. Knowledge will be the primary outcome measure, with modality preference, anxiety, and behaviour change as secondary measures. The searches have been conducted in the following databases: OVID Medline, OVID PsycInfo, OVID Embase, CENTRAL and ProQuest, and hand searching for relevant published and unpublished studies has also been carried out. Screening and data extraction will be conducted independently by 2 researchers. Included studies will be assessed for their risk of bias in accordance with Cochrane guidelines, and heterogeneity will also be assessed before deciding whether a meta-analysis is appropriate or not. Results and Conclusions: Appropriate synthesis of the studies in relation to each outcome measure will be reported, along with the conclusions and implications.

Keywords: long-term condition, patient education, systematic review, video

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Authors: D. P. Gangwar

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Identification of human through facial images has got great importance in forensic science. The video recordings, CCTV footage, passports, driver licenses and other related documents are invariably sent to the laboratory for comparison of the questioned photographs as well as video recordings with suspected photographs/recordings to prove the identity of a person. More than 300 questioned and 300 control photographs received in actual crime cases, received from various investigation agencies, have been compared by me so far using various familiar analysis and comparison techniques such as Holistic comparison, Morphological analysis, Photo-anthropometry and superimposition. On the basis of findings obtained during the examination huge photo exhibits, a realistic and comprehensive technique has been proposed which could be very useful for forensic.

Keywords: CCTV Images, facial features, photo-anthropometry, superimposition

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Authors: Zohre Shahhosseini, Mehdi Pourasghar, AliReza Khalilian, Fariba Salehi

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Objective: The prevalence of anxiety during pregnancy, particularly in developing countries, and its adverse effects on mother and baby, can make pregnancy unpleasant for pregnant women. The effect of anxiety during pregnancy on birth outcomes and children can be a justification for screening of anxious pregnant women in periodic pregnancy care and helping them. In this study, researchers have investigated effects and comparison of group counseling (Cognitive therapy) and interactive lectures on anxiety during pregnancy of primiparas. Methods: The population studied in this semi-experimental trail was nulliparous pregnant women with backgrounds in health care centers in Sari city .They were studied during a period of 3 months from early March to end May 2016. Sample size in this study was 91 patients, who were randomly assigned to three groups: group counseling, interactive lecture, and control group. Demographic questionnaire and Speilberger State –Trait Anxiety Inventory (SPAI) was completed for all three groups after obtaining letter of consent and completing the initial checklist. Then interventions included 4 sessions for group counseling and 4 sessions for interactive lecture which were implemented in two sessions a week. 4 weeks after interventions, Speilberger State – Trait Anxiety Inventory (SPAI), completed by both group counseling and interactive lectures groups again. In control group, the second questionnaire was also completed 4 weeks after completing the initial questionnaire. Data analysis was performed using spss software version 18. At first, the Kalmogorov-Smiranov test was carried out and then chi square tests, Independent t-test, paired t-test, ANOVA test, and Dunnett's post hoc test were applied. Results: Findings show that group counseling and interactive lecture with reducing state and trait anxiety in significant level of P=0/000 contribute to reduction of anxiety in nulliparous pregnant mothers. However, in this study, group counseling was more effective than an interactive lecture in reducing participants' anxiety, but this difference was not significant (P≥0/05). Conclusions: According to the results of this study, it is suggested that by screening of psychological - mental problems of pregnant women in periodic care during pregnancy be considered by revised prenatal care plans and creation of counseling and training units at health centers. Besides owing to the fact that both interactive lecture and group counseling method were effective in reducing anxiety, these methods should be used proportionate to situations and facilities.

Keywords: anxiety, group counseling, cognitive therapy, interactive lecture, nulliparous

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Authors: Keyi Wang

Abstract:

Similar to the touchscreen, hand gesture based human-computer interaction (HCI) is a technology that could allow people to perform a variety of tasks faster and more conveniently. This paper proposes a training method of an image-based hand gesture image and video clip recognition system using a CNN (Convolutional Neural Network) with a dataset. A dataset containing 6 hand gesture images is used to train a 2D CNN model. ~98% accuracy is achieved. Furthermore, a 3D CNN model is trained on a dataset containing 4 hand gesture video clips resulting in ~83% accuracy. It is demonstrated that a Cozmo robot loaded with pre-trained models is able to recognize static and dynamic hand gestures.

Keywords: deep learning, hand gesture recognition, computer vision, image processing

Procedia PDF Downloads 109

Authors: Cristina Hotoleanu

Abstract:

Introduction: The recent Covid-19 pandemic accelerated the development of e-health, including telemedicine, smartphone applications, and medical wearable devices. Providing remote teleconsultations supposes challenges which may require further face-to-face medical interactions. The aim of this study was to assess the correlation between the types of teleconsultations and the need of onsite medical services (investigations and medical visits) for the diagnosis and treatment. Methods: a retrospective study including all the teleconsultations using the platform offered by a telehealth provider in Romania (Telios Care SA) between May 1, 2021- April 30, 2022, was performed. Binary data were analysed using the chi-square test with a significance level of p < 0.05. Results: out of 7163 consultations, 3961 were phone calls, 1981 were online messages, and 1221 were video calls. Onsite medical services were indicated in 3327 (46.44%) cases; the onsite investigations or the onsite visits were recommended for 2908 patients as follows: 2326 in case of phone calls, 582 in case of online messages, none in case of video calls. Both onsite investigations and visits were indicated for 419 patients. The need for onsite additional medical services was significantly higher in the case of phone calls than in the other 2 types of teleconsultations (Chi square= 1207.06, p= 0.00001). The indication for onsite services was done mainly after teleconsultations covering medical specialties (87.34%), significantly higher than the other specialties (Chi square=914.59, p=0.00001). Teleconsultations in surgical specialties and other fields (pharmacy, dentistry, psychology, wellbeing- nutrition, fitness) resulted in 12.13%, respective less than 1%, indication for onsite investigations or visits, explained by using of video calls in most of the cases. Conclusion: a further onsite medical service was necessary in less than a half of the teleconsultations. This indication was done mainly after phone calls and teleconsultations in medical specialties. Video calls were used mostly in psychology, nutrition, and fitness teleconsultations and did not require a further onsite medical service. Other studies are necessary to assess better the types of teleconsultations and the specialties bringing the biggest benefit for the patients.

Keywords: onsite medical services, phone calls, teleconsultations, telemedicine

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Authors: Shu-Chen Wu

Abstract:

This paper will present a study by the author which investigates Chinese teachers’ perspectives on learning at play and their teaching activities in the designed play activities. It asks the question of how Chinese teachers understand learning at play and how they design play activities in the classroom. Six kindergarten teachers in Hong Kong were invited to select and record exemplary play episodes which contain the largest amount of learning elements in their own classrooms. Applying video-stimulated interview, eight teachers in two focus groups were interviewed to elicit their perspectives on designing play activity and their teaching activities. The findings reveal that Chinese teachers have a very structured representation of learning at play, and the phenomenon of uniformity of teachers’ act was found. The contributions of which are important and useful for professional practices and curricular policies.

Keywords: learning at play, teacher involvement, video-stimulated interview, uniformity

Procedia PDF Downloads 109

Authors: Matthew Buns

Abstract:

Training specificity is imperative for successful performance of the elite athlete. Virtual reality (VR) has been successfully applied to a broad range of training domains. However, to date there is little research investigating the use of VR for sport training. The purpose of this study was to address the question of whether virtual reality (VR) training can improve real world hockey shooting performance. Twenty four volunteers were recruited and randomly selected to complete the virtual training intervention or enter a control group with no training. Four primary types of data were collected: 1) participant’s experience with video games and hockey, 2) participant’s motivation toward video game use, 3) participants technical performance on real-world hockey, and 4) participant’s technical performance in virtual hockey. One-way multivariate analysis of variance (ANOVA) indicated that that the intervention group demonstrated significantly more real-world hockey accuracy [F(1,24) =15.43, p <.01, E.S. = 0.56] while shooting on goal than their control group counterparts [intervention M accuracy = 54.17%, SD=12.38, control M accuracy = 46.76%, SD=13.45]. One-way multivariate analysis of variance (MANOVA) repeated measures indicated significantly higher outcome scores on real-world accuracy (35.42% versus 54.17%; ES = 1.52) and velocity (51.10 mph versus 65.50 mph; ES=0.86) of hockey shooting on goal. This research supports the idea that virtual training is an effective tool for increasing real-world hockey skill.

Keywords: virtual training, hockey skills, video game, esports

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Authors: Martha Serrano-Arias, Martha Frías-Armenta

Abstract:

Significant results have been found both supporting universality of emotion recognition and cultural background influence. Thus, the aim of this research was to test a Mexican version of the MTSI in different cultures to find differences in their performance. The MTSI-Mx assesses through a scenario approach were subjects must evaluate real persons. Two target persons were used for the construction, a man (FS) and a woman (AD). The items were grouped in four variables: Picture, Video, and FS and AD scenarios. The test was applied to 201 students from Mexico and Germany. T-test for picture and FS scenario show no significance. Video and AD had a significance at the 5% level. Results show slight differences between cultures, although a more comprehensive research is needed to conclude which culture can perform better in this kind of assessments.

Keywords: emotion recognition, MTSI, social intelligence, transcultural study

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Authors: Ahmed Al Khamisi

Abstract:

The Disaster Preparedness Standard (DPS) is one of the elements that is evaluated by the Accreditation Canada International (ACI). ACI emphasizes to train and educate all staff, including service providers and senior leaders, on emergency and disaster preparedness upon the orientation and annually thereafter. Lack of awareness and deficit of knowledge among the healthcare providers about DPS have been noticed in a tertiary hospital where ACI standards were implemented. Therefore, this paper aims to introduce a video-based e-learning (VB-EL) module that explains the hospital’s disaster plan in a simple language which will be easily accessible to all healthcare providers through the hospital’s website. The healthcare disaster preparedness coordinator in the targeted hospital will be responsible to ensure that VB-EL is ready by 25 April 2019. This module will be developed based on the Kirkpatrick evaluation method. In fact, VB-EL combines different data forms such as images, motion, sounds, text in a complementary fashion which will suit diverse learning styles and individual learning pace of healthcare providers. Moreover, the module can be adjusted easily than other tools to control the information that healthcare providers receive. It will enable healthcare providers to stop, rewind, fast-forward, and replay content as many times as needed. Some anticipated limitations in the development of this module include challenges of preparing VB-EL content and resistance from healthcare providers.

Keywords: Accreditation Canada International, Disaster Preparedness Standard, Kirkpatrick evaluation method, video-based e-learning

Procedia PDF Downloads 124