Search results for: YouTube videos

Authors: Hyun-Koo Kim, Yong-Hun Kim, Soo-Young Suk, Ju H. Park, Ho-Youl Jung

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This paper presents an effective speed hump detection process at the day-time. we focus only on round types of speed humps in the day-time dynamic road environment. The proposed speed hump detection scheme consists mainly of two process as stereo matching and speed hump detection process. Our proposed process focuses to speed hump detection process. Speed hump detection process consist of noise reduction step, data fusion step, and speed hemp detection step. The proposed system is tested on Intel Core CPU with 2.80 GHz and 4 GB RAM tested in the urban road environments. The frame rate of test videos is 30 frames per second and the size of each frame of grabbed image sequences is 1280 pixels by 670 pixels. Using object-marked sequences acquired with an on-vehicle camera, we recorded speed humps and non-speed humps samples. Result of the tests, our proposed method can be applied in real-time systems by computation time is 13 ms. For instance; our proposed method reaches 96.1 %.

Keywords: data fusion, round types speed hump, speed hump detection, surface filter

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Authors: Lisbeth Amhag

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The aim of the study is to describe and analyze the design of mobile teaching for students collaborative learning in distance higher education with a focus on mobile technologies as online webinars (web-based seminars or conferencing) by using laptops, smart phones, or tablets. These multimedia tools can provide face-to-face interactions, recorded flipped classroom videos and parallel chat communications. The data collection consists of interviews with 22 students and observations of online face-to-face webinars, as well two surveys. Theoretically, the study joins the research tradition of Computer Supported Collaborative learning, CSCL, as well as Computer Self-Efficacy, CSE concerned with individuals’ media and information literacy. Important conclusions from the study demonstrated mobile interactions increased student centered learning. As the students were appreciating the working methods, they became more engaged and motivated. The mobile technology using among student also contributes to increased flexibility between space and place, as well as media and information literacy.

Keywords: computer self-efficacy, computer supported collaborative learning, distance and open learning, educational design and technologies, media and information literacy, mobile learning

Procedia PDF Downloads 336

Authors: Ashish Ashish

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In the last few decades, the discrete chaos of difference equations has gained a massive attention of academicians and scholars due to its tremendous applications in each and every branch of science, such as cryptography, traffic control models, secure communications, weather forecasting, and engineering. In this article, a generalized logistic discrete map is established and discrete chaos is reported through period doubling bifurcation, period three orbit and Lyapunov exponent. It is interesting to see that the generalized logistic map exhibits superior chaos due to the presence of an extra degree of freedom of an ordered parameter. The period doubling bifurcation and Lyapunov exponent are demonstrated for some particular values of parameter and the discrete chaos is determined in the sense of Devaney's definition of chaos theoretically as well as numerically. Moreover, the study discusses an extended chaos based image encryption and decryption scheme in cryptography using this novel system. Surprisingly, a larger key space for coding and more sensitive dependence on initial conditions are examined for encryption and decryption of text messages, images and videos which secure the system strongly from external cyber attacks, coding attacks, statistic attacks and differential attacks.

Keywords: chaos, period-doubling, logistic map, Lyapunov exponent, image encryption

Procedia PDF Downloads 117

Authors: Myriam Ferreira

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Websites and social networks allow museums to divulge their works by new and attractive means. Besides, these technologies provide tools to generate a new history of art’s contents and promote visits to their installations. At the same time, museums are proposing more and more activities to families, children and young people. However, these activities usually take place in the museum’s physical installations, while websites and social networks seem to be mainly targeted to adults. The problem is that being children and young people digital natives, they feel apart from museums, so they need a presence of museums in digital means to feel attracted to them. Some institutions are making efforts to fill this vacuum. In this paper, resources designed specifically for children and teenagers have been selected from websites and social networks of five Spanish Museums: Prado Museum, Thyssen Museum, Guggenheim Museum, America Museum and Cerralbo Museum. After that, we have carried out an investigation in a school with children and teenagers between 11 and 15 years old. Those young people have been asked about their valuation of those web pages and social networks, with quantitative-qualitative questions. The results show that the least rated resources were videos and social networks because they were considered ‘too serious’, while the most rated were games and augmented reality. These ratings confirm theoretical papers that affirm that the future of technologies applied to museums is edutainment and interaction.

Keywords: children, museums, social networks, teenagers, websites

Procedia PDF Downloads 124

Authors: Lavanya Srinivasan

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Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

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Authors: Seda Yavuz, Anıl Çelebi, Aysun Taşyapı Çelebi, Oğuzhan Urhan

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Nowadays, demand for using real-time video transmission capable devices is ever-increasing. So, high resolution videos have made efficient video compression techniques an essential component for capturing and transmitting video data. Motion estimation has a critical role in encoding raw video. Hence, various motion estimation methods are introduced to efficiently compress the video. Low bit‑depth representation based motion estimation methods facilitate computation of matching criteria and thus, provide small hardware footprint. In this paper, a hardware implementation of a two-bit transformation based low-complexity motion estimation method using local binary pattern approach is proposed. Image frames are represented in two-bit depth instead of full-depth by making use of the local binary pattern as a binarization approach and the binarization part of the hardware architecture is explained in detail. Experimental results demonstrate the difference between the proposed hardware architecture and the architectures of well-known low-complexity motion estimation methods in terms of important aspects such as resource utilization, energy and power consumption.

Keywords: binarization, hardware architecture, local binary pattern, motion estimation, two-bit transform

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Authors: Stefan Wagenpfeil, Felix Engel, Paul McKevitt, Matthias Hemmje

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Multimedia Indexing and Retrieval is generally designed and implemented by employing feature graphs. These graphs typically contain a significant number of nodes and edges to reflect the level of detail in feature detection. A higher level of detail increases the effectiveness of the results but also leads to more complex graph structures. However, graph-traversal-based algorithms for similarity are quite inefficient and computation intensive, especially for large data structures. To deliver fast and effective retrieval, an efficient similarity algorithm, particularly for large graphs, is mandatory. Hence, in this paper, we define a graph-projection into a 2D space (Graph Code) as well as the corresponding algorithms for indexing and retrieval. We show that calculations in this space can be performed more efficiently than graph-traversals due to a simpler processing model and a high level of parallelization. In consequence, we prove that the effectiveness of retrieval also increases substantially, as Graph Codes facilitate more levels of detail in feature fusion. Thus, Graph Codes provide a significant increase in efficiency and effectiveness (especially for Multimedia indexing and retrieval) and can be applied to images, videos, audio, and text information.

Keywords: indexing, retrieval, multimedia, graph algorithm, graph code

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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: Rylle Evan Gabriel Zamora, Micah Dennise Malia, Abygail Deniese Villabona

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The primary motivators of altruism are usually viewed as mutually exclusive. In this study, we wanted to know if the two primary motivators, reciprocity and empathy, can work together in motivating altruism. Therefore, we wanted to find out if there is a significant interaction of effects between reciprocity and empathy. To show how this may occur, we devised the combined altruism model, which is based on Batson’s empathy altruism hypothesis. A sample of 120, 6th-grade students were randomly selected and then randomly assigned to four treatment groups. A 2x2 between subjects’ design was used, which had empathy and reciprocity as independent variables, and altruism as the dependent variable. The study made use of materials that were effort based, where subjects were required to complete a task or a puzzle to help a person in a given scenario, two videos, one to prime empathy were also used. This along with Witt & Boleman’s adapted Self-Reported Altruism Scale was used to determine an individual’s altruism. It was found that both variables were significant in motivating altruism, with empathy being the greater of the two. However, there was no significant interaction of effects between the two variables. To explain why this occurred, we turned to the combined altruism model, where it was found that when empathically primed, we tend to not think of ourselves when helping others. Future studies could focus on other variables, especially age which is said to be one of the greatest factors that influenced the results of the experiment.

Keywords: reciprocity, empathy, altruism, experimental psychology, social psychology

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Authors: Noor Azwa Azreen Binti Abd. Aziz, Muhamad Zaim Bin Mohd Rozi

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Moving towards the 4th Industrial Revolution, artificial intelligence (AI) is now more popular than ever. This subject is gaining significance every day and is continually expanding, often merging with other fields. Instead of merely being passive observers, there are benefits to understanding modern technology by delving into its inner workings. However, in a world teeming with digital information, the impact of AI on the spread of disinformation has garnered significant attention. The dissemination of inaccurate or misleading information is referred to as misinformation, posing a serious threat to democratic society, public debate, and individual decision-making. This article delves deep into the connection between AI and the dissemination of false information, exploring its potential, risks, and ethical issues as AI technology advances. The rise of AI has ushered in a new era in the dissemination of misinformation as AI-driven technologies are increasingly responsible for curating, recommending, and amplifying information on online platforms. While AI holds the potential to enhance the detection and mitigation of misinformation through natural language processing and machine learning, it also raises concerns about the amplification and propagation of false information. AI-powered deepfake technology, for instance, can generate hyper-realistic videos and audio recordings, making it increasingly challenging to discern fact from fiction.

Keywords: artificial intelligence, digital information, disinformation, ethical issues, misinformation

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Authors: Kerrin Burnell

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In a world of increasingly technology-dependent students, the English language classroom should ideally keep up with developments to keep students engaged as much as possible. Unfortunately, as is the case in Oman, funding is not always adequate to ensure students have the most up to date technology, and most institutions are still reliant on paper-based textbooks. In order to try and bridge the gap between the technology available (smartphones) and textbooks, augmented reality (AR) technology can be utilized to enhance classroom, homework, and extracurricular activities. AR involves overlaying media (videos, images etc) over the top of physical objects (posters, book pages etc) and then sharing the media. This case study involved introducing students to a freely available entry level AR app called Aurasma. Students were asked to augment their English textbooks, word walls, research project posters, and extracurricular posters. Through surveys, interviews and an analysis of time spent accessing the different media, a determination of the appropriateness of the technology for the classroom was determined. Results indicate that the use of AR has positive effects on many aspects of the English classroom. Increased student engagement, total time spent on task, interaction, and motivation were evident, along with a decrease in technology-related anxiety. As it is proving very difficult to get tablets or even laptops in classrooms in Oman, these preliminary results indicate that many positive outcomes will come from introducing students to this innovative technology.

Keywords: augmented reality, classroom technology, classroom innovation, engagement

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Authors: Fredrick Olatunji Ajegbomogun, Bello Modinat Morenikeji, Okorie Nancy Chituru

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Electronic information resources are highly relevant to students' academic and research needs but are grossly underutilized, despite the institutional commitment to making them available. The under-utilisation of these resources could be attributed to a low level of study behaviour coupled with a low level of computer self-efficacy. This study assessed computer self-efficacy, study behaviour, and the use of electronic information resources by students in selected polytechnics in Ogun State. A simple random sampling technique using Krejcie and Morgan's (1970) Table was used to select 370 respondents for the study. A structured questionnaire was used to collect data on respondents. Data were analysed using frequency counts, percentages, mean, standard deviation, Pearson Product Moment Correlation (PPMC) and multiple regression analysis. Results reveal that the internet (= 1.94), YouTube (= 1.74), and search engines (= 1.72) were the common information resources available to the students, while the Internet (= 4.22) is the most utilized resource. Major reasons for using electronic information resources were to source materials and information (= 3.30), for research (= 3.25), and to augment class notes (= 2.90). The majority (91.0%) of the respondents have a high level of computer self-efficacy in the use of electronic information resources through selecting from screen menus (= 3.12), using data files ( = 3.10), and efficient use of computers (= 3.06). Good preparation for tests (= 3.27), examinations (= 3.26), and organization of tutorials (= 3.11) are the common study behaviours of the respondents. Overall, 93.8% have good study behaviour. Inadequate computer facilities to access information (= 3.23), and poor internet access (= 2.87) were the major challenges confronting students’ use of electronic information resources. According to the PPMC results, study behavior (r = 0.280) and computer self-efficacy (r = 0.304) have significant (p 0.05) relationships with the use of electronic information resources. Regression results reveal that self-efficacy (=0.214) and study behavior (=0.122) positively (p 0.05) influenced students' use of electronic information resources. The study concluded that students' use of electronic information resources depends on the purpose, their computer self-efficacy, and their study behaviour. Therefore, the study recommended that the management should encourage the students to improve their study habits and computer skills, as this will enhance their continuous and more effective utilization of electronic information resources.

Keywords: computer self-efficacy, study behaviour, electronic information resources, polytechnics, Nigeria

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Authors: Soraya Tharani

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Social media has changed how public opinion is shaped by enabling more diversified and inclusive participation of audiences. New online forums provide spaces in which governments, NGOs and other organizations can create content and receive feedback. These forums are sites where debate can constitute public opinion. Studies of audience engagement can give an understanding of how different voices from the civil society participate in debates and how discussions can reinforce or bring into question established societal beliefs. The UN’s refugee agency, UNHCR, produces audio-visual stories about displaced people for global audiences on social media platforms. The availability of many views in these forums can give insight into how dialogues regarding transnational issues are formed. The public sphere, as defined by Habermas, is a discursive arena where reasoned debate can take place. Habermas’ concept is combined with theories on celebrity advocacy, and discussions about the role and effect celebrities have in raising public awareness for humanitarian issues. The personal and public lives of celebrities often create emotional engagement from their fans and other audiences. In this study, quantitative and qualitative methods have been used on YouTube comments for uncovering how emotion and reason are constituted in a global public debate on celebrity endorsed UNHCR stories of displaced people. The study shows that engagement intensity is not equally distributed between comment threads; comments presented as facts or emotional claims are often supported by recourse to intertextuality, and specific linguistic strategies are used to put forward emotional and reasoned claims regarding individual and group identities. The findings from this research aim to contribute to an understanding of audience engagement on issues of human survival and solidarity in a global social media public sphere.

Keywords: emotions, engagement, global public sphere, linguistic strategies, reason, refugees, social media, UNHCR

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Authors: Atitallah Sofien, Missaoui Nada, Ben Rabeh Rania, Yahyaoui Salem, Mazigh Sonia, Bouyahia Olfa, Boukthir Samir

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Introduction: Acute bronchiolitis (AB) is a real public health problem on a global and national scale. Its treatment is most often outpatient. The use of audio-visual supports, such as educational videos, is an innovation in therapeutic education in outpatient treatment. The aim of our study was to evaluate the impact of an educational video on the knowledge, attitudes, and practices of mothers of infants with AB. Methodology: This was a descriptive, analytical, and cross-sectional study with prospective data collection, including mothers of infants with AB. We assessed mothers' knowledge, attitudes, and practices regarding AB, and we created an educational video. We used a questionnaire written in Tunisian Arabic concerning sociodemographic data, mothers' knowledge and attitudes regarding AB, and their opinions on the video, as well as an observation grid to evaluate their practices on the nasopharyngeal unblocking technique. We compared the different parameters before and after watching the video. Results: We noted a statistically significant improvement in mothers' knowledge scores on AB (7.46 in the pre-test versus 14.08 in the post-test; p≤0.05), practices (12.42 in the pre-test versus 18 in the post-test; p≤0.05) and attitudes (5.86 in pre-test versus 9.02 in post-test; p≤0.05). Conclusion: The use of an educational video has a positive impact on the knowledge, practices, and attitudes of mothers towards AB.

Keywords: acute bronchiolitis, therapeutic education, mothers, educational video

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Authors: Paulomi (Polly) Burey, Zoe Lynch

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In STEM education, students often have difficulty linking static images and words from textbooks or online resources, to the underlying mechanisms of the topic of study. This can often dissuade some students from pursuing study in the physical and chemical sciences. A growing movement in current day students demonstrates that the YouTube generation feel they learn best from video or dynamic, interactive learning tools, and will seek these out as alternatives to their textbooks and the classroom learning environment. Chemistry, and in particular visualization of molecular structures in everyday materials, can prove difficult to comprehend without significant interaction with the teacher of the content and concepts, beyond the timeframe of a typical class. This can cause a learning hurdle for distance education students, and so it is necessary to provide strong electronic tools and resources to aid their learning. As one of the electronic resources, an animation design approach to link everyday materials to their underlying chemistry would be beneficial for student learning, with the focus here being on food. These animations were designed and storyboarded with a scaling approach and commence with a focus on the food material itself and its component parts. This is followed by animated transitions to its underlying microstructure and identifying features, and finally showing the molecules responsible for these microstructural features. The animation ends with a reverse transition back through the molecular structure, microstructure, all the way back to the original food material, and also animates some reactions that may occur during food processing to demonstrate the purpose of the underlying chemistry and how it affects the food we eat. Using this cyclical approach of linking students’ existing knowledge of food to help guide them to understanding more complex knowledge, and then reinforcing their learning by linking back to their prior knowledge again, enhances student understanding. Food is also an ideal material system for students to interact with, in a hands-on manner to further reinforce their learning. These animations were launched this year in a 2nd year University Food Chemistry course with improved learning outcomes for the cohort.

Keywords: chemistry, food science, future pedagogy, STEM Education

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Authors: Galit Truman Zinman

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The 'Islamic State' (IS) is one of the most successful jihadist groups in the modern history. The 'Islamic State' strives to realize the idea of erasing the borders between Muslim countries and establishing a wide Islamic caliphate. The 'Islamic State' is based on religious unity and opposition to existing political order. In this paper, the main argument is that the 'Islamic State' is characterized by two significant tendencies of state-building: preservation and change. The methodology of this study is based on the process tracing method and the analysis of primary sources: decisions, announcements and speeches of religious leaders of the Islamic State, slogans, rituals and symbols, audio and video clips produced by the Al-Hayat Media Center, films distributed on YouTube, as well as the content analysis of Dabiq`s articles (IS official Journal) and nasheeds (jihadi songs). The major findings of this study indicate that in practice the 'Islamic State' uses the same socio-political functions typical to the modern state (preservation), but introduces a different religious-ideological content (change). On the one hand, there is a preservation of the principles of existing modern state. Even with the rejection of secularization, globalization, and nationalism, there is an establishment of typical modern nation-state patterns. It is still a state entity, which has an ideological infrastructure, territory, population, governance and a monopoly on the use of violence, security services, justice system, tax collection, etc. All these functions characterize the modern state, and despite the desire of the 'Islamic State' to create a new kind of state, it reminds patterns of the typical modern nation-state. As for the religious-ideological content of the new state, here we can see a tendency of great change. The 'Islamic State' aims to create an Islamic caliphate which would allow the establishment of religious law and order, under a big commitment to return civilization to a seventh-century environment. The 'Islamic State' favors the fight against Western culture and its liberal ideology. It supports the struggle for global jihad against the unbelievers. Today, despite the territorial 'contraction' and the undermining of the organization's governance in Iraq and Syria, the 'Islamic State' continues to maintain its brand among jihadist activists around the world.

Keywords: Islamic State, Islamic caliphate, modern nation-state, religious law and order

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Authors: Darsh N. Patel, Eric Olson

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Fractals can be found everywhere, whether it be the shape of a leaf or a system of blood vessels. Fractals are used to help study and understand different physical and mathematical processes; however, their artistic nature is also beautiful to simply explore. This project explores fractals generated by a cubically convergent extension to Newton's method. With this iteration as a starting point, a complex plane spanning from -2 to 2 is created with a color wheel mapped onto it. Next, the polynomial whose roots the fractal will generate from is established. From the Fundamental Theorem of Algebra, it is known that any polynomial has as many roots (counted by multiplicity) as its degree. When generating the fractals, each root will receive its own color. The complex plane can then be colored to indicate the basins of attraction that converge to each root. From a computational point of view, this project’s code identifies which points converge to which roots and then obtains fractal images. A zoom path into the fractal was implemented to easily visualize the self-similar structure. This path was obtained by selecting keyframes at different magnifications through which a path is then interpolated. Using parallel processing, many images were generated and condensed into a video. This project illustrates how practical techniques used for scientific visualization can also have an artistic side.

Keywords: fractals, cubic method, Julia programming language, basin of attraction

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Authors: Saeko Takahashi, Kazuo Hiraki

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Is it more fun to watch videos together than watching alone? Previous studies showed that synchronizing with others enhances subsequent prosocial behavior and affiliation, and conversely, prosocial individuals tend to coordinate with a partner to a greater extent. However, compared to adults, less is known about interpersonal coordination of young children in real-life situations because most studies have focused on children’s particular movement using specific tools or tasks in a laboratory setting. It has also been unclear if prosociality of young children affect the extent of interpersonal coordination within dyads. The present study examined data from motion capture of five body parts of 4-year-old dyads watching the same stimuli together or alone. A questionnaire survey including participants’ prosocial trait was also conducted. The wavelet coherence of each body parts within dyads was calculated as a measure of the extent of interpersonal coordination. Results showed that the dyads became significantly more coordinated in a social situation compared to a non-social situation. Moreover, dyads with averagely higher prosociality were more coordinated. These results shed some light on the development of interpersonal coordination in terms of social ability in young children. This study also offers a useful method for a study of spontaneous coordination in young children and infants without instructions or verbal responses.

Keywords: child development, interpersonal coordination, prosociality, synchrony, wavelet transform

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Authors: Hafiz Muhammad Fazalehaq

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This paper documents the results of a longitudinal study done on two bilingual children who speak English and Punjabi simultaneously. Their father is a native English speaker whereas their mother speaks Punjabi. Their mother can speak both the languages (English and Punjabi) whereas their father only speaks English. At the age of six, these children have difficulty in creative thinking and of course creative writing. So, the first task for the researcher is to impress and entice the children to think creatively. Various and different methodologies and techniques were used to entice them to start thinking creatively. Creative thinking leads to creative writing. These children were exposed to numerous sources including videos, photographs, texts and audios at first place in order to have a taste of creative genres (stories in this case). The children were encouraged to create their own stories sometimes with photographs and sometimes by using their favorite toys. At a second stage, they were asked to write about an event or incident. After that, they were motivated to create new stories and write them. Length of their creative writing varies from a few sentences to a two standard page. After this six months’ study, the researcher was able to develop a ten steps methodology for creating and improving/enhancing creative thinking and creative writing skills of the subjects understudy. This ten-step methodology entices and motivates the learner to think creatively for producing a creative piece.

Keywords: bilinguals, creative thinking, creative writing, simultaneous bilingual

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Authors: Aragorn Joaquin Pineda Dela Cruz

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

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

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Isiya Shinkafi Salihu

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Open education resources (OER) are open learning materials in different formats, course content and context to support learning globally. This study investigated the level of awareness of Hospitality and Tourism OER among students in the Department of Tourism and Hotel Management in a University. Specifically, it investigated students’ awareness, use and accessibility of OER in learning. The research design method used was the quantitative approach, using an online questionnaire. The thesis research shows that respondents frequently use OER but with little knowledge of the content and context of the material. Most of the respondents’ have little knowledge about the concept even though they use it. Information and communication technologies are tools for information gathering, social networking and knowledge sharing and transfer. OER are open education materials accessible online such as curriculum, maps, course materials, and videos that users create, adapt, reuse for learning and research. Few of the respondents that used OER in learning faced some challenges such as high cost of data, poor connectivity and lack of proper guidance. The results suggest a lack of awareness of OER among students in the faculty of tourism and the need for support from the teachers in the utilization of OER. The thesis also reveals that some of the international students are accessing the internet as beginners in their studies which require guidance. The research, however, recommends that further studies should be conducted to other faculties.

Keywords: creative commons, open education resources, open licenses, information and communication technology

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Authors: Rabia Aslam

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Overwhelming evidence from all around the world suggests that high-quality teacher professional development facilitates the improvement of teaching practices which in turn could improve student learning outcomes. The new Continuous Professional Development (CPD) model for primary school teachers in Punjab uses a blended approach in which pedagogical content knowledge is delivered through technology (high-quality instructional videos and lesson plans delivered to school tablets or mobile phones) with face-to-face support by Assistant Education Officers (AEOs). The model also develops Communities of Practice operationalized through formal meetings led by the AEOs and informal interactions through social media groups to provide opportunities for teachers to engage with each other and share their ideas, reflect on learning, and come up with solutions to issues they experience. Using Kirkpatrick’s 4 levels of the learning evaluation model, this paper investigates how school tablets and teacher mobile phones may act as transformational cultural tools to potentially expand perceptions and access to teaching and learning resources and explore some of the affordances of social media (Facebook, WhatsApp groups) in learning in an informal context. The results will be used to inform policy-level decisions on what shape could CPD of all teachers take in the context of a developing country like Pakistan.

Keywords: CPD, teaching & learning, blended learning, learning technologies

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Authors: Payel Saha

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Social media is playing an important role for dissemination of information in society. In 21st century most people have a smart phone and used different social media tools like Facebook, Twitter, Instagram, WhatsApp, Skype etc. in day to day life. It is rapidly growing web-based tool for everyone to share thoughts, ideas and knowledge globally using internet. The study highlights the current use of social media tools for promoting library and information services of Library and Information Professionals of India, which are working in Library. The study was conducted during November, 2017. A structured questionnaire was prepared using google docs and shared using different mailing list, sent to individual email IDs and sharing with other social media tools. Only 90 responses received from the different states of India and analyzed via MS-Excel. The data receive from 17 states and 3 union territories of India; however most of the respondents has come from the states Odisha 23, Himachal Pradesh 14 and Assam 10. The results revealed that out 90 respondents 37 Female and 53 male categories and also majority of respondents 71 have come from academic library followed by special library 15, Public library 3 and corporate library 1 respondent. The study indicates that, out of 90 respondent’s majority of 53 of respondents said that their Library have a social media account while 39 of respondents have not their Library social media account. The study also inform that Facebook, YouTube, Google+, LinkedIn, Twitter and Instagram are using by the LIS professional of India and Facebook 86 was popular social media tool among the other social media tools. Furthermore, respondent reported that they are using social media tools for sharing photos of events and programs of library 72, followed by tips for using different services 64, posting of new arrivals 56, tutorials of database 35 and send brief updates to patrons 32, announcement of library holidays 22. It was also reported by respondents that they are sharing information about scholarships training programs and marketing of library events etc. The study furthermore identify that lack of time is the major problem while using social media with 53 of respondents followed by low speed of internet 35, too many social media tools to learn 17 and some 3 respondents reported that there is no problem while using social media tools. The results also revealed that, majority of the respondents reported that they are using social media tools in daily basis 71 followed by weekly basis 16. It was followed by monthly 1 respondent and other 2 of the respondents. In summary, this study is expected to be useful in further promoting the social media for dissemination of library and information services to the general public.

Keywords: application of social media, India, promoting library services, library professionals

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Authors: Xiang Wang, Yan Pang, Zhaomiao Liu

Abstract:

Droplet-based microfluidics have been studied extensively with the development of the Micro-Electro-Mechanical System (MEMS) which bears the advantages of high throughput, high efficiency, low cost and low polydispersity. Droplets, worked as versatile carriers, could provide isolated chambers as the internal dispersed phase is protected from the outside continuous phase. Droplets are used to add reagents to start or end bio-chemical reactions, to generate concentration gradients, to realize hydrate crystallization or protein analyses, while droplets coalescence acts as an important control technology. In this paper, deionized water is used as the dispersed phase, and several kinds of oil are used as the continuous phase to investigate the influence of the viscosity ratio of the two phases on the coalescence process. The microchannels are fabricated by coating a polydimethylsiloxane (PDMS) layer onto another PDMS flat plate after corona treatment. All newly made microchannels are rinsed with the continuous oil phase for hours before experiments to ensure the swelling fully developed. High-speed microscope system is used to document the serial videos with a maximum speed of 2000 frames per second. The critical capillary numbers (Ca*) of droplet pairs in various junctions are studied and compared. Ca* varies with different junctions or different liquids within the range of 0.002 to 0.01. However, droplets without extra control would have the problem of synchronism which reduces the coalescence efficiency.

Keywords: coalescence, concentration, critical capillary number, droplet pair, split

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Authors: Arth Bohra, Marwa Mahmoud

Abstract:

In this paper, we utilize computer vision to develop a tool for youth coaches to formulate set-piece tactics for their players. We used the Soccernet database to extract the ResNet features and camera calibration data for over 3000 corner kick across 500 professional matches in the top 6 European leagues (English Premier League, UEFA Champions League, Ligue 1, La Liga, Serie A, Bundesliga). Leveraging the provided homography matrix, we construct a feature vector representing the formation of players on these corner kicks. Additionally, labeling the videos manually, we obtained the pass-trajectory of each of the 3000+ corner kicks by segmenting the field into four zones. Next, after determining the localization of the players and ball, we used event data to give the corner kicks a rating on a 1-4 scale. By employing a Convolutional Neural Network, our model managed to predict the success of a corner kick given the formations of players. This suggests that with the right formations, teams can optimize the way they approach corner kicks. By understanding this, we can help coaches formulate set-piece tactics for their own teams in order to maximize the success of their play. The proposed model can be easily extended; our method could be applied to even more game situations, from free kicks to counterattacks. This research project also gives insight into the myriad of possibilities that artificial intelligence possesses in transforming the domain of sports.

Keywords: soccer, corner kicks, AI, computer vision

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Authors: Yu Sin Syu

Abstract:

Objective: The study aimed to improve the patient guidance satisfaction of patients hospitalized in iodine-131 isolation rooms, as well as the patient guidance completion rate for such patients. Method: A patient care guidance checklist and patient care guidance satisfaction questionnaire were administered to 29 patients who had previously been hospitalized in iodine-131 isolation rooms. The evaluation was conducted on a one-on-one basis, and its results showed that the patients’ satisfaction with patient guidance was only 3.7 points and that the completion rate for the patient guidance performed by nurses was only 67%. Therefore, various solutions were implemented to create a more complete patient guidance framework for nurses, including the incorporation of regular care-related training in in-service education courses; the establishment of patient care guidance standards for patients in iodine-131 isolation rooms; the establishment of inpatient care standards and auditing processes for iodine-131 isolation rooms; the creation of an introductory handbook on ward environment; Invite other the care team the revision of iodine-131 health education brochures; the creation of visual cards and videos covering equipment operation procedures; and introduction of QR codes. Results: Following the implementation of the above measures, the overall satisfaction of patients hospitalized in iodine-131 isolation rooms increased from 3.7 points to 4.6 points, and the completion rate for patient guidance rose from 67% to 100%. Conclusion: Given the excellent results achieved in this study, it is hoped that this nursing project can serve as a benchmark for other relevant departments.

Keywords: admission care guidance, guidance satisfaction, integrity, Iodine131 isolation

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Authors: A. Degale Desta, Cheng Jian

Abstract:

Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Ons Slimene, Aroua Taamallah, Maha Khemaja

Abstract:

In recent years, human activity recognition (HAR) has been a key area of research due to its diverse applications. It has garnered increasing attention in the field of computer vision. HAR plays an important role in people’s daily lives as it has the ability to learn advanced knowledge about human activities from data. In HAR, activities are usually represented by exploiting different types of sensors, such as embedded sensors or visual sensors. However, these sensors have limitations, such as local obstacles, image-related obstacles, sensor unreliability, and consumer concerns. Recently, several deep learning-based approaches have been proposed for HAR and these approaches are classified into two categories based on the type of data used: vision-based approaches and sensor-based approaches. This research paper highlights the importance of multimodal data fusion from skeleton data obtained from videos and data generated by embedded sensors using deep neural networks for achieving HAR. We propose a deep multimodal fusion network based on a twostream architecture. These two streams use the Convolutional Neural Network combined with the Bidirectional LSTM (CNN BILSTM) to process skeleton data and data generated by embedded sensors and the fusion at the feature level is considered. The proposed model was evaluated on a public OPPORTUNITY++ dataset and produced a accuracy of 96.77%.

Keywords: human activity recognition, action recognition, sensors, vision, human-centric sensing, deep learning, context-awareness

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Authors: Madeline V. Henry

Abstract:

Sex work is a contested subject in academia. Many authors now argue that the practice should be recognized as a legitimate and rationally chosen form of labor, and that decriminalization is necessary to ensure the safety of sex workers and reduce their stigmatization. However, a prevailing argument remains that the work is inherently violent and oppressive and that all sex workers are directly or indirectly coerced into participating in the industry. This argument has been complicated by the recent proliferation of computer-mediated technologies that allow people to conduct sex work without the need to be physically co-present with customers or pimps. One example of this is the practice of ‘camming’, wherein ‘webcam models’ stream themselves stripping and/or performing autoerotic stimulation in an online chat-room for payment. In this presentation, interviews with eight ‘camgirls’ (aged 22-34) will be discussed. Their talk has been analyzed using Foucauldian discourse analysis, focusing on common discursive threads in relation to the work and their subjectivities. It was found that the participants demonstrated appreciation for the lack of physical danger they were in, but emphasized the unique and significant dangers of online-based sex work (their images and videos being recorded and shared without their consent, for example). Participants also argued that their largest concerns were based around stigma, which they claimed remained prevalent despite the decriminalized legal model in Aotearoa/New Zealand (which has been in place for over 14 years). Overall, this project seeks to challenge commonplace academic approaches to sex work, adding further research to support sex workers’ rights and highlighting new issues to consider in a digital environment.

Keywords: camming, sex work, stigma, risk

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