PEMANFAATAN MEDIA AUGMENTED REALITY (AR) IPA INTEGRATIF KEARIFAN LOKAL DI SEKOLAH DASAR

PEMANFAATAN MEDIA AUGMENTED REALITY (AR) IPA INTEGRATIF KEARIFAN LOKAL DI SEKOLAH DASAR Ana Riani Universitas Negeri Jakarta Email : [email protected] Abstract: This study aims to develop learning media based on the Augmented Reality as a form of learning media that facilitates abstracs material become real, and is able to support the learning process in an effort to improve student learning understanding. The method used is research and development with the 4D (Four D) Model. This research was conducted on fifth grade students at the Aren Jaya XVIII Elementary School, Kota Bekasi, Indonesia. Data collection techniques used were tests, interviews, questionnaires, and documents. The results of this research can be concluded that learning media based on Augmented Reality in blood circulation system integrated martial art is developed effectively and can be uses to assistance as a teacher's aid in delivering learning material. Keyword : Augmented Reality media, Blood Circulation System, Martial Art Abstrak : penelitian ini bertujuan untuk mengembangkan media pembelajaran berbasis Augmented sebagai salah satu bentuk media pembelajaran yang memfasilitasi materi yang abstrak menjadi lebih nyata dan diharapkan mampu mendukung proses pembelajaran dalam upaya peningkatan hasil belajar pada siswa sekolah dasar. Metode penelitian menggunakan pendekatan research and development dengan model yang digunakan 4D (four D). Penelitian ini dilakukan pada siswa kelas V di Sekolah Dasar Negeri Aren Jaya XVIII Kota Bekasi-Indonesia. Teknik pengumpulan data yang digunakan adalah tes, wawancara, angket, dan dokumen. Hasil dalam penelitian ini dapat disimpulkan bahwa media berbasis Augmented Reality sistem peredaran darah terintegrasi Penjaskes gerak dasar pencak silat ini layak dan dapat digunakan sebagai alat bantu guru dalam menyampaikan materi pembelajaran kelas V sekolah dasar. Kata Kunci : Media Augmented Reality, Sistem peredaran darah, Pencak sila

Low-Cost Sensors and Biological Signals

Many sensors are currently available at prices lower than USD 100 and cover a wide range of biological signals: motion, muscle activity, heart rate, etc. Such low-cost sensors have metrological features allowing them to be used in everyday life and clinical applications, where gold-standard material is both too expensive and time-consuming to be used. The selected papers present current applications of low-cost sensors in domains such as physiotherapy, rehabilitation, and affective technologies. The results cover various aspects of low-cost sensor technology from hardware design to software optimization

A Person-Centric Design Framework for At-Home Motor Learning in Serious Games

abstract: In motor learning, real-time multi-modal feedback is a critical element in guided training. Serious games have been introduced as a platform for at-home motor training due to their highly interactive and multi-modal nature. This dissertation explores the design of a multimodal environment for at-home training in which an autonomous system observes and guides the user in the place of a live trainer, providing real-time assessment, feedback and difficulty adaptation as the subject masters a motor skill. After an in-depth review of the latest solutions in this field, this dissertation proposes a person-centric approach to the design of this environment, in contrast to the standard techniques implemented in related work, to address many of the limitations of these approaches. The unique advantages and restrictions of this approach are presented in the form of a case study in which a system entitled the "Autonomous Training Assistant" consisting of both hardware and software for guided at-home motor learning is designed and adapted for a specific individual and trainer. In this work, the design of an autonomous motor learning environment is approached from three areas: motor assessment, multimodal feedback, and serious game design. For motor assessment, a 3-dimensional assessment framework is proposed which comprises of 2 spatial (posture, progression) and 1 temporal (pacing) domains of real-time motor assessment. For multimodal feedback, a rod-shaped device called the "Intelligent Stick" is combined with an audio-visual interface to provide feedback to the subject in three domains (audio, visual, haptic). Feedback domains are mapped to modalities and feedback is provided whenever the user's performance deviates from the ideal performance level by an adaptive threshold. Approaches for multi-modal integration and feedback fading are discussed. Finally, a novel approach for stealth adaptation in serious game design is presented. This approach allows serious games to incorporate motor tasks in a more natural way, facilitating self-assessment by the subject. An evaluation of three different stealth adaptation approaches are presented and evaluated using the flow-state ratio metric. The dissertation concludes with directions for future work in the integration of stealth adaptation techniques across the field of exergames.Dissertation/ThesisDoctoral Dissertation Computer Science 201

L’évaluation archivistique du patrimoine culturel immatériel au regard des technologies numériques

Travail de recherche réalisé à l’hiver 2017 dans le cadre du cours SC6112 Évaluation des archives sous la direction d'Yvon LemayCe travail de recherche propose une réflexion préliminaire sur les techniques de préservation, et, par extension, sur l’évaluation archivistique du patrimoine culturel immatériel, appelé quelques fois « patrimoine vivant », et ce au regard des technologies numériques. À partir d’une brève revue de la littérature sur le sujet, la recherche tente d'amorcer cette réflexion en partant du point de vue qu’il est tout à fait possible de procéder à une évaluation archivistique du patrimoine culturel immatériel, au même titre qu’on le ferait pour n’importe quel autre type d’archives, dans la mesure où celui-ci doit d’abord être consigné sur un support physique facilitant sa conservation. La réflexion s'est construite à partir de l’analyse d’un exemple bien précis, celui du projet Hong Kong Martial Arts Living Archives. Ce projet fait usage de la technologie « capteur de mouvements 3D » (3D motion capture) pour documenter l’enseignement des arts martiaux traditionnels chinois dans un but de préservation de ces traditions de combat. En outre, les conclusions font valoir que les technologies numériques ne permettent peut-être pas de tout préserver du patrimoine vivant, à commencer par les rapports humains qui sont au cœur de la transmission d’une tradition

Videos in Context for Telecommunication and Spatial Browsing

The research presented in this thesis explores the use of videos embedded in panoramic imagery to transmit spatial and temporal information describing remote environments and their dynamics. Virtual environments (VEs) through which users can explore remote locations are rapidly emerging as a popular medium of presence and remote collaboration. However, capturing visual representation of locations to be used in VEs is usually a tedious process that requires either manual modelling of environments or the employment of specific hardware. Capturing environment dynamics is not straightforward either, and it is usually performed through specific tracking hardware. Similarly, browsing large unstructured video-collections with available tools is difficult, as the abundance of spatial and temporal information makes them hard to comprehend. At the same time, on a spectrum between 3D VEs and 2D images, panoramas lie in between, as they offer the same 2D images accessibility while preserving 3D virtual environments surrounding representation. For this reason, panoramas are an attractive basis for videoconferencing and browsing tools as they can relate several videos temporally and spatially. This research explores methods to acquire, fuse, render and stream data coming from heterogeneous cameras, with the help of panoramic imagery. Three distinct but interrelated questions are addressed. First, the thesis considers how spatially localised video can be used to increase the spatial information transmitted during video mediated communication, and if this improves quality of communication. Second, the research asks whether videos in panoramic context can be used to convey spatial and temporal information of a remote place and the dynamics within, and if this improves users' performance in tasks that require spatio-temporal thinking. Finally, the thesis considers whether there is an impact of display type on reasoning about events within videos in panoramic context. These research questions were investigated over three experiments, covering scenarios common to computer-supported cooperative work and video browsing. To support the investigation, two distinct video+context systems were developed. The first telecommunication experiment compared our videos in context interface with fully-panoramic video and conventional webcam video conferencing in an object placement scenario. The second experiment investigated the impact of videos in panoramic context on quality of spatio-temporal thinking during localization tasks. To support the experiment, a novel interface to video-collection in panoramic context was developed and compared with common video-browsing tools. The final experimental study investigated the impact of display type on reasoning about events. The study explored three adaptations of our video-collection interface to three display types. The overall conclusion is that videos in panoramic context offer a valid solution to spatio-temporal exploration of remote locations. Our approach presents a richer visual representation in terms of space and time than standard tools, showing that providing panoramic contexts to video collections makes spatio-temporal tasks easier. To this end, videos in context are suitable alternative to more difficult, and often expensive solutions. These findings are beneficial to many applications, including teleconferencing, virtual tourism and remote assistance

Proceedings of the 9th international conference on disability, virtual reality and associated technologies (ICDVRAT 2012)

The proceedings of the conferenc

The Multimodal Tutor: Adaptive Feedback from Multimodal Experiences

This doctoral thesis describes the journey of ideation, prototyping and empirical testing of the Multimodal Tutor, a system designed for providing digital feedback that supports psychomotor skills acquisition using learning and multimodal data capturing. The feedback is given in real-time with machine-driven assessment of the learner's task execution. The predictions are tailored by supervised machine learning models trained with human annotated samples. The main contributions of this thesis are: a literature survey on multimodal data for learning, a conceptual model (the Multimodal Learning Analytics Model), a technological framework (the Multimodal Pipeline), a data annotation tool (the Visual Inspection Tool) and a case study in Cardiopulmonary Resuscitation training (CPR Tutor). The CPR Tutor generates real-time, adaptive feedback using kinematic and myographic data and neural networks

A data fusion-based hybrid sensory system for older people’s daily activity recognition.

Population aged 60 and over is growing faster. Ageing-caused changes, such as physical or cognitive decline, could affect people’s quality of life, resulting in injuries, mental health or the lack of physical activity. Sensor-based human activity recognition (HAR) has become one of the most promising assistive technologies for older people’s daily life. Literature in HAR suggests that each sensor modality has its strengths and limitations and single sensor modalities may not cope with complex situations in practice. This research aims to design and implement a hybrid sensory HAR system to provide more comprehensive, practical and accurate surveillance for older people to assist them living independently. This reseach: 1) designs and develops a hybrid HAR system which provides a spatio- temporal surveillance system for older people by combining the wrist-worn sensors and the room-mounted ambient sensors (passive infrared); the wearable data are used to recognize the defined specific daily activities, and the ambient information is used to infer the occupant’s room-level daily routine; 2): proposes a unique and effective data fusion method to hybridize the two-source sensory data, in which the captured room-level location information from the ambient sensors is also utilized to trigger the sub classification models pretrained by room-assigned wearable data; 3): implements augmented features which are extracted from the attitude angles of the wearable device and explores the contribution of the new features to HAR; 4:) proposes a feature selection (FS) method in the view of kernel canonical correlation analysis (KCCA) to maximize the relevance between the feature candidate and the target class labels and simultaneously minimizes the joint redundancy between the already selected features and the feature candidate, named mRMJR-KCCA; 5:) demonstrates all the proposed methods above with the ground-truth data collected from recruited participants in home settings. The proposed system has three function modes: 1) the pure wearable sensing mode (the whole classification model) which can identify all the defined specific daily activities together and function alone when the ambient sensing fails; 2) the pure ambient sensing mode which can deliver the occupant’s room-level daily routine without wearable sensing; and 3) the data fusion mode (room-based sub classification mode) which provides a more comprehensive and accurate surveillance HAR when both the wearable sensing and ambient sensing function properly. The research also applies the mutual information (MI)-based FS methods for feature selection, Support Vector Machine (SVM) and Random Forest (RF) for classification. The experimental results demonstrate that the proposed hybrid sensory system improves the recognition accuracy to 98.96% after applying data fusion using Random Forest (RF) classification and mRMJR-KCCA feature selection. Furthermore, the improved results are achieved with a much smaller number of features compared with the scenario of recognizing all the defined activities using wearable data alone. The research work conducted in the thesis is unique, which is not directly compared with others since there are few other similar existing works in terms of the proposed data fusion method and the introduced new feature set