Trade-Off between Task Accuracy, Task Completion Time and Naturalness for Direct Object Manipulation in Virtual Reality

Virtual reality devices are used for several application domains, such as medicine, entertainment, marketing and training. A handheld controller is the common interaction method for direct object manipulation in virtual reality environments. Using hands would be a straightforward way to directly manipulate objects in the virtual environment if hand-tracking technology were reliable enough. In recent comparison studies, hand-based systems compared unfavorably against the handheld controllers in task completion times and accuracy. In our controlled study, we compare these two interaction techniques with a new hybrid interaction technique which combines the controller tracking with hand gestures for a rigid object manipulation task. The results demonstrate that the hybrid interaction technique is the most preferred because it is intuitive, easy to use, fast, reliable and it provides haptic feedback resembling the real-world object grab. This suggests that there is a trade-off between naturalness, task accuracy and task completion time when using these direct manipulation interaction techniques, and participants prefer to use interaction techniques that provide a balance between these three factors.

Pre-define Rotation Amplitudes Object Rotation in Handheld Augmented Reality

Interaction is one of the important topics to be discussed since it includes the interface where the end-user communicates with the augmented reality (AR) system. In handheld AR interface, the traditional interaction techniques are not suitable for some AR applications due to the different attributes of handheld devices that always refer to smartphones and tablets. Currently interaction techniques in handheld AR are known as touch-based technique, mid-air gesture-based technique and device-based technique that can led to a wide discussion in related research areas. However, this paper will focus to discover the device-based interaction technique because it has proven in the previous studies to be more suitable and robust in several aspects. A novel device-based 3D object rotation technique is proposed to solve the current problem in performing 3DOF rotation of 3D object. The goal is to produce a precise and faster 3D object rotation. Therefore, the determination of the rotation amplitudes per second is required before the fully implementation. This paper discusses the implementation in depth and provides a guideline for those who works in related to device-based interaction.

Interactive Design in Enhancing User Experience in Museum

A museum can be a suitable context to experiment with a new interaction technique which guiding visitors and improving their experience for a successful learning environment also to enrich user experience. Mobile technology is used to enhance user experience in a cultural environment that offers more information than physically exposed technology. Therefore, the introduction of augmented reality (AR) that allow visitor to experience interaction in a way that increased knowledge, learning and give additional information with any artefact exhibitions they interact in the museum is applied in this project. The objectives of this research are to develop an interactive design in enhancing user experience in artefact display and evaluate user experience. ADDIE Model is applied as the methodology that consists of five phases which are analysis, design, development, implementation, and evaluation. Principles of Interactive Design is utilized in designing the mobile AR application and developed using Unity, Blender and Vuforia. User Experience evaluation method is conducted where findings shows that most respondents are satisfied, and usage of mobile AR has enhanced their experience through navigation during museum visit that also give a lot of new insight on historical artefact that being displayed.

Evaluation on User Perception Effect based on Interaction Techniques in the Stereoscopic Environment

The interaction of user performance with three-dimensional (3D) objects has become an important issue in the recent development of virtual reality applications. Additionally, the basic conviction of current Virtual Reality (VR) supports the development of the viable interface between humans and machines. The research focuses on the user’s interaction technique by considering two approaches (direct and indirect interaction techniques) for the users while interacting with threedimensional objects. Numerous possible uses can benefit from virtual reality by considering a few fundamental visual and cognitive activities in the Virtual Environment (VE), such as the interpretation of space that users of clear and indirect perception are not well established. The experiment is performed in a stereoscopic environment using a reciprocal tapping task. Participants are expected to use direct pointing as well as indirect cursor techniques to select a stereoscopic spherical target. The results show that, in the sense of a direct interaction technique, user recognition of an object appears to converge in the center of a simulated area. Unfortunately, this convergence is not demonstrated in the indirect cursor situation. The pointing estimation from the users is more accurate when using the indirect interaction approach. The findings provide an understanding of the interaction characteristics done by the users in the stereoscopic environment. Importantly, developers of a virtual environment may use the result when developing effective user interface perception in specific interaction techniques.

Production of Mobile English Language Teaching Application Based on Text Interface Using Deep Learning

This paper proposes a novel text interface using deep learning in a mobile platform environment and presents the English language teaching applications created based on our interface. First, an interface for handwriting texts is designed with a simple structure based on a touch-based input method of mobile platform applications. This input method is easier and more convenient than the existing graphical user interface (GUI), in which menu items such as buttons are selected repeatedly or step by step. Next, an interaction that intuitively facilitates a behavior and decision making from the input text is proposed. We propose an interaction technique that recognizes a text handwritten on the text interface through the Extended Modified National Institute of Standards and Technology (EMNIST) dataset and a convolutional neural network (CNN) model and connects the text to a behavior. Finally, using the proposed interface, we create English language teaching applications that can effectively facilitate learning alphabet writing and words using handwriting. Then, the satisfaction regarding the interface during the educational process is analyzed and verified through a survey experiment with users.

Patterns of Teacher Trainee Grammar Talk in Second Language Classrooms

Literature in Language Teacher Education (LTE) has highlighted that teaching of grammar should be included as a foundational framework for all language teaching. This indicates that teacher trainees need to be trained with a firm foundation for grammar teaching in language classrooms. Thus, an investigation on how teacher trainees taught grammar and the pattern of their grammar instruction can provide insights to teacher trainees and teacher educators on grammar teaching methodology practised in language classrooms. By understanding how teacher trainees present grammar in their classrooms and what patterns emerged from their grammar instruction can lead to ongoing process of searching for better grammar teaching in language classrooms. This article shares the findings on an investigation conducted on how and what was practised by teacher trainees in their grammar instruction. Two prevalent patterns were discovered. Transmission technique which is teacher fronted and interaction technique which is teacher-student-teacher fronted were commonly practised by the trainees. However, the teacher-fronted technique dominates the interaction technique. This signals that teacher educators need to promote more interactive techniques in the LTE programme so that trainees are trained to teach grammar by utilising more interactive techniques such as questioning (to use more convergent and divergent questions instead of literal questions) and giving corrective feedback (to elicit and recast instead of repeating) which promote two-way grammar teaching.

M[eye]cro

We present M[eye]cro an interaction technique to select on-screen objects and navigate menus through the synergistic use of eye-gaze and thumb-to-finger microgestures. Thumb-to-finger microgestures are gestures performed with the thumb of a hand onto the fingers of the same hand. The active body of research on microgestures highlights expected properties including speed, availability and eye-free interaction. Such properties make microgestures a good candidate for multitasking. However, while praised, the state-of-the-art hypothesis stating that microgestures could be beneficial for multitasking has never been quantitatively verified. We study and compare M[eye]cro to a baseline, i.e., a technique based on physical controllers, in a cockpit-based context. This context allows us to design a controlled experiment involving multitasking with low- and high-priority tasks in parallel. Our results show that performances of the two techniques are similar when participants only perform the selection task. However, M[eye]cro tends to yield better time performance when participants additionally need to treat high-priority tasks in parallel. Results also show that M[eye]cro induces less fatigue and is mostly preferred.

Thumb Inclination-Based Manipulation and Exploration, a Machine Learning Based Interaction Technique for Virtual Environments

In the context of Virtual Reality (VR), interactions refer to the plausible actions in a Virtual Environment (VE). To have an engrossing interface, interactions by the gestures of hand are becoming prominent. With thisresearch work, a novel interaction technique is proposed where interactions are performed on the basis of the position of thumb in dynamic image stream. The technique needs no expensive tracker but an ordinary camera to trace hand movements and position of thumb. The interaction tasks are enacted in distinct interaction states, where the Angle of Inclination (AOI) of thumb is used for state-to-state transition. The angle is computed dynamically between the tip-of-thumb and the base of the Region of Interest (ROI) of an input image. The technique works in two phases: learning phase and application phase. In the learning phase, user-defined fist-postures with distinct AOI are learnt. The Support Vector Machine (SVM) classifier is trained by the AOI of the postures. In the application phase, interactions are performed in distinct interaction states whereas a particular state is activated by posing the known posture. To follow the trajectory of thumb, dynamic mapping is performed to control a virtual hand by the position of thumb in the input image. The technique is implemented in a Visual Studio project called Thumb-Based Interaction for Virtual Environments (TIVE). The project was evaluated by a group of 15 users in a moderate lighting condition. The 89.7% average accuracy rate of the evaluation proves suitability of the technique in the wide range VR applications.

Evaluation of 1D Selection Techniques for Mobile Visualizations

In spite of growing demand for mobile data visualization, few design guidelines exist to address its many challenges including small screens and low touch interaction precision. Both of these challenges can restrict the number of data points a user can reliably select and view in more detail, which is a core requirement for interactive data visualization. In this study, we present a comparison of the conventional tap technique for selection with three variations including visual feedback to understand which interaction technique allows for optimal selection accuracy. Based on the results of the user study, we provide actionable solutions to improve interaction design for mobile visualizations. We find that visual feedback, such as selection with a handle, improves selection accuracy three- to fourfold compared to tap selection. With a 75% accuracy, users could select a target item among 176 items total using the handle, but only from 60 items using tap. On the other hand, techniques with visual feedback took about twice as long per selection when compared to tap. We conclude designers should use selection techniques with visual feedback when the data density is high and improved selection precision is required for a visualization.

Rumor surveillance methods in outbreaks: A systematic literature review

Background: The spreading of health-related rumors can profoundly put society at risk, and the investigation of strategies and methods can efficiently prevent the dissemination of hazardous rumor is necessary, especially during a public health emergency including disease outbreaks. In this article we review the studies that implicated the surveillance system in identifying rumors and discuss the different aspects of current methods in this field. Methods: We searched PubMed, EMBASE, Scopus, and Web of Science databases for relevant publications in English from 2000 to 2020. The PICOS approach was used to select articles, and two reviewers extracted the data. Findings were categorized as a source of rumors, type of systems, data collection, and data transmission methods. The quality of the articles was assessed using the Mixed Method Appraisal Tool (MMAT) checklist. Results: Five studies that presented the methods used for rumor detection in different outbreaks were included in the critical appraisal process. Findings were grouped into four categories: source of rumors, type of systems, data collection, and data transmission methods. The source of rumors in most studies was media, including new social and traditional media. The most used data collection methods were human-computer interaction technique, and automatic and manual methods each were discussed in one study. Also, the data transmission method was asynchronous in the majority of studies. Conclusion: Based on our findings, the most common rumor detection systems used in the outbreaks were manual and/or human-computer methods which are considered to be time-consuming processes. Due to the ever-increasing amount of modern social media platforms and the fast-spreading of misinformation in the times of outbreaks, developing the automatically and real-time tools for rumor detection is a vital need.