Enhanced device-based 3D object manipulation technique for handheld mobile augmented reality

3D object manipulation is one of the most important tasks for handheld mobile Augmented Reality (AR) towards its practical potential, especially for realworld assembly support. In this context, techniques used to manipulate 3D object is an important research area. Therefore, this study developed an improved device based interaction technique within handheld mobile AR interfaces to solve the large range 3D object rotation problem as well as issues related to 3D object position and orientation deviations in manipulating 3D object. The research firstly enhanced the existing device-based 3D object rotation technique with an innovative control structure that utilizes the handheld mobile device tilting and skewing amplitudes to determine the rotation axes and directions of the 3D object. Whenever the device is tilted or skewed exceeding the threshold values of the amplitudes, the 3D object rotation will start continuously with a pre-defined angular speed per second to prevent over-rotation of the handheld mobile device. This over-rotation is a common occurrence when using the existing technique to perform large-range 3D object rotations. The problem of over-rotation of the handheld mobile device needs to be solved since it causes a 3D object registration error and a 3D object display issue where the 3D object does not appear consistent within the user’s range of view. Secondly, restructuring the existing device-based 3D object manipulation technique was done by separating the degrees of freedom (DOF) of the 3D object translation and rotation to prevent the 3D object position and orientation deviations caused by the DOF integration that utilizes the same control structure for both tasks. Next, an improved device-based interaction technique, with better performance on task completion time for 3D object rotation unilaterally and 3D object manipulation comprehensively within handheld mobile AR interfaces was developed. A pilot test was carried out before other main tests to determine several pre-defined values designed in the control structure of the proposed 3D object rotation technique. A series of 3D object rotation and manipulation tasks was designed and developed as separate experimental tasks to benchmark both the proposed 3D object rotation and manipulation techniques with existing ones on task completion time (s). Two different groups of participants aged 19-24 years old were selected for both experiments, with each group consisting sixteen participants. Each participant had to complete twelve trials, which came to a total 192 trials per experiment for all the participants. Repeated measure analysis was used to analyze the data. The results obtained have statistically proven that the developed 3D object rotation technique markedly outpaced existing technique with significant shorter task completion times of 2.04s shorter on easy tasks and 3.09s shorter on hard tasks after comparing the mean times upon all successful trials. On the other hand, for the failed trials, the 3D object rotation technique was 4.99% more accurate on easy tasks and 1.78% more accurate on hard tasks in comparison to the existing technique. Similar results were also extended to 3D object manipulation tasks with an overall 9.529s significant shorter task completion time of the proposed manipulation technique as compared to the existing technique. Based on the findings, an improved device-based interaction technique has been successfully developed to address the insufficient functionalities of the current technique

Awareness support for learning designers in collaborative authoring for adaptive learning

Adaptive learning systems offer students a range of appropriate learning options based on the learners’ characteristics. It is, therefore, necessary for such systems to maintain a hyperspace and knowledge space that consists of a large volume of domain and pedagogical knowledge, learner information, and adaptation rules. As a consequence, for a solitary teacher, developing learning resources would be time consuming and requires the teacher to be an expert of many topics. In this research, the problems of authoring adaptive learning resources are classified into issues concerning interoperability, efficiency, and collaboration.This research particularly addresses the question of how teachers can collaborate in authoring adaptive learning resources and be aware of what has happened in the authoring process. In order to experiment with collaboration, it was necessary to design a collaborative authoring environment for adaptive learning. This was achieved by extending an open sourced authoring tool of IMS Learning Design (IMS LD), ReCourse, to be a prototype of Collaborative ReCourse that includes the workspace awareness information features: Notes and History. It is designed as a tool for asynchronous collaboration for small groups of learning designers. IMS LD supports interoperability and adaptation. Two experiments were conducted. The first experiment was a workspace awareness study in which participants took part in an artificial collaborative scenario. They were divided into 2 groups; one group worked with ReCourse, the other with Collaborative ReCourse. The results provide evidence regarding the advantages of Notes and History for enhancing workspace awareness in collaborative authoring of learning designs.The second study tested the system more thoroughly as the participants had to work toward real goals over a much longer time frame. They were divided into four groups; two groups worked with ReCourse, while the others worked with Collaborative ReCourse. The experiment result showed that authoring of learning designs can be approached with a Process Structure method with implicit coordination and without role assignment. It also provides evidence that collaboration is possible for authoring IMS LD Level A for non-adapting and Level B for adapting materials. Notes and History assist in producing good quality output.This research has several contributions. From the literature study, it presents a comparison analysis of existing authoring tools, as well as learning standards. Furthermore, it presents a collaborative authoring approach for creating learning designs and describes the granularity level on which collaborative authoring for learning designs can be carried out. Finally, experiments using this approach show the advantages of having Notes and History for enhancing workspace awareness that and how they benefit the quality of learning designs

A framework for cots software evaluation and selection for COTS mismatches handling and non-functional requirements

The decision to purchase Commercial Off-The-Shelf (COTS) software needs systematic guidelines so that the appropriate COTS software can be selected in order to provide a viable and effective solution to the organizations. However, the existing COTS software evaluation and selection frameworks focus more on functional aspects and do not give adequate attention to accommodate the mismatch between user requirements and COTS software specification, and also integration with non functional requirements of COTS software. Studies have identified that these two criteria are important in COTS software evaluation and selection. Therefore, this study aims to develop a new framework of COTS software evaluation and selection that focuses on handling COTS software mismatches and integrating the nonfunctional requirements. The study is conducted using mixed-mode methodology which involves survey and interview. The study is conducted in four main phases: a survey and interview of 63 organizations to identify COTS software evaluation criteria, development of COTS software evaluation and selection framework using Evaluation Theory, development of a new decision making technique by integrating Analytical Hierarchy Process and Gap Analysis to handle COTS software mismatches, and validation of the practicality and reliability of the proposed COTS software Evaluation and Selection Framework (COTS-ESF) using experts’ review, case studies and yardstick validation. This study has developed the COTS-ESF which consists of five categories of evaluation criteria: Quality, Domain, Architecture, Operational Environment and Vendor Reputation. It also provides a decision making technique and a complete process for performing the evaluation and selection of COTS software. The result of this study shows that the evaluated aspects of the framework are feasible and demonstrate their potential and practicality to be applied in the real environment. The contribution of this study straddles both the research and practical perspectives of software evaluation by improving decision making and providing a systematic guidelines for handling issue in purchasing viable COTS software

From Capture to Display: A Survey on Volumetric Video

Volumetric video, which offers immersive viewing experiences, is gaining increasing prominence. With its six degrees of freedom, it provides viewers with greater immersion and interactivity compared to traditional videos. Despite their potential, volumetric video services poses significant challenges. This survey conducts a comprehensive review of the existing literature on volumetric video. We firstly provide a general framework of volumetric video services, followed by a discussion on prerequisites for volumetric video, encompassing representations, open datasets, and quality assessment metrics. Then we delve into the current methodologies for each stage of the volumetric video service pipeline, detailing capturing, compression, transmission, rendering, and display techniques. Lastly, we explore various applications enabled by this pioneering technology and we present an array of research challenges and opportunities in the domain of volumetric video services. This survey aspires to provide a holistic understanding of this burgeoning field and shed light on potential future research trajectories, aiming to bring the vision of volumetric video to fruition.Comment: Submitte

Examining the Impact of Culture and Language on the User Acceptance of the Media Website in Jordan

This study examines the website acceptance based on the information system quality and the impact of cultural dimensions and language components on the actual acceptance and usage of the identified media websites. Based on the data from three groups of users, namely the users of bbc.com to represent the purely English media websites, the al-jazeera.com representing the semi-localized media website and the al-rai.com representing the local websites. Questionnaires were administered to 420 internet users in different regions in Jordan. The questionnaire measures nine parameters which include the system accessibility, the response time, information quality, cultural adaptation, Arabic language, perceived ease of use, perceived usefulness, attitudes towards using the websites and the behavioral intention to use the websites. Capitalizing on the quantitative research methodology by expanding the technology acceptance model for the research framework, the findings showed that the cultural dimensions of power distance, collectivism, masculinity and uncertainty avoidance have the positive impact on the Jordanian users’ preference of the media websites. The conclusions are drawn from the positive impact of cultural adaptation on the perceived ease of use of the local websites and also on the users’ attitudes towards the use of the local websites. However, there is a negative impact based on the lack of cultural adaptation on the users’ attitudes towards the use of English originated websites. Similarly, there is no significant impact of the cultural adaptation on the users’ attitudes towards the use of the semi- localized websites. The research findings showed that the websites’ information system quality, the Arabic language usage and the Arabic cultural adaptation have positive impacts on the Jordanian users’ perceptions and acceptance in choosing the media websites as preferred websites

"What It Wants Me To Say": Bridging the Abstraction Gap Between End-User Programmers and Code-Generating Large Language Models

Code-generating large language models translate natural language into code. However, only a small portion of the infinite space of naturalistic utterances is effective at guiding code generation. For non-expert end-user programmers, learning this is the challenge of abstraction matching. We examine this challenge in the specific context of data analysis in spreadsheets, in a system that maps the users natural language query to Python code using the Codex generator, executes the code, and shows the result. We propose grounded abstraction matching, which bridges the abstraction gap by translating the code back into a systematic and predictable naturalistic utterance. In a between-subjects, think-aloud study (n=24), we compare grounded abstraction matching to an ungrounded alternative based on previously established query framing principles. We find that the grounded approach improves end-users' understanding of the scope and capabilities of the code-generating model, and the kind of language needed to use it effectively