In real-world scenarios, the identification accuracy of radar pulse data is often hampered by limited recognition features, a large volume of data samples, and unknown signals. To tackle these issues, a Sample Recommendation-based Multidimensional View Collaborative (SR-MDVC) domain adaptation algorithmis proposed. Initially, by integrating transfer learning theory and the hierarchical emission model, unknown and known pulse signals are defined from the perspective of probability density functions （PDFs）. Subsequently，a sample recommendation algorithm based on user collaborative filtering algorithm is introduced. This algorithm effectively reduces the disparity in the PDFs of unknown and known radar pulses. Moreover, a collaborative domain adaptation algorithm for multidimensional perspective model is developed. The model adapts data in the statistical feature dimension and the geometric feature dimension, and is optimized by iterating results across different dimensions. Finally, the domain - adapted data is fed into the least squares support vector machines (LSSVM) to complete the identification of unknown radar pulses. The effectiveness of this method is verified by semi-physical experiments, which demonstrate the excellent recognition performance of the proposed method, with a recognition accuracy of more than 0.9 for unknown and unbalanced data, and a 4-fold improvement in computational efficiency.

Autistic children may often experience challenges in mastering daily living skills crucial for their independence and well-being. This study introduces “Tidd,” an augmented tabletop interactive system designed to assist autistic children in practising daily living skills in an engaging and physically interactive environment. We conducted a user study in a medical rehabilitation centre and an integrated kindergarten. Seventeen autistic children aged three to five years used Tidd in training sessions covering two vital skills: bed-making and dressing. Progress was evaluated through task completion and progress tracking, observational data for children, and therapist qualitative feedback. Therapists reported that Tidd was beneficial in maintaining the children’s attention and enhancing their motivation. Observational data further suggested increased engagement and decreased frustration during tasks. This study with Tidd highlights the potential of tabletop interaction to support therapists in training autistic children to learn daily living skills. • Tidd: AR tabletop device aiding autistic children in bed-making and dressing. • Improved task accuracy and engagement in study with 17 autistic children. • Therapists validated Tidd’s practicality and appeal in autism interventions.

Recognizing the potential of freehand gestures for interacting with virtual objects in virtual environments, our research introduces a user-defined freehand gesture set of typical referents in virtual reality (VR), focusing on a specific scenario: VR museums. We conducted a comprehensive elicitation study with two experiments to define and refine the gesture set. Meanwhile, we demonstrated an enhanced real-time Wizard of Oz approach that facilitated users’ understanding of referents in VR and their gesture design. Our findings revealed significant improvements in gesture consistency and user agreement through two experiments, with an average agreement score of firstchoice and second-choice advancing from 0.211 and 0.160 to 0.412 and 0.284, respectively. By offering a consistent user-centered gesture set, this work contributes to guiding museum curators toward creating more immersive user experiences in VR museums. The gestures can also be extended to other VR applications that necessitate travel, selection and manipulation, and system control tasks.

The ever-increasing demand for videos on mobile devices poses a significant challenge to existing cellular network infrastructures. To cope with the challenge, we propose a user-centric video transmission mechanism based on device-to-device communications that allows mobile users to cache and share videos between each other, in a cooperative manner. The proposed solution jointly considers users' similarity in accessing videos, users' sharing willingness, users' location distribution, and users' quality of experience (QoE) requirements, in order to achieve a QoE-guaranteed video streaming service in a cellular network. Specifically, a service set consisting of several service providers and mobile users, is dynamically configured to provide timely service according to the probability of successful service. Numerical results show that when the number of providers and demanded videos is 40 and 2, respectively, the improved users experience rate in the proposed solution is approximately 85%, and the data offload rate on base station(s) is about 78%.

To relieve the current overload of cellular networks caused by the continuously growing multimedia service, mobile edge collaboration, which exploits edge users to distribute videos for base station (BS), provides an effective way to share the heavy BS load. With the emergence of mobile edge technologies for Internet-of-Things applications, such as device to device and machine to machine, how to exploit users' social characteristics and mobility to minimize the number of transmissions of BS and how to improve the quality of experience of users have become the key challenges. In this paper, we study two aspects that are critical to these issues. One is the two-step detection mechanism, namely the establishment of virtual communities and collaborative clusters. Specifically, we take into consideration user preference for content and location. First of all, a virtual community is established, which exploits the coalition game based on the user's preference list to dynamically divide users into multiple communities. Then, to take full advantage of the temporary link established between users, a grid-based clustering method is proposed to manage the video requesting users. On the other hand, we propose a scalable video coding sharing scheme based on user's social attributes. This approach makes video distribution more flexible at the edge of mobile network through collaboration among users, and effectively reduces transmission energy consumption of transmitters. Numerical results show that the proposed mechanism can not only effectively alleviate the BS load, but also dramatically improve the reliability and adaptability of video distribution.

In this paper, we present an audio codec for portable application, which supports MPEG-2/MPEG-4 AAC LC profile. The presented codec has been implemented using UMC/HJTC 0.18mum CMOS technology. In this implementation, optimized algorithms are developed and most memory and calculation units are shared between encoder and decoder so that the features of low power and low cost are achieved. The codec uses a total of 160k gates, 21KB RAM and 1.7KB ROM. Experiment shows that it is capable of real-time encoding/decoding AAC streams at only 5MHz working frequency. The codec's interface is simple so that it can be reused as IP macro and easily embedded into various multimedia systems