Gwang Hoon Park

Recently, social media have been used by researchers to detect depressive symptoms in individuals using linguistic data from users’ posts. In this study, we propose a framework to identify social information as a significant predictor of depression. Using the proposed framework, we develop an application called the Socially Mediated Patient Portal (SMPP), which detects depression-related markers in Facebook users by applying a data-driven approach with machine learning classification techniques.

Chronic kidney disease (CKD) is one of the leading medical ailments in developing countries. Due to the limited healthcare infrastructure and the lack of trained human resources, the CKD problem aggravates if it is not addressed in its earlier stages. In this regard, the role of machine learning-based automated diagnosis systems plays a vital role to deal with the CKD problem. In most of the studies conducted on the automated CKD decision modeling, the main emphasis is given to enhancing the pre

A deblocking filtering method that reduces the blocking artifacts that result from the use of the illumination change-adaptive motion compensation method, which was already adopted in the current multiview video coding (MVC) standard, is introduced. When the macroblock (MB)-based illumination compensation method is used to compensate local illumination changes in multiview video sequences, the neighboring MBs could have different illumination values that represent the average values of the lumin

Automated medical diagnosis is one of the important machine learning applications in the domain of healthcare. In this regard, most of the approaches primarily focus on optimizing the accuracy of classification models. In this research, we argue that, unlike general-purpose classification problems, medical applications, such as chronic kidney disease (CKD) diagnosis, require special treatment. In the case of CKD, apart from model performance, other factors such as the cost of data acquisition ma

Motion compensation (MC) is a critical component in terms of computational complexity and memory bandwidth. The MC complexity of High Efficiency Video Coding (HEVC) for UHD contents significantly increased more than that of AVC/H.264. This paper reveals and analyzes a feature of generalized P and B pictures in HEVC and introduces a simple and effective method for MC complexity reduction that can be exploited at both the encoder and decoder without affecting the compression performance. The propo

In the era of digital well-being, smart gadgets are the unobtrusive sources of acquiring information. A variety of personalized wellness applications support self-quantification based recommendations to provide wellness status for achieving personalized targets. However, these applications are unable to promote the induction of new healthy habits and thus are not too much effective for long term as users tend to loose their interest. Thus, we have proposed a methodology for User-Centric Adaptive

A lot of 3D contents haven been widely used for multimedia services, however, real 3D video contents have been adopted for a limited applications such as a specially designed 3D cinema. This is because of the difficulty of capturing real 3D video contents and the limitation of display devices available in a market. However, diverse types of display devices for stereoscopic video contents for real 3D video contents have been recently released in a market. Especially, a mobile phone with a stereos

This paper proposes a reusable design for the merging process used in three-dimensional High Efficiency Video Coding (3D-HEVC), which can significantly reduce the implementation complexity by eliminating duplicated module redundancies. The majority of inter-prediction coding tools used in 3D-HEVC are utilized through a merge mode, whose extended merging process is based on built-in integration to completely wrap around the HEVC merging process. Consequently, the implementation complexity is unav

One of the recent and most significant technical properties can be expressed as “digital convergence,” which is helping lead the technical paradigm into a ubiquitous environment. As an initial trial of realizing a ubiquitous environment, the convergence between broadcasting and telecommunication fields is now on the way, where it is required to develop a scalable video coding scheme for one-source and multi-use media. Traditional scalable video coding schemes have, however, limitations for highe

A neural-net based rate control algorithm for MPEG encoders is introduced. It is based on the global rate-distortion model constructed by a self-organising feature map. The performances of the proposed algorithm are better than those for MPEG-4 VM5+ frame-based rate control, based on the criteria of the average number of bits per frame and PSNR.