Yeongjun Lee

Given the rapid speed at which digital transformation has progressed, social or scientific problems that are difficult to solve using knowledge gained from the existing segmented academic paradigm have emerged. To solve these problems, the need for talent convergence has increased, and Korea has begun to provide convergence education, starting with science, technology, engineering, art, and mathematics (STEAM) education. Convergence education is defined as “education to cultivate knowledge that

As sharing images in an instant message is a crucial factor, there has been active research on learning an image-text multi-modal dialogue models. However, training a well-generalized multi-modal dialogue model remains challenging due to the low quality and limited diversity of images per dialogue in existing multi-modal dialogue datasets. In this paper, we propose an automated pipeline to construct a multi-modal dialogue dataset, ensuring both dialogue quality and image diversity without requir

Background/Objectives: This study aimed to investigate and complement the ways of improving the Technological Pedagogical Content Knowledge-Programming (TPACK-P) educational program and verify the improved program’s effect on pre-service teachers’TPACK.Methods/Statistical Analysis: The TPACK-P educational program was conducted for 19 pre-service teachers; two difficulty items were investigated. A survey was administered to identify any improvement. To verify the effect of the improved progra

As the traffic of the Internet increases and diversifies, the needs for a fast flexible router have made researchers to work on software routers. The existing software router systems may utilize the cluster structure of multiple machines or GPU systems. Especially, Packet Shader, which uses GPU to exploit GPU's extensive parallelism, shows higher performance compared to other existing software routers. However, Packet Shader does not utilize the memory architecture in the GPU system. Basically,

Single-stage or single-step high-order temporal discretizations of partial differential equations (PDEs) have shown great promise in delivering high-order accuracy in time with efficient use of computational resources. There has been much success in developing such methods for finite volume method (FVM) discretizations of PDEs. The Picard Integral formulation (PIF) has recently made such single-stage temporal methods accessible for finite difference method (FDM) discretizations. PIF methods rely

To increase social bonding with interlocutors, humans naturally acquire the ability to respond appropriately in a given situation by considering which conversational skill is most suitable for the response - a process we call skill-of-mind. For large language model (LLM)-based conversational agents, planning appropriate conversational skills, as humans do, is challenging due to the complexity of social dialogue, especially in interactive scenarios. To address this, we propose a skill-of-mind-ann

본 논문에서는 광학방식 헤드 트랙커를 위한 맵 생성 알고리즘과 초기자세 추정기법을 제안한다. 제안한 광학방식 헤드 트랙커는 적외선 스테레오 카메라와 특징점으로 사용되는 적외선 다이오드가 부착된 헬멧으로 구성된다. 광학방식 헤드 트랙커의 경우 발광된 특징점의 중심점을 추적하여 조종사 머리의 자세 및 위치를 추정하기 때문에 이를 고려한 특징점의 정확한 위치정보가 요구된다. 제안한 맵 생성 알고리즘은 적외선 다이오드의 방사 형태를 고려하여 정밀한 특징점의 위치 정보가 포함된 맵 데이터와 머리 좌표계를 생성한다. 또한 초기자세 추정 기법은 헬멧에 부착된 특징점의 패턴을 이용하여 카메라와 머리 사이의 초기 자세와 위치를 빠르게 추정하며 이를 바탕으로 동체인 전투기를 기준으로 하는 머리 움직임을 정확하게 추정할 수 있다. This paper presents map creation algorithm and initial attitude estimation method for the propose

High resolution peripheral quantitative computed tomography (HRpQCT) offers detailed bone geometry and microarchitecture assessment, including cortical porosity, but assessing chronic kidney disease (CKD) bone images remains challenging. This proof-of-concept study merges deep learning and machine learning to 1) improve automatic segmentation, particularly in cases with severe cortical porosity and trabeculated endosteal surfaces, and 2) maximize image information using machine learning feature

Recently, many vision-and-language models have demonstrated remarkable performance in various multimodal tasks using a zero-shot approach. However, they lack spatial reasoning abilities, particularly in understanding visuo-spatial information from another’s perspective, a skill known as visual perspective taking. In this paper, we investigate whether vision-and-language models can develop visual perspective-taking abilities in a zero-shot manner. Through a simple experiment, we demonstrate that

There might be nothing more important than local identity when discussing local development or local revitalization. Especially, as a case of Shakespeare (Stratford-on-Avon) clearly underpins this statement, a human resource makes up a very large portion of local resources. Accordingly, since the autonomous local government system was launched in the mid-1990s, each region has tried to discover historical figures based on locality and established regional identity through them while utilizing re