https://scholar.dgist.ac.kr/handle/20.500.11750/12131 2026-04-06T13:35:32Z https://scholar.dgist.ac.kr/handle/20.500.11750/58401 Title: Hardware-Embedded Pointing Transfer Function Capable of Canceling OS Gains Author(s): Kim, Seonho; Kim, Munjeong; Kim, Jonghyun; Kang, Donghyeon; Kim, Sunjun; Lee, Byungjoo Abstract: When using indirect pointing devices in modern operating systems (OS), users' perception of the pointing transfer function is easily influenced by the device's hardware or OS-native transfer function settings. This could hinder users from finding and fully adapting to the transfer function that is optimal for them. We propose a novel hardware-embedded transfer function technique that is expected to allow users to consistently experience the desired function even when device hardware or OS settings change. The technique (1) allows users to define the desired function within the device firmware in physical units and (2) enables the firmware to cancel out the influence of OS-native functions and hardware setting perturbations, so that the uploaded function can persist regardless of the external environment. Through technical evaluation including transfer functions of various shapes, we showed that the proposed technique has comparable robustness and accuracy to the conventional approach. © 2025 Copyright held by the owner/author(s). 2025-04-27T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58400 Title: Modeling User Performance in Multi-Lane Moving-Target Acquisition Author(s): Kim, Jonghyun; Kim, Joongseok; Yoon, June-Seop; Moon, Hee-Seung; Kim, Sunjun; Lee, Byungjoo Abstract: Modern video games often feature moving target acquisition (MTA) tasks, where users must press a button when a moving target reaches an acquisition line. User performance models in MTA are useful for quantitative skill analysis and computational game level design, but have so far been constructed only for cases where there is a single lane for a target to appear and follow. In this study, the first user performance model is presented and validated for an MTA task with multiple lanes. The model is built as an integration of the existing MTA model and the drift-diffusion model, a model of human decision-making process under time-pressure. In a user study, we showed that the model can fit lane recognition error rates and input timing distributions with significantly higher coefficients of determination (R2) and accuracy than a baseline model. © 2025 Copyright held by the owner/author(s). 2025-04-28T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/58399 Title: Study on the Perception of Mouse Weight Based on Moment of Inertia and Center of Mass Author(s): Baek, Minhyeok; Ryu, Yeonsoo; Heo, Daehyun; Kim, Sunjun Abstract: Video games have become a cultural phenomenon that captivate millions of people worldwide. Alongside the growth of gaming culture, the demand for better gaming equipment has led to diverse research on mice. However, there is a lack of research on how mass distribution affects user perception and performance. In this study, we explored the effects of varying mass distributions on user perception of mouse weight. We fabricated mice with variable centers of mass (CoM) and moments of inertia while keeping the actual weight constant. The results showed that changes in CoM can alter perceived weight, but changes in moments of inertia have only a limited effect. The results of this study could provide a preliminary understanding of how weight perception varies with different mass distributions of a mouse. © 2025 Copyright held by the owner/author(s). 2025-07-28T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/57866 Title: Exploring Intervention Techniques to Alleviate Negative Emotions during Video Content Moderation Tasks as a Worker-centered Task Design Author(s): Lee, Dokyun; Seo, Sangeun; Park, Chanwoo; Kim, Sunjun; Chang, Buru; Song, Jean Y. Abstract: Videos are dynamic and multi-modal compared to other types of content, making automatic fltering difcult, which is why content moderators play a crucial role. However, video content moderators are exposed to more profound emotional labor because videos contain rich visual information, sometimes including even harmful content, such as violent or terrifying scenes. In this work, we explore the efect of six intervention techniques on alleviating negative emotions during video content moderation tasks. We conducted one online crowdsourcing experiment and two controlled user studies to fnd out that (i) interleaving with positive videos or (ii) cartoonization could signifcantly reduce negative emotions in the moderators. Participants reported that the advantages of these approaches are in helping reduce negative emotions at the time of moderation while existing approaches focus on post-task activities (e.g., relaxation, talking with others, or getting a hobby). We discuss the applicability of our fndings to broader tasks, including improvement in intervention techniques. © 2024 Copyright held by the owner/author(s). Publication rights licensed to ACM. 2024-06-30T15:00:00Z