https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/268 2026-07-03T23:05:19Z 2026-07-03T23:05:19Z Yeo, Haein Noh, Taehyung Han, Kyungsik https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213162 2026-06-09T02:00:24Z 2026-12-01T00:00:00Z

Title: Llm-generated content-based explanations for user experience in fashion recommender systems Authors: Yeo, Haein; Noh, Taehyung; Han, Kyungsik Abstract: Recommendation explanations are crucial in helping users make informed and confident decisions, especially in domains such as fashion, where personal style and preferences play an important role. While previous studies have predominantly used review data for explanations, the review-based method requires the availability and quality of a good number of reviews. To address this issue, we investigate the effectiveness of content-based recommendation explanations in fashion recommender systems. Using a Large Language Model (LLM) and deep learning techniques trained on fashion attribute data, we developed a framework that extracts essential visual information from product images and generates user-tailored explanations. This approach allows us to generate customized explanations at various levels—basic, simple, and detailed—for each recommendation. We developed a My Own Style (MOS) interface that displays fashion products, recommendations, and explanations. Our user study with 211 participants showed that detailed explanations, especially when combined with diversity-based algorithms, significantly improved user satisfaction and trust in fashion recommendations. This study contributes to clothing and textile research by providing guidelines for fashion-specific LLM prompts and demonstrating the effectiveness of LLM-generated explanations in fashion e-commerce. Our findings point the way to more personalized and transparent AI-driven fashion recommender systems that improve user experience and style exploration in fashion e-commerce.

2026-12-01T00:00:00Z Li, Tao Lee, Dong Yeop Gwac, Hocheol Hyeon, Jae Sang Choi, Jung Gi Lee, Nilüfer Çakmakçı Jeong, Youngjin Choi, Changsoon Kim, Seon Jeong https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212936 2026-06-02T02:00:22Z 2026-10-01T00:00:00Z

Title: Coil order-transformational actuation for high tensile stroke up to 65% with coiled CNT/PDMS fiber Authors: Li, Tao; Lee, Dong Yeop; Gwac, Hocheol; Hyeon, Jae Sang; Choi, Jung Gi; Lee, Nilüfer Çakmakçı; Jeong, Youngjin; Choi, Changsoon; Kim, Seon Jeong Abstract: Coiled fiber actuators have emerged as promising functional materials for soft robotics and intelligent systems. However, their inability to dynamically switch between primary and secondary coiled structures during operation severely limits their actuation performance. In this work, we propose a coil order transformational actuation mechanism based on twisted PDMS/CNT composite fibers that enables reversible switching between primary and secondary coils under dynamic loading and thermal stimulation. By exploiting temperature-induced variations in fiber diameter and mechanical properties, we modulate the critical twist density for secondary coiling and thereby trigger the spontaneous formation of higher-order coils. Under a load of 55 kPa at 200 °C, the actuator achieves a tensile stroke of 65% of its maximum value and can be fully reset under a load of 80 kPa. We further demonstrate a gas overheat protection valve based on this actuator, in which the structure autonomously regulates flow and shuts off at a critical temperature. This study introduces a new actuation paradigm based on reversible structural reconfiguration, thereby significantly enhancing the performance of coiled fiber actuators.

2026-10-01T00:00:00Z Kim, Taeyeong Kang, Kyubeom Lee, Jongho Jeong, Junhwa Oakley, Michael A. Cho, Moon-Kyu Cressler, John D. Lee, Byunghun Song, Ickhyun https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/212946 2026-06-02T05:00:19Z 2026-06-01T00:00:00Z

Title: A compact model for SiGe heterojunction bipolar transistor under AC-stress conditions Authors: Kim, Taeyeong; Kang, Kyubeom; Lee, Jongho; Jeong, Junhwa; Oakley, Michael A.; Cho, Moon-Kyu; Cressler, John D.; Lee, Byunghun; Song, Ickhyun Abstract: This paper presents a compact model of AC-stress-induced performance degradation in silicon–germanium (SiGe) heterojunction bipolar transistor (HBT) high-frequency amplifiers for circuit-level simulations. The proposed model introduces additional diode, resistor, and inductor to existing design-kit model to represent stress-induced base leakage and high-frequency degradation, enabling the analysis of base leakage current, current gain (β), cutoff frequency (fT), maximum oscillation frequency (fmax), impedance variation, and RF performance degradation under large-signal AC stress. The model was validated using two amplifier samples fabricated in GlobalFoundries 130 nm SiGe BiCMOS technology. Under AC stress, both samples exhibited similar RF degradation trends, including reduced power gain, while additional measurements on the second sample confirmed increased base current and reduced current gain after stress. In addition, simulation results showed degradation trends in fT and fmax together with shifts associated with the stress-induced increase in base current. The proposed model reproduced the measured degradation behavior and can be directly implemented in standard design-kit-based simulation environment. These results demonstrate that the proposed approach provides a practical framework for predicting and analyzing AC-stress-induced degradation at both the device and circuit levels.

2026-06-01T00:00:00Z Shin, Won-Gyo Sung, Kiho Bang, Junho Sul, Sunhae Youm, Yoosik Parkinson, Carolyn https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/213266 2026-06-15T04:30:25Z 2026-06-01T00:00:00Z

Title: Early neural attunement to peer status predicts future social network position and popularity in adolescents Authors: Shin, Won-Gyo; Sung, Kiho; Bang, Junho; Sul, Sunhae; Youm, Yoosik; Parkinson, Carolyn Abstract: Popularity is a key marker of social status, yet the phenomena that support its emergence within newly forming social groups remain unclear. We combined functional neuroimaging and longitudinal school-wide social network analysis to track adolescents throughout their first year of high school, examining whether early neural responses to peers of varying social status predict later popularity. Here, we show that greater neural differentiation when viewing the faces of unpopular versus popular peers, particularly in the hippocampus, forecasts greater perceived popularity at the end of the school year. This relationship is mediated by midyear social network centrality, especially in-closeness centrality, which reflects being more easily reachable by peers. These findings suggest that early neural attunement to the status of their peers shapes how adolescents become embedded in their social networks, which in turn contributes to later gains in their own perceived popularity. More generally, these findings reveal how neural and social network-level processes jointly drive adolescents' navigation of evolving social landscapes and attainment of social status.

2026-06-01T00:00:00Z