https://scholar.dgist.ac.kr/handle/20.500.11750/371 2026-04-08T17:02:55Z https://scholar.dgist.ac.kr/handle/20.500.11750/60139 Title: 활성화 기지국 선택 방법 및 장치 Author(s): 수달샨; 박찬원; 이제민; 조혜원 Abstract: 본 개시의 일 측면에 따르면 전자 장치에 의해 수행되는 활성화 기지국 선택 방법이 제공될 수 있다. 상기 방법은 하나 이상의 프로세서 및 상기 하나 이상의 프로세서에 의해 실행되는 적어도 하나의 명령을 저장하는 하나 이상의 메모리를 포함하는 전자 장치에 의해 수행되는 방법으로서, 상기 하나 이상의 프로세서가, 기지국으로부터 사용자 단말로 전송되는 신호의 평균 수신 신호 세기를 복수의 기지국들 각각에 대해 산출하는 단계; 상기 평균 수신 신호 세기에 관한 제1 기준 값에 기초하여 상기 복수의 기지국들 중 적어도 하나의 기지국을 포함하는 협력 기지국 집합을 결정하는 단계; 상기 협력 기지국 집합에 포함된 각각의 기지국에 대한 중요도를 산출하는 단계; 및 상기 중요도에 관한 제2 기준 값에 기초하여 상기 협력 기지국 집합에 포함된 각각의 기지국에 대한 활성화 여부를 결정하는 단계를 포함할 수 있다. https://scholar.dgist.ac.kr/handle/20.500.11750/60121 Title: Efficient Dynamic Scene Editing via 4D Gaussian-based Static-Dynamic Separation Author(s): Kwon, Joohyun; Cho, Hanbyel; Kim, Junmo Abstract: Recent 4D dynamic scene editing methods require editing thousands of 2D images used for dynamic scene synthesis and updating the entire scene with additional training loops, resulting in several hours of processing to edit a single dynamic scene. Therefore, these methods are not scalable with respect to the temporal dimension of the dynamic scene (i.e., the number of timesteps). In this work, we propose Instruct-4DGS, an efficient dynamic scene editing method that is more scalable in terms of temporal dimension. To achieve computational efficiency, we leverage a 4D Gaussian representation that models a 4D dynamic scene by combining static 3D Gaussians with a Hexplane-based deformation field, which captures dynamic information. We then perform editing solely on the static 3D Gaussians, which is the minimal but sufficient component required for visual editing. To resolve the misalignment between the edited 3D Gaussians and the deformation field, which may arise from the editing process, we introduce a refinement stage using a score distillation mechanism. Extensive editing results demonstrate that Instruct-4DGS is efficient, reducing editing time by more than half compared to existing methods while achieving high-quality edits that better follow user instructions. 2025-06-14T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60110 Title: SPATS: a practical system for comparative analysis of spatio-temporal graph neural networks Author(s): Yoon, Heeyong; Chon, Kang-Wook; Kim, Min-Soo Abstract: Thanks to technological advances in sensors and artificial intelligence, large amounts of data that combine spatial and temporal information are being produced in multiple domains. Spatio-temporal graph neural networks (STGNNs) have been recognized as highly effective models for analyzing spatio-temporal data, and so numerous novel STGNN models have recently been developed. However, no systematic and in-depth study has been carried out on the existing STGNN models with various datasets. Thus, it remains to be undecided whether more recent methods achieve better performance than traditional approaches. In this study, we propose a practical system, called SPAtio-Temporal graph System (SPATS), that performs effectively and efficiently the fair comparison of various STGNN models and datasets. SPATS introduces a unified data format to reduce dependency on data models and exploits GPU clusters to handle a large number of model comparisons automatically. Extensive experiments demonstrate that SPATS can efficiently compare STGNN models with reduced memory footprints and fully exploit GPU clusters. Furthermore, SPATS allows us to easily find the effective combination between the STGNN models and the datasets in various domains that have not been examined before. 2025-08-31T15:00:00Z https://scholar.dgist.ac.kr/handle/20.500.11750/60108 Title: Neuroprotective and Neurotrophic Potential of Flammulina velutipes Extracts in Primary Hippocampal Neuronal Culture Author(s): Mitra, Sarmistha; Dash, Raju; Bashar, Md Abul; Mazumder, Kishor; Moon, Il Soo Abstract: Flammulina velutipes (enoki mushroom) is a functional edible mushroom rich in antioxidants, polysaccharides, mycosterols, fiber, and minerals. Accumulating evidence highlights its therapeutic potential across diverse pathological contexts, including boosting cognitive function. However, its role in neuromodulation has not been systematically explored. This study examined the effects of methanolic and ethanolic extracts of F. velutipes on primary hippocampal neurons. Neurons were treated with different extract concentrations, followed by assessments of cell viability, cytoarchitecture, neuritogenesis, maturation, and neuroprotection under oxidative stress. The extracts were further characterized by GC-MS to identify bioactive metabolites, and molecular docking combined with MM-GBSA binding energy analysis was employed to predict potential modulators. Our results demonstrated that the methanolic extract significantly enhanced neurite outgrowth, improved neuronal cytoarchitecture, and promoted survival under oxidative stress, whereas the ethanolic extract produced moderate effects. Mechanistic studies indicated that these neuroprotective and neurodevelopmental benefits were mediated through activation of the NTRK receptors, as validated by both in vitro assays and molecular docking studies. Collectively, these findings suggest that F. velutipes extracts, particularly methanolic fractions, may serve as promising neuromodulatory agents for promoting neuronal development and protecting neurons from oxidative stress. 2025-09-30T15:00:00Z