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Guided Super Resolution of Land Surface Temperature Using Multisatellite Imageries
No full textAs understanding and monitoring global warming and heatwaves have become increasingly important, the demand for higher spatial and temporal resolution in satellite-observed land surface temperature (LST) data has risen. LST derived from geostationary satellite observations plays a crucial role in temperature monitoring, offering high temporal resolution across wide areas. However, a primary limitation of geostationary satellite-derived LST products is their low spatial resolution. In this study, we aim to overcome this limitation by employing a deep learning-based super-resolution (SR) approach and propose a model called References and residual in residual blocks to perform SR Network (3R-Net). This model incorporates terrain-guided reference images and residual blocks to enable more accurate SR. By using LST products from GEO-KOMPSAT-2A (GK2A) as low-resolution (LR) input, visible channel imagery from GEO-KOMPSAT-2B (GK2B) as terrain-reflective high-resolution (HR) reference, and Landsat-8 LST products as HR target images, our model effectively enhances the 2 km resolution of GK2A LST products to the 500 m resolution of Landsat-8 with improved spatial detail and accuracy. Unlike many previous studies relying on single-image SR with synthetically downsampled inputs, our approach uses real-world LR inputs, HR targets, and reference images, making the learning process more realistic and practical. Experimental results show that, when clear guidance is provided through reference images, 3R-Net surpasses existing SR methods, achieving higher peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM), and lower root mean square error (RMSE) while capturing critical spatial and temporal features, including surface characteristics and daily heating patterns. By integrating residual-in-residual (RIR) blocks, our model achieves a simple yet powerful enhancement in capturing fine-grained spatial and temporal patterns. These advancements suggest that 3R-Net can provide enhanced LST data crucial for climate research, environmental monitoring, and early warning systems.
Impact of commercial adaptive cruise control on highway traffic congestion and safety
No full textThe use of Adaptive Cruise Control (ACC) is rapidly increasing on highways, raising concerns about its impact on congestion and safety. This study analyzes the behaviour of commercial ACC vehicles using trajectory data from the OpenACC dataset. A calibrated car-following model simulates traffic flow on a highway on-ramp section, where congestion frequently originates. To isolate merging effects, the simulation restricts the mainline to a single lane. Results show that short-gap ACC vehicles slightly reduce breakdown probability but worsen local congestion due to string instability. Long-gap ACC vehicles, while more stable, reduce road capacity and are prone to frequent cut-ins and abrupt braking. Both ACC types face more hazardous situations than human drivers-short-gap vehicles often violate safe distances, while long-gap vehicles are vulnerable to aggressive merging. The coexistence of these vehicle types amplifies congestion and safety risks. These findings suggest the need for targeted traffic policies to manage ACC integration.
Enhanced geometric accuracy in directed energy deposition via closed-loop melt pool height control using real-time thermal imaging
No full textThis study presents a closed-loop melt pool height control system based on real-time thermal imaging to enhance the geometric accuracy of directed energy deposition (DED). Geometric inaccuracies in DED-printed components arise from the inherent thermal and geometric variations during the printing process. To improve geometric conformity with a predefined digital model, the proposed system employs a long-wave infrared camera to capture real-time thermal images of the melt pool. The peak-to-boundary temperature difference (TD), defined as the difference between the peak and boundary temperatures of the melt pool, is extracted from these images. The correlation between TD, melt pool height, and laser power was analyzed under various DED conditions, and the results demonstrated a strong relationship between TD and both parameters. Using the TD as a feedback parameter, the laser power is dynamically adjusted to maintain a stable melt pool height throughout the printing process. The proposed system enables real-time estimation of the melt pool height, ensures height stability through closed-loop control, and provides detailed insights into the thermal and geometric variations that affect the accuracy of the final part. This approach reduces the geometric error relative to the predefined digital model to below 4 %, highlighting its effectiveness in enhancing the geometric accuracy in complex multi-bead, multilayer structures.
Size-controlled assembly of phase separated protein condensates with interfacial protein cages
No full textPhase separation of specific proteins into liquid-like condensates is a key mechanism for forming membrane-less organelles, which organize diverse cellular processes in space and time. These protein condensates hold immense potential as biomaterials capable of containing specific sets of biomolecules with high densities and dynamic liquid properties. Despite their appeal, methods to manipulate protein condensate materials remain largely unexplored. Here, we present a one-pot assembly method to assemble coalescence-resistant protein condensates, ranging from a few mu m to 100 nm in sizes, with surface-stabilizing protein cages. We discover that large protein cages (similar to 30 nm), finely tuned to interact with condensates, efficiently localize on condensate surfaces and prevent the merging (coalescence) of condensates during phase separation. We precisely control condensate diameters by modulating condensate/cage ratios. In addition, the 3D structures of intact protein condensates with interfacial cages are visualized with cryo-electron tomography (ET). This work offers a versatile platform for designing size-controlled, surface-engineered protein condensate materials.
스트레인드 채널 성장 구조, 및 그를 이용한 스트레인드 채널 및 소자 제조 방법
No full textDisclosed are a growth structure for a strained channel, and a strained channel using the same and a method of manufacturing a device using the same. The growth structure for a strained channel includes a support substrate, a strain-relaxed buffer (SRB) layer disposed on a support substrate, a base growth layer grown to have one composition on the SRB layer, and a strained channel layer grown to have another composition on the base growth layer. The strained channel layer may include at least one of a tensile-strained channel layer or a compressively strained channel layer
Fusion Protein Comprising BP26 and Antigen Polypeptide
No full text본 발명은 본 발명은 BP26 및 항원 폴리펩타이드를 포함하는 융합 단백질 및 이를 포함하는 나노 구조체에 관한 것이다. 본 발명의 융합 단백질, 나노 구조체 또는 이들의 조합을 포함하는 백신 조성물을 이용하는 경우, 병원체 또는 암을 효과적으로 예방하거나 치료할 수 있어 다목적 백신 플랫폼으로 사용가능하다
세신, 길경 및 계지 중 2종 이상의 혼합 추출물을 유효성분으로 포함하는 알레르기성 질환의 예방 또는 치료용 조성물
No full textThe present invention relates to a pharmaceutical composition for prevention or treatment of an allergic disease comprising a mixed extract of two or more selected from the group consisting of Asiasarum root, Platycodon root, and Cinnamomi ramulus as an active ingredient; a method for prevention or treatment of an allergic disease using the pharmaceutical composition; and a health functional food and a feed composition for improvement of an allergic disease. The composition and method of the invention can specifically inhibit the differentiation of Th2 cells and thus can be effectively used as a composition for prevention or treatment of an allergic disease
Chiroptical spectroscopy platform, and Raman data acquiring method using the same
No full text본 발명은, 빛과 기판 모두에 카이랄 성을 부여하고 빛과 기판의 chiral matter-light coupling 현상을 이용하여 하나의 샘플로부터 많은 수의 데이터를 획득할 수 있으며, 동시에 데이터 품질 향상이 가능한 카이롭티컬 분광 플랫폼에 관한 것이다
Continual Learning: Forget-Free Winning Subnetworks for Video Representations
No full textInspired by the Lottery Ticket Hypothesis (LTH), which highlights the existence of efficient subnetworks within larger, dense networks, a high-performing Winning Subnetwork (WSN) in terms of task performance under appropriate sparsity conditions is considered for various continual learning tasks. It leverages pre-existing weights from dense networks to achieve efficient learning in Task Incremental Learning (TIL) and Task-agnostic Incremental Learning (TaIL) scenarios. In Few-Shot Class Incremental Learning (FSCIL), a variation of WSN referred to as the Soft subnetwork (SoftNet) is designed to prevent overfitting when the data samples are scarce. Furthermore, the sparse reuse of WSN weights is considered for Video Incremental Learning (VIL). The use of Fourier Subneural Operator (FSO) within WSN is considered. It enables compact encoding of videos and identifies reusable subnetworks across varying bandwidths. We have integrated FSO into different architectural frameworks for continual learning, including VIL, TIL, and FSCIL. Our comprehensive experiments demonstrate FSO's effectiveness, significantly improving task performance at various convolutional representational levels. Specifically, FSO enhances higher-layer performance in TIL and FSCIL and lower-layer performance in VIL.
APPARATUS AND METHOD FOR CONTROLLING BEAMFORMER IN A WIRELESS COMMUNICATION SYSTEM
No full text본 개시는 LTE(Long Term Evolution)와 같은 4G(4th generation) 통신 시스템 이후 보다 높은 데이터 전송률을 지원하기 위한 5G(5th generation) 또는 pre-5G 통신 시스템에 관련된 것이다. 다중 안테나를 이용하는 무선 통신 시스템에서 기지국의 동작 방법은, 전력 제한에 따라 스케일링 된 제1 빔포머에 기반하여, 상기 다중 안테나 중 전력 임계치를 만족하는 안테나를 결정하는 과정과, 상기 안테나와 연관된 제2 빔포머를 생성하는 과정과, 상기 제2 빔포머에 중첩 계수 행렬을 적용하는 과정과, 상기 중첩 계수 행렬이 적용된 상기 제2 빔포머와 상기 제1 빔포머를 합산하여 제3 빔포머를 생성하는 과정을 포함한다