Yonsei University

About: Yonsei University is a education organization based out in Seoul, South Korea. It is known for research contribution in the topics: Population & Cancer. The organization has 50162 authors who have published 106172 publications receiving 2279044 citations. The organization is also known as: Yonsei.

Super-resolution image reconstruction

Abstract: The spatial resolution that represents the number of pixels per unit area in an image is the principal factor in determining the quality of an image. With the development of image processing applications, there is a big demand for high-resolution (HR) images since HR images not only give the viewer a pleasing picture but also offer additional detail that is important for the analysis in many applications. The current technology to obtain HR images mainly depends on sensor manufacturing technology that attempts to increase the number of pixels per unit area by reducing the pixel size. However, the cost for high-precision optics and sensors may be inappropriate for general purpose commercial applications, and there is a limitation to pixel size reduction due to shot noise encountered in the sensor itself. Therefore, a resolution enhancement approach using signal processing techniques has been a great concern in many areas, and it is called super-resolution (SR) (or HR) image reconstruction or simply resolution enhancement in the literature. In this issue, we use the term “SR image reconstruction” to refer to a signal processing approach toward resolution enhancement, because the term “super” very well represents the characteristics of the technique overcoming the inherent resolution limitation of low-resolution (LR) imaging systems. The term SR was originally used in optics, and it refers to the algorithms that mainly operate on a single image to extrapolate the spectrum of an object beyond the diffraction limit (SR restoration). These two SR concepts (SR reconstruction and SR restoration) have a common focus in the aspect of recovering high-frequency information that is lost or degraded during the image acquisition. However, the cause of the loss of high-frequency information differs between these two concepts. SR restoration in optics attempts to recover information beyond the diffraction cutoff frequency, while the SR reconstruction method in engineering tries to recover high-frequency components corrupted by aliasing. We hope that readers do not confuse the super resolution in this issue with the term super resolution used in optics. SR image reconstruction algorithms investigate the relative motion information between multiple LR images (or a video sequence) and increase the spatial resolution by fusing them into a single frame. In doing so, it also removes the effect of possible blurring and noise in the LR images. In summary, the SR image reconstruction method estimates an HR image with finer spectral details from multiple LR observations degraded by blur, noise, and aliasing. The major advantage of this approach is that it may cost less and the existing LR imaging systems can still be utilized. Considering the maturity of this field and its various prospective applications, it seems timely and appropriate to discuss and adjust the topic of SR in the special issue of the magazine, since we do not have enough materials for ready disposal. This special section contains five articles covering various aspects of SR techniques. The first article, “Super-Resolution Image Reconstruction: A Technical Overview” by Sungcheol Park, Minkyu Park, and Moon Gi Kang, provides an introduction to the concepts and definitions of the SR image reconstruction as well as an overview of various existing SR algorithms. Advanced issues that are currently under investigation in this area are also discussed. The second article, “High-Resolution Images from Low-Resolution Compressed Video,” by Andrew C. Segall, Rafael Molina, and Aggelos K. Katsaggelos, considers the SR techniques for compressed video. Since images are routinely compressed prior to transmission and storage in current acquisition systems, it is important to take into account the characteristics of compression systems in developing the SR techniques. In this article, they survey models for the compression system and develop SR techniques within the Bayesian framework. The third article, by Deepu Rajan, Subhasis Chaudhuri, and Manjunath V. Joshi, titled “Multi-Objective Super-Resolution Technique: Concept and Examples,”

Tokyo Guidelines 2018: flowchart for the management of acute cholecystitis.

Abstract: We propose a new flowchart for the treatment of acute cholecystitis (AC) in the Tokyo Guidelines 2018 (TG18). Grade III AC was not indicated for straightforward laparoscopic cholecystectomy (Lap-C). Following analysis of subsequent clinical investigations and drawing on Big Data in particular, TG18 proposes that some Grade III AC can be treated by Lap-C when performed at advanced centers with specialized surgeons experienced in this procedure and for patients that satisfy certain strict criteria. For Grade I, TG18 recommends early Lap-C if the patients meet the criteria of Charlson comorbidity index (CCI) ≤5 and American Society of Anesthesiologists physical status classification (ASA-PS) ≤2. For Grade II AC, if patients meet the criteria of CCI ≤5 and ASA-PS ≤2, TG18 recommends early Lap-C performed by experienced surgeons; and if not, after medical treatment and/or gallbladder drainage, Lap-C would be indicated. TG18 proposes that Lap-C is indicated in Grade III patients with strict criteria. These are that the patients have favorable organ system failure, and negative predictive factors, who meet the criteria of CCI ≤3 and ASA-PS ≤2 and who are being treated at an advanced center (where experienced surgeons practice). If the patient is not considered suitable for early surgery, TG18 recommends early/urgent biliary drainage followed by delayed Lap-C once the patient's overall condition has improved. Free full articles and mobile app of TG18 are available at: http://www.jshbps.jp/modules/en/index.php?content_id=47. Related clinical questions and references are also included.

An odyssey into virtual worlds: exploring the impacts of technological and spatial environments on intention to purchase virtual products

Abstract: Although research on three-dimensional virtual environments abounds, little is known about the social and business aspects of virtual worlds. Given the emergence of large-scale social virtual worlds, such as Second Life, and the dramatic growth in sales of virtual goods, it is important to understand the dynamics that govern the purchase of virtual goods in virtual worlds. Employing the stimulus-organism-response (S-O-R) framework, we investigate how technological (interactivity and sociability) and spatial (density and stability) environments in virtual worlds influence the participants' virtual experiences (telepresence, social presence, and flow), and how experiences subsequently affect their response (intention to purchase virtual goods). The results of our survey of 354 Second Life residents indicate that interactivity, which enhances the interaction with objects, has a significant positive impact on telepresence and flow. Also, sociability, which fosters interactions with participants, is significantly associated with social presence, although no such significant impact was observed on flow. Furthermore, both density and stability are found to significantly influence participants' virtual experiences; stability helps users to develop strong social bonds, thereby increasing both social presence and flow. However, contrary to our prediction of curvilinear patterns, density is linearly associated with flow and social presence. Interestingly, the results exhibit two opposing effects of density: while it reduces the extent of flow, density increases the amount of social presence. Since social presence is found to increase flow, the net impact of density on flow depends heavily on the relative strength of the associations involving these three constructs. Finally, we find that flow mediates the impacts of technological and spatial environments on intention to purchase virtual products. We conclude the paper with a discussion of the theoretical and practical contributions of our findings.

Ultrabright Luminescence from Gold Nanoclusters: Rigidifying the Au(I)-Thiolate Shell.

Abstract: Luminescent nanomaterials have captured the imagination of scientists for a long time and offer great promise for applications in organic/inorganic light-emitting displays, optoelectronics, optical sensors, biomedical imaging, and diagnostics. Atomically precise gold clusters with well-defined core–shell structures present bright prospects to achieve high photoluminescence efficiencies. In this study, gold clusters with a luminescence quantum yield greater than 60% were synthesized based on the Au22(SG)18 cluster, where SG is glutathione, by rigidifying its gold shell with tetraoctylammonium (TOA) cations. Time-resolved and temperature-dependent optical measurements on Au22(SG)18 have shown the presence of high quantum yield visible luminescence below freezing, indicating that shell rigidity enhances the luminescence quantum efficiency. To achieve high rigidity of the gold shell, Au22(SG)18 was bound to bulky TOA that resulted in greater than 60% quantum yield luminescence at room temperature. Optical mea...