South Koreans' attitudes toward foreigners, minorities and multiculturalism

노트 : Paper prepared for presentation at the annual meeting of the American Sociological Association, Boston, MA from August 1-4, 2008

DBN-Mix: Training Dual Branch Network Using Bilateral Mixup Augmentation for Long-Tailed Visual Recognition

There is growing interest in the challenging visual perception task of learning from long-tailed class distributions. The extreme class imbalance in the training dataset biases the model to prefer recognizing majority class data over minority class data. Furthermore, the lack of diversity in minority class samples makes it difficult to find a good representation. In this paper, we propose an effective data augmentation method, referred to as bilateral mixup augmentation, which can improve the performance of long-tailed visual recognition. The bilateral mixup augmentation combines two samples generated by a uniform sampler and a re-balanced sampler and augments the training dataset to enhance the representation learning for minority classes. We also reduce the classifier bias using class-wise temperature scaling, which scales the logits differently per class in the training phase. We apply both ideas to the dual-branch network (DBN) framework, presenting a new model, named dual-branch network with bilateral mixup (DBN-Mix). Experiments on popular long-tailed visual recognition datasets show that DBN-Mix improves performance significantly over baseline and that the proposed method achieves state-of-the-art performance in some categories of benchmarks

Criterion validity of the Pittsburgh Sleep Quality Index: Investigation in a non-clinical sample

The objective of this study was to investigate the reliability and validity of the Pittsburgh Sleep Quality Index (PSQI) in a non-clinical sample consisting of younger and older adults. There has been little research validating the PSQI with respect to multinight recording as with actigraphy, and more validation is needed in samples not specifically selected for clinical disturbance. Also, the degree to which the PSQI scores may reflect depressive symptoms versus actual sleep disturbance remains unclear. One-hundred and twelve volunteers (53 younger and 59 older) were screened for their ability to perform treadmill exercises; inclusion was not based on sleep disturbance or depression. Internal homogeneity was evaluated by correlating PSQI component scores with the global score. Global and component scores were correlated with a sleep diary, actigraphy, and centers for epidemiological studies – depression scale scores to investigate criterion validity. Results showed high internal homogeneity. PSQI global score correlated appreciably with sleep diary variables and the depression scale, but not with any actigraphic sleep variables. These results suggest that the PSQI has good internal homogeneity, but may be less reflective of actual sleep parameters than a negative cognitive viewpoint or pessimistic thinking. The sleep complaints measured may often be more indicative of general dissatisfaction than of any specifically sleep-related disturbance

Computational Synthesis of Wearable Robot Mechanisms: Application to Hip-Joint Mechanisms

Since wearable linkage mechanisms could control the moment transmission from actuator(s) to wearers, they can help ensure that even low-cost wearable systems provide advanced functionality tailored to users' needs. For example, if a hip mechanism transforms an input torque into a spatially-varying moment, a wearer can get effective assistance both in the sagittal and frontal planes during walking, even with an affordable single-actuator system. However, due to the combinatorial nature of the linkage mechanism design space, the topologies of such nonlinear-moment-generating mechanisms are challenging to determine, even with significant computational resources and numerical data. Furthermore, on-premise production development and interactive design are nearly impossible in conventional synthesis approaches. Here, we propose an innovative autonomous computational approach for synthesizing such wearable robot mechanisms, eliminating the need for exhaustive searches or numerous data sets. Our method transforms the synthesis problem into a gradient-based optimization problem with sophisticated objective and constraint functions while ensuring the desired degree of freedom, range of motion, and force transmission characteristics. To generate arbitrary mechanism topologies and dimensions, we employed a unified ground model. By applying the proposed method for the design of hip joint mechanisms, the topologies and dimensions of non-series-type hip joint mechanisms were obtained. Biomechanical simulations validated its multi-moment assistance capability, and its wearability was verified via prototype fabrication. The proposed design strategy can open a new way to design various wearable robot mechanisms, such as shoulders, knees, and ankles.Comment: 28 pages, 7 figures, Supplementary Material

Effects of fibrin-binding oligopeptide on osteopromotion in rabbit calvarial defects

Purpose: Fibronectin (FN) has been shown to stimulate bone regeneration in animal models. The aim of this study was to evaluate the capacity of bovine bone mineral coated with synthetic oligopeptides to enhance bone regeneration in rabbit calvarial defects. Methods: Oligopeptides including fibrin-binding sequences of FN repeats were synthesized on the basis of primary and tertiary human plasma FN structures. Peptide coated and uncoated bone minerals were implanted into 10 mm calvarial defects in New Zealand white rabbits, and the animals were sacrificed at 4 or 8 weeks after surgery. After specimens were prepared, histologic examination and histomorphometric analysis were performed. Results: At 4 weeks after surgery, the uncoated groups showed a limited amount of osteoid formation at the periphery of the defect and the oligopeptide coated groups showed more osteoid formation and new bone formation in the center of the defect as well as at the periphery. At 8 weeks, both sites showed increased new bone formation. However, the difference between the two sites had reduced. Conclusions: Fibrin-binding synthetic oligopeptide derived from FN on deproteinized bovine bone enhanced new bone formation in rabbit calvarial defects at the early healing stage. This result suggests that these oligopeptides can be beneficial in reconstructing oral and maxillofacial deformities or in regenerating osseous bone defects. ⓒ 2010 Korean Academy of Periodontology.

EFFECTS OF THREE PREPARATORY MOVEMENTS ON SIDEWARD PROPULSIVE MOVEMENT

This study investigated the effects of three preparatory movements (squat, countermovement and hopping) on the sideward propulsive movement. Seven subjects were analyzed in 3-D to determine how fast they reacted to external signals, using three techniques, to reacl1 an aIming spot. The hopping and the countermovement types were considered better than the squat type in the propulsion. The hopping particularly showed the shortest duration from the external signal to take-off and also recorded high extension moments due to the pre-stretch mechanism for the push-off phase

Image-Object-Specific Prompt Learning for Few-Shot Class-Incremental Learning

While many FSCIL studies have been undertaken, achieving satisfactory performance, especially during incremental sessions, has remained challenging. One prominent challenge is that the encoder, trained with an ample base session training set, often underperforms in incremental sessions. In this study, we introduce a novel training framework for FSCIL, capitalizing on the generalizability of the Contrastive Language-Image Pre-training (CLIP) model to unseen classes. We achieve this by formulating image-object-specific (IOS) classifiers for the input images. Here, an IOS classifier refers to one that targets specific attributes (like wings or wheels) of class objects rather than the image's background. To create these IOS classifiers, we encode a bias prompt into the classifiers using our specially designed module, which harnesses key-prompt pairs to pinpoint the IOS features of classes in each session. From an FSCIL standpoint, our framework is structured to retain previous knowledge and swiftly adapt to new sessions without forgetting or overfitting. This considers the updatability of modules in each session and some tricks empirically found for fast convergence. Our approach consistently demonstrates superior performance compared to state-of-the-art methods across the miniImageNet, CIFAR100, and CUB200 datasets. Further, we provide additional experiments to validate our learned model's ability to achieve IOS classifiers. We also conduct ablation studies to analyze the impact of each module within the architecture.Comment: 8 pages, 4 figures, 4 table

Immature Gastric Teratoma in an Infant: A Case Report

Gastric teratomas are extremely rare neoplasms and almost exclusively benign. They occur predominantly in males and generally present as a palpable abdominal mass. To our knowledge, only one adult case has been described in the Korean literature. We report a case in which an immature gastric teratoma in a 3-month-old boy was revealed by CT and US