Assessment of risk priorities by cause of construction safety accidents: A case study of falling accidents in South Korea.

In the construction industry, despite the development of technology and the efforts of companies, safety accidents are frequent, and the types of accidents are also diversified. In particular, when looking at the accident rates of the construction industry, the number of deaths from fall accidents accounts for a very high proportion. To resolve this, various measures to prevent fall, such as installation of safety railings and safety nets, have been proposed at the national level, but the effect is very insignificant.

The prevention and response to infectious diseases in long-term care facilities in Korea: a nationwide survey.

Objectives: Long-term care facilities (LTCFs) are communal environments for patients with chronic diseases or older adults, making them particularly susceptible to significant harm during infectious disease outbreaks. Nonetheless, LTCFs have historically been subject to less stringent infection prevention and control (IPC) mandates. This study aimed to assess the current state of LTCFs and to develop an IPC system tailored for these facilities following the coronavirus disease 2019 (COVID-19) pandemic.

Synthetic Data Enhancement and Network Compression Technology of Monocular Depth Estimation for Real-Time Autonomous Driving System.

Accurate 3D image recognition, critical for autonomous driving safety, is shifting from the LIDAR-based point cloud to camera-based depth estimation technologies driven by cost considerations and the point cloud's limitations in detecting distant small objects. This research aims to enhance MDE (Monocular Depth Estimation) using a single camera, offering extreme cost-effectiveness in acquiring 3D environmental data. In particular, this paper focuses on novel data augmentation methods designed to enhance the accuracy of MDE.

The Impact of the Emotional Responses of Korean Students Participating in School Sports.

Background: Physical education in schools improves students' health, physical strength, and lifelong physical engagement. Therefore, participation must be encouraged. This study aimed to investigate the relationship between emotional responses and participation satisfaction, word-of-mouth (WOM) praise, and WOM activity in students participating in school sports.

Optimal Configuration of Multi-Task Learning for Autonomous Driving.

For autonomous driving, it is imperative to perform various high-computation image recognition tasks with high accuracy, utilizing diverse sensors to perceive the surrounding environment. Specifically, cameras are used to perform lane detection, object detection, and segmentation, and, in the absence of lidar, tasks extend to inferring 3D information through depth estimation, 3D object detection, 3D reconstruction, and SLAM. However, accurately processing all these image recognition operations in real-time for autonomous driving under constrained hardware conditions is practically unfeasible.

The Structural Relationships among Academic Pressure, Independent Learning Ability, and Academic Self-Efficacy.

Background: The coronavirus disease pandemic has caused significant disruption in the field of education, resulting in the need for more online classes and a blended offline and online teaching model. Therefore, understanding what makes this model effective is important. Accordingly, this study explored the structural relationships among academic pressure, independent learning ability, and academic self-efficacy in a blended teaching environment during the pandemic and independent learning ability's mediating effect on the relationship between academic pressure and academic self-efficacy.

Rethinking Breast Cancer Diagnosis through Deep Learning Based Image Recognition.

This paper explored techniques for diagnosing breast cancer using deep learning based medical image recognition. X-ray (Mammography) images, ultrasound images, and histopathology images are used to improve the accuracy of the process by diagnosing breast cancer classification and by inferring their affected location. For this goal, the image recognition application strategies for the maximal diagnosis accuracy in each medical image data are investigated in terms of various image classification (VGGNet19, ResNet50, DenseNet121, EfficietNet v2), image segmentation (UNet, ResUNet++, DeepLab v3), and related loss functions (binary cross entropy, dice Loss, Tversky loss), and data augmentation.

A Method of Deep Learning Model Optimization for Image Classification on Edge Device.

Due to the recent increasing utilization of deep learning models on edge devices, the industry demand for Deep Learning Model Optimization (DLMO) is also increasing. This paper derives a usage strategy of DLMO based on the performance evaluation through light convolution, quantization, pruning techniques and knowledge distillation, known to be excellent in reducing memory size and operation delay with a minimal accuracy drop. Through experiments regarding image classification, we derive possible and optimal strategies to apply deep learning into Internet of Things (IoT) or tiny embedded devices.

Design and Evaluation of Korean Electropalatography (K-EPG).

Recently, the development of medical rehabilitation technology has resulted in an increased interest in speech therapy equipment. In particular, research on articulation therapy for communication disorders is being actively conducted. The existing methods for the diagnosis and treatment of speech disorders, such as traditional tactile perception tests and methods based on the empirical judgment of speech therapists, have many limitations.

Digital-Based Healthy Bra Top Design That Promotes the Physical Activity of New Senior Women by Applying an Optimal Pressure.

A bra use can reduce physiological and physical functions because of clothing pressure, which can be a problem for new senior women starting to lose physical function. The present study presents a bra top design development method for promoting new senior women's physical activity by identifying problems related to bras' effects on women's health and minimizing clothing pressure. The analysis utilized the 3D scan data of 42 adult women (age range: 50s) from the 5th Size Korea Project.

Automatic 360° Mono-Stereo Panorama Generation Using a Cost-Effective Multi-Camera System.

In recent years, 360° videos have gained the attention of researchers due to their versatility and applications in real-world problems. Also, easy access to different visual sensor kits and easily deployable image acquisition devices have played a vital role in the growth of interest in this area by the research community. Recently, several 360° panorama generation systems have demonstrated reasonable quality generated panoramas.

Direct perturbation of neural integrator by bilateral galvanic vestibular stimulation.

Caloric vestibular stimulation (CVS) and galvanic vestibular stimulation (GVS) act primarily on the peripheral vestibular system. Although the electrical current applied during GVS is thought to flow through peripheral vestibular organs, some current may spread into areas within the central nervous system, particularly when the bilateral galvanic vestibular stimulation (bGVS) method is used. According to Alexander's law, the magnitude of nystagmus increases with eccentric gaze movement, due to the function of the neural integrator (NI); thus, if the information for vestibular stimulation corresponds to Alexander's law, the peripheral vestibular organ is stimulated.