Junhee KIM

A full-scale experimental program was used in this study to investigate the structural behavior of novel insulated concrete sandwich wall panels (SWPs) reinforced with grid-type glass-fiber-reinforced polymer (GFRP) shear connectors. Two kinds of insulation-expanded polystyrene (EPS) and extruded polystyrene (XPS) with 100 mm thickness were incased between the two concrete wythes to meet the increasing demand for the insulation performance of building envelope. One to four GFRP shear grids were

A full-scale experimental test was conducted to analyze the composite behavior of insulated concrete sandwich wall panels (ICSWPs) subjected to wind pressure and suction. The experimental program was composed of three groups of ICSWP specimens, each with a different type of insulation and number of glass-fiber-reinforced polymer (GFRP) shear grids. The degree of composite action of each specimen was analyzed according to the load direction, type of the insulation, and number of GFRP shear grids

The aim of this study was to remove 5-hydroxymethyl furfural (5-HMF) and furfural, known as fermentation inhibitors, in acid pretreated hydrolysates (APH) obtained from Scenedesmus obliquus using activated carbon. Microwave-assisted pretreatment was used to produce APH containing glucose, xylose, and fermentation inhibitors (5-HMF, furfural). The response surface methodology was applied to optimize key detoxification variables such as temperature (16.5–58.5 °C), time (0.5–5.5 h), and solid–liqui

Existing vision-based displacement sensors (VDSs) extract displacement data through changes in the movement of a target that is identified within the image using natural or artificial structure markers. A target-less vision-based displacement sensor (hereafter called "TVDS") is proposed. It can extract displacement data without targets, which then serve as feature points in the image of the structure. The TVDS can extract and track the feature points without the target in the image through image

AIM: As the size of the elderly population gradually increases, musculoskeletal disorders, such as sarcopenia, are increasing. Diagnostic techniques such as X-rays, computed tomography, and magnetic resonance imaging are used to predict and diagnose sarcopenia, and methods using machine learning are gradually increasing. This study aimed to create a model that can predict sarcopenia using physical characteristics and activity-related variables without medical diagnostic equipment, such as imagin

Abstract Background The ChatGPT is an artificial intelligence chatbot that processes natural language text learned through reinforcement learning based on the GPT-3.5 architecture, a large-scale language model. Natural language processing models are being used in various fields and are gradually expanding their use in the medical field. Purpose This study aimed to investigate the medical information and treatment options that ChatGPT can provide for SIS. Method Using ChatGPT, which is provided a

This article proposes a statistical framework for the development of design models for concrete sandwich panels with glass-fiber-reinforced polymer shear grids. The framework is developed by integrating the Bayesian parameter estimation method and the Eurocode-based capacity reduction factor calibration method. In the first part of the framework, probabilistic and deterministic shear flow prediction models are proposed based on 32 experimental data. It is seen that the contribution of glass-fibe

This study analyzed the trends and characteristics of shoulder rehabilitation research through keyword analysis, and their relationships were modeled using text mining techniques.