Sheena Kim;Jeongin Choi;Eun Sol Kim;Gi Beom Keum;Hyunok Doo;Jinok Kwak;Sumin Ryu;Yejin Choi;Sriniwas Pandey;Na Rae Lee;Juyoun Kang;Yujung Lee;Dongjun Kim;Kuk-Hwan Seol;Sun Moon Kang;In-Seon Bae;Soo-Hyun Cho;Hyo Jung Kwon;Samooel Jung;Youngwon Lee;Hyeun Bum Kim
Korean Journal of Agricultural Science
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v.50
no.4
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pp.809-815
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2023
This study was conducted to find out the correlation between meat quality and muscle fat ratio in pork part meat (pork belly and shoulder butt) using CT (computed tomography) imaging technique. After 24 hours from slaughter, pork loin and belly were individually prepared from the left semiconductors of 26 pigs for CT measurement. The image obtained from CT scans was checked through the picture archiving and communications system (PACS). The volume of muscle and fat in the pork belly and shoulder butt of cross-sectional images taken by CT was estimated using Vitrea workstation version 7. This assemblage was further processed through Vitrea post-processing software to automatically calculate the volumes (Fig. 1). The volumes were measured in milliliters (mL). In addition to volume calculation, a three-dimensional reconstruction of the organ under consideration was generated. Pearson's correlation coefficient was analyzed to evaluate the relationship by region (pork belly, pork shoulder butt), and statistical processing was performed using GraphPad Prism 8. The muscle-fat ratios of pork belly taken by CT was 1 : 0.86, while that of pork shoulder butt was 1 : 0.37. As a result of CT analysis of the correlation coefficient between pork belly and shoulder butt compared to the muscle-fat ratio, the correlation coefficient was 0.5679 (R2 = 0.3295, p < 0.01). CT imaging provided very good estimates of muscle contents in cuts and in the whole carcass.
Hyo Sub Jun;Kuhyun Yang;Jongyeon Kim;Jin Pyeong Jeon;Sun Jeong Kim;Jun Hyong Ahn;Seung Jin Lee;Hyuk Jai Choi;In Bok Chang;Jeong Jin Park;Jong-Kook Rhim;Sung-Chul Jin;Sung Min Cho;Sung-Pil Joo;Seung Hun Sheen;Sang Hyung Lee
Journal of Korean Neurosurgical Society
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v.67
no.4
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pp.385-396
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2024
Previously, we reported the concept of a cloud-based telemedicine platform for patients with intracerebral hemorrhage (ICH) at local emergency rooms in rural and medically underserved areas in Gangwon state by combining artificial intelligence and remote consultation with a neurosurgeon. Developing a telemedicine ICH treatment protocol exclusively for doctors with less ICH expertise working in emergency rooms should be part of establishing this system. Difficulties arise in providing appropriate early treatment for ICH in rural and underserved areas before the patient is transferred to a nearby hub hospital with stroke specialists. This has been an unmet medical need for decades. The available reporting ICH guidelines are realistically applicable in university hospitals with a well-equipped infrastructure. However, it is very difficult for doctors inexperienced with ICH treatment to appropriately select and deliver ICH treatment based on the guidelines. To address these issues, we developed an ICH telemedicine protocol. Neurosurgeons from four university hospitals in Gangwon state first wrote the guidelines, and professors with extensive ICH expertise across the country revised them. Guidelines and recommendations for ICH management were described as simply as possible to allow more doctors to use them easily. We hope that our effort in developing the telemedicine protocols will ultimately improve the quality of ICH treatment in local emergency rooms in rural and underserved areas in Gangwon state.
Mi ri Jeong;In Sook Lee;Yong Beom Shin;You Seon Song;Sekyoung Park;Jong Woon Song;Jin Il Moon
Journal of the Korean Society of Radiology
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v.81
no.1
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pp.176-189
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2020
Purpose To evaluate the clinical efficacy of real-time sonoelastography (RTS) for the follow-up of congenital muscular torticollis, based on measurements of muscle elasticity. Materials and Methods Thirty-four infants (23 male, 11 female) with congenital sternocleidomastoid (SCM) muscle torticollis underwent ultrasonography and elastography between November 2012 and December 2014. We evaluated the thickness, morphology (mass-like, fusiform, or overall thickened shape), and echogenicity of the SCM muscle on grayscale images and color patterns (homogeneous blue, mixed green < 50% and ≥ 50%, and green to red) on elastography. Strain ratios were measured using Q-lab software. A clinician classified the degree of neck rotation and side flexion deficits using a 5-point grade system based on angles of neck rotation and side flexion. Correlations between the ultrasonography and clinical findings were evaluated by statistical analysis. Results Twenty-two infants had right and 12 had left SCM torticollis, respectively. Linear regression analysis showed that involved/contralateral SCM thickness differences, morphology, elasticity color scores, and strain ratios of the affected SCM muscles were significantly correlated with neck rotation and side flexion deficit scores (p < 0.05). The elasticity color score of the affected SCM muscle was the most significant factor. Conclusion RTS might provide a reliable means for evaluating and monitoring congenital muscular torticollis.
Min Jae Cha;Don-Gwan An;Minsoo Kang;Hyue Mee Kim;Sang-Wook Kim;Iksung Cho;Joonhwa Hong;Hyewon Choi;Jee-Hyun Cho;Seung Yong Shin;Simon Song
Korean Journal of Radiology
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v.24
no.7
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pp.647-659
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2023
Objective: The study was conducted to investigate the effect of correct occlusion of the left atrial appendage (LAA) on intracardiac blood flow and thrombus formation in patients with atrial fibrillation (AF) using four-dimensional (4D) flow magnetic resonance imaging (MRI) and three-dimensional (3D)-printed phantoms. Materials and Methods: Three life-sized 3D-printed left atrium (LA) phantoms, including a pre-occlusion (i.e., before the occlusion procedure) model and correctly and incorrectly occluded post-procedural models, were constructed based on cardiac computed tomography images from an 86-year-old male with long-standing persistent AF. A custom-made closed-loop flow circuit was set up, and pulsatile simulated pulmonary venous flow was delivered by a pump. 4D flow MRI was performed using a 3T scanner, and the images were analyzed using MATLAB-based software (R2020b; Mathworks). Flow metrics associated with blood stasis and thrombogenicity, such as the volume of stasis defined by the velocity threshold ($\left|\vec{V}\right|$ < 3 cm/s), surface-and-time-averaged wall shear stress (WSS), and endothelial cell activation potential (ECAP), were analyzed and compared among the three LA phantom models. Results: Different spatial distributions, orientations, and magnitudes of LA flow were directly visualized within the three LA phantoms using 4D flow MRI. The time-averaged volume and its ratio to the corresponding entire volume of LA flow stasis were consistently reduced in the correctly occluded model (70.82 mL and 39.0%, respectively), followed by the incorrectly occluded (73.17 mL and 39.0%, respectively) and pre-occlusion (79.11 mL and 39.7%, respectively) models. The surfaceand-time-averaged WSS and ECAP were also lowest in the correctly occluded model (0.048 Pa and 4.004 Pa-1, respectively), followed by the incorrectly occluded (0.059 Pa and 4.792 Pa-1, respectively) and pre-occlusion (0.072 Pa and 5.861 Pa-1, respectively) models. Conclusion: These findings suggest that a correctly occluded LAA leads to the greatest reduction in LA flow stasis and thrombogenicity, presenting a tentative procedural goal to maximize clinical benefits in patients with AF.
An intelligent personal assistant (IPA) is a software agent that assists people to perform basic tasks or services for an individual by commonly providing information via natural language. In spite of the versatile capabilities of the IPA to answer a user's simple information-based queries, such as the weather and driving directions, the actual usage rates for IPA services are limited to date. In this research, to evaluate the factors affecting the intention to use IPA, we develop an empirical model based on technology acceptance model, innovation diffusion theory, and IS success model. Afterward, we collect 203 questionnaires from actual users of IPAs. Finally, the structural equation model validates the causal relationship between the constructs of the model. Consequently, the innovation characteristics of IPA drawn from innovation diffusion theory, namely, relative advantage, compatibility, observability, all exerted a positive influence on perceived usefulness. Furthermore, information quality, a quality characteristic of IPA obtained from DeLone and McLean's IS success model, presented a positive effect on perceived usefulness and perceived ease of use. Finally, the perceived intelligence of IPA displayed a positive influence on perceived usefulness and ease of use. This characteristic was also a major factor that can increase the intention to use the IPA. Given these research findings, this study is significant for identifying factors that may influence the intention to use the IPA by providing strategic guidelines to relevant business operators and establishing an integrated model.
As the service robot market grows among the food technology industry, the quality of robot service that affects consumer behavioral intentions in the restaurant industry has become important. Serving robots, which are common in restaurants, reduce employee work through order and delivery, but because they do not respond to service failures, they increase customer dissatisfaction as well as increase employee work. In order to improve the quality of service beyond the simple function of receiving and serving orders, functions of recovery effort, fairness, empathy, responsiveness, and certainty of the process after service failure, such as serving employees, are also required. Accordingly, we assumed the type of failure of restaurant serving service as two internal and external factors, and developed a serving robot with a vocational ethics module to respond with a professional ethical attitude when the restaurant serving service fails. At this time, the expression and action of the serving robot were developed by adding a failure mode reflecting failure recovery efforts and empathy to the normal service mode. And by recruiting college students, we tested whether the service robot's response to two types of service failures had a significant effect on evaluating the robot. Participants responded that they were more uncomfortable with service failures caused by other customers' mistakes than robot mistakes, and that the serving robot's professional ethical empathy and response were appropriate. In addition, unlike the robot's favorability, the evaluation of the safety of the robot had a significant difference depending on whether or not a professional ethical empathy module was installed. A professional ethical empathy response module for natural service failure recovery using generative artificial intelligence should be developed and mounted, and the domestic serving robot industry and market are expected to grow more rapidly if the Korean serving robot certification system is introduced.
The Journal of the Convergence on Culture Technology
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v.10
no.3
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pp.809-818
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2024
This paper proposes an action plan for local governments to safely utilize artificial intelligence technology in various local government policies. The proposed method analyzes cases of application of artificial intelligence-related laws and policies in Gyeonggi Province, Seoul City, and New York City, and then presents matters that local governments should consider when utilizing AI technology in their policies. This paper applies the AILocalism-Korea analysis methodology, which is a modified version of the AILocalsm analysis methodology[1] presented by TheGovLab at New York University. AILocalism-Korea is an analysis methodology created to analyze the current activities of each local government in the fields of legal system, public procurement, mutual cooperation, and citizen participation, and to suggest practical alternatives in each area. In this paper, we use this analysis methodology to present 9 action plans that local governments should take based on safe and reliable use of artificial intelligence. By utilizing various AI technologies through the proposed plan in local government policies, it will be possible to realize reliable public services.
Sheena Kim;Jeongin Choi;Eun Sol Kim;Gi Beom Keum;Hyunok Doo;Jinok Kwak;Sumin Ryu;Yejin Choi;Juyoun Kang;Haram Kim;Yeongjae Chae;Yujung Lee;Dongjun Kim;Kuk-Hwan Seol;Sun Moon Kang;Yunseok Kim;Pil Nam Seong;In-Seon Bae;Soohyun Cho;Hyo Jung Kwon;Samooel Jung;Youngwon Lee;Hyeun Bum Kim
Korean Journal of Agricultural Science
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v.51
no.2
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pp.187-192
/
2024
This research aimed to investigate the relationship between meat quality and muscle-to-fat ratio in specific cuts of pork (pork belly and Boston butt) utilizing magnetic resonance imaging (MRI). Twenty-eight pigs were selected, and 24 hours post-slaughter, pork belly and Boston butt samples were individually extracted from the left half carcass for MRI assessment. The MRI scans were reviewed using the Picture Archiving and Communications System. Muscle and fat volumes in the pork belly and Boston butt from the cross-sectional images captured by MRI were estimated using Vitrea workstation version 7. Subsequently, these data were processed using Vitrea post-processing software to automatically determine the volumes, measured in milliliters (mL). Additionally, a three-dimensional reconstruction of the organ being studied was generated. The relationship between regions (pork belly and Boston butt) was assessed using Pearson's correlation coefficient, and statistical analysis was conducted using Graph Pad Prism 8. The muscle-to-fat ratio determined by MRI for pork belly was 1 : 0.64, whereas for Boston butt it was 1 : 0.35. Results of comparing the muscle-fat ratio, the correlation coefficient between pork belly and Boston butt was found to be 0.6127 (R2 = 0.3754, p < 0.001) based on MRI analysis. As a result of measuring the muscle-to-fat ratio using MRI as a non-destructive approach, there was a positive correlation between the muscle-to-fat ratios of pork belly and Boston butt.
Since the release of Meta's Segment Anything Model (SAM), a large-scale vision transformer generation model with rapid image segmentation capabilities, several studies have been conducted to apply this technology in various fields. In this study, we aimed to investigate the applicability of SAM for water bodies detection and extraction using the QGIS Geo-SAM plugin, which enables the use of SAM with satellite imagery. The experimental data consisted of Compact Advanced Satellite 500 (CAS500)-1 images. The results obtained by applying SAM to these data were compared with manually digitized water objects, Open Street Map (OSM), and water body data from the National Geographic Information Institute (NGII)-based hydrological digital map. The mean Intersection over Union (mIoU) calculated for all features extracted using SAM and these three-comparison data were 0.7490, 0.5905, and 0.4921, respectively. For features commonly appeared or extracted in all datasets, the results were 0.9189, 0.8779, and 0.7715, respectively. Based on analysis of the spatial consistency between SAM results and other comparison data, SAM showed limitations in detecting small-scale or poorly defined streams but provided meaningful segmentation results for water body classification.
Exercises using a Balance Board (BB) are effective in developing balance, strengthening core muscles, and improving physical fitness and concentration. In particular, the Smart Balance Board (SBB), which integrates with various digital content, provides appropriate feedback compared to traditional balance boards, maximizing the effectiveness of the exercise. However, most systems only offer visual and auditory feedback, failing to evaluate the impact on user engagement, interest, and the accuracy of exercise postures. This study proposes an Immersive Smart Balance Board (I-SBB) that utilizes multiple sensors to enable training with various feedback mechanisms and precise postures. The proposed system, based on Arduino, consists of a gyro sensor for measuring the board's posture, a communication module for wired/wireless communication, an infrared sensor to guide the user's foot placement, and a vibration motor for tactile feedback. The board's posture measurements are smoothly corrected using a Kalman Filter, and the multi-sensor data is processed in real-time using FreeRTOS. The proposed I-SBB is shown to be effective in enhancing user concentration and engagement, as well as generating interest, by integrating with diverse content.
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