• Journal of Ginseng Research
• /
• v.48 no.3
• /
• pp.310-322
• /
• 2024

Background: Osteosarcopenia is a common condition characterized by the loss of both bone and muscle mass, which can lead to an increased risk of fractures and disability in older adults. The study aimed to elucidate the response of various mouse strains to treatment with Rg3, one of the leading ginsenosides, on musculoskeletal traits and immune function, and their correlation. Methods: Six Collaborative Cross (CC) founder strains induced muscle atrophy and bone loss with dexamethasone (15 mg/kg) treatment for 1 month, and half of the mice for each strain were orally administered Rg3 (20 mg/kg). Different responses were observed depending on genetic background and Rg3 treatment. Results: Rg3 significantly increased grip strength, running performance, and expression of muscle and bone health-related genes in a two-way analysis of variance considering the genetic backgrounds and Rg3 treatment. Significant improvements in grip strength, running performance, bone area, and muscle mass, and the increased gene expression were observed in specific strains of PWK/PhJ. For traits related to muscle, bone, and immune functions, significant correlations between traits were confirmed following Rg3 administration compared with control mice. The phenotyping analysis was compiled into a public web resource called Rg3-OsteoSarco. Conclusion: This highlights the complex interplay between genetic determinants, pathogenesis of muscle atrophy and bone loss, and phytochemical bioactivity and the need to move away from single inbred mouse models to improve their translatability to genetically diverse humans. Rg3-OsteoSarco highlights the use of CC founder strains as a valuable tool in the field of personalized nutrition.

• Journal of the Korea Convergence Society
• /
• v.8 no.1
• /
• pp.155-162
• /
• 2017

This paper suggests efficient learning improvement method of computer use instruction based on flipped learning. Traditional computer use classes were difficult to practice and collaborative with sufficient lectures. However, we used KOCW (Korea Open Courseware) as a footsteps in the class using the flipped learning method and learned in advance before entering the classroom. In the classroom, we conducted collaborative hands on class based on mutual discussion. After the instruction, we measured learning motivation and satisfaction by gender, grade, and major using the motivation test tool. The results showed that degree of attention awareness, perception of class relevance and perception of learning satisfaction were analyzed as 'very satisfied' and 'satisfied' more than 90%.

• Journal of Digital Convergence
• /
• v.13 no.9
• /
• pp.225-233
• /
• 2015

The convergence social app manufacturing platform for both demander and developer in worldwide provides a collective collaborative development approach. This platform can bring enhanced productivity with exchange of views among participants. If the assessment is not fair that many participants will leave the collective collaborative project. The previous studies verified the reliability of the evaluation based on statistical techniques. Because the previous studies did not consider the task performance of participants, do not reflect the feature of project tasks. So, the contribution scores of the participants can be distorted. In this study, we suggest the method for evaluating the development contributions value. This is considered the task performance of participants and involved the method of equitable and consistency peer assessment.

• Journal of Digital Convergence
• /
• v.10 no.6
• /
• pp.33-39
• /
• 2012

The purpose of this study is to investigate the effect of SNS(Social Network Service) on individual learning performance. To do this, we distribute and collect data by using a survey method. Research results suggest that online social networking engagement and acculturation have an effect on interaction quality with professors. Interaction quality with professors influences individual learning performance as well as collaborative learning. The conclusion and implications are discussed.

• Journal of Korea Multimedia Society
• /
• v.23 no.8
• /
• pp.1075-1087
• /
• 2020

Aviation ICT technology is a convergence technology between aviation and electronics, and has a wide variety of applications, including navigation and education. Among them, in the field of aerial pilot training, there are many problems such as the possibility of accidents during training and the lack of coping skills for various situations. This raises the need for a simulated pilot training system similar to actual training. In this paper, pilot training data were collected in pilot training system using VR/AR to increase immersion in flight training, and Customized Pilot Training Platform with Collaborative Deep Learning in VR/AR Environment that can recommend effective training courses to pilots is proposed. To verify the accuracy of the recommendation, the performance of the proposed collaborative deep learning algorithm with the existing recommendation algorithm was evaluated, and the flight test score was measured based on the pilot's training data base, and the deviations of each result were compared. The proposed service platform can expect more reliable recommendation results than previous studies, and the user survey for verification showed high satisfaction.

• Journal of Internet Computing and Services
• /
• v.11 no.6
• /
• pp.1-11
• /
• 2010

While a supply of GPS-enabled smartphone is increased, LBS which is studied and developed for special function is changed to personal solution. In this paper, we propose and implement on personalized method of individual LBS using collaborative filtering-based recommend system. Proposed personalized LBS system recommends contents which is expected to be interest for individual user, by predicting location-based contents within a user's setting radius. To evaluate performance of proposed system, we observed prediction accuracy with various experimental condition using our prototype. As a result, we confirmed that the convergence of collaborative filtering and LBS is effective for personalized LBS.

• The Journal of Korea Robotics Society
• /
• v.15 no.2
• /
• pp.177-183
• /
• 2020

Collaborative Robot (Cobot) that can collaborate with humans by fusion with many advanced technologies among industrial robots in the industrial field are attracting attention. In this study, the engineers of Small and Medium Enterprises can directly participate in the cobot design, and ultimately, the possibility of deriving the shape design of the differentiated cobot was studied. The method applied to derive the shape design of differentiated cobot is 'Morphological Analysis'. First, the design elements of the form of cobots were derived as 'Link' and 'Joint'. In addition, by analyzing the image form of the Link and Joint of the existing cobot, a new form element of the Link and Joint was proposed. In order to quantitatively identify the most discriminating cobot shape design, FGI (Focus Group Interview) was conducted to derive image types of 4 Link and 3 Joint. Then, the most important 'Shape Combination' was carried out in morphological analysis, and 12 new cobot shape designs were drawn. Through this, the applicability of the morphological analysis method in the derivation of differentiated cobot shape design was examined.

• Proceedings of the Korea Information Assurance Society Conference
• /
• 2004.05a
• /
• pp.119-124
• /
• 2004

The service oriented architecture (SOA) is gaining more momentum with the advent of Web services on internet. A programmable and machine accessible Web is the vision of many, and might represent a step towards the semantic Web. However, security is a crucial requirement for the serious usage and adoption of the Web services technology. This paper proposes design goals for an distributed access control model for CPC(Collaborative Product Commerce). It then design a processor model for CPC components, along with web services standard and concept that can be used as a basis to design an access control processor independent of a particular CPC service implementation.

• Journal of Ship and Ocean Technology
• /
• v.8 no.2
• /
• pp.41-60
• /
• 2004

Ship design process requires lots of complicated analyses for determining a large number of design variables. Due to its complexity, the process is divided into several tractable designs or analysis problems. The interdependent relationship requires repetitive works. This paper employs collaborative optimization (CO), one of the multidisciplinary design optimization (MDO) techniques, for treating such complex relationship. CO guarantees disciplinary autonomy while maintaining interdisciplinary compatibility due to its bi-level optimization structure. However, the considerably increased computational time and the slow convergence have been reported as its drawbacks. This paper proposes the use of an approximation model in place of the disciplinary optimization in the system-level optimization. Neural network classification is employed as a classifier to determine whether a design point is feasible or not. Kriging is also combined with the classification to make up for the weakness that the classification cannot estimate the degree of infeasibility. For the purpose of enhancing the accuracy of a predicted optimum and reducing the required number of disciplinary optimizations, an approximation management framework is also employed in the system-level optimization.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.6
• /
• pp.2282-2303
• /
• 2021

To solve the problems of heavy computing load and system transmission pressure in energy internet (EI), we establish a three-tier cloud-edge integrated EI network based on a cloud-edge collaborative computing to achieve the tradeoff between energy consumption and the system delay. A joint optimization problem for resource allocation and task offloading in the threetier cloud-edge integrated EI network is formulated to minimize the total system cost under the constraints of the task scheduling binary variables of each sensor node, the maximum uplink transmit power of each sensor node, the limited computation capability of the sensor node and the maximum computation resource of each edge server, which is a Mixed Integer Non-linear Programming (MINLP) problem. To solve the problem, we propose a joint task offloading and resource allocation algorithm (JTOARA), which is decomposed into three subproblems including the uplink transmission power allocation sub-problem, the computation resource allocation sub-problem, and the offloading scheme selection subproblem. Then, the power allocation of each sensor node is achieved by bisection search algorithm, which has a fast convergence. While the computation resource allocation is derived by line optimization method and convex optimization theory. Finally, to achieve the optimal task offloading, we propose a cloud-edge collaborative computation offloading schemes based on game theory and prove the existence of Nash Equilibrium. The simulation results demonstrate that our proposed algorithm can improve output performance as comparing with the conventional algorithms, and its performance is close to the that of the enumerative algorithm.