• The Journal of the Society of Korean Medicine Diagnostics
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• v.10 no.2
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• pp.121-131
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• 2006

Background : As each human has a look in the face of oneself, he or she has a look of him or herself in the shape of the body also. And for the shape of the body which gives a big clue in diagnosis in musculoskeletal disorders. Therefor many means are used and developed for diagnosis through body shape or posture analysis for musculoskeletal disorders. X-ray, CT, MRI has been used for diagnosis through image in this way to tell about the inside of the human body. On the other side, moire topography was used for information about the exterior of the human body, but yet only minimal information such as the number of contour lines in each side was available. Therefor there were a few studies to use moire topography or other methods to get information about the surface of the human body in numeric values. The instrument used in this study which is a laser projection moire, is another trial to get numeric data about the surface of the human body. The instrument is composed of laser projector and a computer software to recompose and analyse the image data into depth, height, angle and length. Objectives : The study was focused on whether the instrument is reliable for clinic use, and to seek the proper environment and posture for the examination, and among the data the software provides, which items are more reliable and useful. Methods : For reproductivity and repeatability, 4 testers tested 2 persons. And to how if the body shape changes according to the posture and which posture gives the most reliable data, the test was performed in 6 different positions. Results : Result, the instrument showed sufficient repeatability and reproductivity for clinical use. And among the items the software provides, the length of the back, the angle of the back in the sagittal and coronal plane showed reliable results. And there was difference in the results according to the posture, and Therefor, in following studies using this instrument or similar type of posture analysing instruments, the length of the back, the angle of the back in the sagittal and coronal plane could be reliable item to use.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.5
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• pp.133-138
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• 2022

Recently, as GPU performance has improved in HPC and artificial intelligence, its use is becoming more common, but GPU programming is still a big obstacle in terms of productivity. In particular, due to the difficulty of managing host memory and GPU memory separately, research is being actively conducted in terms of convenience and performance, and various CPU-GPU memory transfer programming methods are suggested. Meanwhile, recently many SoC (System on a Chip) products such as Apple M1 and NVIDIA Tegra that bundle CPU, GPU, and integrated memory into one large silicon package are emerging. In this study, data between CPU and GPU devices are used in such an integrated memory device and performance-related research is conducted during transmission. It shows different characteristics from the existing environment in which the host memory and GPU memory in the CPU are separated. Here, we want to compare performance by CPU-GPU data transmission method in NVIDIA SoC chips, which are integrated memory devices, and NVIDIA SMX-based V100 GPU devices. For the experimental workload for performance comparison, a two-dimensional matrix transposition example frequently used in HPC applications was used. We analyzed the following performance factors: the difference in GPU kernel performance according to the CPU-GPU memory transfer method for each GPU device, the transfer performance difference between page-locked memory and pageable memory, overall performance comparison, and performance comparison by workload size. Through this experiment, it was confirmed that the NVIDIA Xavier can maximize the benefits of integrated memory in the SoC chip by supporting I/O cache consistency.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.128-130
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• 2021

This study aims to implement a Regression Analysis system for predicting the appropriate production of flatfish. Due to Korea's signing of FTAs with countries around the world and accelerating market opening, Korean flatfish farming businesses are experiencing many difficulties due to the specificity and uncertainty of the environment. In addition, there is a need for a solution to problems such as sluggish consumption and price drop due to the recent surge in imported seafood such as salmon and yellowtail and changes in people's dietary habits. in this study, Using the python module, xlwings, it was used to obtain for the production amount of flatfish and to predict the amount of flatfish to be produced later. was used to predict the amount of flatfish to be produced in the future. Therefore, based on the analysis results of this prediction of flatfish production, the flatfish aquaculture industry will be able to come up with a plan to achieve an appropriate production volume and control supply and demand, which will reduce unnecessary economic loss and promote new value creation based on data. In addition, through the data approach attempted in this study, various analysis techniques such as artificial neural networks and multiple regression analysis can be used in future research in various fields, which will become the foundation of basic data that can effectively analyze and utilize big data in various industries.

• The Journal of Bigdata
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• v.8 no.1
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• pp.99-109
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• 2023

Recently, not only in Korea but also around the world, we have been experiencing constant disasters such as typhoons, wildfires, and heavy rains. The property damage caused by typhoons and heavy rain in South Korea alone has exceeded 1 trillion won. These disasters have resulted in significant loss of life and property damage, and the recovery process will also take a considerable amount of time. In addition, the government's contingency funds are insufficient for the current situation. To prevent and effectively respond to these issues, it is necessary to collect and analyze accurate data in real-time. However, delays and data loss can occur depending on the environment where the sensors are located, the status of the communication network, and the receiving servers. In this paper, we propose a two-stage hybrid situation analysis and prediction algorithm that can accurately analyze even in such communication network conditions. In the first step, data on river and stream levels are collected, filtered, and refined from diverse sensors of different types and stored in a bigdata. An AI rule-based inference algorithm is applied to analyze the crisis alert levels. If the rainfall exceeds a certain threshold, but it remains below the desired level of interest, the second step of deep learning image analysis is performed to determine the final crisis alert level.

• The Journal of the Convergence on Culture Technology
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• v.9 no.6
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• pp.1001-1006
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• 2023

Globally, rising energy costs and increased energy demand are important issues for the food processing and manufacturing industries, which consume significant amounts of energy throughout the supply chain. Accordingly, there is a need for the development of a real-time energy monitoring and analysis system that can optimize energy use. In this study, a food factory energy monitoring system was proposed based on IoT installed in a food factory, including monitoring of each facility, energy supply and usage monitoring for the heat treatment process, and search functions. The system is based on the IoT sensor of the food processing plant and consists of PLC, database server, OPC-UA server, UI server, API server, and CIMON's HMI. The proposed system builds big data for food factories and provides facility-specific monitoring through collection functions, as well as energy supply and usage monitoring and search service functions for the heat treatment process. This data collection-based energy monitoring system will serve as a guide for the development of a small and medium-sized factory energy monitoring and management system for energy savings. In the future, this system can be used to identify and analyze energy usage to create quantitative energy saving measures that optimize process work.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.6
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• pp.1121-1126
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• 2017

Recently, the importance of smart gateways that link these with the big data and the development of the Internet of things is getting bigger. The smart gateway includes a network function such as a router and a router, and a sensor network function that links various objects such as a sensor. As the internet market has expanded, network stability and security problems have arisen and VPN technology has been proposed as one of the ways to solve these security problems. Efficient design is needed to implement VPN in low-end smart gateway and SOHO-level Internet environment with poor line quality. In this paper, we propose the concept and principle of VPN tunneling implementation and real - time traffic shaping method according to internet line condition in the Smart Gateway that supports IOT developed based on OpenWRT, the implementation and measured performance indicators are presented.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.12
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• pp.1284-1289
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• 2014

In this Paper, outdoor position estimation system was implemented using GPS (Global Positioning System) and INS (Inertial Navigation System). GPS position information has lots of errors by interference from obstacles and weather, the surrounding environment. To reduce these errors, multiple GPS system is used. Also, the Discrete Wavelet Transforms was applied to INS data for compensation of its error. In this paper, position estimation of the mobile robot in the straight line is conducted by EKF (Extended Kalman Filter). However, curve running position estimation is less accurate than straight line due to phase change in rotation. The curve is recognized through the rate of change in heading angle and the position estimation precision of the initial curve was improved by UPF (Unscented Particle Filter). In the case of UPF, if the number of particle is so many that big memory gets size is needed and processing speed becomes late. So, it only used the position estimation in the initial curve. Thereafter, the position of mobile robot in curve is estimated through switching from UPF to EKF again. Through the experiments, we verify the superiority of the system and make a conclusion.

• Journal of the Korea Convergence Society
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• v.7 no.4
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• pp.9-17
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• 2016

This study is to analyze korea credit card market and the China credit card market, and predict future economic activity by developing the Algorithm for future economic trend Estimation As a results, there is no significant correlation between personal income growth and the credit card usage amount, and significant correlation between the credit card per capita and the credit card usage amount, in korea. there is significant correlation between personal income growth and the credit card usage amount, and between the credit card per capita and the credit card usage amount in china. it could be predicted that the china credit card market would be increased and the rate of increase would be gradually increased over the next five years, under the condition without constraints in the external environment.

• Journal of the Society of Disaster Information
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• v.16 no.2
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• pp.364-373
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• 2020

Purpose: Each local government has a variety of cultural spaces. However, users do not know exactly about cultural information or location. Therefore, information technology application methods are needed to effectively communicate the necessary information to local residents as well as to outsiders. In this paper, we studied the voluntary production of information for the sharing of local culture, and the methods for protecting the environment of the users themselves. Method: For this, information technology such as QR code, big data analysis, and interactive homepage based on SNS was used. Result: As a result, we derived a method of community creation by users, and the personal information protection from such activities. Conclusion: This research will contribute to the development of local culture by encouraging users to understand the local culture more and to participate in autonomous environmental improvement.

• The Journal of Korean Association of Computer Education
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• v.23 no.3
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• pp.71-79
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• 2020

This study investigates the rising issue of verbal violence at non-facing channels. Focus Group Interview(FGI) was conducted to examine verbal violence occurred during emotional labors in real-life cases. In addition, the distribution of verbal violence in the conversation was confirmed through a new big data technology called Speech Analysis(SA). The result findings highlighted the two perspectives as below. First, verbal violence occurred through calls, is classified into personal insult, swearing/verbal abuse, unreasonable demand, (sexual) harassment and intimidation/threat. Second, Speech Analysis result exhibited the most frequently appeared verbal violence were personal insult and swearing/verbal abuse. Informal language use and speaking in disrespectable manner was the highest rate in personal insult category. Moreover general cursing was the highest rate in swearing/verbal abuse category. In particular, the rate of using curse language was the highest in overall cases of verbal violence. This study summarizes the types of verbal violence that occur in non-facing channels and suggests a need for further investigation on how verbal stress affects working environment for emotional labor.