• Proceedings of The Korean Society of Agricultural and Forest Meteorology Conference
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• 2013.11a
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• pp.28-29
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• 2013

We have been measuring $CH_4$ flux in a rice paddy in Gimje using the eddy covariance method since July 2011. In order to measure the fast fluctuations of $CH_4$ concentration, an innovative LI-7700 open-path laser spectrometer is used. This high-precision, low power, light weight, low maintenance sensor enables us to operate it on a continuous and long-term basis. One particular feature, among other things, is the self-cleaning lower mirror which decreases maintenance requirements while ensuring more robust, continuous, high-quality dataset. Its cleaning is initiated at user-specified time intervals or a signal strength threshold, and its status is recorded as a diagnostic index. We have noticed that the operation of LI-7700 at Gimje site is quite challenging particularly due to its frequent mirror cleaning requirement and the associated sensitivity of the instrument. In this presentation, we present some field observation data regarding the mirror cleaning and their analysis, thereby suggesting the pertinent operation options for high-quality, maximum data retrieval in the field.

• Journal of the Korea Society of Computer and Information
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• v.26 no.10
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• pp.139-145
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• 2021

In this paper, by using the cattle feed intake, rumination, and in heat monitoring technology, RFI (Residual Feed Intake) monitoring and wearable devices and PCs for predicting abnormalities in budding target web and smart A monitoring system using a phone application was designed and implemented. With the development of this system, the farmer is expected to increase economic efficiency. By analyzing the feed intake, it is possible to identify the difference between the recommended feed amount based on the cow's weight and the feed amount consumed by the cow, and it is expected that early detection of metabolic disorders (abnormality of metabolism) is possible. Farmers using the results of this thesis can distinguish the cows with the most efficient performance, and the 6-axis motion sensor signals input from the wearable device attached to the cow's skin (neck) and the microphone attached to the wearable device. It is possible to measure the cow's rumination and feed intake through the sound of the cow's throat. In the future, improvements will be made to measure additional vital signs such as heart rate and respiration.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.10a
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• pp.687-689
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• 2014

Due to the development of health promotion and health care technology of smartphones paradigm from treatment to manage change, and this is increasing the fitness in time for the user. However, fitness club, users find the right exercise law-personal trainer must be costly to pay companies describes the management system is required in order to operate the high costs strain. In this paper, such as scalable servers to OpenWrt Fonera is mainly based on the client to configure the server iOS mobile sensors collect a user's movement through the history of the user's input. This data is sent to the Web and check whether the receiving system via a trainer is to record the users through weight training and to receive feedback.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.5
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• pp.969-976
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• 2019

A lightweight artificial intelligence hardware has made great strides in many application areas. In general, a lightweight artificial intelligence system consist of lightweight artificial intelligence engine and preprocessor including feature selection, generation, extraction, and normalization. In order to achieve optimal performance in broad range of applications, lightweight artificial intelligence system needs to choose a good preprocessing function and set their respective hyper-parameters. This paper proposes a unified framework for a lightweight artificial intelligence system and utilization method for finding models with optimal performance to use on a given dataset. The proposed unified framework can easily generate a model combined with preprocessing functions and lightweight artificial intelligence engine. In performance evaluation using handwritten image dataset and fall detection dataset measured with inertial sensor, the proposed unified framework showed building optimal artificial intelligence models with over 90% test accuracy.

• Korean Journal of Applied Biomechanics
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• v.31 no.2
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• pp.140-147
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• 2021

Objective: The purpose of this study is to identify the mechanism of changes in maximum voluntary torque with the magnitude and duration of pre-activation torque during voluntary isometric knee extension. Method: 11 male subjects (age: 25.91±2.43 yrs., height: 173.12±3.51 cm, weight: 76.45±7.74 kg) participated in this study. The subjects were required to produce maximal voluntary isometric torque with a particular pre-activation torque condition. The properties of pre-activation torque consisted of the combinations of 1) three levels of magnitude, e.g., 32 Nm, 64 Nm, 96 Nm, and 2) two levels of duration, e.g., 1 sec, and 3 sec; thus, a total of six conditions were given to the subjects. The force and EMG data were measured using the force transducers and wireless EMG sensor, respectively. Results: The results showed that the maximum voluntary torque increased the most with relatively large and fast (96 Nm, 1 sec) pre-activation condition. Similarly, with relatively large and fast (96 Nm, 1 sec) preactivation, it was found that the integrated EMG (iEMG) of the agonist muscles increased, while no significant changes in the co-contraction of the antagonist muscles for the knee extension. Also, the effect of pre-activation conditions on the rate of torque development was not statistically significant. Conclusion: The current findings suggest that relatively larger in magnitude and shorter in duration as the properties of pre-activation lead to a larger magnitude of maximal voluntary torque, possibly due to the increased activity of the agonist muscles during knee extension.

• Journal of radiological science and technology
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• v.43 no.6
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• pp.481-487
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• 2020

Radiation measurement technology has steadily improved and its usage is expanding in various industries such as nuclear medicine, security search, satellite, nondestructive testing, environmental industries and the domain of nuclear power plants (NPPs). Especially, the simultaneous measurements of gamma rays and neutrons can be even more critical for nuclear safety management of spent nuclear fuel and monitoring of the nuclear material. A semiconductor detector comprising cadmium, zinc, and tellurium (CZT) enables to detect gamma-rays due to the significant atomic weight of the elements via immediate neutron and gamma-ray detection. Semiconductor sensors might be used for nuclear safety management by monitoring nuclear materials and spent nuclear fuel with high spatial resolution as well as providing real-time measurements. We aim to introduce a portable nuclide-analysis device that enables the simultaneous measurements of neutrons and gamma rays using a CZT sensor. The detector has a high density and wide energy band gap, and thus exhibits highly sensitive physical characteristics and characteristics are required for performing neutron and gamma-ray detection. Portable nuclide-analysis device is used on NPP-decommissioning sites or the purpose of nuclear nonproliferation, it will rapidly detect the nuclear material and provide radioactive-material information. Eventually, portable nuclide-analysis device can reduce measurement time and economic costs by providing a basis for rational decision making.

• Fashion & Textile Research Journal
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• v.23 no.1
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• pp.98-105
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• 2021

This study investigates and analyzes user preferences for golf wear with a sense of wear and smart function for the development of smart golf wear based on user convenience. A survey was conducted on 124 males in the age range of 40-60s that consisted of professional golfers, amateur golfers and the public with golf experience (such as major golf consumers) from August 1 to August 30, 2019 (IRB NO. 1040198-190617-HR-057-03); consequently, a 117 copies were accepted for analysis. The findings are as follows. The elbow (4.3%) of golf wear is unsatisfactory. The important part of the golf swing motion is the shoulder (39.3)>, elbow (30.8%)>, and wrist (6.8%). In addition, the unsatisfactory wearing of golf wear due to golf swing movements indicated that the shoulder or elbow area was pulled or the bottom of the top was raised during the back swing movements. The survey results on the expected discomfort when wearing smart wear are 'discomfort of obstruction when wearing' (53.8%), 'discomfort of washing' (17.1%), and 'weight of attached machine' (13.7%). Opinions such as 'Will not feel good when the sensor is attached' were investigated. The examination of the preference for golf wear equipped with smart functions indicated that a posture correction function to correct the golf swing posture is the most desired quality that is also considered important when correcting posture.

• PNF and Movement
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• v.20 no.3
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• pp.431-441
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• 2022

Purpose: The purpose of this study was to compare the changes in the contact area, maximum pressure, maximum mean pressure, and maximum force of functional insoles and general insoles when walking. Methods: Foot pressure was measured by the ignition of functional insoles and general insoles on Company N shoes. The foot pressure was measured using a precision pressure distribution meter (Pedar - X mobile system, Novel, Germany). Each insole sensor contained 99 independent cells and was inserted between the foot and the shoe. A wireless Bluetooth-type program was used to measure the pressure detected by the measuring insoles. In order to eliminate adaptation and fatigue caused by wearing the guide during the experiment, sufficient rest was taken between each experiment, and the wearing order was randomly selected. Results: Functional insole significantly increased the forefoot and midfoot (medial, lateral) (p<0.05), while total foot, forefoot, and rearfoot peak pressure significantly decreased (p < 0.05) compared to the general insole. Conclusion: In the functional insole, a high contact area was measured inside, even in the middle of the foot, leading to a proper change in foot pressure. It was confirmed that the contact area was reduced and dispersion occurred well. In addition, it was found that the maximum pressure in the front and back of the entire foot was reduced, so the weight pressure dispersion in the functional insole was evenly distributed, and the maximum average pressure change was similar.

• Journal of Advanced Navigation Technology
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• v.27 no.1
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• pp.111-118
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• 2023

For the implementation of a smart factory, it is necessary to collect data by connecting various sensors and devices in the manufacturing environment and to diagnose or predict failures in production facilities through data analysis. In this paper, to predict the residual useful lifetime of milling insert used for machining products in CNC machine, weight k-NN algorithm, Decision Tree, SVR, XGBoost, Random forest, 1D-CNN, and frequency spectrum based on vibration signal are investigated. As the results of the paper, the frequency spectrum does not provide a reliable criterion for an accurate prediction of the residual useful lifetime of an insert. And the weighted k-nearest neighbor algorithm performed best with an MAE of 0.0013, MSE of 0.004, and RMSE of 0.0192. This is an error of 0.001 seconds of the remaining useful lifetime of the insert predicted by the weighted-nearest neighbor algorithm, and it is considered to be a level that can be applied to actual industrial sites.

• Journal of Advanced Navigation Technology
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• v.27 no.2
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• pp.182-189
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• 2023

Depth estimation is a key technology in 3D map generation for autonomous driving of vehicles, robots, and drones. The existing sensor-based method has high accuracy but is expensive and has low resolution, while the camera-based method is more affordable with higher resolution. In this study, we propose self-attention-based unsupervised monocular depth estimation for UAV camera system. Self-Attention operation is applied to the network to improve the global feature extraction performance. In addition, we reduce the weight size of the self-attention operation for a low computational amount. The estimated depth and camera pose are transformed into point cloud. The point cloud is mapped into 3D map using the occupancy grid of Octree structure. The proposed network is evaluated using synthesized images and depth sequences from the Mid-Air dataset. Our network demonstrates a 7.69% reduction in error compared to prior studies.