• Journal of Biosystems Engineering
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• v.15 no.3
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• pp.244-256
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• 1990

This study was conducted to select the optimal machinery systems for the Mechanized Farming Groups (MFG) by their sizes. In order to achieve the objective, a survey and systems analysis were taken for 50 MFG of Chungnam province. Then a mathematical model was developed. Based on it, a computer program (MFSDINGP) was developed by the Iterative Nonlinear Goal Programming (INGP) and Hooke & Jeeves pattern search algorithm. Using MFSDINGP, optimal machinery systems were selected and presented with annual costs of machinery for the sizes of 5-40 ha of MFG.

• Current Research on Agriculture and Life Sciences
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• v.15
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• pp.115-122
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• 1997

Grafting is an important skill for the stable supply and production of high quality. However, the shortage of skillful labor has become great difficulty for a mass production of grafting-seedling. In this study, a suitable mechanism for a grafting machine was developed. The following summarize the results of this study: 1. An insertion method was selected for mechanism of the grafting machine without bonding agent, clip, pin. This insertion-grafting method can be applicable to general vegetables and a mass production system. In addition to, this method is suitable for developing the grafting mechanism. 2. Growing point was removed while remaining both cotyledons on rootstock. The productivity of this system was five fold greater than the one of an experienced labor. 3. The rootstock processing was placed on left and scion processing unit was placed on right of the system, then processed rootstock and scion graft by rotating $180^{\circ}$. 4. The efficiency tests on mechanical grafting rate showed 98%.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.7
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• pp.773-778
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• 2011

Accelerometers are widely used to measure the lateral vibrations of pipe-like structures such as a gun tube under impulse loads. Stress waves that precede the lateral vibrations due to the explosion within a gun contribute little to the vibrations, but saturate the accelerometer input. A mechanical filter eliminates this high-frequency stress wave and only transmits the signal corresponding to the lateral vibrations. The mechanical filter consists of a mechanical structure for mounting the accelerometers and a damping material. The low-pass filter characteristics are determined from the equivalent damping and stiffness property of this damping material. In this paper, we tested nine commercially available damping materials for their vibration characteristics by using a test rig. We also observed the change in the vibration characteristics while compressing the material. We designed and manufactured a mechanical filter and verified its filtering performance.

• Journal of the Institute of Convergence Signal Processing
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• v.20 no.2
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• pp.78-83
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• 2019

Sounds based machine fault diagnosis recovers all the studies that aim to detect automatically abnormal sound on machines using the acoustic emission by these machines. Conventional methods that use mathematical models have been found inaccurate because of the complexity of the industry machinery systems and the obvious existence of nonlinear factors such as noises. Therefore, any fault diagnosis issue can be treated as a pattern recognition problem. We propose here an automatic fault diagnosis method of hand drills using discrete wavelet transform(DWT) and pattern recognition techniques such as artificial neural networks(ANN). We first conduct a filtering analysis based on DWT. The power spectral density(PSD) is performed on the wavelet subband except for the highest and lowest low frequency subband. The PSD of the wavelet coefficients are extracted as our features for classifier based on ANN the pattern recognition part. The results show that the proposed method can be effectively used not only to detect defects but also to various automatic diagnosis system based on sound.

• Journal of the Korean Society of Industry Convergence
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• v.21 no.5
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• pp.247-255
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• 2018

In this research, the effect of normal load, sliding velocity, and texture density on thefriction coefficient of surfaces micro-textured on AISI 4140 under paraffin oil lubrication were investigated. The predicted tribological behavior by numerical calculation can be serves as guidance for the designer during the machine development stage. Therefore, in this research friction coefficient prediction model based on response surface methodology (RSM), support vector machine (SVM), and artificial neural network (ANN) were developed. The experimental result shows that the variation of load, speed and texture density were influence the friction coefficient. The RSM, ANN and SVM model was successfully developed based on the experimental data. The ANN model can effectively predict the tribological characteristics of micro-textured AISI 4140 in paraffin oil lubrication condition compare to RSM and SVM.

• Journal of the Korean Society of Radiology
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• v.14 no.7
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• pp.937-946
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• 2020

The grating interferometer provides the differential phase contrast image of an phase object due to refraction of the wavefront by the object, and it needs to be converted to the phase contrast image. The line-integration process to obtain the phase contrast image from a differential phase contrast image accumulates noise and generate stripe artifacts. The stripe artifacts have noise and distortion increases to the integration direction in the line-integrated phase contrast image. In this study, we have configured and compared several machine learning methods to reduce the artifacts. The machine learning methods have been applied to simulated numerical phantoms as well as experimental data from the X-ray and neutron grating interferometer for comparison. As a result, the combination of the wavelet preprocessing and machine learning method (WCNN) has shown to be the most effective.

• Smart Media Journal
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• v.10 no.1
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• pp.25-31
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• 2021

As the machine learning becomes more common, development of application using machine learning is actively increasing. In addition, research on machine learning platform to support development of application is also increasing. However, despite the increasing of research on machine learning platform, research on suitable load balancing for machine learning platform is insufficient. Therefore, in this paper, we propose a load balancing scheme that can be applied to machine learning distributed environment. The proposed scheme composes distributed servers in a level hash table structure and assigns machine learning task to the server in consideration of the performance of each server. We implemented distributed servers and experimented, and compared the performance with the existing hashing scheme. Compared with the existing hashing scheme, the proposed scheme showed an average 26% speed improvement, and more than 38% reduced the number of waiting tasks to assign to the server.

• Korean Chemical Engineering Research
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• v.60 no.2
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• pp.289-294
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• 2022

Oil contained in domestic and industrial wastewater or marine spilled oil gives rise to severe environmental pollution issues such as water pollution and ecosystem destruction. The membrane filtration method as one of representative oil/water separation strategies has technological challenges such as membrane fouling and low separation rate. In this work, we devise a 3D-printed microhydrocyclone for oil/water separation by utilizing a digital lighting processing-based 3D printer. We demonstrate that the 3D-printed microhydrocyclone can effectively separate oil and water phases from oil-in-water emulsion.

• Journal of the Korea Convergence Society
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• v.13 no.2
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• pp.21-29
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• 2022

Based on the importance of dialect research, preservation, and communication, this paper conducted a study on machine translation of Korean dialects for dialect users who may be marginalized. For the dialect data used, AIHUB dialect data distributed based on the highest administrative district was used. We propose a many-to-one dialect machine translation that promotes the efficiency of model distribution and modeling research to improve the performance of the dialect machine translation by applying Copy mechanism. This paper evaluates the performance of the one-to-one model and the many-to-one model as a BLEU score, and analyzes the performance of the many-to-one model in the Korean dialect from a linguistic perspective. The performance improvement of the one-to-one machine translation by applying the methodology proposed in this paper and the significant high performance of the many-to-one machine translation were derived.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.433-440
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• 2022

Recently, owing to global warming, average summer temperatures are increasing and the number of hot days is increasing is increasing, which leads to an increase in heat stroke. In particular, outdoor workers directly exposed to the heat are at higher risk of heat stroke; therefore, preventing heat-related illnesses and managing safety have become important. Although various wearable devices have been developed to prevent heat stroke for outdoor workers, applying various sensors to the safety helmets that workers must wear is an excellent alternative. In this study, we developed a smart helmet that measures various vital signs of the wearer such as body temperature, heart rate, and sweat rate; external environmental signals such as temperature and humidity; and movement signals of the wearer such as roll and pitch angles. The smart helmet can acquire the various data by connecting with a smartphone application. Environmental data can check the status of heat wave advisory, and the individual vital signs can monitor the health of workers. In addition, we developed an algorithm that classifies the risk of heat-related illness as normal and abnormal by inputting a set of vital signs of the wearer using a support vector machine technique, which is a machine learning technique that allows for rapid binary classification with high reliability. Furthermore, the classified results suggest that the safety manager can supervise the prevention of heat stroke by receiving feedback from the control system.