• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.75-82
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• 2021

Mastitis in cows is a major factor that hinders dairy productivity of farms, and many attempts have been made to solve it. However, research on mastitis has been limited to diagnosis rather than prediction, and even this is mostly using a single sensor. In this study, a predictive model was developed using multivariate data including biometric data and environmental data. The data used for the analysis were collected from robot milking machines and sensors installed in farmhouses in Chungcheongnam-do, South Korea. The recurrent neural network model using three weeks of data predicts whether or not mastitis is diagnosed the next day. As a result, mastitis was predicted with an accuracy of 82.9%. The superiority of the model was confirmed by comparing the performance of various data collection periods and various models.

• Tribology and Lubricants
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• v.38 no.5
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• pp.185-190
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• 2022

Among the operating limits of a heat pipe, the capillary limit is significantly affected by the characteristics of the wick, which is determined by the capillary performance. The major parameters for determining capillary performance are the maximum capillary pressure and the spreading characteristics that can be expected through the wick. A well-designed wick structure improves capillary performance and helps improve the stability of the heat pipe by enhancing the capillary limit. The capillary performance can be improved by forming a porous microstructure on the surface of the wick structure through surface modification techniques. In this study, a microstructure is formed on the surface of the wick by using a surface modification method (i.e., an electrochemical etching process). In the experiment, specimens are prepared using stainless-steel screen mesh wicks with various fabrication conditions. In addition, the spreading and capillary rise performances are observed with low-surface-tension fluid to quantify the capillary performance. In the experiments, the capillary performance, such as spreading characteristics, maximum capillary pressure, and capillary rise rate, improves in the specimens with microstructures formed through surface modification compared with the specimens without microstructures on the surface. The improved capillary performance can have a positive effect on the capillary limit of the heat pipe. It is believed that the surface microstructures can enhance the operational stability of heat pipes.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.4
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• pp.679-686
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• 2022

In this paper, we implemented an algae removal device that recognizes and removes algae existing in water using Raspberry Pi camera and DO (Dissolved Oxygen) sensor. The Raspberry Pi board recognizes the color of green algae by converting the RGB values obtained from the camera into HSV. Through this, the location of the algae is identified and when the amount of dissolved oxygen's decrease at the location is more than the reference value using the DO sensor, the algae removal device is driven to spray the algae removal solution. Raspberry Pi's camera uses OpenCV, and the motor movement is controlled according to the output value of the DO sensor and the result of the camera's green algae recognition. Algae recognition and spraying of algae removal solution were implemented through Arduino and Raspberry Pi, and the feasibility of the proposed portable algae removal device was verified through experiments.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.2
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• pp.542-558
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• 2023

A digital focus index (DFI) is a value used to determine image focus in scientific apparatus and smart devices. Automatic focus (AF) is an iterative and time-consuming procedure; however, its processing time can be reduced using a general processing unit (GPU) and a multi-core processor (MCP). In this study, parallel architectures of a minimax search algorithm (MSA) are applied to two DFIs: range algorithm (RA) and image contrast (CT). The DFIs are based on a histogram; however, the parallel computation of the histogram is conventionally inefficient because of the bank conflict in shared memory. The parallel architectures of RA and CT are constructed using parallel reduction for MSA, which is performed through parallel relative rating of the image pixel pairs and halved the rating in every step. The array size is then decreased to one, and the minimax is determined at the final reduction. Kernels for the architectures are constructed using open source software to make it relatively platform independent. The kernels are tested in a hexa-core PC and an embedded device using Lenna images of various sizes based on the resolutions of industrial cameras. The performance of the kernels for the DFIs was investigated in terms of processing speed and computational acceleration; the maximum acceleration was 32.6× in the best case and the MCP exhibited a higher performance.

• Journal of the Korean Society of Industry Convergence
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• v.26 no.1
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• pp.193-199
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• 2023

In this study, an analysis was conducted to analyze the structural stability of the piezoelectric power generation module and to determine the optimal burying hole interval for concrete, the installation site of the power generation module. A piezoelectric element refers to a functional ceramic having a piezoelectric direct effect that converts mechanical energy into electrical energy and a piezoelectric reverse effect. In the analysis of the piezoelectric power generation module, the load condition was applied with about 16 tons and a total of 10 wheels in consideration of the container trailer. The purpose was to evaluate the stability of major components of the piezoelectric power generation module through finite element analysis. In order to determine the optimal burying location of the concrete ground for burying the piezoelectric power generation module, the stability of the ground structure according to the distance of the holes was determined. As a result of the analysis, the maximum stress of the piezoelectric power generation module was generated in the support spring, showing a stress of about 276.7 MPa. It was found that the spacing of holes for embedding the piezoelectric power generation module should be set to a minimum of 100 mm or more.

• Journal of the Korean institute of surface engineering
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• v.56 no.4
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• pp.233-242
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• 2023

In recent years, energy-management studies in buildings have proven useful for energy savings. Typically, during heating and cooling, the energy from a given building is lost through its windows. Generally, to block the entry of ultraviolet (UV) and infrared (IR) rays, thin films of deposited metals or metal oxides are used, and the blocking of UV and IR rays by these thin films depends on the materials deposited on them. Therefore, by controlling the thicknesses and densities of the thin films, improving the transmittance of visible light and the blocking of heat rays such as UV and IR may be possible. Such improvements can be realized not only by changing the two-dimensional thin films but also by altering the zero-dimensional (0-D) nanostructures deposited on the films. In this study, 0-D nanoparticles were synthesized using a sol -gel procedure. The synthesized nanoparticles were deposited as deep coatings on polymer and glass substrates. Through spectral analysis in the UV-visible (vis) region, thin-film layers of deposited zinc oxide nanoparticles blocked >95 % of UV rays. For high transmittance in the visible-light region and low transmittance in the IR and UV regions, hybrid multiple layers of silica nanoparticles, zinc oxide particles, and fluorine-doped tin oxide nanoparticles were formed on glass and polymer substrates. Spectrophotometry in the UV-vis-near-IR regions revealed that the substrates prevented heat loss well. The glass and polymer substrates achieved transmittance values of 80 % in the visible-light region, 50 % to 60 % in the IR region, and 90 % in the UV region.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.177-179
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• 2022

In the Google Deepmind Challenge match, Alphago defeated Korea's Sedol Lee (human) with 4 wins and 1 loss in the Go match. Finally, artificial intelligence is going beyond the use of human intelligence. The Korean government's budget for the Digital New Deal is 9 trillion won in 2022, and an additional 301 types of data construction projects for artificial intelligence learning will be secured. From 2023, the industrial paradigm will change with the use and application of learning of artificial intelligence in all fields of industry. This paper conducts research to utilize artificial intelligence algorithms. Focusing on the analysis and judgment of data in artificial intelligence learning, research on the appropriate target and scope of application of algorithms in artificial intelligence machine learning and deep learning learning is conducted. This study will provide basic data for artificial intelligence in the 4th industrial revolution technology and artificial intelligence robot use in the 5th industrial revolution technology.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.379-386
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• 2023

When patients suffer from finger injuries, their finger joints can become stiff and inflexible due to decreased ability to exercise the finger tendons. This can lead to a loss of strength and difficulty using their hands. To address this, it is important to provide patients with consistent rehabilitation treatment that can help restore finger flexibility and strength simultaneously. In this study, we propose wearable gloves that use FSRs (force sensitive resistors) for finger strength training. The glove is designed to be adjustable using rubber bands and a custom PCB is designed for signal acquisition. For the evaluation of finger strength training, the result was analyzed in four cases. We suggest a vector that represents the center of five finger forces, and the result shows that the vector can indicate the level of force balance.

• Fashion & Textile Research Journal
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• v.25 no.2
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• pp.248-254
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• 2023

This study aims to measure the skin rigidity of different facial areas among Koreans and propose guidelines for each area's skin rigidity that can be applied with a facial robot for testing respiratory protective devices. The facial skin rigidity of 40 participants, which included 20 men and 20 women, aged 20 to 50, was analyzed. The rigidity measurement was conducted in 13 facial areas, including six areas in contact with the mask and seven non-contact areas, by referring to the facial measurement guidelines of Size Korea. The facial rigidity was measured using the Durometer RX-1600-OO while in a supine position. The measurement procedure involved contacting the durometer vertically with the reference point, repeating the measurement of the same area five times, and using the average of three values whose variability was between 0.4 and 4.2 Shore OO. The rigidity data analysis used precision analysis, descriptive statistics analysis, and mixed-effect ANOVA. The analysis confirmed the rigidity of the 13 measurement areas, with the highest rigidity of the face being at the nose and forehead points, with values of 51.2 and 50.8, respectively, and the lowest rigidity being at the chin and center of the cheek points, with values of 19.2 and 20.7, respectively. Significant differences between gender groups were observed in four areas: the tip of the nose, the point below the chin, the area below the lower jaw, and the inner concha.

• Wind and Structures
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• v.36 no.6
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• pp.405-421
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• 2023

Strong wind is the main factors of wind-damage of high-rise buildings, which often creates largely economical losses and casualties. Wind pressure plays a critical role in wind effects on buildings. To obtain the high-resolution wind pressure field, it often requires massive pressure taps. In this study, two traditional methods, including bilinear and bicubic interpolation, and two deep learning techniques including Residual Networks (ResNet) and Generative Adversarial Networks (GANs), are employed to reconstruct wind pressure filed from limited pressure taps on the surface of an ideal building from TPU database. It was found that the GANs model exhibits the best performance in reconstructing the wind pressure field. Meanwhile, it was confirmed that k-means clustering based retained pressure taps as model input can significantly improve the reconstruction ability of GANs model. Finally, the generalization ability of k-means clustering based GANs model in reconstructing wind pressure field is verified by an actual engineering structure. Importantly, the k-means clustering based GANs model can achieve satisfactory reconstruction in wind pressure field under the inputs processing by k-means clustering, even the 20% of pressure taps. Therefore, it is expected to save a huge number of pressure taps under the field reconstruction and achieve timely and accurately reconstruction of wind pressure field under k-means clustering based GANs model.