• Journal of the Ergonomics Society of Korea
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• v.36 no.2
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• pp.109-121
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• 2017

Objective: This study aims to find suitable types and styles for gesture interaction as remote control on smart TVs. Background: Smart TV is being developed rapidly in the world, and gesture interaction has a wide range of research areas, especially based on vision techniques. However, most studies are focused on the gesture recognition technology. Also, not many previous studies of gestures types and styles on smart TVs were carried out. Therefore, it is necessary to check what users prefer in terms of gesture types and styles for each operation command. Method: We conducted an experiment to extract the target user manipulation commands required for smart TVs and select the corresponding gestures. To do this, we looked at gesture styles people use for every operation command, and checked whether there are any gesture styles they prefer over others. Through these results, this study was carried out with a process selecting smart TV operation commands and gestures. Results: Eighteen TV commands have been used in this study. With agreement level as a basis, we compared the six types of gestures and five styles of gestures for each command. As for gesture type, participants generally preferred a gesture of Path-Moving type. In the case of Pan and Scroll commands, the highest agreement level (1.00) of 18 commands was shown. As for gesture styles, the participants preferred a manipulative style in 11 commands (Next, Previous, Volume up, Volume down, Play, Stop, Zoom in, Zoom out, Pan, Rotate, Scroll). Conclusion: By conducting an analysis on user-preferred gestures, nine gesture commands are proposed for gesture control on smart TVs. Most participants preferred Path-Moving type and Manipulative style gestures based on the actual operations. Application: The results can be applied to a more advanced form of the gestures in the 3D environment, such as a study on VR. The method used in this study will be utilized in various domains.

• Proceedings of the Korea Contents Association Conference
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• 2006.11a
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• pp.856-859
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• 2006

Patient's position who muscle ache curer for hospital undergoes person entrance and treatment that take advantage of biological, physical force of low frequency and it is equipment that treat body muscle ache, but use equipment when use patient into compensation in hospital specially, that consider everybody is important first of all. This research question investigation with market survey of old product enforce because preference degree reflected officer a result and apply opinion tuned with product development connection engineers on DESIGN direction via typical product design development process close. This curer development research analyzed data involved directly taking advantage of FGI techniques with literature investigation collection. Investigation examined laying stress on muscle ache curer for hospital and a nurse than a doctor answered on question and purchase selection criterion or price portion to user focus. Direct market survey research that see item indicated by competition four provision shortcomings consequently in NEW MODEL development hereafter supplement and expectation. by contributing greatly in M/S security strategy hereafter because design development consisted for side that improve.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.12
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• pp.2975-2980
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. Detect this edge has been conducted in various fields at domestic and international. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, to complement this, preprocessing using gray-level transformation function and algorithm finding final edge using maximum and minimum value of estimated mask by local mask are proposed. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

• The Korean Journal of Physiology and Pharmacology
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• v.6 no.3
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• pp.131-138
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• 2002

Thanks to recent progress in availability of molecular and functional techniques it became possible to search for the basic molecular and cellular processes that mediate and control $HCO_3{^-}$ and fluid secretion by the pancreatic duct. The coordinated action of various transporters on the luminal and basolateral membranes of polarized epithelial cells mediates the transepithelial $HCO_3{^-}$ transport, which involves $HCO_3{^-}$ absorption in the resting state and $HCO_3{^-}$ secretion in the stimulated state. The overall process of HCO3 secretion can be divided into two steps. First, $HCO_3{^-}$ in the blood enters the ductal epithelial cells across the basolateral membrane either by simple diffusion in the forms of $CO_2$ and $H_2O$ or by the action of an $Na^+-coupled$ transporter, a $Na^+-HCO_3$ cotranporter (NBC) identified as pNBC1. Subsequently, the cells secrete $HCO_3{^-}$ to the luminal space using at least two $HCO_3{^-}$ exit mechanisms at the luminal membrane. One of the critical transporters needed for all forms of $HCO_3{^-}$ secretion across the luminal membrane is the cystic fibrosis transmembrane conductance regulator (CFTR). In the resting state the pancreatic duct, and probably other $HCO_3{^-}$ secretory epithelia, absorb $HCO_3{^-}.$ Interestingly, CFTR also control this mechanism. In this review, we discuss recent progress in understanding epithelial $HCO_3{^-}$ transport, in particular the nature of the luminal transporters and their regulation by CFTR.

• Journal of the Korean Society for Precision Engineering
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• v.32 no.5
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• pp.431-439
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• 2015

One of common challenges in designing modern production machines is realizing high speed motion without sacrificing accuracy. To address this challenge it is necessary to maximize the stiffness of the mechanical structure and the control system with consideration on the main disturbance input, cutting forces. This paper presents analysis technologies for realizing high stiffness in production machines. First, CAE analysis techniques to evaluate the dynamic stiffness of a machine structure and a new method to construct the physical machine model for servo controller simulations are demonstrated. Second, cutting forces generated in milling processes are analyzed to evaluate their effects on the mechatronics system. In the effort to investigate the interaction among the structure, controller, and process, a flexible multi-body dynamics simulation method is implemented on a magnetic bearing stage as an example. The presented technologies can provide better understandings on the mechatronics system and help realizing high stiffness production machines.

• Korean Journal of Poultry Science
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• v.28 no.2
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• pp.125-133
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• 2001

The goal of this paper was to examine the qualify zygote-acquiring method for in-vitro culture and the in-vitro culture method of the acquired zygote from a technological perspective. We have reported the results on the introduction of foreign DNAs using the described culturing method. After performing in-vitro and surrogate eggshell culture on a zygote acquired from the abdomen of a hen, 25.8% hatchability was acquired. After microinjecting foreign DNAs into the acquired zygote and performing in-vitro and surrogate eggshell culture using the same method, 13.1∼11.7% hatchability was acquired. Having compared the developments of the control subjects and the experimental subjects, the viability of the experimental subjects on the 4∼5th day of culturing was much lower compared to that of the control subjects. This is a result that shows that the microinjection process of foreign DNAs might have a negative effect on the existence of the embryo; therefore, various technical attempts should be made to minimize such negative effects. Having microinjected foreign DNAs into the zygote of a hen to produce transgenic chickens, 3 transgenic founders were Produced and 70 G1 progeny were produced as a result of the progeny test that had been performed to the present.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.19 no.8
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• pp.1867-1873
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• 2015

Edge detection is one of image processing techniques applied for a variety of purposes in a number of areas and it is used as a necessary pretreatment process in most applications. In the conventional edge detection methods, there are Sobel, Prewitt, Roberts and LoG, etc using a fixed weights mask. Since conventional edge detection methods apply the images to the fixed weights mask, the edge detection characteristics appear somewhat insufficient. Therefore in this study, an algorithm for detecting the edge is proposed by applying the cross mask based on the center pixel and up, down, left and right mask based on the surrounding pixels of center pixel in order to solve these problems. And in order to assess the performance of proposed algorithm, it was compared with a conventional Sobel, Roberts, Prewitt and LoG edge detection methods.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.6
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• pp.722-728
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• 2020

Digital image processing has been applied in a wide range of fields due to the development of IoT technology and plays an important role in data processing. Various techniques have been proposed to remove such noise, but the conventional impulse noise canceling methods are insufficient to remove noise of edge components of an image, and have a disadvantage of being greatly affected by random impulse noise. Therefore, in this paper, we propose an algorithm that effectively removes edge component noise in random impulse noise environment. The proposed algorithm calculates the threshold value by determining the noise level and switches the filtering process by comparing the reference value with the input pixel value. The proposed algorithm shows good performance in the existing method, and the simulation results show that the noise is effectively removed from the edge of the image.

• Journal of Korean Society of Disaster and Security
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• v.13 no.2
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• pp.65-75
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• 2020

The efficiency of sewage treatment was ananlyzed selecting a sewage treatment plant in Gyeonggi-do where A₂O process was applied. Statistical techniques based on the operation data of the sewage treatment were used. The main factors directly affecting the efficiency of the treatment process were analyzed using a GPS-X model. The correlation analysis and one-way ANOVA were performed. The T-N and NH₄⁺-N values of the effluent did not generate statistically significant level (p-value:>0.05) when compared with C/N ration values. Removel of nitrogen components form sewage treatment plants were affected by temperature, HRT, SRT and DO. In the case of BOD, all operating factors were affected, while COD was affecte by factors of HRT, STR and DO. In simulations using GPS-X, the parameters that greatly influence was included the maximum sedimentation rate, the dependent nutrient microbial yield (anoxic), the phosphorus saturation coefficient, the dependent nutrient microbial killing rate, the dependent nutrient microbial maximum growth rate, and the independent trophic microorganisms. The maximum growth rate and the maximum setting rate were identified.

• Journal of Korea Water Resources Association
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• v.57 no.3
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• pp.151-164
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• 2024

In water treatment plants supplying potable water, the management of chlorine concentration in water treatment processes involving pre-chlorination or intermediate chlorination requires process control. To address this, research has been conducted on water quality prediction techniques utilizing AI technology. This study developed an AI-based predictive model for automating the process control of chlorine disinfection, targeting the prediction of residual chlorine concentration downstream of sedimentation basins in water treatment processes. The AI-based model, which learns from past water quality observation data to predict future water quality, offers a simpler and more efficient approach compared to complex physicochemical and biological water quality models. The model was tested by predicting the residual chlorine concentration downstream of the sedimentation basins at Plant, using multiple regression models and AI-based models like Random Forest and LSTM, and the results were compared. For optimal prediction of residual chlorine concentration, the input-output structure of the AI model included the residual chlorine concentration upstream of the sedimentation basin, turbidity, pH, water temperature, electrical conductivity, inflow of raw water, alkalinity, NH₃, etc. as independent variables, and the desired residual chlorine concentration of the effluent from the sedimentation basin as the dependent variable. The independent variables were selected from observable data at the water treatment plant, which are influential on the residual chlorine concentration downstream of the sedimentation basin. The analysis showed that, for Plant, the model based on Random Forest had the lowest error compared to multiple regression models, neural network models, model trees, and other Random Forest models. The optimal predicted residual chlorine concentration downstream of the sedimentation basin presented in this study is expected to enable real-time control of chlorine dosing in previous treatment stages, thereby enhancing water treatment efficiency and reducing chemical costs.