• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.12 no.1
• /
• pp.413-419
• /
• 2011

Diagnosis X-ray equipment localized at 1950's but it is developed suddenly at 1960's with demand together. Manufacture of Diagnostic X-ray equipment is controled by the KS regulation and the Ministry of Health and Welfare because of hazardous element etc. exposure by radiation. Most of diagnostic X-ray equipment ware single phase and three phase full-wave rectification but from 1980's it transforms it was exchanged in inverter type X-ray equipment. Inverter type X-ray equipment produces approximately 50~80% more average photon intensity then single phase full-wave rectification and the accuracy is high. But from a clinic it dose not use because expensive therefor the efficiency improvement of single phase full-wave rectification is necessary. We produced single phase full-wave rectification X-ray equipment control unit, high tension transformer, filament heating transformer, rectification circuit, high tension cable and others and evaluated efficiency, in result which is excellent compare with Rule of Safety Management and KS regulation.

• Journal of Pharmaceutical Investigation
• /
• v.36 no.2
• /
• pp.89-95
• /
• 2006

A selective and sensitive reversed-phase HPLC method for the determination of pentoxifylline in human serum was developed, validated, and applied to the pharmacokinetic study of pentoxifylline. Pentoxifylline and internal standard, chloramphenicol, were extracted from the serum by liquid-liquid extraction with dichloromethane and analyzed on a Luna CI8(2) column with the mobile phase of acetonitrile-0.034 M phosphoric acid (25:75, v/v, adjusted to pH 4.0 with 10 M NaOH). Detection wavelength of 273 nm and flow rate of 0.8 mL/min were used. This method showed linear response over the concentration range of 10-500 ng/mL with correlation coefficients greater than 0.999. The lower limit of quantification using 0.5 mL of the serum was 10 ng/mL, which was sensitive enough for pharmacokinetic studies of pentoxifylline. The overall accuracy of the quality control samples ranged from 89.3 to 92.7% for pentoxifylline with overall precision (% C.V.) being 4.1-9.2%. The relative mean recovery of pentoxifylline for human serum was 105.8%. Stability (stock solution, short and long-term) studies showed that pentoxifylline was not stable during storage. But three freeze-thaw cycles and extracted serum samples were stable. This method showed good ruggedness (within 15% C.V.) and was successfully applied for the analysis of pentoxifylline in human serum samples for the pharmacokinetic studies of orally administered $Trental^{\circledR}$ tablet (400 mg pentoxifylline), demonstrating the suitability of the method.

• Journal of Pharmaceutical Investigation
• /
• v.37 no.4
• /
• pp.223-227
• /
• 2007

A rapid, simple and sensitive LC/MS/MS method for the determination of lercanidipine in human serum was validated and applied to the pharmacokinetic study of lercanidipine. Lercanidipine and internal standard, amlodipine, were extracted from human serum by liquid-liquid extraction with hexan-isoamyl alcohol (100: 1, v/v) and analyzed on a $Symmetry^{(R)}$ MS $C_{18}$ column with the mobile phase of acetonitrile-0.2% aqueous formic acid (70: 30, v/v). Using MS/MS with multiple reaction monitoring (MRM) mode, lercanidipine and amlodipine were detected without severe interferences from human serum matrix. Lercanidipine produced a protonated precursor ion ($[M+H]^+$) at m/z 612.3 and a corresponding product ion at m/z 280.0. Internal standard produced a protonated precursor ion ($[M+H]^+$]) at m/z 409.0 and a corresponding product ion at m/z 238.0. The ruggedness of this method was investigated using quality control (QC) samples. This method showed linear response over the concentration range of 0.05-20 ng/mL with correlation coefficient greater than 0.999. The lower limit of quantitation using 0.5 mL of serum was 0.05 ng/mL, which was sensitive enough for pharmacokinetic studies. The overall accuracy of the developed method ranged from 85.51 to 112.2% for lercanidipine with overall precision (% C.V.) being 3.56-13.1%. This method showed good ruggedness (within 15% C.V.) and was successfully applied for the analysis of lercanidipine in human serum samples for the pharmacokinetic studies, demonstrating the suitability of the method.

• Journal of Applied Biological Chemistry
• /
• v.57 no.1
• /
• pp.83-87
• /
• 2014

The effects of combined treatment of aqueous chlorine dioxide ($ClO_2$) and fumaric acid on the microbial growth in fresh-cut paprika were investigated. After the combined treatment, the populations of total aerobic bacteria and inoculated Listeria monocytogenes in the paprika sample were reduced by 0.82 and 1.21 log CFU/g, respectively, compared to those of the control. In addition, after 10 d of storage at $10^{\circ}C$, the populations were decreased by 1.21 and 2.10 log CFU/g, respectively. The predictive model for the populations of total aerobic bacteria and L. monocytogenes in the paprika was applied during storage. The prediction equation using Gompertz model was appropriate, based on the statistical analysis such as accuracy factor and bias factor. These results suggest that the combined treatment of aqueous $ClO_2$ and fumaric acid can be an effective technology for microbial decontamination and it can improve microbial safety by decreasing maximum growth rate and increasing lag time of bacteria in the fresh-cut paprika.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.18 no.1
• /
• pp.107-114
• /
• 2017

A turbocharger is an engine supercharger that is driven by exhaust gas. It improves the output and fuel efficiency by increasing the charging efficiency of the mixture gas, which is achieved by changing the rotatory power of the turbine connected to the exhaust passage. It is important to control the supercharging for this purpose. A nozzle slide joint is one of the core parts. Austenitic stainless steel is currently used as the material for this part, and its excellent mechanical properties include high heat resistance and corrosion resistance. However, because of its poor machinability, there are many difficulties in producing products with complicated shapes. Machining is used in the production of nozzle slide joints for high dimensional accuracy after metal powder injection molding. As design variables in this study, we investigated the sintering temperature, product stress, deformation rate, radius of curvature of the punch, and angle of the chamfer punch, which are related to the strain and shapes. The goal is to suggest a forming process using Nitronic 60 that does not require machining to manufacture a nozzle slide joint for a turbocharger. Accordingly, we determined the best process environment using finite-element analysis, the signal-noise ratio, and the Taguchi method for experiment design. The relative density and hydrostatic pressure of the final product were in accordance with the results of the finite element analysis. Therefore, we conclude that the Taguchi method can be applied to the design process of metal powder injection molding.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.21 no.8
• /
• pp.1-8
• /
• 2020

Air ducts installed for ventilation inside buildings accumulate contaminants during their service life. Robots are installed to clean the air duct at low cost, but they are still not fully automated and depend on manpower. In this study, an intersection detection algorithm for autonomous driving was applied to an air duct cleaning robot. Autonomous driving of the robot was achieved by calculating the distance and angle between the extracted point and the center point through the intersection detection algorithm from the camera image mounted on the robot. The training data consisted of CAD images of the duct interior as well as the cross-point coordinates and angles between the two boundary lines. The deep learning-based CNN model was applied as a detection algorithm. For training, the cross-point coordinates were obtained from CAD images. The accuracy was determined based on the differences in the actual and predicted areas and distances. A cleaning robot prototype was designed, consisting of a frame, a Raspberry Pi computer, a control unit and a drive unit. The algorithm was validated by video imagery of the robot in operation. The algorithm can be applied to vehicles operating in similar environments.

• Journal of Distribution Science
• /
• v.11 no.12
• /
• pp.39-49
• /
• 2013

Purpose - This study attempts to examine the underlying dimensions of service quality (tangibility, reliability, responsiveness, assurance, and empathy) for low-cost carriers. It subsequently seeks to determine the effect of the relationships of the dimensions of service quality, airline image, and behavioral intentions on airline services to provide adequate basic information and attributes for developing differentiated and competitive service marketing strategies. Research design, data, and methodology - The survey for this study was conducted on patrons with low-cost carrier boarding experiences in districts near universities and central businesses of Seoul and Busan from 5/10/2012 to 16/10/2012. Out of 346 questionnaires, 20 questionnaires with missing data and insincere answers were excluded for this study. Collected data were processed using SPSS 18.0, and the hypothesis was verified by analyzing the structural equation model with Lisrel 8.54. First, the frequency analysis was conducted to identify universal characteristics. Second, the exploratory factor analysis and reliability analysis were conducted to identify the accuracy of the variable measurements of the construct. Third, to assess uni-dimensionality and reliability, confirmatory factor analysis was conducted. Finally, to verify the adequacy of the research model and research hypothesis, the structural model was employed. Results - The results revealed that the factors, "tangibility, reliability, responsiveness, assurance, and empathy" were shown to be the most important dimensions of service quality for the airline image of the low-cost carrier which was consistent with previous studies. Therefore, it is fair to suggest that these verified factors are crucial attributes for the brand image of low-cost carriers. Second, as reliability and responsiveness were shown to be the most important factors for behavioral intentions, it is viable to suggest that these two attributes are crucial for the sales value of low-cost carriers. Further, it was found that the brand image of low-cost carriers was closely related to behavioral intentions. Therefore, in order to ensure the competitiveness and loyalty of patrons, the airline image value is a crucial attribute. Conclusions - The result of this study established that service quality is the most important attribute for marketing to ensure competitiveness, and intensive and differentiated service marketing play a crucial role in creating profits for low-cost carrier companies. First, as tangibility is found to be the most crucial factor in ensuring service quality, quality control and maintenance of medium and small carriers must be provided to ensure reliability, as they are the main attributes of low-cost carriers. Second, in order to promote positive behavioral intentions, it is essential to enhance the value of airline image. Third, in order to ensure competitiveness, it is imperative to carry out intensive and differentiated service marketing. Therefore, to promote the image of low-cost carriers and enhance behavioral intentions, the level of service quality must be secured by developing appropriate service improvement programs.

• Journal of Intelligence and Information Systems
• /
• v.24 no.1
• /
• pp.125-140
• /
• 2018

As one of the processes in the manufacturing industry, quality inspection inspects the intermediate products or final products to separate the good-quality goods that meet the quality management standard and the defective goods that do not. The manual inspection of quality in a mass production system may result in low consistency and efficiency. Therefore, the quality inspection of mass-produced products involves automatic checking and classifying by the machines in many processes. Although there are many preceding studies on improving or optimizing the process using the data generated in the production process, there have been many constraints with regard to actual implementation due to the technical limitations of processing a large volume of data in real time. The recent research studies on big data have improved the data processing technology and enabled collecting, processing, and analyzing process data in real time. This paper aims to propose the process and details of applying big data for quality inspection and examine the applicability of the proposed method to the dairy industry. We review the previous studies and propose a big data analysis procedure that is applicable to the manufacturing sector. To assess the feasibility of the proposed method, we applied two methods to one of the quality inspection processes in the dairy industry: convolutional neural network and random forest. We collected, processed, and analyzed the images of caps and straws in real time, and then determined whether the products were defective or not. The result confirmed that there was a drastic increase in classification accuracy compared to the quality inspection performed in the past.

• Journal of Advanced Navigation Technology
• /
• v.21 no.6
• /
• pp.554-560
• /
• 2017

Accurate altimetry is required for the reliable flight control of drones or unmanned air vehicles (UAVs), and the radar altimeter is commonly used owing to its accuracy for the ground level. Due to the limitation for size, weight and power consumption, the frequency modulated continuous wave (FMCW) radar is appropriate for drone because it has lower complexity than that of pulse Doppler (PD) radar. Especially, fast-ramp FMCW radar, which transmits linear FM signal during very short period, is generally utilized, because it is robust for the ego-motion of drone. Therefore, we present the design and implementation results of the radar signal processor (RSP) for fast-ramp FMCW radar system. The proposed RSP was designed with Verilog-HDL and implemented with Altera Cyclone-IV FPGA device. Implementation results show that the proposed RSP includes 27,523 logic elements, 15,798 registers and memory of 138Kbits and can measure the altimeter at the rate of 100Hz with the operating frequency of 50MHz.

• Korean Chemical Engineering Research
• /
• v.58 no.4
• /
• pp.588-595
• /
• 2020

Prediction and control of nitrogen oxides (NO_x) emission is of great interest in industry due to stricter environmental regulations. Herein, we propose an artificial intelligence (AI)-based framework for prediction of NO_x emission. The framework includes pre-processing of data for training of neural networks and evaluation of the AI-based models. In this work, Long-Short-Term Memory (LSTM), one of the recurrent neural networks, was adopted to reflect the time series characteristics of NO_x emissions. A decision tree was used to determine a time window of LSTM prior to training of the network. The neural network was trained with operational data from a heating furnace. The optimal model was obtained by optimizing hyper-parameters. The LSTM model provided a reliable prediction of NO_x emission for both training and test data, showing an accuracy of 93% or more. The application of the proposed AI-based framework will provide new opportunities for predicting the emission of various air pollutants with time series characteristics.