• Food Engineering Progress
• /
• v.23 no.2
• /
• pp.87-93
• /
• 2019

Temperature distribution studies were performed in steam-air retort to investigate the influence of various processing conditions (come-up time, sterilization temperature, and internal pressure throughout the steam-air retort). Retort temperature data were analyzed for temperature deviations during holding phase, maximum temperature difference between test locations at the beginning and after 1, 3, and 5 min of the holding phase, and box-and-whiskers plots for each location during the holding phase. The results showed that high sterilization temperature led to a more uniform temperature distribution than low sterilization temperature (pasteurization). In pasteurization condition, the temperature stability was slightly increased by increasing pressure during the holding phase. On the other hand, the temperature stability was slightly decreased in high sterilization temperature condition. Programming of the come-up phase did not affect the temperature uniformity. In addition, the slowest cold spot was found at the bottom floor during the holding phase in all conditions. This study determined that the temperature distribution is affected by retort processing conditions, but the steam-air retort needs more validation tests for temperature stability.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.15 no.5
• /
• pp.1610-1629
• /
• 2021

Failures frequently occurred in manufacturing machines due to complex and changeable manufacturing environments, increasing the downtime and maintenance costs. This manuscript develops a novel deep learning-based method named Multi-Domain Convolutional Neural Network (MDCNN) to deal with this challenging task with vibration signals. The proposed MDCNN consists of time-domain, frequency-domain, and statistical-domain feature channels. The Time-domain channel is to model the hidden patterns of signals in the time domain. The frequency-domain channel uses Discrete Wavelet Transformation (DWT) to obtain the rich feature representations of signals in the frequency domain. The statistic-domain channel contains six statistical variables, which is to reflect the signals' macro statistical-domain features, respectively. Firstly, in the proposed MDCNN, time-domain and frequency-domain channels are processed by CNN individually with various filters. Secondly, the CNN extracted features from time, and frequency domains are merged as time-frequency features. Lastly, time-frequency domain features are fused with six statistical variables as the comprehensive features for identifying the fault. Thereby, the proposed method could make full use of those three domain-features for fault diagnosis while keeping high distinguishability due to CNN's utilization. The authors designed massive experiments with 10-folder cross-validation technology to validate the proposed method's effectiveness on the CWRU bearing data set. The experimental results are calculated by ten-time averaged accuracy. They have confirmed that the proposed MDCNN could intelligently, accurately, and timely detect the fault under the complex manufacturing environments, whose accuracy is nearly 100%.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.22 no.1
• /
• pp.424-430
• /
• 2021

Determining the cause of a traffic signal violation is difficult if the drivers' claims are contradictory. In this study, the process of identifying signal violations using a simulation was presented based on cases. First, statements from the driver or witness whose cause of the signal violation is unclear were excluded. Second, the final position, final location, damaged area, steering status, braking status, and road surface traces of the vehicle were collected. The impact point was investigated from the stop line. Third, simulation data were modified and entered until the collision situation of the accident vehicle and the final stop position were met. Fourth, if the simulation results were consistent with the crash situation, the facts were verified by cross-validation to conform to the driver's statement. The results of the simulation showed that the Lexus entered the left turn signal in the intersection at approximately 55 km/h. In comparison, the Sonata driver saw the vehicle straight ahead at the intersection, entered the 72 km/h intersection, and collided with the Lexus. Therefore, the Sonata was identified as a signal violation, and the claims of the Sonata driver, witnesses, and police were contradictory.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.6
• /
• pp.1167-1187
• /
• 2020

We are facing the situation where cyber threats such as hacking, malware, data leakage, and theft, become an important issue in the perspective of personal daily life, business, and national security. Although various efforts are being made to response to the cyber threats in the national and industrial sectors, the problems such as the industry-academia skill-gap, shortage of cybersecurity professionals are still serious. Thus, in order to overcome the skill-gap and shortage problems, we propose a Cybersecurity technical response Job Competency(CtrJC) framework by adopting the concept of cybersecurity personnel's job competency. As a sample use-case study, we implement the CtrJC against to personals who are charged in realtime cybersecurity response, which is an important job at the national and organization level, and verify the our framework's effects. We implement a sample model, which is a CtrJC against to realtime cyber threats (We call it as CtrJC-R), and study the verification and validation of the implemented model.

• Journal of the Korea Institute of Information Security & Cryptology
• /
• v.30 no.6
• /
• pp.1279-1289
• /
• 2020

To securely protect users' sensitive information and national secrets, the importance of cryptographic modules has been emphasized. Currently, many companies and national organizations are actively using cryptographic modules. In Korea, To ensure the security of these cryptographic modules, the cryptographic module has been verified through the Korea Certificate Module Validation Program(KCMVP). Most of the domestic cryptographic modules are CPU-based software (S/W). However, CPU-based cryptographic modules are difficult to use in servers that need to process large amounts of data. In this paper, we propose an S/W cryptographic module that provides a high-speed operation using GPU. We describe the configuration and operation of the S/W cryptographic module using GPU and present the changes in the cryptographic module security requirements by using GPU. In addition, we present the performance improvement compared to the existing CPU S/W cryptographic module. The results of this paper can be used for cryptographic modules that provide cryptography in servers that manage IoT (Internet of Things) or provide cloud computing.

• Women's Health Nursing
• /
• v.26 no.4
• /
• pp.326-335
• /
• 2020

Purpose: This study was conducted to evaluate the construct validity, reliability, measurement invariance, and latent mean differences in the Breastfeeding Adaptation Scale-Short Form (BFAS-SF) for use with mothers at 2 weeks postpartum. Methods: This methodological study was designed to evaluate the validity, reliability, and measurement invariance of the BFAS-SF at 2 weeks postpartum, with data collected from 431 breastfeeding mothers. Confirmatory factor analysis and multi-group confirmatory factor analysis were conducted to assess the factor structure and the measurement invariance across employment status, delivery mode, parity, and previous breastfeeding experience, and the latent mean differences were then examined. Results: The goodness of fit of the six-factor model at 2 weeks postpartum was acceptable. Multi-group confirmatory factor analysis supported strict invariance of the BFAS-SF across employment status and delivery mode. Full configural invariance, full metric invariance, and partial scalar invariance across parity and full configural invariance and full metric invariance across previous breastfeeding experience were supported, respectively. The results for latent mean differences suggested that mothers who were employed showed significantly higher scores for breastfeeding confidence. Mothers who had a vaginal delivery showed significantly higher scores for sufficient breast milk and baby's feeding capability. Multiparous mothers showed significantly higher scores for baby's feeding capability and baby's satisfaction with breastfeeding. Conclusion: The validity and reliability of the BFAS-SF at 2 weeks postpartum are acceptable. It can be used to compare mean scores of breastfeeding adaptation according to employment status, delivery mode, and parity.

• Journal of Animal Science and Technology
• /
• v.62 no.6
• /
• pp.884-892
• /
• 2020

Corticosterone is known as a biological stress index in many species including birds. Feather corticosterone concentration (FCC) has increasingly been used as a measure for chronic stress status in broiler chickens. As sample preparation is the first step of analytical process, different techniques of feather matrix disruption need to be validated for obtaining better result in analysing corticosterone extraction. The current study was a validation of pulverizing the feather by bead beater (BB) and surgical scissors (SS) processing prior to corticosterone extraction in feather of broiler chickens. The type of feather processing prior to the hormone extraction may alter the final output. Thereby, finding a standard method according to laboratory facilities is pivotal. This study carried out to determine the effects of feather pulverization methods on the extraction amount of corticosterone in broiler chickens. Feathers were sampled from four weeks old Ross 308 broiler chickens (n = 12 birds). All broiler chickens were kept under the same environmental condition and had access to feed and water. Feather samples were assigned to one of the following processing methods 1) using a BB for pulverizing and 2) using a SS for chopping into tiny pieces. Each sample was duplicated into two wells during enzyme immunoassay (EIA) analysis to improve the accuracy of the obtained data. The results showed lower standard errors and constant output of FCC by using the BB method compared with the SS method. Overall comparison of FCC showed a significantly higher (p < 0.001) amount of the FCC in the BB compared with the SS. Overall, using the BB method is recommended over the SS method for feather processing due to the ability to homogenize a large number of samples simultaneously, ease of use and greater extraction of feather corticosterone.

• Korean Journal of Remote Sensing
• /
• v.36 no.6_2
• /
• pp.1567-1577
• /
• 2020

Urban land cover classification is role in urban planning and management. So, it's important to improve classification accuracy on urban location. In this paper, machine learning model, Support Vector Machine (SVM) and Artificial Neural Network (ANN) are proposed for urban land cover classification based on high resolution satellite imagery (KOMPSAT-3A). Satellite image was trained based on 25 m rectangle grid to create training data, and training models used for classifying test area. During the validation process, we presented confusion matrix for each result with 250 Ground Truth Points (GTP). Of the four SVM kernels and the two activation functions ANN, the SVM Polynomial kernel model had the highest accuracy of 86%. In the process of comparing the SVM and ANN using GTP, the SVM model was more effective than the ANN model for KOMPSAT-3A classification. Among the four classes (building, road, vegetation, and bare-soil), building class showed the lowest classification accuracy due to the shadow caused by the high rise building.

• Journal of the Korean Society of Propulsion Engineers
• /
• v.25 no.2
• /
• pp.34-41
• /
• 2021

A commercial HVOF torch (originally designed for coating applications) has been modified as a high temperature flow source for material testing. In this study, a water cooled commercial Gardon gauge was used to measure heat fluxes at four locations away from the nozzle exit. The cooling water temperature data were used to calculate calorimetric heat fluxes at the same locations. The heat fluxes from both methods were compared and the calorimetric heat fluxes were found to be many times higher than the Gardon gauge heat fluxes. A hypothesis is applied to the calorimetric method to understand the discrepancy seen between the methods. The Gardon gauge heat fluxes are seen to be in the range of the hypothesized calorimetric calculations. This can be considered as a considerable validation for the hypothesis, but further refinement needed using appropriate numerical models.

• Journal of Microbiology and Biotechnology
• /
• v.31 no.12
• /
• pp.1716-1721
• /
• 2021

Chikungunya fever is an arboviral disease caused by the Chikungunya virus (CHIKV). The disease has similar clinical manifestations with other acute febrile illnesses which complicates differential diagnosis in low-resource settings. We aimed to develop a rapid test for CHIKV detection based on the nucleic acid lateral flow immunoassay technology. The system consists of a primer set that recognizes the E1 region of the CHIKV genome and test strips in an enclosed cassette which are used to detect amplicons labeled with FITC/biotin. Amplification of the viral genome was done using open-source PCR, a low-cost open-source thermal cycler. Assay performance was evaluated using a panel of RNA isolated from patients' blood with confirmed CHIKV (n = 8) and dengue virus (n = 20) infection. The open-source PCR-NALFIA platform had a limit of detection of 10 RNA copies/ml. The assay had a sensitivity and specificity of 100% (95% CI: 67.56% - 100%) and 100% (95% CI: 83.89% - 100%), respectively, compared to reference standards of any positive virus culture on C6/36 cell lines and/or qRT-PCR. Further evaluation of its performance using a larger sample size may provide important data to extend its usefulness, especially its utilization in the peripheral healthcare facilities with scarce resources and outbreak situations.