• Membrane and Water Treatment
• /
• v.9 no.6
• /
• pp.447-454
• /
• 2018

Although flotation techniques are often used for the removal of algal particles, the practicality of algae-harvesting technologies is limited owing to the complex and expensive facilities and equipment required for chemical coagulation. Here, we examined the feasibility of an approach to separating algal particles from water bodies without the need for chemical coagulants, depending on the condition of the algae, and to determine the optimal conditions. Using Anabaena sp., a cyanobacterium causes algal blooms in lakes, we stimulated auto-flocculation in algal particles without coagulants and conducted solid-liquid separation experiments of algal particles under various conditions. The six cultivation columns included in our analysis comprised four factors: Water temperature, light intensity, nutrients, and carbon source; auto-flocculation was induced under all treatments, with the exception of the treatment involving no limits to all factors, and algal particles were well-settled under all conditions for which auto-flocculation occurred. Meanwhile, flotation removal of auto-flocculated algal particles was attained only when nutrients were blocked after algae were grown in an optimal medium. However, no significant differences were detected between the functional groups of the extracellular polymeric substances (EPSs) of floated and settled algal particles in the FT-IR peak, which can cause attachment by collision with micro-bubbles.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.585-588
• /
• 2005

Many process parameters have an effect on the auto-body panel forming process. A well designed blank shape causes the material to flow smoothly, reduces the punch and yields a product with uniform thickness distribution. Therefore, the determination of an initial blank shape plays the important role of saving time and cost in the auto-body panel forming process. For these reasons, some approaches to estimate the initial blank shape have been implemented, in this paper The one-step approach using a finite element inverse method will be introduced to predict the optimal forming with changing of blank pressure the developed program is applied to auto-body panel forming.

• Transactions on Control, Automation and Systems Engineering
• /
• v.1 no.2
• /
• pp.141-146
• /
• 1999

This paper describes the communication method of an auto-startup system. The Auto-Startup system is designed to operate a nuclear power plant automatically during the startup operation . In general , the operations during startup in existing plant have only been manually controlled by the operator. The manual operation caused to the operator mistake. The Auto-Startup system consists of the Distributed Control System(DCS) and G2 (Expert System). Also, Functional Test Facility(FTF) provides the plant's real-data for an Auto-Startup system. So, it is necessary to develop the communication method between these systems. We developed two methods ; one is a network and the other is a hardwire line. To communicate between these systems (DCS-G2 and DCS-FTF) , we developed the communication program. In case of DCS-FTF, we used the TCP/IP and VXI. BUt, in case of DCS-G2 , we , what it called , developed the bridge program using the GSI(G2 Standard Interface). We test to check the function of the important parameter, in time, for analysis of the developed communication method. The results are a good performance when we check the communication time of important parameter. We conclude that Auto-startup system could save heat-up time about at least 5 hours and reduced the change of the reactor operation and trip.

• Journal of Auto-vehicle Safety Association
• /
• v.13 no.4
• /
• pp.53-59
• /
• 2021

According to the Korean Traffic Accident Analysis System (TAAS), more than 200,000 traffic accidents occur every year. Also, the statistics including auto insurance companies data show 1.3 million traffic accidents. In the case of TAAS, the types of traffic accidents are simply divided into four; frontal collision, side collision, rear collision, and rollover. However, more detailed information is needed to assess for advanced driver assist systems at intersections. For example, directional information is needed, such as whether the vehicle in the car accident way in a straight or a left turn, etc. This study intends to redefine the type of accident with the more clear driving direction and path by referring to the Negligence standards used in automobile insurance accidents. The standards largely divide five categories of car-to-car/motorcycle /pedestrian/cyclist, and highway, and the each category is classified into dozens of types by status of the traffic signal, conflict situations. In order to present more various accident types for auto insurance accidents, the standards are reclassified driving direction and path of vehicles from crash situations. In results, the car-to-car accidents are classified into 33 accident types, car-to-pedestrian accidents have 19 accident types, car-to-motorcycle accidents have 38 accident types, and car-to-cyclist accidents are derived into 26 types.

• Journal of recreation and landscape
• /
• v.12 no.4
• /
• pp.11-16
• /
• 2018

The aim of this study is to obtain basic data to set the direction for construct and managing auto campsites. A survey was conducted with users of an auto campsite located in Jangsu Nuri Park in October 2018, and 32 copies of the questionnaire were used in the analysis. Auto camping is typically undertaken for a night or two with family or friends/colleagues. The adequacy of fees and location are important factors in choosing the campsite, so it is desirable to build one in the suburbs of the city and offer it at a reasonable price. Proximity to tourist spots and convenience in using facilities are also factors that must be considered. People are generally engaged in activities such as taking walks, relaxing, and looking around campsites, and they want to enjoy various other amenities like attractions, experiences, entertainment, and active leisure options, which is why there must be facilities to support these behaviors. The first-time visitors of the campsite showed high satisfaction with its individual facilities, while repeat visitors showed high overall satisfaction, which indicates that satisfaction with individual elements did not lead to overall satisfaction.

• Journal of Koreanology Reviews
• /
• v.2 no.1
• /
• pp.1-8
• /
• 2023

The South Korean automotive industry has been the major producer for both domestic and international market. This rises of the South Korean automotive industry has resulted in combination various factors ranging from government policies and the foreign investment. The Double Helix model provides a comprehensive and useful framework to understand how these factors have interacted to shape the history of the auto industry of South Korea. This research aims to provide the history of the Auto Industry in Korea based on the Double Helix Model. To collect textual literature dataset, the present author tried to screen and select adequate prior studies in the past and current literature to achieve the purpose of the study. According to the literature analysis, the history of the automotive industry in South Korea is an interesting case in the successful implementation of the Double Helix model. The model emphasizes the collaboration between the government and the private sector in achieving common goals. This research founded the four historical events of the development of the South Korean automotive industry based on the Double Helix Models. In sum, the research concludes that the Double Helix Model is an essential tool for understanding the historical development of the auto industry in South Korea.

• The Journal of Advanced Prosthodontics
• /
• v.8 no.4
• /
• pp.285-289
• /
• 2016

PURPOSE. This study evaluated the effect of chemical surface treatment using methyl formate-methyl acetate (MF-MA) solution on the tensile bond strength between acrylic denture teeth and auto-polymerized acrylic resin. MATERIALS AND METHODS. Seventy maxillary central incisor acrylic denture teeth for each of three different brands (Yamahachi New Ace; Major Dent; Cosmo HXL) were embedded with incisal edge downwards in auto-polymerized resin in polyethylene pipes and ground with silicone carbide paper on their ridge lap surfaces. The teeth of each brand were divided into seven groups (n=10): no surface treatment (control group), MF-MA solution at a ratio of 25:75 (v/v) for 15 seconds, 30 seconds, 60 seconds, 120 seconds, 180 seconds, and MMA for 180 seconds. Auto-polymerized acrylic resin (Unifast Trad) was applied to the ground surface and polymerized in a pressure cooker. A tensile strength test was performed with a universal testing machine. Statistical analysis of the results was performed using two-way analysis of variance (ANOVA) and post-hoc Dunnett T3 test (${\alpha}$=.05). RESULTS. The surface treatment groups had significantly higher mean tensile bond strengths compared with the control group (P<.05) when compared within the same brand. Among the surface treatment groups of each brand, there were no significantly different tensile bond strengths between the MF-MA groups and the MMA 180 second group (P>.05), except for the Yamahachi New Ace MF-MA 180-second group (P<.05). CONCLUSION. 15-second MF-MA solution can be an alternative chemical surface treatment for repairing a denture base and rebonding acrylic denture teeth with auto-polymerized acrylic resin, for both conventional and cross-linked teeth.

• Journal of Internet Computing and Services
• /
• v.22 no.2
• /
• pp.1-9
• /
• 2021

Traditionally, most malicious codes have been analyzed using feature information extracted by domain experts. However, this feature-based analysis method depends on the analyst's capabilities and has limitations in detecting variant malicious codes that have modified existing malicious codes. In this study, we propose a ResNet-Variational AutoEncder-based variant malware classification method that can classify a family of variant malware without domain expert intervention. The Variational AutoEncoder network has the characteristics of creating new data within a normal distribution and understanding the characteristics of the data well in the learning process of training data provided as input values. In this study, important features of malicious code could be extracted by extracting latent variables in the learning process of Variational AutoEncoder. In addition, transfer learning was performed to better learn the characteristics of the training data and increase the efficiency of learning. The learning parameters of the ResNet-152 model pre-trained with the ImageNet Dataset were transferred to the learning parameters of the Encoder Network. The ResNet-Variational AutoEncoder that performed transfer learning showed higher performance than the existing Variational AutoEncoder and provided learning efficiency. Meanwhile, an ensemble model, Stacking Classifier, was used as a method for classifying variant malicious codes. As a result of learning the Stacking Classifier based on the characteristic data of the variant malware extracted by the Encoder Network of the ResNet-VAE model, an accuracy of 98.66% and an F1-Score of 98.68 were obtained.

• Korean Journal of Remote Sensing
• /
• v.39 no.6_1
• /
• pp.1491-1495
• /
• 2023

This study utilized automated machine learning (AutoML) to calculate Arctic ice surface temperature (IST). AutoML-derived IST exhibited a strong correlation coefficient (R) of 0.97 and a root mean squared error (RMSE) of 2.51K. Comparative analysis with deep neural network (DNN) models revealed that AutoML IST demonstrated good accuracy, particularly when compared to Moderate Resolution Imaging Spectroradiometer (MODIS) IST and ice mass balance (IMB) buoy IST. These findings underscore the effectiveness of AutoML in enhancing IST estimation accuracy under challenging polar conditions.

• Journal of Biomedical Engineering Research
• /
• v.9 no.1
• /
• pp.93-100
• /
• 1988

The Auto Regressive Parameter Estimation and Pattern Classification of EKG Signal for Automatic Diagnosis. This paper presents the results from pattern discriminant analysis of an AR (auto regressive) model parameter group, which represents the HRV (heart rate variability) that is being considered as time series data. HRV data was extracted using the correct R-point of the EKG wave that was A/D converted from the I/O port both by hardware and software functions. Data number (N) and optimal (P), which were used for analysis, were determined by using Burg's maximum entropy method and Akaike's Information Criteria test. The representative values were extracted from the distribution of the results. In turn, these values were used as the index for determining the range o( pattern discriminant analysis. By carrying out pattern discriminant analysis, the performance of clustering was checked, creating the text pattern, where the clustering was optimum. The analysis results showed first that the HRV data were considered sufficient to ensure the stationarity of the data; next, that the patern discrimimant analysis was able to discriminate even though the optimal order of each syndrome was dissimilar.