• Journal of Korean Society of Transportation
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• v.25 no.6
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• pp.79-88
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• 2007

Design Hourly Volume (DHV) is the hourly volume used for designing a section of road. DHV is also used to estimate the expected number of vehicles to pass or traverse the relevant section of road in a future target year. The Design Hour Factor (DHF) is defined as the ratio of DHV to Average Annual Daily Traffic (AADT). In addition to high precision of predicted traffic volume, in order to design a roadway to be the proper scale, applying appropriate DHFs considering traffic flow characteristics and type of area which surrounds the relevant roadway is important. This study categorizes sections of expressway (Suh Hae An Expressway) according to their area type and estimates DHFs utilizing traffic data obtained from a vehicle detection system (VDS). This study shows that DHFs calculated using VDS data are different from those using traffic data acquired from a coverage survey. While AADTs from both data show similar values, peak hour volumes from both data show significant differences especially for recreational areas. DHFs from the coverage survey are quite different from the values provided by the Korean design guide or previous research results and DHFs for urban areas are higher than recreational areas. However, DHFs from VDS shows similar values to previous research results. The result of this study suggests that using VDS for estimating DHFs is more reliable than using a coverage survey.

• The Korean Journal of Pain
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• v.4 no.2
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• pp.127-132
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• 1991

Recently a non-electronic, disposable and portable infusor(Baxter infusor with patient control module, Baxter health care Co., Deerfield IL 60015 USA: BI $\bar{c}$ PCM) has been developed that will deliver both a continuous drug infusion as well as allow the patient to deliver extra doses of medication on a demand basis under predetermined limitation of analgesics. Patients may also not require as high analgesic dose rate to control pain when the acceptable and tolerable level of pain relief can be maintained by this device. From April l99l, we have used a total l93 units of BI $\bar{c}$ PCM. These units consisting of two components which one made by a balloon reservoir(capacity 65 ml, flow rate 0.5 ml/hr) to store medication and to regulate the pump power(490 torr), and another two PCMs to regulate additional analgesic administration by patients demand at intervals of 1S minutes and 60 minutes. The dose administered to the patient can be varied by changing the concentration of the infusate within the balloon reservoir. These devices were utilized for the pain control of 44 patients. These patients were divided into two groups. Twenty seven cases had cancer pain and 17 cases had non-cancer pain. The Touhy needle(No. l8 G.) tip was inserted into the epidural space and was used to guide the catheter to the spinal nerve level corresponding to the most painful area. The device was connected to the opposite site of the catheter tip and was filled with 60 ml of mixture solution such as 0.5% bupivacaine 15 ml, morphine HCl 10 mg, trazodone 10 ml, Tridol 3 ml and normal saline 31 ml were administed as the initial dose. When the initial dose was less effective, the next dose could be varied by increasing the concentration of bupivacaine, by adding more morphine (5~10 mg), and by reducing the volume of normal saline. Using these modules of drug self administration, we experienced the following: 1) Improvement of patient's self titration of analgesic requirement was provided. 2) The patients anxiety with pain recurrence resulting from delays in administering pain control medication was decreased significantly. 3) The working load accompanying with the single bolus injection as the usual method was reduced remarkably. 4) There was urinary retention in 5 cases and pruritus in 4 eases which developed as side effects but respiratory depression and vomiting was not encountered in a single case.

• Journal of the Korean Society of Marine Environment & Safety
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• v.22 no.6
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• pp.631-638
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• 2016

A mariner cadet gains the ability to identify and avoid potential collisions with other ships through ARPA/Radar simulation education. This research surveyed first domestic and overseas's rules (e.g., MOMAF's Standard, the STCW Convention, etc.) of the simulation education, upon investigation the only content and timing of this simulation-based education are specified according to these rules, and maritime education institutions issue the related certification autonomously after a student has taken the simulation because no simulation education module exists to further guide the ARPA/Radar simulation. As a result, it is difficult for students to acquire consistent maritime ability through ARPA/Radar simulation. This paper discusses standardization of these education modules to produce more consistent mariner ability, and verify the degree of improvement of education that would be achieved by enacting the proposed education module. The simulation education system used in maritime institutions in Korea was investigated, and scenarios reflecting traffic flow in actual waterways was proposed based on marine traffic surveys so teaching modules can educate/assess more effectively based on core marine abilities. Improvements in education and training were also verified using data collected over 2 years based on a standardized module. Each education institution can enact an effective, systematic education approach using standardized ARPA/Radar education modules proposed in this paper, and this can set a foundation to contribute to safer vessel navigation by improving maritime abilities.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.33 no.4
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• pp.287-296
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• 2015

Recent navigation systems provide quick guide services, based on processing real-time traffic information and past traffic information by applying predictable pattern for traffic information. However, the current pattern for traffic information predicts traffic information by processing past information that it presents an inaccuracy problem in particular circumstances(accidents and weather). So, this study presented a more precise predictive traffic information system than historical traffic data first by analyzing route search data which the drivers ask in real time for the quickest way then by grasping traffic congestion levels of the route in which future drivers are supposed to locate. First results of this study, the congested route from Yang Jae to Mapo, the analysis result shows that the accuracy of the weighted value of speed of existing commonly congested road registered an error rate of 3km/h to 18km/h, however, after applying the real predictive traffic information of this study the error rate registered only 1km/h to 5km/h. Second, in terms of quality of route as compared to the existing route which allowed for an earlier arrival to the destination up to a maximum of 9 minutes and an average of up to 3 minutes that the reliability of predictable results has been secured. Third, new method allows for the prediction of congested levels and deduces results of route searches that avoid possibly congested routes and to reflect accurate real-time data in comparison with existing route searches. Therefore, this study enabled not only the predictable gathering of information regarding traffic density through route searches, but it also made real-time quick route searches based on this mechanism that convinced that this new method will contribute to diffusing future traffic flow.

• Journal of Digital Convergence
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• v.19 no.9
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• pp.189-199
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• 2021

In order to increase the self-reliance rate of new and renewable energy in order to respond to the mandatory domestic zero-energy buildings, the taller the building, the more limited the site area, and installing PV modules on the roof is not enough. Therefore, BIPV (Building integrated photovoltaic, hereinafter BIPV) is the industry receiving the most attention as a core energy source that can realize zero-energy buildings. Therefore, this study conducted a survey on the problems of the BIPV industry in a self-discussing method for experts with more than 10 years of experience of designers, builders, product manufacturers, and maintainers in order to suggest the right direction and revitalize the BIPV industry. Industrial problems of BIPV adjustment are drawn extention range of standard and certification for products, range improvement for current small condition of various kind productions, need to revise standards for capable of accomodating roof-type, color-module and louver-module, necessary of barrier in flow of foreign modules into korea through domestic certification mandatory, difficulty in obtaining BIPV information, request to prevent confusion among participants by exact guidelime about architectural application part of BIPV, and lack of the BIPV definition clearness, support policy, etc. Based on the improvements needed for the elements, giving change and competitiveness impacts aims to present and propose counter measures and direction.

• Journal of The Korean Association For Science Education
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• v.39 no.1
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• pp.73-88
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• 2019

The purpose of this study is to explore elementary teachers' difficulties on teaching science by analyzing questions that have been posted for a long time in an autonomous online teacher community named Indischool. For this purpose, 409 question postings(the 2007 and 2009 revised curriculum, third to sixth grade) were analyzed using the framework for analyzing questions about elementary teachers' science teaching(modified from Alake-Tuenter et al., 2013). The study revealed that there were more science-SMK questions than science-PCK questions, and most of the questions were 'about lenses' and 'in 2014 and 2015, when the curriculum was changing from the 2007 to the 2009 revised curriculum'. The long-standing difficulties in science-SMK were 'an application of facts and concepts in lenses' and 'an unexpected experimental error in electricity'. In particular, there are the principle of transparent cup-shaped objects acting as lenses, the process of image formation by convex lenses, experimental errors of 'compass movement due to current flow change' and experimental errors 'serial connection of bulbs'. The long-standing difficulties in science-PCK were 'understanding and response to context' and 'understanding and response to aims mentioned in standard document' and these are not related to physical units but to others. In particular, there are request class materials, activity ideas at the end of the semester and understanding the national curriculum guidelines. These teachers' difficulties should be reflected in the science teaching support system like a teacher's guide compilation, teacher's training curriculum development, etc.

• Journal of Korean Society of Disaster and Security
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• v.14 no.4
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• pp.17-27
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• 2021

Streamflow prediction is a very vital disaster mitigation approach for effective flood management and water resources planning. Lately, torrential rainfall caused by climate change has been reported to have increased globally, thereby causing enormous infrastructural loss, properties and lives. This study evaluates the contribution of rainfall to streamflow prediction in normal and peak rainfall scenarios, typical of the recent flood at Piney Resort in Vernon, Hickman County, Tennessee, United States. Daily streamflow, water level, and rainfall data for 20 years (2000-2019) from two USGS gage stations (03602500 upstream and 03599500 downstream) of the Piney River watershed were obtained, preprocesssed and fitted with Long short term memory (LSTM) model. Tensorflow and Keras machine learning frameworks were used with Python to predict streamflow values with a sequence size of 14 days, to determine whether the model could have predicted the flooding event in August 21, 2021. Model skill analysis showed that LSTM model with full data (water level, streamflow and rainfall) performed better than the Naive Model except some rainfall models, indicating that only rainfall is insufficient for streamflow prediction. The final LSTM model recorded optimal NSE and RMSE values of 0.68 and 13.84 m³/s and predicted peak flow with the lowest prediction error of 11.6%, indicating that the final model could have predicted the flood on August 24, 2021 given a peak rainfall scenario. Adequate knowledge of rainfall patterns will guide hydrologists and disaster prevention managers in designing efficient early warning systems and policies aimed at mitigating flood risks.

• Journal of the Korea Society of Computer and Information
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• v.27 no.11
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• pp.181-190
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• 2022

In this paper, we use a LiDAR sensor and an image camera to detect a left-turning waiting vehicle in two ways, unlike the existing image-type or loop-type left-turn detection system, and a left-turn traffic signal corresponding to the waiting length of the left-turning lane. A system that can efficiently assign a system is introduced. For the LiDAR signal transmitted and received by the LiDAR sensor, the left-turn waiting vehicle is detected in real time, and the image by the video camera is analyzed in real time or at regular intervals, thereby reducing unnecessary computational processing and enabling real-time sensitive processing. As a result of performing a performance test for 5 hours every day for one week with an intersection simulation using an actual signal processor, a detection rate of 99.9%, which was improved by 3% to 5% compared to the existing method, was recorded. The advantage is that 99.9% of vehicles waiting to turn left are detected by the LiDAR sensor, and even if an intentional omission of detection occurs, an immediate response is possible through self-correction using the video, so the excessive waiting time of vehicles waiting to turn left is controlled by all lanes in the intersection. was able to guide the flow of traffic smoothly. In addition, when applied to an intersection in the outskirts of which left-turning vehicles are rare, service reliability and efficiency can be improved by reducing unnecessary signal costs.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.2
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• pp.179-198
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• 2023

The purpose of this study is to verify the role of teacher librarians by examining the cases of media and information literacy(MIL) classes in the joint curriculum of high school credit system research school. The classes were two 34th classes joint curriculum established by two teacher librarians at the high school credit system research school. Individual students set their own inquiry problems integrated with their careers or subjects, and teacher librarians guide the process of solving them based on the process of using MIL. The participants were 22 high school students in Daegu who filled out the questionnaire before and after completing the course. The effect of the classes was analyzed through a questionnaire consisting of 42 questions for the 3 factors of access, evaluation, and creation, which are the components of MIL announced by UNESCO. As a result, all 3 factors and 25 of the sub-42 survey items showed a statistically significant difference before and after class, It was investigated that literacy of students improved through MIL education of teacher librarians. Through this study, it will be possible to expand the awareness of the effect of the educational role of teacher librarians in the flow of future curriculum.

• Korean Chemical Engineering Research
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• v.62 no.3
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• pp.214-224
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• 2024

Valves play an essential role in a chemical plant such as regulating fluid flow and pressure. Therefore, optimal selection of the valve size and type is essential task. Valve size and type have been selected based on theoretical formulas about calculating valve sizing coefficient (Cv). However, this approach has limitations such as requiring expert knowledge and consuming substantial time and costs. Herein, this study developed a model for predicting valve sizes and types using machine learning. We developed models using four algorithms: ANN, Random Forest, XGBoost, and Catboost and model performances were evaluated using NRMSE & R² score for size prediction and F1 score for type prediction. Additionally, a case study was conducted to explore the impact of phases on valve selection, using four datasets: total fluids, liquids, gases, and steam. As a result of the study, for valve size prediction, total fluid, liquid, and gas dataset demonstrated the best performance with Catboost (Based on R², total: 0.99216, liquid: 0.98602, gas: 0.99300. Based on NRMSE, total: 0.04072, liquid: 0.04886, gas: 0.03619) and steam dataset showed the best performance with RandomForest (R²: 0.99028, NRMSE: 0.03493). For valve type prediction, Catboost outperformed all datasets with the highest F1 scores (total: 0.95766, liquids: 0.96264, gases: 0.95770, steam: 1.0000). In Engineering Procurement Construction industry, the proposed fluid-specific machine learning-based model is expected to guide the selection of suitable valves based on given process conditions and facilitate faster decision-making.