• Journal of Korea Water Resources Association
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• v.55 no.spc1
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• pp.1211-1222
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• 2022

Abnormal condition inevitably occurs during operation of water distribution system (WDS) and requires the isolation of certain areas using isolation valves. In general, the determination of the optimal location of isolation valves considered minimization of hydraulic failures as isolation of certain areas causes a change in hydraulic states (e.g., flow direction, velocity, pressure, etc.). Water quality failure can also be induced by changes in hydraulics, which have not been considered for isolation valve system design. Therefore, this study proposes a new isolation valve system design methodology to prevent unexpected water quality failure events. The new methodology considers flow direction change ratio (FDCR), which accounts for flow direction changes after isolation of the area, as a constraint while reliability is used as the objective function. The optimal design model has been applied to a synthetic grid network and the results are compared with the traditional design approach. Results show that considering FDCR can eliminate flow direction changes while average pressure and coefficient of variation of pressure, velocity, and hydraulic geodesic index (HGI) outperform compared to the traditional design approach. The proposed methodology is expected to be a useful approach to minimizing unexpected consequences by traditional design approaches.

• Korean Chemical Engineering Research
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• v.61 no.1
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• pp.123-141
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• 2023

A sufficient amount of data with quality is needed for training artificial neural networks (ANNs). However, developing ANN models with a small amount of data often appears in engineering fields. This paper presented an ANN model to improve prediction performance of the ammonia emission amount with 83 data. The ammonia emission rate included eleven inputs and two outputs (maximum ammonia loss, N_max and time to reach half of N_max, K_m). Categorical input variables were transformed into multi-dimensional equal-distance variables, and 13 data were added into 66 training data using a generative adversarial network. Hyperparameters (number of layers, number of neurons, and activation function) of ANN were optimized using Gaussian process. Using 17 test data, the previous ANN model (Lim et al., 2007) showed the mean absolute error (MAE) of K_m and N_max to 0.0668 and 0.1860, respectively. The present ANN outperformed the previous model, reducing MAE by 38% and 56%.

• Nuclear Engineering and Technology
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• v.26 no.3
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• pp.337-344
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• 1994

Enthalpy rise hot channel factor($F_{\Delta{H}}$$^{N}$) is one of the most limiting constraints in determining the fuel loading pattern(LP) for PWR's. In order to enhance the LP design flexibility without any changes of not only basic fuel specifications but also Technical Specifications and Operation Procedures, we apply the enrichment zoning concept to Westinghouse designed PWR's to flatten the rod power distributions within the fuel assembly and thus to reduce $F_{\Delta{H}}$$^{N}$. Enrichment zoning is described that each assembly consists of two different enrichment fuels ; the lower enriched fuels are located in positions which are expected to have the higher rod power and vice versa for the higher enriched fuels. As a result of unit assembly calculations to flatten the rod power distribution within the assembly, the appropriate enrichment difference is found to be 0.3~0.4w/o. Through core depletion calculations for the 18-month cycle of Kori Unit 4, the $F_{\Delta{H}}$$^{N}$ behavior in core with the enrichment zoning concept is investigated. A comparison with the reference case without the enrichment zoning results in a reduction in $F_{\Delta{H}}$$^{N}$ of approximately 1.5%.TEX>H/$^{N}$ of approximately 1.5%.

• Journal of the Korean Geotechnical Society
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• v.26 no.7
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• pp.147-159
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• 2010

The settlement prediction is very important in preloading method for a construction site on the soft ground. At the design stage, however, it is hard to predict the settlement exactly due to limitations of the site survey. Most of the settlement prediction is performed by a regression settlement curve based on the field data during construction. In Korea, hyperbolic method has been most commonly used to align the settlement curve with the field data, because of its simplicity and many application cases. The results from hyperbolic method, however, may differ by data selections or data fitting methods. In this study, the analyses using hyperbolic method were performed about the field data of $\bigcirc\bigcirc$ site in Pusan. Two data fitting methods, using an axis transformation or an alternative method which is a direct regression method, were applied with various data groups. If data was used only after the ground water level being stabilized, fitting results using both methods were in good agreement with the measured data. Regardless of the information about the ground water level, the alternative method gives better results with the field data than the method using an axis transformation.

• Journal of The Korean Association For Science Education
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• v.43 no.3
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• pp.307-319
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• 2023

This study aims to explain the key concepts and principles of text-based generative artificial intelligence (AI) that has been receiving increasing interest and utilization, focusing on its application in science education. It also highlights the potential and limitations of utilizing generative AI in science education, providing insights for its implementation and research aspects. Recent advancements in generative AI, predominantly based on transformer models consisting of encoders and decoders, have shown remarkable progress through optimization of reinforcement learning and reward models using human feedback, as well as understanding context. Particularly, it can perform various functions such as writing, summarizing, keyword extraction, evaluation, and feedback based on the ability to understand various user questions and intents. It also offers practical utility in diagnosing learners and structuring educational content based on provided examples by educators. However, it is necessary to examine the concerns regarding the limitations of generative AI, including the potential for conveying inaccurate facts or knowledge, bias resulting from overconfidence, and uncertainties regarding its impact on user attitudes or emotions. Moreover, the responses provided by generative AI are probabilistic based on response data from many individuals, which raises concerns about limiting insightful and innovative thinking that may offer different perspectives or ideas. In light of these considerations, this study provides practical suggestions for the positive utilization of AI in science education.

• 한국체육학회지인문사회과학편
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• v.57 no.6
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• pp.293-308
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• 2018

This study was carried out to investigate the current trends in skiing-related research from existing literature in the field of kinematics, measurement sensor and computer simulation. In the field of kinematics, research is being conducted on the mechanism of ski turn, posture analysis according to the grade and skill level of skiers, friction force of ski and snow, and air resistance. In the field of measurement sensor and computer simulation, researches are being conducted for researching and developing equipment using IMU sensor and GPS. The results of this study are as follows. First, beyond the limits of the existing kinematic analysis, it is necessary to develop measurement equipment that can analyze the entire skiing area and can be deployed with ease at the sports scene. Second, research on the accuracy of information obtained using measurement sensors and various analysis techniques based on these measures should be carried out continuously to provide data that can help the sports scene. Third, it is necessary to use computer simulation methods to clarify the injury mechanism and discover ways to prevent injuries related to skiing. Fourth, it is necessary to provide optimized ski trajectory algorithm by developing 3D ski model using computer simulation and comparing with actual skiing data.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.1D
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• pp.17-23
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• 2009

Due to the rapid increase of vehicles on the street, Korean society is facing worsening traffic congestions and air pollutions. Also, the oil price pickup has led to increasing need for the use of public transportation. In particular, transfering among public transportation may be a main factor for riders who are commuting for a long distance journey. In order to ensure such connectivity, transfer stations have been actively built in Korea. However, it would be necessary to shift those vehicles, from cars to public transportations by enhancing the users' satisfaction with public transportation through strategies for minimizing the users' waiting cost by building an efficient connective system between transportation modes as well as the preparation of aforementioned transfer stations. Therefore, this study aimed to develop an algorithm for minimizing transferring passengers' waiting costs based on service intervals of linked buses within the transfer facilities. In order to adjust the service interval, we calculated the total costs, involving the wait cost of transfer passengers and bus operation costs, and produced an allocation interval, that would minimize the costs. We selected a KTX departing from Seoul station, and a No. 6014 bus route in Gwangmyeong city where it starts from the Gwangmyeong station in order to for verifying the model. Then, the transfer passengers' total waitting cost was reduced equivalent to the maximum of 212 minutes, and it revealed that the model performed very effectively.

• Analytical Science and Technology
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• v.22 no.3
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• pp.191-200
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• 2009

The aim of this study was to evaluate and establish of emission test method for liquid phase building materials such as paint, adhesive, sealant by emission cell. A small-scale emission chamber and emission cell were used to evaluate emission of TVOC from paint, adhesive, sealant. The quantity of TVOC emission were measured by a gas chromatography/mass spectrometry (GC/MS). Background concentration of TVOC was below $10{\mu}g/m^3$ in the emission chamber and cell. Air tightness and recovery in chamber and cell showed good results. The recovery of thermal desorber for toluene and n-dodecane were about 120%. The repeatability of response factor and retention time in GC/MS below 30%. The method detection limit of VOCs ranged 0.04~8.82 ng. The concentration of TVOC emission using emission cell was 1.35~1.41 times higher than emission chamber. The correlation of TVOC emission using chamber and cell method was significantly high (r=0.91~0.97).

• Journal of the Korean Recycled Construction Resources Institute
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• v.11 no.3
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• pp.226-233
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• 2023

In this study, two phases were conducted to investigate the direct injection of gaseous CO₂ into cement mortar. The aim was to advance carbon capture, utilization, and storage (CCUS) technology by harnessing industrial waste CO₂ from the domestic ready-mixed concrete industry. In the first phase, the factors influencing the physical properties of cement mortar when using gaseous CO₂ were identified. This included a review of materials to achieve physical properties comparable to a reference formulation. As a result of this phase, it was confirmed that traditional approaches, such as adjusting the water-to-cement ratio, had limitations in achieving the desired physical properties. Consequently, the second phase focused on the optimization of CO₂-injected mortar. This involved studying the CO₂ application and mixing method for cement mortar. Changes in properties were observed when gaseous CO₂ was injected into the mortar. The optimal injection quantity and time to enhance the compressive strength of mortar were determinded. As a result, this study indicated that an extra mixing time exceeding 120 seconds was necessary, compared to conventional mortar. The optimal CO₂ injection rate was identified as 0.1 to 0.2 % by weight of cement, taking both flowability and compressive strength performance into account. Increasing the CO₂ injection time did not further enhance strength. For this approach to be employed as a CCUS technology, additional studies are required, including a microstructural analysis evaluating the amount of immobilized CO₂.

• Information Systems Review
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• v.22 no.2
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• pp.77-99
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• 2020

Smart speaker is a device that provides an interactive voice-based service that can search and use various information and contents such as music, calendar, weather, and merchandise using artificial intelligence. Since AI technology provides more sophisticated and optimized services to users by accumulating data, early smart speaker manufacturers tried to build a platform through aggressive marketing. However, the frequency of using smart speakers is less than once a month, accounting for more than one third of the total, and user satisfaction is only 49%. Accordingly, the necessity of strengthening the user experience of smart speakers has emerged in order to acquire a large number of users and to enable continuous use. Therefore, this study analyzes the user experience of the smart speaker and proposes a method for enhancing the user experience of the smart speaker. Based on the analysis results in two stages, we propose ways to enhance the user experience of smart speakers by model. The existing research on the user experience of the smart speaker was mainly conducted by survey and interview-based research, whereas this study collected the actual review data written by the user. Also, this study interpreted the analysis result based on the smart speaker user experience dimension. There is an academic significance in interpreting the text mining results by developing the smart speaker user experience dimension. Based on the results of this study, we can suggest strategies for enhancing the user experience to smart speaker manufacturers.