Following the signing of the Paris Agreement on Climate Change (UNFCCC, 2015), the world is expanding greenhouse gas reduction activities through comprehensive participation that includes not only developed countries but also developing countries. Major countries around the world are placing high expectations on the effectiveness of total carbon emissions regulation through the carbon emissions market. However, in order to obtain carbon credits, third-party verification is required based on quantitative carbon reduction data. Accordingly, in this paper, we developed an AIoT high-efficiency street light for carbon emissions and conducted a performance analysis study to measure the luminous efficiency of the lighting fixture. To obtain carbon emissions rights, we used high-efficiency LED PKG, developed our own high-voltage PFC, and developed high-efficiency lighting fixtures capable of communication. For communication, the 2.4GHz LoRa method was adopted between the lighting fixture and the gateway. Lens design was conducted through simulation of Korea Expressway Corporation's standard streetlight types A, B, and C. The performance of the streetlight was verified as being more efficient than other existing products through the measurement of luminous efficiency by an accredited rating agency, and it is expected that carbon emissions rights will be obtained by reducing electrical energy through this.
Small and medium-sized mountain rivers that flow through steep, confined valleys carry large amounts of coarse-grained sediment and woody debris during floods. It causes an increase in flood water level by aggrading the riverbed and the cross-section blockage due to driftwood accumulation during flooding. However, the existing flood level calculation in the river basic plan does not consider these changes. In this study, using the Typhoon Hinnamnor flood in September 2022 as an example, we performed numerical simulations using the HEC-RAS model, taking into account the blockage of a cross-section at the bridge and changes in riverbed elevation that occurred during floods, and analyzed the flood level to predict flood risk. This study's results show that flooding occurs if more than 30% of the cross-section is blocked. The rise of flood water levels corresponds to that of the riverbed due to sediment deposition. These results can be used as basic data to prevent and effectively manage flood damage and contribute to establishing flood defense measures that consider actual phenomena.
Agricultural reservoirs supply water for various purposes such as irrigation, maintenance, and living. Since agricultural reservoirs respond sensitively to seasonal and climate changes, it is essential to estimate supply and inflow for efficient operation, and water management should be done based on these data. However, in the case of agricultural reservoirs, the measurement of supply and inflow is relatively insufficient compared to multi-purpose dams, and inflow-supply analysis in agricultural reservoirs through water balance analysis is necessary for efficient water management. Therefore, rainfall-runoff analysis models such as ONE model and Tank model have been developed and used for reservoir water balance analysis, but the applicability analysis for ungauged watersheds is insufficient. The ONE model is designed for daily runoff calculation, and the model has one parameter, which is advantageous for calibration and ungauged watershed analysis. In this study, the water balance was analyzed through the ONE model and the Tank model for 15 watersheds upstream of dams, and R2 and NSE were used to quantitatively compare the performance of the two models. The simulation results show that the ONE model is suitable for predicting the inflow of agricultural reservoirs with the ungauged watershed
Journal of the Korean Institute of Landscape Architecture
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v.52
no.3
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pp.18-32
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2024
This study aims to analyze the summer human thermal environment in Jeju City's outdoor parking lots by measuring microclimate data and comparing pavement and vegetation albedoes and elements through computer simulations. In measured cases, results due to albedo showed no significance, but there was a significant difference between sunny and shaded areas by trees. The sunny area had a PET (physiological equivalent temperature) in the 'very hot' level, while the shaded area exhibited a 2-step lower 'warm' level. UTCI (universal thermal climate index) also showed that the sunny area was in the 'very strong heat stress' level, whereas the shaded area was 1-step lower in the 'strong heat stress' level, confirming the role of trees in reducing incoming solar radiant energy. Simulation results, using the measured albedoes, closely resembled the measured results. Regarding vegetation, scenarios with a wide canopy, high leaf density, and narrow planting spacing were effective in mitigating the human thermal environment, and the differences due to tree height varied across scenarios. The scenario with the lowest PET value was H9W9L3D8 (tree height 9m, canopy width 9m, leaf area index 3.0, planting spacing 8m), indicating a 0.7-step decrease compared to the current landscaping scenario. Thus, it was confirmed that, among landscaping elements, trees have a significant impact on the summer human thermal environment compared to ground pavement.
The Journal of the Korea institute of electronic communication sciences
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v.19
no.1
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pp.65-76
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2024
With the recent activation of the offshore wind power industry, there has been a development of power plants with a scale exceeding 400MW, comparable to traditional thermal power plants. Renewable energy, characterized by intermittency depending on the energy source, is a prominent feature of modern renewable power generation facilities, which are structured based on controllable inverter technology. As the integration of renewable energy sources into the grid expands, the grid codes for power system connection are progressively becoming more defined, leading to active discussions and evaluations in this area. In this paper, we propose a method for selecting optimal reactive power compensation capacity when multiple offshore wind farms are integrated and connected through a shared interconnection facility to comply with grid codes. Based on the requirements of the grid code, we analyze the reactive power compensation and excessive stability of the 400MW wind power generation site under development in the southwest sea of Jeonbuk. This analysis involves constructing a generation site database using PSS/E (Power System Simulation for Engineering), incorporating turbine layouts and cable data. The study calculates reactive power due to charging current in internal and external network cables and determines the reactive power compensation capacity at the interconnection point. Additionally, static and dynamic stability assessments are conducted by integrating with the power system database.
Korea prepares for potential floods by designating June 21st to September 20th as the flood season. However, many dams in Korea have suffered from extreme floods caused by different climate patterns, as in the case of the longest consecutive rain of 54 days in the 2020's flood season. In this context, various studies have tried to develop novel methodologies to reduce flood damage, but no study has ever dealt with the validity of the current statutory flood season thus far. This study first checked the validity of the current flood season through the observation data in the 21st century and proved that the current flood season does not consider the effects of increasing precipitation trends and the changing regional rainfall characteristics. In order to deal with these limitations, this study suggested seven new alternative flood seasons in the research area. The rigid reservoir operation method (ROM) was used for reservoir simulation, and the long short-term memory (LSTM) model was used to derive predicted inflow. Finally, all alternatives were evaluated based on whether if they exceeded the design discharge of the dam and the design flood of the river. As a result, the floods in the shifted period were reduced by 0.068% and 0.33% in terms of frequency and duration, and the magnitude also decreased by 24.6%, respectively. During this period, the second evaluation method also demonstrated that flood decreased from four to two occurrences. As the result of this study, the authors expect a formal reassessment of the flood season to take place, which will ultimately lead to the preemptive flood response to changing precipitation patterns.
Journal of the Korean Society of Marine Environment & Safety
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v.30
no.2
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pp.200-208
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2024
The occurrence a fire on a training ship with a large number of people on board can lead to severe casualties. Hence the Seafarers' Act and Safety Life At Sea(SOLAS) emphasizes the importance of the abandon ship drill. Therefore, in this study, the training ship of Mokpo National Maritime University, Segero, which has a large number of people on board, was selected as the target ship and the likelihood and severity of fire accidents on each deck were predicted through the preliminary hazard analysis(PHA) qualitative risk assessment. Additionally, assuming a fire in a high-risk area, a simulation of evacuation time and population density was performed to quantitatively predict the risk. The the total evacuation time was predicted to be the longest at 501s in the meal time scenario, in which the population distribution was concentrated in one area. Depending on the scenario, some decks had relatively high population densities of over 1.4pers/m2, preventing stagnation in the number of evacuees. The results of this study are expected to be used as basic data to develop training scenarios for training ships by quantifying evacuation time and population density according to various evacuation scenarios, and the research can be expanded in the future through comparison of mathematical models and experimental values.
Since the stock market is driven by the expectation of traders, studies have been conducted to predict stock price movements through analysis of various sources of text data. In order to predict stock price movements, research has been conducted not only on the relationship between text data and fluctuations in stock prices, but also on the trading stocks based on news articles and social media responses. Studies that predict the movements of stock prices have also applied classification algorithms with constructing term-document matrix in the same way as other text mining approaches. Because the document contains a lot of words, it is better to select words that contribute more for building a term-document matrix. Based on the frequency of words, words that show too little frequency or importance are removed. It also selects words according to their contribution by measuring the degree to which a word contributes to correctly classifying a document. The basic idea of constructing a term-document matrix was to collect all the documents to be analyzed and to select and use the words that have an influence on the classification. In this study, we analyze the documents for each individual item and select the words that are irrelevant for all categories as neutral words. We extract the words around the selected neutral word and use it to generate the term-document matrix. The neutral word itself starts with the idea that the stock movement is less related to the existence of the neutral words, and that the surrounding words of the neutral word are more likely to affect the stock price movements. And apply it to the algorithm that classifies the stock price fluctuations with the generated term-document matrix. In this study, we firstly removed stop words and selected neutral words for each stock. And we used a method to exclude words that are included in news articles for other stocks among the selected words. Through the online news portal, we collected four months of news articles on the top 10 market cap stocks. We split the news articles into 3 month news data as training data and apply the remaining one month news articles to the model to predict the stock price movements of the next day. We used SVM, Boosting and Random Forest for building models and predicting the movements of stock prices. The stock market opened for four months (2016/02/01 ~ 2016/05/31) for a total of 80 days, using the initial 60 days as a training set and the remaining 20 days as a test set. The proposed word - based algorithm in this study showed better classification performance than the word selection method based on sparsity. This study predicted stock price volatility by collecting and analyzing news articles of the top 10 stocks in market cap. We used the term - document matrix based classification model to estimate the stock price fluctuations and compared the performance of the existing sparse - based word extraction method and the suggested method of removing words from the term - document matrix. The suggested method differs from the word extraction method in that it uses not only the news articles for the corresponding stock but also other news items to determine the words to extract. In other words, it removed not only the words that appeared in all the increase and decrease but also the words that appeared common in the news for other stocks. When the prediction accuracy was compared, the suggested method showed higher accuracy. The limitation of this study is that the stock price prediction was set up to classify the rise and fall, and the experiment was conducted only for the top ten stocks. The 10 stocks used in the experiment do not represent the entire stock market. In addition, it is difficult to show the investment performance because stock price fluctuation and profit rate may be different. Therefore, it is necessary to study the research using more stocks and the yield prediction through trading simulation.
Han Youngyih;Chu Sung Sil;Huh Seung Jae;Suh Chang-Ok
Radiation Oncology Journal
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v.21
no.3
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pp.238-244
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2003
Purpose: The Planning of High-Dose-Rate (HDR) brachytherapy treatments are becoming individualized and more dependent on the treatment planning system. Therefore, computer software has been developed to perform independent point dose calculations with the integration of an isodose distribution curve display into the patient anatomy images. Meterials and Methods: As primary input data, the program takes patients'planning data including the source dwell positions, dwell times and the doses at reference points, computed by an HDR treatment planning system (TPS). Dosimetric calculations were peformed in a $10\times12\times10\;Cm^3$ grid space using the Interstitial Collaborative Working Group (ICWG) formalism and an anisotropy table for the HDR Iridium-192 source. The computed doses at the reference points were automatically compared with the relevant results of the TPS. The MR and simulation film images were then imported and the isodose distributions on the axial, sagittal and coronal planes intersecting the point selected by a user were superimposed on the imported images and then displayed. The accuracy of the software was tested in three benchmark plans peformed by Gamma-Med 12i TPS (MDS Nordion, Germany). Nine patients'plans generated by Plato (Nucletron Corporation, The Netherlands) were verified by the developed software. Results: The absolute doses computed by the developed software agreed with the commercial TPS results within an accuracy of $2.8\%$ in the benchmark plans. The isodose distribution plots showed excellent agreements with the exception of the tip legion of the source's longitudinal axis where a slight deviation was observed. In clinical plans, the secondary dose calculations had, on average, about a $3.4\%$ deviation from the TPS plans. Conclusion: The accurate validation of complicate treatment plans is possible with the developed software and the qualify of the HDR treatment plan can be improved with the isodose display integrated into the patient anatomy information.
The use of cone-beam computed tomography(CBCT) has been proposed for guiding the delivery of radiation therapy. A kilovoltage imaging system capable of radiography, fluoroscopy, and cone-beam computed tomography(CT) has been integrated with a medical linear accelerator. A standard clinical linear accelerator, operating in arc therapy mode, and an amorphous-silicon (a-Si) with an on-board electronic portal imager can be used to treat palliative patient and verify the patient's position prior to treatment. On-board CBCT images are used to generate patient geometric models to assist patient setup. The image data can also, potentially, be used for dose reconstruction in combination with the fluence maps from treatment plan. In this study, the accuracy of Hounsfield Units of CBCT images as well as the accuracy of dose calculations based on CBCT images of a phantom and compared the results with those of using CT simulator images. Phantom and patient studies were carried out to evaluate the achievable accuracy in using CBCT and CT stimulator for dose calculation. Relative electron density as a function of HU was obtained for both planning CT stimulator and CBCT using a Catphan-600 (The Phantom Laboratory, USA) calibration phantom. A clinical treatment planning system was employed for CT stimulator and CBCT based dose calculations and subsequent comparisons. The dosimetric consequence as the result of HU variation in CBCT was evaluated by comparing MU/cCy. The differences were about 2.7% (3-4MU/100cGy) in phantom and 2.5% (1-3MU/100cGy) in patients. The difference in HU values in Catphan was small. However, the magnitude of scatter and artifacts in CBCT images are affected by limitation of detector's FOV and patient's involuntary motions. CBCT images included scatters and artifacts due to In addition to guide the patient setup process, CBCT data acquired prior to the treatment be used to recalculate or verify the treatment plan based on the patient anatomy of the treatment area. And the CBCT has potential to become a very useful tool for on-line ART.)
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