• Title/Summary/Keyword: 재생기법

Search Result 850, Processing Time 0.028 seconds

Risk Assessment of Stationary Hydrogen Refueling Station by Section in Dispenser Module (고정식 수소충전소에서의 Dispenser Module 내 구역별 위험성 평가)

  • SangJin Lim;MinGi Kim;Su Kim;YoonHo Lee
    • Journal of the Korean Society of Marine Environment & Safety
    • /
    • v.29 no.1
    • /
    • pp.76-85
    • /
    • 2023
  • Demand for hydrogen as a renewable energy resource is increasing. However, unlike conventional fossil fuels, hydrogen requires a dedicated refueling station for fuel supply. A risk assessment of hydrogen refueling stations must be undertaken to secure the infrastructure. Therefore, in this study, a risk assessment for hydrogen refueling stations was conducted through both qualitative and quantitative risk assessments. For the qualitative evaluation, the hydrogen dispenser module was evaluated as two nodes using the hazard and operability (HAZOP) analysis. The risk due to filter clogging and high-pressure accidents was evaluated to be high according to the criticality estimation matrix. For the quantitative risk assessment, the Hydrogen Korea Risk Assessment Module (Hy-KoRAM) was used to indicate the shape of the fire and the range of damage impact, and to evaluate the individual and social risks. The individual risk level was determined of to be as low as reasonably practicable (ALARP). Additional safety measures proposed include placing the hydrogen refueling station about 100m away from public facilities. The social risk level was derived as 1E-04/year, with a frequency of approximately 10 deaths, falling within the ALARP range. As a result of the qualitative and quantitative risk assessments, additional safety measures for the process and a safety improvement plan are proposed through the establishment of a restricted area near the hydrogen refueling station.

Developing Integrated Transportation Service Index for Encouraging Transit-oriented Development (TOD형 개발 촉진을 위한 통합교통서비스 지표의 개발)

  • Hwang, Kee Yeon;Shin, Sang Young;Cho, Yong Hak;Sohn, Kee Min
    • KSCE Journal of Civil and Environmental Engineering Research
    • /
    • v.28 no.1D
    • /
    • pp.1-10
    • /
    • 2008
  • Recently, the Seoul Metropolitan Government (SMG) has initiated several urban redevelopment projects to revitalize the downtown well equipped for transit oriented development (TOD). Since, TOD should incur higher density development in our context, it has negative impacts on travel patterns, congestion, and urban environmental quality. The purpose of this study is to develop new transportation service index which can facilitate higher density TOD. This study includes relevant foreign case studies, the development of multimodal transportation index, and the impact analysis of TOD when it is applied in the downtown Seoul. In chapter III, it developed a so-called ITLOS, new multimodal transportation service index which shows the possibility of accommodating further development by integrating roadway service index with public transportation service index. The study sets ten policy scenarios by varying densities, and run the Seoul Congestion Management Model (SECOMM) to estimate the sustainable transportation impacts of TOD in the downtown. Travel speed index that only represents the availability of road capacity for development reveal that higher density development in the downtown can deteriorate traffic congestion while improving region-wide transportation level of service in Seoul. Also, it is proved that higher density development is more feasible when using ITLOS as the index because it considers not only available road capacity but subway capacity in the analysis area.

Extending StarGAN-VC to Unseen Speakers Using RawNet3 Speaker Representation (RawNet3 화자 표현을 활용한 임의의 화자 간 음성 변환을 위한 StarGAN의 확장)

  • Bogyung Park;Somin Park;Hyunki Hong
    • KIPS Transactions on Software and Data Engineering
    • /
    • v.12 no.7
    • /
    • pp.303-314
    • /
    • 2023
  • Voice conversion, a technology that allows an individual's speech data to be regenerated with the acoustic properties(tone, cadence, gender) of another, has countless applications in education, communication, and entertainment. This paper proposes an approach based on the StarGAN-VC model that generates realistic-sounding speech without requiring parallel utterances. To overcome the constraints of the existing StarGAN-VC model that utilizes one-hot vectors of original and target speaker information, this paper extracts feature vectors of target speakers using a pre-trained version of Rawnet3. This results in a latent space where voice conversion can be performed without direct speaker-to-speaker mappings, enabling an any-to-any structure. In addition to the loss terms used in the original StarGAN-VC model, Wasserstein distance is used as a loss term to ensure that generated voice segments match the acoustic properties of the target voice. Two Time-Scale Update Rule (TTUR) is also used to facilitate stable training. Experimental results show that the proposed method outperforms previous methods, including the StarGAN-VC network on which it was based.

Very Short- and Long-Term Prediction Method for Solar Power (초 장단기 통합 태양광 발전량 예측 기법)

  • Mun Seop Yun;Se Ryung Lim;Han Seung Jang
    • The Journal of the Korea institute of electronic communication sciences
    • /
    • v.18 no.6
    • /
    • pp.1143-1150
    • /
    • 2023
  • The global climate crisis and the implementation of low-carbon policies have led to a growing interest in renewable energy and a growing number of related industries. Among them, solar power is attracting attention as a representative eco-friendly energy that does not deplete and does not emit pollutants or greenhouse gases. As a result, the supplement of solar power facility is increasing all over the world. However, solar power is easily affected by the environment such as geography and weather, so accurate solar power forecast is important for stable operation and efficient management. However, it is very hard to predict the exact amount of solar power using statistical methods. In addition, the conventional prediction methods have focused on only short- or long-term prediction, which causes to take long time to obtain various prediction models with different prediction horizons. Therefore, this study utilizes a many-to-many structure of a recurrent neural network (RNN) to integrate short-term and long-term predictions of solar power generation. We compare various RNN-based very short- and long-term prediction methods for solar power in terms of MSE and R2 values.

Basic Research on the Possibility of Developing a Landscape Perceptual Response Prediction Model Using Artificial Intelligence - Focusing on Machine Learning Techniques - (인공지능을 활용한 경관 지각반응 예측모델 개발 가능성 기초연구 - 머신러닝 기법을 중심으로 -)

  • Kim, Jin-Pyo;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.51 no.3
    • /
    • pp.70-82
    • /
    • 2023
  • The recent surge of IT and data acquisition is shifting the paradigm in all aspects of life, and these advances are also affecting academic fields. Research topics and methods are being improved through academic exchange and connections. In particular, data-based research methods are employed in various academic fields, including landscape architecture, where continuous research is needed. Therefore, this study aims to investigate the possibility of developing a landscape preference evaluation and prediction model using machine learning, a branch of Artificial Intelligence, reflecting the current situation. To achieve the goal of this study, machine learning techniques were applied to the landscaping field to build a landscape preference evaluation and prediction model to verify the simulation accuracy of the model. For this, wind power facility landscape images, recently attracting attention as a renewable energy source, were selected as the research objects. For analysis, images of the wind power facility landscapes were collected using web crawling techniques, and an analysis dataset was built. Orange version 3.33, a program from the University of Ljubljana was used for machine learning analysis to derive a prediction model with excellent performance. IA model that integrates the evaluation criteria of machine learning and a separate model structure for the evaluation criteria were used to generate a model using kNN, SVM, Random Forest, Logistic Regression, and Neural Network algorithms suitable for machine learning classification models. The performance evaluation of the generated models was conducted to derive the most suitable prediction model. The prediction model derived in this study separately evaluates three evaluation criteria, including classification by type of landscape, classification by distance between landscape and target, and classification by preference, and then synthesizes and predicts results. As a result of the study, a prediction model with a high accuracy of 0.986 for the evaluation criterion according to the type of landscape, 0.973 for the evaluation criterion according to the distance, and 0.952 for the evaluation criterion according to the preference was developed, and it can be seen that the verification process through the evaluation of data prediction results exceeds the required performance value of the model. As an experimental attempt to investigate the possibility of developing a prediction model using machine learning in landscape-related research, this study was able to confirm the possibility of creating a high-performance prediction model by building a data set through the collection and refinement of image data and subsequently utilizing it in landscape-related research fields. Based on the results, implications, and limitations of this study, it is believed that it is possible to develop various types of landscape prediction models, including wind power facility natural, and cultural landscapes. Machine learning techniques can be more useful and valuable in the field of landscape architecture by exploring and applying research methods appropriate to the topic, reducing the time of data classification through the study of a model that classifies images according to landscape types or analyzing the importance of landscape planning factors through the analysis of landscape prediction factors using machine learning.

Bias Correction for GCM Long-term Prediction using Nonstationary Quantile Mapping (비정상성 분위사상법을 이용한 GCM 장기예측 편차보정)

  • Moon, Soojin;Kim, Jungjoong;Kang, Boosik
    • Journal of Korea Water Resources Association
    • /
    • v.46 no.8
    • /
    • pp.833-842
    • /
    • 2013
  • The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

Introduction of region-based site functions into the traditional market environmental support funding policy development (재래시장 환경개선 지원정책 개발에서의 지역 장소적 기능 도입)

  • Jeong, Dae-Yong;Lee, Se-Ho
    • Proceedings of the Korean DIstribution Association Conference
    • /
    • 2005.05a
    • /
    • pp.383-405
    • /
    • 2005
  • The traditional market is foremost a regionally positioned place, wherein the market directly represents regional and cultural centered traits while it plays an important role in the circulation of facilities through reciprocal, informative and cultural exchanges while sewing to form local communities. The traditional market in Korea is one of representative retail businesses and premodern marketing techniques by family owned business of less than five members such as product management, purchase method, and marketing patterns etc. Since the 1990s, the appearance of new circulation-type businesses and large discount convenience stores escalated the loss of traditional competitiveness, increased the living standard of customers, changed purchasing patterns, and expanded the ubiquity of the Internet. All of these changes in external circulation circumstances have led the traditional markets to lose their place in the economy. The traditional market should revive on a regional site basis through the formation of a community of regional neighbors and through knowledge-sharing that leads to the creation of wealth. For the purpose of creating a wealth in a place, the following components are necessary: 1) a facility suitable for the spatial place of the present, 2)trust built through exchanges within the changing market environment, which would simultaneously satisfy customer's desires, 3) international bench marking on cases such as regionally centered TCM (England), BID (USA), and TMO (Japan) so that the market unit of store placement transfers from a spot policy to a line policy, 4)conversion of communicative conception through a surface policy approach centered around a macro-region perspective. The budget of the traditional market funding policy was operational between 2001 and 2004, serving as a counter move to solve the problem of the old traditional market through government intervention in regional economies to promote national economic strength. This national treasury funding project was centered on environmental improvement, research corps, and business modernization through the expenditure of 3,853 hundred million won (Korean currency). However, the effectiveness of this project has yet to be to proven through investigation. Furthermore, in promoting this funding support project, a lack of professionalism among merchants in the market led to constant limitations in comprehensive striving strategies, reduced capabilities in middle-and long-term plan setup, and created reductions in voluntary merchant agreement solutions. The traditional market should go beyond mere physical place and ordinary products creative site strategies employing the communicative approach must accompany these strategies to make the market a new regional and spatial living place. Thus, regarding recent paradigm changes and the introduction of region-based site functions into the traditional market, acquiring a conversion of direction into the newly developed project is essential to reinvestigate the traditional market composed of cultural and economic meanings, for the purpose of the research. Excavating social policy demands through the comparative analysis of domestic and international cases as well as innovative and expert management leadership development for NPO or NGO civil entrepreneurs through advanced case research on present promotion methods is extremely important. Discovering the seeds of the cultural contents industry cored around regional resource usages, commercializing regionally reknowned products, and constructing complex cultural living places for regional networks are especially important. In order to accelerate these solutions, a comprehensive and systemized approach research operated within a mentor academy system is required, as research will reveal distinctive traits of the traditional market in the aging society.

  • PDF

Screening of cryoprotectants (CPAs) for cryopreservation in the Nitzschia sp. of marine microalgae (해양 규조류 Nitzschia sp.의 초저온동결보존을 위한 보존제의 영향 분석)

  • Lee, In Hye;Jeon, Ji Young;Kim, Kyeung Mi;Kang, Myung suk
    • Journal of Plant Biotechnology
    • /
    • v.45 no.4
    • /
    • pp.400-408
    • /
    • 2018
  • Biodiversity has continued to degrade in the $21^{st}$ century due to global warming occasioned by destruction of the environment around the world.. The Nagoya protocol places Korea in a unique position to effectively develop and protect its domestic genetic resources. Microalgae under study in this research contains large amount of antioxidant substances such as beta carotene and astaxanthin, that can be used as biological resource owing to the large amounts of biomass that can be secured through photosynthesis. However, it is difficult to preserve it since cryopreservation method used for long-term preservation is yet to be developed. A basic study for long term cryopreservation was carried out on Nizschia frustulum and Nitzschia amabilis which belong to marine diatoms. As cryoprotectants (CPAs), glycerol, DMSO, and methanol which penetrate into cells were prepared at 5%, 10%, and 15% concentrations each, in case of methanol, it was tested at concentrations of 5%, 10% and 12% by its nature. Two kinds of microalgae, N. frustulum and N. amabilis, were diluted with $10^2$, $10^3$ and $10^4cells\;ml^{-1}$, respectively. The highest survival rate was shown at12% concentration of methanol, and the figures were $6.94{\pm}0.31%$ in N. frustulum and $8.85{\pm}0.16%$ in N. amabilis. As a result of 3 weeks cultivation of thawed microalgae after freezing, the result is shows that N. frustulum increased about 10 times faster and N. amabilis increased about 12 times the original concentration.

Analysis of Behavior of Seoullo 7017 Visitors - With a Focus on Text Mining and Social Network Analysis - (서울로 7017 방문자들의 이용행태 분석 -텍스트 마이닝과 소셜 네트워크 분석을 중심으로-)

  • Woo, Kyung-Sook;Suh, Joo-Hwan
    • Journal of the Korean Institute of Landscape Architecture
    • /
    • v.48 no.6
    • /
    • pp.16-24
    • /
    • 2020
  • The purpose of this study is to analyze the usage behavior of Seoullo 7017, the first public garden in Korea, to understand the usage status by analyzing blogs, and to present usage behavior and improvement plans for Seoullo 7017. From June 2017 to May 2020, after Seoullo 7017 was open to citizens, character data containing 'Seoullo 7017' in the title and contents of NAVER and·DAUM blogs were converted to text mining and socialization, a Big Data technique. The analysis was conducted using social network analysis. The summary of the research results is as follows. First of all, the ratio of men and women searching for Seoullo 7017 online is similar, and the regions that searched most are in the order of Seoul and Gyeonggi, and those in their 40s and 50s were the most interested. In other words, it can be seen that there is a lack of interest in regions other than Seoul and Gyeonggi and among those in their 10s, 20s, and 30s. The main behaviors of Seoullo 7017 are' night view' and 'walking', and the factors that affect culture and art are elements related to culture and art. If various programs and festivals are opened and actively promoted, the main behavior will be more varied. On the other hand, the main behavior that the users of Seoullo 7017 want is 'sit', which is a static behavior, but the physical conditions are not sufficient for the behavior to occur. Therefore, facilities that can cause sitting behavior, such as shades and benches must be improved to meet the needs of visitors. The peculiarity of the change in the behavior of Seoullo 7017 is that it is recognized as a good place to travel alone and a good place to walk alone as a public multi-use facility and group activities are restricted due to COVID-19. Accordingly, in a situation like the COVD-19 pandemic, more diverse behaviors can be derived in facilities where people can take a walk, etc., and the increase of various attractions and the satisfaction of users can be increased. Seoullo 7017, as Korea's first public pedestrian area, was created for urban regeneration and the efficient use of urban resources in areas beyond the meaning of public spaces and is a place with various values such as history, nature, welfare, culture, and tourism. However, as a result of the use behavior analysis, various behaviors did not occur in Seoullo 7017 as expected, and elements that hinder those major behaviors were derived. Based on these research results, it is necessary to understand the usage behavior of Seoullo 7017 and to establish a plan for spatial system and facility improvement, so that Seoullo 7017 can be an important place for urban residents and a driving force to revitalize the city.

State of Health and State of Charge Estimation of Li-ion Battery for Construction Equipment based on Dual Extended Kalman Filter (이중확장칼만필터(DEKF)를 기반한 건설장비용 리튬이온전지의 State of Charge(SOC) 및 State of Health(SOH) 추정)

  • Hong-Ryun Jung;Jun Ho Kim;Seung Woo Kim;Jong Hoon Kim;Eun Jin Kang;Jeong Woo Yun
    • Journal of the Microelectronics and Packaging Society
    • /
    • v.31 no.1
    • /
    • pp.16-22
    • /
    • 2024
  • Along with the high interest in electric vehicles and new renewable energy, there is a growing demand to apply lithium-ion batteries in the construction equipment industry. The capacity of heavy construction equipment that performs various tasks at construction sites is rapidly decreasing. Therefore, it is essential to accurately predict the state of batteries such as SOC (State of Charge) and SOH (State of Health). In this paper, the errors between actual electrochemical measurement data and estimated data were compared using the Dual Extended Kalman Filter (DEKF) algorithm that can estimate SOC and SOH at the same time. The prediction of battery charge state was analyzed by measuring OCV at SOC 5% intervals under 0.2C-rate conditions after the battery cell was fully charged, and the degradation state of the battery was predicted after 50 cycles of aging tests under various C-rate (0.2, 0.3, 0.5, 1.0, 1.5C rate) conditions. It was confirmed that the SOC and SOH estimation errors using DEKF tended to increase as the C-rate increased. It was confirmed that the SOC estimation using DEKF showed less than 6% at 0.2, 0.5, and 1C-rate. In addition, it was confirmed that the SOH estimation results showed good performance within the maximum error of 1.0% and 1.3% at 0.2 and 0.3C-rate, respectively. Also, it was confirmed that the estimation error also increased from 1.5% to 2% as the C-rate increased from 0.5 to 1.5C-rate. However, this result shows that all SOH estimation results using DEKF were excellent within about 2%.