• 제목/요약/키워드: model-driven

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Study on the Anchovy Boat Seine - II - On The Hydrodynamic Resistance and Performance of Patti-net (기선권현망의 연구 II - 파치망의 유체저항과 그물꼴에 관하여 -)

  • Lee, Byoung-Gee;Su, Young-Tae;Han, Hi-Soo
    • Journal of the Korean Society of Fisheries and Ocean Technology
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    • v.14 no.2
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    • pp.63-68
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    • 1978
  • A boat seine has been used as a major fishing gear for catching anchovy (Engraulis japonica) in the southern coastal waters of Korea since the 1920s. Since the 1950s some improvement from the original seine has been made; powered boats equipped with net hauler has been used instead of rowing boats with hand-driven capstan, and the seining method has been changed into the trawling method. But even now, there are many problems to be solved in the view point of decreasing man power without decreasing catching efficiency. For the purpose, patti-net has been introduced from Japan and experimented on the commercial base since 1972, and it was known that the patti-net could be operated with man power as half as needed in the coventional net, but catching efficiency was not so desirable. Therefore, the study on the characteristics of it were required. The authors carried out a model experiment with a Qne-twentieth scale model net towed by a powered boat on the sea. The obtained results run as follows: 1. Hydrodynamic resistance of the model net can be explained as $R_p=69.6 V_{I.66}$ $R_h=37 v^2$ where $R_p$ and $R_b$ denote the resistance of the whole gear and the cod end in kg respectively, and v the towing speed in mlsec. 2. Performance of wing and cod end showed no deformation such as observed at the conventional net. 3. The ratio of opening at the entrance of bag net to that of cod end showed about 2: 1. Therefore, when we intend to enlarge the net to be able to operate in the deep fishing ground, the cod end should be enlarged in the same proportion and increased towing power is needed .. Then, it will be better to increase the ratio for increasing fishing efficiency without increasing towing power.

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Minimizing Estimation Errors of a Wind Velocity Forecasting Technique That Functions as an Early Warning System in the Agricultural Sector (농업기상재해 조기경보시스템의 풍속 예측 기법 개선 연구)

  • Kim, Soo-ock;Park, Joo-Hyeon;Hwang, Kyu-Hong
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.24 no.2
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    • pp.63-77
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    • 2022
  • Our aim was to reduce estimation errors of a wind velocity model used as an early warning system for weather risk management in the agricultural sector. The Rural Development Administration (RDA) agricultural weather observation network's wind velocity data and its corresponding estimated data from January to December 2020 were used to calculate linear regression equations (Y = aX + b). In each linear regression, the wind estimation error at 87 points and eight time slots per day (00:00, 03:00, 06:00, 09.00, 12.00, 15.00, 18.00, and 21:00) is the dependent variable (Y), while the estimated wind velocity is the independent variable (X). When the correlation coefficient exceeded 0.5, the regression equation was used as the wind velocity correction equation. In contrast, when the correlation coefficient was less than 0.5, the mean error (ME) at the corresponding points and time slots was substituted as the correction value instead of the regression equation. To enable the use of wind velocity model at a national scale, a distribution map with a grid resolution of 250 m was created. This objective was achieved b y performing a spatial interpolation with an inverse distance weighted (IDW) technique using the regression coefficients (a and b), the correlation coefficient (R), and the ME values for the 87 points and eight time slots. Interpolated grid values for 13 weather observation points in rural areas were then extracted. The wind velocity estimation errors for 13 points from January to December 2019 were corrected and compared with the system's values. After correction, the mean ME of the wind velocities reduced from 0.68 m/s to 0.45 m/s, while the mean RMSE reduced from 1.30 m/s to 1.05 m/s. In conclusion, the system's wind velocities were overestimated across all time slots; however, after the correction model was applied, the overestimation reduced in all time slots, except for 15:00. The ME and RMSE improved b y 33% and 19.2%, respectively. In our system, the warning for wind damage risk to crops is driven by the daily maximum wind speed derived from the daily mean wind speed obtained eight times per day. This approach is expected to reduce false alarms within the context of strong wind risk, by reducing the overestimation of wind velocities.

From a Defecation Alert System to a Smart Bottle: Understanding Lean Startup Methodology from the Case of Startup "L" (배변알리미에서 스마트바틀 출시까지: 스타트업 L사 사례로 본 린 스타트업 실천방안)

  • Sunkyung Park;Ju-Young Park
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.18 no.5
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    • pp.91-107
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    • 2023
  • Lean startup is a concept that combines the words "lean," meaning an efficient way of running a business, and "startup," meaning a new business. It is often cited as a strategy for minimizing failure in early-stage businesses, especially in software-based startups. By scrutinizing the case of a startup L, this study suggests that lean startup methodology(LSM) can be useful for hardware and manufacturing companies and identifies ways for early startups to successfully implement LSM. To this end, the study explained the core of LSM including the concepts of hypothesis-driven approach, BML feedback loop, minimum viable product(MVP), and pivot. Five criteria to evaluate the successful implementation of LSM were derived from the core concepts and applied to evaluate the case of startup L . The early startup L pivoted its main business model from defecation alert system for patients with limited mobility to one for infants or toddlers, and finally to a smart bottle for infants. In developing the former two products, analyzed from LSM's perspective, company L neither established a specific customer value proposition for its startup idea and nor verified it through MVP experiment, thus failed to create a BML feedback loop. However, through two rounds of pivots, startup L discovered new target customers and customer needs, and was able to establish a successful business model by repeatedly experimenting with MVPs with minimal effort and time. In other words, Company L's case shows that it is essential to go through the customer-market validation stage at the beginning of the business, and that it should be done through an MVP method that does not waste the startup's time and resources. It also shows that it is necessary to abandon and pivot a product or service that customers do not want, even if it is technically superior and functionally complete. Lastly, the study proves that the lean startup methodology is not limited to the software industry, but can also be applied to technology-based hardware industry. The findings of this study can be used as guidelines and methodologies for early-stage companies to minimize failures and to accelerate the process of establishing a business model, scaling up, and going global.

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Study on data preprocessing methods for considering snow accumulation and snow melt in dam inflow prediction using machine learning & deep learning models (머신러닝&딥러닝 모델을 활용한 댐 일유입량 예측시 융적설을 고려하기 위한 데이터 전처리에 대한 방법 연구)

  • Jo, Youngsik;Jung, Kwansue
    • Journal of Korea Water Resources Association
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    • v.57 no.1
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    • pp.35-44
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    • 2024
  • Research in dam inflow prediction has actively explored the utilization of data-driven machine learning and deep learning (ML&DL) tools across diverse domains. Enhancing not just the inherent model performance but also accounting for model characteristics and preprocessing data are crucial elements for precise dam inflow prediction. Particularly, existing rainfall data, derived from snowfall amounts through heating facilities, introduces distortions in the correlation between snow accumulation and rainfall, especially in dam basins influenced by snow accumulation, such as Soyang Dam. This study focuses on the preprocessing of rainfall data essential for the application of ML&DL models in predicting dam inflow in basins affected by snow accumulation. This is vital to address phenomena like reduced outflow during winter due to low snowfall and increased outflow during spring despite minimal or no rain, both of which are physical occurrences. Three machine learning models (SVM, RF, LGBM) and two deep learning models (LSTM, TCN) were built by combining rainfall and inflow series. With optimal hyperparameter tuning, the appropriate model was selected, resulting in a high level of predictive performance with NSE ranging from 0.842 to 0.894. Moreover, to generate rainfall correction data considering snow accumulation, a simulated snow accumulation algorithm was developed. Applying this correction to machine learning and deep learning models yielded NSE values ranging from 0.841 to 0.896, indicating a similarly high level of predictive performance compared to the pre-snow accumulation application. Notably, during the snow accumulation period, adjusting rainfall during the training phase was observed to lead to a more accurate simulation of observed inflow when predicted. This underscores the importance of thoughtful data preprocessing, taking into account physical factors such as snowfall and snowmelt, in constructing data models.

Optimization of Multiclass Support Vector Machine using Genetic Algorithm: Application to the Prediction of Corporate Credit Rating (유전자 알고리즘을 이용한 다분류 SVM의 최적화: 기업신용등급 예측에의 응용)

  • Ahn, Hyunchul
    • Information Systems Review
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    • v.16 no.3
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    • pp.161-177
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    • 2014
  • Corporate credit rating assessment consists of complicated processes in which various factors describing a company are taken into consideration. Such assessment is known to be very expensive since domain experts should be employed to assess the ratings. As a result, the data-driven corporate credit rating prediction using statistical and artificial intelligence (AI) techniques has received considerable attention from researchers and practitioners. In particular, statistical methods such as multiple discriminant analysis (MDA) and multinomial logistic regression analysis (MLOGIT), and AI methods including case-based reasoning (CBR), artificial neural network (ANN), and multiclass support vector machine (MSVM) have been applied to corporate credit rating.2) Among them, MSVM has recently become popular because of its robustness and high prediction accuracy. In this study, we propose a novel optimized MSVM model, and appy it to corporate credit rating prediction in order to enhance the accuracy. Our model, named 'GAMSVM (Genetic Algorithm-optimized Multiclass Support Vector Machine),' is designed to simultaneously optimize the kernel parameters and the feature subset selection. Prior studies like Lorena and de Carvalho (2008), and Chatterjee (2013) show that proper kernel parameters may improve the performance of MSVMs. Also, the results from the studies such as Shieh and Yang (2008) and Chatterjee (2013) imply that appropriate feature selection may lead to higher prediction accuracy. Based on these prior studies, we propose to apply GAMSVM to corporate credit rating prediction. As a tool for optimizing the kernel parameters and the feature subset selection, we suggest genetic algorithm (GA). GA is known as an efficient and effective search method that attempts to simulate the biological evolution phenomenon. By applying genetic operations such as selection, crossover, and mutation, it is designed to gradually improve the search results. Especially, mutation operator prevents GA from falling into the local optima, thus we can find the globally optimal or near-optimal solution using it. GA has popularly been applied to search optimal parameters or feature subset selections of AI techniques including MSVM. With these reasons, we also adopt GA as an optimization tool. To empirically validate the usefulness of GAMSVM, we applied it to a real-world case of credit rating in Korea. Our application is in bond rating, which is the most frequently studied area of credit rating for specific debt issues or other financial obligations. The experimental dataset was collected from a large credit rating company in South Korea. It contained 39 financial ratios of 1,295 companies in the manufacturing industry, and their credit ratings. Using various statistical methods including the one-way ANOVA and the stepwise MDA, we selected 14 financial ratios as the candidate independent variables. The dependent variable, i.e. credit rating, was labeled as four classes: 1(A1); 2(A2); 3(A3); 4(B and C). 80 percent of total data for each class was used for training, and remaining 20 percent was used for validation. And, to overcome small sample size, we applied five-fold cross validation to our dataset. In order to examine the competitiveness of the proposed model, we also experimented several comparative models including MDA, MLOGIT, CBR, ANN and MSVM. In case of MSVM, we adopted One-Against-One (OAO) and DAGSVM (Directed Acyclic Graph SVM) approaches because they are known to be the most accurate approaches among various MSVM approaches. GAMSVM was implemented using LIBSVM-an open-source software, and Evolver 5.5-a commercial software enables GA. Other comparative models were experimented using various statistical and AI packages such as SPSS for Windows, Neuroshell, and Microsoft Excel VBA (Visual Basic for Applications). Experimental results showed that the proposed model-GAMSVM-outperformed all the competitive models. In addition, the model was found to use less independent variables, but to show higher accuracy. In our experiments, five variables such as X7 (total debt), X9 (sales per employee), X13 (years after founded), X15 (accumulated earning to total asset), and X39 (the index related to the cash flows from operating activity) were found to be the most important factors in predicting the corporate credit ratings. However, the values of the finally selected kernel parameters were found to be almost same among the data subsets. To examine whether the predictive performance of GAMSVM was significantly greater than those of other models, we used the McNemar test. As a result, we found that GAMSVM was better than MDA, MLOGIT, CBR, and ANN at the 1% significance level, and better than OAO and DAGSVM at the 5% significance level.

Computational Fluid Dynamics Study of Channel Geometric Effect for Fischer-Tropsch Microchannel Reactor (전산유체역학을 이용한 Fischer-Tropsch 마이크로채널 반응기의 채널 구조 영향 분석)

  • Na, Jonggeol;Jung, Ikhwan;Kshetrimayum, Krishnadash S.;Park, Seongho;Park, Chansaem;Han, Chonghun
    • Korean Chemical Engineering Research
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    • v.52 no.6
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    • pp.826-833
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    • 2014
  • Driven by both environmental and economic reasons, the development of small to medium scale GTL(gas-to-liquid) process for offshore applications and for utilizing other stranded or associated gas has recently been studied increasingly. Microchannel GTL reactors have been prefrered over the conventional GTL reactors for such applications, due to its compactness, and additional advantages of small heat and mass transfer distance desired for high heat transfer performance and reactor conversion. In this work, multi-microchannel reactor was simulated by using commercial CFD code, ANSYS FLUENT, to study the geometric effect of the microchannels on the heat transfer phenomena. A heat generation curve was first calculated by modeling a Fischer-Tropsch reaction in a single-microchannel reactor model using Matlab-ASPEN integration platform. The calculated heat generation curve was implemented to the CFD model. Four design variables based on the microchannel geometry namely coolant channel width, coolant channel height, coolant channel to process channel distance, and coolant channel to coolant channel distance, were selected for calculating three dependent variables namely, heat flux, maximum temperature of coolant channel, and maximum temperature of process channel. The simulation results were visualized to understand the effects of the design variables on the dependent variables. Heat flux and maximum temperature of cooling channel and process channel were found to be increasing when coolant channel width and height were decreased. Coolant channel to process channel distance was found to have no effect on the heat transfer phenomena. Finally, total heat flux was found to be increasing and maximum coolant channel temperature to be decreasing when coolant channel to coolant channel distance was decreased. Using the qualitative trend revealed from the present study, an appropriate process channel and coolant channel geometry along with the distance between the adjacent channels can be recommended for a microchannel reactor that meet a desired reactor performance on heat transfer phenomena and hence reactor conversion of a Fischer-Tropsch microchannel reactor.

OPERATIONAL MODEL OF TIME-KEEPING SYSTEMS OF HEUMGYEONGGAK-NU (흠경각루 시보시스템의 작동모델)

  • KIM, SANG HYUK;YUN, YONG-HYUN;MIHN, BYEONG-HEE;LEEM, BYONG GUEN;YOON, MYUNG KYOON;LEEM, BYONG SI
    • Publications of The Korean Astronomical Society
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    • v.34 no.3
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    • pp.31-40
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    • 2019
  • We study the internal structure under the artificial mountain of Heumkyeonggak-nu, a Korean water-powered clock in the early Joseon dynasty. All the puppets on the artificial mountain are driven by the rotational force generated by the water wheel at their designated time. We design a model that work with three parts of the artificial mountain. At the upper part of the artificial mountain to the east, west, north and south, there are four puppets called the Four Mystical Animal Divinity and four ladies called the Jade Lady respectively. The former rotates a quarter every double hour and the latter rings the bell every hour. In the middle part of this mountain is the timekeeping platform with four puppets; the Timekeeping Official (Hour Jack), the Bell-, Drum-, and Gong-Warriors. The Hour Jack controls time with three warriors each hitting his own bell, drum, and gong, respectively. In the plain there are 12 Jade Lady puppets (the lower ladies) combined with 12 Oriental Animal Deity puppets. In his own time a lady doll pops out of the hole and her animal doll gets up. Two hours later, the animal deity lies down and his lady hides in the artificial plain. These puppets are regularly moved by the signal such as iron balls, bumps, levers, and so on. We can use balls and bumps to explain the concept of the Jujeon system. Iron balls were used to manipulate puppets of the timekeeping mechanism in Borugak-nu, another Korean water-powered clock in Joseon dynasty, which was developed earlier than Heumgyeonggak-nu. According to the North Korea's previous study (Choi, 1974), it is obvious that bumps were used in the internal structure of Heumgyeonggak-nu. In 1669, The armillary clock made by Song, I-young was also utilized bumps. Finally we presented mock-ups of three timekeeping systems.

Water Balance Projection Using Climate Change Scenarios in the Korean Peninsula (기후변화 시나리오를 활용한 미래 한반도 물수급 전망)

  • Kim, Cho-Rong;Kim, Young-Oh;Seo, Seung Beom;Choi, Su-Woong
    • Journal of Korea Water Resources Association
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    • v.46 no.8
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    • pp.807-819
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    • 2013
  • This study proposes a new methodology for future water balance projection considering climate change by assigning a weight to each scenario instead of inputting future streamflows based on GCMs into a water balance model directly. K-nearest neighbor algorithm was employed to assign weights and streamflows in non-flood period (October to the following June) was selected as the criterion for assigning weights. GCM-driven precipitation was input to TANK model to simulate future streamflow scenarios and Quantile Mapping was applied to correct bias between GCM hindcast and historical data. Based on these bias-corrected streamflows, different weights were assigned to each streamflow scenarios to calculate water shortage for the projection periods; 2020s (2010~2039), 2050s (2040~2069), and 2080s (2070~2099). As a result by applying the proposed methodology to project water shortage over the Korean Peninsula, average water shortage for 2020s is projected to increase to 10~32% comparing to the basis (1967~2003). In addition, according to getting decreased in streamflows in non-flood period gradually by 2080s, average water shortage for 2080s is projected to increase up to 97% (516.5 million $m^3/yr$) as maximum comparing to the basis. While the existing research on climate change gives radical increase in future water shortage, the results projected by the weighting method shows conservative change. This study has significance in the applicability of water balance projection regarding climate change, keeping the existing framework of national water resources planning and this lessens the confusion for decision-makers in water sectors.

The Introduction of archival science and the renovation of records Management(since 1999) (기록학의 도입과 기록관리혁신(1999년 이후))

  • Kim, Ik-Han
    • The Korean Journal of Archival Studies
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    • no.15
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    • pp.67-93
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    • 2007
  • This article deals with the short history from 1999 to the present time, how the Korean record and archives management world had grown up, and what the development of the branch of records and archives studies resulted in. First of all, it is looked out upon the transition and feature of each initiative bodies of records management, containing the records producing body, records and archives management body, records and archives professional body, and civil society. As a result, this article points out the disequilibrium state of the records producing body and civil society, for all the growth of records and archives management institutions and records and archives professionals. During the time of establishing the law, the Korean records and archives management had been made a rapid progress by some part of the leading group being to Korean Records and Archives Service and the society of professionals. But it is estimated only the malformed development depending on the model of elites, although we could achieve the establishment of Korean Records and Archives Act. The condition of records and archives management of the Participation Government was distinguish from the state of former times, being driven up the renovation of records and archives management. The main power of the renovation was sought our by overcome of the elite model with the development of archival institutions and professionals extending wide range. Particularly professionals to accept the education of graduate school grew up in quantity and quality and then they let the pattern of the collaboration with archival institutions rake root in Korea. As The Road Map on the Renovation of National Records and Archives Management was made, the government put into practice, so the management of records and archives in Korea could take a step of steady and continuous growth. But the development of the records producing bodies and civil society is staying at the low level as yet. Accordingly it is expected to have the most important means that the professional instruction become to normalize and archivists who posted in public agencies after graduating professional education program discharge their duties. And each public agencies have to speed up to set up the institutions for records management including some archivists so that overcome the condition of underdevelopment as fast as possible.

Nomad Thinking Implied in Duchamp's Readymades (뒤샹의 레디메이드에 함의된 노마드적 사유)

  • Song, Hayoung
    • The Journal of the Convergence on Culture Technology
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    • v.7 no.3
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    • pp.215-222
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    • 2021
  • Duchamp chose readymades mainly for his denial of retinal painting and his desire and fluid thinking for changes inside him. His thinking is well presented in his readymade works. One of his early readymades, Bicycle Wheel, expresses correlations between beings and capital. Its essence is capital and the desire of beings. It is connected to Desire or Desire-Machine proposed as a social reform and creation model by Gilles Deleuze and Félix Guattari. Bicycle Wheel does not simply end in desire relations between capital and beings, though. When the desire of beings is converted into positive desire, it can keep inventing and creating something that is repetitive, fluid, and new. Duchamp tried to convey this positive desire through his readymade Fountain. Duchamp created a ready-made article toilet into a work of art in Fountain, being driven by desire flowing inside him. This is connected to the attributes of nomads that refused to settle down and continue to flow in search of new landscapes. This way of his thinking is clearly reflected in his Box in a Valise. He was motivated to create this work by his fluid thinking. In this work, various situations can unfold often according to the directions of two elements, place and arrangement. Here, place guarantees fluidity, and arrangement variability or desire. According to Gilles Deleuze and Félix Guattari, fluidity represents nomads with the characteristics of flow and variation, and desire represents productivity or production or creation. Box in a Valise represents nomads themselves. The nomads defined by Gilles Deleuze and Félix Guattari keep flowing and create a new world. They are in line with the thinking of Duchamp that refused to settle down at one place and escape from the old order to create a new artistic world. This type of nomads can be called revolutionists or creators that acknowledge differences and create. Nomads also contain the concept of resistance to the old order. Deleuze and Guattari proposed a war machine as a model of this resistance. Duchamp and his readymades can thus be called war machines.