• Title/Summary/Keyword: 최적비용

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Development of Greenhouse Cooling and Heating Load Calculation Program Based on Mobile (모바일 기반 온실 냉난방 부하 산정 프로그램 개발)

  • Moon, Jong Pil;Bang, Ji Woong;Hwang, Jeongsu;Jang, Jae Kyung;Yun, Sung Wook
    • Journal of Bio-Environment Control
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    • v.30 no.4
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    • pp.419-428
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    • 2021
  • In order to develope a mobile-based greenhouse energy calculation program, firstly, the overall thermal transmittance of 10 types of major covers and 16 types of insulation materials were measured. In addition, to estimate the overall thermal transmittance when the cover and insulation materials were installed in double or triple layers, 24 combinations of double installations and 59 combinations of triple installations were measured using the hotbox. Also, the overall thermal transmittance value for a single material and the thermal resistance value were used to calculate the overall thermal transmittance value at the time of multi-layer installation of covering and insulating materials, and the linear regression equation was derived to correct the error with the measured values. As a result of developing the model for estimating thermal transmittance when installing multiple layers of coverings and insulating materials based on the value of overall thermal transmittance of a single-material, the model evaluation index was 0.90 (good when it is 0.5 or more), indicating that the estimated value was very close to the actual value. In addition, as a result of the on-site test, it was evaluated that the estimated heat saving rate was smaller than the actual value with a relative error of 2%. Based on these results, a mobile-based greenhouse energy calculation program was developed that was implemented as an HTML5 standard web-based mobile web application and was designed to work with various mobile device and PC browsers with N-Screen support. It had functions to provides the overall thermal transmittance(heating load coefficient) for each combination of greenhouse coverings and thermal insulation materials and to evaluate the energy consumption during a specific period of the target greenhouse. It was estimated that an energy-saving greenhouse design would be possible with the optimal selection of coverings and insulation materials according to the region and shape of the greenhouse.

Effects of Semolina on Quality Characteristics of the Rice Noddles (세몰리나 첨가가 쌀국수의 품질특성에 미치는 영향)

  • Kim, Byong Ki;Park, Jung Eun;Zu, Genuine
    • Food Engineering Progress
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    • v.15 no.1
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    • pp.56-63
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    • 2011
  • Durum wheat semolina was added into wet-milled rice flour in order to improve chewy texture, firm bite ("al dente"), and resistance to overcooking of the ordinary rice noodles. Wet noodles were prepared by mixing 0 (control), 5, 10, 15, and 20% (w/w) of semolina per semolina and rice flour mixtures. Vital gluten (4%, w/w) and salt (2%, w/w) were added to form the pliable strands of wet noodles and final moisture contents of the raw mixtures were equalized at 45%. Pasting properties of the suspended flour mixtures as measured by the Rapid Visco Analyser (RVA) showed slight increases (up to $1.2^{\circ}C)$ in pasting temperatures along with the considerable decreases in peak viscosities as semolina increased at over 15%. Reduced shear thinning and retrogradation of the starch solution that leads to hardening of the cooked noodles were indicated by lowered breakdown viscosities and gaps between finaland setback viscosities from the RVA viscogram as semolina increased at over 10%. Reduced water uptake and turbidity increases of the cooking water as caused by the soluble starches from the noodle were also noted as the content of semolina increased. More or less significant (p<0.05) decreases in colorimetric L (lightness) value of the raw- and cooked noodles were observed as semolina increased while a- (redness) and b (yellowness) values were rather increased at the same moment. Textural properties of the cooked noodles such as hardness, springiness, cohesiveness, gumminess, and chewiness from TPA tests were significantly (p<0.05) influenced by added semolina, even at 5%-levels or more. It can be concluded that addition of semolina into rice flour could provide easy handling of the wet noodles without distortion during transportation, integrity and firm bite of the cooked noodles, and less loss of starch to the cooking water in comparison with the ordinary rice noodle. It was finally suggested that optimum level of the semolina in the product was approximately 10% for the quality wet rice noodle products.

Production of Medium-chain-length Poly (3-hydroxyalkanoates) by Pseudomonas sp. EML8 from Waste Frying Oil (Pseudomonas sp. EML8 균주를 이용한 폐식용류로부터 medium-chain-length poly(3-hydroxyalkanoates) 생합성)

  • Kim, Tae-Gyeong;Kim, Jong-Sik;Chung, Chung-Wook
    • Journal of Life Science
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    • v.31 no.1
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    • pp.90-99
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    • 2021
  • In this study, to reduce the production cost of poly(3-hydroxyalkanoates) (PHA), optimal cell growth and PHA biosynthesis conditions of the isolated strain Pseudomonas sp. EML8 were established using waste frying oil (WFO) as the cheap carbon source. Gas chromatography (GC) and GC mass spectrometry analysis of the medium-chain-length PHA (mcl-PHAWFO) obtained by Pseudomonas sp. EML8 of WFO indicated that it was composed of 7.28 mol% 3-hydrxoyhexanoate, 39.04 mol% 3-hydroxyoctanoate, 37.11 mol% 3-hydroxydecanoate, and 16.58 mol% 3-hydroxvdodecanoate monomers. When Pseudomonas sp. EML8 were culture in flask, the maximum dry cell weight (DCW) and the mcl-PHAWFO yield (g/l) were showed under WFO (20 g/l), (NH4)2SO4 (0.5 g/l), pH 7, and 25℃ culture conditions. Based on this, the highest DCW, mcl-PHAWFO content, and mcl-PHAWFO yield from 3-l-jar fermentation was obtained after 48 hr. Similar results were obtained using 20 g/l of fresh frying oil (FFO) as a control carbon source. In this case, the DCW, the mcl-PHAFFO content, and the mcl-PHAFFO yields were 2.7 g/l, 62 wt%, and 1.6 g/l, respectively. Gel permeation chromatography analysis confirmed the average molecular weight of the mcl-PHAWFO and mcl-PHAFFO to be between 165-175 kDa. Thermogravimetric analysis showed decomposition temperature values of 260℃ and 274.7℃ for mcl-PHAWFO and mcl-PHAFFO, respectively. In conclusion, Pseudomonas sp. EML8 and WFO could be suggested as a new candidate and substrate for the industrial production of PHA.

A Relative Study of 3D Digital Record Results on Buried Cultural Properties (매장문화재 자료에 대한 3D 디지털 기록 결과 비교연구)

  • KIM, Soohyun;LEE, Seungyeon;LEE, Jeongwon;AHN, Hyoungki
    • Korean Journal of Heritage: History & Science
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    • v.55 no.1
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    • pp.175-198
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    • 2022
  • With the development of technology, the methods of digitally converting various forms of analog information have become common. As a result, the concept of recording, building, and reproducing data in a virtual space, such as digital heritage and digital reconstruction, has been actively used in the preservation and research of various cultural heritages. However, there are few existing research results that suggest optimal scanners for small and medium-sized relics. In addition, scanner prices are not cheap for researchers to use, so there are not many related studies. The 3D scanner specifications have a great influence on the quality of the 3D model. In particular, since the state of light reflected on the surface of the object varies depending on the type of light source used in the scanner, using a scanner suitable for the characteristics of the object is the way to increase the efficiency of the work. Therefore, this paper conducted a study on nine small and medium-sized buried cultural properties of various materials, including earthenware and porcelain, by period, to examine the differences in quality of the four types of 3D scanners. As a result of the study, optical scanners and small and medium-sized object scanners were the most suitable digital records of the small and medium-sized relics. Optical scanners are excellent in both mesh and texture but have the disadvantage of being very expensive and not portable. The handheld method had the advantage of excellent portability and speed. When considering the results compared to the price, the small and medium-sized object scanner was the best. It was the photo room measurement that was able to obtain the 3D model at the lowest cost. 3D scanning technology can be largely used to produce digital drawings of relics, restore and duplicate cultural properties, and build databases. This study is meaningful in that it contributed to the use of scanners most suitable for buried cultural properties by material and period for the active use of 3D scanning technology in cultural heritage.

Utilizing the Idle Railway Sites: A Proposal for the Location of Solar Power Plants Using Cluster Analysis (철도 유휴부지 활용방안: 군집분석을 활용한 태양광발전 입지 제안)

  • Eunkyung Kang;Seonuk Yang;Jiyoon Kwon;Sung-Byung Yang
    • Journal of Intelligence and Information Systems
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    • v.29 no.1
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    • pp.79-105
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    • 2023
  • Due to unprecedented extreme weather events such as global warming and climate change, many parts of the world suffer from severe pain, and economic losses are also snowballing. In order to address these problems, 'The Paris Agreement' was signed in 2016, and an intergovernmental consultative body was formed to keep the average temperature rise of the Earth below 1.5℃. Korea also declared 'Carbon Neutrality in 2050' to prevent climate catastrophe. In particular, it was found that the increase in temperature caused by greenhouse gas emissions hurts the environment and society as a whole, as well as the export-dependent economy of Korea. In addition, as the diversification of transportation types is accelerating, the change in means of choice is also increasing. As the development paradigm in the low-growth era changes to urban regeneration, interest in idle railway sites is rising due to reduced demand for routes, improvement of alignment, and relocation of urban railways. Meanwhile, it is possible to partially achieve the solar power generation goal of 'Renewable Energy 3020' by utilizing already developed but idle railway sites and take advantage of being free from environmental damage and resident acceptance issues surrounding the location; but the actual use and plan for these solar power facilities are still lacking. Therefore, in this study, using the big data provided by the Korea National Railway and the Renewable Energy Cloud Platform, we develop an algorithm to discover and analyze suitable idle sites where solar power generation facilities can be installed and identify potentially applicable areas considering conditions desired by users. By searching and deriving these idle but relevant sites, it is intended to devise a plan to save enormous costs for facilities or expansion in the early stages of development. This study uses various cluster analyses to develop an optimal algorithm that can derive solar power plant locations on idle railway sites and, as a result, suggests 202 'actively recommended areas.' These results would help decision-makers make rational decisions from the viewpoint of simultaneously considering the economy and the environment.

Analysis of Management Status and Optimum Production Scale of Quarrying Firms in Korea -Comparative Analysis of Aggregate and Building-Stone Quarrying Firms- (산지채석업체(山地採石業體)의 경영실태(經營實態) 및 적정규모설정(適正規模設定) -골재용(骨材用) 채석업체(採石業體)와 건축용(建築用) 채석업체(採石業體)의 비교(比較) 분석(分析)-)

  • Joung, Ha Hyeon;Cho, Eung Hyouk
    • Journal of Korean Society of Forest Science
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    • v.80 no.1
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    • pp.72-81
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    • 1991
  • This study was carried out to provide necessary information for improving quarrying industry management in Korea. The results of the study are summarized as follows : 1. In aggregate and building-stone quarrying firms the managers over 40 years of age are 97% and 89.1%, the ones above education level of high school are 90% and 85% and the ones not more than 10 years of quarrying experience are 70% and 52%, respectively. Accordingly it can be pointed out that most of the managers of two types of firms are relatively old, have high educational background, while quarrying experiences of building-stone firm managers are longer than that of aggregate firm managers. 2. Most of the management forms are social corporation(60%) for aggregate quarry firms and private management(76%) for building-stone firms. Average areas of permitted stone-pits of aggregate and building-stone quarries are about 2.86ha and 1.66ha respectively. That is, aggregate quarrying firms are carried on a larger scale than building-stone quarrying firms. 3. The yearly average product of aggregate quarrying firms has increased steadily from $88.961m^3$ in 1985 to $144.028m^3$ in 1988, while, in case of building-stone quarry firms, it has significantly increased from $4.155m^3$ to $19.462m^3$ from 1985 to 1987, but reduced to $13.400m^3$ in 1988. Unstable production activities of building-stone quarrying firms may require continuous government support. 4. Major cost items are equipment rental, depreciation, salaries, repair, maintenance for aggregate quarrying firms, and salaries, depreciation, fuel, tax for building-stone quarrying firms. The yearly average rate of return is about 9.7% for aggregate quarry firms and 2.6% for building-stone quarry firms. It can be pointed out that aggregate quarrying firms is better managed than building-stone quarrying firms. 5. The production elasticity of salary for aggregate quarrying firms is 0.495, that of employees is 0.559, and that of capital service is 0.513. The sum of the elasticities is 1.257>1. Fur building-stone quarrying firms, that of employees is 0.492, that of variable costs is 0.192, and that of capital service is 0.498. The sum of elasticities is 1.172>1, thus denotes the increasing returns to scale for both types quarrying firms. 6. The ratio of marginal value product to opportunity cost of empolyees is 2.54, that of variable costs is 3.62, and that of capital service is 1.45, in aggregate quarrying firms. That of employees is 2.47, that is variable costs was 2.34, and that of capital service is 19.67 in building-stone quarrying firms. Therefore the critical factors for more expansion of management scale in aggregate quarrying firms are variable cost and employees, and are capital service in building-stone quarry ing firms. 7. The break-even points of stone sales are about 0.587 billion won and 0.22 billion won in aggregate and building-stone quarrying firms respectively. The optimum sales Level for profit maximization are about 2.0 billion and 0.5 billion in aggregate and building-stone quarry firms respectively.

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A Study on Web-based Technology Valuation System (웹기반 지능형 기술가치평가 시스템에 관한 연구)

  • Sung, Tae-Eung;Jun, Seung-Pyo;Kim, Sang-Gook;Park, Hyun-Woo
    • Journal of Intelligence and Information Systems
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    • v.23 no.1
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    • pp.23-46
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    • 2017
  • Although there have been cases of evaluating the value of specific companies or projects which have centralized on developed countries in North America and Europe from the early 2000s, the system and methodology for estimating the economic value of individual technologies or patents has been activated on and on. Of course, there exist several online systems that qualitatively evaluate the technology's grade or the patent rating of the technology to be evaluated, as in 'KTRS' of the KIBO and 'SMART 3.1' of the Korea Invention Promotion Association. However, a web-based technology valuation system, referred to as 'STAR-Value system' that calculates the quantitative values of the subject technology for various purposes such as business feasibility analysis, investment attraction, tax/litigation, etc., has been officially opened and recently spreading. In this study, we introduce the type of methodology and evaluation model, reference information supporting these theories, and how database associated are utilized, focusing various modules and frameworks embedded in STAR-Value system. In particular, there are six valuation methods, including the discounted cash flow method (DCF), which is a representative one based on the income approach that anticipates future economic income to be valued at present, and the relief-from-royalty method, which calculates the present value of royalties' where we consider the contribution of the subject technology towards the business value created as the royalty rate. We look at how models and related support information (technology life, corporate (business) financial information, discount rate, industrial technology factors, etc.) can be used and linked in a intelligent manner. Based on the classification of information such as International Patent Classification (IPC) or Korea Standard Industry Classification (KSIC) for technology to be evaluated, the STAR-Value system automatically returns meta data such as technology cycle time (TCT), sales growth rate and profitability data of similar company or industry sector, weighted average cost of capital (WACC), indices of industrial technology factors, etc., and apply adjustment factors to them, so that the result of technology value calculation has high reliability and objectivity. Furthermore, if the information on the potential market size of the target technology and the market share of the commercialization subject refers to data-driven information, or if the estimated value range of similar technologies by industry sector is provided from the evaluation cases which are already completed and accumulated in database, the STAR-Value is anticipated that it will enable to present highly accurate value range in real time by intelligently linking various support modules. Including the explanation of the various valuation models and relevant primary variables as presented in this paper, the STAR-Value system intends to utilize more systematically and in a data-driven way by supporting the optimal model selection guideline module, intelligent technology value range reasoning module, and similar company selection based market share prediction module, etc. In addition, the research on the development and intelligence of the web-based STAR-Value system is significant in that it widely spread the web-based system that can be used in the validation and application to practices of the theoretical feasibility of the technology valuation field, and it is expected that it could be utilized in various fields of technology commercialization.

Geochemical Equilibria and Kinetics of the Formation of Brown-Colored Suspended/Precipitated Matter in Groundwater: Suggestion to Proper Pumping and Turbidity Treatment Methods (지하수내 갈색 부유/침전 물질의 생성 반응에 관한 평형 및 반응속도론적 연구: 적정 양수 기법 및 탁도 제거 방안에 대한 제안)

  • 채기탁;윤성택;염승준;김남진;민중혁
    • Journal of the Korean Society of Groundwater Environment
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    • v.7 no.3
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    • pp.103-115
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    • 2000
  • The formation of brown-colored precipitates is one of the serious problems frequently encountered in the development and supply of groundwater in Korea, because by it the water exceeds the drinking water standard in terms of color. taste. turbidity and dissolved iron concentration and of often results in scaling problem within the water supplying system. In groundwaters from the Pajoo area, brown precipitates are typically formed in a few hours after pumping-out. In this paper we examine the process of the brown precipitates' formation using the equilibrium thermodynamic and kinetic approaches, in order to understand the origin and geochemical pathway of the generation of turbidity in groundwater. The results of this study are used to suggest not only the proper pumping technique to minimize the formation of precipitates but also the optimal design of water treatment methods to improve the water quality. The bed-rock groundwater in the Pajoo area belongs to the Ca-$HCO_3$type that was evolved through water/rock (gneiss) interaction. Based on SEM-EDS and XRD analyses, the precipitates are identified as an amorphous, Fe-bearing oxides or hydroxides. By the use of multi-step filtration with pore sizes of 6, 4, 1, 0.45 and 0.2 $\mu\textrm{m}$, the precipitates mostly fall in the colloidal size (1 to 0.45 $\mu\textrm{m}$) but are concentrated (about 81%) in the range of 1 to 6 $\mu\textrm{m}$in teams of mass (weight) distribution. Large amounts of dissolved iron were possibly originated from dissolution of clinochlore in cataclasite which contains high amounts of Fe (up to 3 wt.%). The calculation of saturation index (using a computer code PHREEQC), as well as the examination of pH-Eh stability relations, also indicate that the final precipitates are Fe-oxy-hydroxide that is formed by the change of water chemistry (mainly, oxidation) due to the exposure to oxygen during the pumping-out of Fe(II)-bearing, reduced groundwater. After pumping-out, the groundwater shows the progressive decreases of pH, DO and alkalinity with elapsed time. However, turbidity increases and then decreases with time. The decrease of dissolved Fe concentration as a function of elapsed time after pumping-out is expressed as a regression equation Fe(II)=10.l exp(-0.0009t). The oxidation reaction due to the influx of free oxygen during the pumping and storage of groundwater results in the formation of brown precipitates, which is dependent on time, $Po_2$and pH. In order to obtain drinkable water quality, therefore, the precipitates should be removed by filtering after the stepwise storage and aeration in tanks with sufficient volume for sufficient time. Particle size distribution data also suggest that step-wise filtration would be cost-effective. To minimize the scaling within wells, the continued (if possible) pumping within the optimum pumping rate is recommended because this technique will be most effective for minimizing the mixing between deep Fe(II)-rich water and shallow $O_2$-rich water. The simultaneous pumping of shallow $O_2$-rich water in different wells is also recommended.

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Self-optimizing feature selection algorithm for enhancing campaign effectiveness (캠페인 효과 제고를 위한 자기 최적화 변수 선택 알고리즘)

  • Seo, Jeoung-soo;Ahn, Hyunchul
    • Journal of Intelligence and Information Systems
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    • v.26 no.4
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    • pp.173-198
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    • 2020
  • For a long time, many studies have been conducted on predicting the success of campaigns for customers in academia, and prediction models applying various techniques are still being studied. Recently, as campaign channels have been expanded in various ways due to the rapid revitalization of online, various types of campaigns are being carried out by companies at a level that cannot be compared to the past. However, customers tend to perceive it as spam as the fatigue of campaigns due to duplicate exposure increases. Also, from a corporate standpoint, there is a problem that the effectiveness of the campaign itself is decreasing, such as increasing the cost of investing in the campaign, which leads to the low actual campaign success rate. Accordingly, various studies are ongoing to improve the effectiveness of the campaign in practice. This campaign system has the ultimate purpose to increase the success rate of various campaigns by collecting and analyzing various data related to customers and using them for campaigns. In particular, recent attempts to make various predictions related to the response of campaigns using machine learning have been made. It is very important to select appropriate features due to the various features of campaign data. If all of the input data are used in the process of classifying a large amount of data, it takes a lot of learning time as the classification class expands, so the minimum input data set must be extracted and used from the entire data. In addition, when a trained model is generated by using too many features, prediction accuracy may be degraded due to overfitting or correlation between features. Therefore, in order to improve accuracy, a feature selection technique that removes features close to noise should be applied, and feature selection is a necessary process in order to analyze a high-dimensional data set. Among the greedy algorithms, SFS (Sequential Forward Selection), SBS (Sequential Backward Selection), SFFS (Sequential Floating Forward Selection), etc. are widely used as traditional feature selection techniques. It is also true that if there are many risks and many features, there is a limitation in that the performance for classification prediction is poor and it takes a lot of learning time. Therefore, in this study, we propose an improved feature selection algorithm to enhance the effectiveness of the existing campaign. The purpose of this study is to improve the existing SFFS sequential method in the process of searching for feature subsets that are the basis for improving machine learning model performance using statistical characteristics of the data to be processed in the campaign system. Through this, features that have a lot of influence on performance are first derived, features that have a negative effect are removed, and then the sequential method is applied to increase the efficiency for search performance and to apply an improved algorithm to enable generalized prediction. Through this, it was confirmed that the proposed model showed better search and prediction performance than the traditional greed algorithm. Compared with the original data set, greed algorithm, genetic algorithm (GA), and recursive feature elimination (RFE), the campaign success prediction was higher. In addition, when performing campaign success prediction, the improved feature selection algorithm was found to be helpful in analyzing and interpreting the prediction results by providing the importance of the derived features. This is important features such as age, customer rating, and sales, which were previously known statistically. Unlike the previous campaign planners, features such as the combined product name, average 3-month data consumption rate, and the last 3-month wireless data usage were unexpectedly selected as important features for the campaign response, which they rarely used to select campaign targets. It was confirmed that base attributes can also be very important features depending on the type of campaign. Through this, it is possible to analyze and understand the important characteristics of each campaign type.