• 한국해양학회지
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• 제11권2호
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• pp.57-63
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• 1976

It was attempted to analyze the sensitivity of the oil prospect place named MARIA which placed inside Gulf of Alaska. For the analysis, P6031090, ECOANA( computer) which installed in the head office, Shell Oil Co was used and the data needed for computer programming were 1) Unit of Production data 2) Production Schedule 3) Total Gross Yearly Expenses and 4) Total Gross Capital and so on. The important data among the computer output 1) PVPAT (Present Value After Tax): $1,167,077,500 2) Payout After Tax: 3.14 Years (256,284,810 BBL Production) 3) Earning Power: 42% (After Tax) 4) PVPAT/BBL : $1.22 5) Capital/BBL : $2.00. On the other hand, the effect acted upon PVPAT with varying the Platform cost, Facility cost, Pipeline cost and Well cost was observed in comparion with the basic for range from 50% to 200%. Resultantly, the order was 1) Pipeline cost 2) Facility cost 3) Well cost 4) Platform cost for range form 100% to 200%. This project was completed by the contract with Shell Oil Co., and the geological data needed for this analysis were given by the head office and the development project started from Jan. 1976.

• 한국환경과학회지
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• 제22권9호
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• pp.1171-1180
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• 2013

Recent climate change has led to fluctuations in agricultural production, and as a result national food supply has become an important strategic factor in economic policy. As such, in this study, panel data was collected to analyze the effects of seven meteorological elements and using the Lagrange multipliers method, the fixed-effects model for the production of five types of food crop and the seven meteorological elements were analyzed. Results showed that the key factors effecting increases in production of rice grains were average temperature, average relative humidity and average ground surface temperature, while wheat and barley were found to have positive correlations with average temperature and average humidity. The implications of this study are as follow. First, it was confirmed that the meteorological elements have profound effects on the production of food crops. Second, when compared to existing studies, the study was not limited to one food crop but encompassed all five types, and went beyond other studies that were limited to temperature and rainfall to include various meterological elements.

• 한국작물학회:학술대회논문집
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• 한국작물학회 2022년도 추계학술대회
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• pp.58-58
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• 2022

With the development of advanced technology, automation of agricultural work is spreading. In association with the 4th industrial revolution-based technology, research on field smart farm technology is being actively conducted. A state-of-the-art unmanned automated agricultural production demonstration complex was established in Naju-si, Jeollanam-do. For the operation of the demonstration area platform, it is necessary to build a sophisticated, advanced, and intelligent field smart farming model. For the operation of the unmanned automated agricultural production demonstration area platform, we are building data on the growth of soybean for smart cultivated crops and conducting research to determine the optimal time for agricultural work. In order to operate an unmanned automation platform, data is collected to discover digital factors for water management immediately after planting, water management during the growing season, and determination of harvest time. A subsurface drip irrigation system was established for smart water management. Irrigation was carried out when the soil moisture was less than 20%. For effective water management, soil moisture was measured at the surface, 15cm, and 30cm depth. Vegetation indices were collected using drones to find key factors in soybean production prediction. In addition, major growth characteristics such as stem length, number of branches, number of nodes on the main stem, leaf area index, and dry weight were investigated. By discovering digital factors for effective decision-making through data construction, it is expected to greatly enhance the efficiency of the operation of the unmanned automated agricultural production demonstration area.

• Journal of information and communication convergence engineering
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• 제17권1호
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• pp.8-13
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• 2019

Smart Farming has been regarded as an important application in information and communications technology (ICT) fields. Selecting crops for cultivation at the pre-production stage is critical for agricultural producers' final profits because over-production and under-production may result in uncountable losses, and it is necessary to predict crop production to prevent these losses. The ITU-T Recommendation for Smart Farming (Y.4450/Y.2238) defines plan/production consultation service at the pre-production stage; this type of service must trace crop production in a predictive way. Several research papers present that machine learning technology can be applied to predict crop production after related data are learned, but these technologies have little to do with standardized ICT services. This paper clarifies the relationship between agricultural consultation services and predicting crop production. A prediction scheme is proposed, and the results confirm the usability and superiority of machine learning for predicting crop production.

• 스마트미디어저널
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• 제11권5호
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• pp.9-16
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• 2022

최근 농업 현장에서는 빅데이터와 IoT(Internet of Things) 등 기술을 적용하여 디지털농업 스마트팜으로 자동화를 하고 있다. 이러한 스마트팜은 작물의 환경을 측정하고 데이터를 조사하고 가공하여 생산량의 증대와 작물의 품질을 향상하고자 한다. 생산량 예측은 첨단 농업인 스마트팜 디지털 농업에서 중요한 연구로 빅데이터를 활용하여 환경데이터를 분석하고 나아가 생육정보 데이터 품질 관리를 위한 표준화 연구가 필요하다. 본 논문에서는 스마트팜 딸기 농장에서 수집된 환경 및 생산량 데이터를 분석하여 연구하였다. 회귀분석을 기반으로 릿지회귀(Ridge Regression), LightGBM, XGBoost를 사용하여 작물 생산량 예측 모델을 분석하였다. 3가지 모델 중 최적의 모델은 XGBoost로 R2는 82.5%의 설명력을 보였다. 연구 결과 양액흡수량과 환경데이터간의 상관관계를 확인할 수 있었고, 생산량 예측 연구에 대한 유의미한 결과를 얻을 수 있었다. 향후 작물의 생육환경 정보 및 양액의 성분 등 양액흡수량을 연구하여 양액관리를 통해 환경오염 예방 및 양액 절감에 기여할 것으로 기대된다.

• Journal of Plant Biotechnology
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• 제5권4호
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• pp.193-195
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• 2003

A major goal of agricultural biotechnology is the discovery of genes or genetic loci which are associated with characteristics beneficial to crop production. This knowledge of genetic loci may then be applied to improve crop breeding. Agriculturally important genes may also benefit crop production through transgenic technologies. Recent years have seen an application of high throughput technologies to agricultural biotechnology leading to the production of large amounts of genomic data. The challenge today is the effective structuring of this data to permit researchers to search, filter and importantly, make robust associations within a wide variety of datasets. At the Plant Biotechnology Centre, Primary Industries Research Victoria in Melbourne, Australia, we have developed a series of tools and computational pipelines to assist in the processing and structuring of genomic data to aid its application to agricultural biotechnology resear-ch. These tools include a sequence database, ASTRA, for the processing and annotation of expressed sequence tag data. Tools have also been developed for the discovery of simple sequence repeat (SSR) and single nucleotide polymorphism (SNP) molecular markers from large sequence datasets. Application of these tools to Brassica research has assisted in the production of genetic and comparative physical maps as well as candidate gene discovery for a range of agronomically important traits.

• Nuclear Engineering and Technology
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• 제32권4호
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• pp.361-371
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• 2000

The 123Te(p,n)123I, 124Te(p,n)124I and 124Te(p,2n)123I reactions, among the many reaction channels opened, are the major reactions under consideration from a diagnostic purpose because reaction residuals as the gamma emitters are used for most radiophamaceutical applications involving radioiodine. Based on the available experimental data, the absorption cross sections and elastic scattering angular distributions of the proton-induced nuclear reaction on Te isotopes below 60 MeV are calculated using the optical model code APMNK. The transmission coefficients of neutron, proton, deuteron, trition and alpha particles are calculated by CUNF code and are fed into the GNASH code. By adjusting level density parameters and the pair correction values of some reaction channels, as well as the composite nucleus state density constants of the pre-equilibrium model, the production cross sections and energy-angle correlated spectra of the secondary light particles, as well as production cross sections and energy distributions of heavy recoils and gamma rays are calculated by the statistical plus pre-equilibrium model code GNASH. The calculated results are analysed and compared with the experimental data taken from the EXFOR. The optimized global optical model parameters give overall agreement with the experimental data over both the entire energy range and all tellurium isotopes.

• 산업공학
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• 제24권3호
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• pp.267-273
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• 2011

In the shipbuilding industry, since production processes are so complicated that the data collection for decision making cannot be fully automated, most of production planning and controls are based on the information provided only by field workers. Therefore, without sufficient information it is very difficult to manage the whole production process efficiently. Job status is one of the most important information used for evaluating the remaining processing time in production control, specifically, in block assembly shop. Currently, it is checked by a production manager manually and production planning is modified based on that information, which might cause a delay in production control, resulting in performance degradation. Motivated by these remarks, in this paper we propose an efficient algorithm for identifying job status in block assembly shop for shipbuilding. The algorithm is based on the multi-layer perceptron neural network model using two key factors for input parameters. We showed the superiority of the algorithm by using a numerical experiment, based on real data collected from block assembly shop.

• Asian-Australasian Journal of Animal Sciences
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• 제3권2호
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• pp.107-114
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• 1990

The purpose of this investigation was to study the hematological response of Saudi Arabian Baladi fowl to protein rearing regimens. Males and females were subjected to the following 4 protein rearing regimens: conventional, C; reverse protein, RP; 2 single-stage low protein, $SS_1$ and $SS_2$ using 15% and 12% CP diets, respectively. Regimen effect was highly significant ($$p{\leq_-}.01$$) on BW, PCY, TP and U-Ac and significant ($$p{\leq_-}.05$$) on TL. Serum chol levels were not affected by regimen. In general $SS_{2}$ birds showed the lowest values for all parameters studied, except for PCV. However, the differences were not significant in each case. Age and sex effects were highly significant ($$p{\leq_-}.01$$) for all parameters, however, the regimen X sex interaction was not significant except for PCV. Regimen X age interaction, on the other hand, was highly significant ($$p{\leq_-}.01$$) only for BW, TP and U-Ac concentrations. The data may suggest that low levels of protein in the rearing regimen is an important factor influencing levels of the blood parameters studied. The data also indicate a lack of clear relationship between hen-day egg production and the blood parameters studied.

• Journal of Plant Biology
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• 제38권3호
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• pp.235-242
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• 1995

Effects of methyl jasmonate (MeJA) on ethylene production in tomato(Lycopersicon esculentum Mill.) hypocotyl segments and fruits were studied. Ethylene production in tomato hypocotyl segments was inhibited by the increasing concentratons of MeJA, and 450 $\mu$M of MeJA showed 50% inhibitory effect. Time course data indicate that this inhibitory effect of MeJA appeared after 3 h of incubation period and continued until 24 h. Inhibition of ethylene producton by MeJA was due to the decrease in 1-aminocyclopropane-1-carboxylic acid(ACC) synthase activity. However, MeJA treatment had no effect on ACC oxidase activity and the accumulaton of ACC oxidase mRNAs. MeJA also inhibited auxin-induced ethylene production by decreasing in ACC synthase activity. In contrast, MeJA stimulated ethylene production in tomato fruits. When 30 $\mu$L/mL MeJA was treated in a gaseous state, ethylene production doubled and this stimulating effect continued until 4 days. To investigate the mechanisms of MeJA on ethylene production, ACC synthase and ACC oxidase activities were examined after MeJA treatment. MeJA increased the activities of both ACC synthase and ACC oxidase, and induced ACC oxidase mRNA accumulation. These data suggest that MeJA plays distinct roles in the ethylene production in different tomato tissues. It is possible that MeJA affects differently the mechanisms of signal transuction leading to the ethylene biosynthesis.