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Background Extracellular vesicles (EV) have been proven to contain double-stranded DNA reflecting the mutational status of the parental tumor cells in non-small cell lung cancer (NSCLC), which can be translated into clinically useful EV-based liquid biopsy for Epidermal growth factor receptor (EGFR) genotyping using bronchoalveolar lavage fluid (BALF) obtained from tumor site. Methods Patients subjected for an initial lung cancer work-up underwent bronchoscopy and BALF was obtained from tumor site. After isolating EVs from BALF by ultracentrifugation, EV-derived DNA (EV DNA) was extracted for subsequent EGFR genotyping performed through peptide nucleic acid (PNA)-mediated Real-Time PCR. The sensitivity, specificity, and concordance rate of BALF EV-based EGFR genotyping were calculated in comparison to tissue genotyping. Results The average sensitivity and specificity of BALF EV-based EGFR genotyping were 76% and 87%, respectively, while the sensitivity significantly increased as the stage progressed. Especially, in stage IV, BALF EV-based EGFR typing identified all tissue-proven EGFR mutant cases (n=31) and detected 6 additional mutant cases. The concordance rate was 79% in stage I, 100% in stage II, 74% in stage III, and 92% in stage IV. As TNM stage advanced, especially in the presence of metastasis, concordance rate significantly increased (P

The semiconductor manufacturing process is very complex, and it is the most important part of the semiconductor industry. In order to test whether or not wafers are functioning normally, a pass/fail test is conducted; however, time and cost needed for this testing increase as the number of chips increases. To address this, a machine learning technique is adopted and a high-performance classifier is needed to determine whether a pass/fail test is accurate or not. In this paper, a deep belief network (DBN)-based multi-classifier is proposed for fault detection prediction in the semiconductor manufacturing process. The proposed method consists of two phases: The first phase is a data pre-processing phase in which features required for semiconductor data sets are extracted and the imbalance problem is solved. The second phase is to configure the multi-DBN using selected features. A DBN classifier is created for each feature and, finally, fault detection prediction is performed. The proposed method showed excellent performance and can be used in the semiconductor manufacturing process efficiently.

In industrial applications, software related to computational lithography using a DP system method, which refers to how efficiently hardware resources are used, has a significant impact on performance. Because the amount of data to be processed per unit of time is comparatively large in the current semiconductor industry, the efficiency of hardware should be increased through job 12 scheduling by using the most efficient load balancing techniques possible. For efficient scheduling of the load balancer, these are necessary to predict the end time of a given job, this is calculated based on the performance of computing resources and the development of effective traffic distribution algorithms. Due to the high integration of semiconductor chips, the volume of mask exposure data has increased exponentially, the number of slave nodes is increasing, and most EDA tools require one license per DP node to perform a simulation. In this paper, in order to improve efficiency and reduce cost through more efficient load balancing scheduling, a new type of DEVS load balancing method was studied based on the existing industrial E-beam cluster model. The designed DEVS model showed up to four times the throughput of the existing legacy model for medium and large clusters when the BSF policy was applied.

To identify and quantify the contribution of the major sources for the ambient carbonaceous aerosols at a Global Atmosphere Watch (GAW) station in Korea, a receptor model, the Positive Matrix Factorization (PMF) model was applied for the one-year long measurement data. Particulate matter less than or equal to 2.5 μm in aerodynamic diameter (PM2.5) aerosols were sampled at Anmyeon Island GAW station from June 2015 to May 2016 and carbonaceous species including ~80 organic compounds were analyzed. According to the performance parameter evaluation, 5 or 7 factors were considered as optimal number of factors. It was found out that the results of 7 factors gave less contribution from the factor designated as mixed sources which we could not separate clearly. The major sources with 7 factors were identified with various analyses including chemical characteristics and air parcel movement analysis. The 7 factors with their relative contributions are; anthropogenic Secondary Organic Aerosols (SOA) (14%), biogenic SOA (15%), primary biogenic source (8%), local biomass burning (13%), transported biomass burning (16%), combustion related source (15%), and mixed sources (19%). The air parcel movement analysis results also support the identification of these factors. Thus, the Anmyeon Island GAW station has been affected by both regional and local sources for the carbonaceous aerosols.

Background Although lung adenocarcinoma with activating epidermal growth factor receptor (EGFR) mutations is common in never smokers, one-third of the patients are ever-smokers. We aimed to investigate the effect of cumulative smoking dose(CSD) on clinical outcomes, including progression-free survival (PFS) and overall survival (OS), in patients with EGFR-mutated lung adenocarcinoma receiving EGFR-tyrosine kinase inhibitors (TKIs). Methods We retrospectively analyzed 142 patients with EGFR-mutation positive advanced or recurrent lung adenocarcinoma who were administered gefitinib, erlotinib, afatinib, and osimertinib. These patients were classified based on their CSD as never smokers, light smokers (≤10 pack-years [PYs]), moderate smokers (11–30 PYs), and heavy smokers (> 30 PYs). PFS and OS were analyzed according to smoking subgroups via Kaplan-Meier curves. Results Among the 142 patients, 91 (64.1%), 12 (8.5%), 22 (15.5%), and 17 (12%) were never, light, moderate, and heavy smokers, respectively. CSD was inversely associated with median PFS in a statistically significant dose-dependent manner (11.8 months (mo), 11.0 mo, 7.4 mo, and 3.9 mo; p

Background Co-existence or subsequent isolation of multiple nontuberculous mycobacteria (NTM) species in same patient has been reported. However, clinical significance of these observations is unclear. The aim of this study was to determine clinical implications of changes of NTM species during or after treatment in patients with NTM lung disease. Methods Patients with NTM lung disease, who experienced changes of NTM species during treatment or within 2 years of treatment completion between January 1, 2009 and December 31, 2015, were included in the analysis. Demographic, clinical, microbiological, and radiographic data were reviewed and analyzed. Results During the study period, 473 patients were newly diagnosed with NTM lung disease. Treatment was started in 164 patients (34.6%). Among these 164 patients, 16 experienced changes of NTM species during or within 2 years of treatment completion. Seven showed changes from M. avium complex (MAC) to M. abscessus subspecies abscessus (MAA) and five patients displayed changes from M. abscessus subspecies massiliense (MAM) to MAC. With isolation of new NTM species, 6 out of 7 patients with change from MAC to MAA reported worsening of symptoms, whereas none of the five patients with change from MAM to MAC reported worsening of symptoms. All MAA isolated during or after treatment for MAC lung diseases showed inducible resistance to clarithromycin. Conclusions Change of NTM species may occur during or after treatment for NTM lung disease. Especially, changes from MAC to MAA is accompanied by symptomatic and radiographic worsening as well as inducible resistance to clarithromycin.

Only a few have evaluated the mitigation of greenhouse emissions and profit analysis along with soil carbon sequestration for corn cultivation. This experiment was conducted to evaluate the carbon sequestration and mitigation of greenhouse gas emissions as well as their profit analysis with different composts mixed with biochar during corn cultivation. This experimental data provided the second year of corn cultivation. The soil type used was clay loam. The application amounts of synthetic fertilizer and biochar were 220–30–155 kg ha−1 (N–P–K) as the recommended amount after soil analysis and 2600 kg ha−1 based on 1.3% of soil bulk density. For the biannual experimental results, it appeared that carbon sequestration in cow manure cooperated with biochar was highest at 2.3 tons ha−1 and recovered from 67.3 to 78.5% with biochar application. Furthermore, mitigation of CO2-eq. emission as greenhouse gases was estimated to be at 7.3–8.4 MT ha−1, and its profit was evaluated from $7.2 to 8.4 as lowest, from $57.2 to 66.6 as medium and from $139.7 to 162.7 as highest per hectare regardless of organic compost types used. For agricultural practice in Korea, it is evaluated that the market price of CO2 in corn field cooperated with 2600 kg ha−1 of biochar application ranged from $57.2 to 162.7 per hectare in Korean Climate Exchange. For corn biomass, the treatment with biochar application did not significantly decrease compared with the only organic compost application. Based on these experimental results, it might be applied for carbon trading with clean development mechanism for agricultural practices.

Background A three-drug regimen (macrolide, ethambutol, and rifampicin) is recommended for the treatment of Mycobacterium avium complex pulmonary disease (MAC-PD). Although macrolide has proven efficacy, the role of ethambutol and rifampicin in patients without acquired immune deficiency syndrome is not proven with clinical studies. We aimed to clarify the roles of ethambutol and rifampicin in the treatment of MAC-PD. Methods Patients treated for MAC-PD between March 1st, 2009 and October 31st, 2018 were reviewed retrospectively. Rates of culture conversion, microbiological cure, treatment failure, and recurrence were compared according to the maintenance (≥6 months) of ethambutol or rifampicin with macrolide. Results Among the 237 patients, 122 (51.5%) maintained ethambutol and rifampicin with macrolide, 58 (24.5%) maintained ethambutol and macrolide, 32 (13.5%) maintained rifampicin and macrolide, and 25 (10.6%) maintained macrolide only. Culture conversion was reached for 190/237 (80.2%) patients and microbiological cure was achieved for 129/177 (72.9%) who completed the treatment. Treatment failure despite ≥12 months of treatment was observed in 66/204 (32.4%), and recurrence was identified in 16/129 (12.4%) who achieved microbiological cure. Compared with maintenance of macrolide only, maintenance of ethambutol, rifampicin or both with macrolide were associated with higher odds of culture conversion [odds ratio (OR), 95% confidence interval (CI): 18.06, 3.67–88.92; 15.82, 2.38–105.33; and 17.12, 3.93–74.60, respectively]. Higher odds of microbiological cure were associated with maintenance of both ethambutol and rifampicin with macrolide (OR, 95% CI: 5.74, 1.54–21.42) and macrolide and ethambutol (OR, 95% CI: 5.12, 1.72–15.24) but not macrolide and rifampicin. Maintenance of both ethambutol and rifampicin with macrolide was associated with lower odds of treatment failure (OR, 95% CI: 0.09, 0.01–0.53) compared with macrolide only, while maintenance of one of these with macrolide was not. Maintenance of both ethambutol and rifampicin or one of these with macrolide did not decrease the probability of recurrence when compared with macrolide only. Conclusions Maintenance (≥6 months) of ethambutol and rifampicin with macrolide was associated with the most favorable treatment outcomes among patients with MAC-PD. Given the association between ongoing ethambutol use and microbiological cure, clinicians should maintain ethambutol unless definite adverse events develop.

Objective: In current practice, medical experts use the pathological stage predictions provided in the Partin tables to support their decisions. Hence, the Partin tables are based on logistic regression built from the US data. In the present study, we developed a data-mining model to predict the pathologic stage of prostate cancer. In this newly developed model, using the classification and regression tree-particle swarm optimization analysis of the Korean population data, we aim to improve the prediction accuracy of the pathologic state of prostate cancer. Method: A total of 467 patients from the smart prostate cancer database were evaluated. The results were intended to predict the pathologic stage of prostate cancer: organ-confined disease and non–organ-confined disease. The accuracy of 4 classification and regression tree-particle swarm optimization models was compared; furthermore, the models were validated with the Partin tables using the receiver operating characteristic curve. Results: Among the 467 evaluated patients, 235 patients had organ-confined disease and 232 patients had non–organ-confined disease. The area under the receiver operating characteristic curve of the proposed classification and regression tree-particle swarm optimization model (0.858 ± 0.034) was larger than the 1 in the Partin tables (0.666 ± 0.046). Conclusion: The proposed classification and regression tree-particle swarm optimization model was superior to the Partin tables in terms of predicting the risk of prostate cancer. Compared to the validation of the Partin tables for the Korean population, the classification and regression tree-particle swarm optimization model resulted in a larger receiver operating characteristic curve and a more accurate prediction of the pathologic stage of prostate cancer in the Korean population.

Greenhouse-gas emission factors are widely used to estimate emissions arising from a defined unit of a specific activity. Such estimates are used both for international reporting to the United Nations Framework Convention on Climate Change (UNFCCC) and for myriad national and sub-national reporting purposes (for example, European Union Emissions Trading Scheme; EU ETS). As with the other so-called "Kyoto protocol GHGs", the Intergovernmental Panel on Climate Change (IPCC) provides a methodology for national and sub-national estimation of N₂O emissions, based on the sector from which the emissions arise. The objective of this study was to develop a integrated emission factor to estimate the direct N₂O emission from an agricultural field cultivated with the red pepper, soy bean, spring cabbage, autumn cabbage and potato in 2010∼2012. Emission factor of N₂O calculated using accumulated N₂O emission, N fertilization rate, and background N₂O emission over three year experiment was 0.00596±0.001337 kg N₂O-N (N kg) -1 . More extensive studies need to be conducted to develop N₂O emission factors for other upland crops in the various regions of Korea because N₂O emission is influenced by many factors including climate characteristics, soil properties, and agricultural practices.

건축물의 고층화, 복합화, 대형화에 따라 다양한 공법이 개발되고 있어 주요 공종에 대한 공법 선정의 중요성이 대두되고 있다. 그러나 프로젝트의 특성을 충분히 고려하지 못하고 있고 주요 공법의 선정을 위한 객관적 기준이나 자료 또한 부족한 실정이며, 실무자의 경험과 직관에만 의존하여 선정이 이루어지고 있는 점이 지적되어 왔다. 이러한 문제점을 해소하기 위해 퍼지, AHP, CBR 등 인공지능이론을 이용한 주요 공종의 공법 선정을 위한 다양한 연구가 진행되었다. 그러나 실무에서 공법 선정 시 공종별 특성 및 현장별 조건을 고려하여 주요 공종마다 각기 다른 여러가지 공법 선정 모델을 적용하기는 어렵다. 이에 본 연구에서는 매트릭스 분석과 선형변환을 이용하여, 실무에서 활용이 용이한 범용적인 성격의 의사결정지원 모델을 제시하고, 사례 연구를 통해 흙막이 공법 선정 과정에 적용하여 연구모델의 정합성을 검증하였다.

If the cloud computing environment is not sufficiently provide the required resources due to the number of virtual server to process the request, may cause a problem that the load applied to the specific server. Migration administrator receive the resources of each physical server for improving the efficiency of the virtual server that exists in the physical servers, and determines the migration destination based on the simulation results. But, there is more overhead predicting the future resource consumption of all the physical server to decide the migration destination through the simulation process in large and complex cloud computing environments. To solve this problem, we propose an improved prediction method with the simulation-based approach. The proposed method is a fuzzy-logic based priority model for VM migration. We design a proposed model with the DEVS formalism. And we also measure and compare a performance and migration count with existing simulation-based migration method. FPLM shows high utilization.

Environmental effect of water-saving irrigation on the emissions of greenhouse gases (GHGs) has not been well investigated. The objective of this study was to measure the effect of water-saving irrigation on GHGs as well as water use and rice production yield in paddy field condition in Korea. Four experimental runoff plots of 4x35 m in size were prepared at an existing paddy field. GHGs emission was measured during the 2012∼2013 growing seasons while a Japonica rice variety was cultivated. Four different water management methods, 1) Continuous Flooding (CF), 2) Intermittent Drainage (ID), 3) Water Saving (WS), and 4) CF+WS, were used during a rice growing season to compare the effects of water management methods on GHGs emission. CF method is flooding all the time, ID method makes paddy water drained 40 days after transplanting for about two weeks, WS method maintains 2~3 ㎝ water-level, which should be refilled when the water-level decreased to about 0 ㎝, and CF+WS method combines CF method before 30 days after transplanting (DAT) and WS method after 30 DAT. Regardless of water management methods, paddy field water was drained about 30 days before harvest. Amount of GHGs emission from WS plot was reduced by 69.3% compared to that from CF plot and by 59.0% compared to that from ID plot. Amount of GHGs emission from CF+WS plot was reduced by 60.7% compared to that from CF plot and by 47.5% compared to that from ID plot. Weed occurrence in CF+WS plots was reduced to 62.2% in comparison with the WS plot, implying that CF+WS plot showed the best effect to mitigation of the greenhouse gas emission in the atmosphere.

BACKGROUND: For the heavy metal cotamination sites, it is very important to estimate the human bioavailability quotients for heavy metals in paddy soils released from mine tailings, which is a major source of contamination in Korea, and to assess the human health risks of heavy metals. METHODS AND RESULTS: This experiment was carried out to investigate the human bioavailability quotient of the heavy metals in paddy soils below part of the closed metalliferous mine. For estimating the human bioavailability quotients for heavy metals, 30 paddy soils below part of the closed mine were collected, and analyzed for Cd, Cu, Pb, Zn, and As using simple bioavailability extraction test(SBET). The quantities of Cd, Cu, Pb, Zn and As extracted from paddy soils below part of the mine by using the SBET analysis were 28.1, 17.3, 34.1, 14.6 and 2.3% respectively. Specially, the maximum values of Cd, Pb and Zn were 73.3, 81.5 and 58.1% of human bioavailability quotient, respectively, and varied considerably among the sampling sites. The human bioavailability quotient of Cd, Cu, Pb and Zn in soils near the closed mine showed significant positive correlation among soil pH value, O.M. and Ex. Ca. contents, while it correlated negatively between soil Ex. K and Ex. Mg contents in paddy soils. Also, its of Cd, Cu, Pb and Zn in paddy soils showed significant positive correlation with 0.1M HCl extractable and total contents, while in soils, it correlated negatively with As content in soil near the closed mine. CONCLUSION: The results of the simple bioavailability extraction test (SBET) indicate that regular ingestion of soils by the local population could be closed a potential health threat due to long-term heavy metals exposure in these mine areas.

BACKGROUND: Most of the tailings have been left without any management in abandoned meta lliferous mines and have become the main source of heavy metal contamination for agricultural soils and crops in the these areas. METHODS AND RESULTS: This experiment was carried out to investigate the assessment of the heavy metal contamination in paddy soils located on downstream of the closed metalliferous mine. The average total concentrations of cadmium (Cd), copper (Cu), lead (Pb), zinc (Zn), and arsenic (As) in paddy soils were 8.88, 56.7, 809, 754, and 37.9 mg/kg, respectively. Specially, the average concentrations of Cd, Pb and Zn were higher than those of warning criteria for soil contamination(4 mg/kg for Cd, 200 mg/kg for Pb, and 300 mg/kg for Zn) in agricultural soil established by Soil Environmental Conservation Act in Korea. The proportions of 0.1 M HCl extractable Cd, Cu, Pb, Zn, and As concentration to total concentration of these heavy metals in paddy soils were 27.7, 21.3, 35.1, 13.8 and 10.5%, respectively. The pollution index of these five metals in paddy soils ranged from 0.42 to 11.92. Also, the enrichment factor (EFc) of heavy metals in paddy soils were in the order as Cd>Pb>Zn>Cu>As, and the enrichment factor in paddy soil varied considerably among the sampling sites. The geoaccumulation index (Igeo) of heavy metals in soils were in the order as Cd>Pb>Zn>Cu>As, specially, the average geoaccumulation index of Cd, Pb, and Zn (Igeo 2.49 ～3.10) were relatively higher than that of other metals in paddy soils.

Background We have occasionally encountered advanced lung cancer patients with disseminated carcinomatosis throughout the body and/or within the lung. This study investigated the clinical characteristics and outcomes of advanced lung adenocarcinoma patients with miliary disseminated carcinomatosis. Methods Patients with adenocarcinomas harboring epidermal growth factor receptor (EGFR) mutations who presented with miliary disseminated carcinomatosis (either intrapulmonary or distant site) were enrolled in the study. Clinical characteristics, treatment responses, and survival outcomes were collected from medical records. Results The most frequent EGFR mutation was an in-frame deletion in exon 19 (n = 44, 68.8%). Arginine substitution of leucine 858 in exon 21 and alanine substitution of glycine 719 in exon 18 were detected in 19 patients (29.7%) and one patient (1.6%), respectively. Patients with miliary disseminated carcinomatosis tended to be female and non-smokers. They expressed the E19 deletion more frequently than patients without miliary dissemination and had shorter progression-free survival times in response to EGFR tyrosine kinase inhibitors (9.7 vs. 12.8 months, P = 0.003) and poorer overall survival (15.9 vs. 29.0 months, P = 0.077). Multivariate analyses revealed that metabolic tumor volume correlated with shorter overall survival time. Conclusions Our data indicate that lung adenocarcinoma patients with miliary dissemination have relatively shorter survival times than those without miliary dissemination. The poor prognosis of patients with miliary dissemination may reflect a high tumor burden, as represented by metabolic tumor volume.

Object. Pathologic prediction of prostate cancer can be made by predicting the patient’s prostate metastasis prior to surgery based on biopsy information. Because biopsy variables associated with pathology have uncertainty regarding individual patient differences, a method for classification according to these variables is needed.Method. We propose a deep belief network and Dempster-Shafer- (DBN-DS-) based multiclassifier for the pathologic prediction of prostate cancer. The DBN-DS learns prostate-specific antigen (PSA), Gleason score, and clinical T stage variable information using three DBNs. Uncertainty regarding the predicted output was removed from the DBN and combined with information from DS to make a correct decision.Result. The new method was validated on pathology data from 6342 patients with prostate cancer. The pathology stages consisted of organ-confined disease (OCD; 3892 patients) and non-organ-confined disease (NOCD; 2453 patients). The results showed that the accuracy of the proposed DBN-DS was 81.27%, which is higher than the 64.14% of the Partin table.Conclusion. The proposed DBN-DS is more effective than other methods in predicting pathology stage. The performance is high because of the linear combination using the results of pathology-related features. The proposed method may be effective in decision support for prostate cancer treatment.

Tumor cells shed an abundance of extracellular vesicles (EVs) to body fluids containing bioactive molecules including DNA, RNA, and protein. Investigations in the field of tumor-derived EVs open a new horizon in understanding cancer biology and its potential as cancer biomarkers as well as platforms for personalized medicine. This study demonstrates that successfully isolated EVs from plasma and bronchoalveolar lavage fluid (BALF) of non-small cell lung cancer (NSCLC) patients contain DNA that can be used for EGFR genotyping through liquid biopsy. In both plasma and BALF samples, liquid biopsy results using EV DNA show higher accordance with conventional tissue biopsy compared to the liquid biopsy of cfDNA. Especially, liquid biopsy with BALF EV DNA is tissue-specific and extremely sensitive compared to using cfDNA. Furthermore, use of BALF EV DNA also demonstrates higher efficiency in comparison to tissue rebiopsy for detecting p.T790 M mutation in the patients who developed resistance to EGFR-TKIs. These finding demonstrate possibility of liquid biopsy using EV DNA potentially replacing the current diagnostic methods for more accurate, cheaper, and faster results. Electronic supplementary material The online version of this article (10.1186/s12943-018-0772-6) contains supplementary material, which is available to authorized users.

The level of nitrous oxide (), a long-lived greenhouse gas, in atmosphere has increased mainly due to anthropogenic sources, especially application of nitrogen fertilizers. Quantifying emission in the agricultural field is essential to develop National inventories of greenhouse gases (GHGs) emission. The objective of this study was to develop emission factor to estimate direct emission from agricultural field by measuring emissions in the red pepper cultivating field from 2010 to 2012. Emission factor of calculated from accumulated emission, nitrogen fertilization rate, and background emission was N resulted from three year experiment of the research sites. More extensive studies need to be conducted to develop emission factors for other upland crops in the various regions of Korea because emission is influenced by many factors including climate characteristics, soil properties, and agricultural practices.

To estimate greenhouse gas (GHG) emission, the inventory of rice cultivation at the farming without agricultural chemicals was established from farmers in Gunsan, Jeonbuk province in 2011∼2012. The objectives of this study were to calculate carbon footprint and analyse the major factor of GHGs. To do this, we carried out a sensitivity analysis using the analyzed main factors of GHGs and estimated the mitigation potential of GHGs. Also we suggested agricultural methods to reduce GHGs that can be appled by farmers at this region. At the farming system without agricultural chemicals, carbon footprint of rice production unit of kg was 2.15 kg CO₂.-eq. kg -1 . Although the amount of carbon dioxide (CO₂) emission was the largest among GHGs, methane (CH₄) emission had the highest contribution to carbon footprint on rice production system when it was converted to carbon dioxide equivalent (CO₂-eq.) multiplied by the global warming potential (GWP). Main source of CO₂ emission in the rice farming system without agricultural chemicals was combustion of fossil fuels used by agricultural machinery. Most of the CH₄ was emitted during rice cultivation practice and its major emission factor was flooded paddy field in anaerobic condition. Also, most of the N2O was emitted from rice cultivation process. Major sources of the N₂O emission was application of fertilizer such as compound fertilizer. As a result of sensitivity analysis in energy consumption, diesel had the highest sensitivity among the energy inputs. With the reduction of diesel consumption by 10%, it was estimated that CO₂ potential reduction was about 2.0%. With reducing application rate of compound fertilizer by 10%, the potential reduction was calculated that CO₂ and N₂O could be reduced by 0.5% and 0.9%, respectively. At the condition of 10% reduction of silicate and compost, CO₂ and CH₄ could be reduced by 1.5% and 1.6%, respectively. With 8 days more drainage than the ordinary practice, CH₄ emission could be reduced by about 4.5%. Drainage and diesel consumption were the main sources having the largest effect on the GHG reduction at the farming system without agricultural chemicals. Based on the above results, we suggest that no-tillage and midsummer drainage could be a method to decrease GHG emissions from rice production system.

The worldwide trend of aging is highlighting the importance of the silver generation as a major consumer group for various industries. In particular, the necessity of mobile services for the silver generation in the IT industry is increasing. The purpose of this research is to develop a smart phone utilization plan by analyzing the needs of developing mobile services applying the characteristics of the silver generation on smart phones and by studying the smart phone acceptance factors.

A cloud computing is one of a parallel and distributed computing. The cloud computing provides some service for user with virtual resources. However, a user’s service request does not show a time pattern. As a result, each resource also shows a different availability at the same time. This difference affects a quality of service (QoS) and a resource selection for users. Therefore, we propose the resource availability-based multi auction model for cloud service reservation and resource brokering system. The proposed system is to select the proper resource provider based on the users’ request. The proposal adopts the multi phase of the auction to transact resources. The system evaluates the available factor of each resource on the auction phase, and finally reserves the service on the adaptive queue. The proposed model shows the better performance than other existing method.

This study was conducted to assess N₂O emissions in agricultural soils of Korea under the 1996 IPCC (Intergovernmental Panel on Climate Change) methodology. N₂O emissions in agricultural soils were calculated the sum of direct emission and indirect emission by the N sources and emissions by field burning of crop residues. N₂O emission was highest in animal manure as 1,547 CO₂-eq Gg. Indirect emissions by atmospheric deposition and leaching and runoff were 1,463 and 1,753 CO₂-eq Gg, respectively. N₂O emission by field burning of crop residues was highest in pepper due to the residue/crop ratio and field burning ratio.

The effects of water-saving irrigation on the emissions of greenhouse gases and the prokaryotic communities in rice paddy soils were investigated through a field experiment. In the Water-Saving (WS) irrigation, the water layer was kept at 2~3 cm while it was kept at 6 cm in the Continuousiy Flooding (CF) irrigation. A plot was treated with Intermittently Drainage (ID) that is drained as fine cracks on the floor were seen after transplanting. GHGs emission amounts from WS plots were reduced by 78.1% compared to that from CF plot and by 70.7% compared to that from ID plot, meaning that WS could help contribute to mitigation of the greenhouse gas accumulation in the atmosphere.

Rice cultivation in the paddy field and the burning of crop residues have been identified as the important sources of methane emission in agricultural sector. This study aimed at assessment of the methane emission from croplands in the year of 2011 with the IPCC guideline methodology. Methane from rice cultivation was emitted 6,813 CO₂-eq Gg in 2011. According to the water management, methane emission amounts by continuously flooded and intermittently flooded were 1,499 and 5,314 CO₂-eq Gg, respectively. Methane emission by crop residues burning was highest in red pepper and followed by rice straw, pulses and barely in 2011. Methane emission by field burning was very little compared with rice cultivation.