We examined long-term variations in sea surface temperature (SST) and annual amplitudes of SST around the Korean Peninsula. Two SST data sets with data periods of approximately 51 years and longer than 100 years, respectively, were obtained from the National Institute of Fisheries Science and Japan Meteorological Agency. SST of Korean waters clearly increased during last 51 years (1968-2018), which was 2.5 times higher than the global trend. This significant increasing trend was caused by the dominant increasing SST trend during winter. However, a negative and positive SST anomaly frequently appeared during winter and summer, respectively, in a recent decade. These features of seasonal SST variation have changed the annual amplitude of SST, and resulted in a drastically increasing trend after 2009. Using the longer SST data set, it was revealed that the decreasing SST trend in winter began in the 2000s and the increasing SST trend in summer bagan in the 1990s. During a recent decade, there was a distinctive SST increase in summer, whereas a clear decrease in winter. In summary, the annual amplitude of SST around the Korean Peninsula significantly changed from a decreasing trend to an increasing trend during a recent decade.

해저 파이프라인은 자원개발을 포함한 에너지산업 및 철강산업과 연계한 고부가가치 산업으로서 상당한 관심을 받아왔다. 해저 파이프라인의 설계와 설치 프로젝트 수행을 위해서는 다양한 핵심요소기술들이 필요하다. 특히, 해저 파이프라인의 안전한 운영을 위해서는 예비커미셔닝을 통한 철저한 사전검증과정이 필수 불가결한 부분이다. 해저 파이프라인 예비커미셔닝 과정 중 하이드로테스팅 공정은 파이프라인 주위 온도변화에 크게 영향을 받는 것으로 알려져 있으나 이에 관한 이론적, 수치해석적 접근방법을 활용한 연구는 미미한 편이다. 본 연구에서는 해저 파이프라인의 예비커미셔닝 과정 중 하이드로테스팅 공정에 대해 과도열전달 해석법을 활용하여 내부 온도변화량 산정 및 이를 활용한 파이프라인 내부 압력변동량 예측법을 제시하였고 예측된 결과를 현장 실계측 데이터와 비교·검토하여 그 유효성을 입증하였다. 제안된 해석절차는 해저 파이프라인 설치 프로젝트 수행 사전단계에서부터 파이프라인 열전달 시뮬레이션을 통해 압력변동량 예측을 가능하게 함으로써 해저 파이프라인 설치 프로젝트의 생산성 향상에 크게 기여할 것으로 사료된다.

목적: 백내장 환자를 대상으로 수술 전과 후의 안구표면의 온도변화 양상을 열화상카메라의 서모그래피를 이용하여 연구 하고자 하였다. 방법: 본 연구는 백내장 수술을 받은 환자 50-79세까지 75명 75안의 환자 군을 대상으로 하였다. 과거에 굴절교정수술, 각막관련 수술을 받은 자와 콘택트렌즈를 사용하는 자, 눈물관 이상자, 전신질환 치료 약물을 복용하는 자 등 눈물분비와 눈물막에 영향을 줄 수 있는 자는 연구 대상자에서 제외하였고 눈물막파괴시간 검사(Tear Break Up Time, BUT), 쉬르머 검사(Schirmer’s Test), 맥모니테스트(Mcmonnies questionnaire)를 시행한 후 열화상카메라(Cox CX series, Answer., Korea)를 이용하여 안구표면의 온도변화를 실시간으로 측정하였다. 결과: 전체 대상자의 술 전 안구표면 온도는 35.20±0.54 ℃이었고 술 후에는 35.30±0.53 ℃로 표면온도가 상승하였으나 유의한 차이를 보이지 않았다. 안구표면 온도변화는 술전에서 -0.12±0.08 △(℃/sec)에서 술 후 -0.18±0.07 △(℃/sec)로 통계학적으로 유의한 결과를 나타냈다. 연령 별 비교에서는, 50 대군은 백내장 술 전 대상자의 안구표면 온도변화가 -0.14±0.09 △(℃/sec)에서 -0.19±0.05 △(℃/sec)으로 나타났고 60 대군에서는 -0.12±0.08 △(℃/sec)에서 -0.15±0.07 △(℃/sec)으로 나타났으며 70 대군에서는 술 전 대상자의 안구표면 온도변화는 -0.12±0.08 △(℃/sec)에서 -0.18±0.07 △(℃/sec)으로 전 연령에서 모두 유의한 안구표면 온도변화를 보였다. 결론: 백내장 술 후에는 안구건조증 평가지표가 모두 감소하였고 안구표면 온도변화가 유의함을 보였다. 안구표면의 서모그래피 기술은 비침습적으로 안구건조증을 평가하는데 용이하였고 객관적으로 수치화할 수 있는 장점이 있어 다양한 안구건조증 연구에 활용 될 것으로 기대된다.

대기오염에 대한 관심이 증대하면서 대기오염물질의 저감에 관한 많은 연구가 진행되고 있다. 차량용 요소수(Urea solution)를 이용한 디젤 차량의 질소산화물(NOx) 제거는 큰 효과를 나타내고 있다. 요소수의 품질은 국내법으로 엄격히 규정하고 있으나 요소수 내 불순물의 증대는 질소산화물 저감 효과를 감소시키게 된다. 따라서 본 연구에서는 일정 온도와 시간동안 요소수를 가열한 후 요소수의 물성변화를 분석하였다. 또한, 요소수를 보관하는 저장용기와 저장온도의 변화에 따른 요소수 물성변화도 함께 분석하였다. 요소수를 일정시간 가열한 후 요소수 내 뷰렛함량은 증가하고 요소함량은 감소하였으며, 요소함량 감소에 따라 밀도와 굴절률도 함께 감소하였다. 철제 및 PET 용기와 일정온도(30 ℃, 50℃)에서 실시한 저장안정성 시험에서는 물성변화가 나타나지 않았다.

PURPOSES: This study aimed to evaluate the performance of a model developed for road surface temperature change pattern in reflecting specific road characteristics. Three types of road sections were considered, namely, basic, tunnel, and soundproof tunnel. METHODS: A thermal mapping system was employed to collect actual road surface temperature and locational data of the survey vehicle. Data collection was conducted 12 times from 05:30 am to 06:30 am on the test route, which is an uninterrupted flow facility. A total of 9010 road surface temperature data were collected, and half of these were selected based on a random selection process. The other half was used to evaluate the performance of the model. The model used herein is based on machine learning algorithms. The mean absolute error (MAE) was used to evaluate the accuracy of the estimation performance of the model. RESULTS: The MAE was calculated to determine the difference between the estimated and the actual road surface temperature. A MAE of 0.48℃ was generated for the overall test route. The basic section obtained the smallest error whereas that of the tunnel was relatively high. CONCLUSIONS: The road surface temperature change is closely related to the air temperature. The process of data pre-processing is very important to improve the estimation accuracy of the model. Lastly, it was difficult to determine the influence of the data collection date on the estimation of the road surface temperature change pattern due to the same weather conditions.

본 연구에서는 평균온도 상승에 따른 출수기변화, 수량구성 요소 및 수량, 출수기건물중 및 식물체 질소함량 변화를 평가 한 결과는 다음과 같았다. 1. 생육기 평균온도 1oC 상승 시 밀의 출수기는 약 2.8일 단축된 것으로 판단되었다. 2. 평균온도 상승 시 수량구성요소와 수량이 악화되었는데, 주로 면적당수수 감소에 의해 면적당립수와 수량이 감소한 것으로 판단되었다. 3. 1수립수는 11월 7일 파종 시 고온조건에서 감소하였으나 11월 17일 파종 시 고온조건에서 감소하지 않았다. 4. 천립중은 출수 후 30일간 평균온도 1oC 당 약 2.1g씩 감소하였다. 5. 평균온도 상승 시 출수기 건물중은 감소하지 않았으나, 출수기 면적당경수는 감소한 것으로 판단되었다. 6. 고온처리 시 식물체 질소흡수량이 감소하여 면적당립수가 감소한 것으로 판단되었다.

The road surface condition in winter is important for road maintenance and safety. To estimate the road surface condition in winter, the RWIS(Road Weather Information System) is used. However RWIS is not measured the continuous road surface information but measured the locational road surface information. To overcome the current RWIS limitation, the thermal mapping sensor which can collect the road surface condition employed in some countries. Although the thermal mapping sensor can collect the continuous road surface information, it is difficult to collect vast data due to apply few probe car. This study suggests a specific methodology for the prediction of road surface temperature using vehicular ambient temperature sensors and collect road surface and vehicular ambient temperature data on the defined survey route in 2015 and 2016 year, respectively. To find out the correlation between road surface and ambient temperature which may affect patterns of road surface temperature variation, the various weather and topographical conditions along with the test route were considered. For modelling, all types of collected temperature data should be classified into response and predictor before applying a machine learning tool such as MATLAB. In this study, collected road surface temperature are considered as response while vehicular ambient temperatures defied as predictor. Through data learning using machine learning tool, models were developed and finally compared predicted and actual temperature based on average absolute error. According to comparison results, model enables to estimate actual road surface temperature variation pattern along the roads very well. Model III is slightly better than the rest of models in terms of estimation performance. When correlation between response and predictor is high, when plenty of historical data exists, and when a lot of predictors are available, estimation performance of would be much better.

PURPOSES: This study develops various models that can estimate the pattern of road surface temperature changes using machine learning methods. METHODS : Both a thermal mapping system and weather forecast information were employed in order to collect data for developing the models. In previous studies, the authors defined road surface temperature data as a response, while vehicular ambient temperature, air temperature, and humidity were considered as predictors. In this research, two additional factors-road type and weather forecasts-were considered for the estimation of the road surface temperature change pattern. Finally, a total of six models for estimating the pattern of road surface temperature changes were developed using the MATLAB program, which provides the classification learner as a machine learning tool. RESULTS: Model 5 was considered the most superior owing to its high accuracy. It was seen that the accuracy of the model could increase when weather forecasts (e.g., Sky Status) were applied. A comparison between Models 4 and 5 showed that the influence of humidity on road surface temperature changes is negligible. CONCLUSIONS: Even though Models 4, 5, and 6 demonstrated the same performance in terms of average absolute error (AAE), Model 5 can be considered the optimal one from the point of view of accuracy.

석유제품은 다양한 형태의 탄화수소화합물로 구성되어진 화합물로, 다른 종류의 액체류와 마찬가지로 온도변화에 따른 밀도와 부피의 변화가 발생한다. 액상에서 석유제품의 밀도를 측정하는 방법은 분별 증류된 각 석유제품에 대해 주로 얻어진 실험 데이터를 기반으로 한다. 본 연구에서는 등유와 자동차용 경유의 온도변화에 따른 밀도와 부피변화를 실제 측정하여 온도변화에 따른 변화추이를 분석하고, 국제규격인 ASTM에서 제시하는 밀도부피 환산표를 이용한 환산값을 계산하고 두 값을 비교분석하였다. 또한, 국내 계량 관련법에서 규정하고 있는 온도변화에 대한 기준과 실측값과의 상호 비교를 통해 차이점을 분석하였다.

This study was conducted to clarify the effect of high temperature during winter period(autumn sowing) and spring sowing on yield, quality and growth and development in barley. The varieties used for the experiments were heenchalssalbori and keunalbori 1 having a strong spring habit characteristics. In spring sowing treatment, spikelet differentiation was proceeded rapidly and tillering was proceeded slowly compared to the development stage, because the barley sowed at spring is cultivated in high temperature and long day conditions from sowing to spikelet differentiation stage compared with autumn sowing(control). And in high temperature treatment during winter period, like spring sowing, tillering was inhibited compared to the development stage. The number of grain per panicle and the period required to heading stage from spikelet differentiation were reduced largely at spring sowing, because spring sowing treatment was conducted in high temperature and long day condition compared with autumn sowing and high temperature treatment during the period from spikelet differentiation to heading stage. Meanwhile in spring sowing treatment, average temperature during ripening stage was higher than the autumn sowing and high temperature during winter, because heading stage was so late. After all, starch, amylose content and grain weight were reduced while protein content was relatively increased in spring sowing treatment due to difference of average temperature of ripening stage. These changes affected the decrease of viscosity of peak, trough, breakdown and the increase of setback viscosity

In this study, we investigate the effect of the diffusion barrier and substrate temperature on the length of carbon nanotubes. For synthesizing vertically aligned carbon nanotubes, thermal chemical vapor deposition is used and a substrate with a catalytic layer and a buffer layer is prepared using an e-beam evaporator. The length of the carbon nanotubes synthesized on the catalytic layer/diffusion barrier on the silicon substrate is longer than that without a diffusion barrier because the diffusion barrier prevents generation of silicon carbide from the diffusion of carbon atoms into the silicon substrate. The deposition temperature of the catalyst and alumina are varied from room temperature to 150°C, 200°C, and 250°C. On increasing the substrate temperature on depositing the buffer layer on the silicon substrate, shorter carbon nanotubes are obtained owing to the increased bonding force between the buffer layer and silicon substrate. The reason why different lengths of carbon nanotubes are obtained is that the higher bonding force between the buffer layer and the substrate layer prevents uniformity of catalytic islands for synthesizing carbon nanotubes.

급격한 수온의 변화는 어류의 생리학적인 측면에서 스트레스를 유발한다. 본 연구에서는 넙치 (Paralichthys olivaceus)로부터 각 수온별(9, 12, 15, 18 및 21℃) 조건에 따라 24 및 48시간 동 안 노출시킨 후에, 혈액생리학적 분석, 스트레스 단백질로 알려진 Hsp70 mRNA 발현 및 산소 소비량을 조사하였다. 혈액학적 분석에서 hematocrit (Ht) 및 hemoglobin (Hb), 혈장 코티졸 및 글루코스의 변화, aspartate aminotransferase (AST) 및 alanine aminotransferase (ALT), NH3, 삼 투질농도(osmolality) 및 총단백질(total protein, TP)은 9℃ 및 12℃에서 다른 수온별 실험구에 비 해 대부분의 항목에서 유의적인 차이를 보였다. Hsp70 mRNA 발현은 9℃ 및 12℃에서 다른 실험구에 비해 높은 발현량을 확인하였고, 산소소비량은 9℃ 및 12℃에서 21℃에 비해 낮았다. 이러한 결과는 넙치 종자의 장거리 수송을 위한 수온자료로 활용할 수 있다

PURPOSES:This study suggests a specific methodology for the prediction of road surface temperature using vehicular ambient temperature sensors. In addition, four kind of models is developed based on machine learning algorithms.METHODS:Thermal Mapping System is employed to collect road surface and vehicular ambient temperature data on the defined survey route in 2015 and 2016 year, respectively. For modelling, all types of collected temperature data should be classified into response and predictor before applying a machine learning tool such as MATLAB. In this study, collected road surface temperature are considered as response while vehicular ambient temperatures defied as predictor. Through data learning using machine learning tool, models were developed and finally compared predicted and actual temperature based on average absolute error.RESULTS:According to comparison results, model enables to estimate actual road surface temperature variation pattern along the roads very well. Model III is slightly better than the rest of models in terms of estimation performance.CONCLUSIONS :When correlation between response and predictor is high, when plenty of historical data exists, and when a lot of predictors are available, estimation performance of would be much better.

The purpose of this study is to analyze the climate change exposure of fisheries and fish species in the southern sea of Korea under the RCP climate change scenarios. The extent of exposure was calculated through weighted sum of the sea temperature forecasted by National Institute of Fisheries Science, and the weight were obtained from the time-space distribution of each fisheries or species, based on the micro-data for the fishing information reported by each fisherman. Results show that all the exposed sea temperature of RCP8.5 is higher than that of RCP4.5 in year 2100 as well as in near 2030, therefore it is thought to be very important to reduce the GHG emission even in the short term. The extent of exposure was analyzed to be comparatively high especially in the fisheries such as anchovy drag nets and species like cod, anchovy and squid. Meanwhile the method of this study is considered to be excellent to obtain the accurate extent of exposure under RCP scenarios, and therefore it is applicable on assessing the vulnerability of climate change in fisheries.

The spring emergence of individual insect would be influenced by surface temperature during winter season. The oriental fruit moth, Grapholita molesta, overwinter as a full-grown larva within spherical and compactly woven cocoons in the clefts of tree bark. It consume new shoots early and fruits later in the growing season. To estimate the spring emergence of G. molesta, we used the lower developmental threshold (8.14°C) and thermal constant (279.3) for overwintering G. molesta. The climate data were obtained from the web site of the Korea Meterological Administration(KMA) from 1975 to 2015 at 61 locations, respectively. The spring emergence of G. molesta was changed depending on ambient temperature of each year.

This experiment was conducted to clarify the effect of the high temperature on physicochemical properties of barley kernels during ripening stage. High temperature treatment was lasted from each 10, 17 and 24 days after heading(DAH) until the harvest time at 21oC, 24oC, 27oC in artificial climate room. The results showed that ripening period from heading to maturity was tend to be shorter at higher temperature treatment condition and at longer duration treatment condition. and 1000-grain weight was decreased as the ripening period shortened. Furthermore, gelatinization properties was changed by high temperature due to the reduction of starch and amylose contents. As the shortening of grain filling period by a high temperature treatment, the protein content was increased. In the 10 DAH at 27oC treatment, the grain filling period was shortened by 9 days. The starch contents was reduced by 5.7 %, and the protein content was increased by 5.6 % in a such condition. Protein contents was showed negative correlations with amylose, starch contents and gelatinization properties, respectively. Starch contents, however, showed positive correlations with amlyose content and gelatinization properties.