본 연구는 흑산도 산림유전자원보호구역을 대상으로 산림식생구조를 파악하고자 수행하였으며, 2017년 6월부터 2017년 8월까지 총 59개 조사구에서 식생조사를 실시하였다. Z-M 식물사회학적 방법으로 산림식생 유형을 분류하고 식생단위별 구성종의 중요치와 종다양도를 분석하였다. 산림식생유형분류 결과 최상위 단위에서 동백나무군락군으로 분류되었으며, 군락단위에서는 황칠나무군락(식생단위 1), 소사나무군락, 동백나무전형군락(식생단위 6)의 3개 군락으로 분류되었다. 소사나무군락은 회양목군(식생단위 2), 진달래군(식생단위 3), 왕머루군(식생단위 4), 소사나무전형군 (식생단위 5)의 4개 소군으로 분류되었다. 식생단위별 평균상대우점치 분석 결과 식생단위 1은 붉가시나무, 식생단위 2는 소사나무, 식생단위 3은 곰솔, 식생단위 4는 소나무, 식생단위 5와 6은 구실잣밤나무가 각각 우점치가 가장 높게 나타났다. 종다양도 분석결과 식생단위 2의 종풍부도, 종다양도, 종균재도가 가장 높았으며, 종우점도는 식생단위 6이 가장 높았다. 흑산도 산림유전자원보호구역의 6개 식생단위와 12개 종군에 대한 군집생태학적 접근의 관리방안이 필요할 것으로 판단되었다.

2015년부터 최근까지 차세대도시농림융합기상사업단에서는 수도권에 위치한 도시기상 관측소에서 관측된 기상 자료(14소), 운고계(2소) 그리고 마이크로웨이브 라디오미터(MWR, 7소) 자료를 이용하여 태양에너지를 산출하였다. 수 도권지역에 위치한 운고계에서 관측된 후방산란계수와 MWR에서 추정된 액상물량을 이용하여 구름광학두께와 운량을 산출하였다. 각각의 원격탐사장비에서 산출된 운량을 태양복사모델에 입력하여 지표면에 도달하는 태양에너지를 계산하였다. 추정된 태양에너지를 관측과 비교한 결과, 중랑과 광화문지점에서는 과소추정이 나타났다. 선형회귀분석한 결과 0.8이하의 기울기를 나타냈고 −20W/m 2의 음의 편차와 120 W/m 2의 평방근오차(RMSE)가 나타났다. 그리고 MWR을 이용하여 추정된 태양에너지의 정확도(평균 결정계수(R 2 )=0.8)와 오차율(평균 RMSE=110 W/m 2 )이 향상되었다. 월별 산출된 운량과 태양에너지는 운고계를 이용하여 산출하였을 때 운량이 0.09 이상 크게 나타났으며 태양에너지가 50W/m 2 이상 낮게 산출되었다. 지점에 따라 차이는 있었으나 대체로 7월과 9월의 RMSE가 50W/m 2 이상 크게 계산되었다. 결과적으로 일누적 태양에너지는 광화문지점에서 가장 높은 상관성이 나타났고(R 2 =0.80, RMSE=2.87 MJ/Day), 구로지점에서 상관성이 가장 낮았다(R 2 =0.63, RMSE=4.77 MJ/Day).

동해안 산불피해지역에서 참나무 잎 생산량의 시공간적 변이가 초식자의 밀도, 종풍부도 및 초식 피해에 미치는 영 향을 분석하였다. 본 조사지역에서 참나무 잎의 주요 초식자는 나방 유충이었다. 초식곤충의 유충의 종풍부도와 밀도가 가장 높아지는 시기는 8월 중순이었다. 연간 출현한 초식곤충 유충의 60.5%가 8~9월에 집중적으로 출현하였다. 참나무 잎 생산량이 가장 많은 시기는 7~8월이었고, 초식곤충에 의한 피해가 가장 많은 시기는 8~9월이었다. 조사시기와 장소에 따라 참나무 잎 생산량, 초식곤충의 유충밀도 및 종풍 부도는 큰 변이를 나타내었다. 본 조사지역에서 7~8월에 평균 참나무 잎 생산량은 0.96 ton ha-1로 추정되었다. 또한 이 시기에 참나무 잎의 생산량은 0.34~1.89 ton ha-1의 공간적 인 변이를 나타내었다. 8월에 초식자에 의한 참나무 잎의 소비량은 0.15~1.51 ton ha-1의 공간적인 변이를 나타내었다. 참나무 잎의 생산량이 많은 곳일수록 초식자의 종풍부도와 밀도가 증가하는 경향이 있었다. 참나무 잎 생산량의 증가에 따라 초식자에 의한 소비량과 소비비율도 증가하였다. 이 것은 참나무 잎의 생산이 많은 시기와 공간으로 초식자들이 모이는 집중화 반응이 일어난다는 것을 의미한다. 산불피해 지역에서 먹이자원의 시공간적인 이질성과 그로 인한 먹이망의 상위단계에 미치는 영향에 대한 연구는 산불지역 생태계의 구조와 기능을 정량적으로 이해하고 평가하는 데 도움을 줄 수 있다.

This study was conducted to evaluate the forage production and feed value of Sasa borealis (S. borealis) in Jeju Island in order to improve the utilization of Sasa borealis and to help mitigate the problem of reduced plant species diversity caused by S. borealis in Hanlla Mountain. To investigate the forage production, three quadrat structures were installed in the S. borealis natural community in the middle part of Hanlla Mountain. From May to October 2017, S. borealis in quadrats was cut at a fixed time of each month, and then forage production and regenerated acidity per kg/ha were evaluated. For the evaluation of feed value, compositional analysis was performed on the monthly samples. In vitro digestion experiments were carried out using cannula mounted Hanwoo. In vitro neutral detergent fiber digestibility(IVNDFD) and in vitro acid detergent fiber digestibility(IVADFD) were measured after the experiment. Forage production of S. borealis showed relatively good regeneration ability in May and June, but the regeneration ability decreased as the cutting was repeated. In order to use S. borealis as a forage, it is considered efficient to feed black goats with good fiber decomposition or horses good palatability to S. borealis and relatively good digestibility.

This study estimated the effect of sowing and harvesting dates on dry matter (DM) yield and feed value of forage oats at Sancheong, Korea. The forage oats (Darkhorse vs. Highspeed) were used in this experiment. The experimental main plots consisted of the different sowing and harvesting dates at 2 seasons as follows: spring oats of sowing (February 25, March 3 and March 13) and harvesting (May 27, June 6 and June 16); and fall oats of sowing (August 15, August 25 and September 4) and harvesting (October 15, October 25 and November 4). On spring oats, Highspeed sown on March 3 and then harvesting on June 6 had the highest (p<0.05) plant length and DM yield. Crude protein content decreased (p<0.05) in seed of the delayed-harvesting Highspeed. On fall oats, plant length and DM yield with the delayed-harvesting date increased (p<0.05), while crude protein content of the delayed-harvesting Highspeed decreased (p<0.05). This study concluded that the spring oat sown in early March and then harvesting in early June was recommended to increase dry matter and feed value although the fall oat sown in end August and then harvesting in early November was recommended for fall period.

Background: The craniocervical flexion (CCF) exercise is one of the effective exercise in correcting forward head posture (FHP). However, some people with FHP achieve CCF with compensatory movements, for example, low cervical flexion using superficial neck flexors such as the sternocleidomastoid (SCM) muscle. No study has yet investigated whether a dualpressure biofeedback unit (D-PBU) method to prevent low cervical flexion would be helpful in performing pure CCF movement. Objects: The purpose of this study was to compare the effects of the CCF using D-PBU method and the traditional CCF method on the cross-sectional area (CSA) of the longus colli muscle (LCM) and the activity of SCM muscle in subjects with FHP. Methods: Twentyfour FHP subjects (male: 16, female: 8) were recruited for this study. All subjects performed CCF using two different methods: The traditional CCF method and the CCF using D-PBU method. The CSA of the LCM was measured via ultrasound, and surface electromyography was used to measure SCM muscle activity. Results: The change in CSA of the LCM was significantly larger during the CCF using D-PBU method (1.28±.09) compared with the traditional CCF method (1.19±.08) (p<.05). The SCM muscle activity using the CCF using D-PBU method (2.01±1.97 %MVIC) was significantly lower than when using the traditional CCF method (2.79±2.32 %MVIC) (p<.05). Conclusion: The CCF using D-PBU method can be recommended for increasing LCM activation and decreasing SCM muscle activity during CCF movement in subjects with FHP.

Rest area is a space providing opportunities to use a restroom, refuel, reduce fatigue and receive mechanical maintenance services. In Korea, entering rate to rest area from mainline traffic and duration time in rest area are the key variables in the determination of size of rest area. However, there are many controversies because of inconsistency of those variables between rest areas. Moreover, cases that parking space of newly opened rest area are heavily congested which led to an early expansion are also reported frequently. Review on studies related to design variables for the size of rest area shows that they mostly focus on entering rate, the most superficial aspect of driver’s behavior with regression analysis with mainline traffic volume of and geographical condition. Also, studies did not succeed to explain the difference in entering rates of two different rest areas with similar mainline traffic volume. In this research, aggregate methodology has been adopted to overcome prior studies’ limitation. DSRC (Dedicated Short Rage Communication) data collected from RSE (Road Side Equipment) along expressway has been analyzed to construct trip trajectory of each vehicle. From the analysis of each vehicle’s trip trajectory, rest area usage pattern has been found out to be a result of each vehicle’s travel characteristics including departure time, time of the day when passing rest area, and driving duration. And as a result, data-driven analysis methodology was able to be laid out.

As the demand of fossil fuel has been increased, meeting future will be faced with exhausted non-renewable energy generation. In addition, there is a lot of expectation that fossil fuel resources are expected to get depleted in the end of century. Piezoelectric energy harvesting technology has significant advantages over other renewable energy sources such as solar panel, wind and geothermal energy. By using the pressure of vehicles, the piezoelectric energy transforms to electric energy by deformation of paving materials. There are many studies about this theme, only a few researches have been conducted on-site. It means that piezoelectric harvester is not available for roadway. Therefore, it is necessary to make it better a research framework that is available technology of piezoelectric materials and paving materials. The piezoelectric generator is tested before piezoelectric harvester manufacture for roadway. Each piezoelectric generator produces 9.38[mW/cm²] and piezoelectric harvester is manufactured by the number of 85 the piezoelectric generator. This harvester size has 50*20*9cm3 which is considered for wheel path of vehicle. When the chosen vehicle (about 2 ton) pass this harvester, the amount of electric energy is 255[W/m²] under 2[mm] of deformation and 30[km/h] of velocity. In this situation, the gathered energy is multiplied the maximum of voltage and electric current then divide it for the area of harvester. The test result is the temperature difference between the inside and outside after the thermal insulation coating process. When the external surface temperature is increased to 180 degrees, the internal temperature is kept 80 degrees even after about 30 minutes, indicating that the internal materials are protected from heat. In spite of many advantages with piezoelectric harvesting system, it is very hard to fit between roadway and harvester because of pavement damage. Most of paving material has a strong thickness. In this study, instead of asphalt and concrete pavement, the paving material is compound of poly-urethane to protect rutting and damage. To analysis for behavior, test is conducted by 90,000 times of wheel load on the pavement. The red line on the graph is commonly used asphalt pavement and the green one is polyurethane pavement. As it seemed that polyurethane pavement shows that the depth from wheel load is over 5 times better performance compared with asphalt pavement. Construction design is first of all, cutting off asphalt which is established before, then set up the tenth of piezoelectric harvesters, twenty fourth of road markers is installed into the roadway. Before filling up to space with polyurethane materials, wire arrangement and connect to controller. Each harvester is connected with controller that makes a signal for voltage, temperature sensor, water leak sensor. In order to use electric energy by harvester, road markers are selected, which each harvester has three of road markers. A circuit for lighting the light emitting device using the output of the harvester installed in the rest area was designed and manufactured. Basically, a circuit is configured to light up the harvester output, and a commercial power supply can be used in case the output of the harvester is reduced due to the durability thereof, and a controller is manufactured for each harvester to connect the road markers. Key Words: Piezoelectric Harvester

In the second half of the twentieth century, climate scientists have observed significant climate change events. Climate change scenarios characterized by increased temperature and precipitation in urban areas have resulted in disasters such as the urban heat island effect or street flooding. In response to these extreme climate scenarios, engineers have proposed permeable pavement technology. Permeable pavement is a type of pavement that allows water to flow through existing cavities into the pavement. The benefits of permeable pavement include reducing storm water runoff, reducing the heat island effect, and improving water quality, and reducing noise. In this study, a mechanistic-empirical analysis was performed to model the performance of permeable pavement in a subtropical climate with two variations of base and soil materials under both low and high traffic scenarios. The performance criteria for fatigue cracking and rutting were used to determine the service life of the permeable pavements. Furthermore, the estimated pavement performance was used to perform the life cycle analysis of the permeable pavements. Economic, environmental, and social sustainability aspects during the construction, maintenance, and operation periods were modelled for a 20 year analysis.

The purpose of this study is to review and establish the three concepts of upcycling, zero-waste fashion design, and regional sustainability through a review of domestic and international case studies. Furthermore, it will provide the theoretical basis for using upcycling as a regional sustainability practice to create zero-waste fashion design. To conduct an empirical study, we systematized the stages of the survey on waste resources in Changsin-dong, the sourcing and utilization of waste resources, the design-planning stage, and the co-production with pattern and sewing masters as a suggested practice for regional sustainability. Through this study, we propose the possibility of regional sustainability by developing and sharing the method of zero-waste fashion design. The conclusion of the study as follows: First, upcycling fashion designs can be extended to a regional sustainability practice by taking the characteristics of social design into account. Second, by providing a design development process and methodology suitable for regional sustainability application, it is helpful to revitalize regional upcycling fashion brands and communities by providing data for upcycled fashion branding. Third, as part of the revitalization project for the Changshin and Soongin areas that started in 2014, using the region’s economic, cultural, and environmental characteristics to make and sell high-value, upcycled fashion products will contribute to social and economic achievements and aid in solving regional problems.

금강초롱꽃(Hanabusaya asiatica Nakai)은 한반도 중동 부에서만 제한적으로 분포하는 고유종으로, 현재 1,000 개체 이상 정도만 남아있는 것으로 추정되어 International Union for conservation of Nature(IUCN) 적색 목록(IUCN red list)에 멸종위기(EN)종으로 지정되어 있는 종이다. 금강초롱꽃 보존을 위해서는 금강초롱꽃의 분포지역를 파악 하고 이를 보호지역으로 지정하여야 하나, 금강초롱꽃 분포 지역 대부분이 남북한 접경지역에 위치하고 있어 현장조사 를 통해 정확한 분포지역을 파악하기 쉽지 않은 실정이다. 현장조사의 대안으로 생물종 분포 모형을 활용하여 금강 초롱꽃 분포 지역를 추정해 볼 수 있긴 하지만, 대부분의 생물종 분포 모형이 체계적인 현장 조사를 통해 수집한 출 현-부재 데이터(presence-absence data)를 필요로 하여, 금 강초롱꽃 분포 지역 추정에 활용할 수 없다. Maximumentropy(Maxent)모형은 체계적인 현장 조사 없이 출현지점 만 기록한 데이터(presence-only data)만 가지고도 생물종 분포를 추정할 수 있는 머신러닝 기법의 일종으로, 본 연구와 같이 활용할 수 있는 데이터가 제한된 경우에도 유용하 게 활용할 수 있는 생물종 분포 모형이다. 본 연구에서는 현장 조사를 통해 수집한 금강초롱꽃 출현 지점 데이터와 기후와 지형, 식생 등 환경변수를 가지고 MaxEnt 모형을 학습하여 금강초롱꽃 분포지역을 추정하였다. 주요 금강초롱꽃 분포지역은 강원도 고성군과 양양군과 인제군 일원의 향로봉-건봉산 천연보고구역 일대와 설악산 일대, 인제군과 양구군 일원의 대암산 일대, 인제군 방태산 일대, 인제군 백암산 일대, 양구군 백석산 일대, 화천군 제안 산-해산 일대, 화천 수리봉 일대, 화천군과 철원군 대성산- 복주산-두류산-광덕산 일대, 화천군 화악산 일대로 추정되었고, 이 결과를 바탕으로 금강초롱꽃 보호를 위한 key biodiversity area 경계를 설정하였다.