PURPOSES : In this study, the alkali aggregate reactivity and expansion characteristics of mortar mixed with waste glass (a recycled aggregate) were confirmed to verify the alkali-silica reaction (ASR) stability and review the appropriateness of the alkali aggregate reactivity test method following the replacement of recycled aggregate. METHODS : The alkali-aggregate reactivity of waste glass aggregates was measured using the chemical and physical methods described in KS F 2545 and ASTM C 1260, respectively. The reactivity was classified by comparing the results. Cement with a high-alkali content was used to simulate an environment that can induce ASR. Non-reactive fine aggregates, waste glass fine aggregates, reactive general aggregates, and Ferronickel slag aggregates were used as control groups. RESULTS : Waste glass fine aggregates were classified as reactive when applying the chemical method. In the physical method, they were classified as reactive at 100% and latent reactive at 1%, based on the mixing ratio. Additionally, we discovered that the reliability of the chemical method was low since the ASR of the aggregates was classified differently based on the evaluation method, while the results of the chemical and physical test methods were inconsistent. CONCLUSIONS : To determine the alkali reactivity of recycled aggregates, the complex use of chemical and physical methods and analysis based on the mixing ratio of the reactive aggregates are required. Small amounts of waste glass aggregate replacements affected the ASR. Because ASR reaction products can affect the long-term thermal expansion of the structure, further research is needed to use ASR aggregates in structures.

PURPOSES : The initial smoothness of concrete pavement surfaces must be secured to ensure better driving performance and user comfort. The roughness was measured after hardening the concrete pavement in Korea. When the initial roughness is poor, relatively large-scale repair works, such as milling or reconstruction must be performed. Hence, a method to measure the roughness of the concrete pavements in realtime during construction and immediately correct the abnormal roughness was developed in this study. METHODS : The profile of a concrete pavement section was measured at a construction site using sensors that were attached to the tinning equipment of the paver. The measured data included outliers and noise caused by the sensor and vibration of the paving equipment, respectively, which were further calibrated. Consequently, the calibrated data were input into the ProVAL program to calculate the roughness based on the international roughness index (IRI). Additionally, the profile of the section was re-measured using another method to verify the reliability of the calculated IRI. RESULTS : The profile data measured at the concrete pavement construction site were calibrated using methods, such as overlapped boxplot outlier removal and low-pass filtering. The outlier data from the global positioning system (GPS), which was installed to identify the construction distance, was also calibrated. The IRI was calculated using the ProVAL program by matching the measured profile and GPS data, and applying the moving average method. The calculated IRI was compared to that measured using another method, and the difference was within the tolerance. CONCLUSIONS : A method to measure the roughness of the concrete pavements in real time during construction was developed in this study. Hence, the performance of concrete pavements can be improved by enhancing the roughness of the pavement considerably using the aforementioned method.

목적 : 본 연구의 목적은 발달장애 아동을 위한 태블릿 기반의 인지평가를 통해 세부 인지기능의 프로파일 을 비교함으로써 본 평가가 진단그룹에 따른 인지기능 상태를 평가하는데 변별력이 있는지 알아보고자 하였다. 연구방법 : 총 80명의 만 4~12세 아동이 본 연구에 참여하였다. 진단명별로 자폐 스펙트럼(Autism Spectrum Disorders; ASD) 24명, 지적장애(Intellectual Disability; ID) 20명, 주의력결핍 및 과잉행 동 장애(Attention-Deficit Hyperactivity Disorder; ADHD) 7명, 정상발달 아동 29명이 참여하였다. 태블릿으로 개발된 인지평가는 총 8개 항목으로 공간작업기억, 작업기억용량, 시각적 작업기억, 시지각 처리기술, 집행기능(계획), 집행기능(반응억제 및 주의력), 집행기능(억제)의 세부 인지항목으로 구성되 어 있다. 평가를 시행한 후 진단그룹에 따른 차이를 Kruskal-Wallis 검정을 통해 비교하였다. 통계분석 은 Jamovi 1.6.23 을 사용하였다. 결과 : 정상발달 아동에 비해 자폐 스펙트럼, 지적장애, ADHD 아동의 인지평가 총점이 통계적으로 유의 미하게 다른 것으로 나타났다(χ²= 22.41, p < .001). 정상발달 아동에 비해 자폐 스펙트럼 아동은 시각 처리기술 및 억제기능의 항목에서 유의미한 기능 저하를 보였고, 지적장애 아동은 작업기억 용량, 시각적 작업기억과 반응억제 및 주의력 항목에서 유의미한 기능 저하를 보이는 것으로 나타났다. 한편, ADHD 아동의 경우 정상발달 아동에 비해 통계적으로 유의미한 차이를 보이는 인지평가 항목이 없었다. 결론 : 본 연구에서 개발된 태블릿 기반의 인지평가는 정상발달 아동과 발달장애 아동의 인지기능의 상태 를 변별함으로써 치료의 기초자료로써 활용 가치가 있다.

PURPOSES : Local governments in Korea, including Incheon city, have introduced the pavement management system (PMS). However, the verification of the repair time and repair section of roads remains difficult owing to the non-existence of a systematic data acquisition system. Therefore, data refinement is performed using various techniques when analyzing statistical data in diverse fields. In this study, clustering is used to analyze PMS data, and correlation analysis is conducted between pavement performance and influencing factors. METHODS : First, the clustering type was selected. The representative clustering types include K-means, mean shift, and density-based spatial clustering of applications with noise (DBSCAN). In this study, data purification was performed using DBSCAN for clustering. Because of the difficulty in determining a threshold for high-dimensional data, multiple clustering, which is a type of DBSCAN, was applied, and the number of clustering was set up to two. Clustering for the surface distress (SD), rut depth (RD), and international roughness index (IRI) was performed twice using the number of frost days, the highest temperature, and the average temperature, respectively. RESULTS : The clustering result shows that the correlation between the SD and number of frost days improved significantly. The correlation between the maximum temperature factor and precipitation factor, which does not indicate multicollinearity, improved. Meanwhile, the correlation between the RD and highest temperature improved significantly. The correlation between the minimum temperature factor and precipitation factor, which does not exhibit multicollinearity, improved considerably. The correlation between the IRI and average temperature improved as well. The correlation between the low- and high-temperature precipitation factors, which does not indicate multicollinearity, improved. CONCLUSIONS : The result confirms the possibility of applying clustering to refine PMS data and that the correlation among the pavement performance factors improved. However, when applying clustering to PMS data refinement, the limitations must be identified and addressed. Furthermore, clustering may be applicable to the purification of PMS data using AI.

PURPOSES : The purpose of this study is to confirm the thermal expansion characteristics of concrete mixed with 1% waste glass fine aggregates, which is the amount stipulated for recycled aggregates in the current quality standard. METHODS : The coefficient of thermal expansion was measured by applying AASHTOT 336-10 using a LVDT. The results measured were used as physical properties in a finite element analysis to confirm the change in tensile stress and the displacement of the right angle section of the upper slab of a concrete pavement due to admixture substitution. RESULTS : The thermal expansion coefficients of concrete based on the replacement rate of the admixture when the waste glass fine aggregates are replaced are within the range of the thermal expansion coefficients of concrete specified in the Federal Highway Administration report. As the replacement rate of the admixture increases, the thermal expansion coefficient of concrete decreases. As the thermal expansion coefficient decreases, the slab pavement curling displacement and the tensile stress of the center of the upper slab of concrete decrease. CONCLUSIONS : In the short term, the presence or absence of waste glass fine aggregates does not significantly affect the thermal expansion coefficient of concrete. However, in the long term, waste glass fine aggregates are reactive aggregates that causes ASR, which creates an expandable gel around the aggregates and results in concrete expansion. Therefore, the relationship between ASR and the thermal expansion coefficient must be analyzed in future studies.

PURPOSES : In this study, surface distress (SD), rutting depth (RD), and international roughness index (IRI) prediction models are developed based on the zones of Incheon and road classes using regression analysis. Regression analysis is conducted based on a correlation analysis between the pavement performance and influencing factors. METHODS : First, Incheon was categorized by zone such as industrial, port, and residential areas, and the roads were categorized into major and sub-major roads. A weather station triangle network for Incheon was developed using the Delaunay triangulation based on the position of the weather station to match the road sections in Incheon and environmental factors. The influencing factors of the road sections were matched Based on the developed triangular network. Meanwhile, based on the matched influencing factors, a model of the current performance of the road pavement in Incheon was developed by performing multiple regression analysis. Sensitivity analysis was conducted using the developed model to determine the influencing factor that affected each performance factor the most significantly. RESULTS : For the SD model, frost days, daily temperature range, rainy days, tropical nights, and minimum temperatures are used as independent variables. Meanwhile, the truck ratio, freeze–thaw days, precipitation days, annual temperature range, and average temperatures are used for the RD model. For the IRI model, the maximum temperature, freeze–thaw days, average temperature, annual precipitation, and wet days are used. Results from the sensitivity analysis show that frost days for the SD model, precipitation days and freeze–thaw days for the RD model, and wet days for the IRI model impose the most significant effects. CONCLUSIONS : We developed a road pavement performance prediction model using multiple regression analysis based on zones in Incheon and road classes. The developed model allows the influencing factors and circumstances to be predicted, thus facilitating road management.

PURPOSES : To efficiently manage pavements, a systematic pavement management system must be established based on regional characteristics. Suppose that the future conditions of a pavement section can be predicted based on data obtained at present. In this case, a more reasonable road maintenance strategy should be established. Hence, a prediction model of the annual surface distress (SD) change for national highway pavements in Gangwon-do, Korea is developed based on influencing factors. METHODS : To develop the model, pavement performance data and influencing factors were obtained. Exploratory data analysis was performed to analyze the data acquired, and the results show that the data were preprocessed. The variables used for model development were selected via correlation analysis, where variables such as surface distress, international roughness index, daily temperature range, and heat wave days were used. Best subset regression was performed, where the candidate model was selected from all possible subsets based on certain criteria. The final model was selected based on an algorithm developed for rational model selection. The sensitivity of the annual SD change was analyzed based on the variables of the final model. RESULTS : The result of the sensitivity analysis shows that the annual SD change is affected by the variables in the following order: surface distress ˃ heat wave days ˃ daily temperature range ˃ international roughness index. CONCLUSIONS : An annual SD change prediction model is developed by considering the present performance, traffic volume, and climatic conditions. The model can facilitate the establishment of a reasonable road maintenance strategy. The prediction accuracy can be improved by obtaining additional data, such as the construction quality, material properties, and pavement thickness.

미토콘드리아 시토크롬 c 산화효소 1 (COX1) 유전자 염기서열(658 bp)을 사용하여, 콩 포장에서 채집된 어리팥나방(Matsumuraeses falcana)과 팥나방(Matsumuraeses phaseoli)의 종을 실험실 집단의 종들과 비교하여 동정하였다. COX1 염기서열 분석에서, 어리팥나방 47개체 로부터 10개의 하플로타입이 발견되었고, 종내 유전적 거리는 0.15~0.46%이었다. 이중 하프로타입 A형이 약 70%로 우점형이었다. 팥나방의 30개체로부터는 모두 동일한 하나의 서열만이 확인되었고, 어리팥나방과의 종간 유전적 거리는 4.11~4.61%이었다. 두 종의 COX1 염기서열을 번역한 아미노산 서열은 모두 동일하여 동의적 염기서열 변이(동의치환, 同義置換, synonymous substitution)를 확인할 수 있었다. 포장 조사에 서 두 종의 유충이 콩의 잎과 꼬투리를 가해하였고, 한 포장에서 동시에 발생하였다. 전체 포장에서 어리팥나방의 평균 밀도는 팥나방보다 약 1.5 배 높았다. 이 결과는 콩이 두 종의 동일 기주임을 명백하게 제시하였다. 별도로 이 속의 유충 기생파리로서 Elodia flavipalpis (파리목: 기생파리 과)가 발견되었고, COX1 서열로 동정되었다.

콩줄기명나방은 콩과작물 특히 팥을 가해하는 해충으로 알려져 있다. 본 연구는 온도가 콩줄기명나방의 발육단계별 발육기간, 성충의 수명 과 산란특성에 미치는 영향을 파악하고자 7, 10, 13, 16, 19, 22, 25, 28, 31, 34, 36°C 항온조건에서 조사하였다. 알과 유충은 7, 10, 13°C를 제 외한 항온조건에서 다음 생애단계로 성공적으로 발육하였다. 알, 유충, 번데기의 발육기간은 온도가 상승할수록 짧아지는 경향을 보였다. 콩줄기 명나방 발육단계별 발육 최저, 최고 한계는 LRF와 SSI모델을 이용하여 계산하였고 발육영점온도와 유효적산온일도는 선형회귀분석을 이용하 였다. 1령 유충 부화부터 성충출현까지의 발육영점온도와 유효적산온일도는 13.5°C와 384.5DD로 추정되었다. SSI모델을 이용한 부화부터 성 충출현까지 발육 최저 및 최고온도는 19.4°C과 39.8°C였고 이들간의 차이 즉 발육적정온도범위는 20.4°C였다. 성충은 16°C와 34°C 범위에서 부화하는 알을 생산하였고, 25°C에서 최대 약 416마리의 자손을 낳았다. 노화율, 나이별 생존율, 나이별 누적산란율, 온도의존 산란수에 관련된 성충모델들이 작성되었다. 본 연구에서 제시한 온도발육모형과 산란모형은 야외에서 콩줄기명나방의 개체군동태를 이해하고 콩과작물의 종합적 인 해충군관리체계를 마련하는데 기초기반자료로 활용될 것으로 기대된다.

콩명나방은 콩과작물 특히 팥을 가해하는 해충으로 알려져 있다. 본 연구는 콩명나방의 생물적 특징을 알아보기 위해 발육단계별 발육기 간, 성충의 수명과 번식능력을 13, 16, 19, 22, 25, 28, 31, 34°C 항온조건에서 조사하였다. 알은 모든 항온조건에서 부화하였고 유충은 16~ 31°C 온도조건에서 성공적으로 성충까지 발육을 완료하였다. 알의 발육기간은 31°C까지 온도가 상승할수록 짧아지다가 이후 온도에서 길어지 는 경향을 보였다. 유충, 번데기의 발육기간과 성충수명은 온도가 상승할수록 감소하였다. 콩명나방 발육단계별 발육 최저, 최고 한계는 LRF와 SSI모델을 이용하여 계산하였고 발육영점온도와 유효적산온일도는 선형회귀분석을 이용하였다. 1령 유충 부화부터 성충출현까지의 발육영점온 도와 유효적산온일도는 12.8°C와 280.8DD였다. SSI모델을 이용하여 추정한 부화부터 성충출현까지 발육최저 및 최고온도는 14.2°C과 31.9°C였고 이들간의 차이 즉 발육적정온도범위는 17.7°C였다. 온도와 관련된 콩명나방 성충의 생존, 수명, 산란기간, 산란수 자료들을 이용하 여 산란모형을 작성하였다. 본 연구에서 제시한 온도발육모형과 산란모형은 야외에서 콩명나방의 개체군동태를 이해하고 콩과작물의 종합적인 해충군관리체계 확립에 기여할 것으로 보인다.

팥나방은 콩과작물 특히 팥을 가해하는 해충으로 알려져 있다. 본 연구는 팥나방의 생물적 특징을 알아보기 위해 발육단계별 발육기간, 성 충의 수명과 번식능력을 7, 10, 13, 16, 19, 22, 25, 28, 31, 34°C 항온조건에서 조사하였다. 알은 7°C와 34°C를 제외한 모든 항온조건에서 부화 하였고 유충은 13~28°C 온도조건에서 성공적으로 성충으로 발육하였다. 알의 발육기간은 25°C까지 온도가 상승할수록 짧아지다가 이후 온도 에서 길어지는 경향을 보였다. 유충, 번데기의 발육기간과 성충수명은 온도가 상승할수록 감소하였다. 팥나방 발육단계별 발육 최저, 최고 한계는 LRF와 SSI모델을 이용하여 계산하였고 발육영점온도와 유효적산온일도는 선형회귀분석을 이용하였다. 1령 유충 부화부터 성충출현까지의 발 육영점온도와 유효적산일은 9.1°C와 264.5DD였다. SSI모델을 이용한 부화부터 성충출현까지 발육최저 및 최고온도는 20.0°C과 32.3°C였고 이들간의 차이 즉 발육적정온도범위는 12.3°C였다. 온도와 관련된 팥나방 성충의 생존과 산란특성을 이용하여 산란모형을 작성하였다. 본 연구 에서 제시한 온도발육모형과 산란모형은 야외에서 팥나방의 개체군동태를 이해하고 콩과작물의 종합적인 해충군관리체계 확립에 기여할 것으로 보인다.