PURPOSES : The number of snowfall and the amount of snowfall are gradually increasing, and due to the characteristics of Seoul, which has a lot of traffic, it is difficult to respond quickly with a snow removal method that relies on snow removal vehicles. Therefore, it is necessary to develop an IoT based eco-friendly snow removal system that can respond to unexpected heavy snow in winter. In this study, the low temperature operation and snow removal performance of the IoT road condition snow removal detector and the snow removal system using CNT and PCM are evaluated in the climatic environment chamber. METHODS : To make artificial snow, it consists of an climatic environment chamber that can simulate a low temperature environment and equipment that can supply compressed air and cold water. Depending on the usage characteristics of the climatic environment chamber, use an air-water type snow maker. In order to make artificial snow, wet temperature, which takes into account the actual air temperature and the amount of moisture in the air, acts as the most important variable and is suitable for making snow, below –1.5 ℃. The lower the water temperature, the easier it is to freeze, so the water source was continuously supplied at 0 ℃ to 4 ℃. One of the two different pipes is connected to the water tank to supply water, and the other pipe is connected to the compressor to supply high-pressure air. Water is dispersed by compressed air in the form of many small droplets. The sprayed microscopic water particles freeze quickly in the low temperature environmental climatic chamber air and naturally fall to the floor, forming snow. Based on the KS C IEC 60068-2-1 cold resistance test standard, an integrated environmental test procedure was prepared to apply to IoT-based snow removal systems and performance evaluation was performed accordingly. The IoT based eco-friendly snow removal system is needed to in winter, so visual check and inspect the operation at the climatic chamber before setting up it to the actual site. In addition, grid type equipment was manufactured for consistent and reliable snow removal performance evaluation under controlled environmental conditions. RESULTS : The IoT-based eco-friendly snow removal system normally carried out the task of acquiring data and images without damaging the appearance or freezing in a low temperature environment. It showed clear snow removal performance in areas where PCM and CNT heating technology were applied to the concrete slab. This experiment shows that normal snow removal tasks can be carried out in low temperature environments in winter. CONCLUSIONS : The integrated environmental test procedures and grid type evaluation equipment are applied to low temperature operation and snow removal performance evaluation of snow removal systems. In the climatic environment chamber, where low temperature environments can be simulated, artificial snow is created regardless of the season to derive quantitative experimental results on snow removal performance. PCM and CNT heating technology showed high snow removal performance. The system is expected to be applied to road site situations to preemptively respond to unexpected heavy snow in winter.

스마트팜형 시설 딸기에 예찰 없이 작물 정식 초기에 천적을 먼저 적용하는 생태공학적 Natural Enemy in First (NEF) 기법이 총채벌레류 와 진딧물류의 밀도에 미치는 영향을 확인하였다. 대조구는 약제를 처리하여 비교하였다. NEF 처리구에서 총채벌레류와 진딧물류의 천적과 서식 처로 참멋애꽃노린재와 Portulaca sp.를 적용하여 작기 종료시점까지 해충의 밀도를 대조구와 유사하게 효과적으로 관리할 수 있었다.

이 연구는 1세대 스마트 온실의 재배환경 데이터와 장미 절 화의 품질 특성 데이터를 수집하고 그 요인들 간의 상관 관계 를 분석하여 절화수명 예측 및 최적 환경 조성의 기초 자료를 얻고자 수행되었다. 이를 위해, 토경재배(SC) 및 암면배지경 양액재배(RWH) 하우스 각 1개소를 선정하여 1년간 기온, 상 대습도(RH) 및 수증기압차(VPD), 일적산광량(DLI), 근권온도 등의 환경 데이터와 매월 말 수확된 장미 ‘Miss Holland’ 절 화의 품질 특성 데이터를 수집하였으며, 이 데이터와 절화수 명과의 상관관계를 분석하였다. 절화수명은 10월과 11월을 제외하고는 SC 하우스에서 RWH 하우스보다 더 길었다. 절 화수명과 환경 및 생육 특성 간의 상관관계 분석에서 SC 하우 스의 상관계수는 RWH 하우스보다 조금 더 높았으며, 절화수 명 예측을 위한 요소들도 두 하우스 간에 차이가 있었다. SC 하우스의 절화수명 Y=0.848X1+0.366X2-0.591X3+2.224X4- 0.171X5+0.47X6+0.321X7+9.836X8-110.219(X1-X8: 최고 RH, RH 일교차, DLI, pH, Hunter’s b value, EC, 절화 장, 잎 두께; R2=0.544)로 예측되었고, RWH 하우스의 절화수명 Y=-1.291X1+52.026X2-0.094X3+0.448X4-3.84X5+0.624X6 - 8.528X7+28.45(X1-X7: 경경, 야간 VPD, 최고 근권온도, 최 저 근권온도, 기온 일교차, RH 일교차, 최고 VPD; R2=0.5243) 로 예측되었다. 이 두 모델식으로부터 SC 하우스에서는 RH, EC 및 pH가, 그리고 RWH 하우스에서는 근권 온도가 절화수명에 더 큰 영향을 미친다는 것을 추론할 수 있다. 따라서 각 재배 방법에 따라 장미의 절화수명에 더 큰 영향을 미치는 환경적 요인을 효율적으로 관리할 필요가 있다.

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

PURPOSES : The main purpose of this study is to identify vulnerable areas by evaluating public transit accessibility for the introduction of smart mobility. METHODS : This study proposes a methodology for analyzing public transportation accessibility. We identified the less accessible areas of public transit in Daegu Metropolitan City by dividing them into low- and high-facilitated areas considering travel demand and developed plans to introduce smart mobility based on the analysis results. RESULTS : Areas vulnerable to public transportation in Daegu Metropolitan City can be divided into those with low public transportation accessibility and low usage rates, those with good public transportation accessibility but low usage rates, and those with low public transportation accessibility but high usage rates. CONCLUSIONS : Based on the results of this study, it is possible to introduce customized services for each area with poor public transit accessibility, and some of the inconveniences experienced by citizens using public transit are expected to be resolved.

PURPOSES : The evaluation of the low-temperature performance of an asphalt mixture is crucial for mitigating transverse thermal cracking and preventing traffic accidents on expressways. Engineers in pavement agencies must identify and verify the pavement sections that require urgent management. In early 2000, the research division of the Korea Expressway Corporation developed a three-dimensional (3D) pavement condition monitoring profiler vehicle (3DPM) and an advanced infographic (AIG) highway pavement management system computer program. Owing to these efforts, the management of the entire expressway network has become more precise, effective, and efficient. However, current 3DPM and AIG technologies focus only on the pavement surface and not on the entire pavement layer. Over the years, along with monitoring, further strengthening and verification of the feasibility of current 3DPM and AIG technologies by performing extensive mechanical tests and data analyses have been recommended. METHODS : First, the pavement section that required urgent care was selected using the 3DPM and AIG approaches. Second, asphalt mixture cores were acquired from the specified section, and a low-temperature fracture test, semi- circular bending (SCB) test, was performed. The mechanical parameters, energy-release rate, and fracture toughness were computed and compared. RESULTS : As expected, the asphalt mixture cores acquired from the specified pavement section ( poor condition – bad section) exhibited negative fracture performances compared to the control section (good section). CONCLUSIONS : The current 3DPM and AIG approaches in KEC can successfully evaluate and analyze selected pavement conditions. However, more extensive experimental studies and mathematical analyses are required to further strengthen and upgrade current pavement analysis approaches.

본 연구의 목적은 청소년의 사회재난에 대해 안전하다는 인식이 학교생활 만족도에 미치는 영향에 있어 우울과 스마트폰 의존의 순차적 매개효과를 검증하는 것이다. 이를 위해 <한국아동·청소년패널 2018> 자료 중 중1패널 3차년도 자료를 활용하였고, Hayes(2013)의 SPSS PROCESS MACRO Model 6를 활용하여 순차적 매개효과 분석을 실시하였다. 연구결과는 다음과 같다. 첫째, 청소년의 사회재난 인식은 학교생활 만족도에 직접적으로 영향을 미치지 않았다. 둘째, 청소년의 사회재난 인식 과 학교생활 만족도와의 관계에서 우울과 스마트폰 의존의 매개효과가 각각 유의미했다. 셋째, 청소년 의 사회재난 인식과 학교생활 만족도와의 관계에서 우울과 스마트폰 의존의 순차적 매개효과가 나타났 다. 요컨대, 사회재난으로부터 안전하다는 인식을 가진 청소년들일수록 우울 수준이 낮았고, 이들은 스마트폰 의존이 낮았으며, 결과적으로 학교생활에 대한 만족도가 높았다. 본 연구는 이 같은 연구결과 를 바탕으로 청소년의 사회재난 안전 인식을 증대하고 학교생활 만족도를 높일 수 있는 정책적·실천적 제언을 하였다.