Land monitoring involves systematically understanding changes in land use, leveraging spatial information such as satellite imagery and aerial photographs. Recently, the integration of deep learning technologies, notably object detection and semantic segmentation, into land monitoring has spurred active research. This study developed a web service to facilitate such integrations, allowing users to analyze aerial and drone images using CNN models. The web service architecture comprises AI, WEB/WAS, and DB servers and employs three primary deep learning models: DeepLab V3, YOLO, and Rotated Mask R-CNN. Specifically, YOLO offers rapid detection capabilities, Rotated Mask R-CNN excels in detecting rotated objects, while DeepLab V3 provides pixel-wise image classification. The performance of these models fluctuates depending on the quantity and quality of the training data. Anticipated to be integrated into the LX Corporation's operational network and the Land-XI system, this service is expected to enhance the accuracy and efficiency of land monitoring.

Benthic attached diatoms (BADs), a major primary producer in lotic stream and river ecosystems are micro-sized organisms and require a highly magnified microscopic technique in the observation work. Thus, it is often not easy to ensure accuracy and precision in both qualitative and quantitative analyses. This study proposed a new technique applicable to improve quality control of aquatic ecosystem monitoring and assessment using BADs. In order to meet the purpose of quality control, we developed a permanent mounting slide technique which can be used for both qualitative and quantitative analyses simultaneously. We designed specimens with the combination of grid on both cover and slide glasses and compared their efficiency. As a result of observation and counting of BADs, the slide glass designed with the color-lined grid showed the highest efficiency compared to other test conditions. We expect that the method developed in this study could be effectively used to analyze BADs and contributed to improve the quality control in aquatic ecosystem health monitoring and assessment.

In this study, changes in the microbial ecosystem of the Yeongheungdo island coastal waters were investigated for five years to collect basic data. To evaluate the influence of distance from the coast on the microbial ecosystem, four sites, coastal Site (S1) and 0.75, 1.5, and 3 km away from the coast, were set up and the changes in physicochemical and biological factors were monitored. The results showed seasonal changes in water temperature, dissolved oxygen, salinity, and pH but with no significant differences between sites. For nutrients, the concentration of dissolved inorganic nitrogen increased from 6.4 μM in April-June to 16.4 μM in July-November, while that of phosphorus and silicon phosphate increased from 0.4 μM and 2.5 μM in April-June to 1.1 μM and 12.0 μM in July-November, respectively. Notably, phosphorus phosphate concentrations were lower in 2014-2015 (up to 0.2 μM) compared to 2016-2018 (up to 2.2 μM), indicating phosphorus limitation during this period. However, there were no differences in nutrients with distance from the coast, indicating that there was no effect of distance on nutrients. Phytoplankton (average 511 cells mL-1) showed relatively high biomass (up to 3,370 cells mL-1) in 2014-2015 when phosphorus phosphate was limited. Notably, at that time, the concentration of dissolved organic carbon was not high, with concentrations ranging from 1.1-2.3 mg L-1. However, no significant differences in biological factors were observed between the sites. Although this study revealed that there was no disturbance of the ecosystem, further research and more basic data on the microecosystem are necessary to understand the ecosystem of the Incheon.

본 연구에서는 뇌혈류 신호를 측정할 수 있는 시변자계 기반의 비접촉식 직물센서를 설계하여 뇌혈류 신호 검출 및 감성평가의 가능성을 탐색하고자 하였다. 직물센서는 40 denier의 은사를 30합사 한 후 컴퓨터 기계 자수하여 코일 형 센서로 구현하였다. 뇌혈류 측정 실험을 위해 코일형 센서를 경동맥 부위에 부착하고, ECG (Electrocardiogram) 전극과 RSP (Respiration) 측정 벨트를 부착 및 착용하도록 하였으며, 동시에 초음파 진단기기를 사용해 도플러 초음 파 검사(Doppler Ultrasonography)를 수행하여 혈류 속도를 측정하였다. 피험자에게 Meta Quest 2를 착용시키고, 실 험을 위해 조작된 영상 시각 자극을 보여주면서 혈류 신호를 측정한 후 시각 자극에 대한 감성평가 설문지를 작성하 도록 하였다. 측정 결과, 도플러 초음파 검사를 통해 측정된 혈류 속도 신호에 변화가 생길 때 직물센서로 측정한 신호도 함께 변화하는 것으로 나타났다. 이를 통해 코일형 직물센서를 이용하여 뇌혈류활동 신호를 측정할 수 있다 는 것을 검증하였다. 또한, 감성평가를 위하여 ECG 신호와 PLL 신호(직물센서 신호)에서 추출한 HRV를 계산해서 비교한 결과, 시각 자극으로 인한 교감신경계와 부교감신경계의 활성화에 따른 비율의 변화에 대해서는 직물센서로 측정한 신호와 ECG 신호를 이용해 계산한 값이 비슷한 경향을 보이는 것으로 나타났다. 결론적으로, 본 연구에서 개발된 시변자계 기반의 코일형 직물 센서를 통해 뇌혈류 변화 측정 및 감성 모니터링이 가능할 것으로 사료된다.

This study is to establish optimizing condition of alcohol fermentation in vinegar production with aronia, to confirm whether this can be industrially used, and to compare and analyze a change in anti-oxidative activity and quality characteristic according to alcohol fermentation of aronia. The optimized conditions for alcohol fermentation were as follows: Saccharomyces cerevisiae 5645 of yeast strain, a 5% inoculum size, aronia juice with a brix value of 14, and a glucose content of 7%. As a result to conduct scale up with optimizing conditions of alcohol fermentation of aronia, 8 days (192 hrs) of total alcohol fermentation time and 7.4% of the final alcohol content. The harvest volume accounted for approximately 90.2% with a loss of about 2.8%. As a result of antioxidant test, anti-oxidative activity of alcohol fermented liquor is lower than anti-oxidative activity of aronia extract, because of the decrease of antioxidant by oxidation of the fermentation process. However, the decrease of tannin by the fermentation process reduces acerbity of aronia, so increases overall preference

In this study, we proposed a simulator for the development of a digital multi-process welding machine and a welding process monitoring system. The simulator, which mimics the data generation process of the welding machine, is composed of process control circuit, peripheral device circuit, and wireless communication circuit. Utilizing this simulator, we aimed to develop a welding process monitoring system that can monitor the welding situations of four multi-process welding machines and three processes each, with data transmission through wireless communication. Through the operation of the proposed simulator, sequential digital processing of multi-process welding data and wireless communication were achieved. The welding process monitoring system enabled real-time monitoring and accumulation of the process data. The selection of upper and lower limits for process variables was carried out using a deep neural network based on allowable changes in bead shape, enabling the management of welding quality by applying a process control technique based on the trend of received data.

Fish school monitoring technology is utilized for various purposes, such as boat fishing and resource surveys. With advancements in information and communication technology, this technology has expanded its application to remote areas. Its significance has grown in fishing sites, particularly for improving the efficiency and cost-effectiveness of set-net fishing. Set-net fishing gears are not limited to coastal areas, but are also installed in inland and remote sea regions. Consequently, fishermen require technology that allows them to quickly transmit information about approaching fish schools and enables them to perform long-term monitoring. The development of remote monitoring technology for set-net fish schools must consider crucial design factors such as communication range, transmission speed, power consumption of information modules, and operational expenses. In this study, we developed a low-power remote monitoring module for set-net fish school based on WCDMA. The module was specifically designed to minimize power consumption, allowing for communication over long distances and extended operation times in set-net fishing applications. Furthermore, we developed a web server software application that enables remote access to fish schools and provides real-time weather information. The performance of the developed module was evaluated through set-net fishing site application and experiments with moving ships on the sea. The experimental results demonstrated that the remote monitoring system, consisting of the developed low-power remote monitoring module for set-net fish school based on WCDMA and a fish finder, had an average power consumption of 4.6 W, a maximum communication range of 22.84 km, and a data transmission and reception rate of 98.79%. The maximum fish school information transmission and reception rate was 97.26%.

이 연구는 준수사항 위반행동을 종속변수로 하여 종단적 관점에서 잠재성장모형을 활용하여 각 이론에 기반에 주요 요인들이 종속변수에 어떠한 영향이 있는지를 확인 하고자 하였다. 독립변수는 각각 인구사회학적 변수, 억제이론, 사회유대이론, 사회재 통합이론, 심리적 관점을 기반으로 추출하였다. 연구분석을 위하여 각 변수들에 대한 기술통계분석과 상관관계분석을 선결적으로 진행하였으며, 최종적으로 잠재성장모형 을 활용하였다. 잠재성장모형분석은 총 3단계로 구성되며, 1단계에서는 종속변수의 평균적 발달궤적을 분석하고, 2단계에서 시간적으로 고정된 독립변수를 투입하는 방 식으로 분석하였다. 3단계는 이 연구의 최종모형으로 시간 가변적 변수를 투입하여 분석하였다. 분석결과 시간 고정적 변수 중 전자장치부착기간은 준수사항 위반행동의 발달궤적 초기치에 정(+)의 관계가 있었으며, 총 전과 횟수는 초기치와 변화율, 2차항 모두에서 유의미한 영향을 보였다. 시간 가변적 변수 중에는 부모관계, 생계안정성, 담당관의 지도･감독 횟수가 유의미한 관계가 있는 것으로 분석되었다. 이 연구는 종속변수의 평균적 궤적을 분석대상으로 하였다는 점에 한계가 있으나 그럼에도 불구하고 성폭력범죄 전자감독대상자의 준수사항 위반행동에 영향을 미치는 요인을 종단적 시각에서 검증하고자 하였다는 점, 전자장치부착기간동안 변하는 시간 가변적 변수를 주요 변수로 활용하였다는 점에 그 의의가 있다.

A total of 100 commercially available olive oil products were analyzed for 179 pesticide residues using gas chromatography-tandem mass spectrometry (GC/MS/MS). The olive oil samples were mixed with organic solvents, centrifuged and frozen to remove fat, and pesticide residues were analyzed using the “quick, easy, cheap, effective, rugged, and safe” (QuEChERS) method. The determination coefficient (R2) of the analysis method used in this study was ≥0.998. The detection limit of the method ranged 0.004–0.006 mg/kg and its quantitative limit ranged 0.012–0.017 mg/kg. The recovery rate (n=5) measured at the level ranging 0.01–0.02, 0.1, and 0.5 mg/kg ranged 66.8– 119.5%. The relative standard deviation (RSD) was determined to be ≤5.7%, confirming that this method was suitable for the "Guidelines for Standard Procedures for Preparing Food Test Methods". The results showed that a total of 151 pesticides (including difenoconazole, deltamethrin, oxyfluorfen, kresoxim-methyl, phosmet, pyrimethanil, tebuconazole, and trifloxystrobin) were detected in 64 of the 100 olive oil products. The detection range of these pesticide residues was 0.01–0.30 mg/kg. The percentage acceptable daily intake (%ADI) of the pesticides calculated using ADI and estimated daily intake (EDI) was 0.0001–0.1346, indicating that the detected pesticides were present at safe levels. This study provides basic data for securing the safety of olive oil products by monitoring pesticide residues in commercially available oilve oil products. Collectively, the analysis method used in this study can be used as a method to analyze residual pesticides in edible oils.

We present the analysis results of the simultaneous multifrequency observations of the blazar 4C +28.07. The observations were conducted by the Interferometric Monitoring of Gamma-ray Bright Active Galactic Nuclei (iMOGABA) program, which is a key science program of the Korean Very Long Baseline Interferometry (VLBI) Network (KVN). Observations of the iMOGABA program for 4C +28.07 were conducted from 16 January 2013 (MJD 56308) to 13 March 2020 (MJD 58921). We also used γ-ray data from the Fermi Large Array Telescope (Fermi-LAT) Light Curve Repository, covering the energy range from 100 MeV to 100 GeV. We divided the iMOGABA data and the Fermi-LAT data into five periods from 0 to 4, according to the prosody of the 22 GHz data and the presence or absence of the data. In order to investigate the characteristics of each period, the light curves were plotted and compared. However, a peak that formed a hill was observed earlier than the period of a strong γ-ray flare at 43–86 GHz in period 3 (MJD 57400–58100). Therefore, we assumed that the minimum total CLEANed flux density for each frequency was quiescent flux (Sq) in which the core of 4C +28.07 emitted the minimum, with the variable flux (Svar) obtained by subtracting Sq from the values of the total CLEANed flux density. We then compared the variability of the spectral indices (α) between adjacent frequencies through a spectral analysis. Most notably, α22–43 showed optically thick spectra in the absence of a strong γ-ray flare, and when the flare appeared, α22–43 became optically thinner. In order to find out the characteristics of the magnetic field in the variable region, the magnetic field strength in the synchrotron self-absorption (BSSA) and the equipartition magnetic field strength (Beq) were obtained. We found that BSSA is largely consistent with Beq within the uncertainty, implying that the SSA region in the source is not significantly deviated from the equipartition condition in the γ-ray quiescent periods.

Electric doors have been applied in urban trains since 2007 and operated for a long time. Recently, the failure of mechanical devices in electric doors have been increasing. The door is a device that is directly related to the safety of passengers. The rivet breakage of a ball/nut assembly may occur to an accident during train operation. In this study, the operating voltage and acceleration data of the door were collected for rivet condition monitoring, and 4 features were extracted in the frequency domain using the acceleration data. The classification performance of the rivet condition according to the axial direction of the acceleration data and 4 kernel functions was evaluated using SVM algorithm. When the X-axis data and Gaussian kernel function were used, the highest classification performance was shown for the electric door’s rivet with 90% accuracy.

Governments around the world are enacting laws mandating explainable traceability when using AI(Artificial Intelligence) to solve real-world problems. HAI(Human-Centric Artificial Intelligence) is an approach that induces human decision-making through Human-AI collaboration. This research presents a case study that implements the Human-AI collaboration to achieve explainable traceability in governmental data analysis. The Human-AI collaboration explored in this study performs AI inferences for generating labels, followed by AI interpretation to make results more explainable and traceable. The study utilized an example dataset from the Ministry of Oceans and Fisheries to reproduce the Human-AI collaboration process used in actual policy-making, in which the Ministry of Science and ICT utilized R&D PIE(R&D Platform for Investment and Evaluation) to build a government investment portfolio.

박새는 도시생태계 내 환경변화를 측정할 수 있는 생물지표종이자 대표적인 식충성 조류로 건전성 유지와 같은 중요한 역할을 맡고 있다. 연구자들은 박새과 조류의 번식생태 파악을 위해 인공새집 조사방법을 활용하고 있으나, 공간적･시간적 한계로 거시적 관점의 연구를 진행하기에는 어려움이 있다. 본 연구는 전문가 중심으로 수행된 기존 인공새집 모니터링이 갖는 한계를 벗어나고자 시민참여 인공새집 모니터링 프로젝트를 설계하였다. ‘수원시 앞마당 조류 모니터링단’은 시민조사원 들의 자발적인 참여를 통해 경기도 수원시 내 녹지공간에 인공새집을 설치하고 박새과 조류의 번식생태를 관찰하는 프로젝트이 다. 2021년 2월 9일부터 2월 22일까지 온라인 설문조사를 통해 참가자를 모집하였고, 시민조사원은 2021년 2월 23일부터 8월 31일까지 인공새집 설치부터 관찰까지 직접 수행하였다. 비전문가인 시민조사원들의 진입장벽을 낮추고 일관된 데이터를 수집하기 위해 모니터링 과정 전반에 대한 온라인 교육을 수행하였고 모바일 애플리케이션을 이용하여 인공새집 관찰기록을 수집하였다. 시민참여 인공새집 모니터링 프로젝트에는 98명의 시민조사원이 참여하였고 배포된 206개의 인공새집 중 175(84.95%)개가 수원시 내 녹지공간에 설치되었다. 설치된 인공새집 중 위치 좌표 생성 오류가 발생한 2건을 제외한 173(83.98%)개를 대상으로 시민과학 프로젝트 결과를 확인했다. 시민조사원으로부터 수집한 인공새집 관찰기록은 총 987회 이며, 최솟값은 1회, 최댓값은 26회, 평균은 5.71±4.37회로 나타났다. 월별 인공새집 관찰 횟수는 2월 70회(7.09%), 3월 444회(44.98%), 4월 284회(28.77%), 5월 133회(13.48%), 6월 46회(4.66%), 7월 6회(0.61%), 8월 4회(0.41%)로 조사되었 다. 설치된 173개의 인공새집 중 57개(32.95%)에서 조류의 이용을 관찰할 수 있었고 박새 12개소(21.05%), 곤줄박이 7개소 (12.28%), 미동정 조류 38개소(66.67%)로 확인되었다. 본 연구는 박새과 조류의 번식생태를 조사방법으로 활용되는 인공새집 모니터링에 시민의 참여 가능성을 처음으로 검토한 연구로 향후 시민과학을 접목한 생태모니터링 설계의 기초자료로 활용될 수 있을 것으로 판단된다.

견과류는 영양가가 우수하고 다양한 기능성 생리활성을 가져 건강한 식단에 중요한 요소이다. 멜라토닌은 뇌의 송 과선에서 분비되는 호르몬으로 각종 조직의 산화적 손상을 방지하는 것으로 알려져 있으며, 식물체에서도 중요한 역할 을 한다. 본 연구는 견과류의 멜라토닌 추출 및 정량을 위 한 분석법을 마련하였고, 견과류의 높은 지방함량을 고려한 최적화된 추출 절차를 이용하여 경기도에서 유통되는 견과 종실류 등의 멜라토닌 함량을 조사하였다. 땅콩 또는 견과 류, 유지종실류 및 두류의 평균 멜라토닌 함량은 각각 1200.83 (409.76-2223.56), 934.83 (454.10-1736.60), 616.46 (494.70- 825.12) pg/g으로 나타났다. 호두와 밤의 경우 속껍질을 포 함한 반탈각 상태와 과실만 있는 경우의 멜라토닌 함량을 비교한 결과, 반탈각 상태에서 멜라토닌 함량이 유의적으로 높았다. 또한 호두, 밤 및 땅콩의 경우 2022년 재배된 햇 견 과보다 2021년 재배 후 저장된 견과에서 멜라토닌 함량이 유의적으로 높았다. 이러한 결과는 견과종실류 등의 멜라토 닌 함량이 높아 우수한 기능성 식품임을 시사하였다.

원전 구조물의 실시간 모니터링 기술이 요구되고 있지만, 현재 운영 중인 지진 감시계통으로는 동특성 추출 등 시스템 식별이 제한 된다. 전역적인 거동 데이터 및 동특성 추출을 위해서는 다수의 센서를 최적 배치하여야 한다. 최적 센서배치 연구는 많이 진행되어 왔 지만 주로 토목, 기계 구조물이 대상이었으며 원전 구조물 대상으로 수행된 연구는 없었다. 원전 구조물은 미미한 신호대잡음비에도 강건한 신호를 획득하여야 하며, 모드 기여도가 저차 모드에 집중되어 있어 모드별 잡음 영향을 고려해야 하는 등 구조물 특성을 고려 해야 한다. 이에 본 연구에서는 잡음에 대한 강건도와 모드별 영향을 평가할 수 있는 최적 센서배치 방법론을 제시하였다. 활용한 지표 로서 auto MAC(Modal Assurance Criterion), cross MAC, 노드별 모드형상 분포를 분석하였으며, 잡음에 대한 강건도 평가의 적합성을 수치해석으로 검증하였다.

본 연구에서는 경기도 내 유통 중인 견과 종실류의 잔 류농약 실태를 조사하고자 온라인 또는 유통매장을 통해 131건을 수거하여 조사하였다. 총 14품목의 견과종실류 를 수거하였으며 339종의 잔류농약을 분석한 결과 131건 중 총 8건에서 검출되었으며 범위는 0.01 mg/kg-0.07 mg/ kg 수준으로 나타났다. 검출된 시료 8건 중 7건이 잔류 농약 기준을 초과하여 부적합으로 판정되었으며 부적합 7건 중 6건은 수입농산물에서 판정되었다. 중국산 호박씨 의 경우 PLS가 적용된 피라클로스트로빈이 5건 검출되 었으며 범위는 0.02 mg/kg-0.04 mg/kg 수준으로 나타났다. 인도산 참깨와 국내산 참깨에서도 펜디메탈린, 보스칼리 드, 비펜트린이 각각 0.04 mg/kg, 0.05 mg/kg, 0.06 mg/kg 으로 검출되어 부적합 수치를 보였다. 또한 검출된 8종 의 농약에서 EDI/ADI (%) 값이 0.002%-0.372%으로 낮 은 수준임을 확인하였다.

This study investigated the odor emission characteristics of fertilizer manufacturing facilities. The characteristics were evaluated by measuring the odor concentration at the outlet and site boundary of the complex fertilizer and organic fertilizer manufacturing facilities. The evaluation process utilized the air dilution sensory method and PTR-ToF-MS. The complex odor dilution factor ranged from 100 to 120 times at the outlet of the compound fertilizer manufacturing facility. Specifically, the concentrations of Ammonia and Aldehydes were relatively high as designated odor substances. For the organic fertilizer facility, the dilution factor for complex odors was measured up to a maximum of 3,000. And, designated odorants such as Ammonia and Hydrogen sulfide were measured at levels up to parts per million (ppm). The odor contribution assessment of the fertilizer manufacturing facilities showed that the complex fertilizer facility exhibited similar contributions from Aldehydes and Sulfur compounds. On the other hand, the organic fertilizer facility had the highest contribution of over 62% from Sulfur compounds. As odor substances are easily changed and diffused according to weather conditions, it is difficult to obtain representative data according to the measurement time. Therefore, if continuous monitoring of odorous substances is performed using equipment that can be measured in real time without pretreatment, it becomes feasible to identify odor emission sources and regional spatio-temporal distribution. This information would then serve as a basis for analyzing odorant contamination characteristics and establishing appropriate countermeasures.