• Title/Summary/Keyword: 센서 특성

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An Efficient Algorithm for Streaming Time-Series Matching that Supports Normalization Transform (정규화 변환을 지원하는 스트리밍 시계열 매칭 알고리즘)

  • Loh, Woong-Kee;Moon, Yang-Sae;Kim, Young-Kuk
    • Journal of KIISE:Databases
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    • v.33 no.6
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    • pp.600-619
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    • 2006
  • According to recent technical advances on sensors and mobile devices, processing of data streams generated by the devices is becoming an important research issue. The data stream of real values obtained at continuous time points is called streaming time-series. Due to the unique features of streaming time-series that are different from those of traditional time-series, similarity matching problem on the streaming time-series should be solved in a new way. In this paper, we propose an efficient algorithm for streaming time- series matching problem that supports normalization transform. While the existing algorithms compare streaming time-series without any transform, the algorithm proposed in the paper compares them after they are normalization-transformed. The normalization transform is useful for finding time-series that have similar fluctuation trends even though they consist of distant element values. The major contributions of this paper are as follows. (1) By using a theorem presented in the context of subsequence matching that supports normalization transform[4], we propose a simple algorithm for solving the problem. (2) For improving search performance, we extend the simple algorithm to use $k\;({\geq}\;1)$ indexes. (3) For a given k, for achieving optimal search performance of the extended algorithm, we present an approximation method for choosing k window sizes to construct k indexes. (4) Based on the notion of continuity[8] on streaming time-series, we further extend our algorithm so that it can simultaneously obtain the search results for $m\;({\geq}\;1)$ time points from present $t_0$ to a time point $(t_0+m-1)$ in the near future by retrieving the index only once. (5) Through a series of experiments, we compare search performances of the algorithms proposed in this paper, and show their performance trends according to k and m values. To the best of our knowledge, since there has been no algorithm that solves the same problem presented in this paper, we compare search performances of our algorithms with the sequential scan algorithm. The experiment result showed that our algorithms outperformed the sequential scan algorithm by up to 13.2 times. The performances of our algorithms should be more improved, as k is increased.

Growth Responses of Potted Gerbera 'Sunny Lemon' under Non-Nutrient Solution Recycling System by Media and Nutrient Contents (비순환식 분화 양액재배시 배지와 양액함량에 따른 거베라 'Sunny Lemon'의 생육반응)

  • Kil, Mi-Jung;Shim, Myung-Sun;Park, Sang-Kun;Shin, Hak-Gi;Jung, Jae-A;Kwon, Young-Soon
    • Journal of agriculture & life science
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    • v.45 no.6
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    • pp.73-80
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    • 2011
  • To investigate the characteristics of plant growth and flower quality of gerbera 'Sunny Lemon' by amount of nutrient solution, young seedling plants, 'Sunny Lemon' were transplanted to rock-wool and medium of peat moss and perlite mixed with 1 to 2 and they were acclimatized in greenhouse during about 1 month. Nutrient solution supplied to the plants is sonneveld solution of 1/2 concentration and treatments launched June 24, 2010 when average plant height was $20{\pm}1cm$. Nutrient contents as a standard for starting point of irrigation by time domain reflectometry (TDR) were determined with 60-65%, 70-75%, and 80-85%. Results of growth during vegetative growth, plant height, leaf width and leaf number increased by 10% in rockwool, but they were not significantly different. As for plant growth depending on nutrient content, 80-85% treatment showed the highest values. Leaf number increased by 60%, and leaf width and plant height had a about 40% increase than initial growth. Effectiveness for flower quality, yield and days to flowering were superior when nutrient content of media was higher than in the others. Especially, average days to flowering in 80-85% content was advanced by 7-10 days compared to the day in 60-65% treatment. The total amount of nutrient supply per plant was higher in mixed medium than in rockwool, but change patterns of EC and pH were enhanced in rockwool. Based on our results, we recommended that growth, cut flower, and yield of gerbera 'Sunny Lemon' were more effective when nutrient content of mixed medium was maintained at 80-85%.

Oceanic Application of Satellite Synthetic Aperture Radar - Focused on Sea Surface Wind Retrieval - (인공위성 합성개구레이더 영상 자료의 해양 활용 - 해상풍 산출을 중심으로 -)

  • Jang, Jae-Cheol;Park, Kyung-Ae
    • Journal of the Korean earth science society
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    • v.40 no.5
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    • pp.447-463
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    • 2019
  • Sea surface wind is a fundamental element for understanding the oceanic phenomena and for analyzing changes of the Earth environment caused by global warming. Global research institutes have developed and operated scatterometers to accurately and continuously observe the sea surface wind, with the accuracy of approximately ${\pm}20^{\circ}$ for wind direction and ${\pm}2m\;s^{-1}$ for wind speed. Given that the spatial resolution of the scatterometer is 12.5-25.0 km, the applicability of the data to the coastal area is limited due to complicated coastal lines and many islands around the Korean Peninsula. In contrast, Synthetic Aperture Radar (SAR), one of microwave sensors, is an all-weather instrument, which enables us to retrieve sea surface wind with high resolution (<1 km) and compensate the sparse resolution of the scatterometer. In this study, we investigated the Geophysical Model Functions (GMF), which are the algorithms for retrieval of sea surface wind speed from the SAR data depending on each band such as C-, L-, or X-band radar. We reviewed in the simulation of the backscattering coefficients for relative wind direction, incidence angle, and wind speed by applying LMOD, CMOD, and XMOD model functions, and analyzed the characteristics of each GMF. We investigated previous studies about the validation of wind speed from the SAR data using these GMFs. The accuracy of sea surface wind from SAR data changed with respect to observation mode, GMF type, reference data for validation, preprocessing method, and the method for calculation of relative wind direction. It is expected that this study contributes to the potential users of SAR images who retrieve wind speeds from SAR data at the coastal region around the Korean Peninsula.

Comparison of Wind Vectors Derived from GK2A with Aeolus/ALADIN (위성기반 GK2A의 대기운동벡터와 Aeolus/ALADIN 바람 비교)

  • Shin, Hyemin;Ahn, Myoung-Hwan;KIM, Jisoo;Lee, Sihye;Lee, Byung-Il
    • Korean Journal of Remote Sensing
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    • v.37 no.6_1
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    • pp.1631-1645
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    • 2021
  • This research aims to provide the characteristics of the world's first active lidar sensor Atmospheric Laser Doppler Instrument (ALADIN) wind data and Geostationary Korea Multi Purpose Satellite 2A (GK2A) Atmospheric Motion Vector (AMV) data by comparing two wind data. As a result of comparing the data from September 2019 to August 1, 2020, The total number of collocated data for the AMV (using IR channel) and Mie channel ALADIN data is 177,681 which gives the Root Mean Square Error (RMSE) of 3.73 m/s and the correlation coefficient is 0.98. For a more detailed analysis, Comparison result considering altitude and latitude, the Normalized Root Mean Squared Error (NRMSE) is 0.2-0.3 at most latitude bands. However, the upper and middle layers in the lower latitudes and the lower layer in the southern hemispheric are larger than 0.4 at specific latitudes. These results are the same for the water vapor channel and the visible channel regardless of the season, and the channel-specific and seasonal characteristics do not appear prominently. Furthermore, as a result of analyzing the distribution of clouds in the latitude band with a large difference between the two wind data, Cirrus or cumulus clouds, which can lower the accuracy of height assignment of AMV, are distributed more than at other latitude bands. Accordingly, it is suggested that ALADIN wind data in the southern hemisphere and low latitude band, where the error of the AMV is large, can have a positive effect on the numerical forecast model.

Analysis of growth environment by smart farm cultivation of oyster mushroom 'Chunchu No 2' (병재배 느타리버섯 '춘추 2호'의 스마트팜 재배를 통한 생육환경 분석)

  • Lee, Chan-Jung;Park, Hye-Sung;Lee, Eun-Ji;Kong, Won-Sik;Yu, Byeong-Kee
    • Journal of Mushroom
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    • v.17 no.3
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    • pp.119-125
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    • 2019
  • This study aims to report the results for the analysis of the growth environment by applying smart farm technology to "Chunchu No 2" farmers in order to develop an optimal growth model for precision cultivation of bottle-grown oyster mushrooms. The temperature, humidity, carbon dioxide concentration, and illumination data were collected and analyzed using an environmental sensor installed to obtain growth environment data from the oyster mushroom cultivator. Analysis of the collected temperature data revealed that the temperature at the time of granulation was $19.5^{\circ}C$ after scraping, and the mushroom was generated and maintained at about $21^{\circ}C$ until the bottle was flipped. When the fruiting body grew and approached harvest time, mushrooms were harvested while maintaining the temperature between $14^{\circ}C$ and $18^{\circ}C$. The humidity was maintained at almost 100% during the complete growth stage. Carbon dioxide concentration gradually increased until 3 days after the beginning of cultivation, and then increased rapidly to almost 5,500 ppm. From the 6th day, carbon dioxide concentration was gradually decreased through ventilation and was maintained at 1,600 ppm during harvest. Light intensity of 8 lux was irradiated up to day 6 after seeding, and growth was then continued while periodically irradiating 4 lux light. The fruiting body characteristics of "Chunchu No 2" cultivated in the farmhouse were as follows: pileus diameter of 26.5 mm and thickness of 4.9 mm, stipe thickness of 8.9 mm, and length of 68.7 mm. The fruiting body yield was 166.8 g/850 ml, and the individual weight was 12.8 g/10 units.

Evaluation of Composting Characteristics According to the Air Supply Change in Farm-Sized Swine Manure (농가규모 양돈분뇨 퇴비화시 공기공급량 변화에 따른 퇴비 특성 평가)

  • Lee, Sunghyoun;Jeong, Gwanghwa;Lee, Dongjun;Lee, Donghyeon;Jang, Yuna;Kwag, Junghoon
    • Journal of the Korea Organic Resources Recycling Association
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    • v.27 no.3
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    • pp.49-61
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    • 2019
  • Swine manure has been recognized as a organic sources for composting and many research was conducted to efficiently utilize and treat. This study was to evaluate a feasibility for producing swine manure compost under various treatment with mixture of swine manure and saw dust. Treatments were designed as follows; non aerated composting pile(REF), aerated composting pile of $100L/m^3$(EXP1), and aerated composting pile of $150L/m^3$(EXP2). The total days of fermentation were 28 days and each samples were collected at every 7 days from starting of composting. Temperature sensors were installed under 30~40cm from the surface of composting pile. Inner temperature in composting piles of EXP1 and EXP2 was rapidly increased to $67{\sim}75^{\circ}C$ within 1~2 days. The elevated temperatures found during the thermophilic phase are essential for rapid degradation of organic materials. While swine manure composted, moisture content, total nitrogen, EC of EXP1, EXP2 in sample at 28 days were lower than those of REF. But, pH and organic matter of EXP1, EXP2 in sample at 28 days were higher than those of REF. After finishing fermentation experiment, maturity was evaluated with germination test. Calculated germination index(GI) at REF, EXP1 and EXP2 were 23.49, 68.50 and 51.81, respectively. The values of germination index were higher at EXP1 and EXP2 which is aerated composting piles than REF which is non aerated composting pile. According to the results, composting process by aerated static pile compost had significant effect on the reduction of required period for composting. Supplying adequate amount of air to compost swine manure will greatly reduce composting period.

Coarse Woody Debris (CWD) Respiration Rates of Larix kaempferi and Pinus rigida: Effects of Decay Class and Physicochemical Properties of CWD (일본잎갈나무와 리기다소나무 고사목의 호흡속도: 고사목의 부후등급과 이화학적 특성의 영향)

  • Lee, Minkyu;Kwon, Boram;Kim, Sung-geun;Yoon, Tae Kyung;Son, Yowhan;Yi, Myong Jong
    • Journal of Korean Society of Forest Science
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    • v.108 no.1
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    • pp.40-49
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    • 2019
  • Coarse woody debris (CWD), which is a component of the forest ecosystem, plays a major role in forest energy flow and nutrient cycling. In particular, CWD isolates carbon for a long time and is important in terms of slowing the rate of carbon released from the forest to the atmosphere. Therefore, this study measured the physiochemical characteristics and respiration rate ($R_{CWD}$) of CWD for Larix kaempferi and Pinus rigida in temperate forests in central Korea. In summer 2018, CWD samples from decay class (DC) I to IV were collected in the 14 forest stands. $R_{CWD}$ and physiochemical characteristics were measured using a closed chamber with a portable carbon dioxide sensor in the laboratory. In both species, as CWD decomposition progressed, the density ($D_{CWD}$) of the CWD decreased while the water content ($WC_{CWD}$) increased. Furthermore, the carbon concentrations did not significantly differ by DC, whereas the nitrogen concentration significantly increased and the C/N ratio decreased. The respiration rate of L. kaempferi CWD increased significantly up to DC IV, but for P. rigida it increased to DC II and then unchanged for DC II-IV. Accordingly, except for carbon concentration, all the measured characteristics showed a significant correlation with $R_{CWD}$. Multiple linear regression showed that $WC_{CWD}$ was the most influential factor on $R_{CWD}$. $WC_{CWD}$ affects $R_{CWD}$ by increasing microbial activity and is closely related to complex environmental factors such as temperature and light conditions. Therefore, it is necessary to study their correlation and estimate the time-series pattern of CWD moisture.

Retrieval of Oceanic Skin Sea Surface Temperature using Infrared Sea Surface Temperature Autonomous Radiometer (ISAR) Radiance Measurements (적외선 라디오미터 관측 자료를 활용한 해양 피층 수온 산출)

  • Kim, Hee-Young;Park, Kyung-Ae
    • Journal of the Korean earth science society
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    • v.41 no.6
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    • pp.617-629
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    • 2020
  • Sea surface temperature (SST), which plays an important role in climate change and global environmental change, can be divided into skin sea surface temperature (SSST) observed by satellite infrared sensors and the bulk temperature of sea water (BSST) measured by instruments. As sea surface temperature products distributed by many overseas institutions represent temperatures at different depths, it is essential to understand the relationship between the SSST and the BSST. In this study, we constructed an observation system of infrared radiometer onboard a marine research vessel for the first time in Korea to measure the SSST. The calibration coefficients were prepared by performing the calibration procedure of the radiometer device in the laboratory prior to the shipborne observation. A series of processes were applied to calculate the temperature of the layer of radiance emitted from the sea surface as well as that from the sky. The differences in skin-bulk temperatures were investigated quantitatively and the characteristics of the vertical structure of temperatures in the upper ocean were understood through comparison with Himawari-8 geostationary satellite SSTs. Comparison of the skin-bulk temperature differences illustrated overall differences of about 0.76℃ at Jangmok port in the southern coast and the offshore region of the eastern coast of the Korean Peninsula from 21 April to May 6, 2020. In addition, the root-mean-square error of the skin-bulk temperature differences showed daily variation from 0.6℃ to 0.9℃, with the largest difference of 0.83-0.89℃ at 1-3 KST during the daytime and the smallest difference of 0.59℃ at 15 KST. The bias also revealed clear diurnal variation at a range of 0.47-0.75℃. The difference between the observed skin sea surface temperature and the satellite sea surface temperature showed a mean square error of approximately 0.74℃ and a bias of 0.37℃. The analysis of this study confirmed the difference in the skin-bulk temperatures according to the observation depth. This suggests that further ocean shipborne infrared radiometer observations should be carried out continuously in the offshore regions to understand diurnal variation as well as seasonal variations of the skin-bulk SSTs and their relations to potential causes.

The Washing Effect of Precipitation on PM10 in the Atmosphere and Rainwater Quality Based on Rainfall Intensity (강우 강도에 따른 대기 중 미세먼지 저감효과와 강우수질 특성 연구)

  • Park, Hyemin;Byun, Myounghwa;Kim, Taeyong;Kim, Jae-Jin;Ryu, Jong-Sik;Yang, Minjune;Choi, Wonsik
    • Korean Journal of Remote Sensing
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    • v.36 no.6_3
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    • pp.1669-1679
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    • 2020
  • This study examines the washing effect of precipitation on particulate matter (PM) and the rainwater quality (pH, electrical conductivity (EC), water-soluble ions concentration). Of six rain events in total, rainwater samples were continuously collected every 50 mL from the beginning of the precipitation using rainwater collecting devices at Pukyong National University, Busan, South Korea, from March 2020 to July 2020. The collected rainwater samples were analyzed for pH, EC, and water-soluble ions (cations: Na+, Mg2+, K+, Ca2+, NH4+, and anions: Cl-, NO3-, SO42-). The concentrations of particulate matter were continuously measured during precipitation events with a custom-built PM sensor node. For initial rainwater samples, the average pH and EC were approximately 4.3 and 81.9 μS/cm, and the major ionic components consisted of NO3- (5.4 mg/L), Ca2+ (4.2 mg/L), Cl- (4.1 mg/L). In all rainfall events, rainwater pH gradually increased with rainfall duration, whereas EC gradually decreased due to the washing effect. When the rainfall intensities were relatively weak (<5 mm/h), PM10 reduction efficiencies were less than 40%. When the rainfall intensities were enhanced to more than 7.5 mm/h, the reduction efficiencies reached more than 60%. For heavy rainfall events, the acidity and EC, as well as ions concentrations of initial rainwater samples, were higher than those in later samples. This appears to be related to the washing effect of precipitation on PM10 in the atmosphere.

Evaluation of Sensitivity and Retrieval Possibility of Land Surface Temperature in the Mid-infrared Wavelength through Radiative Transfer Simulation (복사전달모의를 통한 중적외 파장역의 민감도 분석 및 지표면온도 산출 가능성 평가)

  • Choi, Youn-Young;Suh, Myoung-Seok;Cha, DongHwan;Seo, DooChun
    • Korean Journal of Remote Sensing
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    • v.38 no.6_1
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    • pp.1423-1444
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    • 2022
  • In this study, the sensitivity of the mid-infrared radiance to atmospheric and surface factors was analyzed using the radiative transfer model, MODerate resolution atmospheric TRANsmission (MODTRAN6)'s simulation data. The possibility of retrieving the land surface temperature (LST) using only the mid-infrared bands at night was evaluated. Based on the sensitivity results, the LST retrieval algorithm that reflects various factors for night was developed, and the level of the LST retrieval algorithm was evaluated using reference LST and observed LST. Sensitivity experiments were conducted on the atmospheric profiles, carbon dioxide, ozone, diurnal variation of LST, land surface emissivity (LSE), and satellite viewing zenith angle (VZA), which mainly affect satellite remote sensing. To evaluate the possibility of using split-window method, the mid-infrared wavelength was divided into two bands based on the transmissivity. Regardless of the band, the top of atmosphere (TOA) temperature is most affected by atmospheric profile, and is affected in order of LSE, diurnal variation of LST, and satellite VZA. In all experiments, band 1, which corresponds to the atmospheric window, has lower sensitivity, whereas band 2, which includes ozone and water vapor absorption, has higher sensitivity. The evaluation results for the LST retrieval algorithm using prescribed LST showed that the correlation coefficient (CC), the bias and the root mean squared error (RMSE) is 0.999, 0.023K and 0.437K, respectively. Also, the validation with 26 in-situ observation data in 2021 showed that the CC, bias and RMSE is 0.993, 1.875K and 2.079K, respectively. The results of this study suggest that the LST can be retrieved using different characteristics of the two bands of mid-infrared to the atmospheric and surface conditions at night. Therefore, it is necessary to retrieve the LST using satellite data equipped with sensors in the mid-infrared bands.