• Korean Journal of Agricultural and Forest Meteorology
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• v.21 no.4
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• pp.327-336
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• 2019

Soybean is one of the most important crops of which the grains contain high protein content and has been consumed in various forms of food. Soybean plants are generally cultivated on the field and their yield and quality are strongly affected by climate change. Recently, the abnormal climate conditions, including heat wave and heavy rainfall, frequently occurs which would increase the risk of the farm management. The real-time assessment techniques for quality and growth of soybean would reduce the losses of the crop in terms of quantity and quality. The objective of this work was to develop a simple model to estimate the growth of soybean plant using a multispectral sensor mounted on a rotor-wing unmanned aerial vehicle(UAV). The soybean growth model was developed by using simple linear regression analysis with three phenotypic data (fresh weight, dry weight, leaf area index) and two types of vegetation indices (VIs). It was found that the accuracy and precision of LAI model using GNDVI (R²= 0.789, RMSE=0.73 ㎡/㎡, RE=34.91%) was greater than those of the model using NDVI (R²= 0.587, RMSE=1.01 ㎡/㎡, RE=48.98%). The accuracy and precision based on the simple ratio indices were better than those based on the normalized vegetation indices, such as RRVI (R²= 0.760, RMSE=0.78 ㎡/㎡, RE=37.26%) and GRVI (R²= 0.828, RMSE=0.66 ㎡/㎡, RE=31.59%). The outcome of this study could aid the production of soybeans with high and uniform quality when a variable rate fertilization system is introduced to cope with the adverse climate conditions.

• Journal of Environmental Impact Assessment
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• v.29 no.1
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• pp.26-36
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• 2020

This study aimed at investigating present research and knowledge-base on climate change adaptation in ecosystem sector and analyzed the current status of basic information on ecosystem that functions as evidence-base of climate change adaptation to deduce the suggestions for the future development for knowledge and information in biodiversity. In this perspective, a questionary survey titled as "the ecological knowledge-base and information needs for climate change adaptation" with the researchers who were engaged with adaptation studies for biodiversity in the ecosystem related-research institutes including national and 17 regional local governments-affiliated agencies in Korea. The results are as follows; current status of utilizing ecological information which supports climate change adaptation strategy, future needs for adaptation knowledge and ecological information, and activation of utilizing ecological information. The majority of respondents (90.7%) replied that the ecological information has high relevance when conducting research on climate change adaptation. However, only half of all respondents (53.2%) agreed with the real viability of current information to the adaptation research. Particularly, urgent priority for researchers was deduced as intensifying knowledge-base and constructing related information on 'ecosystem change from climate change (productivity, community structure, food chain, phenology, range distribution, and number of individuals) with the overall improvement of information contents and its quality. The respondents emphasized with the necessity of conducting field surveys of local ecosystem and constructing ecosystem inventories, advancing monitoring designs for climate change in ecosystem, and case studies for regional ecosystem changes with the guidance or guidelines for monitoring ecosystem change to enhance the quality of adaptation research and produce related information. In terms of activation for ecological information usage, national and local adaptation network should be working based on the integrated ecological platform necessary to support exchanges of knowledge and information and to expand ecosystem types in time and spatial dimension.

• Science of Emotion and Sensibility
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• v.22 no.4
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• pp.97-106
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• 2019

The purpose of this study was to investigate the effect of the type and measurement location of a fabric strain gauge sensor on the detection performance for respiratory signals. We implemented two types of sensors to measure the respiratory signal and attached them to a band to detect the respiratory signal. Eight healthy males in their 20s were the subject of this study. They were asked to wear two respiratory bands in turns. While the subjects were measured for 30 seconds standing comfortably, the respiratory was given at 15 breaths per minute were synchronized, and then a 10-second break; subsequently, the entire measurement was repeated. Measurement locations were at the chest and abdomen. In addition, to verify the performance of respiratory measurement in the movement state, the subjects were asked to walk in place at a speed of 80 strides per minute(SPM), and the respiratory was measured using the same method mentioned earlier. Meanwhile, to acquire a reference signal, the SS5LB of BIOPAC Systems, Inc., was worn by the subjects simultaneously with the experimental sensor. The Kruskal-Wallis test and Bonferroni post hoc tests were performed using SPSS 24.0 to verify the difference in measurement performances among the group of eight combinations of sensor types, measurement locations, and movement states. In addition, the Wilcoxon test was conducted to examine whether there are differences according to sensor type, measurement location, and movement state. The results showed that the respiratory signal detection performance was the best when the respiratory was measured in the chest using the CNT-coated fabric sensor regardless of the movement state. Based on the results of this study, we will develop a chest belt-type wearable platform that can monitor the various vital signal in real time without disturbing the movements in an outdoor environment or in daily activities.

• Journal of Internet Computing and Services
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• v.16 no.2
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• pp.49-55
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• 2015

According to the statistics of traffic accidents over recent 5 years, traffic accidents during the night times happened more than the day times. There are various causes to occur traffic accidents and the one of the major causes is inappropriate or missing street lights that make driver's sight confused and causes the traffic accidents. In this paper, with smartphones, we designed and implemented a lane luminance measurement application which stores the information of driver's location, driving, and lane luminance into database in real time to figure out the inappropriate street light facilities and the area that does not have any street lights. This application is implemented under Native C/C++ environment using android NDK and it improves the operation speed than code written in Java or other languages. To measure the luminance of road, the input image with RGB color space is converted to image with YCbCr color space and Y value returns the luminance of road. The application detects the road lane and calculates the road lane luminance into the database sever. Also this application receives the road video image using smart phone's camera and improves the computational cost by allocating the ROI(Region of interest) of input images. The ROI of image is converted to Grayscale image and then applied the canny edge detector to extract the outline of lanes. After that, we applied hough line transform method to achieve the candidated lane group. The both sides of lane is selected by lane detection algorithm that utilizes the gradient of candidated lanes. When the both lanes of road are detected, we set up a triangle area with a height 20 pixels down from intersection of lanes and the luminance of road is estimated from this triangle area. Y value is calculated from the extracted each R, G, B value of pixels in the triangle. The average Y value of pixels is ranged between from 0 to 100 value to inform a luminance of road and each pixel values are represented with color between black and green. We store car location using smartphone's GPS sensor into the database server after analyzing the road lane video image with luminance of road about 60 meters ahead by wireless communication every 10 minutes. We expect that those collected road luminance information can warn drivers about safe driving or effectively improve the renovation plans of road luminance management.

• Journal of Internet Computing and Services
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• v.21 no.5
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• pp.139-148
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• 2020

Infectious diseases have long plagued mankind, and predicting and preventing them has been a big challenge for mankind. For this reasen, various studies have been conducted so far to predict infectious diseases. Most of the early studies relied on epidemiological data from the Centers for Disease Control and Prevention (CDC), and the problem was that the data provided by the CDC was updated only once a week, making it difficult to predict the number of real-time disease outbreaks. However, with the emergence of various Internet media due to the recent development of IT technology, studies have been conducted to predict the occurrence of infectious diseases through web data, and most of the studies we have researched have been using single Web data to predict diseases. However, disease forecasting through a single Web data has the disadvantage of having difficulty collecting large amounts of learning data and making accurate predictions through models for recent outbreaks such as "COVID-19". Thus, we would like to demonstrate through experiments that models that use multiple Web data to predict the occurrence of infectious diseases through LSTM models are more accurate than those that use single Web data and suggest models suitable for predicting infectious diseases. In this experiment, we predicted the occurrence of "Malaria" and "Epidemic-parotitis" using a single web data model and the model we propose. A total of 104 weeks of NEWS, SNS, and search query data were collected, of which 75 weeks were used as learning data and 29 weeks were used as verification data. In the experiment we predicted verification data using our proposed model and single web data, Pearson correlation coefficient for the predicted results of our proposed model showed the highest similarity at 0.94, 0.86, and RMSE was also the lowest at 0.19, 0.07.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.39 no.4
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• pp.347-357
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• 2003

This paper describes on the suppression of sea clutter on marine radar display using a cell-averaging CFAR(constant false alarm rate) technique, and on the analysis of radar echo signal data in relation to the estimation of ARPA functions and the detection of the shadow effect in clutter returns. The echo signal was measured using a X -band radar, that is located on the Pukyong National University, with a horizontal beamwidth of $$3.9^{\circ}$$, a vertical beamwidth of $20^{\circ}$, pulsewidth of $0.8 {\mu}s$ and a transmitted peak power of 4 ㎾ The suppression performance of sea clutter was investigated for the probability of false alarm between $l0-^0.25;and; 10^-1.0$. Also the performance of cell averaging CFAR was compared with that of ideal fixed threshold. The motion vectors and trajectory of ships was extracted and the shadow effect in clutter returns was analyzed. The results obtained are summarized as follows；1. The ARPA plotting results and motion vectors for acquired targets extracted by analyzing the echo signal data were displayed on the PC based radar system and the continuous trajectory of ships was tracked in real time. 2. To suppress the sea clutter under noisy environment, a cell averaging CFAR processor having total CFAR window of 47 samples(20+20 reference cells, 3+3 guard cells and the cell under test) was designed. On a particular data set acquired at Suyong Man, Busan, Korea, when the probability of false alarm applied to the designed cell averaging CFAR processor was 10$^{-0}$.75/ the suppression performance of radar clutter was significantly improved. The results obtained suggest that the designed cell averaging CFAR processor was very effective in uniform clutter environments. 3. It is concluded that the cell averaging CF AR may be able to give a considerable improvement in suppression performance of uniform sea clutter compared to the ideal fixed threshold. 4. The effective height of target, that was estimated by analyzing the shadow effect in clutter returns for a number of range bins behind the target as seen from the radar antenna, was approximately 1.2 m and the information for this height can be used to extract the shape parameter of tracked target..

• The Korean Journal of Food And Nutrition
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• v.11 no.2
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• pp.185-191
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• 1998

This study was performed to investigate the nutrition status by weight loss(diet) of 287 female college students, focus on questionnaire about diet survey. The subjects mainly had irregularly one or two meal per a day so food behavior was not good. Over half of subjects had a tendency to overestimate body shape of self. The desired weight(46.95$\pm$0.39kg) was significant lower than real weight(50.32$\pm$0.9)(p=0.0114). The time when diet is first tried was mainly after high school(94.51%). Mean weight loss was 1~4kg but most of subjects didn't maintain the lost weight. The diet approach method tried was sequently the fasting 1 meal or the more in a day(23.61%), exercise(21.92%), restricting calories(15.85%) etc. The source of diet was orderly newspaper or magazine(30.86%), friends or relatives or family(28.86%) etc. The group who recognized the self body shape was normal or a little fat had higher self notion of health than other groups.

• Korean Journal of Agricultural and Forest Meteorology
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• v.17 no.1
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• pp.25-34
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• 2015

In this research, we applied a procedure of quality control (QC) to the agro-meteorological data measured at the Suwon weather station of Korea Meteorological Administration (KMA). The QC was conducted through six steps based on the KMA Real-time Quality control system for Meteorological Observation Data (RQMOD) and four steps based on the International Soil Moisture Network (ISMN) QC modules. In addition, we set up our own empirical method to remove erroneous data which could not be filtered by the RQMOD and ISMN methods. After all these QC procedures, a well-refined agro-meteorological dataset was complied at both air and soil temperatures. Our research suggests that soil moisture requires more detailed and reliable grounds to remove doubtful data, especially in winter with its abnormal variations. The raw data and the data after QC are now available at the NCAM website (http://ncam.kr/page/req/agri_weather.php).

• Journal of Life Science
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• v.23 no.1
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• pp.116-124
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• 2013

The aim was to examine resistance exercise-related genes after 8 weeks of resistance training. Thirty-two male Sprague-Dawley rats were divided into four groups: 4 weeks sedentary (4 wks CON, n=8), 8 weeks sedentary (8 wks CON, n=8), 4 weeks exercise training (4 wks REG, n=8), and 8 weeks exercise training (8 wks REG, n=8). The rats were trained to climb a 1-m vertical incline (85-degree), with weights secured to their tails. They climbed 10 times, 3 days per week, for 8 consecutive weeks. Skeletal muscle was taken from the flexor halucis longus after the exercise training. After separating the total RNA, large-scale gene expression was investigated by beadarray (Illumina RatRef-12 Expression BeadChip) analysis, and qPCR was used to inspect the beadarray data and to analyze the RNA quantitatively. The detection p-value for the genes was p<0.01, the M-value {M=$log_2$(condition)-$log_2$(reference)} was >1.0, and the DiffScore was >20. In total, the expression of 30 genes significantly increased 4 weeks after the exercise training, and the expression of six genes decreased. At 8 weeks, the expression of five genes significantly increased and that of 12 decreased. Several genes are potentially involved in resistance exercise and muscle hypertrophy, including 1) regulation of cell growth (IGFBP1, PLA2G2A, OKL38); 2) myogenesis (CSRP3); 3) tissue regeneration and muscle development (MUSTN1, MYBPH); 4) hypertrophy (CYR61, ATF3, NR4A3); and 5) glucose metabolism (G6PC, PCK1). These results may help to explain previously reported physiological changes of the skeletal muscle and suggest new avenues for further investigation.

• Journal of Life Science
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• v.28 no.5
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• pp.524-531
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• 2018

The essential oil from Abies koreana E.H. Wilson had been developed, however, its efficacy has not yet been studied especially in terms of skin care research. The aim of this study is to investigate the effects of Abies koreana extracts (AKE) on melanogenesis and wrinkle formation in B16F10 melanoma cells (B16F10) and human dermal fibroblast cell line (HDF). The essential oil was extracted by hydrodistillation method and purified by anhydrous sodium sulfate. At a concentration of $10^{-5}$-fold, viability in these cells had been defined by cytotoxicity assays. Anti-melanogenic effects on B16F10 were evaluated using tyrosinase inhibition assay, and real-time PCR for verifying gene expression of tyrosinase, tyrosinase related protein-1 and -2 (TRP-1 and -2). AKEs reduced about 5-fold of tyrosinase inhibitory activity compared to ${\alpha}$-melanocyte-stimulating hormone (${\alpha}$-MSH)-induced group and about 30% reduction compared to Arbutin induced group. The mRNA levels of three melanin-related factors were increased, separately. To investigate the effects of anti-wrinkle, procollagen type I c peptide synthesis assay (PIP) and Western blot were performed. At AKE-treated group, PIP was up-regulated and the expression of collagen type 1 and matrix metalloproteinase (MMP)-1 were improved. Furthermore, AKE presented anti-wrinkle effects by increasing UVB-inhibited collagen type 1 expression, and reducing UVB-induced MMP-1 production at $60mJ/cm^2$ of UVB radiation. Therefore, Abies koreana extracts has potentials as a safe and an effective skin ingredient for whitening and anti-wrinkle.