• Journal of Biosystems Engineering
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• v.41 no.3
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• pp.273-280
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• 2016

Purpose: This experiment was conducted to detect water stress in terms of the moisture content of cucumber seedlings under water stress condition using a hyperspectral image acquisition system, linear regression analysis, and partial least square regression (PLSR) to achieve a non-destructive measurement procedure. Methods: Changes in the reflectance spectrum of cucumber seedlings under water stress were measured using hyperspectral imaging techniques. A model for estimating moisture content of cucumber seedlings was constructed through a linear regression analysis that used the moisture content of cucumber seedlings and a normalized difference vegetation index (NDVI). A model using PLSR that used the moisture content of cucumber seedlings and reflectance spectrum was also created. Results: In the early stages of water stress, cucumber seedlings recovered completely when sub-irrigation was applied. However, the seedlings suffering from initial wilting did not recover when more than 42 h passed without irrigation. The reflectance spectrum of seedlings under water stress decreased gradually, but increased when irrigation was provided, except for the seedlings that had permanently wilted. From the results of the linear regression analysis using the NDVI, the model excluding wilted seedlings with less than 20% (n=97) moisture content showed a precision ($R^2$ and $R^2_{\alpha}$) of 0.573 and 0.568, respectively, and accuracy (RE) of 4.138% and 4.138%, which was higher than that for models including all seedlings (n=100). For PLS regression analysis using the reflectance spectrum, both models were found to have strong precision ($R^2$) with a rating of 0.822, but accuracy (RMSE and RE) was higher in the model excluding wilted seedlings as 5.544% and 13.65% respectively. Conclusions: The estimation model of the moisture content of cucumber seedlings showed better results in the PLSR analysis using reflectance spectrum than the linear regression analysis using NDVI.

• Journal of Korean Society of Forest Science
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• v.88 no.3
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• pp.389-399
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• 1999

This study was conducted to develop an application software, SIDAS3D(Stand Inventory Data Analysis System for 3 Dimensional Representation), of which the purpose of development is to make it easier to analyze and display the 3D spatial structure of a forest stand, based on the data such as tree position, species, DBH, height, clear length of individual trees, and crown width. This program has a statistical analysis function for stand attributes per hectare and displays simple graphs of stand statistics such as the distribution of diameters, heights, and volumes. It also has two additional functions, of which one is to display the 3D image of stand structure and the other is to display the image of crown projection. In addition, this program provides an imaginary treatment simulation function, which can visually confirm the suitability of silvicultural treatments on computers. To test the precision and reliability of SIDAS3D, data obtained by the precision forest inventory method were used. Statistical analysis ability of SIDAS3D was compared with that of SAS. And its representational ability was compared with that of TreeDraw. According to the verification, SIDAS3D was superior to SAS and TreeDraw in both the data processing time and the interpretative ability of results. It was concluded that SIDAS3D could be used to help users efficiently make decisions for appropriate silvicultural treatments and rational management plans because it has analysis functions providing various valuable information.

• Journal of IKEEE
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• v.24 no.1
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• pp.225-231
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• 2020

In this paper, we propose a method to accelerate BWN based on FPGA with limited resources for embedded system. Because of the limited number of logic elements available, a single computing unit capable of handling Conv-layer, FC-layer of various sizes must be designed and reused. Also, if the input feature map can not be parallel processed at one time, the output must be calculated by reading the inputs several times. Since the number of available BRAM modules is limited, the number of data bits in the BWN accelerator must be minimized. The image classification processing time of the BWN accelerator is superior when compared with a embedded CPU and is faster than a desktop PC and 50% slower than a GPU system. Since the BWN accelerator uses a slow clock of 50MHz, it can be seen that the BWN accelerator is advantageous in performance versus power.

• Journal of Auto-vehicle Safety Association
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• v.11 no.2
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• pp.35-43
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• 2019

This paper describes the improved environment recognition algorithms using some type of sensors like LiDAR and cameras. Additionally, integrated control algorithm for an autonomous vehicle is included. The integrated algorithm was based on C++ environment and supported the stability of the whole driving control algorithms. As to the improved vision algorithms, lane tracing and traffic sign recognition were mainly operated with three cameras. There are two algorithms developed for lane tracing, Improved Lane Tracing (ILT) and Histogram Extension (HIX). Two independent algorithms were combined into one algorithm - Enhanced Lane Tracing with Histogram Extension (ELIX). As for the enhanced traffic sign recognition algorithm, integrated Mutual Validation Procedure (MVP) by using three algorithms - Cascade, Reinforced DSIFT SVM and YOLO was developed. Comparing to the results for those, it is convincing that the precision of traffic sign recognition is substantially increased. With the LiDAR sensor, static and dynamic obstacle detection and obstacle avoidance algorithms were focused. Therefore, improved environment recognition algorithms, which are higher accuracy and faster processing speed than ones of the previous algorithms, were proposed. Moreover, by optimizing with integrated control algorithm, the memory issue of irregular system shutdown was prevented. Therefore, the maneuvering stability of the autonomous vehicle in severe environment were enhanced.

• The Journal of the Acoustical Society of Korea
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• v.36 no.1
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• pp.30-38
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• 2017

In this paper, we propose an underwater acoustic sensor fault detection method for passive sonar systems. In general, a passive sonar system displays processed results of array signals obtained from tens of the acoustic sensors as a two-dimensional image such as displays for broadband or narrowband analysis. Since detection result display in the operation software is to display the accumulated result through the array signal processing, it is difficult to determine the possibility where signal may be contaminated by the fault or failure of a single channel sensor. In this paper, accordingly, we propose a detection method based on the analysis of RMSCR (Root Mean Square Crossing-Rate), and the processing techniques for the faulty sensors are analyzed. In order to evaluate the performance of the proposed method, the precision of detecting fault sensors is measured by using signals acquired from real array being operated in several coastal areas. Besides, we compare performance of fault processing techniques. From the experiments, it is shown that the proposed method works well in underwater environments with high average RMS, and mute (set to zero) shows the best performance with regard to fault processing techniques.

• Korean Journal of Optics and Photonics
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• v.4 no.1
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• pp.15-21
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• 1993

This paper describes the design and development of a KrF excimer laser stepper and discusses the detailed system parameters and characterization data obtained from the performance test. We have developed a deep UV step-and-repeat system, operating at 248 nm, by retrofitting a commercial modules such as KrF excimer laser, precision wafer stage and fused silica illumination and 5X projection optics of numerical aperture 0.42. What we have developed, to the basic structure, are wafer alignment optics, reticle alignment system, autofocusing/leveling mechanisms and environment chamber. Finally, all these subsystem were integrated under the control of microprocessor-based controllers and computer. The wafer alignment system comprises the OFF-AXIS and the TTL alignment. The OFF-AXIS alignment system was realized with two kinds of optics. One is the magnification system with the image processing technique and the other is He-Ne laser diffraction type system using the alignment grating on the wafer. 'The TTL alignment system employs a dual beam inteferometric method, which takes advantages of higher diffraction efficiency compared with other TTL type alignment systems. As the results, alignment accuracy for OFF-AXIS and TTL alignment system were obtained within 0.1 $\mu\textrm{m}$/ 3 $\sigma$ for the various substrate on the wafers. The wafer focusing and leveling system is modified version of the conventional systems using position sensitive detectors (PSD). This type of detection method showed focusing and leveling accuracies of about $\pm$ 0.1 $\mu\textrm{m}$ and $\pm$ 0.5 arcsec, respectively. From the CD measurement, we obtained 0.4 $\mu\textrm{m}$ resolution features over the full field with routine use, and 0.3 $\mu\textrm{m}$ resolution was attainable under more strict conditions.

• Proceedings of the KSRS Conference
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• 2002.10a
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• pp.739-744
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• 2002

Recently we have discovered that sediments should be separated from lithosphere, and soil should be separated from biosphere, both sediment and soil will be mixed sediments-soil-sphere (Seso-sphere), which is using particulate mechanics to be solved. Erosion and sediment both are moving by particulate matter with water or wind. But ancient sediments will be erosion same to soil. Nowadays, real soil has already reduced much more. Many places have only remained sediments that have ploughed artificial farming layer. Thus it means sediments-soil-sphere. This paper discusses sediments-soil-sphere erosion modeling. In fact sediments-soil-sphere erosion is including water erosion, wind erosion, melt-water erosion, gravitational water erosion, and mixed erosion. We have established geographical remote sensing information modeling (RSIM) for different erosion that was using remote sensing digital images with geographical ground truth water stations and meteorological observatories data by remote sensing digital images processing and geographical information system (GIS). All of those RSIM will be a geographical multidimensional gray non-linear equation using mathematics equation (non-dimension analysis) and mathematics statistics. The mixed erosion equation is more complex that is a geographical polynomial gray non-linear equation that must use time-space fuzzy condition equations to be solved. RSIM is digital image modeling that has separated physical factors and geographical parameters. There are a lot of geographical analogous criterions that are non-dimensional factor groups. The geographical RSIM could be automatic to change them analogous criterions to be fixed difference scale maps. For example, if smaller scale maps (1:1000 000) that then will be one or two analogous criterions and if larger scale map (1:10 000) that then will be four or five analogous criterions. And the geographical parameters that are including coefficient and indexes will change too with images. The geographical RSIM has higher precision more than mathematics modeling even mathematical equation or mathematical statistics modeling.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.23 no.1
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• pp.63-69
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• 2019

The relative position of the orbital eye can be a criterion for evaluating several pathological conditions. It is especially useful to diagnose orbital fractures, thyroid eye disease, orbital tumors and to evaluate the outcome of medication and surgical treatment. Hertel and Naugle are representative measurement tools used to measure eyeball protrusion values, and have different measurement results, such as fixed orbits, every time they are inspected, even if the same inspector repeatedly measures them. Even with the same calibrator, it is inevitable that different manufacturers will change the design of the stationary part of the orbit, causing the surveyor to make a measurement error. In this paper, we designed and fabricated a protrusion measuring device using a white light interferometer and measured the protrusion of the human eye and found that the precision and repeatability were significantly higher than the manual measurement method.

• Journal of the Institute of Convergence Signal Processing
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• v.22 no.4
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• pp.193-198
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• 2021

Recently, interests in the 4th industry have increased the level of demand for pest control by farmers in the field of rice farming, and the interests and use of agricultural pest control drones. Therefore, the diversification of agricultural control drones that spray high-concentration pesticides and the increase of agricultural exterminators due to the acquisition of national drone certifications are rapidly developing the agricultural sector in the drone industry. In addition, as detailed projects, an effective platform is required to construct large-scale big data due to pesticide management, exterminator management, precise spraying, pest control work volume classification, settlement, soil management, prediction and monitoring of damages by pests, etc. and to process the data. However, studies in South Korea and other countries on development of models and programs to integrate and process the big data such as data analysis algorithms, image analysis algorithms, growth management algorithms, AI algorithms, etc. are insufficient. This paper proposed an online drone pest control management information platform to meet the needs of managers and farmers in the agricultural field and to realize precise AI pest control based on the agricultural drone pest control processor using drones and presented foundation for development of a comprehensive management system through empirical experiments.

• Journal of Biomedical Engineering Research
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• v.40 no.3
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• pp.105-115
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• 2019

Brain tumor surgery may be difficult, but it is also incredibly important. The technological improvements for traditional brain tumor surgeries have always been a focus to improve the precision of surgery and release the potential of the technology in this important area of the body. The need for precision during brain tumor surgery has led to an increase in Robotic-assisted surgeries (RAS). One of the challenges to the widespread acceptance of RAS in the neurosurgery is to recognize invisible tumor accurately. Therefore, it is important to detect brain tumor size and location because surgeon tries to remove as much tumor as possible. In this paper, we proposed brain tumor detection procedures for MRI (Magnetic Resonance Imaging) system. A method of automatic brain tumor detection is needed to accurately target the location of the lesion during brain tumor surgery and to report the location and size of the lesion. In the qualitative assessment, the proposed method showed better results than those obtained with other brain tumor detection methods. Comparisons among all assessment criteria indicated that the proposed method was significantly superior to the threshold method with respect to all assessment criteria. The proposed method was effective for detecting brain tumor.