• KIPS Transactions on Software and Data Engineering
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• v.7 no.9
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• pp.345-350
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• 2018

This study is an algorithm for detecting vein pattern features important for finger vein recognition. The feature detection algorithm is important because it greatly affects recognition results in pattern recognition. The recognition rate is degraded because the reference is changed according to the finger position change. In addition, the image obtained by irradiating the finger with infrared light is difficult to separate the image background and the blood vessel pattern, and the detection time is increased because the image preprocessing process is performed. For this purpose, the presented algorithm can be performed without image preprocessing, and the detection time can be reduced. SWDA (Down Slope Trace Waveform) algorithm is applied to the finger vein images to detect the fingertip position and vein pattern. Because of the low infrared transmittance, relatively dark vein images can be detected with minimal detection error. In addition, the fingertip position can be used as a reference in the classification stage to compensate the decrease in the recognition rate. If we apply algorithms proposed to various recognition fields such as palm and wrist, it is expected that it will contribute to improvement of biometric feature detection accuracy and reduction of recognition performance time.

• The Journal of the Korea Contents Association
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• v.9 no.10
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• pp.1-12
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• 2009

There exist some regular multiple relations in the intervals of notes when they are combined within one measure. This paper presents a method to find the exact measure positions in monophonic song based on those relations. In the proposed method the individual intervals are segmented at first and the rules that state the multiple relations are used to find the measure position. The measures can be applied as the foundational information for extracting beat and tempo of a song which can be used as background knowledge of automatic music transcription system. The proposed method exactly detected the measure positions of 11 songs out of 12 songs except one song which consist of monophonic voice song of the men and women. Also one can extract the information of beat and tempo of a song using the information about extracted measure positions with music theory.

• Korean Journal of Medicinal Crop Science
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• v.16 no.4
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• pp.231-237
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• 2008

This study was conducted to determine the amount of flavonoids in Salicomia herbacea L. grown by a liquid chromatography / mass spectrometry (LC/MS). The flavonoids-contained quercetin (124.43 ppm), rutin (2.57 ppm), quercetin-3-${\beta}$-glucoside (3992.49 ppm), quercetin-3',4'-glucoside (0.08 ppm) and isorhamnetin (27.81 ppm) were detected in the powder sample. In particular, quercetin-3-${\beta}$-glucoside accounted for more than 99% in hay and 96% in powder. These results suggest that S. herbacea, which is one of halophyte plants, has high functional substances as an antioxidant source.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.141-150
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• 2009

This paper proposes a system that can automatically write singing voices to music notes. First, the system uses Stabilized Diffusion Equation(SIDE) to divide the song to a series of syllabic parts based on pitch detection. By the song segmentation, our method can recognize the sound length of each fragment through clustering based on genetic algorithm. Moreover, this study introduces a concept called 'Relative Interval' so as to recognize interval based on pitch of singer. And it also adopted measure extraction algorithm using pause data to implement the higher precision of song transcription. By the experiments using 16 nursery songs, it is shown that the measure recognition rate is 91.5% and DMOS score reaches 3.82. These findings demonstrate effectiveness of system performance.

• Journal of Digital Convergence
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• v.11 no.7
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• pp.157-163
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• 2013

In this paper, we propose a vision and depth information based real-time hand gesture interface method using finger joint estimation. For this, the areas of left and right hands are segmented after mapping of the visual image and depth information image, and labeling and boundary noise removal is performed. Then, the centroid point and rotation angle of each hand area are calculated. Afterwards, a circle is expanded at following pattern from a centroid point of the hand to detect joint points and end points of the finger by obtaining the midway points of the hand boundary crossing and the hand model is recognized. Experimental results that our method enabled fingertip distinction and recognized various hand gestures fast and accurately. As a result of the experiment on various hand poses with the hidden fingers using both hands, the accuracy showed over 90% and the performance indicated over 25 fps. The proposed method can be used as a without contacts input interface in HCI control, education, and game applications.

• Journal of Korean Society of Forest Science
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• v.96 no.6
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• pp.737-741
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• 2007

Typical phytoplasma witches' broom symptoms were observed in black locust (Robinia pseudoacacia L.) in Korea. The symptoms of the disease were showing abnormally small leaves, shortened intemodes and proliferation of shoots. The phytoplasmas were detected consistently in all the symptomatic samples by the amplification with phytoplasma universal primer pairs P1/P7 and R16F2n/R2, and the expected size was 1.8 kb and 1.2 kb. However, the phytoplasma DNA was not detected in healthy seedling. Based on sequence analysis of amplified region, this phytoplasma has close homologies with aster yellow, mulberry dwarf, maize bushy stunt, ash witches' broom and sumac witches' broom phytoplasmas, more than 99.2% but showed homologies with black locust witches' broom (GeneBank Accession No. AF 244363), and jujube witches' broom, 88.6% and 87.7%, respectively. This phylogetic analysis indicates that the black locust witches' broom phytoplasma founded in korea should be classified in the Candidatus phytoplasma asteris (16Sr I) group and clearly distinct from the black locust witches' broom group 16Sr III (peach X-disease phytoplasma group).

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.1464-1466
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• 2015

개인 인증을 위한 바이오인식 방법으로 홍채, 지문, 정맥 인식 등이 널리 사용되고 있다. 하지만 별도의 센서가 필요한 방법들이므로 스마트폰에서 활용하기에 적절하지 않다. 본 논문에서는 엄지손가락 특징을 이용한 새로운 바이오 인식방법을 제안한다. 엄지손가락을 이용한 바이오 인식 방법은 손가락을 촬영하여 영상정보를 획득하는 단계, 영상의 크기와 방향, 밝기를 정규화 하는 단계, 영상 정보로부터 손가락 경계, 손톱 모양, 마디 주름 등의 특징을 검출하는 단계를 포함한다. 제안하는 방법은 카메라가 장착된 스마트기기에서 별도의 센서 추가 없이 개인 인증을 위한 방법으로 활용될 수 있을 것으로 기대된다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.215-217
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• 2021

본 논문은 3D 공간에서 사용자를 추출한 뒤, 체적 정보 분석을 통한 3D 스켈레톤(skeleton) 분석 과정을 통해 정확도 높은 다수 사용자의 위치 추적 기술에 대해 연구하였다. 이를 위하여 YOLO(You Only Look Once)를 활용하여 실시간으로 객체를 검출(Real-Time Object Detection)한 뒤 Google의 Mediapipe를 활용해 스켈레톤 추출, 스켈레톤 정규화(normalization)를 통한 스켈레톤의 크기 및 상대적 비율 계산, RGB 영상 스케일링(Scaling) 후 주요 마디 인접 영역의 RGB 색상 정보를 추출하는 방법을 통해 정확도가 개선된 높은 성능의 다중 사용자 추적 기술을 연구하였다.

• Proceedings of the Korean Society of Crop Science Conference
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• 2022.10a
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• pp.310-310
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• 2022

백리향은 꿀풀과에 속하는 다년생 식물로 세계적으로 약 100여 종이 자생하는 것으로 알려져 있다. 우리나라에서 자생하는 백리향은 외국 허브인 타임(Thymus vulgaris)과는 형태학적 및 유전학적으로 다르나 시중에서 백리향과 타임 구분 없이 유통되고 있다. 백리향은 가지가 많고 포복성으로 자라는 특성이 있어 지피용 식물로 유용하고 독특한 향기를 지니고 있어 식품 및 향장품용 향료자원으로 활용이 가능하다. 또한, 우울증이나 불면증 등과 같은 신경성 질환 예방에 효과적인 것으로 알려져 있다. 본 연구에서는 국내 자생 향료 식물의 발굴 및 산업화 소재 가능성 검토를 위하여 토종 허브인 백리향을 오대산에서 수집하여 증식한 후 외래종 타임과 특성을 비교하였다. 백리향과 골든레몬타임의 유전형태 조사는 국립수목원 백리향 조사 요령을 참고하여 각 20개체씩 조사하였다. 조사항목은 식물의 높이, 엽신의 형태와 길이 및 너비, 화서 길이와 마디당 꽃 수, 꽃의 길이 등이었다. 오대산 백리향의 식물 높이는 평균 14.3 cm, 엽신 형태는 난형, 엽신 길이는 1.24 cm이었고 꽃의 길이는 0.92 cm, 꽃 수는 35개이었다. 골든레몬타임의 식물 높이는 평균 18.03 cm, 엽신 형태는 타원형, 엽신 길이는 1.06 cm이었고 꽃의 길이는 0.59 cm, 꽃 수는 146개이었다. 백리향과 골든레몬타임의 정유 추출수율은 각각 0.22, 0.08%이었으며 추출된 정유를 GC-TOF의 SPME장치를 사용하여 분석한 결과, thymol, Caryophyllene, linalool, camphor 등이 향기 성분으로 검출되었다.

• Journal of the Korean Society of Food Science and Nutrition
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• v.34 no.7
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• pp.1041-1051
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• 2005

In order to assure the safety of the seaweeds, we measured the contents of the trace metals in the seaweeds harvested from Korean coastal area. We collected 620 marine algal samples from fourteen areas, and then analyzed the trace metals such as Hg, Cd, Cr, Cu, Mn, Ni, Pb and Zn. The contents of Hg, Cd, Ni and Mn were higher in the seaweeds collected from Chungnam Taean area. The contents of Cr and Cu were higher in the seaweeds collected from Yeongdeok and Tongyeong area, respectively. And Pb and Zn were highly detected from the seaweeds of Ulsan area. The mean levels of trace metals were high in the order of Zn $(48.02\pm41.20{\mu}g/g)\;>\;Mn (34.63\pm38.95{\mu}g/g)\;>\;Cu(6.29\pm6.52{\mu}g/g)\;>\;Ni(2.17\pm4.00{\mu}g/g)\; >\;Cr(1.61\pm2.35{\mu}g/g)\;>\;Pb(1.28\pm2.37{\mu}g/g)\;>\; Cd(0.67\pm0.75{\mu}g/g)\;>\;Hg(0.02\pm0.02{\mu}g/g)$. Zn was consistently most abundant metal in all samples, followed by Mn and Cu, which are very important for human health. There were higher contents of Hg and Cd in brown algae, the contents of Cr, Cu, Mn, Ni and Pb in green algae, the content of Zn in red algae among them. Additionally, significant linear correlations were observed between a total 28 different pairs of metals, of them, the correlation factor between Cr and Ni showed the highest (r=0.374, p<0.001). The trace metal contents of seaweeds varied with habitats and kinds of samples, nevertheless they showed very safe level in edible seaweeds tested. Scytosiphon lomentaria, which has been known as a little use of food, have shown a clear selectivity for Cr and Pb. Among non-edible seaweeds, Sargassum thunbergii for both Cd and Mn, Lomentaria hakodatensis for Ni and Grateloupia prolongata for Zn have shown a clear selectivity, respectively. Therefore, these seaweeds could be useful as bioindicator for each trace metal pollution.