• Title/Summary/Keyword: signal conversion

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Characterization of SID2 that is required for the production of salicylic acid by using β-GLUCURONIDASE and LUCIFERASE reporter system in Arabidoposis (리포트 시스템을 이용한 살리실산 생합성 유전자 SID2의 발현 해석)

  • Hong, Mi-Ju;Cheong, Mi-Sun;Lee, Ji-Young;Kim, Hun;Jeong, Jae-Cheol;Shen, Mingzhe;Ali, Zahir;Park, Bo-Kyung;Choi, Won-Kyun;Yun, Dae-Jin
    • Journal of Plant Biotechnology
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    • v.35 no.3
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    • pp.169-176
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    • 2008
  • Salicylic acid(SA) is a phytohormone that is related to plant defense mechanism. The SA accumulation is triggered by abiotic and biotic stresses. SA acts as a signal molecular compound mediating systemic acquired resistance and hypersensitive response in plant. Although the role of SA has been studied extensively, an understanding of the SA regulatory mechanism is still lacking in plants. In order to comprehend SA regulatory mechanism, we have been transformed with a SID2 promoter:GUS::LUC fusion construct into siz1-2 mutant and wild plant(Col-0). SIZ1 encodes SUMO E3 ligase and negatively regulates SA accumulation in plants. SID2(SALICYLIC ACID INDUCTION DEFICIENT2) is a crucial enzyme of SA biosynthesis. The Arabidopsis SID2 gene encodes isochorismate synthase(ICS) that controls SA level by conversion of chorismate to isochorismate. We compared the regulation of SID2 in wild-type and siz1-2 transgenic plants that express SID2 promoter:GUS::LUC constructs respectively. The expressions of $\beta$-GLUCURONIDASE and LUCIFERASE were higher in siz 1-2 transgenic plant without any stress treatment. SID2 promoter:GUS::LUC/siz1-2 transgenic plant will be used as a starting material for isolation of siz1-2 suppressor mutants and genes involved in SA-mediated stress signaling pathway.

Development of Movement Analysis Program and its Feasibility Test in Streotactic Body Radiation Threrapy (복부부위의 체부정위방사선치료시 호흡에 의한 움직임분석 프로그램 개발 및 유용성 평가)

  • Shin, Eun-Hyuk;Han, Young-Yih;Kim, Jin-Sung;Park, Hee-Chul;Shin, Jung-Suk;Ju, Sang-Gyu;Lee, Ji-Hea;Ahn, Jong-Ho;Lee, Jai-Ki;Choi, Doo-Ho
    • Progress in Medical Physics
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    • v.22 no.3
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    • pp.107-116
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    • 2011
  • Respiratory gated radiation therapy and stereotactic body radiation therapy require identical tumor motions during each treatment with the motion detected in treatment planning CT. Therefore, this study developed a tumor motion monitoring and analysis system during the treatments employing RPM data, gated setup OBI images and a data analysis software. A respiratory training and guiding program which improves the regularity of breathing was used to patients. The breathing signal was obtained by RPM and the recorded data in the 4D console was read after treatment. The setup OBI images obtained gated at 0% and 50% of breathing phases were used to detect the tumor motion range in crenio-caudal direction. By matching the RPM data recorded at the OBI imaging time, a factor which converts the RPM motion to the tumor motion was computed. RPM data was entered to the institute developed data analysis software and the maximum, minimum, average of the breathing motion as well as the standard deviation of motion amplitude and period was computed. The computed result is exported in an excel file. The conversion factor was applied to the analyzed data to estimate the tumor motion. The accuracy of the developed method was tested by using a moving phantom, and the efficacy was evaluated for 10 stereotactic body radiation therapy patients. For the sine wave motion of the phantom with 4 sec of period and 2 cm of peak-to-peak amplitude, the measurement was slightly larger (4.052 sec) and the amplitude was smaller (1.952 cm). For patient treatment, one patient was evaluated not to qualified to SBRT due to the usability of the breathing, and in one patient case, the treatment was changed to respiratory gated treatment due the larger motion range of the tumor than treatment planed motion. The developed method and data analysis program was useful to estimate the tumor motion during treatment.

An Area-Efficient Time-Shared 10b DAC for AMOLED Column Driver IC Applications (AMOLED 컬럼 구동회로 응용을 위한 시분할 기법 기반의 면적 효율적인 10b DAC)

  • Kim, Won-Kang;An, Tai-Ji;Lee, Seung-Hoon
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.5
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    • pp.87-97
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    • 2016
  • This work proposes a time-shared 10b DAC based on a two-step resistor string to minimize the effective area of a DAC channel for driving each AMOLED display column. The proposed DAC shows a lower effective DAC area per unit column driver and a faster conversion speed than the conventional DACs by employing a time-shared DEMUX and a ROM-based two-step decoder of 6b and 4b in the first and second resistor string. In the second-stage 4b floating resistor string, a simple current source rather than a unity-gain buffer decreases the loading effect and chip area of a DAC channel and eliminates offset mismatch between channels caused by buffer amplifiers. The proposed 1-to-24 DEMUX enables a single DAC channel to drive 24 columns sequentially with a single-phase clock and a 5b binary counter. A 0.9pF sampling capacitor and a small-sized source follower in the input stage of each column-driving buffer amplifier decrease the effect due to channel charge injection and improve the output settling accuracy of the buffer amplifier while using the top-plate sampling scheme in the proposed DAC. The proposed DAC in a $0.18{\mu}m$ CMOS shows a signal settling time of 62.5ns during code transitions from '$000_{16}$' to '$3FF_{16}$'. The prototype DAC occupies a unit channel area of $0.058mm^2$ and an effective unit channel area of $0.002mm^2$ while consuming 6.08mW with analog and digital power supplies of 3.3V and 1.8V, respectively.

Development of B4C Thin Films for Neutron Detection (스퍼터링 코팅기법을 이용한 중성자 검출용 B4C 박막 개발)

  • Lim, Chang Hwy;Kim, Jongyul;Lee, Suhyun;Cho, Sang-Jin;Choi, Young-Hyun;Park, Jong-Won;Moon, Myung Kook
    • Journal of Radiation Protection and Research
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    • v.40 no.2
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    • pp.79-86
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    • 2015
  • $^3He$ gas has been used for neutron monitors as the neutron converter owing to its advantages such as high sensitivity, good ${\gamma}$-discrimination capability, and long-term stability. However, $^3He$ is becoming more difficult to obtain in last few years due to a global shortage of $^3He$ gas. Accordingly, the cost of a neutron monitor using $^3He$ gas as a neutron converter is becoming more expensive. Demand on a neutron monitor using an alternative neutron conversion material is widely increased. $^{10}B$ has many advantages among various $^3He$ alternative materials, as a neutron converter. In order to develop a neutron converter using $^{10}B$ (actually $B_4C$), we calculated the optimal thickness of a neutron converter with a Monte Carlo simulation using MCNP6. In addition, a neutron converter was fabricated by the Ar sputtering method and the neutron signal detection efficiencies were measured with respect to various thicknesses of fabricated a neutron converter. Also, we developed a 2-dimensional multi-wire proportional chamber (MWPC) for neutron beam profile monitoring using the fabricated a neutron converter, and performed experiments for neutron response of the neutron monitor at the 30 MW research reactor HANARO at the Korea Atomic Energy Research Institute. The 2-dimensional MWPC with boron ($B_4C$) neutron converter was proved to be useful for neutron beam monitoring, and can be applied to other types of neutron imaging.

Automatic Target Recognition Study using Knowledge Graph and Deep Learning Models for Text and Image data (지식 그래프와 딥러닝 모델 기반 텍스트와 이미지 데이터를 활용한 자동 표적 인식 방법 연구)

  • Kim, Jongmo;Lee, Jeongbin;Jeon, Hocheol;Sohn, Mye
    • Journal of Internet Computing and Services
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    • v.23 no.5
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    • pp.145-154
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    • 2022
  • Automatic Target Recognition (ATR) technology is emerging as a core technology of Future Combat Systems (FCS). Conventional ATR is performed based on IMINT (image information) collected from the SAR sensor, and various image-based deep learning models are used. However, with the development of IT and sensing technology, even though data/information related to ATR is expanding to HUMINT (human information) and SIGINT (signal information), ATR still contains image oriented IMINT data only is being used. In complex and diversified battlefield situations, it is difficult to guarantee high-level ATR accuracy and generalization performance with image data alone. Therefore, we propose a knowledge graph-based ATR method that can utilize image and text data simultaneously in this paper. The main idea of the knowledge graph and deep model-based ATR method is to convert the ATR image and text into graphs according to the characteristics of each data, align it to the knowledge graph, and connect the heterogeneous ATR data through the knowledge graph. In order to convert the ATR image into a graph, an object-tag graph consisting of object tags as nodes is generated from the image by using the pre-trained image object recognition model and the vocabulary of the knowledge graph. On the other hand, the ATR text uses the pre-trained language model, TF-IDF, co-occurrence word graph, and the vocabulary of knowledge graph to generate a word graph composed of nodes with key vocabulary for the ATR. The generated two types of graphs are connected to the knowledge graph using the entity alignment model for improvement of the ATR performance from images and texts. To prove the superiority of the proposed method, 227 documents from web documents and 61,714 RDF triples from dbpedia were collected, and comparison experiments were performed on precision, recall, and f1-score in a perspective of the entity alignment..