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A 10b 200MS/s 75.6mW $0.76mm^2$ 65nm CMOS Pipeline ADC for HDTV Applications (HDTV 응용을 위한 10비트 200MS/s 75.6mW $0.76mm^2$ 65nm CMOS 파이프라인 A/D 변환기)

  • Park, Beom-Soo;Kim, Young-Ju;Park, Seung-Jae;Lee, Seung-Hoon
    • Journal of the Institute of Electronics Engineers of Korea SD
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    • v.46 no.3
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    • pp.60-68
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    • 2009
  • This work proposes a 10b 200MS/s 65nm CMOS ADC for high-definition video systems such as HDTV requiring high resolution and fast operating speed simultaneously. The proposed ADC employs a four-step pipeline architecture to minimize power consumption and chip area. The input SHA based on four capacitors reduces the output signal range from $1.4V_{p-p}$ to $1.0V_{p-p}$ considering high input signal levels at a low supply voltage of 1.2V. The proposed three-stage amplifiers in the input SHA and MDAC1 overcome the low output resistance problem as commonly observed in a 65nm CMOS process. The proposed multipath frequency-compensation technique enables the conventional RNMC based three-stage amplifiers to achieve a stable operation at a high sampling rate of 200MS/s. The conventional switched-bias power-reduction technique in the sub-ranging flash ADCs further reduces power consumption while the reference generator integrated on chip with optional off-chip reference voltages allows versatile system a locations. The prototype ADC in a 65nm CMOS technology demonstrates a measured DNL and INL within 0.19LSB and 0.61LSB, respectively. The ADC shows a maximum SNDR of 54.BdB and 52.4dB and a maximum SFDR of 72.9dB and 64.8dB at 150MS/S and 200MS/s, respectively. The proposed ADC occupies an active die area of $0.76mm^2$ and consumes 75.6mW at a 1.2V supply voltage.

Evaluation of Absorbed Dose and Skin Dose with MDCT Using Ionization Chamber and TLD (이온 전리함 및 TLD 법을 이용한 Multi-Detector Computed Tomography의 흡수선량 및 체표면 선량 평가)

  • Jeon, Kyung Soo;Oh, Young Kee;Baek, Jong Geun;Kim, Ok Bae;Kim, Jin Hee;Choi, Tae Jin;Jeong, Dong Hyeok;Kim, Jeong Kee
    • Progress in Medical Physics
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    • v.24 no.1
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    • pp.35-40
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    • 2013
  • Recently, the uses of Multi-Detector Computed Tomography (MDCT) for radiation treatment simulation and planning which is used for intensity modulated radiation therapy with high technique are increasing. Because of the increasing uses of MDCT, additional doses are also increasing. The objective of this study is to evaluate the absorbed dose of body and skin undergoing in MDCT scans. In this study, the exposed dose at the surface and the center of the cylindrical water phantom was measured using an pencil ionization chamber, 30 cc ionization chamber and TL Powder. The results of MDCT were 31.84 mGy, 33.58 mGy and 32.73 mGy respectively. The absorbed dose at the surface showed that the TL reading value was 33.92 mGy from MDCT. These results showed that the surface dose was about 3.5% from the MDCT exposure higher than a dose which is located at the center of the phantom. These results mean that the total exposed dose undergoing MDCT 4 times (diagnostic, radiation therapy planning, follow-up et al.), is about 14 cGy, and have to be considered significantly to reduce the exposed dose from CT scan.

Preparation of Polystyrene Beads by Suspension Polymerization with Hydrophobic Silica as a Stabilizer in Aqueous Solution (소수성 실리카를 안정제로 이용하는 수용액 상에서의 현탁중합법에 의한 폴리스티렌 입자 합성)

  • Park, Moon-Soo
    • Polymer(Korea)
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    • v.30 no.6
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    • pp.498-504
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    • 2006
  • A suspension polymerization of styrene In aqueous phase was employed to study if polystyrene particles ranging from 1 to $20{\mu}m$ can be produced. Hydrophobic silica was selected as a stabilizer and azo-bisisobutyronitrile (AIBN) as an initiator. Polymerization reaction was carried out at a selected temperature in the range of $65{\sim}95^{\circ}C$. Stabilizer concentration was varied from 0.17 to 3.33 wt% compared to the water while the concentration of the initiator was raised from 0.13 to 6.0 wt% compared to the monomer. Dispersion of hydrophobic silica into the water phase was achieved by precise control of pH. Optimum dispersion of silica was obtained at pH 10. Average particle diameter decreased with increasing amounts of stabilizer concentration initially, exhibiting the minimum average diameter at 1.67 wt% of stabilizer concentration, after which it started to Increase. It is speculated that an excessive presence of stabilizer encouraged a secondary reaction in the reaction medium, which led to particle agglomeration, and as a result an increase in average particle diameter. Molecular weight was found to be independent of stabilizer concentration between 0.13 and 1.00 wt% whereas, it increased when stabilizer concentration exceeded 1.67 wt%. Variation of molecular weight was probably caused by the reduced activity and efficiency of initiator due to the high concentration of silica, and the secondary reaction in the reaction medium, as well. An increase in the Initiator concentration and/or reaction temperature resulted in an increase in both reaction rate and particle diameter. Consequently, we have confirmed that spherical polystyrene particles with $1{\sim}20{\mu}m$ in diameter can be prepared by careful selection of the concentration of stabilizer, initiator, pH and reaction temperature.

A study on the derivation and evaluation of flow duration curve (FDC) using deep learning with a long short-term memory (LSTM) networks and soil water assessment tool (SWAT) (LSTM Networks 딥러닝 기법과 SWAT을 이용한 유량지속곡선 도출 및 평가)

  • Choi, Jung-Ryel;An, Sung-Wook;Choi, Jin-Young;Kim, Byung-Sik
    • Journal of Korea Water Resources Association
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    • v.54 no.spc1
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    • pp.1107-1118
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    • 2021
  • Climate change brought on by global warming increased the frequency of flood and drought on the Korean Peninsula, along with the casualties and physical damage resulting therefrom. Preparation and response to these water disasters requires national-level planning for water resource management. In addition, watershed-level management of water resources requires flow duration curves (FDC) derived from continuous data based on long-term observations. Traditionally, in water resource studies, physical rainfall-runoff models are widely used to generate duration curves. However, a number of recent studies explored the use of data-based deep learning techniques for runoff prediction. Physical models produce hydraulically and hydrologically reliable results. However, these models require a high level of understanding and may also take longer to operate. On the other hand, data-based deep-learning techniques offer the benefit if less input data requirement and shorter operation time. However, the relationship between input and output data is processed in a black box, making it impossible to consider hydraulic and hydrological characteristics. This study chose one from each category. For the physical model, this study calculated long-term data without missing data using parameter calibration of the Soil Water Assessment Tool (SWAT), a physical model tested for its applicability in Korea and other countries. The data was used as training data for the Long Short-Term Memory (LSTM) data-based deep learning technique. An anlysis of the time-series data fond that, during the calibration period (2017-18), the Nash-Sutcliffe Efficiency (NSE) and the determinanation coefficient for fit comparison were high at 0.04 and 0.03, respectively, indicating that the SWAT results are superior to the LSTM results. In addition, the annual time-series data from the models were sorted in the descending order, and the resulting flow duration curves were compared with the duration curves based on the observed flow, and the NSE for the SWAT and the LSTM models were 0.95 and 0.91, respectively, and the determination coefficients were 0.96 and 0.92, respectively. The findings indicate that both models yield good performance. Even though the LSTM requires improved simulation accuracy in the low flow sections, the LSTM appears to be widely applicable to calculating flow duration curves for large basins that require longer time for model development and operation due to vast data input, and non-measured basins with insufficient input data.

Analyzing Mathematical Performances of ChatGPT: Focusing on the Solution of National Assessment of Educational Achievement and the College Scholastic Ability Test (ChatGPT의 수학적 성능 분석: 국가수준 학업성취도 평가 및 대학수학능력시험 수학 문제 풀이를 중심으로)

  • Kwon, Oh Nam;Oh, Se Jun;Yoon, Jungeun;Lee, Kyungwon;Shin, Byoung Chul;Jung, Won
    • Communications of Mathematical Education
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    • v.37 no.2
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    • pp.233-256
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    • 2023
  • This study conducted foundational research to derive ways to use ChatGPT in mathematics education by analyzing ChatGPT's responses to questions from the National Assessment of Educational Achievement (NAEA) and the College Scholastic Ability Test (CSAT). ChatGPT, a generative artificial intelligence model, has gained attention in various fields, and there is a growing demand for its use in education as the number of users rapidly increases. To the best of our knowledge, there are very few reported cases of educational studies utilizing ChatGPT. In this study, we analyzed ChatGPT 3.5 responses to questions from the three-year National Assessment of Educational Achievement and the College Scholastic Ability Test, categorizing them based on the percentage of correct answers, the accuracy of the solution process, and types of errors. The correct answer rates for ChatGPT in the National Assessment of Educational Achievement and the College Scholastic Ability Test questions were 37.1% and 15.97%, respectively. The accuracy of ChatGPT's solution process was calculated as 3.44 for the National Assessment of Educational Achievement and 2.49 for the College Scholastic Ability Test. Errors in solving math problems with ChatGPT were classified into procedural and functional errors. Procedural errors referred to mistakes in connecting expressions to the next step or in calculations, while functional errors were related to how ChatGPT recognized, judged, and outputted text. This analysis suggests that relying solely on the percentage of correct answers should not be the criterion for assessing ChatGPT's mathematical performance, but rather a combination of the accuracy of the solution process and types of errors should be considered.

Evaluation of Cryptosporidiurn Disinfection by Ozone and Ultraviolet Irradiation Using Viability and Infectivity Assays (크립토스포리디움의 활성/감염성 판별법을 이용한 오존 및 자외선 소독능 평가)

  • Park Sang-Jung;Cho Min;Yoon Je-Yong;Jun Yong-Sung;Rim Yeon-Taek;Jin Ing-Nyol;Chung Hyen-Mi
    • Journal of Life Science
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    • v.16 no.3 s.76
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    • pp.534-539
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    • 2006
  • In the ozone disinfection unit process of a piston type batch reactor with continuous ozone analysis using a flow injection analysis (FIA) system, the CT values for 1 log inactivation of Cryptosporidium parvum by viability assays of DAPI/PI and excystation were $1.8{\sim}2.2\;mg/L{\cdot}min$ at $25^{\circ}C$ and $9.1mg/L{\cdot}min$ at $5^{\circ}C$, respectively. At the low temperature, ozone requirement rises $4{\sim}5$ times higher in order to achieve the same level of disinfection at room temperature. In a 40 L scale pilot plant with continuous flow and constant 5 minutes retention time, disinfection effects were evaluated using excystation, DAPI/PI, and cell infection method at the same time. About 0.2 log inactivation of Cryptosporidium by DAPI/PI and excystation assay, and 1.2 log inactivation by cell infectivity assay were estimated, respectively, at the CT value of about $8mg/L{\cdot}min$. The difference between DAPI/PI and excystation assay was not significant in evaluating CT values of Cryptosporidium by ozone in both experiment of the piston and the pilot reactors. However, there was significant difference between viability assay based on the intact cell wall structure and function and infectivity assay based on the developing oocysts to sporozoites and merozoites in the pilot study. The stage of development should be more sensitive to ozone oxidation than cell wall intactness of oocysts. The difference of CT values estimated by viability assay between two studies may partly come from underestimation of the residual ozone concentration due to the manual monitoring in the pilot study, or the difference of the reactor scale (50 mL vs 40 L) and types (batch vs continuous). Adequate If value to disinfect 1 and 2 log scale of Cryptosporidium in UV irradiation process was 25 $mWs/cm^2$ and 50 $mWs/cm^2$, respectively, at $25^{\circ}C$ by DAPI/PI. At $5^{\circ}C$, 40 $mWs/cm^2$ was required for disinfecting 1 log Cryptosporidium, and 80 $mWs/cm^2$ for disinfecting 2 log Cryptosporidium. It was thought that about 60% increase of If value requirement to compensate for the $20^{\circ}C$ decrease in temperature was due to the low voltage low output lamp letting weaker UV rays occur at lower temperatures.