• Journal of the Institute of Electronics Engineers of Korea SD
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• v.38 no.4
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• pp.251-265
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• 2001

As the device scaling proceeds, the operating voltage(VDD) of giga-bit DRAMs is expected to be reduced to 1.5V or down, fir improving the device reliability and reducing the power dissipation. Therefore the low-voltage circuit design techniques are required to implement giga-bit DRAMs. In this work, state-of-art low-voltage DRAM circuit techniques are reviewed, and four kinds of low-voltage circuit design techniques are newly proposed for giga-bit DRAMs. Measurement results of test chips and SPICE simulation results are presented for the newly proposed circuit design techniques, which include a hierarchical negative-voltage word-line driver with reduced subthreshold leakage current, a two-phase VBB(Back-Bias Voltage) generator, a two-phase VPP(Boosted Voltage) generator and a bandgap reference voltage generator.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.533-536
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• 2016

This paper describes a vibrational energy harvesting circuit with MPPT control. A high-performance AC-DC converter of which the efficiency is improved by using body-bias technique and bulk-driven technique is proposed and applied for the vibrational energy harvesting circuit design. MPPT (Maximum Power Point Tracking) control function is implemented using the linear relationship between the open-circuit voltage of a vibrational device and its MPP voltage. The designed MPPT control circuit traces the maximum power point by periodically sampling the open circuit voltage of a vibrational device, makes the reference voltages using sampled voltage and delivers the maximum available power to load. The proposed circuit is designed with a $0.35{\mu}m$ CMOS process, and the chip area is $1.21mm{\times}0.98mm$.

• The Journal of Industrial Distribution & Business
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• v.13 no.4
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• pp.35-49
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• 2022

Purpose - According to the recently changing consumer smart environment and consumer decision-making process, this study investigates the structural relationship between electronic(online) WOM information characteristics and brand community experience value types on specific brand reliability and brand transformation. In particular, the characteristics of word of mouth information and the experience value of brand community users were divided into detailed fac tors and approached. Methodology - In order to proceed with this study, we review previous studies and setting hypotheses. The hypothesis was verified through a survey that was conducted for the consumers with online consumption activities in less than six months. With reference to previous studies, operational definition was made for the questionnaire design. In order to verify the hypothesis, 282 people were statistically analyzed through the survey This data were used for AMOS for confirm hypothesis established. Results - eWOM information characteristics were classified into usefulness, timeliness and un-bias, and online community experience values were classified into interaction, playfulness, and virtuality. In addition, it is to investigate the relationship between the brand reliability and user's experience value in brad community. The main results are as follows. The first result was that usefulness and un-bias, which are the eWOM information characteristics had a positive effect on forming brand reliability. However, the factor of timeliness did not affect brand reliability. Second, in terms of user experience value and brand reliability in the brand community. It was fo und that experience values such as interaction, playfulness, and vituality all had a positive influence on brand reliability. Third, it was found that brand reliability has a positive influence on the on-line conversion activity of users. Conclusions - Through this study, the field of online consumer behavior research is expanding, and this study suggested that careful management is necessary according to the type or characteristics of eWOM information. Additionally, it presents the importance of the user's empirical value in the brand community influencing brand attitude and reliability. In practice, the implementation of the marketing communication mix in digital marketing has recently been underway to enhance the conversion behavior of users. At this level, it also reveals the preceding factors that increase user conversion behavior.

• Clinics in Shoulder and Elbow
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• v.26 no.2
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• pp.182-190
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• 2023

Elbow traumas represent a relatively common condition in clinical practice. However, there is a lack of evidence regarding the most accurate tests for screening these potentially serious conditions and excluding elbow fractures. The purpose of this investigation was to analyze the literature concerning the diagnostic accuracy of clinical tests for the detection or exclusion of suspected elbow fractures. A systematic review was performed using the Preferred Reporting Items for a Systematic Review and Meta-analysis of Diagnostic Test Accuracy Studies (PRISMA-DTA) guidelines. Literature databases including PubMed, Cumulative Index to Nursing and Allied Health Literature, Diagnostic Test Accuracy, Cochrane Library, the Web of Science, and ScienceDirect were searched for diagnostic accuracy studies of subjects with suspected traumatic elbow fracture investigating clinical tests compared to imaging reference tests. The risk of bias in each study was assessed independently by two reviewers using the Quality Assessment of Diagnostic Accuracy Studies 2 checklist. Twelve studies (4,485 patients) were included. Three different types of index tests were extracted. In adults, these tests were very sensitive, with values up to 98.6% (95% confidence interval [CI], 95.0%-99.8%). The specificity was very variable, ranging from 24.0% (95% CI, 19.0%-30.0%) to 69.4% (95% CI, 57.3%-79.5%). The applicability of these tests was very high, while overall studies showed a medium risk of bias. Elbow full range of motion test, elbow extension test, and elbow extension and point tenderness test appear to be useful in the presence of a negative test to exclude fracture in a majority of cases. The specificity of all tests, however, does not allow us to draw useful conclusions because there was a great variability of results obtained.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1121-1121
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• 2001

A previous study (Berzaghi et al., 2001) evaluated the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural networks (ANN) on the prediction of the chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with reference values for moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected using 10 different Foss NIR Systems instruments, only some of which had been standardized to one master instrument. The aim of the present study was to evaluate the behaviour of these different calibration methods when predicting the same samples measured on different instruments. Twenty-two sealed samples of different kind of forages were measured in duplicate on seven instruments (one master and six slaves). Three sets of near infrared spectra (1100 to 2500nm) were created. The first set consisted of the spectra in their original form (unstandardized); the second set was created using a single sample standardization (Clone1); the third was created using a multiple sample procedure (Clone6). WinISI software (Infrasoft International Inc., Port Mathilda, PA, USA) was used to perform both types of standardization, Clone1 is just a photometric offset between a “master” instrument and the “slave” instrument. Clone6 modifies both the X-axis through a wavelength adjustment and the Y-axis through a simple regression wavelength by wavelength. The Clone1 procedure used one sample spectrally close to the centre of the population. The six samples used in Clone 6 were selected to cover the range of spectral variation in the sample set. The remaining fifteen samples were used to evaluate the performances of the different models. The predicted values for dry matter, protein and neutral detergent fibre from the master Instrument were considered as “reference Y values” when computing the statistics RMSEP, SEPC, R, Bias, Slope, mean GH (global Mahalanobis distance) and mean NH (neighbourhood Mahalanobis distance) for the 6 slave instruments. From the results we conclude that i) all the calibration techniques gave satisfactory results after standardization. Without standardization the predicted data from the slaves would have required slope and bias correction to produce acceptable statistics. ii) Standardization reduced the errors for all calibration methods and parameters tested, reducing not only systematic biases but also random errors. iii) Standardization removed slope effects that were significantly different from 1.0 in most of the cases. iv) Clone1 and Clone6 gave similar results except for NDF where Clone6 gave better RMSEP values than Clone1. v) GH and NH were reduced by half even with very large data sets including unstandardized spectra.

• Nutrition Research and Practice
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• v.12 no.4
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• pp.336-341
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• 2018

BACKGROUND/OBJECTIVES: Dietary Reference Intakes (DRI) for energy are derived from total energy expenditure (TEE) measured using the doubly labelled water (DLW) method. The objective of this study was to assess the validity of DRI for predicting the energy requirements of elementary school-age children. SUBJECTS/METHODS: The present study involved 25 elementary school-age children aged between 9 and 11 years. TEE was assessed by the DLW method, and the results were compared with the TEE predicted by the DRI equations in order to evaluate accuracy. RESULTS: The subjects' TEE measured by the DLW method was $1,925.2{\pm}380.9kcal/day$ in boys and $1,930.0{\pm}279.4kcal/day$ in girls, whereas resting energy expenditure was $1,220.2{\pm}176.9kcal/day$ in boys and $1,245.9{\pm}171.3kcal/day$ for girls. The physical activity level was $1.58{\pm}0.20$ in boys and $1.55{\pm}0.13$ in girls. The mean bias between the predicted and measured TEE was 12.6% in boys and -1.6% in girls, and the percentage of accurate predictions was 28.6% and 63.6%, respectively. In boys, the equation resulted in underprediction of TEE among the subjects having low TEE values, whereas there was overprediction among subjects having high TEE values as shown by the Bland-Altman plot. On the contrary, this proportional bias was not observed in girls. CONCLUSIONS: The findings of this study suggest that the DRI equation for energy could result in the overestimation of energy requirements in elementary school-age boys. In the case of girls, the equations could be accurate at the group level. However, the DRI appears to be invalid for individual girls, as more than one third of girls had their TEE inaccurately predicted. We recommend more studies for confirmation of these results.

• Journal of Advanced Navigation Technology
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• v.19 no.4
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• pp.299-304
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• 2015

This paper introduces development of the MATLAB GUI based software for generating GPS RINEX observation file. The purpose of this software is to generate GPS measurements of reference station or dynamic user, which are similar to the real GPS receiver data, accurately and efficiently. This software includes two data generation modes. One is Precision mode which generates GPS measurements as accurate as possible using post-processing data. The other is Real-time mode which generates GPS measurements using GPS error modeling technique. GPS error sources are calculated on the basis of each data generation mode, and L1/L2 pseudorange, L1/L2 carrier phase, and Doppler measurements are produced. These generated GPS measurements are recorded in the RINEX observation version 3.0 file. Using received GPS data at real reference station, we analyzed three items to verify software reliability; measurement bias, rate of change, and noise level. Consequently, RMS error of measurement bias is about 0.7 m, and this verification results demonstrate that our software can generate relatively exact GPS measurements.

• Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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• 2001.06a
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• pp.1141-1141
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• 2001

The aim of the study was to evaluate the performance of 3 calibration methods, modified partial least squares (MPLS), local PLS (LOCAL) and artificial neural network (ANN) on the prediction of chemical composition of forages, using a large NIR database. The study used forage samples (n=25,977) from Australia, Europe (Belgium, Germany, Italy and Sweden) and North America (Canada and U.S.A) with information relative to moisture, crude protein and neutral detergent fibre content. The spectra of the samples were collected with 10 different Foss NIR Systems instruments, which were either standardized or not standardized to one master instrument. The spectra were trimmed to a wavelength range between 1100 and 2498 nm. Two data sets, one standardized (IVAL) and the other not standardized (SVAL) were used as independent validation sets, but 10% of both sets were omitted and kept for later expansion of the calibration database. The remaining samples were combined into one database (n=21,696), which was split into 75% calibration (CALBASE) and 25% validation (VALBASE). The chemical components in the 3 validation data sets were predicted with each model derived from CALBASE using the calibration database before and after it was expanded with 10% of the samples from IVAL and SVAL data sets. Calibration performance was evaluated using standard error of prediction corrected for bias (SEP(C)), bias, slope and R2. None of the models appeared to be consistently better across all validation sets. VALBASE was predicted well by all models, with smaller SEP(C) and bias values than for IVAL and SVAL. This was not surprising as VALBASE was selected from the calibration database and it had a sample population similar to CALBASE, whereas IVAL and SVAL were completely independent validation sets. In most cases, Local and ANN models, but not modified PLS, showed considerable improvement in the prediction of IVAL and SVAL after the calibration database had been expanded with the 10% samples of IVAL and SVAL reserved for calibration expansion. The effects of sample processing, instrument standardization and differences in reference procedure were partially confounded in the validation sets, so it was not possible to determine which factors were most important. Further work on the development of large databases must address the problems of standardization of instruments, harmonization and standardization of laboratory procedures and even more importantly, the definition of the database population.

• Asian Pacific Journal of Cancer Prevention
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• v.14 no.1
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• pp.589-594
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• 2013

Background: Prospective cohort studies to determine cofactors with oncogenic HPV-infections for cervical cancer are very rare from developing countries and such data are limited to the few screening trials. Large screening trials provide such data as a by product. Some of the cases are prevented by screening and do not surface as invasive cancers at all. Also, pre-invasive lesions are detected almost entirely by screening. Screening causes selection bias if attendance in or effectiveness of screening is correlated with the risk factors. The aim of this study was to quantify the influence of screening on risk factors for cervical cancer. Materials and Methods: Our material stems from a rural cohort of 80,000 women subjected to a randomised screening trial. The effect of screening on the incidence of cervix cancer was estimated with reference to socio-demographic and reproductive risk factors of cervical cancer. We compared these risks with the incidence of cancer in the randomised control population by the same determinants of risk. Results: The results in the screening arm compared to the control arm showed that the women of low SES and young age were benefitting more than those of high SES and old age. The relative risk by age (30-39 vs 50-59) was 0.33 in the control arm and 0.24 in the screening arm. The relative risk by education (not educated vs educated) was 2.8 in the control arm and 1.8 in the screening arm. The previously married women did not benefit (incidence 113 and 115 per 100,000 women years in control vs screening arms) whereas the effect was substantial in those married (86 vs 54). Conclusions: The results in controls were consistent with the general evidence, but results in attenders and nonattenders of the screening arm showed that screening itself and self-selection in attendance and effectiveness can influence the effect estimates of risk factors. The effect of cervical cancer screening programmes on the estimates of incidence of cervical cancer causes bias in the studies on etiology and, therefore, they should be interpreted with caution.

• Korean Journal of Agricultural and Forest Meteorology
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• v.23 no.4
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• pp.405-414
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• 2021

This study predicted waxy corn harvest date in South Korea using 30-year (1991-2020) hindcasts (1-6 month lead) produced by the Pusan National University Coupled General Circulation Model (PNU CGCM)-Weather Research and Forecasting (WRF) chain. To estimate corn harvest date, the cumulative temperature is used, which accumulated the daily observed and predicted temperatures from the seeding date (5 April) to the reference temperature (1,650~2,200℃) for harvest. In terms of the mean air temperature, the hindcasts with a bias correction (20.2℃) tends to have a cold bias of about 0.1℃ for the 6 months (April to September) compared to the observation (20.3℃). The harvest date derived from bias-corrected hindcasts (DOY 187~210) well simulates one from observation (DOY 188~211), despite a slight margin of 1.1~1.3 days. The study shows the possibility of obtaining the gridded (5 km) daily temperature and corn harvest date information based on the cumulative temperature in advance for all regions of South Korea.