• Smart Media Journal
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• v.11 no.2
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• pp.77-83
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• 2022

The neuromorphic architecture uses a spiking neural network (SNN) model to derive more accurate results as more spike values are accumulated through inference experiments. When the inference result converges to a specific value, even if the inference experiment is further performed, the change in the result is smaller and power consumption may increase. In particular, in an AI-based IoT environment, power consumption can be a big problem. Therefore, in this paper, we propose a technique to reduce the power consumption of AI-based IoT by reducing the inference time by adjusting the inference image exposure time in the neuromorphic architecture environment. The proposed technique calculates the next inferred image exposure time by reflecting the change in inference accuracy. In addition, the rate of reflection of the change in inference accuracy can be adjusted with a coefficient value, and an optimal coefficient value is found through a comparison experiment of various coefficient values. In the proposed technique, the inference image exposure time corresponding to the target accuracy is greater than that of the linear technique, but the overall power consumption is less than that of the linear technique. As a result of measuring and evaluating the performance of the proposed method, it is confirmed that the inference experiment applying the proposed method can reduce the final exposure time by about 90% compared to the inference experiment applying the linear method.

• The Sea:JOURNAL OF THE KOREAN SOCIETY OF OCEANOGRAPHY
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• v.6 no.1
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• pp.1-12
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• 2001

Tidal computations of $M_2,\;S_2,\; K_1$ and $O_1$ constituents in the northeast Asian sea are presented by blending the Topex/Poseidon (T/P) altimeter data into a hydrodynamic model with $5'{\times}5'$ resolution. A series of sensitivity experiments on a weighting factor, which is the control parameter in the blending method, are carried out using $M_2$ constituent. The weighting factor is set to be in inverse proportion to the square root of water depth to reduce noises which could occur in data-assimilative model by blending T/P data. Model results obtained by blending the T/P-derived $M_2,\;S_2,\; K_1$ and $O_1$ constituents simultaneously are compared with all T/P-track tidal data; Average values of amplitude and phase errors are close to zero. Standard deviations of amplitude and phase errors are approximately 2 cm and less than 10 degrees respectively. The data-assimilative model results show a quite good agreement with T/P-derived tidal data, particularly in shallow water region (h<250m). In deep water regions, T/P-derived tidal data show unreasonable spatial variations in amplitude and phase. The data-assimilative model results differ from T/P-derived data, but are improved to show reasonable spatial variations in amplitude and phase. In addition, the T/P-blended model results are in good agreement with coastal tide gauge data which are not blended into the model.

• Korean Journal of Remote Sensing
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• v.34 no.3
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• pp.519-533
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• 2018

The sensible heat flux (SHF)and latent heat flux (LHF) over Korean Peninsula ocean during recent 4 years were calculated using Coupled Ocean-Atmosphere Response Experiment (COARE) 3.5 bulk algorithm and satellite-based atmospheric-ocean variables. Among the four input variables (10-m wind speed; U, sea surface temperature; $T_s$, air temperature; $T_a$, and air humidity; $Q_a$) required for heat flux calculation, Ta and $Q_a$, which are not observed directly by satellites, were estimated from empirical relations developed using satellite-based columnar atmospheric water vapor (W) and $T_s$. The estimated satellite-based $T_a$ and $Q_a$ show high correlation coefficients above 0.96 with the buoy observations. The temporal and spatial variability of monthly ocean heat fluxes were analyzed for the Korean Peninsula ocean. The SHF showed low values of $20W/m^2$ over the entire areas from March to August. Particularly, in July, SHF from the atmosphere to the ocean, which is less than $0W/m^2$, has been shown in some areas. The SHF gradually increased from September and reached the maximum value in December. Similarly, The LHF showed low values of $40W/m^2$ from April to July, but it increased rapidly from autumn and was highest in December. The analysis of monthly characteristics of the meteorological variables affecting the heat fluxes revealed that the variation in differences of temperature and humidity between air and sea modulate the SHF and LHF, respectively. In addition, as the sensitivity of SHF and LHF to U increase in winter, it contributed to the highest values of ocean heat fluxes in this season.

• The Journal of the Korea institute of electronic communication sciences
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• v.7 no.6
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• pp.1369-1375
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• 2012

One of important problems in the theory of sequences is to determine the values and number of occurrences of each value taken on by the cross-correlation. In this paper, we find the values and the number of occurrences of each value of cross-correlation between an m-sequence u(t) of period $2^n-1$ and its decimation $u(dt)(0{\leq}t{\leq}2^n-2)$ where n=2m, 2s|m and $d=(2^{2m}+2^{2s+1}-2^{m+s+1}-1)/(2^s-1)$. Also we show that a family of decimations leads to a four-valued cross-correlation.

• Journal of Animal Science and Technology
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• v.46 no.4
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• pp.613-624
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• 2004

This study was aimed at investigating the effect of fat supplementation with divalent ions such as MgO and $CaCl_2$ on 1) in vitro ruminal fermentation characteristics and insoluble fatty acid formation, and on 2) animal performance in finishing Hanwoo bulls. In in vitro trial, five different types of diets based on supplementation sources of fat and divalent ions, i.e. T=basal diet+4% tallow, T-Ca=T+0.5% $CaCl_2$, T-Mg=TA+0.5% MgO, T-MgCa = T +0.5% $CaCl_2$+0.5% MgO, T-caS =4% Ca salt tallow, were tested. Higher pH values were observed at 6 hr incubation(P<0.01) while higher amount of VFA were produced in diets 4 and 5 at 12 hr incubation(P<0.05). Nutrients(DM, OM, Crude protein and NDF) degradation tended to increase in divalent ions or Ca-salts treated tallow treatments compared with tallow treatment after 12 h. The amount of insoluble fatty acid increased by adding MgO or $CaCl_2$ to tallow or Ca soap tallow during incubation(P<0.05). In in vivo trial, thirty finishing Hanwoo(average BW 460kg) were divided into three groups based on fat sources and divalent ions, i.e. Control(EE 2.40), T-MgCa = control + tallow + $CaCl_2$ + MgO, T-CaS = control + Ca soap tallow (EE 5.30%). After feeding each diet for 80 days, average daily weight gain showed 0.89, 1.02, 1.17kg in diets 1, 2 and 3, respectively. The highest feed efficiency was observed(0.12) in diet 2 group, followed by diet 3 (0.10) and 1 groups(0.08; P < 0.05). In conclusion, the present results could be sununarized that the performance of Hanwoo bulls was improved by tallow with divalent ions without any negative effect on rumen fermentation.

• Annual Conference of KIPS
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• 2018.10a
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• pp.995-997
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• 2018

본 논문에서는 운영체제나 하드웨어에 종속되지 않고 IoT 환경을 구축할 수 있는 EdgeX Foundry를 이용하여 EdgeX와 두 대의 라즈베리파이 간의 통신을 구현한다. 두 라즈베리파이가 보낸 센서값은 EdgeX를 거쳐 EdgeX Client로 전해지며, 처리된 값은 두 라즈베리파이 중 특정 명령을 수행할 라즈베리파이로 command 메시지가 전송되어 디바이스를 작동시킨다.

• Food Science of Animal Resources
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• v.29 no.3
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• pp.334-339
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• 2009

This study was carried out to determine the effects of olive-oil prepared tomato powder (OPTP) and lycopene on seasoned raw pork. 1.5% OPTP was added in T1 and 3.0% in T2; and 0.03% refining lycopene was added in T3. While in storage, pH values of the treated samples were lower (p<0.05) than those of the control samples. Upon increasing storage, salinity values of OPTP samples increased as well, however, the values of T3 did not change. There were significantly higher TBARS values observed in the OPTP samples compared to control, but no significant difference between T3 and the control samples in TBARS values during storage. VBN values of T2 samples were lower than that of other samples at Day 3 and Day 6 of storage. At Day 9 however, the VBN values of T1 and T2 were significantly higher than those of the control and T3. There was no significant difference between the control and the treated samples in the total plate counts. There were relatively higher redness, yellowness and chromatic values observed in the treated samples than in control. In sensory evaluation, there was no significant difference between the control and the treated samples in color, tenderness, juiciness and overall acceptability.

• Journal of Food Hygiene and Safety
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• v.25 no.1
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• pp.59-64
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• 2010

The effects of vinegar, alcohol and ascorbic acid on the color, microorganism, sensory properties and flavor pattern of minced ginger (MG) were investigated during storage for 28 days at $30^{\circ}C$. The values of L (lightness), a (redness) and b (yellowness) of the control (T-0) and all the treatments changed slightly at the initial stage of storage, however the elapse of time accelerated the changes. The total bacterial counts of T-0 showed $5.37{\times}10^7\;CFU/g$ at the initial stage, but the MG-treatments decreased the bacteria above 4 log compared to T-0. It was showed that the additives were effective for inhibition of the growth of microorganism. Sensory properties of flavor intensity test showed no significant difference between T-0 and MG-treatments (p < 0.05). The result of volatile flavor contents of electronic nose analyzer (ENZ) showed that MG-treatments (T-I, T-II, T-III) was recognized stronger than non-treatment at the initial stage, but the change of flavor compound were stabilized soon regardless of type or quantity of additives during total storage period at $30^{\circ}C$.

• Journal of radiological science and technology
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• v.39 no.3
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• pp.345-352
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• 2016

The purpose of this study was to needed basis of measure MRI CAD development for signal to noise ratio (SNR) by pulse sequence analysis from region of interest (ROI) in brain magnetic resonance imaging (MRI) contrast. We examined images of brain MRI contrast enhancement of 117 patients, from January 2005 to December 2015 in a University-affiliated hospital, Seoul, Korea. Diagnosed as one of two brain diseases such as meningioma and cysts SNR for each patient's image of brain MRI were calculated by using Image J. Differences of SNR among two brain diseases were tested by SPSS Statistics21 ANOVA test for there was statistical significance (p < 0.05). We have analysis socio-demographical variables, SNR according to sequence disease, 95% confidence according to SNR of sequence and difference in a mean of SNR. Meningioma results, with the quality of distributions in the order of T1CE, T2 and T1, FLAIR. Cysts results, with the quality of distributions in the order of T2 and T1, T1CE and FLAIR. SNR of MRI sequences of the brain would be useful to classify disease. Therefore, this study will contribute to evaluate brain diseases, and be a fundamental to enhancing the accuracy of CAD development.

• Journal of Korea Water Resources Association
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• v.54 no.spc1
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• pp.1071-1081
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• 2021

In addition to the current quality control procedures for the weather observation performed by the Korea Meteorological Administration (KMA), this study proposes quality inspection standards for Internet of Things (IoT) urban weather observed data based on machine learning that can be used in smart cities of the future. To this end, in order to confirm whether the standards currently set based on ASOS (Automated Synoptic Observing System) and AWS (Automatic Weather System) are suitable for urban weather, usability was verified based on SKT AWS data installed in Seoul, and a machine learning-based quality control algorithm was finally proposed in consideration of the IoT's own data's features. As for the quality control algorithm, missing value test, value pattern test, sufficient data test, statistical range abnormality test, time value abnormality test, spatial value abnormality test were performed first. After that, physical limit test, stage test, climate range test, and internal consistency test, which are QC for suggested by the KMA, were performed. To verify the proposed algorithm, it was applied to the actual IoT urban weather observed data to the weather station located in Songdo, Incheon. Through this, it is possible to identify defects that IoT devices can have that could not be identified by the existing KMA's QC and a quality control algorithm for IoT weather observation devices to be installed in smart cities of future is proposed.