• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.1
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• pp.1-10
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• 1985

Solar energy has its advantages not to be interruped by anything, which is wing to not only limitlessness in its source but shortness in its wave. Availing of tha advantages, we can look forword to vast allication. This study whose aim is to raise the effectuality of it by means of chasing the source correctly, which is to be acheved by the circularty of sensor. The consequence has been gained by two sensors is amplified and transfered to TTL leveland becomes "INPUT DATA" of INTE 8080CPU. The INTEL 8080CPU whose system is machinated to give cotrol pulse to moter driving circuit has the source and the sensors placed correctly on the basis of the data. DC motor taskes the advantage not to be in need of UP/DOWN counter, which is defferent from stepping motor. The system is composed of light detector, A/C converter, INPUT Interface, INTEL 8080 CPU, OUTPUT Interface, notor driving circiut. We can give correct chase to light experimentally as far as an error is the space of 1.2.ce of 1.2.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.4
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• pp.904-914
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• 2017

For efficient energy usage, the concept of demand response has been emerged and thereby Open Automated D emand Response(OpenADR) protocol is developed as a standard protocol to provide automated demand response. There have been emerging trends on the demand response services using the Internet of Things(IoT) for smart h ome energy management. In this smart home energy IoT environment, a lightweight protocol is needed rather tha n the existing HTTP/ XML based OpenADR protocol for demand response services since many small devices wi ll be interconnected. In this paper, we propose a lightweight OpenADR protocol based on CoAP protocol for pro viding demand response service in Smart Energy IoT environment, implement the proposed CoAP-based protocol, and analyzed the performance compared to existing HTTP/ XML-based OpenADR 2.0b protocol.

• Journal of Ginseng Research
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• v.34 no.1
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• pp.51-58
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• 2010

This study compared the effects of black, white, and red ginseng extracts (WGE, RGE, BGE, 200 mg/kg, p.o.) on learning and memory deficits associated with scopolamine treatment (SCOP, 2 mg/kg, i.p.). Tacrine (THA, 10 mg/kg, p.o.) was used as a positive control. Ginseng significantly reversed SCOP-induced memory impairment in the passiveavoidance test and also reduced escape latency in training trials of the Morris water maze test. The increased acetylcholinesterase (AChE) activity produced by SCOP was significantly inhibited by WGE and RGE (p<0.001). SCOP administration had no effect on choline acetyltransferase (ChAT) activity, but RGE and BGE significantly increased ChAT activity (p<0.05). SCOP administration increased oxidative damage in the brain. Treatment of amnesic mice with ginseng extracts decreased malondialdehyde (MDA) levels and restored superoxide dismutase (SOD) and catalase (CAT) activity to control levels. These results suggest that black ginseng enhances cognitive activity by regulation of cholinergic enzymes and antioxidant systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.8 no.1
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• pp.45-50
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• 2015

In this paper, we confirm the effective adaptive algorithm for tha active noise contorl (ANC) though the performance comparison between adaptive algorithms. Generally, the normalized least mean square (NLMS) algorithm has been widely used for an adaptive algorithm thanks to its simplicity and having a fast convergence speed. However, the convergence performance of the NLMS algorithms is often deteriorated by colored input signals. To overcome this problem, the affine pojection (AP) algorithm that updates the weight vector based on a number of recent input vectors can be used for allowing a higher convergence speed than the NLMS algorithm, but it is computationally complex. Thus, the proper algorithm were determined by the comparison between NLMS and AP algorithms regarding as the convergence performance and complexity. Simulation results confirmed that the noise reduction performance of NLMS algorithm was comparable to AP algorithm with low complexity. Therefore the NLMS algorithm is more effective for ANC system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.31 no.3A
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• pp.282-290
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• 2006

In this paper, we propose an enhanced Timing Estimator algorithm for 2.45GHz LR-WPAN receiver. Because an expensive and highly efficient oscillator can't be used for low-cost implementation, a Timing Estimator algorithm having stable operation in the channel environment with center frequency tolerance of 80 ppm is required. To enhance the robustness to frequency offset and the stability of receiver performance, multiple delay differential filter is adopted. By utilizing the characteristic that the correlation result between the output signal of Multiple delay differential filter and reference signal is restricted on the In-phase part of the correlator output, a coherent detection scheme instead of the typical noncoherent one is adopted for Timing Estimator. The application of the coherent detection scheme is suitable for LR-WPAN receiver aimed at low-cost, low-power, and low-complexity, since it can remove performance degradation due to squaring loss of I/Q squaring operation and decrease implementation complexity. Computer simulation results show that the proposed algorithm achieved performance improvement compared with the differential detection-based noncoherent scheme by 2dB in average.

• Journal of the Korean Institute of Gas
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• v.23 no.5
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• pp.52-58
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• 2019

In this study, we have developed a forecasting model for city- gas acceptance. City-gas corporations have to report about city-gas sale volume next year to KOGAS. So it is a important thing to them. Factors influenced city-gas have differences corresponding to usage classification, however, in city-gas acceptence, it is hard to classificate. So we have considered tha outside temperature as factor that influence regardless of usage classification and the model development was carried out. ARIMA, one of the traditional time series analysis, and LSTM, a deep running technique, were used to construct forecasting models, and various Ensemble techniques were used to minimize the disadvantages of these two methods.Experiments and validation were conducted using data from JB Corp. from 2008 to 2018 for 11 years.The average of the error rate of the daily forecast was 0.48% for Ensemble LSTM, the average of the error rate of the monthly forecast was 2.46% for Ensemble LSTM, And the absolute value of the error rate is 5.24% for Ensemble LSTM.

• Earthquakes and Structures
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• v.10 no.3
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• pp.523-538
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• 2016

Besides their spiritual significance, minarets are humanity's cultural heritage to the future generations due to their historical and architectural attraction. Currently, many historical masonry minarets are damaged and destroyed due to several reasons such as earthquakes and wind. Therefore, safety of these religiously significant buildings needs to be thoroughly investigated. The utmost care must be taken into account while investigating these structures. Our study investigated earthquake behavior of historical masonry minaret of Haci Mahmut Mosque. Destructive and non-destructive tests were carried out to determine earthquake safety of this structure. Brick-stone masonry material properties of structure were determined by accomplishing ultrasonic wave velocity, Schmidt Hammer, uniaxial compression (UAC) and indirect tension (Brazilian) tests. Determined material properties were used in the finite element analysis of the structure. To validate the numerical analysis, Operational Modal Analysis was applied to the structure and dynamic characteristics of the structure were determined. To this end, accelerometers were placed on the structure and vibrations due to environmental effects were followed. Finite element model of the minaret was updated using dynamic characteristics of the structure and the realistic numerical model of the structure was obtained. This numerical model was solved by using earthquake records of Turkey with time history analysis (THA) and the realistic earthquake behavior of the structure was introduced.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.1
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• pp.109-123
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• 2019

Recently, As the desire of consumer gets complexed and demanding, business environment is they are rapidly changing to customer-oriented ones. In order to survive in an age of fierce competition with competitor encompassing changing and customer's needs of consumer company emphasizes market orientation to have a sustainability. It is necessary not only satisfy consumer but also to provide customer delight. We want to see if customer's loyalty can be increased by experiencing C/S and C/D. First, customer's loyalty influences repurchase intention after experiencing customer's satisfaction and customer's delight. Second, customer's satisfaction is influenced by customer's satisfaction level. Especially Joy is one of the most important factor affecting customers delight. Third, customer's loyalty is one of the most important factor affecting customer's satisfaction. Finally, through this study, it was found tha customer's satisfaction and customer's satisfaction improve the repurchase relationship which is crucial from customer's loyalty.

• Proceedings of the Korea Water Resources Association Conference
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• 2023.05a
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• pp.34-34
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• 2023

The Chah-Nimeh reservoirs, which are a sort of natural lakes located in the border of Iran and Afghanistan, are the main drinking and agricultural water resources of Sistan arid region. Considering the occurrence of intense seasonal wind, locally known as levar wind, this study aims to explore the possibility to provide a TSM (Total Suspended Matter) monitoring model of Chah-Nimeh reservoirs using multi-temporal satellite images and in-situ wind speed data. The results show that a strong correlation between TSM concentration and wind speed are present. The developed empirical model indicated high performance in retrieving spatiotemporal distribution of the TSM concentration with R²=0.98 and RMSE=0.92g/m³. Following this observation, we also consider a machine learning-based model to predicts the average TSM using only wind speed. We connect our in-situ wind speed data to the TSM data generated from the inversion of multi-temporal satellite imagery to train a neural network based mode l(Wind2TSM-Net). Examining Wind2TSM-Net model indicates this model can retrieve the TSM accurately utilizing only wind speed (R²=0.88 and RMSE=1.97g/m³). Moreover, this results of this study show tha the TSM concentration can be estimated using only in situ wind speed data independent of the satellite images. Specifically, such model can supply a temporally persistent means of monitoring TSM that is not limited by the temporal resolution of imagery or the cloud cover problem in the optical remote sensing.

• Journal of Korean Society for Atmospheric Environment
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• v.2 no.3
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• pp.57-63
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• 1986

Atmospheric particulate matter (A.P.M.) was collected on quartz fiber filters from March 1985 to May 1986 according to particle size using Andersen high-volume air sampler, and 6 heavy metals (Fe, Mn, Cu, Ni, Zn, Pb) in these particulates were analyzed by atomic absorption spectrophotometry. The arithmetic mean concentration of A.P.M. was 195.57$\mug/m^3$. The arithmetic mean concentrations of 6 metals (Fe, Mn, Cu, Ni, Zn and Pb) were 3385.04, 1451.67, 897.94, 159.68, 127.14 and 59.49 $ng/m^3$ respectively. The order of heavy metals contributing to A.P.M. was as follows: Fe > Zn > Pb > Cu > Mn > Ni. These heavy metals were devided into 3 groups according to their particle size distribution. The contents of heavy metals belonging to the 1st group (Fe, Mn) were increased with the particle size. On the contrary, the content of Pb belonging to the 2nd group (Pb) was increased with the decrease in the particle size. The heavy metal contents in the 3rd group (Ni, Cu, Zn) were lowest in the particle size range of 2.0-3.3 $\mum$ compared with particles larger or smaller tha this range. The seasonal variation of heavy metal concentration were as follows: Fe and Mn contents were highest in spring, but Ni and Pb contents were highest in winter. Statistical analysis showed that there was a significant correlation between A.P.M. and Fe in coarse particles, meanwhile between A.P.M. and Pb in the case of fine particles.