• The Journal of the Korea institute of electronic communication sciences
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• v.11 no.4
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• pp.421-426
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• 2016

Fluid is normally used so that certain drug can be administered to patients for certain period of time. There are many incidents in which patients or guardians need to call upon medical staff after estimating the time of fluid injection termination. In case fluid injection is terminated during certain period such as sleeping time or others, it may cause more fatigue for either patients or guardians. Also, it may lead to ineffective work as medical staff needs to monitor the quantity of fluid several times in order to check the time of fluid injection termination. Therefore, the purpose of this study is to propose LBS system combined of minimum equipment and active RFID to monitor the level of fluid in order to solve abovementioned problems. Also, it is expected to enhance the quality of medical service with service in which real-time monitoring of fluid quantity and patient location is conducted to provide accurate information to either patients, guardians, or medical staff(nurse) so that medical staff can locate and see patients at the time of fluid injection termination.

• Journal of Korean Tunnelling and Underground Space Association
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• v.11 no.4
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• pp.361-371
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• 2009

Resistivity tomography is very effective geophysical method to find out the resistivity distribution and its change in time around a tunnel. Thus, the resistivity tomogram can provide helpful information which is necessary for the effective maintenance of the tunnel. However, an air filled tunnel severely distorts tomography data, especially when the current or potential electrode is placed near the tunnel. Moreover, the distortion can often lead to misinterpretation of tomography monitoring data. To solve these problem, we developed a resistivity modeling and time-lapse inversion program which include a tunnel. In this study, using the developed program we assured that the inversion including a tunnel gives much more accurate image around a tunnel, compared with the conventional tomogram where the tunnel is not included. We also confirmed that the time-lapse inversion of resistivity monitoring data defines well resistivity changed areas around a tunnel in time.

• Journal of Intelligence and Information Systems
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• v.24 no.2
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• pp.243-264
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• 2018

Although the worldwide battery market is recently spurring the development of lithium secondary battery, lead acid batteries (rechargeable batteries) which have good-performance and can be reused are consumed in a wide range of industry fields. However, lead-acid batteries have a serious problem in that deterioration of a battery makes progress quickly in the presence of that degradation of only one cell among several cells which is packed in a battery begins. To overcome this problem, previous researches have attempted to identify the mechanism of deterioration of a battery in many ways. However, most of previous researches have used data obtained in a laboratory to analyze the mechanism of deterioration of a battery but not used data obtained in a real world. The usage of real data can increase the feasibility and the applicability of the findings of a research. Therefore, this study aims to develop a model which predicts the battery deterioration using data obtained in real world. To this end, we collected data which presents change of battery state by attaching sensors enabling to monitor the battery condition in real time to dozens of golf carts operated in the real golf field. As a result, total 16,883 samples were obtained. And then, we developed a model which predicts a precursor phenomenon representing deterioration of a battery by analyzing the data collected from the sensors using machine learning techniques. As initial independent variables, we used 1) inbound time of a cart, 2) outbound time of a cart, 3) duration(from outbound time to charge time), 4) charge amount, 5) used amount, 6) charge efficiency, 7) lowest temperature of battery cell 1 to 6, 8) lowest voltage of battery cell 1 to 6, 9) highest voltage of battery cell 1 to 6, 10) voltage of battery cell 1 to 6 at the beginning of operation, 11) voltage of battery cell 1 to 6 at the end of charge, 12) used amount of battery cell 1 to 6 during operation, 13) used amount of battery during operation(Max-Min), 14) duration of battery use, and 15) highest current during operation. Since the values of the independent variables, lowest temperature of battery cell 1 to 6, lowest voltage of battery cell 1 to 6, highest voltage of battery cell 1 to 6, voltage of battery cell 1 to 6 at the beginning of operation, voltage of battery cell 1 to 6 at the end of charge, and used amount of battery cell 1 to 6 during operation are similar to that of each battery cell, we conducted principal component analysis using verimax orthogonal rotation in order to mitigate the multiple collinearity problem. According to the results, we made new variables by averaging the values of independent variables clustered together, and used them as final independent variables instead of origin variables, thereby reducing the dimension. We used decision tree, logistic regression, Bayesian network as algorithms for building prediction models. And also, we built prediction models using the bagging of each of them, the boosting of each of them, and RandomForest. Experimental results show that the prediction model using the bagging of decision tree yields the best accuracy of 89.3923%. This study has some limitations in that the additional variables which affect the deterioration of battery such as weather (temperature, humidity) and driving habits, did not considered, therefore, we would like to consider the them in the future research. However, the battery deterioration prediction model proposed in the present study is expected to enable effective and efficient management of battery used in the real filed by dramatically and to reduce the cost caused by not detecting battery deterioration accordingly.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.2
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• pp.159-168
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• 2020

Current residential electricity rates, which are charged regardless of consumption patterns, have a problem of restricting consumer choice. In order to improve the problem, the Korea government started a demonstration project based on Time-Of-Use(TOU) pricing from September 2019. However, the analysis of its effect is still limited. This study analyzed the changes and limitations of TOU pricing compared to the current progressive pricing. The result showed that the high rate payer's bill decreased by up to 33.8 % while the low rate payer's bill increased by up to 117.7 %. This can lead to the problem of accepting electricity rates from a social point of view. In this study, TOU pricing based on progressive pricing was proposed to overcome the problem. The results presented the rate changes depending on the power consumption patterns while decreasing the average rate change from 32 % to -1.9 %. It means that the proposed pricing can support the TOU effect while maintaining the framework of the existing progressive pricing.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38B no.8
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• pp.679-686
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• 2013

Power efficiency becomes more important in wireless LANs as the mobile stations send more data with limited batteries. It has been known that the IEEE 802.11 PSM is not efficient in high load networks: AP cannot deliver buffered packets to a PS station immediately and it can lead the station to stay in active state quite long and result in energy waste. Moreover, it is inefficient that only one data frame is retrieved by a PS-POLL frame. In this paper, we propose a time slotted scheme to enhance the PSM, in which a mobile station can reserve time slots to receive data frames. Our mechanism can reduce collisions by reservation and decrease the channel occupancy by transmitting multiple data frames via one PS-POLL. The analytic model and simulation results show that proposed scheme reduces power consumption significantly and enhances the performance of PSM.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.6B
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• pp.538-547
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• 2004

Optical Burst Switched (OBS) networks usually employ one-way reservation by sending a burst control packet (BCP) with a specific offset time, before transmitting each data burst frame (BDF). Therefore, The quality of service may be degraded because contentions may lead to loss of BDFs. Especially, this phenomenon becomes more serious when burst size is longer. This necessitates an effective method of prevention to avoid burst collision in nodes. OBS networks can employ several methods to avoid such burst losses. One is that burst size is cut short to reduce burst loss probability during scheduling time. In this paper, we evaluate the burst generation and transmission using Sub-Carrier Multiplexting (SCM) in OBS networks. We propose an appropriate burst assembly architecture and transmission scheme based on SCM in OBS networks. The performance of SCM in OBS networks is examined in terms of number of Sub-Carriers per wavelength, burst loss probability, throughput, and total bandwidth of an optical fiber.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.1
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• pp.171-179
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• 2022

This paper introduces a monitoring and tracking system for corona19 confirmed patients based on the collected data by installing a device that can manage the access list at the entrance to each building on the campus. The existing QR-based electronic access list can't measure the temperature of the person entering the building and it is inconvenient that members have to scan their QR codes with a smartphone. In addition, when the state manages information about confirmed patients and contacts on campus, it is not easy for members to quickly share and track information. These could lead to cases where a person is in close contact with an infected person developing another patient. Therefore, this paper introduces a device using face recognition library and a temperature sensor installed at the entrance of each building on the campus, enabling the administrator to monitor the access status and quickly track members of each building in real-time.

• Management & Information Systems Review
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• v.31 no.4
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• pp.287-307
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• 2012

We empirically examine the price discovery dynamics among the VKOSPI, the KOSPI200 spot, and the KOSPI200 futures markets. The analysis employs the vector-autoregression, Granger causality, impulse response function, and variance decomposition using both daily data from 2009. 04. 13 to 2011. 12. 30 and 1 minute data from the bull market, bear market, and the flat period. The main results are as follows; First, the lead lag relationships between KOSPI200 spot(futures) yield VKOSPI returns could not be found from the daily data analysis. But KOSPI200 spot(futures) have a predictive power for VKOSPI from 1 minute data. Especially KOSPI200 spot(futures) and VKOSPI show the bi-directional effects to each other during the return rising period Second, We chose the VAR(1) the model in daily data but adopt the VAR(3) model in the one minute data to determine the lead lag time. We know that there is predictability during the very short period Third, Spot returns and futures returns makes no difference in daily data results. According to the one minite data results, VKOSPI returns have a predictive power for KOSPI200 spot return, but have no predictive power for KOSPI200 futures return.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.58 no.2
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• pp.136-141
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• 2009

An AC generator is an important components in producing a electric power and so it requires highly reliable protection relays to minimize the possibility of demage occurring under fault conditions. Conventionally, a DFT based RDR has been used for protecting the generator stator winding. However, when DFTs based on Fourier analysis are used, it has been pointed out that defects can occur during the process of transforming a time domain signal into a frequency domain one which can lead to loss of time domain information. This paper proposes the internal fault detection and fault type discrimination for the stator winding by applying the detailed coefficients by Daubechies Wavelet Transform to overcome the defects in the DFT process. For the case studies reported in the paper, a model system was established for the simulations utilizing the ATP, and this verified the effectiveness of the proposed technique through various off-line tests carried out on the collected data. The propose method is shown to be able to rapidly identify internal fault and did not operate a miss-operation for all the external fault tested.

• Transactions on Electrical and Electronic Materials
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• v.6 no.4
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• pp.135-139
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• 2005

In this paper, negative SU-8 photoresist processed at low temperature is characterized in terms of delamination. Based on a $3^3$ factorial designed experiment, 27 samples are fabricated, and the degree of delamination is measured for each. In addition, nine samples are fabricated for the purpose of verification. Employing the. neural network modeling technique, a process model is established, and response surfaces are generated to investigate degree of delamination associated with three process parameters: post exposure bake (PEB) temperature, PEB time, and exposure energy. From the response surfaces generated, two significant parameters associated with delamination are identified, and their effects on delamination are analyzed. Higher PEB temperature at a fixed PEB time results in a greater degree of delamination. In addition, a higher dose of exposure energy lowers the temperature at which the delamination begins and also results in a larger degree of delamination. These results identify acceptable ranges of the three process variables to avoid delamination of SU-8 film, which in turn might lead to potential defects in MEMS device fabrication.