• Journal of Food Hygiene and Safety
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• v.32 no.2
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• pp.83-88
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• 2017

We introduced disposable amperometric immunosensors for the detection of Sildenafil and Vardenafil (SDF/VDF) based on screen printed carbon electrodes. The developed immunosensors were used as a non-competitive sandwich-type enzyme immunoassay with a horseradish peroxidase label. The sensors were constructed on screen printed carbon electrodes by the simple electrochemical deposition of a reduced graphene oxide and chitosan (ErGO-CS) composite. To evaluate the sensing chemistry and optimize the sensor characteristics, a series of electrochemical experiments were carried out including electrochemical impedance spectroscopy, cyclic voltammetry and amperometry. The sensors showed a linear response to SDF/VDF concentrations in a range from 100 pg/mL to 300 ng/mL. The lower detection limit was calculated to be 55 pg/mL, the sensitivity was calculated to be $1.02{\mu}Ang/mL/cm^2$, and the sensor performance exhibited good reproducibility with a relative standard deviation (RSD) of 7.1%. The proposed sensing chemistry strategy and the sensor format can be used as a simple, cost-effective, and feasible method for the in-field analysis of SDF/VDF in functional or health supplement food samples.

• Journal of KIISE:Databases
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• v.36 no.6
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• pp.476-485
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• 2009

In sensor networks, many methods have been proposed to process in-network aggregation effectively. Unlike general aggregation queries, skyline query processing compares multi-dimensional data for the result. Therefore, it is very difficult to process the skyline queries in sensor networks. It is important to filter unnecessary data for energy-efficient skyline query processing. Existing approach like MFTAC restricts unnecessary data transitions by deploying filters to whole sensors. However, network lifetime is reduced by energy consumption for many false positive data and filters transmission. In this paper, we propose a bottom up filtering-based skyline query processing algorithm of in-network for reducing energy consumption by filters transmission and a PBFiltering technique for improving performance of filtering. The proposed algorithm creates the skyline filter table (SFT) in the data gathering process which sends from sensor nodes to the base station and filters out unnecessary transmissions using it. The experimental results show that our algorithm reduces false positives and improves the network lifetime over the existing method.

• KIPS Transactions on Software and Data Engineering
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• v.1 no.2
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• pp.127-136
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• 2012

Many research of hand gesture recognition based on vision system have been conducted which enable user operate various electronic devices more easily. 3D position calculation and meaningful gesture classification from similar gestures should be executed to recognize hand gesture accurately. A simple and cost effective method of 3D position calculation and gesture spotting (a task to recognize meaningful gesture from other similar meaningless gestures) is described in this paper. 3D position is achieved by calculation of two cameras relative position through pan/tilt module and a marker regardless with the placed position. Fuzzy garbage model is proposed to provide a variable reference value to decide whether the user gesture is the command gesture or not. The reference is achieved from fuzzy command gesture model and fuzzy garbage model which returns the score that shows the degree of belonging to command gesture and garbage gesture respectively. Two-stage user adaptation is proposed that off-line (batch) adaptation for inter-personal difference and on-line (incremental) adaptation for intra-difference to enhance the performance. Experiment is conducted for 5 different users. The recognition rate of command (discriminate command gesture) is more than 95% when only one command like meaningless gesture exists and more than 85% when the command is mixed with many other similar gestures.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.5
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• pp.349-361
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• 2021

With the development of technology and the advancement of weather forecasting models and prediction methods, higher performance weather forecasting software has been developed, and more precise and accurate weather forecasting is possible by performing software using supercomputers. In this paper, the weather forecast model used by six major countries is investigated and its characteristics are analyzed, and the Korea Meteorological Administration currently uses it in collaboration with the UK Meteorological Administration since 2012 and explains the GloSea However, the existing GloSea was conducted only on the Meteorological Administration supercomputer, making it difficult for various researchers to perform detailed research by specialized field. Therefore, this paper aims to establish a standard experimental environment in which the low-resolution version based on GloSea6 currently used in Korea can be used in local systems and test it to present the localization of low-resolution GloSea6 that can be performed in the laboratory environment. In other words, in this paper, the local portability of low-resolution Globe6 is verified by establishing a basic architecture consisting of a user terminal-calculation server-repository server and performing execution tests of the software.

• Journal of the Korean Applied Science and Technology
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• v.35 no.4
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• pp.1260-1268
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• 2018

To improve fuel performance and specific characteristics of long storage and moving through fuel systems additives should be added in kerosene type aviation turbine fuel (AVTUR) such as antioxidant, fuel system icing inhibitor (FSII), electric conductivity improvers and so on. The dosage of additives has to be analyzed qualitatively and quantitatively due to inspect the quality of abnormal fuel and distinguish other petroleum products. Multi-dimensional GC-MS (MDGC-MS) with Deans switching technique are applied the determination of antioxidant and FSII, which are added with AVTUR containing complex mixture of hydrocarbons. Antioxidant and FSII in the range of 2.5-20 mg/L was quantitatively and qualitatively analyzed using MDGC-MS and the detection limit was about twice as low as that of the 1-dimensional GC-MS results. The method in this study has been higher peak resolution compared with GC-MS and could be simultaneously analyzed different two additives without sample pre-treatment.

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.39 no.1
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• pp.165-174
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• 2019

As a nonstationarity is observed in hydrological data, various studies on nonstationary frequency analysis for hydraulic structure design have been actively conducted. Although the inherent diversity in the atmosphere-ocean system is known to be related to the nonstationary phenomena, a nonstationary frequency analysis is generally performed based on the linear trend. In this study, a nonstationary frequency analysis was performed using climate indices as covariates to consider the climate variability and the long-term trend of the extreme rainfall. For 11 weather stations where the trend was detected, the long-term trend within the annual maximum rainfall data was extracted using the ensemble empirical mode decomposition. Then the correlation between the extracted data and various climate indices was analyzed. As a result, autumn-averaged AMM, autumn-averaged AMO, and summer-averaged NINO4 in the previous year significantly influenced the long-term trend of the annual maximum rainfall data at almost all stations. The selected seasonal climate indices were applied to the generalized extreme value (GEV) model and the best model was selected using the AIC. Using the model diagnosis for the selected model and the nonstationary GEV model with the linear trend, we identified that the selected model could compensate the underestimation of the rainfall quantiles.

• Journal of IKEEE
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• v.23 no.2
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• pp.438-447
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• 2019

As the IoT-based hyper-connected society grows, public-key cryptosystem such as RSA is frequently used for encryption, authentication, and digital signature. Public-key cryptosystem use very large (safe) prime numbers to ensure security against malicious attacks. Even though the performance of the device has greatly improved, the generation of a large (safe)prime is time-consuming or memory-intensive. In this paper, we propose ET-MR and ET-MR-MR using Euler sieve so it runs faster while using less memory. We present a running time prediction model by probabilistic analysis and compare time and memory of our method with conventional methods. Experimental results show that the difference between the expected running time and the measured running time is less than 4%. In addition, the fastest running time of ET-MR is 36% faster than that of TD-MR, 8.5% faster than that of DT-MR and the fastest running time of ET-MR-MR is 65.3% faster than that of TD-MR-MR and similar to that of DT-MR-MR. When k=12,381, the memory usage of ET-MR is 2.7 times more than that of DT-MR but 98.5% less than that of TD-MR and when k=65,536, the memory usage of ET-MR-MR is 98.48% less than that of TD-MR-MR and 92.8% less than that of DT-MR-MR.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.12 no.4
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• pp.406-412
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• 2019

In this paper, we propose two algorithms for classifying services with similar delay characteristics into three classes and allocating radio resources according to priority in LTE-A system where H2H and M2M services coexist. The first is to allocate resources from the higher priority class to the lower priority class, and each class gives priority to H2H over M2M, and the other is to give priority to H2H regardless of delay characteristics except for the class with the highest priority. The RA success probability was analyzed according to the access rate(${\alpha}$) of M2M devices in each class. In comparison with the conventional systems, it was improved from 0.5 to 0.52 for ${\alpha}_{2M}=0.05$ in two classes. In the three classes, the success probability was slightly increased from 0.5 to 0.57 for ${\alpha}_{2M}={\alpha}_{3M}=1$ and from 0.5 to 0.58 for ${\alpha}_{2M}=0.5$ and ${\alpha}_{3M}=0.1$. Although 6 services are considered in the proposed scheme, the RA success probability is almost similar to the previous scheme because the average arrival rate of H2H of each class is set to the same.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.48-57
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• 2019

The purpose of this study is to understand the intention of the inquirer from the single text type question in Goal-oriented dialogue. Goal-Oriented Dialogue system means a dialogue system that satisfies the user's specific needs via text or voice. The intention analysis process is a step of analysing the user's intention of inquiry prior to the answer generation, and has a great influence on the performance of the entire Goal-Oriented Dialogue system. The proposed model was used for a daily chemical products domain and Korean text data related to the domain was used. The analysis is divided into a speech-act which means independent on a specific field concept-sequence and which means depend on a specific field. We propose a classification method using the word embedding model and the CNN as a method for analyzing speech-act and concept-sequence. The semantic information of the word is abstracted through the word embedding model, and concept-sequence and speech-act classification are performed through the CNN based on the semantic information of the abstract word.