• Nuclear Engineering and Technology
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• v.53 no.12
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• pp.3944-3951
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• 2021

Several reasons such as no free lunch theorem indicate that there is not a universal Feature selection (FS) technique that outperforms other ones. Moreover, some approaches such as using synthetic dataset, in presence of large number of FS techniques, are very tedious and time consuming task. In this study to tackle the issue of dependency of estimation accuracy on the selected FS technique, a methodology based on the heterogeneous ensemble is proposed. The performance of the major learning algorithms of neural network (i.e. the FFNN-BR, the FFNN-LM) in combination with the diverse FS techniques (i.e. the NCA, the F-test, the Kendall's tau, the Pearson, the Spearman, and the Relief) and different combination techniques of the heterogeneous ensemble (i.e. the Min, the Median, the Arithmetic mean, and the Geometric mean) are considered. The target parameters/transients of Bushehr nuclear power plant (BNPP) are examined as the case study. The results show that the Min combination technique gives the more accurate estimation. Therefore, if the number of FS techniques is m and the number of learning algorithms is n, by the heterogeneous ensemble, the search space for acceptable estimation of the target parameters may be reduced from n × m to n × 1. The proposed methodology gives a simple and practical approach for more reliable and more accurate estimation of the target parameters compared to the methods such as the use of synthetic dataset or trial and error methods.

• Journal of Ecology and Environment
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• v.46 no.2
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• pp.126-135
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• 2022

Background: Pollinators are important ecological elements due to their role in the maintenance of ecosystem health, wild plant reproduction, crop production and food security. The pollinator-plant interaction supports the preservation of plant and animal populations and it also improves the yield in pollination dependent crops. Having knowledge about the plant-pollinator interaction is necessary for development of pesticide risk assessment of pollinators and conservation of endangering species. Results: Traditional methods to discover the relatedness of insects and plants are based on tracing the visiting pollinators by field observations as well as palynology. These methods are time-consuming and needs expert taxonomists to identify different groups of pollinators such as insects or identify flowering plants through palynology. With pace of technology, using molecular methods become popular in identification and classification of organisms. DNA metabarcoding, which is the combination of DNA barcoding and high throughput sequencing, can be applied as an alternative method in identification of mixed origin environmental samples such as pollen loads attached to the body of insects and has been used in DNA-based discovery of plant-pollinator relationship. Conclusions: DNA metabarcoding is practical for plant-pollinator studies, however, lack of reference sequence in online databases, taxonomic resolution, universality of primers are the most crucial limitations. Using multiple molecular markers is preferable due to the limitations of developed universal primers, which improves taxa richness and taxonomic resolution of the studied community.

• International Journal of Computer Science & Network Security
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• v.22 no.12
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• pp.125-131
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• 2022

The diversity and complexity of criminal, administrative and civil cases resolved by the courts makes it difficult to develop universal automated tools for the analysis and evaluation of justice. However, big data generated in the scope of justice gives hope that this problem will be resolved as soon as possible. The big data applying makes it possible to identify typical options for resolving cases, form detailed rules for the individualization of a court decision, and correlate these rules with an abstract provisions of law. This approach allows us to somewhat overcome the contradiction between the abstract and the concrete in law, to automate the analysis of justice and to model e-justice for scientific and practical purposes. The article presents the results of using dimension reduction, SHAP value, and p-value to identify, analyze and evaluate the individualization of justice and the differentiation of legal regulation. Processing and analysis of arrays of court decisions by computational methods make it possible to identify the typical views of courts on questions of fact and questions of law. This knowledge, obtained automatically, is promising for the scientific study of justice issues, the improvement of the prescriptions of the law and the probabilistic prediction of a court decision with a known set of facts.

• Journal of Positioning, Navigation, and Timing
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• v.12 no.2
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• pp.201-209
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• 2023

Time comparison techniques are required for generating and keeping Coordinated Universal Time (UTC) and to distribute standard clocks. These techniques play an important role in various fields, including science, finance, military, and communication. Among these techniques, Two-Way Satellite Time and Frequency Transfer (TWSTFT) ensures a relatively high accuracy, with a time comparison accuracy at a nanosecond level. However, TWSTFT systems have some limitations, such as the dependency on extra network links. In this paper, we propose an improved method for TWSTFT system operation and design a message structure for the suggestion. Additionally, we estimate the data rate and redundancy for the new TWSTFT signal with the designed message structure.

• Journal of Korea Multimedia Society
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• v.1 no.2
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• pp.249-255
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• 1998

This paper analyzes the impact of Call Setup Time on UPT performance based on the AIN platform. Call Setup Time is used as the performance parameter. In implementing UPT based on the AIN platform, the geographical location of VLR affects network performance. In order to find an optimum location of VLR among three different types of structures, i.e. VLR is located close to Service Switching Point and Cell Site Controller and located at Service Control Point, each Call Setup Time on proposed time delay model is calculated and compared. Network performance is analyzed by changing the number of STP in No.7 signaling network in UPT and the utilization ratio, $\rho$, for SSP, STP and SCP.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.12
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• pp.2730-2736
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• 2010

Recently, various networks have been introduced in the car of the internal and external sides. These have been integrated by one HMI(Human Machine Interface) to control devices of each network and provide information service. The existing vehicle navigation system, providing GPS based vehicle positioning service, has been included to these integrated networks as a default option. The GPS has been used to the most universal device to provide position information by using satellites' signal. But It is impossible to provide the position information when the GPS can't receive the satellites' signal in the area of tunnel, urban canyon, or forest canopy. Thus, this paper propose and implement the method of measuring vehicle position by using the sensing data of internal CAN network and external Wi-Fi network of the integrated car navigation circumstances when the GPS doesn't work normally. The results obtained by implementation shows the proposed method works well by map matching.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.450-450
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• 2021

기후변화 보고서에 따르면 집중 호우의 강도 및 빈도 증가가 향후 몇 년동안 지속될 것이라 제시하였다. 이러한 집중호우가 빈번히 발생하게 된다면 강우 침식성이 증가하여 표토 침식에 더 취약하게 발생된다. Universal Soil Loss Equation (USLE) 입력 매개 변수 중 하나인 강우침식능인자는 토양 유실을 예측할때 강우 강도의 미치는 영향을 제시하는 인자이다. 선행 연구에서 USLE 방법을 사용하여 강우침식능인자를 산정하였지만, 60분 단위 강우자료를 이용하였기 때문에 정확한 30분 최대 강우강도 산정을 고려하지 못하는 한계점이 있다. 본 연구의 목적은 강우침식능인자를 이전의 진행된 방법보다 더 빠르고 정확하게 예측하는 머신러닝 모델을 개발하며, 총 월별 강우량, 최대 일 강우량 및 최대 시간별 강우량 데이터만 있어도 산정이 가능하도록 하였다. 이를 위해 본 연구에서는 강우침식능인자의 산정 값의 정확도를 높이기 위해 1분 간격 강우 데이터를 사용하며, 최근 강우 패턴을 반영하기 위해서 2013-2019년 자료로 이용했다. 우선, 월별 특성을 파악하기 위해 USLE 계산 방법을 사용하여 월별 강우침식능인자를 산정하였고, 국내 50개 지점을 대상으로 계산된 월별 강우침식능인자를 실측 값으로 정하여, 머신러닝 모델을 통하여 강우침식능인자 예측하도록 학습시켜 분석하였다. 이 연구에 사용된 머신러닝 모델들은 Decision Tree, Random Forest, K-Nearest Neighbors, Gradient Boosting, eXtreme Gradient Boost 및 Deep Neural Network을 이용하였다. 또한, 교차 검증을 통해서 모델 중 Deep Neural Network이 강우침식능인자 예측 정확도가 가장 높게 산정하였다. Deep Neural Network은 Nash-Sutcliffe Efficiency (NSE) 와 Coefficient of determination (R²)의 결과값이 0.87로서 모델의 예측성을 입증하였으며, 검증 모델을 테스트 하기 위해 국내 6개 지점을 무작위로 선별하여 강우침식능인자를 분석하였다. 본 연구 결과에서 나온 Deep Neural Network을 이용하면, 훨씬 적은 노력과 시간으로 원하는 지점에서 월별 강우침식능인자를 예측할 수 있으며, 한국 강우 패턴을 효율적으로 분석 할 수 있을 것이라 판단된다. 이를 통해 향후 토양 침식 위험을 지표화하는 것뿐만 아니라 토양 보전 계획을 수립할 수 있으며, 위험 지역을 우선적으로 선별하고 제시하는데 유용하게 사용 될 것이라 사료된다.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.05a
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• pp.237-242
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• 2008

A number of wireless technologies have been implemented, but each technology has its limitation in terms of coverage and bandwidth. WLAN and 3G cellular network has emerged to be a complementary platform for wireless data communications. However, the mobility of roaming terminals in heterogeneous networks poses several risks. To maintain secure communications in universal roaming, the effective authentication must be implemented. The focus of this paper is on analysis of authentication architecture involved in integrated WLAN/3G networks.

• Journal of electromagnetic engineering and science
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• v.4 no.4
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• pp.150-155
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• 2004

Universal design equations are presented for the H-plane T-junction power divider with a circular conducting post in a rectangular waveguide. For a given operating frequency and power split ratio, the post offset from the T-junction center line, the distance between the post and the waveguide wall, and the post diameter can be adjusted to obtain a minimum reflection at the input waveguide. Optimum values of the post offset are given in terms of the normalized frequency and the power split ratio. Corresponding values of the post diameter and the distance of the post from the waveguide wall are given in terms of the normalized frequency and the post offset.

• Journal of electromagnetic engineering and science
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• v.18 no.4
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• pp.254-260
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• 2018

In this study, we suggest an emulator for generating multiple heterogeneous interference signals in the Korean radio frequency identification/ubiquitous sensor network (RFID/USN) frequency band. The proposed emulator uses only one universal software radio peripheral to generate multiple heterogeneous interference signals more economically. Moreover, the physical and media access control parameters can be adjusted in real time using the LabVIEW program, thereby making it possible to create various time-varying interference environments easily. As an example showing the capability of the proposed emulator, multiple interference signals consisting of a frequency-hopping RFID signal and two LoRa signals with different spreading factors were generated. The generated signals were confirmed in both frequency and time domains. From the experimental results, we verified that our emulator could successfully generate multiple heterogeneous interference signals with different frequency and time domain characteristics.