• 한국인터넷방송통신학회논문지
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• 제17권2호
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• pp.211-218
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• 2017

본 연구는 모비우스 플랫폼을 이용하여 IoT 센서 네트워크를 구현하였고 성능을 검증하기 위해 스마트 홈 서비스에 적용 가능한 4종의 Z-Wave 센서를 구현하였다. 모비우스가 제공하는 12가지의 CSF(Common Service Function)은 센서들의 상태 감시를 비롯한 어플리케이션 서비스를 빠른 시간에 구현할 수 있도록 하였다. 표준적인 서비스절차와 프로토콜은 시스템의 설계 과정을 생략할 수 있도록 하였고, 어플리케이션 소프트웨어 개발자, Gateway 개발자 및 센서 개발자들 간의 규약확정을 위한 회의시간, 그리고 의견 조정을 위한 논의 시간을 단축할 수 있도록 하였다. 구현된 센서네트워크를 기반으로 하는 어플리케이션 서비스와 IoT 센서의 구현은 개발일정을 단축시킬 수 있음을 확인하였고, 무엇보다도 시장에서 구매한 상용품을 변경개발 없이 수용이 가능함을 확인하였다. 이러한 신속성과 개방성은 다양한 서비스의 요구에 부응할 수 있도록 하여, 서비스 확대 및 신규 시장 창출에 기여할 수 있을 것으로 기대한다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2003년도 Proceedings of ACRS 2003 ISRS
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• pp.955-958
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• 2003

Nepal is a country of mountains The higher order geodetic points were mostly established on the top of mountains and these points were used for the geodetic network extension. Lower order geodetic control networks were established at different times and used for the surveying and mapping activities of the country.. It has been found that the rate of convergence between north and south borders of Nepal to be 21${\pm}$2 mm each year and the rate translation of Kathmandu to 55${\pm}$3 mm/year to the plates. The most intense deformation in Nepal occurs along the belt of high mountains along its northern border res ulting in a strain contraction rate normal to the Himalayan Arc. This belt is approximately 40 km wide and extends into southern Tibet.( 13). Recently Survey Department of Nepal has lunched a program of strengthening the existing geodetic network of Nepal and re-observed the position of higher order geodetic points by using geodetic GPS receivers to evaluate their position and thus to define the precision of the control points once again. This paper describes the observation procedure and the adjustment results of the existing higher order control network of Nepal established in different time using different types of equipment and techniques; and highlights the observation procedure and the result obtained after the post processing of the GPS observation results. Attempt has been made to give the procedure and identify the methodology for the re observation of existing higher order geodetic points by using GPS receiver and post processing the observed data so that the existing higher order geodetic points are within the given accuracy standard.

• Journal of information and communication convergence engineering
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• 제20권1호
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• Journal of Korea Trade
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• 제25권4호
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• pp.17-36
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• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

• 제어로봇시스템학회논문지
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• 제3권2호
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• pp.204-213
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• 1997

In this paper, an application of fuzzy-neuron reasoning to the control of an activated sludge plant is presented. The activated sludge process is widely used in modern wastewater treatment plants. The operation control of the activated sludge process, however, is difficult due to the following reasons : 1)The complexity of the wastewater components, 2)the change of the wastewater influent, and 3)the adjustment errors in the control process. Because of these reasons, it is difficult to obtain mathematical model that really reflect the relationship between the variables and parameters in the process of wastewater treatment correctively and effectively. In this paper, the activated sludge process(A.S.P.) is modeled by a new fuzzy-neuron network representing nonlinear characteristics. These fuzzy-neurons have fuzzy rules with complementary membership function. Based on the constructed model, graphic simulator on X-window system as a graphic integrated environment is implemented. The efficacy of the proposed control scheme was evaluated and demonstrated by means of the field test.

• 대한전자공학회논문지TC
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• 제42권5호
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• pp.13-22
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• 2005

OFDM(orthogonal frequency division multiplexing) 변조를 이용한 WLAN(wireless local area network) 시스템은 고속 무선 데이터 통신을 위한 대표적 수단으로 전송률의 향상을 위해 활발히 연구되고 있다. 본 논문에서는 WLAN의 정확한 채널 등화와 샘플링 클럭 추적을 위하여 비터비 복호기 출력을 이용한 등화 및 샘플링 클럭 추적 알고리듬을 제안한다. 이 알고리듬은 파일럿 신호를 이용하여 대략의 클럭 주파수 복원과 채널등화를 수행한 후 비터비 복호기의 출력을 다시 부호화하여 등화 및 샘플링 클럭의 추적에 이용하는 알고리듬이다. 제안한 알고리듬의 우수성을 ETSI WLAN 채널 환경에서 컴퓨터 모의실험을 통하여 보였다.

• 한국지능시스템학회논문지
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• 제8권6호
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• pp.12-20
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• 1998

제어 환경의 변화에 강건하게 대처할 수 있는 제어 시스템을 개발하기 위해서, 본 논문에서는 자연계의 면역 시스템과 다층 신경망을 결합한 제어 시스템을 제안한다. 제안한 제어 시스템은 면역 알고리즘을 이용하여 다층 신경망의 가중치를 조절한다. 면역 알고리즘은 초기 방어 단계인 선천성 면역 알고리즘과 적응 단계인 적응 면역 알고리즘으로 구성되어 있다. 과거에 학습한 경험이 있는 환경과 유사한 환경에 대해서 선천성 면역 알고리즘이 동작하고, 학습한 경험이 없는 새로운 제어 환경의 변하에 대해서는 적응 면역 알고리즘이 동작한다. 면역 알고리즘을 이용한 제어 시스템을 로봇 매니퓰레이터의 궤적 추종 제어에 적용하였으며, 컴퓨터 모의 실험을 통해 제어 시스템의 성능을 평가한다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권9호
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• pp.4342-4366
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• 2016

Congestion control in Cluster Wireless Sensor Networks (CWSNs) has drawn widespread attention and research interests. The increasing number of nodes and scale of networks cause more complex congestion control and management. Active Queue Management (AQM) is one of the major congestion control approaches in CWSNs, and Random Early Detection (RED) algorithm is commonly used to achieve high utilization in AQM. However, traditional RED algorithm depends exclusively on source-side control, which is insufficient to maintain efficiency and state stability. Specifically, when congestion occurs, deficiency of feedback will hinder the instability of the system. In this paper, we adopt the Additive-Increase Multiplicative-Decrease (AIMD) adjustment scheme and propose an improved RED algorithm by using neighbor feedback and scheduling scheme. The congestion control model is presented, which is a linear system with a non-linear feedback, and modeled by Lur'e type system. In the context of delayed Lur'e dynamical network, we adopt the concept of cluster synchronization and show that the congestion controlled system is able to achieve cluster synchronization. Sufficient conditions are derived by applying Lyapunov-Krasovskii functionals. Numerical examples are investigated to validate the effectiveness of the congestion control algorithm and the stability of the network.

• 한국유통학회지:유통연구
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• 제4권2호
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• pp.21-39
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• 1999

This study investigates the general applicability of the measurement scale for assessing channel-member performance for the supplier's view that was proposed by Kumar, and Achrol (1992). First, we attempted to examine whether the measurement-scale could be used without any change; the results from the initial data-analysis proposed that the scale needed a certain amount of a revision for further utilization. It seemed that the scale needed some adjustment for being applied to this study; their scale was developed with the data collected from the network of independent dealers handling multiple product items or multiple brands in the U.S. and Canada, while the data of this study were provided by a Korean car manufacturer having a dealer network selling and servicing only its own brand without ownership. Accordingly, we determined that it was necessary to develop a newly finalized performance-measurement scale revising Kumar et al.'s. During the data-analysis of the data resulted in a scale of fifteen items measuring three facets-financial performance, behavioral performance, and competence, each of which consisted of five items respectively. This empirically developed scale looked more valid for the situation of this study than the Kumar, Stern, and Achrol's which was composed of twenty-one items measuring seven facets--three items each.

• 한국측량학회지
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• 제14권2호
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• pp.209-218
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• 1996

본 연구에서는 지적측량기준점의 위치결정에 GPS측량을 실용화하기 위한 방법 도출에 목적을 두고 국내의 일부지역 내 지적삼각점 및 도근점을 대상으로 GPS측량을 수행하고 좌표변환기법과 GPS기선벡터에 의한 2차원 위치해석, 그리고 GPS와 지상측량데이타의 조합에 의한 위치해석을 실시하였다. 그 결과, 기존 지적측량기준망의 점검 에 GPS측량방법이 매우 효과적임을 알 수 있었으며, GPS기선벡터를 이용한 2차원 위치해석방법은 좌표계 변환을 하지 않고도 국내의 좌표체계에서 적용이 가능하였다. 그리고 지적도근점 위치결정과 같은 소규모 지역에서 행하는 측량에는 신속정지측량 또는 이동측량으로 효율성을 높일 수 있을 것으로 기대된다.