• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.9 no.5
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• pp.183-189
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• 2009

Recently, PCS, PDA and mobile devices, such as the proliferation of spread, GPS (Global Positioning System) the use of, the rapid development of wireless network and a regular user even images, audio, video, multimedia data, such as increased use is for. In particular, video data among multimedia data, unlike the moving object, text or image data that contains information about the movements and changes in the space of time, depending on the kinds of changes that have sigongganjeok attributes. Spatial location of objects on the flow of time, changing according to the moving object (Moving Object) of the continuous movement trajectory of the meeting is called, from the user from the database that contains a given query trajectory and data trajectory similar to the finding of similar trajectory Search (Similar Sub-trajectory Retrieval) is called. To search for the trajectory, and these variations, and given the similar trajectory of the user query (Tolerance) in the search for a similar trajectory to approximate data matching (Approximate Matching) should be available. In addition, a large multimedia data from the database that you only want to be able to find a faster time-effective ways to search different from the existing research is required. To this end, in this paper effectively divided into a grid to search for the trajectory to the trajectory of moving objects, similar to the effective support of the search trajectory offers a new grid-based search techniques.

• Journal of Korea Spatial Information System Society
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• v.11 no.3
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• pp.9-18
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• 2009

Recently, due to the advanced technologies of mobile devices and wireless communication, there are many studies on telematics and LBS(location-based service) applications. because moving objects usually move on spatial networks, their locations are updated frequently, leading to the degradation of retrieval performance. To manage the frequent updates of moving objects' locations in an efficient way, a new distributed grid scheme, called DS-GRID (distributed S-GRID), and k-NN(k-nearest neighbor) query processing algorithm was proposed[1]. However, the result of k-NN query processing technique may be invalidated as the location of query and moving objects are changed. Therefore, it is necessary to study on continuous k-NN query processing algorithm. In this paper, we propose both MCE-CKNN and MBP(Monitoring in Border Point)-CKNN algorithmss are S-GRID. The MCE-CKNN algorithm splits a query route into sub-routes based on cell and seproves retrieval performance by processing query in parallel way by. In addition, the MBP-CKNN algorithm stores POIs from the border points of each grid cells and seproves retrieval performance by decreasing the number of accesses to the adjacent cells. Finally, it is shown from the performance analysis that our CKNN algorithms achieves 15-53% better retrieval performance than the Kolahdouzan's algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.7 no.8
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• pp.195-202
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• 2018

With the development of location-based applications such as smart phones and GPS navigation, active research is being conducted to protect location and trajectory privacy. To receive location-related services, users must disclose their exact location to the server. However, disclosure of users' location exposes not only their locations but also their trajectory to the server, which can lead to concerns of privacy violation. Furthermore, users request from the server not only location information but also multimedia information (photographs, reviews, etc. of the location), and this increases the processing cost of the server and the information to be received by the user. To solve these problems, this study proposes the EGTC (Enhanced Grid-based Trajectory Cloaking) technique. As with the existing GTC (Grid-based Trajectory Cloaking) technique, EGTC method divides the user trajectory into grids at the user privacy level (UPL) and creates a cloaking region in which a random query sequence is determined. In the next step, the necessary information is received as index by considering the sub-grid cell corresponding to the path through which the user wishes to move as c(x,y). The proposed method ensures the trajectory privacy as with the existing GTC method while reducing the amount of information the user must listen to. The excellence of the proposed method has been proven through experimental results.

• Journal of the Korea Convergence Society
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• v.12 no.2
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• pp.21-28
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• 2021

In this study, we propose a deep learning-based NILM technique using actual measured power data for 5 kinds of home appliances and verify its effectiveness. For about 3 weeks, the active power of the central power measuring device and five kinds of home appliances (refrigerator, induction, TV, washing machine, air cleaner) was individually measured. The preprocessing method of the measured data was introduced, and characteristics of each household appliance were analyzed through spectogram analysis. The characteristics of each household appliance are organized into a learning data set. All the power data measured by the central power measuring device and 5 kinds of home appliances were time-series mapping, and training was performed using a LSTM neural network, which is excellent for time series data prediction. An algorithm that can disaggregate five types of energies using only the power data of the main central power measuring device is proposed.

• Journal of the Korea Convergence Society
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• v.3 no.1
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• pp.19-25
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• 2012

This paper tries to solve the problems which previous methods have such as the WCDRM(Watermark and Cryptography DRM) and the model using smart card for protecting digital contents. This study provides a contents distribution model to protect the rights of author, distributor, and user as well as user's information by using technologies such as cryptography, DRM(Digital Right Management), access control, etc. The proposed system is evaluated as the most safety model compared with previous methods because it not only solves the problems which the previous methods have, but also protects four type of risks such as use of contents which other mobile devices download, the attack on the key to decode the message, the attack on leaking the contents, and the internal attack such as an illegal reproduction.

• Proceedings of the Korean Information Science Society Conference
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• 2001.04b
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• pp.625-627
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• 2001

기존의 종이지도를 수치지도 처리과정으로 얻어진 등고선(contour line) 데이터는 원격탐사(Remote Sensing)와 지리정보시스템(GIS)의 응용분야에서 주로 사용되어지는 데이터이다. 이러한 등고선은 해당 지역의 DTM(Digital Terrain Model) 데이터 생성을 위해 보간(interpolation)하여 생성하는 데 연구가 집중되어 왔다. 본 논문에서는 DEM(Digital levation Model)으로부터 얻어진 등고선 데이터를 이용하여 사용자에게 3차원으로 가시화 해 줄 수 있는 기법을 소개한다. 등고선 추출을 위한 방법으로는 기존의 소개되어진 Marching Square 알고리즘을 적용하였고, 지역적인 최고점(local minimum)과 최소점(maximum)을 구하기 위해 등고선을 열린 등고선(open contour)과 닫힌 등고선(closed contour)으로 분류하게 된다. 지역적 최고, 최소점을 찾기 위한 탐색공간을 줄이기 위해 닫힌 등고선만을 닫힌 등고만을 대상으로 등고선 트리를 생성하였으며, 생성된 트리의 리프노드에 대해서 최고, 최소점에 대한 근사(approximation)를 수행하게 된다. 이렇게 구해진 근사된 장점들과 등고선 데이털 입력으로 하여 제한된 딜로니 삼각분할(Constrained Delaunay Triangulation)을 수행함으로써, 3차원 지형을 재구성할 수 있다. 실험에서 간단한 그리드 샘플데이터와 USGS로 획득한 데이터를 이용하여 속도 측정을 하였다. 결과적으로 저장공간 측면에서 적은 량의 데이터를 가지면서 등고선을 표현할 수 있는 3차원 지형을 랜더링할 수가 있음을 알 수 있다.

• Journal of the Korean Institute of Telematics and Electronics
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• v.22 no.5
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• pp.93-101
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• 1985

A two-dimensional numerical analysis progranl, called SOMOS ( simulation of MO5 transistors), has been developed for the simulation of MOSFET's with various channel lengths and bias conditions. The finite difference approximation of the fundamental equa-tions are formulated using Newton's method for Poisson's equation and the divergence theorem for the continuity equation. For the solution of the lincariBed equations, SOR (successive over relaxation) method and Gummel's algorithm have been employed, The total simulation time for oar operating point is varying between 30 sec. and 4 min. on VAX 11/780 depending on bias conditions, The nonuniform mesh was generated and refined automatically to account for various bias values and the potential distributions.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.3
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• pp.194-202
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• 2000

In this paper, an efficient fuzzy rule generation scheme for Adaptive Network-based Fuzzy Inference System(ANFIS) using the conditional fuzzy-means(CFCM) and fuzzy equalization(FE) methods is proposed. Usually, the number of fuzzy rules exponentially increases by applying the gird partitioning of the input space, in conventional ANFIS approaches. Therefore, CFCM method is adopted to render the clusters which represent the given input and output fuzzy and FE method is used to automatically construct the fuzzy membership functions. From this, one can systematically obtain a small size of fuzzy rules which shows satisfying performance for the given problems. Finally, we applied the proposed method to the truck backer-upper control and Box-Jenkins modeling problems and obtained a better performance than previous works.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.38-38
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• 2016

기후변화로 인한 기온과 강수량의 변화는 국지적이고 집중적인 강우를 유발하게 되었고 이로 인하여 외수범람에 의한 제내지 침수로 인한 피해가 증가하고 있다. 따라서 제내지의 침수로 인한 피해를 예측하기위한 기술이 필요하다. 본 연구에서는 하천제방의 파쇄로 인한 홍수량이 제내지에서 어떤 경로로 침수-확산되는지를 파악하기 위하여 홍수의 침수경로를 모의할 수 있는 분포형홍수범람모형인 SIMOD(Simplified Inundation MODel) 모형을 개발하였다. 침수경로를 모의하기 위하여 홍수가 발생된 시점에서 그리드화된 주변셀로의 홍수전의를 위하여 주변셀과의 경사를 이용하여 차등 분배하는 다중흐름방향법(Multi Direction Method, MDM)과, 하나의 낮은 고도의 셀에서 수위가 높아져 인접셀보다 수위가 증가하면 그 수위는 인접 셀들과 균등해 진다는 가정인 평수가정법(Flat-Water Assumption, FWA)을 적용하였다. 모형의 평가를 위하여 가상시나리오를 설정하여 대상지역에서 시간에 따른 침수범위를 산정하였다. SIMOD 모형은 지형도(DEM)와 유입 홍수량의 간단한 입력자료를 이용하기 때문에 모의시간을 현저하게 단축시킬 수 있다. 강우-유출 모형 또는 제방붕괴 모형 등을 통해서 유입되는 홍수량만 파악을 할 수 있다면 수 분 내에 결과를 예측할 수 있다. 따라서 EAP(Emergency Action Plan)과 같은 도심지에서 침수로 인한 대피 계획을 수립하는데 활용될 수 있을 것이다.

• Tunnel and Underground Space
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• v.32 no.6
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• pp.502-517
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• 2022

As the use of TBM increases, research has recently increased to to analyze TBM data with machine learning techniques to predict the exchange cycle of disc cutters, and predict the advance rate of TBM. In this study, a regression prediction of disc cutte wear of slurry shield TBM site was made by combining machine learning based on the machine data and the geotechnical data obtained during the excavation. The data were divided into 7:3 for training and testing the prediction of disc cutter wear, and the hyper-parameters are optimized by cross-validated grid-search over a parameter grid. As a result, gradient boosting based on the ensemble model showed good performance with a determination coefficient of 0.852 and a root-mean-square-error of 3.111 and especially excellent results in fit times along with learning performance. Based on the results, it is judged that the suitability of the prediction model using data including mechanical data and geotechnical information is high. In addition, research is needed to increase the diversity of ground conditions and the amount of disc cutter data.