• International Journal of Internet, Broadcasting and Communication
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• 제13권4호
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• pp.135-142
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• 2021

Estimating the locations of workers in a shipyard is beneficial for a variety of applications such as selecting potential forwarders for transferring data in IoT services and quickly rescuing workers in the event of industrial disasters or accidents. In this work, we propose a human movement stream processing system for estimating worker locations in shipyards based on Apache Spark and TensorFlow serving. First, we use Apache Spark to process location data streams. Then, we design a worker location prediction model to estimate the locations of workers. TensorFlow serving manages and executes the worker location prediction model. When there are requirements from clients, Apache Spark extracts input data from the processed data for the prediction model and then sends it to TensorFlow serving for estimating workers' locations. The worker movement data is needed to evaluate the proposed system but there are no available worker movement traces in shipyards. Therefore, we also develop a mobility model for generating the workers' movements in shipyards. Based on synthetic data, the proposed system is evaluated. It obtains a high performance and could be used for a variety of tasksin shipyards.

• 한국통신학회논문지
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• 제41권11호
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• pp.1431-1439
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• 2016

본 논문은 센서 노드들의 에너지 소비를 줄이고 소스로부터 이동 싱크 그룹까지 데이터를 전달하기 위한 새로운 위치 서비스와 위치 기반 라우팅을 제안한다. 기존 방안들과는 다르게, 제안 방안은 그룹 영역 대신 싱크 그룹을 대표하는 리더 싱크 위치 정보를 사용한다. 그래서, 제안 방안은 소스와 리더 싱크 간의 위치 서비스와 위치 기반 라우팅을 위한 상위 계층과 리더 싱크와 멤버 싱크들 간의 위치 서비스와 라우팅을 위한 하위 계층으로 이루어진 계층적 위치 서비스와 위치 기반 라우팅을 사용한다. 각각의 상위와 하위 계층의 위치 서비스와 위치 기반 라우팅은 플러딩을 사용하지 않기 때문에 제안 방안은 센서 노드들의 에너지 소비를 줄일 수 있다. 다양한 시뮬레이션 결과는 제안 방안이 기존 방안보다 우수함을 증명한다.

• 한국군사과학기술학회지
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• 제7권4호
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• pp.61-69
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• 2004

This paper presents a new analytical method for estimating the location of a target using directional data. Based on a nonlinear programming (NLP) problem formulated for the line method, which is a well known algorithm for two-dimensional location estimation, we present a method to find an optimal solution for the problem. Then we present a two-stage method for better location estimation based on the NLP problem. In addition, another two-stage method is presented for location estimation problems in which different types of observers are used to obtain directional data based on the analysis of the maximum likelihood estimate of the target location. The performance of the suggested method is evaluated through simulation experiments, and results show that the two-stage method is computationally efficient and highly accurate.

• 한국컴퓨터정보학회논문지
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• 제22권11호
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• pp.97-104
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• 2017

Location prediction has been successfully utilized to provide high quality of location-based services to customers in many applications. In its usual form, the conventional type of location prediction is to predict future locations based on user's past movement history. However, as location prediction needs are expanded into much complicated cases, it becomes necessary quite frequently to make inference on the locations that target user visited in the past. Typical cases include the identification of locations that infectious disease carriers may have visited before, and crime suspects may have dropped by on a certain day at a specific time-band. Therefore, primary goal of this study is to predict locations that users visited in the past. Information used for this purpose include user's demographic information and movement histories. Data mining classifiers such as Bayesian network, neural network, support vector machine, decision tree were adopted to analyze 6868 contextual dataset and compare classifiers' performance. Results show that general Bayesian network is the most robust classifier.

• Journal of Communications and Networks
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• 제7권4호
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• pp.478-488
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• 2005

To conserve the usage of energy, indexing techniques have been developed in a wireless mobile environment. However, the use of interleaved index segments in a broadcast cycle increases the average access latency for the clients. In this paper, we present the broadcast-based location dependent data delivery scheme (BBS) for dynamic range queries. In the BBS, broadcasted data objects are sorted sequentially based on their locations, and the server broadcasts the location dependent data along with an index segment. Then, we present a data prefetching and caching scheme, designed to reduce the query response time. The performance of this scheme is investigated in relation to various environmental variables, such as the distributions of the data objects, the average speed of the clients, and the size of the service area.

• Communications for Statistical Applications and Methods
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• 제25권3호
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• pp.263-274
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• 2018

One of the common issues in large dataset analyses is to detect and construct homogeneous groups of objects in those datasets. This is typically done by some form of clustering technique. In this study, we present a divisive hierarchical clustering method for two monothetic characteristics of histogram data. Unlike classical data points, a histogram has internal variation of itself as well as location information. However, to find the optimal bipartition, existing divisive monothetic clustering methods for histogram data consider only location information as a monothetic characteristic and they cannot distinguish histograms with the same location but different internal variations. Thus, a divisive clustering method considering both location and internal variation of histograms is proposed in this study. The method has an advantage in interpreting clustering outcomes by providing binary questions for each split. The proposed clustering method is verified through a simulation study and applied to a large U.S. house property value dataset.

• 한국항해항만학회지
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• 제43권5호
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• pp.289-295
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• 2019

In this paper, we implemented a safety navigation mobile application that converged AtoN information and location-based services. When application user uses the smartphone's GPS sensor to transmit the user's vessel location data to the data server, the user receives information of which its providing range is considered, such as stored AtoN data, neighboring vessels information, danger area, and weather information in the server. Providing information is sorted based on the smartphone's direction and inclination and it will be also delivered via wireless network (5G, LTE, 3G, WiFi). Additionally the application is available to implement other functions such as information provision through voice and text alarming service when the user's vessel is either approaching or entering the danger area, and an expanded information provision service that is available in shadow area linking with data-storing methods; other linkable data such as weather and other neighboring vessels will be applied based on the lasted-saved data perceived from the non-shadow area.

• 대한전기학회논문지:전력기술부문A
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• 제49권12호
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• pp.608-613
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• 2000

This paper describes a fault location technique using wavelets in underground transmission power cable system. Estimation of fault location is performed using data smapled at two ends underground system. In the case of 50% fault of total underground transmission line, fault location is calculated using sampled single-end data in underground transmission line. Traveling wave is utilized in capturing the travel time of the transients along the monitored lines between the relay and the fault point. This traveling time information is provided by the wavelet. Simulation was performed using EMTP, ATP Draw and MATLAB. The results of fault location shown in this paper will be evaluated as an effective suggestion for fault location in real underground transmission line.

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.195-200
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• 2021

In this paper, we propose a method for a mobile robot to estimate a specific location of a service provision target using a beacon-tag for the purpose of providing location-based services (LBS) to users in an indoor environment. To estimate the location, the irregular characteristics and error factors of the received signal strength indicator (RSSI) generated from the beacon are analyzed, and the distance conversion function is derived from the RSSI data extracted by applying a Gaussian filter. Then, the distance data converted from the plurality of beacons estimates an indoor location through a triangulation technique. After that, the improvement in the location estimation is analyzed by applying the temporal confidence reasoning technique. The possibility of providing a LBS of a mobile robot was confirmed through a location estimation experiment for a plurality of designated locations in an indoor environment.

• 인터넷정보학회논문지
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• 제7권3호
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• pp.71-82
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• 2006

본 논문은 실내 환경에서 이동객체의 실시간 추적 알고리즘을 제안한다. 제안하는 시스템은 기존에 사용되던 삼각측량 기법과 DCM(Database Correlation Method) 기법을 통해 각각의 위치 데이터를 생성한 후, 그 중 이동객체와 더 근사한 위치 데이터를 실시간으로 선택한다. 또한 Kalman Filter를 사용하여 선택된 위치 데이터를 보정하여 시스템에 적용하므로 이동 객체의 위치 정확도를 향상시켰다. 기존에 연구된 Kalman Filter는 과거의 정보를 이용하여 현재의 위치를 추정해 내는 시스템의 특성상 안정화 되는 시간까지 불확실한 위치 데이터를 가지게 된다. 하지만 제안하는 위치 추적 시스템은 기존의 Kalman Filter를 그대로 적용하지 않고, 더 효율적인 방안을 제시한 후 적용함으로 더 정확한 위치 추적을 가능케 한다.