• Communications for Statistical Applications and Methods
• /
• 제12권3호
• /
• pp.603-613
• /
• 2005

We propose some estimators of the location parameter and derive the approximate maximum likelihood estimators (AMLEs) of the scale parameter in the exponential distribution based on multiply Type-II censored samples. We calculate the moments for the proposed estimators of the location parameter, and the AMLEs which are the linear functions of the order statistics. We compare the proposed estimators in the sense of the mean squared error (MSE) for various censored samples.

• 대한전기학회:학술대회논문집
• /
• 대한전기학회 2005년도 학술대회 논문집 정보 및 제어부문
• /
• pp.606-608
• /
• 2005

In this paper, we introduce localization server system calculated real location of objects using raw data of location-awareness from sensor node gateway. The software architecture of localization server system consists of location calculation and actuator control based on location. Also, this system supports for collecting raw data, calculating location of real objects using raw data, correcting error from outer environment, and server for applications based on location.

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

• 한국정보기술응용학회:학술대회논문집
• /
• 한국정보기술응용학회 2005년도 6th 2005 International Conference on Computers, Communications and System
• /
• pp.27-30
• /
• 2005

Because of unreplenishable power resources, reducing node energy consumption to extend network lifetime is an important requirement in wireless sensor networks. In addition both path length and path cost are important metrics affecting sensor lifetime. We propose a dynamic clustering scheme based on location in wireless sensor networks. Our scheme can localize the effects of route failures, reduce control traffic overhead, and thus enhance the reachability to the destination. We have evaluated the performance of our clustering scheme through a simulation and analysis. We provide simulation results showing a good performance in terms of approximation ratios.

• 제어로봇시스템학회:학술대회논문집
• /
• 제어로봇시스템학회 2001년도 ICCAS
• /
• pp.114.4-114
• /
• 2001

Recently, variety services are more and more developed due to supply of PDA, cellular phone, and etc. Also, a services based on location information are very helpful in traffic, shopping, and emergency. Thus the user position is positively necessary for these services. One of the latest applications in GPS is the E911 call service for wireless phones. In this case, current GPS Navigation accuracy meets the FCC requirements but the hardware size and power consumption of GPS is issued for implementation. And, some case of applications need to snapshot location solution with fast TTFF(Time-To-Fist-Fix) than continuous location solution. The software GPS receiver could be the solution ...

• 한국정보시스템학회지:정보시스템연구
• /
• 제21권4호
• /
• pp.55-79
• /
• 2012

LBS(Location-Based Service) is one of the smartphone application services which has been receiving great attention recently. Various applications of smartphone use LBS to provide innovative services. However, use of LBS raises privacy concerns because the location information of users is constantly exposed. Privacy calculus perspective attempts to understand the characteristics of the user's privacy. It is based on the risk-benefit analysis in the economics' perspective. That is, when the benefit expected through personal information disclosure is higher than risk, we are willing to provide personal information. This research suggested a research model based on the privacy calculus perspective to clarify the effect of information disclosure intention of smartphone LBS application users. Based on the main factors of privacy calculus, perception of privacy risk and privacy benefit, the relationship of the perceived value and the information disclosure intention was empirically analyzed by utilizing structural equation modeling(SEM) methodology. According to the results of the empirical analysis, it was found that all relations have statistically significant explanatory power except the relation between privacy concern and information disclosure intention. This study showed a strong evidence of antecedent factors based on privacy calculus of personal information disclosure in smartphone LBS applications.

• Journal of Information Technology Applications and Management
• /
• 제14권4호
• /
• pp.1-16
• /
• 2007

In the microcell- or picocell-based system the frequent movements of the mobile bring about excessive traffics into the networks. A mobile location estimation mechanism can facilitate both efficient resource allocation and better QoS provisioning through handoff optimization. Existing location estimation schemes consider only LOS model and have poor performance in presence of multi-path and shadowing. In this paper we study a novel scheme which can increase estimation accuracy by considering NLOS environment and other multiple decision parameters than the received signal strength.

• Spatial Information Research
• /
• 제19권1호
• /
• pp.127-133
• /
• 2011

Recently, with the advances in sensor techniques and net work computing, Ubiquitous Sensor Network (USN) has been received a lot of attentions from various communities. The sensor nodes distributed in the sensor network tend to continuously generate a large amount of data, which is called stream data. Sensor stream data arrives in an online manner so that it is characterized as high-speed, real-time and unbounded and it requires fast data processing to get the up-to-date results. The data stream has many application domains such as traffic analysis, physical distribution, U-healthcare and so on. Therefore, there is an overwhelming need of a USN middleware for processing such online stream data to provide corresponding services to diverse applications. In this paper, we propose a novel USN middleware which can provide users both context-aware service and meaningful sequential patterns. Our proposed USN middleware is mainly focused on location based applications which use stream location data. We also show the implementation of our proposed USN middleware. By using the proposed USN middleware, we can save the developing cost of providing context aware services and stream sequential patterns mainly in location based applications.

• 한국융합학회논문지
• /
• 제1권1호
• /
• pp.23-29
• /
• 2010

최근 스마트폰 사용자를 대상으로 다양한 종류의 어플리케이션이 개발/배포되고 있다. 특히 Google에서 개발한 안드로이드 운영체제인 경우 오픈 소스 정책을 채택하였으며 멀티태스킹 서비스를 지원함과 동시에 기존의 구글 서비스와 연계할 수 있다는 장점이 있다. 특히 안드로이드 운영체제에서 Layar, Wikitude, Sherpa 및 a2b 등과 같이 스마트폰 환경에서 GPS 위치정보를 이용한 어플리케이션이 개발되어 다양한 서비스를 제공하고 있다. 하지만 기존의 Cell-ID 기반의 위치정보는 이동통신사업자가 이동통신망에 설치한 교환장치를 통해 직접적으로 수집될 수 있기 때문에 개인 프라이버시 문제가 발생하고, 각종 사업자에 따라 얼마든지 정보가 유출될 가능성이 있는 정보이므로 개인 프라이버시 침해 위험성이 높다. 따라서 본 연구에서는 스마트폰에서의 GPS 기반 개인위치정보를 사용자 스스로 통제 및 접근제어할 수 있는 기술적 방안을 제시하였고 이를 설계하였다. 이를 통해 안드로이드 환경에서 다양한 GPS 개인위치정보 자기제어 SW 개발이 가능하였다.

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