• The KIPS Transactions:PartC
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• v.12C no.4 s.100
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• pp.525-534
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• 2005

We present several distributed algorithms for localizing nodes of a wireless sensor network. Our algorithms determine locations of nodes based on the connectivity between nodes. The basic idea behind our algorithms is to estimate distances between nearby nodes by counting their common neighbors. We analyze the performance of our algorithms experimentally. The results of experiments show that our algorithms achieve performance improvements upon the existing algorithms

• The Journal of Korean Institute of Communications and Information Sciences
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• v.38C no.1
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• pp.33-42
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• 2013

This paper presents a multihop range-free localization algorithm to estimate the physical location of a normal node with local connectivity information in anisotropic sensor networks. In the proposed algorithm, a normal node captures the detour degree of the shortest path connecting an anchor pair and itself by comparing the measured hop count and the expected hop count, and the node estimates the distances to the anchors based on the detour degree. The normal node repeats this procedure with all anchor combinations and pinpoints its location using the obtained distance estimates. The proposed algorithm requires fewer anchors and less communication overhead compared to existing range-free algorithms. We showed the superiority of the proposed algorithm over existing range-free algorithms through MATLA simulations.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.530-536
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• 2008

Localization is one of the fundamental problems in wireless sensor networks (WSNs) that forms the basis for many location-aware applications. Localization in WSNs is to determine the position of node based on the known positions of several nodes. Most of previous localization method use triangulation or multilateration based on the angle of arrival (AOA) or distance measurements. In this paper, we propose an enhanced centroid localization method based on edge weights of adjacent nodes using fuzzy modeling and genetic algorithm when node connectivities are known. The simulation results shows that our proposed centroid method is more accurate than the simple centroid method using connectivity only.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.41 no.9
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• pp.1060-1068
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• 2016

The range-free localization using connectivity information has problems of mobile tracking. This paper proposes two Bayesian filter-based mobile tracking algorithms considering a propagation scenario. Kalman and Markov Chain Monte Carlo (MCMC) particle filters are applied according to linearity of two measurement models. Measurement models of the Kalman and MCMC particle filter-based algorithms respectively are defined as connectivity between mobiles, information fusion of connectivity information and received signal strength (RSS) from neighbors within one-hop. To perform the accurate simulation, we consider a real indoor map of shopping mall and degree of radio irregularity (DOI) model. According to obstacles between mobiles, we assume two types of DOIs. We show the superiority of the proposed algorithm over existing range-free algorithms through MATLAB simulations.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4B
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• pp.647-658
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• 2010

Many localization schemes estimate the locations of radio nodes based on the physical locations of anchors and the connectivity from the anchors. Since they only consider the knowledge of the anchors without else other nodes, they are likely to have enormous error in location estimate unless the range information from the anchors is accurate or there are sufficiently many anchors. In this paper, we propose a novel localization algorithm with the location knowledge of anchors and even one-hop neighbors to localize unknown nodes in the uniform distance from all the one-hop neighbors without the range information. The node in the uniform distance to its all neighbors reduces the location error relative to the neighbors. It further alleviates the location error between its actual and estimated locations. We evaluate our algorithm through extensive simulations under a variety of node densities and anchor placement methods.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.12
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• pp.5785-5804
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• 2019

The information of localization is a fundamental requirement in wireless sensor network (WSN). The method of distance vector-hop (DV-Hop), a range-free localization algorithm, can locate the ordinary nodes by utilizing the connectivity and multi-hop transmission. However, the error of the estimated distance between the beacon nodes and ordinary nodes is too large. In order to enhance the positioning precision of DV-Hop, fast triangle flip bat algorithm, which is based on curve strategy and rank transformation (FTBA-TCR) is proposed. The rank is introduced to directly select individuals in the population of each generation, which arranges all individuals according to their merits and a threshold is set to get the better solution. To test the algorithm performance, the CEC2013 test suite is used to check out the algorithm's performance. Meanwhile, there are four other algorithms are compared with the proposed algorithm. The results show that our algorithm is greater than other algorithms. And this algorithm is used to enhance the performance of DV-Hop algorithm. The results show that the proposed algorithm receives the lower average localization error and the best performance by comparing with the other algorithms.

• Journal of the Economic Geographical Society of Korea
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• v.23 no.3
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• pp.262-275
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• 2020

Due to the pandemic caused by Corona 19, cities around the world have faced a change. As the global economic system weakens, localization is increasing in the product production and distribution system. In addition, consumption patterns have changed in urban where localization has been strengthened. As a result, the way physical places are consumed is also changing. Consumption of large multi-use facilities has drastically decreased, the speed of the collapse of the online and offline boundaries has been accelerated, and the consumption of amenities for sharing tastes has become more subdivided, specialized, and private. A big change also appeared in the urban scene, which is perceived as the concentration of urban amenities. Local scale and locality became important in the urban scene, and a new urban scene element called empathy emerged. Empathy aims to connect socially and emotionally to individuals consuming urban amenities. The pursuit of connectivity, taste consumption, and nostalgia. In this study, the space for cultural consumption based on empathy was named as empathetic space and the concept was explained. The importance of empathic space in the urban scene in the future post-corona situation was presented.

• Journal of Information Technology Services
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• v.12 no.2
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• pp.215-229
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• 2013

The purpose of this research is to identify what factors influence a customer satisfaction and re-purchasing intention and to identify if customer's Intentions are different between a mobile shopping mall and Internet Shopping mall. To perform empirical analysis for the mobile shopping mall, this research reapplied the factors of Parasuraman et al.[77] in a Internet shopping mall, including reliability, reactivity, tangibility, and this research also applied the factors of a mobile properties, including ubiquity, localization, instant connectivity. The empirical results of this research indicate that all hypotheses in our model are significant; However, the factors of a mobile properties negatively. The results of a analysis indicate that the mobile properties in a mobile shopping mall are not significant yet. and customer's recognition in both mobile shopping mall and Internet shopping mall are the similarity. In Conclusion, with the rapid growth of the Mobile Shopping mall market, many mobile shopping mall researches based on customer's Intentions must be published. Therefore, this research will be the foundation of these researches.

• Journal of Korea Spatial Information System Society
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• v.9 no.1
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• pp.15-30
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• 2007

The purpose of this study is to explore essential factors of influencing user's usage intentions on telematics services and to find relationships among factors. This study derives several variables and hypotheses through literature reviews on the extended research model based on Davis's Technology Acceptance Model. With the objective of statistical verification, derived variables were sorted into meaningful categories through various statistical packages. These were included multiple regression analysis to improve the reliability of survey data. The demand analysis was conducted by targeting on users who have previously experienced telematics services. Indicated analyzed results which 'suitability', 'localization', and 'instant connectivity' variables were positively related to the user's usage intentions, especially accuracy of information variable. The factors of influencing the usage intention on telematics services can be useful empirical data in order to analyze the market trends and to suggest industrial or political guideline of telematics services.