Dongsoo Han

Performance Analysis of the Asymmetric Dual-Hop Relay Transmission With Mixed RF/FSO Links

This letter reports a performance analysis of a dual-hop relay system composed of asymmetric radio-frequency and free-space optics (RF/FSO) links. This approach is based on the fact that FSO links can provide even wider bandwidths as compared to RF ones. In particular, an exact closed-form expression for the end-to-end outage probability of the RF/FSO relay links is derived. Overall, the RF/FSO links show a slightly worse performance than the RF/RF links, but the performance gap is gradually reduced as the signal-to-noise ratio (SNR) increases. Our mathematical analysis results were verified by exactly matching Monte Carlo simulation results.

Building a Practical Wi-Fi-Based Indoor Navigation System

This article presents the seven-step process involved in building a practical Wi-Fi-based indoor navigation system, which was implemented at the COEX complex in Seoul, Korea, in October 2010. The article describes the primary activities in each step using the COEX example. More than 200,000 users have downloaded the system since its first release. The successful launch of the COEX indoor navigation system suggests that indoor navigation is becoming a reality.

Voronoi Tessellation Based Interpolation Method for Wi-Fi Radio Map Construction

The fingerprint-based approach for positioning in WLAN has been drawing great attention these days. However, the approach usually requires tremendous time and efforts to collect location fingerprints for the target area. In this paper, we propose an interpolation method based on Voronoi tessellation to significantly reduce such calibration efforts and to improve accuracy. Unlike other interpolation methods, our method refines the propagation model for each cell of the target area tessellated by a higher-order Voronoi diagram. Consequently, our method can take into account the signal fading caused by walls and obstacles more accurately. The proposed method significantly outperformed other interpolation methods in accuracy.

Protein complex prediction based on simultaneous protein interaction network

MOTIVATION The increase in the amount of available protein-protein interaction (PPI) data enables us to develop computational methods for protein complex predictions. A protein complex is a group of proteins that interact with each other at the same time and place. The protein complex generally corresponds to a cluster in PPI network (PPIN). However, clusters correspond not only to protein complexes but also to sets of proteins that interact dynamically with each other. As a result, conventional graph-theoretic clustering methods that disregard interaction dynamics show high false positive rates in protein complex predictions. RESULTS In this article, a method of refining PPIN is proposed that uses the structural interface data of protein pairs for protein complex predictions. A simultaneous protein interaction network (SPIN) is introduced to specify mutually exclusive interactions (MEIs) as indicated from the overlapping interfaces and to exclude competition from MEIs that arise during the detection of protein complexes. After constructing SPINs, naive clustering algorithms are applied to the SPINs for protein complex predictions. The evaluation results show that the proposed method outperforms the simple PPIN-based method in terms of removing false positive proteins in the formation of complexes. This shows that excluding competition between MEIs can be effective for improving prediction accuracy in general computational approaches involving protein interactions. AVAILABILITY http://code.google.com/p/simultaneous-pin/. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.

Crowdsourced radiomap for room-level place recognition in urban environment

The proliferation of WLAN infrastructures has facilitated numerous indoor localization techniques using WLAN fingerprints. In particular, identifying a room or a place in urban environments could be usefully utilized in many application domains such as ubiquitous health. However, it is not straightforward how to bootstrap such a localization system because WLAN fingerprints of all places must be available in advance. In this paper, we propose a crowdsourcing approach for indoor place recognition. The key idea is to build an open participatory system through which users can contribute fingerprints. As the database size increases, it can provide place recognition service. We conducted an extensive experimental study at a university campus to demonstrate the performance of the proposed method in terms of recognition accuracy. We also studied key factors that could undermine the crowdsourcing approach such as fingerprint density, incorrect contribution, uneven contribution, and device heterogeneity.

THE-MUSS: Mobile u-health service system

In this paper, we introduce a mobile u-health service system called THE-MUSS. THE-MUSS supports the development and running of u-health services with functions, modules, and facilities that are commonly required for various mobile u-health services. Aiming to achieve reusability and evolvability design goals, basic modules to support bio-signal capturing, processing, analysis, diagnosis, and feedback are developed and stacked in the layered architecture of THE-MUSS. A U-health service platform, design tool, portal, and matrix-based disease group identification method are the major components constituting the THE-MUSS architecture. We confirmed that THE-MUSS is practically useful for mobile u-health services by developing mobile stress and weight management services on THE-MUSS. The more u-health services are developed in THE-MUSS, the better services it can provide in the future.

Energy-Efficient Location Logging for Mobile Device

Location logging is a technique that continuously records user’s location using various location sensing and positioning technologies. Location logs and information derived from those logs can be useful contexts for various applications. However, previous research related to recording and handling location logs failed to seriously consider heavy battery consumption. Heavy battery consumption is a serious problem in location logging research and applications, and it has obstructed location logging applications to be widely used. In this paper, we present Variable Rate Logging (VRL) mechanism to maximize battery life of continuous logging for user’s location with minimum loss of logging quality. Our mechanism can optimize any application which requires continuous recording of user’s location and dramatically extend its battery life. Evaluation results show that Variable Rate Logging mechanism has 143% longer battery life than fixed rate logging.

Wi-Fi fingerprint-based approaches following log-distance path loss model for indoor positioning

Wi-Fi fingerprint based indoor positioning methods exploits naive signal strength in each location to predict users location. However, using naïve signal strength may limit the prediction accuracy, because the Wi-Fi signals follow the Log-distance path loss model in signal propagation. In this research, we propose to generate Wi-Fi fingerprint with the consideration of radio propagation model to reflex the characteristics of Wi-Fi signal. The evaluation result shows that following log-distance path loss model improves the prediction accuracy in fingerprint based indoor positioning.

THE-MUSS: Mobile U-Health Service System

In this paper, we introduce a mobile u-health service system, named THE-MUSS, which supports u-health service development and running, with functions, modules, and facilities that are commonly required for various mobile u-health services. Basic modules to support bio-signal capturing, processing, analysis, diagnosis, feedbacks are prepared and stacked in the system. Reusability and evolvability are elicited as the primary design goals to achieve in developing THE-MUSS after the understanding of u-health service characteristics. U-health service platform, u-health ontology incorporated u-health service design tool, Matrix based disease group identification framework, and u-health portal are the major components constructing the layered architecture of THE-MUSS. Mobile stress and weigh management services are developed on THE-MUSS to confirm and evaluate the usefulness of THE-MUSS in developing mobile u-health services. According to the evaluation, it turned out that THE-MUSS has strength in reusability and evolvability, but also in system flexibility, adaptability, interoperability, and guideline provision for developing u-health services.

A framework supporting dynamic workflow interoperation and enterprise application integration

In this paper, we propose a framework supporting dynamic interoperation between heterogeneous workflow systems and workflow-based dynamic enterprise application integration (EAI). To this end, based on a subflow task model and multi-tiered dynamic state transition model, four major components are defined: the workflow engine, adapter, service interface repositories (SIRs), and XML messages. The workflow engine provides a user with location transparency of subprocesses by encapsulating and dynamically binding both internal and external subprocesses. As middleware, the adapter achieves location and system transparency with the help of the workflow engine by encapsulating and dynamically binding external subprocesses to its superprocess. SIRs contain the service information of other systems. The local SIR (LSIR) within an organization is an important component for dynamic EAI. The adapter looks up the LSIR at run time when it tries to find external services. Several XML messages enable communications between heterogeneous workflow systems and enterprise applications.