• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.5
• /
• pp.1951-1972
• /
• 2018

Wi-Fi Access Point (AP) optimization approaches are used in indoor positioning systems for signal coverage enhancement, as well as positioning precision improvement. Although the huge power consumption of the AP optimization forms a serious problem due to the signal coverage requirement for large-scale indoor environment, the conventional approaches treat the problem of power consumption independent from the design of indoor positioning systems. This paper proposes a new Fast Water-filling algorithm Group Power Constraint (FWA-GPC) based Wi-Fi AP optimization approach for indoor positioning in which the power consumed by the AP optimization is significantly considered. This paper has three contributions. First, it is not restricted to conventional concept of one AP for one candidate AP location, but considered spare APs once the active APs break off. Second, it utilizes the concept of water-filling model from adaptive channel power allocation to calculate the number of APs for each candidate AP location by maximizing the location fingerprint discrimination. Third, it uses a fast version, namely Fast Water-filling algorithm, to search for the optimal solution efficiently. The experimental results conducted in two typical indoor Wi-Fi environments prove that the proposed FWA-GPC performs better than the conventional AP optimization approaches.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.12 no.5
• /
• pp.2082-2102
• /
• 2018

In recent years, social network related applications such as WeChat, Facebook, Twitter and so on, have attracted hundreds of millions of people to share their experience, plan or organize, and attend social events with friends. In these operations, plenty of valuable information is accumulated, which makes an innovative approach to explore users' preference and overcome challenges in traditional recommender systems. Based on the study of the existing social network recommendation methods, we find there is an abundant information that can be incorporated into probability matrix factorization (PMF) model to handle challenges such as data sparsity in many recommender systems. Therefore, the research put forward a unified social network recommendation framework that combine tags, trust between users, ratings with PMF. The uniformed method is based on three existing recommendation models (SoRecUser, SoRecItem and SoRec), and the complexity analysis indicates that our approach has good effectiveness and can be applied to large-scale datasets. Furthermore, experimental results on publicly available Last.fm dataset show that our method outperforms the existing state-of-art social network recommendation approaches, measured by MAE and MRSE in different data sparse conditions.

• Journal of KIISE:Computer Systems and Theory
• /
• v.32 no.9
• /
• pp.433-444
• /
• 2005

In video-on-demand(VOD) systems, a broadcast-based scheduling mechanism is known to be a very efficient technique for disseminating popular videos to very large client populations. The main motivations of broadcasting scheduling mechanisms are that they scale up extremely well and they have very modest bandwidth requirements. This paper proposes a new dynamic broadcasting scheduling mechanism, named FDBS (fast dynamic broadcasting scheme), and proves its correctness. This paper also evaluates the performance of FDBS on the basis of a simulation approach. The simulation results indicate that FDBS shows a superior performance over UD, CBHD, and NPB in terms of the average response time with very reasonable bandwidth requirements.

• Journal of Intelligence and Information Systems
• /
• v.12 no.4
• /
• pp.61-72
• /
• 2006

Ubiquitous computing technologies become mature enough to be applied in acceptable ubiquitous services. In particular, in u-shopping area, personalized recommender systems which automatically collect the nomadic user-related context data and then provide them with products or shops in a flexible manner. However, legacy cooperative queries and context-aware queries so far do not come up with dynamically changing situations and ambiguous query commands, respectively. Hence, The purpose of this paper is to propose a personalized context-aware cooperative query that supports a multi-level data abstraction hierarchy and conceptual distance metric among node instances, while considering the user's context data. To show the feasibility of the methodology proposed in this paper, we have implemented a prototype system, CACO, in the area of site search in a large-scale shopping mall.

• International Journal of Naval Architecture and Ocean Engineering
• /
• v.7 no.3
• /
• pp.559-579
• /
• 2015

An experimental study of the effect of mooring systems on the dynamics of a SPAR buoy-type floating offshore wind turbine is presented. The effects of the Center of Gravity (COG), mooring line spring constant, and fairlead location on the turbine's motion in response to regular waves are investigated. Experimental results show that for a typical mooring system of a SPAR buoy-type Floating Offshore Wind Turbine (FOWT), the effect of mooring systems on the dynamics of the turbine can be considered negligible. However, the pitch decreases notably as the COG increases. The COG and spring constant of the mooring line have a negligible effect on the fairlead displacement. Numerical simulation and sensitivity analysis show that the wind turbine motion and its sensitivity to changes in the mooring system and COG are very large near resonant frequencies. The test results can be used to validate numerical simulation tools for FOWTs.

• ETRI Journal
• /
• v.44 no.5
• /
• pp.715-732
• /
• 2022

Despite the successful launch of Advanced Television Systems Committee (ATSC) 3.0 broadcasting worldwide, broadcasters are facing obstacles in constructing void-less large-scale single-frequency networks (SFNs). The bottleneck is the absence of decent on-channel repeater (OCR) solutions necessary for SFNs. In the real world, OCRs suffer from the maleficent feedback interference (FI) problem, which overwhelms the desired input signal. Moreover, the undesired multipaths between studio-linked transmitters and the OCR deteriorate the forward signals' quality as well. These problems crucially restrict the feasibility of conventional OCR systems, arousing the strong need for cost-worthy advanced OCR solutions. This paper presents an ATSC 3.0-specific solution of advanced OCR that solves the FI problem and refines the input signal. To this end, the FI canceler and channel equalizer functionalities are carefully implemented into the OCR system. The presented OCR system is designed to be fully compliant with the ATSC 3.0 specifications and performs a fast and efficient signal processing by exploiting the specific frame structure. The real product of ATSC 3.0 OCR is fabricated as well, and its feasibility is verified via field and laboratory experiments. The implemented solution is installed at a commercial on-air site and shown to provide substantial coverage gain in practice.

• Nuclear Engineering and Technology
• /
• v.54 no.5
• /
• pp.1686-1697
• /
• 2022

As a part of probabilistic risk (or safety) assessment (PRA or PSA) of nuclear power plants (NPPs), the primary role of human reliability analysis (HRA) is to provide credible estimations of the human error probabilities (HEPs) of safety-critical tasks. Accordingly, HRA community has emphasized the accumulation of HRA data to support HRA practitioners for many decades. To this end, it is critical to resolve practical problems including (but not limited to): (1) how to collect HRA data from available information sources, and (2) how to inform HRA practitioners with the collected HRA data. In this regard, the U.S. Nuclear Regulatory Commission (NRC) and Korea Atomic Energy Research Institute (KAERI) independently initiated two large projects to accumulate HRA data by using full-scale simulators (i.e., simulator data). In terms of resolving the first practical problem, the NRC and KAERI developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. In addition, to inform HRA practitioners, the NRC and KAERI proposed several ideas to extract useful information from simulator data. This paper is the first of two papers to discuss the technical underpinnings of the development of the SACADA and HuREX systems.

• Nuclear Engineering and Technology
• /
• v.55 no.4
• /
• pp.1400-1409
• /
• 2023

In this study, three condensation models of the CUPID code, i.e., the resolved boundary layer approach (RBLA), heat and mass transfer analogy (HMTA) model, and an empirical correlation, were tested and validated against the COPAIN and CAU tests. An improvement on HMTA model was also made to use well-known heat transfer correlations and to take geometrical effect into consideration. The RBLA was a best option for simulating the COPAIN test, having mean relative error (MRE) about 0.072, followed by the modified HMTA model (MRE about 0.18). On the other hand, benchmark against CAU test (under natural convection and occurred on a slender tube) indicated that the modified HMTA model had better accuracy (MRE about 0.149) than the RBLA (MRE about 0.314). The HMTA model with wall function and the empirical correlation underestimated significantly, having MRE about 0.787 and 0.55 respectively. When using the HMTA model, consideration of geometrical effect such as tube curvature was essential; ignoring such effect leads to significant underestimation. The HMTA and the empirical correlation required significantly less computational resources than the RBLA model. Considering that the HMTA model was reasonable accurate, it may be preferable for large-scale simulations of containment.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
• /
• 2021.05a
• /
• pp.574-576
• /
• 2021

It is necessary to introduce micro-service techniques when constructing large-scale operating systems or systems that take into account scalability. Kafka is a message queue with the pub/sub model, which has features that are well applied to distributed environments and is also suitable for microservices in that it can utilize various data sources. In this paper, we propose a data sharing method for educational video sharing services using Apache's Kafka. The proposed system builds a Kafka cluster for the educational video sharing service to share various data, and also uses a spark cluster to link with recommendation systems based on similarities in educational videos. We also present a way to share various data sources, such as files, various DBMS, etc.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.18 no.3
• /
• pp.685-703
• /
• 2024

Cloud computing provides each consumer with a large-scale computing tool. Different Cyber Attacks can potentially target cloud computing systems, as most cloud computing systems offer services to many people who are not known to be trustworthy. Therefore, to protect that Virtual Machine from threats, a cloud computing system must incorporate some security monitoring framework. There is a tradeoff between the security level of the security system and the performance of the system in this scenario. If strong security is needed, then the service of stronger security using more rules or patterns is provided, since it needs much more computing resources. A new way of security system is introduced in this work in cloud environments to the VM on account of resources allocated to customers are ease. The main spike of Fog computing is part of the cloud server's work in the ongoing study tells the step-by-step cloud server to change the tremendous measurement of information because the endeavor apps are relocated to the cloud to keep the framework cost. The cloud server is devouring and changing a huge measure of information step by step to reduce complications. The Medical Data Health-Care (MDHC) records are stored in Cloud datacenters and Fog layer based on the guard intensity and the key is provoked for ingress the file. The monitoring center sustains the Activity Log, Risk Table, and Health Records. Cloud computing and Fog computing were combined in this paper to review data movement and safe information about MDHC.