• The KIPS Transactions:PartC
• /
• v.18C no.1
• /
• pp.51-60
• /
• 2011

In this paper, we propose a P4P based P2P system for live multimedia streaming services. In order to satisfy the strict requirement of delay in live multimedia streaming, in the proposed scheme, the P4P server of network provider provides the network status information related to delay and congestion links to P2P system in addition to the information to optimize the network resource utilization. The P2P system server, then, makes the peering suggestion based on the information from the network server. Also, we propose a playback synchronization mechanism that enable each peer to start the playback within the limited variation from the playback positions of source peer. Through the simulation results, it is shown that the proposed scheme not only deals with the original objective of the P4P framework, i.e., effective network utilization, but also the live multimedia streaming requirements. It enhances the playback continuity, and reduces the playback start-up latency and the control overhead. In addition, the proposed scheme reduces the variation in playback positions of the peers.

• Journal of KIISE:Computer Systems and Theory
• /
• v.33 no.12
• /
• pp.867-879
• /
• 2006

This paper concerns fast and time accurate HW/SW cosimulation for MPSoC(Multi-Processor System-on-chip) architecture where multiple software and/or hardware components exist. It is becoming more and more common to use MPSoC architecture to design complex embedded systems. In cosimulation of such architecture, as the number of the component simulators participating in the cosimulation increases, the time synchronization overhead among simulators increases, thereby resulting in low overall cosimulation performance. Although SystemC cosimulation frameworks show high cosimulation performance, it is in inverse proportion to the number of simulators. In this paper, we extend the novel technique, called virtual synchronization, which boosts cosimulation speed by reducing time synchronization overhead: (1) SystemC simulation is supported seamlessly in the virtual synchronization framework without requiring the modification on SystemC kernel (2) Parallel execution of component simulators with virtual synchronization is supported. We compared the performance and accuracy of the proposed parallel SystemC cosimulation framework with MaxSim, a well-known commercial SystemC cosimulation framework, and the proposed one showed 11 times faster performance for H.263 decoder example, while the accuracy was maintained below 5%.

• Journal of Korea Water Resources Association
• /
• v.53 no.9
• /
• pp.647-660
• /
• 2020

The objectives of this study are to develop a framework for selecting multi-GCMs considering Asia monsoon characteristics and assess it's applicability. 12 climate variables related to monsoon climates are selected for GCM selection. The framework for selecting multi-GCMs includes the evaluation matrix of GCM performance based on their capability to simulate historical climate features. The climatological patterns of 12 variables derived from individual GCM over the summer monsoon season during the past period (1976-2005) and they are compared against observations to evaluate GCM performance. For objective evaluation, a rigorous scoring rule is implemented by comparing the GCM performance based on the results of statistics between historical simulation derived from individual GCM and observations. Finally, appropriate 5 GCMs (NorESM1-M, bcc-csm1-m, CNRM-CM5, CMCC-CMS, and CanESM2) are selected in consideration of the ranking of GCM and precipitation performance of each GCM. The selected 5 GCMs are compared with the historical observations in terms of monsoon season and monthly mean to validate their applicability. The 5 GCMs well capture the observational climate characteristics of Asia for the 12 climate variables also they reduce the bias between the entire GCM simulations and the observational data. This study demonstrates that it is necessary to consider various climate variables for GCM selection and, the method introduced in this study can be used to select more reliable climate change scenarios for climate change assessment in the Asia region.

• Journal of KIISE:Software and Applications
• /
• v.29 no.7
• /
• pp.436-449
• /
• 2002

This paper describes on our experience of developing the Database Connector as an interconnection method between multimedia database, and the streaming framework. It is possible to support diverse and mature multimedia database services such as retrieval and join operation during the streaming if an interconnection method is provided in between streaming system and multimedia databases. The currently available interconnection schemes, however have mainly used the file systems or the relational databases that are Implemented with separated form of meta data, which deafs with information of multimedia contents, and streaming data which deals with multimedia data itself. Consequently, existing interconnection mechanisms could not come up with many virtues of multimedia database services during the streaming operation. In order to resolve these drawbacks, we propose a novel scheme for an interconnection between streaming framework and multimedia database, called the Inter-Process Communication (IPC) based Database connector, under the assumption that two systems are located in a same host. We define four transaction primitives; Read, Write, Find, Play, as well as define the interface for transactions that are implemented based on the plug-in, which in consequence can extend to other multimedia databases that will come for some later years. Our simulation study show that performance of the proposed IPC based interconnection scheme is not much far behind compared with that of file systems.

• Korean Journal of Optics and Photonics
• /
• v.29 no.6
• /
• pp.268-274
• /
• 2018

In this study we suggest a humidity-sensitive color sensor using a one-dimensional photonic crystal and Hong Kong University of Science and Technology-1 (HKUST-1), which is a metal-organic framework (MOF) substance. One-dimensional photonic crystals have a photonic band gap, due to a periodic refractive-index change, and block and reflect light components in a specific wavelength band. The refractive index of HKUST-1 differs in dry and humid environments. Herein we designed a sensor using the presence of the photonic band gap, with FDTD simulation. As a result of optical analysis, the color conversion of the reflected light was superior to the color conversion of the transmitted light. When the center wavelength of the photonic band gap was 550 nm, the maximum peak value of the wet environment increased by a factor of about 9.5 compared to the dry environment, and the color conversion from achromatic to green was excellent as a sensor. The results of this study suggest the application of MOF materials to moisture sensors, and the nanostructure design of MOF materials will expand the applications to industrial devices.

• Journal of the Korea Convergence Society
• /
• v.10 no.9
• /
• pp.37-45
• /
• 2019

In recent years, the emergence of virtual reality (VR Virtual Reality) technology has provided a new model of safety education, enabling users to learn and respond to disasters in a virtual safety education environment. However, the related VR products related to domestic and foreign R & D are relatively simple, there is no practical training on specific accident, and it is not practical enough to play a sufficient role in safety education. In this paper, the problems and disadvantages of VR technology applied in the field of automobile safety education as an example of automobile accident among the types of disasters are examined, and a system framework of automotive safety education based on VR technology is proposed. The vehicle safety education system proposed in this paper will help users to improve driving safety consciousness, to acquire safety knowledge in driving, and to acquire driving safety skill which is very important for automobile safety education. In addition, the design and production methods of safety education based on VR technology are considered to have important reference implications for the application of modern teaching and teaching theory by integrating with VR technology and developing related teaching materials products and finally introducing education.

• Journal of the Korea Academia-Industrial cooperation Society
• /
• v.16 no.11
• /
• pp.7534-7540
• /
• 2015

In this paper, we set up a vista point overlooking the focus of new research center placed on the existing research literature and point to the selection of books, reports or studies actually suggested focusing on topics such as for landscape simulation evaluation. To re-organize and classify a number of items were presented to spill the evaluation items of this view point selection via the SPSS Statistics. Evaluation items 16 through a professional survey to establish a concrete and systematic plan with selected research results leaked technical characteristics of the view that detailed questions to the factors of technical characteristics and population-specific comparisons through factor analysis in the first, landscapes simulation The views were set out. Second, if you set 16 classified by type of view that considering a similar nature or characteristics depending on the properties of the view that publicity, overlooking castle, the castle was divided into three types of places. Third, the views point for the public good are three items, vista point at which the gender perspective has six items that gender point of view places is set to seven items, was set up to view the most appropriate place to point gender. These results provide a framework for analysis and future system reliability and landscape simulation evaluation study is expected to be used as reference material.

• Journal of The Geomorphological Association of Korea
• /
• v.20 no.4
• /
• pp.85-99
• /
• 2013

The objective of this paper is to analyze the spatial distribution of errors in the DEM generated using waterlines from multi-temporal remote sensing data and to assess flood vulnerability. Unlike conventional research in which only global statistics of errors have been generated, this paper tries to quantitatively analyze the spatial distribution of errors from a probabilistic viewpoint using geostatistical simulation. The initial DEM in Baramarae tidal flats was generated by corrected tidal level values and waterlines extracted from multi-temporal Landsat data in 2010s. When compared with the ground measurement height data, overall the waterline-based DEM underestimated the actual heights and local variations of the errors were observed. By applying sequential Gaussian simulation based on spatial autocorrelation of DEM errors, multiple alternative error distributions were generated. After correcting errors in the initial DEM with simulated error distributions, probabilities for flood vulnerability were estimated under the sea level rise scenarios of IPCC SERS. The error analysis methodology based on geostatistical simulation could model both uncertainties of the error assessment and error propagation problems in a probabilistic framework. Therefore, it is expected that the error analysis methodology applied in this paper will be effectively used for the probabilistic assessment of errors included in various thematic maps as well as the error assessment of waterline-based DEMs in tidal flats.

• The Journal of The Korea Institute of Intelligent Transport Systems
• /
• v.21 no.2
• /
• pp.183-200
• /
• 2022

A variety of simulation approaches based on automated driving technologies have been proposed to develop traffic operations strategies to prevent traffic crashes and alleviate congestion. The maneuver of simulated autonomous vehicles (AVs) needs to be realistic and be effectively differentiated from the behavior of manually driven vehicles (MVs). However, the verification of simulated AV maneuvers is limited due to the difficulty in collecting actual AVs trajectory and interaction data with MVs. The purpose of this study is to develop a methodology to evaluate the suitability of AV maneuvers based on both driving and traffic simulation experiments. The proposed evaluation framework includes the requirements for the behavior of individual AVs and the traffic stream performance resulting from the interactions with surrounding vehicles. A driving simulation approach is adopted to evaluate the feasibility of maneuvering of individual AVs. Meanwhile, traffic simulations are used to evaluate whether the impact of AVs on the performance of traffic stream is reasonable. The outcome of this study is expected to be used as a fundamental for the design and evaluation of transportation systems using automated driving technologies.

• Journal of Intelligence and Information Systems
• /
• v.18 no.4
• /
• pp.43-57
• /
• 2012

To enhance the competitive advantage in a constantly changing business environment, an enterprise management must make the right decision in many business activities based on both internal and external information. Thus, providing accurate information plays a prominent role in management's decision making. Intuitively, historical data can provide a feasible estimate through the forecasting models. Therefore, if the service department can estimate the service quantity for the next period, the service department can then effectively control the inventory of service related resources such as human, parts, and other facilities. In addition, the production department can make load map for improving its product quality. Therefore, obtaining an accurate service forecast most likely appears to be critical to manufacturing companies. Numerous investigations addressing this problem have generally employed statistical methods, such as regression or autoregressive and moving average simulation. However, these methods are only efficient for data with are seasonal or cyclical. If the data are influenced by the special characteristics of product, they are not feasible. In our research, we propose a forecasting framework that predicts service demand of manufacturing organization by combining Case-based reasoning (CBR) and leveraging an unsupervised artificial neural network based clustering analysis (i.e., Self-Organizing Maps; SOM). We believe that this is one of the first attempts at applying unsupervised artificial neural network-based machine-learning techniques in the service forecasting domain. Our proposed approach has several appealing features : (1) We applied CBR and SOM in a new forecasting domain such as service demand forecasting. (2) We proposed our combined approach between CBR and SOM in order to overcome limitations of traditional statistical forecasting methods and We have developed a service forecasting tool based on the proposed approach using an unsupervised artificial neural network and Case-based reasoning. In this research, we conducted an empirical study on a real digital TV manufacturer (i.e., Company A). In addition, we have empirically evaluated the proposed approach and tool using real sales and service related data from digital TV manufacturer. In our empirical experiments, we intend to explore the performance of our proposed service forecasting framework when compared to the performances predicted by other two service forecasting methods; one is traditional CBR based forecasting model and the other is the existing service forecasting model used by Company A. We ran each service forecasting 144 times; each time, input data were randomly sampled for each service forecasting framework. To evaluate accuracy of forecasting results, we used Mean Absolute Percentage Error (MAPE) as primary performance measure in our experiments. We conducted one-way ANOVA test with the 144 measurements of MAPE for three different service forecasting approaches. For example, the F-ratio of MAPE for three different service forecasting approaches is 67.25 and the p-value is 0.000. This means that the difference between the MAPE of the three different service forecasting approaches is significant at the level of 0.000. Since there is a significant difference among the different service forecasting approaches, we conducted Tukey's HSD post hoc test to determine exactly which means of MAPE are significantly different from which other ones. In terms of MAPE, Tukey's HSD post hoc test grouped the three different service forecasting approaches into three different subsets in the following order: our proposed approach > traditional CBR-based service forecasting approach > the existing forecasting approach used by Company A. Consequently, our empirical experiments show that our proposed approach outperformed the traditional CBR based forecasting model and the existing service forecasting model used by Company A. The rest of this paper is organized as follows. Section 2 provides some research background information such as summary of CBR and SOM. Section 3 presents a hybrid service forecasting framework based on Case-based Reasoning and Self-Organizing Maps, while the empirical evaluation results are summarized in Section 4. Conclusion and future research directions are finally discussed in Section 5.