• Journal of Digital Convergence
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• v.12 no.7
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• pp.261-266
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• 2014

When the number of parameters in the time series model are diverse, it is hard to forecast because of the increasing error by a parameter estimation. If the homogeneity hypothesis which was obtained from the same model about severeal data for the time series is selected, it is easy to get the predictive value better. Nonlinear time-series panel data for each parameter for each time series, since there are so many parameters that are present, and the large number of parameters according to the parameter estimation error increases the accuracy of the forecast deteriorated. Panel present in the time series of multiple independent homogeneity is satisfied by a comprehensive time series to estimate and to test of the parameters. For studying about the homogeneity test for the m independent non-linear of the time series panel data, it needs to set the model and to make the normal conditions for the model, and to derive the homogeneity test statistic. Finally, it shows to obtain the limit distribution according to ${\chi}^2$ distribution. In actual analysis,, we can examine the result for the homogeneity test about nonlinear time series panel data which are 2 groups of stock price data.

• Journal of the Korean Institute of Intelligent Systems
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• v.26 no.3
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• pp.182-189
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• 2016

For high accuracy of forecast using numerical weather prediction models, we need to get weather observation data that are large and high dense. Korea Meteorological Administration (KMA) mantains Automatic Weather Stations (AWSs) to get weather observation data, but their installation and maintenance costs are high. Mini-AWS is a very compact automatic weather station that can measure and record temperature, humidity, and pressure. In contrast to AWS, costs of Mini-AWS's installation and maintenance are low. It also has a little space restraints for installing. So it is easier than AWS to install mini-AWS on places where we want to get weather observation data. But we cannot use the data observed from Mini-AWSs directly, because it can be affected by surrounding. In this paper, we suggest a correcting method for using pressure data observed from Mini-AWS as weather observation data. We carried out preconditioning process on pressure data from Mini-AWS. Then they were corrected by using machine learning methods with the aim of adjusting to pressure data of the AWS closest to them. Our experimental results showed that corrected pressure data are in regulation and our correcting method using SVR showed very good performance.

• Journal of the Korean Institute of Landscape Architecture
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• v.46 no.2
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• pp.1-13
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• 2018

This work discusses the major roles of digital technologies in the history of landscape architectural drawing, and offers a critique of the dominant trend towards realism in recent digital landscape representations. During the period of transition from conventional drawing tools, computer technologies generally functioned as mechanical tools to imitate prior manual techniques. Specifically, the GIS was served as a mechanical tool to efficiently process the manual layer cake; CAD software generally functioned to translate physical models to two-dimensional construction documents while graphic software generally functioned as a tool to perform processes similar to those of manual collage and montage techniques. Recent digital landscape drawings tend to adopt a realistic depiction like the painting of landscape appearance. In the representations, discernible traces of cutting and assembling are removed via graphic software; thus, the complete representations are perceived as if they were a copy of an actual landscape. The realistic images are an easy way to communicate with the public. However, it is difficult to achieve a full embodiment of all of the multisensory characteristics of a landscape through these visuals. They often deceive viewers by visualizing idealized conditions of not-yet-actualized landscapes and production of the final images takes up a large portion of the overall design process. Alternatively, 3D digital modeling of landscape performance and creative uses of digital technologies during the overall design process, as well as hybridized techniques with different drawing techniques and technologies, provide the opportunity to explore various aspects of a landscape.

• The Transactions of the Korea Information Processing Society
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• v.7 no.8
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• pp.2484-2496
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• 2000

High speed switches have been developing to interconnect a large number of nodes. It is important to analyze the switch performance under various conditions to satisfy the requirements. Queueing analysis, in general, has the intrinsic problem of large state space dimension and complex computation. In fact, The petri net is a graphical and mathematical model. It is suitable for various applications, in particular, manufacturing systems. It can deal with parallelism, concurrence, deadlock avoidance, and asynchronism. Currently it has been applied to the performance of computer networks and protocol verifications. This paper presents a framework for modeling and analyzing ATM switch using stochastic activity networks (SANs). In this paper, we provide the ATM switch model using SANs to extend easily and an approximate analysis method to apply A TM switch models, which significantly reduce the complexity of the model solution. Cell arrival process in output-buffered Queueing A TM switch with finite buffer is modeled as Markov Modulated Poisson Process (MMPP), which is able to accurately represent real traffic and capture the characteristics of bursty traffic. We analyze the performance of the switch in terms of cell-loss ratio (CLR), mean Queue length and mean delay time. We show that the SAN model is very useful in A TM switch model in that the gates have the capability of implementing of scheduling algorithm.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.11 no.3
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• pp.179-196
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• 1986

In this paper, the peformance of a statistical packet voice/data multiplexer is studied. In ths study we assume that in the packet voice/data multiplexer two separate finite queues are used for voice and data traffics, and that voice traffic gets priority over data. For the performance analysis we divide the output link of the multiplexer into a sequence of time slots. The voice signal is modeled as an (M+1) - state Markov process, M being the packet generation period in slots. As for the data traffic, it is modeled by a simple Poisson process. In our discrete time domain analysis, the queueing behavior of voice traffic is little affected by the data traffic since voice signal has priority over data. Therefore, we first analyze the queueing behavior of voice traffic, and then using the result, we study the queueing behavior of data traffic. For the packet voice multiplexer, both inpur state and voice buffer occupancy are formulated by a two-dimensional Markov chain. For the integrated voice/data multiplexer we use a three-dimensional Markov chain that represents the input voice state and the buffer occupancies of voice and data. With these models, the numerical results for the performance have been obtained by the Gauss-Seidel iteration method. The analytical results have been verified by computer simylation. From the results we have found that there exist tradeoffs among the number of voice users, output link capacity, voic queue size and overflow probability for the voice traffic, and also exist tradeoffs among traffic load, data queue size and oveflow probability for the data traffic. Also, there exists a tradeoff between the performance of voice and data traffics for given inpur traffics and link capacity. In addition, it has been found that the average queueing delay of data traffic is longer than the maximum buffer size, when the gain of time assignment speech interpolation(TASI) is more than two and the number of voice users is small.

• Journal of Dental Rehabilitation and Applied Science
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• v.19 no.4
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• pp.297-308
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• 2003

Face-bow is used to transfer models to the articulator in diagnosing the patient or treating problems associated with occlusion. However, there have been few reports on the reliability of the face-bow procedure and the relationship between the experience of the operator and the reliability of the face-bow procedure. The purposes of this study are to examine the reliability of the face-bow procedure and to evaluate whether the face-bow transferring has any training effect. Nine dentists working at M hospital conducted a face-bow transfer in one patient having a normal dentition and interdental relationship. The procedure was done two times a week for four weeks. The maxillary model was mounted to the articulator every time, then the landmarks on the maxillary right first molar, the maxillary left central incisor, and the maxillary left first molar were measured with a special three-dimensional instrument. These data were input into a computer, and evaluated statistically. The results were as follows ; 1. When examined with ANOVA test, the results were p=0.2040 in maxillary right first molar, p=0.0578 in maxillary left incisor, and p=0.1433 in maxillary left first molar. There was no significant(0< $p{\leq}0.05$). 2. Training 1) The correlation coefficient between trial and rejection was -0.578 when analyzed with T-distribution. The more we tried, the less errors we found. 2) When the S.D. of the first three trials was compared to the S.D. of the last three trials in face-bow transfer, the results showed that the former was larger than the latter in thirty-nine times, and the latter was larger than the former in fifteen times. The more we tried face-bow transfer, the less errors we found. 3. When the S.D. of x, y, z coordinates were examined, the S.D. of x coordinates had the largest measurement in five times, the S.D. of y coordinates had the largest measurement in four times, and the S.D. of z coordinates had the largest measurement in nine times. The possibility which the error can occur in z coordinate was the highest.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.10
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• pp.34-42
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• 2012

This paper analyses the energy saving basic power models in core IP networks, and proposes the adaptive buffer and burst scheme which is a possible energy saving method, and its implementation algorithm in core IP networks. Especially this paper describes the adaptive buffer and burst scheme dynamically varying the buffering interval B according to the input traffic volume of ingress router, and explains the operation principle of proposed scheme. This method is to adjust the buffering interval B according to input traffic volume of ingress router, that is increasing the interval B when input traffic volume is low, and decreasing the interval B when input traffic volume is high between some given interval regions. This method can gets the high energy saving effect as decreasing the transition number of idle/active in networks when input traffic volume is low, and decreasing the transition number of idle/active by the continuous of burst packets in transit router when input traffic volume is high. This paper shows the increasing of asleep rate for the energy saving of core IP networks and confirms the energy saving of core IP networks by the computer simulation. We confirmed that proposed method can be save the energy of IP networks by properly trade off network performances.

• The Journal of the Acoustical Society of Korea
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• v.37 no.1
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• pp.73-81
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• 2018

The quality of side scan sonar images is determined by the frequency of a sonar. A side scan sonar with a low frequency creates low-quality images. One of the factors that lead to low quality is a high-level noise. The noise is occurred by the underwater environment such as equipment noise, signal interference and so on. In addition, in order to compensate for the transmission loss of sonar signals, the received signal is recovered by TVG (Time-Varied Gain), and consequently the side scan sonar images contain non-homogeneous noise which is opposite to optic images whose noise is assumed as homogeneous noise. In this paper, the SSCS (Structural Sparsity based Compressive Sensing) is proposed for removing non-homogeneous noise. The algorithm incorporates both local and non-local models in a structural feature domain so that it guarantees the sparsity and enhances the property of non-local self-similarity. Moreover, the non-local model is corrected in consideration of non-homogeneity of noises. Various experimental results show that the proposed algorithm is superior to existing method.

• Journal of Korea Multimedia Society
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• v.9 no.11
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• pp.1503-1514
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• 2006

Today, consumers can access Internet from everywhere, therefore most commercial and other organizations provide their services on the Web. As the result, countless Web service systems are already on the Internet and more systems are under construction. Therefore, many researches of verifying that the system to be constructed will not have any deadlock and will run successfully without any problem at the early stage of design have been performed. Several Petri net based verification methods have also been published. However, they have focused on building Petri net models of Web service systems and none of them introduces efficient analysis methods. As a mathematical technique with which we can find the minimum duration time needed to fire all the transitions at least once and coming back to the initial marking in a timed net, the minimum cycle time method has been widely used in computer system analysis. A timed net is a modified version of a Petri net where a transition is associated with a delay time. A delay time used in a timed net is a constant even though the duration time associated with an event in the real world is a stochastic number in general. Therefore, this paper proposes 'Mixedly Distributed Stochastic Timed Net' where a transition can be associated with a stochastic number and introduce a minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net'. We also introduce a method of analysing a Web service system's response time with the minimum cycle time analysis method for 'Mixedly Distributed Stochastic Timed Net.'.

• Proceedings of the Korea Water Resources Association Conference
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• 2011.05a
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• pp.18-18
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• 2011

Climate change is impacting and will increasingly impact both the quantity and quality of the world's water resources in a variety of ways. In some areas warming climate results in increased rainfall, surface runoff, and groundwater recharge while in others there may be declines in all of these. Water quality is described by a number of variables. Some are directly impacted by climate change. Temperature is an obvious example. Notably, increased atmospheric concentrations of $CO_2$ triggering climate change increase the $CO_2$ dissolving into water. This has manifold consequences including decreased pH and increased alkalinity, with resultant increases in dissolved concentrations of the minerals in geologic materials contacted by such water. Climate change is also expected to increase the number and intensity of extreme climate events, with related hydrologic changes. A simple framework has been developed in New Zealand for assessing and predicting climate change impacts on water resources. Assessment is largely based on trend analysis of historic data using the non-parametric Mann-Kendall method. Trend analysis requires long-term, regular monitoring data for both climate and hydrologic variables. Data quality is of primary importance and data gaps must be avoided. Quantitative prediction of climate change impacts on the quantity of water resources can be accomplished by computer modelling. This requires the serial coupling of various models. For example, regional downscaling of results from a world-wide general circulation model (GCM) can be used to forecast temperatures and precipitation for various emissions scenarios in specific catchments. Mechanistic or artificial intelligence modelling can then be used with these inputs to simulate climate change impacts over time, such as changes in streamflow, groundwater-surface water interactions, and changes in groundwater levels. The Waimea Plains catchment in New Zealand was selected for a test application of these assessment and prediction methods. This catchment is predicted to undergo relatively minor impacts due to climate change. All available climate and hydrologic databases were obtained and analyzed. These included climate (temperature, precipitation, solar radiation and sunshine hours, evapotranspiration, humidity, and cloud cover) and hydrologic (streamflow and quality and groundwater levels and quality) records. Results varied but there were indications of atmospheric temperature increasing, rainfall decreasing, streamflow decreasing, and groundwater level decreasing trends. Artificial intelligence modelling was applied to predict water usage, rainfall recharge of groundwater, and upstream flow for two regionally downscaled climate change scenarios (A1B and A2). The AI methods used were multi-layer perceptron (MLP) with extended Kalman filtering (EKF), genetic programming (GP), and a dynamic neuro-fuzzy local modelling system (DNFLMS), respectively. These were then used as inputs to a mechanistic groundwater flow-surface water interaction model (MODFLOW). A DNFLMS was also used to simulate downstream flow and groundwater levels for comparison with MODFLOW outputs. MODFLOW and DNFLMS outputs were consistent. They indicated declines in streamflow on the order of 21 to 23% for MODFLOW and DNFLMS (A1B scenario), respectively, and 27% in both cases for the A2 scenario under severe drought conditions by 2058-2059, with little if any change in groundwater levels.