• Journal of Multimedia Information System
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• v.4 no.4
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• pp.163-170
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• 2017

Internet of things (IoT) is a new paradigm for collecting, processing and analyzing various contents in order to detect anomalies and to monitor particular patterns in a specific environment. The collected data can be used to discover new patterns and to offer new insights. IoT-enabled data mashup is a new technology to combine various types of information from multiple sources into a single web service. Mashup services create a new horizon for different applications. Environmental monitoring is a serious tool for the state and private organizations, which are located in regions with environmental hazards and seek to gain insights to detect hazards and locate them clearly. These organizations may utilize IoT - enabled data mashup service to merge different types of datasets from different IoT sensor networks in order to leverage their data analytics performance and the accuracy of the predictions. This paper presents an IoT - enabled data mashup service, where the multimedia data is collected from the various IoT platforms, then fed into an environmental cognition service which executes different image processing techniques such as noise removal, segmentation, and feature extraction, in order to detect interesting patterns in hazardous areas. The noise present in the captured images is eliminated with the help of a noise removal and background subtraction processes. Markov based approach was utilized to segment the possible regions of interest. The viable features within each region were extracted using a multiresolution wavelet transform, then fed into a discriminative classifier to extract various patterns. Experimental results have shown an accurate detection performance and adequate processing time for the proposed approach. We also provide a data mashup scenario for an IoT-enabled environmental hazard detection service and experimentation results.

• The Transactions of the Korea Information Processing Society
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• v.4 no.6
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• pp.1433-1442
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• 1997

Algorithm design is needed to optimized bandwidth which satisfy quality of service(QoS) requirements of vary traffic classes for Multimedia service in ATM networks. The diverse flow characteristics e.g., burstiness, bit rate and burst length, have to guarantee the different quality of service(QoS) requirements in Asynchronous Transfer Mode(ATM). The QoS parameter may be measured in terms of cell loss probability and maximum cell dely. In this paper, we consider the ATM networks which the virtual path(vip) concept is implemented by applying the Markov Modulated Deterministic Process method. We develop an efficient algorithm to computer the minimum capacity required to satisfy all the QoS requirements when multiple classes of on-off source are multiplexed on single VP. Using above the result, we propose a simple algorithm to determine the VP combination to achieve the near optimum of total capacity required for satisfying the individual QoS requirements. Numerical results are also presented to demonstrate the performance of the algorithm, when compared to the optimal total capacity required.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.6
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• pp.1085-1094
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• 1994

We propose a traffic flow control scheme of B-NT with temporary cell buffering and selective cell discarding to prevent congestion state of the network nodes in B-ISDN systems to reduce or suppress output cell strams towards T interface. We define the states of the network nodes as normal, pre-congestion, and congestion. In a pre-congestion state, the loss-sensitive traffic is temporarily buffered to slow down the rate of the output traffic streams. In a congestion state, the delay-sensitive traffic is selectively discarded to suppress the output traffic streams as possible in addition to the cell buffering. We model the input cell streams and the states of the network nodes with Interrupted Bernoulli Process and 3-state Markov chain to analyze the performance of the proposed scheme in the B-NT system. The appropriate size of the cell buffer is explored by means of simulation and the influence on the performance of the proposed scheme by the network node state is discussed. As results, more than 2,00 cells of buffer size is needed for the control of medium of lower than the medium, degree of congestion occurrence in the network node while the control of high degree of congestion occurrence is nearly impossible.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.24 no.9A
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• pp.1372-1382
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• 1999

The major source of errors in high-speed networks such as Broadband ISDN(B-lSDN) is buffer overflow during congested conditions. These congestion errors are the dominant sources of errors in 1high-speed networks and result in cell losses. Conventional communication protocols use error detection and retransmission to deal with lost packets and transmission errors. However, these conventional ARQ(Automatic Repeat Request) methods are not suitable for the high-speed networks since the transmission delay due to retransmissions becomes significantly large. As an alternative, we have presented a method to recover consecutive cell losses using forward error correction(FEC) in ATM(Asynchronous Transfer Mode)networks to reduce the problem. The performance estimation based on the cell discard process model has showed our method can reduce the cell loss rate substantially. Also, the performance estimations in ATM networks by interleaving and IP multicast service are discussed.

• The KIPS Transactions:PartD
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• v.18D no.1
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• pp.67-80
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• 2011

On an automated business document processing system maintaining financial data, errors on query based retrieval of numbers are critical to overall performance and usability of the system. Automatic spelling correction methods have been emerged and have played important role in development of information retrieval system. However scope of the methods was limited to the symbols, for example alphabetic letter strings, which can be reserved in the form of trainable templates or custom dictionary. On the other hand, numbers, a sequence of digits, are not the objects that can be reserved into a dictionary but a pure markov sequence. In this paper we proposed a new OCR model for spelling correction for numbers using the multiple streams and the context based correction on top of probabilistic information retrieval framework. We implemented the proposed error correction model as a sub-module and integrated into an existing automated invoice document processing system. We also presented the comparative test results that indicated significant enhancement of overall precision of the system by our model.

• Journal of the Korean Society for Railway
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• v.12 no.6
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• pp.1043-1048
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• 2009

PES (Programmable Electronic System) is used by software development for the train control system. PES has been widely used in real world and consists of hardware, firmware and application software. The PES are easily apply to many applications because its implementation has high flexibility. Many safety critical functions are realized through software in safety critical system. Normally, it is difficult to detect failures for PES system because the PES is too sophisticated to identify sources of the failure. So, the reliability analysis is needed by using software fault tolerance techniques. Currently, there are the recovery block, distributed recovery block, N-version programming, N self-checking programming in fault tolerance techniques. In this paper, the models of recovery block and N-version programming in software fault tolerance techniques are suggested by using the Markov model. Also, the reliability in the train control system is analyzed through changing time. The fault occupancy rates of the program, adjustment test and voter are stationary. So, the relation between time and reliability is presented by using Matlab program. In the result of reliability, the reliability of recovery block is more high than N-version programming in case of the same number of substitution block.

• The Korean Journal of Applied Statistics
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• v.18 no.2
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• pp.281-296
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• 2005

This article summarizes our research on estimation of area-specific and time-adjusted rainfall rates during 2004KEOP (Korea enhanced observation period: June 1, $2004{\sim}$ August 31, 2004). The rainfall rate is defined as the proportion of rainfall days per week and areas are consisting of Haenam, Yeosu, Janghung, Heuksando, Gwangju, Mokpo, Jindo, and Wando. Our objectives are to analyze periodicity in area-specific precipitation and the meteorological measures and investigate the relationships between the geographic pattern of the rainfall rates and the corresponding pattern in potential explanatory covariates such as temperature, wind, wind direction, pressure, and humidity. A generalized linear model is introduced to implement the objectives and the patterns are estimated by considering a set of rainfall rates produced using samples from the posterior distribution of the population rainfall rates.

• The Korean Journal of Applied Statistics
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• v.31 no.2
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• pp.287-301
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• 2018

It is common to encounter count data with excess zeros in various research fields such as the social sciences, natural sciences, medical science or engineering. Such count data have been explained mainly by zero-inflated Poisson model and extended models. Zero-inflated count data are also often correlated or clustered, in which random effects should be taken into account in the model. Frequentist approaches have been commonly used to fit such data. However, a Bayesian approach has advantages of prior information, avoidance of asymptotic approximations and practical estimation of the functions of parameters. We consider a Bayesian zero-inflated Poisson regression model with random effects for correlated zero-inflated count data. We conducted simulation studies to check the performance of the proposed model. We also applied the proposed model to smoking behavior data from the Regional Health Survey (2015) of the Korea Centers for disease control and prevention.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.194-202
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• 2019

Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters' posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

• Water for future
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• v.26 no.3
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• pp.113-124
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• 1993

This study aims at the evaluation of the stationary distribution and the emptiness passage time for the effectiveness of water utility in the Keumgang estuary reservoir by two-step transition model. It was taken discrete Markovian correlated inflows for the joint probability of inflows and storage, and was used binomial distribution for inflows distribution. As the results, it was decreased from 0.952 to 0.904 the emptiness probability of the reservoir stationary distribution during 1952-1980, and from 0.900 to 0.829 during 1981-1989, and the average emptiness passage time was increased from 23 days to 37 days during 1952-1980, and from 29 days to 61 days during 1981-1989 at low state of storage. From this, it is found that the emptiness passage time is varied with the increase of the inflows auto-correlation coefficient in the Keumgang estuary reservoir. Therefore, it is understood that auto-correlation coefficient must be taken into consideration for the evaluation of water utility in a small reservoir at drought time.