• The Journal of the Korea Contents Association
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• 제6권10호
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• pp.9-16
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• 2006

In this paper, the acoustic model output of CSR(Continuous Speech Recognition) was used to analyze news data News database used in this experiment was consisted of 2,093 articles. Due to the low efficiency of language model, conventional Korean CSR is not appropriate to the analysis of news data. This problem could be handled successfully by introducing post-processing work of recognition result of acoustic model. The acoustic model more robust than language model in Korean environment. The result of post-processing work was made into KIF(Keyword information file). When threshold of acoustic model's output level was 100, 86.9% of whole target morpheme was included in post-processing result. At the same condition, applying length information based normalization, 81.25% of whole target morpheme was recognized. The purpose of normalization was to compensate long-length morpheme. According to experiment result, 75.13% of whole target morpheme was recognized KIF(314MB) had been produced from original news data(5,040MB). The decrease rate of absolute information met was approximately 93.8%.

• Korean Journal of Construction Engineering and Management
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• 제19권3호
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• pp.70-78
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• 2018

Due to the increasing concern about climate change, efforts to reduce environmental load are continuously being made in construction industry, and life cycle assessment (LCA) is being presented as an effective method to assess environmental load. Since LCA requires information on construction quantity used for environmental load estimation, however, it is not being utilized in the environmental review at the initial design stage where it is difficult to obtain such information. In this study, a construction quantity computation system based on the standard section was developed for the drainage facilities of the road and utilized in the model to calculate the environmental load. This model can estimate the environmental load by calculating the amount of resources required for LCA using only the information available at the initial design stage. To verify the validity of the model, five validation cases were applied and compared with the unit estimation model and the multiple regression analysis model. As a result, it is confirmed that the mean absolute error rate is 9.94%, which is relatively accurate and effective model in the initial design stage.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제17권1호
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• pp.216-238
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• 2023

In intelligent transportation systems, traffic management is an important task. The accurate forecasting of traffic characteristics like flow, congestion, and density is still active research because of the non-linear nature and uncertainty of the spatiotemporal data. Inclement weather, such as rain and snow, and other special events such as holidays, accidents, and road closures have a significant impact on driving and the average speed of vehicles on the road, which lowers traffic capacity and causes congestion in a widespread manner. This work designs a model for multivariate short-term traffic congestion prediction using SLSTM_AE-BiLSTM. The proposed design consists of a Bidirectional Long Short Term Memory(BiLSTM) network to predict traffic flow value and a Convolutional Neural network (CNN) model for detecting the congestion status. This model uses spatial static temporal dynamic data. The stacked Long Short Term Memory Autoencoder (SLSTM AE) is used to encode the weather features into a reduced and more informative feature space. BiLSTM model is used to capture the features from the past and present traffic data simultaneously and also to identify the long-term dependencies. It uses the traffic data and encoded weather data to perform the traffic flow prediction. The CNN model is used to predict the recurring congestion status based on the predicted traffic flow value at a particular urban traffic network. In this work, a publicly available Caltrans PEMS dataset with traffic parameters is used. The proposed model generates the congestion prediction with an accuracy rate of 92.74% which is slightly better when compared with other deep learning models for congestion prediction.

• Transactions of the Korean Society of Mechanical Engineers B
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• 제31권7호
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• pp.596-603
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• 2007

As increasing interest for soot emission. etc in combustion systems, various studies are being carried out for the reduction and measurement techniques of soot. Especially, laser induced incandescence is the useful measurement technique which has distinguished spatial and temporal resolution for primary particle size, volume fraction and aggregated particle size etc. Time resolved laser induced incandescence is the technique for measuring primary particle size that is decided to solve the signal decay rate which is related to the cooling behavior of heated particle by pulsed laser. The cooling behavior of heated particle is able to represent the heat and mass transfer model which are involved constants of soot property for surround gas temperature on the our previous work. In this study, it is applied to the time-dependence thermodynamic properties for soot temperature instead of constants of soot property for surround gas temperature and compared two different model results.

• Proceedings of the Korean Society of Soil and Groundwater Environment Conference
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• 한국지하수토양환경학회 2000년도 추계학술대회
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• pp.171-176
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• 2000

Bioremediation of hazardous hydrophobic organic compounds, such as polycyclic aromatic hydrocarbons (PAHs), is a major environmental concern due to their toxic and carcinogenic properties. Due to their hydrophobicity, the hydrophobic organic compounds are mainly associated with the soil organic matter or nonaqueous-phase liquids. A major question concerns the relationships between biodegradation and sorption. This work develops and utilizes a non- steady state model for evaluating the interactions between sorption and biodegradation of phenanthrene, a 3-ring PAH compound, in soil-slurry systems. The model includes sorption/desorption of a target compound, its utilization by microorganisms as a primary substrate existing in the dissolved phase and/or the sorbed phase in biomass and soil, oxygen transfer, and oxygen utilization as an electron acceptor. Biodegradation tests with phenanthrene were conducted in liquid and soil-slurry systems. The soil-slurry tests were performed with very different mass transfer rate: fast mass transfer in a flask test at 150 rpm, and slow mass transfer in a roller-bottle test at 2 rpm. In the slurry tests, phenanthrene was degraded more rapidly than in liquid tests, but with a similar rate in both slurry systems. Modeling analyses with several hypotheses indicate that a model without biodegradation of compound sorbed to the soil was not able to account for the rapid degradation of phenanthrene, particularly in the roller bottle slurry test. Reduced mass-transfer resistance to bacteria attached to the soil is the most likely phenomenon accounting for rapid sorbed-phase biodegradation.

• The Transactions of The Korean Institute of Electrical Engineers
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• 제62권6호
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• pp.870-875
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• 2013

After introducing diagnosis equipment power failure prevention activities for distribution system have become more active. To do facility diagnosis and maintenance work more efficiently we need to evaluate reliability for the system and should determine the priority line with appropriate criteria. Thus, to calculate risk factor for the power distribution line that are composed of many component facilities its historical failure events for the last 5 years are collected and analysed. The failure statics show that more than 60% of various failures are related to environment factors randomly and about 20% of the failures are refer to the aging. As a strategic evaluation system reflecting these environmental influence is needed, a system on the basis of the probabilistic approach related statical variables in terms of failure rate and failure probability of electrical components is proposed. The figures for the evaluation are derived from the field failure DB. With adopting Bayesian rule we can calculate easily about conditional probability query. The proposed evaluation system is demonstrated with model system and the calculated indices representing the properties of the model line are discussed.

• Nuclear Engineering and Technology
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• 제53권8호
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• pp.2556-2563
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• 2021

Metaheuristic algorithms can work well in solving or optimizing problems, especially those that require approximation or do not have a good analytical solution. Particle swarm optimization (PSO) is one of these algorithms. The response quality of these algorithms depends on the objective function and its regulated parameters. The nonlinear nature of the pressurized light-water nuclear reactor (PWR) dynamics is a significant target for PSO. The two-point kinetics model of this type of reactor is used because of fission products properties. The proportional-integral-derivative (PID) controller is intended to control the power level of the PWR at a short-time transient. The absolute error (IAE), integral of square error (ISE), integral of time-absolute error (ITAE), and integral of time-square error (ITSE) objective functions have been used as performance indexes to tune the PID gains with PSO. The optimization results with each of them are evaluated with the number of function evaluations (NFE). All performance indexes achieve good results with differences in the rate of over/under-shoot or convergence rate of the cost function, in the desired time domain.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제15권3호
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• pp.932-951
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• 2021

The effectiveness of testing in Model-based Testing (MBT) for Software Product Line (SPL) can be achieved by considering fault detection in test case. The lack of fault consideration caused test case in test suite to be listed randomly. Test Case Prioritization (TCP) is one of regression techniques that is adaptively capable to detect faults as early as possible by reordering test cases based on fault detection rate. However, there is a lack of studies that measured faults in MBT for SPL. This paper proposes a Test Case Prioritization (TCP) approach based on dissimilarity and string based distance called Last Minimal for Local Maximal Distance (LM-LMD) with Dice-Jaro-Winkler Dissimilarity. LM-LMD with Dice-Jaro-Winkler Dissimilarity adopts Local Maximum Distance as the prioritization algorithm and Dice-Jaro-Winkler similarity measure to evaluate distance among test cases. This work is based on the test case generated from statechart in Software Product Line (SPL) domain context. Our results are promising as LM-LMD with Dice-Jaro-Winkler Dissimilarity outperformed the original Local Maximum Distance, Global Maximum Distance and Enhanced All-yes Configuration algorithm in terms of Average Fault Detection Rate (APFD) and average prioritization time.

• IE interfaces
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• 제13권1호
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• pp.110-119
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• 2000

Resource-constrained project scheduling is to allocate limited resources to activities to optimize certain objective functions and to determine a start time for each activity in the project such that precedence constraints and resource requirements are satisfied. This study suggests a multi-project scheduling model which can level work loads, make the most of production capacity and restrain the delay of delivery by developing a heuristic algorithm which minimizes the project completion time and maximizes the load rate under resource constraints.

• Journal of the Korean Statistical Society
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• 제35권1호
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• pp.1-23
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• 2006

In this paper we consider an estimation of the discontinuous variance function in nonparametric heteroscedastic random design regression model. We first propose estimators of the change point in the variance function and then construct an estimator of the entire variance function. We examine the rates of convergence of these estimators and give results for their asymptotics. Numerical work reveals that using the proposed change point analysis in the variance function estimation is quite effective.