• Smart Structures and Systems
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• v.29 no.1
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• pp.93-103
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• 2022

With the wider availability of sensor technology through easily affordable sensor devices, several Structural Health Monitoring (SHM) systems are deployed to monitor vital civil infrastructure. The continuous monitoring provides valuable information about the health of the structure that can help provide a decision support system for retrofits and other structural modifications. However, when the sensors are exposed to harsh environmental conditions, the data measured by the SHM systems tend to be affected by multiple anomalies caused by faulty or broken sensors. Given a deluge of high-dimensional data collected continuously over time, research into using machine learning methods to detect anomalies are a topic of great interest to the SHM community. This paper contributes to this effort by proposing a relatively new time series representation named "Shapelet Transform" in combination with a Random Forest classifier to autonomously identify anomalies in SHM data. The shapelet transform is a unique time series representation based solely on the shape of the time series data. Considering the individual characteristics unique to every anomaly, the application of this transform yields a new shape-based feature representation that can be combined with any standard machine learning algorithm to detect anomalous data with no manual intervention. For the present study, the anomaly detection framework consists of three steps: identifying unique shapes from anomalous data, using these shapes to transform the SHM data into a local-shape space and training machine learning algorithms on this transformed data to identify anomalies. The efficacy of this method is demonstrated by the identification of anomalies in acceleration data from an SHM system installed on a long-span bridge in China. The results show that multiple data anomalies in SHM data can be automatically detected with high accuracy using the proposed method.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.4008-4023
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• 2022

Since machine learning was introduced into cross-site scripting (XSS) attack detection, many researchers have conducted related studies and achieved significant results, such as saving time and labor costs by not maintaining a rule database, which is required by traditional XSS attack detection methods. However, this topic came across some problems, such as poor generalization ability, significant false negative rate (FNR) and false positive rate (FPR). Moreover, the automatic clustering property of graph convolutional networks (GCN) has attracted the attention of researchers. In the field of natural language process (NLP), the results of graph embedding based on GCN are automatically clustered in space without any training, which means that text data can be classified just by the embedding process based on GCN. Previously, other methods required training with the help of labeled data after embedding to complete data classification. With the help of the GCN auto-clustering feature and labeled data, this research proposes an approach to detect XSS attacks (called GCNXSS) to mine the dependencies between the units that constitute an XSS payload. First, GCNXSS transforms a URL into a word homogeneous graph based on word co-occurrence relationships. Then, GCNXSS inputs the graph into the GCN model for graph embedding and gets the classification results. Experimental results show that GCNXSS achieved successful results with accuracy, precision, recall, F1-score, FNR, FPR, and predicted time scores of 99.97%, 99.75%, 99.97%, 99.86%, 0.03%, 0.03%, and 0.0461ms. Compared with existing methods, GCNXSS has a lower FNR and FPR with stronger generalization ability.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.1
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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.

• Nuclear Engineering and Technology
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• v.25 no.1
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• pp.154-165
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• 1993

A stochastic method using continuous time Markov process is presented to model the one-dimensional convective nuclide transport in geologic media, which have usually heterogeneous feature in physical/geochemical parameters such as velocity, dispersion coefficient, and retardation factor resulting poor description by conventional deterministic advection-dispersion model. The primary desired quantities from a stochastic model are the mean values and variance of the state variables as a function of time. The time-dependent probability distributions of nuclides are presented for each discretized compartment given the volumetric groundwater flux and the intensity of transition. Since this model is discrete in medium space, physical/geochemical parameters which affect nuclide transport can be easily incorporated for the heterogeneous media as well as remarkably layered media having spatially varied parameters. Even though the Markov process model developed in this study was shown to be sensitive to the number of discretized compartments showing numerical dispersion as the number of compartments are increased, this could be easily calibrated by comparing with the analytical deterministic model.

• Nuclear Engineering and Technology
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• v.19 no.3
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• pp.192-197
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• 1987

Two-point kinetic equations for a compact-core-with-bulky-D$_2$O-reflector system were developed. A unique feature of the system is that certain fission gammas create retarded photoneutrons in the D$_2$O reflector by (ｒ, n) reaction. Coupling effect between the core and the reflector was investigated by simulating power transients with various ramp reactivity insertions. Special attention was paid to the phenomenon associated with spatial separation of photoneutrons and their precursors. Simulations show that accuracy of the two-point model is comparable with that of space-dependent approach. Also it is found that the explicily expressed photoneutron terms in the reflector equation slow down the power transient compared to non-photoneutron expressions. Detectors for reactor power control purpose prefer to be deployed in the core zone to be able to accurately perdict transient power.

• Journal of the Korea Society of Computer and Information
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• v.14 no.3
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• pp.173-182
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• 2009

In this paper, we studied about the extraction of the parameter and implementation of speechreading system to recognize the Korean 8 vowel. Face features are detected by amplifying, reducing the image value and making a comparison between the image value which is represented for various value in various color space. The eyes position, the nose position, the inner boundary of lip, the outer boundary of upper lip and the outer line of the tooth is found to the feature and using the analysis the area of inner lip, the hight and width of inner lip, the outer line length of the tooth rate about a inner mouth area and the distance between the nose and outer boundary of upper lip are used for the parameter. 2400 data are gathered and analyzed. Based on this analysis, the neural net is constructed and the recognition experiments are performed. In the experiment, 5 normal persons were sampled. The observational error between samples was corrected using normalization method. The experiment show very encouraging result about the usefulness of the parameter.

• The Journal of the Acoustical Society of Korea
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• v.26 no.2
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• pp.75-79
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• 2007

We propose an effective voice-based gender identification method using a support vector machine(SVM). The SVM is a binary classification algorithm that classifies two groups by finding the voluntary nonlinear boundary in a feature space and is known to yield high classification performance. In the present work, we compare the identification performance of the SVM with that of a Gaussian mixture model(GMM) using the mel frequency cepstral coefficients(MFCC). A novel means of incorporating a features fusion scheme based on a combination of the MFCC and pitch is proposed with the aim of improving the performance of gender identification using the SVM. Experiment results indicate that the gender identification performance using the SVM is significantly better than that of the GMM. Moreover, the performance is substantially improved when the proposed features fusion technique is applied.

• Journal of the Korea Society of Computer and Information
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• v.29 no.3
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• pp.83-90
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• 2024

In this paper, we propose a solution to apply a proximity voice dialog system to voice dialog technology, one of the interaction systems in multimedia environments. A voice dialog between multiple users in a multimedia space is designed by adjusting the volume of the voice according to the distance between the user avatars and muting the user who is beyond the audible distance. The main feature of this research is a reliable UDP-based active server system that delivers low-quality voice data to users who are far away based on distance and does not transmit voice data to users who enter the inaudible area for economic development. The performance of the proposed system was measured in a previously completed project based on the Unity game engine, and it is expected that the system proposed in this research will be actively used in environments that provide interaction between multiple users such as met averse content and real-time battle action games.

• Journal of the Korean Institute of Rural Architecture
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• v.26 no.2
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• pp.35-40
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• 2024

This study examines the classification and typical characteristics of 148 owner shop houses existing in the historical city center of Cheongju. First, they can be classified into single-story, middle-story, and divided types according to the distribution of residential and commercial functions. The single-story(36) has 'ㅡ', 'ㄱ', and 'narrow and deep'-shaped arrangement, with stores on the front and houses on the rear. The middle-story second floor(89) is divided into a first-story store and a second-story house, and the third floor(23) has different functions for each floor, but more than half of them have houses on the second and third floors. Among the total, there are also 16 cases in which the division type is taken with different construction times and structures. Second, in the position of the stairs connected to the upper floor among the middle-floor types(112), the outer stair type(52) to separate from the living space while making the most of the stores on the first floor accounts for 47%, but the biggest feature is that the inner staircase type(34) with privacy reaches 30%. The rear stair room type(26) entering through alleyways or private yards is also 23%. Third, the front pillar spacing varies from 1bay to 4bay in appearance, but the 2bay type on the 2nd floor and the 1bay type on the 3rd floor occupy the largest proportion. This exterior type is a characteristic of a owner shop house that can measure the range of personal ownership. Despite the conflicting functions of stores and houses, 35~40% of the cases are in which the opening positions of the upper and lower floors are unified.

• The Korean Journal of Air & Space Law and Policy
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• v.27 no.2
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• pp.3-27
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• 2012

The Warsaw Convention for the Unification of Certain Rules Relating to International Carriage by Air was adopted in 1929. In 1999, the ICAO adopted the Montreal Convention for the Unification of Certain Rules for International Carriage by Air vastly modernizing the unification of private air law. The Montreal Convention replaced the instruments of the Warsaw system, and came into force on 4 November 2003. The Montreal Convention is not only an international convention. It has also exercised a considerable influence on national legislation. Korea has made the national legislation of the Part VI the Carriage by Air of Commercial Act on April 29, 2011, and it has brought into force on November 24, 2011. The national legislation of the Part VI the Carriage by Air of Commercial Act of Korea has the provisions on the liability for damage caused to passenger, the liability for damage caused to baggage, and the liability for damage caused to cargo. The main feature of the liability regime of the air carrier under the Montreal Convention is the two-tier liability system for death or injury of the passenger with strict liability up to 100,000 SDR and presumptive liability with a reversed burden of proof without any limit above that threshold. The national legislation of the Part VI the Carriage by Air of the Commercial Act of Korea has adopted the main principles of the liability of the air carrier under the Montreal Convention. In conclusion, the national legislation relating to the liability of the air carrier by the Korean government will contribute to settle efficiently the dispute on the carrier' liability in respect of the carriage of passengers, baggage and cargo by air, and to provide proper compensation to the passenger or consignor who has suffered damage, subject to the defenses and limitations it sets out.