• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.10a
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• pp.180-181
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• 2018

JPEG is a most widely used standard image compression technology. This research introduces the JPEG image compression algorithm and describes each step in the compression and decompression. Image compression is the application of data compression on digital images. The DCT (discrete cosine transform) is a technique for converting a time domain to a frequency domain. First, the image is divided into 8 by 8 pixel blocks. Second, working from top to bottom left to right, the DCT is applied to each block. Third, each block is compressed through quantization. Fourth, the array of compressed blocks that make up the image is stored in a greatly reduced amount of space. Finally if desired, the image is reconstructed through decompression, a process using IDCT (inverse discrete cosine transform).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.2
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• pp.513-520
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• 2010

The degradation phenomenon caused by noises significantly corrupts digitalized data. Therefore, a variety of methods to preserve the edge component of signals and remove noise simultaneously have been used in time domain and frequency domain. In this paper, we have proposed a new noise reduction algorithm using wavelet approximation coefficients to reduce the mixed noise overlapping the signal. The proposed algorithm adopts the distribution characteristics of the error function which is obtained by accumulating the wavelet approximation coefficients, in order to improve the capability to separate edges of the signal and noises.

• East Asian Journal of Business Economics (EAJBE)
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• v.9 no.1
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• pp.71-81
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• 2021

Purpose - This study verified the mediating effect of volunteer activities in the influence of global citizenship consciousness on human rights sensitivity of university students majoring in business administration. Research design, data, and methodology - The survey was conducted on 172 4-year college students in G City, Korea. SPSS 23.0 program was used to perform frequency analysis, descriptive statistics analysis, correlation analysis, reliability analysis, and multiple regression analysis. In addition, path analysis was conducted to confirm the mediating effect of volunteer activities. Result - First, the "justice domain" had a statistically significant effect on human rights sensitivity. Second, the "cognitive domain" had a positive and significant effect on volunteer participation. Third, the volunteer participation of university students majoring in business administration had a positive and significant effect on human rights sensitivity. Fourth, in the relationship between global citizenship consciousness and human rights sensibility of university students, volunteer participation had a partial mediating effect. Conclusion - The period of college enrollment is an important time to establish life goals and strategies as adults. Therefore, if the university environment is built to grow into a healthy global citizen, it will help to cultivate global competence and the "sensitivity to human rights" that is more emphasized in the era of the 4th industrial revolution.

• Journal of the Korean Society of Visualization
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• v.19 no.3
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• pp.92-98
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• 2021

Large Eddy Simulation (LES) has been popularly applied and used in the last several decades to simulate turbulent boundary layer in the numerical domain. A fully developed turbulent boundary layer has also been applied to predict the complicated wake flow behind bluff bodies. In this study we aimed to generate an artificial turbulent boundary layer, which is based on an exponential correlation function, and generates a series of realistic three-dimensional velocity data in two-dimensional inlet section which are correlated both in space and in time. The results suggest its excellent capability for high Reynolds number flows. To make an effective generation, a hexahedral mesh has been used and Cholesky decomposition was applied to possess suitable turbulent statistics such as the randomness and correlation of turbulent flow. As a result, the flow characteristics in the domain and fluctuating pressure near the wall are very close to those of fully developed turbulent boundary layers.

• Geomechanics and Engineering
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• v.29 no.1
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• pp.53-63
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• 2022

Simplified analytical solutions are developed for the dynamic analyses of an axially loaded pile foundation embedded in a transverse-isotropic, fluid-filled, poro-visco-elastic soil with rigid substratum. The pile is modeled as a viscoelastic Rayleigh-Love rod, while the surrounding soil is regarded as a transversely isotropic, liquid-saturated, viscoelastic, porous medium of which the mechanical behavior is represented by the Boer's poroelastic media model and the fractional derivative model. Upon the separation of variables, the frequency-domain responses for the impedance function of the pile top, and the vertical displacement and the axial force along the pile shaft are gained. Then by virtue of the convolution theorem and the inverse Fourier transform, the time-domain velocity response of the pile head is derived. The presented solutions are validated, compared to the existing solution, the finite element model (FEM) results, and the field test data. Parametric analyses are made to show the effect of the soil anisotropy and the excitation frequency on the pile-soil dynamic responses.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.142-151
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• 2023

Sentiment analysis is a method used to comprehend feelings, opinions, and attitudes in text, and it is essential for evaluating consumer feedback and social media posts. However, creating sentiment dictionaries, which are necessary for this analysis, is complex and time-consuming because people express their emotions differently depending on the context and domain. In this study, we propose a new method for simplifying this procedure. We utilize syntax analysis of the Korean language to identify and extract sentiment words based on the Reason-Sentiment Pattern, which distinguishes between words expressing feelings and words explaining why those feelings are expressed, making it applicable in various contexts and domains. We also define sentiment words as those with clear polarity, even when used independently and exclude words whose polarity varies with context and domain. This approach enables the extraction of explicit sentiment expressions, enhancing the accuracy of sentiment analysis at the attribute level. Our methodology, validated using Korean cosmetics review datasets from Korean online shopping malls, demonstrates how a sentiment dictionary focused solely on clear polarity words can provide valuable insights for product planners. Understanding the polarity and reasons behind specific attributes enables improvement of product weaknesses and emphasis on strengths. This approach not only reduces dependency on extensive sentiment dictionaries but also offers high accuracy and applicability across various domains.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.219-222
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• 2011

There are number of methods that track the movement of an object or the change of state, such as Kalman filter, particle filter, dynamic clustering, and so on. Amongst these method, dynamic clustering method is an useful way to track cluster across multiple data frames and analyze their trend. In this paper we suggest the similarity-based dynamic clustering method, and verifies it's performance by simulation. Proposed dynamic clustering method is how to determine the same clusters for each continuative frame. The same clusters have similar characteristics across adjacent frames. The change pattern of cluster's characteristics in each time frame is throughly studied. Clusters in each time frames are matched against each others to see their similarity. Mamdani fuzzy model is used to determine similarity based matching algorithm. The proposed algorithm is applied to radar reflectivity data over time domain. We were able to observe time dependent characteristic of the clusters.

• Smart Structures and Systems
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• v.23 no.3
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• pp.263-278
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• 2019

Moving train load parameters, including train speed, axle spacing, gross train weight and axle weights, are identified based on strain-monitoring data. In this paper, according to influence line theory, the classic moving force identification method is enhanced to handle time-varying velocity of the train. First, the moments that the axles move through a set of fixed points are identified from a series of pulses extracted from the second derivative of the structural strain response. Subsequently, the train speed and axle spacing are identified. In addition, based on the fact that the integral area of the structural strain response is a constant under a unit force at a unit speed, the gross train weight can be obtained from the integral area of the measured strain response. Meanwhile, the corrected second derivative peak values, in which the effect of time-varying velocity is eliminated, are selected to distribute the gross train weight. Hence the axle weights could be identified. Afterwards, numerical simulations are employed to verify the proposed method and investigate the effect of the sampling frequency on the identification accuracy. Eventually, the method is verified using the real-time strain data of a continuous steel truss railway bridge. Results show that train speed, axle spacing and gross train weight can be accurately identified in the time domain. However, only the approximate values of the axle weights could be obtained with the updated method. The identified results can provide reliable reference for determining fatigue deterioration and predicting the remaining service life of railway bridges.

• Journal of KIISE:Databases
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• v.29 no.6
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• pp.429-440
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• 2002

Temporal databases manage time-evolving data. They provide built-in supports for efficient recording and querying of temporal data. The temporal aggregate in temporal databases is an extension of the conventional aggregate to include time concept on the domain and range of aggregation. This paper focuses on multidimensional temporal aggregation. In a multidimensional temporal aggregate, we use one or more general attributes as well as a time attribute on the range of aggregation, thus it is a useful operation for historical data warehouse, Call Data Records(CDR), etc. In this paper, we propose a structure for multidimensional temporal aggregation, called PTA-tree, and an aggregate processing method based on the PTA-tree. Through analyses and performance experiments, we also compare the PTA-tree with the simple extension of SB-tree that was proposed for temporal aggregation.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.513-516
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• 2013

In this paper, we present an information collecting system in medical information management domain. Our proposed system performs a systemized process, consisting of collection, transmission, and management, to develop intelligent medical information system and medical big data processing system. Our information collecting system consists of low-power biomedical sensors, biomedical information collecting devices, and storage systems. Currently, almost biomedical information of patients is collected manually by employees like nurses and medical doctors. Therefore, collected biometric data can be error-pronoun data. Since there is a lack to make big data of medical information, it is difficult to enhance the quality of medical services and researches. Accordingly, through our proposed system, we can overcome the problems like error-pronoun biometric data. In addition, we can extremely extend the area of collectable biometric data. Furthermore, using this system, we are able to make a real-time biomedical analysis system, like a real-time patient diagnosis system, and establish a strategy to against future medical markets changing rapidly.