• Journal of Convergence for Information Technology
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• v.11 no.8
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• pp.36-41
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• 2021

Although the technology for prediction or analysis using artificial intelligence is constantly developing, a black-box problem does not interpret the decision-making process. Therefore, the decision process of the AI model can not be interpreted from the user's point of view, which leads to unreliable results. We investigated the problems of artificial intelligence and explainable artificial intelligence using Blockchain to solve them. Data from the decision-making process of artificial intelligence models, which can be explained with Blockchain, are stored in Blockchain with time stamps, among other things. Blockchain provides anti-counterfeiting of the stored data, and due to the nature of Blockchain, it allows free access to data such as decision processes stored in blocks. The difficulty of creating explainable artificial intelligence models is a large part of the complexity of existing models. Therefore, using the point cloud to increase the efficiency of 3D data processing and the processing procedures will shorten the decision-making process to facilitate an explainable artificial intelligence model. To solve the oracle problem, which may lead to data falsification or corruption when storing data in the Blockchain, a blockchain artificial intelligence problem was solved by proposing a blockchain-based explainable artificial intelligence model that passes through an intermediary in the storage process.

• Journal of the Korea Computer Graphics Society
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• v.28 no.2
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• pp.29-41
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• 2022

In this paper, we introduce a novel real-time, interactive animation system which uses real-time motion inputs from a low-cost motion-sensing device Kinect. Our system generates interaction motions between the user character and the counterpart character in real-time. While the motion of the user character is generated mimicking the user's input motion, the other character's motion is decided to react to the user avatar's motion. During a pre-processing step, our system analyzes the reference motion data and generates mapping model in advance. At run-time, our system first generates initial poses of two characters and then modifies them so that it could provide plausible interacting behavior. Our experimental results show plausible interacting animations in that the user character performs a modified motion of user input and the counterpart character properly reacts against the user character. The proposed method will be useful for developing real-time interactive animation systems which provide a better immersive experience for users.

• Geophysics and Geophysical Exploration
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• v.25 no.1
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• pp.14-25
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• 2022

The passive surface wave method measures seismic signals from ambient noises or vibrations of natural phenomena without using an artificial source. Since passive sources are usually in lower frequencies than artificial ones being able to ensure the information on deeper geological structures, the passive surface wave method can investigate deeper geological structures. In the passive method, frequency dispersion curves are obtained after data acquisition, and the dispersion curves are analyzed by assuming 1D-layered earth, which is like the method of active surface wave survey. However, when computing dispersion curves, the passive method first obtains and analyzes coherence curves of received signals from a set of receivers based on spatial autocorrelation. In this review, we explain how passive surface wave methods measure signals, and make data processing and interpretation, before analyzing field application cases.

• The Journal of the Acoustical Society of Korea
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• v.42 no.5
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• pp.403-411
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• 2023

Functional ultrasound imaging, such as elasticity imaging and micro-blood flow Doppler imaging, enhances diagnostic capability by providing useful mechanical and functional information about tissues. However, the implementation of functional ultrasound imaging poses limitations such as the storage of vast amounts of data in Radio Frequency (RF) data acquisition and processing. In this paper, we propose a sub-Nyquist approach that reduces the amount of acquired axial samples for efficient shear-wave elasticity imaging. The proposed method acquires data at a sampling rate one-third lower than the conventional Nyquist sampling rate and tracks shear-wave signals through RF signals reconstructed using band-pass filtering-based interpolation. In this approach, the RF signal is assumed to have a fractional bandwidth of 67 %. To validate the approach, we reconstruct the shear-wave velocity images using shear-wave tracking data obtained by conventional and proposed approaches, and compare the group velocity, contrast-to-noise ratio, and structural similarity index measurement. We qualitatively and quantitatively demonstrate the potential of sub-Nyquist sampling-based shear-wave elasticity imaging, indicating that our approach could be practically useful in three-dimensional shear-wave elasticity imaging, where a massive amount of ultrasound data is required.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.23 no.3
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• pp.119-125
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• 2023

IT infrastructure operation has advanced, and the methods for managing systems have become widely adopted. Recently, research has focused on improving system management using Syslog. However, utilizing log data collected through these methods presents challenges, as logs are extracted in various formats that require expert analysis. This paper proposes a system that utilizes edge computing to distribute the collection of Syslog data and preprocesses duplicate data before storing it in a central database. Additionally, the system constructs a data dictionary to classify and count data in real-time, with restrictions on transmitting registered data to the central database. This approach ensures the maintenance of predefined patterns in the data dictionary, controls duplicate data and temporal duplicates, and enables the storage of refined data in the central database, thereby securing fundamental data for big data analysis. The proposed algorithms and procedures are demonstrated through simulations and examples. Real syslog data, including extracted examples, is used to accurately extract necessary information from log data and verify the successful execution of the classification and storage processes. This system can serve as an efficient solution for collecting and managing log data in edge environments, offering potential benefits in terms of technology diffusion.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.42 no.2
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• pp.281-290
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• 2022

In Korea, the number of national facilities for which a safety inspection is mandatory is increasing, and a safer safety inspection method is needed. This study aimed to increase the efficiency of the bridge safety inspection by enabling rapid exterior inspection while securing the safety of inspectors by using drones to perform the safety inspections of bridges, which had mainly relied on visual inspections. For the research, the Youngjong Grand Bridge in Incheon was selected as a test bed and was divided into four parts: the warren truss, suspension bridge main cable, main tower, and pier. It was possible to establish a five-step standard procedure for drone safety inspections. The step-by-step contents of the standard procedure obtained as a result of this research are: Step 1, facility information collection and analysis, Step 2, analysis of vulnerable parts and drone flight planning, Step 3, drone photography and data processing, Step 4, condition evaluation by external inspection, Step 5, building of external inspection diagram and database. Therefore, if the safety inspections of civil engineering facilities including bridges are performed according to this standard procedure, it is expected that these inspection can be carried out more systematically and efficiently.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.34 no.2
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• pp.251-274
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• 2023

This study aimed to examine the mediating effect of positive psychological capital in the relationship between emotional labor and Professional Quality of Life (ProQOL) of librarians belonging to the Widely Representative Library. From February 13, 2023 to February 24, 2023, 159 librarians working in 17 Widely Representative Libraries nationwide were surveyed for general characteristics, emotional labor, ProQOL, and positive psychological capital through questionnaires. For statistical analysis, frequency analysis, descriptive statistics analysis, confirmatory factor analysis, reliability analysis, correlation analysis, and measurement model analysis were conducted using SPSS Statistics 24.0 and Amos 25.0. In addition, the mediating effect of positive psychological capital in the relationship between emotional labor and ProQOL of librarians in the Widely Representative Library was analyzed using a bootstrapping analysis method. The results of this study are summarized as follows. First, it was found that there was a significant effect among librarians' emotional labor, ProQOL, and positive psychological capital in the Widely Representative Library. Second, the indirect effect of positive psychological capital in the relationship between Emotional Labor and ProQOL of Widely Representative Library librarians was found to be statistically significant. In other words, considering the direct effect of emotional labor on ProQOL, it can be inferred that there is a partial mediating effect. Therefore, it is suggested to develop a program that can improve the quality of professional life by reducing emotional labor and strengthening the positive psychological capital of librarians in further studies.

• Journal of Practical Engineering Education
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• v.14 no.3
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• pp.505-512
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• 2022

The purpose of this study is to synthesize effects of the living lab-based education through meta-analysis. Seven primary studies reporting the effect of living lab-based education were carefully selected for data analysis. Research questions are as follows. First, what is the overall effect size of the living lab-based education? The overall effect size refers to the effect on the cognitive and affective domains. Second, what is the effect size of the living lab-based education according to categorical variables? Categorical variables are outcome characteristics, study characteristics, and design characteristics. Results are summarized as follows. First, the overall effect size of living lab-based education was 0.347. Second, the effect size according to the cognitive domain was 1.244 for information process, 0.593 for communication, 0.261 for problem solving, and 0.26 for creativity. Third, the effect size according to subject area was shown in the order of electrical and electronic engineering 1.146, technology and home economics 0.489, artificial intelligence 0.379, and practical arts 0.168. Fourth, the effect size according to school level was 1.058 for high school, 0.312 for middle school, and 0.217 for elementary school. Fifth, the effect size by grade level was 0.295 when two or more grades were integrated and 0.294 for a single grade.

• The Journal of the Acoustical Society of Korea
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• v.28 no.6
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• pp.572-577
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• 2009

Large corpus-based concatenating Text-to-Speech (TTS) systems can generate natural synthetic speech without additional signal processing. To prune the redundant speech segments in a large speech segment DB, we can utilize a decision-tree based triphone clustering algorithm widely used in speech recognition area. But, the conventional methods have problems in representing the acoustic transitional characteristics of the phones and in applying context questions with hierarchic priority. In this paper, we propose a new clustering algorithm to downsize the speech DB. Firstly, three 13th order MFCC vectors from first, medial, and final frame of a phone are combined into a 39 dimensional vector to represent the transitional characteristics of a phone. And then the hierarchically grouped three question sets are used to construct the triphone trees. For the performance test, we used DTW algorithm to calculate the acoustic similarity between the target triphone and the triphone from the tree search result. Experimental results show that the proposed method can reduce the size of speech DB by 23% and select better phones with higher acoustic similarity. Therefore the proposed method can be applied to make a small sized TTS.

• Journal of Intelligence and Information Systems
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• v.24 no.1
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• pp.183-203
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• 2018

News articles are the most suitable medium for examining the events occurring at home and abroad. Especially, as the development of information and communication technology has brought various kinds of online news media, the news about the events occurring in society has increased greatly. So automatically summarizing key events from massive amounts of news data will help users to look at many of the events at a glance. In addition, if we build and provide an event network based on the relevance of events, it will be able to greatly help the reader in understanding the current events. In this study, we propose a method for extracting event networks from large news text data. To this end, we first collected Korean political and social articles from March 2016 to March 2017, and integrated the synonyms by leaving only meaningful words through preprocessing using NPMI and Word2Vec. Latent Dirichlet allocation (LDA) topic modeling was used to calculate the subject distribution by date and to find the peak of the subject distribution and to detect the event. A total of 32 topics were extracted from the topic modeling, and the point of occurrence of the event was deduced by looking at the point at which each subject distribution surged. As a result, a total of 85 events were detected, but the final 16 events were filtered and presented using the Gaussian smoothing technique. We also calculated the relevance score between events detected to construct the event network. Using the cosine coefficient between the co-occurred events, we calculated the relevance between the events and connected the events to construct the event network. Finally, we set up the event network by setting each event to each vertex and the relevance score between events to the vertices connecting the vertices. The event network constructed in our methods helped us to sort out major events in the political and social fields in Korea that occurred in the last one year in chronological order and at the same time identify which events are related to certain events. Our approach differs from existing event detection methods in that LDA topic modeling makes it possible to easily analyze large amounts of data and to identify the relevance of events that were difficult to detect in existing event detection. We applied various text mining techniques and Word2vec technique in the text preprocessing to improve the accuracy of the extraction of proper nouns and synthetic nouns, which have been difficult in analyzing existing Korean texts, can be found. In this study, the detection and network configuration techniques of the event have the following advantages in practical application. First, LDA topic modeling, which is unsupervised learning, can easily analyze subject and topic words and distribution from huge amount of data. Also, by using the date information of the collected news articles, it is possible to express the distribution by topic in a time series. Second, we can find out the connection of events in the form of present and summarized form by calculating relevance score and constructing event network by using simultaneous occurrence of topics that are difficult to grasp in existing event detection. It can be seen from the fact that the inter-event relevance-based event network proposed in this study was actually constructed in order of occurrence time. It is also possible to identify what happened as a starting point for a series of events through the event network. The limitation of this study is that the characteristics of LDA topic modeling have different results according to the initial parameters and the number of subjects, and the subject and event name of the analysis result should be given by the subjective judgment of the researcher. Also, since each topic is assumed to be exclusive and independent, it does not take into account the relevance between themes. Subsequent studies need to calculate the relevance between events that are not covered in this study or those that belong to the same subject.