• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.1960-1972
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each cu. Using this mobile technique in a wireless network searches for specific plate numbers and information about the location of the car is transmitted to a remote sewer. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the cu, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• Journal of KIISE:Software and Applications
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• v.29 no.1_2
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• pp.80-90
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• 2002

Clustering is a useful technique for grouping data points such that points within a single group/cluster have similar characteristics. Many clustering algorithms have been developed and used in engineering applications including pattern recognition and image processing etc. Recently, it has drawn increasing attention as one of important techniques in data mining. However, clustering algorithms such as K-means and Fuzzy C-means suffer from difficulties. Those are the needs to determine the number of clusters apriori and the clustering results depending on the initial set of clusters which fails to gain desirable results. In this paper, we propose a new clustering algorithm, which solves mentioned problems. In our method we use evolutionary algorithm to solve the local optima problem that clustering converges to an undesirable state starting with an inappropriate set of clusters. We also adopt a new measure that represents how well data are clustered. The measure is determined in terms of both intra-cluster dispersion and inter-cluster separability. Using the measure, in our method the number of clusters is automatically determined as the result of optimization process. And also, we combine heuristic that is problem-specific knowledge with a evolutionary algorithm to speed evolutionary algorithm search. We have experimented our algorithm with several sets of multi-dimensional data and it has been shown that one algorithm outperforms the existing algorithms.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.6
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• pp.295-306
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• 2016

The purpose of this paper is both to analyze research trends and to predict industrial flows using the meta-data from the previous studies on data quality. There have been many attempts to analyze the research trends in various fields till lately. However, analysis of previous studies on data quality has produced poor results because of its vast scope and data. Therefore, in this paper, we used a text mining, social network analysis for time series network analysis to analyze the vast scope and data of data quality collected from a Web of Science index database of papers published in the international data quality-field journals for 10 years. The analysis results are as follows: Decreases in Mathematical & Computational Biology, Chemistry, Health Care Sciences & Services, Biochemistry & Molecular Biology, Biochemistry & Molecular Biology, and Medical Information Science. Increases, on the contrary, in Environmental Sciences, Water Resources, Geology, and Instruments & Instrumentation. In addition, the social network analysis results show that the subjects which have the high centrality are analysis, algorithm, and network, and also, image, model, sensor, and optimization are increasing subjects in the data quality field. Furthermore, the industrial connection analysis result on data quality shows that there is high correlation between technique, industry, health, infrastructure, and customer service. And it predicted that the Environmental Sciences, Biotechnology, and Health Industry will be continuously developed. This paper will be useful for people, not only who are in the data quality industry field, but also the researchers who analyze research patterns and find out the industry connection on data quality.

• Journal of Korean Society of Transportation
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• v.26 no.4
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• pp.173-184
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• 2008

Development of an accident estimation model based on accident data can be made after accident occurrences. However, the taking of historical accident data is not easy, and there have been differences between real accident data and police-reported accident data. Also, another difficult shortcoming is that historical traffic accident data better consider driver behavior or intersection characteristics. A new method needs to be developed that can predict accident occurrences for traffic safety improvement in black spots. Traffic conflict decision techniques can acquire and analyze data in time and space, requiring less data collection through investigation. However, there are shortcomings: as existing traffic conflict techniques do not operate automatically, the analyst's opinion could easily affect the study results. Also, existing methods do not consider the severity of traffic conflicts. In this study, the authors presented traffic conflict decision criteria which consider conflict severity, including opposing left turn traffic conflict and cross traffic conflict decision criteria. In order to test these criteria, the authors acquired three signalized intersection images (two intersections in Sungnam city and one intersection in Paju) and analyzed the acquired images using image processing techniques based on individual vehicle tracking technology. Within the analyzed images, level 1 conflicts occurred 343 times over three intersections. Some of these traffic conflicts resulted in level 3 conflict situations. Level 3 traffic conflicts occurred 25 times. From the study results, the authors found that traffic conflict decision techniques can be an alternative to evaluate traffic safety in black spots.

• Journal of Korea Multimedia Society
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• v.9 no.5
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• pp.595-605
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• 2006

In this thesis, GPS and the electronic mapping were used to realize such a system by recognizing license plate numbers and identifying the location of objects that move at synchronous times with simulated movement in the electronic map. As well, throughout the study, a camera attached to a PDA, one of the mobile devices, automatically recognized and confirmed acquired license plate numbers from the front and back of each car. Using this mobile technique in a wireless network, searches for specific plate numbers and information about the location of the car is transmitted to a remote server. The use of such a GPS-based system allows for the measurement of topography and the effective acquisition of a car's location. The information is then transmitted to a central controlling center and stored as text to be reproduced later in the form of diagrams. Getting positional information through GPS and using image-processing with a PDA makes it possible to estimate the correct information of a car's location and to transmit the specific information of the car to a control center simultaneously, so that the center will get information such as type of the car, possibility of the defects that a car might have, and possibly to offer help with those functions. Such information can establish a mobile system that can recognize and accurately trace the location of cars.

• Journal of Conservation Science
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• v.37 no.3
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• pp.232-244
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• 2021

This study examined the physical attributes and heat treatment characteristics of glass beads excavated from the Gimhae area, which is the location of Geumgwan Gaya. This enabled classification of surface characteristics of the beads based on the investigation of the color, size, and shape. The glass beads were classified into eight color systems, with purplish-blue beads as the representative color. Bead size was categorized into three types depending on the outer diameter and how it increased over time. Bead shapes were categorized as round, tubular, or doughnut-shaped based on the inner diameter and length, with round being the typical shape. According to the degree of heat treatment, there are three types of cross-section for glass beads that are manufactured by the drawing technique, most of which are the HT-III type. In addition, it is estimated that the heat treatment technology has more considerable effects than other methods. Through non-destructive analysis, the chemical composition was obtained and categorized as flux, stabilizer, and colorant. Analysis confirmed the presence of 63 and 9 pieces in the potash and soda glass groups, respectively. Overall findings from the study highlighted a correlation between the chemical composition and the external factors such as color, size, shape, and manufacturing technology of glass beads recovered from Geumgwan Gaya, revealing characteristics related to that time and region.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.6
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• pp.275-284
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• 2023

Virtual reality simulations are used for education and training in various fields, and are especially widely used in the medical field recently. The education/training simulator consists of tactile/force feedback generation and image/sound output hardware that provides a sense similar to a doctor's treatment of a real patient using real surgical tools, and software that produces realistic images and tactile feedback. Existing simulators are complicated and expensive because they have to use various types of hardware to simulate various surgical instruments used during surgery. In this paper, we propose a dental surgical simulation system using a force feedback device and a morphable haptic controller. Haptic hardware determines whether the surgical tool collides with the surgical site and provides a sense of resistance and vibration. In particular, haptic controllers that can be deformed, such as length changes and bending, can express various senses felt depending on the shape of various surgical tools. When the user manipulates the haptic feedback device, events such as movement of the haptic feedback device or button clicks are delivered to the simulation system, resulting in interaction between dental surgical tools and oral internal models, and thus haptic feedback is delivered to the haptic feedback device. Using these basic techniques, we provide a realistic training experience of impacted wisdom tooth extraction surgery, a representative dental surgery technique, in a virtual environment represented by sophisticated three-dimensional models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.05a
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• pp.41-43
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• 2022

In order to prevent and block infectious diseases caused by the recent COVID-19 pandemic, non-contact biometric information acquisition and analysis technology is attracting attention. The invasive and attached biometric information acquisition method accurately has the advantage of measuring biometric information, but has a risk of increasing contagious diseases due to the close contact. To solve these problems, the non-contact method of extracting biometric information such as human fingerprints, faces, iris, veins, voice, and signatures with automated devices is increasing in various industries as data processing speed increases and recognition accuracy increases. However, although the accuracy of the non-contact biometric data acquisition technology is improved, the non-contact method is greatly influenced by the surrounding environment of the object to be measured, which is resulting in distortion of measurement information and poor accuracy. In this paper, we propose a context-based bio-signal modeling technique for the interpretation of personalized information (image, signal, etc.) for bio-information analysis. Context-based biometric information modeling techniques present a model that considers contextual and user information in biometric information measurement in order to improve performance. The proposed model analyzes signal information based on the feature probability distribution through context-based signal analysis that can maximize the predicted value probability.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.37 no.3
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• pp.173-178
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• 2024

This study presents a technique for assessing the dimensional quality of assembly parts in Prefabricated Steel Structures (PSS) using a stereo vision sensor. The stereo vision system captures images and point cloud data of the assembly area, followed by applying image processing algorithms such as fuzzy-based edge detection and Hough transform-based circular bolt hole detection to identify bolt hole locations. The 3D center positions of each bolt hole are determined by correlating 3D real-world position information from depth images with the extracted bolt hole positions. Principal Component Analysis (PCA) is then employed to calculate coordinate axes for precise measurement of distances between bolt holes, even when the sensor and structure orientations differ. Bolt holes are sorted based on their 2D positions, and the distances between sorted bolt holes are calculated to assess the assembly part's dimensional quality. Comparison with actual drawing data confirms measurement accuracy with an absolute error of 1mm and a relative error within 4% based on median criteria.

• Journal of the Korean Society of Marine Environment & Safety
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• v.30 no.2
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• pp.147-156
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• 2024

The sustainable management and enhancement of marine resources are becoming increasingly important issues worldwide. This study was conducted in response to these challenges, focusing on the development and performance comparison of fish detection and classification models as part of a deep learning-based technique for assessing the effectiveness of marine resource enhancement projects initiated by the Korea Fisheries Resources Agency. The aim was to select the optimal model by training various sizes of YOLOv8-Seg models on a fish image dataset and comparing each performance metric. The dataset used for model construction consisted of 36,749 images and label files of 12 different species of fish, with data diversity enhanced through the application of augmentation techniques during training. When training and validating five different YOLOv8-Seg models under identical conditions, the medium-sized YOLOv8m-Seg model showed high learning efficiency and excellent detection and classification performance, with the shortest training time of 13 h and 12 min, an of 0.933, and an inference speed of 9.6 ms. Considering the balance between each performance metric, this was deemed the most efficient model for meeting real-time processing requirements. The use of such real-time fish detection and classification models could enable effective surveys of marine resource enhancement projects, suggesting the need for ongoing performance improvements and further research.