• Journal of Conservation Science
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• v.29 no.4
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• pp.297-309
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• 2013

Iron objects become corroded at fast speed from the moment when they are excavated, so it is needed to control corrosion through processes of conservation treatment. However, re-corrosion mostly takes place in excavate iron objects, although they have already gone through the process of conservation treatment, and it is more difficult to carry out the second conservation treatment of re-corroded excavated iron objects than the first conservation treatment, and it requires a longer period of time to treat them as well. In this study, aims to discover factors of re-corrosion by scientifically analyzing corrosion products generated during the process of storage after the process of conservation treatment. The finished on conservation treatment of the iron artifacts, which were unearthed from three ancient site in Gyeongju by using the same conservation method between 2002 and 2009, re-corrosion condition observed on the packaging-iron artifacts. Focused on 9 target forged iron artifacts among them, this study analyzed the physical changes by mass measurement, naked-eye and microscopic observations and the chemical changes by SEM-EDS, XRD, IC and ICP analysis. The results show that the yellowish brown corrosion products formed on the facing surface of part dropped from the artifacts had different associated forms but acicular shape. In addition, the acicular shape became clearer as the color changed from red to yellowish brown. According to the process when the conservation treatment was completed, the mass of the artifacts increased in proportion to the corrosion products and the chloride ion ($Cl^-$) concentration had a tendency to increase relatively. ${\beta}$-FeOOH (akaganeite) was confirmed in the XRD analysis for the corrosion products of all the collected samples. As a result of ICP analysis, $Na^+$ and $Ca^{2+}$ components were confirmed.

• Journal of Korean Society for Geospatial Information Science
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• v.24 no.4
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• pp.59-66
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• 2016

For the performance experiments of databases systems with moving object databases, we need moving object trajectory data sets. For example, benchmark data sets of moving object trajectories are required for experiments on query processing of moving object databases. For those reasons, several tools have been developed for generating moving objects in Euclidean spaces or road network spaces. Indoor space differs from outdoor spaces in many aspects and moving object generator for indoor space should reflect these differences. Even some tools were developed to produce virtual moving object trajectories in indoor space, the movements generated by them are not realistic. In this paper, we present a moving object generation tool for indoor space. First, this tool generates trajectories for pedestrians in an indoor space. And it provides a parametric generation of trajectories considering not only speed, number of pedestrians, minimum distance between pedestrians but also type of spaces, time constraints, and type of pedestrians. We try to reflect the patterns of pedestrians in indoor space as realistic as possible. For the reason of interoperability, several geospatial standards are used in the development of the tool.

• Journal of KIISE:Databases
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• v.29 no.5
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• pp.367-380
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• 2002

Due to recent increase in applications requiring huge amount of data such as spatial data analysis and image analysis, clustering on large databases has been actively studied. In a hierarchical clustering method, a tree representing hierarchical decomposition of the database is first created, and then, used for efficient clustering. Existing hierarchical clustering methods mainly adopted the bottom-up approach, which creates a tree from the bottom to the topmost level of the hierarchy. These bottom-up methods require at least one scan over the entire database in order to build the tree and need to search most nodes of the tree since the clustering algorithm starts from the leaf level. In this paper, we propose a novel top-down hierarchical clustering method that uses multidimensional indexes that are already maintained in most database applications. Generally, multidimensional indexes have the clustering property storing similar objects in the same (or adjacent) data pares. Using this property we can find adjacent objects without calculating distances among them. We first formally define the cluster based on the density of objects. For the definition, we propose the concept of the region contrast partition based on the density of the region. To speed up the clustering algorithm, we use the branch-and-bound algorithm. We propose the bounds and formally prove their correctness. Experimental results show that the proposed method is at least as effective in quality of clustering as BIRCH, a bottom-up hierarchical clustering method, while reducing the number of page accesses by up to 26～187 times depending on the size of the database. As a result, we believe that the proposed method significantly improves the clustering performance in large databases and is practically usable in various database applications.

• The Mathematical Education
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• v.61 no.3
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• pp.419-439
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• 2022

This study is based on Freudenthal's mathmatising process and the didactical phenomenology of linear function concept, I have described and examined the process in which students represent the constant rate of change into tables, graphs and equations and, in this way, how they construct mental objects and essence of the linear function concept. The students used the proportionality as composite units, when they represented the phenomenon with constant rate of change into tables. When representing in graphs, all but one student represented it into a line. There were differences among the students in the level they were using the given conditions, co-variation perspective, and corresponding rules when formulating equations. The students compared the relationship between two variables in a multiplicative way, and under the guidance of teachers they reached to the understanding that its relationship becomes a constant. Moreover, they could construct mental objects of a constant rate of change, understanding the situation where the relationship between time difference and distance difference becomes one value, namely speed. The students had difficulties in connecting the rate of change with the inclination of a line. The students constructed the essence (concept) of linear functions, after building and organizing the image that the rate of change is constant, the graph is linear, and the equation is formulated as y=ax+b (a: inclination, b: intercept).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.10
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• pp.1331-1340
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• 2020

Object detection in maritime means that the captain detects floating objects that has a risk of colliding with the ship using the computer automatically and as accurately as human eyes. In conventional ships, the presence and distance of objects are determined through radar waves. However, it cannot identify the shape and type. In contrast, with the development of AI, cameras help accurately identify obstacles on the sea route with excellent performance in detecting or recognizing objects. The computer must calculate high-volume pixels to analyze digital images. However, the CPU is specialized for sequential processing; the processing speed is very slow, and smooth service support or security is not guaranteed. Accordingly, this study developed maritime object detection software and implemented it with FPGA to accelerate the processing of large-scale computations. Additionally, the system implementation was improved through embedded boards and FPGA interface, achieving 30 times faster performance than the existing algorithm and a three-times faster entire system.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.7C
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• pp.421-427
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• 2011

The importance of the real-time object recognition and tracking field has been growing steadily due to rapid advancement in the computer vision applications industry. As is well known, the mean-shift algorithm is widely used in robust real-time object tracking systems. Since the mentioned algorithm is easy to implement and efficient in object tracking computation, many say it is suitable to be applied to real-time object tracking systems. However, one of the major drawbacks of this algorithm is that it always converges to a local mode, failing to perform well in a cluttered environment. In this paper, an Optical Flow-based algorithm which fits for real-time recognition of multiple moving objects is proposed. Also in the tests, the newly proposed method contributed to raising the similarity of multiple moving objects, the similarity was as high as 0.96, up 13.4% over that of the mean-shift algorithm. Meanwhile, the level of pixel errors from using the new method keenly decreased by more than 50% over that from applying the mean-shift algorithm. If the data processing speed in the video surveillance systems can be reduced further, owing to improved algorithms for faster moving object recognition and tracking functions, we will be able to expect much more efficient intelligent systems in this industrial arena.

• The Journal of the Korea Contents Association
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• v.21 no.1
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• pp.147-161
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• 2021

Through photogrammetry techniques, what current researches can achieve at present is rough 3D mesh and color map of objects, rather than usable photo-realistic 3D assets. This research aims to propose a new method to create photo-realistic 3D assets that can be used in the field of visualization applications. The new method combines photogrammetry with computer graphics modeling. Through the description of the production process of three objects in the real world - "Bullet Box", "Gun" and "Metal Beverage Bottle," it introduces in details the concept, functions, operating skills and software packages used in the steps including the photograph object, white balance, reconstruction, cleanup reconstruction, retopology, UV unwrapping, projection, texture baking, De-Lighting and Create Material Maps. In order to increase the flexibility of the method, alternatives to the software packages are also recommended for each step. In this research, 3D assets are produced that are accurate in shape, correct in color, easy to render and can be physically interacted with dynamic lighting in texture. The new method can obtain more realistic visual effects at a faster speed. It does not require large-scale teams, expensive equipment and software packages, therefore it is suitable for small studios and independent artists and educational institutions.

• International Journal of Computer Science & Network Security
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• v.22 no.6
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• pp.131-138
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• 2022

Novel Coronavirus (COVID-19) is viewed as one of the main general wellbeing theaters on the worldwide level all over the planet. Because of the abrupt idea of the flare-up and the irresistible force of the infection, it causes individuals tension, melancholy, and other pressure responses. The avoidance and control of the novel Covid pneumonia have moved into an imperative stage. It is fundamental to early foresee and figure of infection episode during this troublesome opportunity to control of its grimness and mortality. The entire world is investing unimaginable amounts of energy to fight against the spread of this lethal infection. In this paper, we utilized machine learning and deep learning techniques for analyzing what is going on utilizing countries shared information and for detecting the climate factors that effect on spreading Covid-19, such as humidity, sunny hours, temperature and wind speed for understanding its regular dramatic way of behaving alongside the forecast of future reachability of the COVID-2019 around the world. We utilized data collected and produced by Kaggle and the Johns Hopkins Center for Systems Science. The dataset has 25 attributes and 9566 objects. Our Experiment consists of two phases. In phase one, we preprocessed dataset for DL model and features were decreased to four features humidity, sunny hours, temperature and wind speed by utilized the Pearson Correlation Coefficient technique (correlation attributes feature selection). In phase two, we utilized the traditional famous six machine learning techniques for numerical datasets, and Dense Net deep learning model to predict and detect the climatic factor that aide to disease outbreak. We validated the model by using confusion matrix (CM) and measured the performance by four different metrics: accuracy, f-measure, recall, and precision.

• Physical Therapy Korea
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• v.30 no.2
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• pp.92-101
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• 2023

Background: Stroke is one of the causes affecting gait and balance. Taping is considered an effective method for improving balance and gait in stroke patients. Numerous studies have confirmed the functional effects of taping in stroke patients. However, there is still no consensus regarding the use of taping to improve gait and balance. Objects: The purpose of this review was to investigate the effects of taping on the balance and gait of patients with stroke through meta-analysis of studies. Methods: PubMed, Medline, Embase, Web of Science, Cochrane Review, RISS, DBPia, and Science on were used to collect articles on Kinesio and non-elastic taping. The key terms were "Stroke", "Hemiplegia", "Taping", "Tape", "Balance", and "Gait" with cut-off of October, 2022. Taping group was compared with control groups with sham, placebo, and no taping. The outcome measures included the Berg Balance Scale (BBS), Timed Up and Go (TUG) test, and gait speed (cm/s). Eighteen studies (524 patients) were selected for the meta-analysis. Results: Overall, taping improved balance and gait in stroke patients, and Kinesio and non-elastic taping had similar effect sizes. Taping improved the BBS and TUG, and was most effective on gait speed. Contrary to the expectation that a longer duration of taping would be more affective, taping was most effective when the total taping duration was shorter than 500 minutes. In addition, the effect size of taping was greater when it was simultaneously attached to multiple locations. Conclusion: This meta-analysis supports the use of taping to improve gait and balance in stroke patients, and provides guidelines for the location, duration, and type of tape to increase taping efficiency.

• Wind and Structures
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• v.30 no.2
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• pp.181-198
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• 2020

In the traditional buffeting response analysis method, the spanwise incomplete correlation of buffeting forces is always assumed to be same as that of the incident wind turbulence and the action of the signature turbulence is ignored. In this paper, three typical bridge decks usually adopted in the real bridge engineering, a single flat box deck, a central slotted box deck and a two-separated paralleled box deck, were employed as the investigated objects. The wind induced pressure on these bridge decks were measured via a series of wind tunnel pressure tests of the sectional models. The influences of the wind speed in the tests, the angle of attack, the turbulence intensity and the characteristic distance were taken into account and discussed. The spanwise root coherence of buffeting forces was also compared with that of the incidence turbulence. The signature turbulence effect on the spanwise root coherence function was decomposed and explained by a new empirical method with a double-variable model. Finally, the formula of a sum of rational fractions that accounted for the signature turbulence effect was proposed in order to fit the results of the spanwise root coherence function. The results show that, the spanwise root coherence of the drag force agrees with that of incidence turbulence in some range of the reduced frequency but disagree in the mostly reduced frequency. The spanwise root coherence of the lift force and the torsional moment is much larger than that of the incidence turbulence. The influences of the wind speed and the angle of attack are slight, and they can be ignored in the wind tunnel test. The spanwise coherence function often involves several narrow peaks due to the signature turbulence effect in the high reduced frequency zone. The spanwise coherence function is related to the spanwise separation distance and the spanwise integral length scales, and the signature turbulence effect is related to the deck-width-related reduced frequency.