• Journal of Software Assessment and Valuation
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• v.17 no.1
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• pp.17-24
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• 2021

There is a problem that unknown paintings are sophisticated in the level of forgery, making it difficult for even experts to determine whether they are genuine or counterfeit. These problems can be suspected of forgery even if the genuine product is submitted, which can lead to a decline in the value of the work and the artist. To address these issues, in this paper, we propose a system to classify chromaticity data among extracted data through objective analysis into quadrants, extracting comparisons and intersections, and estimating authors of unknown paintings using XRF and hyperspectral spectrum data from corresponding points.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.2
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• pp.299-304
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• 2023

Among artificial intelligence techniques, deep learning is a model that has been used in many places and has proven its effectiveness. However, deep learning models are not used effectively in everywhere. In this paper, we will show the limitations of deep learning models through comparison of regression analysis and deep learning models, and present a guide for effective use of deep learning models. In addition, among various techniques used for optimization of deep learning models, data normalization and data shuffling techniques, which are widely used, are compared and evaluated based on actual data to provide guidelines for increasing the accuracy and value of deep learning models.

• International Journal of Computer Science & Network Security
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• v.23 no.10
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• pp.169-178
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• 2023

Wireless sensor network is wieldy use for IoT application. The sensor node consider as physical device in IoT architecture. This all sensor node are operated with battery so the power consumption is very high during the data communication and low during the sensing the environment. Without proper planning of data communication the network might be dead very early so primary objective of the cluster based routing protocol is to enhance the battery life and run the application for longer time. In this paper we have comprehensive of twenty research paper related with clustering based routing protocol. We have taken basic information, network simulation parameters and performance parameters for the comparison. In particular, we have taken clustering manner, node deployment, scalability, data aggregation, power consumption and implementation cost many more points for the comparison of all 20 protocol. Along with basic information we also consider the network simulation parameters like number of nodes, simulation time, simulator name, initial energy and communication range as well energy consumption, throughput, network lifetime, packet delivery ration, jitter and fault tolerance parameters about the performance parameters. Finally we have summarize the technical aspect and few common parameter must be fulfill or consider for the design energy efficient cluster based routing protocol.

• Korean Journal of Remote Sensing
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• v.29 no.2
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• pp.219-233
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• 2013

In this study, spatio-temporal variations of Land Surface Emissivity (LSE) of the three LSE data sets in the Asian-Oceanian regions were addressed. The MODerate Resolution Imaging Spectroradiometer (MODIS) LSE, Cooperative Institute for Meteorological Satellite Studies (CIMSS) LSE, and Kongju National Univ. (KNU) LSE data sets were used. The three data sets showed very similar emissivity in the Tibetan Plateau, desert in the Middle East and Australia, and low latitude regions irrespective of season. The emissivity of $12{\mu}m$ was systematically greater than that of $11{\mu}m$, in particular, in the Tibetan Plateau, desert over Middle East and Australia. In general, they showed a weak seasonal variation in the low latitude regions although the emissivity was different among them. However, the three data sets showed quite different spatial and temporal variations in the other regions of Asian-Oceanian regions. The KNU LSE showed a systematic seasonal variation with a high emissivity during summer and low emissivity during winter but the other two LSE data sets showed irregular seasonal variations without regard to the regions. And the annual mean correlations of $11{\mu}m$ and $12{\mu}m$ between KNU LSE and MODIS LSE (KNU LSE and CIMSS LSE; MODIS LSE and CIMSS LSE) were 0.423 and 0.399 (0.330, 0.101; 0.541, 0.154), respectively. The relatively low correlations and strong inter-month variations, in particular, in $12{\mu}m$, indicated that consistency in spatial variation was very low. The comparison results showed that caution should be given before operational use of the LSE data sets in these regions.

• 한국데이터정보과학회:학술대회논문집
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• 2005.10a
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• pp.59-69
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• 2005

Data mining technique is used to find hidden knowledge by massive data, unexpectedly pattern, relation to new rule. The methods of data mining are decision tree, association rules, clustering, neural network and so on. Clustering is the process of grouping the data into clusters so that objects within a cluster have high similarity in comparison to one another. It has been widely used in many applications, such that pattern analysis or recognition, data analysis, image processing, market research on off-line or on-line and so on. We analyze Gyeongnam social indicator survey data by 2001 using twostep clustering technique for environment information. The twostep clustering is classified as a partitional clustering method. We can apply these twostep clustering outputs to environmental preservation and improvement.

• Journal of information and communication convergence engineering
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• v.17 no.4
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• pp.239-245
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• 2019

Recently, effort to obtain various information from the vast amount of social network services (SNS) big data generated in daily life has expanded. SNS big data comprise sentences classified as unstructured data, which complicates data processing. As the amount of processing increases, a rapid processing technique is required to extract valuable information from SNS big data. We herein propose a system that can extract human sentiment information from vast amounts of SNS unstructured big data using the naïve Bayes algorithm and natural language processing (NLP). Furthermore, we analyze the effectiveness of the proposed method through various experiments. Based on sentiment accuracy analysis, experimental results showed that the machine learning method using the naïve Bayes algorithm afforded a 63.5% accuracy, which was lower than that yielded by the NLP method. However, based on data processing speed analysis, the machine learning method by the naïve Bayes algorithm demonstrated a processing performance that was approximately 5.4 times higher than that by the NLP method.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.11
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• pp.74-81
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• 1995

Several non-manifold data structures have been compared, which are radial-edge data structure, partial-face data structure, vertex-based data structure, and Yamaguchi's data structrue. All the entities in the data structures are classified into common entities and special entities. The entities are also classified as model entities, primitive entities bounding entities, and coupling entities. The four data structures for nonmanifold solid modelers are compared in terms of accessing efficiency, storage requirements, and inclusion of circulation. The results of comparison will serve as the basis to develope a nonmanifold modeler.

• Asia-pacific Journal of Multimedia Services Convergent with Art, Humanities, and Sociology
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• v.8 no.5
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• pp.369-383
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• 2018

In this paper, suggests a gamification analysis method applied to screen sports. The analysis method is through the process of comparison, collection and application. In the process of comparison, compare the characteristics of actual sports and screen sports and Data collection to complement the differences derived from the comparison process is done during the collection process. Process of application is verify for application status of Gamification. and analyzed of screen golf and screen baseball. The result shows that screen golf couldn't apply walking exercise in the comparison process, and screen baseball couldn't apply exercise elements except batting. During the collection process, driving distance and swing data were used for screen golf, and driving distance, batting average and RBI (runs batted in) data were used for screen baseball. Lastly, it was revealed during the application process that both screen golf and screen baseball provide data to users by using reward, competition and Self-expression elements of gamification. The analysis methods presented in this study can be a method to analyze screen sports, and are expected to be appropriate methods to make screen sports.

• Informatization Policy
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• v.24 no.2
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• pp.43-67
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• 2017

In 2015, Korea won the first place among 30 countries in Open, Useful, and Reusable (OUR) Data Index, which is an OECD's open government data indicator. On the other hand, Korea was ranked the 17th among 86 countries in Open Data Barometer (ODB) of World Wide Web Foundation. In this study, the research subject comes from two reasonable academic doubts on why the gap is wide between the two indicators of Korea and whether the OUR Data Index made proper evaluation on Korea's open government data. Based on the assumption that there may be some critical points in the measuring method of OUR Data Index, the study conducted a comparison of the two indicators. The result found that first, the two indicators almost had no correlation to each other; second, OUR Data Index had a more vague evaluation framework as well as less amount of government data for evaluation than ODB; third, while the government support takes a significant share in the OUR Data Index, it is considered as a mere input element; and fourth, the OUR Data Index does not evaluate the impact of open government data, whereas ODB includes the impact of open data on the government, economy, and society.

• Journal of The Korean Association For Science Education
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• v.15 no.2
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• pp.164-172
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• 1995

In this study, the researcher tried to find out the effect of using a computer interface in teaching speed concept in the elementary school. The 4th and 5th pupils were sampled for this study. The school is located in a sub-urban agricultural area in Korea. In the study, the subjects were divided into two groups: experimental and comparison group. From the pretest, two groups did not show any difference in the understanding of speed concept. The computer interface and the programs to operate the interface and data analysis were developed by researcher. The interface is a modular type and designed ready to connect to microcomputer. The test items were consisted of (1) comparison of speed, (2) change of motion, (3) acceleration, and (4) deceleration. As the result, the researcher found the following results: 1. In case of speed comparison, no significant difference was found between experimental and comparison group. 2. In case of change of motion, acceleration, and deceleration, the experimental groups showed higher achievement both in 4th grade and 5th grade. However, the 4th graders showed more learning than the 5th graders. In conclusion, this study showed that the use of computer interface seemed to be very effective in teaching and learning speed concept in elementary school.