• Journal of Korea Multimedia Society
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• v.19 no.9
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• pp.1647-1658
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• 2016

RGB+D database has been widely used in object recognition, object tracking, robot control, to name a few. While rapid advance of active depth sensing technologies allows for the widespread of indoor RGB+D databases, there are only few outdoor RGB+D databases largely due to an inherent limitation of active depth cameras. In this paper, we propose a novel method used to build outdoor RGB+D databases. Instead of using active depth cameras such as Kinect or LIDAR, we acquire a pair of stereo image using high-resolution stereo camera and then obtain a depth map by applying stereo matching algorithm. To deal with estimation errors that inevitably exist in the depth map obtained from stereo matching methods, we develop an approach that estimates confidence of depth maps based on unsupervised learning. Unlike existing confidence estimation approaches, we explicitly consider a spatial correlation that may exist in the confidence map. Specifically, we focus on refining confidence feature with the assumption that the confidence feature and resultant confidence map are smoothly-varying in spatial domain and are highly correlated to each other. Experimental result shows that the proposed method outperforms existing confidence measure based approaches in various benchmark dataset.

• ETRI Journal
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• v.43 no.1
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• pp.40-52
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• 2021

DNS (Domain Name System) tunnels almost obscure the true network activities of users, which makes it challenging for the gateway or censorship equipment to identify malicious or unpermitted network behaviors. An efficient way to address this problem is to conduct a temporal-spatial analysis on the tunnel traffic. Nevertheless, current studies on this topic limit the DNS tunnel to those with a single protocol, whereas more than one protocol may be used simultaneously. In this paper, we concentrate on the refined identification of two protocols mixed in a DNS tunnel. A feature set is first derived from DNS query and response flows, which is incorporated with deep neural networks to construct a regression model. We benchmark the proposed method with captured DNS tunnel traffic, the experimental results show that the proposed scheme can achieve identification accuracy of more than 90%. To the best of our knowledge, the proposed scheme is the first to estimate the ratios of two mixed protocols in DNS tunnels.

• Journal of Convergence for Information Technology
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• v.11 no.4
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• pp.161-167
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• 2021

This study was conducted to identify the relationship between the dual task performance and driving behavior of the elderly driver in order to identify whether the dual task can be utilized as a test to screen the driving ability of the elderly driver. We surveyed general information and driving-related information for 32 normal elderly drivers, and evaluated Y-DuCog(Yonsei-Dual task Cognitive screening) and the K-DBQ (Korean-Driving Behavior Questionnaire). As a result of the study, the performance of the dual task using the pegboard task and the animal name speaking showed a significant correlation with the score of the violation domain of K-DBQ. With this study, it was possible to confirm the possibility as a test for discrimination of driving ability.

• International Journal of Computer Science & Network Security
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• v.23 no.5
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• pp.1-6
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• 2023

Text mining (TM) is most widely used to process the various unstructured text documents and process the data present in the various domains. The other name for text mining is text classification. This domain is most popular in many domains such as movie reviews, product reviews on various E-commerce websites, sentiment analysis, topic modeling and cyber bullying on social media messages. Cyber-bullying is the type of abusing someone with the insulting language. Personal abusing, sexual harassment, other types of abusing come under cyber-bullying. Several existing systems are developed to detect the bullying words based on their situation in the social networking sites (SNS). SNS becomes platform for bully someone. In this paper, An Enhanced text mining approach is developed by using Ensemble Algorithm (ETMA) to solve several problems in traditional algorithms and improve the accuracy, processing time and quality of the result. ETMA is the algorithm used to analyze the bullying text within the social networking sites (SNS) such as facebook, twitter etc. The ETMA is applied on synthetic dataset collected from various data a source which consists of 5k messages belongs to bullying and non-bullying. The performance is analyzed by showing Precision, Recall, F1-Score and Accuracy.

• Annual Conference on Human and Language Technology
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• 2019.10a
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• pp.339-342
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• 2019

본 논문에서는 소프트웨어 정의 네트워크를 이용한 한중일 한자-한국어 변환 키워드 도메인 이름 시스템을 제안하였다. 한자 체계를 주로 사용하는 한국, 중국, 일본에서 세 나라의 한자 수량이 너무 많기 때문에 우선 한국, 중국, 일본이 공용으로 사용하는 한자 체계인 CJK808을 가지고 연구하였다. 연구를 통해 CJK808 한자 체계에서 각 나라의 한자 특징도 많이 발견하였고, 그 중에서 표준자와 이체자의 다양성이 더욱 두드러졌다. SDN을 이용함으로써 관리 측면에서 다양한 이점을 얻을 수 있다. 제안하는 시스템을 통하여 사용자들은 한국, 중국, 일본 한자를 입력하면 SDN에서 관리하는 도메인 네임 서버를 통해 IP 주소를 얻을 수 있다.

• International Journal of Computer Science & Network Security
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• v.24 no.3
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• pp.93-100
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• 2024

In this paper, we propose a novel robust blind crypto-watermarking method for medical images security based on hiding of DICOM patient information (patient name, age...) in the medical imaging. The DICOM patient information is encrypted using the AES standard algorithm before its insertion in the medical image. The cover image is divided in blocks of 8x8, in each we insert 1-bit of the encrypted watermark in the hybrid transform domain by applying respectively the 2D-LWT (Lifting wavelet transforms), the 2D-DCT (discrete cosine transforms), and the SVD (singular value decomposition). The scheme is tested by applying various attacks such as noise, filtering and compression. Experimental results show that no visible difference between the watermarked images and the original images and the test against attack shows the good robustness of the proposed algorithm.

• Journal of Distribution Science
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• v.13 no.1
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• pp.57-70
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• 2015

Purpose - Open source software has high utilization in most of the server market. The utilization of open source software is a global trend. Particularly, Internet infrastructure and platform software open source software development has increased rapidly. Since 2003, the Korean government has published open source software promotion policies and a supply promotion policy. The dynamism of the open source software market, the lack of relevant expertise, and the market transformation due to reasons such as changes in the relevant technology occur slowly in relation to adoption. Therefore, this study proposes an assessment model of services provided in an open source software service company. In this study, the service level of open source software companies is classified into an enterprise-level assessment area, the service level assessment area, and service area. The assessment model is developed from an on-site driven evaluation index and proposed evaluation framework; the evaluation procedures and evaluation methods are used to achieve the research objective, involving an impartial evaluation model implemented after pilot testing and validation. Research Design, data, and methodology - This study adopted an iteration development model to accommodate various requirements, and presented and validated the assessment model to address the situation of the open source software service company. Phase 1 - Theoretical background and literature review Phase 2 - Research on an evaluation index based on the open source software service company Phase 3 - Index improvement through expert validation Phase 4 - Finalizing an evaluation model reflecting additional requirements Based on the open source software adoption case study and latest technology trends, we developed an open source software service concept definition and classification of public service activities for open source software service companies. We also presented open source software service company service level measures by developing a service level factor analysis assessment. The Behavior-Structure-Evolution Evaluation Model (BSEM) proposed in this study consisted of a rating methodology for calculating the level that can be granted through the assessment and evaluation of an enterprise-level data model. An open source software service company's service comprises the service area and service domain, while the technology acceptance model comprises the service area, technical domain, technical sub-domain, and open source software name. Finally, the evaluation index comprises the evaluation group, category, and items. Results - Utilization of an open source software service level evaluation model For the development of an open source software service level evaluation model, common service providers need to standardize the quality of the service, so that surveys and expert workshops performed in open source software service companies can establish the evaluation criteria according to their qualitative differences. Conclusion - Based on this evaluation model's systematic evaluation process and monitoring, an open source software service adoption company can acquire reliable information for open source software adoption. Inducing the growth of open source software service companies will facilitate the development of the open source software industry.

• Journal of the Korea Society of Computer and Information
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• v.28 no.12
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• pp.129-136
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• 2023

The government of the Republic of Korea is conducting quality management of public open data by conducting a public data quality management level evaluation. Public open data is provided in various open formats such as XML, JSON, and CSV, with CSV format accounting for the majority. When diagnosing the quality of public open data in CSV format, the quality diagnosis manager determines and diagnoses the domain for each field based on the field name and data within the field of the public open data file. However, it takes a lot of time because quality diagnosis is performed on large amounts of open data files. Additionally, in the case of fields whose meaning is difficult to understand, the accuracy of quality diagnosis is affected by the quality diagnosis person's ability to understand the data. This paper proposes a domain discrimination model for public open data in CSV format using field names and data distribution statistics to ensure consistency and accuracy so that quality diagnosis results are not influenced by the capabilities of the quality diagnosis person in charge, and to support shortening of diagnosis time. As a result of applying the model in this paper, the correct answer rate was about 77%, which is 2.8% higher than the file format open data diagnostic tool provided by the Ministry of Public Administration and Security. Through this, we expect to be able to improve accuracy when applying the proposed model to diagnosing and evaluating the quality management level of public data.

• Journal of Educational Research in Mathematics
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• v.22 no.3
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• pp.429-444
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• 2012

As one of the trials for a systematic approach to mathematics terms which occupies an important place in teaching and learning mathematics, compositions of listed terms in 2011 elementary mathematics curriculum in Korea are discussed in this study. To this end, listed terms are classified in view of three points and looked for their characteristics, from which implications are found out for elementary mathematics teaching and learning First of all classifications into grade-group and domain-specific terms, then into newly coined terms and terms from everyday life, and then into korean terms and chinese character terms and english terms are attempted. Next, terms with a kernel and terms without a kernel are distinguished, and in this process, term-sets are presented. Finally, object terms, operation terms, relationship terms, measure terms, conditions terms, graphics terms, name terms are classified. Based on these results, the following implications for elementary mathematics teaching and learning are suggested. First, it should be considered that many of the listed terms in 2011 curriculum are newly coined and chinese character terms. Second, the interconnections between terms should be considered. Third, a variety of roles and functions of the terms should be considered.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.30 no.4
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• pp.29-50
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• 2019

This study was to suggest the considerations for application profiles of 2019 revised RDA using literature reviews and case studies according to new RDA that revised in order to reflect the LRM and linked data. First, the additional elements were recommended as the contents of application profiles such as inverse element, broader element, narrow element, domain, range, alternate label name, mapping to MARC, mapping to BIBFRAME, and RDA description examples as new elements as well as element name, element ID, element URL, description method, vocabulary encoding scheme, data provenance element, data provenance value, and notes as the elements that were already suggested by previous researches. Second, RDA rules' representations in forms of flow chart and application profiles through analyzing RDA rules were suggested in order to apply the rules to RDA application profiles to structure the rules in which every element has 4 types of description method, many conditions, and options. Third, the RDA mapping to BIBFRAME was suggested in RDA application profiles because RDA and BIBFRAME are co-related in context of content standard and encoding format, and mapping BIBFRAME and RDA is necessitated for programming BIBFRAME editors with RDA as content standard. This study will contribute to find the methods for constructing RDA application profiles and BIBFRAME application profiles with RDA as content standard.