• The Journal of the Acoustical Society of Korea
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• v.17 no.2
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• pp.32-42
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• 1998

본 논문은 비균일 분포 수동형 견인 배열 센서를 사용하여 입사각 추정은 물론, 도 플러 주파수를 동시에 추정해내기 위한 기법을 제안한다. 균일 선형 센서 배열을 사용하는 전통적인 수동형 견인 센서 배열 처리기법은 센서간의 등 간격 구조 및 단순한 표본 과정에 기인하여 활용 분야의 한계성을 가지며, 주된 응용 분야가 방사된 음향신호의 입사각을 추 정하는데만 국한되어 사용될 수 있다는 문제점을 내포하고 있다. 이러한 사실 때문에, 수중 천해 환경 하에서 견인함의 등속 이동에 의해 발생하는 도플러 주파수들에 대한 정보는 목 표물에 대한 식별이나 음향신호 전달 경로의 모델링에 중요한 매개변수로 작용하며, 일반적 인 수동형 견인 센서 배열의 사용에 의한 처리 방식으로는 이러한 매개변수의 추출이 불가 능하게 된다. 본 논문은 이러한 제한성을 극복하고 방사 신호들의 개별적인 입사각 및 도플 러 주파수의 동시 추정을 가능케하도록 비균일 분포의 선형 센서 배열과 Sample Skipping 기법(Sample Skipping Technique;SST)을 적용한 새로운 형태의 수동형 견인 배열 센서 처 리 기법을 제안한다.

• Journal of KIISE
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• v.45 no.2
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• pp.165-174
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• 2018

An online community is a virtual group whose members share their interests and hobbies anonymously with nicknames unlike Social Network Services. However, there are malicious user problems such as users who write offensive contents and there may exist data fragmentation problems in which the data of the same user exists in different nicknames. In addition, nicknames are frequently changed in the online community, so it is difficult to identify them. Therefore, in this paper, to remedy these problems we propose a behavior pattern feature vectors for users considering online community characteristics, propose a new implicit behavior pattern called relationship pattern, and identify the nickname of the same user based on Random Forest classifier. Also, Experimental results with the collected real world online community data demonstrate that the proposed behavior pattern and classifier can identify the same users at a meaningful level.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.42 no.2
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• pp.493-504
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• 2017

Recently, tremendous amounts of unstructured text data that is distributed through news, blogs, and social media has gained much attention from many researchers and practitioners as this data contains abundant information about various consumers' opinions. However, as the usefulness of text data is increasing, more and more attempts to gain profits by distorting text data maliciously or nonmaliciously are also increasing. This increase in spam text data not only burdens users who want to obtain useful information with a large amount of inappropriate information, but also damages the reliability of information and information providers. Therefore, efforts must be made to improve the reliability of information and the quality of analysis results by detecting and removing spam data in advance. For this purpose, many studies to detect spam have been actively conducted in areas such as opinion spam detection, spam e-mail detection, and web spam detection. In this study, we introduce core concepts and current research trends of spam detection and propose a methodology to detect the spam tag of a blog as one of the challenging attempts to improve the reliability of blog information.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.201-210
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• 2023

Deep learning-based face verificattion model show high performance and are used in many fields, but there is a possibility the user's face image may be leaked in the process of inputting the face image to the model. Althoughde-identification technology exists as a method for minimizing the exposure of face features, there is a problemin that verification performance decreases when the existing technology is applied. In this paper, after combining the face features of other person, a de-identified face image is created through StyleGAN. In addition, we propose a method of optimizingthe combining ratio of features according to the face verification model using HopSkipJumpAttack. We visualize the images generated by the proposed method to check the de-identification performance, and evaluate the ability to maintain the performance of the face verification model through experiments. That is, face verification can be performed using the de-identified image generated through the proposed method, and leakage of face personal information can be prevented.

• Convergence Security Journal
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• v.22 no.5
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• pp.11-20
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• 2022

As the Internet and web technology develop around mobile devices, image data contains various types of sensitive information such as people, text, and space. In addition to these characteristics, as the use of SNS increases, the amount of damage caused by exposure and abuse of personal information online is increasing. However, research on de-identification technology based on multi-type object detection for personal information protection is insufficient. Therefore, this paper proposes an artificial intelligence model that detects and de-identifies multiple types of objects using existing single-type object detection models in parallel. Through cutmix, an image in which person and text objects exist together are created and composed of training data, and detection and de-identification of objects with different characteristics of person and text was performed. The proposed model achieves a precision of 0.724 and mAP@.5 of 0.745 when two objects are present at the same time. In addition, after de-identification, mAP@.5 was 0.224 for all objects, showing a decrease of 0.4 or more.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.3
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• pp.133-138
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• 2024

In the modern academic research environment, the advancement of digital technology provides researchers with increasingly diverse and rich access to information, but at the same time, the issue of author identification has emerged as a new challenge. The problem of author identification is a major factor that undermines the transparency and accuracy of academic communication, potentially causing confusion in the accurate attribution of research results and the construction of research networks. In response, identifier systems such as the International Standard Name Identifier (ISNI) and Open Researcher and Contributor ID (ORCID) have been introduced, but still face limitations due to low participation by authors and inaccurate entry of information. This study focuses on researching information management methods for identification from the moment author information is first entered into the system, proposing ways to improve the accuracy of author identification and maximize the efficiency of academic information services. Through this, it aims to renew awareness of the issue of author identification within the academic community and present concrete measures that related institutions and researchers can take to solve this problem.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.7
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• pp.4918-4924
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• 2015

In this paper, we consider the capacity improvement of systems exploiting dual-polarized antennas for two-user transmission. To this end, we analyze the upper bounds of ergodic capacities for multicast and unicast data services in the systems, and propose the condition for adjusting the complex cross-polarization discriminations (XPDs) to maximize the ergodic capacities. In addition, we present the adjustment condition of the complex XPDs that can achieve spectral efficiencies close to the maximum ergodic capacities with lower system complexity. Lastly simulation results demonstrate that the systems using the proposed conditions can obtain higher spectral efficiencies than the ones employing different adjustment conditions including the exiting adjustment condition.

• The Korean Journal of Applied Statistics
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• v.31 no.1
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• pp.1-11
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• 2018

Multivariate process control has become important in various applied fields. For instance, there are many situations in which the simultaneous monitoring of multivariate quality characteristics is necessary for the manufacturing industry. Despite its importance, its practical usage is not as convenient because it is difficult to identify the source of the out-of-control signal in a multivariate control chart. In this paper, we will introduce how to detect the source of the out-of-control by using confidence intervals for new observations, and will discuss the identification and interpretation of the out-of-control variable through simulation studies.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.21 no.1
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• pp.105-118
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• 2010

In this paper, we proposed the effectively method for constructing of name authority data in korean academic papers and designed the authority database system that is applied the method. For these, we analyze the requisite for identifying the author name and suggest the author identification method. Because construction of name authority record costs time and effort, and considering frequently period of large-scale acquisitions of academic papers, our suggestion includes the system that be able to manage and construct the name authority database, and that is tightly connected with the academic paper management and service systems.

• Journal of KIISE:Computing Practices and Letters
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• v.14 no.2
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• pp.221-225
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• 2008

In this paper, to avoid the frequency analysis requiring a high sampling rate, time-warped similarity measure algorithms, which are able to classify objects even with a low-rate sampling rate as time- series methods, are presented and proposed the DTW-Cosine algorithm, as the best classifier among them in wireless sensor networks. Two problems, local time shifting and spatial signal variation, should be solved to apply the time-warped similarity measure algorithms to wireless sensor networks. We find that our proposed algorithm can overcome those problems very efficiently and outperforms the other algorithms by at least 10.3% accuracy.