• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.515-522
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• 2022

This study analyzed the child protection system in Germany from a preventive perspective and attempts to find the applicable implications to Korea. The research method was analyzed in terms of legal, policy and professionalism. The result is as follows. First, Child and Youth Support Act in Germany stipulated a preventive support system to restore the function of the family. Second, according to the Civil Act, it was stipulated that the family court could intervene early. Third, the federal Child Protection Act stipulated community cooperation for thd child protection system. Fourth, the Youth Agency as the general authority made it possible to provide preventive support and intervention at the same time. Firth, qualification standards were specified in the Child and Youth Support Act. Child protection specialists are granted to public officials who have worked for more than three years. The implications are as follows. First, the child protection system, which operates as a child abuse reporting system, should be expanded to a preventive support system. Second, it is necessary to expand monitoring by establishing an early warning system between networks in order to establish a support system for potentially at-risk children. Third, local governments should support children and parents flexibly and comprehensively for dysfunction caused by difficulties at home. Fourth, it is necessary to enact the Child Protection System Cooperation Act for a network cooperation system.

• Journal of The Korean Association of Information Education
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• v.25 no.6
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• pp.947-960
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• 2021

In this study, we examine the AI ethics perception of university students to explore the direction of AI ethics education. For this, 83 students wrote their thoughts about 5 discussion topics on online bulletin board. We analyzed it using language networks, one of the text mining techniques. As a result, 62.5% of students spoke the future of the AI society positively. Second, if there is a self-driving car accident, 39.2% of students thought it is the vehicle owner's responsibility at the current level of autonomous driving. Third, invasion of privacy, abuse of technology, and unbalanced information acquisition were cited as dysfunctions of the development of AI. It was mentioned that ethical education for both AI users and developers is required as a way to minimize malfunctions, and institutional preparations should be carried out in parallel. Fourth, only 19.2% of students showed a positive opinion about a society where face recognition technology is universal. Finally, there was a common opinion that when collecting data including personal information, only the part with the consent should be used. Regarding the use of AI without moral standards, they emphasized the ethical literacy of both users and developers. This study is meaningful in that it provides information necessary to design the contents of artificial intelligence ethics education in liberal arts education.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.93-114
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• 2023

Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.

• The Korean Journal of Archival Studies
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• no.75
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• pp.177-212
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• 2023

Private archives are an important indicator of understanding a society that contains various memories, the lives and experiences of members, daily lives, morality, and values. Recently, as diversity has emerged as an important value in Korean society, a number of individuals and communities have been appeared based on different bases and purposes, and the contents, types, and categories of private archives produced from their voluntary activities have also diversified. These private organizations and communities are potential targets for producing and holding private archives, but most of them do not have the minimum infrastructure or system for management of archives, and the foundation for management of archives is weak only to be supported with the voluntary will and activities of the private sector. Therefore, there is a need for a plan to support activities to manage archives suitable for each organization's level while respecting the unique characteristics and methods of the private sector within the national management system of archives. In addition, since it is difficult to solve all issues related to management of archives in the private sector with only a small number of process topics, a cooperative system should be established to sustain activities to manage archives on its own through networks between private sectors. In this study, we intend to propose a 'private archives information network platform (hereinafter referred to as a platform)' as a way to establish a communication and network foundation between private sectors and share resources with each other. Based on the results of analysis of cases of building network between private sectors and expected user requirements, we would like to establish a vision and target model of the platform and discuss ways to continuously operate the platform.

• The Korean Journal of Coaching Psychology
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• v.5 no.1
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• pp.33-65
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• 2021

This study is an exploratory study to investigate the concept of student success recognized by college students. In order to listen to students' free thoughts, an open questionnaire was conducted using an online questionnaire and 99 responses were analyzed. The response results were analyzed using CQR-M (Consensual Qualitative Research-Modified). As a result of the analysis, 25 categories were derived from three domains. The frist domain, 'meaning of student success' recognized by college students is with 9 categories: 'academic achievement', 'job competency improvement', 'gaining diverse experiences', 'satisfactory employment', 'setting of desired career path', 'relationship-building ability improvement', 'setting and achievement of own goals', 'self-development', and 'satisfactory college life'. The second domain, 'college environmental factors for student success' is with 7 categories: 'career development support', 'job competency improvement system', 'support for participation in college life', 'opportunities to form human networks', 'learning capability enhancement system', 'expansion of economic support', and 'environment for student convenience'. The third domain, 'psychological factors necessary for student success' is with 9 categories: 'learning ability', 'self-efficacy', 'interpersonal competence', 'self-awareness and improvement', 'job competency', 'self-regulation ability', 'rich experience', 'career awareness', and 'self-esteem'. The frequency and results of each domain were analyzed and presented, the significance and limitations of the study were discussed, and suggestions for subsequent studies were made.

• Journal of Microbiology and Biotechnology
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• v.33 no.2
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• pp.219-227
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• 2023

Lettuce is one of the most consumed vegetables worldwide. However, it has potential risks associated with pathogenic bacterial contamination because it is usually consumed raw. In this study, we investigated the changes in the bacterial community on lettuce (Lactuca sativa L.) in Chungcheong-do, South Korea, and the prevalence of foodborne pathogens on lettuce in different seasons using 16S rRNA gene-based sequencing. Our data revealed that the Shannon diversity index showed the same tendency in term of the number of OTUs, with the index being greatest for summer samples in comparison to other seasons. Moreover, the microbial communities were significantly different between the four seasons. The relative abundance of Actinobacteriota varied according to the season. Family Micrococcaceae was most dominant in all samples except summer, and Rhizobiaceae was predominant in the microbiome of the summer sample. At the genus level, the relative abundance of Bacillus was greatest in spring samples, whereas Pseudomonas was greatest in winter samples. Potential pathogens, such as Staphylococcus and Clostridium, were detected with low relative abundance in all lettuce samples. We also performed metagenome shotgun sequencing analysis on the selected summer and winter samples, which were expected to be contaminated with foodborne pathogens, to support 16S rRNA gene-based sequencing dataset. Moreover, we could detect seasonal biomarkers and microbial association networks of microbiota on lettuce samples. Our results suggest that seasonal characteristics of lettuce microbial communities, which include diverse potential pathogens, can be used as basic data for food safety management to predict and prevent future outbreaks.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.193-200
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• 2023

Cryptanalysis can be performed by various techniques such as known plaintext attack, differential attack, side-channel analysis, and the like. Recently, many studies have been conducted on cryptanalysis using deep learning. A known-plaintext attack is a technique that uses a known plaintext and ciphertext pair to find a key. In this paper, we use deep learning technology to perform a known-plaintext attack against S-PRESENT, a reduced version of the lightweight block cipher PRESENT. This paper is significant in that it is the first known-plaintext attack based on deep learning performed on a reduced lightweight block cipher. For cryptanalysis, MLP (Multi-Layer Perceptron) and 1D and 2D CNN(Convolutional Neural Network) models are used and optimized, and the performance of the three models is compared. It showed the highest performance in 2D convolutional neural networks, but it was possible to attack only up to some key spaces. From this, it can be seen that the known-plaintext attack through the MLP model and the convolutional neural network is limited in attackable key bits.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.179-188
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• 2023

Recently, fake news disguises the form of news content and appears whenever important events occur, causing social confusion. Accordingly, artificial intelligence technology is used as a research to detect fake news. Fake news detection approaches such as automatically recognizing and blocking fake news through natural language processing or detecting social media influencer accounts that spread false information by combining with network causal inference could be implemented through deep learning. However, fake news detection is classified as a difficult problem to solve among many natural language processing fields. Due to the variety of forms and expressions of fake news, the difficulty of feature extraction is high, and there are various limitations, such as that one feature may have different meanings depending on the category to which the news belongs. In this paper, emotional change patterns are presented as an additional identification criterion for detecting fake news. We propose a model with improved performance by applying a convolutional neural network to a fake news data set to perform analysis based on content characteristics and additionally analyze emotional change patterns. Sentimental polarity is calculated for the sentences constituting the news and the result value dependent on the sentence order can be obtained by applying long-term and short-term memory. This is defined as a pattern of emotional change and combined with the content characteristics of news to be used as an independent variable in the proposed model for fake news detection. We train the proposed model and comparison model by deep learning and conduct an experiment using a fake news data set to confirm that emotion change patterns can improve fake news detection performance.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.33 no.1
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• pp.371-401
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• 2022

If the blockchain means storing information in a distributed environment that cannot be forged or altered, it is mentioned that this is similar to what librarians collect, preserve, and share authoritative information. In this way, this study examined blockchain technology as a way to collect and provide reliable information, increase work efficiency inside and outside the library, and strengthen cooperative networks. This study attempted to propose various ways to utilize blockchain technology in book relations based on literature surveys and case studies in other fields. To this end, this study first analyzed the field and cases of blockchain application to confirm the possibility and value of blockchain application in the library field, and proposed 12 ways to utilize it based on this. The utilization model was proposed by dividing it into operation and service sectors. In the operation sector, it is a digital identity-based user record storage and authentication function, transparent management and traceable monitoring function, voting-based personnel and recruitment system, blockchain governance-based network efficiency function, and blockchain-based next-generation device management and information integration function. The service sector includes improved book purchase and sharing efficiency due to simplification of intermediaries, digital content copyright protection and management functions, customized service provision based on customer behavior analysis, blockchain-based online learning platforms, sharing platforms, and P2P-based reliable information sharing platforms.

• Journal of Aerospace System Engineering
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• v.16 no.1
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• pp.86-96
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• 2022

The development trend of jet fighter's avionics system architecture is the digitization of subsystem component functions, increased RF sensor sharing, fiber optic channel networks, and modularized integrated structures. The avionics system architecture of the fifth generation jet fighters (F-22, F-35) has evolved into an integrated modular avionics system based on computing function integration and RF integrated sensor systems. The integrated modular avionics system of jet fighters should provide improved combat power, fault tolerance, and ease of jet fighter control. To this aim, this paper presents the direction and requirements of the next-generation jet fighter's avionics system architecture through analysis of the fifth generation jet fighter's avionics system architecture. The core challenge of the integrated modularized avionic system architecture requirements for next-generation fighters is to build a platform that integrates major components and sensors into aircraft. In other words, the architecture of the next-generation fighters is standardization of systems, sensor integration of each subsystem through open interfaces, integration of functional elements, network integration, and integration of pilots and fighters to improve their ability to respond and control.