• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.264-266
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• 2022

In order to apply the RNN model to the radio fingerprint-based indoor path generation technology, the data set must be continuous and sequential. However, Wi-Fi radio fingerprint data is not suitable as RNN data because continuity is not guaranteed as characteristic information about a specific location at the time of collection. Therefore, continuity information of sequential positions should be given. For this purpose, clustering is possible through classification of each region based on signal data. At this time, the continuity information between the clusters does not contain information on whether actual movement is possible due to the limitation of radio signals. Therefore, correlation information on whether movement between adjacent clusters is possible is required. In this paper, a deep learning network, a recurrent neural network (RNN) model, is used to predict the path of a moving object, and it reduces errors that may occur when predicting the path of an object by generating continuous location information for path generation in an indoor environment. We propose a method of giving correlation between clustering for generating an improved moving path that can avoid erroneous path prediction that cannot move on the predicted path.

• Smart Media Journal
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• v.12 no.9
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• pp.81-88
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• 2023

Recently, communication through online is increasing due to the spread of non-face-to-face services due to COVID-19. In non-face-to-face situations, the other person's opinions and emotions are recognized through modalities such as text, speech, and images. Currently, research on multimodal emotion recognition that combines various modalities is actively underway. Among them, emotion recognition using speech data is attracting attention as a means of understanding emotions through sound and language information, but most of the time, emotions are recognized using a single speech feature value. However, because a variety of emotions exist in a complex manner in a conversation, a method for recognizing multiple emotions is needed. Therefore, in this paper, we propose a multi-emotion regression model that extracts feature vectors after preprocessing speech data to recognize complex, inherent emotions and takes into account the passage of time.

• Journal of the Korea institute for structural maintenance and inspection
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• v.28 no.2
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• pp.77-86
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• 2024

In this study, authors attempted to determine the bond behavior characteristics to utilize Grid typed CFRP reinforcement as an alternative to steel rebar used as concrete reinforcement. Since it is difficult to understand the influence of the transverse grid length of the Grid typed CFRP reinforcement in the existing numerical analysis proposal for bond behavior, a nonlinear 3D model was created and finite element analysis was performed. To perform the analysis, the analysis was conducted by inputting a nonlinear material model and modeling the bond interface characteristics between the Grid typed CFRP reinforcement and concrete and comparing them with the actual direct pull-out test results. The bond behavior characteristics of the Grid typed CFRP reinforcement were found to be very dominated by the factors of the transverse grid, and showed a tendency to continuously increase load.

• Smart Media Journal
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• v.13 no.2
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• pp.44-51
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• 2024

The construction of a stress measurement detaset plays a curcial role in various modern applications. In particular, for the efficient training of artificial intelligence models for stress measurement, it is essential to compare various biases and construct a quality-controlled dataset. In this paper, we propose the construction of a stress measurement dataset with quality management through the comparison of various biases. To achieve this, we introduce strss definitions and measurement tools, the process of building an artificial intelligence stress dataset, strategies to overcome biases for quality improvement, and considerations for stress data collection. Specifically, to manage dataset quality, we discuss various biases such as selection bias, measurement bias, causal bias, confirmation bias, and artificial intelligence bias that may arise during stress data collection. Through this paper, we aim to systematically understand considerations for stress data collection and various biases that may occur during the construction of a stress dataset, contributing to the construction of a dataset with guaranteed quality by overcoming these biases.

• Journal of the Korean Society for Library and Information Science
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• v.58 no.1
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• pp.123-149
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• 2024

The purpose of this study is to present a plan to simplify the issuance of public library loan membership cards for children under the age of 14, and to devise measures to promote the convenience of using public libraries and to promote their use. To this end, related laws and systems, related services, and systems were analyzed. The issuance cases for each type were derived and analyzed by thoroughly investigating the procedure for issuing loan membership cards for children under the age of 14 in 1,211 public libraries nationwide, and focus group interviews were conducted. Based on this, the "double diamond model" was employed among service design methodologies to propose step-by-step guidelines for simplifying the procedure for issuing public library loan membership cards for children under the age of 14, as well as improving the environment, such as the roles of stakeholders, laws, and systems.

• Knowledge Management Research
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• v.24 no.4
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• pp.43-61
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• 2023

Businesses recognize the importance of empathy among members for achieving organizational goals. Accordingly, they have developed and implemented communication programs aimed at enhancing mutual understanding between the MZ generation and the older generation. However, recent communication programs conducted by businesses differ in that they involve compulsory participation driven by the organization. This study sought to empirically examine their effectiveness. Data was collected from 697 participants in communication programs to validate the proposed research model, which was empirically tested through regression analysis. The results of the analysis confirmed the effectiveness of communication programs even in non-voluntary situations and highlighted intergenerational perception differences. The findings of this study emphasize the significant role of communication and empathy within organizations. Consequently, they have impacted the development of communication strategies and culture within organizations, and are expected to provide theoretical and practical insights valuable to researchers and practitioners interested in intergenerational perception differences from a knowledge management perspective.

• Knowledge Management Research
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• v.25 no.2
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• pp.1-18
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• 2024

With the increasing demand for and utilization of large language models (LLMs), the risk of user sensitive information being inputted and leaked during the use of LLMs also escalates. Typically recognized as a tool for mitigating the hallucination issues of LLMs, knowledge graphs, constructed independently from LLMs, can store and manage sensitive user information separately, thereby minimizing the potential for data breaches. This study, therefore, presents a knowledge graph-based chatbot that transforms user-inputted natural language questions into queries appropriate for the knowledge graph using LLMs, subsequently executing these queries and extracting the results. Furthermore, to evaluate the functional validity of the developed knowledge graph-based chatbot, performance tests are conducted to assess the comprehension and adaptability to existing knowledge graphs, the capability to create new entity classes, and the accessibility of LLMs to the knowledge graph content.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.163-174
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• 2024

Currently, the urban railway operating agency is improving the emergency telephone in operation into an IP-based "trackside integrated interface communication facility" that can support a variety of additional services in order to quickly respond to emergency situations within the tunnel. This study is based on this Analyze the needs of various stakeholders regarding the design of a system architecture that establishes an IoT sensor network environment to detect abnormal situations in the tunnel and transmits the collected information to the control center to predict disaster situations in advance, and defines the system requirements. In addition, a scenario model for disaster response was provided through the presentation of a service model. Through this, the perspective of responding to urban railway disasters changes from reactive response to proactive prevention, thereby ensuring safe operation of urban railways and preventing major industrial accidents.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.35 no.2
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• pp.157-183
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• 2024

This study aims to develop a research methodology course for graduate-level students using an information-seeking behaviour model of distance learners. Based on a case study and structured survey, the factors that motivate and hinder information-seeking behaviours were identified. The motivating factor for students seeking information through the research methodology course was the necessity to obtain a master's degree, while the hindering factor was the challenge of balancing work and study. The course was developed by leveraging motivational factors and addressing hindering factors. The results of this study can serve as foundational data for understanding students' information-seeking behaviour and establishing teaching and learning strategies to enhance students' information-seeking skills when developing online courses.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.1
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• pp.143-156
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• 2024

Federated Learning (FL) has emerged as a potent methodology for decentralized model training across multiple collaborators, eliminating the need for data sharing. Although FL is lauded for its capacity to preserve data privacy, it is not impervious to various types of privacy attacks. Differential Privacy (DP), recognized as the golden standard in privacy-preservation techniques, is widely employed to counteract these vulnerabilities. This paper makes a specific contribution by applying an existing, task-specific adaptive DP mechanism to the FL environment. Our comprehensive analysis evaluates the impact of this mechanism on the performance of a shared global model, with particular attention to varying data distribution and partitioning schemes. This study deepens the understanding of the complex interplay between privacy and utility in FL, providing a validated methodology for securing data without compromising performance.