• Journal of the Korean Society for Library and Information Science
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• v.55 no.4
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• pp.141-157
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• 2021

In this study, we aimed to understand research trends of domestic artificial intelligence research. To achieve the goal, we applied network analysis and dynamic topic modeling to domestic research papers on artificial intelligence. Among the papers that have been indexed in KCI (Korean Journal of Citation Index) by 2020, metadata and abstracts of 2,552 papers where the titles or indexed keywords include 'artificial intelligence' both in Korean and English were collected. Keyword, affiliation, subject field, and abstract were extracted and preprocessed for further analyses. We identified main keywords in the field by analyzing keyword co-occurrence networks as well as the degree and characteristics of research collaboration between domestic and foreign institutions and between industry and university by analyzing institutional collaboration networks. Dynamic topic modeling was performed on 1845 abstracts written in Korean, and 13 topics were obtained from the labeling process. This study broadens the understanding of domestic artificial intelligence research by identifying research trends through dynamic topic modeling from abstracts as well as the degree and characteristics of research collaboration through institutional collaboration networks from author affiliation information. In addition, the results of this study can be used by governmental institutions for making policies in accordance with artificial intelligence era.

• KIPS Transactions on Computer and Communication Systems
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• v.9 no.12
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• pp.291-306
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• 2020

Nowadays, Data-Network-AI (DNA)-based intelligent services and applications have become a reality to provide a new dimension of services that improve the quality of life and productivity of businesses. Artificial intelligence (AI) can enhance the value of IoT data (data collected by IoT devices). The internet of things (IoT) promotes the learning and intelligence capability of AI. To extract insights from massive volume IoT data in real-time using deep learning, processing capability needs to happen in the IoT end devices where data is generated. However, deep learning requires a significant number of computational resources that may not be available at the IoT end devices. Such problems have been addressed by transporting bulks of data from the IoT end devices to the cloud datacenters for processing. But transferring IoT big data to the cloud incurs prohibitively high transmission delay and privacy issues which are a major concern. Edge computing, where distributed computing nodes are placed close to the IoT end devices, is a viable solution to meet the high computation and low-latency requirements and to preserve the privacy of users. This paper provides a comprehensive review of the current state of leveraging deep learning within edge computing to unleash the potential of IoT big data generated from IoT end devices. We believe that the revision will have a contribution to the development of DNA-based intelligent services and applications. It describes the different distributed training and inference architectures of deep learning models across multiple nodes of the edge computing platform. It also provides the different privacy-preserving approaches of deep learning on the edge computing environment and the various application domains where deep learning on the network edge can be useful. Finally, it discusses open issues and challenges leveraging deep learning within edge computing.

• The KIPS Transactions:PartB
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• v.17B no.6
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• pp.437-444
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• 2010

In this paper, we propose a method of analysing the relation between the patient's face color and his(her) kidney disease using image processing technology. This method is based on the ocular inspection which is one of the most famous diagnosis methods used in the oriental medical system. The way of processing and analysing the face image, which is for visualization and objectification of the color difference, is included. The objects are selected from the patients who suffer the kidney disease and use the hemodialyzer. Their facial images and clinical data are collected. From these data, we propose a hypothesis that the color of the patient's face is changed according to the patient's kidney state. At the same time, we present two algorithms of extracting the specific part of face which can identify the state of the patient's kidney and tracing the history of the color's change. This proposed method is evaluated through the practical experiments and their analysis.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.16 no.2
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• pp.139-156
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• 2005

In this paper, we design and implement electronic book system providing web-based interface for the ebook. The aim of this study is to optimize the effective reading and management of electronic text for its users(readers and librarians). Advanced functions of the electronic book system are the following: 1) Electronic book system is not dependent to specific software and tool. 2) Electronic book system is able to. minimize images(table, image, icon etc) to improve the meaning and readability of information. 3) Electronic book system is able to reduce the effort for indexing extraction and constructing the table of content. 4) The system is able to collect the user log files that are created during the process of reading ebook from various points of view. 5) When reading, the system uses the DRM through decoding and encoding the ebook.

• The Journal of Society for e-Business Studies
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• v.16 no.2
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• pp.39-71
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• 2011

Lately, developing systems fully interoperable with others is considered an essential element for successful projects, as not only do e-commerce becomes ubiquitous but also distributed systems' paradigm spreads. However, since definitions of interoperability vary by viewpoints, it is still difficult to have the same understanding and evaluation criteria on interoperability. For instance, various interoperability parties in military use different definitions of interoperability, and its T&E is not conducted according to the definition, but only to levels of information exchange. In this paper, we proposed a new definition of interoperability as followsm First of all, we collected existing and various interoperability definitions, extracting key components in each of them. Second, we statistically analyzed those components and applied the association rules discovery in data mining. We compared existing interoperability definitions to ours. From this research, we found associations among the components from various definitions applying market-basketanalysis, redefining interoperability. Key findings of this research can contribute to a unified viewpoint on the definition, level, and evaluation items of interoperability.

• Convergence Security Journal
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• v.20 no.3
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• pp.21-28
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• 2020

In recent years, hacking and malware techniques have evolved and become sophisticated and complex, and numerous cyber-attacks are constantly occurring in various fields. Among them, the most widely used route for compromise incidents such as information leakage and system destruction was found to be E-Mails. In particular, it is still difficult to detect and identify E-Mail APT attacks that employ zero-day vulnerabilities and social engineering hacking techniques by detecting signatures and conducting dynamic analysis only. Thus, there has been an increased demand for indicators of compromise (IOC) to identify the causes of malicious activities and quickly respond to similar compromise incidents by sharing the information. In this study, we propose a method of extracting various forensic artifacts required for detecting and investigating Hacking E-Mails, which account for large portion of damages in security incidents. To achieve this, we employed a digital forensic indicator method that was previously utilized to collect information of client-side incidents.

• Journal of Korean Society of Transportation
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• v.23 no.1
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• pp.83-92
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• 2005

This study if the first trial toward realizing a new methodology for vehicle re-identification based on heterogeneous sensor systems. A major interest of the author is how to effectively utilize information obtained from different sensors to derive accurate and reliable section travel times. The 'blade' sensor that is a newly developed sensor for capturing vehicle wheel information and the existing square loop sensor are employed to extract the inputs of the proposed vehicle re-identification algorithm. The fundamental idea of the algorithm developed in this study, which is so called 'anonumous vehicle re-identification,' it to match vehicle features obtained from both sensors. The results of the algorithm evaluation reveal that the proposed methodology could be successfully implemented in the field. The proposed methodology would be an invaluable tool for operating agencies in support of traffic monitoring systems and traveler information systems.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.11 no.6
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• pp.664-670
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• 2018

In modern society, CCTV, which is the eye of surveillance, is being used to collect image data in various ways in daily life. CCTV is used not only for security, surveillance, and crime prevention but also in many fields such as automobile and black box. In this paper, we have developed a STM32F407 ARM chip based camera system for various applications. In order to develop camera system, modeling of camera system based on 3D structure was carried out in SolidWorks environment. The PCB board design was developed to extract the PCB parts from the camera system modeling files into iges files, convert them from the Altium Designer tool into 3D and 2D boards, After designing the camera system circuit and PCB, we have been studying the implementation of the stable system by using TRM (Thermal Risk Management) tool to cope with the heat simulation generated on the board.

• Journal of Digital Forensics
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• v.12 no.3
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• pp.71-82
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• 2018

Using small cameras such as smartphones, criminals shoot secretly in public restrooms and women's changing rooms. And Revenge porn is also increasing. As a result social damage is increasing. Tumblr is an overseas service and it is very difficult to work with Tumbler on international legal cooperation and deletions. Thus In order to block the distribution of videos, victims must find and report the video URL themselves. But it's hard for victims who lack IT expertise to proceed those procedure. In this study, we automatically collect the URL of stored information and hash values of the images from API permlink of Tumbler blog. It is then saved as a document file with and presented to the victim. Through these technical methods, we can help victims report violations easily and quickly.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.3
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• pp.464-470
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• 2021

Automobiles have been used as simple means of transportation, but recently, as automobiles are rapidly becoming intelligent and smart, and automobile preferences are increasing, research on IT technology convergence is underway, requiring basic high-performance functions such as driver's convenience and safety. As a result, autonomous driving and semi-autonomous vehicles are developed, and these technologies sometimes deviate from lanes due to environmental problems, situations that cannot be judged by autonomous vehicles, and lane detectors may not recognize lanes. In order to improve the performance of lane departure from the lane detection system of autonomous vehicles, which is such a problem, this paper uses fast recognition, which is a characteristic of YOLO(You only look once), and is affected by the surrounding environment using CSI-Camera. We propose a lane detection system that recognizes the situation and collects driving data to extract the region of interest.