• The KIPS Transactions:PartC
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• v.11C no.5
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• pp.697-702
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• 2004

As for the digital content, a reproduction is easy and manuscript is identical with original copy. Because of these characteristics, there are difficulties on prevention of an illegal reproduction and an illegal currency. In recent days various digital content service systems based on a web are commercialized. An appropriate copyright protection technology is required so that these systems develop as a profit model. Generally we use encrypted digital content transmission method for the copyright protection on a web base system. At the time of this, it is increased sire of encrypted digital content. As for this, it be increased time required on an execution process. Therefore, a design of the system that considered a execution time and a security is required. In this study, we designed the digital content transmission system that considered execution time and a security through a partial encryption based on a digital content copyright management technique. Also we evaluated performance of a proposed system through analysis.

• The Journal of the Korea Contents Association
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• v.20 no.2
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• pp.240-247
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• 2020

There have been many efforts to understand the trends of IT environments that have been rapidly changed. In a view point of management, it needs to prepare the social systems in advance by using Big-data these days. This research is for the implementation of Issue Analysis System for the Big-data based on Artificial Intelligence. This paper aims to confirm the possibility of new technology for Big-data processing through the proposed Issue Analysis System using. We propose a technique for semantic reasoning and pattern analysis based on the AI and show the proposed method is feasible to handle the Big-data. We want to verify that the proposed method can be useful in dealing with Big-data by applying latest security issues into the system. The experiments show the potentials for the proposed method to use it as a base technology for dealing with Big-data for various purposes.

• Nuclear Engineering and Technology
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• v.52 no.4
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• pp.835-840
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• 2020

A position-sensitive CsI(Tl) crystal array coupled with the multi-anode position sensitive photomultiplier tube (PS-PMT), Hamamatsu H8500C, has been developed at the Institute of Modern Physics. An effective, fast, and economical readout circuit based on discretized positioning circuit (DPC) bridge was designed for the 64-channel multi-anode flat panel PSPMT. The horizontal and vertical position resolutions are 0.58 mm and 0.63 mm respectively for the 1.0 × 1.0 × 5.0 ㎣ CsI(Tl) array, and the horizontal and vertical position resolutions are 0.86 mm and 0.80 mm respectively for the 2.0 × 2.0 × 10.0 ㎣ CsI(Tl) array. These results show that the CsI(Tl) crystal array with low cost could be applied in the fields of medical imaging and high-resolution gamma camera.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.44 no.3
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• pp.229-238
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• 2008

This paper describes on the consolidation of AIS and ARPA radar positions by comparing the AIS and ARPA radar information for the tracked ship targets using a PC-based ECDIS in Busan harbor, Korea. The information of AIS and ARPA radar target was acquired independently, and the tracking parameters such as ship's position, COG, SOG, gyro heading, rate of turn, CPA, TCPA, ship s name and MMSI etc. were displayed automatically on the chart of a PC-based ECDIS with radar overlay and ARPA tracking. The ARPA tracking information obtained from the observed radar images of the target ship was compared with the AIS information received from the same vessel to investigate the difference in the position and movement behavior between AIS and ARPA tracked target ships. For the ARPA radar and AIS targets to be consolidated, the differences in range, speed, course, bearing and distance between their targets were estimated to obtain a clear standards for the consolidation of ARPA radar and AIS targets. The average differences between their ranges, their speeds and their courses were 2.06% of the average range, -0.11 knots with the averaged SOG of 11.62 knots, and $0.02^{\circ}$ with the averaged COG of $37.2^{\circ}$, respectively. The average differences between their bearings and between their positions were $-1.29^{\circ}$ and 68.8m, respectively. From these results, we concluded that if the ROT, COG, SOG, and HDG informations are correct, the AIS system can be improved the prediction of a target ship's path and the OOW(Officer of Watch) s ability to anticipate a traffic situation more accurately.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.46 no.4
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• pp.15-31
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• 2023

In this study, we propose a novel approach to analyze big data related to patents in the field of smart factories, utilizing the Latent Dirichlet Allocation (LDA) topic modeling method and the generative artificial intelligence technology, ChatGPT. Our method includes extracting valuable insights from a large data-set of associated patents using LDA to identify latent topics and their corresponding patent documents. Additionally, we validate the suitability of the topics generated using generative AI technology and review the results with domain experts. We also employ the powerful big data analysis tool, KNIME, to preprocess and visualize the patent data, facilitating a better understanding of the global patent landscape and enabling a comparative analysis with the domestic patent environment. In order to explore quantitative and qualitative comparative advantages at this juncture, we have selected six indicators for conducting a quantitative analysis. Consequently, our approach allows us to explore the distinctive characteristics and investment directions of individual countries in the context of research and development and commercialization, based on a global-scale patent analysis in the field of smart factories. We anticipate that our findings, based on the analysis of global patent data in the field of smart factories, will serve as vital guidance for determining individual countries' directions in research and development investment. Furthermore, we propose a novel utilization of GhatGPT as a tool for validating the suitability of selected topics for policy makers who must choose topics across various scientific and technological domains.

• Journal of Korean Society of Water and Wastewater
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• v.38 no.1
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• pp.1-15
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• 2024

Occurrence of process environment changes, such as influent load variances and process condition changes, can reduce treatment efficiency, increasing effluent water quality. In order to prevent exceeding effluent standards, it is necessary to manage effluent water quality based on process operation data including influent and process condition before exceeding occur. Accordingly, the development of the effluent water quality prediction system and the application of technology to wastewater treatment processes are getting attention. Therefore, in this study, through the multi-channel measuring instruments in the bio-reactor and smart multi-item water quality sensors (location in bio-reactor influent/effluent) were installed in The Seonam water recycling center #2 treatment plant series 3, it was collected water quality data centering around COD, T-N. Using the collected data, the artificial intelligence-based effluent quality prediction model was developed, and relative errors were compared with effluent TMS measurement data. Through relative error comparison, the applicability of the artificial intelligence-based effluent water quality prediction model in wastewater treatment process was reviewed.

• The Journal of Korea Robotics Society
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• v.17 no.3
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• pp.264-272
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• 2022

Human-robot cooperative tasks are increasingly required in our daily life with the development of robotics and artificial intelligence technology. Interactive reinforcement learning strategies suggest that robots learn task by receiving feedback from an experienced human trainer during a training process. However, most of the previous studies on Interactive reinforcement learning have required an extra feedback input device such as a mouse or keyboard in addition to robot itself, and the scenario where a robot can interactively learn a task with human have been also limited to virtual environment. To solve these limitations, this paper studies training strategies of robot that learn table balancing tasks interactively using deep reinforcement learning with human's facial expression feedback. In the proposed system, the robot learns a cooperative table balancing task using Deep Q-Network (DQN), which is a deep reinforcement learning technique, with human facial emotion expression feedback. As a result of the experiment, the proposed system achieved a high optimal policy convergence rate of up to 83.3% in training and successful assumption rate of up to 91.6% in testing, showing improved performance compared to the model without human facial expression feedback.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.14 no.2
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• pp.149-160
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• 2021

In this study, artificial intelligence-based algorithms were proposed, which included a fuzzy search for matching suspects between current and historical crimes in order to obtain related cases in criminal history, as well as conditional generative adversarial networks for crime prediction system (CPS) using Timor-Leste as a case study. By comparing the data from the criminal records, the built algorithms transform witness descriptions in the form of sketches into realistic face images. The proposed algorithms and CPS's findings confirmed that they are useful for rapidly reducing both the time and successful duties of police officers in dealing with crimes. Since it is difficult to maintain social safety nets with inadequate human resources and budgets, the proposed implemented system would significantly assist in improving the criminal investigation process in Timor-Leste.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.10a
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• pp.277-280
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• 2021

Recently as various contents are mass produced based on high accessibility, the media contents market is more active. Users want to find content that suits their taste, and each platform is competing for personalized recommendations for content. For an efficient recommendation system, high-quality metadata is required. Existing platforms take a method in which the user directly inputs the metadata of an image. This will waste time and money processing large amounts of data. In this paper, for media hyperpersonalization recommendation, keyframes are extracted based on the YCrCb color model of the video based on movie trailers, movie genres are distinguished through supervised learning of artificial intelligence and In the future, we would like to propose a utilization plan for generating metadata.

• Journal of Korea Society of Digital Industry and Information Management
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• v.19 no.2
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• pp.135-145
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• 2023

ChatGPT is an artificial intelligence-based conversation agent developed by OpenAI using natural language processing technology. In this study, an empirical study was conducted on incumbent teachers on the intention to use the newly emerged Chat GPT. First, we studied how accuracy, entertainment, system accessibility, perceived usefulness, and perceived ease of use affect ChatGPT's acceptance intention. In addition, we analyzed whether perceived usefulness and perceived ease of use differ in the intention to accept depending on the digital technology of teachers. As a result of the study, the suitability of the structural equation model was generally good. Accuracy and entertainment were found to have a significant effect on perceived usefulness, and system accessibility was found to have a significant effect on perceived ease of use. In the analysis of teachers' digital technology control effects, it was found that perceived usefulness and perceived ease of use had a control effect between acceptance intentions. It was found that the group with high digital skills of teachers was strongly intended to accept the service regardless of perceived usefulness and ease of use. In the group with low digital skills of teachers, it is thought that ChatGPT's service shows the acceptance intention only when the perceived usefulness and ease of use are high. Therefore, in the group with low digital technology, it is necessary to seek teaching activities such as the development of instructional models using ChatGPT.