• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.46-52
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• 2008

In this paper, we present the Mont-Saint-Michel virtual reality system designed to create the virtual heritage environment, which is enriched with personalized tour guide service. The tour guide system allows users to travel in the virtual heritage site and get more information about the sites or items of user's interests. It also allows users to make their own tour guidebook with the pictures they have taken during the virtual tour and more detail descriptions from the tour guide database. It then generates the web-based tour guidebook for users to utilize it for the actual site visit or share it with others over the Internet. The components of this system are designed with the consideration of reusability to be used for other interactive tour guide systems. This paper describes the motivation the development and a preliminary user study of Mont-Saint-Michel virtual reality personalized tour guide system.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.108-114
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• 2008

Since flash memory cannot be overwritten, new data are updated in new area. If data are frequently updated, garbage collection which is achieved by erasing blocks, should be performed to reclaim new area. Hence, because the count of erase operations is limited due to characteristics of flash memory, every block should be evenly written and erased. However, if data with access locality are processed by cost benefit algorithm with separation of hot block ad cold block though the performance of processing is hight wear-leveling is not even. In this paper, we propose CB-MB (Cost Benefit between Multi Bank) algorithm in which hot data are allocated in one bank and cold data in another bank, and in which role of hot bank and cold bank is exchanged every period. CB-MB shows that its performance is 30% better than cost benefit algorithm with separation of cold block and hot block its wear-leveling is about a third of that in standard deviation.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.4
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• pp.737-744
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• 2007

It need estimation model who is efficient and estimate correctly organization's information security level to achieve effectively organization's information security target. Also, estimate class information security level for this and need reformable estimation indicator or standard and estimation methodology of information security systems that application is possible should be studied in our country. Therefore many research centers including ISO are preparing the measuring and evaluating method for network duality. This study will represent an evaluating model for network security based on checklist. In addition, we propose ah measuring and evaluating method for network performance. The purpose of two studies is to present the evaluating procedure and method for measuring security of network on set workwill be identified and a measuring method and procedure will be proposed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.6
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• pp.1101-1106
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• 2008

People who have hearing difficulties suffer from satisfactory mutual interaction with normal people because there are little chances of communicating each other. It is caused by rare communication of people who have hearing difficulties with normal people because majority of normal people can not understand sing language that is represented by gestures and is used by people who have hearing difficulties as a principal way of communication. In this paper, we propose a recognition method of finger language using FCM algorithm in order to be possible of communication of people who have hearing difficulties with normal people. In the proposed method, skin regions are extracted from images acquired by a camera using YCbCr and HSI color spaces and then locations of two hands are traced by applying 4-directional edge tracking algorithm on the extracted skin lesions. Final hand regions are extracted from the traced hand regions by noise removal using morphological information. The extracted final hand regions are classified and recognized by FCM algorithm. In the experiment using images of finger language acquired by a camera, we verified that the proposed method have the effect of extracting two hand regions and recognizing finger language.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.11 no.10
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• pp.1835-1844
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• 2007

Recently there have been some positive evidences on the effects of learning in a virtual environment. However, most of these educational VR systems were not deeply considered in the design of drawing a learner's attention on lesson contents, which would help enhance retained memory. Hence, a study was conducted to measure 17 subjects' attention states using EEC, ECG, GSR, and eye-tracking and their behaviors while they were given guided search task or exploration task in a virtual environment consisting of five major events. It also analyzed the subject's remembered items after their VR experiences using a surrey. This paper Int describes an overview of the ocean virtual environment used in this study, and it then explains the experimental design, apparatus, and method. It will also discuss the results by a detail analysis (in a whole VR session as well as event-related 10-second 33 sub-sessions) with the subjects' attention states and their retained memory after the learning.

• Journal of Convergence for Information Technology
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• v.9 no.11
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• pp.8-14
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• 2019

Due to the development of computer technology, IoT technology is being used in various fields of industry, economy, medical service and education. However, multimedia information processed through IoT equipment is still one of the major issues in the application sector. In this paper, a big data protection model for users of IoT based IoT is proposed to ensure integrity of users' multimedia information processed through IoT equipment. The proposed model aims to prevent users' illegal exploitation of big data information collected through IoT equipment without users' consent. The proposed model uses signatures and authentication information for IoT users in a hybrid cryptographic method. The proposed model feature ensuring integrity and confidentiality of users' big data collected through IoT equipment. In addition, the user's big data is not abused without the user's consent because the user's signature information is encrypted using a steganography-based cryptography-based encryption technique.

• Proceedings of the Korea Water Resources Association Conference
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• 2016.05a
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• pp.72-72
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• 2016

최근 발생하고 있는 기후변화로 인하여 하천 및 저수지의 수질문제가 커지고 있다. 특히 여름철 부영양화로 인해 발생하는 녹조현상은 사회적인 문제로 과학적인 수질사고에 대한 예측과 관리가 필요한 실정이다. 수질예보는 정기적으로 하천 및 저수지의 수질을 예측하여 사용자에게 제공하는 분석기법으로 수질현황을 파악하고 수질을 관리하고 의사결정을 하는데 도움을 줄 수 있다. 수질예보에 사용되는 모형은 유역모형, 하천모형, 저수지모형이 있으며, 이중 하천 및 저수지에 주로 적용되고 있는 3차원 수리수질모형의 경우 격자의 개수가 많아 모의시간이 길어지게 되고 이로 인해 일일 수질 예보가 어렵게 된다. 3차원 수리수질모형의 모의속도를 개선하는 방법에는 하드웨어의 성능을 높이는 방법과 병렬화를 이용한 소프트웨어적인 방법이 있다. 이중 하드웨어의 성능을 높이는 방법은 컴퓨터의 사양을 높이는 방법으로 높은 비용이 소요된다. 하지만 병렬화 방법은 컴퓨팅 기술의 발전으로 멀티코어가 대중화가 된 최근에 코드의 적용만으로 모의속도를 향상시킬 수 있다. 본 연구에서 사용된 모형은 서호주대학에서 개발한 3차원 수리 수질모형인 ELCOM-CAEDYM 모형으로 적용된 병렬화 기법은 OpenMP(Open Multi-Processing)방법이다. 기존 직렬 컴퓨팅 방식으로 구성되어 한번에 한 개의 명령어 밖에 처리할 수 없었던 작업방법을 동시에 여러 개의 처리요소를 이용하여 명령을 실행할 수 있게 하는 방식이다. 하지만 CPU의 개수는 제한되어 있으며, Amdahl's law에 따르면 OpenMP방식의 병렬화시 속도개선효과는 95% 병렬화 프로그램에서 최대 CPU 개수의 제한이 없다면 20배 까지 속도향상이 가능하다고 하였다. 본 연구에서는 3차원 수리 수질예측 모형인 ELCOM-CAEDYM에 적용된 병렬화 기법을 적용하는데 있어 최적 CPU사용 개수를 파악 하고자 하였으며, 이를 통해 수질예보시스템을 운영하는데 가장 효율적인 방법을 찾아 적용하고자 하고자 한다.

• KIPS Transactions on Software and Data Engineering
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• v.8 no.10
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• pp.411-420
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• 2019

Camera model identification has been a subject of steady study in the field of digital forensics. Among the increasingly sophisticated crimes, crimes such as illegal filming are taking up a high number of crimes because they are hard to detect as cameras become smaller. Therefore, technology that can specify which camera a particular image was taken on could be used as evidence to prove a criminal's suspicion when a criminal denies his or her criminal behavior. This paper proposes a deep learning model to identify the camera model used to acquire the image. The proposed model consists of four convolution layers and two fully connection layers, and a high pass filter is used as a filter for data pre-processing. To verify the performance of the proposed model, Dresden Image Database was used and the dataset was generated by applying the sequential partition method. To show the performance of the proposed model, it is compared with existing studies using 3 layers model or model with GLCM. The proposed model achieves 98% accuracy which is similar to that of the latest technology.

• KIPS Transactions on Computer and Communication Systems
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• v.10 no.12
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• pp.311-318
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• 2021

With the rapid development of the Internet of Things(IoT) technology recently, multi-access edge computing(MEC) is emerged as a next-generation technology for real-time and high-performance services. High mobility of users between MECs with limited service areas is considered one of the issues in the MEC environment. In this paper, we consider a vehicle edge computing(VEC) environment which has a high mobility, and propose a task migration algorithm to decide whether or not to migrate and where to migrate using DQN, as a reinforcement learning method. The objective of the proposed algorithm is to improve the system throughput while satisfying QoS(Quality of Service) requirements by minimizing the difference between queueing delays in vehicle edge computing servers(VECSs). The results show that compared to other algorithms, the proposed algorithm achieves approximately 14-49% better QoS satisfaction and approximately 14-38% lower service blocking rate.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.5
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• pp.203-208
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• 2021

At the manufacturing site, workers have been operating by inputting materials into the manufacturing process and leaving input records according to the work instructions, but product LOT tracking has been not possible due to many omissions. Recently, it is being carried out as a system to automatically input materials using RFID-Tag. In particular, the initial automatic recognition rate was good at 97 percent by automatically generating input information through RACK (TAG) ID and RACK input time analysis, but the automatic recognition rate continues to decrease due to multi-material RACK, TAG loss, and new product input issues. It is expected that it will contribute to increasing speed and yield (normal product ratio) in the overall production process by improving automatic recognition rate and real-time monitoring through the establishment of artificial intelligent smart factory datasets.