• The Journal of the Korea Contents Association
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• v.9 no.4
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• pp.131-141
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• 2009

An increasing variety of malware, such as worms, spyware and adware, threatens both personal and business computing. Remotely controlled bot networks of compromised systems are growing quickly. This paper proposes an intrusion detection system based outflow traffic analysis. Many research efforts and commercial products have focused on preventing intrusion by filtering known exploits or unknown ones exploiting known vulnerabilities. Complementary to these solutions, the proposed IDS can detect intrusion of unknown new mal ware before their signatures are widely distributed. The proposed IDS is consists of a outflow detector, user monitor, process monitor and network monitor. To infer user intent, the proposed IDS correlates outbound connections with user-driven input at the process level under the assumption that user intent is implied by user-driven input. As a complement to existing prevention system, proposed IDS decreases the danger of information leak and protects computers and networks from more severe damage.

• Journal of the Korea Computer Graphics Society
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• v.27 no.4
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• pp.1-9
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• 2021

Segmenting the compartments of neurons, such as axons, dendrites, and cell bodies, is helpful in the analysis of neurological phenomena. Recently, there have been several studies to segment the compartments through deep learning. However, this approach has the potential to include errors in the results due to noise in data and differences between training data and actual data. Therefore, in order to use these for actual analysis, it is essential to proofread the results. The proofreading process requires a lot of effort and time because an expert must perform it manually. We propose an interactive neuron structure proofreading method that can more easily correct errors in the segmentation results of a deep learning. This method proofread the neuron structure based on the characteristics of the neuron with structural consistency, so that a high-accuracy proofreading result can be obtained with less interaction.

• The Journal of the Acoustical Society of Korea
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• v.25 no.5
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• pp.213-221
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• 2006

Phone segmentation of speech waveform is especially important for concatenative text to speech synthesis which uses segmented corpora for the construction of synthetic units. because the quality of synthesized speech depends critically on the accuracy of the segmentation. In the beginning. the phone segmentation was manually performed. but it brings the huge effort and the large time delay. HMM-based approaches adopted from automatic speech recognition are most widely used for automatic segmentation in speech synthesis, providing a consistent and accurate phone labeling scheme. Even the HMM-based approach has been successful, it may locate a phone boundary at a different position than expected. In this paper. we categorized adjacent phoneme pairs and analyzed the mismatches between hand-labeled transcriptions and HMM-based labels. Then we described the dominant error patterns that must be improved for the speech synthesis. For the experiment. hand labeled standard Korean speech DB from ETRI was used as a reference DB. Time difference larger than 20ms between hand-labeled phoneme boundary and auto-aligned boundary is treated as an automatic segmentation error. Our experimental results from female speaker revealed that plosive-vowel, affricate-vowel and vowel-liquid pairs showed high accuracies, 99%, 99.5% and 99% respectively. But stop-nasal, stop-liquid and nasal-liquid pairs showed very low accuracies, 45%, 50% and 55%. And these from male speaker revealed similar tendency.

• Journal of the Korea Society of Computer and Information
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• v.12 no.6
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• pp.297-306
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• 2007

Bar-code based airway logistics systems have many problems like freight loss and data management error due to semiskilled air-cargo process and individual information system. To solve these problems, this paper analyzed how to process an air-cargo practically and designed and implemented the RFID-based airway logistics system. This system has an information service system which manages data from RFID systems in realtime and provides a communication interface for data sharing. And, this system precesses data queries from capture applications and access applications to provide various services to users such as the freight track and trace service. Also, this system includes a H/H reader agent to integrate existing bar-cord systems. It allows us to realize automation and information-oriented air-cargo process and achieve improvement of air-cargo services with reduction of freight loss and management error.

• Journal of the Korea Society of Computer and Information
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• v.11 no.2 s.40
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• pp.83-92
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• 2006

This paper describes an image disparity estimation method using region-based stereo matching. Region-based disparity estimation yields a disparity map as the unit of segmented region. However it estimates disparity imprecisely because it not only has matching errors but also applies an identical way to disparity estimation, which does not consider each type of matched regions. To solve this problem, we proposes a disparity estimation method which considers the type of matched regions. That is, the proposed method classifies whole matched regions into a similar-matched region, a dissimilar-matched region, a false-matched region and a miss-matched region. We then performs proper disparity estimation for each type of matched regions. This method minimizes the error in estimating disparity which is caused by inaccurate matching and also improves the accuracy of disparity of the well-matched regions. The experimental results show the improved accuracy of the proposed method.

• Journal of Convergence for Information Technology
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• v.12 no.1
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• pp.31-38
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• 2022

This paper applies an expert independent unsupervised neural network learning-based multivariate time series data analysis model, MSCRED(Multi-Scale Convolutional Recurrent Encoder-Decoder), and to overcome the limitation, because the MCRED is based on Auto-encoder model, that train data must not to be contaminated, by using learning data sampling technique, called Subset Sampling Validation. By using the vibration data of power plant equipment that has been labeled, the classification performance of MSCRED is evaluated with the Anomaly Score in many cases, 1) the abnormal data is mixed with the training data 2) when the abnormal data is removed from the training data in case 1. Through this, this paper presents an expert-independent anomaly diagnosis framework that is strong against error data, and presents a concise and accurate solution in various fields of multivariate time series data.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.211-219
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• 2019

Accomplishing information system, techniques, methodology have been studied continuously and give much help to auditors who are using them. Additionally audit report which is the conclusion of accomplishing ISA(information system audit), has law of a basis and phase with ITA/EA Law(Electronic Government Law). This paper is for better quality of ISA report. But it has more errors about sentence and Grammatical structures. In this paper, to achieve quality improvement objectives, it is necessary to recognize the importance of an audit report by investigating on objectives, functionality, structures and usability of a report firstly, and a legal basis, the presence of report next. Several types of audit reports were chosen and the reports errors were divided into several categories and analyzed. After grasping reasons of those errors, the methods for fixing those errors and check-lists model was provided. And based on that foundation, the effectiveness validation about real audit reports was performed. The necessity for efforts to improve the quality of audit reports was emphasized and further research subject(AI Automatic tool) of this paper conclusion. We also expect this paper to be useful for the organization to improve on ISA in the future.

• The Journal of Korean Association of Computer Education
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• v.7 no.6
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• pp.1-12
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• 2004

Current computer education is difficult to educate basic concepts and principals of the computer science because the 7th curriculum of computer education is focused on the application of software. According to the ACM K-12 report about the computer science education model, current computer education is taking the wrong way and we should put the highly priority on the education of the fundamentals through programming languages for a better computer education oriented to the computer science. This paper introduces a new object-oriented educational programming language "Dolittle". The design principals of Dolittle are simple syntax of Korean, incremental programming, text based programming, aliasing of function, and object-oriented programming. Being applied to middle school classes, we can confirm that Dolittle is easy to learn, and gives rise to high interest and keeps interest through a course, and also is of great practical use in class for programming novice.

• Journal of Internet of Things and Convergence
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• v.10 no.4
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• pp.101-108
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• 2024

Indoor localization is a critical component for numerous applications, ranging from navigation in large buildings to emergency response. This paper presents an enhanced Pedestrian Dead Reckoning (PDR) scheme using smartphone sensors, integrating neural network-aided motion recognition, Kalman filter-based error correction, and multi-sensor data fusion. The proposed system leverages data from the accelerometer, magnetometer, gyroscope, and barometer to accurately estimate a user's position and orientation. A neural network processes sensor data to classify motion modes and provide real-time adjustments to stride length and heading calculations. The Kalman filter further refines these estimates, reducing cumulative errors and drift. Experimental results, collected using a smartphone across various floors of University, demonstrate the scheme's ability to accurately track vertical movements and changes in heading direction. Comparative analyses show that the proposed CNN-LSTM model outperforms conventional CNN and Deep CNN models in angle prediction. Additionally, the integration of barometric pressure data enables precise floor level detection, enhancing the system's robustness in multi-story environments. Proposed comprehensive approach significantly improves the accuracy and reliability of indoor localization, making it viable for real-world applications.

• Proceedings of the Korea Society for Industrial Systems Conference
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• 2006.05a
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• pp.53-62
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• 2006

인터넷 및 IT 기술의 획기적인 발전으로 인해 우리가 접하는 정보는 그 양적 측면 뿐만 아니라 질적 측면에서도 비약적인 발전을 가지고 왔다. 또한 인터넷 보급의 활성화로 대부분의 사람들은 많은 종류의 정보 속에서 그리고 다양한 형식으로 구성된 정보 속에서 지내고 있다. 특히 웹의 사용이 일상화 되어감에 따라 컴퓨터를 다루기 힘든 정보소외계층의 웹사이트 정보 접근성에 대한 관심이 증가하고 있으며 그와 관련한 다각적인 연구도 활발히 진행 중이다. 본 연구에서는 선행된 웹 사이트 접근성에 관한 연구와 한국형 자동화 접근성 평가도구의 분석을 통하여 기존의 웹 접근성 평가의 한계를 파악하고 이를 통해 새로운 유형의 웹사이트 접근성 평가모형을 제안하고자 한다. 이를 위한 접근성 평가의 효율성 및 타당성 확보를 위해 먼저 자동화 평가도구인 Kado-Wah 를 이용하여 기본 평가를 진행하였고, 그 결과를 바탕으로 웹 페이지 소스분석 및 음성합성 S/W 를 통한 메뉴얼 평가를 실시하였다. 평가결과를 바탕으로 접근성 오류정도를 산출하여 한국과 미국의 교육기관 웹사이트의 접근성을 비교 분석하고 그 결과를 통해 향후 웹 기반 정보접근에 대한 효율성을 최대화 할 수 있도록 웹 구현에 대한 지침을 제안하고자 한다.