• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.529-531
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• 2003

최근 이동성을 가진 노드들에 의해 자율적으로 구성되는 무선 애드 혹 네트워크(Ad­hoc Network)에 대한 연구가 진행되고 있다. 무선 애드 혹 네트워크 환경을 위한 라우팅 프로토콜은 크게 테이블 기반 라우팅 프로토콜. 요구 기반 라우팅 프로토콜. 그리고 혼합형 라우팅 프로토콜로 구분된다. 특히 무선 애드 혹 네트워크의 요구 기반 라우팅 프로토콜 상에서 한 노드에 여러 데이터가 한꺼번에 집중될 경우 데이터 집중화 현상으로 데이터의 손실이 발생될 수 있다. 이를 해결하기 위해 본 논문에서는 대체 경로를 이용하여 데이터의 손실을 줄이는 라우팅 기법을 제시한다. 제안 기법은 향후 데이터 트래픽이 많이 발생하는 네트워크에 응용될 수 있다.

• The Journal of the Korea institute of electronic communication sciences
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• v.14 no.3
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• pp.483-488
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• 2019

The propagation prediction model of the earth-space communication link used as an international standard was used to calculate and analyze the total losses on the communication path. The standard definition and scope of ITU-R Rec. were analyzed for each parameter(rain, scintillation, atmospheric gas, clouds) used to calculate the total loss. The total losses were calculated using the standard model for each parameter and the statistical data provided by ITU-R, and the results were analyzed using the validation examples data. The rain losses were calculated using long-term local rainfall attenuation statistics data measured in the region, and compared with the calculation results using a rainfall map in the ITU-R Recommendation. The data of Cheollian satellites for the L-Band and Ka-Band were used to calculate the rainfall attenuation. In the range of 0.01% to 0.1%, it was found to have a greater attenuation slope when using local data than attenuation by the model of ITU-R.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.3
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• pp.34-41
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• 2009

This paper investigates the issue of efficient reading for sensor data of semi-passive sensor tag. The Cold Chain management system requires complete sensor data without data loss and the short processing time of reading sensor tag data. However, reading the sensed data could be interfered by RF environment such as a jamming, obstacle and so on. This study found that it could lead to loss of the sensed data and takes much time to read it when data loss is occurred. To solve this problem, we propose the transaction processing mechanism that guarantees efficient reading of the sensed data. To do this, we present the technique of dynamic packet size and technique of data recovery to execute read transaction. These techniques improve the reliability of reading operation as well as speed up of read process for the large capacity data. This paper contributes to the improvement of efficient reading of sensed data without any loss of data and large time required.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.24 no.1
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• pp.49-54
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• 2024

Data imbalance is a common issue encountered in classification problems, stemming from a significant disparity in the number of samples between classes within the dataset. Such data imbalance typically leads to problems in classification models, including overfitting, underfitting, and misinterpretation of performance metrics. Methods to address this issue include resampling, augmentation, regularization techniques, and adjustment of loss functions. In this paper, we focus on loss function adjustment, particularly comparing the performance of various configurations of loss functions (Cross Entropy, Balanced Cross Entropy, two settings of Focal Loss: 𝛼 = 1 and 𝛼 = Balanced, Asymmetric Loss) on Multi-Class black-box video data with imbalance issues. The comparison is conducted using the I3D, and R3D_18 models.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.72-74
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• 2021

The deep learning process currently utilized in various fields consists of data preparation, data preprocessing, model generation, model learning, and model evaluation. In the process of model learning, the loss function compares the value of the model with the actual value and outputs the difference. In this paper, we analyze various loss functions used in the deep learning model for biomarker extraction, which measure the degree of loss of neural network output values, and try to find the best loss function through experiments.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.34 no.3
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• pp.379-392
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• 2024

With the rapid increase in data, saving storage space and improving the efficiency of data transmission have become critical issues, making the research on the efficiency of data compression technologies increasingly important. Lossless algorithms can precisely restore original data but have limited compression ratios, whereas lossy algorithms provide higher compression rates at the expense of some data loss. There has been active research in data compression using deep learning-based algorithms, especially the autoencoder model. This study proposes a new side-channel analysis data compressor utilizing autoencoders. This compressor achieves higher compression rates than Deflate while maintaining the characteristics of side-channel data. The encoder, using locally connected layers, effectively preserves the temporal characteristics of side-channel data, and the decoder maintains fast decompression times with a multi-layer perceptron. Through correlation power analysis, the proposed compressor has been proven to compress data without losing the characteristics of side-channel data.

• The Journal of Korean Institute of Next Generation Computing
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• v.13 no.2
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• pp.18-25
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• 2017

In computer science, an encoding is a standardization of converting information to one format for audio, video or text. Therefore, the encoding information of the data should be known to open and read it and there are algorithms detecting encoder of the data. However, some informations of data could be disappeared by packet loss when transmitted on network, especially, if the data is snatched by packet sniffing or eavesdropping from wireless communications. In this paper, we improve the performance of encoding detection algorithm of 'uchardet' program for multi-byte encoded data with errors based on bit-shift algorithm. To simulate the performance, we generated Korean and Japanese text data with errors that is removed some random bits at random positions. Then the detection algorithm are tested using the data and 'uchardet-bitshift' showed better performance than 'uchardet'. When Korean texts are used, 'uchardet' could detect perfectly with ≤0.005% errors but it showed 0% detection rate with ≥1% errors while 'uchardet-bitshift' detected perfectly with ≤0.05% errors and it showed correct detection cases with ≥1% errors. Japanese texts with errors tend to report falsely as Chinese encoding because Japanese texts include lots of Chinese characters. As a results, we improved encoding detection algorithms by applying bit shift operation.

• Proceedings of the Korean Information Science Society Conference
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• 2012.06a
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• pp.311-312
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• 2012

도시 컴퓨팅에서의 파일 시스템은 하나의 메타 데이터 서버와 여러 개의 데이터 저장 서버로 구성되어 있다. 이 데이터 저장 서버의 자료구조를 사용자의 두 가지 질의에 맞게 구성함으로써 미리읽기의 성능을 향상시킨다. 또한 데이터의 손실을 방지하기 위해 복사본을 만들 때, 두 가지의 형태로 바꿔 저장함으로써 데이터의 손실을 막고 여러 질의에 대응하여 좋은 성능을 낼 수 있다.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• 2010.07a
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• pp.291-293
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• 2010

이 논문은 공간 영역에서 하나의 키 파라미터로 영상에 데이터를 삽입하고 추출해 내는 무손실 데이터 삽입 알고리즘에 기반하여, 키 파라미터의 유도 및 데이터 삽입 방법을 개선한 알고리즘을 제안한다. 제안한 알고리즘은 기존의 방법에 비해 삽입 가능한 데이터 용량의 효율이 크게 증가하였다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.10c
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• pp.268-270
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• 2003

전송 기존의 유선 네트？과 새로이 신설되고 있는 무선 네트？을 통합하려는 노력은 보다 폭넓은 사용 가치를 이끌어내는 주요 역할을 하고 있다. 이러한 목적을 위해서 유선의 안정되고 빠른 속도의 데이터 통신에 간섭과 데이터 손실로 인한 비교적 불안정하고 느린 무선 데이터 통신의 효율적 통합이 선결적으로 요구되어진다. 본 논문에서는 데이터 버퍼에 유지되는 데이터 패킷을 보다 빨리 전송하여 유무선 통신의 속도 차이에서 오는 손실을 최대한으로 방지함으로써 그렇지 않았을 경우 발생하는 트래픽 성능의 저하를 막고자 하는 방법을 제안하고자 한다.