• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.173-178
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• 2014

In this study, we introduce ASM-based face recognition classifier and its design methodology with the aid of 2-dimensional 2-directional hybird preprocessing algorithm. Since the image of face recognition is easily affected by external environments, ASM(active shape model) as image preprocessing algorithm is used to resolve such problem. In particular, ASM is used widely for the purpose of feature extraction for human face. After extracting face image area by using ASM, the dimensionality of the extracted face image data is reduced by using $(2D)^2$hybrid preprocessing algorithm based on LDA and PCA. Face image data through preprocessing algorithm is used as input data for the design of the proposed polynomials based radial basis function neural network. Unlike as the case in existing neural networks, the proposed pattern classifier has the characteristics of a robust neural network and it is also superior from the view point of predictive ability as well as ability to resolve the problem of multi-dimensionality. The essential design parameters (the number of row eigenvectors, column eigenvectors, and clusters, and fuzzification coefficient) of the classifier are optimized by means of ABC(artificial bee colony) algorithm. The performance of the proposed classifier is quantified through yale and AT&T dataset widely used in the face recognition.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.594-596
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• 2022

This paper relates to a system for pre-processing high-definition images acquired through a camera mounted on an unmanned aerial vehicle(UAV) and transmitting them to a server through a mobile communication network. In the case of the existing UAV system for image acquisition service, the acquired image was stored in the external storage device of the camera mounted on the UAV, and the image was checked by directly moving the storage device after the flight was completed. In the case of this method, there is a limitation in that it is impossible to check whether image acquisition or pre-processing is properly performed before directly checking image data through an external storage device. In addition, since the data is stored only in an external storage device, there is a disadvantage that data sharing is cumbersome. In this paper, to solve the above problems, we propose a system that can remotely check images in real time. Furthermore, we propose a system and method capable of performing pre-processing such as geo-tagging and transmission through a mobile communication network in addition to image acquisition through shooting in an UAV.

• Water for future
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• v.54 no.11
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• pp.69-75
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• 2021

• Transactions of the Korean hydrogen and new energy society
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• v.13 no.1
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• pp.52-64
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• 2002

유기성 폐기물을 이용하여 생물학적 수소생산 통합화 시스템 연구를 수행하였다. 통합화 시스템은 유기성폐기물의 전처리, 2단계 혐기발효 및 광합성 배양으로 구성된 생물학적 수소생산 공정, 초임계수 가스화 공정, 생산된 가스의 저장, 분리 및 연료전지를 이용한 전력 생산으로 구성되었다. 실험에 사용된 유기성 폐자원은 식품공장 폐수, 과일폐기물, 하수슬러지이며, 전처리는 폐기물에 따라 열처리 및 물리적 처리를 하였으며, 전처리된 시료는 생물학적 수소생산 공정에 직접 적용되었다. Clostridium butyricum 및 메탄 생성조에서 발생하는 하수슬러지중의 미생물 복합체는 수소생산 혐기 발효공정에 사용되었으며, 광합성 수소생산 미생물인 홍색 비유황 세균은 광합성 배양에 사용되었다. 생물학적 공정에서 발생하는 미생물 슬러지는 초임계수 가스화 공정으로 수소를 발생하였으며, 슬러지 중의 COD를 저하시켰다. 생물학적 공정 및 초임계수 가스화 공정에서 발생하는 수소는 가스탱크에 가입상태로 저장한 후, 95%순도로 분리하였으며, 정제된 수소는 연료전지에 연결하여 전력 생산을 하였다.

• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.2
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• pp.27-34
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• 2013

We propose a simple power allocation scheme for an amplify-and-forward multiple relay system with multiple-input multiple-output antennas. Unlike the existing relay precoding matrix with full elements, proposed precoder is a diagonal matrix whose diagonal element is the relay gain for each stream. Furthermore, a weight vector is applied to streams, such that the mutual information of the system approaches that of the exhaustive search scheme, regardless of the number of antennas. Numerical results show that proposed scheme outperforms the conventional schemes with respect to mutual information.

• Journal of the Korea Society of Computer and Information
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• v.25 no.12
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• pp.165-172
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• 2020

Recently, due to exponential growth of access information on the web, the importance of predicting a user's next web page use has been increasing. One of the methods that can be used for predicting user's next web page is deep learning. To predict next web page, web logs are analyzed by data preprocessing and then a user's next web page is predicted on the output of the analyzed web logs using a deep learning algorithm. In this paper, we propose a framework for web page prediction that includes methods for web log preprocessing followed by deep learning techniques for web prediction. To increase the speed of preprocessing of large web log, a Hadoop based MapReduce programming model is used. In addition, we present a web prediction system that uses an efficient deep learning technique on the output of web log preprocessing for training and prediction. Through experiment, we show the performance improvement of our proposed method over traditional methods. We also show the accuracy of our prediction.

• Proceedings of the Korea Information Processing Society Conference
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• 2023.05a
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• pp.81-83
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• 2023

태양 에너지 수집형 IoT 기기는 주기적으로 재충전되는 태양 에너지의 특성상, 에너지 소모를 최소화하기보다는 수집된 에너지를 최대한 유용하게 사용하는 것이 중요하다. 한편, 데이터 기밀성과 프라이버시, 응답속도, 비용 등의 이유로 클라우드가 아닌 데이터 소스 근처에서 머신러닝을 수행하는 엣지 AI에 대한 연구도 활발한데, 그 중 하나는 여러 IoT 장치들이 수집한 오디오 데이터를 활용하여, 다양한 AI 응용들을 IoT 엣지 컴퓨팅 환경에서 제공하는 것이다. 그러나, 이와 관련된 많은 연구에서, IoT 기기들은 에너지의 제약으로 인하여, 엣지 서버(IoT 서버)로의 센싱 데이터 전송만을 수행하고, 데이터 전처리를 포함한 모든 AI 과정은 엣지 서버에서 수행한다. 이 경우, 엣지 서버의 과부하 문제 뿐 아니라, 학습 및 추론에 불필요한 데이터까지도 서버에 그대로 전송되므로 네트워크 과부하 문제도 야기한다. 또한, 이를 해결하고자, 데이터 전처리 과정을 각 IoT 기기에 모두 맡긴다면, 기기의 에너지 부족으로 정전시간이 증가하는 또 다른 문제가 발생한다. 본 논문에서는 각 IoT 기기의 에너지 상태에 따라 데이터 전처리 여부를 결정함으로써, 기기들의 정전시간 증가 문제를 완화시키면서 서버 집중형 엣지 AI 환경의 문제들(엣지 서버 및 네트워크 과부하)을 완화시키고자 한다. 제안기법에서 IoT 장치는 기기가 기본적으로 동작하는 데 필요한 에너지 외의 여분의 에너지 양을 예측하고, 이 여분의 에너지가 있는 경우에만 이를 사용하여 기기에서 전처리 과정, 즉 수집 대상 소리 판별과 잡음 제거 과정을 거친 후 서버에 전송함으로써, IoT기기의 정전시간에 영향을 주지 않으면서, 에너지 적응적으로 데이터 전처리 위치(IoT기기 또는 엣지 서버)를 결정하여 수행한다.

• Aerospace Engineering and Technology
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• v.4 no.1
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• pp.229-238
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• 2005

The main objective of this study is to develop RPC geometric correction module for the pre-processing systems of the satellite image. For this purpose, the Terrain-Independent Ⅰ, Terrain-Independent Ⅱ and Terrain-Dependent Ⅲ have been applied in tests with KOMPSAT-1 EOC and SPOT PAN images.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2006.05a
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• pp.69-70
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• 2006

Waste vinyl tretreatment system has been developed by the joint project between KIMM and Woosung Co. General process for removal of impurities from waste vinyl is consisted of feeding, separating, cutting, washing, drying and recovering impurities. However, there are problems such as wastewater when washing of waste vinyl. In order to solve these problems we have developed new dry type cleaning system.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.213-220
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• 2011

In this paper, the channel preprocessor with an area-efficient architecture is proposed for the MIMO symbol detector which can support four transmit and receive antennas. The proposed channel preprocessor can shrink the channel dimension to reduce the hardware complexity of the MIMO symbol detector. Also, the proposed channel preprocessor is implemented with very low complexity by using QR decomposition (QRD) and log-number system (LNS). By applying QRD and LNS to the nulling matrix calculation block, the numbers of matrix-multiplications and matrix-divisions are decreased and thus the complexity of the proposed channel preprocessor is significantly reduced. The proposed channel preprocessor was designed in a hardware description language (HDL) and synthesized to gate-level circuits using 0.13um CMOS standard cell library. With the proposed channel preprocessor, the number of logic gates for channel preprocessor is reduced by 20.2% compared with the conventional architecture.