• KSII Transactions on Internet and Information Systems (TIIS)
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• 제14권6호
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• pp.2310-2332
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• 2020

In recent years, deep learning techniques have achieved tremendous successes in natural language processing, speech recognition and image processing. Collaborative filtering(CF) recommendation is one of widely used methods and has significant effects in implementing the new recommendation function, but it also has limitations in dealing with the problem of poor scalability, cold start and data sparsity, etc. Combining the traditional recommendation algorithm with the deep learning model has brought great opportunity for the construction of a new recommender system. In this paper, we propose a novel collaborative recommendation model based on auxiliary stacked denoising autoencoder(ASDAE), the model learns effective the preferences of users from auxiliary information. Firstly, we integrate auxiliary information with rating information. Then, we design a stacked denoising autoencoder based collaborative recommendation model to learn the preferences of users from auxiliary information and rating information. Finally, we conduct comprehensive experiments on three real datasets to compare our proposed model with state-of-the-art methods. Experimental results demonstrate that our proposed model is superior to other recommendation methods.

• Journal of the Korean Data and Information Science Society
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• 제17권4호
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• pp.1309-1317
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• 2006

The paper considers some Bayes estimators of the finite population mean with auxiliary information under priors which are scale mixtures of normal, and thus have tail heavier than that of the normal. The proposed estimators are quite robust in general. Numerical methods of finding Bayes estimators under these heavy tailed priors are given, and are illustrated with an actual example.

• 전력전자학회논문지
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• 제17권4호
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• pp.298-305
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• 2012

This paper proposes a soft switching boost converter with an auxiliary resonant circuit. The auxiliary resonant circuit is added to a general boost converter and that is composed of one switch, one diode, one inductor and two capacitors. The resonant network helps the main switch to operate with a zero voltage switching(ZVS) and auxiliary switch also operates under the zero voltage and zero current conditions. The soft switching range is extended by the auxiliary switch and it is possible to control the proposed converter with a pulse width modulation(PWM). The ZVS and ZCS techniques make switching losses decreased and efficiency of the system improved. A theoretical analysis is verified through the simulation and experiment.

• 응용통계연구
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• 제20권2호
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• pp.333-343
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• 2007

고객의 도착간격시간과 서비스시간 중 어느 하나가 지수분포가 아닌 큐를 분석할 때 중요하게 등장하는 함수가 보조재생함수(auxiliar renewal function)이다. 재생함수와 마찬가지로 보조재생함수도 이론적으로는 정의할 수 있으나 함수값을 실제로 계산하기에는 어려움이 많아 근사값을 구하는 연구가 필요하다. 본 논문에서는 보조재생함수의 값을 근사적으로 계산하는 두 가지 방법을 보여주고 부분적으로 알려져 있는 보조재생 함수의 참값과의 비교를 통하여 두 방법을 서로 비교한다.

• Communications for Statistical Applications and Methods
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• 제10권3호
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• pp.665-678
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• 2003

In this paper we suggest the new calibration estimator, which is called to the recalibration estimator, and its variance estimator using two-phase sampling technique according to the auxiliary information having strong correlation with the variable of interest under the unit nonresponse. In this unit nonresponse situation, an available information may exists at the level of whole population or the first-phase sample. The proposed recalibration estimator derives from the first and second phase weights respectively.

• 한국정보통신학회논문지
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• 제23권3호
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• pp.237-246
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• 2019

추천 시스템의 등급 예측 정확도를 높이기 위해서는, 사용자 항목 등급 데이터뿐만 아니라 주석, 태그 또는 설명과 같은 항목의 보조 정보도 고려해야만 한다. 기존 접근법에서는 단어 단위에서 bag-of-words 모델을 사용하여 보조 정보를 모델링한다. 그러나 이러한 모델은 보조 정보를 효과적으로 활용할 수 없으므로 보조 정보를 제한적으로 이해하게 된다. 한편, 컨볼루션 신경망(CNN)에서는 보조 정보로부터 특징 벡터를 효과적으로 포착하고 추출할 수 있다. 따라서 본 논문에서는 새로운 추천 모델을 위해 딥 CNN을 행렬 분해에 통합시킨 문자 수준의 딥 컨볼루션 신경망 기반 행렬 분해 (Char-DCNN-MF) 방법을 제안한다. Char-DCNN-MF에서는 보조 정보를 더 심층적으로 이해하고 추천 성능을 더욱 향상시킬 수 있다. 실험은 세 가지 다른 실제 데이터 세트에서 수행되었으며 그 결과는 Char-DCNN-MF가 다른 비교 모델보다 유의적으로 뛰어난 성능을 보여주었다.

• 전기학회논문지P
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• 제56권2호
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• pp.109-114
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• 2007

This paper summarize about the auxiliary electrode measured a ground resistance. The method to measure a ground resistance is the fall-of-potential method to using an auxiliary electrode. And an auxiliary electrode must be set up on the ground. Today it is so difficult to set up the auxiliary electrode on the ground because of many concrete building and many paved roads. So this paper is regarding a trust analysis of the ground resistance measurement by the substitute auxiliary electrode. It substituted a iron structure around the building, a neutral line multiplex ground to earth, a wire net for auxiliary electrode. This information is confirmed bv compared with the measurement value.

• Journal of the Korean Statistical Society
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• 제27권3호
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• pp.331-348
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• 1998

In this paper, we have proposed some robust Bayes estimators using ML-II priors as well as certain empirical Bayes estimators in estimating the finite population mean in the presence of auxiliary information. These estimators are compared with the classical ratio estimator and a subjective Bayes estimator utilizing the auxiliary information in terms of "posterior robustness" and "procedure robustness" Also, we have addressed the issue of choice of sampling design from a robust Bayesian viewpoint.

• 대한방사선기술학회지:방사선기술과학
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• 제46권6호
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• pp.485-491
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• 2023

As an auxiliary tool for fixing the patient's posture when taking an X-ray, sponges with high radiolucencies are laminated in various thicknesses. This study aimed to evaluate the usefulness of an auxiliary tool for hand oblique projection X-ray by manufacturing it with a uniform thickness by 3D printing and comparing it with existing sponge tools. In the auxiliary tool, radiolucency was measured at the stairs where each finger was located, and pixel information values were compared in the digital imaging and communications in medicine(DICOM) image. Contrast to noise ratio(CNR) and signal to noise ratio(SNR) were compared by shooting the hand phantom and the auxiliary tool together. As the thickness of the sponge tool increased, radiolucency decreased by 15.52% and pixel information value increased by 20.61%. The transmittance of the 3D printing tool increased by 0.82%, and the pixel information value differed by 5.66%. CNR and SNR increased by 20.03% and 22.42% in 3D printing compared to existing sponge tools. while taking hand oblique projection, maintaining the thickness of the auxiliary tool uniformly through 3D printing maintains high radiolucency and minimal impact on medical images, and increases CNR and SNR, making it useful as an auxiliary tool for taking hand oblique projection.

• 응용통계연구
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• 제16권1호
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• pp.33-44
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• 2003

조사과정에서 필연적으로 발생하는 무응답을 보정하기 위해 보조정보를 사용해야 한다. 이 때, 이용 가능한 보조정보의 차원이 크면, 계산과정에서 많은 시간이 소요되며 데이터를 다루기가 매우 어렵다. 또한 추정량의 분산이 보조전보의 차원에 의존하기 때문에 과소추정의 문제가 발생한다. 이러한 문제를 해결하기 위해 무응답 보정에서 적절한 보조정보의 선택 방법을 제안하였고, 이에 대한 효율성을 모의실험을 통해 살펴보았다.