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부정당업자제재와 계약금액조정제도에 근거한 공공조달계약의 공법적 특수성
황준화 ( Hwang Joon Hwa ),정영철 ( Jung Young Chul ) 단국대학교 법학연구소 2019 법학논총 Vol.43 No.1
Even under the Supreme Court’s case of identifying the National Contracts Act as a private legal system and public procurement contracts as private contracts based on the principle of contract freedom, the public procurement contract has the nature of a public law in that public procurement contracts are a means for the administration to implement public tasks. Among the provisions that reflect this specificity of a public law in the National Contracts Act the penalties imposed by fraudulent parties and the contract amount adjustment system for price changes are typical and exemplary. In order to establish a fair procurement administrative order, the administrative agency can make an intrusive disposal of fraudulent party sanctions against the counterparty and protect the interests of the weak by using the private law’s principles of changing the circumstances through the contract amount adjustment regulation. These two systems have a strong specificity of a public law in that they have not only standard and procedures stipulated in the National Contracts Act, but the penalties imposed by fraudulent parties are typical administrative acts of a public law and also in that the contract amount adjustment system is a forced rule in the form of a subjunctive nature that arises from the application of the parties to the contract. Therefore, the legal nature of public procurement contracts as public legal contracts should be emphasized further under the public law as they have the legal nature of public performance in that they comply with fairness through invasive sanctions and the contract amount adjustment regulations have reasonable execution of budgets.
황준화(Junhwa Hwang),김보우(Bowoo Kim),전우성(Woosung Jeun),서동준(Dongjun Suh) 한국통신학회 2022 한국통신학회 학술대회논문집 Vol.2022 No.2
빅데이터에서의 데이터 품질은 연구의 활용성과 정확성을 위한 중요한 부분을 차지한다. 데이터의 활용성과 정밀성을 위해 결측값 보간은 필수적이다. 본 논문은 범용적인 빅데이터 분석 및 활용을 위해 기계학습 기반 모델의 AutoEncoder (AE), Convolutional AutoEncoder (CAE), Generative Adversarial Imputation Network (GAIN) 모델을 활용하여 결측 데이터 보간을 진행하였다. 광주 광역시 소재의 18 개 업무용 건물을 대상으로 하여 결측 비율에 따라 결측 데이터 보간 및 성능 평가를 진행하였다. 본 연구를 통해 결측 데이터 보간에 가장 적합한 모델을 확인하였다.