The water supply facilities of Korea have achieved a rapid growth, along with the other social infrastructures consisting a city, due to the phenomenon of urbanization according to economic development. Meanwhile, the level of water supply service demanded by consumer is also steadily getting higher in keeping with economic growth. However, as an adverse effect of rapid growth, the quantity of aged water supply pipes are increasing rapidly, Bursts caused by pipe aging brought about an enormous economic loss of about 6,161 billion won as of 2019. These problems are not only worsening water supply management, also increasing the regional gap in water supply services. The purpose of this study is to classify hazard evaluation indicators and to rank the water distribution network hazard by cluster using the TOPSIS method. In conclusion, in this study, the entropy-based multi-criteria decision-making methods was applied to rank the hazard management of the water distribution network, and the hazard management ranking for each cluster according to the water supply conditions of the county-level municipalities was determined according to the evaluation indicators of water outage, water leakage, and pipe aging. As such, the hazard ranking method proposed in this study can consider various factors that can impede the tap water supply service in the water distribution network from a macroscopic point of view, and it can be reflected in evaluating the degree of hazard management of the water distribution network from a preventive point of view. Also, it can be utilized in the implementation of the maintenance plan and water distribution network management project considering the equity of water supply service and the stability of service supply.

Failure modes and effects analysis (FMEA) is a widely used engineering tool in the fields of the design of a product or a process to improve its quality or performance by prioritizing potential failure modes in terms of three risk factors―severity, occurrence, and detection. In a classical FMEA, the risk priority number is obtained by multiplying the three values in 10 score scales which are evaluated for the three risk factors. However, the drawbacks of the classical FMEA have been mentioned by many previous researchers. As a way to overcome these difficulties, this paper suggests the ELECTRE III that is a representative technique among outranking models. Furthermore, fuzzy linguistic variables are included to deal with ambiguous and imperfect evaluation process. In addition, when the importances for the three risk factors are obtained, the entropy method is applied. The numerical example which was previously studied by Kutlu and Ekmek‡ioğlu(2012), who suggested the fuzzy TOPSIS method along with fuzzy AHP, is also adopted so as to be compared with the results of their research. Finally, after comparing the results of this study with that of Kutlu and Ekmek‡ioğlu(2012), further possible researches are mentioned.

In a companion paper, we have presented so-called Spatio-Spectral Maximum Entropy Method (SSMEM) particularly designed for Fourier-Transform imaging over a wide spectral range. The SSMEM allows simultaneous acquisition of both spectral and spatial information and we consider it most suitable for imaging spectroscopy of solar microwave emission. In this paper, we run the SSMEM for a realistic model of solar microwave radiation and a model array resembling the Owens Valley Solar Array in order to identify and resolve possible issues in the application of the SSMEM to solar microwave imaging spectroscopy. We mainly concern ourselves with issues as to how the frequency dependent noise in the data and frequency-dependent variations of source size and background flux will affect the result of imaging spectroscopy under the SSMEM. We also test the capability of the SSMEM against other conventional techniques, CLEAN and MEM.

Decision analysis has becomes an important technique for decision making in the face of uncertainty. It is characterized by enumerating all the available courses of action, identifying the payoffs for all possible outcomes, and quantifying the subjective probabilities for the all possible random events. When the data are available, decision analysis becomes a powerful tool for determining an optimal course of action. We study the multi-attribute decision making in a compensatory models. In this paper, we use the entropy methods in weights calculating. For the purpose of making optimal decision, the data of five different car models are used. For computing, we used Visual Numerica Version 1.0 software package.

We propose to use the entropy of power spectra defined in the frequency domain for the deconvolution of extended images. Spatial correlations requisite for extended sources may be insured by increasing the role of power entropy because the power is just a representation of spatial correlations in the frequency domain. We have derived a semi-analytical solution which is found to severely reduce computing time compared with other iteration schemes. Even though the solution is very similar to the well-known Wiener filter, the regularizingng term in the new expression is so insensitive to the noise characteristics as to assure a stable solution. Applications have been made to the IRAS 60μm and 100 μm images of the dark cloud B34 and the optical CCD image of a solar active region containing a circular sunspot and a small pore.

최근 항만하역근로자의 인명사고가 지속적으로 발생함에 따라 사고관리에 대한 필요성이 증대되고 있다. 이 연구는 GRA법과 Entropy법을 이용하여 우리나라 항만에 대해 하역근로자의 재해 위험성을 평가하고 위험성이 높은 항만을 결정하기 위한 것이다. 이러한 목적을 달성하기 위해 먼저 우리나라 항만을 11개의 대상항만으로 구분하고, 브레인스토밍법으로 항만하역근로자 재해 위험성 평가를 위한 평가항목을 추출한다. 두번째는 GRA법을 이용하여 대상항만의 회색관계계수를 산정한다. 마지막으로 엔트로피법을 이용하여 산출한 평가항목의 중요도와 GRA법의 회색관계계수를 결합하여 회색관계등급을 산정하여 재해 위험성의 우선순위를 결정한다. 따라서 제안된 모델에서는 항만하역근로자수, 50세 이상 항운노조원수, 총근로시간, 하역장비수, 철재화물량, 총화물량, 사상자수, 사망자수 등 8개의 평가 항목을 추출되었다. 그 결과 부산항의 재해 위험성이 가장 높게 나타났으며 이에 따라 우선적으로 재해위험성을 경감하는 방안이 검토되어야 할 것이다.

기후변화와 기후변화 외적인 요인으로 인해 지하수자원은 고갈되어가고 있다. 지하수자원의 효율적인 관리를 위해 유역 단위의 지하수자원 관리 취약시기 평가 방법을 개발하였다. 유역 단위의 취약시기 평가는 취약 지역 평가와 소유역에 대한 취약시기 평가를 독립적으로 진행하여 각각의 지수를 산정하였다. 취약 지역 평가 지수를 표준화하여 독립적으로 진행한 취약시기 평가 지수에 적용하여 유역 단위의 취약시기 평가 방법을 개발하였으며, 개발한 방법을 낙동강 상류 지역인 봉화군, 안동시, 예천군, 문경시, 상주시에 적용하였다. 그 결과 상주의 8월이 0.278로 가장 취약한 것으로 나타났으며, 안동시는 1년 중 8개월간 5개 지역 중 지하수자원 관리에 취약한 것으로 나타났다. 개발된 방법을 이용하여 지하수자원의 시공간을 고려한 효율적인 관리방안을 모색할 수 있을 것이다.

본 논문에서는 가중치 산정방법의 하나인 엔트로피(Entropy)기법을 통해 평가항목별 가중치를 산정하고 다기준 의사결정 방법의 하나인 프로메티(Preference Ranking Organization METHod for Enrichment Evaluations, PROMETHEE)를 적용하여 도시유역의 위험도 평가기법을 제안하였다. 도시유역내 소유역의 위험도와 관련된 항목들로는 자연적 요인과 사회적 요인에 따른 항목으로 구분하였다. 엔트로피 기법과 프로메티를 이용한 도시유역 위험도 평가기법은 그 적용성을 검증하고자 서울시 대표적 저지대 지역인 성내배수분구에 적용하였으며, 전체 26개 소유역에 대한 각각의 가중치와 위험도가 산정되었다. 또한 26개의 소유역은 위험도 평가구분에 따라 고·중·저 위험유역으로 분류되었으며, 이중 높은 위험도에 해당하는 소유역이 과거 집중호우에 따른 침수이력이 있는 것으로 확인되었다.