• Journal of Information Technology Services
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• v.1 no.1
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• pp.45-55
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• 2002

This paper suggests a new approach to IT project management based on a regular project meeting results to consider the recent project environment. The greater part of recent IT projects are related to e-business transformation. Transforming to e-business is a new problem very different from those they have been worked, in several point of views. Under e-business era, therefore any IT project is being implemented in more complex, dynamic and uncertain environment than traditional. That is, project leaders must consider more factors to control projects including resources, quality, risks, and technologies, and human resources. The project organizations and software corporations thus need to develop and establish new concepts or methodologies to manage e-business projects. In this point of view, an entropy model in this study is introduced for estimating and managing the uncertainty in project control using multi-attributes of project meeting. This paper proposes a new frame work based on entropy model using project meeting results to consider eIT project environment with a small pilot study.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.1
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• pp.52-57
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• 1999

In this paper, the methods which calculate the tuple membership values in a vague model of the fuzzy databases are analyzed A method among them is proposed to offer the effective solutions to the users. Also an information theory is studied to calculate the entropy of the results of a fuzzy query and an algorithm is proposed to control the size of the entropy.

• Journal of the Semiconductor & Display Technology
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• v.22 no.2
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• pp.40-44
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• 2023

The defect detection based on deep learning requires minimal loss and high accuracy to pinpoint product defects. In this paper, we confirm the loss rate of deep learning training based on disc-shaped artificial scaffold images. It is intended to compare the performance of Cross-Entropy functions used in object detection algorithms. The model was constructed using normal, defective artificial scaffold images and category cross entropy and sparse category cross entropy. The data was repeatedly learned five times using each loss function. The average loss rate, average accuracy, final loss rate, and final accuracy according to the loss function were confirmed.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• v.4 no.2
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• pp.79-85
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• 2023

The Tibetan Plateau is home to the only alpine crane species, the black-necked crane (Grus nigricollis). Conservation efforts are severely hampered by a lack of knowledge on the spatial distribution and breeding habitats of this species. The ecological niche modeling framework used to predict the spatial distribution of this species, based on the maximum entropy and occurrence record data, allowed us to generate a species-specific spatial distribution map in Ladakh, Trans-Himalaya, India. The model was created by assimilating species occurrence data from 486 geographical sites with 24 topographic and bioclimatic variables. Fourteen variables helped forecast the distribution of black-necked cranes by 96.2%. The area under the curve score for the model training data was high (0.98), indicating the accuracy and predictive performance of the model. Of the total study area, the areas with high and moderate habitat suitability for black-necked cranes were anticipated to be 8,156 km² and 6,759 km², respectively. The area with high habitat suitability within the protected areas was 5,335 km². The spatial distribution predicted using our model showed that the majority of speculated conservation areas bordered the existing protected areas of the Changthang Wildlife Sanctuary. Hence, we believe, that by increasing the current study area, we can account for these gaps in conservation areas, more effectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.2
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• pp.147-162
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• 2009

In this paper, we propose a Cooperative Transmission Strategy using Entropy-based Relay Selection in Mobile Ad-hoc Wireless Sensor Networks(MAWSN) with Rayleigh Fading Environments. The main features and contributions of the proposed cooperative transmission strategy are as follows. First, entropy-based relay selection is used to improve data transmission reliability from a source node to a destination node. Second, we present a theoretical analysis model for the proposed cooperative transmission strategy with the outage probability of the end-to-end performance. The performance of our protocol is evaluated using analysis and simulation.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.12 no.8
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• pp.589-597
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• 2002

In this paper the nonstationary response of accelerating vehicle is firstly obtained by using nonstationary road roughness model in time domain. To get the result of nonstationary response in frequency domain, the maximum entropy method is used for Processing nonstationary response of vehicle in frequency domain. The three-dimensional transient maximum entropy spectrum (MES) of response is given.

• Communications for Statistical Applications and Methods
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• v.6 no.3
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• pp.771-771
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• 1999

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.12
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• pp.985-992
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• 2001

This paper proposes a self-organizing fuzzy modeling(SOFUM)which an create a new hyperplane shaped cluster and adjust parameters of the fuzzy model in repetition. The suggested algorithm SOFUM is composed of four steps: coarse tuning. fine tuning cluster creation and optimization of learning rates. In the coarse tuning fuzzy C-regression model(FCRM) clustering and weighted recursive least squared (WRLS) algorithm are used and in the fine tuning gradient descent algorithm is used to adjust parameters of the fuzzy model precisely. In the cluster creation, a new hyperplane shaped cluster is created by applying multiple regression to input/output data with relatively large fuzzy entropy based on parameter tunings of fuzzy model. And learning rates are optimized by utilizing meiosis-genetic algorithm in the optimization of learning rates To check the effectiveness of the suggested algorithm two examples are examined and the performance of the identified fuzzy model is demonstrated via computer simulation.

• 한국HCI학회:학술대회논문집
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• 2006.02a
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• pp.1240-1245
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• 2006

한국어 문장을 구조 분석할 때에 모호성을 발생시키는 유형 중의 하나가 나열 및 병렬형이다. 문장 구조 복잡도를 증가시키는 나열 및 병렬형을 구조 분석 전에 미리 하나의 단위로 묶어서 처리하는 것이 문장 구조 분석의 정확도를 높이는데 중요하다. 본 연구에서는 형태소 태그를 이용한 기본 규칙으로 문장을 청크 단위로 분할하고 분할된 청크 중에서 나열형을 인식하여 해당되는 청크들을 하나의 나열 청크로 통합하여 청크의 개수를 줄인다. 병렬형에 대해서는 반복되는 병렬 청크의 범위와 생략된 용언을 복원한다. 이러한 인식은 첫 단계로 기호(symbol)를 중심으로 구축된 간단한 규칙으로 인식을 하고 이러한 규칙에 해당되지 않는 형태의 나열 및 병렬형은 Maximum Entropy 모델을 이용하여 적용한다. ME모델은 어휘자질, 형태소 품사 자질, 거리 자질, 의미자질, 구 단위 태그 자질(NP:명사구, VP:동사구, AP:형용사구), BIO 태그(Begin, Inside, Outside) 자질에 대한 ME(Maximum Entropy) 모델을 이용하여 구축되었다.

• Journal of Korean Society of Water and Wastewater
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• v.26 no.1
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• pp.1-12
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• 2012

The purpose of water distribution system is supplying water to users by maintaining appropriate pressure and water quality. For efficient monitoring of the water distribution system, determination of optimal locations for pressure monitoring is essential. In this study, entropy theory was applied to determine the optimal locations for pressure monitoring. The entropy which is defined as the amount of information was calculated from the pressure change due to the variation of demand reflected the abnormal conditions at nodes, and the emitter function (fire hydrant) was used to reproduce actual pressure change pattern in EPANET. The optimal combination of monitoring points for pressure detection was determined by selecting the nodes receiving maximum information from other nodes using genetic algorithm. The Ozger's and a real network were evaluated using the proposed model. From the results, it was found that the entropy theory can provide general guideline to select the locations of pressure sensors installation for optimal design and monitoring of the water distribution systems. During decision-making phase, optimal combination of monitoring points can be selected by comparing total amount of information at each point especially when there are some constraints of installation such as limitation of available budget.