• Proceedings of the Korea Society for Energy Engineering kosee Conference
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• 1998.10a
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• pp.64-68
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• 1998

This paper discusses the potential application of fuzzy set theory to the decision-making in the area of radioactive waste management. the approach proposed in this study is based on the concepts of fuzzy set theory and the hierarchical structure analysis. The linguistic variables and fuzzy numbers are used to aggregate the decision maker's subjective assessments of the decision criteria and of the decision alternatives with respect to these criteria. For each alternative, the fuzzy appropriateness index is evaluated to obtain the final score. Using total integral value method, one of methods for ranking fuzzy numbers, the fuzzy appropriateness indices are ranked. As a case problem, selection of the most suitable option for spent fuel storage is illustrated.

• Journal of Engineering Education Research
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• v.17 no.3
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• pp.3-7
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• 2014

This study was conducted to compare global mindset competency between engineering and non-engineering college students. Participants were 100 engineering and 202 non-engineering college students. Results indicated that engineering college students showed significantly lower mean scores on foreign understanding and self-directed adaptability than non-engineering college students, whereas there were no significant differences on self-ratings of foreign language ability. Hierarchical regression analyses revealed that the incremental validity of global mindset competency factors on global competency was significant. Finally, limitations of the present study and suggestions for further studies were discussed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.2
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• pp.559-573
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• 2016

In this paper, we investigate the problem of achieving proportional fairness in hierarchical wireless sensor networks. Combining clustering formulation and scheduling, we maximize total bandwidth utility for proportional fairness while controlling the power consumption to a minimum value. This problem is decomposed into two sub-problems and solved in two stages, which are Clustering Formulation Stage and Scheduling Stage, respectively. The above algorithm, called CSPF_PC, runs in a network formulation sequence. In the Clustering Formulation Stage, we let the sensor nodes join to the cluster head nodes by adjusting transmit power in a greedy strategy; in the Scheduling Stage, the proportional fairness is achieved by scheduling the time-slot resource. Simulation results verify the superior performance of our algorithm over the compared algorithms on fairness index.

• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.555-559
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• 1998

The human chromosome analysis is widely used to diagnose genetic disease and various congenital anomalies. Many researches on automated chromosome karyotype analysis have been carried out, some of which produced commercial systems. However, there still remains much room for improving the accuracy of chromosome classification. In this paper, We proposed an optimal pattern classifier by neural network to improve the accuracy of chromosome classification. The proposed pattern classifier was built up of two-step multi-layer neural network(TMANN). We reconstructed chromosome image to improve the chromosome classification accuracy and extracted four morphological features parameters such as centromeric index (C.I.), relative length ratio(R.L.), relative area ratio(R.A.) and chromosome length(C.L.). These Parameters employed as input in neural network by preprocessing twenty human chromosome images. The experiment results shown that the chromosome classification error was reduced much more than that of the other classification methods.

• Proceedings of the Korean Information Science Society Conference
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• 2002.04b
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• pp.64-66
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• 2002

최근 다차원 공간색인 방법의 성능 향상을 위해 근사법을 사용하여 노드의 팬아웃을 증가시키려는 시도가 많이 행해졌다. 하지만 이러한 방법은 색인 구조의 정확성이 떨어져 불필요한 노드를 방문할 확률을 높다는 단점이 있다 본 논문에서는 정적 데이터에 대하여 노드의 팬아웃을 증가시키기 위해 하향식 STR 공간분할방법을 사용한 새로운 색인 방법을 제안한다. 제안한 방법은 공간분할방법을 사용하므로 근사법을 이용한 방법에 비해 정확성이 높을 백 아기라 하향식 계층 STR을 제안하여 STR 공간 분할방법을 효율적으로 트리 구조에 적용할 수 있도록 하였다. 이 피에도 이중분할 방법을 제안하여 점 데이터 및 사각형 데이터의 색인을 가능하게 딸 딱 아니라 사상 공간을 줄여 불필요한 노드의 방문을 막아 성능을 향상시켰다.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.366-368
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• 2003

In this paper, a parametric evaluation method of protection ability is proposed. The adequacy of every parameter is evaluated for the setting rules. Then the results are combined to give protection level of a whole protective system. The setting rules are categorized into three groups for hierarchical calculation. The proposed scheme is applied to a location problem of a new protective device to show its effectiveness.

• Journal of Korean Academy of Fundamentals of Nursing
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• v.21 no.2
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• pp.123-130
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• 2014

Purpose: The purpose of this study was to identify quality of sleep and health-promoting behaviors in rotating-shift nurses and to explore the influence of health promoting behaviors on quality of sleep. Method: Participants were 161 staff nurses working in an irregular three shift system in one of three general hospitals located in Kyungpook province. Data were collected using the Pittsburgh Sleep Quality Index and the Health Promoting Lifestyle Profile-IIand were analyzed using hierarchical multiple regression analysis. Results: The majority of the participants had very poor quality of sleep and performed a low level of health promoting behaviors. In terms of health promoting behaviors, nutrition and stress management significantly influenced quality of sleep of these nurses. Conclusion: Results indicate the importance of encouraging rotating-shift nurses to enhance their health promoting behaviors in order to improve quality of sleep.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.39 no.5
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• pp.470-477
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• 1990

Singh's multi-level method is extended to the optimal tracking control of a large interconnected dynamical system which has coupled states and coupled inputs. The steady-state tracking error and a convergence condition for the extended multi-level method are derived analytically and the results show that the steady-state tracking error and a convergence rate have to be compromised. Also, a new multi-level method which is advantageous over the Singh's method in steady-state tracking error and computational burden is proposed by introducing nominal inputs into the performance index. The resulting feedback gain matrix and the compensation vector are optimal for all initial conditions so that eventual on-line computation is minimal.

• Journal of Electrical Engineering and Technology
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• v.9 no.4
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• pp.1171-1181
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• 2014

Different power quality (PQ) disturbance sources can have major impacts on the power supply grid. This study proposes, for the first time, an early warning approach to identifying PQ problems and providing early warning prompts based on the monitored data of PQ disturbance sources. To establish a steady-state power quality early warning index system, the characteristics of PQ disturbance sources are analyzed and summed up. The higher order statistics anomaly detection (HOSAD) algorithm, based on skewness and kurtosis, and hierarchical power quality early warning flow, were then used to mine limit-exceeding and abnormal data and analyze their severity. Cases studies show that the proposed approach is effective and feasible, and that it is possible to provide timely power quality early warnings for limit-exceeding and abnormal data.

• Korean Journal of Remote Sensing
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• v.19 no.5
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• pp.381-392
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• 2003

Multi-temporal approaches using sequential data acquired over multiple years are essential for satisfactory discrimination between many land-cover classes whose signatures exhibit seasonal trends. At any particular time, the response of several classes may be indistinguishable. A harmonic model that can represent seasonal variability is characterized by four components: mean level, frequency, phase and amplitude. The trigonometric components of the harmonic function inherently contain temporal information about changes in land-cover characteristics. Using the estimates which are obtained from sequential images through spectral analysis, seasonal periodicity can be incorporates into multi-temporal classification. The Normalized Difference Vegetation Index (NDVI) was computed for one week composites of the Advanced Very High Resolution Radiometer (AVHRR) imagery over the Korean peninsula for 1996 ～ 2000 using a dynamic technique. Land-cover types were then classified both with the estimated harmonic components using an unsupervised classification approach based on a hierarchical clustering algorithm. The results of the classification using the harmonic components show that the new approach is potentially very effective for identifying land-cover types by the analysis of its multi-temporal behavior.