• Journal of Fisheries and Marine Sciences Education
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• v.16 no.1
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• pp.1-10
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• 2004

The department of education developed editing data of fisheries and shipping high school subject in 1987. But as change to informational society, the new term and predicate were built on a textbook of fisheries and shipping that was not in the past. Terms came into being in this way, it was used indiscreetly by spending a different expression on a textbook. In this study based on currently subject of fisheries and shipping high school 36books, examined an elementary school junior high school and a definition related term in order to solve these problems. Specialist on each field selected term and the predicate which is objective and proper. Especially field of fisheries and shipping uses a japanese term as it is. So there are a lot of the terms that is hard for students. Using these terms yet, the term that meaning delivery is uncertain and hard expression is going to carry out role to convert to a clear and easy term through this study.

• Journal of the Korean Solar Energy Society
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• v.33 no.5
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• pp.1-8
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• 2013

Wind resource data of short-term period has to be corrected a long-term period by using MCP method that Is a statistical method to predict the long-term wind resource at target site data with a reference site data. Because the field measurement for wind assessment is limited to a short period by various constraints. In this study, 2 different MCP methods such as Linear regression and Matrix method were chosen to compare the predictive accuracy between the methods. Finally long-term wind speed, wind power density and capacity factor at the target site for 20 years were estimated for the variability of wind and wind energy. As a result, for 20 years annual average wind speed, Yellow sea off shore wind farm was estimated to have 4.29% for coefficient of variation, CV, and -9.57%~9.53% for range of variation, RV. It was predicted that the annual wind speed at Yellow sea offshore wind farm varied within ${\pm}10%$.

• The Journal of the Acoustical Society of Korea
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• v.42 no.4
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• pp.313-319
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• 2023

In this paper, a time series machine learning model, Long Short Term Memory (LSTM), is applied into the bubble flow noise data and the underwater projectile launch noise data to predict missing values of time-series underwater noise data. The former is mixed with bubble noise, flow noise, and fluid-induced interaction noise measured in a pipe and can be classified into three types. The latter is the noise generated when an underwater projectile is ejected from a launch tube and has a characteristic of instantaenous noise. For such types of noise, a data-driven model can be more useful than an analytical model. We constructed an LSTM model with given data and evaluated the model's performance based on the number of hidden units, the number of input sequences, and the decimation factor of signal. It is shown that the optimal LSTM model works well for new data of the same type.

• Journal of East-West Nursing Research
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• v.22 no.1
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• pp.24-31
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• 2016

Purpose: The purpose of this study was to identify and compare the differences on perceived health status, Activities of Daily Livings (ADL), social support, and residential satisfaction between long-term care hospitals and nursing homes. Methods: Data was collected through questionnaires and interviews conducted from March 29 to April 22, 2011. The subjects were 66 old adults in 3 long-term care hospitals and 53 old adults in 6 nursing homes. Data were analyzed by Pearson's correlation analysis and t-tests. Results: ADL and subjective health status in nursing homes were worse than those in long-term hospitals, but it was not statistically significant (p>.05). Old adults in nursing homes received more emotional support from other residents and staff, and received more instrumental support from staff than those in long-term care hospitals (p<.001). The mean scores of resident satisfaction in long-term care hospitals and nursing homes were 3.53 ($SD={\pm}0.36$) and 3.97 ($SD={\pm}0.44$), respectively. Resident satisfaction in nursing homes significantly was higher than long-term care hospitals (p<.001). Conclusion: Health care personnels in long-term care hospitals should enhance resident satisfaction and social support and need to coordinate long-stay patients with nursing homes.

• Korean Journal of Adult Nursing
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• v.25 no.3
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• pp.298-311
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• 2013

Purpose: The purpose of this study was to compare reported physical symptoms, hope and family support of cancer patients between general hospitals and long-term care hospitals. Methods: Subjects were 175 patients diagnosed with cancers from two general hospitals and six long-term care hospitals located in G city. Subjects completed a questionnaire with questions about general characteristics and questions about the disease, physical symptoms, hope and family support. Data was collected from February to April and the data were analyzed using an independent t-test and one-way ANOVA. Results: The subjects in long-term care hospitals showed higher percentage in pain, nausea, fatigue, sleep disorder, and change in appearance. There was a significant difference in family support between two groups. A significant positive correlation was found between hope and family support in subjects in general and long-term care hospitals. Conclusion: Significant differences were found in some physical symptoms and family support between cancer patients in general hospitals and long-term care hospitals. Thus, nurses in long-term care hospitals need provide care suitable for the characteristics of cancer patients in long-term care hospitals.

• Communications for Statistical Applications and Methods
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• v.24 no.4
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• pp.325-337
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• 2017

In this paper, we proposed a new long-term lifetime distribution with four parameters inserted in a risk competitive scenario with decreasing, increasing and unimodal hazard rate functions, namely the Weibull-Poisson long-term distribution. This new distribution arises from a scenario of competitive latent risk, in which the lifetime associated to the particular risk is not observable, and where only the minimum lifetime value among all risks is noticed in a long-term context. However, it can also be used in any other situation as long as it fits the data well. The Weibull-Poisson long-term distribution is presented as a particular case for the new exponential-Poisson long-term distribution and Weibull long-term distribution. The properties of the proposed distribution were discussed, including its probability density, survival and hazard functions and explicit algebraic formulas for its order statistics. Assuming censored data, we considered the maximum likelihood approach for parameter estimation. For different parameter settings, sample sizes, and censoring percentages various simulation studies were performed to study the mean square error of the maximum likelihood estimative, and compare the performance of the model proposed with the particular cases. The selection criteria Akaike information criterion, Bayesian information criterion, and likelihood ratio test were used for the model selection. The relevance of the approach was illustrated on two real datasets of where the new model was compared with its particular cases observing its potential and competitiveness.

• The Plant Pathology Journal
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• v.38 no.4
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• pp.395-402
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• 2022

To predict rice blast, many machine learning methods have been proposed. As the quality and quantity of input data are essential for machine learning techniques, this study develops three artificial neural network (ANN)-based rice blast prediction models by combining two ANN models, the feed-forward neural network (FFNN) and long short-term memory, with diverse input datasets, and compares their performance. The Blast_Weathe long short-term memory r_FFNN model had the highest recall score (66.3%) for rice blast prediction. This model requires two types of input data: blast occurrence data for the last 3 years and weather data (daily maximum temperature, relative humidity, and precipitation) between January and July of the prediction year. This study showed that the performance of an ANN-based disease prediction model was improved by applying suitable machine learning techniques together with the optimization of hyperparameter tuning involving input data. Moreover, we highlight the importance of the systematic collection of long-term disease data.

• Journal of the Semiconductor & Display Technology
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• v.22 no.3
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• pp.142-148
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• 2023

In this paper, we identify performance issues in executing compute kernels from PolyBench, which includes compute kernels that are the core computational units of various data-intensive workloads, such as deep learning and data-intensive applications, on Processing-in-Memory (PIM) devices. Therefore, using our in-house simulator, we measured and compared the various performance metrics of workloads based on traditional out-of-order and in-order processors with Processing-in-Memory-based systems. As a result, the PIM-based system improves performance compared to other computing models due to the short-term data reuse characteristic of computational kernels from PolyBench. However, some kernels perform poorly in PIM-based systems without a multi-layer cache hierarchy due to some kernel's long-term data reuse characteristics. Hence, our evaluation and analysis results suggest that further research should consider dynamic and workload pattern adaptive approaches to overcome performance degradation from computational kernels with long-term data reuse characteristics and hidden data locality.

• Journal of Home Health Care Nursing
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• v.12 no.1
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• pp.70-91
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• 2005

Purpose: Long-term care facilities have a responsibility to provide care service that enables residents to maintain their maximal functional capacity and quality of life. Also their needs must be reflected to the service programs. In oder to provide an adequate service, we should assess the elderly's physical, psychological and social health status and the need. In addition to this, the long-term care facilities must be defined clearly by the type of services. This study would contribute to conduct appropriate services in public long-term care policy for the older population in the future. This study would provide informations of long-term care facilities' services and older persons' needs for long-term care. Method: To achieve this objectives, this paper investigates the types, service programs of long-term care institutes and job descriptions of workers. The subjects were consisted of 150 long-term care institutes. 150 institutes of long-term care facilities were drawn from all over the country by a nonrandom, convenience sampling. The data were analyzed by frequency, percentage, $x^2$-test using SPSS program. The instruments of this study were self-reported questionnaires for long-term care institutes. The data were collected from March 1, 2004 to may 31, 2004. Results: Service programs of long-term care institutes were not enough for residents' demands. The job descriptions among nurse, social worker and physical therapist were not clearly defined. The nurse's main role was medication and checking vital sign(49.7%), that of social worker's was observation and supervising (31.2%). The most significant problems were lacking of diverse service programs for residents. Conclusion: Considering these findings and conclusion, the needs of long-term care services should be provided by individual physical and psychological level. And the professional manpower for elderly should be educated in multi disciplines.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2008.10a
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• pp.225-228
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• 2008

The electricity supply and demand to be stable to a system link increase of the variance power supply and operation are requested in jeju Island electricity system. A short-term Load forecasting which uses the characteristic of the Load is essential consequently. We use the interrelationship of the electricity Load and change of a summertime temperature and data refining in the paper. We presented a short-term Load forecasting algorithm of jeju Island and used the correlation coefficient to the criteria of the refining. We used each temperature area data to be refined and forecasted a short-term Load to an exponential smoothing method.