• Journal of Electrical Engineering and Technology
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• v.12 no.5
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• pp.2043-2050
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• 2017

This paper presents two MPC (Model Predictive Control) based charging and discharging algorithms of BESS (Battery Energy Storage System) for capacity firming of wind generation. To deal with the intermittency of the output of wind generation, a single BESS is employed. The proposed algorithms not only make the output of combined systems of wind generation and BESS track the predefined reference, but also keep the SoC (State of Charge) of BESS within its physical limitation. Since the proposed algorithms are both presented in simple if-then statements which are the optimal solutions of related optimization problems, they are both easy to implement in a real-time system. Finally, simulations of the two strategies are done using a realistic wind farm library and a BESS model. The results on both simulations show that the proposed algorithms effectively achieve capacity firming while fulfilling all physical constraints.

• International Journal of Internet, Broadcasting and Communication
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• v.12 no.2
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• pp.45-50
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• 2020

A Language model with neural networks commonly trained with likelihood loss. Such that the model can learn the sequence of human text. State-of-the-art results achieved in various language generation tasks, e.g., text summarization, dialogue response generation, and text generation, by utilizing the language model's next token output probabilities. Monotonous and boring outputs are a well-known problem of this model, yet only a few solutions proposed to address this problem. Several decoding techniques proposed to suppress repetitive tokens. Unlikelihood training approached this problem by penalizing candidate tokens probabilities if the tokens already seen in previous steps. While the method successfully showed a less repetitive generated token, the method has a large memory consumption because of the training need a big vocabulary size. We effectively reduced memory footprint by encoding words as sequences of subword units. Finally, we report competitive results with token level unlikelihood training in several automatic evaluations compared to the previous work.

• MALSORI
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• no.61
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• pp.87-100
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• 2007

A punctuation generation system which combines prosodic information with acoustic and language model information is presented. Experiments have been conducted first for the reference text transcriptions. In these experiments, prosodic information was shown to be more useful than language model information. When these information sources are combined, an F-measure of up to 0.7830 was obtained for adding punctuation to a reference transcription. This method of punctuation generation can also be applied to the 1-best output of a speech recogniser. The 1-best output is first time aligned. Based on the time alignment information, prosodic features are generated. As in the approach applied in the punctuation generation for reference transcriptions, the best sequence of punctuation marks for this 1-best output is found using the prosodic feature model and an language model trained on texts which contain punctuation marks.

• The Journal of Korean Academic Society of Nursing Education
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• v.28 no.3
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• pp.305-316
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• 2022

Purpose: The purpose of this study was to construct a structural equation model of organizational commitment in hospital nurses based on a job demands-resources model and to confirm the moderating effect(s) according to the nurses' generation. Methods: The model was constructed of the exogenous variables of social support, emotional intelligence, emotional labor, and job conflict and the endogenous variables of burnout, job engagement, and organizational commitment. The participants were 560 hospital nurses working in 3 general hospitals. Data were collected from August 1 to September 30, 2021, and analyzed using SPSS Window 23.0 and IBM AMOS 23.0. Results: The strongest factor directly influencing hospital nurses' organizational commitment was social support. In a multiple group analysis, nurses' generation had a partial moderating effect. In a generation-specific analysis, the Z generation group was higher than the X and Y generation groups in the variables of emotional labor and burnout related to organizational commitment. Conclusion: Based on the findings of this study, to improve hospital nurses' organizational commitment, social support is needed as an important management strategy. At the organizational level, we need to develop ways to improve organizational commitment by reducing the emotional labor and burnout of Generation Z.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.5
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• pp.487-496
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• 2022

This study attempts to discover a differentiated service strategy for the hotpot restaurant industry from the perspective of Chinese Generation Z customers, as well as to further explore the inner needs of Chinese Generation Z to make practical implications for discovering the method of gaining their satisfaction and loyalty. This paper employs questionnaires to collect analytical data and through a case study to produce company strategies. Smith's Marketing Ethics Sequential System Model (SMESSM) is introduced in this paper for the decision of whether the case study company Haidilao Hot Pot should make a new strategy on service based on Generation Z's consuming behavior. The findings of this study demonstrate that hotpot restaurant must differentiate their services for Generation Z from older generation customers to gain a sustainable development of the hotpot business. Proper differentiated service will not only improve Generation Z's dining experience but also reduce costs. This paper is the first to discuss differentiated service strategy in the hotpot restaurant business from the perspective of Generation Z customers. And a Chinese experience of SMESSM for practical use is introduced in this paper, which enriches the relevant implications for future research on business strategy.

• Asian Journal of Atmospheric Environment
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• v.10 no.3
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• pp.156-161
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• 2016

In order to deal with current environmental issues and their backgrounds, further development of current teaching methods and tools are essential. The result of questionnaire performed in this study indicates that the effect and the change of the perception of power generation in Japan after the great disaster of East Japan have caused many students (both high school and college students) to become interested in the energy situation. In the present study, we made an attempt to develop a model instrument of a thermal power plant that can be applied as a teaching tool for understanding of air pollutant forming as well as power generation. Our novel model tool consists of a body (30 cm width, 21 cm depth, and 41 cm height), a combustion chamber, two motors, a boiler, a voltmeter, and a chimney for measurement of exhaust gas. Using our novel hand-made power plant, we carried out some model experiments with learners (i.e. high school and college students). Through model experiments, students can be experienced not only about power generation but also about generation of air pollutants. In order to estimate the applicability of our novel instrument as an educational tool, we carried out the questionnaires before and after model experiments. More than 80% of educatees reported that it was very useful as a teaching tool for energy and environmental education. The results of questionnaires indicated that learners achieved a very deep understanding of the principles of power generation and the forming of air pollutants.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.1
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• pp.85-94
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• 2017

In this paper, I proposed a sound model generation and a most frequent model search algorithm for recognizing animal vocalization. The sound model generation algorithm generates a optimal set of models through repeating processes such as the training process, the Viterbi Search process, and the most frequent model search process while adjusting HMM(Hidden Markov Model) structure to improve global recognition rate. The most frequent model search algorithm searches the list of models produced by Viterbi Search Algorithm for the most frequent model and makes it be the final decision of recognition process. It is implemented using MFCC(Mel Frequency Cepstral Coefficient) for the sound feature, HMM for the model, and C# programming language. To evaluate the algorithm, a set of animal sounds for 27 species were prepared and the experiment showed that the sound model generation algorithm generates 27 HMM models with 97.29 percent of recognition rate.

• Journal of the Society of Naval Architects of Korea
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• v.43 no.2 s.146
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• pp.246-257
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• 2006

In the ship building industry, the generation of a structural analysis model, that is, a finite element model of a hull structure, has been manually performed by a designer and thus has required lots of time as compared with that of a mechanical part, because of many constraints, the complexity, and the huge size of the hull structure. To make this task automatic, a generation method of the structural analysis model is proposed through the reconstruction of the topological information of a hull structural model in this study. The applicability of the proposed method is demonstrated by applying it to the generation of the structural analysis model of a deadweight 300,000ton VLCC(Very Large Crude oil Carrier).

• Journal of the Korean Society for Precision Engineering
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• v.16 no.4 s.97
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• pp.229-236
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• 1999

The surface, generated by end milling operation, is deteriorated by tool runout, vibration, tool wear and tool deflection, etc. Among them, the effect of tool deflection on surface accuracy is analyzed. Surface generation model for the prediction of the topography of machined srufaces has been developed based on cutting mechanism and cutting tool geometry. This model accounts for not only the ideal geometrical surface, but also the deflection of tool due to cutting force. For the more accurate prediction of cutting force, flexible end mill model is used to simulate cutting process. Computer simulation has shown the feasibility of the surface generation system. Using developed simulation system, the relations between the shape of end mill and cutting conditions are analyzed.

• Water for future
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• v.12 no.2
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• pp.63-69
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• 1979

The sequences of monthly streamflows constitute a non-statonary time series. The purely stochastic model has been applied to data generation of non-stationary time series. Tow different mothods--single site and multisite generation--have been used on the hydrologic time series. In this study the synthetic generation method by bivariate analysis, studied by Thomas Fiering, one of multi-site models, has been applied to the historical data on monthly streamflows at two sites in Nakdong River, and also for validity of this model the single site Thomas Fiering model applied. Through statistical analysis it has been shown that the performance of bivariate Thomas Fiering model was better than that of the other. By comparison of mean and standard deviaion between the historical and the generated, and cross correlogram interpretation, it has been known that the model used herein has good performance to simultaneously generate the monthly streamflows at two sites in a river hasin.