• The Transactions of The Korean Institute of Electrical Engineers
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• v.66 no.5
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• pp.745-749
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• 2017

Climate change and energy security are major factors for future national energy policy. To resolve these issues, many countries are focusing on creating new growth industries and energy services such as smartgrid, renewable energy, microgrid, energy management system, and peer to peer energy trading. The financial and economic evaluation of new energy services basically requires energy savings estimation technologies. This paper presents the baseline load estimation method, which is used to calculate energy savings resulted from participating in the new energy program, using moving average model with heating degree days (HDD) and cooling degree days (CDD) adjustment. To demonstrate the improvement of baseline load estimation accuracy, the proposed method is tested. The results of case studies are presented to show the effectiveness of the proposed baseline load estimation method.

• MALSORI
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• no.56
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• pp.207-223
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• 2005

The goal of language model adaptation is to improve the background language model with a relatively small adaptation corpus. This study presents a language model adaptation technique where additional text data for the adaptation do not exist. We propose the information retrieval (IR) technique with N-gram language modeling to collect the adaptation corpus from baseline text data. We also propose to use a dynamic language model interpolation coefficient to combine the background language model and the adapted language model. The interpolation coefficient is estimated from the word hypotheses obtained by segmenting the input speech data reserved for held-out validation data. This allows the final adapted model to improve the performance of the background model consistently The proposed approach reduces the word error rate by $13.6\%$ relative to baseline 4-gram for two-hour broadcast news speech recognition.

• Journal of the Optical Society of Korea
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• v.15 no.1
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• pp.30-37
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• 2011

Binocular-pair images obtained from two cameras can be used to calculate the three-dimensional (3D) world coordinate of a feature point. However, to apply this method, measurement accuracy of binocular vision depends on some structure factors. This paper presents an experimental study of measurement distance, baseline distance, and baseline direction. Their effects on camera reconstruction accuracy are investigated. The testing set for the binocular model consists of a series of feature points in stereo-pair images and corresponding 3D world coordinates. This paper discusses a method to increase the baseline distance of two cameras for enhancing the accuracy of a binocular vision system. Moreover, there is an inflexion point of the value and distribution of measurement errors when the baseline distance is increased. The accuracy benefit from increasing the baseline distance is not obvious, since the baseline distance exceeds 1000 mm in this experiment. Furthermore, it is observed that the direction errors deduced from the set-up are lower when the main measurement direction is similar to the baseline direction.

• Journal of Korean Society of Forest Science
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• v.103 no.3
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• pp.439-445
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• 2014

In this study, we developed a dynamic stand yield model to estimate the baseline carbon stock, which is essentially required for a forest carbon offset project based on forest management. For developing the yield model, the data was acquired from the databases of the $5^{th}$ National Forest Inventory. The model was validated by comparing its estimations with field measurements that were conducted from 4 study sites (14 plots with thinning treatments) located in Hong-chun, Hoeng-sung, Yang-yang Daechi and Yang-yang Jungja. The difference between the estimations and the field measurements was less than 5%. Using the dynamic stand yield model, we estimated the changes in stand yield volume and carbon stocks for each species according to the baseline scenarios. As the results, we found that baseline carbon stock was the highest at Quercus acutissima stand (83.01tC/ha), while the lowest at Pinus rigida stand (32.17tC/ha) and Pinus densiflora stand of central region (39.09tC/ha). Hence, a project provider could get more carbon emission credits from an improved forest management project when considering the project with Pinus rigida stand or Pinus densiflora stand (central region). The baseline carbon stock and the dynamic stand yield model developed from this study would be useful for designing carbon offset projects based on improved forest management.

• Journal of The Korean Society of Agricultural Engineers
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• v.52 no.3
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• pp.57-64
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• 2010

The impacts of climate change on yield and evapotranspiration of rice have been modeled using AquaCrop model developed by Food and Agriculture Organization (FAO). Climate change scenario downscaled by Mesoscale Model 5 (MM5) regional model from ECHO-G General Circulation Model (GCM) outputs by Korea Meteorological Research Institute (METRI) was used in this study. Monthly average climate data for baseline (1971-2000) and three time periods (2020s, 2050s and 2080s) were used as inputs to the AquaCrop model. The results showed that the evapotranspiration after transplanting was projected to increase by 4 % (2020s), 8 % (2050s) and 14 % (2080s), respectively, from the baseline value of 464 mm. The potential rice yield was 6.4 t/ha and water productivity was 1.4 kg/$m^3$ for the baseline. The potential rice yield was projected to increase by 23 % (2020s), 55 % (2050s), and 98 % (2080s), respectively, by the increased photosynthesis along with the $CO_2$ concentration increases. The water productivity was projected to increase by 19 % (2020s), 44 % (2050s), and 75 % (2080s), respectively.

• Journal of The Korean Society of Agricultural Engineers
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• v.51 no.4
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• pp.7-13
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• 2009

The paddy irrigation demand for Nakdong river basin in Korea due to the climate change have been analyzed using regional climate model outputs. High-resolution (27 ${\times}$ 27 km) climate data for SRES A2 scenario produced by the Meteorological Research Institute (METRI), South Korea, and the observed baseline climatology dataset (1971-2000) were used. The outputs from the ECHO-G GCM model were dynamically downscaled using the MM5 regional model by METRI. Maps showing the predicted spatial variations of changes in climate parameters and paddy irrigation requirements have been produced using the geographic information system. The results of this study showed that the average growing season temperature will increase steadily by 1.5 $^{\circ}C$ (2020s A2), 3.2 $^{\circ}C$ (2050s A2) and 5.2 $^{\circ}C$ (2080s A2) from the baseline (1971-2000) 19.8 $^{\circ}C$. The average growing season rainfall will change by -3.4 % (2020s A2), 0.0 % (2050s A2) and +16.5 % (2080s A2) from the baseline value 886 mm. Assuming paddy area and cropping pattern remain unchanged the average volumetric irrigation demands were predicted to increase by 5.3 % (2020s A2), 8.1 % (2050s A2) and 2.2 % (2080s A2) from the baseline value 1.159 ${\times}$ $10^6\; m^3$. These projections are different from the previous study by Chung (2009) which used a different GCM and downscaling method and projected decreasing irrigation demands. This indicates that one should be careful in interpreting the results of similar studies.

• Transactions of the Korean Society of Automotive Engineers
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• v.21 no.2
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• pp.45-54
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• 2013

In this paper, a theoretical weight-reduction method was suggested to substitute an underframe material of a box-type bodyshell having cut-outs with an alternative light-weight material. To utilize the material substitution method previously developed for a box-type hybrid bodyshell not having cut-outs, we derived a box-type baseline model without cut-outs which is similar to the stiffness condition of a box-type bodyshell having cut-outs. To do this, the thicknesses of roof and walls of the baseline model were determined such that the deflection of the baseline model under a distributed vertical load condition is equal to the sum of the theoretical section deflections of the original box model with cut-outs. Next, to derive a hybrid bodyshell by under-frame material substitution, the material substitution method for a box-type hybrid bodyshell without cut-outs was applied to the box-type baseline model. Finally, we compared the FE simulation results of the derived hybrid bodyshells having cut-outs for various materials with the theoretical results of the suggested method, and we obtained their good correlations.

• Proceedings of the KSPS conference
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• 2003.10a
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• pp.185-188
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• 2003

In this paper, we construct phonetic GMM for text-independent speaker identification system. The basic idea is to combine of the advantages of baseline GMM and HMM. GMM is more proper for text-independent speaker identification system. In text-dependent system, HMM do work better. Phonetic GMM represents more sophistgate text-dependent speaker model based on text-independent speaker model. In speaker identification system, phonetic GMM using HMM-based speaker-independent phoneme recognition results in better performance than baseline GMM. In addition to the method, N-best recognition algorithm used to decrease the computation complexity and to be applicable to new speakers.

• ETRI Journal
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• v.45 no.6
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• pp.1079-1089
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• 2023

Stroke is one of the leading causes of long-term disability worldwide, placing huge burdens on individuals and society. Further, automatic human activity recognition is a challenging task that is vital to the future of healthcare and physical therapy. Using a baseline long short-term memory recurrent neural network, this study provides a novel dataset of stretching, upward stretching, flinging motions, hand-to-mouth movements, swiping gestures, and pouring motions for improved model training and testing of stroke-affected patients. A MATLAB application is used to output textual and audible prediction results. A wearable sensor with a triaxial accelerometer is used to collect preprocessed real-time data. The model is trained with features extracted from the actual patient to recognize new actions, and the recognition accuracy provided by multiple datasets is compared based on the same baseline model. When training and testing using the new dataset, the baseline model shows recognition accuracy that is 11% higher than the Activity Daily Living dataset, 22% higher than the Activity Recognition Single Chest-Mounted Accelerometer dataset, and 10% higher than another real-world dataset.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.12 no.4
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• pp.357-364
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• 1987

In this paper we consider the performance Analysis of multistage interconnection network, which is major parts of multi-processor system. We review the Hardware configuration of STAR network system using base-line interconnection network and obtain the probability of clustering basing on analytical model. In addition, Instead of Baseline interconnection system, mentioned above, STAR network system using delta network is considered and TWO probability mentioned above is obtained, finally the comparative result is shown in the figure.