• The Transactions of the Korean Institute of Power Electronics
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• v.6 no.2
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• pp.149-157
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• 2001

A nonlinear speed control for a permanent magnet synchronous motor (PMSM) using a simple disturbance estimation technique is presented. By using a feedback linearization scheme, the nonlinear motor model can be linearized in a controllable canonical form, and the desired speed dynamics can be obtained based on the linearized model. This technique, however, gives an undesirable output performance under the mismatch of the system parameters and load conditions. To cancel disturbance by parameter variation, the controller parameters will be estimated by using a disturbance observer theory where the disturbance torque and flux linkage are estimated. since only the two reduced order observers are used for the parameter estimations, the observer designs are considerably simple and the additional load for computation of the controller is negligibly small. The proposed control scheme is implemented on a PMSM using DSP TMS320C31 and the effectiveness is verified through the comparative simulations and experiments.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.26 no.11A
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• pp.1812-1819
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• 2001

In this paper, it investigated the permitted limit of the analog nonideality for the SOSOC Σ-Δ modulator design which is satisfied with 1 [MHz] signal bandwidth and 12-bit resolution in the OSR=25. Firstly, it get the SOSOC Σ-Δ modulator model and gain coefficient which is suitable in low voltage for the Σ-Δ modulator design which is satisfied with the specification in the supply voltage 3.3 [Vl. And it provided the performance prediction of the Σ-Δ modulator and the permitted limit of the nonideality by adding the performance degradation facts of the Σ-Δ modulator such as the finite gain of the amplifier, the SR, the closed-loop pole, the switch ON resistance and the capacitor mismatch to the ideal Σ-Δ modulator model. When designed the Σ-Δ modulator which is satisfied with the specification by the base above, it will be able to predict the performance of the Σ-Δ modulator and the guide for the specification of the circuit which composes the Σ-Δ modulator.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.23 no.6
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• pp.29-41
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• 2020

Wild pollinators provide important pollination services for crops. However, their geographical ranges and impact on pollination services have not been fully explored within the scope of Korean agricultural land. This study aims to identify spatial supply-demand mismatches across orchard fields in the context of assessing pollination service risk. We first used National Ecosystem Survey data and a species distribution model (MaxEnt) to develop the geographic range of each of 32 wild pollinators belonging to three families (Diptera, Hymenoptera, and Lepidoptera). We then summed the modeled presence probability of each species to obtain a measure of spatially explicit pollinator richness. This modeled richness, defined as pollination supply, was compared with the summed area of orchard fields at the municipal boundary level to identify areas with supply-demand mismatches. The study found that Lepidoptera showed the highest species richness (8.3±1.5), followed by Hymenoptera (4.3±0.8) and Diptera (3.5±0.8) species. Median orchard area was 1.5 ㎢ (range of 0-176.7 ㎢) among 250 municipal regions in South Korea. The municipal regions were divided into three categories (tertiles) of low, middle, and high pollination supply and demand according to, respectivley, average polliator richness and orhard area. Finally, we found that 55 municipal regions (accounting for 49% of national orchard land) potentially faced high risk of pollination deficits, 81 regions (48% of national orchard land) faced intermediate risk, and 63 regions faced low risk (3% of national orchard land). In conclusion, this study revealed significant mismatch between pollination supply and demand and developed risk assessment map will guide our future efforts on pollinator habitat conservation and monitoring to conserve crop pollination services.

• Journal of the Korea Society of Computer and Information
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• v.27 no.8
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• pp.123-133
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• 2022

In this paper, we propose a Leveled Micro-Degree Job Competency Certification Model that considers the level of the job based on the job defined in the NCS. There is a mismatch of manpower due to the problem of university education that cannot keep up with the rapidly changing technological environment caused by the 4th Industrial Revolution. The Nano-Degree and Micro-Degree systems designed to solve this problem are used for job competency certification of cyber security personnel. NCS sub-categorized job field is defined as Micro-Degree and detailed job by ability unit is defined as Nano-Degree, the level of the ability unit defined by level is equally applied to the Micro-Degree. And it is a system that certifies the job competency corresponding to the degree-based university academic background. By applying this system to the curriculum of Cyber Security School, Yeungnam University College, we proposed a method to configure the Nano-Degree course based on NCS duties. The method proposed in this paper can be used as a method for verifying job competency of Nano-Degree and Micro-Degree, which are recently introduced by many universities.

• Journal of the Korean association of regional geographers
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• v.12 no.5
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• pp.614-630
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• 2006

Improved estimates of populations at risk for quick and effective response to natural and man-made disasters require spatial disaggregation of zonal population data because of the spatial mismatch problem in areal units between census and impact zones. This paper implements a dasymetric surface model to facilitate spatial disaggregation of the population of a census block group into populations associated with each constituent pixel and evaluates the performance of the surface-based spatial disaggregation model visually and statistically. The surface-based spatial disaggregation model employed geographic information systems (GIS) to enable dasymetric interpolation to be guided by satellite-derived land use and land cover data as additional information about the geographic distributor of population. In the spatial disaggregation, percent cover based empirical sampling and areal weighting techniques were used to objectively determine dasymetric weights for each grid cell. The dasymetric population surface for the Atlanta metropolitan area was generated by the surface-based spatial disaggregation model. The accuracy of the dasymetric population surface was tested on census counts using the root mean square error (RMSE) and an adjusted RMSE. The errors related to each census track and block group were also visualized by percent error maps. Results indicate that the dasymetric population surface provides high-precision estimates of populations as well as the detailed spatial distribution of population within census block groups. The results also demonstrate that the population surface largely tends to overestimate or underestimate population for both the rural and forested and the urban core areas.

• Journal of Practical Engineering Education
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• v.15 no.3
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• pp.671-679
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• 2023

This study aims to establish an evaluation model by quantifying the evaluation index as a follow-up study to the development of evaluation index for work-study parallel learning companies. An evaluation model was established by verifying the 2nd level components based on the quantitative factors of the learning company, the qualitative factors, the competency factors of the person in charge, and the competency factors of the learning workers, which are the highest-level components derived from previous study. For the evaluation of a learning company, an AHP survey was conducted with experts in charge of the company consulting to derive important factors that determine the quality of on-site education and training, and the evaluation model of the learning company was completed and grouped by calculating the weight between evaluation items proceeded. Work-study parallel program was promoted as a key policy to resolve the mismatch between industrial sites and school education and realize a competency-centered society, and as of December 2022, 16,664 companies participated in the training. Learning companies play a very important role as education and training supply organizations that conduct field training. It is expected that the support and consulting plan for each level of learning companies according to the evaluation model presented in this study will be used as basic data to improve the quality of work-study parallel program.

• Journal of Environmental Impact Assessment
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• v.32 no.4
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• pp.203-213
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• 2023

The AERMOD model was the most used, accounting for 89.0%, based on the analysis of the environmental impact assessment reports published in the Environmental Impact Assessment Information Support System (EIASS) between 2021 and 2022. The mismatch of versions between AERMET and AERMOD was found to be 25.3%. There was the operational time discrepancy of 50.6% from industrial complexes, urban development projects between used in the model and applied in estimating pollutant emissions. The results of applying various versions of the AERMET and AERMOD models to both area sources and point sources in both simple and complex terrain in the Gunsan area showed similar values after AERMOD version 12 (15181). Emissions are assessed as 24-hour operation, and the predicted concentration in both simple and complex terrain when using the variable emission coefficient option that applies an 8-hour daytime operation in the model is lowered by 37.42% ~ 74.27% for area sources and by 32.06% ~ 54.45% for point sources. Therefore, to prevent the error in using the variable emission coefficient, it is required to clearly present the emission calculation process and provide a detailed explanation of the composition of modeling input data in the environmental impact assessment reports. Also, thorough reviews by special institutions are essential.

• Economic and Environmental Geology
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• v.36 no.3
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• pp.213-223
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• 2003

We estimated the Moho depth of Korean Peninsula from gravity anomalies and digital elevation model. The satellite radar altimetry-derived global free-air gravity model was used to ensure the homogeneity in both data and frequency domains of the original data. Two different methods were implemented to calculate the Moho depth; the wavenumber correlation analysis (Kim et al., 2000a) and the power spectrum analysis. The former method calculates depth-to-the-Moho by correlating topographic gravity effect with free-air gravity anomaly in the wavenumber domain under the assumption that the study area is not isostatically compensated. The latter one, on the other hand, considers the different density layers (i.e., Conrad and Moho), using complete Bouguer gravity anomaly in the Frequency domain of the Fourier transform. The correlation coefficient of the two Moho model is 0.53, and methodology and numerical error are mainly responsible for any mismatch between the two models. In order to integrate the two independentely-estimated models, we applied least-squares adjustment using the differenced depth. The resultant model has mean and standard deviation Moho depths of 32.0 km and 2.5 km with (min, max) depths of (20.3, 36.6) kms. Although this result does not include any topographic gravity effect, however, the validity of isostasy and the role of local stress field in the study area should be further studied.

• Journal of Korea Technology Innovation Society
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• v.10 no.1
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• pp.22-46
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• 2007

This article introduces a recent innovation in Korea's human resources development policy in the SW sector. Facing serious problems in cultivating SW engineers such as a mismatch in supply and demand of SW workers, shortage of globally competitive SW professionals, and insufficient education and training of university graduates, the Korean government has decided to adopt a new paradigm in national SW engineering education, based on supply chain management (SCM) in manufacturing. SCM has been a major component of the corporate competitive strategy, enhancing organizational productiveness and responsiveness in a highly competitive environment. It weighs improving competitiveness of the supply chain as a whole via long-term commitment to supply chain relationships and a cooperative, integrated approach to business processes. These characteristics of SCM are believed to provide insight into a more effective IT education and university-industry collaboration. On the basis of the SCM literature, a framework for industry-oriented SW human resources development is designed, and then applied in the case of nurturing computer-software engineers in Korea. This approach is expected to fumish valuable implications not only to Korean policy makers, but also to other countries making similar efforts to enhance the effectiveness and flexibility in human resources development. The construction of SCM-based SW HRD model is first trial to apply SCM into SW HRD field. The model is divided into three kinds of primary activities and two kinds of supportive activities in the field of value chain such as SW HRD Council, SW demand and supply plan establishment and the integration of SW engineering capabilities that contribute the reduction of the skill and job matching through SW HR demand and supply collaboration.

• Database Research
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• v.34 no.3
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• pp.137-147
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• 2018

A key to a well-performing human activity recognition (HAR) system through machine learning technique is the availability of a substantial amount of labeled data. Collecting sufficient labeled data is an expensive and time-consuming task. To build a HAR system in a new environment (i.e., the target domain) with very limited labeled data, it is unfavorable to naively exploit the data or trained classifier model from the existing environment (i.e., the source domain) as it is due to the domain difference. While traditional machine learning approaches are unable to address such distribution mismatch, transfer learning approach leverages the utilization of knowledge from existing well-established source domains that help to build an accurate classifier in the target domain. In this work, we propose a transfer learning approach to create an accurate HAR classifier with very limited data through the multitask neural network. The classifier loss function minimization for source and target domain are treated as two different tasks. The knowledge transfer is performed by simultaneously minimizing the loss function of both tasks using a single neural network model. Furthermore, we utilize the unlabeled data in an unsupervised manner to help the model training. The experiment result shows that the proposed work consistently outperforms existing approaches.