• Journal of IKEEE
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• v.22 no.3
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• pp.672-679
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• 2018

Recently, microgrid (MG) has been proposed as one of the most critical solutions for various energy problems. For the optimal and economic operation of MGs, it is very important to forecast the load profile. However, it is not easy to predict the load accurately since the load in a MG is small and highly variable. In this paper, we propose an artificial neural network (ANN) based method to predict the energy use in campus buildings in short-term time series from one hour up to one week. The proposed method analyzes and extracts the features from the historical data of load and temperature to generate the prediction of future energy consumption in the building based on sparsified K-means. To evaluate the performance of the proposed approach, historical load data in hourly resolution collected from the campus buildings were used. The experimental results show that the proposed approach outperforms the conventional forecasting methods.

• Journal of Biomedical Engineering Research
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• v.32 no.4
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• pp.336-344
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• 2011

This article describes a new recognition algorithm using correlation coefficient for intelligent wheelchair to avoid collision for elderly or disabled people. The correlation coefficient can be used to represent the relationship of two different areas. The algorithm has three steps: Firstly, we extract an edge vector using the Histogram of Oriented Gradients(HOG) which includes gradient information and unique magnitude for each cell. From this result, the correlation coefficients are calculated between one cell and others. Secondly, correlation coefficients are used as the weighting factors for normalizing the HOG cell. And finally, these features are used to classify or detect variable and complicated shapes of two wheelers using Adaboost algorithm. In this paper, we propose a new feature vectors which is calculated by weighted cell unit to classify with multiple view-based shapes: frontal, rear and side views($60^{\circ}$, $90^{\circ}$ and mixed angle). Our experimental results show that two wheeler detection system based on a proposed approach leads to a higher detection accuracy than the method using traditional features in a similar detection time.

• Journal of Internet Computing and Services
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• v.7 no.4
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• pp.11-22
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• 2006

Software product-lines methodology is the software development paradigm to build the target system by customizing the variable part of software assets according to requirements. To attain this, the commonalities and variabilities of the system family should be modeled explicitly at early stage. Although the researches on general software product-lines are active, the researches on component-based real-time embedded software product-lines are rather inactive. In this paper a code generation system to support the functional variabilities via feature model and generate the code for synchronization via state model is proposed to increase the productivity of the development of the real-time embedded software product-lines.

• Journal of Fashion Business
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• v.14 no.5
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• pp.158-175
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• 2010

Culture means a lifestyle realizing a definite object or ideal. Each local special culture is enormous in value as a local culture inheritance. If it is developed a local culture products representing local culture, it can perform an important role on one of the strategies for revitalizing local economy. One of the typical cultures in Kyung-Nam is the Gaya culture. The most characteristic of the Gaya culture is powerful iron culture and lots of cultural properties have been founding as relics. Judging from a lot of iron relics, we can figure out a high level of iron manufacturing technology. I studied focussing on the plasticity of Gaya relics and collected base materials for developing local cultural goods, using the motif of Gaya culture with excellent aesthetic consciousness. I classfied Gaya relics into a crown style, jewelry, harnessry, weapons, armor, earthenware, and considered its characteristic of the plastic arts, based on the preceding studies and document data. There exists natural, moderate, polished, indigenous, simple, rhythmical, delicate, florid, technical, symbolical, strong, diverse, naive beauty in the plastic characteristic of Gaya relics. Gaya culture with the special excellence of aesthetic resources, is worthy enough to be recreated as local cultural goods. Variable and special cultural fashion-products with the distinctive feature of Gaya culture need to be developed without delay.

• Proceedings of the Korean Society for Agricultural Machinery Conference
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• 1996.06c
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• pp.773-779
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• 1996

Dried oak mushroom have complex and various visual features. Grading and sorting of dried oak mushrooms has been done by the human expert. Though actions involved in human grading looked simple, a decision making underneath the simple action comes from the result of the complex neural processing of the visual image. Through processing details involved in human visual recognition has not been fully investigated yet, it might say human can recognize objects via one of three ways such as extracting specific features or just image itself without extracting those features or in a combined manner. In most cases, extracting some special quantitative features from the camera image requires complex algorithms and processing of the gray level image requires the heavy computing load. This fact can be worse especially in dealing with nonuniform, irregular and fuzzy shaped agricultural products, resulting in poor performance because of the sensitiveness to the crisp criteria or specific ules set up by algorithms. Also restriction of the real time processing often forces to use binary segmentation but in that case some important information of the object can be lost. In this paper, the neuro net based real time recognition algorithm was proposed without extracting any visual feature but using only the directly captured raw gray images. Specially formated adaptable size of grids was proposed for the network input. The compensation of illumination was also done to accomodate the variable lighting environment. The proposed grading scheme showed very successful results.

• The Korean Journal of Applied Statistics
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• v.30 no.5
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• pp.793-808
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• 2017

We compare various variable screening methods on multiclass classification problems when the data is ultrahigh-dimensional. Two different approaches were considered: (1) pairwise extension from binary classification via one versus one or one versus rest comparisons and (2) direct classification of multiclass responses. We conducted extensive simulation studies under different conditions: heavy tailed explanatory variables, correlated signal and noise variables, correlated joint distributions but uncorrelated marginals, and unbalanced response variables. We then analyzed real data to examine the performance of the methods. The results showed that model-free methods perform better for multiclass classification problems as well as binary ones.

• Korean Journal of Ecology and Environment
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• v.41 no.spc
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• pp.1-10
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• 2008

We patterned water quality of agricultural reservoirs according to the differences of six physico-chemical environmental factors (TN, TP, DO, BOD, COD, and SS) using four different ordination methods: Principal Components Analysis (PCA), Detrended Correspondence Analysis (DCA), Nonmetric Multidimensional Scaling (NMS), and Isometric Feature Mapping (Isomap). The data set was obtained from the water quality monitoring networks operated by the Ministry of Agriculture and Forestry and the Ministry of Environments. Chlorophyll-${\alpha}$ displayed the highest correlation with COD, followed by TP, BOD, SS, and TN (p<0.01), while negatively correlated with altitude and bank height of the reservoirs (p<0.01). Although four different ordination methods similarly patterned the reservoirs according to the gradient of nutrient concentration, PCA and NMS appeared to be the most efficient methods to pattern water quality of reservoirs based on the explanation power. Considering variable scores in the ordination map, the concentration of nutrients was positively correlated with Chl-${\alpha}$, while negatively correlated with altitude and bank height. These ordination methods may help to pattern agricultural reservoirs according to their water quality characteristics.

• The Korean Journal of Cytopathology
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• v.18 no.1
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• pp.74-80
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• 2007

Parathyroid tumors may be difficult to distinguish from thyroid follicular lesions, especially when a tumor is nonfunctioning. We report here two cases of asymptomatic parathyroid carcinoma preoperatively misdiagnosed as thyroid follicular lesions, and one case of parathyroid adenoma showing hyperparathyroidism, and review the cytologic features favoring the diagnosis of parathyroid neoplasm. The cytologic findings that are characterized by clean background, monomorphic small cells, cohesive three-dimensional papillary clusters, small tight clusters with scattered naked nuclei, and well-defined clear cytoplasm favor a diagnosis for the parathyroid lesions. Cytologic findings such as macrofollicular structure, presence of colloid and macrophages, and presence of perivacuolar cytoplasmic granules on May-Grunwald-Giemsa stain support a diagnosis of a thyroid follicular lesion. The cytomorphology of parathyroid tumors is so variable that the distinction from a thyroid lesion cannot be based on the presence or absence of a single feature only but on the cytologic features as a whole.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.8 no.5
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• pp.1817-1827
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• 2014

As a new type of wireless network, Ad hoc network does not depend on any pre-founded infrastructure, and it has no centralized control unit. The computation and transmission capability of each node are limited. In this paper, a self-updating one-time password mutual authentication protocol for Ad hoc network is proposed. The most significant feature is that a hash chain can update by itself smoothly and securely through capturing the secure bit of the tip. The updating process does not need any additional protocol or re-initialization process and can be continued indefinitely to give rise to an infinite length hash chain, that is, the times of authentication is unlimited without reconstructing a new hash chain. Besides, two random variable are added into the messages interacted during the mutual authentication, enabling the protocol to resist man-in-the-middle attack. Also, the user's identity information is introduced into the seed of hash chain, so the scheme achieves anonymity and traceability at the same time.

• Proceedings of the KIEE Conference
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• 1988.07a
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• pp.898-901
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• 1988

Up to now, using adaptive control method, Identification deals with system whose entire state variables and prameters are accessible for measurement. In practical situations, all the state variables cannot be measured and it is impossible to directly apply since the parameters of the system are unknown. Therefore, in this paper, using only input-output data, such a model of the system is not available since the parameters of the system are unknown. this leads to the concept of an adptive observer in which both the parameters and the state variable of the system are identified simultaniously. Lyapunov's direct method and Kalman-Yakubovich (K-Y) lemma are employed to ensure the stability of this schemes. The feature is that the signal and adaptive gain which is generated from filter is imposed upon feedback vector and then state variables and the unknown parameters can be identified. To show the usefulness of the proposed schemes, computer simulation result of unknown second-order system shows the effectiveness of the proposed schems.