• Journal of the Institute of Electronics Engineers of Korea SP
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• v.48 no.5
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• pp.84-95
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• 2011

In this paper, we present a deblocking algorithm that removes grid and staircase noises, which are called "blocking artifacts", occurred in the compressed satellite images. Particularly, the given satellite images are compressed with equal quantization coefficients in row according to region complexity, and more complicated regions are compressed more. However, this approach has a problem that relatively less complicated regions within the same row of complicated regions have blocking artifacts. Removing these artifacts with a general deblocking algorithm can blur complex and undesired regions as well. Additionally, the general filter lacks in preserving the curved edges. Therefore, the proposed algorithm presents an adaptive filtering scheme for removing blocking artifacts while preserving the image details including curved edges using the given quantization step size and content analysis. Particularly, WLFPCA (weighted lowpass filter using principle component analysis) is employed to reduce the artifacts around edges. Experimental results showed that the proposed method outperforms SA-DCT in terms of subjective image quality.

• The Journal of Information Systems
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• v.25 no.4
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• pp.105-119
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• 2016

Purpose The conventional solution methods for production scheduling problems typically focus on the active schedules, which result in short makespans. However, the active schedules are more difficult to generate than the semi active schedules. In other words, semi active schedule based search strategy may help to reduce the computational costs associated with production scheduling. In this context, this paper aims to compare the performances of active schedule based and semi active schedule based search methods for production scheduling problems. Design/methodology/approach Two decoding approaches, active schedule decoding and semi active schedule decoding, are introduced in this paper, and they are used to implement genetic algorithms for classical job shop scheduling problem. The permutation representation is adopted by the genetic algorithms, and the decoding approaches are used to obtain a feasible schedule from a sequence of given operations. Findings The semi active schedule based genetic algorithm requires slightly more iterations in order to find the optimal schedule, while its execution time is quite shorter than active schedule based genetic algorithm. Moreover, the operations of semi active schedule decoding is easy to understand and implement. Consequently, this paper concludes that semi active schedule based search methods also can be useful if effective search strategies are given.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.63-70
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• 2006

In general, a corpus contains lots of linguistic information and is widely used in the field of natural language processing and computational linguistics. The creation of such the corpus, however, is an expensive, labor-intensive and time-consuming work. To alleviate this problem, annotation tools to build corpora with much linguistic information is indispensable. In this paper, we design and implement an annotation tool for establishing a Korean dependency tree-tagged corpus. The most ideal way is to fully automatically create the corpus without annotators' interventions, but as a matter of fact, it is impossible. The proposed tool is semi-automatic like most other annotation tools and is designed to edit errors, which are generated by basic analyzers like part-of-speech tagger and (partial) parser. We also design it to avoid repetitive works while editing the errors and to use it easily and friendly. Using the proposed annotation tool, 10,000 Korean sentences containing over 20 words are annotated with dependency structures. For 2 months, eight annotators have worked every 4 hours a day. We are confident that we can have accurate and consistent annotations as well as reduced labor and time.

• Journal of the Korean Geographical Society
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• v.42 no.4
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• pp.560-581
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• 2007

The purpose of this paper is to present a conceptual framework and a stage of development of trust building and to study the factors affecting on the trust building in economics space. Conceptual framework on trust building in economics space is combined of in the three approaches. The macro(structural and institutional) approach includes normative and regulative factors(laws, norms), and positionality in social and economic systems(beliefs, political ideologies, institutions). The meso(intersubjective) approach contains the personal fronts(expressive factors, social cues, significant symbols) and settings(physical space, intermediary such as technologies & knowledges). The micro(subjective) approach comprises the willingness(internalization of value) and calculation(risk and uncertainties analysis) of economic actors. According to sustainable cooperation among economic actors, trust building to the macro(structural and institutional) level, the meso(intersubjective) level, and the micro(subjective) level develop by stages. The factors such as long-term and repeated interaction, information sharing and reciprocity, interdependence and asset specificity, uncertainty, proximity, and culture & norm of corporate and formal institution are determinants on the trust building across economic actors in economic space.

• Journal of the Institute of Electronics and Information Engineers
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• v.49 no.12
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• pp.64-72
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• 2012

Synchronization including timing recovery, frequency offset compensation, and frame synchronization is most important signal processing block in all wireless/wired communication systems. In most communication systems, synchronization schemes based on training sequences or preambles are used. WLAN standards of 802.11a/g/n released by IEEE are based on OFDM systems. OFDM systems are known to be much more sensitive to frequency and timing synchronization errors than single carrier systems. A loss of orthogonality between the multiplexed subcarriers can result in severe performance degradations. The starting position of the frame and the beginning of the symbol and training symbol can be estimated using correlation methods. Correlation processing functionality is usually complex because of large number of multipliers in implementation especially when the reference signal is non-binary. In this paper, a simple correlation based synchronization scheme is proposed for IEEE 802.11a/g/n systems. Existing property of a periodicity in the training symbols are exploited. Simulation and implementation results show that the proposed method has much smaller complexity without any performance degradation than the existing schemes.

• Journal of Bio-Environment Control
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• v.23 no.1
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• pp.39-42
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• 2014

The objective of this study was to estimate cardinal temperatures for germination of lettuce (Lactuca sativar L.) using bilinear, parabolic, and beta distribution functions. Seeds of lettuce were germinated in a growth chamber at 7 constant temperatures: 10, 14, 16, 20, 24, 28, and $32^{\circ}C$. Four replicates of 100 seeds were placed on two layers of filter paper in a 9 cm petri-dish. Radicle emergence of 1 mm was scored as germination. The time course of germination was modeled using a logistic function. These minimum, optimum, and maximum temperatures were estimated by regression of the inverse of time to 50% germination rate against the temperature gradient. In bilinear function, minimum, optimum, and maximum temperatures were $7.9^{\circ}C$, $23.3^{\circ}C$, and $28.0^{\circ}C$, respectively. In parabolic function, minimum, optimum, and maximum temperatures were $9.7^{\circ}C$, $19.5^{\circ}C$, and $29.4^{\circ}C$, respectively. In beta distribution function, minimum, optimum, and maximum temperatures were $3.7^{\circ}C$, $20.7^{\circ}C$ and $32.0^{\circ}C$, respectively. Minimum, optimum, and maximum ranges of temperatures were $3.7{\sim}9.7^{\circ}C$, $19.5{\sim}23.3^{\circ}C$, and $28.0{\sim}32.0^{\circ}C$, respectively.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.33 no.4
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• pp.1413-1424
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• 2013

Recently, the frequency of severe storms increases in Korea. Severe storms occurring in a short time cause huge losses of both life and property. A considerable research has been performed for the flood control system development based on an accurate stream discharge prediction. A physical model is mainly used for flood forecasting and warning. Physical rainfall-runoff models used for the conventional flood forecasting process require extensive information and data, and include uncertainties which can possibly accumulate errors during modelling processes. ANFIS, a data driven model combining neural network and fuzzy technique, can decrease the amount of physical data required for the construction of a conventional physical models and easily construct and evaluate a flood forecasting model by utilizing only rainfall and water level data. A data driven model, however, has a disadvantage that it does not provide the mathematical and physical correlations between input and output data of the model. The characteristics of a data driven model according to functional options and input data such as the change of clustering radius and training data length used in the ANFIS model were analyzed in this study. In addition, the applicability of ANFIS was evaluated through comparison with the results of HEC-HMS which is widely used for rainfall-runoff model in Korea. The neuro-fuzzy technique was applied to a Cheongmicheon Basin in the South Han River using the observed precipitation and stream level data from 2007 to 2011.

• Journal of Life Science
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• v.20 no.9
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• pp.1345-1352
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• 2010

We investigated the effect of brown-rice vinegar (BRV) ingestion after strenuous Wingate tests on energy substrates during a 2 hr recovery period. For this, seven healthy male adolescents were chosen as subjects. They performed 3 Wingate tests to induce fatigue, after which they ingested brown-rice vinegar (BRV) drink and/or water as a control (CON) after 15 min of the test. Blood was obtained pre-exercise and 30 min, 60 min, and 120 min post-exercise, and blood glucose, lactate, free fatty acids, ammonia, and cortisol were analyzed. After 120 min of recovery period, the 4th Wingate test was conducted to calculate the power recovery ratio of the 3rd and 4th trials. Breathing frequency, oxygen saturation, and heart rate did not show significant changes. Blood glucose level was lower in CON than BRV after 120 min of recovery, and blood lactate and ammonia levels were lower in BRV at 60 and 120 min. The higher free fatty acids were found at 60 and 120 min in BRV. In addition, Wingate power recovery ratio of peak power and peak power/body weight was significantly higher in BRV compared to CON. These results suggested that BRV ingestion after strenuous exercise facilitates fatigue recovery. Therefore, BRV might be effectively used as an ergogenic aid for events in which competitors compete two or more times a day.

• Spatial Information Research
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• v.18 no.4
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• pp.129-140
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• 2010

Large portal sites such as Google, NAVER provide Various services based on the map. Thus, interest and demand of users who want to obtain the region-related information has been increased. And services that combine the regional information with the map are provided currently at the large portal sites. However, the existing services of large portal sites do not provide enough detailed information and are inconvenient because acquisition process of related information is repeated. Therefore, the system that enables users to obtain detailed information related on the specific region synthetically and easily is needed. In this paper, we propose a system model using map interface and knowledge-processing in order to build the system that is useful for acquiring regional information. The model consists of 3-Layers: 'Regional Information Web-Documents Layer', 'Unique Regional Information Layer', and "Map-Interface Layer'. The Integrated Region~Related Information Searching System based on the model is implemented through the following 4-steps: (1) extracting the keywords that represent specific region (2) collecting the related web pages (3) extracting a set of related keywords and computing an association between the keywords (4) implementing a user interface. We verified validity on the model we proposed. knowledge-processing algorithm using affinity matrix, and UI that help users conveniently search by applying the system to region of the Goyang City. This system integrates regional information existing merely individual 'information' and provides users the 'knowledge' that is newly produced and organized. Users can obtain various detailed regional information and easily get related information through this system.

• Journal of the Korea Society of Computer and Information
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• v.16 no.2
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• pp.25-31
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• 2011

Principal component analysis (PCA) is a well-known method for dimensionality reduction and feature extraction. Although PCA has been applied in many areas successfully, it is sensitive to outliers due to the use of sum-square-error. Several variants of PCA have been proposed to resolve the noise sensitivity and, among the variants, improved robust fuzzy PCA (RF-PCA2) demonstrated promising results. RF-PCA2, however, still can fall into a local optimum due to equal initial membership values for all data points. Another reason comes from the fact that RF-PCA2 is based on sum-square-error although fuzzy memberships are incorporated. In this paper, a variant of RF-PCA2 called RF-PCA3 is proposed. The proposed algorithm is based on the objective function of RF-PCA2. RF-PCA3 augments RF-PCA2 with the objective function of PCA and initial membership calculation using data distribution, which make RF-PCA3 to have more chance to converge on a better solution than that of RF-PCA2. RF-PCA3 outperforms RF-PCA2, which is demonstrated by experimental results.