• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1187-1189
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• 1997

Currently, EMS(Energy Management System) database is implemented by relational concept but, It is hard to describe the characteristic of power system data which require real time management and composite type. This paper present the way how to design conceptual schema for EMS database using object-oriented concept which is free to describe composite data type and support inheritance concept.

• Geomechanics and Engineering
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• v.23 no.1
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• pp.51-59
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• 2020

In this paper, the WEKA platform was used to mine and analyze measured data of floor failure depth and a prediction system of floor failure depth was developed with Java. Based on the standardization and discretization of 35-set measured data of floor failure depth in China, the grey correlation degree analysis on five factors affecting the floor failure depth was carried out. The correlation order from big to small is: mining depth, working face length, floor failure resistance, mining thickness, dip angle of coal seams. Naive Bayes model, neural network model and decision tree model were used for learning and training, and the accuracy of the confusion matrix, detailed accuracy and node error rate were analyzed. Finally, artificial neural network was concluded to be the optimal model. Based on Java language, a prediction system of floor failure depth was developed. With the easy operation in the system, the prediction from measured data and error analyses were performed for nine sets of data. The results show that the WEKA prediction formula has the smallest relative error and the best prediction effect. Besides, the applicability of WEKA prediction formula was analyzed. The results show that WEKA prediction has a better applicability under the coal seam mining depth of 110 m~550 m, dip angle of coal seams of 0°~15° and working face length of 30 m~135 m.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.10
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• pp.85-96
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• 2022

CEO duality and its impact on firm performance represent one of the most contentious issues in both academia and business. This study, therefore, aims to examine the moderating role of CEO duality in the relationship between intellectual capital Efficiency (human, structural, relational, Capital Employed, and Innovation) and firm performance (earnings per share and Tobin's Q) among Jordanian companies. The study sample consists of services listed companies on Amman Stock Exchange. The study used panel data for the period 2014-2018 with a sample size of 230 observations. SPSS software was used to analyze the collected data. The regression results indicate a significant relationship between, IC and firm performance. When CEO Duality is incorporated into the model as a moderator, there is an increase in the R² by 7.9%. The findings from this study expand the theoretical underpinning of corporate governance research by identifying the performance implications of CEO duality within the Jordanian context. It also contributes significantly to the literature review about the current status of the practices taken in the intellectual capital components efficiency among companies listed on the Amman Stock Exchange. Findings from this study also provide contributions to the concerned policymakers such as the Ministry of Finance, Securities Commission, and Amman Stock Exchange in Jordan, to improve the current policies related to intellectual capital efficiency.

• Korean Journal of Remote Sensing
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• v.37 no.1
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• pp.69-84
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• 2021

Awareness of boats is a main issue in areas of fishery management, illegal fishing, and maritime traffic, etc. For the awareness, Automatic Identification System (AIS) and Vessel-Pass System (V-PASS) have been widely used to collect the boat-related information. However, only using these systems makes it difficult to collect the accurate information. Recently, satellite-based data has been increasingly used as a cooperative system. In 2015, U.S. National Oceanic and Atmospheric Administration (NOAA) developed a boat detection algorithm using Visible Infrared Imaging Radiometer Suite (VIIRS) Day & Night Band (DNB) data. Although the detections have been widely utilized in many publications, it is difficult to estimate the night-time fishing boats immediately. Particularly, it is difficult to estimate the threshold due to the lunar irradiation effect. This effect must be corrected to apply a single specific threshold. In this study, the moon phase was considered as the main frequency of this effect. Considering the moon phase, relational expressions are derived and then used as offsets for relative correction. After the correction, it shows a significant reduction in the standard deviation of the threshold compared to the threshold of NOAA. Through the correction, this study can set a constant threshold every day without determination of different thresholds. In conclusion, this study can achieve the detection applying the single specific threshold regardless of the moon phase.

• Proceedings of the Korea Information Processing Society Conference
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• 2008.11a
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• pp.325-327
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• 2008

In electrical industry, classification methodology has been an important issue for analyzing power consumption patterns. It has many applications including decisions on energy purchasing, load switching as well as helping in infrastructure development. Our aim in this work is to classify the electrical section and find potentially non-safe electrical sections. For this purpose, we use Emerging Patterns based classification. The classification method uses the aggregate score of emerging patterns to build classifier. The proposed methodology was applied to a set of electrical section data of the Korea power. The test data and relational electricity information and knowledge are supported by Korea Electric Power Research Institute (KEPRI).

• Korean Journal of Construction Engineering and Management
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• v.23 no.3
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• pp.45-55
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• 2022

BIM models allow building spaces to be instantiated and recognized as unique objects independently of model elements. These instantiated spaces provide the required semantics that can be leveraged for building code checking, energy analysis, and evacuation route analysis. However, theses spaces or rooms need to be designated manually, which in practice, lead to errors and omissions. Thus, most BIM models today does not guarantee the semantic integrity of space designations, limiting their potential applicability. Recent studies have explored ways to automate space allocation in BIM models using artificial intelligence algorithms, but they are limited in their scope and relatively low classification accuracy. This study explored the use of Graph Convolutional Networks, an algorithm exclusively tailored for graph data structures. The goal was to utilize not only geometry information but also the semantic relational data between spaces and elements in the BIM model. Results of the study confirmed that the accuracy was improved by about 8% compared to algorithms that only used geometric distinctions of the individual spaces.

• Fire Science and Engineering
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• v.28 no.2
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• pp.82-90
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• 2014

According to recent government's 3.0 operating paradigm for the opening and sharing of public information, relationship between humidity, temperature and fire occurrence were analyzed using the data in National Weather Service and National Emergency Management Agency. In order to analyze the relationships between humidity, temperature and fire occurrence, hourly frequency of fire occurrence compared with humidity and temperature ranges was suggested as an analysis method. Tendencies of fire occurrence frequencies were examined through this and characteristics of detailed attributes could be statistically identified. Results about hourly frequencies of fire occurrence by classifying the humidity ranges in each region showed increasing frequencies in all areas where the humidity is lower. Hourly frequencies of fire occurrence according to temperature ranges were identified to be similar in each area as well. In addition, characteristics of objects' attributes were analyzed including types of fire, igniting source of fire, initial complex, reasons of fire occurrence, and distinctive directions were suggested. Suggested method in this paper could be practically used when suggesting the frequency in each category in fire occurrence statistics of National Fire Information System.

• Nuclear Engineering and Technology
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• v.25 no.4
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• pp.552-560
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• 1993

In this study, the detailed fuel assembly stress analysis model to evaluate the structural integrity for seismic and blowdown accidents is developed. For this purpose, as the first step, the program MAIN which identifies the worst bending mode shaped fuel assembly(FA) in core model is made. And the finite element model for stress calculation of FA components is developed. In the model the fuel rods (FRs) and the guide thimbles are modelled by 3-dimensional beam elements, and the spacer grid spring is modelled by a linear and relational spring. The constraints come from the results of the program MAIN. The stress analysis of the 16$\times$16 type FA under arbitary seismic load is performed using the developed program and modelling technique as an example. The developed stress model is helpful for the stress calculation of FA components for seismic and blowdown loads to evaluate the structural integrity of FA.

• Spatial Information Research
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• v.19 no.6
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• pp.11-18
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• 2011

Urban space is the main contributor of greenhouse gas emissions, a primary cause of global warming. In order to reduce greenhouse gas emissions, planning at a city-level is necessary. The aim of this research is to develop a carbon emission model which can be used to create and manage urban spaces. In order to achieve this aim, the following methodologies were utilized. First, urban planning criteria related to population, landuse, and activity level were selected through theoretical speculation. Second, carbon dioxide emission was calculated based on electricity, gas energy, heating, petroleum, and water usages. Third, Seoul was selected as a case study city, and a carbon emission model was developed through a relational analysis between Seoul's urban planning criteria and carbon emissions. Thus far, various efforts have been made to respond to climate changes in urban spaces, but these have been limited to analyzing contributing factors in terms of their total amounts of carbon emissions in the entire city. However, the carbon emission model of this study is derived from urban planing criteria at a detailed scale. This sets our study apart from other studies by demonstrating a specific model in a local setting which can be utilized for lowering carbon emissions at a city level.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.24 no.5
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• pp.326-332
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• 2012

In this paper, error analyses on the calculation of offshore wind speed have been conducted using HeMOSU-1 data to develop offshore wind energy in Yeonggwang sea of Korea and onshore observed wind data in Buan, Gochang and Yeonggwang for 2011. Offshore wind speed data at 98.69 m height above M.S.L is estimated using relational expression induced by linear regression analysis between onshore and offshore wind data. In addition, estimated offshore wind speed data is set at 87.65 m above M.S.L using power law wind profile model with power law exponent(0.115) and its results are compared with the observed data. As a result, the spatial adjustment error are 1.6~2.2 m/s and the altitude adjustment error is approximately 0.1 m/s. This study shows that the altitude adjustment error is about 5% of the spatial adjustment error. Thus, long term observed data are needed when offshore wind speed was estimated by onshore wind speed data. because the conversion of onshore wind data lead to large error.