• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.3
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• pp.1-7
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• 2021

The number of new students at many domestic universities is declining. In particular, private universities, which are highly dependent on tuition, are experiencing a crisis of existence. Amid the declining school-age population, universities are striving to fill new students by improving the quality of education and increasing the student employment rate. Recently, there is an increasing number of cases of using the accumulated big data of universities to prepare measures to fill new students. A representative example of this is the analysis of factors that affect student employment. Existing employment-influencing factor analysis studies have applied quantitative models such as regression analysis to university big data. However, since the factors affecting employment differ by major, it is necessary to reflect this. In this paper, the factors affecting employment by major are analyzed using the data of University C and the decision tree model. In addition, based on the analysis results, a roadmap for student employment by major is recommended. As a result of the experiment, four decision tree models were constructed for each major, and factors affecting employment by major and roadmap were derived.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.627-637
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• 2021

This research extends the literature on the effect of board characteristics and ownership structure on audit fees; these factors affect the firm's agency costs and how the auditor assesses various risks, hence the audit efforts and fees. The paper introduces political connections as a determinant of audit fees for the first time in Jordan, where the political connection is prevalent and affects decision making on the Jordanian boards. The sample consists of 109 manufacturing and service firms listed on the Amman Stock Exchange (ASE) over the years 2012-2019. Data is obtained from the ASE and the company's annual reports. Board characteristics are measured by board size, independence, leadership duality, meetings frequency, political connections, and audit committee. Ownership structure was measured by concentration, foreign ownership, and Institutional ownership. The study hypotheses were tested by using Generalized Least Squares regression. The Findings showed that larger boards, politically connected firms, and firms with leadership duality are more likely to pay higher fees. Besides, Firms with greater foreign ownership pay less fees, whereas the rest of the variables are insignificant. Results suggest that political connections play a major role in determining audit fees; this provides a recommendation to policymakers in Jordan to reconsider regulations regarding political connections.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.7
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• pp.3550-3565
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• 2019

This paper proposes a new measurement method for the effective measurement of the 99% occupied bandwidth (OBW) at monitoring stations. Although the OBW measurement of radio signal is recommended by the International Telecommunication Union Radio (ITU-R) with several methods, there still does not exist a clear measurement recommendation or standard for terrestrial DTV signal on-air environment. Modified adjacent channel power ratio (MACPR), which can be applied to 8-VSB (Vestigial Side Band) DTV (Digital Television) signal, is herein defined to verify the results of measurements obtained using the proposed measurement method. MACPR is a proper measuring parameter for determining the measuring area of a monitoring station. From measurement results obtained in real field environment, it has been found that the OBW of 8-VSB DTV signal can be effectively measured in areas where the MACPR value is over 35 dB and when the measurements are repeated more than 600 times in the same reception site. It also has been verified that measured results are within an error range of +/-0.1% compared to results directly obtained at a transmission station. It is expected that the proposed method is able to be employed in order to determine the proper location of monitoring station and provide a reliable OBW measurement procedure for 8-VSB DTV signal on-air environment.

• Steel and Composite Structures
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• v.32 no.3
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• pp.347-359
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• 2019

Modular construction has been increasingly used for mid-to-high rise buildings attributable to the high construction speed, improved quality and low environmental pollution. The individual and repetitive room-sized module unit is usually fully finished in the factory and installed on-site to constitute an integrated construction. However, there is a lack of design guidance on modular structures. This paper mainly focuses on the evaluation of the initial stiffness of corrugated steel plate shears walls (CSPSWs) in container-like modular construction. A finite element model was firstly developed and verified against the existing cyclic tests. The theoretical formulas predicting the initial stiffness of CSPSWs were then derived. The accuracy of the theoretical formulas was verified by the related numerical and test results. Furthermore, parametric analysis was conducted and the influence of the geometrical parameters on the initial stiffness of CSPSWs was discussed and evaluated in detail. The present study provides practical design formulas and recommendations for CSPSWs in modular construction, which are useful to broaden the application of modular construction in high-rise buildings and seismic area.

• Journal of Advanced Navigation Technology
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• v.22 no.6
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• pp.670-674
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• 2018

Social network service (SNS) related data including comments/text, images, videos, blogs, and user experiences contain a wealth of information which can be used to build recommendation systems for various clients' and provide insightful data/results to business analysts. Multimedia data, especially visual data like image and videos are the richest source of SNS data which can reflect particular region, and cultures values/interests, form a gigantic portion of the overall data. Mining such huge amounts of data for extracting actionable intelligence require efficient and smart data analysis methods. The purpose of this paper is to focus on this particular modality for devising ways to model, index, and retrieve data as and when desired.

• Journal of the Society of Naval Architects of Korea
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• v.56 no.2
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• pp.117-127
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• 2019

Vessel's ice speed performances will be verified in ice sea trial but environmental conditions of ice fields are changeable according to the weather condition of ice trial area. Speed performance has to correct in the no wind, wave and current etc. after sea trial. Especially finding ice fields which is exact the same as owner's ice thickness and strength requirements is not easy. Therefore speed correction according to environment condition has to be done after sea trial measurements. Correction methods for ice thickness, ice strength, wave, wind and ship draft, trim, ice drift etc. are checked in ice sea trial based on literature review such as ISO standard, ITTC recommendation, journal papers and proceedings of conferences. Possibility of application for current and ice drift correction in ice field are discussed and measuring schemes and procedures of correction methods are described in this paper. All of correction schemes are calculated for 'Araon' which is ice breaking research vessel with Arctic and Antarctic ice field test results. Analyzed results shows that Araon is satisfied with her official ice speed performance of 3 knots with 10MW power at 1m ice thickness, 570kPa ice flexural strength.

• International Journal of High-Rise Buildings
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• v.7 no.4
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• pp.265-285
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• 2018

This paper presents a state-of-the-art review on the design, research and education aspects of fire safety engineering (FSE) with a particular concern on high-rise buildings. FSE finds its root after Great Fire of Rome in 64 AD, followed by Great London Fire in 1666. The development of modern FSE is continuously driven by industry revolution, insurance community and government regulations. Now FSE has become a unique engineering discipline and is moving towards performance-based design since 1990s. The performance-based fire safety design (PBFSD) involves identification of fire safety goals, design objectives, establishment of performance criteria, and selection of proper solutions for fire safety. The determination of fire scenarios and design fires have now become major contents for PBFSD. To experience a rapid and positive evolution in design and research consistent with other engineering disciplines, it is important for fire safety engineering as a profession to set up a special educational system to deliver the next-generation fire safety engineers. High-rise buildings have their unique fire safety issues such as rapid fire and smoke spread, extended evacuation time, longer fire duration, mixed occupancies, etc., bringing more difficulties in ensuring life safety and protection of property and environment. A list of recommendations is proposed to improve the fire safety of high-rise buildings. In addition, some source information for specific knowledge and information on FSE is provided in Appendix.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.784-786
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• 2016

Recent research has been related to the health of the various systems. In contrast the system are the level insufficient for accurate analysis that the body of the user information and service information. In this paper, in order to solve this problem, we propose a fitness system based on the algorithm for analyzing the body of the user information. Algorithm to analyze the user's body information by analyzing the user's height and weight to calculate the BMI(Body Mass Index) index and BMR(Basal Metabolic Rate) value. The proposed system is considered to be able to give recommendations to the user for the exercise on the basis of the calculated BMI index and BMR value.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2016.10a
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• pp.787-789
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• 2016

Today, need for a development system that provides the data to a chronic disease, and management has emerged. However, for most of the disease management system provides a wide range of data to the user and problem does not provide for important keyword or data existed. In this paper, analyzing the data for a disease through the R Programing it makes like the most relevant keyword in the illness to the user. This study was a system in which only the important parts when the user to manage their disease can be efficiently managed. By utilizing the proposed system to the user it is considered to be Except for unnecessary data or keyword and to be able to see the data and the keyword in need.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.5
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• pp.1649-1665
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• 2021

In view of the low accuracy of the traditional FunkSVD algorithm, and in order to improve the computational efficiency of the algorithm, this paper proposes a parallel algorithm of improved FunkSVD based on Spark (SP-FD). Using RMSProp algorithm to improve the traditional FunkSVD algorithm. The improved FunkSVD algorithm can not only solve the problem of decreased accuracy caused by iterative oscillations but also alleviate the impact of data sparseness on the accuracy of the algorithm, thereby achieving the effect of improving the accuracy of the algorithm. And using the Spark big data computing framework to realize the parallelization of the improved algorithm, to use RDD for iterative calculation, and to store calculation data in the iterative process in distributed memory to speed up the iteration. The Cartesian product operation in the improved FunkSVD algorithm is divided into blocks to realize parallel calculation, thereby improving the calculation speed of the algorithm. Experiments on three standard data sets in terms of accuracy, execution time, and speedup show that the SP-FD algorithm not only improves the recommendation accuracy, shortens the calculation interval compared to the traditional FunkSVD and several other algorithms but also shows good parallel performance in a cluster environment with multiple nodes. The analysis of experimental results shows that the SP-FD algorithm improves the accuracy and parallel computing capability of the algorithm, which is better than the traditional FunkSVD algorithm.