• International conference on construction engineering and project management
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• 2013.01a
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• pp.267-273
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• 2013

Early design phase energy modeling is used to provide the design team with first order of magnitude feedback about the impact of various building configurations. For better energy-conscious and sustainable building design and operation, the construction of BIM data interoperability for energy performance assessment in the early design phase is important. The purpose of this study is to suggest construction of BIM data interoperability for energy performance assessment based on BIM. To archive this purpose, the authors have investigated advantage of BIM-based energy performance assessment through comparison with traditional energy performance assessment and suggested requirement for construction of open BIM environment such as BIM data creation, BIM data software practical use, BIM data application and verification. In addition, the authors have suggested BIM data interoperability and BIM energy property mapping method focused on materials.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.22 no.2
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• pp.63-79
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• 2011

This study tried to provide users with customized services by applying the CRM theory of the MyLibrary functions of the academic library system. The first data were collected through documentary survey and homepage survey, and case study of domestic and overseas college libraries was performed and 3 systems among academic library systems were selected to conduct a survey with their librarians and users of the academic libraries. It was found that librarians in charge of each function of services didn't much utilize information data of users created in the MyLibrary functions. As for an improvement method, it was suggested that systematic management to raise recognition on CRM and utilize it as feedback data is required in order to provide high quality services as well as customized information services to users based on data created in MyLibrary.

• Journal of Broadcast Engineering
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• v.19 no.4
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• pp.510-520
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• 2014

By adopting the MAC(Media Access Control) protocol which enables to pack multiple MPDUs(MAC-level Protocol Data Units) into a single PPDU(Physical Layer Protocol Data Unit), IEEE 802.11n WLAN supports high throughput. Up to now, there have been a lot of existing channel information-based A-MPDU schemes dynamically determining the number of MSDUs according to the wireless channel condition information which is sent from the receiver to sender. However, the channel information-based scheme has a serious drawback having a high system overhead due to the frequent channel feedback information. To reduce the system overhead, the proposed BA-base dynamic A-MPDU scheme simply chooses the number of MSDUs to be retransmitted by not the frequent channel feedback information but the BA signal representing whether MPSUs belonging to the A-MPDU are received or not. Through NS-2(Network Simulator-2), we found that the proposed scheme had higher throughput and lower packet error rate than the existing fixed A-MPDU scheme.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.2
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• pp.190-197
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• 2011

In industrial distributed control systems, sensors collect data from the physical environment periodically and transmit them to the actuators, which process the control operations based on the received data. For the effective operation of the control systems, the data transmitted by the sensors has to be delivered to the actuators reliably within the deadline, and if the message reception rate of the actuators becomes lower than a threshold, then the performance of the control systems drops greatly. This paper suggests a message routing protocol to transmit periodic messages reliably in a distributed control system based on wireless sensor networks. For reliable message transmission, the proposed protocol selects a routing path whose end-to-end message reception rate is the highest before transmitting data messages. The proposed protocol has the capability of maintaining a target message reception rate for each flow. To maintain the required target reception rate, each destination monitors the actual message reception rate periodically and transmits a feedback message to the source if it drops below the target reception rate. On receiving the feedback message, the source tries to find a new path which can satisfy the target rate. The performance of the proposed protocol has been evaluated using simulation and compared with other protocols in terms of the message reception rate, the message delay and delay jitter, and so on. The simulation results show that the proposed protocol has a higher message reception rate and comparable message delay and delay jitter to other protocols. The simulation results also show that the proposed protocol has an ability to adapt well to the dynamic network traffic change.

• Journal of the Korean Society for Aeronautical & Space Sciences
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• v.49 no.10
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• pp.871-877
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• 2021

Aircraft defects are important matters directly related to the operation of the aircraft and the life of the pilot. The defects in the mission software that occur during aircraft control seriously affect the pilot's mission performance and safety. Therefore, the organization in charge of aircraft development or software defects are reinforced in the process to identify and eliminate defects in the early stages of development, and a lot of labor and time are spent, but due to the nature of the mission software, strong functional coupling with other avionics and high complexity, so there are restrictions on the identification and removal of software defects through the existing test method. This study analyzes the effect of securing mission software integrity and reducing test cost through data integrity verification by developing a tool that automates the verification of expected value of feedback data among communication data of mission computer interlocking equipment.

• Knowledge Management Research
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• v.16 no.4
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• pp.69-87
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• 2015

Given the huge number of data produced by its users, SNS is a great source of customer insights. Since viral trends in SNS reflect customers' direct feedback, companies can draw out highly meaningful business insights when such data is effectively analyzed and managed. However, while the importance of understanding SNS big data keeps growing, the methods for analyzing atypical data such as SNS postings for business insights over product has not been well studied. This study aims to demonstrate the way to exploit topic modeling method to support marketing strategy generation and therefore leverage business process. First, we conducted topic modeling analysis for twitter data of Apple and Samsung smartphones. Then we comparatively examined the analysis results to draw meaningful market insights about each smartphone product. Finally, we draw out a strategic marketing recommendation for each smartphone brand based on the findings.

• Journal of the Korean Data and Information Science Society
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• v.18 no.2
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• pp.375-384
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• 2007

As teachings that use the ICT are more popular, many studies on the dynamic geometry environment(DGE) are under way. An important factor emphasized in the studies is to practical use learning activities of learners. In this study, we first define the learning history data in DGE. Second we develop a prototype of the DGE that is able to collect and analyze the learning history data automatically. The environment enables not only to grasp leaning history but also to create and manage new learning objects.

• Journal of The Korean Association For Science Education
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• v.42 no.6
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• pp.611-619
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• 2022

The purpose of this study is to explore the possibility of applying big data analysis to provide appropriate feedback to students using evaluation data in science education at a time when interest in educational data mining has recently increased in education. In this study, we use the evaluation data of 2,576 students who took 24 questions of the national assessment of educational achievement. And we use K-means cluster analysis as a method of unsupervised machine learning for clustering. As a result of clustering, students were divided into six clusters. The middle-ranking students are divided into various clusters when compared to upper or lower ranks. According to the results of the cluster analysis, the most important factor influencing clusterization is academic achievement, and each cluster shows different characteristics in terms of content domains, subject competencies, and affective characteristics. Learning motivation is important among the affective domains in the lower-ranking achievement cluster, and scientific inquiry and problem-solving competency, as well as scientific communication competency have a major influence in terms of subject competencies. In the content domain, achievement of motion and energy and matter are important factors to distinguish the characteristics of the cluster. As a result, we can provide students with customized feedback for learning based on the characteristics of each cluster. We discuss implications of these results for science education, such as the possibility of using this study results, balanced learning by content domains, enhancement of subject competency, and improvement of scientific attitude.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2005.09a
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• pp.101-106
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• 2005

Recently, as the size of genetic knowledge grows faster, automated analysis and systemization into high-throughput database has become hot issue. One essential task is to recognize and identify genomic entities and discover their relations. However, ambiguity of name entities is a serious problem because of their multiplicity of meanings and types. So far, many effective techniques have been proposed to analyze documents. Yet, accuracy is high when the data fits the model well. The purpose of this paper is to design and implement a document classification system for identifying entity problems using text/data mining combination, supplemented by rich data mining algorithms to enhance its performance. we propose RTP ost system of different style from any traditional method, which takes fault tolerant system approach and data mining strategy. This feedback cycle can enhance the performance of the text mining in terms of accuracy. We experimented our system for classifying RB-related documents on PubMed abstracts to verify the feasibility.

• Journal of Information Technology Services
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• v.9 no.1
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• pp.113-125
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• 2010

Recently, a smart space with Ubiquitous Environment is expanding rapidly due to the development of Ubiquitous Sensor Network. Therefore, more appropriate and intelligent services of the context awareness system is being required. The previous context awareness system can provide a service to the user through the inference only on the current situation. But, it does not handle certain situation properly when the system provides abnormal result. Also it does not have any proper method of generating reliable semantic data from sensed raw data. In this paper, we are trying to solve the problems as the following approaches. First, the system recognizes abnormal result and corrects it by learning feedback from the user. Second, we suggest a method of converting sensed data into more reliable semantic data. Third, we build the system based on an Ontological context model that is capable of interoperability and reusability. Therefore, the context awareness system of our study can enhance the previous system that can generate more reliable context data, can provide more effective inference method, and can provide more intelligent system structure.