• Journal of the Korean association of regional geographers
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• v.4 no.2
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• pp.65-77
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• 1998

One of the fundamental, important preconditions for effective teaching of geography is to collect a variety of picture data available for class and to manage the data systematically. The purpose of this study is to present one method about how to supply basic picture data available for class of Korean geography for the high school program to teachers in service and how to collect, manage and utilize the data. A total of 233 picture data related to contents of the textbook of Korean Geography have been gathered through this study, and a database has been constructed for the data. Directories were generated for individual units of the textbook, and the collected picture data was stored in the image file of each directory. This data was recorded in a CD and attached as an appendix. Since the primary purpose of this study is to suggest one method, the picture data in a database for the present study is just a fraction of lots of data available for class of Korean geography. If the user persistently enlarges and manages data based on the results of this study, the data will become a good instructional aid. The picture data can be printed over the transparent film and used for class by using the overhead protector (OHP), or it can be also used as a remote self-study tool through the computer telecommunications network (e.g., LAN or INTERNET. etc,). Most desirable, however, is to develop teachers' own method by taking account of separate units of the textbook or diverse educational environments.

• Journal of Engineering Education Research
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• v.24 no.2
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• pp.20-28
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• 2021

In 2020, the COVID-19 pandemic has brought dramatic changes in the field of engineering education. Contrary to the traditional engineering education emphasis on content-oriented, design-based, hands-on, experimental, and field experience, most of engineering classes in 2020 had to be undertaken remotely online. However, it has not been explored how professors and students perceive about such a shift in engineering education. The aim of the current study was to investigate the perceptions of professors and students on online classes in engineering colleges during spring Semester 2020. Questionnaire data were collected from 100 professors and 4,152 students in the college of engineering. The results of this study were as following: Students were less satisfied with the online classes than professors. The online lecture method that students were most satisfied with was the recorded lecture. This is likely due to the fact that the recorded lectures can be repeated multiple times anytime, anywhere. Moreover, the experimental classes, which conventionally has more of an emphasis on the hands-on experience, also had to be conducted remotely, showing even lower satisfaction among students. Most of professors reported that the average hours they spent on preparing for online lecture increased compared to face-to-face class. Both professors and students preferred in-person exam as a desirable method of end-of-semester assessment for grading. The results of the current study have important implications for the improvement of online course environments. It is important for professors to design a structured class suitable for online education and understand the challenges students encounter during online classes. Also, professors should communicate more openly about their expectations and rubrics for class goals and assignments. Schools also needs to make effort to provide the support for the internet environment of students.

• The Journal of the Korea Contents Association
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• v.11 no.12
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• pp.969-975
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• 2011

The purpose of this study is to investigate the effects of learners' self-motivational attitudes, use of instructional function, and understanding of successful learning on achievement in college e-learning classes. The study analyzed 297 college students' questionnaire about their internet learning attitudes based on how they understand e-learning and use various internet functions for their learning achievement. After factor analyses, the results found that there were three major factors such as self-motivational attitude, use of instructional function, and understanding of successful learning out of 15 survey items. Multiple regression showed that the self-motivational factor affects the learning achievement with overall three factors analyses. This result indicates that college e-learning classes should focus on the analysis of learners' self-motivational issues in college e-learning classes. This study suggest that the relationship between learners' e-learning experience and learning achievement should be examined in the near future to show how it affects on learners e-learning class management and their achievement.

• Journal of Internet Computing and Services
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• v.15 no.1
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• pp.63-71
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• 2014

Currently many non-traditional application areas such as artificial intelligence and web databases require advanced modeling power than the existing relational data model. In those application areas, object-oriented database (OODB) is better data model since an OODB can providemodeling power as grouping similar objects into class, and organizing all classes into a hierarchy where a subclass inherits all definitions from its superclasses. The purpose of this paper is to develop an OODB concurrency control scheme dealing with multiple inheritance. The proposed scheme, called Multiple Inheritance Implicit Locking (MIIL), is based on so-called implicit locking. In the proposed scheme, we eliminate redundant locks that are necessary in the existing implicit locking scheme. Intention locks are required as the existing implicit locking scheme. In this paper, it is shown that MIIL has less locking overhead than implicit locking does. We use only OODB inheritance hierarchies, single inheritance and multiple inheritance so that no additional overhead is necessary for reducing locking overhead.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.5
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• pp.111-117
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• 2017

The National Competency Standards (NCS) was designed to implement a competence-based society and solve the problem of inconsistency between the industrial field and education, training, and certification system. This study designed and developed the Korean NCS core vocational competence system, in accordance with the NCS, as an infrastructure to solve fundamental problems such as re-education and the social costs that are incurred in the workplace. Further, this study designed and developed standard indicators to evaluate the technical performance of the system for the global advancement of the Korean NCS core vocational competence system. The NCS core vocational competence system has been developed as an appropriate response type for multiple devices such as computers, tablet PCs, and cellular phones. For the global advancement of the Korean NCS core vocational competence system, this study designed and developed 10 performance evaluation indicators in accordance with 10 global standards, such as linkage-target operating system, interface protocol, packet format, encryption, class component, simultaneous access number, supervisor-to-testtaker response speed, server-to-admin response speed, auto-recovery speed for test answers, and real-time answer transmission speed.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.2
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• pp.41-45
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• 2019

In this paper, we propose the interference cancellation scheme of end-to-end method algorithm for power line communication (PLC) systems in smart grid. The proposed scheme estimates the channel noise information of receiver by applying a deep learning model at the receiver. Then, the estimated channel noise is updated in database. In the modulator, the channel noise which reduces the power line communication performance is effectively removed through interference cancellation technique. As an impulsive noise model, Middleton Class A interference model was employed. The performance is evaluated in terms of bit error rate (BER). From the simulation results, it is confirmed that the proposed scheme has better BER performance compared to the theoretical model based on additive white Gaussian noise. As a result, the proposed interference cancellation with deep learning improves the signal quality of PLC systems by effectively removing the channel noise. The results of the paper can be applied to PLC for smart grid and general communication systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.6
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• pp.121-126
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• 2018

IEEE 802.1 TSN TG is developing standards for end-to-end delay bounds and zero packet loss based on Ethernet technology. We focus on packet forwarding techniques. TSN packet forwarding techniques can be classified into Synchronous and Asynchronous framework. Synchronous approach allocates fixed time period for a class, yet is complex for large networks. Asynchronous approach provides delay guarantee by regulator-scheduler pair, yet is unnecessarily complex, too. We propose network components for TSN Asynchronous architecture, which remove the complexity of maintaining flow state for regulation decisions. Despite such a simplicity, the proposed architecture satisfies the TSN's delay requirements provided the limited high priority traffic's maximum packet length.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.100-103
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• 2019

Due to the fourth industrial revolution called 'fusion and connection', interest in 'high connectivity society' and 'highland society' is increasing, and related objects are not limited to automation and connected cars. The Internet of Things is the main concern of the 4th Industrial Revolution and it is expected to play an important role in establishing the basis of the next generation mobile communication service. Several domestic and foreign companies have been studying various types of LPWANs for the construction of the Internet based on things, and there is Semtech's LoRaWAN technology as representative. LoRaWAN is a long-distance, low-power network designed to manage a large number of devices and sensors, with communications from hundreds to thousands to thousands of devices and sensors. In this paper, we analyze the optimum node capacity of gateway for maximum performance while reducing resource waste in using LoRaWAN.

• International journal of advanced smart convergence
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• v.9 no.1
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• pp.193-201
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• 2020

The main objective of this study is to investigate the impact of additional modalities on the performance of emotion recognition using speech, facial expression and physiological measurements. In order to compare different approaches, we designed a feature-based recognition system as a benchmark which carries out linear supervised classification followed by the leave-one-out cross-validation. For the classification of four emotions, it turned out that bimodal fusion in our experiment improves recognition accuracy of unimodal approach, while the performance of trimodal fusion varies strongly depending on the individual. Furthermore, we experienced extremely high disparity between single class recognition rates, while we could not observe a best performing single modality in our experiment. Based on these observations, we developed a novel fusion method, called parametric decision fusion (PDF), which lies in building emotion-specific classifiers and exploits advantage of a parametrized decision process. By using the PDF scheme we achieved 16% improvement in accuracy of subject-dependent recognition and 10% for subject-independent recognition compared to the best unimodal results.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.30 no.4
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• pp.631-646
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• 2020

The government is pursuing a policy to remove plug-ins for public and private websites to create a convenient Internet environment for users. In general, financial institution websites that provide financial services, such as banks and credit card companies, operate fraud detection system(FDS) to enhance the stability of electronic financial transactions. At this time, the installation software is used to collect and analyze the user's information. Therefore, there is a need for an alternative technology and policy that can collect user's information without installing software according to the no-plug-in policy. This paper introduces the device fingerprinting that can be used in the standard web environment and suggests a guideline to select from various techniques. We also propose a user authentication model using device fingerprints based on machine learning. In addition, we actually collected device fingerprints from Chrome and Explorer users to create a machine learning algorithm based Multi-class authentication model. As a result, the Chrome-based Authentication model showed about 85%~89% perfotmance, the Explorer-based Authentication model showed about 93%~97% performance.