• Korean Business Review
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• v.19 no.2
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• pp.141-154
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• 2006

Mentoring as a human resources development program is being reconceptualized because of the rapidly shifting work environment which has been recently focused on the necessity of knowledge management. That is, new mentoring network theory as a reconceptualization of mentoring is structured by researchers who have related social network theory and mentoring and they have discovered that the development of individual and organizational is built by the relationships of multiple selves. In their paper, they have asserted that an individual's developmental stage is an important antecedent to the nature of mentoring and developmental networks that are possible. Further, they are suggesting that mentoring developmental network is a key tool for learning, development, and successful performance outcomes in challenging assignments. This paper aims to describe the next empirical research plan that will investigate the developmental stage of teachers as an antecedent of mentoring network. An introduction and background to the research will be explained to provide a conceptual framework for the next study.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.39C no.9
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• pp.841-851
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• 2014

Wireless technologies sharing the same frequency band and operating in the same environment often interfere with each other, causing severe decrease in performance. In this paper, we propose a algorithm based on traffic scheduling techniques that mitigate interference between different wireless systems operating in the 2.4-GHz industrial, medical, and scientific band. In particular, we consider IEEE 802.11 wireless local area networks (WLANs) and Bluetooth data transfer, showing that the proposed algorithms can work when the two systems are able to exchange information as well as when they operate independently of one another. Results indicate that the proposed algorithm remarkably mitigate the interference between the WLAN and Bluetooth technologies at the expense of a small additional delay in the data transfer.

• Clean Technology
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• v.21 no.1
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• pp.62-67
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• 2015

We have developed a versatile method for the preparation of chemically linked graphene/multi-walled carbon nanotubes (MWNTs) hybrid materials via simple acid-catalyzed dehydration reaction between graphene oxide (GO) and amine-functionalized MWNTs (af-MWNTs). In this condition, ketone (-C=O) groups in GO and primary amine (-NH₂) moieties in af-MWNTs readily react to form imine (-C=N-) linkage. The chemical structures of graphene/MWNTs hybrid materials have been investigated using various microscopic and spectroscopic measurements. As a result of the synergetic effects of hybrid materials such as improved surface area and the superior structural restoration of graphitic networks, the hybrid materials demonstrate improved capacitance with excellent long-term stability. Furthermore, controlled experiments were conducted to optimize the weight ratio of graphene/MWNTs in hybrid materials. The highest capacitance of 132.4 F/g was obtained from the GM7.5 material, in which the weight ratio between graphene and MWNTs was adjusted to 7.5/1, in 1M KOH electrolyte at a scan rate of 100 mV/s.

• Journal of Convergence for Information Technology
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• v.10 no.8
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• pp.15-22
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• 2020

The 4th industrial revolution and the rapid change in the data environment revealed technical limitations in the existing relational database(RDB). As a new analysis method for unstructured data in all fields such as IDC/finance/insurance, interest in graph database(GDB) technology is increasing. The graph database is an efficient technique for expressing interlocked data and analyzing associations in a wide range of networks. This study extended the existing RDB to the GDB model and applied machine learning algorithms (pattern recognition, clustering, path distance, core extraction) to detect new abnormal signs. As a result of the performance analysis, it was confirmed that the performance of abnormal behavior(about 180 times or more) was greatly improved, and that it was possible to extract an abnormal symptom pattern after 5 steps that could not be analyzed by RDB.

• Journal of Korea Port Economic Association
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• v.26 no.2
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• pp.99-118
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• 2010

This objective of this study is to thoroughly analyze the policies of international organizations and major advanced countries relevant to the realization of Green port To construct Green ports, there first must be competition to build such ports in sustainable, fixed quantities. Second, there is a great need for cooperation and support networks made binding by mutual agreements on ship recycling. Third, there is a need for scientific research on responses to changes in environmental regulations and on environmental issues. Today, the majority of the world's ports use gasoline or electric energy, and improving capacities for self-sufficiency through development of new and renewable energy is judged to be a pressing task. The conditions for an eco-friendly port is that it must be an important center for economic and industrial activity, and valuable as a site where people live and work, with residences and work places existing in close proximity.

• Journal of Digital Convergence
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• v.17 no.12
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• pp.197-202
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• 2019

In line with the era of the 4th Industrial Revolution, 5G technology has become common technology, and 5G technology is evaluated as a technology that minimizes the speed and response speed compared to 4G using technologies such as network slicing and ultra-multiple access. 5G NR stands for 5G mobile communication standard, and network slicing cuts the network into parallel connections to optimize the network. In addition, the risk of hacking is increasing as data is processed in the base station unit. In addition, since the number of accessible devices per unit area increases exponentially, there is a possibility of base station attack after hacking a large number of devices in the unit area. To solve this problem, this study proposes the introduction of quantum cryptography and 5G security standardization.

• KEPCO Journal on Electric Power and Energy
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• v.6 no.3
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• pp.259-269
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• 2020

With the proposal-agreement procedure, RSTP can reduce the network recovery time to 400 ms or less in the case of 40 bridges. While the legacy RSTP reverts the previous agreement at the bridge with the alternate port role in the ring during the fault recovery, a new position based fast fault recovery procedure is proposed in this paper to guarantee a single proposal-agreement transaction which can provide more faster recovery. By knowing the relative position of the faulty link or bridge in hops, the bridge on the middle of the ring can complete the recovery procedure without revert. The performance of proposed procedure is numerically calculated and verified by simulation and the result shows that the recovery time can be reduced up to 100 ms, which is 1/4 times of the legacy RSTP.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.13 no.4
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• pp.283-292
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• 2020

Artificial intelligence, which is one of the representative images of the 4th industrial revolution, has been highly recognized since 2016. This paper analyzed domestic paper trends for 'Artificial Intelligence', 'Machine Learning', and 'Deep Learning' among the domestic papers provided by the Korea Academic Education and Information Service. There are approximately 10,000 searched papers, and word count analysis, topic modeling and semantic network is used to analyze paper's trends. As a result of analyzing the extracted papers, compared to 2015, in 2016, it increased 600% in the field of artificial intelligence, 176% in machine learning, and 316% in the field of deep learning. In machine learning, a support vector machine model has been studied, and in deep learning, convolutional neural networks using TensorFlow are widely used in deep learning. This paper can provide help in setting future research directions in the fields of 'artificial intelligence', 'machine learning', and 'deep learning'.

• Journal of Electrical Engineering and Technology
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• v.13 no.1
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• pp.513-520
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• 2018

Since Paris Climate Change Conference in 2015, many policies to reduce the emission of greenhouse gas have been accelerating, which are mainly related to renewable energy resources and micro-grid. Presently, the technology development and demonstration projects are mostly focused on diversifying the power resources by adding wind turbine, photo-voltaic and battery storage system in the island-type small micro-grid. It is expected that the large-scaled micro-grid projects based on the regional district and town/complex city, e.g. the block type micro-grid project in Daegu national industrial complex will proceed in the near future. In this case, the economic cost or the carbon emission can be optimized by the efficient operation of energy mix and the appropriate construction of electric and heat supplying facilities such as cogeneration, renewable energy resources, BESS, thermal storage and the existing heat and electricity supplying networks. However, when planning a large residential town or city, the concrete plan of the energy infrastructure has not been established until the construction plan stage and provided by the individual energy suppliers of water, heat, electricity and gas. So, it is difficult to build the efficient energy portfolio considering the characteristics of town or city. This paper introduces an energy mix optimization(EMO) method to determine the optimal capacity of thermal and electric resources which can be applied in the design stage of the real large-scaled residential town or city, and examines the feasibility of the proposed method by applying the real heat and electricity demand data of large-scale residential towns with thousands of households and by comparing the result of HOMER simulation developed by National Renewable Energy Laboratory(NREL).

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.8
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• pp.1743-1750
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• 2003

DC motor requires a rotor speed sensor for accurate speed control. The speed sensors such as resolvers and encoders are used as a speed detector, but they increase cost and size of the motor and restrict the industrial drive applications. So in these days, many papers have reported in the sensorless operation of DC motor〔3­5〕. This paper presents a new sensorless strategy using neural networks〔6­8〕. Neural network has three layers which are input layer, hidden layer and output layer. The optimal neural network structure was tracked down by trial and error, and it was found that 4­16­1 neural network structure has given suitable results for the instantaneous rotor speed. Also, learning method is very important in neural network. Supervised learning methods〔8〕 are typically used to train the neural network for learning the input/output pattern presented. The back­propagation technique adjusts the neural network weights during training. The rotor speed is gained by weights and four inputs to the neural network. The experimental results were found satisfactory in both the independency on machine parameters and the insensitivity to the load condition.