• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.4
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• pp.227-238
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• 2013

Although several studies show close relationships between social capitals and their performances, a little is known about specific social capitals and their effects on organizational culture and behaviour leading to their innovative outcomes within small and medium sized enterprises(: SMEs). This study examines some dimensions of social capitals and their influences on creating innovative culture and employees' behaviour. The importance of these are regarded as an imperative for SMEs to overcome the inequality of financial leverage and competitive power over resources. For the empirical analysis, survey data were collected from 51 domestic SMEs and analyzed by partial least squares(: PLS) that is one of popular structural modeling and multi-variate projection techniques to latent variables. The findings confirm a positive support of social capitals and their influences on the innovative culture and bahaviour. This result implies that managing the capability of social capitals is important for SMEs to develop the innovative culture and bahaviour and create a competitive advantage.

• Journal of Korea Water Resources Association
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• v.53 no.spc1
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• pp.785-795
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• 2020

Recently, the integrated management of the quantity and quality of water was been derived by the Ministry of Environment in Korea. This reconstruction in the national government organization can be recognized as the major politic measure. For this IWRM (Integrated Water Resources Management), it is necessary to be able to fairly distribute, operate and manage water resources in a situation where related techniques are needed to fully support, such as measuring exactly the demand and supply of water resources. The reason why IWRM is difficult, despite the development of related technologies, is because the management entities are highly diverse and their interests are much complicated. Thus, this study is tried to suggest specific improvement for current policies by benchmarking the KPX (Korea Power Exchange). In the field of water management as similar to the electric industry, there is an essential need for a working-level organization that can manage, control, monitor, and regulate water resources with practical and plenipotentiary control like the non-profit organization, KPX. Such time has come for decisive policy changes through benchmarking the structure, system, productivity, and challenges of the electricity industry in the water policy.

• International Journal of Computer Science & Network Security
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• v.22 no.10
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• pp.374-388
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• 2022

Cloud computing has been one of the most critical technology in the last few decades. It has been invented for several purposes as an example meeting the user requirements and is to satisfy the needs of the user in simple ways. Since cloud computing has been invented, it had followed the traditional approaches in elasticity, which is the key characteristic of cloud computing. Elasticity is that feature in cloud computing which is seeking to meet the needs of the user's with no interruption at run time. There are traditional approaches to do elasticity which have been conducted for several years and have been done with different modelling of mathematical. Even though mathematical modellings have done a forward step in meeting the user's needs, there is still a lack in the optimisation of elasticity. To optimise the elasticity in the cloud, it could be better to benefit of Machine Learning algorithms to predict upcoming workloads and assign them to the scheduling algorithm which would achieve an excellent provision of the cloud services and would improve the Quality of Service (QoS) and save power consumption. Therefore, this paper aims to investigate the use of machine learning techniques in order to predict the workload of Physical Hosts (PH) on the cloud and their energy consumption. The environment of the cloud will be the school of computing cloud testbed (SoC) which will host the experiments. The experiments will take on real applications with different behaviours, by changing workloads over time. The results of the experiments demonstrate that our machine learning techniques used in scheduling algorithm is able to predict the workload of physical hosts (CPU utilisation) and that would contribute to reducing power consumption by scheduling the upcoming virtual machines to the lowest CPU utilisation in the environment of physical hosts. Additionally, there are a number of tools, which are used and explored in this paper, such as the WEKA tool to train the real data to explore Machine learning algorithms and the Zabbix tool to monitor the power consumption before and after scheduling the virtual machines to physical hosts. Moreover, the methodology of the paper is the agile approach that helps us in achieving our solution and managing our paper effectively.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.10
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• pp.59-65
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• 2007

Recently, ubiquitous sensor network(USN) techniques have been applied to electric power facility management. This paper dealt with the designed and fabricated ubiquitous sensors which monitor transformers and lightning arresters installed in overhead distribution systems. The sensors consist of a 8-[bit] microprocessor unit, a wireless communication nodule specified in IEEE 802.15.4, and associated electronics. A Rogowski coil was fabricated to measure load of transformer and surge current without saturation having good linearity up to 1000[A]. A zero-phase current transformer with a high relative permeability of $10^5$ at 180[Hz] was used to detect small leakage current of $50[{\mu}A]{\sim}1[mA]$ flowing lightning arrester, and the frequency bandwidth of the module is ranges from 12[Hz] to 1.24[kHz] at -3[dB].

• The Transactions of the Korean Institute of Power Electronics
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• v.23 no.4
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• pp.247-255
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• 2018

This paper proposes a transformer design of a direct cell-to-cell active cell balancing circuit with a multi-winding transformer for battery management system (BMS) applications. The coupling coefficient of the multi-winding transformer and the output capacitance of MOSFETs significantly affect the balancing current transfer efficiency of the cell balancing operation. During the operation, the multi-winding transformer stores the energy charged in a specific source cell and subsequently transfers this energy to the target cell. However, the leakage inductance of the multi-winding transformer and the output capacitance of the MOSFET induce an abnormal energy transfer to the non-target cells, thereby degrading the transfer efficiency of the balancing current in each cell balancing operation. The impacts of the balancing current transfer efficiency deterioration are analyzed and a transformer design methodology that considers the coupling coefficient is proposed to enhance the transfer efficiency of the balancing current. The efficiency improvements resulting from the selection of an appropriate coupling coefficient are verified by conducting a simulation and experiment with a 1 W prototype cell balancing circuit.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.20 no.6
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• pp.15-21
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• 2010

In the recent years, various researches about the signal processing have been presented to improve the performance of power analysis. Among these signal processing techniques, the research about the signal compression is not enough than a signal alignment and a noise reduction; even though that can reduce considerably the computation time for the power analysis. But, the existing compression method can sometimes reduce the performance of the power analysis because those are the unsophisticated method not considering the characteristic of the signal. In this paper, we propose the new PCA (principal component analysis)-based signal compression method, which can block the loss of the meaningful factor of the original signal as much as possible, considering the characteristic of the signal. Also, we prove the performance of our method by carrying out the experiment.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2011.04a
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• pp.465-465
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• 2011

Rolls-Royce is a global company producing advanced power systems for use on land, at sea and in the air. In order to develop competitive products and services, Rolls-Royce invests in technology, infrastructure and capability with much of the research carried out in a global network of University Technology Centres, such as the UTC in Thermal management at Pusan National University. Heat exchangers and thermal management play a critical role in today's gas turbine engines, maintaining the fuel and oil temperatures within the correct operational range. Future products are likely to place an increased duty on the thermal management system and thus require advances in heat exchanger design, installation and manufacturing. Heat exchangers further have the potential to play a vital role in Advanced Cycle Gas Turbine products. The Intercooled and recuperated WR21 marine gas turbine engine recently entered service with the Royal Navy and is delivering very attractive fuel burn in service. The development of an advanced cycle aero-engine is a significantly greater challenge, requiring better understanding of compact and light weight heat exchanger surfaces, novel installations and ducting systems and may required novel manufacturing techniques to achieve the volume, weight and cost necessary to realise a viable advanced cycle gas turbine aero-engine.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.39 no.1
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• pp.25-30
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• 2016

It is critical to forecast the maximum daily and monthly demand for power with as little error as possible for our industry and national economy. In general, long-term forecasting of power demand has been studied from both the consumer's perspective and an econometrics model in the form of a generalized linear model with predictors. Time series techniques are used for short-term forecasting with no predictors as predictors must be predicted prior to forecasting response variables and containing estimation errors during this process is inevitable. In previous researches, seasonal exponential smoothing method, SARMA (Seasonal Auto Regressive Moving Average) with consideration to weekly pattern Neuron-Fuzzy model, SVR (Support Vector Regression) model with predictors explored through machine learning, and K-means clustering technique in the various approaches have been applied to short-term power supply forecasting. In this paper, SARMA and intervention model are fitted to forecast the maximum power load daily, weekly, and monthly by using the empirical data from 2011 through 2013. $ARMA(2,\;1,\;2)(1,\;1,\;1)_7$ and $ARMA(0,\;1,\;1)(1,\;1,\;0)_{12}$ are fitted respectively to the daily and monthly power demand, but the weekly power demand is not fitted by AREA because of unit root series. In our fitted intervention model, the factors of long holidays, summer and winter are significant in the form of indicator function. The SARMA with MAPE (Mean Absolute Percentage Error) of 2.45% and intervention model with MAPE of 2.44% are more efficient than the present seasonal exponential smoothing with MAPE of about 4%. Although the dynamic repression model with the predictors of humidity, temperature, and seasonal dummies was applied to foretaste the daily power demand, it lead to a high MAPE of 3.5% even though it has estimation error of predictors.

• Journal of Environmental Impact Assessment
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• v.9 no.4
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• pp.277-290
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• 2000

The purpose of this study is to identify the problems of environmental impact assessment(EIA) and to suggest new EIA technology. The problems of EIA in Korea can be summarized as follows. First, the EIA does not reflect the impact of policy, plan and program on environment. Second, the project EIA does not consider the cumulative impacts such as additive impacts, synergistic impacts, threshold/saturation impacts, induced and indirect impacts, time-crowded impacts, and space-crowded impacts. Third, the EIA techniques in Korea are not standardized. Finally, the present EIA suggests only alternatives to reduce adverse impacts. To solve above-mentioned problems, the development of new EIA technology is essential. First, the new EIA technology should be developed toward pollution prevention technology and comprehensive and integrated environmental management technology. Second, new fields of EIA for pollution prevention contain strategic environmental assessment, cumulative impacts assessment, socio-economic impact assessment, cyber EIA and EIA technology necessary after the reunification of Korean Peninsula. Third, EIA technology for integrated environmental management contains the development of integated environment assessment system and the development of packaged EIA technology. The EIA technology for integrated environmental assessment system contains (1) development of integrated impact assessment technology combining air/water quality model, GIS and remote sensing, (2) integrated impact assessment of EIA, traffic impact assessment, population impact assessment and disaster impact assessment. (3) development of integrated technology combining risk assessment and EIA (4) development of integrated technology of life cycle assessment and EIA, (5) development of integrated technology of spatial planning and EIA, (6) EIA technology for biodiversity towards sustainable development, (7) mathematical model and GIS based location decision techniques, and (8) environmental monitoring and audit. Furthermore, there are some fields which need packaged EIA technology. In case of dam development, urban or industrial complex development, tourist development, landfill or combustion facilities construction, electric power plant development, development of port, road/rail/air port, is necessary the standardized and packaged EIA technology which considers the common characteristics of the same kind of development project.

• Journal of Advanced Navigation Technology
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• v.18 no.2
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• pp.158-164
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• 2014

For transmitting the ultra-high speed optical signals with better performance, the techniques to suppress or mitigate the signal distortion due to group velocity dispersion and optical Kerr effects are required. Dispersion management (DM), optical phase conjugation, and the combination of these two are promising techniques to compensate for the signal distortion. However, the fixed length of single mode fiber (SMF) and the fixed residual dispersion per span (RDPS) usually used in these optical links restricts flexible link configuration. The goal of this paper is to investigate the possibility of the flexible configurations of the ultra-high and long-haul optical transmission systems by using the artificial and the random distribution of SMF length and RDPS of each fiber spans consisted of the optical link. It is confirmed that the proposed link configurations should be one of the methods suitable for implementing the flexible optical transmission systems, however which depend on other link parameters, such as the averaged RDPS, and the launch power.