• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1362-1376
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• 2016

A cloud computing system can be characterized by the provision of resources in the form of services to third parties on a leased, usage-based basis, as well as the private infrastructures maintained and utilized by individual organizations. To attain the desired reliability and energy efficiency in a cloud data center, trade-offs need to be carried out between system performance and power consumption. Resolving these conflicting goals is often the major challenge encountered in the design of optimization strategies for cloud data centers. The work presented in this paper is directed towards the development of an Energy-efficient and Performance-aware Cloud System equipped with strategies for dynamic switching of optimization approach. Moreover, a platform is also provided for the deployment of a Wind Farm CMS (Condition Monitoring System) which allows ubiquitous access. Due to the geographically-dispersed nature of wind farms, the CMS can take advantage of the cloud's highly scalable architecture in order to keep a reliable and efficient operation capable of handling multiple simultaneous users and huge amount of monitoring data. Using the proposed cloud architecture, a Wind Farm CMS is deployed in a virtual platform to monitor and evaluate the aging conditions of the turbine's major components in concurrent, yet isolated working environments.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.19 no.11
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• pp.326-331
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• 2018

Evaporative humidification using a humidifying element is used widely for the humidification of a building or a data center. The performance of a humidifying element is commonly expressed as the humidification efficiency, which is assumed to be independent of the air temperature or humidity. To verify this assumption, a series of tests were conducted under two air conditions - data center ($25^{\circ}C$ DBT, $15^{\circ}C$ WBT) and commercial building ($35^{\circ}C$ DBT, $21^{\circ}C$ WBT) - using humidifying elements made from cellulose/PET and changing the frontal air velocity from 1.0 m/s to 4.5 m/s. Three samples having a 100 mm, 200 mm, or 300 mm depth were tested. The results showed that the humidification efficiency is dependent on the air condition. Indeed, even dehumidification occurred at the inlet of the humidifying element at the air condition of commercial building. This suggests that a proper thermal model should account for the inlet area, where the amount of moisture transfer may be different from the other part of the humidification element. As the depth of the element increased from 100 mm to 200 mm, the humidification efficiency increased by 29%. With further increases to 300 mm, it increased by 42%. On the other hand, the pressure drop also increased by 47% and 86%.

• Journal of the Korean Society for Precision Engineering
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• v.28 no.9
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• pp.1025-1031
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• 2011

Take-out robots used for handling of the plastic parts manufactured with the injection mold are usually the gantry type that consists of long and thin links, The performance of the take-out robot is determined by the speed of the motion and the positioning accuracy to grab the part out of the mold, As the speed of the robot increases the flexure in the links of the take-out robot becomes more significant and it results in more residual vibration, The residual vibration deteriorates the positioning accuracy and compels the operator to slow down the motion of the robot. The typical method to reduce the vibration in the robot requires stiffening the links and/or slowing down the robot, Vibration control could achieve the desired performance without increasing the manufacturing cost or the operation cost that would be incurred otherwise, Considering the point-to-point nature of the task to be performed by the take-out robot the time-delay command (or input) shaping filter approach would be the most effective control method to be adopted among a few available control schemes. In this paper a direct adaptive command shaping filter (ACSF) algorithm has been modified and applied to design the optimal command shaping filters for various configuration of the take-out robot. Optimal filters designed by ACSF algorithm have been implemented on a take-out robot and the effectiveness of the designed filters in terms of vibration suppression has been verified for multiple positions of the robot.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.5 no.11
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• pp.2035-2051
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• 2011

Theoretical Bit Error Rate (BER) and channel capacity analysis are always of great interest to the designers of wireless communication systems. At the center of such analyses people are often encountered with a high-dimensional multiple integrals with quite complex integrands. Conventional Gaussian quadrature is inefficient in handling problems like this, as it tends to entail tremendous computational overhead, and the principal order of its error term increase rapidly with the dimension of the integral. In this paper, we propose a new approach to calculate complex multi-fold integrals based on the number theory. In contrast to Gaussian quadrature, the proposed approach requires less computational effort, and the principal order of its error term is independent of the dimension. The effectiveness of the number theory based approach is examined in BER and capacity analyses for practical systems. In particular, the results generated by numerical computation turn out in good match with that of Monte-Carlo simulations.

• KIEE International Transaction on Systems and Control
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• v.2D no.2
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• pp.65-71
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• 2002

In this paper, an experiment for the active vibration control of a cantilever beam uses electromagnet as an actuator and uses a laser sensor to measure the position of the bending beam, constituting a non-contacting control system. A mathematical model of the overall system is derived to analytically design an appropriate controller. Dynamic equations of the electromagnetic actuator and the beam are combined to find the transfer function from the actuator to the sensor. The effectiveness of the obtained model is verified by various experiments and an improper PID controller is designed based on the obtained model. According to analysis, the coefficient of the derivative controller is the most important parameter for handling the performance and the stability margin of the control system. The experimental results of the active control system are compared with those of the open loop system.

• Journal of Navigation and Port Research
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• v.41 no.6
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• pp.373-380
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• 2017

Operational errors caused by human factors, which is the major cause of marine accidents, include lack of knowledge, misunderstanding knowledge, and inadequate procedures. Recently, the type of propulsion mounted on KCG cutters has been diversified. In particular, the water jet propulsion unit, which was mainly installed in small boats, have been gradually expanded to medium and large size Coast Guard cutters, reaching 50% of the total. Axes types are divided into 2 to 4, and the bucket types are divided into Double Reverse Bucket(DRB) and Single Reverse Bucket(SRB); in these, the backward and steering control methods are completely different. Diversification of these operating systems can increase factors causing human error by the ships' operators. However, there is a lack of research on the maneuvering methods, considering the inherent active characteristics of each type of water jet. In this paper, we analyze the sideway method suitable for the condition of Coast Guard Exclusive wharf without assistance, based on the astern performance of each type. Then, a ship handling simulator was used for the experiment; they compared and verified through interviews of captains.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.117-120
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• 2001

In this work, we propose a new method of extracting and weighting representative keywords(RKs) from a few documents that might interest a user. In order to extract RKs, we first extract candidate terms and then choose a number of terms called initial representative keywords (IRKS) from them through fuzzy inference. Then, by expanding and reweighting IRKS using term co-occurrence similarity, the final RKs are obtained. Performance of our approach is heavily influenced by effectiveness of selection method of IRKS so that we choose fuzzy inference because it is more effective in handling the uncertainty inherent in selecting representative keywords of documents. The problem addressed in this paper can be viewed as the one of calculating center of document vectors. So, to show the usefulness of our approach, we compare with two famous methods - Rocchio and Widrow-Hoff - on a number of documents collections. The results show that our approach outperforms the other approaches.

• Proceedings of the SAREK Conference
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• 2006.06a
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• pp.442-447
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• 2006

In semiconductor manufacturing clean rooms, it becomes important to remove airborne molecular contaminants as well as particulate contaminant in outdoor air introduced into clean rooms. One suitable control technique for these chemical contaminants is air washing by water in an outdoor air handling unit. In order to enhance the removal efficiency of chemical contaminants the effect of adding a heating and humidifying process before an air washer was examined.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• International Journal of Computer Science & Network Security
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• v.22 no.7
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• pp.301-307
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• 2022

Energy consumption has grown alongside dramatic population increases. Statistics show that buildings in particular utilize a significant amount of energy, worldwide. Because of this, building energy prediction is crucial to best optimize utilities' energy plans and also create a predictive model for consumers. To improve energy prediction performance, this paper proposes a ResNet-LSTM model that combines residual networks (ResNets) and long short-term memory (LSTM) for energy consumption prediction. ResNets are utilized to extract complex and rich features, while LSTM has the ability to learn temporal correlation; the dense layer is used as a regression to forecast energy consumption. To make our model more robust, we employed Huber loss during the optimization process. Huber loss obtains high efficiency by handling minor errors quadratically. It also takes the absolute error for large errors to increase robustness. This makes our model less sensitive to outlier data. Our proposed system was trained on historical data to forecast energy consumption for different time series. To evaluate our proposed model, we compared our model's performance with several popular machine learning and deep learning methods such as linear regression, neural networks, decision tree, and convolutional neural networks, etc. The results show that our proposed model predicted energy consumption most accurately.