• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.2
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• pp.1070-1088
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• 2017

Recently, the applications of Internet of Things (IoTs) are growing rapidly. Wireless Sensor Network (WSN) becomes an emerging technology to provide the low power wireless connectivity for IoTs. The IPv6 over low-power wireless personal area networks (6LoWPAN) has been proposed by IETF, which gives each WSN device an IPv6 address to connect with the Internet. The transmission congestion in IoTs could be a problem when a large numbers of sensors are deployed in the field. Therefore, it is important to consider whether the WSN devices have be completely integrated into the Internet with proper quality of service (QoS) requirements. The Software Defined Network (SDN) is a new architecture of network decoupling the data and control planes, and using the logical centralized control to manage the forwarding issues in large-scale networks. In this research, the SDN-based 6LoWPAN Border Router (6LBR) is proposed to integrate the transmission from WSNs to Internet. The proposed SDN-based 6LBR communicating between WSNs and the Internet will bring forward the requirements of end-to-end QoS with bandwidth guarantee. Based on our experimental results, we have observed that the selected 6LoWPAN traffic flows achieve lower packet loss rate in the Internet. Therefore, the 6LoWPAN traffic flows classified by SDN-based 6LBR can be reserved for the required bandwidth in the Internet to meet the QoS requirements.

• Atmosphere
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• v.26 no.2
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• pp.301-319
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• 2016

The evolutionary process of the polar low, which caused the heavy snowfall in the East Coast area on 11~12 February 2011, was investigated to describe in detail using synoptic weather charts, satellite imageries, and ERA (European Centre for Medium-Range Weather Forecasts Re-Analysis) -Interim reanalysis data. It was revealed that 1) the polar low was generated over the sea near Busan where a large cyclonic shear in the inverted trough branched from the parent low existed, 2) during the developing and mature stages, there was a convectively unstable region in the lower layer around the polar low and its south side, 3) the polar low was developed in the region where the static stability in the 500~850 hPa layer was the lowest, 4) the result from the budget analysis of the vorticity equation indicated that the increase in the vorticity at the lower atmosphere, where the polar low was located, was dominated mainly by the stretching term, 5) the warm core structure of the polar low was identified in the surface-700 hPa layer during the mature stage, 6) there was a close inverse relationship between a development of the polar low and the height of the dynamic tropopause over the polar low, and 7) for generation and development of the polar low, large-scale circulation systems, such as upper cold low and its combined short wave trough, major low (parent low), and polar air outbreak, should be presented, indicating that the polar low has the nature of the baroclinic disturbance.

• Publications of The Korean Astronomical Society
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• v.30 no.2
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• pp.409-411
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• 2015

Galaxy clusters, the largest gravitationally bound systems, are an important subject of study to place constraints on cosmological models. Moreover, they are excellent places to test galaxy evolution models in connection to their environments. To date, massive clusters have been found unexpectedly (Kang & Im 2009; Gonzales et al. 2012) and the evolution of galaxies in clusters is still controversial (Elbaz et al. 2007; Faloon et al. 2013). Finding galaxy cluster candidates at z > 1 in a wide, deep imaging survey data will enable us to solve such issues of modern extragalactic astronomy. We report new candidate galaxy clusters in one of the wide and deep survey fields, the European Large Area ISO Survey North1 (ELAIS-N1) and North2 (ELAIS-N2) fields, covering a sky area of $8.75deg^2$ and $4.85deg^2$ each. We also suggest a new useful color selection technique to separate z > 1 galaxies from low - z galaxies by combining multi-wavelength data.

• Smart Structures and Systems
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• v.9 no.2
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• pp.165-188
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• 2012

In the first part of the paper, the optimal design parameters for tuned liquid column dampers (TLCD) in harmonic pitching motion were investigated. The configurations in design tables include uniform and non-uniform TLCDs with cross-sectional ratios of 0.3, 0.6, 1, 2 and 3 for the design in different situations. A closed-form solution of the structural response was used for performing numerical optimization. The results from optimization indicate that the optimal structural response always occurs when the two resonant peaks along the frequency axis are equal. The optimal frequency tuning ratio, optimal head loss coefficient, the corresponding response and other useful quantities are constructed in design tables as a guideline for practitioners. As the value of the head loss coefficient is only available through experiments, in the second part of the paper, the prediction of head loss coefficients in the form of a design chart are proposed based on a series of large scale tests in pitching base motions, aiming to ease the predicament of lacking the information of head loss for those who wishes to make designs without going through experimentation. A large extent of TLCDs with cross-sectional ratios of 0.3, 0.6, 1, 2 and 3 and orifice blocking ratios ranging from 0%, 20%, 40%, 60% to 80% were inspected by means of a closed-form solution under harmonic base motion for identification. For the convenience of practical use, the corresponding empirical formulas for predicting head loss coefficients of TLCDs in relation to the cross-sectional ratio and the orifice blocking ratio were also proposed. For supplemental information to horizontal base motion, the relation of head loss values versus blocking ratios and the corresponding empirical formulas were also presented in the end.

• Journal of Power Electronics
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• v.19 no.6
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• pp.1505-1514
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• 2019

The permanent magnet synchronous motor (PMSM) is widely used in various fields and the proportional-integral (PI) controller is popular in PMSM control systems. However, the motor parameters are usually unknown, which can lead to a complicated PI controller design and poor performance. In order to design a PI controller with good performance when the motor parameters are unknown, a control algorithm based on stability margin is proposed in this paper. First of all, based on the mathematical model of the PMSM and the least squares (LS) method, motor parameters are estimated offline. Then based on the estimation values of the motor parameters, natural angular frequency and phase margin, a PI controller is designed. Performance indices including the natural angular frequency and the phase margin are used directly to design the PI controller in this paper. Scalar functions of the d-loop and the q-loop are selected. It can be seen that the designed controller parameters satisfy Lyapunov large scale asymptotic stability theory if the natural angular frequencies of the d-loop and the q-loop are large than 0. Experimental results show that the parameter estimation method has good accuracy and the designed PI controller proposed in this paper has good static and dynamic performances.

• The Journal of Society for e-Business Studies
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• v.23 no.4
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• pp.153-169
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• 2018

Previous e-financial anomalies analysis and detection technology collects large amounts of electronic financial transaction logs generated from electronic financial business systems into big-data-based storage space. And it detects abnormal transactions in real time using detection rules that analyze transaction pattern profiling of existing customers and various accident transactions. However, deep analysis such as attempts to access e-finance by insiders of financial institutions with large scale of damages and social ripple effects and stealing important information from e-financial users through bypass of internal control environments is not conducted. This paper analyzes the management status of e-financial security programs of financial companies and draws the possibility that they are allies in security control of insiders who exploit vulnerability in management. In order to efficiently respond to this problem, it will present a comprehensive e-financial security management environment linked to insider threat monitoring as well as the existing e-financial transaction detection system.

• KIPS Transactions on Computer and Communication Systems
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• v.8 no.2
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• pp.35-40
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• 2019

Traditional Malware Detection is susceptible for detecting malware which is modified by polymorphism or obfuscation technology. By learning patterns that are embedded in malware code, machine learning algorithms can detect similar behaviors and replace the current detection methods. Data must collected continuously in order to learn malicious code patterns that change over time. However, the process of storing and processing a large amount of malware files is accompanied by high space and time complexity. In this paper, an HDFS-based distributed processing system is designed to reduce space complexity and accelerate feature extraction time. Using a distributed processing system, we extract two API features based on filtering basis, 2-gram feature and APICFG feature and the generalization performance of ensemble learning models is compared. In experiments, the time complexity of the feature extraction was improved about 3.75 times faster than the processing time of a single computer, and the space complexity was about 5 times more efficient. The 2-gram feature was the best when comparing the classification performance by feature, but the learning time was long due to high dimensionality.

• Journal of the Korean Society of Safety
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• v.36 no.2
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• pp.87-93
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• 2021

Modern society shows rapid growth that is different from that of the development of existing technologies. The development of these technologies has led to the tendency of buildings to become dense, large and advancing. Regarding fire hazards, the possibility of large-scale fires causing fatal damage, due to the rapid spread of fire, increases. Therefore, for this reason, fire defense, i.e. detection and fire extinguishing facilities, in buildings are essential and well applied. But there are always limitations to that. Based on this reason, we would like to suggest the introduction of a new concept of a fire safety system. The method presented here is not only to use a single system for fire detection and fire extinguishing systems but to jointly use it in the environment and energy management fields within the building. However, an important step is required before introducing a system of these technologies. The fire extinguishing method proposed by this system is a method of extinguishing by blocking oxygen flowing into the space where the fire occurred. However, a sufficient basis is needed for this system to be applied in practice. Therefore, in this study, we intend to conduct a preliminary experiment to introduce the new concept of fire detection and extinguishing. The experiment used ethanol with a relatively simple combustion reaction and a high possibility of complete combustion. As a result, it was confirmed how the internal values changed during a fire using ethanol. Resultingly, we obtained the internal oxygen concentration and internal environmental changes according to the initial flame size. Lastly, the data accumulated in this study can be used as data for application in an automatic fire extinguishing system.

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.423-427
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• 2022

A pressure sensor that mimics the sensing ability of human skin has emerged as high-profile technology because it shows remarkable applications in numerous fields such as robotics, human health monitoring, and artificial prosthetics. Whereas recent pressure sensors have achieved high sensitivity similar to that of human skin, they still show limited detection bandwidth. Moreover, once these e-skin are fabricated, their sensitivity and stiffness are fixed; therefore, they can be used for only limited applications. Our study proposes a new adaptive pressure sensor built with uniform gallium microdroplet-elastomer composite. Based on the phase transition of gallium microdroplets, the proposed sensor undergoes mode transformation, enabling it to have a higher sensitivity and wider detection bandwidth compared with those of human skin. In addition, we succeeded in extending a single adaptive pressure sensor to sensor arrays based on its high uniformity, reproducibility, and large-scale manufacturability. Finally, we designed an adaptive e-skin with the sensor array and demonstrated its applications on health monitoring tasks including blood pulse and body weight measurements.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.12
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• pp.3904-3922
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• 2022

As a research hotspot, pedestrian detection has a wide range of applications in the field of computer vision in recent years. However, current pedestrian detection methods have problems such as insufficient detection accuracy and large models that are not suitable for large-scale deployment. In view of these problems mentioned above, a lightweight pedestrian detection and early warning method using a new model called you only look once (Yolov5) is proposed in this paper, which utilizing advantages of Yolov5s model to achieve accurate and fast pedestrian recognition. In addition, this paper also optimizes the loss function of the batch normalization (BN) layer. After sparsification, pruning and fine-tuning, got a lot of optimization, the size of the model on the edge of the computing power is lower equipment can be deployed. Finally, from the experimental data presented in this paper, under the training of the road pedestrian dataset that we collected and processed independently, the Yolov5s model has certain advantages in terms of precision and other indicators compared with traditional single shot multiBox detector (SSD) model and fast region-convolutional neural network (Fast R-CNN) model. After pruning and lightweight, the size of training model is greatly reduced without a significant reduction in accuracy, and the final precision reaches 87%, while the model size is reduced to 7,723 KB.