• Journal of the Korea Concrete Institute
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• v.23 no.4
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• pp.487-494
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• 2011

In this research, the possibility of using bottom ash as a binder for the alkali-activated cement mortar is studied. Several experiments were performed to investigate the variation of the material properties according to the mix proportion. In the experimental program, the flowability and compressive strength were evaluated for various values of water/ash ratio, activator/ash ratio, sodium silicate to sodium hydroxide ratio, curing temperature, and the fineness of bottom ash as the main variables. The experimental results showed that high strength of 40 MPa or greater could be achieved in $60^{\circ}C$ high temperature curing condition with proper flowability. For $20^{\circ}C$ ambient temperature curing, the 28 days compressive strength of approximately 30MPa could be obtained although the early-age strength development was very slow. Based on the results, the range of optimized mix design of bottom-ash based alkali-activated cement mortar was suggested. In addition, using the artificial neural network analysis, the flowability and compressive strength were predicted with the difference in the mix proportion of the bottom-ash based alkali-activated cement mortar.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.29 no.1
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• pp.42-49
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• 2018

In this paper, a dual-band microstrip-fed monopole antenna with a DGS(defected ground structure) for WLAN(wireless local area network) applications is presented. The antenna consists of a monopole and a defected ground, which were etched on both sides of the FR-4 substrate. The defected ground structure was used to obtain the dual band, while the step-by-step reduction in the monopole width was used to improve the impedance matching of the antenna. The antenna has an overall compact size of $44{\times}51{\times}1.6mm^3$, which was optimized by varying the size of the monopole and the ground plane such that it may resonate at the 2.4 GHz and 5 GHz bands of the WLAN. The measurement results showed that the antenna operates in the frequency band of 210 MHz(2.29~2.50 GHz) and 900 MHz(5.05~5.95 GHz) for a VSWR under 2, and showed omnidirectional radiation pattern at all desired frequencies.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.5
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• pp.981-986
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• 2020

The Internet of Things refers to a space-of-things connection network configured to allow things with built-in sensors and communication functions to interact with people and other things, regardless of the restriction of place or time.IoT is a network developed for the purpose of services for human convenience, but the scope of its use is expanding across industries such as power transmission, energy management, and factory automation. However, the communication protocol of IoT, MQTT, is a lightweight message transmission protocol based on the push technology and has a security vulnerability, and this suggests that there are risks such as personal information infringement or industrial information leakage. To solve this problem, we designed a synchronous MQTT security channel that creates a secure channel by using the characteristic that different chaotic dynamical systems are synchronized with arbitrary values in the lightweight message transmission MQTT protocol. The communication channel we designed is a method of transmitting information to the noise channel by using characteristics such as random number similarity of chaotic signals, sensitivity to initial value, and reproducibility of signals. The encryption method synchronized with the proposed key value is a method optimized for the lightweight message transmission protocol, and if applied to the MQTT of IoT, it is believed to be effective in creating a secure channel.

• Korean Journal of Remote Sensing
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• v.36 no.3
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• pp.487-501
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• 2020

As a viable option for retrieval of LST (Land Surface Temperature), this paper presents a DNN (Deep Neural Network) based approach using 148 Landsat 8 images for South Korea. Because the brightness temperature and emissivity for the band 10 (approx. 11-㎛ wavelength) of Landsat 8 are derived by combining physics-based equations and empirical coefficients, they include uncertainties according to regional conditions such as meteorology, climate, topography, and vegetation. To overcome this, we used several land surface variables such as NDVI (Normalized Difference Vegetation Index), land cover types, topographic factors (elevation, slope, aspect, and ruggedness) as well as the T₀ calculated from the brightness temperature and emissivity. We optimized four seasonal DNN models using the input variables and in-situ observations from ASOS (Automated Synoptic Observing System) to retrieve the LST, which is an advanced approach when compared with the existing method of the bias correction using a linear equation. The validation statistics from the 1,728 matchups during 2013-2019 showed a good performance of the CC=0.910~0.917 and RMSE=3.245~3.365℃, especially for spring and fall. Also, our DNN models produced a stable LST for all types of land cover. A future work using big data from Landsat 5/7/8 with additional land surface variables will be necessary for a more reliable retrieval of LST for high-resolution satellite images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.30 no.5B
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• pp.253-263
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• 2005

This paper proposed a mobile multicast technique to satisfy end-to-end QoS for various user requirements in mobile network environment. In order to provide seamless mobility, fast handoff technique was applied. By using L2 mobile trigger, it was possible to minimize remarkable amount of packet loss by delay occurred during handoff. To provide efficient multicast, concept of hierarchy was introduced to Xcast++, which results in a creation of HXcast++. HXcast++ optimized transfer path of multicast and reduced expensive multicast maintenance costs caused by frequent handoff. Suggestion of GMA (Group Management Agent) mechanism allows joining to group immediately without waiting IGMP Membership query during handoff. GMA mechanism will minimize the delay for group registration process and the resource usage due to delay of withdrawal process. And also use of buffering & forwarding technique minimized packet loss during generation of multicast tree. IntServ/RSVP was used to provide End-to-End QoS in local domain and DiffServ was used in global domain. To minimize reestablishment of RSVP session delay, extended HXcast++ control messages ware designed to require PATH message. HXcast++ proposed in this thesis is defined as multicast technique to provide end-to-end QoS and also to satisfy various user requirements in mobile network environment.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.46 no.4
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• pp.61-68
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• 2009

In this paper, we propose a Cluster-based Cooperative Routing using ARQ (CCRA) for supporting both reliability and transmitting efficient service in mobile ad-hoc wireless sensor networks with Rayleigh fading environments. The main contributions and features of this paper are as follows. First, the clustering method which uses the position information of nodes as underlying structure for supporting reliable transmission services is used. Second, the cooperative data transmission method based on the underlying clustering informations is used to improve both reliability and data transmission efficiency. Third, the ARQ-based transmission is used to improve transmission reliability. Fourth, we consider a realistic approach, in the points of view of mobile ad-hoc wireless sensor networks, based on mobile sensor nodes as well as fixed sensor nodes in the sensor fields while the conventional research for sensor networks focus on mainly fixed sensor networks. The performance evaluation of proposed routing protocol implemented via simulation using Optimized Network Engineering Tool (OPNET) and theoretical analysis.

• Journal of the Institute of Electronics Engineers of Korea TC
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• v.41 no.12
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• pp.41-49
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• 2004

Increase of internet users and new types of applied traffics, have led to demand for more bandwidth for each application. Hence, the amount of internet traffic has risen sharply and it has demanded to use limited resources, such as wavelength and bandwidth, more effectively. These kind of needs can be satisfied with OXC(Optical cross-connects) based on GMPLS that carry out IP packet switching and wavelength switching at the same time and Provide very wide bandwidth. In RSVP-TE signaling of GMPLS studied by IETF. every lambda router in core network should be able to convert wavelength. So, lots of wavelength converters and needed and building and managing cost is high. Another problem is that optimized traffic is limited. In this paper We suggest strengthened GMPLS RSVP-TE signaling algorithm for a better lightpath setup. When setup signaling is blocked suggested algorithm does not send PathErr message to Edge Router, but looks for nearest lambda router which can convert wavelength and carry out setup signaling from that node. Such algorithm can reduce the chance of blocked lightpath setup signaling and provide effective arrangement of lambda router in core network by calculating proper number of wavelength converter.

• Journal of the Korean Institute of Intelligent Systems
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• v.24 no.2
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• pp.173-178
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• 2014

In this study, we introduce ASM-based face recognition classifier and its design methodology with the aid of 2-dimensional 2-directional hybird preprocessing algorithm. Since the image of face recognition is easily affected by external environments, ASM(active shape model) as image preprocessing algorithm is used to resolve such problem. In particular, ASM is used widely for the purpose of feature extraction for human face. After extracting face image area by using ASM, the dimensionality of the extracted face image data is reduced by using $(2D)^2$hybrid preprocessing algorithm based on LDA and PCA. Face image data through preprocessing algorithm is used as input data for the design of the proposed polynomials based radial basis function neural network. Unlike as the case in existing neural networks, the proposed pattern classifier has the characteristics of a robust neural network and it is also superior from the view point of predictive ability as well as ability to resolve the problem of multi-dimensionality. The essential design parameters (the number of row eigenvectors, column eigenvectors, and clusters, and fuzzification coefficient) of the classifier are optimized by means of ABC(artificial bee colony) algorithm. The performance of the proposed classifier is quantified through yale and AT&T dataset widely used in the face recognition.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.476-482
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• 1997

A portable electronic nose system has been fabricated and characterized using an oxide semiconductor gas sensor array and pattern recognition techniques such as principal component analysis and back-propagation artificial neural network. The sensor array consists of six thick-film gas sensors whose sensing layers are Pd-doped $WO_{3}$, Pt-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$ + Pd coated layer, $Al_{2}O_{3}$-doped ZnO and $PdCl_{2}$-doped $SnO_{2}$. The portable electronic nose system consists of an 16bit Intel 80c196kc as CPU, an EPROM for storing system main program, an EEPROM for containing optimized connection weights of artificial neural network, an LCD for displaying gas concentrations. As an application the system has been used to identify 26 carbon monoxide/hydrocarbon (CO/HC) car exhausting gases in the concentration range of CO 0%/HC 0 ppm to CO 7.6%/HC 400 ppm and the identification has been successfully demonstrated.

• Journal of the Institute of Convergence Signal Processing
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• v.19 no.1
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• pp.7-13
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• 2018

In the current study, we proposed an optimized brain-computer interface (BCI) which employed blind source separation (BBS) approach to remove noises. Thus motor imagery (MI) signal and steady state visual evoked potential (SSVEP) signal were easily to be detected due to enhancement in signal-to-noise ratio (SNR). Moreover, a combination between MI and SSVEP which is typically can increase the number of commands being generated in the current BCI. To reduce the computational time as well as to bring the BCI closer to real-world applications, the current system utilizes a single-channel EEG signal. In addition, a convolutional neural network (CNN) was used as the multi-class classification model. We evaluated the performance in term of accuracy between a non-BBS+BCI and BBS+BCI. Results show that the accuracy of the BBS+BCI is achieved $16.15{\pm}5.12%$ higher than that in the non-BBS+BCI by using BBS than non-used on. Overall, the proposed BCI system demonstrate a feasibility to be applied for multi-dimensional control applications with a comparable accuracy.