• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.7
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• pp.993-999
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• 2021

Recently, many studies on VNDN technology have been conducted to graft Named Data Networking (NDN) into VANET as a core network technology. VNDN can use the content name to deliver various infotainment application content data through name-based forwarding. When VNDN is used as a communication technology for infotainment applications in connected vehicles, it is possible to realize data-centric networking technology in which data is the subject of communication. It can overcome the limitations of connected vehicle infotainment application service technology based on the host-centric current Internet, such as security attack/hacking, performance degradation in long-distance data transmission, frequent data cut-off. In this paper, we present the main functions provided by VNDN technology, and systematically analyze and organize the issues necessary to realize infotainment application services for connected vehicles in the VNDN environment. Based on this, it can be utilized as basic information necessary to establish infotainment application requirements in VNDN environment.

• Fashion & Textile Research Journal
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• v.21 no.2
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• pp.133-140
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• 2019

This study developed smart fashion prototypes that provide utilitarian functionality by combining Fashion and Electronics regarding the IT focused convergence tendency in modern industries. A convergence R&D workshop was performed by Fashion design majors and Engineering majors for the study. As a result, 5 functional smart fashion prototypes were developed and the outline of each prototype are as follows. The $1^{st}$ prototype, 'Hidden Camera Detecting Coat' focused on gender-related crimes. The coat uses infrared lighting and LED technologies to provide a function to detect hidden cameras in suspicious public spaces such as toilets. The $2^{nd}$ prototype, 'Heating-massage Suit' targeted patients with musculoskeletal system difficulties. The suit uses heating and vibration technologies to provide a heating massage treatment for patients with ongoing difficulties in their daily lives. The $3^{rd}$ prototype is an air-bag jacket to prevent sexual molestation on public transportation. The jacket extends its volume through pressure sensing, air compressing, motors and 3D-printing technology to secure the wearer's personal preventive space between the user's body and others. The $4^{th}$ prototype is a town wear for people suffering from synesthesia. People with synesthesia inadvertently see colors when exposed to certain sounds. This town wear uses sound sensing, air compressing, motors and 3D-printing technology to provide sound prevention and a comfortable sound playing function. The $5^{th}$ prototype is a set of a vest and a gloves for visually impaired people. The vest and gloves uses DMS, voice playing, vibration technology to provide distance measuring and warning functions.

• Korean Journal of Remote Sensing
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• v.35 no.1
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• pp.29-37
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• 2019

Synthetic Aperture Radar (SAR) observations are powerful tools to monitor surface's displacement very accurately, induced by earthquake, volcano, ground subsidence, glacier movement, etc. Especially, radar interferometry (InSAR) which utilizes phase information related to distance from sensor to target, can generate displacement map in line-of-sight direction with accuracy of a few cm or mm. Due to decorrelation effect, however, degradation of coherence in the InSAR application often prohibit from construction of differential interferogram. Offset tracking method is an alternative approach to make a two-dimensional displacement map using intensity information instead of the phase. However, there is limitation in that the offset tracking requires very intensive computation power and time. In this paper, efficiency of parallel computing has been investigated using high performance computer for estimation of glacier velocity. Two TanDEM-X SAR observations which were acquired on September 15, 2013 and September 26, 2013 over the Narsap Sermia in Southwestern Greenland were collected. Atotal of 56 of 2.4 GHz Intel Xeon processors(28 physical processors with hyperthreading) by operating with linux environment were utilized. The Gamma software was used for application of offset tracking by adjustment of the number of processors for the OpenMP parallel computing. The processing times of the offset tracking at the 256 by 256 pixels of window patch size at single and 56 cores are; 26,344 sec and 2,055 sec, respectively. It is impressive that the processing time could be reduced significantly about thirteen times (12.81) at the 56 cores usage. However, the parallel computing using all the processors prevent other background operations or functions. Except the offset tracking processing, optimum number of processors need to be evaluated for computing efficiency.

• Journal of Convergence for Information Technology
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• v.9 no.9
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• pp.126-132
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• 2019

This study presents a TOPSIS-based application for the evaluation of administrative purposes on the website of university's departments. As the school age population decreases, the homepage of the university's departments also has important promotional means. However, most of them are not well managed until a full renewal. This is because the investment is difficult compared to strategic importance. Therefore, this paper tries to show its usefulness by applying a partially modified TOPSIS for management purposes, in consideration of the practicality. TOPSIS is appropriate for target management as a conceptual reason to prioritize based on the distance from the ideal target for each criterion. Also, in the case of monotonic functions of the evaluation criteria used, the same results can be obtained by reducing the amount of calculations through a partially modified procedure as presented in this study.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.78.2-78.2
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• 2019

We develop an Alcock-Paczynski (AP) test method that uses the evolution of redshift-space two-point correlation function (2pCF) of galaxies. The method improves the AP test proposed by Li et al. (2015) in that it uses the full two-dimensional shape of the correlation function. Similarly to the original method, the new one uses the 2pCF in redshift space with its amplitude normalized. Cosmological constraints can be obtained by examining the redshift dependence of the normalized 2pCF. This is because the 2pCF should not change apart from the expected small non-linear evolution if galaxy clustering is not distorted by incorrect choice of cosmology used to convert redshift to comoving distance. Our new method decomposes the redshift difference of the 2-dimensional correlation function into the Legendre polynomials whose amplitudes are modelled by radial fitting functions. The shape of the normalized 2pCF suffers from small intrinsic time evolution due to non-linear gravitational evolution and change of type of galaxies between different redshifts. It can be accurately measured by using state of the art cosmological simulations. We use a set of our Multiverse simulations to find that the systematic effects on the shape of the normalized 2pCF are quite insensitive to change of cosmology over \Omega_m=0.21 - 0.31 and w=-0.5 - -1.5. Thanks to this finding, we can now apply our method for the AP test using the non-linear systematics measured from a single simulation of the fiducial cosmological model.

• Journal of Fashion Business
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• v.23 no.2
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• pp.156-169
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• 2019

The objective of this study was to develop lightweight, stretchable, tight-fit smart sportswear using the conductive yarns into the garment and demonstrating its usefulness. Sportswears with the ability to control LEDs with respect to lighting of the surrounding were developed by applying embroidery with conductive yarns to 2 types of men's T-shirts and 2 types of women's leggings pants for outdoor activities and exercise purposes. LEDs were applied to the front and back of men's T-shirts and to the rear of the waist of women's leggings. Men's T-shirts were printed where the LEDs were to be applied, and inside, they were embroidered with conductive threads on the hot-melt fabric to be attached, and then connected with LED. Women's pants were embroidered on the elastic band, in the form of a sine wave that gives it ability to stretch, and finally the elastic band was hidden inside the waistband. The operation of the light sensor in the dark provided the ability to protect joggers from night drivers or cyclists. LEDs were activated when the wearer turns on the fashionable device on his/her shoulder by pressing it. It was able to reduce the risk of accidents by giving recognizability to vehicles, bicycles, and athletes approaching or passing by at night, and securing safe distance from vehicles, etc. Internal embroidery technology had the same flexible and lightweight functions as ordinary clothing products, making it possible to apply to tight-fit smart T-shirts or leggings pants designs.

• Journal of IKEEE
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• v.24 no.4
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• pp.1022-1027
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• 2020

In this paper, SVM-based speaker classification is experimented with GMM-supervector. To create a speaker cluster, conventional speaker change detection is performed with the KL distance using the SNR-based weighting function. SVM-based speaker classification consists of two steps. In the first step, SVM-based classification between UBM and speaker models is performed, speaker information is indexed in each cluster, and then grouped by speaker. In the second step, the SVM-based classification between UBM and speaker models is performed by inputting the speaker cluster group. Linear and RBF are applied as kernel functions for SVM-based classification. As a result, in the first step, the case of applying the linear kernel showed better performance than RBF with 148 speaker clusters, MDR 0, FAR 47.3, and ER 50.7. The second step experiment result also showed the best performance with 109 speaker clusters, MDR 1.3, FAR 28.4, and ER 32.1 when the linear kernel was applied.

• Journal of information and communication convergence engineering
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• v.20 no.1
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• pp.22-30
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• 2022

The reinforcement learning algorithm has proven its potential in solving sequential decision-making problems under uncertainties, such as finding paths to route data packets in wireless sensor networks. With reinforcement learning, the computation of the optimum path requires careful definition of the so-called reward function, which is defined as a linear function that aggregates multiple objective functions into a single objective to compute a numerical value (reward) to be maximized. In a typical defined linear reward function, the multiple objectives to be optimized are integrated in the form of a weighted sum with fixed weighting factors for all learning agents. This study proposes a reinforcement learning -based routing protocol for wireless sensor network, where different learning agents prioritize different objective goals by assigning weighting factors to the aggregated objectives of the reward function. We assign appropriate weighting factors to the objectives in the reward function of a sensor node according to its hop-count distance to the sink node. We expect this approach to enhance the effectiveness of multi-objective reinforcement learning for wireless sensor networks with a balanced trade-off among competing parameters. Furthermore, we propose SDN (Software Defined Networks) architecture with multiple controllers for constant network monitoring to allow learning agents to adapt according to the dynamics of the network conditions. Simulation results show that our proposed scheme enhances the performance of wireless sensor network under varied conditions, such as the node density and traffic intensity, with a good trade-off among competing performance metrics.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1311-1316
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• 2021

In this paper, we present a bifocal stereo camera system combining two cameras with different focal length cameras to generate stereoscopic image and their corresponding depth map. In order to obtain the depth data using the bifocal stereo camera system, we perform camera calibration to extract internal and external camera parameters for each camera. We calculate a common image plane and perform a image rectification for generating the depth map using camera parameters of bifocal stereo camera. Finally we use a SGM(Semi-global matching) algorithm to generate the depth map in this paper. The proposed bifocal stereo camera system can performs not only their own functions but also generates distance information about vehicles, pedestrians, and obstacles in the current driving environment. This made it possible to design safer autonomous vehicles.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.6
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• pp.1287-1294
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• 2021

This paper is a study on the implementation of a sensor-based smart compression system for improving home and street environments. Since modernization, the amount of garbage has been increasing every year, and this has seriously adversely affected not only people but also ecosystems such as marine pollution and soil pollution. In particular, in large cities with large floating populations, garbage is dumped on the streets without proper measures to deal with the amount of waste generated. In order to improve this problem, this paper intends to implement a system with automatic compression and opening/closing functions using sensors. This system is designed to activate automatic opening/closing function through an infrared sensor, and automatically opening and closing when the inclination is changed using an impact sensor. In addition, by installing a distance sensor, the amount of internal waste can be easily monitored from the outside, and a manual compression switch and a manual opening/closing switch is separately designed to enable opening and closing and compression as needed to increase the effectiveness.