• Science of Emotion and Sensibility
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• v.25 no.1
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• pp.67-78
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• 2022

Interest in bio-signal monitoring of wearable devices is increasing significantly as the next generation needs to develop new devices to dominate the global market of the information and communication technology industry. Accordingly, this research developed a resistive textile strain sensor through a wetting process in a single-wall carbon nanotube dispersion solution using an E-Band with low hysteresis. To measure the resistance signal in the E-Band to which electrical conductivity is applied, a universal material tester, an Arduino, and LCR meters that are microcontroller units were used to measure the resistance change according to the tensile change. To effectively handle various noises generated due to the characteristics of the fabric textile strain sensor, the filter performance of the sensor was evaluated using the moving average filter, Savitsky-Golay filter, and intermediate filters of signal processing. As a result, the reliability of the filtering result of the moving average filter was at least 89.82% with a maximum of 97.87%, and moving average filtering was suitable as the noise filtering method of the textile strain sensor.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.11
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• pp.403-410
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• 2022

Non-Fungible Tokens (NFTs) created on the basis of blockchain have their own unique value, so they cannot be forged or exchanged with other tokens or coins. Using these characteristics, NFTs can be issued to digital assets such as images, videos, artworks, game characters, and items to claim ownership of digital assets among many users and objects in cyberspace, as well as proving the original. However, interest in NFTs exploded from the beginning of 2020, causing a lot of load on the blockchain network, and as a result, users are experiencing problems such as delays in computational processing or very large fees in the mining process. Additionally, all actions of users are stored in the blockchain, and digital assets are stored in a blockchain-based distributed file storage system, which may unnecessarily expose the personal information of users who do not want to identify themselves on the Internet. In this paper, we propose an NFT platform using cloud computing, access gate, conversion table, and cloud ID to improve usability and privacy problems that occur in existing system. For performance comparison between local and cloud systems, we measured the gas used for smart contract deployment and NFT-issued transaction. As a result, even though the cloud system used the same experimental environment and parameters, it saved about 3.75% of gas for smart contract deployment and about 4.6% for NFT-generated transaction, confirming that the cloud system can handle computations more efficiently than the local system.

• Smart Media Journal
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• v.11 no.10
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• pp.65-75
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• 2022

Deep learning is used as a creative tool that could overcome the limitations of existing analysis models and generate various types of results such as text, image, and music. In this paper, we propose a method necessary to preprocess audio data using the Niko's MIDI Pack sound source file as a data set and to generate music using Bi-LSTM. Based on the generated root note, the hidden layers are composed of multi-layers to create a new note suitable for the musical composition, and an attention mechanism is applied to the output gate of the decoder to apply the weight of the factors that affect the data input from the encoder. Setting variables such as loss function and optimization method are applied as parameters for improving the LSTM model. The proposed model is a multi-channel Bi-LSTM with attention that applies notes pitch generated from separating treble clef and bass clef, length of notes, rests, length of rests, and chords to improve the efficiency and prediction of MIDI deep learning process. The results of the learning generate a sound that matches the development of music scale distinct from noise, and we are aiming to contribute to generating a harmonistic stable music.

• Science of Emotion and Sensibility
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• v.25 no.4
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• pp.45-52
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• 2022

Recently, interest in and demand for sensors that recognize physical activity and their products are increasing. In particular, the development of wearable materials that are flexible, stretchable, and able to detect the user's biological signals is drawing attention. In this study, an experiment was conducted to improve the dip-coating efficiency of a single-walled carbon nanotube dispersion solution after fine holes were made in a hydrophobic material with a micro needle. In this study, dip-coating was performed with a material that was not penetrated, and comparative analysis was performed. The electrical conductivity of the sensor was measured when the sensor was stretched using a strain universal testing machine (Dacell Co. Ltd., Seoul, Korea) and a multimeter (Keysight Technologies, Santa Rosa, CA, USA) was used to measure resistance. It was found that the electrical conductivity of a sensor that was subjected to needling was at least 16 times better than that of a sensor that was not. In addition, the gauge factor was excellent, relative to the initial resistance of the sensor, so good performance as a sensor could be confirmed. Here, the dip-coating efficiency of hydrophobic materials, which have superior physical properties to hydrophilic materials but are not suitable due to their high surface tension, can be adopted to more effectively detect body movements and manufacture sensors with excellent durability and usability.

• Smart Media Journal
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• v.12 no.1
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• pp.9-16
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• 2023

Recently, a convolutional neural network (CNN) based system is being developed to overcome the limitations of human resources in the apple quality classification of farmhouse. However, since convolutional neural networks receive only images of the same size, preprocessing such as sampling may be required, and in the case of oversampling, information loss of the original image such as image quality degradation and blurring occurs. In this paper, in order to minimize the above problem, to generate a image patch based graph of an original image and propose a random walk-based positional encoding method to apply the graph transformer model. The above method continuously learns the position embedding information of patches which don't have a positional information based on the random walk algorithm, and finds the optimal graph structure by aggregating useful node information through the self-attention technique of graph transformer model. Therefore, it is robust and shows good performance even in a new graph structure of random node order and an arbitrary graph structure according to the location of an object in an image. As a result, when experimented with 5 apple quality datasets, the learning accuracy was higher than other GNN models by a minimum of 1.3% to a maximum of 4.7%, and the number of parameters was 3.59M, which was about 15% less than the 23.52M of the ResNet18 model. Therefore, it shows fast reasoning speed according to the reduction of the amount of computation and proves the effect.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.7
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• pp.4528-4535
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• 2014

In this paper, a distributed evacuation system based on the positioning information of subway passengers is proposed. Recently, the subway station is becoming complicated by combining with shopping malls, and movie theaters. Compared to the increasing complexity of subway stations, evacuation systems are less complex. Subway passengers in each cell were estimated to use the access point in the subway cells and statistics information. The evacuation route is provided through a direction indicator and push alarm of a smart phone based on estimated the number of passengers and exit information of the subway station. Based on this schemes, a quick and safe evacuation system of subway passengers was proposed. The number of connection passengers was estimated using AP with OpenWrt embedded OS installed. The average error rate of the number of passenger was confirmed to be 15%, 17% and 23% at the confidence parameter of $1{\sigma}$, $2{\sigma}$, and $3{\sigma}$, respectively, through a simulation. The possibility of the system through a simple experiment was examined.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.36 no.2B
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• pp.176-183
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• 2011

In this paper, we propose the implementation and performance analysis of power line communication based on SISO/MIMO-OFDM which focuses on high speed data transmission in smart grid and future power line grid. We employ Zimmermann frequency model and Middleton Class A model as the multipath power line fading channel and impulse noise channel, respectively. In this paper, in order to improve the three-phase or single-phase PLC performance, we introduce a new MRC (called a&f-MRC) which effectively sums up multiple antenna diversity gain and multipath fading diversity gain. Via simulation, we prove the performance advantage over existing SISO/MIMO systems. In addition, we offer the tradeoff on system design through comparing with MRC, EGC and SC.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.20 no.1
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• pp.142-152
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• 2016

GPS is not able to be used for indoor positioning and currently most of techniques emerging to overcome the limit of GPS utilize private wireless networks. However, these methods require high costs for installation and maintenance, and they are inappropriate to be used in the place where precise positioning is needed as in indoor parking lots. This paper proposes a vehicular indoor positioning method based on QR-code recognition. The method gets an absolute coordinate through QR-code scanning, and obtain the location (an relative coordinate) of a black-box camera using the tilt and roll angle correction through affine transformation, scale transformation, and trigonometric function. Using these information of an absolute coordinate and an relative one, the precise position of a car is estimated. As a result, average error of 13.79cm is achieved and it corresponds to just 27.6% error rate in contrast to 50cm error of the recent technique based on wireless networks.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.10
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• pp.1795-1803
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• 2011

Advanced Metering Infrastructure (AMI) is one of the important components to form a smart-gird, which is an advanced power system by combining the power system with the communication systems. This AMI makes it possible to exchange information between operators and consumers for the efficient and reliable operation of the power system through a smart meter or a In-Home Display. However, according to the increase of the demanded information such as the power quality, the accurate load-profile, and the billing data to help customers manage their power consumption, it is necessary to gather more accurate analytical data from each house appliances and transfer it to the smart meter for synthesizing the information and controlling each loads. In this paper, the development of the wireless data acquisition device for the individual load data metering, which is connected with the smart meter for advanced functions, is proposed. AVR, a kind of microcontroller, and Bluetooth are used and integrated into the proposed the wireless data acquisition device to transmit the detailed power data (voltage and current) to the smart meter. To verify the effectiveness of the proposed system, a hardware experiment is carried out including the confirmation of the possibility for providing the more various information by applying analysis algorithms to the obtained data. Also, the application structure of the wireless data acquisition device to gather the data from the various house appliances is presented.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.16 no.1
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• pp.147-156
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• 2017

This paper analyzes the performance limit of WAVE system for the platooning service requirements which is referred from the de facto standards. The performance of the packet error rate and mean delay as key parameters in the wireless communication systems should be satisfied to provide safety to the platooning vehicles. The test scenarios are conducted by considering the following vehicle groups: platooning vehicles, vehicles within a hop distance and vehicles within two hop distance( called hidden node vehicles). The models of packet error rate and delay deals with the topology of aforementioned vehicle groups, vehicle speed and communication range. The numerical results are obtained in terms of packet size, packet arrival rate and data transmission rate. Finally, this paper suggests the robust range of packet error rate and delay for the WAVE system to provide the platooning vehicle service.