• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2019.05a
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• pp.607-609
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• 2019

The split-channel two-tone OOK method proposed in this paper can improve the communication performance of IoT in fading channel environment. The frequency diversity effect can be obtained by separating the interval of the two tone signals, and a performance gain of 8 dB can be obtained in the fading channel. In addition, by using split-channel, the problem of degradation of the channel bandwidth efficiency caused by the frequency diversity technique can be prevented, thereby reducing the bandwidth efficiency by allocating the remaining frequency channels to other users.

• Journal of IKEEE
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• v.26 no.3
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• pp.500-505
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• 2022

In this study, we designed oxide thin-film transistors (TFTs) with dual gate and tri layered split channels, and investigated the structural effect of the TFTs on the electrical characteristics. The dual gates played a key role in increasing the driving current, and the channel structure of tri layers and split form contributed to the increase in the carrier mobility. The tri layered channels consisting of the a-ITGZO and two ITO layers inserted between the gate dielectric and a-ITGZO led to the increase in the on-current by using ITO layers with high conductivity, and the split channels lowered series resistance of the channels. Compared with the mobility (15 cm²/V·s) of the single gate a-ITGZO TFT, the mobility (134 cm²/V·s) of the dual gate tri-layer split channel TFT was remarkably enhanced by the structural effect.

• Journal of Information Processing Systems
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• v.18 no.1
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• pp.12-25
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• 2022

In recent years, deep convolutional neural networks have made significant progress in the research of single image super-resolution. However, it is difficult to be applied in practical computing terminals or embedded devices due to a large number of parameters and computational effort. To balance these problems, we propose CSRNet, a lightweight neural network based on channel split residual learning structure, to reconstruct highresolution images from low-resolution images. Lightweight refers to designing a neural network with fewer parameters and a simplified structure for lower memory consumption and faster inference speed. At the same time, it is ensured that the performance of recovering high-resolution images is not degraded. In CSRNet, we reduce the parameters and computation by channel split residual learning. Simultaneously, we propose a double-upsampling network structure to improve the performance of the lightweight super-resolution network and make it easy to train. Finally, we propose a new evaluation metric for the lightweight approaches named 100_FPS. Experiments show that our proposed CSRNet not only speeds up the inference of the neural network and reduces memory consumption, but also performs well on single image super-resolution.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.28 no.9A
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• pp.717-727
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• 2003

The HIPERLAN/2(HIgh PERformance Local Area Network Type2) is one of the wireless LAN standards for providing raw data rates of up to 54 Mbps. The MAC protocol of HIPERLAN/2 is based on TDMA/TDD, and resources in one MAC frame can be allocated dynamically by Access Point(AP). The random channel(RCH) is defined for the purpose of giving a mobile terminal the opportunity to request transmission resources in the uplink MAC frames. It is desirable that the number of RCHs is dynamically adapted by the AP depending on the current traffic situation. Allocation of excessive RCHs may waste radio resources and insufficient RCHs compared to traffic loads may result in many collisions in access attempts. We propose an RCH allocation scheme based on split algorithm in HIPERLAN/2. The simulation and analytic results show that the proposed scheme achieves a higher channel throughput, lower access delay and delay jitter than previously proposed RCH allocation schemes.

• JSTS:Journal of Semiconductor Technology and Science
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• v.15 no.5
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• pp.504-510
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• 2015

This paper presents a power and area efficient SAR ADC for multi-channel near threshold-voltage (NTV) applications such as neural recording systems. This work proposes a split dual-capacitive-array (S-DCA) structure with shifted input range for ultra low-switching energy and architecture of multi-channel single-ended SAR ADC which employs only one comparator. In addition, the proposed ADC has the same amount of equivalent capacitance at two comparator inputs, which minimizes the kickback noise. Compared with conventional SAR ADC, this work reduces the total capacitance and switching energy by 84.8% and 91.3%, respectively.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.32 no.3
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• pp.217-222
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• 2008

Equal channel angular pressing (ECAP) is one of the effective methods to produce bulk-nano materials by accumulating plastic strain into the workpiece without changing its cross-sectional shape in the multi-pass processing. However, the forming load becomes higher for manufacturing large specimens using conventional solid or split dies because of friction, flash formation, and usage of dummy specimen. In the present investigation, better split die was designed to reduce the forming loads and improve the geometrical accuracy of the specimen in the multi-pass ECAP. The new die exit channel was also designed to reduce the friction effect. Experiments with AA1050 specimens with a square cross-section were carried out to examine the design goal using the proposed split dies for routes A and C up to four passes. The numerical forming simulations were used to determine the effective geometry of various die models in the present work.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.783-790
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• 2005

In this paper, we have simulated a Symmetric Dual-gate Single-Si TFT which has three split floating n+ zones. This structure reduces the kink-effect drastically and improves the on-current. Due to the separated floating n+ zones, the transistor channel region is split into four zones with different lengths defined by a floating n+ region, This structure allows an effective reduction of the kink-effect depending on the length of two sub-channels. The on-current of the proposed dual-gate structure is 0.9mA while that of the conventional dual-gate structure is 0.5mA at a 12V drain voltage and a 7V gate voltage. This result shows a 80% enhancement in on-current. Moreover we observed the reduction of electric field in the channel region compared to conventional single-gate TFT and the reduction of the output conductance in the saturation region. In addition, we also confirmed the reduction of hole concentration in the channel region so that the kink-effect reduces effectively.

• Journal of Advanced Navigation Technology
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• v.15 no.2
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• pp.307-312
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• 2011

In the macro/femto cellular networks, the portion of channels assigned to each cell is a critical factor which sets the stability and the performance of the whole system. To grasp the concrete influence that the channel split portion have on the system, we present the queueing model for IP based macro/femto cellular networks, and find the stability conditions. Additionally we provide the strategy to decide the portion of channels allocated to each cell. Through the experiments, we prove that the proposed strategies operate feasibly in various network environments, and on the basis of these results we discuss the efficient system structure plan.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.18 no.5
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• pp.423-430
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• 2005

In this paper, we have simulated a Symmetric Dual-gate Single-Si TFT which has three split floating $n^{+}$ zones. This structure reduces the kink-effect drastically and improves the on-current. Due to the separated floating $n^{+}$ zones, the transistor channel region is split into four zones with different lengths defined by a floating $n^{+}$ region. This structure allows an effective reduction of the kink-effect depending on the length of two sub-channels. The on-current of the proposed dual-gate structure is 0.9 mA while that of the conventional dual-gate structure is 0.5 mA at a 12 V drain voltage and a 7 V gate voltage. This results show a $80 {\%}$ enhancement in on-current by adding two floating $n^{+}$ zones. Moreover we observed the reduction of electric field In the channel region compared to conventional single-gate TFT and the reduction of the output conductance in the saturation region. In addition we also confirmed the reduction of hole concentration in the channel region so that the kink-effect reduces effectively.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.19 no.5
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• pp.178-188
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• 2020

This paper proposes a lane recognition CNN network using split-attention network as a backbone to extract feature. Split-attention is a method of assigning weight to each channel of a feature map in the CNN feature extraction process; it can reliably extract the features of an image during the rapidly changing driving environment of a vehicle. The proposed deep neural networks in this paper were trained and evaluated using the Tusimple data set. The change in performance according to the number of layers of the backbone network was compared and analyzed. A result comparable to the latest research was obtained with an accuracy of up to 96.26, and FN showed the best result. Therefore, even in the driving environment of an actual vehicle, stable lane recognition is possible without misrecognition using the model proposed in this study.