• Proceedings of the IEEK Conference
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• 2003.07a
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• pp.97-100
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• 2003

The quasi-complementary turbo codes (QCTC) proposed by Kim [1] is used for a fast hybrid ARQ scheme with incremental redundancy and adaptive modulation coding in the cdma2000 1xEV-DV [2]. The QCTC provides various code rates with good performance, a very simple encoder structure, and an inherent channel interleaving. It is shown that the QCTC is a unified scheme of channel coding and channel interleaving. In this paper, we introduce the properties of QCTC and various hybrid ARQ-QCTC schemes for the system.

• Annual Conference of KIPS
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• 2005.05a
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• pp.221-224
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• 2005

In this paper, we propose a fast video mixing method for reducing the computational complexity in the MCU (Multipoint Control Unit) used in the video conferencing. The conventional mixing method is based on the pixeldomain transcoder, of which computational complexity is linearly increased as the number of participants is increased. Basically the method requires N decoders and one huge encoder to mix the bitstreams from the N participants. To reduce the computational complexity, we propose a hybrid mixing method based on the bitstreamdomain and pixel-domain transcoding methods. The proposed method reduces the computational complexity about 45% at the improved quality, compared with the conventional mixing method based on the pixel-domain transcoders.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.46 no.2
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• pp.85-92
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• 2009

This paper proposes a full-search block-matching motion estimation circuit with hybrid architecture combining systolic arrays and adder trees for an MPEG-4 encoder. The proposed circuit uses systolic arrays for motion estimation with a small number of clock cycles and adder trees to reduce required circuit resources. The interpolation circuit for 1/2 pixel motion estimation consists of six adders, four subtracters and ten registers. We improved the circuit performance by resource sharing and efficient scheduling techniques. We described the motion estimation circuit for integer and 1/2 pixels at RTL in Verilog HDL. The logic-level circuit synthesized by using 130nm standard cell library contains 218,257 gates and can process 94 D1($720{\times}480$) image frames per second.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.519-536
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• 2007

In this paper, we combine the Hybrid-Automatic Repeat reQuest (HARQ) algorithm with joint Tx and Rx antenna selection based on the reliability of the individual antennas links. The cyclic redundancy check (CRC) is applied on the data before being encoded using the Turbo encoder. In the receiver the CRC is used to detect errors of each antenna stream and to decide whether a retransmission is required or not. The receiver feeds back the transmitter with the Tx antennas ordering and the acknowledgement of each antenna (ACK or NACK). If the number of ACK antennas is higher than the NACK antennas, then the retransmission takes place from the ACK antennas using the Chase Combining (CC). If the number of the NACK antennas is higher than the ACK antennas then the ACK antennas are used to retransmit the data streams using the CC algorithm and additional NACK antennas are used to retransmit the remaining streams using Incremental Redundancy (IR, i.e. the encoder rate is reduced). Furthermore, the HARQ is used with the I-BLAST (Iterative-BLAST) which grantees a high transmission rate.

• Convergence Security Journal
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• v.21 no.3
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• pp.13-23
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• 2021

The attacker's techniques and tools are becoming intelligent and sophisticated. Existing Anti-Virus cannot prevent security accident. So the security threats on the endpoint should also be considered. Recently, EDR security solutions to protect endpoints have emerged, but they focus on visibility. There is still a lack of detection and responsiveness. In this paper, we use real-world EDR event logs to aggregate knowledge-based MITRE ATT&CK and autoencoder-based anomaly detection techniques to detect anomalies in order to screen effective analysis and analysis targets from a security manager perspective. After that, detected anomaly attack signs show the security manager an alarm along with log information and can be connected to legacy systems. The experiment detected EDR event logs for 5 days, and verified them with hybrid analysis search. Therefore, it is expected to produce results on when, which IPs and processes is suspected based on the EDR event log and create a secure endpoint environment through measures on the suspicious IP/Process.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.18 no.10
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• pp.2966-2983
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• 2024

Considering the intricate and ever-changing nature of the marine environment and the diverse range of sizes for targets involved in marine ship target recognition, which present challenges in detecting specific targets, a marine ship target detection algorithm has been developed based on an enhanced iteration of YOLOv5. Initially, the integration of dynamic snake convolution (DySnakeConv) into the feature extraction network and subsequent enhancement of the C3 module based on this integration were implemented. This integration enables dynamic adjustments based on the input image size, adaptive fusion of feature sequences, and resolution of accuracy and continuity issues during the recognition process. Subsequently, a novel hybrid encoder (FSI) was devised, utilizing target scale characteristics to enhance the extraction capability of multi-scale information, facilitating effective detection and recognition of objects within images. Finally, we selected the Shape-IOU bounding box loss function to mitigate fixed target frame issues and enhance target detection accuracy. Experimental evaluations were conducted utilizing the Infrared Maritime Ship dataset. The results demonstrated that our enhanced model achieved a prediction accuracy of 93.8% and an average precision (mAP) value of 93.89%, surpassing YOLOv8s by 1.2% and 1.8%, respectively. Moreover, there was an increase in recall rate by 2% compared to YOLOv8n while reducing parameters from 10,473,392 to 6,549,901 only. The computational load decreased by 6.3 GFLOps compared with YOLOV8n, resulting in better performance in ocean target detection and recognition.

• Journal of Broadcast Engineering
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• v.19 no.5
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• pp.687-698
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• 2014

ATSC is currently working on standardization of hybrid 3DTV broadcasting service in heterogenous network environment after completion of service-compatible 3DTV broadcasting service standard based on broadcasting channel. This paper proposes a convergence 3D video broadcasting method on broadcasting and IP network while guaranteeing a Full-HD 3D quality without degrading the image quality of legacy DTV. Specifically, this paper describes transmission of the 3D additional video using the ISO/IEC 23009-1 DASH, robust synchronization method under heterogenous network environments and system target decoder model for hybrid 3DTV receiver. Based on experimental results, we confirm that proposed technologies can be used as a core technology in the hybrid 3DTV standardization and a reference model for a development of hybrid 3DTV encoder and receiver.

• Nuclear Engineering and Technology
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• v.55 no.8
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• pp.2854-2863
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• 2023

Objective: To present a hybrid approach that incorporates a constrained beam-hardening estimator (CBHE) and deep learning (DL)-based post-refinement for metal artifact reduction in dental cone-beam computed tomography (CBCT). Methods: Constrained beam-hardening estimator (CBHE) is derived from a polychromatic X-ray attenuation model with respect to X-ray transmission length, which calculates associated parameters numerically. Deep-learning-based post-refinement with an artifact disentanglement network (ADN) is performed to mitigate the remaining dark shading regions around a metal. Artifact disentanglement network (ADN) supports an unsupervised learning approach, in which no paired CBCT images are required. The network consists of an encoder that separates artifacts and content and a decoder for the content. Additionally, ADN with data normalization replaces metal regions with values from bone or soft tissue regions. Finally, the metal regions obtained from the CBHE are blended into reconstructed images. The proposed approach is systematically assessed using a dental phantom with two types of metal objects for qualitative and quantitative comparisons. Results: The proposed hybrid scheme provides improved image quality in areas surrounding the metal while preserving native structures. Conclusion: This study may significantly improve the detection of areas of interest in many dentomaxillofacial applications.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.8
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• pp.1996-2015
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• 2023

High-definition (HD) maps can provide precise road information that enables an autonomous driving system to effectively navigate a vehicle. Recent research has focused on leveraging semantic segmentation to achieve automatic annotation of HD maps. However, the existing methods suffer from low recognition accuracy in automatic driving scenarios, leading to inefficient annotation processes. In this paper, we propose a novel semantic segmentation method for automatic HD map annotation. Our approach introduces a new encoder, known as the convolutional transformer hybrid encoder, to enhance the model's feature extraction capabilities. Additionally, we propose a multi-level fusion module that enables the model to aggregate different levels of detail and semantic information. Furthermore, we present a novel decoupled boundary joint decoder to improve the model's ability to handle the boundary between categories. To evaluate our method, we conducted experiments using the Bird's Eye View point cloud images dataset and Cityscapes dataset. Comparative analysis against stateof-the-art methods demonstrates that our model achieves the highest performance. Specifically, our model achieves an mIoU of 56.26%, surpassing the results of SegFormer with an mIoU of 1.47%. This innovative promises to significantly enhance the efficiency of HD map automatic annotation.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.43 no.7 s.349
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• pp.50-57
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• 2006

Low-density parity-check (LDPC) codes are recently emerged due to its excellent performance. However, the parity check (H) matrices of the previous works are not adequate for hardware implementation of encoders or decoders. This paper proposes a hybrid parity check matrix which is efficient in hardware implementation of both decoders and encoders. The hybrid H-matrices are constructed so that both the semi-random technique and the partly parallel structure can be applied to design encoders and decoders. Using the proposed methods, the implementation of encoders can become practical while keeping the hardware complexity of the partly parallel decoder structures. An encoder and a decoder are designed using Verilog-HDL and compared with the previous results.