• Journal of Communications and Networks
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• v.18 no.1
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• pp.27-39
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• 2016

This paper derives and analyzes a novel block fast Fourier transform (FFT) based joint detection algorithm. The paper compares the performance and complexity of the novel block-FFT based joint detector to that of the Cholesky based joint detector and single user detection algorithms. The novel algorithm can operate at chip rate sampling, as well as higher sampling rates. For the performance/complexity analysis, the time division duplex (TDD) mode of a wideband code division multiplex access (WCDMA) is considered. The results indicate that the performance of the fast FFT based joint detector is comparable to that of the Cholesky based joint detector, and much superior to that of single user detection algorithms. On the other hand, the complexity of the fast FFT based joint detector is significantly lower than that of the Cholesky based joint detector and less than that of the single user detection algorithms. For the Cholesky based joint detector, the approximate Cholesky decomposition is applied. Moreover, the novel method can also be applied to any generic multiple-input-multiple-output (MIMO) system.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.3 no.3
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• pp.266-284
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• 2009

The challenges of rapidly growing numbers of mobile nodes in IPv6-based networks are being faced by mobile computing researchers worldwide. Recently, IETF has standardized Mobile IPv6 and Fast Handover for Mobile IPv6(FMIPv6) for supporting IPv6 mobility. Even though existing literatures have asserted that FMIPv6 generally improves MIPv6 in terms of handover speed, they did not carefully consider the details of the whole handover procedures. Therefore, in conventional protocols, the handover process reveals numerous problems manifested by a time-consuming network layer based movement detection and latency in configuring a new care of address with confirmation. In this article, we study the impact of the address configuration and confirmation procedure on the IP handover latency. To mitigate such effects, we propose a new scheme which can reduce the latency taken by the movement detection, address configuration and confirmation from the whole handover latency. Furthermore, a mathematical analysis is provided to show the benefits of our scheme. In the analysis, various parameters are used to compare our scheme with the current procedures, while our approach is focused on the reduction of handover latency. Finally, we demonstrate total handover scenarios for the proposed techniques and discussed the major factors which contribute to the handover latency.

• ETRI Journal
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• v.41 no.4
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• pp.473-482
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• 2019

High availability and reliability have been considered promising requirements for the support of seamless network services such as real-time video streaming, gaming, and virtual and augmented reality. Increased availability can be achieved within a local area network with the use of the virtual router redundancy protocol that utilizes backup routers to provide a backup path in the case of a master router failure. However, the network may still lose a large number of packets during a failover owing to a late failure detections and lazy responses. To achieve an efficient failover, we propose the implementation of fast detection with virtual router redundancy protocol (FDVRRP) in which the backup router quickly detects a link failure and immediately serves as the master router. We implemented the FDVRRP using open neutralized network operating system (OpenN2OS), which is an open-source-based network operating system. Based on the failover performance test of OpenN2OS, we verified that the FDVRRP exhibits a very fast failure detection and a failover with low-overhead packets.

• Journal of Korea Multimedia Society
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• v.21 no.3
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• pp.342-347
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• 2018

We proposed a fast detection of copy-move image forgery using four step search algorithm in the spatial domain. In the four-step search algorithm, the search area is 21 (-10 ~ +10), and the number of pixels to be scanned is 33. Our algorithm reduced computational complexity more than conventional copy move image forgery methods. The proposed method reduced 92.34 % of computational complexity compare to exhaustive search algorithm.

• Journal of Multimedia Information System
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• v.6 no.1
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• pp.1-6
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• 2019

In the field of industrial applications, the real-time performance of the target detection problem is very important. The most serious time consumption in the pedestrian detection process is the extraction phase of the candidate window. To accelerate the speed, in this paper, a fast extraction of pedestrian candidate window based on the BING (Binarized Normed Gradients) algorithm replaces the traditional sliding window scanning. The BING features are extracted with the positive and negative samples and input into the two-stage SVM (Support Vector Machine) classifier for training. The obtained BING template may include a pedestrian candidate window. The trained template is loaded during detection, and the extracted candidate windows are input into the classifier. The experimental results show that the proposed method can extract fewer candidate window and has a higher recall rate with more rapid speed than the traditional sliding window detection method, so the method improves the detection speed while maintaining the detection accuracy. In addition, the real-time requirement is satisfied.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.29 no.7B
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• pp.650-659
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• 2004

Domestic wireless network environment is changing rapidly while adapting to meet service requirements of users and growth of market. As a result, reliable data transmission using TCP is also expected to increase. Since TCP assumes that it is used in wired networt TCP suffers significant performance degradation over wireless network where packet losses are not always result of network congestion. Especially RTO imposes a great performance degradation of TCP. In this paper, we propose DAC$^{＋}$ and EFR in order to prevent performance degradation by quickly detecting and recovering loss without RTO during fast recovery. Compared with TCP NewReno, proposed scheme shows improvements in steady-state in terms of higher fast recovery Probability and reduced response time.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.7
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• pp.865-870
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• 2018

A machine vision based industrial inspection includes defects detection and classification. Fast inspection is a fundamental problem for many applications of real-time vision systems. It requires little computation time and localizing defects robustly with high accuracy. Deep learning technique have been known not to be suitable for real-time applications. Recently a couple of fast region-based CNN algorithms for object detection are introduced, such as Faster R-CNN, and YOLOv2. We apply these methods for an industrial inspection problem. Three CNN based detection algorithms, VOV based CNN, Faster R-CNN, and YOLOv2, are experimented for defect detection on metal surface. The results for inspection time and various performance indices are compared and analysed.

• Journal of the Institute of Convergence Signal Processing
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• v.16 no.2
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• pp.44-49
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• 2015

When the scene has less texture or when camera pose largely changes, the existing texture-based feature tracking methods are not reliable. Topology-based feature description methods, which use the geometric relationship between features such as LLAH, is a good alternative. However, they require feature detection methods with high performance. As a basic study on developing an effective feature detection method for topology-based feature description, this paper aims at examining their applicability to topology-based feature description by analyzing the repeatability of several feature detection methods that are included in the OpenCV library. Experimental results show that FAST outperforms the others.

• International Journal of Naval Architecture and Ocean Engineering
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• v.13 no.1
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• pp.187-193
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• 2021

In order to solve the problem of false terrains caused by environmental interferences and tunneling effect in the conventional multi-beam seafloor terrain detection, this paper proposed a seafloor topography detection method based on fast two-dimensional (2D) Censored Mean Level Detector-statistics Constant False Alarm Rate (CMLD-CFAR) method. The proposed method uses s cross-sliding window. The target occlusion phenomenon that occurs in multi-target environments can be eliminated by censoring some of the large cells of the reference cells, while the remaining reference cells are used to calculate the local threshold. The conventional 2D CMLD-CFAR methods need to estimate the background clutter power level for every pixel, thus increasing the computational burden significantly. In order to overcome this limitation, the proposed method uses a fast algorithm to select the Regions of Interest (ROI) based on a global threshold, while the rest pixels are distinguished as clutter directly. The proposed method is verified by experiments with real multi-beam data. The results show that the proposed method can effectively solve the problem of false terrain in a multi-beam terrain survey and achieve a high detection accuracy.

• ETRI Journal
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• v.38 no.4
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• pp.599-605
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• 2016

For the implementation of a real-time holographic camera, fast and automatic holographic image reconstruction is an essential technology. In this paper, we propose a new automatic depth-detection algorithm for fast holography reconstruction, which is particularly useful for optical scanning holography. The proposed algorithm is based on the inherent phase difference information in the heterodyne signals, and operates without any additional optical or electrical components. An optical scanning holography setup was created using a heterodyne frequency of 4 MHz with a 500-mm distance and 5-mm depth resolution. The reconstruction processing time was measured to be 0.76 s, showing a 62% time reduction compared to a recent study.