• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.4
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• pp.1373-1391
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• 2022

We investigate mobile multiple-input multiple-output (MIMO) molecular communication via diffusion (MCvD) system which is consisted of two source nodes, two destination nodes and one relay node in the mobile three-dimensional channel. First, the combinations of decode-and-forward (DF) relaying protocol and network coding (NC) scheme are implemented at relay node. The adaptive thresholds at relay node and destination nodes can be obtained by maximum a posteriori (MAP) probability detection method. Then the mathematical expressions of the average bit error probability (BEP) of this mobile MIMO MCvD system based on DF and NC scheme are derived. Furthermore, in order to minimize the average BEP, we establish the optimization problem with optimization variables which include the ratio of the number of emitted molecules at two source nodes and the initial position of relay node. We put forward an iterative scheme based on block coordinate descent algorithm which can be used to solve the optimization problem and get optimal values of the optimization variables simultaneously. Finally, the numerical results reveal that the proposed iterative method has good convergence behavior. The average BEP performance of this system can be improved by performing the joint optimizations.

• Journal of IKEEE
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• v.26 no.4
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• pp.524-530
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• 2022

When radar return contains strong jammers along with ground clutter echo, a STAP(space-time adaptive processing) algorithms tend to suppress jammer components more severely than it does the clutter. This hinders moving target detection in that the target echo is apt to be buried by clutter echo. This paper presents a two-step STAP algorithm in which the pre-suppression of jammer by the spatial filtering is applied, prior to applying the STAP algorithm. We propose how to find the coefficients of the spatial filter and show that the spatial filtering barely alter the spectra of the target and the clutter echo, having only to suppress the jammers. Finally, we simulate a STAP scenario with strong jammers and show the proposed algorithm can improve STAP performance.

• Current Optics and Photonics
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• v.7 no.4
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• pp.345-353
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• 2023

We propose a turbulence-tolerant Manchester on-off keying (M-OOK) transmission for free-space optical (FSO) communication. At the transmitter end, a M-OOK signal featuring a spectrum with low-frequency components absent is modulated and transmitted into a turbulent channel. At the receiver end, a low-pass filter (LPF) -based adaptive-threshold decision (ATD) with LPF-extracted channel-state information (CSI) and a high-pass filter (HPF)-based fixed-threshold decision (FTD) are employed to compensate for the effects of turbulence, owing to the low-frequency spectral characteristics of the turbulent channel. The performance of LPF-based ATD and HPF-based FTD are evaluated for various cutoff frequencies for the LPF and HPF. Besides, the proposed M-OOK transmission is compared to conventional non-return-to-zero OOK (NRZ-OOK) for different data rates. The proposed technique is verified in simulation. The simulation results show that the proposed M-OOK detection with optimized cutoff frequencies of LPF and HPF has better bit-error-rate (BER) performance compared to NRZ-OOK, and it is close to the theoretical ATD with the knowledge of precise CSI under various degrees of turbulence effects.

• Current Optics and Photonics
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• v.8 no.1
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• pp.30-37
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• 2024

Implemented at the Geochang Observatory in South Korea, our slope detection and ranging (SLO-DAR) system features a 508 mm Cassegrain telescope (f /7.8), incorporating two Shack-Hartmann wave-front sensors (WFS) for precise measurements of atmospheric phase distortions, particularly from nearby binary or double stars, utilizing an 8 × 8 grid of sampling points. With an ability to reconstruct eight-layer vertical atmospheric profiles, the system quantifies the refractive index structure function (C_n²) through the crossed-beam method. Adaptable in vertical profiling altitude, ranging from a few hundred meters to several kilometers, contingent on the separation angle of binary stars, the system operates in both wide (2.5 to 12.5 arcminute separation angle) and narrow modes (11 to 15 arcsecond separation angle), covering altitudes from 122.3 to 611.5 meters and 6.1 to 8.3 kilometers, respectively. Initial measurements at the Geochang Observatory indicated C_n² values up to 181.7 meters with a Fried parameter (r₀) of 8.4 centimeters in wide mode and up to 7.8 kilometers with an r₀ of 8.0 centimeters in narrow mode, suggesting similar seeing conditions to the Bohyun Observatory and aligning with a comparable 2014-2015 seeing profiling campaign in South Korea.

• Journal of Digital Convergence
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• v.10 no.10
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• pp.215-220
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• 2012

This paper proposes a ontology of tree structure approach for adaptive object recognition in a situation-variant environment. In this paper, we introduce a new concept, ontology of tree structure ontology, for context sensitivity, as we found that many developed systems work in a context-invariant environment. Due to the effects of illumination on a supreme obstinate designing context-sensitive recognition system, we have focused on designing such a context-variant system using ontology of tree structure. Ontology can be defined as an explicit specification of conceptualization of a domain typically captured in an abstract model of how people think about things in the domain. People produce ontologies to understand and explain underlying principles and environmental factors. In this research, we have proposed context ontology, context modeling, context adaptation, and context categorization to design ontology of tree structure based on illumination criteria. After selecting the proper light-ontology domain, we benefit from selecting a set of actions that produces better performance on that domain. We have carried out extensive experiments on these concepts in the area of object recognition in a dynamic changing environment, and we have achieved enormous success, which will enable us to proceed on our basic concepts.

• Journal of Sensor Science and Technology
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• v.11 no.2
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• pp.84-92
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• 2002

A $32{\times}32$ pixels foveated (linear-polar) structure retina chip with the function of local-light adaptation for edge detection has been designed and fabricated using CMOS technology. Human retina can detect a wide range of light intensity. In this study, we use the biologically-inspired visual signal processing mechanism that consists of photoreceptors, horizontal cells, and bipolar cells in order to implement the function of edge detection in the retina chip. For a local-light adaptive function, the size of receptive field is changed locally according to the input light intensity. The spatial distribution of sensing pixels in the foveated retina chip has the advantages of selective reduction of image data and good resolution in central part to carry out the elaborate image processing with still enough resolution in the outer parts. The designed chip has been fabricated using standard $0.6\;{\mu}m$ double-poly triple-metal CMOS technology and optimized using HSPICE simulator.

• KIPS Transactions on Computer and Communication Systems
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• v.11 no.1
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• pp.23-34
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• 2022

With the development of network technology, the application area has also been diversified, and protocols for various purposes have been developed and the amount of traffic has exploded. Therefore, it is difficult for the network administrator to meet the stability and security standards of the network with the existing traditional switching and routing methods. Software Defined Networking (SDN) is a new networking paradigm proposed to solve this problem. SDN enables efficient network management by programming network operations. This has the advantage that network administrators can flexibly respond to various types of attacks. In this paper, we design a threat level management module, an attack detection module, a packet statistics module, and a flow rule generator that collects attack information through the controller and switch, which are components of SDN, and detects attacks based on these attributes of SDN. It proposes a method to block denial of service attacks (DoS) of advanced attackers by programming and applying honeypot. In the proposed system, the attack packet can be quickly delivered to the honeypot according to the modifiable flow rule, and the honeypot that received the attack packets analyzed the intelligent attack pattern based on this. According to the analysis results, the attack detection module and the threat level management module are adjusted to respond to intelligent attacks. The performance and feasibility of the proposed system was shown by actually implementing the proposed system, performing intelligent attacks with various attack patterns and attack levels, and checking the attack detection rate compared to the existing system.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.87-96
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• 2014

In this paper, we propose a directionally adaptive aliasing and noise removal using dictionary learning based on space-frequency analysis. The proposed aliasing and noise removal algorithm consists of two modules; i) aliasing and noise detection using dictionary learning and analysis of frequency characteristics from the combined wavelet-Fourier transform and ii) aliasing removal with suppressing noise based on the directional shrinkage in the detected regions. The proposed method can preserve the high-frequency details because aliasing and noise region is detected. Experimental results show that the proposed algorithm can efficiently reduce aliasing and noise while minimizing losses of high-frequency details and generation of artifacts comparing with the conventional methods. The proposed algorithm is suitable for various applications such as image resampling, super-resolution image, and robot vision.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.46 no.1
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• pp.23-31
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• 2009

Recently, biometric techniques such as face recognition, finger-print recognition and iris recognition have been widely applied for various applications including door access control, finance security and electric passport. This paper presents the method of using finger-vein pattern for the personal identification. In general, when the finger-vein image is acquired from the camera, various conditions such as the penetrating amount of the infrared light and the camera noise make the segmentation of the vein from the background difficult. This in turn affects the system performance of personal identification. To solve this problem, we propose the novel and fast method for extracting the finger-vein region. The proposed method has two advantages compared to the previous methods. One is that we adopt a locally adaptive thresholding method for the binarization of acquired finger-vein image. Another advantage is that the simple morphological opening and closing are used to remove the segmentation noise to finally obtain the finger-vein region from the skeletonization. Experimental results showed that our proposed method could quickly and exactly extract the finger-vein region without using various kinds of time-consuming filters for preprocessing.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.44 no.2 s.314
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• pp.116-125
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• 2007

In this paper, we propose a illumination environment adaptive real-time surveillance system for security of important area such as military bases, prisons, and strategic infra structures. The proposed system recognizes movement of objects on the bright environments as well as in dark illumination. The procedure of proposed system may be summarized as follows. First, the system discriminates between bright and dark with input image distribution. Then, if the input image is dark, the system has a pre-processing. The Multi-scale Retinex Color Restoration(MSRCR) is processed to enhance the contrast of image captured in dark environments. Secondly, the enhanced input image is subtracted with the revised background image. And then, we take a morphology image processing to obtain objects correctly. Finally, each bounding box enclosing each objects are tracked. The center point of each bounding box obtained by the proposed algorithm provides more accurate tracking information. Experimental results show that the proposed system provides good performance even though an object moves very fast and the background is quite dark.