• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.17 no.12 s.115
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• pp.1249-1258
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• 2006

Two-dimensional(2-D) radar images, namely, ISAR images from a maneuvering target include unwanted phase errors due to the target's motion. These phase errors make ISAR images to be blurred. The ISAR autofocus technique is required in order to remove these unwanted phase errors. Unless those unwanted phase errors produced by the target's motion are removed prior to target identification, we cannot expect a reliable target identification performance. In this paper, we use the entropy-based ISAR autofocus technique which consists of two steps: range alignment and phase adjustment. We analyze a relationship between the number of sampling point and a image quality in a range alignment algorithm and also analyze a technique for reducing computation time of the SSA(Stage-by-Stage Approachng) algorithm in a phase adjustment.

• Proceedings of the KSRS Conference
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• 2007.10a
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• pp.629-632
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• 2007

While conventional interferometric SAR (InSAR) technique is an excellent tool for displacement observation, it is only sensitive to one-dimensional deformation along the satellite's line-of-sight (LOS). Recently, a multiple aperture interferogram (MAI) technique has been developed to overcome this drawback. This method successfully extracted along-track displacements from InSAR data, based on split-beam InSAR processing, to create forward- and backward- looking interferograms, and was superior to along-track displacements derived by pixel-offset algorithm. This method is useful to measure along-track displacements. However, it does not only decrease the coherence of MAI because three co-registration and resampling procedures are required for producing MAI, but also is confined to a suitable interferometric pair of SAR images having zero Doppler centroid. In this paper, we propose an efficient and robust method to generate MAI from interferometric pair having non-zero Doppler centroid. The proposed method efficiently improves the coherence of MAI, because the co-registration of forward- and backward- single look complex (SLC) images is carried out by time shift property of Fourier transform without resampling procedure. It also successfully removes azimuth flat earth and topographic phases caused by the effect of non-zero Doppler centroid. We tested the proposed method using ERS images of the Mw 7.1 1999 California, Hector Mine Earthquake. The result shows that the proposed method improved the coherence of MAI and generalized MAI processing algorithm.

• Journal of information and communication convergence engineering
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• v.9 no.1
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• pp.83-88
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• 2011

Abstract. Image segmentation is always a challenging task in computer vision as well as in pattern recognition. Nowadays, this method has great importance in the field of stereo vision. The disparity information extracting from the binocular image pairs has essential relevance in the fields like Stereoscopic (3D) Imaging Systems, Virtual Reality and 3D Graphics. The term 'disparity' represents the horizontal shift between left camera image and right camera image. Till now, many methods are proposed to visualize or estimate the disparity. In this paper, we present a new technique to visualize the horizontal disparity between two stereo images based on image segmentation method. The process of comparing left camera image with right camera image is popularly known as 'Stereo-Matching'. This method is used in the field of stereo vision for many years and it has large contribution in generating depth and disparity maps. Correlation based stereo-matching are used most of the times to visualize the disparity. Although, for few stereo image pairs it is easy to estimate the horizontal disparity but in case of some other stereo images it becomes quite difficult to distinguish the disparity. Therefore, in order to visualize the horizontal disparity between any stereo image pairs in more robust way, a novel stereo-matching algorithm is proposed which is named as "Quadtree Segmentation of Pixels Disparity Estimation (QSPDE)".

• Journal of the Korean Institute of Intelligent Systems
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• v.20 no.1
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• pp.116-122
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• 2010

This paper proposes a method for classifying targets robust to geometric transformations of targets such as rotation, scale change, translation, and pose change. Targets which have rotation, scale change, and shift is firstly classified based on CM(Confidence Map) which is generated by similarity, scale ratio, and range of orientation for SIFT(Scale-Invariant Feature Transform) feature vectors. On the other hand, DB(DataBase) which is acquired in various angles is used to deal with pose variation of targets. Range of the angle is determined by comparing and analyzing the execution time and performance for sampling intervals. We experiment on various images which is geometrically changed to evaluate performance of proposed target classification method. Experimental results show that the proposed algorithm has a good classification performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• v.9 no.1
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• pp.315-318
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• 2005

Recently, the advent of wireless communication and other handhold devices like Personal Digital Assistants and smart cards have made in implementation of cryptosystems a major issue. One important aspect of modern day ciphers is the scope for hardware sharing between the encryption and decryption algorithm. The cellular Automata which have been proposed as an alternative to linear feedback shift registers(LFSRs) can be programmed to perform the operations without using any dedicated hardware. But to generalize and analyze CA is not easy. In this paper, we characterizes uniform/hybird complemented group CA with rules 195/153/51 that divide the entire state space into smaller spaces of maximal equal lengths. This properties can be useful in constructing key agreement algorithm.

• KIPS Transactions on Computer and Communication Systems
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• v.1 no.1
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• pp.11-20
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• 2012

Stream data shows a sequence of values changing continuously over time. Due to the nature of stream data, its trend is continuously changing according to various time intervals. Therefore the prediction of stream data must be carried out simultaneously with respect to multiple intervals, i.e. Continuous Multiple Prediction(CMP). In this paper, we propose a Continuous Integrated Hierarchical Temporal Memory (CIHTM) network for CMP based on the Hierarchical Temporal Memory (HTM) model which is a neocortex leraning algorithm. To develop the CIHTM network, we created three kinds of new modules: Shift Vector Senor, Spatio-Temporal Classifier and Multiple Integrator. And also we developed learning and inferencing algorithm of CIHTM network.

• Smart Structures and Systems
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• v.13 no.2
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• pp.203-217
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• 2014

Due to the shift in paradigm from passive control to adaptive control, smart tuned mass dampers (STMDs) have received considerable attention for vibration control in tall buildings and bridges. STMDs are superior to tuned mass dampers (TMDs) in reducing the response of the primary structure. Unlike TMDs, STMDs are capable of accommodating the changes in primary structure properties, due to damage or deterioration, by tuning in real time based on a local feedback. In this paper, a novel adaptive-length pendulum (ALP) damper is developed and experimentally verified. Length of the pendulum is adjusted in real time using a shape memory alloy (SMA) wire actuator. This can be achieved in two ways i) by changing the amount of current in the SMA wire actuator or ii) by changing the effective length of current carrying SMA wire. Using an instantaneous frequency tracking algorithm, the dominant frequency of the structure can be tracked from a local feedback signal, then the length of pendulum is adjusted to match the dominant frequency. Effectiveness of the proposed ALP-STMD mechanism, combined with the STFT frequency tracking control algorithm, is verified experimentally on a prototype two-storey shear frame. It has been observed through experimental studies that the ALP-STMD absorbs most of the input energy associated in the vicinity of tuned frequency of the pendulum damper. The reduction of storey displacements up to 80 % when subjected to forced excitation (harmonic and chirp-signal) and a faster decay rate during free vibration is observed in the experiments.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.21 no.6
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• pp.163-171
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• 2021

In this paper, the energy transaction system was optimized by applying a resource allocation algorithm and deep reinforcement learning in the distributed power system. The power demand and supply environment were predicted by deep reinforcement learning. We propose a system that pursues common interests in power trading and increases the efficiency of long-term power transactions in the paradigm shift from conventional centralized to distributed power systems in the power trading system. For a realistic energy simulation model and environment, we construct the energy market by learning weather and monthly patterns adding Gaussian noise. In simulation results, we confirm that the proposed power trading systems are cooperative with each other, seek common interests, and increase profits in the prolonged energy transaction.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.10
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• pp.3815-3833
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• 2021

MILP-based automatic search is the most common method in analyzing the security of cryptographic algorithms. However, this method brings many issues such as low efficiency due to the large size of the model, and the difficulty in finding the contradiction of the impossible differential distinguisher. To analyze the security of ESF algorithm, this paper introduces a simplified MILP-based search model of the differential distinguisher by reducing constrains of XOR and S-box operations, and variables by combining cyclic shift with its adjacent operations. Also, a new method to find contradictions of the impossible differential distinguisher is proposed by introducing temporary variables, which can avoid wrong and miss selection of contradictions. Based on a 9-round impossible differential distinguisher, 15-round attack of ESF can be achieved by extending forward and backward 3-round in single-key setting. Compared with existing results, the exact lower bound of differential active S-boxes in single-key setting for 10-round ESF are improved. Also, 2108 9-round impossible differential distinguishers in single-key setting and 14 12-round impossible differential distinguishers in related-key setting are obtained. Especially, the round of the discovered impossible differential distinguisher in related-key setting is the highest, and compared with the previous results, this attack achieves the highest round number in single-key setting.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.33 no.2
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• pp.183-191
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• 2023

Cryptographic algorithms require extensive computational resources and rely on complex mathematical principles for security. However, IoT devices have limited resources, leading to insufficient computing power. As a result, lightweight cryptography has emerged, which uses fewer computational resources. NIST organized a competition to standardize lightweight cryptography and TinyJAMBU, one of the algorithms in the competition, is a permutation-based algorithm that repeats many permutation operations. In this paper, we implement TinyJAMBU on an 8-bit AVR processor with a proposedtechnique that includes a reverse shift method and precomputing some operations in a fixed key and nonce environment. Our techniques showed a maximum performance improvement of 7.03 times in permutation operations and 5.87 times in the TinyJAMBU algorithm, improving up to 9.19 times in a fixed key and nonce environment.