• Journal of the Institute of Electronics and Information Engineers
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• v.50 no.1
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• pp.225-231
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• 2013

In this study, we propose the design of optimized pRBFNNs-based night vision face recognition system using PCA algorithm. It is difficalt to obtain images using CCD camera due to low brightness under surround condition without lighting. The quality of the images distorted by low illuminance is improved by using night vision camera and histogram equalization. Ada-Boost algorithm also is used for the detection of face image between face and non-face image area. The dimension of the obtained image data is reduced to low dimension using PCA method. Also we introduce the pRBFNNs as recognition module. The proposed pRBFNNs consists of three functional modules such as the condition part, the conclusion part, and the inference part. In the condition part of fuzzy rules, input space is partitioned by using Fuzzy C-Means clustering. In the conclusion part of rules, the connection weights of pRBFNNs is represented as three kinds of polynomials such as linear, quadratic, and modified quadratic. The essential design parameters of the networks are optimized by means of Differential Evolution.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.42 no.8 s.338
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• pp.1-6
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• 2005

A dual-level low voltage differential signalling (DLVDS) circuit is proposed aiming at reducing transmission lines for LCD driver IC. In the proposed circuit, we apply a couple of primitive data to DLVDS circuit as inputs. The transmitter converts two inputs to two kinds of fully differential level signals. In this circuit, two transmission lines are sufficient to transfer two primitive inputs while keeping the LVDS feature. The receiver recovers The original input data through a level decoding circuit. We fabricated the proposed circuit using $0.25\mu m$ CMOS technology. The resultant circuit shows 1-Gbps/2-line data rate and 35-mW power consumption at 2.5V supply voltage, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.1
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• pp.476-496
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• 2018

With the advancement and deployment of wireless communication techniques, wireless body area network (WBAN) has emerged as a promising approach for e-healthcare that collects the data of vital body parameters and movements for sensing and communicating wearable or implantable healthful related information. In order to avoid any possible rancorous attacks and resource abuse, employing lightweight ciphers is most effective to implement encryption, decryption, message authentication and digital signature for security of WBAN. As a typical lightweight cryptosystem with an extended sponge function framework, the PHOTON family is flexible to provide security for the RFID and other highly-constrained devices. In this paper, we propose a differential fault analysis to break three flavors of the PHOTON family successfully. The mathematical analysis and simulating experimental results show that 33, 69 and 86 random faults in average are required to recover each message input for PHOTON-80/20/16, PHOTON-160/36/36 and PHOTON-224/32/32, respectively. It is the first result of breaking PHOTON with the differential fault analysis. It provides a new reference for the security analysis of the same structure of the lightweight hash functions in the WBAN.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.1
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• pp.536-551
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• 2017

With the advancement and deployment of leading-edge telecommunication technologies for sensing and collecting, computing related information, Cloud of Things (CoTs) has emerged as a typical application platform that is envisioned to revolutionize the daily activities of human society, such as intelligent transportation, modern logistics, food safety, environmental monitoring, etc. To avoid any possible malicious attack and resource abuse, employing hash functions is widely recognized as one of the most effective approaches for CoTs to achieve message integrity and data authentication. The Whirlpool hash function has served as part of the joint ISO/IEC 10118-3 International Standard by the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC). In this paper, we propose an effective differential fault analysis on Whirlpool in the byte-oriented random fault model. The mathematical analysis and experimental results show that 8 random faults on average are required to obtain the current 512-bit message input of whirlpool and the secret key of HMAC-Whirlpool. Our work demonstrates that Whirlpool and HMAC-Whirlpool are both vulnerable to the single byte differential fault analysis. It provides a new reference for the security analysis of the same structure of the hash functions in the CoTs.

• Journal of The Korean Astronomical Society
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• v.47 no.2
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• pp.49-67
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• 2014

A novel method to characterize the topology of the early-universe intergalactic medium during the epoch of cosmic reionization is presented. The 21-cm radiation background from high redshift is analyzed through calculation of the 2-dimensional (2D) genus. The radiative transfer of hydrogen- ionizing photons and ionization-rate equations are calculated in a suite of numerical simulations under various input parameters. The 2D genus is calculated from the mock 21-cm images of high-redshift universe. We construct the 2D genus curve by varying the threshold differential brightness temperature, and compare this to the 2D genus curve of the underlying density field. We find that (1) the 2D genus curve reflects the evolutionary track of cosmic reionization and (2) the 2D genus curve can discriminate between certain reionization scenarios and thus indirectly probe the properties of radiation-sources. Choosing the right beam shape of a radio antenna is found crucial for this analysis. Square Kilometre Array (SKA) is found to be a suitable apparatus for this analysis in terms of sensitivity, even though some deterioration of the data for this purpose is unavoidable under the planned size of the antenna core.

• Journal of IKEEE
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• v.18 no.2
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• pp.220-227
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• 2014

This paper presents a control method of Single-Inductor Dual-Output DC-DC Converter using Common mode feedback and differential feedback loops. To generate duty used for differential mode feedback loop, this paper propose relative sawtooth circuit using current divider circuit which makes ramp signal with variable dead-time. Two outputs of the Single-Inductor Dual-Output DC-DC Converter are specified for 2.8 V and 4.2 V with input voltage 2.5 V. The maximum conversion efficiency of designed SIDO DC-DC Converter is 95% at total output power of 539mW. Cross regulations of Boost1 and Boost2 are 3.57% and 4% each, when increasing twice times output current.

• The KIPS Transactions:PartB
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• v.15B no.6
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• pp.603-608
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• 2008

In this paper an approach to building fuzzy model to predict daily open, close, high, and low stock prices is presented. One of prior problems in building a stock prediction model is to select most effective indicators for the stock prediction. The problem is overcome by the selection of information used in the analysis of stick-chart as the input variables of our fuzzy model. The fuzzy rules have the premise and the consequent, in which they are composed of trapezoidal membership functions, and nonlinear equations, respectively. DE(Differential Evolution) searches optimal fuzzy rules through an evolutionary process. To evaluate the effectiveness of the proposed approach numerical example is considered. The fuzzy models to predict open, high, low, and close prices of KOSPI(KOrea composite Stock Price Index) on a daily basis are built, and their performances are demonstrated and compared with those of neural network.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.49 no.5
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• pp.30-36
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• 2012

A new BIST(Built-In Self-Test) scheme to test ADC(Analog-to-Digital Converter) with a transition detector is proposed. The proposed BIST is able to replaces histogram method, the most popular approach in static testing of ADC. With a ramp signal as an input test stimulus, the proposed BIST calculates ADC's static parameters such as offset, gain, INL(Integral Non-Linearity) and DNL(Differential Non-Linearity). The three detectors in the proposed BIST can deal with a transient zone problem, a phenomenon due to random noise in real test environments and are cost efficient at various acceptable ranges determined as a test spec. The simulation results validate that our method performs accurate static test and show the reduction of the hardware overhead.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.27 no.10
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• pp.941-944
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• 2016

This paper proposes 24 GHz power amplifier for automotive collision avoidance and surveillance short range radar using Samsung 65-nm CMOS process. The proposed circuit has a 2-stage differential power amplifier which includes common source structure and transformer for single to differential conversion, impedance matching, and power combining. The measurement results show 15.5 dB maximum voltage gain and 3.6 GHz 3 dB bandwidth. The measured maximum output power is 13.1 dBm, input $P1_{dB}$ is -4.72 dBm, output $P1_{dB}$ is 9.78 dBm, and maximum power efficiency is 17.7 %. The power amplifier consumes 74 mW DC power from 1.2 V supply voltage.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.61 no.5
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• pp.744-752
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• 2012

In this study, the Polynomial-based Radial Basis Function Neural Networks is proposed as an one of the recognition part of overall face recognition system that consists of two parts such as the preprocessing part and recognition part. The design methodology and procedure of the proposed pRBFNNs are presented to obtain the solution to high-dimensional pattern recognition problems. In data preprocessing part, Principal Component Analysis(PCA) which is generally used in face recognition, which is useful to express some classes using reduction, since it is effective to maintain the rate of recognition and to reduce the amount of data at the same time. However, because of there of the whole face image, it can not guarantee the detection rate about the change of viewpoint and whole image. Thus, to compensate for the defects, Linear Discriminant Analysis(LDA) is used to enhance the separation of different classes. In this paper, we combine the PCA&LDA algorithm and design the optimized pRBFNNs for recognition module. The proposed pRBFNNs architecture consists of three functional modules such as the condition part, the conclusion part, and the inference part as fuzzy rules formed in 'If-then' format. In the condition part of fuzzy rules, input space is partitioned with Fuzzy C-Means clustering. In the conclusion part of rules, the connection weight of pRBFNNs is represented as two kinds of polynomials such as constant, and linear. The coefficients of connection weight identified with back-propagation using gradient descent method. The output of the pRBFNNs model is obtained by fuzzy inference method in the inference part of fuzzy rules. The essential design parameters (including learning rate, momentum coefficient and fuzzification coefficient) of the networks are optimized by means of Differential Evolution. The proposed pRBFNNs are applied to face image(ex Yale, AT&T) datasets and then demonstrated from the viewpoint of the output performance and recognition rate.