• Korean Journal of Optics and Photonics
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• v.17 no.5
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• pp.401-411
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• 2006

We propose an optical encryption/decryption technique for a security system based on 2-step phase-shifting digital holography. Phase-shilling digital holography is used for recording phase and amplitude information on a CCD device. 2-step phase-shifting is implemented by moving the PZT mirror with phase step of 0 or ${\pi}/2$. The binary data and the key are expressed with random code and random phase patterns. The digital hologram is a Fourier transform hologram and is recorded on CCD with 256 gray level quantization. We remove the DC term of the digital hologram fur data reconstruction, which is essential to reconstruct the original binary input data/image. The error evaluation fer the decrypted binary data is analyzed. One of errors is a quantization error in detecting the hologram intensity on CCD, and the other is generated from decrypting the data with the incorrect key. The technique using 2-step phase-shifting holography is more efficient than a 4-step method because 2-step phase-shifting holography system uses less data than the 4-step method for data storage or transmission. The simulation shows that the proposed technique gives good results fur the optical encryption of binary information.

• Journal of Industrial Technology
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• v.21 no.B
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• pp.67-74
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• 2001

According as the patterns of PCB (Printed Circuit Board) become denser and complicated, quality and accuracy of PCB influence the performance of final product. It's attempted to obtain trust of 100% about all of parts. Because human inspection in mass-production manufacturing facilities are both time-consuming and very expensive, the automation of visual inspection has been attempted for many years. Thus, automatic visual inspection of PCB is required. In this paper, we used an algorithm which compares the reference PCB patterns and the input PCB patterns are separated an object and a scene by filtering and edge detection. And than compare two image using pattern matching algorithm. We suggest an defect inspection algorithm in PCB pattern, to be satisfied low cost, high speed, high performance and flexibility on the basis of $640{\times}480$ binary pattern.

• Phonetics and Speech Sciences
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• v.3 no.4
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• pp.23-31
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• 2011

This paper examines the production patterns of the acquisition of coda consonants in monosyllabic words in English-speaking children with cochlear implants. The data come from the transcribed speech of children with cochlear implants. This study poses three questions. First, do children with cochlear implants acquire onset consonants earlier than codas? Second, do children's productions have a bimoraic-sized constraint that maintains binary feet? Third, what patterns emerge from production of coda consonants? The results revealed that children with cochlear implants acquire onset consonants earlier than codas. With regard to the bimoraic-sized constraints, the productions of vowel type (i.e., monomoraic and bimoraic) were more accurate for monomoraic vowels than bimoraic ones for some children with cochlear implants, although accuracy in vowel productions showed high proportion regardless of vowel types. The variations of coda production exhibited individual differences. Some children produced less sonorant consonants with high frequency and others produced more sonorant ones. The results of this study were similar to those pertaining to children with normal hearing. In the process of coda consonant acquisition, the error patterns of prosody-sensitive production may be regarded as articulatory challenges to produce higher-level prosodic structures.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.52 no.1
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• pp.35-41
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• 2003

In this paper, a machine vision system for recognizing and classifying the patterns and marks engraved by die molding or laser marking on the glass panels of computer monitors is suggested and evaluated experimentally. The vision system is equipped with a neural network and an NGC pattern classifier including searching process based on normalized grayscale correlation and adaptive binarization. This system is found to be applicable even to the cases in which the segmentation of the pattern area from the background using ordinary blob coloring technique is quite difficult. The inspection process is accomplished by the use of the NGC hypothesis and ANN verification. The proposed pattern recognition system is composed of three parts: NGC matching process and the preprocessing unit for acquiring the best quality of binary image data, a neural network-based recognition algorithm, and the learning algorithm for the neural network. Another contribution of this paper is the method of generating the training patterns from only a few typical product samples in place of real images of all types of good products.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.285-289
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• 1992

This paper describes a new optimization technique for the design of traffic signal patterns. The proposed method uses a Genetic Algorithm for searching through the better signal patterns. Since the Genetic Algorithm is effective to search directly through a huge binary coded state spaces, the proposed design method has the following advantages over the conventional OR methods: (1) on-line optimization is available within a reasonable time, (2) there is no limitation to the types of signals to be optimized. Some computer simulations are carried out and its ability of getting high quality control in a short period is demonstrated.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2726-2728
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• 2001

This paper describes an optimal synthesis method of binary neural network(BNN) for an approximation problem of a circular region using a newly proposed learning algorithm[7] Our object is to minimize the number of connections and neurons in hidden layer by using a Newly Expanded and Truncated Learning Algorithm(NETLA) for the multilayer BNN. The synthesis method in the NETLA is based on the extension principle of Expanded and Truncated Learning(ETL) and is based on Expanded Sum of Product (ESP) as one of the boolean expression techniques. And it has an ability to optimize the given BNN in the binary space without any iterative training as the conventional Error Back Propagation(EBP) algorithm[6] If all the true and false patterns are only given, the connection weights and the threshold values can be immediately determined by an optimal synthesis method of the NETLA without any tedious learning. Futhermore, the number of the required neurons in hidden layer can be reduced and the fast learning of BNN can be realized. The superiority of this NETLA to other algorithms was proved by the approximation problem of one circular region.

• Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT)
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• v.19 no.3
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• pp.353-366
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• 2021

The solubilities of different multicomponent lanthanide oxide (Ln₂O₃) solid solutions including binary (Ln₁ and Ln₂ = La, Nd, Eu, or Tm), ternary (Ln₁, Ln₂, and Ln₃ = La, Nd, Eu, or Tm), and higher systems (Ln = La, Ce, Pr, Nd, Sm, Eu, Gd, Tb, Dy, Ho, Er, Tm, Yb, and Lu) were studied after aging for four weeks at 60℃. Our recent study revealed that the phase transformations in binary ((La, Nd) and (La, Eu)) and ternary (La, Nd, Eu) systems are responsible for the formation of (La, Nd)(OH)₃, (La, Eu)(OH)₃, and (La, Nd, Eu)(OH)₃ solid solutions, respectively. The variations in the mole fractions of La³⁺, Nd³⁺, and Eu³⁺ in the sample solutions of these hydroxide solid solutions indicated that a thermodynamic equilibrium might account for the apparent La, Nd, and Eu solubilities. Conversely, the binary and ternary systems containing Tm₂O₃ as the heavy lanthanide oxide retained the oxide-based solid solutions, and their solubility behaviors were dominated by their congruent dissolutions. In the higher multicomponent system, the X-ray diffraction patterns of the solid phases, before and after contact with the aqueous phase indicated the formation of a stable oxide solid solution and their solubility behavior was explained by its congruent dissolution.

• Journal of KIISE:Software and Applications
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• v.34 no.7
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• pp.585-594
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• 2007

The back propagation algorithm took a long time to learn the input patterns and was difficult to train the additional or repeated learning patterns. So Aleksander proposed the binary neural network which could overcome the disadvantages of BP Network. But it had the limitation of repeated learning and was impossible to extract a generalized pattern. In this paper, we proposed a dynamic 3 dimensional Neuro System which was consisted of a learning network which was based on weightless neural network and a feedback module which could accumulate the characteristic. The proposed system was enable to train additional and repeated patterns. Also it could be produced a generalized pattern by putting a proper threshold into each learning-net's discriminator which was resulted from learning procedures. And then we reused the generalized pattern to elevate the recognition rate. In the last processing step to decide right category, we used maximum response detector. We experimented using the MNIST database of NIST and got 99.3% of right recognition rate for training data.

• Journal of Electrical Engineering and Technology
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• v.10 no.5
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• pp.2142-2148
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• 2015

This paper proposes novel real-time footstep planning and following methods for the navigation of humanoid robots. A footstep command is defined by a walking direction and step lengths for footstep planning. The walking direction is determined by a uni-vector field navigation method, and the allowable yawing range caused by hardware limitation is considered. The lateral step length is determined to avoid collisions between the two legs while walking. The sagittal step length is modified by a binary search algorithm when collision occurs between the robot body and obstacles in a narrow space. If the robot body still collides with obstacles despite the modification of the sagittal step length, the lateral step length is shifted at the next footstep. For footstep following, a walking pattern generator based on a 3-D linear inverted pendulum model is utilized, which can generate modifiable walking patterns using the zero-moment point variation scheme. Therefore, it enables a humanoid robot to follow the footstep command planned for each footstep. The effectiveness of the proposed method is verified through simulation and experiment.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1602-1605
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• 1987

This paper describes the isolated word recognition using binary patterns denoting the presence or absence of a local peak at a particular channel. In closed test, 81.3% and 76.8% of correct recognition rate were achieved in case of 10 males and 10 females with each 1588 test samples.