• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.10
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• pp.166-174
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• 1998

Neural networks, having highly nonlinear dynamics by virtue of the distributed nonlinearities and the learing ability, have the potential for the adaptive prediction of nonstationary signals. This paper describes the nonlinear prediction of these signals in two ways; using a nonlinear module and the cascade combination of nonlinear and linear modules. Fully-connected recurrent neural networks (RNNs) and a conventional tapped-delay-line (TDL) filter are used as the nonlinear and linear modules respectively. The dynamic behavior of the proposed predictors is demonstrated for chaotic time series adn speech signals. For the relative comparison of prediction performance, the proposed predictors are compared with a conventional ARMA linear prediction model. Experimental results show that the neural networks based adaptive predictor ourperforms the traditional linear scheme significantly. We also find that the cascade combination predictor is well suitable for the prediction of the time series which contain large variations of signal amplitude.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.41 no.7
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• pp.683-689
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• 2017

We have carried out the development for hydraulic breaker which can be operated by optimal mode with ICT convergence technology. This developed system can predict the rock properties. Moreover, this system can maximize the energy efficient with intelligent control of hydraulic system. In order to provide the optimal impact force, this system can measure the descending depth of piston with the proximity sensor and discriminate the rock properties with the measuring data and control the piston stroke using solenoid valve eventually. In addition, we have developed the controller, display module and operating device for cascade (multi-level impact) system and applied the module which can communicate each system by wireless communications. In conclusion, the control system which can control the multi-level impact in accordance with strength of rocks has been developed and approved by several field tests.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.44 no.4
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• pp.43-54
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• 2007

This paper presents design and verification of a face detection hardware for real time application. Face detection algorithm detects rough face position based on already acquired feature parameter data. The hardware is composed of five main modules: Integral Image Calculator, Feature Coordinate Calculator, Feature Difference Calculator, Cascade Calculator, and Window Detection. It also includes on-chip Integral Image memory and Feature Parameter memory. The face detection hardware was verified by using S3C2440A CPU of Samsung Electronics, Virtex4LX100 FPGA of Xilinx, and a CCD Camera module. Our design uses 3,251 LUTs of Xilinx FPGA and takes about 1.96${\sim}$0.13 sec for face detection depending on sliding-window step size, when synthesized for Virtex4LX100 FPGA. When synthesized on Magnachip 0.25um ASIC library, it uses about 410,000 gates (Combinational area about 345,000 gates, Noncombinational area about 65,000 gates) and takes less than 0.5 sec for face realtime detection. This size and performance shows that it is adequate to use for embedded system applications. It has been fabricated as a real chip as a part of XF1201 chip and proven to work.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.705-708
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• 2018

Among biometrics commercialized for security, iris recognition technology has the most excellent security for the probability of the match between individuals is the lowest. Current commercialized iris recognition technology has excellent recognition ability, but this technology has a fatal drawback. Without the user's active cooperation, it cannot recognize the iris correctly. To make up for this weakness, recent trend of iris recognition development mounts a non-volunteering, unconstrained method. According to this information, the objective of this research is developing a module that can identify people iris from a video acquired by high performance infrared camera in a range of 3m and in a involuntary way. For this, we import images from the video and find people's face and eye positions from the images using Haar classifier trained through Cascade training method. finally, we crop the iris by Hough circle transform and compare it with data from the database to identify people.

• Membrane Journal
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• v.21 no.2
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• pp.177-192
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• 2011

Hollow fiber membrane using CTA polymers were prepared by the phase separation method for the separation and purification of biogas and the hollow fiber gas separation membrane modules with the effective surface area of 0.17 $m^2$ were prepared. The pure gas permeation properties of membrane modules for methane, oxygen and carbon dioxide were measured. The permeance of $CO_2$ and $CH_4$were 0.46 GPU and 18.52 GPU, respectively, therefore, the high $CO_2$/$CH_4$ selectivity of 40.4 was obtained. The separation and purification test for 4 different simulated mixed gases were carried out after the pure gas test and the gas concentration and flux of the permeate at the various stage-cut were measured from the 1 stage, 2 stage, and 3 stage cascade of membrane modules. In the 1 stage test, the concentration of $CH_4$ increased as the increase of the stage-cut, while the $CH_4$ recovery efficiency ratio decreased. In the 2 stage test, the $CH_4$ recovery efficiency ratio increased compared to the 1 stage. The 3 stage test was employed to reduce the loss of $CH_4$ in biogas and the result showed less than 5% of $CH_4$ recovery loss.

• Proceedings of the Microbiological Society of Korea Conference
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• 2007.05a
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• pp.120-122
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• 2007

All living organisms use numerous signal-transduction pathways to sense and respond to their environments and thereby survive and proliferate in a range of biological niches. Molecular dissection of these signalling networks has increased our understanding of these communication processes and provides a platform for therapeutic intervention when these pathways malfunction in disease states, including infection. Owing to the expanding availability of sequenced genomes, a wealth of genetic and molecular tools and the conservation of signalling networks, members of the fungal kingdom serve as excellent model systems for more complex, multicellular organisms. Here, we employed Cryptococcus neoformans as a model system to understand how fungal-signalling circuits operate at the molecular level to sense and respond to a plethora of environmental stresses, including osmoticshock, UV, high temperature, oxidative stress and toxic drugs/metabolites. The stress-activated p38/Hog1 MAPK pathway is structurally conserved in many organisms as diverse as yeast and mammals, but its regulation is uniquely specialized in a majority of clinical Cryptococcus neoformans serotype A and D strains to control differentiation and virulence factor regulation. C. neoformans Hog1 MAPK is controlled by Pbs2 MAPK kinase (MAPKK). The Pbs2-Hog1 MAPK cascade is controlled by the fungal "two-component" system that is composed of a response regulator, Ssk1, and multiple sensor kinases, including two-component.like (Tco) 1 and Tco2. Tco1 and Tco2 play shared and distinct roles in stress responses and drug sensitivity through the Hog1 MAPK system. Furthermore, each sensor kinase mediates unique cellular functions for virulence and morphological differentiation. We also identified and characterized the Ssk2 MAPKKK upstream of the MAPKK Pbs2 and the MAPK Hog1 in C. neoformans. The SSK2 gene was identified as a potential component responsible for differential Hog1 regulation between the serotype D sibling f1 strains B3501 and B3502 through comparative analysis of their meiotic map with the meiotic segregation of Hog1-dependent sensitivity to the fungicide fludioxonil. Ssk2 is the only polymorphic component in the Hog1 MAPK module, including two coding sequence changes between the SSK2 alleles in B3501 and B3502 strains. To further support this finding, the SSK2 allele exchange completely swapped Hog1-related phenotypes between B3501 and B3502 strains. In the serotype A strain H99, disruption of the SSK2 gene dramatically enhanced capsule biosynthesis and mating efficiency, similar to pbs2 and hog1 mutations. Furthermore, ssk2, pbs2, and hog1 mutants are all hypersensitive to a variety of stresses and completely resistant to fludioxonil. Taken together, these findings indicate that Ssk2 is the critical interface protein connecting the two-component system and the Pbs2-Hog1 pathway in C. neoformans.

• Membrane Journal
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• v.15 no.4
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• pp.310-319
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• 2005

This paper describes the preliminary study on the development of multi-stage membrane demonstration plant for removal of carbon dioxide from flue gas stream being emitted from LNG boiler in thermal power generation plant. The prerequisite requirement is to design and develop the membrane process producing a $99\%\;CO_2$ with $90\%$ recovery from LNG flue gas of 1,000 $Nm^3$/day. Asymmetric polyethersulfone hollow fiber membranes and membrane modules developed in this laboratory[1] were used in this study. Using the permeation data for the hollow fiber membranes, modelling on the membrane module and multi-stage membrane process was done to meet the requirement condition of the process design. The effects of the operating pressure of feed and permeate side and feed concentration on $CO_2$ purity and recovery were investigated experimentally with the developed hollow fiber modules. These experimental results matched well with theoretical modelling results.