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Protective Effect of Kimchi against Aβ25-35-induced Impairment of Cognition and Memory (아밀로이드 베타에 의해 유도된 인지 및 기억능력 손상에 대한 김치의 보호 효과)

  • Choi, Ji Myung;Lee, Sanghyun;Park, Kun Young;Kang, Soon Ah;Cho, Eun Ju
    • Journal of the Korean Society of Food Science and Nutrition
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    • v.43 no.3
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    • pp.360-366
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    • 2014
  • Kimchi is a Korean traditional fermented food with various health functionalities. However, the protective effects of kimchi against Alzheimer's disease (AD) have not been studied yet. In this study, the protective activities of kimchi extract against oxidative stress and AD were investigated in an amyloid beta ($A{\beta}$)-induced AD model using ICR mice. Kimchi extract exerted strong scavenging activities against 1,1-diphenyl-2-picrylhydrazyl and hydroxyl radical. In addition, T-maze, object cognition, and water maze tests were carried out using the AD model. The $A{\beta}_{25-35}$-injected groups showed impairment of cognition and memory. However, the abilities of novel object recognition and new route awareness were improved by administration of kimchi extract (100 and 200 mg/kg/day) for 2 weeks. Furthermore, the results on water maze test indicated that kimchi extract exerted protective activity against cognitive impairment induced by $A{\beta}_{25-35}$. The present study suggested that kimchi protected against $A{\beta}$-induced impairment of memory and cognition as well as attenuated oxidative stress.

Recognition of Tactilie Image Dependent on Imposed Force Using Fuzzy Fusion Algorithm (접촉력에 따라 변하는 Tactile 영상의 퍼지 융합을 통한 인식기법)

  • 고동환;한헌수
    • Journal of the Korean Institute of Intelligent Systems
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    • v.8 no.3
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    • pp.95-103
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    • 1998
  • This paper deals with a problem occuring in recognition of tactile images due to the effects of imposed force at a me urement moment. Tactile image of a contact surface, used for recognition of the surface type, varies depending on the forces imposed so that a false recognition may result in. This paper fuzzifies two parameters of the contour of a tactile image with the membership function formed by considering the imposed force. Two fuzzifed paramenters are fused by the average Minkowski's dist; lnce. The proposed algorithm was implemented on the multisensor system cnmposed of an optical tact le sensor and a 6 axes forceltorque sensor. By the experiments, the proposed algorithm has shown average recognition ratio greater than 869% over all imposed force ranges and object models which is about 14% enhancement comparing to the case where only the contour information is used. The pro- ~oseda lgorithm can be used for end-effectors manipulating a deformable or fragile objects or for recognition of 3D objects by implementing on multi-fingered robot hand.

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Queue Detection using Fuzzy-Based Neural Network Model (퍼지기반 신경망모형을 이용한 대기행렬 검지)

  • KIM, Daehyon
    • Journal of Korean Society of Transportation
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    • v.21 no.2
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    • pp.63-70
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    • 2003
  • Real-time information on vehicle queue at intersections is essential for optimal traffic signal control, which is substantial part of Intelligent Transport Systems (ITS). Computer vision is also potentially an important element in the foundation of integrated traffic surveillance and control systems. The objective of this research is to propose a method for detecting an exact queue lengths at signalized intersections using image processing techniques and a neural network model Fuzzy ARTMAP, which is a supervised and self-organizing system and claimed to be more powerful than many expert systems, genetic algorithms. and other neural network models like Backpropagation, is used for recognizing different patterns that come from complicated real scenes of a car park. The experiments have been done with the traffic scene images at intersections and the results show that the method proposed in the paper could be efficient for the noise, shadow, partial occlusion and perspective problems which are inevitable in the real world images.

Defect Detection of the Wall Thinning Pipe of the Nuclear Power Plant Using Infrared Thermography (적외선열화상을 이용한 원자력발전소 감육 배관의 결함 검출)

  • Kim, Kyeong-Suk;Chang, Ho-Sub;Hong, Dong-Pyo;Park, Chan-Joo;Na, Sung-Won;Kim, Kyung-Su;Jung, Hyun-Chul
    • Journal of the Korean Society for Nondestructive Testing
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    • v.30 no.2
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    • pp.85-90
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    • 2010
  • The infrared energy is emitted in the infrared wavelength range that corresponds to the surface temperature of a object which has temperature that is over the absolute the temperature(OK). The infrared thermography (IRT) is a non-destrnctive testing method that provides thermal video for the user in real-time by converting the infrared quantity that is detected by the infrared detector into temperature. The pipes of nuclear power plant(NPP) could be thinned by the corrosion and fatigue and the defect could lead to a big accident. For this reason, the effective non-destructive testing method is necessary. In this study, the relationship between the measured temperature and the defect depth or size of NPP pipes were recognized and that was applied to detect the wall thinning defects of NPP pipes.

Examination of Aggregate Quality Using Image Processing Based on Deep-Learning (딥러닝 기반 영상처리를 이용한 골재 품질 검사)

  • Kim, Seong Kyu;Choi, Woo Bin;Lee, Jong Se;Lee, Won Gok;Choi, Gun Oh;Bae, You Suk
    • KIPS Transactions on Software and Data Engineering
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    • v.11 no.6
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    • pp.255-266
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    • 2022
  • The quality control of coarse aggregate among aggregates, which are the main ingredients of concrete, is currently carried out by SPC(Statistical Process Control) method through sampling. We construct a smart factory for manufacturing innovation by changing the quality control of coarse aggregates to inspect the coarse aggregates based on this image by acquired images through the camera instead of the current sieve analysis. First, obtained images were preprocessed, and HED(Hollistically-nested Edge Detection) which is the filter learned by deep learning segment each object. After analyzing each aggregate by image processing the segmentation result, fineness modulus and the aggregate shape rate are determined by analyzing result. The quality of aggregate obtained through the video was examined by calculate fineness modulus and aggregate shape rate and the accuracy of the algorithm was more than 90% accurate compared to that of aggregates through the sieve analysis. Furthermore, the aggregate shape rate could not be examined by conventional methods, but the content of this paper also allowed the measurement of the aggregate shape rate. For the aggregate shape rate, it was verified with the length of models, which showed a difference of ±4.5%. In the case of measuring the length of the aggregate, the algorithm result and actual length of the aggregate showed a ±6% difference. Analyzing the actual three-dimensional data in a two-dimensional video made a difference from the actual data, which requires further research.

A Object-Based Image Retrieval Using Feature Analysis and Fractal Dimension (특징 분석과 프랙탈 차원을 이용한 객체 기반 영상검색)

  • 이정봉;박장춘
    • Journal of Korea Multimedia Society
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    • v.7 no.2
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    • pp.173-186
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    • 2004
  • This paper proposed the content-based retrieval system as a method for performing image retrieval through the effective feature extraction of the object of significant meaning based on the characteristics of man's visual system. To allow the object region of interest to be primarily detected, the region, being comparatively large size, greatly different from the background color and located in the middle of the image, was judged as the major object with a meaning. To get the original features of the image, the cumulative sum of tile declination difference vector the segment of the object contour had and the signature of the bipartite object were extracted and used in the form of being applied to the rotation of the object and the change of the size after partition of the total length of the object contour of the image into the normalized segment. Starting with this form feature, it was possible to make a retrieval robust to any change in translation, rotation and scaling by combining information on the texture sample, color and eccentricity and measuring the degree of similarity. It responded less sensitively to the phenomenon of distortion of the object feature due to the partial change or damage of the region. Also, the method of imposing a different weight of similarity on the image feature based on the relationship of complexity between measured objects using the fractal dimension by the Boxing-Counting Dimension minimized the wrong retrieval and showed more efficient retrieval rate.

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Plant Regeneration from Adventitious Roots of Rehmannia glutinosa Liboschitz and Bioreactor Culture (지황 부정근을 이용한 식물체 재분화 및 생물반응기 배양)

  • Jeong, Jae-Hun;Yu, Kee-Won;Kim, Sun-Ja;Choi, Yong-Eui;Paek, Kee-Yoeup
    • Journal of Plant Biotechnology
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    • v.31 no.1
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    • pp.55-60
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    • 2004
  • This experiment was carried out to develop rapid mass propagation via shoot organogenesis system from adventitious roots of Rehmannia glutinosa. The induction of adventitious roots from leaf explants was most favorable to MS solid medium supplemented with 2mg/L IBA. However, the growth of adventitious roots was highest when they were cultured on 1/3 strength MS liquid medium supplemented with 2mg/L IBA. When the adventitious roots were grown in 10L bioreactor, 10g roots as initial inoculum was increased to 225g after 6 weeks of culture. The harvested roots were cultured onto solid medium to induce plant regeneration. The optimal adventitious shoot formation was observed on MS medium supplemented with 2mg/L BA. Rooting of individual shoots was induced after transfer to half strength MS medium without growth regulators. Plantlets after acclimatization were successfully transplanted in the field and no phenotypic variation was observed among them.