• International journal of advanced smart convergence
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• v.5 no.3
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• pp.1-7
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• 2016

In existing Convolutional Neural Network (CNNs) for object recognition task, there are only few efforts known to reduce the noises from the images. Both convolution and pooling layers perform the features extraction without considering the noises of the input image, treating all pixels equally important. In computer vision field, there has been a study to weight a pixel importance. Seam carving resizes an image by sacrificing the least important pixels, leaving only the most important ones. We propose a new way to combine seam carving approach with current existing CNN model for object recognition task. We attempt to remove the noises or the "unimportant" pixels in the image before doing convolution and pooling, in order to get better feature representatives. Our model shows promising result with CIFAR-10 dataset.

• Korean Journal of Child Studies
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• v.23 no.3
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• pp.123-137
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• 2002

This study investigated children's cognitions of physically impossible events by characteristics of the events. The 67 subjects were 3-, 5-, and 7-year old children from one day care center and one elementary school in Seoul. Children's responses to questions regarding the events were taped and transcribed. Cognition of the events was measured by recognition of impossibility, possibility of replication, and reasons for the possibility of replication of the events. Data were analyzed by ANOVA(repeated measures), and Pearson's correlation. Children's recognition of the impossibility of the events varied by type of task : Recognition of gravity tasks was different from irreversibility tasks, but there were no differences between recognition of irreversibility and gravity and between irreversibility and object permanence. The possibility of replication correlated significantly with reasons given by the children.

• Journal of the Korean Physical Society
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• v.73 no.12
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• pp.1908-1917
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• 2018

The binding affinity between the T-cell receptors (TCRs) and antigenic peptides mainly determines immunological recognition. It is not a trivial task that T cells identify the digital sequences of peptide amino acids by simply relying on the integrated binding affinity between TCRs and antigenic peptides. To address this problem, we examine whether the affinity-based discrimination of peptide sequences is learnable and generalizable by artificial neural networks (ANNs) that process the digital experimental amino acid sequence information of receptors and peptides. A pair of TCR and peptide sequences correspond to the input for ANNs, while the success or failure of the immunological recognition correspond to the output. The output is obtained by both theoretical model and experimental data. In either case, we confirmed that ANNs could learn the immunological recognition. We also found that a homogenized encoding of amino acid sequence was more effective for the supervised learning task.

• Journal of Physiology & Pathology in Korean Medicine
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• v.20 no.2
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• pp.471-476
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• 2006

Chongmyung-tang(CMT, 聰明湯), oriental herbal medicine which consists of Polygaglae Radix(遠志), Acori Graminei Rhizoma(石菖蒲) and Hoelen(白茯神) has effect on amnesia, dementia. In order to evaluate effect of CMT on memory and learning in mice, CMT extract was used for studies. This paper describes the effects of CMT extract on memory and learning processes by using the passive and active avoidance performance tests, novel object recognition task and water maze task. The CMT extract ameliorated the memory retrieval deficit induced by ethanol in the passive avoidance responses but did not affect ambulatory activity of normal mice. These results suggest that CMT has an ameliorating effect on memory retrieval impairment. CMT extract decreased spontaneous motor activity(SMA) in the latter sessions of memory registration in active avoidance responses. These results suggest that CMT has partly transquilizing or antianxiety effects. In novel object recognition task to measure visual recognition memory, CMT-administered mice enhanced in long term memory for 1-3 days. In water maze task to measure spatial learning, which requires the activation of NMDA receptors in the hippocampus, spatial learning in CMT-administered mice was faster than in wild-type mice. These results suggest that CMT enhances memory and activates NMDA receptors.

• Korean Journal of Culture and Social Issue
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• v.11 no.4
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• pp.83-95
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• 2005

The purpose of the present study was to investigate the relationship between spatial-erceptual ability and several aspects of driving-related situation awareness(in particular, recognition and prediction). Video clips of real driving were used in both recognition and prediction tasks, and the digit calculation task during driving the simulator was required as the integration task of recognition and prediction. The results showed that the subjects of higher spatial-perceptual ability performed better in recognition task, especially in terms of sensitivity measured in d'(as signal detection theory), prediction task, and digits calculation performance than those of lower spatial-perceptual ability.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.516-519
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• 1996

Sub-assembly in ship manufacturing is a sequence of filet joint welding of stiffeners on metal panels and the process is different depending on companies. In this paper, we introduce a new intelligent robotic system of the sub-assembly process in Samsung Heavy Industry, where one shift of 22m * 9m workspace includes one to ten panels and each panel includes up to 10 stiffeners. The inherent problems such as several hundreds of different panels, unstructured task environment and the large scale do not allow a fixed automation, but needs highly intelligent versatile automation. The robotic system is composed of four 14DOF macro-mini robots and a task recognition system. Application of this system has verified the task specification such as low temperature environment(-10.deg. C) and productivity is satisfied successfully.

• Korean Journal of Cognitive Science
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• v.23 no.2
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• pp.225-248
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• 2012

The summed-similarity model of visual short-term recognition proposes that the estimated amount of summed similarity between remembered items and a recognition probe determines recognition judgement decision (Kahan & Sekuler, 2002). This study examined the effect of a task-irrelevant location change on the recognition decision against two remembered Gabor gratings differing in their spatial frequencies. On each trial in Experiment, participants reported if two gratings displayed across the visual fields are the same or not as the probe grating displayed after about a second of memory delay. The probe grating would be the same as or different from the memory items (lure) by 1 or 4 JND units. The location of the probe would also vary randomly across the left and right visual field with respect to the location of the corresponding memory item. The participants were instructed to perform their recognition task exclusively to the spatial frequencies of the memory items and the probe while ignoring the potential location change of the probe. The results showed that false-recognition rates of the lure probe increased as the summed similarity between the memory items and the probe increased. The rates also further increased in the condition where the probe location was different from the location of the corresponding memory item compared to the condition where the probe location was the same. The increased false-recognition rates indicate that information stored into visual short-term memory is represented as a form of well-bound visual features rather than independent features.

• Journal of Broadcast Engineering
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• v.24 no.1
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• pp.58-66
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• 2019

Recognition of named entity such as proper nouns in conversation sentences is the most fundamental and important field of study for efficient conversational information prediction. The most important part of a task-oriented dialogue system is to recognize what attributes an object in a conversation has. The named entity recognition model carries out recognition of the named entity through the preprocessing, word embedding, and prediction steps for the dialogue sentence. This study aims at using user - defined dictionary in preprocessing stage and finding optimal parameters at word embedding stage for efficient dialogue information prediction. In order to test the designed object name recognition model, we selected the field of daily chemical products and constructed the named entity recognition model that can be applied in the task-oriented dialogue system in the related domain.

• The Korean Journal of Rehabilitation Nursing
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• v.3 no.2
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• pp.181-195
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• 2000

The purpose of this study is to find out the effects of personal characteristics, social support, depression, and metamemory on the older adults' memory performances. The subjects of the study consisted of 95 older adults over the age of 60 who are living in Busan. Some data were collected by means of the interview method, using questionnaires for metamemory (MIA questionnaire by Dixon, et al., 1988), and depression(GDS by Yesavage and Sheikl, 1986), social resoueces(Duke university, 1978), family support(Hyun-Sook Kang, 1985). The other data were collected by the testing method on the memory performance such as the immeadiate word recall task, the delayed word recall task, the word recognition task(Elderly Verbal Learning Test by Kyung Mi Choi, 1998), and the face recognition task(Face Recognition Task tool developed by Hye-Sook Min). The results of this study were as follows; 1. The level of metamemory is 3.4 points in the 5 point scale, the grades of the task and the achievement are relatively high and the grades of the change, the control, and the anxiety are relatively low in the sub-concepts. 2. Metamemory have significant relation with age(r=-.44), educational attainment(r=.46), depression(r=-.58), family support(r=.20), social resources(r=.20). 3. The significant variables to predict older adults' metamemory are educational attainment(22%), sex(11%), age (8.3%), depression(4.7%), and illness state(3%). 4. The strong variables to predict memory performances are metamemory, age, depression, social resources, educational attainment, illness state, and limitation of daily living activity related to illness. In conclusion, the enhancement strategies of metamemory and the social support and the prevention or reduction of depression are necessary to increase older adults' memory performances. Ultimately in this respect nurses' roles are very important in developing and performing some intervention programs for old adults' memory improvement, which have significant meanings in the field of nursing science.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09a
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• pp.480-483
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• 2003

We propose a new framework that aims at multi-purpose image recognition, a difficult task for the conventional rule-based systems. This framework is farmed based on the idea of computer-based learning algorithm. In this research, we introduce the new functions of an additional learning and a knowledge reconstruction on the Fuzzy Inference Neural Network (FINN) (1) to enable the system to accommodate new objects and enhance the accuracy as necessary. We examine the capability of the proposed framework using two examples. The first one is the capital letter recognition task from UCI machine learning repository to estimate the effectiveness of the framework itself, Even though the whole training data was not given in advance, the proposed framework operated with a small loss of accuracy by introducing functions of the additional learning and the knowledge reconstruction. The other is the scenery image recognition. We confirmed that the proposed framework could recognize images with high accuracy and accommodate new object recursively.