• 생물정신의학
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• 제21권2호
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• pp.65-73
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• 2014

Objectives This study aimed to identify the differences and the profiles of cognitive deficits in remitted patients with schizophrenia and first-degree relatives of schizophrenic probands. Methods A total of 26 remitted states of schizophrenia patients were included in the study and the same number of unaffected first-degree relatives of schizophrenic probands and healthy controls were matched for age, sex, years of education. Cognitive function of all participants was measured by using the Digit span test, the Continuous performance test, the Rey auditory & visual learning test, the Complex figure test, the Verbal fluency test, the Wisconsin card sorting test and the Finger tapping test. The effects of subsyndromal symptomatology and general intelligence score were controlled. Results Schizophrenia patients' group showed more significant impairment than other groups in verbal memory (learning, immediate recall, delayed recall), visual memory (copy, immediate recall, delayed recall) and cognitive flexibility domains. The family group and the patient group commonly performed significantly worse than healthy controls in working memory and verbal fluency (category) tests. There were no differences in sustained attention, psychomotor performance. Conclusions Our research shows that the deficit in working memory and verbal fluency could be strong candidates of endophenotypic marker in schizophrenia.

• Proceedings of the National Institute of Ecology of the Republic of Korea
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• 제4권4호
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• pp.159-176
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• 2023

The conservation of the raccoon dog (Nyctereutes procyonoides) in South Korea requires the protection and preservation of natural habitats while additionally ensuring coexistence with human activities. Applying habitat map modeling techniques provides information regarding the distributional patterns of raccoon dogs and assists in the development of future conservation strategies. The purpose of this study is to generate potential habitat distribution maps for the raccoon dog in South Korea using geospatial technology-based models. These models include the frequency ratio (FR) as a bivariate statistical approach, the group method of data handling (GMDH) as a machine learning algorithm, and convolutional neural network (CNN) and long short-term memory (LSTM) as deep learning algorithms. Moreover, the imperialist competitive algorithm (ICA) is used to fine-tune the hyperparameters of the machine learning and deep learning models. Moreover, there are 14 habitat characteristics used for developing the models: elevation, slope, valley depth, topographic wetness index, terrain roughness index, slope height, surface area, slope length and steepness factor (LS factor), normalized difference vegetation index, normalized difference water index, distance to drainage, distance to roads, drainage density, and morphometric features. The accuracy of prediction is evaluated using the area under the receiver operating characteristic curve. The results indicate comparable performances of all models. However, the CNN demonstrates superior capacity for prediction, achieving accuracies of 76.3% and 75.7% for the training and validation processes, respectively. The maps of potential habitat distribution are generated for five different levels of potentiality: very low, low, moderate, high, and very high.

• 한국시스템다이내믹스연구
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• 제9권1호
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• pp.57-71
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• 2008

This research paper describes a complex and vague settings in which organization makes a decision and explains a role of decision maker's learning process. The original paper, written by Cohen, March, Olsen in 1972, said that all members of organization depended on the technology taken through trials and errors, which is the 'learning' process literally. But they intended to exclude the learning process in their simulation model because their PORTRAN model couldn't replicate the learning concept. As a result, they couldn't explain how all agents of garbage can simulation model resolve the problem dynamically. To overcome this original paper's limitations, we try to rebuild a learning process simulation model using by system dynamics approach that can capture the linkage between organization leanings and agents-based decision-makings. Our learning simulation results reveal two points. First, decision maker's leanings process improves the efficiency of decision making in complex situation. Second, group learning shows a superior efficiency to an individual learning because group members share organizational memory and energy.

• 대한본초학회지
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• 제22권4호
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• pp.51-58
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• 2007

Objectives : Investigation of the memory and cognitive enhancing effect of HT008-1 in scopolamine induced amnesia mice. Methods : At 60 min before acquisition trials, HT008-1 (30, 100, 300 mg/kg p.o.) was administered, and 30 min later, mice were injected with scopolamin (1.0 mg/kg, i.p.). In the passive avoidance test, acquisition trials were carried out 30 min after a single scopolamine treatment. Retention trials were carried out 24h after acquisition trials. Y-maze test was carried out 30 min after a single scopolamine treatment. Spontaneous alternation behavior during an 8-min session was recorded. Inhibitory effects of HT008-1 (0.01, 0.1, 1.0 mg/ml) on AChE activity was measured. Result : HT008-1 ameliorated scopolamine-induced learning impairments and spatial cognitive function in passive avoidance and Y-maze test, respectively. Moreover HT008-1 showed a significant inhibitory effect on AChE activity. Discussion: This study presented that eMultiherb mixture HT008-1 enhanced learning memory and spatial cognitive function in scopolamine-induced amnesia mice. These results suggest that the effect of HT008-1 may be dependent on the inhibition of AChE activity.

• 대한한방소아과학회지
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• 제19권2호
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• pp.99-114
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• 2005

Objectives: This study was aimed to find out the anti-stress and protective-memory effect of Quibitanggagam(QBT) on stress of rats Methods : This experimental study was conducted with elevated plus maze test, passive avoidance test, morris water maze test, and consequently density of AchE reactivity in the CA1 of hippocampus to research the learning and memory of rats affected by restraint stress, Results: Passive avoidance test revealed that time latency of retention test for QBT+Stress group significantly decreased on 2, 3rd day. Morris water maze revealed that acqusitive ability of QBT+Stress group significantly improved on 2, 3rd day and retentive ability of QBT+Stress group was significantly improved on 7th day. Elevated plus maze test revealed that latency in open arm of QBT+Stress group significantly decreased and locomotor activity(number of entered arm) of QBT+Stress group was significantly increased. The values of density of AchE stained nuclei in the CA1 of hippocampus QBT+Stress group was significantly increased compared with SAL+Stress group. Conclusion : According to the above results, it is concluded that QBT will be useful as a remedy against stress disease and improving memory.

• 대한전자공학회논문지SP
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• 제48권1호
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• pp.54-63
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• 2011

본 논문은 저해상도 입력 영상을 고해상도 영상으로 복원하는 고속 학습기반 보간 기법을 제안한다. 일반적인 학습기반 초고해상도 기법은 여러 종류의 저해상도 영상과 고해상도 영상의 상관성을 통해 고주파 정보를 사전에 학습하고, 합성 단계에서 학습한 정보를 이용해 임의의 저해상도 영상을 고해상도 영상으로 복원한다. 이런 기존 학습기반 초 고해상도 기법은 방대한 양의 학습된 정보를 메모리에 저장해야만 하는 단점이 있을 뿐만 아니라 이차원 블록 단위 정합 과정을 거쳐야 하기 때문에 상당한 연산량이 요구된다. 이러한 문제점을 보완하기 위해 본 논문은 일차원 패치 단위 학습을 통해 학습 정보 저장용 메모리 크기 및 연산량을 크게 줄이는 기법을 제안한다. 실험 결과에 따르면, 제안한 기법은 전통적인 bicubic 보간 기법보다 평균 0.7dB 정도 높은 PSNR을 보이며, SSIM도 평균 0.01이상 향상되는 결과를 보인다.

• International Journal of Internet, Broadcasting and Communication
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• 제15권1호
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• pp.157-163
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• 2023

Recently, as businesses and data types become more complex and diverse, efficient data analysis using machine learning is required. However, since communication in the cloud environment is greatly affected by network latency, data analysis is not smooth if information delay occurs. In this paper, SPT (Safe Proper Time) was applied to the cluster-based machine learning data analysis agent proposed in previous studies to solve this delay problem. SPT is a method of remotely and directly accessing memory to a cluster that processes data between layers, effectively improving data transfer speed and ensuring timeliness and reliability of data transfer.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 2001년도 ICCAS
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• pp.22.2-22
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• 2001

Recently, Reinforcement Learning (RL) methods in MDP have been extended and applied to the POMDP problems. Currently, hierarchical RL methods are widely studied. However, they have the drawback that the learning time and memories are exhausted only for keeping the hierarchical structure, though they aren´t necessary. On the other hand, our "Labeling Q-learning (LQ-learning) proposed previously, has no hierarchical structure, but adopts a characteristic internal memory mechanism. Namely, LQ-1earning agent percepts the state by pair of observation and its label, and the agent can distinguish states, which look as same, but obviously different, more exactly. So to speak, at each step t, we define a new type of perception of its environment ～ot = (ot, $\theta$t), where of is conventional observation, and $\theta$t is the label attached to the observation. Then the conventional ...

• 대한임베디드공학회논문지
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• 제16권5호
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• pp.215-223
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• 2021

3D data can be categorized into two parts : Euclidean data and non-Euclidean data. In general, 3D data exists in the form of non-Euclidean data. Due to irregularities in non-Euclidean data such as mesh and point cloud, early 3D deep learning studies transformed these data into regular forms of Euclidean data to utilize them. This approach, however, cannot use memory efficiently and causes loses of essential information on objects. Thus, various approaches that can directly apply deep learning architecture to non-Euclidean 3D data have emerged. In this survey, we introduce various deep learning methods for mesh and point cloud data. After analyzing the operating principles of these methods designed for irregular data, we compare the performance of existing methods for shape classification and segmentation tasks.

• 대한본초학회지
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• 제30권2호
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• pp.43-48
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• 2015

Objectives : The aim of this study was to investigate the memory enhancing properties of extract of Hoelen Cum Radix (HCR) and its possible mechanism in mice of normal condition. Methods : We evaluated the effects of HCR on cognitive function and memory enhancement in normal mice. Male ICR mice were orally administrated with HCR 100 mg/kg for 7 days and equal volume of saline was administrated to the control group in the same condition. We conducted two behavioral tests which measure the spatial working memory (Y-maze test) and cognitive fear memory (passive avoidance test). We also investigated whether HCR affects the hippocampal neurogenesis in the brain. To assess the effects of HCR on neural progenitor cell differentiation and neurite outgrowth in the early stage of hippocampal neurogenesis, we performed doublecortin (DCX), a direct neurogenesis marker, immunohistochemical analysis in the dentate gyrus (DG) of the mouse hippocampus. Results : HCR significantly enhanced memory and cognitive function as determined by the Y-maze test (p<0.05) and passive avoidance test (p<0.001). Moreover, HCR increased DCX positive cells (p<0.01) and neurite length (p<0.01) compared to the control group. These results indicated that HCR stimulates differentiation of neural progenitor cells and promotes neurite outgrowth in hippocampal DG of the mice. Conclusion : We concluded that HCR shows memory enhancing effects through the stimulation of hippocampal neurogenesis as a consequence of accelerated neuronal differentiation and neurite outgrowth in the DG of the hippocampus after HCR treatment.