• Korean Journal of Biological Psychiatry
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• v.12 no.2
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• pp.207-215
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• 2005

Objectives:This study was to compare verbal memory ability among patients with schizophrenia, bipolar manic patients and unipolar depressive patients, and to understand their charicteristics of memory process. Methods:All subjects were hospitalized patients and had been interviewed by using the Structured Clinical Interview for DSM-IV(SCID). Schizophrenic patients(N=40), bipolar manic patients(N=17), and unipolar depressive patients(N=20) were assessed with K-AVLT for verbal memory and with K-WAIS for verbal IQ. Three groups were compared regarding total immediate recall, delayed recall, delayed recognition, learning curve, memory retention, and retrieval efficiency under controlled verbal IQ. Multiple regression analysis was performed to find which clinical factors have an influence on verbal memory ability. Results:In MANCOVA, differences of verbal memory test scores among the groups were statistically significant(F=1.800, p<.05). In post hoc analysis, Patients with schizophrenia and bipolar mania showed poorer performance in immediate recall, delayed recall, delayed recognition, retrieval efficiency than unipolar depres- sive patients. And schizophrenics performed poorly in delayed recall, delayed recognition, retrieval efficiency than nonpsychotic affective disorder group, but no difference in total immediate recall, delayed recall, delayed recognition, retrieval efficiency between the schizophrenic group and the psychotic affective group. Conclusions:These results partially confirm previous reports of verbal memory ability among major psychiatric disorders. Our results showed that psychotic symptoms were related with verbal memory, and longer duration of illness was related with poorer performance in schizophrenia and unipolar depression.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.18 no.5
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• pp.44-51
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• 1999

This paper presents a massively parallel computational model for the efficient integration of speech and natural language understanding. The phoneme model is based on continuous Hidden Markov Model with context dependent phonemes, and the language model is based on a knowledge base approach. To construct the knowledge base, we adopt a hierarchically-structured semantic network and a memory-based parsing technique that employs parallel marker-passing as an inference mechanism. Our parallel speech recognition algorithm is implemented in a multi-Transputer system using distributed-memory MIMD multiprocessors. Experimental results show that the parallel speech recognition system performs better in recognition accuracy than a word network-based speech recognition system. The recognition accuracy is further improved by applying code-phoneme statistics. Besides, speedup experiments demonstrate the possibility of constructing a realtime parallel speech recognition system.

• 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.

• The Journal of the Acoustical Society of Korea
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• v.25 no.1E
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• pp.20-24
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• 2006

In this paper, we focused on the real time implementation of a speech recognition system with medium size of vocabulary considering its application to a mobile phone. First, we developed the PC based variable vocabulary word recognizer having the size of program memory and total acoustic models as small as possible. To reduce the memory size of acoustic models, linear discriminant analysis and phonetic tied mixture were applied in the feature selection process and training HMMs, respectively. In addition, state based Gaussian selection method with the real time cepstral normalization was used for reduction of computational load and robust recognition. Then, we verified the real-time operation of the implemented recognition system on the TMS320C6201 EVM board. The implemented recognition system uses memory size of about 610 kbytes including both program memory and data memory. The recognition rate was 95.86% for ETRI 445DB, and 96.4%, 97.92%, 87.04% for three kinds of name databases collected through the mobile phones.

• The Korean Journal of Rehabilitation Nursing
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• v.10 no.2
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• pp.134-140
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• 2007

Purpose: The purpose of this study was to find out relation of general characteristics and memory performance of old adults. Method: The subjects consisted of 160 old adults over the age 60 who living in Seoul. Data were collected by the interview method, using a structured questionnaire and the testing method on the memory performance. Data were analyzed by SPSS PC. Result: The level of memory performance is 63.0 points in the 84 point scale, immediate recall is 7.8 points in the 12 point scale, delayed recall is 7.6 points in the 12 point scale, word recognition is 16 points in the 24 point scale, & face recognition is 16 points in the 24 point scale, & face recognition is 26.8 points in the 40 point scale. Analysis of memory performance according to general characteristics showed that there were statistically differences for age, sex, religion and alcohol. Memory performance showed a significantly negative correlation with age and alcohol, but positive correlation with sex. The significant variables to predict old adults'memory performance are age and alcohol. Conclusion: The findings of this study give useful information for constructing an memory performance improving program based on general characteristics in old adults.

• Journal of Digital Convergence
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• v.12 no.11
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• pp.499-504
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• 2014

This experimental research explores the effect of infographic, visual element of TV news, on audience's memory and comprehension. For this experimental research, 2 groups of subjects composed of 87 university students were exposed to two different types of TV news, one group was exposed to news with infographic, the other group was exposed to news without infographic. and questions which were designed to measure recognition memory, recall memory, and comprehension, were asked and analysed. This research found that subjects who watched news with infographic showed higher degree of recall memory and comprehension than those who watched news without infographic. however effect of infographic on audience's recognition memory could not be found.

• Korean Journal of Adult Nursing
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• v.18 no.3
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• pp.468-478
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• 2006

Purpose: The purpose of this study were to find out the degree of memory decline and to confirm its correlated factors in old adults. Method: The subjects consisted of 68 old adults over the age 65 who living in Busan. Data were collected by the interview method, using a structured questionnaire and the testing method on the memory performance. Results: The old adults' memory performances declined in tasks of immediately word recall, delayed word recall, and face recognition and increased slightly in word recognition over 2 years. However, there was only significant difference in delayed word recall task. The significant variables to predict memory decline were age, literacy, depression, locus, and strategy. Conclusion: The memory decline of old adults wasn't more serious problem than the perceived one. There needs to be some intervention programs to prevent memory decline for the elderly.

• Smart Structures and Systems
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• v.8 no.1
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• pp.69-92
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• 2011

This paper presents an emergent pattern recognition approach based on the immune network theory and hierarchical clustering algorithms. The immune network allows its components to change and learn patterns by changing the strength of connections between individual components. The presented immune-network-based approach achieves emergent pattern recognition by dynamically generating an internal image for the input data patterns. The members (feature vectors for each data pattern) of the internal image are produced by an immune network model to form a network of antibody memory cells. To classify antibody memory cells to different data patterns, hierarchical clustering algorithms are used to create an antibody memory cell clustering. In addition, evaluation graphs and L method are used to determine the best number of clusters for the antibody memory cell clustering. The presented immune-network-based emergent pattern recognition (INEPR) algorithm can automatically generate an internal image mapping to the input data patterns without the need of specifying the number of patterns in advance. The INEPR algorithm has been tested using a benchmark civil structure. The test results show that the INEPR algorithm is able to recognize new structural damage patterns.

• KIPS Transactions on Software and Data Engineering
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• v.10 no.5
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• pp.187-194
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• 2021

A person's behavioral recognition is the recognition of what a person does according to joint movements. To this end, we utilize computer vision tasks that are utilized in image processing. Human behavior recognition is a safety accident response service that combines deep learning and CCTV, and can be applied within the safety management site. Existing studies are relatively lacking in behavioral recognition studies through human joint keypoint extraction by utilizing deep learning. There were also problems that were difficult to manage workers continuously and systematically at safety management sites. In this paper, to address these problems, we propose a method to recognize risk behavior using only joint keypoints and joint motion information. AlphaPose, one of the pose estimation methods, was used to extract joint keypoints in the body part. The extracted joint keypoints were sequentially entered into the Long Short-Term Memory (LSTM) model to be learned with continuous data. After checking the behavioral recognition accuracy, it was confirmed that the accuracy of the "Lying Down" behavioral recognition results was high.