• Proceedings of the IEEK Conference
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• 2002.07a
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• pp.98-101
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• 2002

This paper reports a parallel architecture in a HMM based speech recognition system for a low-power LSI design. The proposed architecture calculates output probability of continuous HMM (CHMM) by using concurrent and pipeline processing. They enable to reduce memory access and have high computing efficiency. The novel point is the efficient use of register arrays that reduce memory access considerably compared with any conventional method. The implemented system can achieve a real time response with lower clock in a middle size vocabulary recognition task (100-1000 words) by using this technique.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.492-494
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• 1993

CMAC (Cerebeller Model Articulation Controller) is kind of Neural Networks that imitate the human cerebellum. For storage and retrieval of learned data, the input of CMAC is used as a key to determine the memory location. he learned information is distributively stored in physical memory. The learning of CMAC is very fast and converged well, therefore, it effects the application of Pattern Recognition. Through the our experiment of Pattern Recognition, we will prove that CMAC is very suitable for On-line real time processing and incremental learning of Neural Networks.

• Proceedings of the KIEE Conference
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• 2004.05a
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• pp.147-149
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• 2004

Although most of the people have studied English for a long time, their English conversation capability is low. When we provide them portable conversational-type English learners by the application of computer and information process technology, such portable learners can be used to enhance their English conversation capability by their conventional conversation exercises. The core technology to develop such learner is the development of a voice recognition and synthesis module under an embedded environment. This paper deals with voice recognition and synthesis, prototype of the learner module using a DSP(Digital Signal Processing) chip for voice processing, voice playback function, flash memory file system, PC download function using USB ports, English conversation text function by the use of SMC(Smart Media Card) flash memory, LCD display function, MP3 music listening function, etc. Application areas of the prototype equipped with such various functions are vast, i.e. portable language learners, amusement devices, kids toy, control by voice, security by the use of voice, etc.

• Sleep Medicine and Psychophysiology
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• v.26 no.1
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• pp.16-22
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• 2019

Objectives: The objective of this study was to investigate the correlation between insufficient sleep and visuospatial memory in adolescents using a computerized neurocognitive function test. Methods: A total of 103 high school students (26 males and 77 females; mean age $17.11{\pm}8.50years$) without a serious psychiatric problem was recruited. All subjects were requested to complete a self-report questionnaire about weekday total sleep time and weekend total sleep time. The epworth sleepiness scale (ESS) and the beck depression inventory (BDI) were administered to measure daytime sleepiness and symptoms of depression. Seven subsets of the Cambridge Neuropsychological test automated battery were examined to assess visuospatial memory. Results: After controlling for age, sex, ESS, and BDI, longer weekend total sleep time was correlated with poor performance on delayed matching to sample (r = -0.312, p = 0.002) and immediate recall on pattern recognition memory (r = -0.225, p = 0.025). Increased weekend catch-up sleep time was correlated with poor performance of delayed matching to sample (r = -0.236, p = 0.018), immediate recall on pattern recognition memory (r = -0.220, p = 0.029), and delayed recall on pattern recognition memory (r = -0.211, p = 0.036) after controlling for age, sex, ESS, and BDI. Conclusion: This study showed that increased weekend catch-up sleep time reflecting insufficient weekday sleep were associated with poor performance in delayed recall tasks of visual memory. This finding suggests that insufficient sleep during adolescence might produce a decline of visuospatial memory.

• Proceedings of the Optical Society of Korea Conference
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• 1991.07a
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• pp.33-39
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• 1991

We have developed a new holographic associative memory(HAN) based on an adaptive learning which uses learning pattern method (LPM). The LPM utilizes the simple optical implementation of outer-product learning, performance of adapitive learning. simulation are represented.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.723-724
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• 2008

In this paper, we explore face recognition technology for embedded system. We develop an algorithm suitable for systems under ubiquitous environment. The basic requirements includes appropriate data format and ratio of feature data to achieve efficiency of algorithm. Our experiment presents a face recognition technique for handheld devices. The essential parts for face recognition based on embedded system includes; integer representation from floating point calculation and optimization for memory management.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.12
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• pp.1770-1776
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• 2021

For hand expression recognition, hand pose recognition based on the static shape of the hand and hand gesture recognition based on hand movement are used together. In this paper, we proposed a hand expression recognition method that recognizes symbols based on the trajectory of a hand movement on a virtual blackboard. In order to recognize a sign drawn by hand on a virtual blackboard, not only a method of recognizing a sign from a hand movement, but also hand pose recognition for finding the start and end of data input is also required. In this paper, MediaPipe was used to recognize hand pose, and LSTM(Long Short Term Memory), a type of recurrent neural network, was used to recognize hand gesture from time series data. To verify the effectiveness of the proposed method, it was applied to the recognition of numbers written on a virtual blackboard, and a recognition rate of about 94% was obtained.

• The KIPS Transactions:PartB
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• v.11B no.4
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• pp.449-456
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• 2004

This paper proposes a novel recognition model, a recurrent fuzzy associative memory(RFAM), for recognizing time-series patterns contained an ambiguity. RFAM is basically extended from FAM(Fuzzy Associative memory) by adding a recurrent layer which can be used to deal with sequential input patterns and to characterize their temporal relations. RFAM provides a Hebbian-style learning method which establishes the degree of association between input and output. The error back-propagation algorithm is also adopted to train the weights of the recurrent layer of RFAM. To evaluate the performance of the proposed model, we applied it to a word boundary detection problem of speech signal.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2013.10a
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• pp.77-80
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• 2013

SURF algorithm is an algorithm to extract feature points and to generate descriptors from input images. It is robust to change of environment such as scale, rotation, illumination and view points. Because of these features, it is used for many image processing applications such as object recognition, constructing panorama pictures and 3D image restoration. But there is disadvantage for real time operation because many recognition algorithms such as SURF algorithm requires a lot of calculations. In this paper, we propose a design of feature extractor and descriptor generator based on SURF for high memory efficiency. The proposed design reduced a memory access and memory usage to operate in real time.

• Korean Journal of Pharmacognosy
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• v.51 no.4
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• pp.310-316
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• 2020

Kyung-Ok-Go (KOK) is a traditional prescription used for debilitating natural aging and post-illness debilitation. KOK has been used in a variety of ways because it strengthens immunity, prevents illness, and helps recovery in case of illness. In particular, recent research has revealed that KOK helps improve memory and cognition. Therefore, in this study, we investigated whether KOK was effective in improving memory decline and depression-state observed during menopause. In the present study, we employed ovariectomized mouse as an animal model for measuring menopausal syndrome. The administration of KOK for 8 weeks, the object recognition memory and working memory were improved in novel object recognition test and Y-maze test. And in the forced swimming test, the immobility time were decreased. Additionally, the expression level of mature brain derived neurotropic factor (mBDNF) was increased by KOK administration in ovariectomized mouse hippocampus. These results suggested that KOK could improve cognitive decline and depression during menopausal period, and it might be come from enhancing expression level of mBDNF in hippocampus.