• Journal of The Korean Society of Integrative Medicine
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• v.1 no.3
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• pp.79-95
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• 2013

Purpose : This study aims to investigate the effect of the Snoezelen and Rehacom programs on improvement of attention and memory, and the effect of the Snoezelen program on stress reduction. Method : This study was targeted at 11 subjects in the Snoezelen experimental group, 11 subjects in the Rehacom group and 11 subjects in the non-experimental group. As the initial evaluation, all the subjects took electroencephalography. Then, the Snoezelen group and Rehacom group did Snoezelen training and Rehacom training, respectively total 12 times(for 20 minutes twice per week for six weeks), but no training was applied to the control group. Three weeks after the training, the interim was carried out, and four weeks after the training, the final evaluation was carried out. Results : Subjects' attention increased to $58.15{\pm}4.96$ from $43.75{\pm}4.69$ during the Snoezelen training, and increased to $49.85{\pm}1.91$ from $43.28{\pm}2.71$ during the Rehacom training, which means the Snoezelen training was more effective in improving attention(P<0.05). Subjects' memory increased to $56.14{\pm}1.26$ from $43.19{\pm}3.46$ during the Snoezelen training, and increased to $50.94{\pm}4.0$ from $43.07{\pm}2.58$ during the Rehacom training. This also implies that the Snoezelen training was more effective in improving memory(P<0.05). Conclusion : Though both of the Snoezelen training and Rehacom training improved attention and memory, the Snoezelen program was more effective, and it also influenced stress resistance and physical arousal.

• The Journal of Korean Medicine
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• v.28 no.2 s.70
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• pp.1-12
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• 2007

Objective : Gagamchongmyung-tang is clinically one of the most popular prescriptions as an herbal medicine for the treatment of amnesia. In order to evaluate its neuroprotective effects on the ischemia-induced cognitive deficits caused by middle cerebral artery occlusion (MCAO), we examined its ability to reduce impairments of learning and memory of rats in the Morris water maze. Method and Result : Focal cerebral ischemia produced a decrease in acetylcholine transmission in the hippocampus, and deficits of learning and memory in the Morris water maze task. Treatment with two types of Gagamchongmyung-tang, methanol and water extracts, produced a substantial increase in acquisition in the Morris water maze. Treatment with methanol extract of Gagamchongmyung-tang increased the performance of the retention test in the Morris water maze. Consistent with behavioral data, immunohistochemical data showed that treatment with methanol extract, but not water extract, of Gagamchongmyung-tang significantly recovered reduction of AchE and ChAT reactivity in the hippocampal CAl area. Conclusion : These results demonstrated that methanol extract of Gagamchongmyung-tang has protective effects against ischemia-induced learning and memory impairments, and provided evidence of methanol extract of Gagamchongmyung-tang as a putative treatment for amnesia, vascular dementia, and longer memory.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.6
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• pp.567-582
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• 2000

We propose a new way of managing flash memory space for flash memory-specific file system based on log-structured file system. Flash memory has attractive features such as non-volatility, and fast I/O speed, but it also suffers from inability to update in place and limited usage cycles. These drawbacks require many changes to conventional storage (file) management techniques. Our focus is on lowering cleaning cost and evenly utilizing flash memory cells while maintaining a balance between the two often-conflicting goals. The proposed cleaning method performs well especially when storage utilization and the degree of locality are high. The cleaning efficiency is enhanced by dynamically separating cold data and non-cold data. The second goal, cycle-leveling is achieved to the degree where the maximum difference between erase cycles is below the error range of the hardware. Simulation results show that the proposed method has significant benefit over naxve methods: maximum of 35% reduction in cleaning cost with even spreading writes across segments.

• Journal of KIISE:Computer Systems and Theory
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• v.27 no.4
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• pp.408-415
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• 2000

Large scale shared memory multiprocessors have suffered from large access latency to shared memory. The large latency partially stems from a feature of directory-based cache coherence schemes which require a shared memory access to be serviced at a home node of the memory block. The home visit results in three or more hops traversal for a memory read access. The traversal becomes much longer as a system scales up. In this paper, we propose a new cache coherence scheme that reduces read access latency. The proposed scheme exploits ideas of invalid hint. Invalid hint for a cache block means which node has invalidated the cache block before. Thus a read access request can be directly sent to and serviced by the node (called owner) without help of a home node. Execution-driven simulation is employed to evaluate performance of the proposed scheme. The simulation results show that read access latency and execution time are reduced.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.41 no.10
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• pp.85-94
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• 2004

In this paper, a register allocation techlique that translates memory accesses to register accesses Is presented to enhance embedded software performance. In the proposed method, a source code is profiled to generate a memory trace. From the profiling results, target functions with high dynamic call counts are selected, and the proposed register allocation technique is applied only to the target functions to save the compilation time. The memory trace of the target functions is searched for the memory accesses that result in cycle count reduction when replaced by register accesses, and they are translated to register accesses by modifying the intermediate code and allocating Promotion registers. The experiments where the performance is measured in terms of the cycle count on MediaBench and DSPstone benchmark programs show that the proposed method increases the performance by 14% and 18% on the average for ARM and MCORE, respectively.

• Transactions of the Society of Information Storage Systems
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• v.6 no.1
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• pp.31-36
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• 2010

Data storage related with writing and retrieving requires high storage capacity, fast transfer rate and less access time. Today any data storage system cannot satisfy these conditions, however holographic data storage system can perform faster data transfer rate because it is a page oriented memory system using volume hologram in writing and retrieving data. System can be constructed without mechanical actuating part so fast data transfer rate and high storage capacity about 1Tb/cm3 can be realized. In this research, to correct errors of binary data stored in holographic data storage system, a new method for reduction errors is suggested. First, find cluster centers using subtractive clustering algorithm then reduce intensities of pixels around cluster centers. By using this error reduction method following results are obtained ; the effect of Inter Pixel Interference noise in the holographic data storage system is decreased and the intensity profile of data page becomes uniform therefore the better data storage system can be constructed.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.13 no.2
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• pp.832-854
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• 2019

Action recognition has been studied in computer vision field for years. We present an effective approach to recognize actions using a dimension reduction method, which is applied as a crucial step to reduce the dimensionality of feature descriptors after extracting features. We propose to use sparse matrix and randomized kd-tree to modify it and then propose modified Local Fisher Discriminant Analysis (mLFDA) method which greatly reduces the required memory and accelerate the standard Local Fisher Discriminant Analysis. For feature encoding, we propose a useful encoding method called mix encoding which combines Fisher vector encoding and locality-constrained linear coding to get the final video representations. In order to add more meaningful features to the process of action recognition, the convolutional neural network is utilized and combined with mix encoding to produce the deep network feature. Experimental results show that our algorithm is a competitive method on KTH dataset, HMDB51 dataset and UCF101 dataset when combining all these methods.

• Journal of Internet Computing and Services
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• v.10 no.4
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• pp.35-44
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• 2009

The emerging notion of data stream has brought many new challenges to the research communities as a consequence of its conceptual difference with conventional concepts of just data. One typical example is data stream processing in sensor networks. The range of data processing considerations in a sensor network is very wide, from physical resource restrictions such as bandwidth, energy, and memory to the peculiarities of query processing including continuous and specific types of queries. In this paper, as one of the physical constraints in data stream processing, we consider the problem of limited memory and propose a new scheme for data stream reduction based on the Principal Component Analysis (PCA) technique. PCA can transform a number of (possibly) correlated variables into a (smaller) number of uncorrelated variables. We adapt PCA for the data stream of a sensor network assuming the cooperation of a query engine (or application) with a network base station. Our method exploits the spatio-temporal correlation among multiple measurements from different sensors. Finally, we present a new framework for data processing and describe a number of experiments under this framework. We compare our scheme with the wavelet transform and observe the effect of time stamps on the compression ratio. We report on some of the results.

• The Journal of the Korea institute of electronic communication sciences
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• v.15 no.4
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• pp.717-724
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• 2020

Due to the important role played by emotion in human interaction, affective computing is dedicated in trying to understand and regulate emotion through human-aware artificial intelligence. By understanding, emotion mental diseases such as depression, autism, attention deficit hyperactivity disorder, and game addiction will be better managed as they are all associated with emotion. Various studies for emotion recognition have been conducted to solve these problems. In applying machine learning for the emotion recognition, the efforts to reduce the complexity of the algorithm and improve the accuracy are required. In this paper, we investigate emotion Electroencephalogram (EEG) feature reduction and classification using Stack AutoEncoder (SAE) and Long-Short-Term-Memory/Recurrent Neural Networks (LSTM/RNN) classification respectively. The proposed method reduced the complexity of the model and significantly enhance the performance of the classifiers.

• Journal of The Korean Society of Clinical Toxicology
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• v.19 no.2
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• pp.100-109
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• 2021

Purpose: The purpose of this study was to investigate effect of N-acetylcysteine (NAC) on the injury of putative parvalbumin positive interneurons defined by molecular marker and hippocampal long-term potentiation (LTP), a marker of neural plasticity following acute carbon monoxide (CO) poisoning. Methods: Adult Sprague-Dawley rats were exposed to 1100 ppm CO for 40 minutes followed by 3000 ppm CO for 20 minutes. Animals received daily intraperitoneal injection of NAC (150 mg/kg) for 5 days after CO exposure. Changes in learning and spatial memory were evaluated by Y-maze test 5 days after the poisoning. In vivo LTP in hippocampal CA1 area was evaluated by using extracellular electrophysiological technique. Immunohistochemical staining were adopted to observe expressional damages of parvalbumin (PV) immunoreactive interneurons in the hippocampus following the poisoning. Results: Acute CO intoxication resulted in no changes in memory performance at Y-maze test but a significant reduction of LTP in the in hippocampal CA1 area. There was also a significant reduction of PV (+) interneurons in the hippocampal CA1 area 5 days after CO poisoning. Daily treatment of NAC significantly improved hippocampal LTP impairment and reduced immunoreactivity for PV in the hippocampus following the acute CO poisoning. Conclusion: The results of this study suggest that reduction of hippocampal LTP and PV (+) interneurons in the hippocampus is sensitive indicator for brain injury and daily NAC injections can be the alternative therapeutics for the injury induced by acute CO poisoning.