• Proceedings of the SAREK Conference
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• 2009.06a
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• pp.1055-1060
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• 2009

Noise is one of the major environmental problems in human life. But hot water distributers with the flow rate control valve bring about often noise according to the heating control condition in residential buildings. The sound power level increased as the flow rate and pressure difference increased. And thus, experimental analyses for the flow rate control and the pressure difference control were carried out in this study to reduce the noise emitted from the flow rate control valve. As the results, the flow rate control method using a SMA(Shape Memory Alloy)-valve and the flow rate control system using a pressure difference sensor can be expected to control noise in the region of below 50 dB of sound power level.

• ETRI Journal
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• v.32 no.3
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• pp.380-389
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• 2010

This paper presents a new edge-protection algorithm and its very large scale integration (VLSI) architecture for block artifact reduction. Unlike previous approaches using block classification, our algorithm utilizes pixel classification to categorize each pixel into one of two classes, namely smooth region and edge region, which are described by the edge-protection maps. Based on these maps, a two-step adaptive filter which includes offset filtering and edge-preserving filtering is used to remove block artifacts. A pipelined VLSI architecture of the proposed deblocking algorithm for HD video processing is also presented in this paper. A memory-reduced architecture for a block buffer is used to optimize memory usage. The architecture of the proposed deblocking filter is verified on FPGA Cyclone II and implemented using the ANAM 0.25 ${\mu}m$ CMOS cell library. Our experimental results show that our proposed algorithm effectively reduces block artifacts while preserving the details. The PSNR performance of our algorithm using pixel classification is better than that of previous algorithms using block classification.

• Earthquakes and Structures
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• v.4 no.6
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• pp.607-627
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• 2013

The application of shape memory alloys (SMAs) to the seismic response reduction of civil engineering structures has attracted growing interest due to their self-centering feature and excellent fatigue performance. The loading rate dependence of SMAs raises a concern in the seismic analysis of SMA-based devices. However, the implementation of micromechanics-based strain-rate-dependent constitutive models in structural analysis software is rather complicated and computationally demanding. This paper investigates the feasibility of replacing complex rate-dependent models with rate-independent constitutive models for superelastic SMA elements in seismic time-history analysis. Three uniaxial constitutive models for superelastic SMAs, including one rate-dependent thermomechanical model and two rate-independent phenomenological models, are considered in this comparative study. The pros and cons of the three nonlinear constitutive models are also discussed. A parametric study of single-degree-of-freedom systems with different initial periods and strength reduction factors is conducted to examine the effect of the three constitutive models on seismic simulations. Additionally, nonlinear time-history analyses of a three-story prototype steel frame building with special SMA-based damping braces are performed. Two suites of seismic records that correspond to frequent and design basis earthquakes are used as base excitations in the seismic analyses of steel-braced frames. The results of this study show that the rate-independent constitutive models, with their parameters properly tuned to dynamic test data, are able to predict the seismic responses of structures with SMA-based seismic response modification devices.

• Journal of IKEEE
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• v.21 no.2
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• pp.136-141
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• 2017

In this paper, we propose an algorithm for memory optimization to apply deep learning to PC. The proposed algorithm minimizes the memory and computation processing time by reducing the amount of computation processing and data required in the conventional deep learning structure in a general PC. The algorithm proposed in this paper consists of three steps: a convolution layer configuration process using a random filter with discriminating power, a data reduction process using PCA, and a CNN structure creation using SVM. The learning process is not necessary in the convolution layer construction process using the discriminating random filter, thereby shortening the learning time of the overall deep learning. PCA reduces the amount of memory and computation throughput. The creation of the CNN structure using SVM maximizes the effect of reducing the amount of memory and computational throughput required. In order to evaluate the performance of the proposed algorithm, we experimented with Yale University's Extended Yale B face database. The results show that the algorithm proposed in this paper has a similar performance recognition rate compared with the existing CNN algorithm. And it was confirmed to be excellent. Based on the algorithm proposed in this paper, it is expected that a deep learning algorithm with many data and computation processes can be implemented in a general PC.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.47 no.3
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• pp.7-17
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• 2010

In this paper, an innovative low-power SRAM based on 4-transistor latch cell is described. The memory cells are composed of two cross-coupled inverters without access transistors. The sources of PMOS transistors are connected to bitlines while the sources of NMOS transistors are connected to wordlines. They are accessed by totally new read and write method which results in low operating power dissipation in the nature. Moreover, the design reduces the leakage current in the memory cells. The proposed SRAM has been demonstrated through 16-kbit test chip fabricated in a 0.18-${\mu}m$ CMOS process. It shows 17.5 ns access at 1.8-V supply while consuming dynamic power of $87.6\;{\mu}W/MHz$ (for read cycle) and $70.2\;{\mu}W/MHz$ (for write cycle). Compared with those of the conventional 6-transistor SRAM, it exhibits the power reduction of 30 % (read) and 42 % (write) respectively. Silicon measurement also confirms that the proposed SRAM achieves nearly 64 % reduction in the total standby power dissipation. This novel SRAM might be effective in realizing low-power embedded memory in future mobile applications.

• Herbal Formula Science
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• v.25 no.1
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• pp.69-87
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• 2017

Objectives : Cheongnoemyeongsin-hwan (CNMSH) is a herb medicine to treat cognitive impairment. This study was investigated the effects of CNMSH on learning and memory impairment induced by cerebral hypoperfusion. Cerebral hypoperfusion was produced chronically by permanent bilateral common carotid artery occlusion (BCCAO) in rats. Methods : CNMSH was administered orally once a day (250 mg/kg) for 28 days starting at 4th week after the BCCAO. The acquisition of learning and the retention of memory were tested on 9th week after the BCCAO using the Morris water maze. In addition, effect of CNMSH on neuronal apoptosis and ${\beta}-amyloid$ accumulation in the hippocmapus was evaluated with immunohistochemistry and Western blotting. Results : 1. CNMSH and ChAL significantly shortened the escape latencies on the 2nd day of acquisition training trials. 2. ChAL significantly prolonged the swimming time spent in the target and peri-target zones and CNMSH also significantly prolonged the swimming time spent in the peri-target zone. 3. CNMSH and ChAL significantly increased the number of target heading in the retention test. 4. ChAL significantly shortened the time of the 1st target heading in the retention test, but CNMSH insignificantly shortened the time of that. 5. CNMSH and ChAL significantly increased the memory score in the retention test. 6. CNMSH and ChAL significantly attenuated the reduction of CA1 neurons, but insignificantly attenuated the reduction of CA1 thickness. 7. CNMSH and ChAL significantly attenuated the up-regulation of Bax expression in the CA1 of hippocampus. 8. CNMSH and ChAL significantly attenuated the up-regulation of cascapse-3 expression in the CA1 of hippocampus. 9. CNMSH and ChAL significantly attenuated the ${\beta}-amyloid$ accumulation in the CA1 of hippocampus. 10. CNMSH and ChAL significantly attenuated the up-regulation of APP expression in the CA1 of hippocampus. 11. CNMSH and ChAL significantly attenuated the up-regulation of BACE-1 expression in the CA1 of hippocampus. Conclusions : The results show that CNMSH attenuates neuronal apoptosis and ${\beta}-amyloid$ accumulation in the hippocampus and alleviates the impairment of learning and memory produced by chronic cerebral hypoperfusion. These results suggest that CNMSH may be a beneficial medicinal herb to treat cognitive impairment associated with neurodegenerative diseases.

• Journal of Physiology & Pathology in Korean Medicine
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• v.17 no.1
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• pp.50-56
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• 2003

This research was done to make the effective prescription and cope with various senile dementia. So Sprague-Dawley rats were injected with ibotenate to make a damage on learning and memory functions. At first acquisition test and retention rest were done in the Morris water maze. And to evaluate the effects of the sample drug(TBM) on choline acetyltranferase and acetylcholine esterase, immunoreactive measurement and enzymatic activity measuring were carried out. The ibotenic acid were injected to hippocampus CA1 and CA3 area. The results were as following. TBM improved the learning ability in the acquisition test and memory function in the retention test significantly. And TBM increased the level of ChAT which is synthesizing acetylcholine in CA3 area, and at the same time it increased the level of AChE which is resolving acetylcholine. These results show that T8M improved the cholinergic catabolism and anabolism, and the increment of metabolic activity of cholinergic system. In other words, it contributes to the recovery of damaged learning and memory function by ibotenic acid. So it can be concluded that TBM will be helpful to cholinergic brain damage induced by primary or senile reduction of acetylcholine secretive activity.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.39 no.2
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• pp.7-13
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• 2002

When a USB digital camera is used for PC video-conference applications, motion picture data need to be transferred to the PC through the USB port. Due to the mismatch between the data rates of the USB and the motion picture, data compression should be performed before the transmission from the USB. While many motion picture compression algorithms require large intermediate memory space, the JPEG algorithm does not need to store an entire frame for the compression. Instead, a relatively small buffer is required at the input of the JPEG compression engine to resolve the inconsistency between the orders of the inputted data and the consumed data. Data reordering can be easily implemented using a double buffering scheme, which still requires a considerable size of memory. In this paper, a novel memory management scheme is proposed to avoid the double buffering. The proposed memory architecture requires a small amount of memory and a simple address generation scheme, resulting in overall cost reduction.

• The Korean Journal of Physiology and Pharmacology
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• v.8 no.4
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• pp.173-179
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• 2004

Amyloid ${\beta}-peptide\;(A{\beta})$ contributes to the pathogenesis of Alzheimer's disease (AD), causing neuronal death through apoptosis. In this study, the neuroprotective role of BF-7, extracted form sericultural product, was examined against $A{\beta}-induced$ toxicity in cultured human neuronal cell SKN-SH. In order to know if the BF-7 has positive role on the cognition and memory in human, the mixture of BF-7, DHA and EPA (BDE) was examined using Rey Kim and K-WAIS test with 50 healthy high school student. We report here that BDE significantly attenuated $A{\beta}-induced$ apoptosis through the reduction of ROS accumulation, and diminished caspase-like protease activity. Moreover, the memory index and memory preservation, and attentative concentration of BDE treated group for 1 month were significantly improved, in contrast to the case of placebo control treated with DHA and EPA. This result represent that the BF-7 play significant positive role on learning memory. Taken together, our result suggested the natural product BF-7 is a good substance for the brain functionally and physiologically.

• 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.