• Journal of Menopausal Medicine
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• v.24 no.3
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• pp.183-187
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• 2018

Objectives: The present mini review aimed to summarize the existing knowledge regarding the beneficial and adverse effects of raloxifene in menopausal women. Methods: This study is a review of relevant publications about the effects of raloxifene on sleep disorder, depression, venous thromboembolism, the plasma concentration of lipoprotein, breast cancer, and cognitive function among menopausal women. Results: Raloxifene showed no significant effect on depression and sleep disorder. Verbal memory improved with administration of 60 mg/day of raloxifene while a mild cognitive impairment risk reduction by 33% was observed with administration of 120 mg/day of raloxifene. Raloxifene was associated with a 50% decrease in the need for prolapse surgery. The result of a meta-analysis showed a significant decline in the plasma concentration of lipoprotein in the raloxifene group compared to placebo (standardized mean difference, -0.43; 10 trials). A network meta-analysis showed that raloxifene significantly decreased the risk of breast cancer (relative risk, 0.572; 95% confidence interval, 0.327-0.881; P = 0.01). In terms of adverse effects of raloxifene, the odds ratio (OR) was observed to be 1.54 (P = 0.006), indicating 54% increase in the risk of deep vein thrombosis (DVT) while the OR for pulmonary embolism (PE) was 1.05, suggesting a 91% increase in the risk of PE alone (P = 0.03). Conclusions: Raloxifene had no significant effect on depression and sleep disorder but decreased the concentration of lipoprotein. Raloxifene administration was associated with an increased risk of DVT and PE and a decreased risk of breast cancer and pelvic organ prolapse in postmenopausal women.

• Smart Structures and Systems
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• v.6 no.5_6
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• pp.675-687
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• 2010

Structural Health Monitoring (SHM) is the science and technology of monitoring and assessing the condition of aerospace, civil and mechanical infrastructures using a sensing system integrated into the structure. Impedance-based SHM measures impedance of a structure using a PZT (Lead Zirconate Titanate) patch. This paper presents a low-power wireless autonomous and active SHM node called Autonomous SHM Sensor 2 (ASN-2), which is based on the impedance method. In this study, we incorporated three methods to save power. First, entire data processing is performed on-board, which minimizes radio transmission time. Considering that the radio of a wireless sensor node consumes the highest power among all modules, reduction of the transmission time saves substantial power. Second, a rectangular pulse train is used to excite a PZT patch instead of a sinusoidal wave. This eliminates a digital-to-analog converter and reduces the memory space. Third, ASN-2 senses the phase of the response signal instead of the magnitude. Sensing the phase of the signal eliminates an analog-to-digital converter and Fast Fourier Transform operation, which not only saves power, but also enables us to use a low-end low-power processor. Our SHM sensor node ASN-2 is implemented using a TI MSP430 microcontroller evaluation board. A cluster of ASN-2 nodes forms a wireless network. Each node wakes up at a predetermined interval, such as once in four hours, performs an SHM operation, reports the result to the central node wirelessly, and returns to sleep. The power consumption of our ASN-2 is 0.15 mW during the inactive mode and 18 mW during the active mode. Each SHM operation takes about 13 seconds to consume 236 mJ. When our ASN-2 operates once in every four hours, it is estimated to run for about 2.5 years with two AAA-size batteries ignoring the internal battery leakage.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2009.10a
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• pp.175-178
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• 2009

H.264/AVC is a video coding standard of ITU-T and ISO/IEC, and widely spreads its application due to its high compression ratio more than twice that of MPEG-2 and high image quality. In this paper, we explained Intra Prediction in H.264/AVC, which is able to achieve higher compressing efficiency from correlation removal of adjacent samples in spatial domain, and proposed efficient Intra Predictor architecture design for H.264/AVC decoder. The proposed system reduced computation cycle using processing element and precomputation processing element and also reduced the number of access to external memory using efficient register. We designed the proposed system with Verilog-HDL and verified with suitable test vector. The proposed Intra Predictor achieved about 60% cycle reduction comparing with existing Intra Predictors.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.12
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• pp.1697-1703
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• 2020

Sensor nodes that directly collect data from the surrounding environment have many constraints, such as power supply and memory size, thus efficient use of resources is required. In this paper, in a sensor node that receives location data of a vehicle on a lane, the data reception period is changed by the target's speed estimated by the Kalman filter and distance weight. For a slower speed of the vehicle, the longer data reception interval of the sensor node can reduce the processing time performed in the entire sensor network. The proposed method was verified through a traffic simulator implemented as MATLAB, and the results achieved that the processing time was reduced in the entire sensor network using the proposed method compared to the baseline method that receives all data from the vehicle.

• Journal of Ceramic Processing Research
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• v.20 no.5
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• pp.484-489
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• 2019

VO2 is an attractive candidate as a transition metal oxide switching material as a selection device for reduction of sneak-path current. We demonstrate deposition of nanoscale VO2 thin films via thermal atomic layer deposition (ALD) with H2O reactant. Using this method, we demonstrate VO2 thin films with high-quality characteristics, including crystallinity, reproducibility using X-ray diffraction, and X-ray photoelectron spectroscopy measurement. We also present a method that can increase uniformity and thin film quality by splitting the pulse cycle into two using scanning electron microscope measurement. We demonstrate an ON / OFF ratio of about 40, which is caused by metal insulator transition (MIT) of VO2 thin film. ALD-deposited VO2 films with high film uniformity can be applied to next-generation nonvolatile memory devices with high density due to their metal-insulator transition characteristic with high current density, fast switching speed, and high ON / OFF ratio.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.9
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• pp.1180-1186
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• 2020

One of the Embedded systems Tiny Processing Unit (TPU) usually acts in harsh environments like external shock or insufficient power. In these cases, data could be polluted, and cause critical problems. As a solution to data pollution, many embedded systems are using Error Correcting Code (ECC) to protect and restore data. However, ECC processing in TPU increases the overall processing time by increasing the time of instruction fetch which is the bottleneck. In this paper, we propose an architecture of parallelized ECC block to the reduce bottleneck of TPU. The proposed architecture results in the reduction of time 10% compared to the original model, although memory usage increased slightly. The test is evaluated with a matrix product that has various instructions. TPU with proposed parallelized ECC block shows 7% faster than the original TPU with ECC and was able to perform the proposed test accurately.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.9
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• pp.2991-3007
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• 2022

Two dimensional locality preserving projections (2D-LPP) is an improved algorithm of 2D image to solve the small sample size (SSS) problems which locality preserving projections (LPP) meets. It's able to find the low dimension manifold mapping that not only preserves local information but also detects manifold embedded in original data spaces. However, 2D-LPP is simple and elegant. So, inspired by the comparison experiments between two dimensional linear discriminant analysis (2D-LDA) and linear discriminant analysis (LDA) which indicated that matrix based methods don't always perform better even when training samples are limited, we surmise 2D-LPP may meet the same limitation as 2D-LDA and propose a novel matrix exponential method to enhance the performance of 2D-LPP. 2D-MELPP is equivalent to employing distance diffusion mapping to transform original images into a new space, and margins between labels are broadened, which is beneficial for solving classification problems. Nonetheless, the computational time complexity of 2D-MELPP is extremely high. In this paper, we replace some of matrix multiplications with multiple multiplications to save the memory cost and provide an efficient way for solving 2D-MELPP. We test it on public databases: random 3D data set, ORL, AR face database and Polyu Palmprint database and compare it with other 2D methods like 2D-LDA, 2D-LPP and 1D methods like LPP and exponential locality preserving projections (ELPP), finding it outperforms than others in recognition accuracy. We also compare different dimensions of projection vector and record the cost time on the ORL, AR face database and Polyu Palmprint database. The experiment results above proves that our advanced algorithm has a better performance on 3 independent public databases.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.3
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• pp.355-366
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• 2022

This paper proposes a microcode-based neural network accelerator controller for artificial intelligence accelerators that can be reconstructed using a programmable architecture and provide the advantages of low-power and ultra-small chip size. In order for the target accelerator to support various neural network models, the neural network model can be converted into microcode through microcode compiler and mounted on accelerator to control the operators of the accelerator such as datapath and memory access. While the proposed controller and accelerator can run various CNN models, in this paper, we tested them using the YOLOv2-Tiny CNN model. Using a system clock of 200 MHz, the Controller and accelerator achieved an inference time of 137.9 ms/image for VOC 2012 dataset to detect object, 99.5ms/image for mask detection dataset to detect wearing mask. When implementing an accelerator equipped with the proposed controller as a silicon chip, the gate count is 618,388, which corresponds to 65.5% reduction in chip area compared with an accelerator employing a CPU-based controller (RISC-V).

• Journal of Life Science
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• v.34 no.3
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• pp.208-213
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• 2024

Depression is one of the greatest health concerns in the world. Symptoms include emotion disorders, loss of appetite, reduction in interest, and insomnia. The prevalence of depression is increasing rapidly around the world and in South Korea. Elderly people are vulnerable to depression, resulting in serious socioeconomic problems. Depression in the elderly can cause sleep disorders, cognitive impairment, memory impairment, and many other diseases. Additionally, depression can cause frailty, which is associated with increased falls, chronic diseases, and mortality. Therefore, this study empirically analyzed sleep disorders in relation to depression, the link between exercise and the hippocampus in mitigating depression, and physical activity and exercise in the management of depression for successful aging.

• Korean Journal of Materials Research
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• v.34 no.6
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• pp.283-290
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• 2024

The aggressive scaling of dynamic random-access memory capacitors has increased the need to maintain high capacitance despite the limited physical thickness of electrodes and dielectrics. This makes it essential to use high-k dielectric materials. TiO₂ has a large dielectric constant, ranging from 30~75 in the anatase phase to 90~170 in rutile phase. However, it has significant leakage current due to low energy barriers for electron conduction, which is a critical drawback. Suppressing the leakage current while scaling to achieve an equivalent oxide thickness (EOT) below 0.5 nm is necessary to control the influence of interlayers on capacitor performance. For this, Pt and Ru, with their high work function, can be used instead of a conventional TiN substrate to increase the Schottky barrier height. Additionally, forming rutile-TiO₂ on RuO₂ with excellent lattice compatibility by epitaxial growth can minimize leakage current. Furthermore, plasma-enhanced atomic layer deposition (PEALD) can be used to deposit a uniform thin film with high density and low defects at low temperatures, to reduce the impact of interfacial reactions on electrical properties at high temperatures. In this study, TiO₂ was deposited using PEALD, using substrates of Pt and Ru treated with rapid thermal annealing at 500 and 600 ℃, to compare structural, chemical, and electrical characteristics with reference to a TiN substrate. As a result, leakage current was suppressed to around 10^-6 A/cm² at 1 V, and an EOT at the 0.5 nm level was achieved.