• Smart Structures and Systems
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• v.22 no.4
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• pp.399-411
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• 2018

The difficulty in modeling complex nonlinear structures lies in the presence of significant sources of uncertainties mainly attributed to sudden changes in the structure's behavior caused by regular aging factors or extreme events. Quantifying these uncertainties and accurately representing them within the complex mathematical framework of Structural Health Monitoring (SHM) are significantly essential for system identification and damage detection purposes. This study highlights the importance of uncertainty quantification in SHM frameworks, and presents a comparative analysis between intrusive and non-intrusive techniques in quantifying uncertainties for SHM purposes through two different variations of the Kalman Filter (KF) method, the Ensemble Kalman filter (EnKF) and the Polynomial Chaos Kalman Filter (PCKF). The comparative analysis is based on a numerical example that consists of a four degrees-of-freedom (DOF) system, comprising Bouc-Wen hysteretic behavior and subjected to El-Centro earthquake excitation. The comparison is based on the ability of each technique to quantify the different sources of uncertainty for SHM purposes and to accurately approximate the system state and parameters when compared to the true state with the least computational burden. While the results show that both filters are able to locate the damage in space and time and to accurately estimate the system responses and unknown parameters, the computational cost of PCKF is shown to be less than that of EnKF for a similar level of numerical accuracy.

• International journal of advanced smart convergence
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• v.7 no.1
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• pp.1-6
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• 2018

In addition to the instability of energy import costs caused by the depletion of petroleum resources, which is a representative energy resource, and the strengthening of various regulations such as the convention on climate change, the plant for bio energy production, which is being watched as the next generation energy, and became subject of various complaints. In order to solve this problem, the bio-plant is underground and the ground is parked, making the convenience and accessibility of citizens more and more accessible. In this situation, the development of bioenergy production technology also increases the risk factor in bioenergy production process. Accordingly this paper explains method about apply the wide angle camera based AOA algorithm to the bio plant to prevent the accidents from spreading due to the lack of facilities and safety devices and the aging of the facilities and suggests a technique that can quickly identify the location and direction when it occurs.

• Smart Structures and Systems
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• v.7 no.1
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• pp.41-57
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• 2011

A deeper understanding of the effectiveness of adopting devices mounting shape memory alloy (SMA) elements in applications targeted to the mitigation of vibrations is pursued via an experimental approach. During a seismic event, less than 1000 loading-unloading cycles of the alloy are required to mitigate the earthquake effects. However, the aging effects during the time of inactivity prior to the oscillations (several decades characterized by the yearly summer-winter temperature wave) should be considered in order to avoid and/or minimize them. In this paper, the results obtained by carrying out, in different laboratories, fatigue tests on SMA specimens are compared and discussed. Furthermore, the effects of seismic events on a steel structure, with and without SMA dampers, are numerically simulated using ANSYS. Under an earthquake excitation, the SMA devices halve the oscillation amplitudes and show re-centering properties. To confirm this result, an experimental campaign is conducted by actually installing the proposed devices on a physical model of the structure and by evaluating their performance under different excitations induced by an actuator.

• Smart Structures and Systems
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• v.12 no.3_4
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• pp.427-440
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• 2013

A growing need has developed in the United States to obtain more specific knowledge on the structural integrity of infrastructure due to aging service lives, heavier and more frequent loading conditions, and durability issues. This need has spurred extensive research in the area of structural health monitoring over the past few decades. Several structural health monitoring techniques have been developed that are capable of locating damage in structures using modal strain energy of mode shapes. Typically in the past, bending strain energy has been used in these methods since it is a dominant vibrational mode in many structures and is easily measured. Additionally, there may be cases, such as pipes, shafts, or certain bridges, where structures exhibit significant torsional behavior as well. In this research, torsional strain energy is used to locate damage. The damage index method is used on two numerical models; a cantilevered steel pipe and a simply-supported steel plate girder bridge. Torsion damage indices are compared to bending damage indices to assess their effectiveness at locating damage. The torsion strain energy method is capable of accurately locating damage and providing additional valuable information to both of the structures' behaviors.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.31 no.6
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• pp.422-426
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• 2018

The lithium-ion battery pack of an electric vehicle (EV) deserves to be considered for an alternative use within smart-grid infrastructure. Despite the long automotive service life, EV batteries retain over 70~80% of their initial capacity. These battery packs must be managed for their reliability and safety. Therefore, a battery management system (BMS) should use specific algorithms to measure and estimate the status of the battery. Most importantly, the BMS of a grid-connected energy storage system (ESS) must ensure that the lithium-ion battery does not catch fire or explode due to an internal short from uncontrolled dendrite growth. In other words, the BMS of a lithium-ion battery pack should be capable of detecting the battery's status based on the electrochemical reaction continuously until the end of the battery's lifespan. In this paper, we propose a new protection algorithm for a dendritic lithium battery. The proposed algorithm has applied a parameter from battery pack aging results and has control power managing.

• Journal of Preventive Medicine and Public Health
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• v.46 no.sup1
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• pp.22-27
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• 2013

The purpose of this study was to examine the beneficial effects of a new cognitive intervention program designed for the care and prevention of dementia, namely Learning Therapy. The training program used systematized basic problems in arithmetic and Japanese language as training tasks. In study 1, 16 individuals in the experimental group and 16 in the control group were recruited from a nursing home. In both groups, all individuals were clinically diagnosed with senile dementia of the Alzheimer type. In study 2, we performed a single-blind, randomized controlled trial in our cognitive intervention program of 124 community-dwelling seniors. In both studies, the daily training program using reading and arithmetic tasks was carried out approximately 5 days a week, for 15 to 20 minutes a day in the intervention groups. Neuropsychological measures were determined simultaneously in the groups both prior to and after six months of the intervention. The results of our investigations indicate that our cognitive intervention using reading and arithmetic problems demonstrated a transfer effect and they provide convincing evidence that cognitive training maintains and improves the cognitive functions of dementia patients and healthy seniors.

• Journal of Korea Multimedia Society
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• v.17 no.5
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• pp.640-653
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• 2014

Recently medical consumers pursue high leveled quality of life through active promotion, prevention, management activity of health as the importance of health during home life is emerged to meet the aging society and chronic diseases. In addition, people are directed to the m-Health for managing yourself their health by using smartphone and various personal health devices, if necessary transmits health data to the physician himself. In the previous studies, m-Health Application were developed and applied in the real clinical environment by adopting the medical information standards was rarely conducted. Therefore, in this study, the m-Health application platform was developed. Developed application was communicate with IEEE 11073 standard protocol using the Bluetooth Health Device Profile in personal health device via smart phone to process blood pressure information, and it converted to HL7 V2.6 ORU_R01 message for send to remote medical server. In addition, we tested the interoperability and safety of the developed application for 23 inpatient and 17 outpatient at D University Hospital. As a result, the blood pressure information has been transmitted without error.

• Annual Conference of KIPS
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• 2015.10a
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• pp.1711-1714
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• 2015

스마트 디바이스가 사회와 소통할 수 있는 도구가 되었음에도 불구하고 아직까지 노인들이 사용하기에는 어려움이 있다. 여기에 음성인식 기술을 이용한 음성인터페이스를 활용함으로써 노인들의 스마트 디바이스에 대한 사용성을 높일 수 있다. 하지만 일반적인 음성인식 시스템은 청장년의 발성 스타일에 맞춰져 있기 때문에, 노화된 노인의 발성이 그대로 입력될 경우 음성인식률이 하락한다. 본 연구에서는 노인의 음절 별 발화속도가 일반적인 음성인식 시스템의 성능을 보증할 수 있는 범위를 벗어나는 경우가 많다는 분석 결과를 토대로 노인의 음절 별 발화속도를 조정한 결과 노인남녀 평균 음성인식률이 15.3% 상승하였다. 이처럼 노인의 음성인식 오류 원인들 중 하나인 발화속도의 재조정으로 음성 인식률을 높일 수 있는 토대를 마련하였다. 이는 노인들이 스마트 디바이스를 이용하여 쉽고 정확한 작업을 수행할 수 있게 됨으로써, 노인들의 사회 참여와 정보 획득이 용이해 지고 더 나아가 세대 간의 소통에도 이바지할 것으로 기대한다.

• Smart Structures and Systems
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• v.23 no.3
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• pp.227-242
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• 2019

Seismic isolation systems employ structural control that protect both buildings and vibration-sensitive contents from destructive effects of earthquakes. Structural control is divided into three main groups: passive, active, and semi-active. Among them, semi-active isolation systems, which can reduce floor displacements and accelerations concurrently, has gained importance in recent years since they don't require large power or pose stability problems like active ones. However, their seismic performance may vary depending on the variations that may be observed in the mechanical properties of semi-active devices and/or seismic isolators. Uncertainties relating to isolators can arise from variations in geometry, boundary conditions, material behavior, or temperature, or aging whereas those relating to semi-active control devices can be due to thermal changes, inefficiencies in calibrations, manufacturing errors, etc. For a more realistic evaluation of the seismic behavior of semi-active isolated buildings, such uncertainties must be taken into account. Here, the probabilistic behavior of semi-active isolated buildings under historical pulse-like near-fault earthquakes is evaluated in terms of their performance in preserving structural integrity and protecting vibration-sensitive contents considering aforementioned uncertainties via Monte-Carlo simulations of 3-story and 9-story semi-active isolated benchmark buildings. The results are presented in the form of fragility curves and probability of failure profiles.

• Journal of Information Processing Systems
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• v.16 no.6
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• pp.1238-1249
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• 2020

Throughout the world, aging populations and doctor shortages have helped drive the increasing demand for smart healthcare systems. Recently, these systems have benefited from the evolution of the Internet of Things (IoT), big data, and machine learning. However, these advances result in the generation of large amounts of data, making healthcare data analysis a major issue. These data have a number of complex properties such as high-dimensionality, irregularity, and sparsity, which makes efficient processing difficult to implement. These challenges are met by big data analytics. In this paper, we propose an innovative analytic framework for big healthcare data that are collected either from IoT wearable devices or from archived patient medical images. The proposed method would efficiently address the data heterogeneity problem using middleware between heterogeneous data sources and MapReduce Hadoop clusters. Furthermore, the proposed framework enables the use of both fog computing and cloud platforms to handle the problems faced through online and offline data processing, data storage, and data classification. Additionally, it guarantees robust and secure knowledge of patient medical data.