• Science of Emotion and Sensibility
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• v.20 no.3
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• pp.97-108
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• 2017

The purpose of this study was to propose a product planning and design direction for smart fitness wear that will improve the impact of personal training based on researching the requirements of smart fitness wear and its acceptance level, as well as the functional demand. The study conducted in-depth interviews with professional fitness trainers and derived five categories and thirteen keywords by analyzing the categorical data analysis using the interview data. In addition, we surveyed general consumers to measure the acceptance level of smart fitness wear and the functional demand for product development. The results revealed that the difference in the acceptance level of smart fitness wear generally depended on the characteristics related to exercise involvement and exercise-related culture rather than on the demographic characteristics. With regard to the difference in the functional demand of smart fitness wear, the results showed that professional trainers focused on the scientific improvement of the effect of exercise while general consumers focused on the function that considers the sustainability of exercise. Based on the results, we proposed product planning and design directions such as 'mounting of heart rate sensing, muscle activity sensing, motion angle or posture sensing, and motion sensing', 'development of concepts and contents for expert line, ordinary line', 'compression wear design', and 'differentiation of product development according to exercise areas'.

• Journal of the Korea institute for structural maintenance and inspection
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• v.26 no.5
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• pp.57-65
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• 2022

This study investigated the electromechanical response of smart ultra-high performance fiber reinforced concretes (S-UHPFRCs) under flexural loading to evaluate the self-sensing capacity of S-UHPFRCs in both tension and compression region. The electrical resistivity of S-UHPFRCs under flexural continuously changed even after first cracking due to the deflection-hardening behavior of S-UHPFRCs with the appearance of multiple microcracks. As the equivalent bending stress increased, the electrical resistivity of S-UHPFRCs decreased from 976.57 to 514.05 kΩ(47.0%) as the equivalent bending stress increased in compression region, and that did from 979.61 to 682.28 kΩ(30.4%) in tension region. The stress sensitivity coefficient of S-UHPFRCs in compression and tension region was 1.709 and 1.098 %/MPa, respectively. And, the deflection sensitivity coefficient of S-UHPFRCs in compression region(30.06 %/mm) was higher than that in tension region(19.72 %/mm). The initial deflection sensing capacity of S-UHPFRCs was almost 50% of each deflection sensitivity coefficient, and it was confirmed that it has an excellent sensing capacity for the initial deflection. Although both stress- and deflection-sensing capacity of S-UHPFRCs under flexural were higher in compression region than in tension region, S-UHPFRCs are sufficient as a self-sensing material to be applied to the construction field.

• 한국HCI학회:학술대회논문집
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• 2008.02a
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• pp.251-255
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• 2008

We have developed an electronic aids, called SmartWand, which can help visually impaired people walk safely and tell them an object's color and environmental brightness SmartWand can inform visually impaired people of the dangerous obstacles around which they can't notice by the white cane such as a large panel with supporting poles on the street. Especially we have lmproved the previous version of SmartWand by reflecting the result of user study.

• Smart Structures and Systems
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• v.4 no.3
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• pp.367-389
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• 2008

Shape Memory Alloys (SMAs) are unique materials with a paramount potential for various applications in bridges. The novelty of this material lies in its ability to undergo large deformations and return to its undeformed shape through stress removal (superelasticity) or heating (shape memory effect). In particular, Ni-Ti alloys have distinct thermomechanical properties including superelasticity, shape memory effect, and hysteretic damping. SMA along with sensing devices can be effectively used to construct smart Reinforced Concrete (RC) bridges that can detect and repair damage, and adapt to changes in the loading conditions. SMA can also be used to retrofit existing deficient bridges. This includes the use of external post-tensioning, dampers, isolators and/or restrainers. This paper critically examines the fundamental characteristics of SMA and available sensing devices emphasizing the factors that control their properties. Existing SMA models are discussed and the application of one of the models to analyze a bridge pier is presented. SMA applications in the construction of smart bridge structures are discussed. Future trends and methods to achieve smart bridges are also proposed.

• Journal of the Optical Society of Korea
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• v.7 no.2
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• pp.106-112
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• 2003

In order to do continuous health monitoring of large structures, it is necessary that the distributed sensing of strain and temperature of the structures be measured. So, we present the temperature compensation of a signal from a fiber optic BOTDA (Brillouin Optical Time Domain Analysis) sensor. A fiber optic BOTDA sensor has good performance of strain measurement. However, the signal of a fiber optic BOTDA sensor is influenced by strain and temperature. Therefore, we applied an optical fiber on the beam as follows: one part of the fiber, which is sensitive to the strain and the temperature, is bonded on the surface of the beam and another part of the fiber, which is only sensitive to the temperature, is located nearby the strain sensing fiber. Therefore, the strains can be determined from the strain sensing fiber while compensating for the temperature from the temperature sensing fiber. These measured strains were compared with the strains from electrical strain gages. After temperature compensation, it was concluded that the strains from the fiber optic BOTDA sensor had good coincidence with those values of the conventional electrical strain gages.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.22 no.5
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• pp.81-88
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• 2021

Structural health monitoring (SHM) systems have attracted considerable interest owing to the frequent earthquakes over the last decade. Smart concrete is a technology that can analyze the state of structures based on their electro-mechanical behavior. On the other hand, most research on the self-sensing response of smart concrete generally investigated the electro-mechanical behavior of smart concrete under a static loading rate, even though the loading rate under an earthquake would be much faster than the static rate. Thus, this study evaluated the electro-mechanical behavior of smart ultra-high-performance concrete (S-UHPC) at three different loading rates (1, 4, and 8 mm/min) using a Universal Testing Machine (UTM). The stress-sensitive coefficient (SC) at the maximum compressive strength of S-UHPC was -0.140 %/MPa based on a loading rate of 1 mm/min but decreased by 42.8% and 72.7% as the loading rate was increased to 4 and 8 mm/min, respectively. Although the sensing capability of S-UHPC decreased with increased load speed due to the reduced deformation of conductive materials and increased microcrack, it was available for SHM systems for earthquake detection in structures.

• Journal of Sensor Science and Technology
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• v.27 no.2
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• pp.137-141
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• 2018

Detecting the ego-lane of a vehicle (the lane on which the vehicle is currently running) is one of the basic techniques for a smart car. Vision sensing is a widely-used method for the ego-lane detection. Existing studies usually find road lane lines by detecting edge pixels in the image from a vehicle camera, and then connecting the edge pixels using Hough Transform. However, this approach takes rather long processing time, and too many straight lines are often detected resulting in false detections in various road conditions. In this paper, we find the lane lines by scanning only a limited number of horizontal lines within a small image region of interest. The horizontal image line scan replaces the edge detection process of existing methods. Automatic thresholding and spatiotemporal filtering procedures are also proposed in order to make our method reliable. In the experiments using real road images of different conditions, the proposed method resulted in high success rate.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.7
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• pp.649-657
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• 2004

A windshield wiper system plays a key part in assurance of driver's safety at rainfall. However, because quantity of rain and snow vary irregularly according to time and velocity of automotive, a driver changes speed and operation period of a wiper from time to time in order to secure enough visual field in the traditional windshield wiper system. Because a manual operation of wiper distracts driver's sensitivity and causes inadvertent driving, this is becoming direct cause of traffic accident. Therefore, this paper presents the basic architecture of vision-based smart wiper system and the rain sensing algorithm that regulate speed and interval of wiper automatically according to quantity of rain or snow. Also, this paper introduces the fuzzy wiper control algorithm based on human's expertise, and evaluates performance of suggested algorithm in the simulator model. Especially the vision sensor can measure wider area relatively than the optical rain sensor, hence, this grasps rainfall state more exactly in case disturbance occurs.

• International Journal of Advanced Culture Technology
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• v.5 no.1
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• pp.64-69
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• 2017

The rapid growth of algae occurs can induce the algae bloom when nutrients are supplied from anthropogenic sources such as fertilizer, animal waste or sewage in runoff the water currents or upwelling naturally. The algae blooms creates the human health problem in the environment as well as in the water resource managers including hypoxic dead zones and harmful toxins and pose challenges to water treatment systems. The algal blooms in the source water in water treatment systems affects the drinking water taste & odor while clogging or damaging filtration systems and putting a strain on the systems designed to remove algal toxins from the source water. This paper propose the emerging In-Situ self-diagnosable smart algae sensing device with wireless connectivity for smart remote monitoring and control. In this research, we developed the In-Site Algae diagnosable sensing device with wireless sensor network (WSN) connectivity with Optical Biological Sensor and environmental sensor to monitor the water treatment systems. The proposed system emulated in real-time on the water treatment plant and functional evaluation parameters are presented as part of the conceptual proof to the proposed research.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.28 no.4
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• pp.999-1007
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• 2018

To implement crowdsensing system in reality, trustiness between service provider server and user is necessary. Service provider server could manipulate the evaluation of sensing data to reduce incentive. Moreover, user could send a fake sensing data to get unjust incentive. In this paper, we adopt private blockchain on crowdsensing system, and thus paid incentives and sent data are unmodifiablely recorded. It makes server and users act as watcher of each others. Through adopting smart contract, our system automates sensing data evaluation and opens to users how it works. Finally, we show the feasibility of proposing system with performance evaluation and comparison with other systems.