• Smart Structures and Systems
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• v.3 no.2
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• pp.133-146
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• 2007

This paper addresses a new type of broad and stage-based hybrid carbon fiber reinforced polymer (HCFRP) sensor that is suitable for the sensing of infrastructures. The HCFRP sensors, a type of composite sensor, are fabricated with three types of carbon tows of different strength and moduli. For all of the specimens, the active materials are carbon tows by virtue of their electrical conductivity and piezoresistivity. The measurement principles are based on the micro- and macro-fractures of different types of carbon tows. A series of experiments are carried out to investigate the sensing performances of the HCFRP sensors. The main variables include the stack order and volume fractions of different types of carbon tows. It is shown that the change in electrical resistance is in direct proportion to the strain/load in low strain ranges. However, the fractional change in electrical resistance (${\Delta}R/R_0$) is smaller than 2% prior to the macrofractures of carbon tows. In order to improve the resistance changes, measures are taken that can enhance the values of ${\Delta}R/R_0$ by more than 2 times during low strain ranges. In high strain ranges, the electrical resistance changes markedly with strain/load in a step-wise manner due to the gradual ruptures of different types of carbon tows at different strain amplitudes. The values of ${\Delta}R/R_0$ due to the fracture of high modulus carbon tows are larger than 36%. Thus, it is demonstrated that the HCFRP sensors have a broad and stage-based sensing capability.

• Journal of the Korea Society of Computer and Information
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• v.19 no.9
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• pp.75-84
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• 2014

In this paper, we constructed a sensor network environment where various sensors are used. Then, we evaluated the performance when this environment adopted existing clustering algorithms that are designed for only single type sensors network. In our experiments, we considered two different types of the networks. In the first, all nodes are equipped with identical sensors. In the second, all nodes are equipped with three different types of sensors. We measured performance variations of several clustering schemes in accordance with sensor data accuracy, sensor node resource depletion timing, amount of available energy, node isolation ratio, and network lifetime. According to our performance analysis, we proved that existing clustering algorithms are partially inefficient to maintain the various-sensor network. Consequently we suggest that a new algorithm is required to take aim at the various sensor network.

• Proceedings of the KSRS Conference
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• v.2
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• pp.852-855
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• 2006

There is an increasing need to use data from different sensors in order to maximize the chances of obtaining a cloud-free image and to meet timely requirements for information. However, the use of data from multiple sensor systems is depending on comprehensive relationships between sensors of different types. Indeed, a study of inter-sensor relationships is well advanced in the effective use of remotely sensed data from multiple sensors. This paper was concerned with relationships between sensors of different types for vegetation indices (VI). The study was conducted using IKONOS and Landsat-7 ETM+ images. IKONOS and Landsat-7 ETM+ image of the same or about the same dates were acquired. The Landsat-7 ETM+ images were resampled in order to make them coincide with the pixel sizes of IKONOS. Inter-relationships of vegetation indices between images were performed using at-satellite reflectance obtained by converting image digital number (DN). All images were applied to topographic normalization method in order to reduce topographic effect in digital imagery. Also, Inter-sensor model equations between two sensors were developed and applied to other study region. In the result, the relational equations can be used to compute or interpret VI of one sensor using the VI of another sensor.

• Proceedings of the Korean Society of Propulsion Engineers Conference
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• 2017.05a
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• pp.1088-1092
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• 2017

In this study, a comparison of dynamic pressure data measured in hot-firing tests of liquid rocket engine gas generators with different types of dynamic pressure sensors is presented. The dynamic pressure sensors of different types and manufacturers have exhibited different dynamic pressure due to the influence of thermal shock. However, for the characteristic frequencies and RMS(root mean square) values which are important factors for the analysis of combustion instability, the differences between sensors have been found to be negligible.

• Journal of the Korean Geographical Society
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• v.43 no.2
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• pp.220-234
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• 2008

In many security monitoring contexts, the performance or efficiency of surveillance sensors/networks based on a single sensor type may be limited by environmental conditions, like illumination change. It is well known that different modes of sensors can be complementary, compensating for failures or limitations of individual sensor types. From a location analysis and modeling perspective, a challenge is how to locate different modes of sensors to support security monitoring. A coverage-based optimization model is proposed as a way to simultaneously site k different sensor types. This model considers common coverage among different sensor types as well as overlapping coverage for individual sensor types. The developed model is used to site sensors in an urban area. Computational results show that common and overlapping coverage can be modeled simultaneously, and a rich set of solutions exists reflecting the tradeoff between common and overlapping coverage.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2001.05a
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• pp.318-322
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• 2001

This paper deals with sensing ability of smart sensor that has a sensing ability to distinguish materials according to surface types of smart sensor. We have developed a new signal processing method that can distinguish among different materials. The smart sensor was developed for recognition of materials. We made two types of smart sensors in our experiment. Then, we estimated the ability to recognize objects according to smart sensor type. We estimated the sensing ability of smart sensor with the $R_{SAI}$ method. Experiments and analysis were executed to estimate the ability to recognize objects according to surface types of smart sensor. Sensing ability of smart sensors was evaluated relatively through a new $R_{SAI}$ method. Applications of smart sensors are for finding abnormal conditions of objects (auto-manufacturing), feeling of objects (medical product), robotics, safety diagnosis of structure, etc.etc.

• Journal of the Ergonomics Society of Korea
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• v.34 no.2
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• pp.191-198
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• 2015

Objective: As a cue for desired mood, we attempted to identify types of sitting postures when people are involved in various tasks during their working hours. Background: Physical behaviors in reaction to user contexts were studied, such as automated posture analysis for detecting a subject's emotion. Sitting postures have high feasibility and can be detected robustly with a sensing chair, especially when it comes to an office. Method: First, we attached seven sensors, including six pressure sensors and one distance sensor, to an office chair. In Part 1, we recorded participants' postures while they took part in four different tasks. From the seven sensors, we gathered five sets of data related to the head, the lumbar, the hip, thigh pressure and the distance between the backrest and the body. We classified them into four postures: leaning forward, upright, upright with the lumbar supporting, and leaning backward. In part 2, we requested the subjects to take suitable poses for the each of the four task types. In this way, we compared the matches between postures and tasks in a natural setting to those in a controlled situation. Results: We derived four types of sitting postures that were mapped onto the different tasks. The comparison yielded no statistical significance between Parts 1 and 2. In addition, there was a significant association between the task types and the posture types. Conclusion: The users' sitting postures were related to different types of tasks. This study demonstrates how human emotion can interact with lighting, as mediated through physical behavior. Application: We developed a posture-based lighting system that manipulates the quality of office lighting and is operated by changes in one's posture. Facilitated by this system, color temperatures ranging between 3,000K and 7,000K and illuminations ranging between 300lx and 700lx were modulated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.13 no.9
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• pp.1928-1934
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• 2009

This paper proposes a power management scheme for sensor nodes in wireless sensor networks based on sensor node operating system supporting the sensor transparency, which can turn off the sensors when the MCU is in sleep mode. We classify the sensors in two types, that is, event sensors and polling sensors, to be able to decide whether the sensor is a type of sensors whose power supply can be turned off or not, and we design a new scheduler to support recognition of those different types of sensors. Implementing and evaluation of the scheduler and the power manager supporting sensor transparency are shown based on Nano-Q+.

• Journal of the Korean Society of Tobacco Science
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• v.27 no.1 s.53
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• pp.134-140
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• 2005

The purpose of this study was the discrimination of different tobacco types by the E-Nose/tongue and the analysis of what human sensory attributes are correlated with e-instrument's sensors. Samples were made from five groups of Korean domestic tobacco leaves, aged burley and not aged, aged flue-cured and not aged and blending types of the four. Instrumental tests were conducted to discriminate characteristics among different tobacco samples by the E-Nose and the E-Tongue. Sensory attributes of tobacco tastes were impact, irritation, bitterness, hay-like, tobacco taste, smoke volume, smoke pungent and mouth cleanness. STATISTICA software was used to analyze correlation between the human sensory data and the raw data of e-instruments. Discrimination analysis can be achieved using principal components analysis (PCA) and discriminant factorial analysis(DFA). As a result, impact, bitterness, irritation, smoke volume and smoke pungent of human sensory attributes were correlated with data from the several clustered E-Nose sensors(p < 0.10). And bitterness, irritation, and smoke pungent of human sensory attributes were correlated with data from the E-Tongue sensors(p < 0.10). PCA plot by the E-Nose shows that aged tobacco and not aged were discriminated and DFA plot shows that three groups(aged burley, not aged burley and flue-cured) were discriminated. PCA plot by the E- Tongue shows that flue-cured tobacco was separated from burley. Our results indicated that the e-instruments are sensitive enough to distinguish among tobacco types and their several sensors are reacted to the human sensory attributes.

• The Transactions of the Korean Institute of Electrical Engineers C
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• v.51 no.6
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• pp.246-252
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• 2002

This paper describes the acoustic emission measurement method to diagnose GIS for particles. We measured and analyzed the signals of acoustic waves using acoustic two types sensors with 125KHz and 50KHz resonant frequency respectively when the particles were dropped on the surfaces of circular plates and inside of GlS tanks. We found that the difference between peak outputs of two sensors depended on the types and materials of particles and the conditions of dropping position. These results showed that the outputs of 125KHz sensor were higher than those of 50KHz sensor in circular plate and 362㎸ GIS tank made of steel and vice versa in circular plate and 800㎸ GIS tank made of aluminum. The ratios outputs of 125KHz sensor to those of 50KHz sensor were 1.4 - 2.37 in 800㎸ GIS tank and were 0.5 - 1.0 in 362㎸ GIS tank. Therefore we knew that adaption of two types acoustic sensors which had different resonant frequencies as a very useful method in diagnosis of GIS.