• Journal of Power Electronics
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• v.11 no.2
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• pp.218-227
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• 2011

The subject of variable step size maximum power point tracking (MPPT) algorithms has been addressed in the literature. However, most of the addressed algorithms tune the variable step size according to two variables: the photovoltaic (PV) array voltage ($V_{PV}$) and the PV array current ($I_{PV}$). Therefore, both the PV array current and voltage have to be measured. Recently, maximum power point trackers that arc based on a single variable ($I_{PV}$ or $V_{PV}$) have received a great deal of attention due to their simplicity and ease of implementation, when compared to other tracking techniques. In this paper, two methods have been proposed to design a variable step size MPPT algorithm using only a single current sensor for stand-alone battery storage PV systems. These methods utilize only the relationship between the PV array measured current and the converter duty cycle (D) to automatically adapt the step change in the duty cycle to reach the maximum power point (MPP) of the PV array. Detailed analyses and flowcharts of the proposed methods are included. Moreover, a comparison has been made between the proposed methods to investigate their performance in the transient and steady states. Finally, experimental results with field programmable gate arrays (FPGAs) are presented to verify the performance of the proposed methods.

• Progress in Superconductivity and Cryogenics
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• v.24 no.1
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• pp.29-33
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• 2022

Recently, development of a cryogenic fluids storage tank for storing or transporting liquid hydrogen is actively in progress. In cryogenic fluids storage tanks, hydrogen evaporates due to the extreme temperature difference inside and outside the tank. As the mass of the cryogenic fluids changes with continuous vaporization, the fluids level also changes. Therefore, there is need for a method of accurately measuring the level change in the storage tank. In the case of general cryogenic fluids, it is difficult to accurately measure the level because the dielectric constant is very low. As a method of measuring cryogenic fluids level with low dielectric constant, it can be used an Millimeter wave (MM wave) FMCW radar sensor. However, the signal sensitivity is very weak and the level accuracy is poor. In this paper, the signal sensitivity is improved by designing the horn lens antenna of the existing 80 GHz FMCW radar sensor. Horn lens antenna is fabricated by FDM/SLA type 3D printer according to horn and lens characteristics. The horn is used to increase the signal gain and the lens improves the signal straightness. This makes it possible to measure the level of cryogenic fluids with a low dielectric constant.

• Journal of the Korean Society for Nondestructive Testing
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• v.31 no.3
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• pp.246-259
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• 2011

This study presents a structural health monitoring (SHM) method for bolted connections by using multi-channel wireless impedance sensor nodes and multiple PZT-interfaces. To achieve the objective, the following approaches are implemented. Firstly, a PZT-interface is designed to monitor bolt loosening in bolted connection based on variation of electro-mechanical(EM) impedance signatures. Secondly, a wireless impedance sensor node is designed for autonomous, cost-efficient and multi-channel monitoring. For the sensor platform, Imote2 is selected on the basis of its high operating speed, low power requirement and large storage memory. Finally, the performance of the wireless sensor node and the PZT-interfaces is experimentally evaluated for a bolt-connection model Damage monitoring method using root mean square deviation(RMSD) index of EM impedance signatures is utilized to estimate the strength of the bolted joint.

• Proceedings of the KSRS Conference
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• 2005.10a
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• pp.276-279
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• 2005

As the Ubiquitous generation approaches, the importance of the sensor data processing is growing. The data approximation scheme, one of the data processing methods, can be the key of sensor data processing, for it is related not only to the lifetime of sensors but also to the size of the storage. In this paper, we propose the Harmonic Wavelet transform which can minimize the relative error for given sensor data. Harmonic Wavelets use the harmonic mean as a representative which is the minimum point of the maximum relative error between two data values. In addition, Harmonic Wavelets retain the relative errors as wavelet coefficients so we can select proper wavelet coefficients that reduce the relative error more easily. We also adapt the greedy algorithm for local optimization to reduce the time complexity. Experimental results show the performance and the scalability of Harmonic Wavelets for sensor data.

• 정보저장시스템학회:학술대회논문집
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• 2005.10a
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• pp.160-161
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• 2005

Using a Shack-Hartmann sensor, we construct an optical testing system measuring the wavefront error of small optical components. The systematic error of the sensor is compensated with a reference plane-wave system that produces almost perfect plane waves. Several types of lenses are tested using a point source that generates spherical waves emitted from a pinhole. The results of the optical testing obtained with the Shack- Hartman sensor are compared with those measured with Zygo interferometer.

• Bulletin of the Korean Chemical Society
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• v.31 no.11
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• pp.3084-3092
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• 2010

This paper describes the development of an automated, hand-held sensor for the fast assessment of seafood freshness. The sensor developed here combined: an array-based chemical sensor, composed of incrementally different conducting polymer elements deposited on a small chip; a highly sensitive, custom-made electronics for the detection of very small signal changes; precise temperature control of the sensor chamber; and an on-board microcontroller for data collection, storage, automation, and analysis. The instrument was used to successfully test seafood samples with different degree of freshness and spoilage. A linear relationship between microbiological count and e-Nose signal for three different fish fillet was developed. Once the linear relationship is included into the hand-held unit software, the e-Nose signal can be used for assessment of seafood freshness without performing the microbiological count technique.

• Journal of Information Processing Systems
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• v.17 no.6
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• pp.1035-1043
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• 2021

An Internet of Things (IOT) sensor network is an effective solution for monitoring environmental conditions. However, IOT sensor networks generate massive data such that the abilities of massive data storage, processing, and query become technical challenges. To solve the problem, a Hadoop cloud platform is proposed. Using the time and workload genetic algorithm (TWLGA), the data processing platform enables the work of one node to be shared with other nodes, which not only raises efficiency of one single node but also provides the compatibility support to reduce the possible risk of software and hardware. In this experiment, a Hadoop cluster platform with TWLGA scheduling algorithm is developed, and the performance of the platform is tested. The results show that the Hadoop cloud platform is suitable for big data processing requirements of IOT sensor networks.

• Smart Structures and Systems
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• v.2 no.2
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• pp.189-208
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• 2006

Monitoring large-scale civil engineering structures such as offshore platforms and high-large buildings requires a large number of sensors of different types. Innovative sensor data information technologies are very extremely important for data transmission, storage and retrieval of large volume sensor data generated from large sensor networks. How to obtain the optimal sensor set and placement is more and more concerned by researchers in vibration-based SHM. In this paper, a method of determining the sensor location which aims to extract the dynamic parameter effectively is presented. The method selects the number and place of sensor being installed on or in structure by through the tolerance domain statistical inference algorithm combined with second order sensitivity technology. The method proposal first finds and determines the sub-set sensors from the theoretic measure point derived from analytical model by the statistical tolerance domain procedure under the principle of modal effective independence. The second step is to judge whether the sorted out measured point set has sensitive to the dynamic change of structure by utilizing second order characteristic value sensitivity analysis. A 76-high-building benchmark mode and an offshore platform structure sensor optimal selection are demonstrated and result shows that the method is available and feasible.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.7
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• pp.1756-1776
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• 2012

Wireless sensor networks (WSNs) are likely to be more prevalent as their cost-effectiveness improves. The spectrum of applications for WSNs spans multiple domains. In environmental sciences, in particular, they are on the way to become an essential technology for monitoring the natural environment and the dynamic behavior of transient physical phenomena over space. Existing sensor network query processors (SNQPs) have also demonstrated that in-network processing is an effective and efficient means of interaction with WSNs for performing queries over live data. Inspired by these findings, this paper investigates the question as to whether spatio-temporal and historical analysis can be carried over WSNs using distributed query-processing techniques. The emphasis of this work is on the spatial, temporal and historical aspects of sensed data, which are not adequately addressed in existing SNQPs. This paper surveys the novel approaches of storing the data and execution of spatio-temporal and historical queries. We introduce the challenges and opportunities of research in the field of in-network storage and in-network spatio-temporal query processing as well as illustrate the current status of research in this field. We also present new areas where the spatio-temporal and historical query processing can be of significant importance.

• Journal of KIISE:Databases
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• v.33 no.1
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• pp.32-41
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• 2006

In data-centric networks, various data items, such as temperature, humidity, etc. are sensed and stored in sensor nodes. As these attributes are mostly scalar values and inter-related, multi-dimensional range queries are useful. To process multi-dimensional range queries efficiently in data-centric storage, data addressing is essential. The Previous work focused on efficient query processing without considering overall network lifetime. To prolong network lifetime and support multi-dimensional range queries, we propose a dynamic data distribution method for multi-dimensional data, where data space is divided into equal-sized regions and linearized by using Hilbert space filling curve.