• Journal of Sensor Science and Technology
• /
• v.21 no.3
• /
• pp.172-179
• /
• 2012

This paper presents the design and analysis of a vibration-driven electromagnetic energy harvester that uses a multi-pole magnet. The physical backgrounds of the vibration electromagnetic energy harvester are reported, and an ANSYS finite element analysis simulation has been used to determine the different alignments of the magnetic pole array with their flux lines and density. The basic working principles for a single and multi-pole magnet are illustrated and the proposed harvester has been presented in a schematic diagram. Mechanical parameters such as input frequency, maximum displacement, number of coil turns, and load resistance have been analyzed to obtain an optimized output power for the harvester through theoretical study. The paper reports a maximum of 1.005 mW of power with a load resistance of $1.9k{\Omega}$ for 5 magnets with 450 coil turns.

• Journal of Korea Society of Digital Industry and Information Management
• /
• v.7 no.3
• /
• pp.11-23
• /
• 2011

Recently, Open APIs are getting attention with the advent of Web 2.0. Open APIs are used to combine services and generate new services by Mashup. However, the growing number of available Open APIs raises a challenging issue how to locate the desired APIs. We automatically build ontologies from WSDL, WADL, HTML, and their underlying semantics. The key ingredient of our method is a technique that clusters input/output parameters in the collection of API methods into semantically meaningful concepts, and captures the hierarchical relationships between the terms contained in a parameter. These semantic ontologies allow search engines to support a similarity search for Open APIs based on various protocols such as SOAP, REST, JavaScript, and XML-RPC, and significantly improve the quality of APIs matching by the clustering and hierarchical relationships mechanism.

• ETRI Journal
• /
• v.34 no.6
• /
• pp.858-868
• /
• 2012

In this paper, stochastic models for the cross-correlation of multiple channels are established based on measurement data collected using a wideband multiple-input multiple-output relay Band Exploration and Channel Sounder system at 3.7 GHz. We propose models for the cross-correlation characteristics of large-scale parameters (LSPs) between two links, that is, the base station and mobile station (MS) link and the relay station and MS link. The LSPs include shadow fading, Rician K-factor, delay spread, angle spread of arrival, and angle spread of departure. Furthermore, models are established for the cross-correlation of the small-scale fading in the impulse responses of two links. The statistics of these model parameters are investigated as functions of geometrical features of the multilink. They are extracted from a large amount of cross-correlation observations, which are obtained in three measurement sites along more than one hundred measurement routes. These models can be used together with the standard single-link channel models for the generation of correlated components, for example, path clusters, in two separate channels.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.10
• /
• pp.1861-1868
• /
• 2008

In this paper, Passive Telemerty RF Sensor System using Unscented Kalman Filter algorithm(UKF) is proposed. General Passive Telemerty RF Sensor System means that it should be "wireless", "implantable" and "batterless". Conventional Passive Telemerty RF Sensor System adopts Integrated Circuit type, but there are defects like complexity of structure and limit of large power consumption in some cases. In order to overcome these kinds of faults, Passive Telemetry RF Sensor System based on inductive coupling principle is proposed in this paper. Because passive components R, L, C have stray parameters in the range of high frequency such as about 200[KHz] used in this paper, Passive Telemetry RF Sensor System considering stray parameters has to be derived for accurate model identification. Proposed Passive Telemetry RF Sensor System is simple because it consists of R, L and C and measures the change of environment like pressure and humidity in the type of capacitive value. This system adopted UKF algorithm for estimation of this capacitive parameter included in nonlinear system like Passive Telemetry RF Sensor System. For the purpose of obtaining learning data pairs for UKF Algorithm, Phase Difference Detector and Amplitude Detector are proposed respectively which make it possible to get amplitude and phase between input and output voltage. Finally, it is verified that capacitive parameter of proposed Passive Telemetry RF Sensor System using UKF algorithm can be estimated in noisy environment efficiently.

• Geomechanics and Engineering
• /
• v.22 no.1
• /
• pp.81-95
• /
• 2020

Measurement of the unconfined compressive strength (UCS) of the rock is critical to assess the quality of the rock mass ahead of a tunnel face. In this study, extensive field studies have been conducted along 3,885 m of the new Nagasaki tunnel in Japan. To predict UCS, a hybrid model of artificial neural network (ANN) based on genetic algorithm (GA) optimization was developed. A total of 1350 datasets, including six parameters of the Measurement-While- Drilling data and the UCS were considered as input and output parameters respectively. The multiple linear regression (MLR) and the ANN were employed to develop contrast models. The results reveal that the developed GA-ANN hybrid model can predict UCS with higher performance than the ANN and MLR models. This study is of great significance for accurately and effectively evaluating the quality of rock masses in tunnel engineering.

• Computers and Concrete
• /
• v.24 no.2
• /
• pp.137-150
• /
• 2019

In this paper, surrogate models such as multivariate adaptive regression splines (MARS) and M5P model tree (M5P MT) methods have been investigated in order to propose a new formulation for the 28-days compressive strength of self-compacting concrete (SCC) incorporating metakaolin as a supplementary cementitious materials. A database comprising experimental data has been assembled from several published papers in the literature and the data have been used for training and testing. In particular, the data are arranged in a format of seven input parameters covering contents of cement, coarse aggregate to fine aggregate ratio, water, metakaolin, super plasticizer, largest maximum size and binder as well as one output parameter, which is the 28-days compressive strength. The efficiency of the proposed techniques has been demonstrated by means of certain statistical criteria. The findings have been compared to experimental results and their comparisons shows that the MARS and M5P MT approaches predict the compressive strength of SCC incorporating metakaolin with great precision. The performed sensitivity analysis to assign effective parameters on 28-days compressive strength indicates that cementitious binder content is the most effective variable in the mixture.

• Journal of the Korean Society of Safety
• /
• v.32 no.1
• /
• pp.115-120
• /
• 2017

The aim of this study is to develop construction safety and health management cost prediction model using support vector machine (SVM). To this end, theoretical concept of SVM is investigated to formulate the cost prediction model. Input and output variables have been selected by analyzing the balancing accounts for the completed construction project. In order to train and validate the proposed prediction model, 150 data sets have been gathered from field. Effects of SVM parameters on prediction accuracy are analyzed and from which the optimal parameter values have been determined. The prediction performance tests are conducted to confirm the applicability of the proposed model. Based on the results, it is concluded that the proposed SVM model can effectively be used to predict the construction safety and health management cost.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
• /
• 2005.11a
• /
• pp.39-44
• /
• 2005

A broadband DC to 40 GHz 5-bit MMIC digital attenuator has been developed. The ultra broadband attenuator has been achieved by newly inserted the transmission lines in conventional Switched-T attenuator and the optimization of the transmission line parameters. Momentum was employed in design for an accurate performance prediction at high frequencies and Monte Carlo analysis was applied to verify performance stability against the MMIC process variation. The attenuator has been fabricated with 0.15 $\mu$m GaAs pHEMT process. This attenuator has 1 dB resolution and 23 dB dynamic range. High attenuation accuracy has been achieved over all attenuation range and full 40 GHz bandwidth with the reference state insertion loss of less than 6 dB at 20 GHz. The input and output return losses of the attenuator are better than 14 dB over all attenuation states and frequencies.

• Journal of Broadcast Engineering
• /
• v.14 no.4
• /
• pp.428-437
• /
• 2009

A high dynamic range (HDR) image can represent real world scenes that have a wide range of luminance intensity. However, compared with the range of real world luminance, conventional display devices have a low dynamic range (LDR). To display HDR images onto conventional displayable devices such as monitors and printers, we propose the logarithmic based global reproduction algorithm that considers the features of the image using reproduction parameters. Based on the characteristics of the image, we first modify the input luminance values for reproducing perceptually tuned images and then obtain the displayable output values directly. The experimental results show that the proposed algorithm achieves good subjective results while preserving details of the image; furthermore, the proposed algorithm has a fast, simple and practical structure for implementation.

• 제어로봇시스템학회:학술대회논문집
• /
• 1994.10a
• /
• pp.113-116
• /
• 1994

In this paper. we suggest new fuzzy modeling algorithm, which can be easily implemented, by combining HPC-MEANS Algorithm and Genetic Algorithm. HPC-MEANS used to cluster the sample data in input-output space will hyper planes and to make structure identification roughly and Genetic Algorithm is used to nine the premise and consequent parameters. For the validity of suggested methods we model the system with I/O data from known system. and then compare two systems.