• Smart Structures and Systems
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• v.25 no.1
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• pp.37-45
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• 2020

This paper aims at enlightening the properties, computational and implementation issues related to Kalman filter based state estimation algorithms and sliding mode observers, by applying them for estimating the states of a smart structure system. The Kalman based estimators considered in this work are Kalman filter and information filter and, the sliding mode observers considered are Utkin observer and higher order sliding mode observer. A fourth order linear time invariant model of a piezo actuated beam is used in this work. This structure is embedded with four number of piezo patches, of which two act as sensors, one as disturbance actuator and the other as control actuator. The performance of the state estimation algorithms is evaluated through simulation, for the first two vibrating modes of the piezo actuated structure, when the structure is maintained at first mode and second mode resonance.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.11
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• pp.2849-2865
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• 2012

In order to block mobile junk messages automatically, many studies on spam filters have applied machine learning algorithms. Most previous research focused only on the accuracy rate of spam filters from the view point of the algorithm used, not on individual user's preferences. In terms of individual taste, the spam filters implemented on a mobile device have the advantage over spam filters on a network node, because it deals with only incoming messages on the users' phone and generates no additional traffic during the filtering process. However, a spam filter on a mobile phone has to consider the consumption of resources, because energy, memory and computing ability are limited. Moreover, as time passes an increasing number of feature words are likely to exhaust mobile resources. In this paper we propose a spam filter model distributed between a users' computer and smart phone. We expect the model to follow personal decision boundaries and use the uniform resources of smart phones. An authorized user's computer takes on the more complex and time consuming jobs, such as feature selection and training, while the smart phone performs only the minimum amount of work for filtering and utilizes the results of the information calculated on the desktop. Our experiments show that the accuracy of our method is more than 95% with Na$\ddot{i}$ve Bayes and Support Vector Machine, and our model that uses uniform memory does not affect other applications that run on the smart phone.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.2
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• pp.271-278
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• 2021

This paper is a study on the implementation of smart filter system that recognizes the external environment and automatically removes pollutants according to pollution level. Recently, the occurrence of various pollutants in indoor and outdoor space has adversely affected the human body. Especially, various fine dust generated in the atmosphere becomes worse in closed residential space or office space. Although air pollution can be temporary lowered through ventilation, it is difficult to respond to fine dust changes in real time, and such problems become serious in the space where many people reside, such as at home or industry. Therefore, it is necessary to measure the pollution level of fine dust inside the residential space in real time and to reduce the pollution of indoor ventilation through automatic ventilation with the outside. To improve these problems, this paper proposes the implementation of smart filter system for external environment recognition. The structure of smart filter system that automatically measures air quality inside and outside, removes pollutants, implements the function, and confirms the operability by manufacturing prototypes. Finally, the effectiveness of the smart filter system for solving fine dust problems was examined.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.60 no.12
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• pp.2299-2304
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• 2011

In this paper, we propose the methodology to make the bandpass filters for the Smart Grid IED(Intelligent Electronic Device) smaller than the conventional bandpass filters. The size-reduction of the filters and the filter performances are indebted to devising small CRLH(composite right- and left-handed) resonators and coupling them as the metamaterial structures. The design methodology is validated by the equivalent circuit to be compared with the reliable full-wave EM simulation, and the proposed metamaterial filter outperforms the standard parallel-edge coupled filter with respect to the miniaturization and frequency response.

• JSTS:Journal of Semiconductor Technology and Science
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• v.16 no.5
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• pp.682-686
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• 2016

A fully differential RC calibrator for accurate cut-off frequency of a programmable channel selection filter is proposed. The proposed RC calibrator consists of an RC timer, clock generator, synchronous counter, digital comparator, and control block. To verify the proposed RC calibrator, a six-order Chebyshev programmable low-pass filter with adjustable 3 dB cut-off frequency, which is controlled by the proposed RC calibrator, was implemented in a $0.18-{\mu}m$ CMOS technology. The channel selection filter with the proposed RC calibrator draws 1.8 mA from a 1.8 V supply voltage and the measured 3 dB cut-off frequencies of the channel selection LPF is controlled accurately by the RC calibrator.

• Journal of the Korea Society of Computer and Information
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• v.24 no.5
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• pp.67-72
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• 2019

The self-driving cars identify appropriate navigation paths and obstacles to arrive at their destinations without human control. The autonomous cars are capable of sensing driving environments to improve driver and pedestrian safety by sharing with neighbor traffic infrastructure. In this paper, we have focused on pedestrian protection and have designed an improved localization algorithm to track mobile users on roads by interacting with smart traffic lights in vehicle environments. We developed smart traffic lights with the RSSI sensor and built the proposed method by improving the Kalman filter algorithm to localize mobile users accurately. We successfully evaluated the proposed algorithm to improve the mobile user localization with deployed five smart traffic lights.

• Smart Structures and Systems
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• v.12 no.1
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• pp.23-39
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• 2013

In this article, a smart multifunctional optical system-on-a-chip (SOC) sensor platform is presented and its application for fiber Bragg grating (FBG) sensor interrogation in optical sensor networks is investigated. The smart SOC sensor platform consists of a superluminescent diode as a broadband source, a tunable microelectromechanical system (MEMS) based Fabry-P$\acute{e}$rot filter, photodetectors, and an integrated microcontroller for data acquisition, processing, and communication. Integrated with a wireless sensor network (WSN) module in a compact package, a smart optical sensor node is developed. The smart multifunctional sensor platform has the capability of interrogating different types of optical fiber sensors, including Fabry-P$\acute{e}$rot sensors and Bragg grating sensors. As a case study, the smart optical sensor platform is demonstrated to interrogate multiplexed FBG strain sensors. A time domain signal processing method is used to obtain the Bragg wavelength shift of two FBG strain sensors through sweeping the MEMS tunable Fabry-P$\acute{e}$rot filter. A tuning range of 46 nm and a tuning speed of 10 Hz are achieved. The smart optical sensor platform will open doors to many applications that require high performance optical WSNs.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.5 no.2
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• pp.96-100
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• 2012

Existing, widely used industrial controller programmable logic controller (PLC) using the high cost and maintenance was a difficult problem. In addition, the network configuration was not easy. Thus, the filter press by remote control and management to improve productivity and shorten maintenance time. Variety of smart devices (smart phones, iPad, tablet PC, etc.) Remote control is possible by utilizing the existing controlled by the PLC addresses maintenance and improved performance compared to that of possible filter press control and management system was developed.

• Journal of Korea Multimedia Society
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• v.16 no.8
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• pp.962-971
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• 2013

In this paper, we propose a method to infer the user's behavior and situation through collected data from multi-sensor equipped with a smart clothing and it was implemented as a smart-phone App. This smart-clothes is able to monitor wearer users' health condition and activity levels through the gyro, temp and acceleration sensor. Sensed vital signs are transmitted to a bluetooth-enabled smart-phone in the smart-clothes. Thus, users are able to have real time information about their user condition, including activities level on the smart-application. User context reasoning and behavior determine is very difficult using multi-sensor depending on the measured value of the sensor varies from environmental noise. So, the reasoning and the digital filter algorithms to determine user behavior reducing noise and are required. In this paper, we used Multi-black Filter and SVM processing behavior for 3-axis value as a representative value of one.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2014.05a
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• pp.896-897
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• 2014

Multi-lane detection is useful for the smart navigation system. In this paper, a novel multi-lane detection method is presented. The proposed three point Laplacian filter (TPLF) can complement the weak points of the previous box filter and step filter. The experimental results validate the feasibility of the proposed multi-lane detection method.