• Journal of Sensor Science and Technology
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• v.24 no.1
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• pp.29-34
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• 2015

This study aimed to evaluate the characterization of a metal oxide semiconductor and electrochemical gas sensor array for measuring wastewater odor. The sensitivity of all gas sensors observed in sampling method by stripping was 6.7 to 20.6 times higher than that by no stripping, except sensor D (electrochemical gas sensor). The average reduction ratio of sensor signal as a function of initial dilution rate of wastewater was in the order of food plant > food waste reutilization facility > plating plant. The sensitivity of gas sensors was dependent on both the type of wastewater and the dilution rate. The sensor signals observed by the gas sensor array were correlated with the dilution factor (OU) calculated by the air dilution sensory test with several wastewater ($r^2=0.920{\sim}0.997$), except the sensor signals of sensor D measured in the plating plant wastewater. It seems likely that the gas sensor array plays a role in the evaluation of odor in wastewater and is useful tool for on-site odor monitoring in the wastewater facilities.

• Journal of Sensor Science and Technology
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• v.23 no.2
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• pp.99-104
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• 2014

Sensor arrays based on chemical sensors produce multidimensional patterns of data that may be used discriminate between different chemicals. For the human observer, visualization of multidimensional data is difficult, since the eye and brain process visual information in two or three dimensions. To devise a simple means of data inspection from the response of sensor arrays, PCA (Principal Component Analysis) or Sammon's nonlinear mapping technique can be applied. The PCA, which is a well-known statistical method and widely used in data analysis, has disadvantages including data distortion and the axes for plotting the dimensionally reduced data have no physical meaning in terms of how different one cluster is from another. In this paper, we have investigated two techniques and proposed a combination technique of PCA and nonlinear Sammom mapping for visualization of multidimensional patterns to two dimensions using data sets from odor sensing system. We conclude the combination technique has shown more advantages comparing with the PCA and Sammon nonlinear technique individually.

• Journal of IKEEE
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• v.24 no.1
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• pp.275-283
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• 2020

A leader-follower robot system using low cost small mobile robots has been developed. Sine the developed mobile robot is made of widely used low cost parts, it can be built easily and fastly. Characteristics of the developed sensor array composed of seven low-cost infrared(IR) distance sensors has been investigated, and a positioning algorithm of the reader robot is proposed. Through a series of experiments, it has been verified that the proposed algorithm can detect the position of the reader robot well.

• Journal of Sensor Science and Technology
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• v.17 no.6
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• pp.406-413
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• 2008

We have been implemented simple statistical pattern recognition methods for harmful gases classification using gas sensors array fabricated by MEMS (Micro Electro Mechanical System) technology. The performance of pattern recognition method as a gas classifier is highly dependent on the choice of pre-processing techniques for sensor and sensors array signals and optimal classification algorithms among the various classification techniques. We carried out pre-processing for each sensor's signal as well as sensors array signals to extract features for each gas. We adapted simple statistical pattern recognition algorithms, which were PCA (Principal Component Analysis) for visualization of patterns clustering and MLR (Multi-Linear Regression) for real-time system implementation, to classify harmful gases. Experimental results of adapted pattern recognition methods with pre-processing techniques have been shown good clustering performance and expected easy implementation for real-time sensing system.

• Journal of Sensor Science and Technology
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• v.22 no.4
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• pp.286-291
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• 2013

This paper presents to analyze patterns from single and complex malodors using gas sensor array based on metal oxide semiconductors. The aim of research is to identify and discriminate single malodors such as $NH_3$, $CH_3SH$ and $H_2S$ and their mixtures according to concentration levels. Measurement system for analyzing patterns from malodors is constructed by an array of metal oxide semiconductor sensors which are available commercially together with associate electronics. The patterns from sensory system are analyzed by Principal Component Analysis (PCA) which is simple statistical pattern recognition technique. Throughout the experimental trails, we confirmed the experimental procedure for measurement system such as sensors calibration time and gas flow rate, and discriminated malodors using pattern analysis technique.

• Journal of Sensor Science and Technology
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• v.32 no.2
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• pp.95-99
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• 2023

Forest healing is an activity that enhances immunity and human health using various elements of nature, such as fragrance and scenery. Particularly, phytoncide composed of terpene, a natural volatile substance emitted by forest plants, activates the immune function and is an important raw material in health-related products, such as antibacterial and insect repellents. Moreover, phytoncide is used as a measure to evaluate the impact of the forest atmosphere on the human body. This study aims to implement a highly sensitive gas sensor system that can measure phytoncide in real-time, which is an essential element for realizing a forest healing environment. A gas generation apparatus was implemented by using an adsorption tube in consideration of filed applicability in a laboratory atmosphere to enable the measurement of α-pinene and limonene, which are among the main components of phytoncide. Throughout the experimental trials, the sensitivity of gas sensor arrays to α-pinene and limonene was confirmed. In addition, the classification results demonstrated the AVOCs and NVOCs can be well discriminated using PCA. The primary results confirmed the possibility of developing a high-sensitivity gas sensor system for phytoncide sensing in real time.

• Journal of the Institute of Electronics and Information Engineers
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• v.54 no.4
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• pp.68-74
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• 2017

This paper presents a joint demosaicking and arbitrary-ratio down sampling algorithm for color filter array (CFA) images. Color demosaiking is a necessary part of image signal processing pipeline for many types of digital image recording system using single sensor. Also, such as smart phone, obtained high resolution image from image sensor has to be down-sampled to be displayed on the screen. The conventional solution is "Demosaicking first and down sampling later". However, this scheme requires a significant amount of memory and computational cost. Also, artifacts can be introduced or details get damaged during demosaicking and down sampling process. In this paper, we propose a method in which demosaicking and down sampling are working simultaneously. We use inverse mapping of Bayer CFA and then joint demosaicking and down sampling with arbitrary-ratio scheme based on signal decomposition of high and low frequency component in input data. Experimental results show that our proposed algorithm has better image quality performance and much less computational cost than those of conventional solution.

• Journal of Sensor Science and Technology
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• v.6 no.6
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• pp.476-482
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• 1997

A portable electronic nose system has been fabricated and characterized using an oxide semiconductor gas sensor array and pattern recognition techniques such as principal component analysis and back-propagation artificial neural network. The sensor array consists of six thick-film gas sensors whose sensing layers are Pd-doped $WO_{3}$, Pt-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$, $TiO_{2}-Sb_{2}O_{5}-Pd$-doped $SnO_{2}$ + Pd coated layer, $Al_{2}O_{3}$-doped ZnO and $PdCl_{2}$-doped $SnO_{2}$. The portable electronic nose system consists of an 16bit Intel 80c196kc as CPU, an EPROM for storing system main program, an EEPROM for containing optimized connection weights of artificial neural network, an LCD for displaying gas concentrations. As an application the system has been used to identify 26 carbon monoxide/hydrocarbon (CO/HC) car exhausting gases in the concentration range of CO 0%/HC 0 ppm to CO 7.6%/HC 400 ppm and the identification has been successfully demonstrated.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.7
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• pp.1235-1242
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• 2008

In this paper, x-ray image sensor of photon counting type having a $32{\times}32$ pixel array is designed with $0.18{\mu}m$ triple-well CMOS process. Each pixel of the designed image sensor has an area of loot $100{\times}100\;{\mu}m2$ and is composed of about 400 transistors. It has an open pad of an area of $50{\times}50{\mu}m2$ of CSA(charge Sensitive Amplifier) with x-ray detector through a bump bonding. To reduce layout size, self-biased folded cascode CMOS OP amp is used instead of folded cascode OP amp with voltage bias circuit at each single-pixel CSA, and 15-bit LFSR(Linear Feedback Shift Register) counter clock generator is proposed to remove short pulse which occurs from the clock before and after it enters the counting mode. And it is designed that sensor data can be read out of the sensor column by column using a column address decoder to reduce the maximum current of the CMOS x-ray image sensor in the readout mode.

• Journal of the Institute of Electronics Engineers of Korea SD
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• v.45 no.12
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• pp.8-14
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• 2008

A fully CMOS-integrated carbon nanotube (CNT) sensor array is proposed. After the sensor chip is fabricated in commercial CMOS process, the CNTs network is formed on the top of the fabricated sensor chip through the room-temperature post-CMOS processes. When the resistance of the CNT is changed by the chemical reaction, the read-out circuit in the chip measures the charging time of the $R_{CNT}$-Capacitor. finally the information of measured frequency is converted to a digital code. The CMOS sensor chip was fabricated by standard 0.18um technology and the size of the $8{\times}8$ sensor array is $2mm{\times}2mn$. We have carried out an experiment detecting the biochemical material, glutamate, using this sensor chip. From the experiment the CMOS sensor chip shows the feasibility of sensor for the simultaneous detection of the various target materials.