• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.10
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• pp.4908-4928
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• 2017

Recent research into wireless sensor network (WSN)-related technology that senses various data has recognized the need for spatio-temporal queries for searching necessary data from wireless sensor nodes. Answers to the queries are transmitted from sensor nodes, and for the efficient transmission of the sensed data to the application server, research on index processing methods that increase accuracy while reducing the energy consumption in the node and minimizing query delays has been conducted extensively. Previous research has emphasized the importance of accuracy and energy efficiency of the sensor node's routing process. In this study, we propose an itinerary-based R-tree (IR-tree) to solve the existing problems of spatial query processing methods such as efficient processing and expansion of the query to the spatio-temporal domain.

• Journal of the Korea Society of Computer and Information
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• v.17 no.1
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• pp.193-202
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• 2012

RFID tag awareness information and sensor data continuously change, and are categorized with the position. They are able to similar data in the side, called massive data to change in time. If two data are managed together, a convergence process of object awareness along change of environment is possible. If RFID middleware and EPCIS repository realized the integrated system, it is usable with the functions of middleware and repository at the same time. The real-time awareness information retrieval is possible without process, getting information from another middleware. In this paper, it is able to continuously read information from RFID reader and sensor equipment and store to database in order to make general object awareness and an object retrieval dependent on an environmental information change possible by real time. ALE-compliant middleware and EPCIS repository proposing for standards at EPCglobal is designed and implemented to be able to deal with RFID and sensor data to bases on the collected data.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.6 no.6
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• pp.1546-1564
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• 2012

Pattern-based query processing has not attracted much attention in wireless sensor network though its counterpart has been studied extensively in data stream. The methods used for data stream usually consume large memory and much energy. This conflicts with the fact that wireless sensor networks are heavily constrained by their hardware resources. In this paper, we use piece wise representation to represent sensor nodes' collected data to save sensor nodes' memory and to reduce the energy consumption for query. After getting data stream's and patterns' approximated line segments, we record each line's slope. We do similar matching on slope sequences. We compute the dynamic time warping distance between slope sequences. If the distance is less than user defined threshold, we say that the subsequence is similar to the pattern. We do experiments on STM32W108 processor to evaluate our strategy's performance compared with naive method. The results show that our strategy's matching precision is less than that of naive method, but our method's energy consumption is much better than that of naive approach. The strategy proposed in this paper can be used in wireless sensor network to process pattern-based queries.

• The Journal of Society for e-Business Studies
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• v.15 no.4
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• pp.1-19
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• 2010

Recently, it is necessary to process real time sensor data, which is generated from ubiquitous environments. Data, which are written by XML, are small, but, large volumes of data. Therefore, weneed to use an efficient method for processing a large amount of it. An XQuery has two types for sensor data: one is to get sensor identification and value from sensor data; the other is restructuring for user's convenience. Existing XQuery engines don't have efficient method for batch processing of sensor data. This paper proposed the twig query processing over reverse path summary, and we developed and applied restructuring batch processing method for real time processing of a large amount of sensor data. Finally, we do performance evaluation using XMark and RFID EPC data, and comparison analysis with MonetDB/XQuery and Berkeley DB XML.

• 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 Powder Materials
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• v.27 no.2
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• pp.111-118
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• 2020

The convergence of artificial intelligence with smart factories or smart mechanical systems has been actively studied to maximize the efficiency and safety. Despite the high improvement of artificial neural networks, their application in the manufacturing industry has been difficult due to limitations in obtaining meaningful data from factories or mechanical systems. Accordingly, there have been active studies on manufacturing components with sensor integration allowing them to generate important data from themselves. Additive manufacturing enables the fabrication of a net shaped product with various materials including plastic, metal, or ceramic parts. With the principle of layer-by-layer adhesion of material, there has been active research to utilize this multi-step manufacturing process, such as changing the material at a certain step of adhesion or adding sensor components in the middle of the additive manufacturing process. Particularly for smart parts manufacturing, researchers have attempted to embed sensors or integrated circuit boards within a three-dimensional component during the additive manufacturing process. While most of the sensor embedding additive manufacturing was based on polymer material, there have also been studies on sensor integration within metal or ceramic materials. This study reviews the additive manufacturing technology for sensor integration into plastic, ceramic, and metal materials.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.11 no.1
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• pp.26-32
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• 2012

Polishing is one of the important methods in manufacturing of Si wafers and in thinning of completed device wafers. This study will report the characteristic of wafer according to processing time, machining speed and pressure which have major influence on the abrasion of Si wafer polishing. It is possible to evaluation of wafer abrasion by load cell and infrared temperature sensor. The characteristic of wafer surface according to processing condition is selected to use a result data that measure a pressure, machining speed, and the processing time. This result is appeared by the characteristic of wafer surface in machining condition. Through that, the study cans evaluation a wafer characteristic in variable machining condition. It is important to obtain optimal condition. Thus the optimum condition selection of ultra precision Si wafer polishing using load cell and infrared temperature sensor. To evaluate each machining factor, use a data through each sensor. That evaluation of abrasion according to variety condition is selected to use a result data that measure a pressure, machining speed, and the processing time. And optimum condition is selected by this result.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2956-2958
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• 2000

This paper describes the design of a real time traffic data acquisition system using loop detector and piezzo sensor. Loop detector is the cheapest method to measure the speed and piezzo is used to detect the vehicle axle information. A ISA slot based I/O board is designed for data acquisition and PC process the raw traffic data and transfer the data to the host system. Simulation kit is designed with toy car kits. simulated loop detector and piezzo sensor. The data acquisition system collects up to 10 lane highway traffic data such as vehicle count. speed. length axle count. distance between the axles. The data is processed to generate traffic count, vehicle classification, which are to be used for ITS. The system architecture and simulation data is included and the system will be tested for field operation.

• Atmosphere
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• v.24 no.3
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• pp.433-444
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• 2014

Although the Radar-AWS Rainrate (RAR) calculation system operated by Korea Meteorological Administration estimated precipitation using 2-dimensional composite components of single polarization radars, this system has several limitations in estimating the precipitation accurately. To to overcome limitations of the RAR system, the Korea Meteorological Administration developed and operated the RMQ (Radar-based Multi-sensor Quantitative Precipitation Estimation) system, the improved version of NMQ (National Mosaic and Multi-sensor Quantitative Precipitation Estimation) system of NSSL (National Severe Storms Laboratory) for the Korean Peninsula. This study introduced the RMQ system domestically for the first time and verified the precipitation estimation performance of the RMQ system. The RMQ system consists of 4 main parts as the process of handling the single radar data, merging 3D reflectivity, QPE, and displaying result images. The first process (handling of the single radar data) has the pre-process of a radar data (transformation of data format and quality control), the production of a vertical profile of reflectivity and the correction of bright-band, and the conduction of hydrid scan reflectivity. The next process (merger of 3D reflectivity) produces the 3D composite reflectivity field after correcting the quality controlled single radar reflectivity. The QPE process classifies the precipitation types using multi-sensor information and estimates quantitative precipitation using several Z-R relationships which are proper for precipitation types. This process also corrects the precipitation using the AWS position with local gauge correction technique. The last process displays the final results transformed into images in the web-site. This study also estimated the accuracy of the RMQ system with five events in 2012 summer season and compared the results of the RAR (Radar-AWS Rainrate) and RMQ systems. The RMQ system ($2.36mm\;hr^{-1}$ in RMSE on average) is superior to the RAR system ($8.33mm\;hr^{-1}$ in RMSE) and improved by 73.25% in RMSE and 25.56% in correlation coefficient on average. The precipitation composite field images produced by the RMQ system are almost identical to the AWS (Automatic Weather Statioin) images. Therefore, the RMQ system has contributed to improve the accuracy of precipitation estimation using weather radars and operation of the RMQ system in the work field in future enables to cope with the extreme weather conditions actively.

• The Journal of Korean Association of Computer Education
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• v.15 no.6
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• pp.75-82
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• 2012

The sensor registry system has been proposed to interpret and process semantics of sensor data independently of heterogeneous sensor networks. However, the existing sensor registry system provides the static processing method. In other words, the existing system reduces the overall performance because it executes unnecessary operations and does not consider data scope to be used. To resolve the problem of the existing sensor registry system, this paper proposes a performance enhancement model based on sensor metadata reusability and scoping. The proposed model in this paper provides a function that can decide a proper scope of sensor metadata from the sensor registry system. The proposed model improves the overall performance by providing reusability of sensor metadata. This paper also shows the advantages of the proposed model through the comparative performance evaluation.