• Journal of Positioning, Navigation, and Timing
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• v.8 no.4
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• pp.193-200
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• 2019

The auto-encoder network which is a good candidate to handle the modeling of the signal strength attenuation is designed for denoising and compensating the distortion of the received data. It provides a non-linear mapping function by iteratively learning the encoder and the decoder. The encoder is the non-linear mapping function, and the decoder demands accurate data reconstruction from the representation generated by the encoder. In addition, the adaptive network width which supports the automatic generation of new hidden nodes and pruning of inconsequential nodes is also implemented in the proposed algorithm for increasing the efficiency of the algorithm. Simulation results show that the proposed method can improve the neural network training surface to achieve the highest possible accuracy of the signal modeling compared with the conventional modeling method.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.243-244
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• 2008

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.2
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• pp.404-420
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• 2021

In this paper, an automatic system of locating the indoor area with weak or no mobile signal was proposed and demonstrated experimentally by using the Internet of Things (IoT) technology. Nowadays, the technicians of mobile services providers need to go along with numerous heavy equipment to measure and record the mobile signal strength at outside environment. Recently, there are systems proposed to do such measurement at outdoor area by using the IoT technology automatically. However, these works could not be applied in the indoor area since there are difficulties to do the indoor mapping and positioning. In this work, the Bluetooth Low Energy (BLE) was used to tackle these two difficulties. After a proper placement of BLE in the testing site, while the technician walk around with a handheld analyzer, the data can be obtained accordingly for further analysis in the proposed system which includes the construction of floor plan, detection of mobile signal strength and suggestion of indoor base stations. The gift wrapping and centroid algorithms were used during the analysis. The experimental results showed that the proposed system successfully demonstrated the indoor mapping, positioning of weak mobile signal area and suggestion of indoor base stations for the normal rectangular rooms with an area of 100 m² on single floor.

• Journal of Internet Computing and Services
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• v.13 no.2
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• pp.13-20
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• 2012

SLM (Selected Mapping) is an efficient PAPR (Peak-to-Average Power Ratio) reduction scheme without transmitted signal distortion in OFDM (Orthogonal Frequency Division Multiplexing) systems. However, enormous IFFTs (Inverse Fast Fourier Transforms) are needed to generate sufficient candidate OFDM signals, which cause the SLM to become quite complex. In this paper, we propose a new SLM scheme that replaces the IFFT operations with a conversion of the first candidate OFDM signal. The proposed scheme significantly reduces computational complexity, while it shows almost the same PAPR performance as the conventional SLM scheme.

• Nuclear Engineering and Technology
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• v.54 no.12
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• pp.4684-4692
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• 2022

Radionuclide identification is an important part of the nuclear material identification system. The development of artificial intelligence and machine learning has made nuclide identification rapid and automatic. However, many methods directly use existing deep learning models to analyze the gamma-ray spectrum, which lacks interpretability for researchers. This study proposes an explainable radionuclide identification algorithm based on the convolutional neural network and class activation mapping. This method shows the area of interest of the neural network on the gamma-ray spectrum by generating a class activation map. We analyzed the class activation map of the gamma-ray spectrum of different types, different gross counts, and different signal-to-noise ratios. The results show that the convolutional neural network attempted to learn the relationship between the input gamma-ray spectrum and the nuclide type, and could identify the nuclide based on the photoelectric peak and Compton edge. Furthermore, the results explain why the neural network could identify gamma-ray spectra with low counts and low signal-to-noise ratios. Thus, the findings improve researchers' confidence in the ability of neural networks to identify nuclides and promote the application of artificial intelligence methods in the field of nuclide identification.

• Journal of the Institute of Convergence Signal Processing
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• v.25 no.1
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• pp.21-26
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• 2024

In this study, a USV(Unmanned Surface Vehicle) equipped with high-accuracy DGPS(Differential GPS) and single-beam echo sounder was developed. The depth of the reservoir was measured using a USV and a GCS(Ground Control System). A 3D mapping drawing was created using the commercial software ReefMaster. By using USV, the accuracy and efficiency of work was improved. Depth surveying, which was difficult with human resources, is performed using automatic navigation and the volume of the reservoir was calculated. Using 3D mapping drawing, we were able to conduct a detailed investigation of reservoir dredging and ecological environment. It is also expected to be effective in identifying environmental issues.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1152-1154
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• 2003

The needs of 3-D data have been increasing for various applications like visualization, 3-D modeling, planning and management as well as entertainment. Mobile mapping has become a quick and practical means for acquiring necessary 3-D data for above-mentioned applications. A mobile mapping system mainly consists of two main components, viz. data acquisition devices and positioning devices. The data acquisition devices consist of CCD cameras or/and laser scanners. The positioning devices consist of GPS, INS, Odometer (shaft encoder) and some other referencing devices. The overall accuracy of mobile mapping system depends on the accuracy of positioning devices and their integrated output. Though, GPS is the main input device for the position information, the signal is not available for the computation of position all the times in urban area. The GPS satellites are normally obstructed by high-rise buildings. Thus it is very important to understand the accuracy of such a system in different environments and means to solve such problems. We have developed a mobile mapping system called VLMS (Vehicle-borne Laser Mapping System), which consists of CCD Cameras, Laser scanners, GPS, INS and Odometer. In this paper, we will present and discuss the accuracy of this system with data acquired in different environments (open area, urban area, tunnel, express way etc) by analyzing the data with respect to other existing digital data.

• Journal of Biomedical Engineering Research
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• v.27 no.4
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• pp.154-163
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• 2006

A 64-channel magnetocardiogram (MCG) system using low-noise superconducting quantum interference device (SQUID) planar gradiometers was developed for the measurements of cardiac magnetic fields generated by the heart electric activity. Owing to high flux-to-voltage transfers of double relaxation oscillation SQUID (DROS) sensors, the flux-locked loop electronics for SQUID operation could be made simpler than that of conventional DC SQUIDs, and the SQUID control was done automatically through a fiber-optic cable. The pickup coils are first-order planar gradiometers with a baseline of 4 em. The insert has 64 planar gradiometers as the sensing channels and were arranged to measure MCG field components tangential to the chest surface. When the 64-channel insert was in operation everyday, the average boil-off rate of the dewar was 3.6 Lid. The noise spectrum of the SQUID planar gradiometer system was about 5 fT$_{rms}$/$\checkmark$Hz at 100 Hz, operated inside a moderately shielded room. The MCG measurements were done at a sampling rate of 500 Hz or 1 kHz, and realtime display of MCG traces and heart rate were displayed. After the acquisition, magnetic field mapping and current mapping could be done. From the magnetic and current information, parameters for the diagnosis of myocardial ischemia were evaluated to be compared with other diagnostic methods.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.828-831
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• 1996

Radiation monitoring system is needed at nuclear power plant and nuclear facility. Manual survey techniques are commonly used, but they are time consuming and somewhat inaccurate. Automatic radiation surveys are very important because it provides significant savings in men-rem and wages. Unmanned, remote automatic radiation measurement system should be small and light-weighted in order to mount on robotic system. The system we have developed consists of detection parts, signal processing part, interface, and software part. Position information is provided by using of a collimator. The measurement process is achieved by the scanning of detector and image processing techniques are used to display radiation levels. We designed collimators, detectors, signal processing circuit, and constructed prototype system. The goal of this system is the mapping of camera image and radiation level distribution.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2003.06a
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• pp.106-109
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• 2003

This paper presents a hue preserving gamut mapping algorithm for color monitor and printer. The gamuts of monitor and printer are set by the profile of color reproduction media, specified by ICC(International Color Consortium) and provided by vendors, then those gamuts are represented on the CIE xy color space. In case that the color of monitor are located on out-of-gamut of printer, these are clipped on the point of gamut boundary of printer towards a reference white point. On the other hand, colors are in-gamut of printer are unchanged. An image generated by the algorithm keeps a ratio of each pixel of original image. Advantages of the algorithm are easy to implement and fast processing time than other algorithms which involve hue preserving especially in CIELAB color space.