• The Journal of the Acoustical Society of Korea
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• v.39 no.3
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• pp.191-199
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• 2020

Currently, studies on the estimation algorithm based on compressive sensing are actively underway, but to the best of our knowledge, no study on the performance of the Sparse Spectrum Fitting (SpSF) algorithm in nonuniform sensor arrays has been made. This paper deals with the derivation of the compressive sensing based covariance fitting algorithm extended to the frequency domain. In addition, it shows the performance of directon-of-arrival estimation of the frequency domain SpSF algorithm in non-uniform linear sensor array system and the sensor array failure situation.

• Journal of the Institute of Electronics Engineers of Korea SC
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• v.43 no.2 s.308
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• pp.33-39
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• 2006

This paper designed the electronic circuit part of Potable Infrared Night Vision Scope for a small size, light weight, and low power. Designed electronic circuit part is composed of an Auto Voltage Selecting Module, and a Power Supply Module. An Auto Voltage Selecting Modulo is composed of a switch, a battery, a step up voltage part, and a selecting voltage part. A Power Supply Module is composed of a high luminous sensing part, a battery voltage sensing part, a infrared illumination part, a connection sensing part, and a power control part. And this module controls the power of Image Intensifier Tube. To verify the performance of the designed electronic circuit part, we experimented the consumption power and continuous using time. Experimental results show that the designed electronic circuit part improves considerably on the performance of the AN/PVS-14. performance.

• Journal of Construction Engineering and Project Management
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• v.5 no.4
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• pp.16-22
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. Several case studies were conducted to experimentally evaluate their impact on BIM-based energy analysis to calculate energy load. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• International conference on construction engineering and project management
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• 2015.10a
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• pp.532-536
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• 2015

This paper presents an automated computer vision-based system to update BIM data by leveraging multi-modal visual data collected from existing buildings under inspection. Currently, visual inspections are conducted for building envelopes or mechanical systems, and auditors analyze energy-related contextual information to examine if their performance is maintained as expected by the design. By translating 3D surface thermal profiles into energy performance metrics such as actual R-values at point-level and by mapping such properties to the associated BIM elements using XML Document Object Model (DOM), the proposed method shortens the energy performance modeling gap between the architectural information in the as-designed BIM and the as-is building condition, which improve the reliability of building energy analysis. The experimental results on existing buildings show that (1) the point-level thermography-based thermal resistance measurement can be automatically matched with the associated BIM elements; and (2) their corresponding thermal properties are automatically updated in gbXML schema. This paper provides practitioners with insight to uncover the fundamentals of how multi-modal visual data can be used to improve the accuracy of building energy modeling for retrofit analysis. Open research challenges and lessons learned from real-world case studies are discussed in detail.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.34 no.2A
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• pp.132-138
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• 2009

Cognitive radio is considered as a promising solution to scarce spectrum problem. The primary object of cognitive radio is to increase spectral efficiency, while causing limited interference to primary users who are using the spectrum. Hence, an essential part of cognitive radio systems is spectrum sensing which determines whether a particular spectrum is occupied or not by a primary user at a particular time. However, sensing decision of each individual secondary user alone may not be reliable enough due to shadowing and multipath fading of wireless channels. The so called hidden terminal problem makes the problem even worse, possibly yielding undesired interference to the primary users. Recently, cooperative spectrum sensing is emerging as a remedy to these problems of individual sensing. Cooperative sensing allows a group of secondary users to share local sensing information to extract a global decision with high fidelity. In this paper, we investigate a cooperative spectrum sensing algorithm based on hard decisions of local sensing outcomes. Specifically, we propose an effective scheme for combining local decisions by introducing weighting factors that reflect reliability of the corresponding secondary user. Through computer simulations, the performance of the proposed combining scheme is compared with that of the conventional scheme without weighting factors in various environments.

• Proceedings of the KSRS Conference
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• 2003.11a
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• pp.1149-1151
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• 2003

We performed a validation study of the MODIS active fire detection algorithm using high resolution SPOT image as the reference data set. Fire with visible smoke plumes are detected in the SPOT scenes, while the hotspots in MODIS data are detected using NASA's new version 4 fire detection algorithm. The detection performance is characterized by the commission error rate (false alarms) and the omission error rate (undetected fires). In the Sumatra and Kalimantan study area, the commission rate and the omission rate are 27% and 34% respectively. False alarms are probably due to recently burnt areas with warm surfaces. False negative detection occur where there are long smoke plumes and where fires occur in densely vegetated areas.

• Smart Structures and Systems
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• v.8 no.5
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• pp.471-486
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• 2011

Various types of strain sensors have been developed and widely used in the field for monitoring the mechanical deformation of structures. However, conventional strain sensors are not suited for measuring large strains associated with impact damage and local crack propagation. In addition, strain sensors are resistive-type transducers, which mean that the sensors require an external electrical or power source. In this study, a gold nanoparticle (GNP)-based polymer composite is proposed for large strain sensing. Fabrication of the composites relies on a novel and simple in situ GNP reduction technique that is performed directly within the elastomeric poly(dimethyl siloxane) (PDMS) matrix. First, the reducing and stabilizing capacities of PDMS constituents and mixtures are evaluated via visual observation, ultraviolet-visible (UV-Vis) spectroscopy, and transmission electron microscopy. The large strain sensing capacity of the GNP-PDMS thin film is then validated by correlating changes in thin film optical properties (e.g., maximum UV-Vis light absorption) with applied tensile strains. Also, the composite's strain sensing performance (e.g., sensitivity and sensing range) is also characterized with respect to gold chloride concentrations within the PDMS mixture.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.39-48
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• 2009

The Spectrum Sensing technology is the core technology of the Cognitive Radio (CR) system that is one of the future wireless communication technologies. This is the technology that temporarily allocates the frequency bandwidth by scanning surrounding wireless environments to keep licensed terminals and search the unused frequency bandwidth. In this paper, we implement the efficient Spectrum Sensing methods based on CR technology in an embedded board. The DVB-H signal with the 6MHz bandwidth is used as the RF input signal. And we confirm the Spectrum Sensing result using Modified Periodogram Method, Welch's Method, SCF Method. And also, We examine the execution speed of each of detailed functions and the performance of Spectrum Sensing methods on TI320C6416 DSP board inserted in an embedded board.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.5
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• pp.2468-2483
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• 2017

The construction of completely random sensing matrices of Compressive Sensing requires a large number of random numbers while that of deterministic sensing operators often needs complex mathematical operations. Thus both of them have difficulty in acquiring large signals efficiently. This paper focuses on the enhancement of the practicability of the structurally random matrices and proposes a semi-deterministic sensing matrix called Partial Kronecker product of Identity and Hadamard (PKIH) matrix. The proposed matrix can be viewed as a sub matrix of a well-structured, sparse, and orthogonal matrix. Only the row index is selected at random and the positions of the entries of each row are determined by a deterministic sequence. Therefore, the PKIH significantly decreases the requirement of random numbers, which has a complex generating algorithm, in matrix construction and further reduces the complexity of sampling. Besides, in order to process large signals, the corresponding fast sampling algorithm is developed, which can be easily parallelized and realized in hardware. Simulation results illustrate that the proposed sensing matrix maintains almost the same performance but with at least 50% less random numbers comparing with the popular sampling matrices. Meanwhile, it saved roughly 15%-35% processing time in comparison to that of the SRM matrices.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.12 no.1
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• pp.37-43
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• 2012

In this paper, we analysis wideband spectrum sensing with distance based weight combining for Cognitive Radio (CR) systems. CR systems is implemented the spectrum of the Primary User(PU) by using a energy detection method. Threshold is determined in accordance with the constant false alarm rate (CFAR) algorithm for energy detection. The signal of PU is BPSK signal and the wireless channel between a PU and CR systems is modeled as Gaussian channel. From the simulation results, the wideband sensing with distance based and Distance based weight Combing (DWC) methods shows higher spectrum sensing performance than single CR user spectrum sensing.