• Title/Summary/Keyword: Sensing rate

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A Study on the Possibility of Three-dimensional Wearable Respiration Rate Sensor based on Surface Area Changes (표면적 변화에 기반한 입체적 웨어러블 호흡수 센서의 가능성 탐색)

  • Lee, Seungpyo;Ban, Hyunsung;Lee, Joohyeon
    • Science of Emotion and Sensibility
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    • v.21 no.1
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    • pp.35-44
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    • 2018
  • This study suggests the sensing method of the Three-dimensional respiration rate sensor based on surface area changes, and exploring the design direction of the three-dimensional breathing sensor and the design orientation of the garment. To achieve this, two types of three-dimensional respiration rate sensor were produced, and the study of the dummy and the subjects studied. The study I investigated the possibility of measurement of the three-dimensional respiration sensor by the study variables of the sensor type and speed of respiration. The study II proposes a suitable type of sensor for each of the three measuring positions in addition to the study variables in the study I. To evaluate accuracy, reproducibility, and reliability of the three-dimensional respiration rate sensor, the BIOPAC was used to measure the respiration rate simultaneously with the three-dimensional respiration rate sensor. Through all these results of the experiment, it explored the possibility of measurement of the three-dimensional respiration sensor for the dummy. It also proposed a suitable type of sensor by measuring the respiration rate for the human body.

Study on hybrid sensing matrix for compressive sensing of images (영상 압축 센싱을 위한 하이브리드 센싱 행렬 연구)

  • Phan, Minh Van;Dinh, Khanh Quoc;Jeon, Byeungwoo
    • Proceedings of the Korean Society of Broadcast Engineers Conference
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    • 2014.06a
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    • pp.230-231
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    • 2014
  • Compressive sensing is a new sampling technique, which allows to sample a signal under the Nyquist-Shannon sampling rate. For block-based compressive sensing, a hybrid sensing matrix which contains low-frequency patterns in addition to the random Gaussian numbers is good for exploiting typical property of natural images. By noting that MH-BCS-SPL is well known for its good recovery performance, this paper investigates effect of the hybrid sensing matrix on MH-BCS-SPL in the sense of how large portion of low-frequency patterns can provide performance improvement.

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Analysis on Urban Sprawl and Landcover Change Using TM, ETM+ and GIS

  • Xiao, Jieying;Ryutaro, Tateishi;Shen, Yanjun;Ge, Jingfeng;Liang, Yanqing;Chang, Chunping
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.978-980
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    • 2003
  • This study explores the temporal and spatial features near 67years (1934 ?2001) and landcover change in last 14 years (1987-2001) in Shijiazhuang, China, based on 67-year time series data edited from historical maps, TM and ETM+ imageries by integrating GIS and remote sensing method. An index named Annual Growth Rate (AGR) is used to analyze the spatial features of urban sprawl, and Maximum Likelihood classification method is utilized to detect the land cover types change. At last, the relationship between urbanization and factors is analyzed.

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An Automatic Signature Verification Algorithm for Smart Devices

  • Kim, Seong-Hoon;Fan, Yunhe;Heo, Gyeongyong
    • Journal of the Korea Society of Computer and Information
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    • v.20 no.10
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    • pp.15-21
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    • 2015
  • In this paper, we propose a stable automatic signature verification algorithm applicable to various smart devices. The proposed algorithm uses real and forgery data all together, which can improve the verification rate dramatically. As a tool for signature acquisition in a smart device, two applications, one using touch with a finger and the other using a pressure-sensing-stylus pen, are developed. The verification core is based on SVM and some modifications are made to include the characteristics of signatures. As shown in experimental results, the minimum error rate was 1.84% in the SVM based method, which can easily defeat 4.38% error rate with the previous parametric approach. Even more, 2.43% error rate was achieved with the features excluding pressure-related features, better than the previous approach including pressure-related features and only about 0.6% more error than the best result, which means that the proposed algorithm can be applied to a smart device with or without pressure-sensing-stylus pens and used for security purposes.

Frequency Division Concurrent Sensing Method for High-Speed Detection of Large Touch Screens (대형 터치스크린의 고속감지를 위한 주파수분할 동시센싱 기법)

  • Jang, Un-Yong;Kim, HyungWon
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.19 no.4
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    • pp.895-902
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    • 2015
  • This paper presents a high-speed sensing and noise cancellation technique for large touch screens, which is called FDCS (Frequency Division Concurrent Sensing). Most conventional touch screen detection methods apply excitation pulses sequentially and analyze the sensing signals sequentially, and so are often unacceptably slow for large touch screens. The proposed technique applies sinusoidal signals of orthogonal frequencies simultaneously to all drive lines, and analyzes the signals from each sense line in frequency domain. Its parallel driving allows high speed detection even for a very large touch screens. It enhances the sensing SNR (Signal to Noise Ratio) by introducing a frequency domain noise filtering scheme. We also propose a pre-distortion equalizer, which compensates the drive signals using the inverse transfer function of touch screen panel to further enhance the sensing SNR. Experimental results with a 23" large touch screen show that the proposed technique enhances the frame scan rate by 273% and an SNR by 43dB compared with a conventional scheme.

Compressed Sensing and the Applications of Wireless Communications (압축 감지 기술과 무선통신 응용)

  • Hwang, Dae-Sung;Kim, Dae-Sung;Choi, Jin-Ho;Ha, Jeong-Seok
    • Journal of the Institute of Electronics Engineers of Korea SP
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    • v.46 no.5
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    • pp.32-39
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    • 2009
  • Compressed Sensing is a method to sample analog signals at a rate under the Nyquist rate. With this scheme, it is possible to represent signals with a relatively smaller number of measurements than that of the conventional sampling method, and the original signals are reconstructed with high probability from the acquired measurements using the linear programming. Compressed sensing allows measurement time and/or the amount of ADC (analog-to-digital converter) resources for the signal acquisitions to be reduced. In this paper, we presents the backgrounds of the compressed sensing, a way to acquire measurements from an analog signal with a random basis, and the signal recovery method. Also we introduce applications of compressed sensing in wireless communications.

Cloud Physics Observation System (CPOS) and Validation of Its Products (구름물리 관측시스템 및 산출물 검정)

  • Chang, Ki-Ho;Oh, Sung-Nam;Jeong, Ki-Deok;Yang, Ha-Young;Lee, Myoung-Joo;Jeong, Jin-Yim;Cho, Yohan;Kim, Hyo-Kyung;Park, Gyun-Myeong;Yum, Seong-Soo;Cha, Joo-Wan
    • Atmosphere
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    • v.17 no.1
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    • pp.101-108
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    • 2007
  • To observe and analyze the cloud and fog characteristics, the METeorological Research Institute (METRI) has established the Cloud Physics Observation System (CPOS) by implementing the cloud observation instruments: Forward Scattering Spectrometer Probe (FSSP), PARticle SIze and VELocity (PARSIVEL), Microwave Radiometer (MWR), Micro Rain Radar (MRR), and 3D-AWS at the Daegwallyeong Enhanced Mountain Weather Observation Center. The cloud-related products of CPOS and the validation status for the size distribution of FSSP, the precipitable water of MWR, and the rainfall rate of MRR and PARSIVEL are described.

Enhanced remote-sensing scale for wind damage assessment

  • Luo, Jianjun;Liang, Daan;Kafali, Cagdas;Li, Ruilong;Brown, Tanya M.
    • Wind and Structures
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    • v.19 no.3
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    • pp.321-337
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    • 2014
  • This study has developed an Enhanced Remote-Sensing (ERS) scale to improve the accuracy and efficiency of using remote-sensing images of residential building to predict their damage conditions. The new scale, by incorporating multiple damage states observable on remote-sensing imagery, substantially reduces measurement errors and increases the amount of information retained. A ground damage survey was conducted six days after the Joplin EF 5 tornado in 2011. A total of 1,400 one- and two-family residences (FR12) were selected and their damage states were evaluated based on Degree of Damage (DOD) in the Enhanced Fujita (EF) scale. A subsequent remote-sensing survey was performed to rate damages with the ERS scale using high-resolution aerial imagery. Results from Ordinary Least Square regression indicate that ERS-derived damage states could reliably predict the ground level damage with 94% of variance in DOD explained by ERS. The superior performance is mainly because ERS extracts more information. The regression model developed can be used for future rapid assessment of tornado damages. In addition, this study provides strong empirical evidence for the effectiveness of the ERS scale and remote-sensing technology for assessment of damages from tornadoes and other wind events.

Spectrum Sensing and Data Transmission in a Cognitive Relay Network Considering Spatial False Alarms

  • Tishita, Tasnina A.;Akhter, Sumiya;Islam, Md. Imdadul;Amin, M. Ruhul
    • Journal of Information Processing Systems
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    • v.10 no.3
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    • pp.459-470
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    • 2014
  • In this paper, the average probability of the symbol error rate (SER) and throughput are studied in the presence of joint spectrum sensing and data transmission in a cognitive relay network, which is in the environment of an optimal power allocation strategy. In this investigation, the main component in calculating the secondary throughput is the inclusion of the spatial false alarms, in addition to the conventional false alarms. It has been shown that there exists an optimal secondary power amplification factor at which the probability of SER has a minimum value, whereas the throughput has a maximum value. We performed a Monte-Carlo simulation to validate the analytical results.

압축센싱 기반의 무선통신 시스템

  • Reu, Na-Tan;Sin, Yo-An
    • The Magazine of the IEIE
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    • v.38 no.1
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    • pp.56-67
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    • 2011
  • As a result of quickly growing data, a digital transmission system is required to deal with the challenge of acquiring signals at a very high sampling rate, Fortunately, the CS (Compressed Sensing or Compressive Sensing) theory, a new concept based on theoretical results of signal reconstruction, can be employed to exploit the sparsity of the received signals. Then, they can be adequately reconstructed from a set of their random projections, leading to dramatic reduction in the sampling rate and in the use of ADC (Analog-to-Digital Converter) resources. The goal of this article is provide an overview of the basic CS theory and to survey some important compressed sensing applications in wireless communications.

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