• Title/Summary/Keyword: enhanced error detection

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THE MODIFIED BRIGHTNESS TEMPERATURE DIFFERENCE FOR AEROSOL DETECTION

  • Kim, Jae-Hwan;Ha, Jong-Sung;Lee, Hyun-Jin
    • Proceedings of the KSRS Conference
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    • v.2
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    • pp.794-796
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    • 2006
  • This study investigated the Brightness Temperature Difference threshold as criterion between aerosols and clouds in conjunction with radiative transfer model. Surface temperature is caused by a significant error over 50% in the BTD threshold. In addition, The BTD threshold contains the uncertainties about 20% due to the surface emissivity and 8% due to the satellite zenith angle. Therefore, we have composed the Look-up table for BTD between 11㎛and 12㎛ according to satellite zenith angle, surface temperature, and surface emissivity. The modified BTD show the enhanced signal, especially over bright surface such as desert in China. However, a weak aerosol signal over Ocean remains in the modified BTD.

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A position Detector of Permanent Magnet Step Motors (영구 자석형 스텝모터의 위치 검출)

  • 원종수;정훈
    • The Transactions of the Korean Institute of Electrical Engineers
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    • v.36 no.10
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    • pp.703-712
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    • 1987
  • A position detection method for 2 phase bifilar permanent magnet step motors is proposed. The back emfgenerated on 2 phase windings by rotor permanent magnet is calculated using motor terminal voltage and current by analog circuit, and the rotor position output is obtained from tese back emf signals through some logical manipulation circuit. This position detector functionally acts like a 2 channel optical incremental encoder, and it is also shown by experimental results that it works well over wide range of speed or under resonant condition where the rotor rings around the detent position. Its resolution is twice of the number of steps per revolution. Bu software implemented on micro-processor, the reliability of position output is enhanced, detecting and correcting error dut to external and/ or internal noise.

Active Shape Model with Directional Profile (방향성 프로파일을 적용한 능동형태 모델)

  • Kim, Jeong Yeop
    • Journal of Korea Multimedia Society
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    • v.20 no.11
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    • pp.1720-1728
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    • 2017
  • Active shape model is widely used in the field of image processing especially on arbitrary meaningful shape extraction from single gray level image. Cootes et. al. showed efficient detection of variable shape from image by using covariance and mean shape from learning. There are two stages of learning and testing. Hahn applied enhanced shape alignment method rather than using Cootes's rotation and scale scheme. Hahn did not modified the profile itself. In this paper, the method using directional one dimensional profile is proposed to enhance Cootes's one dimensional profile and the shape alignment algorithm of Hahn is combined. The performance of the proposed method was superior to Cootes's and Hahn's. Average landmark estimation error for each image was 27.72 pixels and 39.46 for Cootes's and 33.73 for Hahn's each.

Mathematical Analysis Power Spectrum of M-ary MSK and Detection with Optimum Maximum Likelihood

  • Niu, Zheng;Jiang, Yuzhong;Jia, Shuyang;Huang, Zhi;Zou, Wenliang;Liu, Gang;Li, Yu
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • v.15 no.8
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    • pp.2900-2922
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    • 2021
  • In this paper, the power spectral density(PSD) for Multilevel Minimum Shift Keyed signal with modulation index h = 1/2 (M-ary MSK) are derived using the mathematical method of the Markov Chain model. At first, according to an essential requirement of the phase continuity characteristics of MSK signals, a complete model of the whole process of signal generation is built. Then, the derivations for autocorrelation functions are carried out precisely. After that, we verified the correctness and accuracy of the theoretical derivation by comparing the derived results with numerical simulations using MATLAB. We also divided the spectrum into four components according to the derivation. By analyzing these figures in the graphic, each component determines the characteristics of the spectrum. It is vital for enhanced spectral characteristics. To more visually represent the energy concentration of the main flap and the roll-down speed of the side flap, the specific out-of-band power of M-ary MSK is given. OMLCD(Optimum Maximum Likelihood Coherent Detection) of M-ary MSK is adopted to compare the signal received with prepared in advance in a code element T to go for the best. And M-ary MSK BER(Bit Error Rate) is compared with the same ary PSK (Phase Shift Keying) with M=2,4,6,8. The results show the detection method could improve performance by increasing the length of L(memory inherent) in the phase continuity.

Study on Face recognition algorithm using the eye detection (눈 검출을 이용한 얼굴인식 알고리즘에 관한 연구)

  • Park, Byung-Joon;Kim, Ki-young;Kim, Sun-jib
    • The Journal of Korea Institute of Information, Electronics, and Communication Technology
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    • v.8 no.6
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    • pp.491-496
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    • 2015
  • Cloud computing has emerged with promise to decrease the cost of server additional cost and expanding the data storage and ease for computer resource sharing and apply the new technologies. However, Cloud computing also raises many new security concerns due to the new structure of the cloud service models. Therefore, the secure user authentication is required when the user is using cloud computing. This paper, we propose the enhanced AdaBoost algorithm for access cloud security zone. The AdaBoost algorithm despite the disadvantage of not detect a face inclined at least 20, is widely used because of speed and responsibility. In the experimental results confirm that a face inclined at least 20 degrees tilted face was recognized. Using the FEI Face Database that can be used in research to obtain a result of 98% success rate of the algorithm perform. The 2% failed rate is due to eye detection error which is the people wearing glasses in the picture.

A New Cancer Cell Detection Method Using an Infectivity-enhanced Adenoviral Vector

  • Uchino, Junji;Takayama, Koichi;Nakagaki, Noriaki;Shuo, Wang;Hisasue, Junko;Nakatom, Keita;Ohta, Keiichi;Hirano, Ryosuke;Tashiro, Naoki;Miiru, Izumi;Fujita, Masaki;Watanabe, Kentaro;Nakanishi, Yoichi
    • Asian Pacific Journal of Cancer Prevention
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    • v.13 no.11
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    • pp.5551-5556
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    • 2012
  • Cytological examination is widely used as a diagnostic tool because of the ease of collecting cells from the involved area. However, the diagnostic yield of cytological examination is unsatisfactory; the reasons include sampling error, poorly prepared samples, small numbers of malignant cells, and low grades of cellular atypia. In this study, we focused on the high infectivity of adenovirus towards epithelial cells and applied the luciferase-expressing adenoviral vector to a new cancer cell detection tool. In addition, adenoviral infectivity was enhanced by modifying viral fiber proteins. The sensitivity of the diagnostic tool was tested using the NCI-H1299 lung cancer cell line, and validated in body fluid samples from cancer patients with a variety of etiology. Results showed that the adenovirus efficiently transfected NCI-H1299 with high sensitivity. Only 10 cancer cells were sufficient for detection of luciferase signals. In body fluid samples, the adenovirus confirmed the diagnosis for malignant and benign cancer, but not in non-epithelial cell derived samples. This study provides proof-of-concept for a more reliable and sensitive diagnostic tool for epithelium-derived cancer.

An automated memory error detection technique using source code analysis in C programs (C언어 기반 프로그램의 소스코드 분석을 이용한 메모리 접근오류 자동검출 기법)

  • Cho, Dae-Wan;Oh, Seung-Uk;Kim, Hyeon-Soo
    • The KIPS Transactions:PartD
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    • v.14D no.6
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    • pp.675-688
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    • 2007
  • Memory access errors are frequently occurred in C programs. A number of tools and research works have been trying to detect the errors automatically. However, they have one or more of the following problems: inability to detect all memory errors, changing the memory allocation mechanism, incompatibility with libraries, and excessive performance overhead. In this paper, we suggest a new method to solve these problems, and then present a result of comparison to the previous research works through the experiments. Our approach consists of two phases. First is to transform source code at compile time through inserting instrumentation into the source code. And second is to detect memory errors at run time with a bitmap that maintains information about memory allocation. Our approach has improved the error detection abilities against the binary code analysis based ones by using the source code analysis technique, and enhanced performance in terms of both space and time, too. In addition, our approach has no problem with respect to compatibility with shared libraries as well as does not need to modify memory allocation mechanism.

Wide-area Surveillance Applicable Core Techniques on Ship Detection and Tracking Based on HF Radar Platform (광역감시망 적용을 위한 HF 레이더 기반 선박 검출 및 추적 요소 기술)

  • Cho, Chul Jin;Park, Sangwook;Lee, Younglo;Lee, Sangho;Ko, Hanseok
    • Korean Journal of Remote Sensing
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    • v.34 no.2_2
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    • pp.313-326
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    • 2018
  • This paper introduces core techniques on ship detection and tracking based on a compact HF radar platform which is necessary to establish a wide-area surveillance network. Currently, most HF radar sites are primarily optimized for observing sea surface radial velocities and bearings. Therefore, many ship detection systems are vulnerable to error sources such as environmental noise and clutter when they are applied to these practical surface current observation purpose systems. In addition, due to Korea's geographical features, only compact HF radars which generates non-uniform antenna response and has no information on target information are applicable. The ship detection and tracking techniques discussed in this paper considers these practical conditions and were evaluated by real data collected from the Yellow Sea, Korea. The proposed method is composed of two parts. In the first part, ship detection, a constant false alarm rate based detector was applied and was enhanced by a PCA subspace decomposition method which reduces noise. To merge multiple detections originated from a single target due to the Doppler effect during long CPIs, a clustering method was applied. Finally, data association framework eliminates false detections by considering ship maneuvering over time. According to evaluation results, it is claimed that the proposed method produces satisfactory results within certain ranges.

An Enhanced Step Detection Algorithm with Threshold Function under Low Sampling Rate (낮은 샘플링 주파수에서 임계 함수를 사용한 개선된 걸음 검출 알고리즘)

  • Kim, Boyeon;Chang, Yunseok
    • KIPS Transactions on Computer and Communication Systems
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    • v.4 no.2
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    • pp.57-64
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    • 2015
  • At the case of peak threshold algorithm, 3-axes data should sample step data over 20 Hz to get sufficient accuracy. But most of the digital sensors like 3-axes accelerometer have very low sampling rate caused by low data communication speed on limited SPI or $I^2C$ bandwidth of the low-cost MPU for ubiquitous devices. If the data transfer rate of the 3-axes accelerometer is getting slow, the sampling rate also slows down and it finally degrades the data accuracy. In this study, we proved there is a distinct functional relation between the sampling rate and threshold on the peak threshold step detection algorithm under the 20Hz frequency, and made a threshold function through the experiments. As a result of experiments, when we apply threshold value from the threshold function instead of fixed threshold value, the step detection error rate can be lessen about 1.2% or under. Therefore, we can suggest a peak threshold based new step detection algorithm with threshold function and it can enhance the accuracy of step detection and step count. This algorithm not only can be applied on a digital step counter design, but also can be adopted any other low-cost ubiquitous sensor devices subjected on low sampling rate.

A Method for Improving Object Recognition Using Pattern Recognition Filtering (패턴인식 필터링을 적용한 물체인식 성능 향상 기법)

  • Park, JinLyul;Lee, SeungGi
    • Journal of the Institute of Electronics and Information Engineers
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    • v.53 no.6
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    • pp.122-129
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    • 2016
  • There have been a lot of researches on object recognition in computer vision. The SURF(Speeded Up Robust Features) algorithm based on feature detection is faster and more accurate than others. However, this algorithm has a shortcoming of making an error due to feature point mismatching when extracting feature points. In order to increase a success rate of object recognition, we have created an object recognition system based on SURF and RANSAC(Random Sample Consensus) algorithm and proposed the pattern recognition filtering. We have also presented experiment results relating to enhanced the success rate of object recognition.