BASIC DESIGN OF JAPANESE NATIONWIDE GPS BUOY NETWORK WITH MULTI-PURPOSE OFFSHORE OBSERVATION SYSTEM

2009 ◽  
Vol 03 (02) ◽  
pp. 113-119 ◽  
Author(s):  
TOSHIHIKO NAGAI ◽  
KATSUYOSHI SHIMIZU
Keyword(s):  
Detection System ◽  
Processing System ◽  
Offshore Wind ◽  
Observation System ◽  
Basic Design ◽  
Wave Analysis ◽  
Current Analysis ◽  
Future Plan ◽  
Gps Buoy ◽  
Directional Wave

This paper introduces a basic design of GPS buoy multi-purpose data processing system using numerical filtering analysis. GPS buoy system and future plan of the GPS buoy network in Japan are introduced. Tsunami detection system with time series is considered. Directional wave analysis and offshore wind and current analysis methods are also investigated.

Analysis of Different Harmonic and Intermodulation Distortions for CATV Systems

2015 ◽  
Vol 36 (2) ◽  
Author(s):  
Sandeep Singh ◽  
Singh Bhatia Kamaljit ◽  
Sharma Anurag ◽  
Harsimrat Kaur
Keyword(s):  
Relative Intensity ◽  
Basic Design ◽  
Design Issues ◽  
Current Analysis ◽  
Intermodulation Distortions ◽  
Different Order

AbstractIn this paper, after examining all the basic design issues of CATV systems, prominent distortions like harmonic and intermodulation distortions are taken into account for different order. Besides outer distortions for CATV sources, inner distortion of relative intensity to noise is disabled for current analysis.

scholarly journals Evolution in diagnosis and detection of brain tumor – review

2021 ◽  
Vol 2115 (1) ◽  
pp. 012039
Author(s):  
A Sravanthi Peddinti ◽  
Suman Maloji ◽  
Kasiprasad Manepalli
Keyword(s):  
Machine Learning ◽  
Brain Tumor ◽  
Detection System ◽  
Early Stage ◽  
Processing System ◽  
Tumor Detection ◽  
Machine Learning Algorithms ◽  
Learning Ability ◽  
Future Perspective ◽  
Automation Systems

Abstract Diagnosis of Brain tumor at an early stage has became an important topic of research in recent time. Detection of tumor at an early stage for primary treatment increases the patient’s survival rate. Processing of Magnetic resonance image (MRI) for an early tumor detection face the challenge of high processing overhead due to large volume of image input to the processing system. This result to large delay and decrease in system efficiency. Hence, the need of an enhanced detection system for accurate segmentation and representation for a faster and accurate processing has evolved in recent past. Development of new approaches based on improved learning and processing for brain tumor detection has been proposed in recent literatures. This paper outlines a brief review on the developments made in the area of MRI processing for an early diagnosis and detection of brain tumor for segmentation, representation and applying new machine learning (ML) methods in decision making. The learning ability and fine processing of Machine learning algorithms has shown an improvement in the current automation systems for faster and more accurate processing for brain tumor detection. The current trends in the automation of brain tumor detection, advantages, limitations and the future perspective of existing methods for computer aided diagnosis in brain tumor detection is outlined.

The Present Development Situation of Laser Ultrasonic Nondestructive Testing Signal Processing System

2012 ◽  
Vol 532-533 ◽  
pp. 369-373
Author(s):  
Lie Xiang Xia ◽  
Yan Zhao ◽  
Yong Zhong Ma ◽  
Xiao Ning An
Keyword(s):  
Signal Processing ◽  
Nondestructive Testing ◽  
Detection System ◽  
Matching Pursuit ◽  
Ultrasonic Inspection ◽  
Processing System ◽  
Guided Wave ◽  
Ultrasonic Nondestructive Testing ◽  
Laser Ultrasonic ◽  
Signal Processing System

Currently, laser ultrasonic nondestructive testing is the best application prospect of nondestructive testing methods. This paper expounds the mechanism and the qualitative analysis of the common defects of the laser ultrasonic inspection and introduces the application of matching pursuit algorithm guided wave testing technology in signal processing. This paper focuses on the laser ultrasonic detection system and analysis of the detected data using the finite element method.

ARM-Based Embedded Visual Processing System

2012 ◽  
Vol 220-223 ◽  
pp. 1973-1976
Author(s):  
Guo Hao He
Keyword(s):  
Power Systems ◽  
Visual Processing ◽  
Detection System ◽  
Processing System ◽  
Smart Devices ◽  
Smart Environment ◽  
Embedded Devices ◽  
The Past ◽  
Embedded Computer Vision ◽  
Embedded Computer

Embedded computer vision is a relatively new concept, it is only in the past few years that embedded devices have become fast enough and the component cost low enough that they can be used in small low power systems. In this paper, the design and development of a vision-based detection system with smart devices features is proposed. The main functionality of the equipment is introduced as well as the additional features it should provide to be integrated into a smart environment.

Study of the Design of Radar Life Detector Based on DSP Signal Processing System

2014 ◽  
Vol 543-547 ◽  
pp. 1009-1012 ◽  
Author(s):  
Jin Jing
Keyword(s):  
Signal Processing ◽  
Detection System ◽  
Human Life ◽  
Rapid Development ◽  
Full Range ◽  
Processing System ◽  
Digital Signal ◽  
Signal Processing System ◽  
Implementation Scheme ◽  
The Time Domain

In recent years radar life detector is the rapid development product of information technology and Biomedical Engineering, and its core is to not contact with the human body, but to realize the detection of the parameters of human life which has a breakthrough, and to explore with full range. This paper first analyzes the principle of radar life detection system and the implementation scheme of each module technology. Based on this, DSP digital signal processing method is used to design the structure system of radar life detector. Further based on the DSP signal processing principle, PD distance tracking is used to approximately simulate the time domain of human heartbeat signal. The results show that the tracking effect that is under this structure is remarkable, which has provided technical support for the practice of the area to a certain extent.

Assessing the Quality of Directional Wave Measurement by a Differential GPS Buoy

2001 ◽  
Author(s):  
M. Rossouw ◽  
A. van Tonder ◽  
U. von St Ange ◽  
L. Coetzee ◽  
J. Davies
Keyword(s):  
Differential Gps ◽  
Wave Measurement ◽  
Gps Buoy ◽  
Directional Wave

The PCB Surface Defect Detection System Based on GPU Acceleration

2015 ◽  
Vol 713-715 ◽  
pp. 347-352
Author(s):  
Yu Liu ◽  
Si Zhe Li
Keyword(s):  
Defect Detection ◽  
Rapid Detection ◽  
Surface Defect ◽  
Printed Circuit Board ◽  
Detection System ◽  
Processing System ◽  
Circuit Board ◽  
Computing Platform ◽  
Surface Defect Detection ◽  
Time Requirements

Defective products are unavoidable in printed circuit board production process, so rapid detection and identificationmethods are badly in need of. PCB surface defect detection including a series of processing such as surface imagecapture, mixed noise filtering,images registering and so on, so it takes a lot of CPU time. To improve detection speed, based on GPU parallel computing platform, we designed a reasonable parallel processing system for PCB defect detectionto meet the need of real-time requirements of a production line. Experimental results show that parallel image processing algorithms based on GPU can achieve good results compared to the CPU-based serial algorithm (with speed up ratio up to8.34 in this paper),providing a new approachfor rapid detection of PCB surface defect.

scholarly journals Estimation Method of Directional Wave Spectra from GPS Buoy Motion

2013 ◽  
Vol 69 (2) ◽  
pp. I_1431-I_1435
Author(s):  
Katsumi SEKI ◽  
Hiroyasu KAWAI ◽  
Koji KAWAGUCHI ◽  
Tsutomu INOMATA ◽  
Noriaki HASHIMOTO
Keyword(s):  
Estimation Method ◽  
Wave Spectra ◽  
Gps Buoy ◽  
Directional Wave
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