Comparison of measured and predicted statistical measures in military jet noise propagation

2015 ◽  
Vol 138 (3) ◽  
pp. 1893-1893
Author(s):  
Brent O. Reichman ◽  
Alan T. Wall ◽  
Kent L. Gee ◽  
Tracianne B. Neilsen
Keyword(s):  
Jet Noise ◽  
Noise Propagation ◽  
Statistical Measures

Comparison of nonlinear, geometric, and absorptive effects in high-amplitude jet noise propagation

2014 ◽  
Vol 136 (4) ◽  
pp. 2102-2102 ◽  
Author(s):  
Brent O. Reichman ◽  
Kent L. Gee ◽  
Tracianne B. Neilsen ◽  
Joseph J. Thaden ◽  
Michael M. James
Keyword(s):  
Jet Noise ◽  
High Amplitude ◽  
Noise Propagation ◽  
Nonlinear Geometric

Wing Effect on Jet Noise Propagation

1981 ◽  
Vol 18 (4) ◽  
pp. 295-302 ◽  
Author(s):  
M. E. Wang
Keyword(s):  
Jet Noise ◽  
Noise Propagation

Development of Dermatological Skin Disease Detection and Classification based on Wavelet and ANN

2018 ◽  
Vol 8 (5) ◽  
pp. 10
Author(s):  
Revati Kadu ◽  
U. A. Belorkar
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Skin Disease ◽  
Skin Diseases ◽  
Screening Method ◽  
Phase Detection ◽  
Statistical Measures ◽  
The World ◽  
Artificial Neural ◽  
Wavelet Techniques

One of the most common and augmenting health problems in the world are related to skin. The most  unpredictable and one of the most difficult entities to automatically detect and evaluate is the human skin disease because of complexities of texture, tone, presence of hair and other distinctive features. Many cases of skin diseases in the world have triggered a need to develop an effective automated screening method for detection and diagnosis of the area of disease. Therefore the objective of this work is to develop a new technique for automated detection and analysis of the skin disease images based on color and texture information for skin disease screening. In this paper, system is proposed which detects the skin diseases using Wavelet Techniques and Artificial Neural Network. This paper presents a wavelet-based texture analysis method for classification of five types of skin diseases. The method applies tree-structured wavelet transform on different color channels of red, green and blue dermoscopy images, and employs various statistical measures and ratios on wavelet coefficients. In all 99 unique features are extracted from the image. By using Artificial Neural Network, the system successfully detects different types of dermatological skin diseases. It consists of mainly three phases image processing, training phase, detection  and classification phase.

Robust Watermarking Scheme for GIS Vector Maps

2018 ◽  
Vol 31 (1) ◽  
pp. 277 ◽  
Author(s):  
Methaq Talib Gaata
Keyword(s):  
Main Idea ◽  
Geospatial Data ◽  
Robust Watermarking ◽  
Digital Map ◽  
Statistical Measures ◽  
Data Authentication ◽  
Two Factors ◽  
Illegal Copying ◽  
Value Decomposition ◽  
Watermarking Scheme

  With the fast progress of information technology and the computer networks, it becomes very easy to reproduce and share the geospatial data due to its digital styles. Therefore, the usage of geospatial data suffers from various problems such as data authentication, ownership proffering, and illegal copying ,etc. These problems can represent the big challenge to future uses of the geospatial data. This paper introduces a new watermarking scheme to ensure the copyright protection of the digital vector map. The main idea of proposed scheme is based on transforming  the digital map to frequently domain using the Singular Value Decomposition (SVD) in order to determine suitable areas to insert the watermark data. The digital map is separated into the isolated parts.Watermark data are embedded within the nominated magnitudes in each part when satisfied the definite criteria. The efficiency of proposed watermarking scheme is assessed within statistical measures based on two factors which are fidelity and robustness. Experimental results demonstrate the proposed watermarking scheme representing ideal trade off for disagreement issue between distortion amount and robustness. Also, the proposed scheme shows  robust resistance for many kinds of attacks.

Energy transfer mechanism of supersonic jet noise through rectangular nozzles

2017 ◽  
Vol 65 (2) ◽  
pp. 110-120 ◽  
Author(s):  
Zhe Chen ◽  
Jiu-Hui Wu ◽  
A-Dan Ren ◽  
Xin Chen ◽  
Zhen Huang
Keyword(s):  
Energy Transfer ◽  
Supersonic Jet ◽  
Jet Noise ◽  
Transfer Mechanism ◽  
Energy Transfer Mechanism ◽  
Supersonic Jet Noise
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