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This study explored how the Lombard effect, a natural or artificial increase in speech loudness in noisy environments, can improve speech-in-noise communication. This study consisted of several experiments that measured the impact of different types of noise on synthesizing the Lombard effect. The main steps were as follows: first, a dataset of speech samples with and without the Lombard effect was collected in a controlled setting; then, the frequency changes in the speech signals were detected using the McAulay and Quartieri algorithm based on a 2D speech representation; next, an average formant track error was computed as a metric to evaluate the quality of the speech signals in noise. Three image assessment methods, namely the SSIM (Structural SIMilarity) index, RMSE (Root Mean Square Error), and dHash (Difference Hash) were used for this purpose. Furthermore, this study analyzed various spectral features of the speech signals in relation to the Lombard effect and the noise types. Finally, this study proposed a method for automatic noise profiling and applied pitch modifications to neutral speech signals according to the profile and the frequency change patterns. This study used an overlap-add synthesis in the STRAIGHT vocoder to generate the synthesized speech. [ABSTRACT FROM AUTHOR]

The study aims to find a low-cost alternate technology to get imagery, using mobile platform, and produce digital orthophoto for corridor mapping, with a higher degree of accuracy and which can reduce the lag time of acquisition of data. The present study uses digital single-lens reflex cameras, mounted on a mobile vehicle, and acquisition of data in the video format rather than still photographs, as traditionally used in mobile mapping systems. The videos are used to create a set of images and orthophotos. A widespread ground control points were recorded in the study area, using the global navigation satellite system receiver, which measured the control points in real-time kinematic mode. Generation of digital orthophoto has been completed using the captured mobile imagery and ground control point. Furthermore, procurement of satellite imagery and aerial triangulation using ground control points have been done. While comparing the planimetric accuracy of orthophoto against satellite imagery using the ground control points, the achieved root mean square error value of produced orthophoto is 0.171 m in X axis and 0.205 m in Y axis. However, for Cartosat -1 satellite imagery, the RMSE value for X is 1.22 m and for Y is 1.98 m. This research proposes the alternate low-cost mobile mapping method to capture the imagery for orthophoto production. The cost of orthophoto production from mobile image was found 77% cheaper than the orthophoto cost from fresh/latest satellite imagery procurement, while the overall production was 70% cost-effective than the orthophoto maps made from archived imagery. [ABSTRACT FROM AUTHOR]

In this paper, an algorithm for extracting and localizing a radar pulse in a noisy environment is described. The algorithm combines two powerful tools: wavelet denoising and the short-time Fourier transform (STFT) analysis with statistical-based threshold. We aim to detect radar pulses transmitted by any radar in blind mode regardless of the intra-pulse modulation and parametric features. The use of the proposed technique makes the detection and localization of radar pulses possible under very low signal-to-noise ratio conditions (−18 dB), which leads to a reduction of the required signal power or alternatively extends the detection range of radar systems. Radar classes pattern-based analysis is used in blind mode to decrease the probability of false alarm. [ABSTRACT FROM AUTHOR]

In this paper a square wavelet thresholding method is proposed and evaluated as compared to the other classical wavelet thresholding methods (like soft and hard). The main advantage of this work is to design and implement a new wavelet thresholding method and evaluate it against other classical wavelet thresholding methods and hence search for the optimal wavelet mother function among the wide families with a suitable level of decomposition and followed by a novel thresholding method among the existing methods. This optimized method will be used to shrink the wavelet coefficients and yield an adequate compressed pressure signal prior to transmit it. While a comparison evaluation analysis is established, A new proposed procedure is used to compress a synthetic signal and obtain the optimal results through minimization the signal memory size and its transmission bandwidth. There are different performance indices to establish the comparison and evaluation process for signal compression; but the most well-known measuring scores are: NMSE, ESNR, and PDR. The obtained results showed the dominant of the square wavelet thresholding method against other methods using different measuring scores and hence the conclusion by the way for adopting this proposed novel wavelet thresholding method for 1D signal compression in future researches. [ABSTRACT FROM AUTHOR]

Inflation is the increase of prices of goods that can affect other prices of goods. Inflation is a main economic problem often faced by society. This economic problem could cause detrimental economic, political, and social effects. Inflation can be caused by a variety of sources. One of them comes from imported goods. Therefore, forecasting is needed to find out the inflation rate in the future. Inflation forecasting can be used to prepare government policies to keep inflation at a low level. In addition, the forecasting results can also be utilized by all members of the society. This study proposed the Backpropagation Neural Network method to forecast the inflation rate in the future. This study used time-series data of inflation rate and CPI (Consumer Price Index). The tested data resulted in a forecast. The RMSE (Root Mean Square Error) technique was used to test the accuracy of the forecasting results. This study also implemented the Sugeno FIS model as a comparison method. The result showed that the performance of the proposed method is better than the comparison method with an RMSE value of 0.204. [ABSTRACT FROM AUTHOR]

Nowadays DEMs are indispensable tools in studies and analysis regarding Earth's surface. Generating DEMs closely to the true surfaces and with high accuracy represent a main issue. The aim of the study is to improve the geomorphometric analysis based on DEMs. In this study a statistical approach was used to assess various DEMs generated with different methods to compare their accuracy. DEMs were created on the base of a topographic map using classical interpolation methods (Spline, IDW, Kriging, Simple linear interpolation) and simulated surfaces. The results suggest that data source is more important in error propagation, followed by interpolation methods. [ABSTRACT FROM AUTHOR]