scholarly journals Research on Endpoint Detection Algorithm in High Altitude Explosion Point Location Technology

2021 ◽  
Vol 10 (11) ◽  
pp. 226-231
Author(s):  
Yafei Wang ◽  
Wen Bin
Keyword(s):  
High Altitude ◽  
Sound Source ◽  
Detection Algorithm ◽  
Sound Signal ◽  
Single Element ◽  
Endpoint Detection ◽  
Weather Modification ◽  
Short Term ◽  
Zero Crossing ◽  
The Time Domain

Aiming at the problem of inadequate positioning accuracy of sound endpoints by the dual-element single-threshold endpoint detection algorithm and the single-element dual-threshold endpoint detection algorithm in the process of locating the sound source of weather modification bombs at high altitudes during artificial weather modification, a multi-element dual threshold endpoint detection algorithm. First, according to the characteristics of high-altitude explosion of weather modification bombs and ground reception, the sound signal is filtered and denoised, divided into frames, and windowed. Then, the time-domain feature short-term energy, short-term zero-crossing rate and frequency domain feature short-term information entropy of each frame of the sound signal are calculated, and double thresholds are set for detection. In this way, the start and end points of the explosion sound in the collected sound signal are found, and the data is imported into the positioning algorithm for processing, and then the explosion point of the weather modification bombs in the high air is located. The test results show that the method can accurately distinguish the end point of effective explosion sound, and has practical application value for the location of the sound source of the high-altitude explosion point of the weather modification bombs.

scholarly journals EVALUATION AND COMPARISON USING ACTIVITY SIGNALS OF SPEECH METHODS IN RIVER PLATE SPANISH USING BEPPA CORPUS

2016 ◽  
Vol 28 (1) ◽  
pp. 138-144
Author(s):  
Horderlin Vrangel Robles ◽  
Valentin Molina ◽  
Luis Martinez ◽  
Hermann Davila
Keyword(s):  
State Of The Art ◽  
Detection Algorithm ◽  
Spectral Energy ◽  
Activity Detection ◽  
Endpoint Detection ◽  
Zero Crossing ◽  
Order Difference ◽  
Rate Method ◽  
Short Time ◽  
Voice Activity

The results obtained after comparing several algorithms which use basic methods of signal processing for speech activity detection of voice or VAD (Voice Activity Detection-VAD), were assessed in order to determine their effectiveness. The algorithms presented in this article are short-time or spectral energy based endpoint detection algorithm, the zero crossing rate method, and the higher order differential (High Order Difference, HOD) method. First, an introduction of the concept of VAD is presented and the need to apply such language algorithms in River Plate is Spanish. Then a summary of the state of the art techniques and algorithms for detecting voice activity is shown with evidence and experiments used to implement algorithms with BEPPA corpus (Evaluation Battery for Patients with Auditive Prostheses, BEPPA – in Spanish).

scholarly journals Sound Localization for Ad-Hoc Microphone Arrays

Energies ◽  
2021 ◽  
Vol 14 (12) ◽  
pp. 3446
Author(s):  
Muhammad Usman Liaquat ◽  
Hafiz Suliman Munawar ◽  
Amna Rahman ◽  
Zakria Qadir ◽  
Abbas Z. Kouzani ◽  
...  
Keyword(s):  
Sound Localization ◽  
Sound Source ◽  
Ad Hoc ◽  
Dimensional Space ◽  
Computation Time ◽  
Location Estimation ◽  
Microphone Arrays ◽  
Sound Signal ◽  
Experimental Arrangement ◽  
Advantages And Disadvantages

Sound localization is a field of signal processing that deals with identifying the origin of a detected sound signal. This involves determining the direction and distance of the source of the sound. Some useful applications of this phenomenon exists in speech enhancement, communication, radars and in the medical field as well. The experimental arrangement requires the use of microphone arrays which record the sound signal. Some methods involve using ad-hoc arrays of microphones because of their demonstrated advantages over other arrays. In this research project, the existing sound localization methods have been explored to analyze the advantages and disadvantages of each method. A novel sound localization routine has been formulated which uses both the direction of arrival (DOA) of the sound signal along with the location estimation in three-dimensional space to precisely locate a sound source. The experimental arrangement consists of four microphones and a single sound source. Previously, sound source has been localized using six or more microphones. The precision of sound localization has been demonstrated to increase with the use of more microphones. In this research, however, we minimized the use of microphones to reduce the complexity of the algorithm and the computation time as well. The method results in novelty in the field of sound source localization by using less resources and providing results that are at par with the more complex methods requiring more microphones and additional tools to locate the sound source. The average accuracy of the system is found to be 96.77% with an error factor of 3.8%.

scholarly journals Performance Evaluation of Neural Network-Based Short-Term Solar Irradiation Forecasts

Energies ◽  
2021 ◽  
Vol 14 (11) ◽  
pp. 3030
Author(s):  
Simon Liebermann ◽  
Jung-Sup Um ◽  
YoungSeok Hwang ◽  
Stephan Schlüter
Keyword(s):  
Neural Network ◽  
Goodness Of Fit ◽  
Renewable Energy Sources ◽  
Weather Conditions ◽  
Solar Irradiation ◽  
Weather Data ◽  
Short Term ◽  
Climate Conditions ◽  
Lstm Network ◽  
The Time Domain

Due to the globally increasing share of renewable energy sources like wind and solar power, precise forecasts for weather data are becoming more and more important. To compute such forecasts numerous authors apply neural networks (NN), whereby models became ever more complex recently. Using solar irradiation as an example, we verify if this additional complexity is required in terms of forecasting precision. Different NN models, namely the long-short term (LSTM) neural network, a convolutional neural network (CNN), and combinations of both are benchmarked against each other. The naive forecast is included as a baseline. Various locations across Europe are tested to analyze the models’ performance under different climate conditions. Forecasts up to 24 h in advance are generated and compared using different goodness of fit (GoF) measures. Besides, errors are analyzed in the time domain. As expected, the error of all models increases with rising forecasting horizon. Over all test stations it shows that combining an LSTM network with a CNN yields the best performance. However, regarding the chosen GoF measures, differences to the alternative approaches are fairly small. The hybrid model’s advantage lies not in the improved GoF but in its versatility: contrary to an LSTM or a CNN, it produces good results under all tested weather conditions.

scholarly journals Simulation of Temperature Regime of Pavement Layers in Transition Periods of Road Climatic Zone IV

2019 ◽  
Vol 9 (1) ◽  
pp. 6142-6148
Keyword(s):  
Temperature Regime ◽  
Traffic Accidents ◽  
Road Traffic ◽  
Climatic Zone ◽  
Short Term ◽  
Zero Crossing ◽  
Krasnodar Krai ◽  
Weather Forecasts ◽  
Road Pavement ◽  
Pavement Layers

Pavement icing during short-term night temperature drops leads to deterioration of highway performances and increase in road traffic accidents (RTA) in Krasnodar Krai. Peculiar features of temperature regime in road climatic zone (RCZ) IV are analyzed. The considered climatic zone is characterized by frequent zero crossing temperatures of air and road pavement, sharp short-term temperature drops in nighttime, frequent icing of road pavement. Main factors are highlighted which effect temperature regime of road structures. Mathematical model is presented for prediction of road pavement temperature based on weather forecasts. Possibility to decrease the volume of pavement icing by means of thermophysical properties of pavement layers is analyzed.

Adaptations to High-Altitude Hypoxia

2021 ◽  
Author(s):  
Cynthia M. Beall ◽  
Kingman P. Strohl
Keyword(s):  
High Altitude ◽  
Oxygen Delivery ◽  
Hemoglobin Concentration ◽  
Barometric Pressure ◽  
Ambient Air ◽  
Extreme Environment ◽  
Indigenous Populations ◽  
East African ◽  
Short Term

Biological anthropologists aim to explain the hows and whys of human biological variation using the concepts of evolution and adaptation. High-altitude environments provide informative natural laboratories with the unique stress of hypobaric hypoxia, which is less than usual oxygen in the ambient air arising from lower barometric pressure. Indigenous populations have adapted biologically to their extreme environment with acclimatization, developmental adaptation, and genetic adaptation. People have used the East African and Tibetan Plateaus above 3,000 m for at least 30,000 years and the Andean Plateau for at least 12,000 years. Ancient DNA shows evidence that the ancestors of modern highlanders have used all three high-altitude areas for at least 3,000 years. It is necessary to examine the differences in biological processes involved in oxygen exchange, transport, and use among these populations. Such an approach compares oxygen delivery traits reported for East African Amhara, Tibetans, and Andean highlanders with one another and with short-term visitors and long-term upward migrants in the early or later stages of acclimatization to hypoxia. Tibetan and Andean highlanders provide most of the data and differ quantitatively in biological characteristics. The best supported difference is the unelevated hemoglobin concentration of Tibetans and Amhara compared with Andean highlanders as well as short- and long-term upward migrants. Moreover, among Tibetans, several features of oxygen transfer and oxygen delivery resemble those of short-term acclimatization, while several features of Andean highlanders resemble the long-term responses. Genes and molecules of the oxygen homeostasis pathways contribute to some of the differences.

Determination of tonal signal parameters based on zero crossing detection

2021 ◽  
Vol 263 (5) ◽  
pp. 1794-1803
Author(s):  
Michal Luczynski ◽  
Stefan Brachmanski ◽  
Andrzej Dobrucki
Keyword(s):  
High Efficiency ◽  
Detection Algorithm ◽  
Sine Wave ◽  
Time Interval ◽  
Zero Crossing ◽  
Tonal Signal ◽  
Zero Crossings ◽  
Tonal Component ◽  
Signal Parameters ◽  
The Moment

This paper presents a method for identifying tonal signal parameters using zero crossing detection. The signal parameters: frequency, amplitude and phase can change slowly in time. The described method allows to obtain accurate detection using possibly small number of signal samples. The detection algorithm consists of the following steps: frequency filtering, zero crossing detection and parameter reading. Filtering of the input signal is aimed at obtaining a signal consisting of a single tonal component. Zero crossing detection allows the elimination of multiple random zero crossings, which do not occur in a pure sine wave signal. The frequency is based on the frequency of transitions through zero, the amplitude is the largest value of the signal in the analysed time interval, and the initial phase is derived from the moment at which the transition through zero occurs. The obtained parameters were used to synthesise a compensation signal in an active tonal component reduction algorithm. The results of the algorithm confirmed the high efficiency of the method.

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