Search results for: spectral amplitude coding (SAC)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 1831

Search results for: spectral amplitude coding (SAC)

1531 Application Research of Stilbene Crystal for the Measurement of Accelerator Neutron Sources

Authors: Zhao Kuo, Chen Liang, Zhang Zhongbing, Ruan Jinlu. He Shiyi, Xu Mengxuan

Abstract:

Stilbene, C₁₄H₁₂, is well known as one of the most useful organic scintillators for pulse shape discrimination (PSD) technique for its good scintillation properties. An on-line acquisition system and an off-line acquisition system were developed with several CAMAC standard plug-ins, NIM plug-ins, neutron/γ discriminating plug-in named 2160A and a digital oscilloscope with high sampling rate respectively for which stilbene crystals and photomultiplier tube detectors (PMT) as detector for accelerator neutron sources measurement carried out in China Institute of Atomic Energy. Pulse amplitude spectrums and charge amplitude spectrums were real-time recorded after good neutron/γ discrimination whose best PSD figure-of-merits (FoMs) are 1.756 for D-D accelerator neutron source and 1.393 for D-T accelerator neutron source. The probability of neutron events in total events was 80%, and neutron detection efficiency was 5.21% for D-D accelerator neutron sources, which were 50% and 1.44% for D-T accelerator neutron sources after subtracting the background of scattering observed by the on-line acquisition system. Pulse waveform signals were acquired by the off-line acquisition system randomly while the on-line acquisition system working. The PSD FoMs obtained by the off-line acquisition system were 2.158 for D-D accelerator neutron sources and 1.802 for D-T accelerator neutron sources after waveform digitization off-line processing named charge integration method for just 1000 pulses. In addition, the probabilities of neutron events in total events obtained by the off-line acquisition system matched very well with the probabilities of the on-line acquisition system. The pulse information recorded by the off-line acquisition system could be repetitively used to adjust the parameters or methods of PSD research and obtain neutron charge amplitude spectrums or pulse amplitude spectrums after digital analysis with a limited number of pulses. The off-line acquisition system showed equivalent or better measurement effects compared with the online system with a limited number of pulses which indicated a feasible method based on stilbene crystals detectors for the measurement of prompt neutrons neutron sources like prompt accelerator neutron sources emit a number of neutrons in a short time.

Keywords: stilbene crystal, accelerator neutron source, neutron / γ discrimination, figure-of-merits, CAMAC, waveform digitization

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1530 Rock Thickness Measurement by Using Self-Excited Acoustical System

Authors: Janusz Kwaśniewski, Ireneusz Dominik, Krzysztof Lalik

Abstract:

The knowledge about rock layers thickness, especially above drilled mining pavements are crucial for workers safety. The measuring systems used nowadays are generally imperfect and there is a strong demand for improvement. The application of a new type of a measurement system called Self-Excited Acoustical System is presented in the paper. The system was applied until now to monitor stress changes in metal and concrete constructions. The change in measurement methodology resulted in possibility of measuring the thickness of the rocks above the tunnels as well as thickness of a singular rock layer. The idea is to find two resonance frequencies of the self-exited system, which consists of a vibration exciter and vibration receiver placed at a distance, which are coupled with a proper power amplifier, and which operate in a closed loop with a positive feedback. The resonance with the higher amplitude determines thickness of the whole rock, whereas the lower amplitude resonance indicates thickness of a singular layer. The results of the laboratory tests conducted on a group of different rock materials are also presented.

Keywords: auto-oscillator, non-destructive testing, rock thickness measurement, geotechnic

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1529 Machine Learning Classification of Fused Sentinel-1 and Sentinel-2 Image Data Towards Mapping Fruit Plantations in Highly Heterogenous Landscapes

Authors: Yingisani Chabalala, Elhadi Adam, Khalid Adem Ali

Abstract:

Mapping smallholder fruit plantations using optical data is challenging due to morphological landscape heterogeneity and crop types having overlapped spectral signatures. Furthermore, cloud covers limit the use of optical sensing, especially in subtropical climates where they are persistent. This research assessed the effectiveness of Sentinel-1 (S1) and Sentinel-2 (S2) data for mapping fruit trees and co-existing land-use types by using support vector machine (SVM) and random forest (RF) classifiers independently. These classifiers were also applied to fused data from the two sensors. Feature ranks were extracted using the RF mean decrease accuracy (MDA) and forward variable selection (FVS) to identify optimal spectral windows to classify fruit trees. Based on RF MDA and FVS, the SVM classifier resulted in relatively high classification accuracy with overall accuracy (OA) = 0.91.6% and kappa coefficient = 0.91% when applied to the fused satellite data. Application of SVM to S1, S2, S2 selected variables and S1S2 fusion independently produced OA = 27.64, Kappa coefficient = 0.13%; OA= 87%, Kappa coefficient = 86.89%; OA = 69.33, Kappa coefficient = 69. %; OA = 87.01%, Kappa coefficient = 87%, respectively. Results also indicated that the optimal spectral bands for fruit tree mapping are green (B3) and SWIR_2 (B10) for S2, whereas for S1, the vertical-horizontal (VH) polarization band. Including the textural metrics from the VV channel improved crop discrimination and co-existing land use cover types. The fusion approach proved robust and well-suited for accurate smallholder fruit plantation mapping.

Keywords: smallholder agriculture, fruit trees, data fusion, precision agriculture

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1528 Free Vibration Analysis of Timoshenko Beams at Higher Modes with Central Concentrated Mass Using Coupled Displacement Field Method

Authors: K. Meera Saheb, K. Krishna Bhaskar

Abstract:

Complex structures used in many fields of engineering are made up of simple structural elements like beams, plates etc. These structural elements, sometimes carry concentrated masses at discrete points, and when subjected to severe dynamic environment tend to vibrate with large amplitudes. The frequency amplitude relationship is very much essential in determining the response of these structural elements subjected to the dynamic loads. For Timoshenko beams, the effects of shear deformation and rotary inertia are to be considered to evaluate the fundamental linear and nonlinear frequencies. A commonly used method for solving vibration problem is energy method, or a finite element analogue of the same. In the present Coupled Displacement Field method the number of undetermined coefficients is reduced to half when compared to the famous Rayleigh Ritz method, which significantly simplifies the procedure to solve the vibration problem. This is accomplished by using a coupling equation derived from the static equilibrium of the shear flexible structural element. The prime objective of the present paper here is to study, in detail, the effect of a central concentrated mass on the large amplitude free vibrations of uniform shear flexible beams. Accurate closed form expressions for linear frequency parameter for uniform shear flexible beams with a central concentrated mass was developed and the results are presented in digital form.

Keywords: coupled displacement field, coupling equation, large amplitude vibrations, moderately thick plates

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1527 Efficient Wind Fragility Analysis of Concrete Chimney under Stochastic Extreme Wind Incorporating Temperature Effects

Authors: Soumya Bhattacharjya, Avinandan Sahoo, Gaurav Datta

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Wind fragility analysis of chimney is often carried out disregarding temperature effect. However, the combined effect of wind and temperature is the most critical limit state for chimney design. Hence, in the present paper, an efficient fragility analysis for concrete chimney is explored under combined wind and temperature effect. Wind time histories are generated by Davenports Power Spectral Density Function and using Weighed Amplitude Wave Superposition Technique. Fragility analysis is often carried out in full Monte Carlo Simulation framework, which requires extensive computational time. Thus, in the present paper, an efficient adaptive metamodelling technique is adopted to judiciously approximate limit state function, which will be subsequently used in the simulation framework. This will save substantial computational time and make the approach computationally efficient. Uncertainty in wind speed, wind load related parameters, and resistance-related parameters is considered. The results by the full simulation approach, conventional metamodelling approach and proposed adaptive metamodelling approach will be compared. Effect of disregarding temperature in wind fragility analysis will be highlighted.

Keywords: adaptive metamodelling technique, concrete chimney, fragility analysis, stochastic extreme wind load, temperature effect

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1526 Effects of Spectrotemporal Modulation of Music Profiles on Coherence of Cardiovascular Rhythms

Authors: I-Hui Hsieh, Yu-Hsuan Hu

Abstract:

The powerful effect of music is often associated with changes in physiological responses such as heart rate and respiration. Previous studies demonstrate that Mayer waves of blood pressure, the spontaneous rhythm occurring at 0.1 Hz, corresponds to a progressive crescendo of the musical phrase. However, music contain dynamic changes in temporal and spectral features. As such, it remains unclear which aspects of musical structures optimally affect synchronization of cardiovascular rhythms. This study investigates the independent contribution of spectral pattern, temporal pattern, and dissonance level on synchronization of cardiovascular rhythms. The regularity of acoustical patterns occurring at a periodic rhythm of 0.1 Hz is hypothesized to elicit the strongest coherence of cardiovascular rhythms. Music excerpts taken from twelve pieces of Western classical repertoire were modulated to contain varying degrees of pattern regularity of the acoustic envelope structure. Three levels of dissonance were manipulated by varying the harmonic structure of the accompanying chords. Electrocardiogram and photoplethysmography signals were recorded for 5 minutes of baseline and simultaneously while participants listen to music excerpts randomly presented over headphones in a sitting position. Participants were asked to indicate the pleasantness of each music excerpt by adjusting via a slider presented on screen. Analysis of the Fourier spectral power of blood pressure around 0.1 Hz showed a significant difference between music excerpts characterized by spectral and temporal pattern regularity compared to the same content in random pattern. Phase coherence between heart rate and blood pressure increased significantly during listening to spectrally-regular phrases compared to its matched control phrases. The degree of dissonance of the accompanying chord sequence correlated with level of coherence between heart rate and blood pressure. Results suggest that low-level auditory features of music can entrain coherence of autonomic physiological variables. These findings have potential implications for using music as a clinical and therapeutic intervention for regulating cardiovascular functions.

Keywords: cardiovascular rhythms, coherence, dissonance, pattern regularity

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1525 Normalized Difference Vegetation Index and Hyperspectral: Plant Health Assessment

Authors: Srushti R. Joshi, Ujjwal Rakesh, Spoorthi Sripad

Abstract:

The rapid advancement of remote sensing technologies has revolutionized plant health monitoring, offering valuable insights for precision agriculture and environmental management. This paper presents a comprehensive comparative analysis between the widely employed normalized difference vegetation index (NDVI) and state-of-the-art hyperspectral sensors in the context of plant health assessment. The study aims to elucidate the weigh ups of spectral resolution. Employing a diverse range of vegetative environments, the research utilizes simulated datasets to evaluate the performance of NDVI and hyperspectral sensors in detecting subtle variations indicative of plant stress, disease, and overall vitality. Through meticulous data analysis and statistical validation, this study highlights the superior performance of hyperspectral sensors across the parameters used.

Keywords: normalized difference vegetation index, hyperspectral sensor, spectral resolution, infrared

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1524 Seismic Data Analysis of Intensity, Orientation and Distribution of Fractures in Basement Rocks for Reservoir Characterization

Authors: Mohit Kumar

Abstract:

Natural fractures are classified in two broad categories of joints and faults on the basis of shear movement in the deposited strata. Natural fracture always has high structural relationship with extensional or non-extensional tectonics and sometimes the result is seen in the form of micro cracks. Geological evidences suggest that both large and small-scale fractures help in to analyze the seismic anisotropy which essentially contribute into characterization of petro physical properties behavior associated with directional migration of fluid. We generally question why basement study is much needed as historically it is being treated as non-productive and geoscientist had no interest in exploration of these basement rocks. Basement rock goes under high pressure and temperature, and seems to be highly fractured because of the tectonic stresses that are applied to the formation along with the other geological factors such as depositional trend, internal stress of the rock body, rock rheology, pore fluid and capillary pressure. Sometimes carbonate rocks also plays the role of basement and igneous body e.g basalt deposited over the carbonate rocks and fluid migrate from carbonate to igneous rock due to buoyancy force and adequate permeability generated by fracturing. So in order to analyze the complete petroleum system, FMC (Fluid Migration Characterization) is necessary through fractured media including fracture intensity, orientation and distribution both in basement rock and county rock. Thus good understanding of fractures can lead to project the correct wellbore trajectory or path which passes through potential permeable zone generated through intensified P-T and tectonic stress condition. This paper deals with the analysis of these fracture property such as intensity, orientation and distribution in basement rock as large scale fracture can be interpreted on seismic section, however, small scale fractures show ambiguity in interpretation because fracture in basement rock lies below the seismic wavelength and hence shows erroneous result in identification. Seismic attribute technique also helps us to delineate the seismic fracture and subtle changes in fracture zone and these can be inferred from azimuthal anisotropy in velocity and amplitude and spectral decomposition. Seismic azimuthal anisotropy derives fracture intensity and orientation from compressional wave and converted wave data and based on variation of amplitude or velocity with azimuth. Still detailed analysis of fractured basement required full isotropic and anisotropic analysis of fracture matrix and surrounding rock matrix in order to characterize the spatial variability of basement fracture which support the migration of fluid from basement to overlying rock.

Keywords: basement rock, natural fracture, reservoir characterization, seismic attribute

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1523 Constructions of Linear and Robust Codes Based on Wavelet Decompositions

Authors: Alla Levina, Sergey Taranov

Abstract:

The classical approach to the providing noise immunity and integrity of information that process in computing devices and communication channels is to use linear codes. Linear codes have fast and efficient algorithms of encoding and decoding information, but this codes concentrate their detect and correct abilities in certain error configurations. To protect against any configuration of errors at predetermined probability can robust codes. This is accomplished by the use of perfect nonlinear and almost perfect nonlinear functions to calculate the code redundancy. The paper presents the error-correcting coding scheme using biorthogonal wavelet transform. Wavelet transform applied in various fields of science. Some of the wavelet applications are cleaning of signal from noise, data compression, spectral analysis of the signal components. The article suggests methods for constructing linear codes based on wavelet decomposition. For developed constructions we build generator and check matrix that contain the scaling function coefficients of wavelet. Based on linear wavelet codes we develop robust codes that provide uniform protection against all errors. In article we propose two constructions of robust code. The first class of robust code is based on multiplicative inverse in finite field. In the second robust code construction the redundancy part is a cube of information part. Also, this paper investigates the characteristics of proposed robust and linear codes.

Keywords: robust code, linear code, wavelet decomposition, scaling function, error masking probability

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1522 Removal of Aromatic Fractions of Natural Organic Matter from Synthetic Water Using Aluminium Based Electrocoagulation

Authors: Tanwi Priya, Brijesh Kumar Mishra

Abstract:

Occurrence of aromatic fractions of Natural Organic Matter (NOM) led to formation of carcinogenic disinfection by products such as trihalomethanes in chlorinated water. In the present study, the efficiency of aluminium based electrocoagulation on the removal of prominent aromatic groups such as phenol, hydrophobic auxochromes, and carboxyl groups from NOM enriched synthetic water has been evaluated using various spectral indices. The effect of electrocoagulation on turbidity has also been discussed. The variation in coagulation performance as a function of pH has been studied. Our result suggests that electrocoagulation can be considered as appropriate remediation approach to reduce trihalomethanes formation in water. It has effectively reduced hydrophobic fractions from NOM enriched low turbid water. The charge neutralization and enmeshment of dispersed colloidal particles inside metallic hydroxides is the possible mechanistic approach in electrocoagulation.

Keywords: aromatic fractions, electrocoagulation, natural organic matter, spectral indices

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1521 Power Allocation in User-Centric Cell-Free Massive Multiple-Input Multiple-Output Systems with Limited Fronthaul Capacity

Authors: Siminfar Samakoush Galougah

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In this paper, we study two power allocation problems for an uplink user-centric (UC) cell-free massive multiple-input multiple-output (CF-mMIMO) system. Besides, we assume each access point (AP) is connected to a central processing unit (CPU) via a fronthaul link with limited capacity. To efficiently use the fronthaul capacity, two strategies for transmitting signals from APs to the CPU are employed, namely, compress-forward estimate (CFE), estimate-compress-forward (ECF). The capacity of the aforementioned strategies in user-centric CF-mMIMO is drived. Then, we solved the two power allocation problems with minimum Spectral Efficiency (SE) and sum-SE maximization objectives for ECF and CFE strategies.

Keywords: cell-free massive MIMO, limited capacity fronthaul, spectral efficiency

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1520 Energy Content and Spectral Energy Representation of Wave Propagation in a Granular Chain

Authors: Rohit Shrivastava, Stefan Luding

Abstract:

A mechanical wave is propagation of vibration with transfer of energy and momentum. Studying the energy as well as spectral energy characteristics of a propagating wave through disordered granular media can assist in understanding the overall properties of wave propagation through inhomogeneous materials like soil. The study of these properties is aimed at modeling wave propagation for oil, mineral or gas exploration (seismic prospecting) or non-destructive testing for the study of internal structure of solids. The study of Energy content (Kinetic, Potential and Total Energy) of a pulse propagating through an idealized one-dimensional discrete particle system like a mass disordered granular chain can assist in understanding the energy attenuation due to disorder as a function of propagation distance. The spectral analysis of the energy signal can assist in understanding dispersion as well as attenuation due to scattering in different frequencies (scattering attenuation). The selection of one-dimensional granular chain also helps in studying only the P-wave attributes of the wave and removing the influence of shear or rotational waves. Granular chains with different mass distributions have been studied, by randomly selecting masses from normal, binary and uniform distributions and the standard deviation of the distribution is considered as the disorder parameter, higher standard deviation means higher disorder and lower standard deviation means lower disorder. For obtaining macroscopic/continuum properties, ensemble averaging has been used. Interpreting information from a Total Energy signal turned out to be much easier in comparison to displacement, velocity or acceleration signals of the wave, hence, indicating a better analysis method for wave propagation through granular materials. Increasing disorder leads to faster attenuation of the signal and decreases the Energy of higher frequency signals transmitted, but at the same time the energy of spatially localized high frequencies also increases. An ordered granular chain exhibits ballistic propagation of energy whereas, a disordered granular chain exhibits diffusive like propagation, which eventually becomes localized at long periods of time.

Keywords: discrete elements, energy attenuation, mass disorder, granular chain, spectral energy, wave propagation

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1519 MCDM Spectrum Handover Models for Cognitive Wireless Networks

Authors: Cesar Hernández, Diego Giral, Fernando Santa

Abstract:

The spectral handoff is important in cognitive wireless networks to ensure an adequate quality of service and performance for secondary user communications. This work proposes a benchmarking of performance of the three spectrum handoff models: VIKOR, SAW and MEW. Four evaluation metrics are used. These metrics are, accumulative average of failed handoffs, accumulative average of handoffs performed, accumulative average of transmission bandwidth and, accumulative average of the transmission delay. As a difference with related work, the performance of the three spectrum handoff models was validated with captured data of spectral occupancy in experiments realized at the GSM frequency band (824 MHz-849 MHz). These data represent the actual behavior of the licensed users for this wireless frequency band. The results of the comparative show that VIKOR Algorithm provides 15.8% performance improvement compared to a SAW Algorithm and, 12.1% better than the MEW Algorithm.

Keywords: cognitive radio, decision making, MEW, SAW, spectrum handoff, VIKOR

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1518 Sparse Coding Based Classification of Electrocardiography Signals Using Data-Driven Complete Dictionary Learning

Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

Abstract:

In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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1517 Discrimination Between Bacillus and Alicyclobacillus Isolates in Apple Juice by Fourier Transform Infrared Spectroscopy and Multivariate Analysis

Authors: Murada Alholy, Mengshi Lin, Omar Alhaj, Mahmoud Abugoush

Abstract:

Alicyclobacillus is a causative agent of spoilage in pasteurized and heat-treated apple juice products. Differentiating between this genus and the closely related Bacillus is crucially important. In this study, Fourier transform infrared spectroscopy (FT-IR) was used to identify and discriminate between four Alicyclobacillus strains and four Bacillus isolates inoculated individually into apple juice. Loading plots over the range of 1350 and 1700 cm-1 reflected the most distinctive biochemical features of Bacillus and Alicyclobacillus. Multivariate statistical methods (e.g. principal component analysis (PCA) and soft independent modeling of class analogy (SIMCA)) were used to analyze the spectral data. Distinctive separation of spectral samples was observed. This study demonstrates that FT-IR spectroscopy in combination with multivariate analysis could serve as a rapid and effective tool for fruit juice industry to differentiate between Bacillus and Alicyclobacillus and to distinguish between species belonging to these two genera.

Keywords: alicyclobacillus, bacillus, FT-IR, spectroscopy, PCA

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1516 Sparse Unmixing of Hyperspectral Data by Exploiting Joint-Sparsity and Rank-Deficiency

Authors: Fanqiang Kong, Chending Bian

Abstract:

In this work, we exploit two assumed properties of the abundances of the observed signatures (endmembers) in order to reconstruct the abundances from hyperspectral data. Joint-sparsity is the first property of the abundances, which assumes the adjacent pixels can be expressed as different linear combinations of same materials. The second property is rank-deficiency where the number of endmembers participating in hyperspectral data is very small compared with the dimensionality of spectral library, which means that the abundances matrix of the endmembers is a low-rank matrix. These assumptions lead to an optimization problem for the sparse unmixing model that requires minimizing a combined l2,p-norm and nuclear norm. We propose a variable splitting and augmented Lagrangian algorithm to solve the optimization problem. Experimental evaluation carried out on synthetic and real hyperspectral data shows that the proposed method outperforms the state-of-the-art algorithms with a better spectral unmixing accuracy.

Keywords: hyperspectral unmixing, joint-sparse, low-rank representation, abundance estimation

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1515 Study and Solving Partial Differential Equation of Danel Equation in the Vibration Shells

Authors: Hesamoddin Abdollahpour, Roghayeh Abdollahpour, Elham Rahgozar

Abstract:

This paper we deal with an analysis of the free vibrations of the governing partial differential equation that it is Danel equation in the shells. The problem considered represents the governing equation of the nonlinear, large amplitude free vibrations of the hinged shell. A new implementation of the new method is presented to obtain natural frequency and corresponding displacement on the shell. Our purpose is to enhance the ability to solve the mentioned complicated partial differential equation (PDE) with a simple and innovative approach. The results reveal that this new method to solve Danel equation is very effective and simple, and can be applied to other nonlinear partial differential equations. It is necessary to mention that there are some valuable advantages in this way of solving nonlinear differential equations and also most of the sets of partial differential equations can be answered in this manner which in the other methods they have not had acceptable solutions up to now. We can solve equation(s), and consequently, there is no need to utilize similarity solutions which make the solution procedure a time-consuming task.

Keywords: large amplitude, free vibrations, analytical solution, Danell Equation, diagram of phase plane

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1514 Band Characterization and Development of Hyperspectral Indices for Retrieving Chlorophyll Content

Authors: Ramandeep Kaur M. Malhi, Prashant K. Srivastava, G.Sandhya Kiran

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Quantitative estimates of foliar biochemicals, namely chlorophyll content (CC), serve as key information for the assessment of plant productivity, stress, and the availability of nutrients. This also plays a critical role in predicting the dynamic response of any vegetation to altering climate conditions. The advent of hyperspectral data with an enhanced number of available wavelengths has increased the possibility of acquiring improved information on CC. Retrieval of CC is extensively carried through well known spectral indices derived from hyperspectral data. In the present study, an attempt is made to develop hyperspectral indices by identifying optimum bands for CC estimation in Butea monosperma (Lam.) Taub growing in forests of Shoolpaneshwar Wildlife Sanctuary, Narmada district, Gujarat State, India. 196 narrow bands of EO-1 Hyperion images were screened, and the best optimum wavelength from blue, green, red, and near infrared (NIR) regions were identified based on the coefficient of determination (R²) between band reflectance and laboratory estimated CC. The identified optimum wavelengths were then employed for developing 12 hyperspectral indices. These spectral index values and CC values were then correlated to investigate the relation between laboratory measured CC and spectral indices. Band 15 of blue range and Band 22 of green range, Band 40 of the red region, and Band 79 of NIR region were found to be optimum bands for estimating CC. The optimum band based combinations on hyperspectral data proved to be the most effective indices for quantifying Butea CC with NDVI and TVI identified as the best (R² > 0.7, p < 0.01). The study demonstrated the significance of band characterization in the development of the best hyperspectral indices for the chlorophyll estimation, which can aid in monitoring the vitality of forests.

Keywords: band, characterization, chlorophyll, hyperspectral, indices

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1513 Low-Level Forced and Ambient Vibration Tests on URM Building Strengthened by Dampers

Authors: Rafik Taleb, Farid Bouriche, Mehdi Boukri, Fouad Kehila

Abstract:

The aim of the paper is to investigate the dynamic behavior of an unreinforced masonry (URM) building strengthened by DC-90 dampers by ambient and low-level forced vibration tests. Ambient and forced vibration techniques are usually applied to reinforced concrete or steel buildings to understand and identify their dynamic behavior, however, less is known about their applicability for masonry buildings. Ambient vibrations were measured before and after strengthening of the URM building by DC-90 dampers system. For forced vibration test, a series of low amplitude steady state harmonic forced vibration tests were conducted after strengthening using eccentric mass shaker. The resonant frequency curves, mode shapes and damping coefficients as well as stress distribution in the steel braces of the DC-90 dampers have been investigated and could be defined. It was shown that the dynamic behavior of the masonry building, even if not regular and with deformable floors, can be effectively represented. It can be concluded that the strengthening of the building does not change the dynamic properties of the building due to the fact of low amplitude excitation which do not activate the dampers.

Keywords: ambient vibrations, masonry buildings, forced vibrations, structural dynamic identification

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1512 Tree Species Classification Using Effective Features of Polarimetric SAR and Hyperspectral Images

Authors: Milad Vahidi, Mahmod R. Sahebi, Mehrnoosh Omati, Reza Mohammadi

Abstract:

Forest management organizations need information to perform their work effectively. Remote sensing is an effective method to acquire information from the Earth. Two datasets of remote sensing images were used to classify forested regions. Firstly, all of extractable features from hyperspectral and PolSAR images were extracted. The optical features were spectral indexes related to the chemical, water contents, structural indexes, effective bands and absorption features. Also, PolSAR features were the original data, target decomposition components, and SAR discriminators features. Secondly, the particle swarm optimization (PSO) and the genetic algorithms (GA) were applied to select optimization features. Furthermore, the support vector machine (SVM) classifier was used to classify the image. The results showed that the combination of PSO and SVM had higher overall accuracy than the other cases. This combination provided overall accuracy about 90.56%. The effective features were the spectral index, the bands in shortwave infrared (SWIR) and the visible ranges and certain PolSAR features.

Keywords: hyperspectral, PolSAR, feature selection, SVM

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1511 Real Time Acquisition and Psychoacoustic Analysis of Brain Wave

Authors: Shweta Singh, Dipali Bansal, Rashima Mahajan

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Psychoacoustics has become a potential area of research due to the growing interest of both laypersons and medical and mental health professionals. Non-invasive brain computer interface like Electroencephalography (EEG) is widely being used in this field. An attempt has been made in this paper to examine the response of EEG signals to acoustic stimuli further analysing the brain electrical activity. The real time EEG is acquired for 6 participants using a cost effective and portable EMOTIV EEG neuron headset. EEG data analysis is further done using EMOTIV test bench, EDF browser and EEGLAB (MATLAB Tool) application software platforms. Spectral analysis of acquired neural signals (AF3 channel) using these software platforms are clearly indicative of increased brain activity in various bands. The inferences drawn from such an analysis have significant correlation with subject’s subjective reporting of the experiences. The results suggest that the methodology adopted can further be used to assist patients with sleeping and depressive disorders.

Keywords: OM chant, spectral analysis, EDF browser, EEGLAB, EMOTIV, real time acquisition

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1510 Remote Sensing and GIS-Based Environmental Monitoring by Extracting Land Surface Temperature of Abbottabad, Pakistan

Authors: Malik Abid Hussain Khokhar, Muhammad Adnan Tahir, Hisham Bin Hafeez Awan

Abstract:

Continuous environmental determinism and climatic change in the entire globe due to increasing land surface temperature (LST) has become a vital phenomenon nowadays. LST is accelerating because of increasing greenhouse gases in the environment which results of melting down ice caps, ice sheets and glaciers. It has not only worse effects on vegetation and water bodies of the region but has also severe impacts on monsoon areas in the form of capricious rainfall and monsoon failure extensive precipitation. Environment can be monitored with the help of various geographic information systems (GIS) based algorithms i.e. SC (Single), DA (Dual Angle), Mao, Sobrino and SW (Split Window). Estimation of LST is very much possible from digital image processing of satellite imagery. This paper will encompass extraction of LST of Abbottabad using SW technique of GIS and Remote Sensing over last ten years by means of Landsat 7 ETM+ (Environmental Thematic Mapper) and Landsat 8 vide their Thermal Infrared (TIR Sensor) and Optical Land Imager (OLI sensor less Landsat 7 ETM+) having 100 m TIR resolution and 30 m Spectral Resolutions. These sensors have two TIR bands each; their emissivity and spectral radiance will be used as input statistics in SW algorithm for LST extraction. Emissivity will be derived from Normalized Difference Vegetation Index (NDVI) threshold methods using 2-5 bands of OLI with the help of e-cognition software, and spectral radiance will be extracted TIR Bands (Band 10-11 and Band 6 of Landsat 7 ETM+). Accuracy of results will be evaluated by weather data as well. The successive research will have a significant role for all tires of governing bodies related to climate change departments.

Keywords: environment, Landsat 8, SW Algorithm, TIR

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1509 Spatially Encoded Hyperspectral Compressive Microscope for Broadband VIS/NIR Imaging

Authors: Lukáš Klein, Karel Žídek

Abstract:

Hyperspectral imaging counts among the most frequently used multidimensional sensing methods. While there are many approaches to capturing a hyperspectral data cube, optical compression is emerging as a valuable tool to reduce the setup complexity and the amount of data storage needed. Hyperspectral compressive imagers have been created in the past; however, they have primarily focused on relatively narrow sections of the electromagnetic spectrum. A broader spectral study of samples can provide helpful information, especially for applications involving the harmonic generation and advanced material characterizations. We demonstrate a broadband hyperspectral microscope based on the single-pixel camera principle. Captured spatially encoded data are processed to reconstruct a hyperspectral cube in a combined visible and near-infrared spectrum (from 400 to 2500 nm). Hyperspectral cubes can be reconstructed with a spectral resolution of up to 3 nm and spatial resolution of up to 7 µm (subject to diffraction) with a high compressive ratio.

Keywords: compressive imaging, hyperspectral imaging, near-infrared spectrum, single-pixel camera, visible spectrum

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1508 Water Droplet Impact on Vibrating Rigid Superhydrophobic Surfaces

Authors: Jingcheng Ma, Patricia B. Weisensee, Young H. Shin, Yujin Chang, Junjiao Tian, William P. King, Nenad Miljkovic

Abstract:

Water droplet impact on surfaces is a ubiquitous phenomenon in both nature and industry. The transfer of mass, momentum and energy can be influenced by the time of contact between droplet and surface. In order to reduce the contact time, we study the influence of substrate motion prior to impact on the dynamics of droplet recoil. Using optical high speed imaging, we investigated the impact dynamics of macroscopic water droplets (~ 2mm) on rigid nanostructured superhydrophobic surfaces vibrating at 60 – 300 Hz and amplitudes of 0 – 3 mm. In addition, we studied the influence of the phase of the substrate at the moment of impact on total contact time. We demonstrate that substrate vibration can alter droplet dynamics, and decrease total contact time by as much as 50% compared to impact on stationary rigid superhydrophobic surfaces. Impact analysis revealed that the vibration frequency mainly affected the maximum contact time, while the amplitude of vibration had little direct effect on the contact time. Through mathematical modeling, we show that the oscillation amplitude influences the possibility density function of droplet impact at a given phase, and thus indirectly influences the average contact time. We also observed more vigorous droplet splashing and breakup during impact at larger amplitudes. Through semi-empirical mathematical modeling, we describe the relationship between contact time and vibration frequency, phase, and amplitude of the substrate. We also show that the maximum acceleration during the impact process is better suited as a threshold parameter for the onset of splashing than a Weber-number criterion. This study not only provides new insights into droplet impact physics on vibrating surfaces, but develops guidelines for the rational design of surfaces to achieve controllable droplet wetting in applications utilizing vibration.

Keywords: contact time, impact dynamics, oscillation, pear-shape droplet

Procedia PDF Downloads 436
1507 Effect of Single Overload Ratio and Stress Ratio on Fatigue Crack Growth

Authors: M. Benachour, N. Benachour, M. Benguediab

Abstract:

In this investigation, variation of cyclic loading effect on fatigue crack growth is studied. This study is performed on 2024 T351 and 7050-T74 aluminum alloys, used in aeronautical structures. The propagation model used in this study is NASGRO model. In constant amplitude loading (CA), the effect of stress ratio has been investigated. Fatigue life and fatigue crack growth rate were affected by this factor. Results showed an increasing in fatigue crack growth rates (FCGRs) with increasing stress ratio. Variable amplitude loading (VAL) can take many forms i.e with a single overload, overload band etc. The shape of these loads affects strongly the fracture life and FCGRs. The application of a single overload (ORL) decrease the FCGR and increase the delay crack length caused by the formation of a larger plastic zone compared to the plastic zone due without VAL. The fatigue behavior of the both material under single overload has been compared.

Keywords: fatigue crack growth, overload ratio, stress ratio, generalized willenborg model, retardation, al-alloys

Procedia PDF Downloads 341
1506 FT-NIR Method to Determine Moisture in Gluten Free Rice-Based Pasta during Drying

Authors: Navneet Singh Deora, Aastha Deswal, H. N. Mishra

Abstract:

Pasta is one of the most widely consumed food products around the world. Rapid determination of the moisture content in pasta will assist food processors to provide online quality control of pasta during large scale production. Rapid Fourier transform near-infrared method (FT-NIR) was developed for determining moisture content in pasta. A calibration set of 150 samples, a validation set of 30 samples and a prediction set of 25 samples of pasta were used. The diffuse reflection spectra of different types of pastas were measured by FT-NIR analyzer in the 4,000-12,000 cm-1 spectral range. Calibration and validation sets were designed for the conception and evaluation of the method adequacy in the range of moisture content 10 to 15 percent (w.b) of the pasta. The prediction models based on partial least squares (PLS) regression, were developed in the near-infrared. Conventional criteria such as the R2, the root mean square errors of cross validation (RMSECV), root mean square errors of estimation (RMSEE) as well as the number of PLS factors were considered for the selection of three pre-processing (vector normalization, minimum-maximum normalization and multiplicative scatter correction) methods. Spectra of pasta sample were treated with different mathematic pre-treatments before being used to build models between the spectral information and moisture content. The moisture content in pasta predicted by FT-NIR methods had very good correlation with their values determined via traditional methods (R2 = 0.983), which clearly indicated that FT-NIR methods could be used as an effective tool for rapid determination of moisture content in pasta. The best calibration model was developed with min-max normalization (MMN) spectral pre-processing (R2 = 0.9775). The MMN pre-processing method was found most suitable and the maximum coefficient of determination (R2) value of 0.9875 was obtained for the calibration model developed.

Keywords: FT-NIR, pasta, moisture determination, food engineering

Procedia PDF Downloads 236
1505 Exploring the Development of Communicative Skills in English Teaching Students: A Phenomenological Study During Online Instruction

Authors: Estephanie S. López Contreras, Vicente Aranda Palacios, Daniela Flores Silva, Felipe Oliveros Olivares, Romina Riquelme Escobedo, Iñaki Westerhout Usabiaga

Abstract:

This research explored whether the context of online instruction has influenced the development of first-year English-teaching students' communication skills, being these speaking and listening. The theoretical basis finds its niche in the need to bridge the gap in knowledge about the Chilean online educational context and the development of English communicative skills. An interpretative paradigm and a phenomenological design were implemented in this study. Twenty- two first-year students and two teachers from an English teaching training program participated in the study. The students' ages ranged from 18 to 26 years of age, and the teachers' years of experience ranged from 5 to 13 years in the program. For data collection purposes, semi- structured interviews were applied to both students and teachers. Interview questions were based on the initial conceptualization of the central phenomenon. Observations, field notes, and focus groups with the students are also part of the data collection process. Data analysis considered two-cycle methods. The first included descriptive coding for field notes, initial coding for interviews, and creating a codebook. The second cycle included axial coding for both field notes and interviews. After data analysis, the findings show that students perceived online classes as instances in which active communication cannot always occur. In addition, changes made to the curricula as a consequence of the COVID-19 pandemic have affected students' speaking and listening skills.

Keywords: attitudes, communicative skills, EFL teaching training program, online instruction, and perceptions

Procedia PDF Downloads 94
1504 Spectral Mapping of Hydrothermal Alteration Minerals for Geothermal Exploration Using Advanced Spaceborne Thermal Emission and Reflection Radiometer Short Wave Infrared Data

Authors: Aliyu J. Abubakar, Mazlan Hashim, Amin B. Pour

Abstract:

Exploiting geothermal resources for either power, home heating, Spa, greenhouses, industrial or tourism requires an initial identification of suitable areas. This can be done cost-effectively using remote sensing satellite imagery which has synoptic capabilities of covering large areas in real time and by identifying possible areas of hydrothermal alteration and minerals related to Geothermal systems. Earth features and minerals are known to have unique diagnostic spectral reflectance characteristics that can be used to discriminate them. The focus of this paper is to investigate the applicability of mapping hydrothermal alteration in relation to geothermal systems (thermal springs) at Yankari Park Northeastern Nigeria, using Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) satellite data for resource exploration. The ASTER Short Wave Infrared (SWIR) bands are used to highlight and discriminate alteration areas by employing sophisticated digital image processing techniques including image transformations and spectral mapping methods. Field verifications are conducted at the Yankari Park using hand held Global Positioning System (GPS) monterra to identify locations of hydrothermal alteration and rock samples obtained at the vicinity and surrounding areas of the ‘Mawulgo’ and ‘Wikki’ thermal springs. X-Ray Diffraction (XRD) results of rock samples obtained from the field validated hydrothermal alteration by the presence of indicator minerals including; Dickite, Kaolinite, Hematite and Quart. The study indicated the applicability of mapping geothermal anomalies for resource exploration in unmapped sparsely vegetated savanna environment characterized by subtle surface manifestations such as thermal springs. The results could have implication for geothermal resource exploration especially at the prefeasibility stages by narrowing targets for comprehensive surveys and in unexplored savanna regions where expensive airborne surveys are unaffordable.

Keywords: geothermal exploration, image enhancement, minerals, spectral mapping

Procedia PDF Downloads 340
1503 Using New Machine Algorithms to Classify Iranian Musical Instruments According to Temporal, Spectral and Coefficient Features

Authors: Ronak Khosravi, Mahmood Abbasi Layegh, Siamak Haghipour, Avin Esmaili

Abstract:

In this paper, a study on classification of musical woodwind instruments using a small set of features selected from a broad range of extracted ones by the sequential forward selection method was carried out. Firstly, we extract 42 features for each record in the music database of 402 sound files belonging to five different groups of Flutes (end blown and internal duct), Single –reed, Double –reed (exposed and capped), Triple reed and Quadruple reed. Then, the sequential forward selection method is adopted to choose the best feature set in order to achieve very high classification accuracy. Two different classification techniques of support vector machines and relevance vector machines have been tested out and an accuracy of up to 96% can be achieved by using 21 time, frequency and coefficient features and relevance vector machine with the Gaussian kernel function.

Keywords: coefficient features, relevance vector machines, spectral features, support vector machines, temporal features

Procedia PDF Downloads 293
1502 Evaluation of P300 and CNV Changes in Patients with Essential Tremor

Authors: Sehur Sibel Ozkaynak, Zakir Koc, Ebru Barcın

Abstract:

Essential tremor (ET) is one of the most common movement disorders and has long been considered a monosymptomatic disorder. While ET has traditionally been categorized as a pure motor disease, cross-sectional and longitudinal studies of cognition in ET have been demonstrated that these patients may have cognitive dysfunction. We investigated the neuro physiological aspects of cognition in ET, using event-related potentials (ERPs).Twenty patients with ET and 20 age-education and sex matched healthy controls underwent a neuro physiological evaluation. P300 components and Contingent Negative Variation (CNV) were recorded. The latencies and amplitudes of the P300 and CNV were evaluated. P200-N200 amplitude was significantly smaller in the ET group, while no differences emerged between patients and controls in P300 latencies. CNV amplitude was significantly smaller at Cz electrode site in the ET group. No differences were observed between in the two groups in CNV latencies. As a result, P300 and CNV parameters did not show significant differences between in the two groups, does not mean that there aren't mild cognitive changes in ET patients. In this regard, there is a need to further studies using electro physiological tests related to cognitive changes in ET patients.

Keywords: cognition, essential tremor, event related potentials

Procedia PDF Downloads 259