scholarly journals Singer Identification using Autocorrelation Method

2020 ◽  
Vol 9 (4) ◽  
pp. 134-138
Keyword(s):  
Data Set ◽  
Identification Test ◽  
Bartlett Test ◽  
Human Emotions ◽  
Autocorrelation Method ◽  
Singer Identification

songs are the compositions embedding voice and different instrument’s sound. Different human emotions can be created by playing the appropriate song .autocorrelation algorithm is used here to find out singer identification. In the first experiment three singers with three hindi songs (vocal) are taken as data set. Tempo is used as musical features. Then autocorrelation is proposed on concerning a total of three singers. Using bartlett test we have found the most significant autocorrelation values of those songs of three singers. In second experiment three singers with one hindi song (vocal) are taken as data set. Here rms is used as musical features. Then autocorrelation is proposed on concerning those three singers. Using bartlett test we have found the insignificant autocorrelation values of the song of three singers. The first experiment is used to identify the singers for each song. Here three singers identify their own identification test giving most significant values of their songs .the second experiment gives the insignificant value. The insignificance values of musical features of three singers does not give the singer’s identification test

scholarly journals Sentiment Analysis of the Syrian Conflict on Twitter

2021 ◽  
Vol 11 (22) ◽  
pp. 46-61
Author(s):  
Danijela Lucić ◽  
Josip Katalinić ◽  
Tomislav Dokman
Keyword(s):  
Social Networks ◽  
Social Media ◽  
Sentiment Analysis ◽  
Data Set ◽  
Political Landscape ◽  
Important Means ◽  
Human Emotions ◽  
Syrian Conflict

Social media have become an important means of imposing ideas and interests in social‏ conflicts. The Syrian conflict is analysed using sentiment analysis of tweets in order to establish how the‏ sentiment shapes the modern political landscape and influences recipient knowledge. The importance of‏ social networks and their potential in overthrowing regimes as well as in radicalization are highlighted.‏ The authors suggest several stages that can be used for analysing tweets and how they impact the reader‏ with selected narration. Sentiment analysis is used on a trained data set as a way to gain insight into‏ tweets of different factions in the Syria conflict. Selected tweets on missile strikes were published on 14‏ April 2018 and the day after. The Twitter profiles of three different sides – pro-Assad, pro-West and anti-‏ Assad – were also analysed. The results show that there is a real battle on social media with the purpose‏ of influencing human emotions.

scholarly journals Identification of Nonlinear Vibrating Structures: Part II—Applications

1987 ◽  
Vol 54 (4) ◽  
pp. 923-929 ◽  
Author(s):  
S. F. Masri ◽  
R. K. Miller ◽  
A. F. Saud ◽  
T. K. Caughey
Keyword(s):  
Structural Characteristics ◽  
Companion Paper ◽  
Dynamic Loads ◽  
High Fidelity ◽  
Data Set ◽  
Reduced Order ◽  
Vibrating Structures ◽  
Convenient Means ◽  
Calibration Problem ◽  
Identification Test

A time-domain procedure for the identification of nonlinear vibrating structures, presented in a companion paper, is applied to a “calibration” problem which incorporates realistic test situations and nonlinear structural characteristics widely encountered in the applied mechanics field. The “data” set is analyzed to develop suitable, approximate nonlinear system representations. Subsequently, a “validation” test is conducted to demonstrate the range of validity of the method under discussion. It is shown that the procedure furnishes a convenient means for constructing reduced-order nonlinear nonparametric mathematical models of reasonably high fidelity in regard to reproducing the response of the test article under dynamic loads that differ from the identification test loads.

scholarly journals A Comprehensive Review for Emotion Detection Based on EEG Signals: Challenges, Applications, and Open Issues

2021 ◽  
Vol 38 (4) ◽  
pp. 1189-1200
Author(s):  
Awf Abdulrahman ◽  
Muhammet Baykara
Keyword(s):  
Data Sets ◽  
Emotion Detection ◽  
Emotion Classification ◽  
Eeg Signals ◽  
Data Set ◽  
The Past ◽  
Human Emotions ◽  
Tone Of Voice ◽  
Electroencephalogram Eeg ◽  
Open Issues

Emotion classification based on physiological signals has become a hot topic in the past decade. Many studies have attempted to classify emotions using various techniques, to discover human emotions accurately. This study focused on listing the most recent studies that have classified emotions based on electroencephalogram (EEG) signals. This study also focused on solving the problems and challenges facing researchers in emotion classification and EEG applications used in several fields. The plan of this study is based on a strategy with three aspects within specific rules: The first aspect is the methods; we chose studies that included new methods to extract features. The second aspect is the data sets. We tried to choose a study that classified the same data set. The third aspect is applications; we have listed many applications of the EEG in several areas. We concluded from this study that detecting human emotions using the EEG signals is one of the most reliable and widely used methods of detecting emotions in the past few years. Also, we have noticed that the EEG can detect human emotions, especially in psychiatry, for example, for epileptic patients whose emotions cannot be extracted using traditional methods such as facial expressions and tone of voice.

scholarly journals The Mediating Role of Cognitive Flexibility in the Effect of Empathic Tendency on Teacher Professionalism

2021 ◽  
Vol 8 (1) ◽  
pp. 124-134
Author(s):  
ZÜLBIYE KAÇAY
Keyword(s):  
Physical Education ◽  
Cognitive Flexibility ◽  
Structural Equation ◽  
Personal Information ◽  
Equation Model ◽  
Teacher Professionalism ◽  
Data Set ◽  
Mediating Role ◽  
Normality Test ◽  
Bartlett Test

The aim of the study was to determine whether cognitive flexibility had a mediating role in the effect of empathic tendencies of physical education and sports teachers on their professionalism. Empathic Tendency, Teacher Professionalism and Cognitive Flexibility Scales were used in the study with personal information form. A total of 283 physical education and sports teachers, 85 (30%) female and 198 (70%) male, voluntarily participated in the study. In the analysis of data, The Shapiro-Wilk normality test was used to determine if data set had a normal distribution or not.  Kaiser-Mayer-Olkin (KMO) coefficient and Bartlett test were used to determine the suitability of the data for factor analysis. The theoretically created model was tested with a structural equation model. In the study, descriptive statistics were used in order to determine the average scores obtained from the scales. AMOS and SPSS package programs were used for analysis of data set. It was determined that the participants' Empathic Tendency, Professionalism and Cognitive Flexibility levels were high. Also, all variables were determined to had a significant correlation between each other. It was determined that all variables positively affected each other, empathic tendency predicted both cognitive flexibility and teacher professionalism at certain rates (40%-28%), and cognitive flexibility had a mediating role in the relationship between empathic tendency and teacher professionalism. As a result, multifaceted and effective studies that will increase the empathic tendency and cognitive flexibility levels should be carried out.

Statistical Approaches to Estimating the Relative Contribution of Intermolecular Interactions in Aliphatic Alcohols: Application to QSPR/QSAR Modeling of Their Boiling Points

2009 ◽  
Vol 4 (1) ◽  
Author(s):  
Mohamed Nohair ◽  
Noura Mallouk ◽  
Marouane Benmarzouk ◽  
El Morrakchi Mohssine
Keyword(s):  
Boiling Point ◽  
Intermolecular Forces ◽  
Aliphatic Alcohols ◽  
General Description ◽  
Back Propagation Algorithm ◽  
Qsar Modeling ◽  
Data Set ◽  
Relative Contribution ◽  
Boiling Points ◽  
Autocorrelation Method

A three-layer feed forward neural network trained with a Levenberg–Marquardt batch error back propagation algorithm has been used to model the strong relationships between the boiling point of aliphatic alcohols and intermolecular forces consisting both in Van Der Waals forces and polar interactions, respectively. For that purpose, we use the multifunctional autocorrelation method to provide an appropriate topological description. Two types of descriptors are generated: the first is commonly used in QSARs and QSPRs modelling, it gives a general description of the whole of the molecule; the second is attributed to the local description of the group hydroxyl. In this we have turned our interests to the explanatory capacities of our methodology to explore the relative contribution and/or the contribution profile of the input factors compared to the size of the molecule. The initial data set is divided into different subsets in increasing order of values of boiling point. Then, we explore the good descriptive ability of the molecular descriptors calculated solely from the modified autocorrelation method to carry out a variable analysis and give information about features of the compounds responsible for their boiling points. This is made possible by comparing the regression coefficients for the established linear model, and by using the Garson weight portioning method for the ANN analysis.

Rotational Characteristics of the Green Solar Corona: 1947-1991

1994 ◽  
Vol 144 ◽  
pp. 139-141 ◽  
Author(s):  
J. Rybák ◽  
V. Rušin ◽  
M. Rybanský
Keyword(s):  
Solar Corona ◽  
World Wide ◽  
Rotation Period ◽  
Original Data ◽  
Coronal Emission ◽  
Time Intervals ◽  
Data Set ◽  
The World ◽  
Coronal Emission Line ◽  
Homogeneous Data

AbstractFe XIV 530.3 nm coronal emission line observations have been used for the estimation of the green solar corona rotation. A homogeneous data set, created from measurements of the world-wide coronagraphic network, has been examined with a help of correlation analysis to reveal the averaged synodic rotation period as a function of latitude and time over the epoch from 1947 to 1991.The values of the synodic rotation period obtained for this epoch for the whole range of latitudes and a latitude band ±30° are 27.52±0.12 days and 26.95±0.21 days, resp. A differential rotation of green solar corona, with local period maxima around ±60° and minimum of the rotation period at the equator, was confirmed. No clear cyclic variation of the rotation has been found for examinated epoch but some monotonic trends for some time intervals are presented.A detailed investigation of the original data and their correlation functions has shown that an existence of sufficiently reliable tracers is not evident for the whole set of examinated data. This should be taken into account in future more precise estimations of the green corona rotation period.

Difference Fourier Analysis of Glucose Embedded and Frozen Hydrated Purple Membrane

1982 ◽  
Vol 40 ◽  
pp. 74-75
Author(s):  
Jules S. Jaffe ◽  
Robert M. Glaeser
Keyword(s):  
Purple Membrane ◽  
Data Set ◽  
High Resolution Data ◽  
X Ray ◽  
X Ray Crystallography ◽  
Fourier Techniques ◽  
Versus Protein ◽  
The Difference ◽  
Difference Fourier ◽  
Ideal Method

Although difference Fourier techniques are standard in X-ray crystallography it has only been very recently that electron crystallographers have been able to take advantage of this method. We have combined a high resolution data set for frozen glucose embedded Purple Membrane (PM) with a data set collected from PM prepared in the frozen hydrated state in order to visualize any differences in structure due to the different methods of preparation. The increased contrast between protein-ice versus protein-glucose may prove to be an advantage of the frozen hydrated technique for visualizing those parts of bacteriorhodopsin that are embedded in glucose. In addition, surface groups of the protein may be disordered in glucose and ordered in the frozen state. The sensitivity of the difference Fourier technique to small changes in structure provides an ideal method for testing this hypothesis.

Algorithms for automated montage synthesis of images from laser-scanning confocal microscopes

1995 ◽  
Vol 53 ◽  
pp. 650-651
Author(s):  
D. E. Becker
Keyword(s):  
Image Analysis ◽  
High Resolution ◽  
Laser Scanning ◽  
Cell Counting ◽  
Wide Area ◽  
Data Set ◽  
Computational Synthesis ◽  
Automated Cell Counting ◽  
Partial View ◽  
The Individual

An efficient, robust, and widely-applicable technique is presented for computational synthesis of high-resolution, wide-area images of a specimen from a series of overlapping partial views. This technique can also be used to combine the results of various forms of image analysis, such as segmentation, automated cell counting, deblurring, and neuron tracing, to generate representations that are equivalent to processing the large wide-area image, rather than the individual partial views. This can be a first step towards quantitation of the higher-level tissue architecture. The computational approach overcomes mechanical limitations, such as hysterisis and backlash, of microscope stages. It also automates a procedure that is currently done manually. One application is the high-resolution visualization and/or quantitation of large batches of specimens that are much wider than the field of view of the microscope.The automated montage synthesis begins by computing a concise set of landmark points for each partial view. The type of landmarks used can vary greatly depending on the images of interest. In many cases, image analysis performed on each data set can provide useful landmarks. Even when no such “natural” landmarks are available, image processing can often provide useful landmarks.

Merging of electron-diffraction intensities acquired with a slow-scan CCD camera of crotoxin complex crystals to 3.5Å resolution

1994 ◽  
Vol 52 ◽  
pp. 104-105
Author(s):  
Jaap Brink ◽  
Wah Chiu
Keyword(s):  
Electron Diffraction ◽  
Ccd Camera ◽  
Crystal Thickness ◽  
Local Contrast ◽  
Camera Model ◽  
Data Set ◽  
3 Dimensional ◽  
Diffraction Mode ◽  
Diffraction Patterns ◽  
Complex Crystals

Crotoxin complex is the principal neurotoxin of the South American rattlesnake, Crotalus durissus terrificus and has a molecular weight of 24 kDa. The protein is a heterodimer with subunit A assigneda chaperone function. Subunit B carries the lethal activity, which is exerted on both sides ofthe neuro-muscular junction, and which is thought to involve binding to the acetylcholine receptor. Insight in crotoxin complex’ mode of action can be gained from a 3 Å resolution structure obtained by electron crystallography. This abstract communicates our progress in merging the electron diffraction amplitudes into a 3-dimensional (3D) intensity data set close to completion. Since the thickness of crotoxin complex crystals varies from one crystal to the other, we chose to collect tilt series of electron diffraction patterns after determining their thickness. Furthermore, by making use of the symmetry present in these tilt data, intensities collected only from similar crystals will be merged.Suitable crystals of glucose-embedded crotoxin complex were searched for in the defocussed diffraction mode with the goniometer tilted to 55° of higher in a JEOL4000 electron cryo-microscopc operated at 400 kV with the crystals kept at -120°C in a Gatan 626 cryo-holder. The crystal thickness was measured using the local contrast of the crystal relative to the supporting film from search-mode images acquired using a 1024 x 1024 slow-scan CCD camera (model 679, Gatan Inc.).

Three-dimensional image analysis and visualization in confocal light microscopy

1993 ◽  
Vol 51 ◽  
pp. 158-159
Author(s):  
J. K. Samarabandu ◽  
R. Acharya ◽  
D. R. Pareddy ◽  
P. C. Cheng
Keyword(s):  
Depth Perception ◽  
Computer Graphic ◽  
Three Dimensional ◽  
Cellular Organization ◽  
Data Set ◽  
Computational Burden ◽  
Interactive Operation ◽  
Cell Organization ◽  
Confocal Images ◽  
3D Digitization

In the study of cell organization in a maize meristem, direct viewing of confocal optical sections in 3D (by means of 3D projection of the volumetric data set, Figure 1) becomes very difficult and confusing because of the large number of nucleus involved. Numerical description of the cellular organization (e.g. position, size and orientation of each structure) and computer graphic presentation are some of the solutions to effectively study the structure of such a complex system. An attempt at data-reduction by means of manually contouring cell nucleus in 3D was reported (Summers et al., 1990). Apart from being labour intensive, this 3D digitization technique suffers from the inaccuracies of manual 3D tracing related to the depth perception of the operator. However, it does demonstrate that reducing stack of confocal images to a 3D graphic representation helps to visualize and analyze complex tissues (Figure 2). This procedure also significantly reduce computational burden in an interactive operation.

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