The fundamental frequency plays a significant part in understanding and perceiving the pitch of a sound. The pitch is a fundamental attribute employed in numerous speech-related works. For fundamental frequency extraction, several algorithms have been developed which one to use relies on the signal's characteristics and the surrounding noise. Thus, the algorithm's noise resistance becomes more critical than ever for precise fundamental frequency estimation. Nonetheless, numerous state-of-the-art algorithms face struggles in achieving satisfying outcomes when confronted with speech recordings that are noisy with low signal-to-noise ratio (SNR) values. Also, most of the recent techniques utilize different frame lengths for pitch extraction. From this point of view, This research considers different frame lengths on male and female speech signals for fundamental frequency extraction. Also, analyze the frame length dependency on the speech signal analytically to understand which frame length is more suitable and effective for male and female speech signals specifically. For the validation of our idea, we have utilized the conventional autocorrelation function (ACF), and state-of-the-art method BaNa. This study puts out a potent idea that will work better for speech processing applications in noisy speech. From experimental results, the proposed idea represents which frame length is more appropriate for male and female speech signals in noisy environments.
Rolling element bearings are commonly used in rotary mechanical and electrical equipment. According to investigation, more than half of rotating machinery defects are related to bearing faults. However, reliable bearing fault detection still remains a challenging task, especially in industrial applications. The objective of this work is to propose an adaptive variational mode decomposition (AVMD) technique for non-stationary signal analysis and bearing fault detection. The AVMD includes several steps in processing: 1) Signal characteristics are analyzed to determine the signal center frequency and the related parameters. 2) The ensemble-kurtosis index is suggested to decompose the target signal and select the most representative intrinsic mode functions (IMFs). 3) The envelope spectrum analysis is performed using the selected IMFs to identify the characteristic features for bearing fault detection. The effectiveness of the proposed AVMD technique is examined by experimental tests under different bearing conditions, with the comparison of other related bearing fault techniques.
The caprice for the study came from an indigenous designed instructional board for teaching learners in nursery/primary schools (2 - 10 years) and the task whose overall topic is the reminiscence, retention of visuals aid use in the pedagogy. The study is to appraise the opinion of toddlers/teachers about the helpfulness of 3D-visuals (ergonomic board); the clarity of the intended functions of the 3D-visuals in the toddler’s lessons instruction and support from the producers in using them; and why visuals (conventional visual aids) in schoolroom instruction are misjudged/misinterpreted; their view about the functions in specific (conventional visuals) for the instruction pedagogy; and other sources of visuals provided other than the lesson’s instruction. Four nursery/primary schools participated in the study. Seventy-two (72) toddler’s/teachers participated in the study. The study examined using quantitative and qualitative approach for statistical analysis (using pie-chart and histogram). The findings suggested that the aspects of visuals items selected for comment and description are to some extent circumscribed by toddler’s learners’ linguistic resources. Understandably, the point made by researchers referred that visuals often fail to support learning as effectively as they might because they are not regarded as a full-fledged information mode that requires the same careful processing as verbal text, is borne out by the findings. Recommendation, the accountability is above all on producers of kid’s instructional materials: authors, editors, designers and illustrators of the materials. The implication of this is that toddlers’ instructional materials should, as in the case of illustrated books include both an overt explanation of the overall philosophy toward visuals and overview of their use.
The study of the morphology of White Blood Cells (WBCs) further contributes to the clinical diagnosis of blood diseases. In this research paper, we come up with an image segmentation enhancement by combining Fourier Fast Transform on smear blood capture and classical thresholding. The Fast Fourier Transform (FFT) is a very powerful tool in image processing and it was used to segment and extract the WBCs. Our image processing method uses a Fast Fourier Transform combined with filtering and an Inverse Fast Fourier Transform for the extraction and visualization of the high frequency region of the image. In order to remove residual Red Blood Cells acting as noise in the expected result, a final thresholding step is added at the end of the processing. The results presented in this article report the tests performed using our mathematical implementation. Moreover, we were able to detect and differentiate the sub-families of WBCs.
The adopters of IoT face challenges with the surging Internet-based attacks on their IoT assets and inefficiencies within the technology. Unfortunately, IoT is overly distributed, still evolving and facing implementation and security challenges. Given the above scenario, we argue that the IoT network should always be decentralized design, and security should be built by design. The paper is the design and construction of a decentralized IoT security framework, with the goal of making emerging IoT systems more resilient to attacks and supporting complex communication and resource sharing. The framework improves efficiency and scalability in IoT, exposes vulnerable subsystems and components as possible weak links to system compromise, and meets the requirements of a heterogeneous computing environment. Other features of the framework including efficient resource sharing, fault tolerance, and distributed storage support the Internet of Things. We discuss the design requirements and carry out the implementation of Proof of Concept and evaluation of our framework. Two underlying technologies: the actor model and the blockchain were used for the implementation. Our reason for choosing the actor model and blockchain is to compare its suitability for IoT integration in parallel. Hence, evaluation of the system is performed based on computational and memory efficiency, security, and scalability. We conclude from the evaluations that the actorbased implementation has better scalability than the block-chain-based implementation. Also, the blockchain seems to be computationally more intensive than the actors and less suitable for IoT systems.
The National Institute of Standards and Technology (NIST) document is a list of fifteen tests for estimating the probability of signal randomness degree. Test number six in the NIST document is the Discrete Fourier Transform (DFT) test suitable for stationary incoming sequences. But, for cases where the input sequence is not stationary, the DFT test provides inaccurate results. For these cases, test number seven and eight (the Non-overlapping Template Matching Test and the Overlapping Template Matching Test) of the NIST document were designed to classify those non-stationary sequences. But, even with test number seven and eight of the NIST document, the results are not always accurate. Thus, the NIST test does not give a proper answer for the non-stationary input sequence case. In this paper, we offer a new algorithm or test, which may replace the NIST tests number six, seven and eight. The proposed test is applicable also for non-stationary sequences and supplies more accurate results than the existing tests (NIST tests number six, seven and eight), for non-stationary sequences. The new proposed test is based on the Wigner function and on the Generalized Gaussian Distribution (GGD). In addition, this new proposed algorithm alarms and indicates on suspicious places of cyclic sections in the tested sequence. Thus, it gives us the option to repair or to remove the suspicious places of cyclic sections (this part is beyond the scope of this paper), so that after that, the repaired or the shortened sequence (original sequence with removed sections) will result as a sequence with high probability of random degree.
In a context marked by the proliferation of smartphones and multimedia applications, the processing and transmission of images have become a real problem. Image compression is the first approach to address this problem, it nevertheless suffers from its inability to adapt to the dynamics of limited environments, consisting mainly of mobile equipment and wireless networks. In this work, we propose a stochastic model to gradually estimate an image upon information on its pixels that are transmitted progressively. We consider this transmission as a dynamical process, where the sender pushes the data in decreasing significance order. In order to adapt to network conditions and performances, instead of truncating the pixels, we suggest a new method called Fast Reconstruction Method by Kalman Filtering (FRM-KF) consisting of recursive inference of the not yet received layers belonging to a sequence of bitplanes. After empirical analysis, we estimate parameters of our model which is a linear discrete Kalman Filter. We assume the initial law of information to be the uniform distribution on the set [0, 255] corresponding to the range of gray levels. The performances of FRM-KF method have been evaluated in terms of the ratios in the quality of data image/size sent and in the quality of image/time required for treatment. A high quality was reached faster with relatively small data (less than 10% of image data is needed to obtain up to the sixth-quality image). The time for treatment also decreases faster with number of received layers. However, we found that the time of image treatment might be large starting from a image resolution of 1024 * 1024. Hence, we recommend FRM-KF method for resolutions less or equal to How to cite this paper: Saoungoumi-Sourpele, R., Nlong, J.M., Fotsa-Mbogne, D.J., Kamdjoug, J.-R.K. and Bitjoka, L. (2021) Full Image Inference Conditionally upon Available Pieces Transmitted into Limited Resources Context. Journal of Signal and Information Processing, 12, 57-69. https://doi.org/10.4236/jsip.2021.123003 Received: April 25, 2021 Accepted: July 3, 2021 Published: July 6, 2021 Copyright © 2021 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution-NonCommercial International License (CC BY-NC 4.0). http://creativecommons.org/licenses/by-nc/4.0/ Open Access R. Saoungoumi-Sourpele et al. DOI: 10.4236/jsip.2021.123003 58 Journal of Signal and Information Processing 512 * 512. A statistical comparative analysis reveals that FRM-KF is competitive and suitable to be implemented on limited resource environments.
The presence of bearing faults reduces the efficiency of rotating machines and thus increases energy consumption or even the total stoppage of the machine.It becomes essential to correctly diagnose the fault caused by the bearing.Hence the importance of determining an effective features extraction method that best describes the fault.The vision of this paper is to merge the features selection methods in order to define the most relevant featuresin the texture of the vibration signal images.In this study, the Gray Level Co-occurrence Matrix (GLCM) in texture analysis is applied on the vibration signal represented in images.Features selection based on the merge of PCA (Principal component Analysis) method and SFE (Sequential Features Extraction) method is done to obtain the most relevant features.The multiclass-Naïve Bayesclassifier is used to test the proposed approach.The success rate of this classification is 98.27%.The relevant features obtained give promising results and are more efficient than the methods observed in the literature.
Edge detection is an important aspect to improve image edge quality in image processing. The purpose of edge detection is to identify the points in digital images with great brightness variation. However, the accuracy of traditional edge detection methods in edge extraction is low. For the actual image, the grey edge is sometimes not very clear, the image also contains noise. The detection result of the traditional Sobel operator is relatively accurate, but the detection result is rough and sensitive to noise. To solve the above problems, this paper proposes an improved eight-direction Sobel operator based on grey relevancy degree, which combines 5 × 5 Sobel operator with a grey relational degree and a new eight-direction grey relevancy method. The results show that this method can detect the useful information of edge more accurately and improve the anti-noise performance. However, the drawback is that the algorithm is not automatic.
A new Modified Discrete Wavelets Packets Transform (MDWPT) based method for the compression of Surface EMG signal (s-EMG) data is presented. A Modified Discrete Wavelets Packets Transform (MDWPT) is applied to the digitized s-EMG signal. A Discrete Cosine Transforms (DCT) is applied to the MDWPT coefficients (only on detail coefficients). The MDWPT+ DCT coefficients are quantized with a Uniform Scalar Dead-Zone Quantizer (USDZQ). An arithmetic coder is employed for the entropy coding of symbol streams. The proposed approach was tested on more than 35 actuals S-EMG signals divided into three categories. The proposed approach was evaluated by the following parameters: Compression Factor (CF), Signal to Noise Ratio (SNR), Percent Root mean square Difference (PRD), Mean Frequency Distortion (MFD) and the Mean Square Error (MSE). Simulation results show that the proposed coding algorithm outperforms some recently developed s-EMG compression algorithms.
Local Binary Patterns (LBPs) have been highly used in texture classification for their robustness, their ease of implementation and their low computational cost. Initially designed to deal with gray level images, several methods based on them in the literature have been proposed for images having more than one spectral band. To achieve it, whether assumption using color information or combining spectral band two by two was done. Those methods use micro structures as texture features. In this paper, our goal was to design texture features which are relevant to color and multicomponent texture analysis without any assumption. Based on methods designed for gray scale images, we find the combination of micro and macro structures efficient for multispectral texture analysis. The experimentations were carried out on color images from Outex databases and multicomponent images from red blood cells captured using a multispectral microscope equipped with 13 LEDs ranging from 375 nm to 940 nm. In all achieved experimentations, our proposal presents the best classification scores compared to common multicomponent LBP methods. 99.81%, 100.00%, 99.07% and 97.67% are maximum scores obtained with our strategy respectively applied to images subject to rotation, blur, illumination variation and the multicomponent ones.
In order to study the strength of the composite material plate problems, need to adopt a nondestructive testing method to obtain the specimen surface under the effect of high-speed impact regularity of shape.The projection profilometry was used to measure the surface profile or the full field deformation.Furtherly, by using the Fourier transform algorithm, there is only one frame of captured image which is needed in the measurement, so that it can be introduced into the high speed impaction procedure measurement.An experimental system, which was contained with an impact setup and the projection profilometry measurement part, was constructed for the impaction action characteristic research.The metallic impact object can be launched by a gas gun or a spin fan, respectively.The detected object is manufactured by composite materials.In order to increase the surface deformation measurement accuracy, the calibration method and the error was discussed with different calibration specimen.And then, the proposed profilometry measurement method is proved by the gas gun and spin fan projectile test.The surface deformation of the manufactured composite plates and fan case are measured in the impaction procedure.So that the impact action details can be described much more clearly than the traditional video monitoring method.
