Princy Yadav, Department of Mathematics, Chandigarh University, Mohali, Punjab
Various research fields require different sampling techniques for conducting the research efficiently. It is very essential to choose the adequate technique of sampling. This paper gives an idea on different sampling techniques and their importance in different fields. In this paper, we discuss sampling and various types of sampling techniques. We go through two types of sampling techniques i.e., probability and non- probability sampling techniques. We study their subcategories. Further, we discuss the pros and cons of these techniques. Discussing different sampling techniques and their pros and cons will give the reader better understanding of the sampling techniques. It will help the reader to choose the right sampling technique for particular research. Choosing the correct sampling technique is very important for research. If a researcher knows well about different sampling techniques, he can choose adequate sampling technique for his research work. The aim of the study is fulfilled when a researcher understands which sampling technique is good for his research.
Population, Sampling, Sampling Techniques, Probability Sampling, Non-Probability Sampling.
Rajah Iyer,Microsoft, Redmund, Seattle, USA, R&D
We present herein a new approach to the Continuum hypothesis CH. We will establish a technique for forming a subset K of R, further to this, we will extend the logical premise of Cantor’s Diagonal Argument to devise a means by which the cardinality of K is established between (N,R) respectively.
Diagonal Argument, Continuum Hypothesis CH, Resolution to CH
Jagat Chaitanya Prabhala, Dr. Venkatnareshbabu K, Dr. Ragoju Ravi, Department of Applied Sciences, National Institute of Technology, Goa, India
In this research, we propose a novel approach for speaker diarization, which is the process of determining who spoke when in an audio or video recording that contains unknown amount of speech from unknown speakers and unknown number of speakers. Speaker diarization has several applications in the field of speech processing and is often used as a pre-processing step. However, traditional supervised and unsupervised algorithms for speaker diarization have limitations, such as the high cost of providing exhaustive labeling for training datasets in the case of supervised learning and compromised accuracy when using unsupervised approaches.
To address these limitations, we propose a method that utilizes x-vector embedding, abstract similarity metrics, and a combination of graph theory, matrix algebra, and genetic algorithm. We also introduce the concept of loosely labeled data and demonstrate how our approach effectively clusters temporal segments into unique user segments for speaker diarization.
We evaluate the performance of our proposed algorithm on audio recordings in English, Spanish, and Chinese and compare it with well-known similarity metrics. Our results demonstrate that our approach effectively optimizes the speaker diarization process and outperforms traditional methods. This research has significant implications for various applications in speech processing and has the potential to improve the performance of other related tasks.
signal processing, speaker diarization, discrete optimization, neural networks
Bradford Hansen-Smith, USA
To introduce folding circles at the same time we are drawing pictures and making symbols of them is one thing we can do to enlarge our approach to math and science. It brings 2-D and 3-D together through the movement of folding the circle that is not predictable by either one of them. If it were so, we would already be doing it.
geometry, folding circles, symmetry, unity
Dr SANGOUARD Patrick, France
This theoretical work corresponds to the hope of extracting, without contradicting EMMY NOETHER's theorem, an energy present throughout the universe: that of the spatial quantum vacuum! This article shows that it should be theoretically possible to maintain a continuous periodic vibration of a piezoelectric structure, which generates current peaks during a fraction of the vibration period. Electronics without any power supply, then transform these alternating current signals into a usable direct voltage. To manufacture these different structures, we also present an original microtechnology to realize elec-tronics, and for controlling the very weak interfaces between the Casimir electrodes and of the return electrodes! These vibrations are obtained by controlling automatically and at appropriate instants the action of the attractive Casimir force by a repulsive Coulomb force applied to return electrodes. The Casimir force deforms a piezoelectric bridge, his internal field attracts opposing moving charges used to generate an opposing Coulomb force.
Casimir, Coulomb, Vacuum Quantum Energy Extraction, Piezoelectric, MEMS
Abdel Hamid Mbouombouo Mboungam1, Zhi Yongfeng2, Wilfried Andre Tiako Youani3, 1Doctorate Student, School of Automation, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China, 2Professor, School of Automation, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China, 3Doctorate applicant, Mechanical Engineering, Northwestern Polytechnical University, Xi’an, Shaanxi, 710072, China
Modernization of radar technology and improved signal processing techniques are necessary to improve detection systems in complex situations. A fundamental problem in radar systems is to automatically detect targets while maintaining a desired constant false alarm probability. This work studies two detection approaches, the first with a fixed threshold and the other with an adaptive one. In the latter, we have learned the three types of detectors CA, SO, and GO-CFAR. This research aims to apply intelligent techniques to improve detection performance in a nonhomogeneous environment using standard CFAR detectors. The objective is to maintain the false alarm probability and enhance target detection by combining intelligent techniques. With these objectives in mind, implementing standard CFAR detectors is applied to nonhomogeneous environment data. The primary focus is understanding the reason for the false detection when applying standard CFAR detectors in a nonhomogeneous environment and how to avoid it using intelligent approaches.
CFAR detector, detection, adaptive threshold, non-homogeneous, false alarm probability.