Shear wave velocity is an important feature in the seismic exploration that could be utilized in reservoir development strategy and characterization. Its vital applications in petrophysics, seismic, and geomechanics to predict rock elastic and inelastic properties are essential elements of good stability and fracturing orientation, identification of matrix mineral and gas-bearing formations. However, the shear wave velocity that is usually obtained from core analysis which is an expensive and time-consuming process and dipole sonic imager tool is not commonly available in all wells. In this study, a statistical method is presented to predict shear wave velocity from wireline log data. The model concentrated to predict shear wave velocity fr

Wireless sensor applications are susceptible to energy constraints. Most of the energy is consumed in communication between wireless nodes. Clustering and data aggregation are the two widely used strategies for reducing energy usage and increasing the lifetime of wireless sensor networks. In target tracking applications, large amount of redundant data is produced regularly. Hence, deployment of effective data aggregation schemes is vital to eliminate data redundancy. This work aims to conduct a comparative study of various research approaches that employ clustering techniques for efficiently aggregating data in target tracking applications as selection of an appropriate clustering algorithm may reflect positive results in the data aggregati

Abstract

The research Compared two methods for estimating fourparametersof the compound exponential Weibull - Poisson distribution which are the maximum likelihood method and the Downhill Simplex algorithm. Depending on two data cases, the first one assumed the original data (Non-polluting), while the second one assumeddata contamination. Simulation experimentswere conducted for different sample sizes and initial values of parameters and under different levels of contamination. Downhill Simplex algorithm was found to be the best method for in the estimation of the parameters, the probability function and the reliability function of the compound distribution in cases of natural and contaminateddata.

In this study, the mobile phone traces concern an ephemeral event which represents important densities of people. This research aims to study city pulse and human mobility evolution that would be arise during specific event (Armada festival), by modelling and simulating human mobility of the observed region, depending on CDRs (Call Detail Records) data. The most pivot questions of this research are: Why human mobility studied? What are the human life patterns in the observed region inside Rouen city during Armada festival? How life patterns and individuals' mobility could be extracted for this region from mobile DB (CDRs)? The radius of gyration parameter has been applied to elaborate human life patterns with regards to (work, off) days for

In this study, we review the ARIMA (p, d, q), the EWMA and the DLM (dynamic linear moodelling) procedures in brief in order to accomdate the ac(autocorrelation)  structure of data .We consider the recursive estimation and prediction algorithms based on Bayes and KF (Kalman filtering) techniques for correlated observations.We investigate the effect on the MSE of  these procedures and compare them using generated data.

Data compression offers an attractive approach to reducing communication costs using available bandwidth effectively. It makes sense to pursue research on developing algorithms that can most effectively use available network. It is also important to consider the security aspect of the data being transmitted is vulnerable to attacks. The basic aim of this work is to develop a module for combining the operation of compression and encryption on the same set of data to perform these two operations simultaneously. This is achieved through embedding encryption into compression algorithms since both cryptographic ciphers and entropy coders bear certain resemblance in the sense of secrecy. First in the secure compression module, the given text is p

Blockchain technology relies on cryptographic techniques that provide various advantages, such as trustworthiness, collaboration, organization, identification, integrity, and transparency. Meanwhile, data analytics refers to the process of utilizing techniques to analyze big data and comprehend the relationships between data points to draw meaningful conclusions. The field of data analytics in Blockchain is relatively new, and few studies have been conducted to examine the challenges involved in Blockchain data analytics. This article presents a systematic analysis of how data analytics affects Blockchain performance, with the aim of investigating the current state of Blockchain-based data analytics techniques in research fields and

The research seeks to identify the contemporary events that face the use of electronic payment methods to localize the salaries of state employees and its impact in enhancing the mental image of customers, and to achieve this purpose from the fact that a questionnaire was designed and distributed to an optional sample of (31) individual customers (employees) dealing With the researched private banks, it has been analyzed and reached a number of conclusions and recommendations, the most prominent of which is the lack of modernity of electronic payment methods by customers, which is reflected in the mental image of customers and the achievement of their satisfaction, in the Emiratization project for salaries needs an advanced leade