The Weibull distribution is considered one of the Type-I Generalized Extreme Value (GEV) distribution, and it plays a crucial role in modeling extreme events in various fields, such as hydrology, finance, and environmental sciences. Bayesian methods play a strong, decisive role in estimating the parameters of the GEV distribution due to their ability to incorporate prior knowledge and handle small sample sizes effectively. In this research, we compare several shrinkage Bayesian estimation methods based on the squared error and the linear exponential loss functions. They were adopted and compared by the Monte Carlo simulation method. The performance of these methods is assessed based on their accuracy and computational efficiency in estimati

􀀨􀀅􀀆􀀔􀀜􀀄􀀂􀀆􀀈􀀓􀀌􀀩􀀏􀀆􀀉􀀅􀀆􀀉􀀅􀀉􀀚􀀝􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀓􀀚􀀁􀀔􀀄􀀓􀀅􀀆􀀄􀀂􀀆􀀔􀀓􀀆􀀃􀀂􀀔􀀄􀀟􀀉􀀔􀀃􀀆􀀔􀀜􀀃􀀆􀀛􀀃􀀜􀀄􀀗􀀚􀀃􀀆􀀗􀀌􀀄􀀔􀀄􀀗􀀉􀀚􀀆􀀂􀀘􀀃􀀃􀀊􀀂􀀆􀀓􀀖􀀆􀀓􀀛􀀃􀀌􀀔􀀁􀀌􀀅􀀄􀀅􀀕􀀢􀀆􀀪􀀜􀀃􀀆􀀄􀀅􀀛􀀃􀀂􀀔􀀄􀀕􀀉􀀔􀀄􀀓􀀅􀀂􀀆 􀀉􀀌􀀃􀀆􀀙􀀉􀀂􀀃􀀊􀀆􀀓􀀅􀀆􀀉􀀁􀀔􀀓􀀟􀀓􀀙􀀄􀀚􀀃􀀆􀀚􀀉􀀔􀀃􀀌􀀉􀀚􀀆􀀂􀀘􀀉􀀗􀀃􀀆􀀟􀀄􀀊􀀂􀀔􀀆􀀔􀀜􀀃􀀆􀀗􀀃􀀅􀀔􀀃􀀌􀀚􀀄􀀅􀀃􀀂􀀆􀀓􀀖􀀆􀀔􀀜􀀃􀀆􀀙􀀉􀀂􀀃􀀆

<span lang="EN-US">The use of bio-signals analysis in human-robot interaction is rapidly increasing. There is an urgent demand for it in various applications, including health care, rehabilitation, research, technology, and manufacturing. Despite several state-of-the-art bio-signals analyses in human-robot interaction (HRI) research, it is unclear which one is the best. In this paper, the following topics will be discussed: robotic systems should be given priority in the rehabilitation and aid of amputees and disabled people; second, domains of feature extraction approaches now in use, which are divided into three main sections (time, frequency, and time-frequency). The various domains will be discussed, then a discussion of e

Background: Obesity tends to appear in modern societies and constitutes a significant public health problem with an increased risk of cardiovascular diseases.

Objective: This study aims to determine the agreement between actual and perceived body image in the general population.

Methods: A descriptive cross-sectional study design was conducted with a sample size of 300. The data were collected from eight major populated areas of Northern district of Karachi Sindh with a period of six months (10^th January 2020 to 21^st June 2020). The Figure rating questionnaire scale (FRS) was applied to collect the demographic data and perception about body weight. Body mass index (BMI) used for ass

In this paper, the effect of wear in the fluid film journal bearings on the dynamic behavior of rotor bearing system has been studied depending on the analytical driven of dynamic stiffness and damping coefficients of worn journal bearing. The finite element method was used to modeling rotor bearing system. The unbalance response, critical speed and natural frequency of rotor bearing system have been studied to determine the changes in these parameters due to wear. MATLAB software was used to find the analytical values of dynamic coefficients of journal bearing. The results of rotor mounted on fluid film journal bearings showed that the wear in journal bearing increases the amplitude of unbalance response and decrease critical speed, sta

Reliable estimation of critical parameters such as hydrocarbon pore volume, water saturation, and recovery factor are essential for accurate reserve assessment. The inherent uncertainties associated with these parameters encompass a reasonable range of estimated recoverable volumes for single accumulations or projects. Incorporating this uncertainty range allows for a comprehensive understanding of potential outcomes and associated risks. In this study, we focus on the oil field located in the northern part of Iraq and employ a Monte Carlo based petrophysical uncertainty modeling approach. This method systematically considers various sources of error and utilizes effective interpretation techniques. Leveraging the current state of a

Finding orthogonal matrices in different sizes is very complex and important because it can be used in different applications like image processing and communications (eg CDMA and OFDM). In this paper we introduce a new method to find orthogonal matrices by using tensor products between two or more orthogonal matrices of real and imaginary numbers with applying it in images and communication signals processing. The output matrices will be orthogonal matrices too and the processing by our new method is very easy compared to other classical methods those use basic proofs. The results are normal and acceptable in communication signals and images but it needs more research works.

Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

Background: Multiple sclerosis is a chronic autoimmune inflammatory demyelinating disease of the central nervous system of unknown etiology. Different techniques and magnetic resonance image sequences are widely used and compared to each other to improve the detection of multiple sclerosis lesions in the spinal cord. Objective: To evaluate the ability of MRI short tau inversion recovery sequences in improvementof multiple sclerosis spinal cord lesion detection when compared to T2 weighted image sequences. Type of the study: A retrospective study. Methods: this study conducted from 15thAugust 2013 to 30thJune 2014 at Baghdad teaching hospital. 22 clinically definite MS patients with clinical features suggestive of spinal cord involvement,