This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different

The load shedding  scheme has been extensively implemented as a fast solution for unbalance conditions. Therefore, it's crucial to investigate supply-demand balancing in order to protect the network from collapsing and to sustain stability as possible, however its implementation is mostly undesirable. One of the solutions to minimize the amount of load shedding is the integration renewable energy  resources, such as wind power, in the electric power generation could contribute significantly to minimizing power cuts as it is ability to positively improving the stability of the electric grid. In this paper propose a method for shedding the load base on the priority demands with incorporating the wind po

The implementation of technology in the provision of public services and communication to citizens, which is commonly referred to as e-government, has brought multitude of benefits, including enhanced efficiency, accessibility, and transparency. Nevertheless, this approach also presents particular security concerns, such as cyber threats, data breaches, and access control. One technology that can aid in mitigating the effects of security vulnerabilities within e-government is permissioned blockchain. This work examines the performance of the hyperledger fabric private blockchain under high transaction loads by analyzing two scenarios that involve six organizations as case studies. Several parameters, such as transaction send ra

Big data analysis is essential for modern applications in areas such as healthcare, assistive technology, intelligent transportation, environment and climate monitoring. Traditional algorithms in data mining and machine learning do not scale well with data size. Mining and learning from big data need time and memory efficient techniques, albeit the cost of possible loss in accuracy. We have developed a data aggregation structure to summarize data with large number of instances and data generated from multiple data sources. Data are aggregated at multiple resolutions and resolution provides a trade-off between efficiency and accuracy. The structure is built once, updated incrementally, and serves as a common data input for multiple mining an

The present study was conducted with a view to determine whether focal laser therapy result in visual recovery and regression of macular edema in patients with non proliferative diabetic retinopathy and maculopathy ,and whether combined focal and scatter laser therapy in patients with proliferative diabetic retinopathy and maculopathy results in visual recovery ,regression of macular edema and regression of the risk factors. In the present work, a frequency doubled Nd: YAG laser was used for the treatment of diabetic retinopathy. The study evaluates 41 eyes of 33 diabetic patients both with Insulin Dependent Diabetes Mellitus IDDM, (n=16) and Non Insulin Dependent Diabetes Mellitus NIDDM, (n=17) with diabetic retinopathy divided into two

            The widespread use of the Internet of things (IoT) in different aspects of an individual’s life like banking, wireless intelligent devices and smartphones has led to new security and performance challenges under restricted resources. The Elliptic Curve Digital Signature Algorithm (ECDSA) is the most suitable choice for the environments due to the smaller size of the encryption key and changeable security related parameters. However, major performance metrics such as area, power, latency and throughput are still customisable and based on the design requirements of the device.

The present paper puts forward an enhancement for the throughput performance metric by p

Thyroid disease is a common disease affecting millions worldwide. Early diagnosis and treatment of thyroid disease can help prevent more serious complications and improve long-term health outcomes. However, thyroid disease diagnosis can be challenging due to its variable symptoms and limited diagnostic tests. By processing enormous amounts of data and seeing trends that may not be immediately evident to human doctors, Machine Learning (ML) algorithms may be capable of increasing the accuracy with which thyroid disease is diagnosed. This study seeks to discover the most recent ML-based and data-driven developments and strategies for diagnosing thyroid disease while considering the challenges associated with imbalanced data in thyroid dise

This study describes the preparation of new series of tetra-dentate N2O2 dinuclear complexes (Cr3+, Co2+, Cu2+) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and 1H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all complexes of the (Cr3+, Co2+, Cu2+). conductivity measurement shows t

This study describes the preparation of new series of tetra-dentate N₂O₂ dinuclear complexes (Cr³⁺, Co²⁺, Cu²⁺) of the Schiff base derived from condensation of 1-Hydroxy-naphthalene-2-carbaldehyde with 2-amino-5-(2-hydroxy-phenyl)-1,3,4-thiadiazole. The structures of the ligands were identified using IR, UV-Vis , mass,  elemental analysis and ¹H-NMR techniques. All prepared complexes have been characterized by conductance measurement, magnetic susceptibility, electronic spectra, infrared spectrum, theromgravimatric analysis (TGA) and metal analysis by atomic absorption. From stoichiometry of metal to ligand and all measurements show a octahedral geometry proposed for all