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 exploring how specific features of this new technology may transform traditional business methods. The primary objectives of this study are to summarize the significant Blockchain techniques used thus far, identify current challenges and barriers in this field, determine the limitations of each paper that could be used for future development, and assess the extent to which Blockchain and data analytics have been effectively used to evaluate performance objectively. Moreover, we aim to identify potential future research paths and suggest new criteria in this burgeoning discipline through our review. Index Terms— Blockchain, Distributed Database, Distributed Consensus, Data Analytics, Public Ledger.
In the present study, mixed ligand compounds of Mn(II), Ni(II), Co(II), Cu(II), Cd(II) and Hg(II) were synthesized using new Ligand N1,N4-bis (pyrimidin-2-ylcarbamothioyl) succinimide (NPS) derived from [Butanedioyl diisothiocyanate with 2- aminipyridine] as first ligand, proline (pro) as second ligand and evaluation of their antioxidant activities for ligand, nickel and cobalt complex towards 1.1-Di-phenyl-2picrylhydrazyl (DPPH) will be compared to the standard anti-oxidants (i.e. the ascorbic acid). Those materials that have been prepared provided results are a result of exhibiting different activities of the radical scavenging for all of the compounds. Compounds were observed then confirmed through the Fourier-tra
... Show MoreColumns subjected to pure axial load rarely exist in practice. Reinforced concrete columns are usually subjected to combination of axial and lateral actions and deformations, caused by spatially‐complex loading patterns as during earthquakes causes lateral deflection that in turn affects the horizontal stiffness. In this study, a numerical model was developed in threedimensional nonlinear finite element and then validated against experimental results reported in the literatures,
to investigate the behavior of conventionally RC columns subjected to axial load and . lateral reversal cyclic loading. To achieve this goal, numerical analysis was conducted by using finite element program ABAQUS/Explicit. The variables co
Everywhere carriers incur a measure of liability for the safety of the goods. Carriers are liable for any damage or for the loss of the goods that are in their possession as carriers unless they prove that the damage or loss is attributable to certain excepted causes. Damaged and lost items can unfortunately be a common problem when shipping freight. Legal responsibilities arise due to loss or damage during transit while cargo is in their care. This study intends to investigate the nature of the liability of the maritime carrier when this liability is realized, and the extent to which it can be paid or disposed of given the risks realized from the transportation process, which may result in damage or loss of the goods, and the damag
... Show MoreAn experiment was carried out on the fields of the college of Agriculture - Abu Ghraib, of a silty clay loam soil that has moisture of 15-16%, to study the effect of plowing and pulverization systems on some plant indicators of onion. The experiment included plowing systems with three levels (plowing with a moldboard plow, plowing by chisel plow and zero tillage plowing) as a primary factor. The second factor was that pulverization for only one time and repeating the pulverization twice through the use of the rotary tiller. The plant indicators of onion that are studied: plant length, onion diameter, onion weight and onion neck diameter. The experiment has carried out according to SPLIT PLOT design according to RCBD design by three replicat
... Show MoreThis study focused on spectral clustering (SC) and three-constraint affinity matrix spectral clustering (3CAM-SC) to determine the number of clusters and the membership of the clusters of the COST 2100 channel model (C2CM) multipath dataset simultaneously. Various multipath clustering approaches solve only the number of clusters without taking into consideration the membership of clusters. The problem of giving only the number of clusters is that there is no assurance that the membership of the multipath clusters is accurate even though the number of clusters is correct. SC and 3CAM-SC aimed to solve this problem by determining the membership of the clusters. The cluster and the cluster count were then computed through the cluster-wise J
... Show MoreIn the theoretical part, removal of direct yellow 8 (DY8) from water solution was accomplished using Bentonite Clay as an adsorbent. Under batch adsorption, the adsorption was observed as a function of contact time, adsorbent dosage, pH, and temperature. The equilibrium data were fitted with the Langmuir and Freundlich adsorption models, and the linear regression coefficient R2 was used to determine the best fitting isotherm model. thermodynamic parameters of the ongoing adsorption mechanism, such as Gibb's free energy, enthalpy, and entropy, have also been measured. The batch method was also used for the kinetic calculations, and the day's adsorption assumes first-order rate kinetics. The kinetic studies also show that the intrapar
... Show MoreThe deep learning algorithm has recently achieved a lot of success, especially in the field of computer vision. This research aims to describe the classification method applied to the dataset of multiple types of images (Synthetic Aperture Radar (SAR) images and non-SAR images). In such a classification, transfer learning was used followed by fine-tuning methods. Besides, pre-trained architectures were used on the known image database ImageNet. The model VGG16 was indeed used as a feature extractor and a new classifier was trained based on extracted features.The input data mainly focused on the dataset consist of five classes including the SAR images class (houses) and the non-SAR images classes (Cats, Dogs, Horses, and Humans). The Conv
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