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Data Analytics and Blockchain: A Review
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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.

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Publication Date
Tue Jan 06 2004
Journal Name
Iraqi Journal Of Science
Cluster and factor analyses R and Q mode technique of geochemical and petrological data of the Shalair Metamorphic Rock Group, Shalair Valley area, Northeastern Iraq
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Publication Date
Wed Mar 10 2021
Journal Name
Baghdad Science Journal
A Comparison Between the Theoretical Cross Section Based on the Partial Level Density Formulae Calculated by the Exciton Model with the Experimental Data for (_79^197)Au nucleus
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In this paper, the theoretical cross section in pre-equilibrium nuclear reaction has been studied for the reaction  at energy 22.4 MeV. Ericson’s formula of partial level density PLD and their corrections (William’s correction and spin correction) have been substituted  in the theoretical cross section and compared with the experimental data for  nucleus. It has been found that the theoretical cross section with one-component PLD from Ericson’s formula when  doesn’t agree with the experimental value and when . There is little agreement only at the high value of energy range with  the experimental cross section. The theoretical cross section that depends on the one-component William's formula and on-component corrected to spi

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Publication Date
Wed Dec 01 2021
Journal Name
International Journal Of Research In Social Sciences & Humanities. E-issn
CONCEPTS OF LITERATURE: COMPARATIVE LITERATURE BY HENRY GIFFORD (an Article REVIEW).
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BOOK REVIEW

Publication Date
Sat Mar 23 2024
Journal Name
Journal Of Optics
Review Recent Developments In High-Power Diode Lasers For Biomedical Applications
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Diode laser technology is well established for biomedicine applications which demand high-power pulse-wave. They are extensively utilized from medical imaging and testing to surgical therapies and the latest aesthetic processes. For medical therapeutic practices, diode lasers have become the ideal laser source for this particular purpose. In the last previous years, semiconductor laser technology has evolved to produce high-repetitions rate near-infrared pulsed lasers diodes that are dependable, low-cost, portable, and small-weight, about few grams. In this paper, we review the recent development and demonstration of diode laser devices for biomedical applications recorded in the latest years taking into account the power, wavelength, and p

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Publication Date
Wed Sep 23 2020
Journal Name
Artificial Intelligence Research
Hybrid approaches to feature subset selection for data classification in high-dimensional feature space
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This paper proposes two hybrid feature subset selection approaches based on the combination (union or intersection) of both supervised and unsupervised filter approaches before using a wrapper, aiming to obtain low-dimensional features with high accuracy and interpretability and low time consumption. Experiments with the proposed hybrid approaches have been conducted on seven high-dimensional feature datasets. The classifiers adopted are support vector machine (SVM), linear discriminant analysis (LDA), and K-nearest neighbour (KNN). Experimental results have demonstrated the advantages and usefulness of the proposed methods in feature subset selection in high-dimensional space in terms of the number of selected features and time spe

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Publication Date
Sat Dec 01 2007
Journal Name
Journal Of Economics And Administrative Sciences
دور تنقيب البيانات Data Mining في زيادة أداء المنظمة (( دراسة تحليلية في المصرف الصناعي ))
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تمهيد

غالبا ما يكون تعامل المنظمات المالية والمصرفية مع الزبائن بشكل أساسي مما يتطلب منها جمع كميات هائلة من البيانات عن هؤلاء الزبائن هذا بالإضافة الى ما يرد اليها يوميا من بيانات يجعلها أمام أكداس كبيرة من البيانات تحتاج الى جهود جبارة تحسن التعامل معها والاستفادة منها بما يخدم المنظمة.

ان التعامل اليدوي مع مثل هذه البيانات دون استخدام تقنيات حديثة يبعد المنظمة عن التط

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Publication Date
Tue Jan 01 2019
Journal Name
Baghdad Science Journal
Hazard Rate Estimation Using Varying Kernel Function for Censored Data Type I Article Sidebar
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n this research, several estimators concerning the estimation are introduced. These estimators are closely related to the hazard function by using one of the nonparametric methods namely the kernel function for censored data type with varying bandwidth and kernel boundary. Two types of bandwidth are used: local bandwidth and global bandwidth. Moreover, four types of boundary kernel are used namely: Rectangle, Epanechnikov, Biquadratic and Triquadratic and the proposed function was employed with all kernel functions. Two different simulation techniques are also used for two experiments to compare these estimators. In most of the cases, the results have proved that the local bandwidth is the best for all the types of the kernel boundary func

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Publication Date
Sun Jun 05 2016
Journal Name
Baghdad Science Journal
Developing an Immune Negative Selection Algorithm for Intrusion Detection in NSL-KDD data Set
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With the development of communication technologies for mobile devices and electronic communications, and went to the world of e-government, e-commerce and e-banking. It became necessary to control these activities from exposure to intrusion or misuse and to provide protection to them, so it's important to design powerful and efficient systems-do-this-purpose. It this paper it has been used several varieties of algorithm selection passive immune algorithm selection passive with real values, algorithm selection with passive detectors with a radius fixed, algorithm selection with passive detectors, variable- sized intrusion detection network type misuse where the algorithm generates a set of detectors to distinguish the self-samples. Practica

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Publication Date
Fri Mar 31 2023
Journal Name
Iraqi Geological Journal
Subsurface Structural Image of Galabat Field, North East of Iraq Using 2D Seismic Data
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This research had been achieved to identify the image of the subsurface structure representing the Tertiary period in the Galabat Field northeast of Iraq using 2D seismic survey measurements. Synthetic seismograms of the Galabat-3 well were generated in order to identify and pick the reflectors in seismic sections. Structural Images were drawn in the time domain and then converted to the depth domain by using average velocities. Structurally, seismic sections illustrate these reflectors are affected by two reverse faults affected on the Jeribe Formation and the layers below with the increase in the density of the reverse faults in the northern division. The structural maps show Galabat field, which consists of longitudinal Asymmetrical narr

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Publication Date
Sun Jan 01 2017
Journal Name
Statistical Applications In Genetics And Molecular Biology
Mixture model-based association analysis with case-control data in genome wide association studies
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Abstract<p>Multilocus haplotype analysis of candidate variants with genome wide association studies (GWAS) data may provide evidence of association with disease, even when the individual loci themselves do not. Unfortunately, when a large number of candidate variants are investigated, identifying risk haplotypes can be very difficult. To meet the challenge, a number of approaches have been put forward in recent years. However, most of them are not directly linked to the disease-penetrances of haplotypes and thus may not be efficient. To fill this gap, we propose a mixture model-based approach for detecting risk haplotypes. Under the mixture model, haplotypes are clustered directly according to their estimated d</p> ... Show More
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