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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
Sun Jan 01 2023
Journal Name
Journal Of Intelligent Systems
A study on predicting crime rates through machine learning and data mining using text
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Abstract<p>Crime is a threat to any nation’s security administration and jurisdiction. Therefore, crime analysis becomes increasingly important because it assigns the time and place based on the collected spatial and temporal data. However, old techniques, such as paperwork, investigative judges, and statistical analysis, are not efficient enough to predict the accurate time and location where the crime had taken place. But when machine learning and data mining methods were deployed in crime analysis, crime analysis and predication accuracy increased dramatically. In this study, various types of criminal analysis and prediction using several machine learning and data mining techniques, based o</p> ... Show More
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Publication Date
Tue Aug 01 2023
Journal Name
Baghdad Science Journal
Digital Data Encryption Using a Proposed W-Method Based on AES and DES Algorithms
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This paper proposes a new encryption method. It combines two cipher algorithms, i.e., DES and AES, to generate hybrid keys. This combination strengthens the proposed W-method by generating high randomized keys. Two points can represent the reliability of any encryption technique. Firstly, is the key generation; therefore, our approach merges 64 bits of DES with 64 bits of AES to produce 128 bits as a root key for all remaining keys that are 15. This complexity increases the level of the ciphering process. Moreover, it shifts the operation one bit only to the right. Secondly is the nature of the encryption process. It includes two keys and mixes one round of DES with one round of AES to reduce the performance time. The W-method deals with

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Publication Date
Mon Apr 01 2019
Journal Name
2019 International Conference On Automation, Computational And Technology Management (icactm)
Multi-Resolution Hierarchical Structure for Efficient Data Aggregation and Mining of Big Data
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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

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Publication Date
Wed Oct 01 2008
Journal Name
2008 First International Conference On Distributed Framework And Applications
A strategy for Grid based t-way test data generation
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Publication Date
Sat Oct 01 2022
Journal Name
Baghdad Science Journal
A Crime Data Analysis of Prediction Based on Classification Approaches
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Crime is considered as an unlawful activity of all kinds and it is punished by law. Crimes have an impact on a society's quality of life and economic development. With a large rise in crime globally, there is a necessity to analyze crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. The purpose of this research is to develop predictive models that can aid in crime pattern analysis and thus support the Boston department's crime prevention efforts. The geographical location factor has been adopted in our model, and this is due to its being an influential factor in several situations, whether it is traveling to a specific area or livin

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Publication Date
Wed Mar 05 2025
Journal Name
Lecture Notes In Networks And Systems
Leveraging AI for Disaster Management: A Comprehensive Review of Applications and Challenges
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Publication Date
Wed Jun 01 2022
Journal Name
Iraqi Journal Of Industrial Research (ijoir)
Biofuel Production and Its Impact on Global Food Security: A Review Article
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The aim of this study is to shed light on the importance of biofuels as an alternative to conventional energy, in addition to the importance of preserving agricultural crops, which are the main source of this fuel, to maintain food security, especially in developing countries. The increase in global oil prices, in addition to the fear of global warming, are among the main factors that draw the world’s attention to searching for alternative sources of traditional energy, which are sustainable on the one hand, and on the other hand reduce carbon emissions. Therefore, the volume of global investment in renewable energy in general, and in liquid biofuels and biomass in particular, has increased. Global fears emerged that the excessive convers

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Publication Date
Sun Jan 31 2021
Journal Name
Systematic Reviews In Pharmacy
Schiff Bases and Their Metal Complexes Derived from Ortho-phthalaldehyde: A review
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Trimethoprim derivative Schiff bases are versatile ligands synthesized with carbonyl groups from the condensation of primary amines (amino acids). Because of their broad range of biological activity, these compounds are very important in the medical and pharmaceutical fields. Biological activities such as antibacterial, antifungal and antitumor activity are often seen. Transition metal complexes derived from biological activity Schiff base ligands have been commonly used.

Publication Date
Sun Jun 01 2025
Journal Name
Journal Of University Of Anbar For Pure Science
SARS-CoV-2 history, diagnosis, genetic diversity and treatment: a comprehensive review
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Publication Date
Thu Dec 09 2021
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Algae Bioactive Constituents and Possible Role During COVID-19 Pandemic (A review)
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Nowadays, the use of natural bio-products in pharmaceuticals is gaining popularity as safe alternatives to chemicals and synthetic drugs. Algal products are offering a pure, healthy and sustainable choice for pharmaceutical applications. Algae are photosynthetic microorganisms that can survive in different environmental conditions. Algae have many outstanding properties that make them excellent candidate for use in therapeutics. Algae grow in fresh and marine waters and produce in their cells a wide range of biologically active chemical compounds. These bioactive compounds are offering a great source of highly economic bio-products. The prese
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