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3D Parallel Coordinates for Multidimensional Data Cube Exploration
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Visual analytics becomes an important approach for discovering patterns in big data. As visualization struggles from high dimensionality of data, issues like concept hierarchy on each dimension add more difficulty and make visualization a prohibitive task. Data cube offers multi-perspective aggregated views of large data sets and has important applications in business and many other areas. It has high dimensionality, concept hierarchy, vast number of cells, and comes with special exploration operations such as roll-up, drill-down, slicing and dicing. All these issues make data cubes very difficult to visually explore. Most existing approaches visualize a data cube in 2D space and require preprocessing steps. In this paper, we propose a visualization technique for visual analytics of data cubes using parallel coordinates. The proposed technique extends parallel coordinates to a 3D space to reflect concept hierarchy …

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Publication Date
Mon Jan 01 2024
Journal Name
Aip Conference Proceedings
A multivariate Bayesian model using Gibbs sampler with real data application
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In many scientific fields, Bayesian models are commonly used in recent research. This research presents a new Bayesian model for estimating parameters and forecasting using the Gibbs sampler algorithm. Posterior distributions are generated using the inverse gamma distribution and the multivariate normal distribution as prior distributions. The new method was used to investigate and summaries Bayesian statistics' posterior distribution. The theory and derivation of the posterior distribution are explained in detail in this paper. The proposed approach is applied to three simulation datasets of 100, 300, and 500 sample sizes. Also, the procedure was extended to the real dataset called the rock intensity dataset. The actual dataset is collecte

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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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

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Publication Date
Tue Mar 01 2022
Journal Name
Asian Journal Of Applied Sciences
Comparison between Expert Systems, Machine Learning, and Big Data: An Overview
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Today, the science of artificial intelligence has become one of the most important sciences in creating intelligent computer programs that simulate the human mind. The goal of artificial intelligence in the medical field is to assist doctors and health care workers in diagnosing diseases and clinical treatment, reducing the rate of medical error, and saving lives of citizens. The main and widely used technologies are expert systems, machine learning and big data. In the article, a brief overview of the three mentioned techniques will be provided to make it easier for readers to understand these techniques and their importance.

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Publication Date
Tue Aug 29 2023
Journal Name
Geomatics And Environmental Engineering
Challenges and Issues in Spatial Data Infrastructure (SDI) Development in Iraq
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This paper addresses the nature of Spatial Data Infrastructure (SDI), considered as one of the most important concepts to ensure effective functioning in a modern society. It comprises a set of continually developing methods and procedures providing the geospatial base supporting a country’s governmental, environmental, economic, and social activities. In general, the SDI framework consists of the integration of various elements including standards, policies, networks, data, and end users and application areas. The transformation of previously paper-based map data into a digital format, the emergence of GIS, and the Internet and a host of online applications (e.g., environmental impact analysis, navigation, applications of VGI dat

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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
IMPLEMENTATION OF THE SKIP LIST DATA STRUCTURE WITH IT'S UPDATE OPERATIONS
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A skip list data structure is really just a simulation of a binary search tree. Skip lists algorithm are simpler, faster and use less space. this data structure conceptually uses parallel sorted linked lists. Searching in a skip list is more difficult than searching in a regular sorted linked list. Because a skip list is a two dimensional data structure, it is implemented using a two dimensional network of nodes with four pointers. the implementation of the search, insert and delete operation taking a time of upto . The skip list could be modified to implement the order statistic operations of RANKand SEARCH BY RANK while maintaining the same expected time. Keywords:skip list , parallel linked list , randomized algorithm , rank.

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Publication Date
Sat Nov 02 2013
Journal Name
International Journal Of Computer Applications
Mixed Transforms Generated by Tensor Product and Applied in Data Processing
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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.

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Publication Date
Mon Feb 18 2019
Journal Name
Iraqi Journal Of Physics
Data visualization and distinct features extraction of the comet Ison 2013
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The distribution of the intensity of the comet Ison C/2013 is studied by taking its histogram. This distribution reveals four distinct regions that related to the background, tail, coma and nucleus. One dimensional temperature distribution fitting is achieved by using two mathematical equations that related to the coordinate of the center of the comet. The quiver plot of the gradient of the comet shows very clearly that arrows headed towards the maximum intensity of the comet.

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Publication Date
Thu May 01 2025
Journal Name
Applied Data Science And Analysis
Strengthening cloud data protection based on a novel cyber security framework
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Cybersecurity involves protecting computer networks, systems, and data from unauthorized access and disruptions using advanced technologies. The purpose of this research is to establish a novel cyber security framework for strengthening cloud data protection. In this paper, we propose a novel Dung Beetle optimization-redefined Intelligent Random Forest (DB-IRF) for accurate detection of intrusions in a cloud environment. We obtained a dataset that includes cloud system logs and network traffic data, including normal and malicious activities, to train our proposed model. We utilized z-score normalization to pre-process the gathered raw data. Our suggested model enhances classification accuracy by integrating DB optimization with the

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Publication Date
Tue May 17 2022
Journal Name
Egyptian Journal Of Chemistry
Determination of Ferrous Ion in Pure & Pharmaceutical Preparation by Continuous Flow Injection Analysis Via Turbidmetric Utilizing NAG-4SX3-3D Analyzer
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Publication Date
Fri Mar 15 2024
Journal Name
Journal Of Baghdad College Of Dentistry
Assessment of the correlation between the tensile and diametrical compression strengths of 3D-printed denture base resin reinforced with ZrO2 nanoparticles
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Background: The mechanical properties of 3D-printed denture base resins are crucial factors for determining the quality and performance of dentures inside a patient’s mouth. Tensile strength and diametral compressive strength are two properties that could play significant roles in assessing the suitability of a material. Although they measure different aspects of material behavior, a conceptual link exists between them in terms of overall material strength and resilience. Aim: This study aims to investigate the correlation between tensile strength and diametral compressive strength after incorporating 2% ZrO2 nanoparticles (NPs) by weight into 3D-printed denture base resin. Methods: A total of 40 specimens (20 dumbbell-shaped and

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