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Bayes Classification and Entropy Discretization of Large Datasets using Multi-Resolution Data Aggregation
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Big data analysis has important applications in many areas such as sensor networks and connected healthcare. High volume and velocity of big data bring many challenges to data analysis. One possible solution is to summarize the data and provides a manageable data structure to hold a scalable summarization of data for efficient and effective analysis. This research extends our previous work on developing an effective technique to create, organize, access, and maintain summarization of big data and develops algorithms for Bayes classification and entropy discretization of large data sets using the multi-resolution data summarization structure. Bayes classification and data discretization play essential roles in many learning algorithms such as decision tree and nearest neighbor search. The proposed method can handle streaming data efficiently and, for entropy discretization, provide su the optimal split value.

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Publication Date
Mon Apr 24 2017
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Estimate the Parameters and Related Probability Functions for Data of the Patients of Lymph Glands Cancer via Birnbaum-Saunders Model
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 In this paper,we estimate the parameters and related probability functions, survival function, cumulative distribution function , hazard function(failure rate) and failure  (death) probability function(pdf) for two parameters Birnbaum-Saunders distribution which is fitting the complete data for the patients of  lymph glands cancer. Estimating the parameters (shape and scale) using (maximum likelihood , regression quantile and shrinkage) methods and then compute the value of mentioned related probability  functions depending on sample from real data which describe the duration of survivor for patients who suffer from the lymph glands cancer based on diagnosis of disease or the inter of patients in a hospital for perio

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Publication Date
Sat May 31 2025
Journal Name
Iraqi Journal For Computers And Informatics
Discussion on techniques of data cleaning, user identification, and session identification phases of web usage mining from 2000 to 2022
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The data preprocessing step is an important step in web usage mining because of the nature of log data, which are heterogeneous, unstructured, and noisy. Given the scalability and efficiency of algorithms in pattern discovery, a preprocessing step must be applied. In this study, the sequential methodologies utilized in the preprocessing of data from web server logs, with an emphasis on sub-phases, such as session identification, user identification, and data cleansing, are comprehensively evaluated and meticulously examined.

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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Analysis of the indicators of the educational process and scientific levelUsing the analysis of variance of ordered data in repeated measurements
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In this research want to make analysis for some indicators and it's classifications that related with the teaching process and the            scientific level for graduate studies in the university by using analysis of variance for ranked data for repeated measurements instead of the ordinary analysis of variance . We reach many conclusions  for the                         

important classifications for each indicator that has affected on   the teaching process.         &nb

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Publication Date
Wed Aug 23 2023
Journal Name
International Journal Of Mental Health Nursing
Self and public stigma towards mental illnesses and its predictors among university students in 11 Arabic‐speaking countries: A multi‐site study
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Abstract<p>This study aimed to explore self and public stigma towards mental illness and associated factors among university students from 11 Arabic‐speaking countries. This cross‐sectional study included 4241 university students recruited from Oman, Saudi Arabia, the United Arab Emirates (UAE), Syria, Sudan, Bahrain, Iraq, Jordan, Lebanon, Palestine and Egypt. The participants completed three self‐administrative online questionnaires—Demographic Proforma (age, gender, family income, etc.), Peer Mental Health Stigmatization Scale and Mental Health Knowledge Questionnaire. There was a significant difference in the average mean between the 11 countries (<italic>p</italic> < 0.01) based on</p> ... Show More
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Publication Date
Sun Dec 09 2018
Journal Name
Baghdad Science Journal
Optimal UAV Deployment for Data Collection in Deadline-based IoT Applications
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The deployment of UAVs is one of the key challenges in UAV-based communications while using UAVs for IoT applications. In this article, a new scheme for energy efficient data collection with a deadline time for the Internet of things (IoT) using the Unmanned Aerial Vehicles (UAV) is presented. We provided a new data collection method, which was set to collect IoT node data by providing an efficient deployment and mobility of multiple UAV, used to collect data from ground internet of things devices in a given deadline time. In the proposed method, data collection was done with minimum energy consumption of IoTs as well as UAVs. In order to find an optimal solution to this problem, we will first provide a mixed integer linear programming m

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Publication Date
Sat Mar 01 2008
Journal Name
Iraqi Journal Of Physics
Comparison between Different Data Image Compression Techniques Applied on SAR Images
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In this paper, image compression technique is presented based on the Zonal transform method. The DCT, Walsh, and Hadamard transform techniques are also implements. These different transforms are applied on SAR images using Different block size. The effects of implementing these different transforms are investigated. The main shortcoming associated with this radar imagery system is the presence of the speckle noise, which affected the compression results.

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Publication Date
Sun Mar 15 2020
Journal Name
Journal Of The College Of Education For Women
Data-Driven Approach for Teaching Arabic as a Foreign Language: Eygpt
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Corpus linguistics is a methodology in studying language through corpus-based research. It differs from a traditional approach in studying a language (prescriptive approach) in its insistence on the systematic study of authentic examples of language in use (descriptive approach).A “corpus” is a large body of machine-readable structurally collected naturally occurring linguistic data, either written texts or a transcription of recorded speech, which can be used as a starting-point of linguistic description or as a means of verifying hypotheses about a language.  In the past decade, interest has grown tremendously in the use of language corpora for language education. The ways in which corpora have been employed in language pedago

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Publication Date
Mon Dec 25 2023
Journal Name
Ieee Access
ITor-SDN: Intelligent Tor Networks-Based SDN for Data Forwarding Management
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Tor (The Onion Routing) network was designed to enable users to browse the Internet anonymously. It is known for its anonymity and privacy security feature against many agents who desire to observe the area of users or chase users’ browsing conventions. This anonymity stems from the encryption and decryption of Tor traffic. That is, the client’s traffic should be subject to encryption and decryption before the sending and receiving process, which leads to delay and even interruption in data flow. The exchange of cryptographic keys between network devices plays a pivotal and critical role in facilitating secure communication and ensuring the integrity of cryptographic procedures. This essential process is time-consuming, which causes del

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Publication Date
Fri Apr 26 2019
Journal Name
Journal Of Contemporary Medical Sciences
Breast Cancer Decisive Parameters for Iraqi Women via Data Mining Techniques
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Objective This research investigates Breast Cancer real data for Iraqi women, these data are acquired manually from several Iraqi Hospitals of early detection for Breast Cancer. Data mining techniques are used to discover the hidden knowledge, unexpected patterns, and new rules from the dataset, which implies a large number of attributes. Methods Data mining techniques manipulate the redundant or simply irrelevant attributes to discover interesting patterns. However, the dataset is processed via Weka (The Waikato Environment for Knowledge Analysis) platform. The OneR technique is used as a machine learning classifier to evaluate the attribute worthy according to the class value. Results The evaluation is performed using

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Publication Date
Tue Mar 01 2022
Journal Name
International Journal Of Nonlinear Analysis And Applications
The suggested threshold to reduce data noise for a factorial experiment
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In this research, a factorial experiment (4*4) was studied, applied in a completely random block design, with a size of observations, where the design of experiments is used to study the effect of transactions on experimental units and thus obtain data representing experiment observations that The difference in the application of these transactions under different environmental and experimental conditions It causes noise that affects the observation value and thus an increase in the mean square error of the experiment, and to reduce this noise, multiple wavelet reduction was used as a filter for the observations by suggesting an improved threshold that takes into account the different transformation levels based on the logarithm of the b

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