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Razy: A String Matching Algorithm for Automatic Analysis of Pathological Reports
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Pathology reports are necessary for specialists to make an appropriate diagnosis of diseases in general and blood diseases in particular. Therefore, specialists check blood cells and other blood details. Thus, to diagnose a disease, specialists must analyze the factors of the patient’s blood and medical history. Generally, doctors have tended to use intelligent agents to help them with CBC analysis. However, these agents need analytical tools to extract the parameters (CBC parameters) employed in the prediction of the development of life-threatening bacteremia and offer prognostic data. Therefore, this paper proposes an enhancement to the Rabin–Karp algorithm and then mixes it with the fuzzy ratio to make this algorithm suitable for working with CBC test data. The selection of these algorithms was performed after evaluating the utility of various string matching algorithms in order to choose the best ones to establish an accurate text collection tool to be a baseline for building a general report on patient information. The proposed method includes several basic steps: Firstly, the CBC-driven parameters are extracted using an efficient method for retrieving data information from pdf files or images of the CBC tests. This will be performed by implementing 12 traditional string matching algorithms, then finding the most effective ways based on the implementation results, and, subsequently, introducing a hybrid approach to address the shortcomings or issues in those methods to discover a more effective and faster algorithm to perform the analysis of the pathological tests. The proposed algorithm (Razy) was implemented using the Rabin algorithm and the fuzzy ratio method. The results show that the proposed algorithm is fast and efficient, with an average accuracy of 99.94% when retrieving the results. Moreover, we can conclude that the string matching algorithm is a crucial tool in the report analysis process that directly affects the efficiency of the analytical system.

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Publication Date
Sat Jun 01 2019
Journal Name
Al-nahrain Journal Of Science
THREE DIMENSIONAL EXPLICIT MODEL FOR COMETARY TAIL IONSINTERACTIONSWITH SOLAR WIND
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The different interactions between cometary tail and solar wind ions are studied in the present paper based on three-dimensional Lax explicit method. The model used in this research is based on the continuity equations describing the cometary tail-solar wind interactions. Three dimensional system was considered in this paper. Simulation of the physical system was achieved using computer code written using Matlab 7.0. The parameters studied here assumed Halley comet type and include the particle density , the particles velocity v, the magnetic field strength B, dynamic pressure p and internal energy E. The results of the present research showed that the interaction near the cometary nucleus is mainly affected by the new ions added to the

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Publication Date
Sat Sep 01 2018
Journal Name
Journal Of Engineering
Buckling Loads and Effective Length Factor for Non-Prismatic Columns
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Publication Date
Thu Apr 21 2022
Journal Name
Journal Of Petroleum Research And Studies
Smart Well Modelling for As Reservoir in AG Oil Field
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Intelligent or smart completion wells vary from conventional wells. They have downhole flow control devices like Inflow Control Devices (ICD) and Interval Control Valves (ICV) to enhance reservoir management and control, optimizing hydrocarbon output and recovery. However, to explain their adoption and increase their economic return, a high level of justification is necessary. Smart horizontal wells also necessitate optimizing the number of valves, nozzles, and compartment length. A three-dimensional geological model of the As reservoir in AG oil field was used to see the influence of these factors on cumulative oil production and NPV. After creating the dynamic model for the As reservoir using the program Petrel (2017.4), we

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Boundary & Geometric Region Features Image Segmentation for Quadtree Partitioning Scheme
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In this paper, an efficient image segmentation scheme is proposed of boundary based & geometric region features as an alternative way of utilizing statistical base only. The test results vary according to partitioning control parameters values and image details or characteristics, with preserving the segmented image edges.

Publication Date
Sun Jan 02 2011
Journal Name
Journal Of Educational And Psychological Researches
Mental Health and Its Relationship with Shyness for University Students
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This study aimed to show the relationship between mental health and shyness for university students in Baghdad and Al – Mustansiria university which its subject was (200) students  ,          ( 100) males and  ( 100) females , Mental Health scale which is constructed by (Al – Janabi 1991) and developed by (Hassan 2006) was used for this aim  ,The scale of shyness was built according to a questioner to the students and according to previous publications and studies .

Multiple regulation analysis step - wise was used for data analysis in order to identify the possibility to find single or couple indications for the independent variable (mental

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Publication Date
Wed Jan 01 2014
Journal Name
Ieice Transactions On Communications
Fast Handoff Scheme for Cluster-Based Proxy Mobile IPv6 Protocol
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Publication Date
Sun Feb 10 2019
Journal Name
Journal Of The College Of Education For Women
New Commands to Improve the Monitor for the ELWE Microcomputer
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The base of the ELWE MPF-1 microcomputer is the Z80 microprocessor. The Z80 programs are written in assembly language. The main advantage of assembly language is that: it is much faster to code and the mnemonics makes it easier for the user to remember the instruction. The purpose of this paper is to improve the monitor process for didactic microcomputer ELWE MPF-1 by appending new powerful commands (MOVE, FILL, SEARCH and COMPARE) to the existing monitor to make it more useful and flexible. 8085 assembly language is used to execute this program. The letters used for abbreviation: M for MOVE, F for FILL, S for SEARCH and C for COMPARE.

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Publication Date
Tue Jan 01 2013
Journal Name
International Journal Of Application Or Innovation In Engineering & Management (ijaiem)
Probabilistic Neural Network for User Authentication Based on Keystroke Dynamics
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Computer systems and networks are increasingly used for many types of applications; as a result the security threats to computers and networks have also increased significantly. Traditionally, password user authentication is widely used to authenticate legitimate user, but this method has many loopholes such as password sharing, brute force attack, dictionary attack and more. The aim of this paper is to improve the password authentication method using Probabilistic Neural Networks (PNNs) with three types of distance include Euclidean Distance, Manhattan Distance and Euclidean Squared Distance and four features of keystroke dynamics including Dwell Time (DT), Flight Time (FT), mixture of (DT) and (FT), and finally Up-Up Time (UUT). The resul

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Publication Date
Mon Dec 01 2025
Journal Name
University Of Kirkuk Journal For Administrative And Economic Science
Anova For Fuzzy Data With Practical in The Medical Field
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This research study Blur groups (Fuzzy Sets) which is the perception of the most modern in the application in various practical and theoretical areas and in various fields of life, was addressed to the fuzzy random variable whose value is not real, but the numbers Millbh because it expresses the mysterious phenomena or uncertain with measurements are not assertive. Fuzzy data were presented for binocular test and analysis of variance method of random Fuzzy variables , where this method depends on a number of assumptions, which is a problem that prevents the use of this method in the case of non-realized.

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Publication Date
Thu Mar 13 2025
Journal Name
Academia Open
Deep Learning and Fusion Techniques for High-Precision Image Matting:
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General Background: Deep image matting is a fundamental task in computer vision, enabling precise foreground extraction from complex backgrounds, with applications in augmented reality, computer graphics, and video processing. Specific Background: Despite advancements in deep learning-based methods, preserving fine details such as hair and transparency remains a challenge. Knowledge Gap: Existing approaches struggle with accuracy and efficiency, necessitating novel techniques to enhance matting precision. Aims: This study integrates deep learning with fusion techniques to improve alpha matte estimation, proposing a lightweight U-Net model incorporating color-space fusion and preprocessing. Results: Experiments using the AdobeComposition-1k

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