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Extractive Multi-Document Summarization Model Based On Different Integrations of Double Similarity Measures

Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload. 

Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and defined as a single-objective optimization problem. Also, for improving the performance of the proposed model, different integrations concerning two similarity measures have been introduced and applied to the proposed model along with the single similarity measures that are based on using Cosine, Dice and  similarity measures for measuring text similarity. For solving the proposed model, Genetic Algorithm (GA) has been used. Document sets supplied by Document Understanding Conference 2002 ( ) have been used for the proposed system as an evaluation dataset. Also, as an evaluation metric, Recall-Oriented Understudy for Gisting Evaluation ( ) toolkit has been used for performance evaluation of the proposed method. Experimental results have illustrated the positive impact of measuring text similarity using double integration of similarity measures against single similarity measure when applied to the proposed model wherein the best performance in terms of  and  has been recorded for the integration of Cosine similarity and  similarity.

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Publication Date
Wed Apr 01 2015
Journal Name
Journal Of Economics And Administrative Sciences
Multi-level model of the factors that affect the escalation of dust in Iraq

In this research The study of Multi-level  model (partial pooling model) we consider The partial pooling model which is one Multi-level  models and one of  the Most important models and extensive use and application in the analysis of the data .This Model characterized by the fact that the treatments take hierarchical or structural Form, in this partial pooling models, Full Maximum likelihood FML was used to estimated parameters of partial pooling models (fixed and random ), comparison between the preference of these Models, The application was on the Suspended Dust data in Iraq, The data were for four and a half years .Eight stations were selected randomly  among the stations in Iraq. We use Akaik′s Informa

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Publication Date
Fri Mar 01 2019
Journal Name
Applied Acoustics
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Publication Date
Tue May 23 2023
Journal Name
Journal Of Sensors
On-Board Digital Twin Based on Impedance and Model Predictive Control for Aerial Robot Grasping

Aerial manipulation of objects has a number of advantages as it is not limited by the morphology of the terrain. One of the main problems of the aerial payload process is the lack of real-time prediction of the interaction between the gripper of the aerial robot and the payload. This paper introduces a digital twin (DT) approach based on impedance control of the aerial payload transmission process. The impedance control technique is implemented to develop the target impedance based on emerging the mass of the payload and the model of the gripper fingers. Tracking the position of the interactional point between the fingers of gripper and payload, inside the impedance control, is achieved using model predictive control (MPD) approach.

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Publication Date
Tue Dec 01 2015
Journal Name
Journal Of Engineering
Improved Automatic Registration Adjustment of Multi-source Remote Sensing Datasets

Registration techniques are still considered challenging tasks to remote sensing users, especially after enormous increase in the volume of remotely sensed data being acquired by an ever-growing number of earth observation sensors. This surge in use mandates the development of accurate and robust registration procedures that can handle these data with varying geometric and radiometric properties. This paper aims to develop the traditional registration scenarios to reduce discrepancies between registered datasets in two dimensions (2D) space for remote sensing images. This is achieved by designing a computer program written in Visual Basic language following two main stages: The first stage is a traditional registration p

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Publication Date
Wed Jun 01 2022
Journal Name
Baghdad Science Journal
Advanced GIS-based Multi-Function Support System for Identifying the Best Route

Geographic Information Systems (GIS) are obtaining a significant role in handling strategic applications in which data are organized as records of multiple layers in a database. Furthermore, GIS provide multi-functions like data collection, analysis, and presentation. Geographic information systems have assured their competence in diverse fields of study via handling various problems for numerous applications. However, handling a large volume of data in the GIS remains an important issue. The biggest obstacle is designing a spatial decision-making framework focused on GIS that manages a broad range of specific data to achieve the right performance. It is very useful to support decision-makers by providing GIS-based decision support syste

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Publication Date
Thu Nov 30 2023
Journal Name
Iraqi Journal Of Science
A Key Based Hybrid Approach for Privacy and Integrity in Multi-Cloud

    Before users store data in the cloud, many security issues must be addressed, as they will have no direct control over the data that has been outsourced to the cloud, particularly personal and sensitive data (health, finance, military, etc.). This article proposes a system based on chaotic maps for private key generation. A hybrid encryption for fast and secure cryptography. In addition to a multi-cloud storage with Pseudonymized file names to preserve user data privacy on the cloud while minimizing data loss. As well as a hash approach to check data integrity. AES in combination with RSA and fragmenting the file is used for the encryption. Integrity is cheeked using SHA-3. The experiments demonstrated that the key generation stra

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Publication Date
Wed May 31 2023
Journal Name
International Journal Of Sustainable Development And Planning
Prediction of Formal Transformations in City Structure (Kufa as a Model) Based on the Cellular Automation Model and Markov Chains

The research utilizes data produced by the Local Urban Management Directorate in Najaf and the imagery data from the Landsat 9 satellite, after being processed by the GIS tool. The research follows a descriptive and analytical approach; we integrated the Markov chain analysis and the cellular automation approach to predict transformations in city structure as a result of changes in land utilization. The research also aims to identify approaches to detect post-classification transformations in order to determine changes in land utilization. To predict the future land utilization in the city of Kufa, and to evaluate data accuracy, we used the Kappa Indicator to determine the potential applicability of the probability matrix that resulted from

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Publication Date
Mon Dec 03 2018
Journal Name
Association Of Arab Universities Journal Of Engineering Sciences
Condition assessment and rehabilitation for trunk sewer deterioration based on Semi-Markov model

An accurate assessment of the pipes’ conditions is required for effective management of the trunk sewers. In this paper the semi-Markov model was developed and tested using the sewer dataset from the Zublin trunk sewer in Baghdad, Iraq, in order to evaluate the future performance of the sewer. For the development of this model the cumulative waiting time distribution of sewers was used in each condition that was derived directly from the sewer condition class and age data. Results showed that the semi-Markov model was inconsistent with the data by adopting ( 2 test) and also, showed that the error in prediction is due to lack of data on the sewer waiting times at each condition state which can be solved by using successive conditi

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Publication Date
Tue Nov 19 2024
Journal Name
Journal Of The College Of Basic Education
Fuzzy Nonparametric Regression Model Estimation Based on some Smoothing Techniques With Practical Application

In this research, we use fuzzy nonparametric methods based on some smoothing techniques, were applied to real data on the Iraqi stock market especially the data about Baghdad company for soft drinks for the year (2016) for the period (1/1/2016-31/12/2016) .A sample of (148) observations was obtained in order to construct a model of the relationship between the stock prices (Low, high, modal) and the traded value by comparing the results of the criterion (G.O.F.) for three techniques , we note that the lowest value for this criterion was for the K-Nearest Neighbor at Gaussian function .

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Publication Date
Tue Sep 10 2019
Journal Name
Periodicals Of Engineering And Natural Sciences (pen)
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