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Sequential feature selection for heart disease detection using random forest
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Heart disease identification is one of the most challenging task that requires highly experienced cardiologists. However, in developing nations such as Ethiopia, there are a few cardiologists and heart disease detection is more challenging. As an alternative solution to cardiologist, this study proposed a more effective model for heart disease detection by employing random forest and sequential feature selection (SFS). SFS is an effective approach to improve the performance of random forest model on heart disease detection. SFS removes unrelated features in heart disease dataset that tends to mislead random forest model on heart disease detection. Thus, removing inappropriate and duplicate features from the training set with sequential feature selection approach plays significant role in improving the performance of the proposed model. The proposed feature selection approach is evaluated using real world clinical heart disease dataset collected from University of California Irvine (UCI) data repository. Empirical test on validation set reveals that the proposed model performs well as compared to the existing methods. Overall, the state of-the-art heart disease detection model with classification accuracy of 98.53% is proposed for heart disease detection using SFS and random forest model.

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Publication Date
Thu Jul 01 2021
Journal Name
Computers & Electrical Engineering
A new proposed statistical feature extraction method in speech emotion recognition
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Publication Date
Wed Jun 30 2021
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
VISUAL CONTAMINATION WITH RANDOM ADVERTISEMENTS AND THE POSSIBILITY OF APPLYING FINES TO THEIR OWNERS: VISUAL CONTAMINATION WITH RANDOM ADVERTISEMENTS AND THE POSSIBILITY OF APPLYING FINES TO THEIR OWNERS
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Baghdad governorate has many areas of distinctive architectural and architectural character, which are heritage and valuable areas that we must preserve and take care of. But we see many manifestations of it, which have a negative impact on buildings, areas and roads, so that they distort the view and thus lead to visual pollution in general. The research examined the visual pollution from random advertising, which stretched buildings, walls, electricity poles and sidewalks. The study covered different areas of al-Karkh and al-Rassafa (Jadreya Bridge, Nation Square, Jordan Square, alkindy Street)Most of the distortions were the result of non-removable posters, Handwriting, election candidate adve

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Publication Date
Mon Dec 06 2021
Journal Name
Iraqi Journal Of Science
Detecting and Monitoring the Vegetal Cover of Karbala Province (Iraq) Using Change Detection Methods
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Karbala province was one of the most important areas in Iraq and considered an
economic resource of vegetation such as trees of fruits, sieve and other vegetation.
This research aimed to utilize change detection for investigating the current
vegetation cover at last three decay. The main objectives of this research are collect
a group of studied area (Karbala province) satellite images in sequence time for
the same area, these image captured by Landsat (TM 1995, ETM+ 2005 and
Landsat 8 OLI (Operational Land Imager) 2015. Preprocessing such as atmosphere
correction and rectification has been done. Mosaic model between the parts of
studied area was performing. Gap filling consider being very important step has
be

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Publication Date
Sat Jan 13 2018
Journal Name
Journal Of Engineering
Producing Coordinate Time Series for Iraq's CORS Site for Detection Geophysical Phenomena
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Global Navigation Satellite Systems (GNSS) have become an integral part of wide range of applications. One of these applications of GNSS is implementation of the cellular phone to locate the position of users and this technology has been employed in social media applications. Moreover, GNSS have been effectively employed in transportation, GIS, mobile satellite communications, and etc. On the other hand, the geomatics sciences use the GNSS for many practical and scientific applications such as surveying and mapping and monitoring, etc.

In this study, the GNSS raw data of ISER CORS, which is located in the North of Iraq, are processed and analyzed to build up coordinate time series for the purpose of detection the

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Publication Date
Mon Oct 30 2023
Journal Name
Iraqi Journal Of Science
Transfer Learning Based Traffic Light Detection and Recognition Using CNN Inception-V3 Model
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Due to the lack of vehicle-to-infrastructure (V2I) communication in the existing transportation systems, traffic light detection and recognition is essential for advanced driver assistant systems (ADAS) and road infrastructure surveys. Additionally, autonomous vehicles have the potential to change urban transportation by making it safe, economical, sustainable, congestion-free, and transportable in other ways. Because of their limitations, traditional traffic light detection and recognition algorithms are not able to recognize traffic lights as effectively as deep learning-based techniques, which take a lot of time and effort to develop. The main aim of this research is to propose a traffic light detection and recognition model based on

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Publication Date
Fri Nov 05 2021
Journal Name
Semiconductor Science And Information Devices
Cladding Modified Fiber Bragg Grating for Copper Ions Detection
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This paper reports a fiber Bragg grating (FBG) as a biosensor. The FBGs were etched using a chemical agent,namely,hydrofluoric acid (HF). This implies the removal of some part of the cladding layer. Consequently, the evanescent field propagating out of the core will be closer to the environment and become more sensitive to the change in the surrounding. The proposed FBG sensor was utilized to detect toxic heavy metal ions aqueous medium namely, copper ions (Cu2+). Two FBG sensors were etched with 20 and 40 μm diameters and fabricated. The sensors were studied towards Cu2+ with different concentrations using wavelength shift as a result of the interaction between the evanescent field and copper ions. The FBG sensors showed

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Publication Date
Sat Aug 01 2015
Journal Name
International Journal Of Advanced Research In Computer Science And Software Engineering
Partial Encryption for Colored Images Based on Face Detection
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Publication Date
Thu Apr 18 2019
Journal Name
Al-kindy College Medical Journal
Detection Of Candida Albicans Responsible For Vulvovaginitis In Women
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Background: The vaginal microbial ecosystem stability preclude many other organisms but sometimes the vaginal micro biota is disturbed and this cause change in the normal

balance causing symptoms of vulvuvaginitis like abnormal or increased vaginal discharge, redness and itching.

Objective: To prove C. albicans presence in their vagina clinically and laboratory by culture of vaginal swab on two media.

Type of the study: This study is a case control study

Methods: This study is a case control study in which 100 clinically patient women admitted to maternity hospital in kalar city and khanaqin hospital during the pe

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Publication Date
Fri Dec 30 2022
Journal Name
Iraqi Journal Of Science
An Improved Outlier Detection Model for Detecting Intrinsic Plagiarism
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     In the task of detecting intrinsic plagiarism, the cases where reference corpus is absent are to be dealt with. This task is entirely based on inconsistencies within a given document. Detection of internal plagiarism has been considered as a classification problem. It can be estimated through taking into consideration self-based information from a given document.

The core contribution of the work proposed in this paper is associated with the document representation. Wherein, the document, also, the disjoint segments generated from it, have been represented as weight vectors demonstrating their main content. Where, for each element in these vectors, its average weight has been considered instead of its frequency.

Th

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Publication Date
Sun Oct 15 2023
Journal Name
Journal Of Yarmouk
Artificial Intelligence Techniques for Colon Cancer Detection: A Review
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