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Texture Classification Using Spline, Wavelet Decomposition and Fractal Dimension
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Publication Date
Mon Feb 28 2022
Journal Name
Journal Of Educational And Psychological Researches
The Social Dimension of the Phenomenon of Suicide in Iraq: Reasons and Proposals "Field Study in Baghdad Police Stations
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There have been many negative phenomena in Iraqi society, especially after the political crises over the last years, such as the spread of violence, the deterioration of the economic situation, the spread of unemployment and poverty, and the disintegration of social ties, divorce, and the entry of the scourge of drugs. Among the most dangerous of these emergent phenomena, the phenomenon of suicide among young people of both sex, which has grown and increased in an unprecedented manner, surpassing all known social norms in Iraqi society and the prevailing religious values. Suicide in Iraqi society has transformed from a simple case to a visible presence in all Iraqi provinces. Suicides cases have registered in all cities of Iraq and of bo

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Publication Date
Mon Mar 01 2010
Journal Name
Journal Of Economics And Administrative Sciences
The ethical dimension of administrative accountants And its impact on the improvement and growth of staff potential in the economic unit
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تعد المحاسبة بشكل عام علماً لكنها ليست من العلوم الصرفة وإنما من العلوم الإجتماعية مما يتطلب للتعامل مع المواضيع المحاسبية الأخذ بنظر الاعتبار الأشخاص المعنيين بالموضوع سواء كانوا المعدين للمخرجات المحاسبية أي المحاسبين، أو الاطراف ذوي المصالح المعنيين والمستفيدين من هذه المخرجات أي المستخدمين، ويعد المحاسب جزءاً من العملية الاجرائية نفسها وبهذا يكون دوره مزدوجاً يجمع بين كونه القائم بالبحث والقي

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Publication Date
Tue Jun 30 2015
Journal Name
International Journal Of Computer Techniques
Multifractal-Based Features for Medical Images Classification
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This paper presents a method to classify colored textural images of skin tissues. Since medical images havehighly heterogeneity, the development of reliable skin-cancer detection process is difficult, and a mono fractaldimension is not sufficient to classify images of this nature. A multifractal-based feature vectors are suggested hereas an alternative and more effective tool. At the same time multiple color channels are used to get more descriptivefeatures.Two multifractal based set of features are suggested here. The first set measures the local roughness property, whilethe second set measure the local contrast property.A combination of all the extracted features from the three colormodels gives a highest classification accuracy with 99.4

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Publication Date
Mon Jan 01 2024
Journal Name
Bio Web Of Conferences
An overview of machine learning classification techniques
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Machine learning (ML) is a key component within the broader field of artificial intelligence (AI) that employs statistical methods to empower computers with the ability to learn and make decisions autonomously, without the need for explicit programming. It is founded on the concept that computers can acquire knowledge from data, identify patterns, and draw conclusions with minimal human intervention. The main categories of ML include supervised learning, unsupervised learning, semisupervised learning, and reinforcement learning. Supervised learning involves training models using labelled datasets and comprises two primary forms: classification and regression. Regression is used for continuous output, while classification is employed

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Scopus (32)
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Publication Date
Fri Jan 05 2018
Journal Name
International Journal Of Science And Research (ijsr)
Image Steganography Based on Discrete Wavelet Transform and Chaotic Map, IJSR, Call for Papers, Online Journal
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'Steganography is the science of hiding information in the cover media', a force in the context of information sec, IJSR, Call for Papers, Online Journal

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Publication Date
Sun Aug 01 2021
Journal Name
Journal Of Physics: Conference Series
EEG Motor-Imagery BCI System Based on Maximum Overlap Discrete Wavelet Transform (MODWT) and cubic SVM
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Abstract<p>Communication of the human brain with the surroundings became reality by using Brain- Computer Interface (BCI) based mechanism. Electroencephalography (EEG) being the non-invasive method has become popular for interaction with the brain. Traditionally, the devices were used for clinical applications to detect various brain diseases but with the advancement in technologies, companies like Emotiv, NeuoSky are coming up with low cost, easily portable EEG based consumer graded devices that can be used in various application domains like gaming, education etc as these devices are comfortable to wear also. This paper reviews the fields where the EEG has shown its impact and the way it has p</p> ... Show More
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Publication Date
Fri Sep 15 2023
Journal Name
Al-academy
The plastic dimension of the balcony scene in the movie (Romeo and Juliet) and its relationship to the movie and theatrical original text
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This research deals with one scene from the movie Romeo and Juliet, which is the balcony scene, due to the importance of this scene in the formation of the construction of the subsequent events of the movie.

The first chapter contained the methodological framework of the research, where the research problem was identified in how Zeffirelli dealt with the balcony scene in the play Romeo and Juliet and enriched it in the cinematic language with a comparison with the original text of the scene. In the balcony scene with comparative parts between the film and the text and the limits of the research that was limited to the film Zeffirelli and the translated text by Munis Taha Hussein.

The second chapter contained the theoretic

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Publication Date
Wed Aug 27 2025
Journal Name
Journal Of Baghdad College Of Dentistry
Mesio-distal crown dimension of permanent dentition in normal, crowding, and spacing of young adult sample aged 18-25 years
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Background: This study aimed to assess the effect of tooth width in malocclusion in relation to normal, crowding, and spacing dentition. Materials and methods: The sample included dental casts of some dental students and orthodontic patients; their age was (18-25) years and having three groups normal, crowding, and spacing dentition groups. The sample was equally divided to three groups normal, crowding, and spacing dentition groups, each group contained 50 maxillary and 50 mandibular casts that were further subdivided by gender; all the stone casts were measured by highly sensitive digital vernier. Results and Conclusions: Non-significant side difference was found in both dental arches in the three studied groups. Males had higher mesiodis

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Publication Date
Tue May 16 2023
Journal Name
International Journal Of Online And Biomedical Engineering (ijoe)
Comparative Study of Anemia Classification Algorithms for International and Newly CBC Datasets
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Data generated from modern applications and the internet in healthcare is extensive and rapidly expanding. Therefore, one of the significant success factors for any application is understanding and extracting meaningful information using digital analytics tools. These tools will positively impact the application's performance and handle the challenges that can be faced to create highly consistent, logical, and information-rich summaries. This paper contains three main objectives: First, it provides several analytics methodologies that help to analyze datasets and extract useful information from them as preprocessing steps in any classification model to determine the dataset characteristics. Also, this paper provides a comparative st

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Publication Date
Tue Aug 31 2021
Journal Name
International Journal Of Intelligent Engineering And Systems
FDPHI: Fast Deep Packet Header Inspection for Data Traffic Classification and Management
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Traffic classification is referred to as the task of categorizing traffic flows into application-aware classes such as chats, streaming, VoIP, etc. Most systems of network traffic identification are based on features. These features may be static signatures, port numbers, statistical characteristics, and so on. Current methods of data flow classification are effective, they still lack new inventive approaches to meet the needs of vital points such as real-time traffic classification, low power consumption, ), Central Processing Unit (CPU) utilization, etc. Our novel Fast Deep Packet Header Inspection (FDPHI) traffic classification proposal employs 1 Dimension Convolution Neural Network (1D-CNN) to automatically learn more representational c

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Scopus (9)
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