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Feature extraction for co-occurrence-based cosine similarity score of text documents
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Publication Date
Sun Jan 01 2017
Journal Name
Aro-the Scientific Journal Of Koya University
A Comparative Study for String Metrics and the Feasibility of Joining them as Combined Text Similarity Measures
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Publication Date
Mon Aug 01 2016
Journal Name
2016 38th Annual International Conference Of The Ieee Engineering In Medicine And Biology Society (embc)
Myoelectric feature extraction using temporal-spatial descriptors for multifunction prosthetic hand control
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Publication Date
Sun Jan 16 2022
Journal Name
Iraqi Journal Of Science
Proposed Hiding Text in Text Based On RNA for Encoding Secret Information
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In any security system, we need a high level of security, to maintain the secrecy of important data. Steganography is one of the security systems that are hiding secret information within a certain cover (video, image, sound, text), so that the adversary does not suspect the existence of such confidential information. In our proposed work will hide secret messages (Arabic or English) text in the Arabic cover text, we employed the RNA as a tool for encoding the secret information and used non-printed characters to hide these codes. Each character (English or Arabic) is represented by using only six bits based on secret tables this operation has provided a good compression since each Arabic character needs 16 bits and each English characte

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Publication Date
Wed Dec 30 2020
Journal Name
Iraqi Journal Of Science
The Evaluation of Accuracy Performance in an Enhanced Embedded Feature Selection for Unstructured Text Classification
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Text documents are unstructured and high dimensional. Effective feature selection is required to select the most important and significant feature from the sparse feature space. Thus, this paper proposed an embedded feature selection technique based on Term Frequency-Inverse Document Frequency (TF-IDF) and Support Vector Machine-Recursive Feature Elimination (SVM-RFE) for unstructured and high dimensional text classificationhis technique has the ability to measure the feature’s importance in a high-dimensional text document. In addition, it aims to increase the efficiency of the feature selection. Hence, obtaining a promising text classification accuracy. TF-IDF act as a filter approach which measures features importance of the te

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Publication Date
Thu Jan 01 2015
Journal Name
Journal Of Theoretical And Applied Information Technology
Graph based text representation for document clustering
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Advances in digital technology and the World Wide Web has led to the increase of digital documents that are used for various purposes such as publishing and digital library. This phenomenon raises awareness for the requirement of effective techniques that can help during the search and retrieval of text. One of the most needed tasks is clustering, which categorizes documents automatically into meaningful groups. Clustering is an important task in data mining and machine learning. The accuracy of clustering depends tightly on the selection of the text representation method. Traditional methods of text representation model documents as bags of words using term-frequency index document frequency (TFIDF). This method ignores the relationship an

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Publication Date
Sun Jan 01 2017
Journal Name
Iec2017 Proceedings Book
Improving TF-IDF with Singular Value Decomposition (SVD) for Feature Extraction on Twitter
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Publication Date
Thu Dec 29 2016
Journal Name
Ibn Al-haitham Journal For Pure And Applied Sciences
Proposal for Exchange Text message Based on Image
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     The messages are ancient method to exchange information between peoples. It had many ways to send it with some security.

    Encryption and steganography was oldest ways to message security, but there are still many problems in key generation, key distribution, suitable cover image and others. In this paper we present proposed algorithm to exchange security message without any encryption, or image as cover to hidden. Our proposed algorithm depends on two copies of the same collection images set (CIS), one in sender side and other in receiver side which always exchange message between them.

      To send any message text the sender converts message to ASCII c

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Publication Date
Sat Jan 01 2022
Journal Name
Proceedings Of International Conference On Computing And Communication Networks
Speech Gender Recognition Using a Multilayer Feature Extraction Method
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Publication Date
Wed Feb 08 2023
Journal Name
Iraqi Journal Of Science
Texture Features Analysis using Gray Level Co-occurrence Matrix for Abnormality Detection in Chest CT Images
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Texture is an important characteristic for the analysis of many types of images because it provides a rich source of information about the image. Also it provides a key to understand basic mechanisms that underlie human visual perception. In this paper four statistical feature of texture (Contrast, Correlation, Homogeneity and Energy) was calculated from gray level Co-occurrence matrix (GLCM) of equal blocks (30×30) from both tumor tissue and normal tissue of three samples of CT-scan image of patients with lung cancer. It was found that the contrast feature is the best to differentiate between textures, while the correlation is not suitable for comparison, the energy and homogeneity features for tumor tissue always greater than its valu

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Publication Date
Sat May 01 2021
Journal Name
Journal Of Physics: Conference Series
Image Steganography using Dynamic Threshold based on Discrete Cosine Transform
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The art of preventing the detection of hidden information messages is the way that steganography work. Several algorithms have been proposed for steganographic techniques. A major portion of these algorithms is specified for image steganography because the image has a high level of redundancy. This paper proposed an image steganography technique using a dynamic threshold produced by the discrete cosine coefficient. After dividing the green and blue channel of the cover image into 1*3-pixel blocks, check if any bits of green channel block less or equal to threshold then start to store the secret bits in blue channel block, and to increase the security not all bits in the chosen block used to store the secret bits. Firstly, store in the cente

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