We propose a new method for detecting the abnormality in cerebral tissues present within Magnetic Resonance Images (MRI). Present classifier is comprised of cerebral tissue extraction, image division into angular and distance span vectors, acquirement of four features for each portion and classification to ascertain the abnormality location. The threshold value and region of interest are discerned using operator input and Otsu algorithm. Novel brain slices image division is introduced via angular and distance span vectors of sizes 24˚ with 15 pixels. Rotation invariance of the angular span vector is determined. An automatic image categorization into normal and abnormal brain tissues is performed using Support Vector Machine (SVM). Standard Deviation, Mean, Energy and Entropy are extorted using the histogram approach for each merger space. These features are found to be higher in occurrence in the tumor region than the non-tumor one. MRI scans of the five brains with 60 slices from each are utilized for testing the proposed method’s authenticity. These brain images (230 slices as normal and 70 abnormal) are accessed from the Internet Brain Segmentation Repository (IBSR) dataset. 60% images for training and 40% for testing phase are used. Average classification accuracy as much as 98.02% (training) and 98.19% (testing) are achieved.
Steganography is the art of secret communication. Its purpose is to hide the presence of information, using, for example, images as covers. The frequency domain is well suited for embedding in image, since hiding in this frequency domain coefficients is robust to many attacks. This paper proposed hiding a secret image of size equal to quarter of the cover one. Set Partitioning in Hierarchal Trees (SPIHT) codec is used to code the secret image to achieve security. The proposed method applies Discrete Multiwavelet Transform (DMWT) for cover image. The coded bit stream of the secret image is embedded in the high frequency subbands of the transformed cover one. A scaling factors ? and ? in frequency domain control the quality of the stego
... Show MoreIt is noted in the title that the paper studies the viewpoint in the novel The Dog and the Long Night by the Iranian novelist Shahranoush Parsi Pour and in the novel Alibaba's Sad Night by the Iraqi novelist Abdulkhaliq Ar-Rikabi. Both are well known novelists, and about whose stories and novels many critical books, MA theses, and Ph.D. dissertations have been written. Also, some of their literary works have won prizes. Here, the researcher shed light on the concept of viewpoint, its types, and its importance in novels in general. This was done along with tackling the two viewpoints in both novels, where similarities and differences were identified. For this end, the researcher has adopted the analytic-descriptive appro
... Show MoreIt is very known how great is the role of the Jewish writers in the system of the Zionist movement. The movement relied on writers and writers to carry out their programs, especially those pertaining to the creation of a "national homeland" for Jews. Most Jewish writers sang of Palestine even though they were not born there.
On such a basis, we have followed closely the writings of writers, critics and others by the end of the nineteenth century and the beginning of the twentieth century. We found that these writings are based on one common question: What is the fate of the Jewish people?
Most of these writings were accompanied by Theodor Herzl's proj
... Show MoreOsteoarthritis (OA) is recognized as a main public health difficult. It is one of the major reasons of reduced function that diminishes quality of life worldwide. Osteoarthritis is a very common disorder affecting the joint cartilage. As there is no cure for osteoarthritis, treatments currently focus on management of symptoms. Pain relief, improved joint function, and joint stability are the main goals of therapy. The muscle weakness and muscle atrophy contribute to the disease process. So, rehabilitation and physiotherapy were often prescribed with the intention to alleviate pain and increase mobility. Medical therapy provides modest benefits in pain reduction and functional improvement; however, non-steroidal anti-inflammatory dru
... Show MoreIn this paper, a handwritten digit classification system is proposed based on the Discrete Wavelet Transform and Spike Neural Network. The system consists of three stages. The first stage is for preprocessing the data and the second stage is for feature extraction, which is based on Discrete Wavelet Transform (DWT). The third stage is for classification and is based on a Spiking Neural Network (SNN). To evaluate the system, two standard databases are used: the MADBase database and the MNIST database. The proposed system achieved a high classification accuracy rate with 99.1% for the MADBase database and 99.9% for the MNIST database
In this paper, integrated quantum neural network (QNN), which is a class of feedforward
neural networks (FFNN’s), is performed through emerging quantum computing (QC) with artificial neural network(ANN) classifier. It is used in data classification technique, and here iris flower data is used as a classification signals. For this purpose independent component analysis (ICA) is used as a feature extraction technique after normalization of these signals, the architecture of (QNN’s) has inherently built in fuzzy, hidden units of these networks (QNN’s) to develop quantized representations of sample information provided by the training data set in various graded levels of certainty. Experimental results presented here show that
... Show MoreSupport Vector Machines (SVMs) are supervised learning models used to examine data sets in order to classify or predict dependent variables. SVM is typically used for classification by determining the best hyperplane between two classes. However, working with huge datasets can lead to a number of problems, including time-consuming and inefficient solutions. This research updates the SVM by employing a stochastic gradient descent method. The new approach, the extended stochastic gradient descent SVM (ESGD-SVM), was tested on two simulation datasets. The proposed method was compared with other classification approaches such as logistic regression, naive model, K Nearest Neighbors and Random Forest. The results show that the ESGD-SVM has a
... Show MoreIn this paper two main stages for image classification has been presented. Training stage consists of collecting images of interest, and apply BOVW on these images (features extraction and description using SIFT, and vocabulary generation), while testing stage classifies a new unlabeled image using nearest neighbor classification method for features descriptor. Supervised bag of visual words gives good result that are present clearly in the experimental part where unlabeled images are classified although small number of images are used in the training process.
Secure data communication across networks is always threatened with intrusion and abuse. Network Intrusion Detection System (IDS) is a valuable tool for in-depth defense of computer networks. Most research and applications in the field of intrusion detection systems was built based on analysing the several datasets that contain the attacks types using the classification of batch learning machine. The present study presents the intrusion detection system based on Data Stream Classification. Several data stream algorithms were applied on CICIDS2017 datasets which contain several new types of attacks. The results were evaluated to choose the best algorithm that satisfies high accuracy and low computation time.
Colloidal dispersions of mono Au, Ag , Cu and bimetallic Ag/Au and Cu/Au
core/shell nanoparticles are synthesized by pulsed laser ablation of metals targets
immersed in 5 ml distilled water (DW). Surface Plasmon resonance (SPR) and
particle sizes are characterized by UV-VIS and HRTEM, the X-ray diffraction
shows the structure of core/shell. The Surface Plasmon resonance of the produced
nanoparticles solutions for silver nanoparticles about 402 nm and copper
nanoparticles about 636 nm. While for the core-shell observed two peaks of SPR,
Ag/Au core/shell at (406-516) nm, and Cu/Au core/shell observed one peak at
565nm, because the region of gold and copper close together. The shape and
particle size have been con