15 research outputs found
Deep learning for COVID-19 diagnosis based on chest X-ray images
No full textCoronavirus disease 2019 (COVID-19) is a recent global pandemic that has affected many countries around the world, causing serious health problems, especially in the lungs. Although temperature testing is suggested as a firstline test for COVID-19, it was not reliable because many diseases have the same symptoms. Thus, we propose a deep learning method based on X-ray images that used a convolutional neural network (CNN) and transfer learning (TL) for COVID-19 diagnosis, and using gradient-weighted class activation mapping (Grad-CAM) technique for producing visual explanations for the COVID-19 infection area in the lung. The low sample size of coronavirus samples was considered a challenge, thus, this issue was overridden using data augmentation techniques. The study found that the proposed (CNN) and the modified pre-trained networks VGG16 and InceptionV3 achieved a promising result for COVID-19 diagnosis by using chest X-ray images. The proposed CNN was able to differentiate 284 patients with COVID-19 or normal with 98.2 percent for training accuracy and 96.66 percent for test accuracy and 100.0 percent sensitivity. The modified VGG16 achieved the best classification result between all with 100.0 percent for training accuracy and 98.33 percent for test accuracy and 100.0 percent sensitivity, but the proposed CNN overcame the others in the side of reducing the computational complexity and training time significantly
Deep learning-based cancer classification for microarray data: a systematic review
No full textDeep neural networks are robust techniques and recently used extensively for building cancer classification models from different types of data. Nowadays, microarray gene expression datasets consider an essential source of data that is used in cancer classifications. However, due to the small size of samples compared to the high dimensionality of microarray data, many machine learning techniques have failed to distinguish the most relevant and informatics genes. Therefore, deep learning is demand due to its ability to automatically discovering the complex relationship between features with significant accuracy and high performance. The current study aims to reveal the state-of-the-art of deep neural network architectures and how it can utilize from microarray data. Therefore, several deep neural network architectures were built such as CNN, DNN, RNN, DBN, DBM and DAE to be compatible with the different learning processes (supervised, unsupervised and semi-supervised). As a result, CNN considers the most common neural network architecture used in the medical field due to its robustness and high performance in cancer classification. Results indicate that choosing suitable architecture of the deep neural network and its hyperparameters is one of the most difficulties facing the researcher in designing models for cancer prediction and classification because there is no particular rule to ensure high prediction accuracy
A Review of the Book Nashat al-Masrah in the East (The Emergence of Theater in the East)
No full textThe art of play is the result of human social life, more than any other type of art in relation to social man, and accordingly, its connection with the new civilization can be emphasized more than other components. In the new era, the play is one of the most important topics for critical discussions, whether as a text or as a collection of narratives performed by actors on stage to the extent that the critical and historical books of this type of art have a wide range of the oldest types of art. One of the most recent works of this kind is Nashat 'al-Masrah fi al-Mashreq, (The Emergence of Theater in the East), whose author has studied the origin and evolution of this art in the Orient, focusing on Lebanon and Syria, Turkey and Iran. The article intends to provide a critical reading of it by adopting a descriptive method, and the results show that although the value of the book in question is small, the author has been able to use accurate methods in reviewing the evolution of the work as a historical-analytical book by using reliable documents and sources
Neighborhood search methods with Moth Optimization algorithm as a wrapper method for feature selection problems
No full textFeature selection methods are used to select a subset of features from data, therefore only the useful information can be mined from the samples to get better accuracy and improves the computational efficiency of the learning model. Moth-flam Optimization (MFO) algorithm is a population-based approach, that simulates the behavior of real moth in nature, one drawback of the MFO algorithm is that the solutions move toward the best solution, and it easily can be stuck in local optima as we investigated in this paper, therefore, we proposed a MFO Algorithm combined with a neighborhood search method for feature selection problems, in order to avoid the MFO algorithm getting trapped in a local optima, and helps in avoiding the premature convergence, the neighborhood search method is applied after a predefined number of unimproved iterations (the number of tries fail to improve the current solution). As a result, the proposed algorithm shows good performance when compared with the original MFO algorithm and with state-of-the-art approaches
Currency quality and changes in the behavior of depository institutions
No full textBanks and banking
THE INTEGRATIVE PERSONALITY IN THE NOVEL 'BAYT ABU BAYYUT' BY HUSSAM KHWAM AL YAHYA
No full textThis paper aims to study the integrative personality or fictional character within the crisis of self and reality in the novel "Bayt Abu Bayyut" by the Iraqi author Hussam Khwam Al Yahya. The novel delves into the existential crisis faced by Iraq and its people amidst Western colonization during the fall of the Ba'athist regime. This study seeks to elucidate the concept of the fictional character in general and the integrative personality specifically within the context of the complex dialectical relationship between self and reality, or reality and the imagined, while considering the influence and impact between the character and other elements or components of the narrative, such as time, place, and levels of linguistic performance employed in the narrative text.
The novel sheds light on the Iraqi reality within an open temporal context that encompasses history, the present, and the future simultaneously. The author skillfully combines two narrative trajectories regarding character construction: the relationship between the self and objective reality, and the relationship between the realistic and the dreamlike or the objective and the imagined. Through this, we analyze practically the contours of the integrative personality, its nature, semantic dimensions, temporal and spatial realms ”both inherited and contemporary ”within the context of the author's objective and artistic vision
Determining the Responsibility of the Insurance Company in Transporting International Goods
No full textThe paper deals with a complete analysis of the liability of the insurer in the international carriage of goods. The paper lays down the international instruments that govern the field and to what extent they affect the liability of the insurer. The paper also analyzes the conflict of laws issues related to the international insurance. The paper further does a study of the concepts related to the international insurance of carriage of goods and liability of the insurer. The focus has been on the common law principles. Aim and Objectives The paper analyzes the extent of liability of the insurance company. It would give a critical analysis of the liability and limitation of liability of the insurance company under different heads. The paper has targeted different instruments like international conventions, municipal laws and most importantly principles of common law on this subject. Scope: Due to the paucity of time and space the researchers have limited the scope of the paper to the liability of insurance company in general sense. There is also a lacuna in International Law on this particular aspect of insurer’s liability thus more attention is paid to common law principles and the Marine Insurance Act, 1906. The author has referred to case laws from different jurisdictions to give a wider prospective but has not done a comparative study of different legal regimes. PROBLEM STATEMENT: The International legal existing setup is not in itself equipped to deal with issues in determining the liability of the insurance company for the transport of international goods when the ship sank for a reason beyond the control of the captain. RESEARCH Methodology: The methodology adopted in the research for this paper involves a thorough reading and analysis of the liability of insurer in the international carriage of goods. The study is thus based primarily on a doctrinal-qualitative approach. Based on the research, co-relations have been drawn with the position of the law in other jurisdictions. DOI: 10.7176/IAGS/92-03 Publication date: December 31st 202
Behind the Veil An American Woman\u27s Memoir of the 1979 Iran Hostage Crisis
No full textIn Behind the Veil, Debra Johanyak weaves the personal with the historical in fascinating detail. Through her own story, a Midwestern woman married to an Iranian man and living in Iran during the hostage crisis, Johanyak provides the reader with sharp insights into similarities as well as differences between the two cultures. The memoir offers a thoughtful perspective on cultural chasms and the bridges we could build to conquer them. —Nahid Rachlin, author of Persian Girls, a memoir, and Jumping Over Fire, a novel
Debra Johanyak, a young American wife with an Iranian husband, gives a moving account of her experiences in the early days of the Iranian revolution in 1979. She not only vividly recounts the fears that the hostage crisis ignited in her, but also fondly recalls the deep bonds she formed with her Iranian in-laws. Elegiac and informative, the work is essential reading for anyone interested in gaining a better understanding about Iran and its people.—Guity Nashat, professor of Middle Eastern history, University of Illinois at Chicagohttps://ideaexchange.uakron.edu/uapress_publications/1104/thumbnail.jp
Fabrication of novel electropolymerized conductive polymer of hydrophobic perfluorinated aniline as transducer layer on glassy carbon electrode: application to midazolam as a model drug of benzodiazepines
No full textThe objective of this study is to fabricate solid-contact ion selective electrodes (SC-ISEs) that have long term stable potential. Various conducting polymers such as polyaniline and its derivatives have been successfully employed to improve the potential stability in SC-ISEs. Recently, the role of hydrophobicity at the interface between the conducting polymer solid contact and the ion sensing membrane has been investigated and figured out that the hydrophobic interfaces preclude water layer formation that deteriorate the SC-ISEs potential stability and reproducibility. In this work, a hydrophobic polyaniline derivative was fabricated on the surface of a glassy carbon electrode by electropolymerization of perfluorinated aniline monomers in acidic solution. The electropolymerized hydrophobic polymer was characterized by electrochemical impedance spectroscopy and X-ray photoelectron spectroscopy. The fabricated electrode was employed for determination of midazolam—a model drug-in pharmaceutical formulation without prior extraction. The SC-ISEs performance was optimized, and the potential drift was compared to control SC-ISEs, the SC-ISE linear range was 1 × 10–6–1 × 10–2 M, LOD was estimated to be 9.0 × 10–7 M, and potential drift was reduced to 100 μV/h. © 2023, The Author(s)
Memory based cuckoo search algorithm for feature selection of gene expression dataset
No full textCancer prediction has been shown to be important in the cancer research area. This importance has prompted many researchers to review machine learning-approaches to predict cancer outcome using gene expression dataset. This dataset consists of many genes (features) which can mislead the prediction ability of the machine learning methods, as some features may lead to confusion or inaccurate classification. Since finding the most informative genes for cancer prediction is challenging, feature selection techniques are recommended to pick important and relevant features out of large and complex datasets. In this research, we propose the Cuckoo search method as a feature selection algorithm, guided by the memory-based mechanism to save the most informative features that are identified by the best solutions. The purpose of the memory is to keep track of the selected features at every iteration and find the features that enhance classification accuracy. The suggested algorithm has been contrasted with the original algorithm using microarray datasets and the proposed algorithm has been shown to produce good results as compared to original and contemporary algorithms
