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A Framework for Predicting Airfare Prices Using Machine Learning
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Many academics have concentrated on applying machine learning to retrieve information from databases to enable researchers to perform better. A difficult issue in prediction models is the selection of practical strategies that yield satisfactory forecast accuracy. Traditional software testing techniques have been extended to testing machine learning systems; however, they are insufficient for the latter because of the diversity of problems that machine learning systems create. Hence, the proposed methodologies were used to predict flight prices. A variety of artificial intelligence algorithms are used to attain the required, such as Bayesian modeling techniques such as Stochastic Gradient Descent (SGD), Adaptive boosting (ADA), Decision Trees (DT), K-nearest neighbor (KNN), and Logistic Regression (LR), have been used to identify the parameters that allow for effective price estimation. These approaches were tested on a data set of an extensive Indian airline network. When it came to estimating flight prices, the results demonstrate that the Decision tree method is the best conceivable Algorithm for predicting the price of a flight in our particular situation with 89% accuracy. The SGD method had the lowest accuracy, which was 38 %, while the accuracies of the KNN, NB, ADA, and LR algorithms were 69 %, 45 %, and 43 %, respectively. This study's presented methodologies will allow airline firms to predict flight prices more accurately, enhance air travel, and eliminate delay dispersion. Index Terms— Machine learning, Prediction model, Airline price prediction, Software testing,

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Publication Date
Mon Mar 31 2025
Journal Name
International Journal Of Advanced Technology And Engineering Exploration
Breast cancer survival rate prediction using multimodal deep learning with multigenetic features
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Breast cancer is a heterogeneous disease characterized by molecular complexity. This research utilized three genetic expression profiles—gene expression, deoxyribonucleic acid (DNA) methylation, and micro ribonucleic acid (miRNA) expression—to deepen the understanding of breast cancer biology and contribute to the development of a reliable survival rate prediction model. During the preprocessing phase, principal component analysis (PCA) was applied to reduce the dimensionality of each dataset before computing consensus features across the three omics datasets. By integrating these datasets with the consensus features, the model's ability to uncover deep connections within the data was significantly improved. The proposed multimodal deep

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Publication Date
Sun Dec 01 2019
Journal Name
مجلة الاستاذ-
The Effect of Using PBLA on Iraqi EFL Academic Students` Learning Achievement
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Assessment should give more attention on the learning achievement of the curriculum. Portfolio- based learning assessment (PBLA) is utilized in language learning materials recently .It is assessment tools to test the learners’ learning for instance open-ended problem solving, and creative and critical thinking, imaginative, reflective, have the capacity to apply their information in new issues, and to express oral and composing. This paper aims to discover the impact of utilizing (PBLA) on students’ performance at College of Education (Ibn –Rushd) in English Department the third stage. To fulfill the aim, a sample of the study is (64) EFL students of two groups. The study used a test and an instrument design .The test group ut

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Publication Date
Wed May 17 2023
Journal Name
International Journal Of Computational Intelligence Systems
Prediction of ROP Zones Using Deep Learning Algorithms and Voting Classifier Technique
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Abstract<p>Retinopathy of prematurity (ROP) can cause blindness in premature neonates. It is diagnosed when new blood vessels form abnormally in the retina. However, people at high risk of ROP might benefit significantly from early detection and treatment. Therefore, early diagnosis of ROP is vital in averting visual impairment. However, due to a lack of medical experience in detecting this condition, many people refuse treatment; this is especially troublesome given the rising cases of ROP. To deal with this problem, we trained three transfer learning models (VGG-19, ResNet-50, and EfficientNetB5) and a convolutional neural network (CNN) to identify the zones of ROP in preterm newborns. The dataset to train th</p> ... Show More
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Publication Date
Mon Nov 27 2023
Journal Name
Journal Of Periodontal Research
Ability of gingival crevicular fluid volume, E‐cadherin, and total antioxidant capacity levels for predicting outcomes of nonsurgical periodontal therapy for periodontitis patients
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Abstract<sec><title>Objectives

To determine the potential of gingival crevicular fluid (GCF) volume, E‐cadherin and total antioxidant capacity (TAC) levels to predict the outcomes of nonsurgical periodontal therapy (NSPT) for periodontitis patients.

Background

NSPT is the gold‐standard treatment for periodontal pockets < 6 mm in depth, however, successful outcomes are not always guaranteed due to several factors. Periodontitis‐associated tissue destruction is evidenced by the increased level of soluble E‐cadherin and reduced antioxidants in oral fluids which could be used as predictors for success/failure of N

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Publication Date
Wed Jan 04 2023
Journal Name
College Of Islamic Sciences
Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange: Predicting the financial distress of companies using logistic regression and its impact on earnings per share in companies listed on the Iraqi Stock Exchange
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Abstract

The prevention of bankruptcy not only prolongs the economic life of the company and increases its financial performance, but also helps to improve the general economic well-being of the country. Therefore, forecasting the financial shortfall can affect various factors and affect different aspects of the company, including dividends. In this regard, this study examines the prediction of the financial deficit of companies that use the logistic regression method and its impact on the earnings per share of companies listed on the Iraqi Stock Exchange. The time period of the research is from 2015 to 2020, where 33 companies that were accepted in the Iraqi Stock Exchange were selected as a sample, and the res

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Publication Date
Sat Feb 09 2019
Journal Name
Journal Of The College Of Education For Women
A Study of the Problems of Learning and Translating Idioms
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Idioms are a very important part of the English language: you are told that if you want to go far (succeed) you should pull your socks up (make a serious effort to improve your behaviour, the quality of your work, etc.) and use your grey matter (brain).1 Learning and translating idioms have always been very difficult for foreign language learners. The present paper explores some of the reasons why English idiomatic expressions are difficult to learn and translate. It is not the aim of this paper to attempt a comprehensive survey of the vast amount of material that has appeared on idioms in Adams and Kuder (1984), Alexander (1984), Dixon (1983), Kirkpatrick (2001), Langlotz (2006), McCarthy and O'Dell (2002), and Wray (2002), among others

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Publication Date
Sat Jan 31 2026
Journal Name
International Journal Of Intelligent Engineering And Systems
Low-complexity Deep Learning for Joint Channel-type Identification and SNR Estimation in MIMO-OFDM Using CNN–BRNN with LUT Labels
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Channel estimation (CE) is essential for wireless links but becomes progressively onerous as Fifth Generation (5G) Multi-Input Multi-Output (MIMO) systems and extensive fading expand the search space and increase latency. This study redefines CE support as the process of learning to deduce channel type and signal-tonoise ratio (SNR) directly from per-tone Orthogonal Frequency-Division Multiplexing (OFDM) observations,with blind channel state information (CSI). We trained a dual deep model that combined Convolutional Neural Networks (CNNs) with Bidirectional Recurrent Neural Networks (BRNNs). We used a lookup table (LUT) label for channel type (class indices instead of per-tap values) and ordinal supervision for SNR (0–20 dB,5-dB steps). T

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Publication Date
Sat Feb 01 2014
Journal Name
Journal Of Economics And Administrative Sciences
Philosophical Framework To Intellectual Capital Readiness in Iraqi Organizations
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           This research aim to present theoretical and philosophical framework regards topic of intellectual capital readiness in Iraqi universities. That is, by using strategic map in balanced score card of Norton and Kaplan (2004). This research discusses theoretical content for three main aspects reflect in its nature elements of intellectual capital readiness in organizations. This includes human capital readiness, information capital readiness and organizational capital readiness. To clear each element, the authors relay on mechanism to determine gape per element of intellectual capital elements.

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Publication Date
Sat Dec 31 2022
Journal Name
Res Militaris
Deterritorialized States Within the Framework of Public International Law
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one of the most important consequences of climate change is the rise in sea levels, which leads to the drowning of some low-lying island states, which leads to them losing the elements of statehood and thus affecting their status as a state, this resulted in several proposals made by the jurisprudence of international law to solve this issue, perhaps the most important of which is the idea of the government in exile, and the proposal to continue recognition of submerged countries, in a way that makes it possible to talk about a new concept of states represented by deterritorialized states, all of which are ultimately proposals that contain great difficulties that hinder their implementation in reality.

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Publication Date
Wed Feb 20 2019
Journal Name
Political Sciences Journal
Iraqi Woman Political situation in Quota Framework after 2003
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Abstract Since 2003. Iraq has begun a new phase in its modern history, which was after a long period of tyranny, repression of freedom of expression, and women were no better off than men; they suffered marginalization and exclusion, but after the fall of the former regime and the adoption of a parliamentary system of government, The level of participation in the government; where it approved the share of women in the legislative authority called "quota" which reflects the legislative level of a certain proportion of the seats in Parliament, amounting to 25%, and this is approved by the Iraqi constitution for 2005. But it is noticeable that women in parliament did not work within the quota; in other words they belonged to the pol

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