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Forecasting Cryptocurrency Market Trends with Machine Learning and Deep Learning
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Cryptocurrency became an important participant on the financial market as it attracts large investments and interests. With this vibrant setting, the proposed cryptocurrency price prediction tool stands as a pivotal element providing direction to both enthusiasts and investors in a market that presents itself grounded on numerous complexities of digital currency. Employing feature selection enchantment and dynamic trio of ARIMA, LSTM, Linear Regression techniques the tool creates a mosaic for users to analyze data using artificial intelligence towards forecasts in real-time crypto universe. While users navigate the algorithmic labyrinth, they are offered a vast and glittering selection of high-quality cryptocurrencies to select. The ability of the tool in analyzing past data on historical prices combined with machine learning, orchestrate an appealing scene of predictions equipped with choices and information, users turn into the main characters in a financial discovery story conducted by the cryptocurrency system. The numerical results also support the effectiveness of the tool as highlighted by standout corresponding numbers such as lower RMSE value 150.96 for ETH and minimized normalized RMSE scaled down to under, which is. The quantitative successes underline the usefulness of this tool to give precise predictions and improve user interaction in an entertaining world of cryptocurrency investments.

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Advance Science And Technology
MR Images Classification of Alzheimer's Disease Based on Deep Belief Network Method
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Background/Objectives: The purpose of this study was to classify Alzheimer’s disease (AD) patients from Normal Control (NC) patients using Magnetic Resonance Imaging (MRI). Methods/Statistical analysis: The performance evolution is carried out for 346 MR images from Alzheimer's Neuroimaging Initiative (ADNI) dataset. The classifier Deep Belief Network (DBN) is used for the function of classification. The network is trained using a sample training set, and the weights produced are then used to check the system's recognition capability. Findings: As a result, this paper presented a novel method of automated classification system for AD determination. The suggested method offers good performance of the experiments carried out show that the

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Publication Date
Mon Jun 30 2014
Journal Name
Al-kindy College Medical Journal
Evaluation of D-Dimer in the diagnosis of suspected deep vein thrombosis
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Background: Deep vein thrombosis is a multi causal disease and its one of most common venous disorder, but only one quarter of the patients who have signs and symptoms of a clot in the vein actually have thrombosis and need treatment .The disease can be difficult to diagnose. Venous ultrasound in combination with clinical finding is accurate for venous thromboembolism, its costly because a large number of patients with suspicious signs and symptoms. Venography still the gold standard for venous thromboembolism but it is invasive. The D-dimer increasingly is being seen as valuable tool rolling out venous thromboembolism and sparing low risk patients for further workup.Objectives: this study has designed the role of D-dimer to confirm diag

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Publication Date
Tue Apr 30 2024
Journal Name
Iraqi Journal Of Science
Crescent Moon Visibility: A New Criterion using Deep learned Artificial Neural-Network
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     Many authors investigated the problem of the early visibility of the new crescent moon after the conjunction and proposed many criteria addressing this issue in the literature. This article presented a proposed criterion for early crescent moon sighting based on a deep-learned pattern recognizer artificial neural network (ANN) performance. Moon sight datasets were collected from various sources and used to learn the ANN. The new criterion relied on the crescent width and the arc of vision from the edge of the crescent bright limb. The result of that criterion was a control value indicating the moon's visibility condition, which separated the datasets into four regions: invisible, telescope only, probably visible, and certai

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Publication Date
Wed Jan 01 2020
Journal Name
International Journal Of Computational Intelligence Systems
Evolutionary Feature Optimization for Plant Leaf Disease Detection by Deep Neural Networks
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Publication Date
Mon Dec 31 2018
Journal Name
Iraqi Journal Of Market Research And Consumer Protection
EXPOSURE TO TELEVISION PROMOTION OF PHARMACEUTICAL PRODUCTS AND TRENDS TOWARDS THEM / FIELD RESEARCH FOR A SAMPLE OF THE AUDIENCE IN THE CITY OF BAGHDAD: EXPOSURE TO TELEVISION PROMOTION OF PHARMACEUTICAL PRODUCTS AND TRENDS TOWARDS THEM / FIELD RESEARCH FOR A SAMPLE OF THE AUDIENCE IN THE CITY OF BAGHDAD
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A field study was conducted on a sample of the public in Baghdad to study the audience's exposure to the television promotion of pharmaceutical products and their trends in order to determine the rate of exposure of the public to the television promotion of pharmaceutical products according to the theory of uses and rumors and to determine the public's attitudes towards television promotion of pharmaceutical products. A survey of (25) a questions was distributed to a sample of the audience of 150 people. The statistical program SPSS was used to unload the data and for the calculation of frequencies and percentages and correlation coefficients. The research reached several results, Most importantly, the television promotion is well receiv

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Publication Date
Fri Apr 26 2024
Journal Name
Mathematical Modelling Of Engineering Problems
Solving Tri-criteria: Total Completion Time, Total Earliness, and Maximum Tardiness Using Exact and Heuristic Methods on Single-Machine Scheduling Problems
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Publication Date
Mon Jun 15 2020
Journal Name
Al-academy
Saudi society’s trends towards visiting museums and art galleries: منال بنت مرشد الحربي -حنان بنت يوسف الأحمد-مها بنت عبد الله السنان
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The aim of the research is to identify the trends of Saudi society towards visiting art galleries and museums in light of economic and social transformations after the implementation of the 2030 vision plans. The importance of the research is to track the reasons behind the reluctance of members of society to visit such cultural institutions, and to plan proposals and recommendations for how to attract members of society and motivate them. This research followed the descriptive approach, and the study sample reached 103 members of the Saudi community. several research tools were used in this research such as questionnaire, personal interviews in addition to the researcher notes. The results concluded that the art galleries attract the ap

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Publication Date
Sun Dec 02 2018
Journal Name
Journal Of The College Of Education For Women
The Role of Local Satellite Channels in the formation of knowledge and trends of the Iraqi Public Towards Terrorism: A Field Study
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Terrorism is a global phenomenon that engulfs most regions of the world to varying degrees. Media outlets are aware of the many incidents of violence and terrorism that have increased in recent times. The differences between the size of the phenomenon in different societies are the causes and severity of the phenomenon. On the role of local satellite channels in shaping the knowledge and trends of the Iraqi public towards the events of terrorism, in light of the assumptions of reliance on the media. The importance of this study is that it assesses the role of local satellite channels in the formation of knowledge and trends The study seeks to know the extent of exposure of the Iraqi public to local satellite channels, and to reveal the e

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Publication Date
Fri Jan 01 2016
Journal Name
Al–bahith Al–a'alami
The Influence of Turkish Soap Operas in the Behavior and Trends of the Iraqi Audience (A Field Study on Iraqi University's Students)
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This research seeks the effects of dubbed Turkish TV series on Iraqi audiences. The chosen sample is about 600 Iraqi students at Baghdad and al-Anbar Universities. This study consists of four sections: section one deals with the theoretical framework of the study. Section two studies the dubbed Turkish TV series. The third section explores the role of mass media in forming tendencies, and the last section seeks the field study by analyzing the tendencies if Iraqi viewers of these series.
The goal of this study is to know the role these series played in affecting the behavior and attitudes of Iraqi people and how it can change their morals.
The research ends with the number of results like the negative effect of these series on the

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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Fuzzy Analytic Hierarchy Process FEAHP to Prioritize The Evaluation of The Main and Subsidiary Criteria in B2B Industrial Market Sectors – Applied Research
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The research aims to define the main and subsidiary criteria for evaluating the industrial market sectors and proposing a model for arranging these criteria according to priority and knowing the highest criteria in terms of relative importance in the General Company for Automobile Trade and Machinery, and for the purpose of establishing this model, experiences in the concerned company were approved, and this study proposes a multi-criteria decision model According to the FEAHP, the expanded fuzzy hierarchical analysis method enables the commercial company to develop clear strategic policies on which the company’s management system depends on determining criteria for evaluating and selecting market sectors and making appropriate

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