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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 06 2021
Journal Name
المجلة العراقية لبحوث السوق وحماية المستهلك
The exposure of Baghdad slum residents to television drug advertisements and its trends
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Publication Date
Thu Dec 15 2022
Journal Name
Al-academy
Inventory of Saudi youth trends towards choosing fashion accessories
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This research aims to determine the Attitudes Towards Fashion accessories of Saudi youth, and the descriptive analytical method was used in this research. The research sample was 500 youth in Riyadh that age between 20 to less than 40.  The most important results show that young people prefer shoes by 53.2%, that 45.2% of young people prefer acquiring modern designs in fashion accessories, and the research emphasized the importance of studying the impact of rapid economic, social and cultural developments on young people’s attitudes towards fashion and its accessories, directing the attention of Saudi fashion designers towards complements Fashion to offer designs that match their trends

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Publication Date
Wed Jan 01 2014
Journal Name
The Saudi Journal For Dental Research
Oral cancer trends in Iraq from 2000 to 2008
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Abstract Background The aim of this study was to identify differences in oral cancer incidence among sexes, age groups and oral sites over time in Iraqi population. Methods Data was obtained from Iraqi cancer registry, differences and trends were assessed with the Wilcoxon matched-pairs signed-ranks test and Regression test, respectively. Results In Iraq from 2000 to 2008, there were 1787 new cases of oral cancer registered, 1035 in men and 752 in women. Cancer at all oral sites affected men more than women. The Tongue other (ICD-02) is the most frequent site follow by lip (ICD-00). Conclusion The decrease in the percent of oral cancer incidence in Iraq not compatible with the high percent of exposure to the risk factors, Iraqi cancer regis

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Publication Date
Fri Sep 15 2023
Journal Name
Al-academy
Modern trends in the architecture of mosques in Jordan
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This study analyzes the features of historical and modern mosques in Jordan compared to that of Amman. The architecture of the Jordanian mosques reflects the images of great ancient empires and kingdoms of Europe and the Middle East. This has happened due to the geographical position of the country. From the studies of historians and archaeologists, comparative analysis of planning solutions, the use of plastics and decor of the facades of mosques, and the literature on the construction methods of the mosques allow us to conclude that age-old traditions have been preserved through the establishment of mosques in both the countries. Besides, the emergence of new features in constructing mosques has been observed. We find the influence of

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Publication Date
Fri Jan 01 2021
Journal Name
Cogent Engineering
Content-based image retrieval: A review of recent trends
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Publication Date
Sat Jun 21 2025
Journal Name
Economics And Administrative Studies Journal (easj) (formerly Al-dananeer Journal)
The use of the MADC indicator for entry and exit from financial market.
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Publication Date
Thu Sep 01 2011
Journal Name
Journal Of Economics And Administrative Sciences
Analyzing the relationship between stock market volatility and economic activity in the USA
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This study examines the dynamic relationship between stock market and economic activity in the United States to verify the possibility of using financial indicators to monitor the turning points in the expected path of future economic activity. Has been used methodology (Johansen - Juselius) for the Co-integration and causal (Granger) to test the relationship between the (S & P 500 , DJ) index  and gross domestic product (GDP) in the United States for the period
(1960-2009). The results of the analysis revealed the existence of a causal relationship duplex (two-way) between the variables mentioned. which means the possibility of the use stock market indicators to pre

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Publication Date
Tue Jun 23 2020
Journal Name
Baghdad Science Journal
Anomaly Detection Approach Based on Deep Neural Network and Dropout
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   Regarding to the computer system security, the intrusion detection systems are fundamental components for discriminating attacks at the early stage. They monitor and analyze network traffics, looking for abnormal behaviors or attack signatures to detect intrusions in early time. However, many challenges arise while developing flexible and efficient network intrusion detection system (NIDS) for unforeseen attacks with high detection rate. In this paper, deep neural network (DNN) approach was proposed for anomaly detection NIDS. Dropout is the regularized technique used with DNN model to reduce the overfitting. The experimental results applied on NSL_KDD dataset. SoftMax output layer has been used with cross entropy loss funct

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Publication Date
Fri Jan 01 2021
Journal Name
Int. J. Agricult.
FORECASTING THE EXCHANGE RATES OF THE US DOLLAR AGAINST THE IRAQI DINAR USING THE BOX-JENKINS METHODOLOGY IN TIME SERIES WITH PRACTICAL APPLICATION
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The goal of the study is to discover the best model for forecasting the exchange rate of the US dollar against the Iraqi dinar by analyzing time series using the Box Jenkis approach, which is one of the most significant subjects in the statistical sciences employed in the analysis. The exchange rate of the dollar is considered one of the most important determinants of the relative level of the health of the country's economy. It is considered the most watched, analyzed and manipulated measure by the government. There are factors affecting in determining the exchange rate, the most important of which are the amount of money, interest rate and local inflation global balance of payments. The data for the research that represents the exchange r

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Publication Date
Tue Oct 19 2021
Journal Name
Big Data Summit 2: Hpc & Ai Empowering Data Analytics 2018 | Conference Paper
Deep Bayesian for Opinion-target identification
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The use of deep learning.

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