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Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index
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Forest fires continue to rise during the dry season and they are difficult to stop. In this case, high temperatures in the dry season can cause an increase in drought index that could potentially burn the forest every time. Thus, the government should conduct surveillance throughout the dry season. Continuous surveillance without the focus on a particular time becomes ineffective and inefficient because of preventive measures carried out without the knowledge of potential fire risk. Based on the Keetch-Byram Drought Index (KBDI), formulation of Drought Factor is used just for calculating the drought today based on current weather conditions, and yesterday's drought index. However, to find out the factors of drought a day after, the data is needed about the weather. Therefore, we need an algorithm that can predict the dryness factor. So, the most significant fire potential can be predicted during the dry season. Moreover, daily prediction of the dry season is needed each day to conduct the best action then a qualified preventive measure can be carried out. The method used in this study is the backpropagation algorithm which has functions for calculating, testing and training the drought factors. By using empirical data, some data are trained and then tested until it can be concluded that 100% of the data already well recognized. Furthermore, some other data tested without training, then the result is 60% of the data match. In general, this algorithm shows promising results and can be applied more to complete several variables supporters.

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Publication Date
Fri Sep 08 2006
Journal Name
Journal Of Engineering
INFLUENCE OF DEFECT IN THE CONCRETE PILES USING NON-DESTRUCTIVE TESTING
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This paper presents the results of experimental investigation carried out on concrete model piles to study the behaviour of defective piles. This was achieved by employing non-destructive tests using ultrasonic waves. It was found that the reduction in pile stiffness factor is found to be about (26%) when the defect ratio increased from (5%) to (15%). The modulus of elasticity reduction factor as well as the dynamic modulus of elasticity reduction factor increase with the defect ratio

Publication Date
Sun Mar 03 2024
Journal Name
Mesopotamian Journal Of Cybersecurity
Using Information Technology for Comprehensive Analysis and Prediction in Forensic Evidence
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With the escalation of cybercriminal activities, the demand for forensic investigations into these crimeshas grown significantly. However, the concept of systematic pre-preparation for potential forensicexaminations during the software design phase, known as forensic readiness, has only recently gainedattention. Against the backdrop of surging urban crime rates, this study aims to conduct a rigorous andprecise analysis and forecast of crime rates in Los Angeles, employing advanced Artificial Intelligence(AI) technologies. This research amalgamates diverse datasets encompassing crime history, varioussocio-economic indicators, and geographical locations to attain a comprehensive understanding of howcrimes manifest within the city. Lev

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Publication Date
Sat Dec 31 2022
Journal Name
Wasit Journal Of Computer And Mathematics Science
An Improved Method for Hiding Text in Image Using Header Image
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The necessities of steganography methods for hiding secret message into images have been ascend. Thereby, this study is to generate a practical steganography procedure to hide text into image. This operation allows the user to provide the system with both text and cover image, and to find a resulting image that comprises the hidden text inside. The suggested technique is to hide a text inside the header formats of a digital image. Least Significant Bit (LSB) method to hide the message or text, in order to keep the features and characteristics of the original image are used. A new method is applied via using the whole image (header formats) to hide the image. From the experimental results, suggested technique that gives a higher embe

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Publication Date
Sun Sep 04 2016
Journal Name
Baghdad Science Journal
Spectrophotometric Determination of Chromium Using Indigo Carmine -Application in Various Samples
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A rapid, simple and sensitive spectrophotometric method for the determination of trace amounts of chromium is studied. The method is based on the interaction of chromium with indigo carmine dye in acidic medium and the presence of oxalates as a catalyst for interaction, and after studying the absorption spectrum of the solution resulting observed decrease in the intensity of the absorption. As happened (Bleaching) for color dye, this palace and directly proportional to the chromium (VI) amount was measured intensity of the absorption versus solution was figurehead at a wavelength of 610 nm. A plot of absorbance with chromium (VI) concentration gives a straight line indicating that Beer’s law has been obeyed over the range of 0.5

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Publication Date
Fri Jan 01 2016
Journal Name
Journal Of Computer And Communications
Pathfinding in Strategy Games and Maze Solving Using A* Search Algorithm
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Publication Date
Sat Jul 01 2023
Journal Name
Journal Of Engineering
Study the Effect of using RAP in Warm Mix Asphalt Pavement.
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Sustainability is providing the needs without compromising the ability of the strategical forming to meet their requirements. The production of warm asphalt mixtures using recycled pavements produces economic and environmentally friendly mixtures, which is the most important advantage of this work. This research aims to determine the effect of recycled asphalt concrete (RAP) on the indirect tensile strength of warm asphalt mixtures and Marshall Properties. Models of warm asphalt mixtures using Aggregate from the Al-Nibaay quarry, Asphalt with a degree of penetration (40-50) from the refinery of the cycle, and obtained Recycled asphalt concrete from Salah Al-Din Road, Al-Ameriya area in Baghdad are prepared. Use five rati

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Publication Date
Mon Jan 01 2024
Journal Name
Explainable Artificial Intelligence In The Digital Sustainability Administration
Artificial Intelligence and Trends Using in Sustainability Audit: A Bibliometric Analysis
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Publication Date
Mon Mar 30 2009
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Prediction of bubble size in Bubble columns using Artificial Neural Network
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In the literature, several correlations have been proposed for bubble size prediction in bubble columns. However these correlations fail to predict bubble diameter over a wide range of conditions. Based on a data bank of around 230 measurements collected from the open literature, a correlation for bubble sizes in the homogenous region in bubble columns was derived using Artificial Neural Network (ANN) modeling. The bubble diameter was found to be a function of six parameters: gas velocity, column diameter, diameter of orifice, liquid density, liquid viscosity and liquid surface tension. Statistical analysis showed that the proposed correlation has an Average Absolute Relative Error (AARE) of 7.3 % and correlation coefficient of 92.2%. A

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Publication Date
Tue Jun 17 2025
Journal Name
Research In Social Sciences
Using Chatbot and ChatGPT as Useful Tools in Scientific Academic Writing
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This review investigates the practice and influence of chatbots and ChatGPT as employable tools in writing for scientific academic purposes. A primary collection of 150 articles was gathered from academic databases, but it was systematically chosen and refined to include 30 studies that focused on the use of ChatGPT and chatbot technology in academic writing contexts. Chatbots and ChatGPT in writing enhancement, support for student learning at higher education institutions, scientific and medical writing, and the evolution of research and academic publishing are some of the topics covered in the reviewed literature. The review finds these tools helpful, with their greatest advantages being in areas such as structuring writings, gram

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Publication Date
Fri Jun 01 2018
Journal Name
International Journal Of Computer Science Trends And Technology
Secure Video Data Deduplication in the Cloud Storage Using Compressive Sensing
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Cloud storage provides scalable and low cost resources featuring economies of scale based on cross-user architecture. As the amount of data outsourced grows explosively, data deduplication, a technique that eliminates data redundancy, becomes essential. The most important cloud service is data storage. In order to protect the privacy of data owner, data are stored in cloud in an encrypted form. However, encrypted data introduce new challenges for cloud data deduplication, which becomes crucial for data storage. Traditional deduplication schemes cannot work on encrypted data. Existing solutions of encrypted data deduplication suffer from security weakness. This paper proposes a combined compressive sensing and video deduplication to maximize

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