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Condition Prediction Models of Deteriorated Trunk Sewer Using Multinomial Logistic Regression and Artificial Neural Network
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Sewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the deterioration models' application showed that NNDM gave the highest overall prediction efficiency of 93.6% by adapting the confusion matrix test, while multinomial logistic regression was inconsistent with the data. The error in prediction of related model was due to its inability to reflect the dependent variable (condition classes) ordered nature.

Publication Date
Wed Aug 30 2023
Journal Name
Al-kindy College Medical Journal
Pancreatic Stone Protein/ regenerating Protein (PSP/reg) as a Biochemical Marker for prediction of Microvascular Complications of Type 2 Diabetes Mellitus
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Background: Type 2 diabetes mellitus (T2DM) characterized by insulin resistance (IR) and progressive decline in functional beta (β) cell mass partially due to increased β cell apoptosis rate. Pancreatic stone protein /regenerating protein (PSP/reg) is produced mainly by the pancreas and elevated drastically during pancreatic disorder. Beta cells are experiencing apoptosis that stimulate the expression of PSP/reg gene in surviving neighboring cells, and that PSP/reg protein is subsequently secreted from these cells which could play a role in their regeneration.

Objectives: To analyze serum levels of PSP/reg protein in T2DM patients and evaluate its correlation with the microvasc

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Publication Date
Sat Feb 07 2026
Journal Name
Asian Journal Of Pharmaceutical And Clinical Research
EVALUATING THE ANTI-INFLAMMATORY ACTIVITY OF ETHYL ACETATE AND METHANOL EXTRACTS OF LORANTHUS EUROPAEUS SEEDS IN RAT MODELS OF EXPERIMENTALLY INDUCED CHRONIC INFLAMMATION: A COMPARATIVE STUDY WITH DEXAMETHASONE
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Objective: Loranthus europaeus is a parasitic plant that lives on the branches of trees. The present study aimed to evaluate the anti-inflammatory effects of two different extracts on chronic inflammation induced by cotton pellets in rats. Methods: Loranthus seed was extracted by maceration with absolute methanol, in which dry Loranthus seeds were triturated in a mortar and macerated with 500 mL of methanol. After 24 h, the mixture was filtered, and the residue was re-extracted. The filtrates were combined and dried under vacuum. The mixture was mixed with 100 mL of distilled water and fractionated by petroleum ether and ethyl acetate using 70 mL × 3 times each. The organic fractions were dried, filtered, and evaporated to dryness.

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Publication Date
Sat Dec 01 2018
Journal Name
Journal Of Accounting And Financial Studies ( Jafs )
The role of artificial intelligence in achieving Customer satisfaction and its reflection on cost accounting: An applied research in the Iraqi electronic industries company
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Based economic units to technology to add innovations that lead to contribute to customer satisfaction, under intense competition and rapid development in customer taste, the economic units tend to apply the concepts that contribute to customer satisfaction led by the introduction of artificial intelligence techniques. In the production prominent role in the contributing and responding to the rapid changes in customer tastes, and consequent impact this in achieving customer satisfaction. Search gained importance of relying on artificial intelligence techniques to achieve customer satisfaction through speed of response to changes in the tastes of customers and thus be able to increase its market share، and sales growth، and to achieve a

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Publication Date
Mon Sep 30 2019
Journal Name
College Of Islamic Sciences
Some Applied Models of Appreciation   From the Book of Almbsot Imam Muhammad bin Hassan al-Shaibani (d 189 e): - Fundamental study -
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The forensic evidence important for the sources of legislation after the book of God Almighty and the Sunnah of the purified, including what is agreed upon in the protest, which is the book and the Sunnah and consensus, and what is different in the protest, such as measurement and approval and say companions and interests sent, and that the approval of the evidence that did not agree Accordingly, the terms of the fundamentalists differed and their definition differed with the similarity between each other, and the approval in some schools is an argument is not considered as the Shaafa'is, so it may correspond to measurement with them, but the approval at the tap and those who agree is a hidden measurement is likely to clear measurement,I

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Publication Date
Sun Oct 19 2025
Journal Name
Lecture Notes In Networks And Systems
The Role of Artificial Intelligence in Studying the Impact of Contemporary Revolutions on Political Systems in the Middle East
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In this study, we tackle the understudied area of Artificial Intelligence (AI) and its role in examining how modern revolutions may affect political systems across the Middle Eastern region. despite hundreds of studies documenting Middle Eastern uprisings over the past three decades, there has been little effort to harness AI to better understand or predict these multifaceted events. This study seeks to address this gap by assessing the performance of AI-intelligence in analyzing (broadly) revolutionary processes and their effects on regional political systems. The research uses a mixedmethod methodology that involves a systematic literature review of contemporary scholarly articles, and an analytics study using AI tools. Our results show t

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Publication Date
Fri Nov 15 2024
Journal Name
Iraqi Journal Of Science
A Comparative Investigation of Different Ionospheric Models to Predict the MUF Parameter During Severe Geomagnetic Storm on 17th March 2015.
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The present work aimed to make a comparative investigation between three different ionospheric models: IRI-2020, ASAPS and VOACAP. The purpose of the comparative study is to investigate the compatibility of predicting the Maximum Usable Frequency parameter (MUF) over mid-latitude region during the severe geomagnetic storm on 17 March 2015. Three stations distributed in the mid-latitudes were selected for study; these are (Athens (23.50o E, 38.00o N), Jeju (124.53o E, 33.6o N) and Pt. Arguello (239.50o W, 34.80o N). The daily MUF outcomes were calculated using the tested models for the three adopted sites, for a span of five-day (the day of the event and two days preceding and following the event day). The calculated datasets were co

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Publication Date
Tue Sep 01 2015
Journal Name
Journal Of Engineering
Application of Box-Behnken Method Based ANN-GA to Prediction of wt.% of Doping Elements for Incoloy 800H Coated by Aluminizing-Chromizing
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In this work , an effective procedure of Box-Behnken based-ANN (Artificial Neural Network) and GA (Genetic Algorithm) has been utilized for finding the optimum conditions of wt.% of doping elements (Ce,Y, and Ge) doped-aluminizing-chromizing of Incoloy 800H . ANN and Box-Behnken design method have been implanted for minimizing hot corrosion rate kp (10-12g2.cm-4.s-1) in Incoloy 800H at 900oC . ANN was used for estimating the predicted values of hot corrosion rate kp (10-12g2.cm-4.s-1) . The optimal wt.% of doping elements combination to obtain minimum hot corrosion rate was calculated using genetic alg

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Publication Date
Tue Jan 14 2025
Journal Name
South Eastern European Journal Of Public Health
Deep learning-based threat Intelligence system for IoT Network in Compliance With IEEE Standard
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The continuous advancement in the use of the IoT has greatly transformed industries, though at the same time it has made the IoT network vulnerable to highly advanced cybercrimes. There are several limitations with traditional security measures for IoT; the protection of distributed and adaptive IoT systems requires new approaches. This research presents novel threat intelligence for IoT networks based on deep learning, which maintains compliance with IEEE standards. Interweaving artificial intelligence with standardization frameworks is the goal of the study and, thus, improves the identification, protection, and reduction of cyber threats impacting IoT environments. The study is systematic and begins by examining IoT-specific thre

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Publication Date
Mon Dec 01 2025
Journal Name
Sensors And Actuators A: Physical
IoT based hybrid optical-wireless microstructured optical fiber sensor network for cadmium ions detection
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Publication Date
Wed Jan 01 2020
Journal Name
International Conference Of Numerical Analysis And Applied Mathematics Icnaam 2019
Functionalized multi-walled carbon nanotubes network sensor for NO2 gas detection at room temperature
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