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Probabilistic Inventory Models With Pareto Distribution
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Inventory or inventories are stocks of goods being held for future use or sale. The demand for a product in is the number of units that will need to be removed from inventory for use or sale during a specific period. If the demand for future periods can be predicted with considerable precision, it will be reasonable to use an inventory rule that assumes that all predictions will always be completely accurate. This is the case where we say that demand is deterministic.

The timing of an order can be periodic (placing an order every days) or perpetual (placing an order whenever the inventory declines to units).

in this research we discuss how to  formulating inventory model with probabilistic capital and area constraints with pareto distribution.

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Publication Date
Thu Dec 15 2022
Journal Name
Journal Of Baghdad College Of Dentistry
Impact of different types of storage media on enamel surface roughness and granularity distribution of avulsed teeth (In vitro study)
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Background: To investigate the effect of different types of storage media on enamel surface microstructure of avulsed teeth by using atomic force microscope.Materials and methods : Twelve teeth blocks from freshly extracted premolars for orthodontic treatment were selected . The study samples were divided into three groups according to type of storage media :A-egg white , B- probiotic yogurt , and C-bovine milk . All the samples were examined for changes in surface roughness and surface granularity distribution  using atomic force microscope, at two periods: baseline, and after 8 hours of immersing in the three types of storage media. Results: Milk group had showed a significant increase in the mean of the  roughness values at

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Publication Date
Sat Feb 14 2026
Journal Name
Architecture Image Studies
The role of artificial intelligence in developing humanities studies from archaeological discovery to historical recording and geographical analysis: Application models
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

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Publication Date
Sat Feb 14 2026
Journal Name
Architecture Image Studies
The role of artificial intelligence in developing humanities studies from archaeological discovery to historical recording and geographical analysis: Application models
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The Fourth Industrial Revolution represents an advanced stage of technological development, characterized by the integration of digital, physical, and biological technologies, with a strong focus on smart connectivity and advanced data analysis. At the core of this revolution stands Artificial Intelligence (AI), which enables the processing of vast amounts of data, decision-making with speed and accuracy, automation of processes, and enhancement of productivity and quality. This research examines the transformative role of AI in the humanities, particularly in archaeological, historical, and geographical studies, where traditional methods face limitations in handling complex and extensive datasets.The study aims to highlight these l

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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
Sun Jan 01 2023
Journal Name
Journal Of Robotics And Control (jrc)
Automated Stand-alone Surgical Safety Evaluation for Laparoscopic Cholecystectomy (LC) using Convolutional Neural Network and Constrained Local Models (CNN-CLM)
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In this golden age of rapid development surgeons realized that AI could contribute to healthcare in all aspects, especially in surgery. The aim of the study will incorporate the use of Convolutional Neural Network and Constrained Local Models (CNN-CLM) which can make improvement for the assessment of Laparoscopic Cholecystectomy (LC) surgery not only bring opportunities for surgery but also bring challenges on the way forward by using the edge cutting technology. The problem with the current method of surgery is the lack of safety and specific complications and problems associated with safety in each laparoscopic cholecystectomy procedure. When CLM is utilize into CNN models, it is effective at predicting time series tasks like iden

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Publication Date
Fri Feb 28 2025
Journal Name
Energies
Synergizing Machine Learning and Physical Models for Enhanced Gas Production Forecasting: A Comparative Study of Short- and Long-Term Feasibility
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Advanced strategies for production forecasting, operational optimization, and decision-making enhancement have been employed through reservoir management and machine learning (ML) techniques. A hybrid model is established to predict future gas output in a gas reservoir through historical production data, including reservoir pressure, cumulative gas production, and cumulative water production for 67 months. The procedure starts with data preprocessing and applies seasonal exponential smoothing (SES) to capture seasonality and trends in production data, while an Artificial Neural Network (ANN) captures complicated spatiotemporal connections. The history replication in the models is quantified for accuracy through metric keys such as m

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Publication Date
Thu May 21 2026
Journal Name
Scientific Reports
Prediction of unerupted canines and premolars widths in an Emirati population: development and validation of regression and machine learning models
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Abstract<p> This study aimed to develop a more accurate model for predicting the widths of unerupted canines and premolars in Emirati children, using deep learning and machine learning techniques. Dental models of 380 Emirati individuals aged 15–30 years were collected. The mesiodistal widths of permanent teeth were measured with a standardized orthodontic digital caliper. Regression models were developed using linear regression, Support Vector Regression (SVR; machine learning), and Artificial Neural Networks (ANN; deep learning). The widths of mandibular lateral incisors, central incisors, and the summed width of mandibular incisors were used as predictors. A two-tail</p> ... Show More
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Publication Date
Tue Dec 01 2020
Journal Name
Journal Of Economics And Administrative Sciences
Use The moment method to Estimate the Reliability Function Of The Data Of Truncated Skew Normal Distribution
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The Estimation Of The Reliability Function Depends On The Accuracy Of The Data Used To Estimate The Parameters Of The Probability distribution, and Because Some Data Suffer from a Skew in their Data to Estimate the Parameters and Calculate the Reliability Function in light of the Presence of Some Skew in the Data, there must be a Distribution that has flexibility in dealing with that Data. As in the data of Diyala Company for Electrical Industries, as it was observed that there was a positive twisting in the data collected from the Power and Machinery Department, which required distribution that deals with those data and searches for methods that accommodate this problem and lead to accurate estimates of the reliability function,

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Publication Date
Sun Jun 07 2009
Journal Name
Baghdad Science Journal
Investigation of the Optical Properties of the Achromatic Quadrupole Lens by Using the Rectangular Potential Distribution Model
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An optimization calculation is made to find the optimum properties of combined quadrupole lens which consists of electrostatic and magnetic lens. Both chromatic and spherical aberration coefficients are reduced to minimum values and the achromatic aberration is found for many cases. These calculations are achieved with the aid of transfer matrices method and using rectangular model of field distribution, where the path of charged-particles beam traversing the field has been determined by solving the trajectory equation of motion and then the optical properties for lens have been computed with the aid of the beam trajectory along the lens axis. The computations have been concentrated on determining the chromatic and spher

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Publication Date
Sun Dec 19 2021
Journal Name
Bulletin Of The Iraq Natural History Museum (p-issn: 1017-8678 , E-issn: 2311-9799)
FIRST PHOTOGRAPHIC RECORDS AND NEW DISTRIBUTION RANGE OF THE ENDANGERED LONG-TAILED NESOKIA NESOKIA BUNNII (KHAJURIA, 1981)
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In the 1970s, the world knew the long-tailed nesokia Nesokia bunnii (Khajuria, 1981) (Rodentia, Muridae) from the Mesopotamian marshes of Garden of Eden in Southern Iraq. This distinct rodent was known from only five voucher specimens collected at the confluence of Tigris and Euphrates Rivers in southern Iraq while its occurrence in Southwestern Iran had
never been reported. In the 1990s, a large extent of its natural habitat was catastrophically desiccated and the animal was last seen in the 1970s. Since then, the status of this elusive rodent was shrouded in mystery. In 2007, an extraordinary photograph of a carcass of this species came to the light from Hawizeh Marsh which was interpreted as concrete evidence of the species’ pers

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