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Developing Bulk Arrival Queuing Models with Constant Batch Policy Under Uncertainty Data Using (0-1) Variables
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This paper delves into some significant performance measures (PMs) of a bulk arrival queueing system with constant batch size b, according to arrival rates and service rates being fuzzy parameters. The bulk arrival queuing system deals with observation arrival into the queuing system as a constant group size before allowing individual customers entering to the service. This leads to obtaining a new tool with the aid of generating function methods. The corresponding traditional bulk queueing system model is more convenient under an uncertain environment. The α-cut approach is applied with the conventional Zadeh's extension principle (ZEP) to transform the triangular membership functions (Mem. Fs) fuzzy queues into a family of conventional bulk queues. This new model focus on mixed-integer non-linear programming (MINLP) tenders a mathematical computational approach is known as (0 -1) variables. To measure the efficiency of the method, the efficient solution strategy plays a crucial role in the adequate application of these techniques. Furthermore, different stages of the α-cut intervals were analyzed and the final part of the article gives a numerical solution of the proposed model to achieve practical issues.

Publication Date
Wed Jan 01 2025
Journal Name
Journal Of Engineering And Sustainable Development
Improving Performance Classification in Wireless Body Area Sensor Networks Based on Machine Learning Techniques
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Wireless Body Area Sensor Networks (WBASNs) have garnered significant attention due to the implementation of self-automaton and modern technologies. Within the healthcare WBASN, certain sensed data hold greater significance than others in light of their critical aspect. Such vital data must be given within a specified time frame. Data loss and delay could not be tolerated in such types of systems. Intelligent algorithms are distinguished by their superior ability to interact with various data systems. Machine learning methods can analyze the gathered data and uncover previously unknown patterns and information. These approaches can also diagnose and notify critical conditions in patients under monitoring. This study implements two s

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Publication Date
Sat Dec 30 2023
Journal Name
Iraqi Journal Of Chemical And Petroleum Engineering
Selecting Optimum Dimensions for a Three-Phase Horizontal Smart Separator for Khor Mor Gas-Condensate Processing Plant
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      The Khor Mor gas-condensate processing plant in Iraq is currently facing operational challenges due to foaming issues in the sweetening tower caused by high-soluble hydrocarbon liquids entering the tower. The root cause of the problem could be liquid carry-over as the separation vessels within the plant fail to remove liquid droplets from the gas phase. This study employs Aspen HYSYS v.11 software to investigate the performance of the industrial three-phase horizontal separator, Bravo #2, located upstream of the Khor Mor sweetening tower, under both current and future operational conditions. The simulation results, regarding the size distribution of liquid droplets in the gas product and the efficiency gas/liquid separation, r

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Publication Date
Fri Jan 01 2021
Journal Name
International Journal Of Agricultural And Statistical Sciences
NONPARAMETRIC ESTIMATION IN DOUBLY GEOMETRIC STOCHASTIC PROCESSES
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A stochastic process {Xk, k = 1, 2, ...} is a doubly geometric stochastic process if there exists the ratio (a > 0) and the positive function (h(k) > 0), so that {α 1 h-k }; k ak X k = 1, 2, ... is a generalization of a geometric stochastic process. This process is stochastically monotone and can be used to model a point process with multiple trends. In this paper, we use nonparametric methods to investigate statistical inference for doubly geometric stochastic processes. A graphical technique for determining whether a process is in agreement with a doubly geometric stochastic process is proposed. Further, we can estimate the parameters a, b, μ and σ2 of the doubly geometric stochastic process by using the least squares estimate for Xk a

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Publication Date
Wed Apr 02 2025
Journal Name
Current Studies On Probability And Statistics
SAR-HDP: Non-parametric Topic Model for Aspect categorisation based on online reviews
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Aspect categorisation and its utmost importance in the eld of Aspectbased Sentiment Analysis (ABSA) has encouraged researchers to improve topic model performance for modelling the aspects into categories. In general, a majority of its current methods implement parametric models requiring a pre-determined number of topics beforehand. However, this is not e ciently undertaken with unannotated text data as they lack any class label. Therefore, the current work presented a novel non-parametric model drawing a number of topics based on the semantic association present between opinion-targets (i.e., aspects) and their respective expressed sentiments. The model incorporated the Semantic Association Rules (SAR) into the Hierarchical Dirichlet Proce

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Publication Date
Sun Oct 01 2017
Journal Name
International Journal Of Hydrogen Energy
Determination of best possible correlation for gas compressibility factor to accurately predict the initial gas reserves in gas-hydrocarbon reservoirs
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Gas compressibility factor or z-factor plays an important role in many engineering applications related to oil and gas exploration and production, such as gas production, gas metering, pipeline design, estimation of gas initially in place (GIIP), and ultimate recovery (UR) of gas from a reservoir. There are many z-factor correlations which are either derived from Equation of State or empirically based on certain observation through regression analysis. However, the results of the z-factor obtained from different correlations have high level of variance for the same gas sample under the same pressure and temperature. It is quite challenging to determine the most accurate correlation which provides accurate estimate for a range of pressures,

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Publication Date
Wed Nov 01 2023
Journal Name
Iraqi Journal Of Pharmaceutical Sciences ( P-issn 1683 - 3597 E-issn 2521 - 3512)
Synthesis, Characterization, and Preliminary Evaluation of Antimicrobial activity of Imines derived from Vanillic Acid Conjugated to Heterocyclic
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The purpose of this research is to prepare new vanillic acid derivatives with 1,2,4-triazole-3-thiol heterocyclic ring and evaluate their antimicrobial activity in a preliminary assessment. A multistep synthesis was established for the preparation of new vanillic acid-triazole conjugates. The intermediate of 4-(4-amino-5-mercapto-4H-1,2,4-triazol-3-yl)-2-methoxyphenol (4) reacts with different heterocyclic aldehydes (thiophene-2-carboxaldehyde, pyrrole-2-carboxaldehyde, thiophene-3-carboxaldehyde, and furfural ) in ethanol containing few drops of acetic acid yielded the corresponding 4-(4-(substituted amino)-5-mercapto-4H-1,2,4-1triazol-3-yl)-2-methoxy phenol derivatives (5-8). These compounds were characterized spectroscopically by

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Publication Date
Sun Mar 03 2013
Journal Name
Baghdad Science Journal
Comparative study of oxidative stress in diabetes mellitus
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The aim of the study was comparative between oxidative stress in diabetes mellitus using the measurement of some biophysical and biochemical parameters on two groups of diabetic patients, were conducted in the Al-Yarmuk Teaching Hospital,30 patients insulin dependent diabetes mellitus (IDDM) or type 1 ,their ages ranged between (15-45) and30 patients non- insulin dependent diabetes mellitus (NIDDM) or type 2,their ages ranged between (42-65).This study has been compared with 30 healthy subjects. The present study was demonstrated to evaluate the alteration in oxidative stress as measured by plasma and red blood cells Malondialdehyde (MDA) andchanges in antioxidant mechanism as measured by plasma and red blood cells Glutathione (GSH)

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Publication Date
Tue Jun 01 2021
Journal Name
Iraqi Journal Of Physics
Influence of Laser Energy on the Structural and Optical Properties of (CdO):(CoO) Thin Films Produced by Laser-Induced Plasma (LIP)
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In this work, (CdO)1-x (CoO)x thin films were prepared on glass slides by laser-induced plasma using Nd:YAG laser with (λ=1064 nm) and duration (9 ns) at different laser energies (200-500 mJ) with ratio (x=0.5), The influence of laser energy on structural and optical properties has been studied. XRD patterns show the films have a structure of polycrystalline wurtzite. As for AFM tests results for the topography of the surface of the film, where the results showed that the grain size and the average roughness increase with increasing laser energy. The optical properties of all films were also studied and the results showed that the absorption coefficient for within the wavelength range (280-1100 nm), The value of the optical power gap fo

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Publication Date
Thu Feb 24 2022
Journal Name
Journal Of Educational And Psychological Researches
Statistical analysis from a Gender perspective
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This research is a theoretical study that deals with the presentation of the literature of statistical analysis from the perspective of gender or what is called Engendering Statistics. The researcher relied on a number of UN reports as well as some foreign sources to conduct the current study. Gender statistics are defined as statistics that reflect the differences and inequality of the status of women and men overall domains of life, and their importance stems from the fact that it is an important tool in promoting equality as a necessity for the process of sustainable development and the formulation of national and effective development policies and programs. The empowerment of women and the achievement of equality between men and wome

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Publication Date
Tue Aug 23 2022
Journal Name
Int. J. Nonlinear Anal. Appl.
Face mask detection based on algorithm YOLOv5s
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Determining the face of wearing a mask from not wearing a mask from visual data such as video and still, images have been a fascinating research topic in recent decades due to the spread of the Corona pandemic, which has changed the features of the entire world and forced people to wear a mask as a way to prevent the pandemic that has calmed the entire world, and it has played an important role. Intelligent development based on artificial intelligence and computers has a very important role in the issue of safety from the pandemic, as the Topic of face recognition and identifying people who wear the mask or not in the introduction and deep education was the most prominent in this topic. Using deep learning techniques and the YOLO (”You on

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