Preferred Language
Articles
/
bsj-7015
Mathematical Models Used for Brachytherapy Treatment Planning Dose Calculation Algorithms
...Show More Authors

Brachytherapy treatment is primarily used for the certain handling kinds of cancerous tumors. Using radionuclides for the study of tumors has been studied for a very long time, but the introduction of mathematical models or radiobiological models has made treatment planning easy. Using mathematical models helps to compute the survival probabilities of irradiated tissues and cancer cells. With the expansion of using HDR-High dose rate Brachytherapy and LDR-low dose rate Brachytherapy for the treatment of cancer, it requires fractionated does treatment plan to irradiate the tumor. In this paper, authors have discussed dose calculation algorithms that are used in Brachytherapy treatment planning. Precise and less time-consuming calculations using 3D dose distribution for the patient is one of the important necessities in modern radiation oncology. For this it is required to have accurate algorithms which help in TPS. There are certain limitations with the algorithm which are used for calculating the dose. This work is done to evaluate the correctness of five algorithms that are presently employed for treatment planning, including pencil beam convolution (PBC), superposition (SP), anisotropic analytical algorithm (AAA), Monte Carlo (MC), Clarkson Method, Fast Fourier Transform, Convolution method. The algorithms used in radiotherapy treatment planning are categorized as correction‐based and model‐based.

Scopus Crossref
View Publication Preview PDF
Quick Preview PDF
Publication Date
Sun Jan 22 2023
Journal Name
Mesopotamian Journal Of Big Data
Parallel Machine Learning Algorithms
...Show More Authors

 To expedite the learning process, a group of algorithms known as parallel machine learning algorithmscan be executed simultaneously on several computers or processors. As data grows in both size andcomplexity, and as businesses seek efficient ways to mine that data for insights, algorithms like thesewill become increasingly crucial. Data parallelism, model parallelism, and hybrid techniques are justsome of the methods described in this article for speeding up machine learning algorithms. We alsocover the benefits and threats associated with parallel machine learning, such as data splitting,communication, and scalability. We compare how well various methods perform on a variety ofmachine learning tasks and datasets, and we talk abo

... Show More
View Publication
Scopus (23)
Crossref (16)
Scopus Crossref
Publication Date
Thu Nov 29 2018
Journal Name
Al-khwarizmi Engineering Journal
Surface Roughness Prediction for Steel 304 In Edm Using Response Graph Modeling
...Show More Authors

Electrical Discharge Machining (EDM) is a non-traditional cutting technique for metals removing which is relied upon the basic fact that negligible tool force is produced during the machining process. Also, electrical discharge machining is used in manufacturing very hard materials that are electrically conductive. Regarding the electrical discharge machining procedure, the most significant factor of the cutting parameter is the surface roughness (Ra). Conventional try and error method is time consuming as well as high cost. The purpose of the present research is to develop a mathematical model using response graph modeling (RGM). The impact of various parameters such as (current, pulsation on time and pulsation off time) are studied on

... Show More
View Publication
Crossref (1)
Crossref
Publication Date
Fri Jan 01 2016
Journal Name
Aip Conference Proceedings
Application of simulated annealing to solve multi-objectives for aggregate production planning
...Show More Authors

Aggregate production planning (APP) is one of the most significant and complicated problems in production planning and aim to set overall production levels for each product category to meet fluctuating or uncertain demand in future. and to set decision concerning hiring, firing, overtime, subcontract, carrying inventory level. In this paper, we present a simulated annealing (SA) for multi-objective linear programming to solve APP. SA is considered to be a good tool for imprecise optimization problems. The proposed model minimizes total production and workforce costs. In this study, the proposed SA is compared with particle swarm optimization (PSO). The results show that the proposed SA is effective in reducing total production costs and req

... Show More
View Publication Preview PDF
Scopus (14)
Crossref (6)
Scopus Clarivate Crossref
Publication Date
Wed Nov 01 2017
Journal Name
Journal Of Computational And Theoretical Nanoscience
Solution for Multi-Objective Optimisation Master Production Scheduling Problems Based on Swarm Intelligence Algorithms
...Show More Authors

The emphasis of Master Production Scheduling (MPS) or tactic planning is on time and spatial disintegration of the cumulative planning targets and forecasts, along with the provision and forecast of the required resources. This procedure eventually becomes considerably difficult and slow as the number of resources, products and periods considered increases. A number of studies have been carried out to understand these impediments and formulate algorithms to optimise the production planning problem, or more specifically the master production scheduling (MPS) problem. These algorithms include an Evolutionary Algorithm called Genetic Algorithm, a Swarm Intelligence methodology called Gravitational Search Algorithm (GSA), Bat Algorithm (BAT), T

... Show More
View Publication Preview PDF
Scopus (15)
Crossref (13)
Scopus Crossref
Publication Date
Tue Dec 01 2009
Journal Name
Journal Of Economics And Administrative Sciences
Using Artificial Neural Network Models For Forecasting & Comparison
...Show More Authors

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

... Show More
View Publication Preview PDF
Crossref
Publication Date
Mon Dec 01 2025
Journal Name
Journal Of Physics: Conference Series
Advanced Machine Learning Models for Banana Sweetness Classification
...Show More Authors

It takes a lot of time to classify the banana slices by sweetness level using traditional methods. By assessing the quality of fruits more focus is placed on its sweetness as well as the color since they affect the taste. The reason for sorting banana slices by their sweetness is to estimate the ripeness of bananas using the sweetness and color values of the slices. This classifying system assists in establishing the degree of ripeness of bananas needed for processing and consumption. The purpose of this article is to compare the efficiency of the SVM-linear, SVM-polynomial, and LDA classification of the sweetness of banana slices by their LRV level. The result of the experiment showed that the highest accuracy of 96.66% was achieved by the

... Show More
View Publication
Crossref
Publication Date
Tue Jul 01 1997
Journal Name
Polymer-plastics Technology And Engineering
Reverse Calculation of Pressure from Pseudopressure
...Show More Authors

View Publication
Scopus Clarivate Crossref
Publication Date
Sun Aug 01 2021
Journal Name
Telkomnika (telecommunication Computing Electronics And Control)
Online 3D path planning for Tri-copter drone using GWO-IBA algorithm
...Show More Authors

View Publication
Scopus (4)
Crossref (1)
Scopus Crossref
Publication Date
Tue Jun 20 2023
Journal Name
Baghdad Science Journal
Computation of Several Banhatti and Reven Invariants of Silicon Carbides
...Show More Authors

Expressions for the molecular topological features of silicon carbide compounds are essential for quantitative structure-property and structure-activity interactions. Chemical Graph Theory is a subfield of computational chemistry that investigates topological indices of molecular networks that correlate well with the chemical characteristics of chemical compounds. In the modern age, topological indices are extremely important in the study of graph theory. Topological indices are critical tools for understanding the core topology of chemical structures while examining chemical substances. In this article, compute the first and second k-Banhatti index, modified first and second k-Banhatti index, first and second k-hyper Banhatti index, fir

... Show More
View Publication Preview PDF
Scopus (7)
Crossref (5)
Scopus Crossref
Publication Date
Sun Jun 11 2017
Journal Name
Al-academy
Ceramic Art and Urban Planning for the city of Baghdad
...Show More Authors

Ceramic art associated with urban growth in the cities, it overlapped with architectural construction, the increasing of population, urban growth, knowledge, and civilization was considered ceramic arts as an important aesthetically architecturally complement in the cities, including those in the squares and architectural institutions in the city of Baghdad .the title (Ceramic Art and Urban Planning in the City of Baghdad) the problem was its wonders : 1- Does ceramic monuments suited their locations in the city of Baghdad with the architectural planning urban of the city.2- Does the recipient interacted with these monuments and the reasons of their existence. Then the aim: knowing the relationship of the ceramic monuments with the urban

... Show More
View Publication Preview PDF
Crossref