bluuebunny/crossref_metadata_2025_split huggingface dataset:
Two Numerical Algorithms for Solving Nonlinear Equation of Solar Cell
Authors: RASHEED Mohammed , SHIHAB Suha , RASHID Taha , Enneffati Marwa 
Published: October 2023

In this paper, we propose a new iterative method that has free from the second derivative of functions for solving nonlinear equations of a PV cell including different data for R (load resistance). These equations are determined using Kirchhoff's current law (KCL) applied on a closed network. Some numerical experiments are offered to illustrate that the Dekker's formula has more efficient and accurate than other iterative method Predictor-Corrector Type.
Some Topological Indices and ( Hosoya and Schultz) Polynomial of Subgroup intersection graph of a group Z_r
Authors: Nawaf Alaa J. , Mohammad Akram S.M. 
Published: October 2023

Let be any group with identity element (e) . A subgroup intersection graph of a group is the Graph with V (G) = - e and two separate a vertices a and b contiguous for a and b if and only if , Where is a cyclic subgroup of generated by . We found some topological indices in this paper and (Hosoya and Schultz) Polynomial of , where , is a prime number.
Duo Submodule and C_1-module
Authors: Talak Abdulsalam F. , Abed Majid Mohammed 
Published: October 2023

In this paper, we will give high priority to some important results about the duality property of submodule. The main reason for choosing this property is that duo is one of the important applications of extending modules. Note that any module will be chosen we will deal with it as a submodule on itself.
Noetherian, Artinian Regular Modules and Injective Property
Authors: Hamad Fawzi N. , Abed Majid Mohammed 
Published: October 2023

In this article we provide that several relationships between some concepts and injective module. We investigate, if is a cyclic and regular module is injective. Also, if is regular with N≤ is finitely generated submodule, so is injective. Finally, some relationships have been studied about injective module in details.
Survey on Crime Analysis Using Data Mining Based on Mobile Platforms
Authors: Hussain Fatima Shaker , Aljuboori Abbas Fadhil 
Published: October 2023

With a large rise in crime globally, there is a necessity to analysis crime data to bring down the rate of crime. This encourages the police and people to occupy the required measures and more effectively restricting the crimes. Crime analysis and spatial analysis using Geographic Information System(GIS) tools such as hot spot generation, zoning, navigation and crime profiling, detection of mobile locations and various web-based applications are well known and can be used scientifically for citizens advancement, while crime prediction and control can be used effectively. Crime data analysts will enable the law enforcement officials to speed up the crime resolution process. We can analyze previously unknown, helpful information from unstructured data by using the theory of data mining. The purpose of this work is to perform a survey on the crime analysis by using several data mining techniques that has been applied towards criminal activities over the years to be a valuable guide to young researchers that are interested in this field.
Mathematical Modeling and Statistical prediction of the spread of the Covid-19 Epidemic in Iraq with use SIR, R0
Authors: Mohammad Gorgees Shaheed 
Published: October 2023

In this research, a mathematical model was used to find epidemiological predictions for the coronavirus epidemic in Iraq to control and prevent the epidemic. Where the data of the reported cases until Nov. 21, 2020 from the Iraqi Ministry of Health and the Iraqi Public Health Committee were used, where the parameters of the form were determined and based on determining the number of reported cases, the unreported cases are determined and then the model is used to project the epidemic forward with appropriate levels of Iraqi Public Health Authority interventions. The model's predictions underscore the importance of major public health interventions in controlling COVID-19 epidemics. Whereas, the research work strategy was adopted by Liu et al (2020). The simulation was performed with R.
Cryptography model based on the principles of the geometric Series
Authors: Majeed Sundus Hatem 
Published: October 2023

Given the rapid advancement of data innovation and the massive volume of data exchanged over the Internet, which needs protection from electronic theft and extortion, there are many encryption algorithms that developed to protect data. Development in the field of coding (Cryptography) has always been accompanied by a development in the field of decoding and Cryptanalysis. This led to the Weakness of many encryption algorithms. Therefore, the need to develop a new methods are necessary. In this paper, a method based on geometric series for encrypting data was proposed, where two keys are used, the amount of the incremental in sequence represents the first key; the number of terms in the sequence represents the second key. The proposed model has been tested using a number of appropriate attack techniques; the proposed model has proved its efficiency and strength against attacks several technique of attacks are applying on the propose model, the results proved that the strength of the proposed method. As a contribution, this paper using a sequence to concatenate the values of the sequence terms to hide the origin character ASCII code which adds fuzzy cryptography to guess the correct ASCII code.
Enhanced PSO Based on Population Initialization and Exploration for the Permutation Flow Shop Scheduling Problem
Authors: Abdulhussein Azhar Y. , AL-Behadili Mohanad 
Published: October 2023

In this paper, a hybrid PSO (NLPSO*) is adapted to improve the obtained local optimal solution for the Permutation Flow Shop Scheduling Problem (PFSP) with minimizing the makespan. In this method, an improved NEH heuristic called -NEH+ is used to generate a good initial population. Then the PSO is triggered, followed by Iterated Local Search (ILS) to increase the coverage of exploration and exploitation search in the solution space. Both of the -NEH+ and ILS are simple and efficient algorithms. A computational study is performed to show the efficiency of the proposed technique. Several of well-known PFSP instances of small, medium, and large sizes were used in this study. The experimental study shows that the NLPSO* algorithm is significantly efficient in reaching better local optimal solutions.
A Comparative Study for Skeleton Representation Methods Using Data Visualization
Authors: Zalaan Zainab H. , Najimb Safa A. 
Published: October 2023

Data visualization is a technique used to see the unseen information, that will help humanity to discover important things. There are many methods to represent the datasets, but data visualization is the best because it can preserve the information. Skeleton is used to analyse the visualization, thus data visualization gives efficient results. Comparison among well-known methods is the goal of this paper. The conclusion of this paper showed all the comparative results will be important for any further study. This study will use data visualization to discover novel dataset representations, which is the main goal of data visualization and can be useful in presenting necessary data.
Comparison of LSTM And SVM For Classification of Eye Movements in EOG Signals
Authors: Abih Aya R. , Hayawi Mustafa J. 
Published: October 2023

People with disabilities suffer from inability to communicate with their surroundings, so Human-Computer Interaction (HCI) technologies are used to have a means of communication for people with disabilities with their surroundings. HCI is an emerging technology in the disciplines of Artificial Intelligence and Biomedical Engineering. To power an external device, HCI technology uses several basic signals such as ECG, EMG, and EEG. Electrooculography (EOG) is a technique for measuring the potential difference between the cornea and the retina located between the front and back of the human eye, and the main application of EOG is to determine the directions of different eye movements. This study aims to assess eye movement for communication by persons with disabilities using electrocardiogram (EOG) data. In this study, the Supporting Vector Machine (SVM) and Long- Short term memory (LSTM) classification techniques was used and two types of features (statistical and time domain features) were used. Classification accuracy was 90.7% and 93.9% when using SVM with statistical domain and time domain features, respectively ,whereas Classification accuracy was 90.1% when using LSTM .
Almost Approximaitly Nearly Quasiprime Submodules
Authors: Ajeel Ali Sh. , Mohammadali Haibat K. 
Published: October 2023

Let be a commutative ring with identity and be an -module. This study deals the concept of almost approximaitly nearly quasiprime submodules as a new generalization of quasiprime submodules, also generalizations of (prime, nearly quasiprime, nearly prime, approximaitly quasiprime and approximaitly prime) submodules. We give same basic properties, and characterizations of this concept. Furthermore, we study the behaviour of almost approximaitly nearly quasiprime submodules under -homomorphisms. Also, we explain the relationships between almost approximaitly nearly quasiprime submodules with the above concepts.
Principally ⨁-G-〖Rad〗_g-supplemented modules
Authors: Ghawi Thaar Younis , Kamil Narjis Mujtabah 
Published: October 2023

In this paper, a new concept has been presented that is a stronger than a previous concept called -G--supplemented. The basic definition is in an ring where an -module is said to be principally -G--supplemented (shortly, -PG--supplemented) if any cyclic submodule of with , there exists a direct summand of such that and . A set of properties and relations between previous modules and the given module has been dealt with simple examples illustrating those relations.
Asymptotic behavior of Eigenvalues and Eigenfunctions of T.Regge Fractional Problem
Authors: Faraj Jwamer Karwan Hama , Hilmi Hozan Dlshad 
Published: October 2023

The asymptotic behavior of eigenvalues and eigenfunctions of T.Regge fractional boundary value problem has been shown, and we state and prove some theorems for many results, also some necessary definitions and results. In this paper, we look into a group of fractional boundary value problem equations involving fractional derivative fractional orders and with two boundary value conditions. We will which are important to state and prove those theorems; our primary findings are illustrated using examples.
An Approach to Compute the Multi-Objective Programming Problem Under Triangular Fuzzy Numbers
Authors: Mitlif Rasha Jalal 
Published: October 2023

The most important one advantages of the operation research (OR) theory is displayed of this paper for tackling multi-objective function programming problems (MOFPP). In this study, we present an approach for multi-objective fractional programming problems (MOFrPP) using fuzzy numbers (FN) coefficients in the objective functions (OF). The objective functions' (OF) parameters are all considered to be fuzzy triangular fuzzy numbers (FTrFN). This problem's multi-objective function (MOF) case was resolved by transforming the MOF to a linear programming problem (LnPP) that could be resolved using the simplex method (SM). The problem is being solved using algorithms. Then the value is compared with a result, which obtained by simplex method (SM). These techniques are illustrated with numerical examples (NE). This study shows the reliability of our methods and their utility to this specific set of multi-objective functions (MOF).
Dom Tree as the base for webpage content extraction: Review
Authors: Rahim Hind Sabah , Sabir Aliea Salman , Flayh Nahla Abbas 
Published: October 2023

Because of the fast advancement of internet technology in the last twenty years, which leads to a huge number of web pages that contain a massive amount of information in every domain, the volume of available information has been steadily expanding every minute, so the analyzing and extracting information from web pages is becoming increasingly crucial, add to that information in webpages in an unstructured or semi-structured format need to transform in a structured format.
Since it is hard to collect the information manually, scientists have devised a variety of methods to help extract information from different domains in an automatic way. the main information in web pages is mixed with a significant amount of unrelated information (noise) like advertisements, boxes with links to relevant material, boxes with photos or other media, top and/or side navigation bars, animated commercials, etc., effect on the performance of information extraction and web content analysis technologies. to eliminate the noise by using the Document Object Model (DOM) that can easily reach every tag in the structure of the webpages to extract the information or delete the noise.
This article explores in-depth DOM tree-based approaches, such as HTML tags and the DOM tree, by reviewing works from 2011 to 2021 and comparing numerous elements comprehensively, including classifier methods, contribution, limitation, and evaluation metrics.
Optimize Weight sharing for Aggregation Model in Federated Learning Environment of Brain Tumor classification
Authors: Mahlool Dhurgham Hassan , Abed Mohamed Hamzah 
Published: October 2023

Clinical diagnosis and therapy of brain tumors are greatly aided by proper classification of the tumors. Brain tumors can be diagnosed more quickly and accurately if radiologists use deep learning to help the specialist and doctors examine the enormous volume of brain MRI Images. Large datasets are required in training process, and whole of such data must be centralized for be handled by such techniques. It is sometimes impossible to collect and distribute patient data on a centralized data server because of medical data privacy regulations. In this paper, federated learning (FL) is proposed, in which data is non-shareable because of patient privacy issues. Using the FL approach, we have proposed two methods of aggregation; first, which concerns ranking the weight percentage of each client, and Second average weights method. and to evaluate the suggested model, we have compared the performance of the ranking weights percentage method with the average weights of proposed CNN and pre-training (VGG-16) in the FL environment in addition to SVM and VGG-16 . The experiments result was applied on two datasets, it shows our model accuracy result is very effective when using the ranking weight percentage method as compared with other methods, it achieves accuracy (98%) on datasets (BT_large-1c) and achieve (97.14%) on the dataset (BT-large-2c).
Mining Distributed Data using Vertical Federated Learning Review
Authors: Yassen MManaaf Abdulredha , Muhammed Lamia AbedNoor 
Published: October 2023

Federated Learning was designed to allow collaborative learning without revealing raw data as worries about machine learning privacy grew. Vertical Federated Learning (VFL) may be utilized for a distributed dataset with the same sample ID space but differs in feature space. And may be used in a wide variety of real-world contexts when parties have the same set of samples but only have partial attributes. Achieving privacy will be a result of this technique's capacity.
Federated Learning enables different repositories of data to learn a shared model collaboratively and at the same time keep the privacy of each one because of the increasing awareness of large firms compromising on data security and user privacy. To accomplish federated learning, three learning ways were suggested; horizontal federated learning, vertical federated learning, and transfer federated learning.
Vertical federated learning was adopted when data were spread among different parties. However, each one has different features from the others for identical objects. This paper is related to this type of federated learning.

To maximize model performance while maintaining the privacy of dispersed data, we'll create a framework based on vertical federated learning and suitable techniques.
Some Properties of The Difference Quadruple Sequences Spaces of Fuzzy Complex Numbers Related to The Space (l_p )^4 Defined by Triple Maximal Orlicz Functions
Authors: Hussein Aqeel Mohammed 
Published: October 2023

In this paper, we present some properties of the difference for quadruple sequences spaces of fuzzy complex numbers related to the space defined by triple maximal Orlicz functions and discuss some properties such as completeness, solidity, monotonicity, symmetric, convergence-freeness, and so on.
Strength Pareto Evolutionary Algorithm Based on New Fitness Strategy for Multi Objective Knapsack Problem
Authors: Salman Muna Shaker 
Published: October 2023

problems. Many different experiments have shown that the evolutionary algorithm Strength Pareto Evolutionary Algorithm 2 (SPEA2) outperforms other approaches, and this makes it an excellent candidate for inclusion in the final design. According to Strength, one of SPEA2's core concepts, the population is sorted into niches based on the Pareto Front idea. With regard to outcomes this technique has a flaw that is mitigated by adding a fitness density estimator. Weakness in Strength is addressed with an approach called Strength by objective, which aims to include solution who do not dominate or are dominated by others inside the process. In this paper, the results will show a clear superiority of the proposed method comparing with the original method in solving the multi-objective Knapsack problem using three sizes of the Knapsack and the problem size of 750 items which is generated randomly. The comparison results between the proposed method and the other algorithms show outperformance of the Proposed algorithm using the dominance inductor showed the superiority of the proposed algorithm by a percentage of more than 1 %, Thanks to a highly diverse population and the inclusion of solutions that can be improved, the (SPEA2) algorithm's performance has been vastly enhanced by the Objective sorting mechanism
A Study of Hausdorff Measure in Fuzzy Soft Metric Spaces
Authors: Mohammedali Mayada N. , Sadiq Fatema Ahmad , Sabri Raghad I. 
Published: October 2023

In fields such as mathematics, statistics, computer science, etc., the theory of fuzzy metric spaces is crucial. In this work, a new significant characteristics of the space of fuzzy soft metric are presented, following Kider's (2020) proposal of the fuzzy soft metric model. furthermore, to study hyperspaces in terms of this specific fuzzy soft metric notion. A fuzzy soft distance between two fuzzy soft compact sets is created. A formulation has been proposed for establishing a Hausdorff fuzzy soft metric on the collection of non-empty fuzzy soft compact subsets. Additionally, a variety of essential features of the Hausdorff fuzzy soft metric concept are described.
Codisk-cyclic Mixing Operators
Authors: Jamil Zeana Zaki 
Published: October 2023

Let be an infinite dimensional separable complex Hilbert space, and be a bounded linear operator. is called codisk mixing operator, - mixing operator, if for any non-empty open subsets of , there are and such that for all . In this paper, we studied a necessarily and sufficiently conditions of - mixing operators, and discused the direct sum of two - mixing operators.
Strongly Pseudo Nearly Quasi-2-Absorbing Submodules(II)
Authors: Dahash Mohmad E. , Mohammadali Haibat K. 
Published: October 2023

In this research, we presented the concept of Strongly Pseudo Nearly Quasi 2-Absorbing submodules . Which is a generalization of the concepts of 2-Absorbing and Quasi 2-Absorbing submodules and the ideal is not Strongly Pseudo Nearly Quasi 2-Absorbing submodulesand we gave an example of that . We also noted that is STPNS-2-Absorbing ideals under several conditions. Also in this part we introduce the characterization of the concept of STPNS-2-Absorbing ideals by special kind of submodules.
Strongly Pseudo Nearly Quasi-2-Absorbing Submodules(I)
Authors: Dahash Mohmad E. , Mohammadali Haibat K. 
Published: October 2023

In this research, we presented the notion of Strongly Pseudo Nearly Quasi 2-Absorbing submodules . Which is a generalization of the notions of 2-Absorbing and Quasi 2-Absorbing submodules and stronger than the notions (Nearly 2-Absorbing, pseudo 2-Absorbing , Nearly Quasi 2-Absorbing and pseudo Quasi 2-Absorbing) submodules. Give us the properties, characterizations and examples of this new concept. We studied the relationship between the notion of Strongly Pseudo Nearly Quasi 2-Absorbingsubmodules and notion (Nearly 2-Absorbing, pseudo 2-Absorbing , Nearly Quasi 2-Absorbing and pseudo Quasi 2-Absorbing) submodules with special types of modules.
Extend Nearly Pseudo Semi-2-Absorbing Submodules (II)
Authors: Abdullah Omar A. , Mohammadali Haibat K. 
Published: October 2023

In this work we will study the concept of Extend Nearly Pseudo Semi-2-Absorbing submodules in multiplication modules and characterization of Extend Nearly Pseudo Semi-2-Absorbing ideals by of Extend Nearly Pseudo Semi-2-Absorbing submodules.
On the Study Sum Graph of the Group Z_(p^n ) with Some Topological Index
Authors: Qasem Mahera R. , Arif Nabeel E. , Mohammed Akram S. 
Published: October 2023

In this research, we study the graph theory in the sum group via using concept of two distinct orders the sum it is always greatest that and equal the order of the group , where p is prime number. We have shown that the group sum graph of are connected, cyclic, etc. if it satisfied some properties of the graph theory and founded all the degree of graphs, we shall compute the famous of topological indices via generalized it.
The Hierarchical Classification for The Rituals of Hajj Using Ontology
Authors: Youssef Fatima Y. , Othman Zainab I. 
Published: October 2023

In our dynamic world, knowledge is linked to data and information that already exists, and knowledge management can be shared and linked. In a broader scope, it can be used to structure ontology. Using ontology helps users understand structure easier and faster. In recent years, there has been a growing interest in developing and building an ontology for many fields.
However, relatively few works related to the religious aspect were conducted, especially regarding the pilgrimage and its rituals. This research paper was proposed given the importance of this field in Islam and the knowledge and exchange of everything related to it. Therefore, the proposed field was represented in ontology by showing the relationships between the categories that make up this field, which was organized hierarchically. When the relationship is already defined, the structure of the ontology can be modeled in the field of knowledge (pilgrimage and its rituals), and an appropriate methodology has been used for this work, which we will explain later.
This paper proposes to perform a hierarchical classification of pilgrimage rituals using an ontology file generated using the Protégé tool for modeling the ontology structure. This ontology structure will help share knowledge about Hajj and its rituals.