Journal of Kufa for Mathematics and Computer
type: channel
description: Journal of Kufa for Mathematics and Computer (JoKMC) ISSN (Print): 2076-1171 | ISSN (Online): 2518-0010 The Journal of Kufa for Mathematics and Computer (JoKMC) utilizes advanced online technology to streamline the dissemination of research, enhancing accessibility and service for its readership. Since its inception in 2010, JoKMC has focused on publishing high-quality original research articles in the fields of mathematics and computer science. Through a robust open-access policy, JoKMC ensures that all papers are freely available online, and every submission undergoes a thorough peer-review process managed by an expert Editorial Board, upholding the journal’s commitment to academic excellence.
publisher: Faculty of Computer Science and Mathematics - University of Kufa
language: en
publication name: Journal of Kufa for Mathematics and Computer
issn: 2076-1171
copyright: which allows users to copy, create extracts, abstracts, and new works from the Article, alter and revise the Article, and make commercial use of the Article (including reuse and/or resale of the Article by commercial entities), provided the user gives appropriate credit (with a link to the formal publication through the relevant DOI), provides a link to the license, indicates if changes were made and the licensor is not represented as endorsing the use made of the work.
items: Forward -Backward System for Delay Doubly Stochastic Differential Equations
items: Applying Modren Fuzzy Partial Transform in Solving A Heat Equations
items: Maclaurin Coefficient Estimates for Bi‑Univalent Function Classes Generated by a Parameterized Integral Transformation
items: Chromaticity of Sylow Graph for the Cyclic Groups
items: Applications of Novel Integral transform: 'Kuffi-Abbas-Jawad' (KAJ) Transform to Damped Mechanical and Electrical Oscillators
items: A Tau Method for Solving Second-Order Partial Integro-Differential Equations with Weakly Singular Kernels
items: Harnessing the Iman Transform for Efficient Solutions to Heat and Wave Problems
items: Crypto Algorithm for Binary Numbers using Knapsack via Bezier curve
items: An Approach for Emotion Detection Using a Hybrid Vision Sequence-Based Convolutional Neural Networks (Vi-CNN) Model
items: A Proposed Method by Using the Adjacency Matrix to Solve the Edges Deletion Problem of Complete Graphs
items: On Double AL- ughair Transform Partial Technique and Solving Telegraphic Equation
items: New Applications of A Generalization of Tremblay Fractional Differential Operator for Defining Subclasses of Analytic
items: Link Quality Estimation VBF Routing for Underwater Wireless Sensor Networks (UWSNs)
items: A Review of Sentiment Analysis in Social Media Perspectives
items: Incidence and Non-incidence Soft Topology with Application
items: A Model-based Simulation to Evaluate the Attack's Severity in a Wirelessly Connected Mobile Vehicle Platoons
items: Building an Intelligent Energy Management System for Enhancing Energy Consumption in Smart Houses
items: Stock Market Forecasting Trends and Price using Different Machine Learning Techniques: Systematic Review
items: Uniformly MetriBornologies: A Unified Characterization and Applications to Fundamental Bornologies in Metric Spaces
items: Bifurcation Analysis of the Generalized Computer Virus Propagation Model
items: Approximate solution of integral-algebraic equations of index-2 by numerical multi-step method
items: On the graph of the Maximal subgroup of the Cyclic Group
items: On s-g-coc-Proper Functions
items: Generalized Bivariate Fibonacci Polynomials and a Related Class of Bi-Univalent Functions
items: Energy and Time Efficient Task Scheduling in Cloud Computing Using a Hybrid Genetic Algorithm - Approach
items: An Approach for Prediction of Osteoporosis and Its Association with Osteoporotic Fracture Risk Using Machine Learning
items: Properties of Asymptotic Behaviour Regarding the resolution of linear neutral difference equations of the second order with positive and negative coefficients
items: A Study of The Neighborhood of A New Class of Analytic Functions Containing The q-Symmetric Multiplier Transform Operator
items: Farsi Digit Recognition Using GAN-Generated Data and Convolutional Neural Networks
items: A Proposed Approach for Crime Type Prediction using Machine Learning Techniques

Forward -Backward System for Delay Doubly Stochastic Differential Equations
type: item
description: The research aims to study a general category of forward-backward double delay differential equations system , with a focus on solutions and their characteristics. The existence and uniqueness of solution to the front and rear equation of the system is proven according to the conditions of Lipchitz, which confirms the existence of a maximum solution under the conditions of unilateral continuity
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Ito’s integral
  topic: keywords
subject: Forward Doubly stochastic differential equations
  topic: keywords
subject: Backward Doubly stochastic differential equations
  topic: keywords
subject: Delay of the random variable
  topic: keywords
subject: Maximal solution.
  topic: keywords
creator: Ghufran Abdul Amir
creator: Falah H. Sarhan
rights: Copyright (c) 2025 Ghufran Abdul Amir, Falah H. Sarhan https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 1
ending page: 8
doi: 10.31642/JoKMC/2018/120201

Applying Modren Fuzzy Partial Transform in Solving A Heat Equations
type: item
description: Fuzzyi partialy integro-differentiall equationss are used extensively in the scientific and engineering domains. This work presents a new method for using the fuzzya Roi-transform to solvee fuzzy partial differential equations. We use highly expanded notions of H-differentiability to establish formulas for fuzzy partial derivatives of first and second order. Fuzzy partial Ro-transforms are introduced at the beginning of the work, and fuzzy partial differential equations are then developed using these novel findings. Lastly, an application shows the potential of the suggested approach.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: partial Ro-transform
  topic: keywords
subject: fuzzy partial Ro- transform
  topic: keywords
subject: , heat equation
  topic: keywords
creator: Roaa H. Hasan
creator: Ameraa N. Alkiffai
rights: Copyright (c) 2025 Roaa H. Hasan, Ameraa N. Alkiffai https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 9
ending page: 13
doi: 10.31642/JoKMC/2018/120202

Maclaurin Coefficient Estimates for Bi‑Univalent Function Classes Generated by a Parameterized Integral Transformation
type: item
description: This paper introduces new subclasses of the bi-univalent function class , defined via a newly constructed integral operator denoted by ​, acting on analytic functions within the open unit disc . These subclasses are formulated based on multi-parameter operator structures that exhibit rich analytic behavior. We investigate the coefficient bounds associated with functions belonging to these classes, with particular focus on deriving sharp estimates for the first two Taylor–Maclaurin coefficients, namely . The findings contribute to the structural understanding of bi-univalent functions and offer new directions for application within the framework of geometric function theory.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Bi-univalent functions
  topic: keywords
subject: coefficient estimates
  topic: keywords
subject: integral operator.
  topic: keywords
creator: Amal Darweesh
creator: Waggas Galib Atshan
creator: Ali Hussein Battor
rights: Copyright (c) 2025 Amal Darweesh, Waggas Galib Atshan , Ali Hussein Battor https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 14
ending page: 20
doi: 10.31642/JoKMC/2018/120203

Chromaticity of Sylow Graph for the Cyclic Groups
type: item
description: In our work, we will find the new results on the chromatic uniqueness of Sylow graphs of cyclic group , . Moreover, we will determine the results about the chromatic number and chromatic polynomial of these graphs. We will discuss all the cases of , where is the prime number. Moreover, we prove that if , , and , then is not , where and , otherwise it is .
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Chromatic number;
  topic: keywords
subject: Chromatic polynomial;
  topic: keywords
subject: Chromaticity;
  topic: keywords
subject: Sylow Graph.
  topic: keywords
creator: Abdullah AbdulRazzaq Obaid
creator: Haneen Al-Janabi
rights: Copyright (c) 2025 Abdullah AbdulRazzaq Obaid , Haneen Al-Janabi https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 55
ending page: 60
doi: 10.31642/JoKMC/2018/120208

Applications of Novel Integral transform: 'Kuffi-Abbas-Jawad' (KAJ) Transform to Damped Mechanical and Electrical Oscillators
type: item
description: This study utilizes the 'Kuffi-Abbas-Jawad' (KAJ) transform to determine the responses of mechanical and electrical oscillators. The paper introduces the KAJ transform as a novel approach for analyzing simple harmonic oscillators, as well as damped mechanical and electrical oscillators. Similar to other integral transform techniques, the 'Kuffi-Abbas-Jawad' (KAJ) transform serves as a practical and effective mathematical tool for obtaining these responses.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: 'Kuffi-Abbas-Jawad' (KAJ) transform
  topic: keywords
subject: 'Kuffi-Abbas-Jawad' (KAJ) transform inverse
  topic: keywords
subject: Damped Mechanical
  topic: keywords
subject: Electrical Oscillators, Differential Equation Responses.
  topic: keywords
creator: Dr.Prakash Chand Thakur
rights: Copyright (c) 2025 Dr.Prakash Chand Thakur https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 69
ending page: 76
doi: 10.31642/JoKMC/2018/120210

A Tau Method for Solving Second-Order Partial Integro-Differential Equations with Weakly Singular Kernels
type: item
description: This paper introduces a numerical method to approximate the solutions of initial-boundary value problems for a specific class of partial integro-differential equations. The approach utilizes Volterra Fredholm Integro Differential with Weakly singular kernel for spatial derivatives and the backward Tau method for temporal derivatives. The study delves into detailed Converting BVP to Volterra Fredholm Integral Differential Equation of the Second Kind with tau methode and using the Legendre or Chebyshev polynomials, proving their convergence and stability. The proposed method is then applied to several test cases, with the numerical outcomes compared with The Finite Element Method . The results demonstrate the computational efficiency of the method, leading to the conclusion that it is effective for solving initial-boundary value problems.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Volterra-Fredholm Integro Differential Equation
  topic: keywords
subject: Tau Method,Weakly singular Kernel
  topic: keywords
subject: Finite element method Method.
  topic: keywords
creator: Amenah Hadi AlSharmani
creator: Ahmed M. Rajab
rights: Copyright (c) 2025 Amenah Hadi AlSharmani, Ahmed M. Rajab https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 61
ending page: 68
doi: 10.31642/JoKMC/2018/120209

Harnessing the Iman Transform for Efficient Solutions to Heat and Wave Problems
type: item
description: The heat and wave equations are prominent partial differential equations with extensive applications in fundamental sciences and engineering. Integral transform methods provide effective solutions to various challenges in these fields. This chapter explores the Iman transform technique as a tool for solving heat and wave equations represented by partial differential equations.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Iman Transform
  topic: keywords
subject: Heat equation
  topic: keywords
subject: Wave equation
  topic: keywords
subject: Differential Equations.
  topic: keywords
creator: Dr.Prakash Thakur
creator: Dinesh Thakur
creator: Emad A. Kuffi
rights: Copyright (c) 2025 Dr.Prakash Thakur, Dinesh Thakur, Emad A. Kuffi https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 49
ending page: 54
doi: 10.31642/JoKMC/2018/120207

Crypto Algorithm for Binary Numbers using Knapsack via Bezier curve
type: item
description: These days we are constantly sharing and storing sensitive information online. From credit card numbers to personal identity details, our data is vulnerable to cyber-attacks and breaches. With the increase in cybercrime and hacking techniques, it is becoming increasingly important to protect our data through encryption. This work aims to create a secure binary number of the system of encryption and to make cipher analysis impossible. We will combine Knapsack’s cipher with the equations of Bezier curves using the three-pass protocol. The robustness of the proposed methods has been proved and the high security level by the experimental results, where the proposed methods have been more efficient and complex. The computational complexity of this method has been implemented in detail.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Binary numbe
  topic: keywords
subject: Knapsack cipher
  topic: keywords
subject: Bezier curves
  topic: keywords
creator: Adil AL-Rammahi
creator: Baleegh Alshaeer
rights: Copyright (c) 2025 Adil AL-Rammahi, Baleegh Alshaeer https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 12
ending page: 16
doi: 10.31642/JoKMC/2018/120103

An Approach for Emotion Detection Using a Hybrid Vision Sequence-Based Convolutional Neural Networks (Vi-CNN) Model
type: item
description: Emotion represents the significant reflection or indicator of human mental states, biological effects, and physiological statements, and it also plays a vital role in human interpersonal communication and decision-making. People convey their emotions naturally via everyday interactive communication due to the increasing advancement of social media platforms. Nowadays, detecting emotions from extensive textual data helps to provide expressive information for understanding the behavior of humans. Meanwhile, most prior techniques used for emotion detection are insufficient in providing promising results from long-term contextual information. Thus, it motivates introducing a hybrid deep learning model, Vision sequence-based Convolutional Neural Network (Vi-CNN), from text data to detect emotion. The Bidirectional Encoder Representation from Transformer (BERT) transforms the input texts into tokens. Then, extracting the most suitable and appropriate features from the text tokens is executed. Following this, the Vi-CNN model significantly detects emotions from the extracted features and classifies the recognized emotions. Furthermore, the results obtained by Vi-CNN are compared with those of other prevailing schemes. The experimental results highlight that the Vi-CNN attained promising results with maximum recall of 94.765%, precision of 92.988%, and F-measure of 93.867%.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Deep learning
  topic: keywords
subject: emotion recognition
  topic: keywords
subject: Vision transformer
  topic: keywords
subject: Convolutional Neural Network
  topic: keywords
subject: text data.
  topic: keywords
creator: Vian Sabeeh
creator: Ahmed Bahaaulddin Alwahhab
rights: Copyright (c) 2025 Vian Sabeeh, Ahmed Bahaaulddin Alwahhab https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 28
ending page: 42
doi: 10.31642/JoKMC/2018/120205

A Proposed Method by Using the Adjacency Matrix to Solve the Edges Deletion Problem of Complete Graphs
type: item
description: Graph theory approaches can be used to investigate a network’s dependability and effectiveness, and the network’s connectivity can be used to assess its dependability. The efficiency of a network is measured by its diameter, which can be somewhat increased by removing some vertices or edges. In this work, the maximum diameter fn(tt) of the modified graph G with n (n≥4) vertices, which resulted from removing t edges from the complete graph Kn ,(n≥4) was determined using the adjacency matrix adj(Kn).
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Edges deletion problem
  topic: keywords
subject: Maximum diameter
  topic: keywords
subject: Complete graph
  topic: keywords
subject: Adjacency matrix .
  topic: keywords
creator: Anwar Nasif Jasim
rights: Copyright (c) 2025 Anwar Nasif Jasim https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 1
ending page: 5
doi: 10.31642/JoKMC/2018/120101

On Double AL- ughair Transform Partial Technique and Solving Telegraphic Equation
type: item
description: In this paper, we developing one of the new transform, namely (AL- ughair transform),was introduced through the study of (Double AL- ughair transform, inverse Double AL- ughair transform), method is introduced used to solve the one dimensional partial differential equations with variable coefficients and then we discussed some examples to illustrate this concept and properties. On the other hand, (Double AL- ughair transform ) was presented for the partial derivatives with two variables and the transport equation and some other partial equations were solved, which indicates the effectiveness of this transformation in solving them in a quick and simplified manner.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: AL-Zughair transform
  topic: keywords
subject: Double AL-Zughair transform
  topic: keywords
subject: inverse of double AL-Zughair transform.
  topic: keywords
subject: partial differential equations (PDEs)
  topic: keywords
creator: Rakzan Shaker Naji
creator: Ali Hassan Mohammed
rights: Copyright (c) 2025 Rakzan Shaker Naji, Ali Hassan Mohammed https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 56
ending page: 60
doi: 10.31642/JoKMC/2018/120108

New Applications of A Generalization of Tremblay Fractional Differential Operator for Defining Subclasses of Analytic
type: item
description: In this paper, we study basic geometric properties of analytic and univalent functions in the open unit disk. A new family of analytic and univalent functions is defined by using a generalization of Tremblay fractional differential operator associated with the convolution product of a multiplier transformation and a Ruscheweyh derivative, especially. Coefficient-related studies and extreme points, distortion properties for the functions in class are given and properties of starlikeness and the convexity of this class are also presented.
subject: Articles
  topic: section
subject: Mathematics
  topic: category
subject: Analytic and univalent function
  topic: keywords
subject: generalization of Tremblay fractional differential operator
  topic: keywords
subject: open unit disk.
  topic: keywords
creator: Asst. Prof. Dr. Zainab Esa Abdulnaby
creator: Mohammed Ali
rights: Copyright (c) 2025 Asst. Prof. Dr. Zainab Esa Abdulnaby, Mohammed Ali https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 17
ending page: 24
doi: 10.31642/JoKMC/2018/120104

Link Quality Estimation VBF Routing for Underwater Wireless Sensor Networks (UWSNs)
type: item
description: The Underwater Wireless Sensor Networks are necessary for many applications such as marine search and underwater monitoring like measuring water speeds, currents and temperatures. The challenges is, needing for the special underwater environment, which is, require specified routing and security protocols and the traditional protocols are suffer many problems. Therefor there is continuous motivation for search and develop to enhance its performance in viral applications. Vector Based Forwarding is an Underwater Wireless Sensor Networks protocol. This protocol recognized by its depending on defaults pipelines for routing, the packets are routed through these pipes. The disadvantages of this protocol are, the sensitivity to the pipes radius, which is effect on routing efficiency and in the case of spaces found (voids) the protocol may fail to fined communication path. This paper conduct enhancing on VBF by Link Quality Estimation to enhance packet delivery ratio, end to end delay and energy efficiency. The simulation was done and we fined regarded enhancement in these terms.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: UWSNs
  topic: keywords
subject: Efficient Routing
  topic: keywords
subject: VBF
  topic: keywords
subject: LQE
  topic: keywords
subject: PDR
  topic: keywords
subject: E2E delay
  topic: keywords
creator: Hayder Khudhair
rights: Copyright (c) 2025 Hayder Khudhair https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 46
ending page: 55
doi: 10.31642/JoKMC/2018/120107

A Review of Sentiment Analysis in Social Media Perspectives
type: item
description: The widespread use of the Internet and social media platforms has led to an increase in the number of individuals who declare their feelings publicly. Therefore, sentiment analysis systems have proceeded because of their crucial role in determining the personal opinions of users. This is can greatly influence the decision-making process in various fields. To create a robust and reliable sentiment analysis system, it was necessary to apply techniques capable of dealing with these scattered opinions. Natural language processing techniques are commonly used to extract information from unstructured text data published by humans. The comments and posts in social media platforms are often ignore the grammar rules and sentence structure. This is resulting in many ambiguities in lexical, syntactic, and semantic aspects. As a result, researchers have developed different methods for text mining and defining real information. This survey aims to study the different methods used in sentiment analysis filed. We discussed two common models of classification, including the vocabulary-based model and the supervision-based approach.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Sentiment Analysis
  topic: keywords
subject: Twitter
  topic: keywords
subject: Pre-processing technique
  topic: keywords
subject: Supervised learning algorithms
  topic: keywords
subject: Unsupervised learning algorithm
  topic: keywords
creator: noralhuda alabid
rights: Copyright (c) 2024 noralhuda alabid https://creativecommons.org/licenses/by/4.0
date: 2025-05-19
publication date: 2025-05-19
starting page: 1
ending page: 11
doi: 10.31642/JoKMC/2018/110201

Incidence and Non-incidence Soft Topology with Application
type: item
description: In this work, incidence and non-incidence relations are used to create a new type of soft topology on soft graphs. Every edge in the graph is used as a parameter, and ordered pairs are used to build soft sets. The first part of an ordered pair is the edge, and the second part is the point that is connected to the edge. The sub-base, base, and soft topologies are explained, and then properties, theorems, and a full example are given to show how they work. This method gives a combinatorial structure encoding and makes it possible to do new kinds of study in soft topological spaces.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Soft graph
  topic: keywords
subject: Soft topology
  topic: keywords
subject: Incidence and non-incidence relations
  topic: keywords
subject: Soft Topology on Soft Graphs
  topic: keywords
creator: Iman Abbas Ali
creator: Asmhan Flieh Hassan
rights: Copyright (c) 2026 Iman Abbas Ali, Asmhan Flieh Hassan https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 84
ending page: 90
doi: 10.31642/JoKMC/2018/130111

A Model-based Simulation to Evaluate the Attack's Severity in a Wirelessly Connected Mobile Vehicle Platoons
type: item
description: In this paper, a model-based is presented for co-simulation framework to evaluate the severity of cyber-attacks on the wirelessly connected platoons of vehicles (Vehicular network). Two representative attack scenarios are implemented (Shift & Scale) and simulated in a simplified CACC-like model. Numerical results quantify spacing deviations, acceleration anomalies and recovery behavior, illustrating the framework's utility for assessing resilience and guiding mitigation strategies.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Cyber-physical systems
  topic: keywords
subject: Model-based design
  topic: keywords
subject: Cyber-attacks
  topic: keywords
subject: Vehicle platoons
  topic: keywords
subject: System resilience.
  topic: keywords
creator: Ahmed Waleed Khalil Al-Nasir
rights: Copyright (c) 2026 Ahmed Waleed Khalil Al-Nasir https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 80
ending page: 83
doi: 10.31642/JoKMC/2018/130110

Building an Intelligent Energy Management System for Enhancing Energy Consumption in Smart Houses
type: item
description: This trend of increasing residential energy consumption accounts for a significant and growing fraction of total global electricity demand — it also presents a bad economic incentive while being a burden for grid stability and sustainableisation. Existing smart home energy management systems typically do not strike an adequate trade-off between the three main conflicting objectives, namely, operational cost minimization, occupant thermal comfort satisfaction, and renewable energy usage maximization. To fill this gap, this paper presents a new Intelligent Energy Management System (IEMS) based on a Mixed-Integer Linear Programming (MILP) framework. It combines all the large and complex real-world inputs — hourly solar photovoltaic (PV) generation forecasts, dynamic time-of-use (TOU) electricity pricing, user-defined appliance preference windows, lithium-ion battery dynamics, and a linearized HVAC thermal model — into one single, tractable optimization problem. Calculated for a typical winter day in Helsinki, data from Climate-Data. org and Oomi. To summarize, the proposed IEMS can reduce daily electricity expenses by 73.1% (from €1.04 to €0.2805) and 68% of grid price, while simultaneously maintaining indoor temperature strictly between comfort band of 20–24°C and without violating user scheduling preferences. Our results show that the MILP approach provides a mathematically tractable, transparent and reproducible solution which outperforms rule-based heuristics and uncoordinated operation. This work provides such a generalizable and implementable framework for sustainable and demand-centric home energy management in smart grids
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Intelligent Energy Management System
  topic: keywords
subject: Energy Consumption
  topic: keywords
subject: Smart Houses
  topic: keywords
creator: Waad Zaid Saleh
rights: Copyright (c) 2026 Waad Zaid Saleh https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 49
ending page: 62
doi: 10.31642/JoKMC/2018/130108

Stock Market Forecasting Trends and Price using Different Machine Learning Techniques: Systematic Review
type: item
description: Financial stock markets play a significant role in supporting the economy by enhancing market liquidity, facilitating risk-sharing, minimizing the costs of financing, and contributing to the capital market. These functions offer more opportunities for economic growth. Stock market forecasting of prices or trends is a critical endeavor for investors and financial institutions to mitigate risk, optimize returns, and improve portfolio management. To address these challenges, numerous approaches have been proposed, involving time series forecasting, machine learning models, deep learning, ensemble techniques, and hybrid forecasting, which enhance the accuracy and reliability of forecasts. This study provides a systematic review of the literature on stock market forecasting, highlighting methodologies through comparative tables.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: stock market
  topic: keywords
subject: time series
  topic: keywords
subject: forecasting
  topic: keywords
subject: Deep learning
  topic: keywords
creator: mohammed jabardi
creator: Hawraa Abdulnabi
rights: Copyright (c) 2026 mohammed jabardi, Hawraa Abdulnabi https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 63
ending page: 79
doi: 10.31642/JoKMC/2018/130109

Uniformly MetriBornologies: A Unified Characterization and Applications to Fundamental Bornologies in Metric Spaces
type: item
description: This paper presents a study of bornological structures within metric spaces, with a central focus on the property of being a "uniform metric" bornology. The primary objectives are to characterize such bornologies and to establish necessary and sufficient conditions for this property to hold for several fundamental types. We provide a characterization theorem for uniform metric bornologies and apply this framework to analyze specific cases, including the compact, totally bounded, and Bourbaki-bornological structures. Furthermore, we demonstrate that several previously known results emerge as direct corollaries of our general theorems. The analysis employs tools from mathematical analysis and topology, utilizing the construction of characteristic functions alongside concepts of metric extensions and uniform restrictions. This work yields a deeper theoretical understanding of uniform metric bornologies and provides applicable tools for their investigation in varied contexts. The results are subsequently applied to the study of metric spaces possessing special properties, such as locally bounded and complete spaces.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Bornology
  topic: keywords
subject: Uniform Metrizability
  topic: keywords
subject: Characteristic Function
  topic: keywords
subject: Compact Bornology
  topic: keywords
subject: Totally Bounded Bornology
  topic: keywords
subject: Bourbaki-Bounded Set
  topic: keywords
subject: Heine-Borel Property.
  topic: keywords
creator: Hasan Khaled AL omar
creator: Zahir Dobeas AL-Nafie
rights: Copyright (c) 2026 Hasan Khaled AL omar, Zahir Dobeas AL-Nafie https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 43
ending page: 48
doi: 10.31642/JoKMC/2018/130107

Bifurcation Analysis of the Generalized Computer Virus Propagation Model
type: item
description: This research examines the generalized Computer Virus Propagation Model by analyzing its local bifurcation behavior, with particular attention to Hopf and transcritical bifurcations. The stability of equilibrium points and the emergence of periodic solutions are investigated through the computation of the first Lyapunov coefficient. A detailed exploration of the system’s dynamics reveals the presence of both stable and unstable periodic solutions, depending on specific parameter choices. To support the theoretical results, numerical simulations are provided, highlighting how parameter variations significantly influence the nature of the bifurcating periodic solution.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Computer Virus Propagation
  topic: keywords
subject: Stability Theory
  topic: keywords
subject: Hopf Bifurcation
  topic: keywords
subject: Transcritical Bbifurcation
  topic: keywords
subject: First Lyapunov Coefficient
  topic: keywords
creator: Qaraman Muhammed
creator: Rizgar H. Salih
rights: Copyright (c) 2026 Qaraman Muhammed, Rizgar H. Salih https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 34
ending page: 42
doi: 10.31642/JoKMC/2018/130106

Approximate solution of integral-algebraic equations of index-2 by numerical multi-step method
type: item
description: This paper presents a numerical approach for solving index-2 integral algebraic equations (IAEs) based on multi-step collocation techniques. The authors first examine the solvability and smoothness of index-2 IAE solutions via the differentiation index framework. The proposed method integrates principles from multi-step methods and collocation, where the approximate solution is determined by satisfying specific matching conditions at designated collocation points. We perform a convergence analysis to prove that the algorithm’s approximations converge to the exact solution and to determine their rate of convergence. For comparison, we also solve the equation using a one-step collocation method, thereby highlighting the superior efficiency and precision of our multi-step approach.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Integral-algebraic equations
  topic: keywords
subject: Index
  topic: keywords
subject: Piecewise polynomial numerical method
  topic: keywords
subject: Convergence analysis
  topic: keywords
creator: bahaa hussein Alrikabi
rights: Copyright (c) 2026 bahaa hussein Alrikabi https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 27
ending page: 33
doi: 10.31642/JoKMC/2018/130105

On the graph of the Maximal subgroup of the Cyclic Group
type: item
description: The maximal graph is a finite graph for any two vertices that are joined if is a maximal subgroup and is denoted by .In this paper, we will present an algorithm for calculating the graph of .Where we will study several cases of the value of so there will be an algorithm for each case. To calculate the maximum number of subgroups of the cyclic group . We’ll employ the Gap program. and use this to find some of the properties of the maximal graph.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Maximal subgroup
  topic: keywords
subject: Max graph
  topic: keywords
subject: Cyclic group
  topic: keywords
creator: Ohood A. Hadi
creator: Hayder B. Shelash
rights: Copyright (c) 2026 Ohood A. Hadi, Hayder B. Shelash https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 22
ending page: 26
doi: 10.31642/JoKMC/2018/130104

On s-g-coc-Proper Functions
type: item
description: This research introduces a novel classification of s-g-coc-Proper and s-g-coc'-Proper functions within topological spaces. The study focuses on examining the fundamental properties of these functions, such as continuity, closure, and compactness, while analyzing the impact of topological operations like composition, restriction, and product on their behavior. Furthermore, the research investigates the relationships between these functions and other topological concepts, including s-g-coc-Closed and s-g-coc-Compact sets. The research includes rigorous mathematical proofs, establishing new theorems such as the stability of topological properties under composition and the analysis of compact fibers of these functions. Additionally, illustrative examples are provided to highlight specific cases where certain properties fail or results deviate.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: s-g-coc-open
  topic: keywords
subject: s-g-coc-closed
  topic: keywords
subject: s-g-coc-compact
  topic: keywords
subject: s-g-coc-continuous
  topic: keywords
subject: s-g-coc-proper
  topic: keywords
creator: Ruaa Muslim Abd
creator: Noor Hasan Kadhim
creator: Saja Mahdi AL-Khafaji
rights: Copyright (c) 2026 Ruaa Muslim Abd, Noor Hasan Kadhim, Saja Mahdi AL-Khafaji https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 91
ending page: 100
doi: 10.31642/JoKMC/2018/130112

Generalized Bivariate Fibonacci Polynomials and a Related Class of Bi-Univalent Functions
type: item
description: In this study, we propose and analyze a new subclass of analytic bi-univalent functions defined on U=ζ∈C:|ζ|<1. The functions considered are characterized by subordination to a generating function constructed via generalized bivariate Fibonacci polynomials. In particular, we derive bounds for the initial coefficients in the Taylor–Maclaurin series expansion of functions belonging to this subclass. Furthermore, we obtain estimates for the Fekete–Szegö functional. The results presented here generalize and extend several known results in the theory of bi-univalent functions. The relevance of the main results and their relationship to previously defined subclasses are illustrated with examples and comments..
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: regular functions,
  topic: keywords
subject: Subordination.
  topic: keywords
subject: Bi-univalent functions
  topic: keywords
creator: Swamy SR
creator: Vinutha Raghu
creator: Mamatha P.K
rights: Copyright (c) 2026 Swamy SR, Vinutha R, Mamatha p.K https://creativecommons.org/licenses/by/4.0
date: 2026-06-01
publication date: 2026-06-01
starting page: 101
ending page: 107
doi: 10.31642/JoKMC/2018/130113

Energy and Time Efficient Task Scheduling in Cloud Computing Using a Hybrid Genetic Algorithm - Approach
type: item
description: Efficient task scheduling in cloud computing is a challenging problem, particularly when multiple competing objectives such as execution time, power consumption, and resource utilization must be optimized simultaneously. Traditional metaheuristic algorithms like Genetic Algorithms (GA) and Multi-Objective Particle Swarm Optimization (MOPSO) have been widely applied, but they suffer from drawbacks including premature convergence, limited diversity preservation, and difficulty in maintaining a well-distributed Pareto front. This paper proposes a hybrid GA-MOPSO algorithm in which GA’s crossover and mutation operators are embedded directly into the MOPSO updating process. Unlike conventional sequential or loosely coupled hybrids, our design allows GA to dynamically inject new genetic diversity into the swarm at each iteration, thereby preventing stagnation and guiding particles towards unexplored regions of the Pareto front. This integration preserves MOPSO’s fast convergence while enhancing diversity and solution quality through GA’s exploration capabilities. Simulation results on benchmark cloud scheduling scenarios demonstrate that the proposed algorithm consistently outperforms standalone GA and MOPSO in terms of makespan, energy efficiency, and average response ratio. These results prove the effectiveness of the proposed hybrid approach in multi-objective scheduling problems of cloud environment.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Cloud Computing
  topic: keywords
subject: Task Scheduling
  topic: keywords
subject: Genetic Algorithm (GA)
  topic: keywords
subject: Particle Swarm Optimization (PSO)
  topic: keywords
creator: Zainab Kashlan Yaser
creator: Abdulrahman D. Alhusaynat
creator: Walaa Alajali
rights: Copyright (c) 2026 Zainab Kashlan Yaser, Abdulrahman D. Alhusaynat, Walaa Alajali https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 1
ending page: 8
doi: 10.31642/JoKMC/2018/130101

An Approach for Prediction of Osteoporosis and Its Association with Osteoporotic Fracture Risk Using Machine Learning
type: item
description: Osteoporosis is a prevalent condition characterized by decreased bone mineral density and increased fracture risk, representing a significant global health concern, especially in aging populations. Early detection and risk stratification are critical for preventing fractures and reducing healthcare burdens associated with osteoporosis. A dataset of 1,958 individuals with demographic, lifestyle, and clinical features is analyzed, with the data explicitly split into 75% for training and 25% for testing. Three machine learning models—Random Forest, Decision Tree, and Multilayer Perceptron (MLP)—are developed and evaluated by using accuracy, precision, recall, F1-score, ROC-AUC, and balanced accuracy. The Decision Tree model achieved the highest accuracy (0.884) and perfect precision (1.0), while Random Forest and MLP models demonstrated competitive performance with ROC-AUC values of 0.876 and 0.875, respectively. Feature importance analysis confirmed age as the most influential predictor, with prior fractures, low BMI, glucocorticoid use, and smoking contributing to osteoporosis risk classification. On another side, to determine the degrees of fracture risks and their categories using the Fracture Risk Assessment Tool (FRAX) medical tool. So, we suggested a system using three machine learning (ML) techniques known for their success in diseases prediction, significant results were obtained compared to previous related studies according to the usual evaluation criteria for ML techniques which used to reach the best one to be relied upon in building the future model for prediction of osteoporosis, among all the algorithms, all evaluation metrics indicated that the Decision Tree (DT) was the best model (Accuracy: 0.884, Precision: 1.000, Recall: 0.767, F1-score: 0.868, and Area Under the Receiver Operating characteristic Curve (AUROC): 0.889), followed by the Random Forest (RF) and then the Feedforward Neural Network (Multi-Layer Perceptron MLP). On another side, to determ…
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Osteoporosis
  topic: keywords
subject: Machine Learning
  topic: keywords
subject: DEXA
  topic: keywords
subject: Osteoporotic fracture
  topic: keywords
subject: FRAX tool.
  topic: keywords
subject: Big Data
  topic: keywords
creator: Muayad H. Abdul-Zahra
creator: Salam Al-augby
rights: Copyright (c) 2026 Muayad H. Abdul-Zahra, Salam Al-augby https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 15
ending page: 21
doi: 10.31642/JoKMC/2018/130103

Properties of Asymptotic Behaviour Regarding the resolution of linear neutral difference equations of the second order with positive and negative coefficients
type: item
description: In this research concerns the asymptotic behavior properties for resolve second order of linear Neutral Difference equations with Positive and Negative Coefficients. Some necessary and Sufficients obtained for all solution non oscillatory tend to zero or infinity n→∞ . Example are given to illustrated the ordinary results.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Non Oscillatory
  topic: keywords
subject: Asymptotic behavior
  topic: keywords
subject: Neutral Difference Equation.
  topic: keywords
creator: Wafaa Zuhar Hemead
creator: Sattar Naser Ketab
rights: Copyright (c) 2026 Wafaa Zuhar Hemead, Sattar Naser Ketab https://creativecommons.org/licenses/by/4.0
date: 2026-03-30
publication date: 2026-03-30
starting page: 9
ending page: 14
doi: 10.31642/JoKMC/2018/130102

A Study of The Neighborhood of A New Class of Analytic Functions Containing The q-Symmetric Multiplier Transform Operator
type: item
description: In this paper I have defined new subclasses of analytic functions characterized by negativity of their coefficients by the q-symmetric multiplier transform operator. In fact, they are subclasses of the class of starlike and convex functions of complex order, and through them I studied the neighborhood of these subclasses and the inclusion relations between them. So I put forward the conditions through which these subclasses belong to the neighborhood or vice versa, the neighborhood belongs to them, and I explained the special cases of them.
subject: Mathematics
  topic: section
subject: Mathematics
  topic: category
subject: Analytic Functions
  topic: keywords
subject: Multiplier Transform Operator
  topic: keywords
subject: Neighborhood
  topic: keywords
subject: q- Derivative
  topic: keywords
subject: Convex Function
  topic: keywords
subject: Starlike Function.
  topic: keywords
creator: Hazha Zirar Hussain
rights: Copyright (c) 2025 Hazha Zirar Hussain https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 43
ending page: 48
doi: 10.31642/JoKMC/2018/120206

Farsi Digit Recognition Using GAN-Generated Data and Convolutional Neural Networks
type: item
description: Handwritten digit recognition is one of the most active study areas in computer vision because to its numerous applications such as automatically identifying the digits in bank checks and car numbers. Handwritten Latin digits have been the subject of extensive research over the last three decades, whereas Persian handwritten digits have received far less attention. For this reason, we will concentrate on the problem of recognizing Persian (Farsi) handwritten numerals. The main challenge in the recognition of Persian handwritten digits is the presence of different patterns in Persian digit writing, which complicates the feature extraction process. An appropriate approach for automated feature extraction has been the focus of most earlier investigations since handcrafted feature extraction methods are complex and have unstable performance levels. This paper studies the use of a dataset of Persian handwritten digits generated by a Generative Adversarial Network (GAN) to develop a highly accurate Convolutional Neural Network (CNN) model for digit recognition. The proposed CNN architecture achieved a test accuracy of 99.7%, demonstrating its effectiveness. This study highlights the viability of GAN-generated datasets for machine learning applications, especially in resource-constrained scenarios.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Handwritten Digit Recognition,
  topic: keywords
subject: Convolutional Neural Network,
  topic: keywords
subject: Persian digits,
  topic: keywords
subject: CNN ,
  topic: keywords
subject: Farsi
  topic: keywords
creator: Farah Jawad
creator: Nisreen Ryadh Hamza
rights: Copyright (c) 2025 Farah Jawad, Nisreen Ryadh Hamza https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 6
ending page: 11
doi: 10.31642/JoKMC/2018/120102

A Proposed Approach for Crime Type Prediction using Machine Learning Techniques
type: item
description: Abstract— Crime and suspect prediction represent an immerging field where machine learning can be useful when applied efficiently. The available data can be used to train the proposed prediction model (building the model, classifier for example) and then this model can be tested and used to predict the crime type and suspect information such as sex, race and age category. The work in this paper presents a proposed approach for such prediction by using real world dataset available on the internet. The gathered data were preprocessed(deletion of the rows with missing and unknown attribute content, converting some attribute values into nominal or categorical data and concept hierarchy techniques) and reduced the number of attributes by choosing the most important features using different approaches and algorithms, then different Decision Tree types, Naïve Bayes Classifier and Association Rules prediction techniques were used to create the required models and to find out associations between different attributes of the given data. Testing phase shows high efficiency and effectiveness of the proposed approaches which in turn provide models that can be used as reliable predictors. An accuracy of more than 85% was achieved when using different classification techniques. WEKA software, Microsoft Excel and XLSTAT mining software were used to analyze the given data.
subject: Computer Science
  topic: section
subject: Computer
  topic: category
subject: Machine learning
  topic: keywords
subject: Classification
  topic: keywords
subject: Decision Tree
  topic: keywords
subject: Association Rule Mining
  topic: keywords
creator: seham Adnan
creator: Kadhim B. S. Aljanabi
creator: Salam Alaugby
rights: Copyright (c) 2025 seham Adnan, Kadhim B. S. Aljanabi , Salam Alaugby https://creativecommons.org/licenses/by/4.0
date: 2026-01-05
publication date: 2026-01-05
starting page: 25
ending page: 31
doi: 10.31642/JoKMC/2018/120105