AL-Rafidain Journal of Computer Sciences and Mathematics

In this research, we investigate the effect of image curvelet transform coefficients in image denoising. The curvelet transform applies to input images, resulting in a set of curvelet coefficients that capture different frequency and directional components of the image. To improve the denoising process, we introduce an approach (CTRLC: Curvelet Transformation Remove Least Correlation) based on the correlation between the abstract coefficient and other coefficients. By analyzing the correlation values, we identify the coefficient that is least associated with the abstract coefficient and remove it from the transformed image. This selective removal allows us to attenuate noise while preserving the relevant image information. Experimental evaluations are conducted on a variety of images contaminated with different levels of noise. The results show that our proposed method effectively reduces noise and enhances the image quality. Comparative analyses with existing denoising techniques further validate the superiority of our approach in terms of noise reduction and preservation of important image details. The CTRLC method achieved a PSNR of 87.2695, compared to other methods that ranged between 23.43 and 77.5. This confirms the effectiveness of our proposed approach in image restoration after denoising. The findings of this research contribute to the field of image denoising by highlighting the significance of curvelet transform coefficients and the correlation-based coefficient removal technique. The proposed method offers a solution for effectively reducing noise in images while maintaining their visual integrity.

In digit age, understand user behaviors with optimizing interactions on website crucial for achieve engaging and satisfactory. This study uses back propagation method for analyze user behavior pattern and utilize information for enhancement website design, include preprocess user data, convert category page names to numbers, and normalization usage time values. Neural network architecture simplified use, with input layer represent sequence of encoded pages, hidden layer extract feature, and output layer predict user behaviors. Neural networks trained use back propagation algorithm with sigmoid activation function. The dataset uses for training consist of an encoded sequence of pages and corresponding labels of user behavior. After training, the accuracy of network assesses using test data, and evaluate the effectiveness of forecasting. The information obtains from trained neural networks use for identifying influential pages and predict user behavior pattern based on interactions. The results indicate that average prediction accuracy based on test result be 75%. When analysis significance functions, pages stand out have significant impact on predict user behavior. This data use for enhancement website interaction. While personalized recommendations design particularly for users based on predictable behavior, website optimization need prioritize influential pages.

The conjugate gradient (CG) method is the most widely used and has an important role in solving unconstrained optimization problems over a large scale due to its simplicity and lack of need for memory. Whereas a new parameter was proposed that enhances the Dai-Yuan formula so that it achieves better numerical results, in addition to the overall regression and convergence properties of the proposed method. The proposed method was compared with classical methods."

In this paper, by making some modifications to the Dai-Yuan method, we propose a new method to solve large-scale unconstrained optimization problems due to its simplicity and low need for memory. In addition to the comprehensive regression and convergence properties of the proposed method, the proposed method was compared with classical methods. There are researchers who have worked on developing and modifying the Dai Yuan method within their theses Among them is Hoda -Younis [15] and others."

The main access to modern healthcare using artificial technologies is related to the medical topic and prediction of risks to human health. Enhance patient medical care using intelligent prediction models such as machine learning, like gradient boosting trees, supervised machine learning and logistic regression which have a great importance in detecting diseases by analyzing medical images and diagnosing chronic diseases, in addition to use deep learning models like deep neural networks, recurrent neural networks, and long short term memory to predict many disease like depression risk, lung cancer, heart diabetic and kidney diseases. Enhance healthcare provider insights using intelligent prediction models to predict future health conditions, treatment outcomes, and disease progression. Moreover, the contribution of the intelligent prediction model helps the healthcare professional identify potential risks and intervene proactively by analyzing patient historical data for early diseases detection like using. Ultimately, the combination of medical history, intelligent prediction, and healthcare data analysis will empower healthcare providers with valuable tools to improve patient outcomes in efficient healthcare organizations.

In this research, we explore the impact of using delay differential equations in analyzing and understanding actions within the framework of studying the life cycle of insects. It demonstrates how these equations can be used to predict insect population outbreaks and identify environmental conditions conducive to reproduction. In this paper, we rely on the growth function of the prey and predator equations to study the effect of delayed differential equations on the insect life cycle. The results and comparisons were obtained using MATLAB. Also, we give an applied example of the fruit fly and used numerical methods, namely Euler's method, to obtain accurate approximate values to study the phenomenon of the delay effect of the differential delay equations for the life cycle of the fruit fly. Finally, the new idea from this work is Include time delay effect where the Ordinary differential equations (ODEs) assume that changes occur instantaneously, which may not be accurate in many biological systems. While the delay differential equations (DDEs) allow the inclusion of time delays between different events, such as the time required for eggs to transform into larvae, larvae to pupae, and pupae to adults.

The use of deep learning models for analyzing electronic health records (EHR) data in diabetes management has grown significantly. Researchers are leveraging deep learning technologies to enhance the diagnosis, treatment, and management of diabetes mellitus by extracting valuable insights from EHR data. Various deep learning models, including convolutional neural networks (CNNs) and recurrent neural networks (RNNs), have been evaluated for their effectiveness in handling EHR data and predicting clinical outcomes. CNNs excel at processing spatial data, while RNNs are adept at managing sequential data, although both have limitations. Advanced models like autoencoders (AEs) and deep belief networks (DBNs) offer improvements in feature extraction and predictive accuracy. Hybrid and ensemble techniques also show promise in enhancing performance. Despite these advancements, challenges such as data availability, model interpretability, and generalizability remain. Ongoing research is essential to address these issues and further improve diabetes management through EHR analysis.

The purpose of this work is to demonstrate that, for any value of a_1, a_2, and a_3, the generalized Michelson system u ̇= v,v ̇=w,w ̇= a_1 +a_2 v+ a_3 w-u^2/2 has neither a Darboux nor a rational first integral. Furthermore, we shall demonstrate that for a_3<0,√(2 a_1 ) >0 and a_3 a_2-√(2 a_1 ) >0, this system has no global C^1 first integrals. Additionally, the analytic first integral of this system for a generic condition is investigated near the equilibrium point (√(2 a_1 ),0,0). The purpose of this work is to demonstrate that, for any value of a_1, a_2, and a_3, the generalized Michelson system u ̇= v,v ̇=w,w ̇= a_1 +a_2 v+ a_3 w-u^2/2 has neither a Darboux nor a rational first integral. Furthermore, we shall demonstrate that for a_3<0,√(2 a_1 ) >0 and a_3 a_2-√(2 a_1 ) >0, this system has no global C^1 first integrals. Additionally, the analytic first integral of this system for a generic condition is investigated near the equilibrium point (√(2 a_1 ),0,0).

Feature selection is one of the methods used to improve the performance of machine learning algorithms, especially when classifying the big data. the fined of new method was be more needed when dealing with the imbalanced big data. An imbalance in the data appears when there is a discrepancy in the sampling distribution between the two data classes in the training set. To solve the imbalance problem, there are several methods used, some of which depend on redistributing the data and others of which depend on improving the classification algorithm itself. The feature selection can also affect the improvement of imbalanced data classification results when the features are chosen carefully. Therefore, this research proposed a composed feature selection method using the filter feature selection technique and permutation-based important features with the ensemble learning method. Three classifiers were used with three performance metrics (AUC, G-means, and F-score ) to show the effect of proposed feature selection method with imbalanced big data. The results of using proposed method led to improved classification on five standard imbalanced data sets.

If every element of a ring ℜ is the sum of idempotent and nilpotent that commute, then the
ring is said to be a strongly nil-clean. Further features of a strongly nil-clean ring are given in
this paper. Furthermore, we present and investigate a special class of strongly nil-clean rings
with order two units. Additionally, we examine a ring with each element ???????? in ℜ, ????????2 and ????????4 is a
strongly nil-clean with order two and order four units. Among other results, we prove that: If ℜ
is a strongly nil-clean ring of order two units, then for all ???????? in ℜ, existing ???????? in ℜ, such that
????????. ???????? = Ψ, ???????? − ???????? − 1 = ???????? and ???????? 2 = 1, and the converse of this result is true if 2 is nilpotent.

One of the best qualities for any software design is stability. Any initial adjustment to a design
will have a significant effect on it if it lacks stability. And for greater software quality, software
stability is crucial. Stable classes typically result in lower effort and expense for
software maintenance. Thus, in the case when developing software, achieving class stability is a
crucial quality aim. If designers could use certain predictors for predicting class stability before it happens, they will be able to make better decisions for improving class stability. This work presents the most significant metrics that scholars have utilized to quantify stability in object-oriented (OO) design, together with the most well-known studies that have employed these metrics.

An analysis and paper were provided for Fisher's reaction-diffusion equation using the time-frictional Caputo-Fabrizio equation. In addition, we offered the modified problem's iterative method solution. We demonstrated the stability of the approach using fixed-point theory. These operators, however, are limited in their ability to mimic physical situations and have a power law kernel. Recently, Caputo and Fabrizio presented an alternative fractional differential operator with an exponentially decaying kernel in order to get around this problem. The Caputo-Fabrizio (C-F) operator is a revolutionary method for fractional derivatives that has drawn the attention of several researchers because of its non-singular kernel. Additionally, the C-F operator works best when representing a certain class.

An element a in a ring ℛ is referred to be strongly 2T-clean (2 – STC element for short), ???????? = Ω−Λ+????????, where Ω,Λ are idempotent elements and ???????? is a unit elements of order three. A ring ℛ is considered to be 2 - STC ring if every member of ℛ are 2 - STC ring. This paper presents the idea of an strongly 2T-clean ring and lists some of its fundamental characteristics. Further more we consider 2 - STC ring with 3 is nilpotent, we demonstrate that this ring is equivalent to strongly 2- nil clean ring and the Jacobson radical and the right singular ideal of such ring with 3 is nilpotent is a nil ideal. Finally we exhibit that if ℛ is an 2 - STC ring and if 2 is nilpotent, then ????????4−???????? is nilpotent for every ???????? in ℛ. We domonstrale that if ℛ is 2 - STC ring, then ????????∈ℛ such that ???????? = Ω−h+????????, Ω is idempotent, ℎ is a unit
of order two and ???????? is a unit of order three.

This research dealt with a numerical simulation of the issue of heat transfer by conduction and convection in two dimensions resulting from the flow of fluid in horizontal and inclined cavities. The cavity walls are long H and wide L and consist of a porous material. Ode45 techniques were used to represent the governing equations (volume, momentum, and energy) after converting them to non-dimensional formulas using some appropriate transformations. The results showed the effect of the Reynolds number, Prandtl number, Rayleigh number, Hartmann number, Darcy number, Eckert number, in addition to the angle of inclination, on the problem, as shown in the drawings and illustrations.

An element is considered as a strong SITN, if it is the sum of idempotent, tripotent and nilpotent, that commute with one another. A ring ℛ is referred to be SITN ring if each member of ℛ is a strongly SITN. In this paper additional properties of a strongly SITN – ring is given. We prove that if ℛis a strongly SITN – ring, then ????????5−5????????3+4???????? is a nilpotent for every ???????? in ℛ, we also give a necessary and sufficient condition for a strongly SITN ring to be a strongly nil clean ring. Among other results, we show that the Jacobson radical of a strongly SITN is a nil ideal. Finally, we are considering a special SITN-ring.

Diagnosing diseases in humans is the first step in treating diseases, and knowing it is important to determine treatment and deal with the disease in the correct way. Diagnosis is made in medical institutions using available tools and specialists in each medical field to determine the problem presented by the patient. Modeling and analysis of medical data is important in healthcare and social applications in areas related to disease prediction and diagnosis. The model selection strategy is an important determinant of the performance and acceptance of a medical diagnostic decision support system. This paper proposes a stacked learning model derived from multiple ensembles learning algorithms, including Random Forest, Catboost and XGBoost. To determine the effectiveness of the model, it was tested using eight data sets covering different diseases to help make disease diagnosis decisions. The results show that the proposed model generally outperforms individual machine learning models in terms of accuracy.

A recent year, several studies have emerged on the graphs for commutative rings. Researchers have investigated ideal based zero-divisor graphs linked to commutative rings, delving into the characteristics of these graphs. Although significant progress has been made for rings with degrees up to 11, the exploration of this classification for degrees 12, 13, and 14 is still a subject of on-going study. In this work, we study the other type of graph of commutative ring called the ideal based zero divisor graph denoted by ГI(R ). J. Smith investigated the ideal based zero divisor graph of vertices less than or equal 7. In this work, also we used ГI(R )orders 12,13 and 14 to find all possible rings with respect to ideal I. To represent ГI(R ), utilize the characteristic
| ????????(ГI(R ))|=| ???????? |∙|????????(Г( ???????? / ???????? ) |.

This paper investigates moments for Ito's integral formula involving general form of hyperbolic stochastic functions, hyperbolic stochastic functions, which combine the deterministic structure of hyperbolic functions with stochastic elements such as noise and random fluctuations. The formulation of these functions through stochastic differential equations (SDEs) is discussed, along with methods for solving and analyzing such equations., with a specific focus on stochastic processes governed by Brownian motion. By utilizing Ito's integral calculus, we derive moments for integrals of hyperbolic sine and cosine functions. These results extend the classical Ito integral formula to hyperbolic trigonometric functions, providing a comprehensive understanding of their stochastic properties. These outcomes have applications in various fields such as mathematical finance, physics, and engineering, where modeling using hyperbolic functions under random effects is prevalent. Some examples are given to illustrate the theoretical results.

In this paper, we generalize a norm topology in Wielandt’s theorem for unital normed algebras and in Bhatt-Dedania’s theorem for Banach algebras, with each element being a zero topological divisor, by using 2-normed algebra and 2-Banach algebra, respectively.

The advent of digital and information technologies has revolutionized demographic data collection, storage, and analysis processes, enabling more efficient and accurate information management systems. Globally, demographic data plays a crucial role in policy formulation, resource allocation, and health/socio-economic planning for national development. However, in Nigeria, the lack of synergies among the relevance agencies and the existing manual system of demographic data collection and processing presents numerous challenges, including inefficiencies, inaccuracies, security vulnerabilities and delays. This research paper proposes architectural framework for an integrated e-demographic system (IEDS) based on browser-server (B/S) structure to improve data accessibility, availability, security, and scalability. The system is designed to streamline demographic data collection, management, and analysis by utilizing a centralized server accessible via standard web browsers. This architecture doesn’t require any specialized software, is a user-friendly interface that allowing users to access the system from any device at any time with just an internet connectivity. The browser-server model ensures real-time data synchronization and facilitating up-to-date demographic analysis.

Associate graph Л(R) is said to be idempotent divisor graph with vertices set in R*=R-{0} and two non- zero distinct vertices a and b are adjacent if and only if a.b=e, where e an idempotent element non equal 1. In this work we study the extended idempotent divisor graph of Zn is denoted by Л(R)????????????????????????????, with vertices set in R* that is for any two distinct vertices a and b are adjacent if there are positive integers t1,t2 such that at1. bt2=e, where at1, bt2≠ 0 and an idempotent element e not equal 1, and we found the order and the size for some kinds of the idempotent divisor graph of the rings Zn. Also, we found the Hosoya polynomial and the Wiener index for these graphs.

Overflow and excessive use are two major causes of water waste in daily life. Additionally contributing to the rate of water waste is overflow from overhead tanks. A crucial component that lessens human intervention in preventing such circumstances is the use of an automatic water level control mechanism. In this research, we suggest an intelligent system to regulate the water level and the process of turning on and off. The water level is detected by this method using an ultrasonic sensor and an Arduino. The water level is calculated in percentage based on the sound the water makes, and the result is displayed on the LCD screen. The water level is computed up to 100%. The relay switch attached to this system will automatically turn on and off when the water level exceeds the preset algorithmic value, which is then displayed on the LCD screen. When the water level falls to 0%, it will activate automatically, and once it reaches 100%, it will switch off. Additionally, we will observe that the pump will not operate in the absence of a water source to fill the tank since air will enter the pump and cause damage if it runs without water. Under these circumstances, the LCD panel will display the words "dry protection," which refers to the condition. Given that it would make it simpler for the user to fill the tank without assistance, the results showed that the automatic water level control device employing ultrasonic technology was effective based on readings that were practically monitored during the project's operation.