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Wasit Journal of Computer and Mathematics Science
ISSN 2788-5879 · College of Computer and Information Technology – University of Wasit, Iraq · 172 artikel di indeks
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Hybrid Generalization Open Sets in Generalization Topological Spaces
In this paper, we define a new class of generalized open sets in a generalized topological space , referred to as sets. We further explore topological concepts such as the and based on these sets. Additionally, we introduce and examine several types of functions including function, and . Various…
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Experimental Evaluation of Attention-Based Explainable AI Models for Detecting Zero-Day Threats in (IoT) Systems
The paper proposes to evaluate attention-based explainable artificial intelligence (XAI) models for their potential to detect zero-day attacks on Internet of Things (IoT) networks. The evaluation will be done by comparing the performance of attention-based XAI models with other baseline models and…
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A recent study of the Darbaugh problem's stability in partial differential equations using fixed-point theory
The stability analysis of solutions to nonlinear PDEs involves a fundamental and serious problem in applied mathematics and physics. The paper aims for the first time ever to provide a stability analysis for a class of nonlinear initial-boundary value problems called Darbaugh problems. To achieve…
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Innovative New Framework of Complex Q-Fuzzy Set and Its Application
The Q-fuzzy set (Q-FS) is a powerful general formal framework that generalises the notion of a fuzzy set (FS) when the domain of the FS extends from the universal set X to the product between X and Q. This article presents a novel complex Q-fuzzy set (CQ-FS) notion by extending the range of Q-fuzzy…
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Expert Systems Using Fuzzy Logic for the Early Alzheimer’s Disease Diagnosis
Alzheimer’s disease continues to be an important international health concern and early, accurate diagnosis is essential for treatment initiation and management of the disease. However, early identification of Alzheimer ’s disease (AD) remains a formidable challenge, mainly attributed to the…
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An Information Technology System for Measuring Organizational Culture and Predicting Employee Turnover Based on Questionnaire Data and Text Mining
Abstract: This paper implements the prediction of employees leaving their company using conventional methods such as surveys and modern techniques like mining textual data. The open-ended responses were analyzed (12,847 words of text in total) resulting in a vocabulary of 1,892 unique words. The…
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Educational Data Mining for Predicting Academic Attrition in Iraqi Universities: A Hybrid KDD-Based Approach using Weighted Euclidean Distance and Neural Architectures
Academic attrition within the higher education sector of Iraq is accepted as a notable phenomenon with substantial socio-economic impacts. Within the digital revolution environment of the higher education sector of Iraq, there is a growing need to exploit the student data repositories as a…
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Real-Time Emotion Recognition in Human-Robot Interaction Using Deep AI Models
Emotion recognition in human-robot interaction (HRI) is important in order to develop socially aware and responsive robotic systems. In this work, a near real-time emotion recognition architecture is introduced which combines deep AI models such as CNN, and recurrent architectures (LSTM/ GRU) for…
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The combined method for solve the constraint optimization problems uses the augmented Lagrangian and line search technique
This paper presents an effective hybrid optimization methodology that combines the Augmented Lagrangian (AL) framework with the Limited-memory Broyden–Fletcher–Goldfarb–Shanno (L-BFGS) algorithm to address large-scale constrained problems. The method leverages the AL framework to impose quadratic…
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Design of Reliable Queue Systems in Complicated Logistics Networks by Using Mathematical Programming Methods
How to construct strong queuing schemes in a network logistics setting using mathematical programming will be considered in this paper. As global supply chains get increasingly complex, Effective management of queues at logistics hubs is crucial for business performance. This work provides a…
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A Graph-Aware Recurrent Fusion Deep Ensemble Architecture for Fake News Detection
With the rapid spread of fake news on social media platforms, it has become essential to develop effective detection mechanisms that overcome the limitations of content-only or propagation-only approaches. This study aims to design a unified framework that jointly models textual semantics and…
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Some approaches to solving fuzzy linear fractional programming
An important planning tool is linear fuzzy fractional programming, it is used in various fields such as business, engineering, and others. We are trying to get one of the direct and effective methods that contain some arithmetic operations to obtain the optimal real values through which a…
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Low-Cost Vehicle Tracking System Based Web Application
Tracking and monitoring systems are a necessity and are widely used in various industries and fields for security and supervision purposes. Particularly in vehicle monitoring perspectives, it is considered a sophisticated technology that is conducted and designed to monitor and manage the location…
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Blockchain Scalability Analysis and Improvement of Bitcoin Network through Enhanced Transaction Adjournment Techniques
Bitcoin is the most popular among the cryptocurrency it includes Litecoin, Dogecoin, and Peercoin. Blockchain is the foundation of cryptocurrencies, most cryptocurrency technologies are decentralized. Despite its benefits, blockchain remains a cutting-edge technology with flaws that can be…
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A New Conjugate Gradient for Efficient Unconstrained Optimization with Robust Descent Guarantees
The Conjugate Gradient method is a powerful iterative algorithm aims to find the minimum of a function by iteratively searching along conjugate directions. This work presents a nonlinear conjugate gradient approach for unconstrained optimization, resulting from the resolution of a novel…
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Boosting Malware Detection with AlexNet and Optimized Neural Networks Using the Grasshopper Algorithm
That risk is compounded as more critical infrastructure and systems are being managed by computers in general, connected over the Internet. To combat such nefarious software that can steal data and do a number of other privatively outcomes, you need to be very vigilant and also train all our…
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Enhancing IoT Network Security Through Deep Learning-Based Intrusion Detection
The internet of today is a mainstream aspect of life, with increasingly more devices in the Internet of Things (IoT) ecosystem becoming networked. Although they are leaders in the market today, IoT networks are beset by increasingly more degrading security problems that confuse neatly defined…
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Evaluation Study for Celiac Disease Diagnosing by using Deep Learning Techniques
Celiac disease (CD) is the autoimmune reaction that occurs as a result of ingestion of gluten, which results to mucosal injury. Proper screening is especially important here, though the existing diagnostic techniques are frequently expensive, as well as the time-consuming. This review seeks to…
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Brain Tumor Classification of Medical Images based on Transfer Pre-trained Learning Models
Identifying brain tumor types is crucial for accurate diagnoses and appropriate therapeutic planning in medical imaging. The study aims to develop a robust and accurate system for categorizing medical images of brain tumors, utilizing transfer learning from pre-trained neural network models. The…
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Cyberbullying Detection in Arabic Text Using Different Deep Learning Approaches
The rise of social media has enabled the rapid spread of user-generated content across various domains, including advertising, entertainment, politics, and economics. However, this growth has also facilitated the increase of harmful behaviors, notably cyberbullying. Addressing this issue requires…