SoftWeak θ-Continuity and Preservations of Soft Hyperconnectedness and Soft Near Compactness

Jawaher Al-Mufarrij; Samer Al-Ghour

doi:https://doi.org/10.54216/IJNS.250404

Financial Technology and Innovation | 2026

Open Banking Infrastructure and Banking-as-a-Service Adoption: A Multi-Level Competitive Dynamics Framework with Panel Evidence

Open banking standards call for banks to publish standardised Application Programming Interfaces (APIs) that give authorised third parties access to account and transaction data, with the consumer’s permission, that was once only available within the bank’s own systems. The real-world outcome is a transformation of the financial intermediation chain – banks are infrastructure providers, FinTech firms are service assemblers, and non-financial brands are including banking services directly within their own platform via Banking-as-a-Service architectures. This paper introduces the Open Banking Competitive Dynamics Framework (OBCDF), a multi-layered analytical framework that considers data, platform, competitor, and outcome layers, and tests the competitive impact of open banking API adoption on bank performance using a staggered difference-in-differences design with a panel of 45 banks over 10 quarters. API adoption is found to increase connections with third-party providers by 7.2 per quarter and the share of non-interest income by 0.62 percentage points, but also result in a statistically significant, although small, decline in the share of the deposit market. The TPP connections gained from early adoption are also found to be different by bank size, with larger banks seeing the largest absolute increase in TPP connections, and smaller banks seeing the largest absolute increase in non-interest income. Pre-treatment parallel trends tests are used to validate the identification assumption. The results have implications for incumbent bank strategy, the incentives for FinTech players and the design of open banking regulatory frameworks in jurisdictions currently developing mandates that are outside of the PSD2’s scope.

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Serkan Yilmaz Kandir mail -

Murat Ismet Haseki mail

link https://doi.org/10.54216/FinTech-I.060204

Volume & Issue

Vol. Volume 6 / Iss. Issue 2

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Metaheuristic Optimization Review | 2024

Metaheuristic Optimization for Scheduling in Cloud Computing Environments: A Review

This review reviews metaheuristic optimization algorithms for solving various important issues in cloud computing, such as scheduling, resource provisioning and energy consumption. Specifically, PSO, GA, and DRL are application area-specific intelligent scheduling algorithms that offer high scalability, flexibility, and efficiency in solving NP-hard problems, thereby improving system performance and QoS. The following are some of the key strengths in the study: The energy utilization and the cost utilization as key strengths are presented; the weaknesses are programs and things such as scalability and integration issues that arise when using hybrid systems. The focus for the future lies in combining machine-learning techniques, improving the further development of hybrid approaches, and testing them in real cloud systems to cope with the increasing sophistication of distributed systems. This paper provides an outline of metaheuristic optimization with an emphasis on how this area can contribute to enhancements and further developments in the capacity, recyclability, and dependability of cloud computing.

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Rokaia M. Zaki mail

link https://doi.org/10.54216/MOR.020202

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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Metaheuristic Optimization Review | 2024

A Review of Machine Learning in Predicting Heart Disease Risk Based on Medical Data

Heart diseases go on to be the primary cause of such mortality all over the world and hence call for accurate and efficient diagnostic tools. Traditional diagnostics are not scalable and precise in analyzing large and complex datasets generated in healthcare. Machine learning has come as a revolutionary solution in the form of advanced prediction models in the diagnosis and risk assessment of heart diseases. The authors present all machine-learning techniques like Random Forest, Support Vector Machine (SVM), Logistic Regression, Naïve Bayes, and hybrid models containing deep learning versions like CNN and LSTM in the study. These techniques consumed multi-source data found in Cleveland, Statlog, and UCI repositories and combined feature selection methods with different data preprocessing techniques to achieve improved accuracy, reliability, and scalability of outcomes while applying ensemble methods like majority voting and boosting to show enhancements in model working robustness and adopting SMOTE to tackle the imbalanced data scenario. Despite these developments, specific challenges remain mostly: Model Interpretability, Data Diversity, and Clinical Integration. The present review discusses progress, challenges, and future avenues in using machine learning in predicting heart diseases, which focus on the critical need for explainable AI models, diverse datasets, and real-world validation for the optimum use of clinical applications to improve global healthcare outcomes eventually.

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Safa S. Abdul-Jabbar mail

link https://doi.org/10.54216/MOR.020203

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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Metaheuristic Optimization Review | 2024

Artificial Intelligence in Path Planning for Autonomous Robots: A Review

Automated motion planning is an essential component of any autonomous system that effectively and safely finds the route in different application areas such as industry, hospitals, and cars. New developments in artificial intelligence and machine learning have improved additional attributes of path-planning algorithms in dealing with the complexities of their environment. This review also covers traditional algorithms, including RRT and A*, integrated frameworks, and AI solutions encompassing reinforcement learning, deep neural networks, and the Large Language Model (LLM). This paper looks at these methods' essence, advantages and disadvantages, and use for flexibility, productivity, and feasibility. It also outlines practical problems such as real-world testing, multi-robot operation, and energy issues and finally describes research directions in both cross-disciplinary research and practical application. This review aims to present the current developments and possibilities for robotic path planning to the researcher and practitioner communities.

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Shahid Mahmood mail

link https://doi.org/10.54216/MOR.020204

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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Metaheuristic Optimization Review | 2024

A Review of Hybrid Machine Learning and Metaheuristics for Vehicle Routing Problems

Vehicle Routing Problem (VRP) variants and modifications are significant problems in combinatorial programming and logistics. They relate to efficient and optimal transport routing for customer demand fulfillment while monitoring operational costs. Traditional methods have been exact algorithms, heuristics, and metaheuristics; however, it has yet to be known to cater to the scalability, computational, efficiency, and adaptability challenges posed by dynamic and large-scale VRPs. Recent advances have shown enormous promise in combining this with learning approaches in hybrid forms: ML and metaheuristic and optimization techniques to overcome them. Such hybrid approaches now promise even better quality solutions, computational speeds, and real-world applicability for two actual ML methods: deep reinforcement learning and meta-learning. The present study surveys the current state of the art of hybrid methods applying to VRPs to find strengths, weaknesses, and directions that future research could intensify to enhance efficiency, scalability, and applicability to transportation and logistics systems.

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Ali Wagdy Mohamed mail

link https://doi.org/10.54216/MOR.020205

Volume & Issue

Vol. Volume 2 / Iss. Issue 2

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International Journal of Neutrosophic Science | 2025

The Applications of Runge-Kutta Numerical Methods to Numerical Solutions of Several Neutrosophic Problems

In This paper, we develop the Runge-Kutta numerical method to be applied on neutrosophic problems of high orders, where we present generalized neutrosophic versions of Runge-Kutta methods of rank five, six and seven to use them in finding numerical solutions for some neutrosophic differential problems. In addition, we apply our generalized methods to some solid problems with many illustrated examples and numerical tables for comparing the results and the absolute errors.

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Belal Batiha mail

link https://doi.org/10.54216/IJNS.250346

Volume & Issue

Vol. Volume 25 / Iss. Issue 3

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International Journal of Neutrosophic Science | 2025

A New Algebraic Approach of Neutrosophic Lie Algebra by AH Isometry

This paper introduces a novel approach to the concept of neutrosophic Lie algebra by leveraging the AH isometry framework. We establish foundational properties of neutrosophic Lie algebra, demonstrating that each neutrosophic algebra inherently fulfills the criteria of a Lie algebra. Moreover, we introduce distinct neutrosophic Lie algebraic structures, providing illustrative examples to support these constructs. By integrating neutrosophic logic, our approach effectively addresses indeterminacy, ambiguity, and imprecision, enhancing the classical algebraic structures with new dimensions of flexibility. The potential applications of neutrosophic Lie algebra are vast, particularly in fields requiring nuanced treatments of uncertainty.

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Nader Mahmoud Taffach mail -

Mohammad Alsheikh mail -

Ahmed Hatip mail

link https://doi.org/10.54216/IJNS.250401

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2025

The Runge-Kutta Numerical Method of Rank Seven for the Solutions of Some Refined Neutrosophic Differential Problems

In this paper, we present a numerical approach to the seventh rank refined neutrosophic Runge-Kutta numerical method, where we provide the theoretical basis of this formula to be applicable on refined neutrosophic differential equations. In addition, we provide numerical tables to compare the validity of this new method with other methods, as well as a clear computation of absolute errors in terms of refined neutrosophic numbers.

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Belal Batiha mail

link https://doi.org/10.54216/IJNS.250402

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

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International Journal of Neutrosophic Science | 2025

On A Novel Neutrosophic Numerical Method for Solving Some Neutrosophic Boundary Value Problems

In this paper, we study a novel numerical method for finding the neutrosophic numerical solutions to some neutrosophic boundary values problems in differential equations of high orders. The proposed method based on neutrosophic numerical collocations of higher degree polynomials as an approximation to solve the problems. In addition, we provide many mathematical proofs about the existence of the solutions with many different examples and numerical tables that clarify the validity of the proposed method.

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Ahmed Salem Heilat mail

link https://doi.org/10.54216/IJNS.250403

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new

International Journal of Neutrosophic Science | 2025

SoftWeak θ-Continuity and Preservations of Soft Hyperconnectedness and Soft Near Compactness

In this paper, we introduce a new weak form of soft continuity called soft weak θ-continuity in soft topological spaces and investigate the relationships between soft weak θ-continuity and θ-continuity (resp. soft weak continuity and soft δ-continuity). We obtain several characterizations of soft weak θ-continuity. Also, we give sufficient conditions for the equivalence between soft weak θ-continuity and soft θ-continuity (resp. soft δ-continuity). Moreover, we investigate the link between soft weak θ-continuity and weak θ-continuity in classical topology. Furthermore, via soft weak θ-continuity, we obtain preservation theorems of soft hyperconnectedness and soft near compactness. Finally, we obtain soft restriction, soft product, and soft graph theorems of soft weak θ-continuity.

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Jawaher Al-Mufarrij mail -

Samer Al-Ghour mail

link https://doi.org/10.54216/IJNS.250404

Volume & Issue

Vol. Volume 25 / Iss. Issue 4

Details open_in_new