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258 articles for “I-convergence”
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Beyond Walls: The Transformative Power of Art Galleries in a Diverse Society
Abstract: Art galleries serve as dynamic spaces where artistic expression converges with cultural appreciation, fostering dialogue, reflection, and inspiration. This abstract explores the multifaceted role of art galleries in contemporary society, examining their significance as hubs of creativity, education, and community engagement. Through curate exhibitions, educational programs, and interactive experiences, galleries provide platforms for artists to showcase their works, audiences to explore diverse perspectives, and communities to connect with the transformative …
Published in Recent Trends in Social Studies · Vol. 1, Issue 1, 2024 · pp. 25–40 Read article
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Expanding Hicks Contraction Theory, Multi-Valued Mappings in Generalized b-Menger Spaces
Abstract: This paper extends the Hicks contraction theory to multi-valued mappings within generalized b-Manger spaces, a class of metric-like structures that accommodate more flexible distance functions. By introducing new definitions, such as generalized admissibility conditions and weak compatibility in the multivalued sense, we provide a comprehensive analysis of how these contractions behave in broader topological and metric contexts. Our approach systematically generalizes classical contraction principles by relaxing conventional constraints, thereby broadening …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 1–05 Read article
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Advancements in K-Means Clustering: Boosting Algorithm Performance through Innovations
Abstract: K-Means clustering is a widely used unsupervised learning algorithm for partitioning a dataset into distinct clusters. Despite its popularity and simplicity, K-Means has several limitations, such as sensitivity to initial centroids, convergence to local minima, and inefficiency with large datasets. This paper reviews recent advancements aimed at addressing these challenges and enhancing the performance of the K-Means algorithm. Innovations include improved initialization methods, such as K-Means++, which significantly reduce the …
Published in International Journal of Solid State Innovations & Research · Vol. 3, Issue 1, 2025 · pp. 30–37 Read article
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AI EdTech Synergy: From Chalkboards to Smartboards
Abstract: Beyond textbooks and classrooms, AI paints a future from adaptive tutors to immersive realities. AI is not just a tool sculpted by algorithms but an architect of a learning revolution where knowledge becomes truly boundless. The convergence of AI marks an era of revolution in learning, promising individualized learning pathways, optimized evaluative metrics, interactive virtual pedagogies, and enhanced accessibility. This convergence examines the emergent field of AI-powered educational innovation, shedding …
Published in Journal of Open Source Developments · Vol. 12, Issue 3, 2025 · pp. 18–25 Read article
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A Comprehensive Review on IoT and Edge Computing in Electronics: Trends, Challenges, and Future Directions
Abstract: The Internet of Things (IoT) transformed the electronics industry by enabling ubiquitous connectivity between billions of devices. This has created an unprecedented amount of data, challenging traditional cloud-based architectures with latency, bandwidth, and security issues. Edge computing came as an additive architecture by distributing computation and bringing intelligence to IoT edges to provide real-time responsiveness and reduce dependence on centralized infrastructure. This study offers a thorough analysis of current developments …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 1–9 Read article
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Bridging Brain-Inspired Learning and Quantum Reasoning for Future AGI Systems
Abstract: This research paper presents a novel neuromorphic–quantum hybrid computing framework envisioned to advance intelligent systems toward artificial general intelligence. The architecture integrates brain-inspired spiking networks for adaptive, energy-efficient learning with quantum processors for non-classical optimization and reasoning. A shared synaptic–quantum memory layer enables dual information representation, while neuromorphic adaptive controllers provide real-time stabilization of noisy quantum circuits. While quantum processors offer features like superposition- enabled exploration and entanglement-based correlations that …
Published in Current Trends in Signal Processing · Vol. 16, Issue 1, 2026 · pp. 1–9 Read article
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Parallel Privacy-Preserving Adaptive Federated Learning on GPU-Enabled Multi-Core Architectures
Abstract: The increasing deployment of parallel and distributed intelligent systems has intensified the need for privacy-preserving learning frameworks that can exploit multi-core and graphics processing unit (GPU)-based architectures without centralizing sensitive data. This work proposes a parallel adaptive federated learning (AFL) framework that integrates differential privacy and secure aggregation over heterogeneous multi-core and GPU platforms to enhance both data confidentiality and convergence efficiency. The framework dynamically adjusts client participation, learning rates, …
Published in Recent Trends in Parallel Computing · Vol. 13, Issue 1, 2026 · pp. 09–16 Read article
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Lyapunov-Stable Adaptive Fractional-Order Interval Type-2 Fuzzy Control for Robust Anti-Lock Braking Under Uncertain Road Adhesion Conditions
Abstract: This paper proposes a Lyapunov-stable Adaptive Fractional-Order Interval Type-2 Fuzzy Logic Controller (FO-IT2FLC) for robust anti-lock braking system (ABS) control under nonlinear vehicle dynamics and uncertain road adhesion conditions. The proposed framework integrates fractional-order error dynamics to capture memory-dependent tire–road interaction, interval Type-2 fuzzy inference to model uncertainty via footprint-of-uncertainty representation, and a Lyapunov-based adaptive learning mechanism for real-time parameter tuning. A rigorous stability proof guarantees boundedness of all closed-loop …
Published in Journal of Control & Instrumentation · Vol. 17, Issue 2, 2026 · pp. 31–41 Read article
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Study of an Improved Quantum Particle Swarm Optimization-Based Framework for Neural Network Optimization in Modelling of Polymer Data
Abstract: The accurate forecasting of polymer viscosity at various physicochemical conditions has been quite critical due to the nonlinear interactions and interrelations between the variables. This paper suggests a better hybrid modelling framework, which involves the use of Artificial Neural Networks (ANN) and more advanced versions of Quantum Particle Swarm Optimization (QPSO) to better predict polymer viscosity. The input parameters taken are, namely, log (shear rate), polymer concentration, NaCl concentration, Ca …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 282–297 Read article
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Hybrid Approach between LMS and Self-Correcting Adaptive Algorithm for Real Time Audio Noise Cancellation
Abstract: In present era of public address systems one of the most important issue is removing the noise signal from original signal. In various types of noise, which annoys audience, one of the most annoying problems is active feedback causing howling effect. This effect can be removed with the help of adaptive filters. There are various popular adaptive algorithms like LMS, NLMS, VLMS commonly used for this purpose. As public address …
Published in Current Trends in Signal Processing · Vol. 6, Issue 2, 2016 · pp. 36–41 Read article
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Finite Difference Analysis of Plane Couette Flow using MATLAB
Abstract: AbstractInternal flow is a flow for which the fluid is confined by a surface. Hence, the boundary layer is unable to develop without eventually being constrained. An internal flow is constrained by the bounding walls, and the viscous effects will grow and meet and permeate the entire flow. Some examples of internal flows are flow between two parallel horizontal plates, Couette flow, plane poiseuille flow, flow through pipes, etc. In …
Published in Journal of Microcontroller Engineering and Applications · Vol. 5, Issue 3, 2018 · pp. 7–11 Read article
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ATC Calculation in OPF Environment Using Hybrid Grey Wolf Optimizer and Particle Swarm Optimization
Abstract: Evolution of hybrid optimization provides new research direction in the real world problem solving by using more than one optimization techniques for obtaining speedy convergence and/or global optimal solution or solution near the global optimal. In this paper, a novel hybrid particle swarm optimization (PSO) and grey wolf optimizer (GWO) technique is used to calculate the available transfer capability in an optimal power flow environment. The proposed method has been …
Published in Trends in Electrical Engineering · Vol. 6, Issue 1, 2016 · pp. 84–93 Read article
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Designing an Energy Efficient Induction Motor: Advanced Computational Intelligence Technique
Abstract: Abstract—This paper presents an advanced computational intelligence technique (CIT), modified particle swarm optimization (MPSO) for designing energy efficient three-phase induction motor (DEEIM) including active power loss effect. PSO performs well for small dimensional and less complicated problems but fails to locate global minima for complex multi-minima functions. Even if PSO algorithm is easy to implement and has been shown to perform well on various power system optimization problems, they may …
Published in Current Trends in Information Technology · Vol. 9, Issue 2, 2019 · pp. 5–13 Read article
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Binary GA for Sidelobe Reduction and Null Steering in 5G Array
Abstract: This paper presents a comprehensive performance evaluation of a Binary Genetic Algorithm (BGA) for optimizing radiation characteristics of an active phased array antenna used in fifth-generation (5G) wireless communication systems. The primary objective is to achieve effective null steering while maintaining the desired main beam direction and simultaneously reducing the side lobe level (SLL). These improvements are essential for minimizing co-channel interference, enhancing spatial selectivity, and improving the Signal-to-Interference-plus-Noise Ratio …
Published in International Journal of Radio Frequency Innovations · Vol. 4, Issue 2, 2026 Read article
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GA with Modifications for Efficiently Solving Number Puzzles
Abstract: The previous research on the genetic algorithm (GA) applications especially for puzzle solving focuses on the GA capability for solving the puzzles of differing difficulty levels viz. magic square, jigsaw, sliding tile, crossword, path finding and of similar type. But this work attempts to solve logical number puzzles of exponential and factorial complexity using conventional GA with some important modifications depending on the puzzle type. The overall modifications done in …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 1, 2016 · pp. 1–7 Read article
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On Some Triple Almost Lacunary Sequence Spaces Defined by Orlicz Functions
Abstract: In this paper we introduce the concept of almost lacunary strong convergent triple sequences with respect to an Orlicz function and examine some properties of these sequence spaces. We also introduce and study almost lacunary statistical convergence for triple sequences and also present some inclusion relations.
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 1, Issue 2, 2014 · pp. 16–25 Read article
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Greedy Algorithm
Abstract: In mathematics and computer science, an algorithm is a self-contained step-by-step set of operations to be performed. Algorithms exist that perform calculation, data processing, and automated reasoning. A greedy algorithm is an algorithm that follows the problem solving heuristic of making the locally optimal choice at each stage[1] with the hope of finding a global optimum. In many problems, a greedy strategy does not in general produce an optimal solution, …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 2, Issue 2, 2015 · pp. 10–14 Read article
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Unveiling Distinctions: An In-depth Comparative Study of Cloudera, Microsoft Azure, and Amazon Web Services
Abstract: The purpose of this study is to compare and contrast the different on-premises and cloud-based Hadoop distributions. We will also analyze and contrast various cloud-based offerings and parts. We have settled on Cloudera as our Hadoop distribution of choice and Amazon and Azure as our cloud distribution services of choice. The advent of distributed cloud services has made it feasible to utilize and integrate a wide range of IT services …
Published in Journal of Advances in Shell Programming · Vol. 10, Issue 1, 2023 · pp. 27–34 Read article
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Optimization of Venturimeter Geometry for Minimum Pressure Drop using CFD Analysis
Abstract: A venturimeter is one of the accurate flow measurement devices used to measure volumetric flow rate based on differential pressure. Pressure recovery is a problem when flow measurement is done by venturimeter. So, it is necessary to select its geometrical parameters in such a way that minimum pressure loss occurs. In this paper, optimization of geometrical parameters of venturimeter for minimum pressure drop has been done using CFD analysis. For …
Published in Recent Trends in Fluid Mechanics · Vol. 3, Issue 2, 2016 · pp. 31–35 Read article
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Design and Analysis Versatile Thrust Vectoring Characteristics of A Military Turbojet Engine
Abstract: This paper under the title of “Versatile thrust vectoring characteristics of a military turbojet engine" deals with the latest developments that exist and those which are proposed to be established in the field of VTOL (Vertical Take-Off and Landing) aeronautical engineering. The biggest problem that exists today in that field is that no aircraft can have both Vertical takeoff and Supersonic cruise on a same design. To overcome this, a …
Published in Journal of Aerospace Engineering & Technology · Vol. 5, Issue 1, 2015 · pp. 37–46 Read article