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303 articles for “computational complexity”
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A Quantitative Fuzzy MCDM Framework for Decision Support in Uncertain Environments
Abstract: Fuzzy mathematics play an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and it signs other possible solutions in addition to fuzzy mathematics. Fuzzy models offer a versatile and precise approach to assessing complex situations through the use of fuzzy sets, membership functions, and aggregation methods. Through time, cost and quality, the project management case study illustrates how fuzzy logic works for them. …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 13, Issue 1, 2026 · pp. 1–8 Read article
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Fuzzy Mathematics in Decision-Making: A Quantitative Perspective
Abstract: Fuzzy mathematics plays an increasingly generalized role in decision-making, and thus, this paper details different types of fuzzy mathematics and highlights other possible alternatives alongside fuzzy methodologies. Fuzzy models offer a versatile and precise approach to assessing complex and uncertain situations using fuzzy sets, membership functions, linguistic variables, and aggregation methods. Through the lenses of time, cost, and quality, the project management case study illustrates how fuzzy logic effectively evaluates …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 12, Issue 1, 2025 · pp. 6–12 Read article
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Optimization of Robotic Path Planning Algorithms for Autonomous Material Handling Systems
Abstract: For autonomous systems for handling materials (AMHS) to operate as efficiently as possible in industrial and logistical settings, robotic route planning is essential. This study examines many robotic route planning algorithms, emphasizing their use, ways of optimization, and difficulties in material handling systems. To improve the effectiveness, precision, and computational viability of these algorithms, the study also examines a number of optimization strategies, including machine learning, parallelization, heuristic search, and …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 2, Issue 2, 2024 · pp. 15–20 Read article
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Wireless Sensor Network Localization Based on Static Anchor Node
Abstract: Anchor-based localization is a crucial challenge in wireless sensor networks (WSNs), aiming to determine the positions of all sensors by leveraging a limited number of anchor nodes whose locations are known. In this paper, we propose a novel algorithm for anchor-based localization in a static network, which improves the localization accuracy while reducing the computational complexity compared to existing methods. Our algorithm uses a range-based approach to estimate the distances …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 12–20 Read article
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Data Recovery Using Brute Force Algorithm: A Review
Abstract: This article delves into the intriguing field of data recovery, with a particular emphasis on the brute force approach, a powerful yet frequently underappreciated method. We begin by exploring the evolution of data recovery techniques since the 1970s and 1980s, examining traditional methods used to retrieve lost or corrupted data. Following this historical perspective, the article provides a brief overview of various methodologies employed in data recovery, including techniques that …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 10–16 Read article
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Modelling Electronic Diode Networks with PSPICE Simulation
Abstract: The dual of Thevenin, Norton equivalent circuit is used in place of any circuit/network of linear sources and immittances at at a given frequency. Both Thevenin with Norton theorem is useful for analyses and modification of circuits, to study /obtain network’s steady state response and initial condition. Methods to represent different circuits with Thevenin/Norton impedances connected at desired nodes are given using Spice/Pspice. The Thevenin/Norton impedances connected are of other …
Published in International Journal of VLSI Circuit Design & Technology · Vol. 2, Issue 2, 2024 · pp. 17–37 Read article
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Deep Learning-Based Thermal Prediction Models for Solid-State Electronic Devices
Abstract: The rapid advancement of solid-state electronic devices in high-performance computing, communication systems, automotive electronics, and renewable energy applications has significantly increased concerns related to thermal management and device reliability. Excessive heat generation in semiconductor devices adversely affects operational efficiency, switching performance, lifespan, and overall system stability. Traditional thermal prediction methods often require complex numerical computations and extensive simulation time, making them less suitable for real-time monitoring and adaptive control applications. …
Published in International Journal of Solid State Innovations & Research · Vol. 4, Issue 1, 2026 Read article
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Integrated Perspectives on Fluid Mechanics and Energy Transport in Complex Flow Systems
Abstract: Fluid mechanics plays a central role in understanding the transport of mass, momentum, and energy in complex flow systems encountered in both natural and engineered environments. This review presents an integrated perspective on fluid behavior by combining fundamental principles with modern approaches to energy transport analysis. The study emphasizes the significance of conservation laws and their application to diverse flow regimes, including laminar, turbulent, compressible, and multiphase flows. Energy transport …
Published in Recent Trends in Fluid Mechanics · Vol. 13, Issue 1, 2026 · pp. 22–31 Read article
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Algorithmic Strategies for Complex Data Handling: Optimizing Data Structures for Enhanced Computational Performance
Abstract: We live in an age of big data and processing very large often complicated datasets can be crucial to efficient algorithmic performance. This paper discusses different algorithmic techniques when working with difficult data and how to arrange your information structures correctly for better functionality in large-scale methods. It checks the impact of different algorithms like sorting, searching, and hashing in boosting its processing speed as well as memory use. This …
Published in International Journal of Data Structure Studies · Vol. 2, Issue 2, 2024 · pp. 1–10 Read article
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Performance Analysis of Deep CNN Architectures
Abstract: A Convolutional Neural Network (CNN) is an artificial neural network renowned for its remarkable ability to handle large image datasets effectively, particularly excelling in tasks such as image recognition and classification. The fundamental structure of a CNN relies on mathematical convolution operations, comprising essential components such as convolutional layers, activation functions, pooling layers, and fully connected layers. These components work synergistically to extract and learn hierarchical features from input data, …
Published in Journal of Communication Engineering & Systems · Vol. 14, Issue 2, 2024 · pp. 1–8 Read article
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Asymptotic Notations: A Review
Abstract: Asymptotic notations play a fundamental role in assessing the efficiency and performance of algorithms, particularly as input sizes grow larger. This paper delves into three key asymptotic notations: Big O, Theta, and Omega, which are essential for understanding the upper, average, and lower bounds of an algorithm’s runtime. Big O notation specifically helps in determining the worst-case scenario of an algorithm’s growth rate, providing an upper bound on time or …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 3, 2024 · pp. 17–33 Read article
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Fuzzy Probability Distributions and Their Applications in Uncertain Data Analysis
Abstract: This study explores the use of fuzzy probability distributions in data analysis under uncertain conditions, with a specific focus on their implementation in evaluating call center customer satisfaction. Traditional probability models rely on precise parameters, often failing to account for the inherent variability and subjectivity present in real-world data. In contrast, fuzzy probability distributions, which integrate fuzzy logic principles, offer a more adaptable and realistic framework for addressing such complexities. …
Published in Research & Reviews : Journal of Statistics · Vol. 13, Issue 3, 2024 · pp. 1–8 Read article
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AI for Cybersecurity: Deploying Machine Learning for Network Traffic Anomaly Detection
Abstract: The growing sophistication of cyberattacks and the growth of network traffic necessitate sophisticated anomaly detection methods. This study overviews the use of artificial intelligence (AI) and machine learning (ML) to counter these challenges, as noted in current studies. It analyses supervised learning (SVM, Decision Trees), unsupervised learning (K-means, DBSCAN), and deep learning (CNNs, RNNs, Auto-encoders) approaches, considering their strengths and weaknesses. The research integrates current developments in AI/ML-based network anomaly …
Published in International Journal of Computer Science Languages · Vol. 3, Issue 2, 2025 · pp. 1–10 Read article
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Computational Study of Sombor Index on Generalized Abid–Waheed Graphs for Polymer Modeling
Abstract: This study investigates the topological properties of generalized Abid Waheed graphs. Development of theoretical models in chemistry, reducing computational complexity while analysing large molecules or networks Abid Waheed graphs play a significant role. Motivated by these findings, the research was extended to encompass generalized Abid Waheed graphs, characterized by r cycles of order s. A notable similarity between Abid Waheed graphs and Jahangir graphs was observed. The potential applications of …
Published in Journal of Polymer & Composites · Vol. 13, Issue 5, 2025 · pp. 267–274 Read article
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Integrating Genetic Algorithms with Lean Manufacturing for Enhanced Production Efficiency
Abstract: Lean manufacturing is a well-established philosophy focusing on the systematic reduction of waste and the ongoing development of value supplied to the customer. It emphasizes efficiency, quality, and adaptability through ideas such as just-in-time production, continuous improvement (Kaizen), and value stream optimization. However, the increased complexity of modern production systems, driven by global rivalry, product variety, and rapid technology innovation, has shown the limitations of classic lean tools in achieving …
Published in Journal of Production Research & Management · Vol. 15, Issue 3, 2025 · pp. 38–43 Read article
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A Comparative Study of Transfer Learning-Based Deep Learning Models for Breast Cancer Detection
Abstract: Breast cancer is a major concern in the world today, and early and accurate diagnosis is most crucial in the case of breast cancer, as it is among the disorders where the total cost of loss of life is high. Traditional screening processes are subjective and vulnerable to inter-observer reliability issues and diagnostic errors, being primarily based on manual interpretation of medical images. To address these limitations, Deep Learning (DL) …
Published in Research and Reviews : A Journal of Medical Science and Technology · Vol. 15, Issue 1, 2026 · pp. 24–34 Read article
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Mitigation of Peak to Average Power Ratio in Orthogonal Frequency Division Multiplexing through SOP-PTS
Abstract: Orthogonal Frequency Division Multiplexing (OFDM) is a popular multicarrier modulation technology extensively employed in 4G wireless communication systems to transmit data over a dispersive channel. To address the Peak-to-Average Power Ratio (PAPR) issue in OFDM, a technique called Partial Transmit Sequence (PTS) is commonly utilized. The PTS method involves dividing the data block into non-overlapping sub-blocks and then combining them using phase factors to mitigate PAPR. However, the conventional PTS …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 32–39 Read article
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Exhaustive Search Meets DNA Sequencing: A Comprehensive Review of TSP-Based Approaches
Abstract: Exhaustive search is a highly computational complex algorithm that checks every possibility to obtain the best solution. We illustrate an exhaustive search by applying it to three important problems: the traveling salesman problem, the knapsack problem, and the assignment problem. In this paper, we took a traveling salesman problem to explain DNA Sequencing. Since traveling salesman problem is an algorithmic problem that finds the shortest route between a set of …
Published in International Journal of Bioinformatics and Computational Biology · Vol. 2, Issue 2, 2024 · pp. 11–21 Read article
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Entropy, Symmetry, and Data Fusion: Emerging Methods in Multi-Objective Decision- Making and Smart Systems
Abstract: In the era of intelligent technologies and data-driven systems, multi-objective decision-making (MODM) has become an essential aspect of managing complex environments such as smart cities, autonomous systems, and cyber-physical networks. As decision-making scenarios become increasingly dynamic and uncertain, there is a growing need for advanced methodologies that can handle diverse objectives, conflicting constraints, and incomplete information. This review highlights the emerging role of entropy, symmetry, and data fusion as foundational …
Published in Emerging Trends in Symmetry · Vol. 1, Issue 2, 2025 · pp. 44–49 Read article
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CMOS-Based Process-Scalable Analog Circuits for Machine Learning: A Comprehensive Review and Future Directions.
Abstract: Analog computing techniques are gaining attention for machine learning (ML) applications due to their ability to reduce computational complexity. Continuous operations such as addition and subtraction offer a simpler and more efficient approach compared to probabilistic product decoding, which can be sensitive to noise and inconsistent measurements. This paper presents a simulated VLSI implementation of a broadcast edge connection, independent of the MOS component model, along with experimental results. The …
Published in Journal of VLSI Design Tools and Technology · Vol. 15, Issue 1, 2025 · pp. 8–17 Read article