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303 articles for “computational complexity”
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Swarm Intelligence in Software Engineering: A Systematic Review of Crowd-Based Development Models
Abstract: The crowd-based software production model has emerged as a transformative paradigm, leveraging global collaboration, decentralized governance, and artificial intelligence (AI)-driven automation to develop software efficiently. Traditional software development models, characterized by centralized control and in-house teams, are increasingly giving way to distributed, community-driven efforts. Key advancements such as blockchain-based decentralized autonomous organizations (DAOs), AI-assisted coding and debugging, and edge computing applications are reshaping the landscape of software engineering. DAOs provide …
Published in Journal of Software Engineering Tools & Technology Trends · Vol. 12, Issue 2, 2025 · pp. 01–11 Read article
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A Novel Symmetric Anchor Scoring (SAS) Method for Industrial Location Selection: Application to Electric Vehicle Manufacturing in Tamil Nadu, India
Abstract: This work highlights the city-level detail of decision-making enabled by a new MCDM method Symmetry Anchor Scoring (SAS). Generally conventional methods are good at selecting one best and one worst alternative, but not differentiating among the many strong contenders more likely in practice. Linking MCDM methods to the tradition of decision making, the paper discusses the mathematics and analogical basis of SAS design, provides a visual proof of its ideal …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 8–19 Read article
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Fracture Analysis of Laminated composite plates using Extended Finite Element Method: A Review
Abstract: Laminated composite plates are used in aerospace, automotive, and marine industries. They feature great durability against fatigue, a high strength-to-weight ratio, and mechanical attributes that may be altered. However, they are prone to fracture and delamination under complex loading, requiring accurate fracture analysis for structural integrity. Traditional finite element methods (FEM) need extensive mesh refinement for modelling crack propagation which increases the computational costs. The Extended Finite Element Method (XFEM) …
Published in International Journal of Fracture Mechanics and Damage Science · Vol. 4, Issue 1, 2026 · pp. 16–25 Read article
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Nano‑Enabled CT for Cancer Imaging: From Molecular Targeting to Image‑Guided Therapy
Abstract: Nano‑enabled computed tomography (CT) exploits high‑atomic‑number (high‑Z) nanomaterials engineered with targeting ligands and therapeutic payloads to enhance contrast, enable molecular imaging, and support image‑guided interventions in oncology. Tumor‑specific nanoprobes such as RGD‑modified gold nanorods, polymer‑coated bismuth nanoparticles, and peptide, antibody, or aptamer‑functionalized platforms can intensify tumor conspicuity, allow early lesion detection and staging, and provide real‑time treatment monitoring. Integration of CT visibility with photothermal, photodynamic, chemo‑, radio‑, and immunotherapeutic functions …
Published in Nano Trends – A Journal of Nano Technology & Its Applications · Vol. 28, Issue 1, 2025 · pp. 40–49 Read article
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Harnessing Deep Learning to Explore Microbial Community Structure and Carbon Storage Capacity in Mangrove Ecosystems: A Framework for Computationally
Abstract: Mangrove ecosystems represent one of the most efficient natural carbon sinks on Earth, functioning as critical blue carbon habitats that sustain diverse microbial communities responsible for biogeochemical cycling and long-term carbon storage. Despite their global ecological significance, accurately quantifying and predicting carbon sequestration in mangrove systems remains challenging due to the complex interactions between microbial diversity, sediment chemistry, and environmental drivers. This study presents a comprehensive and sustainable artificial intelligence …
Published in Research and Reviews : Journal of Computational Biology · Vol. 15, Issue 1, 2026 Read article
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Autonomous 6G Physical Layer Architectures for Space-Air-Ground Integrated Networks
Abstract: The emergence of sixth generation (6G) wireless systems calls for a significant shift away from conventional deterministic communication models. As communication infrastructures evolve into Space- Air-Ground Integrated Networks (SAGIN), traditional physical layer (PHY) techniques struggle to operate effectively under the severe Doppler effects and long propagation delays associated with space environments. This paper examines the role of artificial intelligence embedded directly within the 6G transceiver architecture to enable ultra-reliable and …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 13, Issue 2, 2026 Read article
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AI/ML-Based Approach to Solar Irradiance Prediction and Energy Suitability
Abstract: In this paper, due to challenges in precisely predicting solar irradiance, which is essential for solar power system optimization, we employed six diverse machine learning (ML) techniques: Linear Regression, Decision Tree, Random Forest, Gradient Boosting methods (including XGBoost), and Neural Networks—to analyze and predict outcomes using a dataset containing meteorological and temporal features. Key variables include wind speed, humidity, and temperature, which significantly influence the model’s predictive capability. Each method …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 16, Issue 3, 2025 · pp. 36–48 Read article
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Integrated Qualitative Response Assessment System
Abstract: Examinations for universities and yearboards are traditionally administered offline, with a significant number of students opting for subjective exams. This preference stems from the labor-intensive nature of evaluating subjective responses, which requires considerable time and effort from educators. Additionally, subjective grading can be influenced by the evaluator’s mood, leading to inconsistencies. In contrast, multiple-choice and objective questions are prevalent in entrance and competitive exams due to their ease of automated …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 18–24 Read article
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Animated Transient Response of High Voltage Power Line Towers Equipped with Nonlinear Footing Resistances
Abstract: This study focuses, among other objectives, on the use of animation techniques for visualizing the electromagnetic transients in high voltage power line towers. The model includes parameters such as the tower’s footing resistance and its location-dependent surge impedance. It describes the governing algebraic/partial differential equations expressed in terms of the current and voltage distributions as functions of time and location. The transients are assumed initiated by a lightning discharge of …
Published in Trends in Electrical Engineering · Vol. 14, Issue 1, 2024 · pp. 44–52 Read article
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An in-Depth Analysis of Cyber Security: Vulnerabilities, Threat Landscapes, Attack Mechanisms, and Defense Solutions
Abstract: In a highly digitalized world today, cyber security has taken over as a necessary component to safeguarding the modern world technology. With the increase in the dependency on the digital platform and online services, the threat of cyber threats has also risen. Such threats are not confined to mere attacks anymore, as they have taken a new form of complexity and magnitude to impact individuals, businesses, government institutions among others. …
Published in Journal Of Network security · Vol. 14, Issue 2, 2026 Read article
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Sustainable Cotton Crop Productivity through Precision Weed Detection: A Deep Learning-Based Approach with UAV Integration
Abstract: Weeds present a major challenge to crop productivity by competing with crops for vital resources, including water, sunlight, and nutrients, often resulting in significant yield reductions. On a global scale, weeds are responsible for approximately 13.2% of annual crop losses, a quantity sufficient to feed nearly one billion people. These invasive plants disrupt agricultural systems and adversely impact crop yields. Given their uneven distribution in fields, ground or aerial robots …
Published in Journal of Aerospace Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 19–26 Read article
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Electronic Design Technology: From Circuits to Smart Systems
Abstract: Electronic Design Technology has changed a lot over the years. It has gone from making simple circuits to making smart, complicated systems that run modern life. This article looks at how electronic design methods have changed over time, focusing on important improvements in tools, materials, and integrated systems. It looks at how new technologies like computer-aided design (CAD), embedded systems, and automation have made product creation faster, more accurate, and …
Published in Journal of Electronic Design Technology · Vol. 17, Issue 1, 2026 · pp. 25–36 Read article
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Ai-Driven Healthcare System for Enhanced Diagnosis and Patient Interaction
Abstract: Deep learning techniques are used in an AI-driven healthcare system to improve disease identification and medical picture analysis. Data collection, preprocessing, model training, and evaluation are all part of the system's systematic workflow. Various deep learning architectures, such as ResNet50, VGG-16, and U-Net, are employed for precise classification and segmentation of medical images. The approach incorporates advanced techniques such as optimization, transfer learning, and data augmentation to significantly enhance the …
Published in Research and Reviews: A Journal of Health Professions · Vol. 15, Issue 2, 2025 Read article
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Fortifying the Cloud: AI-Driven Security Paradigms and Evolving Threat Defenses in Modern Cloud Computing
Abstract: Organizations worldwide are raising their concerns about security maintenance while cloud computing expands rapidly to serve as a digital transformation foundation. The study explores modern cloud security patterns while also evaluating how artificial intelligence modifies the identification and evaluation of complex cyber threats along with their prevention methods. New security threats such as insider operations and DDoS attacks and data breaches alongside insecure APIs can be detected through machine learning …
Published in Journal of Operating Systems Development & Trends · Vol. 12, Issue 2, 2025 · pp. 34–40 Read article
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The Future of Robotics: A Review of AI-Enabled Robotics Research, Development, and Applications
Abstract: Robotics powered by artificial intelligence (AI) is transforming contemporary industries by empowering machines to learn, adapt, and operate on their own in intricate, changing contexts. The breadth and capabilities of automation have been greatly expanded by the convergence of AI technologies with robots, including machine learning, deep learning, computer vision, and natural language processing (NLP). With an emphasis on technological advancements, application areas, and research advances, this study examines current …
Published in International Journal of Robotics and Automation in Mechanics · Vol. 3, Issue 2, 2025 · pp. 33–38 Read article
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Predicting and Prohibiting the Risk of Heart Failure Using Machine Learning
Abstract: It is challenging to estimate the likelihood of complex chronic disease while treating conditions like heart failure. The application of machine learning, an area of artificial intelligence, in cardiovascular care is growing quickly. In essence, it defines how computers classify and understand data, or choose a task with or without human intervention. The theoretical underpinnings of machine learning are models that accept input data (such as images or text) and …
Published in International Journal of Computer Science Languages · Vol. 1, Issue 1, 2023 · pp. 15–20 Read article
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A Survey on the Evolution of AI (Artificial Intelligence) and Robotics
Abstract: This is the age of new technology and gadgets to improve the livelihood of human beings in aspects of every manner while arranging the host of facilities for every task related to our daily lifestyle. To improve the machine and their working manner smartly only programming is not enough it takes a lot more than just programming and here the implementation of AI tools takes place to improve the quality, …
Published in Journal of Advancements in Robotics · Vol. 11, Issue 3, 2024 · pp. 10–17 Read article
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Encoding-Decoding Algorithm Using the Catalan Transform of Weighted Tribonacci Sequence
Abstract: In order to improve information security, this paper presents a unique algorithm for encoding and decoding messages utilizing the Catalan Transform of a Weighted Tribonacci Sequence. Utilizing the Catalan and Tribonacci sequences, the methodology combines the concepts of number theory and combinatorics to create an effective encryption and decryption process. First, an array is created by mapping each character in the plaintext message to its corresponding ASCII value. The ASCII-weighted …
Published in Research & Reviews: Discrete Mathematical Structures · Vol. 11, Issue 3, 2024 · pp. 12–16 Read article
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A Comprehensive Review of Metabolite
Abstract: Metabolites, tiny chemicals, are essential to physiology, signalling, and biological function. This extensive review classifies metabolites into primary and secondary categories by biological relevance. Alkaloids, flavonoids, and terpenoids contribute to ecological interactions and defence systems, while amino acids, nucleotides, and carbohydrates directly affect development and cellular function. The article examines metabolic pathways, mass spectrometry, NMR, and metabolomics, a growing field. Metabolites play a crucial role in various scientific and practical …
Published in Emerging Trends in Metabolites · Vol. 2, Issue 2, 2025 Read article
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Triple-Threat Analysis: Measuring Mythril, Slither and Oyente Against Real-World Smart Contract Vulnerabilities
Abstract: Smart contracts have become fundamental building blocks of blockchain ecosystems, yet their immutable nature makes security vulnerabilities particularly devastating. This pa- per presents a comprehensive evaluation of three prominent static analysis tools—Mythril, Slither, and Oyente—for detecting vulnerabilities in Ethereum smart contracts. Through systematic experimentation with real-world contract categories (voting sys- tems, land registries, and crowdfunding platforms), we quantify the effectiveness of each tool across eight critical vulnerability types, including reentrancy, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article