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404 articles for “complex algorithms”
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Social Media Blog Analysis using Watson Analytics
Abstract: AbstractAnalytics is defined as the discovery, interpretation, and communication of meaningful patterns in data. A blog is a discussion or informational website published on the world wide web consisting of discrete, often informal diary-style text entries and may contain unstructured or semi-structured data. The analysis of unstructured data types is current challenge, getting attention in industry. Challenges include analysis, capture, data curation, search, sharing, storage, transfer, visualization and information privacy. …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 3, Issue 3, 2016 · pp. 15–21 Read article
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Innovative Approaches to Fake Product Detection: Blockchain and QR Code Synergy
Abstract: For consumers, corporations, and regulatory agencies, the worldwide market's rise of counterfeit goods presents serious issues. Maintaining consumer confidence, guaranteeing product safety, and preserving brand reputation all depend on the ability to identify counterfeit goods. An overview of the different approaches and difficulties associated with spotting counterfeit goods is given in this abstract. First off, the ability to identify sophisticated counterfeit goods is limited by the use of conventional techniques …
Published in International Journal of Radio Frequency Innovations · Vol. 2, Issue 1, 2024 · pp. 21–27 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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Emerging Paradigms: Leveraging Artificial Intelligence and Machine Learning for Enhanced Wireless Network Security
Abstract: Wireless networks have now become an indispensable component of our contemporary communication infrastructure, offering both connectivity and convenience. Nonetheless, the increasing complexity and constantly evolving nature of wireless networks present substantial security challenges. This work investigates the utilization of artificial intelligence (AI) and machine learning (ML) techniques to tackle these security issues in wireless networks. We delve into the principles and practices of applying AI and ML algorithms to enhance …
Published in Journal Of Network security · Vol. 11, Issue 2, 2023 · pp. 18–25 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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Performance Analysis of Encryption and Decryption Using Chaotic Neural Network
Abstract: Abstract: A neural network is a machine that is designed to model the way in which the brain performs a task or function of interest. It has the ability to perform complex computations with ease. The goal of this task was to examine the utilization of artificial neural networks (ANNs) in different sorts of digital circuits just as in the field of cryptography. During our project, we have studied chaotic …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 6, Issue 3, 2019 · pp. 8–11 Read article
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Revolutionizing Wireless Communication: AI & ; ML in the Era of 6G
Abstract: With rapid technological advancement, sophisticated techniques are significantly enhancing the performance of wireless networks. In parallel, the growth of artificial intelligence (AI) has empowered systems to perform intelligent decision-making, automate processes, analyze data, generate insights, and predict future outcomes. AI systems are now capable of learning and adapting to dynamic environments. Particularly, machine learning and deep learning techniques have achieved remarkable success across a wide range of applications in recent …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 3, 2025 · pp. 29–36 Read article
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Improving Supply Chain Resilience through Predictive Analytics and Real-Time Data Integration
Abstract: Demand forecasting has under gone major changes because to the incorporation of automated analytics into supply chain management (SCM), which has improved company productivity, accuracy, and responsiveness. Central to this transformation is the application of machine learning (ML), which enables the analysis of large and complex datasets to identify patterns, detect trends, and generate precise forecasts. Conventional methods for predicting frequently rely on linear models and historical sales data, which …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 8–17 Read article
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Cyberattack Detection and Prevention Using Empowering AI Tools
Abstract: With more organizations entering the digital transformation sphere, the opportunities and risks in cyberspace have increased and gone up in levels of sophistication and occurrence. Many of these developments are attributed to the limits of existing cyber security solutions where addressing new threats requires advanced detection technologies and techniques. Cyber threats gained a new meaning and dimension with artificial intelligence (AI) coming into play in ways that supplement security systems …
Published in International Journal of Information Security Engineering · Vol. 2, Issue 2, 2024 · pp. 1–7 Read article
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Artificial Intelligence in Cybersecurity: Emerging Trends, Technological Advancements, and Future Directions for Cyber Defense
Abstract: Artificial Intelligence (AI) is revolutionizing the field of cybersecurity by automating complex security tasks, improving threat detection capabilities, and enhancing the precision of threat response mechanisms. With the rapid evolution of cyber threats such as malware, ransomware, phishing, and data breaches, conventional security systems are often insufficient to provide timely and accurate protection. AI, powered by machine learning algorithms and neural networks, enables the analysis of vast datasets to detect …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 12, Issue 2, 2025 · pp. 103–112 Read article
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The Principles and Applications of Structural Symmetry in Natural and Engineered Systems: A Comprehensive Review
Abstract: Structural symmetry is a fundamental constraint across scientific domains, dictating the stability, functionality, and efficiency of systems from the subatomic to the macroscopic. In physics and chemistry, symmetry is mathematically defined through Group Theory, specifically point groups (e.g., Cnv, Oh). These groups govern molecular orbital interactions; high-symmetry configurations, such as the icosahedral C60 fullerene, achieve optimal energy distribution and structural resilience. In Structural Biology, symmetry is an evolutionary strategy for …
Published in Emerging Trends in Symmetry · Vol. 2, Issue 1, 2026 · pp. 30–34 Read article
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Comparative Analysis of CMOS CNFET and Memristor Based Full Adder Circuits and CMOS Memristor Based Multiplexer Circuits
Abstract: Continued developments in microelectronics technology have led to a myriad of new compute- intensive applications at the micro-edge, such as artificial intelligence and signal and image processing. Multiplication is a crucial arithmetic process in such applications. However, large logic complexities typically seen in traditional multipliers generate combinatorial blocks with long chains of cascaded carry addition. As such, energy efficiency has remained a primary design challenge for these applications, when powered …
Published in Journal of VLSI Design Tools and Technology · Vol. 12, Issue 4, 2022 · pp. 23–35 Read article
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Using AIML to Enhance Demand Forecasting in Business
Abstract: Artificial intelligence machine learning (AIML) can play a significant role in enhancing demand forecasting in business. AIML is a programming language designed for creating chatbots and conversational agents, but its application extends beyond simple interactions. In the context of demand forecasting, AIML can be utilized to analyze historical data, customer interactions, and market trends. By implementing AIML algorithms, businesses can create intelligent models that learn from past demand patterns, customer …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 35–40 Read article
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Revolutionizing oncology - role of artificial intelligence in early cancer detection and diagnostic advances-A comprehensive review
Abstract: Oncology has experienced a remarkable transformation with the adoption of artificial intelligence (AI), which has greatly enhanced cancer detection and diagnosis. As one of the leading causes of death worldwide, cancer highlights the importance of early detection in improving patient outcomes and survival rates. AI’s ability to analyze vast and complex datasets has enabled groundbreaking innovations in imaging, pathology, biomarker discovery, and predictive analytics. This review highlights key AI-driven advancements …
Published in Research and Reviews: Journal of Oncology and Hematology · Vol. 14, Issue 1, 2025 · pp. 18–22 Read article
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Comparative Analysis of CMOS CNFET and Memristor Based Full Adder Circuits and CMOS Memristor Based Multiplexer Circuits
Abstract: Continued developments in microelectronics technology have led to a myriad of new compute-intensive applications at the micro-edge, such as artificial intelligence and signal and image processing. Multiplication is a crucial arithmetic process in such applications. However, large logic complexities typically seen in traditional multipliers generate combinatorial blocks with long chains of cascaded carry addition. As such, energy efficiency has remained a primary design challenge for these applications, when powered by …
Published in Journal of VLSI Design Tools and Technology · Vol. 12, Issue 2, 2022 · pp. 22–33 Read article
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Development and Performance Evaluation of Efficient Low-Complexity SPIHT Image Coder
Abstract: Wavelet transform is one of the advanced, effective and computationally fast methods for image data as well as video compression. The wavelet based image compression is particularly a nonreversible method that has been growing computationally more complicated as they getting more accurate and reliable. In this work we have developed an image compression technique based on main concepts related to partial ordering of the coefficients of image matrix elements by …
Published in Journal of Advanced Database Management & Systems · Vol. 2, Issue 3, 2015 · pp. 5–10 Read article
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A Review of Machine and Deep Learning Techniques for Cyber Security
Abstract: Nowadays in the digital landscape, cyber threats and attacks are increasing in an exponential manner, posing server risks to organizations and critical infrastructures. Data breaches often result from sophisticated threat models that exploit vulnerabilities in networks, systems and user behaviors. Cyber solutions are increasingly incorporating machine learning and deep learning to prevent and mitigate these security issues. These technologies have the potential to detect anomalies, classify threats and predict potential …
Published in Journal of Computer Technology & Applications · Vol. 16, Issue 3, 2025 · pp. 01–07 Read article
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Disease Prediction Using Ensemble Learning Models: A Comprehensive Approach
Abstract: In recent years, ensemble learning techniques have become pivotal in advancing predictive analytics within healthcare, particularly for early disease detection. The inherent variability and complexity of medical data, often characterized by high dimensionality, class imbalance, and noise, make it challenging for standalone classifiers to maintain high predictive accuracy. Ensemble learning, by integrating multiple models through bagging, boosting, or stacking, offers a more robust and generalizable approach. This study explores the …
Published in Journal of Communication Engineering & Systems · Vol. 15, Issue 3, 2025 · pp. 26–33 Read article
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Artificial Intelligence in Microbiological Research: Methods, Applications and Implications
Abstract: Artificial Intelligence (AI) is revolutionising microbiological research by enabling the rapid analysis of complex biological data and improving the accuracy, efficiency, and reliability of scientific investigations. Recent advances in machine learning, deep learning, and bioinformatics have transformed AI into a powerful tool for studying microorganisms, their genetic composition, evolutionary patterns, and interactions with hosts and the environment. AI-driven computational models can process large and complex datasets far more efficiently than …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 16, Issue 2, 2026 · pp. 22–36 Read article
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Adaptive Machine Learning Framework for Navigation Control of Autonomous Drones
Abstract: The rise of autonomous drones has expanded UAV applications across sectors like surveillance, delivery, agriculture, and rescue operations. However, traditional navigation systems face limitations in adapting to dynamic environments. This study proposes an AI-driven adaptive navigation framework that leverages real-time sensor data, reinforcement learning, and adaptive control strategies to enhance drone autonomy, scalability, and security. The system processes mission inputs, environmental data (from LiDAR, cameras, GPS, and weather sensors), and …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 1–7 Read article