Search
1868 articles for “Artificial intelligence, Natural Language Processing (NLP), Fuzzy Logic, Deep Learning, Covid-19” (ranking capped at the first 2,000 matches — narrow the search to see the rest)
Nothing matched all of your words, so these match any of them.
-
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
-
A Short Discussion About E-learning
Abstract: Improvement in E-learning activities supports the country for development. At present time all education systems are based on E-learning all over the world because of digitization and covid pandemic. Web-based learning, online learning, internet-based learning, distance learning, distance education, distributed learning, computer-mediated learning, computer-assisted learning, Virtual Learning, and Blended Learning are all terms used to describe E-learning. The current study's goal is to evaluate the efficiency of e-learning in smart …
Published in Journal of Production Research & Management · Vol. 11, Issue 3, 2021 · pp. 27–31 Read article
-
A Taxonomy of Machine Learning Techniques
Abstract: Learning is any process by which a system improves performance from experience. Training a model simply means learning (i.e., determining) good values for all the weights and therefore the bias from labeled examples. Machine learning (ML) is a sub-field of artificial intelligence that creates machines which exhibits learning capability and improve their performance from experience without being explicitly programmed. ML focuses on the creation of computer programs that can access …
Published in Journal of Advancements in Robotics · Vol. 8, Issue 3, 2021 · pp. 18–25 Read article
-
Enhancing Profanity Detection in Dravidian Languages: Leveraging Language Models for Optimization and Improvement
Abstract: Detecting and documenting instances of abusive behaviour can significantly improve the quality of virtual environments. Given the vast amount of content published daily on social media, it is impractical for human annotators to manually identify potentially harmful content. Recent algorithmic initiatives, especially on platforms like Twitter, have advanced in abuse detection. However, for Dravidian texts, there remains a need to understand the context better and build robust language models for …
Published in Recent Trends in Programming languages · Vol. 11, Issue 2, 2024 · pp. 17–23 Read article
-
Text Summarizer using NLP (Natural Language Processing)
Abstract: Enormous amounts of information are available online on the World Wide Web. To access information from databases, search engines like Google and Yahoo were created. Because the amount of electronic information is growing every day, the real outcomes have not been reached. As a result, automated summarization is in high demand. Automatic summary takes several papers as input and outputs a condensed version, saving both information and time. The study …
Published in Journal of Computer Technology & Applications · Vol. 12, Issue 3, 2021 · pp. 1–6 Read article
-
The Influence of Artificial Intelligence on Literary Criticism
Abstract: Artificial Intelligence (AI) has emerged as a significant force in reshaping contemporary literary criticism. Traditionally, the interpretation of literature has relied primarily on human-centered methods such as close reading, contextual analysis, and theoretical framing. However, the integration of AI-based techniques including Natural Language Processing (NLP), Machine Learning (ML), stylometry, and sentiment analysis has introduced new possibilities for examining literary texts at both micro and macro levels. These computational approaches allow …
Published in International Journal of Trends in Humanities · Vol. 3, Issue 2, 2026 · pp. 22–29 Read article
-
Artificial Intelligence In Transfusion Medicine And In Our Mission To “BEAT- COVID”
Abstract: The key objectives of this manuscript are: 1] Demystifying the buzzword of Artificial Intelligence [AI] and comparing neuronal networkings similarity of machines with some mammals; 2] Exploring, from outside sources, the breath of some computerized procedural data generated in laboratory and clinical areas of medicine, by robotic tools in the cutting age of transfusion medicine; 3] Expressing views on the variabilities of covid- associated long lasting microcirculatory disseminated pathogenic autoimmune …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 7, Issue 3, 2020 · pp. 10–21 Read article
-
Artificial Intelligence for Real-time Water Management
Abstract: Effective water management is vital for sustainable development, requiring the strategic allocation and utilization of water resources to satisfy the diverse demands of agriculture, industry, and households. Traditional methods are increasingly inadequate due to escalating challenges from climate change and population growth, which amplify water scarcity and distribution issues. To overcome these challenges, we need innovative solutions. Artificial intelligence offers significant potential in revolutionizing realtime water management through advanced techniques …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 13–20 Read article
-
Empowering Vehicle: The Impact of Deep and Reinforcement Learning in IoV
Abstract: Deep learning and reinforcement learning represent two pivotal pillars within the realm of artificial intelligence and machine learning, bearing transformative potential in the domain of the Internet of Vehicles (IoV). This abstract explores the multifaceted applications of these cutting-edge techniques within the IoV framework. Deep learning, exemplified by convolution neural networks (CNNs) and recurrent neural networks (RNNs), empowers IoV systems with the prowess to discern complex patterns in sensory data. …
Published in International Journal of Advanced Robotics and Automation Technology · Vol. 3, Issue 2, 2025 · pp. 1–12 Read article
-
AI-Powered Defense: Advancing Cybersecurity Through Artificial Intelligence Innovations
Abstract: In the current landscape of escalating cyber threats and increasingly sophisticated attack vectors, integrating artificial intelligence (AI) within cybersecurity strategies has become a critical step forward. This study explores the role of AI in strengthening cybersecurity by utilizing its strengths in data analysis, pattern recognition, and predictive modeling. Through AI, organizations can greatly enhance their ability to detect and respond to threats. Machine learning algorithms enable ongoing adaptation to new …
Published in International Journal of Information Security Engineering · Vol. 4, Issue 1, 2026 · pp. 35–41 Read article
-
Artificial Intelligence for Sustainable Agriculture, Forestry and Rural Development: Recent Advances, Applications and Research Opportunities
Abstract: Artificial Intelligence (AI) has emerged as a transformative technology with the potential to revolutionize agriculture, forestry, and rural development by enabling data-driven decision-making, resource optimization, and sustainable management practices. Rapid developments in computer vision (CV), machine learning (ML), deep learning (DL), natural language processing (NLP), and predictive analytics have increased the use of AI in a variety of rural industries. In agriculture, AI-driven technologies support precision farming, crop yield prediction, …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 3, 2025 Read article
-
Use of Artificial Intelligence to Access and Ensure Safe Drinking Water Supply: A Review
Abstract: Ensuring access to safe drinking water is a critical public health challenge. Traditional water quality assessment methods are often labor-intensive and time-consuming. Artificial intelligence offers a promising alternative, providing rapid, accurate, and scalable solutions for monitoring and predicting water quality. This systematic review examines the application of AI. The review highlights various AI models, including artificial neural networks, support vector machines, decision trees, and ensemble methods, in predicting water quality …
Published in Journal of Water Resource Engineering and Management · Vol. 11, Issue 2, 2024 · pp. 21–28 Read article
-
Integrating Deep Learning and Computer Vision for Recognizing American Sign Language
Abstract: The only way the hearing-impaired community can exchange ideas is by utilizing non-verbal communication. The main challenge, however, is that the non-impaired community, which may not comprehend non-verbal communication, would struggle to communicate effectively with this group, and vice versa. The project is purposely devised to admit unwilling and dumb societies to transport ideas and connect with the organization. It aims to bridge the gap between the hearing- and speech-impaired …
Published in Current Trends in Information Technology · Vol. 14, Issue 3, 2024 · pp. 10–17 Read article
-
Laboratory Diagnosis of COVID-19—Lessons Learnt So Far: A Review of Literature
Abstract: The world has been experiencing a viral pandemic called as Coronavirus Disease-2019 (COVID-19) from beginning of 2020. The cases have been initially recorded in Wuhan, China but over a 4-month period (till the time this review is written) spread throughout the world causing severe morbidity and mortality. As it is a new viral infection, newer diagnostic techniques are in the pipeline. As of now, the recommended tests are the molecular …
Published in Research and Reviews: A Journal of Microbiology and Virology · Vol. 10, Issue 2, 2020 · pp. 14–21 Read article
-
Text-to-SQL Systems: A Comprehensive Study of Evolution, Architectural Advancements, Challenges, and the Role of Large Language Models in Intelligent Query Generation
Abstract: Interacting with relational databases traditionally requires knowledge of Structured Query Language (SQL), which creates a significant barrier for users who do not have technical expertise. To address this challenge, Text-to-SQL systems have emerged as an important area of research, enabling users to express their information needs in natural language while automatically generating executable SQL queries. These systems aim to make database access more intuitive, efficient, and accessible across a wide …
Published in Journal of Advanced Database Management & Systems · Vol. 13, Issue 2, 2026 · pp. 10–19 Read article
-
NLP Revolution in Education Feedback Analysis: Trends and Challenges
Abstract: Artificial Intelligence (AI) is a rapidly growing area of study in many domains like research and business. Various subsets of AI, such as Machine Learning, Deep Learning, and Natural Language Processing (NLP), are employed to address diverse aspects of data processing and modeling. This review is about the impact of AI on the education system and students feedback for the analysis is required for the enhancement of the technology used …
Published in International Journal of Wireless Security and Networks · Vol. 1, Issue 1, 2023 · pp. 21–25 Read article
-
Deep Guard: A Comprehensive Deep Learning System for Unmasking Suspicious Activities in Surveillance Footage
Abstract: These days, video surveillance is quite vital. Technology has evolved considerably as machine learning, artificial intelligence, and deep learning become increasingly widespread. There are several algorithms that assist in identifying distinct kinds of suspicious behaviour from live footage by combining the techniques. A person's behaviour is the most unpredictable thing, and it can be quite challenging to determine whether it is normal or suspicious. Video surveillance is automated to address …
Published in International Journal of Satellite Remote Sensing · Vol. 1, Issue 1, 2023 · pp. 23–28 Read article
-
Enhancing Business Expansion through the Integration of Artificial Intelligence and Business Intelligence
Abstract: Business intelligence (BI) and artificially intelligent technology (AI) give businesses a competitive edge and significantly boost growth. AI emulates human cognitive processes, learns from data, and makes intelligent decisions, while BI analyzes data for strategic insights. This study explores the synergies of integrating AI and BI, revealing opportunities for business expansion. AI algorithms analyze extensive datasets, enhancing predictions for customer behavior. The reciprocal relationship automates processes, elevates decision-making, and enables …
Published in International Journal of Electrical and Communication Engineering Technology · Vol. 1, Issue 2, 2023 · pp. 27–33 Read article
-
Transformative Digital Learning Through AI Technologies
Abstract: The progress of artificial intelligence (AI) has brought about a remarkable change in the educational system. It has paved the way for the development of new educational paradigms like adaptive, personalized, and data-driven digital learning environments, replacing the old ones which were more or less teacher-cantered. In the new digital world, AI technologies have become the main drivers for educational systems to go digital and for human teachers to shift …
Published in Journal of Artificial Intelligence Research & Advances · Vol. 13, Issue 1, 2025 Read article
-
Understanding Sentiment Trends Through Zero-Shot and Few-Shot Learning Models
Abstract: The requirement for large, manually labeled datasets is one of the main barriers to applying sentiment analysis algorithms in specialized or rapidly evolving disciplines in the present natural language processing (NLP) landscape. This work investigates a paradigm shift from traditional fully supervised learning to data-efficient methods, specifically zero-shot learning (ZSL) and few-shot learning (FSL). This study uses the advanced capabilities of instruction-tuned large language models (LLMs), like GPT-4, to assess …
Published in International Journal of Computer Science Languages · Vol. 4, Issue 1, 2026 · pp. 01–08 Read article