Academic Articles & Research Papers

A Survey of the Application of Neural Networks to Event Extraction

Event extraction is an important part of natural language information extraction, and it’s widely employed in other natural language processing tasks including question answering and machine reading comprehension. However, there is a lack o...

The Problem of Choosing the Language of Communication: Ukrainian Realities

The article analyses the situational change in the language behaviour (code switching) of representatives from different regions of Ukraine based on the data of a statistically significant mass survey of the adult population of different re...

Several Sociolinguistic Particularities of French-English Bi-Lingualism in Canada

Introduction. The relevance of the study is explained by the necessity to preserve Frenchspeaking culture and language on the territory of Canada in the conditions of globalization, the spread of American mass culture and the significant im...

Machine Vision and Canny Edge Detector–Based Printing Image Detection and Recognition Model

Traditional image detection and recognition models face issues such as high miss detection rates, low classification accuracy, and poor real-time performance when dealing with complex printing images, including defects and flaws. To address...

Gestalt Theory and Computer Vision

In the Wertheimer programme there are two kinds of organizing laws. The rst kind are grouping laws which, starting from atomic and local data, recursively construct larger groups in the perceived image. Each grouping law focuses on a single...

Integrating Computer Vision: Advancements in Fire and Smoke Detection Using CNNs

Conventional fire detection systems, which depend on smoke and fire sensors, frequently have problems with calibration, susceptibility to environmental changes, and the requirement for ongoing maintenance. These flaws can result in unfavora...

Deep Learning in Image Cytometry: A Review

Artificial intelligence, deep convolutional neural networks, and deep learning are all niche terms that are increasingly appearing in scientific presentations as well as in the general media. In this review, we focus on deep learning and ho...

Compilation of training datasets for use of convolutional neural networks supporting automatic inspection processes in industry 4.0 based electronic manufacturing

Ensuring the highest quality standards at competitive prices is one of the greatest challenges in the manufacture of electronic products. The identification of flaws has the uppermost priority in the field of automotive electronics, particu...

Spatiotemporal prediction of sneeze pollutants in enclosed spaces: a CNN-LSTM approach validated by field measurements and CFD-Robotics arm twin system

Densely populated enclosed environments, characterized by complex thermal stratification and overlapping breathing zones, represent high-risk clusters for the airborne transmission of respiratory pathogens. To address the dual challenges of...

Downscaling atmospheric chemistry simulations with physically consistent deep learning

Recent advances in deep convolutional neural network (CNN)-based super resolution can be used to downscale atmospheric chemistry simulations with substantially higher accuracy than conventional downscaling methods. This work both demonstrat...

Machine learning for metabolic engineering: A review

Machine learning provides researchers a unique opportunity to make metabolic engineering more predictable. In this review, we offer an introduction to this discipline in terms that are relatable to metabolic engineers, as well as providing ...

Machine Learning in Medicine

Spurred by advances in processing power, memory, storage, and an unprecedented wealth of data, computers are being asked to tackle increasingly complex learning tasks, often with astonishing success. Computers have now mastered a popular va...

Anti-corruption laws as a pillar of national security protection: wartime peculiarities

The analysis focuses on how anti-corruption rules ensure both national security and support it during times of war when corruption endangers stability. Our study checks if existing anti-corruption rules and institution systems help protect ...

Blockchain and Artificial Intelligence

It is undeniable that artificial intelligence (AI) and blockchain concepts are spreading at a phenomenal rate. Both technologies have distinct degree of technological complexity and multi-dimensional business implications. However, a common...

A physics-informed spatiotemporal graph neural network for photovoltaic power forecasting and micro-anomaly localization

Accurate power forecasting and precise fault diagnosis are critical for the reliable operation of large-scale photovoltaic systems. However, existing data-driven models often fail to capture complex spatiotemporal dependencies and lack phys...

Discussion on Artificial Intelligence Safety and Ethical Issues

As artificial intelligence (AI) is increasingly integrated into society, people are relying on it more and more, and higher requirements are put forward for the safety and ethical standards of AI. This article explores the development of ar...

Artificial intelligence and ambient intelligence

Ambient intelligence (AmI) is intrinsically and thoroughly connected with artificial intelligence (AI).Some even say that it is, in essence, AI in the environment.AI, on the other hand, owes its success to the phenomenal development of the ...

Managing artificial intelligence

By the time you finish reading this editorial about artificial intelligence (AI), it will be outdated; the AI field is growing beyond the imagination of many. One cannot even look at the news without finding something about AI: duplication ...

Workforce Perceptions of a Conceptual Hospital-at-Home Digital Twin: Qualitative Study.