Computers, Volume 14, Issue 3

Hellenic Open University has developed Onlabs, a virtual biology laboratory designed to safely and effectively prepare its students for hands-on work in the university’s on-site labs. This platform simulates key experimental processes, such as...

The smart-pixel-based optical convolutional neural network was proposed to improve kernel refresh rates in scalable optical convolutional neural networks (CNNs) by replacing the spatial light modulator with a smart pixel light modulator while preserv...

Verifying sequential consistency (SC) in concurrent programs is computationally challenging due to the exponential growth of possible interleavings among read and write operations. Many of these interleavings produce identical outcomes, rendering exh...

Improving the recognition of online learning engagement is a critical issue in educational information technology, due to the complexities of student behavior and varying assessment standards. Additionally, the scarcity of publicly available datasets...

Deep Neural Networks (DNNs) have been widely used to solve complex problems in natural language processing, image classification, and autonomous systems. The strength of DNNs is derived from their ability to model complex functions and to improve det...

The present study discusses the design and development of a digital repository for the preservation and dissemination of the cultural and natural heritage of Zakynthos Island (Greece). Following a crowdsourcing approach, the platform allows users to...

Coordination among multiple interdependent processes and stakeholders and the allocation of optimal resources make enterprise systems management a challenging process. Even for experienced professionals, it is not uncommon to cause inefficiencies and...

Automating fish freshness assessment is crucial for ensuring quality control and operational efficiency in large-scale fish processing. This study evaluates deep learning models for classifying the freshness of Barbonymus gonionotus (Silver Barb) and...

Recent advancements in planning prompting techniques for Large Language Models have improved their reasoning, planning, and action abilities. This paper develops a planning framework for Large Language Models using model predictive control that enabl...

Nowadays, quantum computing is developing at an unprecedented speed. This will pose a serious threat to the security of widely used public-key cryptosystems in the near future. Scientists are actively looking for ways to protect against quantum attac...

In recent years, the advances in deep neural networks (DNNs) and large language models (LLMs) have led to major breakthroughs and new levels of performance in Natural Language Processing (NLP), including tasks related to speech processing. Based on t...

This research explores opportunities for generative artificial intelligence (GenAI) in higher education constituent (customer) relationship management (CRM) to address the industry’s need for digital transformation driven by demographic shifts,...

Large language models (LLMs) are increasingly being utilized to develop tools and services in various domains, including education. However, due to the nature of the training data, these models are susceptible to inherent social or cognitive biases,...

The rapid development of Internet of Things (IoT) devices in various smart city-based applications such as healthcare, traffic management systems, environment sensing systems, and public safety systems produce large volumes of data. To process these...

This paper presents MultiGLICE (Multi class Graph Neural Network with Program Slice), a model for static code analysis to detect security vulnerabilities. MultiGLICE extends our previous GLICE model with multiclass detection for a large number of vul...

Optimization algorithms for solving technological and scientific problems often face long convergence times and high computational costs due to numerous input/output parameters and complex calculations. This study focuses on proposing a method for mi...

The disruptive innovation of artificial intelligence (AI) chatbots is affecting educational dominance, which must be considered by higher educational institutions. Open and Distance Learning (ODL) becomes imperative for the effective and interactive...

Sarcasm detection is a crucial task in natural language processing (NLP), particularly in sentiment analysis and opinion mining, where sarcasm can distort sentiment interpretation. Accurately identifying sarcasm remains challenging due to its context...

Recent AI-assisted coding tools, such as GitHub Copilot and Cursor, have enhanced developer productivity through real-time snippet suggestions. However, these tools primarily assist with isolated coding tasks and lack a structured approach to automat...

Machine learning (ML) and deep learning (DL), subsets of artificial intelligence (AI), are the core technologies that lead significant transformation and innovation in various industries by integrating AI-driven solutions. Understanding ML and DL is...

The rapid development of technology sets its own rules for adults and children. For younger schoolchildren, acquiring digital skills from primary school will give them the confidence to apply them correctly in school, at university, and in their live...

Public transportation plays a crucial role in our lives, and the road network is a vital component in the implementation of smart cities. Recent advancements in AI have enabled the development of advanced monitoring systems capable of detecting anoma...

There is an ongoing need to evaluate whether commonly used educational software effectively supports inquiry-based learning and computational thinking skills development, which are key objectives in secondary STEM curricula. This research establishes...

Educational AI systems often do not employ proper sophistication techniques to enhance learner interactions, organize their contextual knowledge or even deliver personalized feedback. To address this gap, this paper seeks to reform the way ChatGPT su...

This paper presents a traffic sign recognition (TSR) system based on the deep convolutional neural network (CNN) architecture, which proves to be extremely accurate in recognizing traffic signs under challenging conditions such as bad weather, low-re...

The rapid growth of digital communications and extensive data exchange have made computer networks integral to organizational operations. However, this increased connectivity has also expanded the attack surface, introducing significant security risk...

The accurate segmentation of 3D spheroids is crucial in advancing biomedical research, particularly in understanding tumor development and testing therapeutic responses. As 3D spheroids emulate in vivo conditions more closely than traditional 2D cult...

With the explosive growth of sequencing data, rapidly and accurately classifying and identifying species has become a critical challenge in amplicon analysis research. The internal transcribed spacer (ITS) region is widely used for fungal species cla...

The combination of connectivity and automation allows connected and autonomous vehicles (CAVs) to operate autonomously using advanced on-board sensors while communicating with each other via vehicle-to-vehicle (V2V) technology to enhance safety, effi...

This study investigates the use of educational data mining (EDM) techniques to predict student performance and enhance learning outcomes in higher education. Leveraging data from Moodle, a widely used learning management system (LMS), we analyzed 450...

Recent advancements across various sectors have resulted in a significant increase in the utilization of smart gadgets. This augmentation has resulted in an expansion of the network and the devices linked to it. Nevertheless, the development of the n...

Priority in task scheduling and resource allocation for cloud computing has attracted significant attention from the research community. However, traditional scheduling algorithms often lack the ability to differentiate between tasks with varying lev...

Shadows in remote sensing images often introduce challenges in accurate segmentation due to their variability in shape, size, and texture. To address these issues, this study proposes the Supervised Dynamic Kernel U-Net (SDKU-Net), a novel architectu...

We propose a novel approach to real-time anomaly detection at the Large Hadron Collider, aimed at enhancing the discovery potential for new fundamental phenomena in particle physics. Our method leverages the Latent Outlier Exposure technique and is e...

Patent keyword analysis involves extracting and examining keywords from patent documents. Since patents contain detailed information about technologies, analyzing them can provide valuable insights for efficient technology management. This paper prop...

The COVID-19 pandemic accelerated the shift to digital education as universities across the world rapidly adopted virtual classrooms for remote learning. Ensuring continuous student engagement in virtual environments remains one of the key challenges...