Entropy is a basic and important concept in information theory. It is also often used as a measure of the unpredictability of a cryptographic key in cryptography research areas. Ubiquitous computing (Ubi-comp) has emerged rapidly as an exciting new p...
Doctoral training in applied computing and information systems is the structured development of a researcher’s capacity to produce original, rigorous, and scholarship that is relevant to practice, supported through doctoral supervision, which p...
Applied computing and artificial intelligence methods have been attracting growing interest in recent years due to their effectiveness in solving technical problems [...]
The problem of data exchange between multiple nodes with storage and communication capabilities models several current multi-user communication problems like Coded Caching, Data Shuffling, Coded Computing, etc. The goal in such problems is to design...
Diverse problems of radiative transfer remain as yet unsolved due to the difficulties of the calculations involved, especially if the intervening shapes are geometrically complex. The main goal of our investigation in this domain is to convert the eq...
Currently, in many data landscapes, the information is distributed across various sources and presented in diverse formats. This fragmentation can pose a significant challenge to the efficient application of analytical methods. In this sense, distrib...
This paper introduces an enhanced algorithm for computing generalized Nash equilibria for multiple player nonlinear games, which degenerates in a gradient algorithm for single player games (i.e., optimization problems) or potential games (i.e., equiv...
With the increase in life expectancy and consequent aging of the world’s population, the prevalence of many neurodegenerative diseases is increasing, without concomitant improvement in diagnostics and therapeutics. These diseases share neuropat...
The spread of panic can swiftly trigger group behaviors, leading to public security incidents and significant social hazards. Increasing attention is being paid to the impact of human psychology and behavior on the evolution and management of emergen...
In recent years, many important yet complex problems, either continuous or combinatorial, suffer the intractability of the problem of nature [...]
With the rapid advancement of artificial intelligence and machine learning technologies, the demand for enhanced device computing capabilities has significantly increased. Neuromorphic computing, an emerging computational paradigm inspired by the hum...
Against the background of the unprecedented advancements related to Industry 4.0 and beyond, transitioning from classical mathematical models to fully embodied digital twins represents a critical change in the planning, monitoring, and optimization o...
Differential models, numerical methods and computer simulations play a fundamental role in applied sciences. Since most of the differential models inspired by real world applications have no analytical solutions, the development of numerical methods...
A smart grid is a promising use-case of AIoT (AI (artificial intelligence) across IoT (internet of things)) that enables bidirectional communication among utilities that arises with demand response (DR) schemes for demand-side management (DSM) and co...
Behavioral observation is central to animal welfare assessment in zoological institutions, but manual observation is time-consuming and difficult to apply continuously. We developed and applied a LabGym-based workflow for automated behavioral monitor...
The objective of this research was to propose a conceptual cybersecurity framework aimed at guiding developers in generating and implementing technological solutions for Edge Computing and Internet of Things (IoT) environments. The framework integrat...
The management and proper use of the Urban Public Transport Systems (UPTS) constitutes a critical field that has not been investigated in accordance to its relevance and urgent idiosyncrasy within the Smart Cities realm. Swarm Intelligence is a very...
This research addresses the problem of multi-objective resource allocation or resource deficits, offering robust answers to planning decisions that involve the elementary question: “How is it done?”. The solution to the problem is realize...
This exploratory study examines the implementation of a GenAI-supported curriculum redesign in a project-based multimedia computing course by comparing students’ experiences in Python-based and GenAI-supported production pathways in relation to...
Non-intrusive load monitoring (NILM) is a cost-effective approach that electrical appliances are identified from aggregated whole-field electrical signals, according to their extracted electrical characteristics, with no need to intrusively deploy sm...
The integration of machine learning (ML) with edge computing and wearable devices is rapidly advancing healthcare applications. This study systematically maps the literature in this emerging field, analyzing 171 studies and focusing on 28 key article...
Social robots keep proliferating. A critical challenge remains their sensible interaction with humans, especially in real world applications. Hence, computing with real world semantics is instrumental. Recently, the Lattice Computing (LC) paradigm ha...
Recently, chaotic dynamics-based data encryption techniques for wired and wireless networks have become a topic of active research in computer science and network security such as robotic systems, encryption, and communication. The main aim of deploy...
Artificial intelligence applied to the educational field has a vast potential, especially after the effects worldwide of the COVID-19 pandemic. Online or blended educational modes are needed to respond to the health situation we are living in. The tu...
Recent developments have reported on the feasibility of interconnecting small quantum registers in a quantum information network of a few meter-scale for distributed quantum computing purposes. Small quantum processors in a network represent a promis...
Unmanned aerial vehicles (UAVs) are now considered one of the best remote sensing techniques for gathering data over large areas. They are now being used in the industry sector as sensing tools for proactively solving or preventing many issues, besid...
Conventional sense amplifiers limit the performance of current RRAM computing-in-memory (CIM) macro circuits, resulting in high latency and energy consumption. This paper introduces a multi-bit quantization technology low-latency voltage sense amplif...
Amid the escalating complexity of networks, wireless intelligent devices, constrained by energy and resources, bear the increasing burden of managing various tasks. The decision of whether to allocate tasks to edge servers or handle them locally on d...
The Special Issue “Artificial Intelligence Applied to Medical Imaging and Computational Biology” of the Applied Sciences Journal has been curated from February 2021 to May 2022, which covered the state-of-the-art and novel algorithms and...
To accurately estimate the dynamic properties of the asphalt mixtures to be used in the Mechanistic-Empirical Pavement Design Guide (MEPDG), a novel neural computing model using the improved beetle antennae search was developed. Asphalt mixtures were...
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Epidemiological inquiries study and evaluate the health status of the population. For dental caries, the World Health Organization (WHO) recommends the DMFT and DMFS indexes, which represent the sum of the decayed, missing and filled teeth, divided b...
The digital humanities and social sciences are critical for addressing societal challenges such as climate change and disaster risk reduction. One way in which the digital humanities and social sciences add value, particularly in an increasingly digi...
Background—In the field of aviation, maintenance and inspections of engines are vitally important in ensuring the safe functionality of fault-free aircrafts. There is value in exploring automated defect detection systems that can assist in this...
ICSAM’23 is an ideal forum for different researchers to present excellent results and new challenges facing the field of computer science and applied mathematics [...]
Recently, symbolic computations and soft computing have played an increasingly important role in various domains of applied sciences [...]
New Testament studies has over the past years seen an increase in the use of digital methods, but some of the more advanced methods still lack proper integration. This article explores some of the advantages and disadvantages in employing computation...
We are pleased to present the third edition of the Special Issue “Applied and Innovative Computational Intelligence Systems” in Applied Sciences, a journal with an Impact Factor of 2 [...]
Food waste is a global problem, which becomes apparent at various stages of the food supply chain. The present research study focuses on the optimization of food consumption in schools and effective food management through data-driven decision making...
Several phenomena in nature are subjected to the interaction of various physical parameters, which, if these latter are well known, allow us to predict the behavior of such phenomena. In most cases, these physical parameters are not exactly known, or...
Distance learning has been adopted as a very extended model during COVID-19-related confinement. It is also a methodology that can be applied in environments where people do not have easy access to schools. In this study, we automatically classify st...
Cell counting in immunocytochemistry is vital for biomedical research, supporting the diagnosis and treatment of diseases such as neurological disorders, autoimmune conditions, and cancer. However, traditional counting methods are manual, time-consum...
In the evolving landscape of computer vision, the integration of machine learning algorithms with cutting-edge hardware platforms is increasingly pivotal, especially in the context of disruptive healthcare systems. This study introduces an optimized...
Clustered regularly interspaced short palindromic repeats (CRISPR)-driven traits are commonly introduced into tomato (Solanum lycopersicum) in less than a year. Although CRISPR technology is highly suitable for rapid incorporation of new traits into...
The 1st International Electronic Conference on Games (IECGA 2025) was hosted online from 15 to 16 October 2025 [...]
Biased estimates and fluctuating measures of central tendency are significant impediments to statistical inference and computational data analysis and are often caused by partial and distorted observations. The imputed least-squares-based estimators...
The real-time deployment of cascaded generative AI pipelines for applications like video translation is constrained by significant system-level challenges. These include the cumulative latency of sequential model inference and the quadratic (
Nowadays, the treatment costs associated with lameness rank second among common diseases of cattle. The standard method for detecting lameness is visual observation of the herd by the farmer. However, these methods are time-consuming and labor-intens...
Extrusion-based three-dimensional (3D) bioprinting has enabled the fabrication of complex, cell-laden constructs; however, process parameter selection remains largely empirical and system-specific. As biofabrication workflows scale in complexity and...
A technique for optimizing large-scale differential-algebraic process models under uncertainty using a parallel embedded model approach is developed in this article. A combined multi-period multiple-shooting discretization scheme is proposed, which c...
This article provides an empirical statistical analysis and discussion of the predictive abilities of selected customer lifetime value (CLV) models that could be used in online shopping within e-commerce business settings. The comparison of CLV predi...
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