Emanuele Frontoni

University of Macerata | UNIMC

Blockchain-based sensor networks offer promising solutions for secure and transparent data management in IoT ecosystems. However, efficient set membership proofs remain a critical challenge, particularly in resource-constrained environments. This paper introduces a novel OR-aggregation approach (where “OR” refers to proving that an element equals a...

Extended Reality (XR) integrates real and virtual environments through spatial computing technologies, playing a crucial role in the development of the Metaverse. The synergy of XR with Artificial Intelligence (AI), referred to as Extended Artificial Intelligence (XRAI), enhances immersive experiences and operational efficien-cies across various do...

Blockchain-based sensor networks offer promising solutions for secure and transparent data management in IoT ecosystems. However, efficient set membership proofs remain a critical challenge, particularly in resource-constrained environments. This paper introduces a novel OR-aggregation approach for zero-knowledge set membership proofs, tailored spe...

Recent advancements in Artificial Intelligence and Computer Vision, in particular Deep Learning (DL), have transformed the analysis of human faces, enabling different tasks, ranging from classification to synthesis. Despite these advancements, color analysis in face images remains underexplored, especially concerning well-defined datasets and frame...

Recent advances in Novel-View Synthesis (NVS) and 3D Generation (3DGen) from 2D images have marked significant progress in various domains. While the Structure-from-Motion (SfM) and Multi-View Stereo (MVS) pipelines remain prevalent, their limitations have driven the exploration of Deep Learning (DL)-based methods. Among these, Neural Radiance Fiel...

The joint usage of Extended Reality (XR) and Artificial Intelligence (AI) has enabled different Metaverse-related use cases. Such paradigms were recently adopted for immersive content creation, particularly considering Neural Rendering (NR) techniques to project scenes from the real world in the 3D realm. These methods are particularly beneficial i...

Semantic segmentation of point clouds plays a critical role in various applications, such as urban planning, infrastructure management, environmental analyses and autonomous navigation. Understanding the behaviour of deep neural networks (DNNs) in analysing point cloud data is essential for improving segmentation accuracy and developing effective n...

Artificial Intelligence (AI) has witnessed remarkable advancements in recent years and has significantly impacted various domains, including cultural heritage. Indeed, AI technologies offer unprecedented capacities to analyze huge amounts of historical data, enabling researchers and art historians to uncover precious patterns, connections, and insi...

In the rapidly evolving field of digital asset management, centralized and decentralized global registries have become essential tools for organizing, tracking, and distributing digital assets. However, existing systems often face challenges regarding security, censorship resistance, interoperability, customizability, and scalability. This research...

This study explores the application of genetic algorithms in generating highly nonlinear substitution boxes (S-boxes) for symmetric key cryptography. We present a novel implementation that combines a genetic algorithm with the Walsh-Hadamard Spectrum (WHS) cost function to produce 8x8 S-boxes with a nonlinearity of 104. Our approach achieves perfor...

The efficiency of heuristic search algorithms is a critical factor in the realm of cryptographic primitive construction, particularly in the generation of highly nonlinear bijective permutations, known as substitution boxes (S-boxes). The vast search space of 256! (256 factorial) permutations for 8-bit sequences poses a significant challenge in iso...

In the realm of smart communication systems, where the ubiquity of 5G/6G networks and IoT applications demands robust data confidentiality, the cryptographic integrity of block and stream cipher mechanisms plays a pivotal role. This paper focuses on the enhancement of cryptographic strength in these systems through an innovative approach to generat...

This study investigates the innovative application of Direct Sequence Spread Spectrum (DSSS) technology in the realm of image steganography, known as Spread Spectrum Image Steganography (SSIS). By interpreting the cover image as noise in the communication channel, SSIS capitalizes on the noise-resistant properties of broadband communication systems...

The integration of Clinical Decision Support Systems (CDSS) based on artificial intelligence (AI) in healthcare is groundbreaking evolution with enormous potential, but its development and ethical implementation, presents unique challenges, particularly in critical care, where physicians often deal with life-threating conditions requiring rapid act...

As school-based nutrition education interventions have become increasingly popular in recent years, they have proven effective in raising children awareness and responsibility toward good eating habits as well as improving their knowledge, skills, and attitudes. The aim of this work is to evaluate whether a gamification approach, using a digital ap...

Public space is usually conceived as where people live, perceive, and interact with other people. The environment affects people in several different ways as well. The impact of environmental problems on humans is significant, affecting all human activities, including health and socio-economic development. Thus, there is a need to rethink how space...

In fashion domain, companies increasingly navigate a complex web of data involving intricate correlations, dependencies, and the unpredictability of human behavior. Managing these diverse data flows is critical to improving decision-making in an industry that depends on both creativity and precision. In this context, artificial intelligence (AI) te...

Real-world classification problems may disclose different hierarchical levels where the categories are displayed in an ordinal structure. However, no specific deep learning (DL) models simultaneously learn hierarchical and ordinal constraints while improving generalization performance. To fill this gap, we propose the introduction of two novel ordi...

Artificial intelligence (AI) has made significant advancements in the field of geomatics, revolutionizing the way geospatial data is processed, analyzed, and interpreted. While these advancements have brought numerous benefits, they also raise ethical risks that must be carefully considered. The improvement of AI in geomatics has introduced ethical...

This study explores the use of Federated Learning (FL) for stenosis detection in coronary angiography images (CA). Two heterogeneous datasets from two institutions were considered: Dataset 1 includes 1219 images from 200 patients, which we acquired at the Ospedale Riuniti of Ancona (Italy); Dataset 2 includes 7492 sequential images from 90 patients...

In an era where biometric security serves as a keystone of modern identity verification systems, ensuring the authenticity of these biometric samples is paramount. Liveness detection, the capability to differentiate between genuine and spoofed biometric samples, stands at the forefront of this challenge. This research presents a comprehensive evalu...

In the contemporary digital era, images are omnipresent, serving as pivotal entities in conveying information, authenticating experiences, and substantiating facts. The ubiquity of image editing tools has precipitated a surge in image forgeries, notably through copy-move attacks where a portion of an image is copied and pasted within the same image...

As reliance on disruptive applications based on Artificial Intelligence (AI) and Blockchain grows, the need for secure and trustworthy solutions becomes ever more critical. Whereas much research has been conducted on AI and Blockchain, there is a shortage of comprehensive studies examining their integration from a security perspective. Hence, this...

Presents corrections to the paper, (Corrections to “On the Integration of Artificial Intelligence and Blockchain Technology: A Perspective About Security”).

In computer graphics, 3D modeling is a fundamental concept. It is the process of creating three-dimensional objects or scenes using specialized software that allows users to create, manipulate and modify geometric shapes to build complex models. This operation requires a huge amount of time to perform and specialised knowledge. Typically, it takes...

In contemporary digital security systems, the generation and management of cryptographic keys, such as passwords and pin codes, often rely on stochastic random processes and intricate mathematical transformations. While these keys ensure robust security, their storage and distribution necessitate sophisticated and costly mechanisms. This study expl...

The trajectories of shopping carts and baskets in a supermarket are an information-rich feature that can help in understanding the retail environment, gives idea about the interactions between objects and the ongoing events. This paper is interested in understanding, improving and personalising shopping experience by clustering the trajectories acq...

In the domain of digital steganography, the problem of efficient and accurate steganalysis is of utmost importance. Steganalysis seeks to detect the presence of hidden data within digital media, a task that is continually evolving due to advancements in steganographic techniques. This study undertakes a detailed exploration of the SRNet model, a pr...

S-boxes, the key nonlinear component in numerous cryptographic systems, play a crucial role in ensuring security. The quest for random highly nonlinear S-boxes, a desirable attribute for better diffusion and confusion properties, is, therefore, a critical endeavor in cryptographic research. However, generating such nonlinear S-boxes often involves...

In recent years, the need for contactless and sustainable systems has become increasingly relevant. The traditional water dispensers, which require contact with the dispenser and often involve single-use plastic cups or bottles, are not only unhygienic but also contribute to environmental pollution. This paper presents a touchless water dispenser s...

The early detection of handguns and knives from surveillance videos is crucial to enhance people’s safety. Despite the increasing development of Deep Learning (DL) methods for general object detection, weapon detection from surveillance videos still presents open challenges. Among these, the most significant are: (i) the very small size of the weap...

Heuristic algorithms are used to solve complex computational problems quickly in various computer applications. Such algorithms use heuristic functions that rank the search alternatives instead of a full enumeration of possible variants. The algorithm selects, at each iteration, an alternative with the best value for the heuristics. In this paper,...

The simulated annealing algorithm relates to heuristic techniques for approximating optimization problems. It is well suited to finding a solution in a discrete state space. This algorithm simulates the physical processes that occur during metal annealing. While the temperature of the metal is high, the atoms of the substance can pass between the c...

The pioneering use of Artificial Intelligence (AI) in various fields and sectors, and the growing ethical debate about its application have led research centers, public and private institutions to establish ethical guidelines for a trustworthy implementation of these powerful algorithms. Despite the recognized definition of ethical principles for a...

The missing data mechanism is a relevant problem in Machine Learning (ML) and biomedical informatics communities. Real-world Electronic Health Record (EHR) datasets comprise several missing values, thus revealing a high level of spatiotemporal sparsity in the predictors' matrix. Several approaches in the state-of-the-art tried to deal with this pro...

Background and objectives: Patients suffering from neurological diseases may develop dysarthria, a motor speech disorder affecting the execution of speech. Close and quantitative monitoring of dysarthria evolution is crucial for enabling clinicians to promptly implement patients' management strategies and maximizing effectiveness and efficiency of...

Nonlinear substitutions or S-boxes are important cryptographic primitives of modern symmetric ciphers. They are designed to complicate the plaintext-ciphertext dependency. According to modern ideas, the S-box should be bijective, have high nonlinearity and algebraic immunity, low delta uniformity, and linear redundancy. These criteria directly affe...

In contemporary digital security systems, the generation and management of cryptographic keys, such as passwords and pin codes, often rely on stochastic random processes and intricate mathematical transformations. While these keys ensure robust security, their storage and distribution necessitate sophisticated and costly mechanisms. This study expl...

This work proposes an ethical framework that highlights possible ethical risks in the design and use of deep-learning-based vision systems for monitoring infants’ movements in neonatal intensive care units. We discuss biases and ways to mitigate them for promoting accountable systems in clinical practice.

The problem of nonlinear substitution generation (S-boxes) is investigated in many related works in symmetric key cryptography. In particular, the strength of symmetric ciphers to linear cryptanalysis is directly related to the nonlinearity of substitution. In addition to being highly nonlinear, S-boxes must be random, i.e., must not contain hidden...

The surge of Mobile Virtual Reality (VR) applications is getting growing attention among researchers and practitioners. The recent literature demonstrates its benefits when used for education purposes, since virtual immersion yields promising results for learning. Leveraging this trend, within the so called “digital didactics”, the need to gauge VR...

In recent years, advancements in remote and proximal sensing technology have driven innovation in environmental and land surveys. The integration of various geomatics devices, such as reflex and UAVs equipped with RGB cameras and mobile laser scanners (MLS), allows detailed and precise surveys of monumental trees. With these data fusion method, we...

This paper explores the potential of using Chat Generative Pre-trained Transformer (ChatGPT), a Large Language Model (LLM) developed by OpenAI, to address the main challenges and improve the efficiency of the Gcode generation process in Additive Manufacturing (AM), also known as 3D printing. The Gcode generation process, which controls the movement...

In the last years, multiple quality control tasks consist in classifying some items based on their aesthetic characteristics (aesthetic quality control, AQC), where usually the aspect of the material is not measurable and is based on expert observation. Given the increasing amount of images in this domain, deep learning (DL) models can be used to e...

Industry 4.0 technologies are expected to enhance healthcare quality at the minimum cost feasible by using innovative solutions based on a fruitful exchange of knowledge and resources among institutions, firms and academia. These collaborative mechanisms are likely to occur in an innovation ecosystem where different stakeholders and resources inter...

Early diagnosis of neurodevelopmental impairments in preterm infants is currently based on the visual analysis of newborns’ motion patterns by trained operators. To help automatize this time-consuming and qualitative procedure, we propose a sustainable deep-learning algorithm for accurate limb-pose estimation from depth images. The algorithm consis...

One of the main relevant topics of Industry 4.0 is related to the prediction of Remaining Useful Life (RUL) of machines. In this context, the “Smart Manufacturing Machine with Predictive Lifetime Electronic maintenance” (SIMPLE) project aims to promote collaborations among different companies in the scenario of predictive maintenance. One of the to...

Deep-learning (DL) algorithms are becoming the standard for processing ultrasound (US) fetal images. A number of survey papers in the field is today available, but most of them are focusing on a broader area of medical-image analysis or not covering all fetal US DL applications. This paper surveys the most recent work in the field, with a total of...

Ultrasound (US) imaging is recognized as a useful support for Carpal Tunnel Syndrome (CTS) assessment through the evaluation of median nerve morphology. However, US is still far to be systematically adopted to evaluate this common entrapment neuropathy, due to US intrinsic challenges, such as its operator dependency and the lack of standard protoco...

In this paper we present a method of the user behavior (UB) tracking by capturing and measuring user activities through the defined procedural model of the reverse virtualization process, implementing a proof of concept on a real case scenario: the Civic Gallery of Ascoli. In order to define the universal model of such “vice versa” virtual reality...

In recent years, we have witnessed the spread of computer graphics techniques, used as a background map for movies and video games. Nevertheless, when creating 3D models with conventional computer graphics software, it is necessary for the user to manually change the placement and size. This requires expertise of computer graphics architecture and...