Savvas A. Chatzichristofis

Neapolis University Pafos · Department of Computer Science

I am extremely excited to announce that we are organizing for the third time a minisymposium at the COMPDYN 2025, titled “Artificial Intelligence & Machine Learning in Design and Assessment of Structures”. The minisymposium’s organizers are me, Prof Chatzichristofis Savvas (Neapolis University Pafos, Cyprus), and Senior Data Analyst Nikolaos Bakas...

This paper focuses on Coverage Path Planning (CPP) methodologies, particularly in the context of multi-robot missions, to efficiently cover user-defined Regions of Interest (ROIs) using groups of UAVs, while emphasizing on the reduction of energy consumption and mission duration. Optimizing the efficiency of multi-robot CPP missions involves addres...

Despite the concerns that recent developments in Large Language Models (LLMs) have raised, they undoubtedly revealed a novel potential of Artificial Intelligence (AI) algorithms in educational environments. Whether they are used for tutoring, in a manner similar to that of Intelligent Tutoring Systems (ITS), or to support assessment design and deli...

Data-driven models utilizing powerful artificial intelligence (AI) algorithms have been implemented over the past two decades in different fields of simulation-based engineering science. Most numerical procedures involve processing data sets developed from physical or numerical experiments to create closed-form formulae to predict the corresponding...

In this study, we introduce a versatile and scalable optimization tool designed to address several critical project management needs. Our aim is to provide project managers with a robust decision support system that enhances and streamlines decision-making processes. Building upon our previously proposed global scheme—which optimizes project schedu...

Extensive research has been conducted on educational robotics (ER) platforms to explore their usage across different educational levels and assess their effectiveness in achieving desired learning outcomes. However, the existing literature has a limitation in regard to addressing learners’ specific preferences and characteristics regarding these pl...

Data-driven models utilizing powerful artificial intelligence (AI) algorithms have been implemented over the past two decades in different fields of simulation-based engineering science. Most numerical procedures involve processing data sets developed from physical or numerical experiments to create closed-form formulae to predict the corresponding...

This work focuses on the efficiency improvement of grid-based Coverage Path Planning (CPP) methodologies in real-world applications with UAVs. While several sophisticated approaches are met in literature, grid-based methods are not commonly used in real-life operations. This happens mostly due to the error that is introduced during the region's rep...

This paper describes the design and implementation procedure of a Robot Operating System (ROS) testbed for research on the concept of Internet of Vehicles and the integration of Digital Twins in autonomous vehicles. The proposed testbed integrates communication devices, sensors, and micro-controllers to collect real-time data from the physical envi...

We present a numerical scheme for computation of Artificial Neural Networks (ANN) weights, which stems from the Universal Approximation Theorem, avoiding costly iterations. The proposed algorithm adheres to the underlying theory, is highly fast, and results in remarkably low errors when applied to regression and classification problems of complex d...

The widespread use of artificial intelligence and robotics contributes, among other things, to create a new scientific field that aims to modernize and disrupt education. The term ’educational robotics’ is being introduced as a learning tool and definitively transforming young people’s education. At the same time, however, it is helping to create a...

The overall purpose of this study is to propose a novel fine-tuning method for the CLIP architecture that enables the retention of pre-existing knowledge from large datasets and the creation of a domain-agnostic image encoder for universal image embedding, addressing the challenge of transferring knowledge from source to target tasks using deep lea...

This paper presents the 6th place solution to the Google Universal Image Embedding competition on Kaggle. Our approach is based on the CLIP architecture, a powerful pre-trained model used to learn visual representation from natural language supervision. We also utilized the SubCenter ArcFace loss with dynamic margins to improve the distinctive powe...

In this review paper, we computationally analyze a vast volume of published articles in the field of Adaptive Learning, as obtained by the Scopus Database. Particularly, we use a query with search terms targeting the area of Adaptive Learning Systems by utilizing a combination of specific keywords. Accordingly, we apply a multidimensional scaling a...

Scientific literature is prosperously evolving, exhibiting exponential growth in the last decades. For a wide range of scientific thematic areas, it is hard or even impossible for individual researchers to analyze in detail the available published works. For this purpose, we utilize a robust multidimensional scaling procedure, to construct the bibl...

Optimization algorithms appear in the core calculations of numerous Artificial Intelligence (AI) and Machine Learning methods and Engineering and Business applications. Following recent works on AI’s theoretical deficiencies, a rigour context for the optimization problem of a black-box objective function is developed. The algorithm stems directly f...

Recent advances in technology lead to the use of robotic systems as part of the modern working environment. Single and multiple robotic systems work closely with humans to accomplish desired tasks, and the recent advancements have made the usage of multi-robot teams more appealing. One critical problem in utilizing the robot’s full potential is the...

Image transmission over Low-Power Wide Area Networks (LP-WAN) protocols has always been a difficult task since it necessitates high data rates and high energy consumption. Long Range (LoRa) is one such protocol, which is excellent for transferring data over long distances but has generated severe doubts regarding the viability of image transmission...

STEM education is of paramount importance, especially in the lower levels of education, and it has been proven beneficial for students in many ways. Although there are various tools available, there are significant drawbacks mainly related to the cost and the ease of use. In this study, we introduce a new low-cost educational framework oriented tow...

This paper presents a distributed algorithm applicable to a wide range of practical multi-robot applications. In such multi-robot applications, the user-defined objectives of the mission can be cast as a general optimization problem, without explicit guidelines of the subtasks per different robot. Owing to the unknown environment, unknown robot dyn...

Educational robotics has gained a lot of attention in the past few years in K-12 education. Prior studies have shown enough shreds of evidence and highlight the benefits of educational robotics as being effective in providing impactful learning experiences. At the same time, today, the scientific subject of computer vision seems to dominate the fie...

Nowadays, the use of Convolutional Neural Networks (CNNs) has led to tremendous achievements in several computer vision challenges. CNN-based image retrieval methods vary in complexity, growing capacity, and execution time. This work presents a state-of-the-art review in Deep Convolutional Features for image retrieval, pointing out their scope, adv...

Technology is composed of the words “Techne” and “Logos” that refer to the artistic/creative and the logical/scientific aspects of its dualism. And so inherent this Promethean concept lie the concepts of the Schumpeterian creative destruction and also the promise and potential for humanity’s better tomorrows. We live in an era of artificial intelli...

Today, in the era of robotics, different types of educational robots have been used extensively in school classrooms to facilitate teaching activities that relate to a variety of computer science concepts. Numerous studies have been performed that attempt to examine the effects of using tangible interfaces to enhance collaborative learning experien...

This paper introduces a plug-and-play descriptor that can be effectively adopted for image retrieval tasks without prior initialization or preparation. The description method utilizes the recently proposed Vision Transformer network while it does not require any training data to adjust parameters. In image retrieval tasks, the use of Handcrafted gl...

Recent research has proved the positive therapeutic impacts of robot interaction with children diagnosed with the autism spectrum condition. Until now, most of the evaluated treatment methods apply one-to-one sessions between a single robot and a child. This article explores the potential therapeutic effects of multirobot-assisted therapies, along...

The purpose of this letter is to investigate the time complexity consequences of the truncated Taylor series, known as Taylor Polynomials \cite{bakas2019taylor,Katsoprinakis2011,Nestoridis2011}. In particular, it is demonstrated that the examination of the $\mathbf{P=NP}$ equality, is associated with the determination of whether the $n^{th}$ deriva...

Motivated by the recent explosion of interest around Educational Robotics (ER), this paper attempts to re-approach this area by suggesting new ways of thinking and exploring the related concepts. The contribution of the paper is fourfold. First, future readers can use this paper as a reference point for exploring the expected learning outcomes of e...

Optimization algorithms appear in the core calculations of numerous Artificial Intelligence and Machine Learning methods, as well as Engineering and Business applications. Following recent works on the theoretical deficiencies of AI, a rigor context for the optimization problem of an unknown objective function is developed. The algorithm stems dire...

Students face difficulties in learning mathematical processes. As a result, they have negative emotions toward mathematics. The use of technology is employed to change the student’s attitude toward mathematics. Some methods utilize intelligent tutoring systems to recognize student’s emotional state and adapt the learning process accordingly. These...

This paper presents a distributed algorithm applicable to a wide range of practical multi-robot applications. In such multi-robot applications, the user-defined objectives of the mission can be cast as a general optimization problem, without explicit guidelines of the subtasks per different robot. Owing to the unknown environment, unknown robot dyn...

Low level features play a significant role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper presents CoMo: a moment based composite and compact low-level descriptor that can be used effectively for image retrieval and robot visi...

Fractions are considered to be a difficult cognitive area for students. Fractions are represented in different ways and various software systems are used to support, as pedagogical agents, the teaching process with the aim to achieve a desired teaching result for students. This article attempts to present the basic features of three e-learning, web...

This research develops a new on-line trajectory planning algorithm for a team of Autonomous Underwater Vehicles (AUVs). The goal of the AUVs is to cooperatively explore and map the ocean seafloor. As the morphology of the seabed is unknown and complex, standard non-convex algorithms perform insufficiently. To tackle this, a new simulation-based app...

The Bag-of-Visual-Words (BoVW) model is widely used for image classification, object recognition and image retrieval problems. In BoVW model, the local features are quantized and 2-D image space is represented in the form of order-less histogram of visual words. The image classification performance suffers due to the order-less representation of im...

Low level features play a vital role in image retrieval. Image moments can effectively represent global information of image content while being invariant under translation, rotation, and scaling. This paper briefly presents a moment based composite and compact low-level descriptor for image retrieval. In order to test the proposed feature, the aut...

The field of similarity based image retrieval has experienced a game changer lately. Hand crafted image features have been vastly outperformed by machine learning based approaches. Deep learning methods are very good at finding optimal features for a domain, given enough data is available to learn from. However, hand crafted features are still mean...

This paper deals with the path planning problem of a team of mobile robots, in order to cover an area of interest, with prior-defined obstacles. For the single robot case, also known as single robot coverage path planning (CPP), an 𝓞(n) optimal methodology has already been proposed and evaluated in the literature, where n is the grid size. The majo...

Remote pest population monitoring is of major importance within the context of precision agriculture. Information acquired from the field has been proved essential for proper decision making and pest management against various cultivation threats. Bactrocera oleae (Gmelin) consists the major pest for olive orchards. The key factor for a successful...

In this paper, a novel visual Place Recognition approach is evaluated based on a visual vocabulary of the Color and Edge Directivity Descriptor (CEDD) to address the loop closure detection task. Even though CEDD was initially designed so as to globally describe the color and texture information of an input image addressing Image Indexing and Retrie...

During the last decades much attention was given to bio-inspired techniques able to successfully handle really complex algorithmic problems. As such Ant Colony Optimization (ACO) algorithms have been introduced as a metaheuristic optimization technique arriving from the swarm intelligence methods family and applied to several computational and comb...

SIMPLE (Searching Images with MPEG-7 (& MPEG-7-like) Powered Localized dEscriptors) is a model that proposes the reuse of well-established global descriptors by localizing their description mechanism on image patches located by local features' detectors. Having displayed impressive retrieval results on two different databases, in this paper we exte...

This paper deals with the problem of autonomous exploration of unknown areas using teams of Autonomous X Vehicles (AXVs)—with X standing for Aerial, Underwater or Sea-surface—where the AXVs have to autonomously navigate themselves so as to construct an accurate map of the unknown area. Such a problem can be transformed into a dynamic optimization p...

With the recent evolution of technology, the number of image archives has increased exponentially. In Content-Based Image Retrieval (CBIR), high-level visual information is represented in the form of low-level features. The semantic gap between the low-level features and the high-level image concepts is an open research problem. In this paper, we p...

Current multi-AUV systems are far from being capable of fully autonomously taking over real-life complex situation-awareness operations. As such operations require advanced reasoning and decision-making abilities, current designs have to heavily rely on human operators. The involvement of humans, however, is by no means a guarantee of performance;...

Accurate maps are essential in the case of robot teams, so that they can operate autonomously and accomplish their tasks efficiently. In this work we present an approach which allows the generation of detailed maps, suitable for robot navigation, from a mesh of sparse points using Cellular Automata and simple evolutions rules. The entire map area c...

In this paper, we explore, extend and simplify the localization of the description ability of the well-established MPEG-7 (Scalable Colour Descriptor (SCD), Colour Layout Descriptor (CLD) and Edge Histogram Descriptor (EHD)) and MPEG-7-like (Color and Edge Directivity Descriptor (CEDD)) global descriptors, which we call the SIMPLE family of descrip...

Within the project NOPTILUS, a fully functional system/methodology had been developed that allows the cooperative, fully-autonomous navigation of teams of AUVs when deployed in Static or Dynamic Underwater Map Construction (SDUMC) or Dynamic Underwater Phenomena Tracking (DUPT) missions. The key ingredient of this fully functional system/methodolog...

In this paper, we focus on implementing the extraction of a well-known low-level image descriptor using the multicore power provided by general-purpose graphic processing units (GPGPUs). The color and edge directivity descriptor, which incorporates both color and texture information achieving a successful trade-off between effectiveness and efficie...

This paper presents an image retrieval framework that uses affine image moment invariants as descriptors of local image areas. Detailed feature vectors are generated by feeding the produced moments into a Bag-of-Visual-Words representation. Image moment invariants have been selected for their compact representation of image areas as well as due to...

In the last decade the amount of the stored data related to almost all areas of life has rapidly increased. However, the overall process of discovering knowledge from data demands more powerful clustering techniques to ensure that this knowledge is useful. In this paper, two nature inspired computation techniques, Cellular Automata (CA) and Ant Col...