Sandi Baressi Šegota

• Master of Engineering
• Research Associate at University of Rijeka

Obtaining a dynamic model of the robotic manipulator is a complex task. With the growing application of machine learning (ML) approaches in modern robotics, a question arises of using ML for dynamic modeling. Still, due to the large amounts of data necessary for this approach, data collection may be time and resource-intensive. For this reason, thi...

Lowering joint torques of a robotic manipulator enables lowering the energy it uses as well as increase in the longevity of the robotic manipulator. This article proposes the use of evolutionary computation algorithms for optimizing the paths of the robotic manipulator with the goal of lowering the joint torques. The robotic manipulator used for op...

Inverse kinematic equations allow the determination of the joint angles necessary for the robotic manipulator to place a tool into a predefined position. Determining this equation is vital but a complex work. In this article, an artificial neural network, more specifically, a feed-forward type, multilayer perceptron (MLP), is trained, so that it co...

This article presented an improvement of marine steam turbine conventional exergy analysis by application of neural networks. The conventional exergy analysis requires numerous measurements in seven different turbine operating points at each load, while the intention of MLP (Multilayer Perceptron) neural network-based analysis was to investigate th...

Urinary bladder cancer is one of the most common urinary tract cancers. Standard diagnosis procedure can be invasive and time-consuming. For these reasons, procedure called optical biopsy is introduced. This procedure allows in-vivo evaluation of bladder mucosa without the need for biopsy. Although less invasive and faster, accuracy is often lower....

This paper presents an exergy analysis of six pressure reduction valves which operate in a condensate/feedwater heating system of a 660 MW coal-fired steam power plant. For all observed pressure reduction valves is additionally investigated the ambient temperature change influence of their exergy parameters. Second pressure reduction valve (PRV2) h...

Exergy analysis of three cylinder steam turbine segments is performed in this research. The highest mechanical power of 47389.66 kW is developed in the first segment (Seg. I, which actually represents the entire HPC-High Pressure Cylinder). Intermediate Pressure Cylinder (IPC) is the dominant mechanical power producer of all cylinders and it develo...

As the windage area of containerships increases, wind loads are becoming a more significant factor in navigating ships at open sea. This can lead to increased resistance and affect ship stability, maneuverability, and fuel efficiency. In this study, machine learning models based on the multilayer perceptron and gradient-boosted tree methods were em...

Android malware detection using artificial intelligence today is a mandatory tool to prevent cyber attacks. To address this problem in this paper the proposed methodology consists of the application of genetic programming symbolic classifier (GPSC) to obtain symbolic expressions (SEs) that can detect if the android is malware or not. To find the op...

Large-scale photovoltaic (solar) farms play a crucial role in harnessing solar energy for electricity generation through photovoltaic (PV) technology. However, the control and management of such systems pose significant challenges, particularly in fault detection. This paper introduces the application of a genetic programming symbolic classifier (G...

In this paper, the dataset is collected from the fluidic muscle datasheet. This dataset is then used to train models predicting the pressure, force, and contraction length of the fluidic muscle, as three separate outputs. This modeling is performed with four algorithms-extreme gradient boosted trees (XGB), ElasticNet (ENet), support vector regresso...

The detection of Android malware is of paramount importance for safeguarding users’ personal and financial data from theft and misuse. It plays a critical role in ensuring the security and privacy of sensitive information on mobile devices, thereby preventing unauthorized access and potential damage. Moreover, effective malware detection is essenti...

This paper presents an exergy analysis of a two-cylinder low power steam turbine from combined cycle power plant at three operating regimes. The highest mechanical power produced in the whole turbine is 6807.24 kW in Operating regime 1. Cylinders of the observed turbine did not have the same operation dynamics in relation to produced mechanical pow...

Detecting the crystal system of lithium-ion batteries is crucial for optimizing their performance and safety. Understanding the arrangement of atoms or ions within the battery’s electrodes and electrolyte allows for improvements in energy density, cycling stability, and safety features. This knowledge also guides material design and fabrication tec...

Frequency-modulated (FM) signals, prevalent across various applied disciplines, exhibit time-dependent frequencies and a multicomponent nature necessitating the utilization of time-frequency methods. Accurately determining the number of components in such signals is crucial for various applications reliant on this metric. However, this poses a chal...

In the preliminary ship design, the accurate determination of a vessel’s main engine power is one of the most critical aspects next to service speed, main particulars, and cargo capacity. However, this task can be quite intricate due to its reliance on an extremely great number of influencing factors. In the research that is presented in this paper...

Motor power models are a key tool in robotics for modeling and simulations related to control and optimization. The authors collect the dataset of motor power using the ABB IRB 120 industrial robot. This paper applies a multilayer perceptron (MLP) model to the collected dataset. Before the training of MLP models, each of the variables in the datase...

These authors contributed equally to this work. Abstract: This investigation underscores the paramount imperative of discerning network intrusions as a pivotal measure to fortify digital systems and shield sensitive data from unauthorized access, manipulation, and potential compromise. The principal aim of this study is to leverage a publicly avail...

This paper presents isentropic analysis results of the whole steam turbine (as well as turbine cylinders) from nuclear power plant. In the analyzed steam turbine, LPC (Low Pressure Cylinder) is the dominant mechanical power producer-mechanical power produced in the LPC is more than two times higher in comparison to mechanical power produced in the...

Developing a method for determining password strength using artificial intelligence (AI) is crucial as it enhances cybersecurity by providing a more robust defense against unauthorized access. AI can analyze complex patterns and trends, allowing for the identification of weak passwords and potential vulnerabilities more effectively than traditional...

One of the main problems in the application of machine learning techniques is the need for large amounts of data necessary to obtain a well-generalizing model. This is exacerbated for studies in which it is not possible to access large amounts of data—for example, in the case of ship main data modelling, where a limited amount of real-world data (s...

Smart tire technologies offer a novel sensing methodology for vehicle environment perception by providing direct measurements of tire dynamics parameters. This information can be utilized in advanced driver assistance systems as well as autonomous vehicle control to enhance vehicle performance and safety. Considering these criteria, we develop algo...

The study addresses the formidable challenge of calculating atomic coordinates for carbon nanotubes (CNTs) using density functional theory (DFT), a process that can endure for days. To tackle this issue, the research leverages the Genetic Programming Symbolic Regression (GPSR) method on a publicly available dataset. The primary aim is to assess if...

This paper presents an energy analysis of a three-cylinder steam turbine from a combined cycle power plant. Observing all the cylinders from the analyzed turbine, it is found that the dominant mechanical power producer is Low Pressure Cylinder (LPC), followed by the Intermediate Pressure Cylinder (IPC), while High Pressure Cylinder (HPC) is the cyl...

Malware detection using hybrid features, combining binary and hexadecimal analysis with DLL calls, is crucial for leveraging the strengths of both static and dynamic analysis methods. Artificial intelligence (AI) enhances this process by enabling automated pattern recognition, anomaly detection, and continuous learning, allowing security systems to...

Predicting the stability of a Decentralized Smart Grid is key to the control of such systems. One of the key aspects that is necessary when observing the control of DSG systems is the need for rapid control. Due to this, the application of AI-based machine learning (ML) algorithms may be key to achieving a quick and precise stability prediction. In...

Machine learning applications have demonstrated the potential to generate precise models in a wide variety of fields, including marine applications. Still, the main issue with ML-based methods is the need for large amounts of data, which may be impractical to come by. To assure the quality of the models and their robustness to different inputs, syn...

Simple Summary Breast cancer is a type of cancer with several sub-types and correct sub-type classification based on a large number of gene expressions is challenging even for artificial intelligence. However, the accurate classification of breast cancer in a patient is mandatory for the application of proper treatment. To obtain the equations that...

A common issue with X-ray examinations (XE) is the erroneous quality classification of the XE, implying that the process needs to be repeated, thus delaying the diagnostic assessment of the XE and increasing the amount of radiation the patient receives. The authors propose a system for automatic quality classification of XE based on convolutional n...

The use of synthetic, generated, data to address the machine-learning algorithms' needs for a large amount of data points is a growing trend in the research community. This paper tests four methods-Copula Generative Adversarial Network (GAN), CTGAN, Gaussian Copula, and Triplet-based variable encoder (TVAE) on the dataset defining risk factors for...

Exploration and detection of underground objects without excavation can be achieved by utilizing ground penetrating radar. Since such an approach is nondestructive, electromagnetic radiation has been used in order to accomplish sub-surface surveying. The correct interpretation of acquired ground penetrating radar data can be demanding, time-consumi...

This paper presents an energy analysis of main and auxiliary steam turbines from conventional coal fired power plant. Main turbine is composed of three cylinders connected to the same shaft which drives an electric generator, while auxiliary steam turbine is used for the boiler feedwater pump drive. The whole analyzed main steam turbine produces me...

The goal of the paper is estimating the normalized friction torque of a joint in an industrial robotic manipulator. For this purpose a source data, given as a figure, is digitized using a tool WebPlotDigitizer in order to obtain numeric data. The numeric data is the used within the machine learning algorithm genetic programming (GP), which performs...

The Super Cryogenic Dark Matter Search (SuperCDMS) experiment is used to search for Weakly Interacting Massive Particles (WIMPs)-candidates for dark matter particles. In this experiment, the WIMPs interact with nuclei in the detector; however, there are many other interactions (background interactions). To separate background interactions from the...

In autonomous manufacturing lines, it is very important to detect the faulty operation of robot manipulators to prevent potential damage. In this paper, the application of a genetic programming algorithm (symbolic classifier) with a random selection of hyperparameter values and trained using a 5-fold cross-validation process is proposed to determin...

For accurate and efficient control performance of electrical drives, precise values of phase voltages are required. In order to achieve control of the electric drive, the development of mathematical models of the system and its parts is often approached. Data-driven modeling using artificial intelligence can often be unprofitable due to the large a...

Path planning is one of the key steps in the application of industrial robotic manipulators. The process of determining trajectories can be time-intensive and mathematically complex, which raises the complexity and error proneness of this task. For these reasons, the authors tested the application of a genetic algorithm (GA) on the problem of conti...

Imaging is one of the main tools of modern astronomy—many images are collected each day, and they must be processed. Processing such a large amount of images can be complex, time-consuming, and may require advanced tools. One of the techniques that may be employed is artificial intelligence (AI)-based image detection and classification. In this pap...

In the case of pandemics such as COVID-19, the rapid development of medicines addressing the symptoms is necessary to alleviate the pressure on the medical system. One of the key steps in medicine evaluation is the determination of pIC50 factor, which is a negative logarithmic expression of the half maximal inhibitory concentration (IC50). Determin...

The navigation of mobile robots throughout the surrounding environment without collisions is one of the mandatory behaviors in the field of mobile robotics. The movement of the robot through its surrounding environment is achieved using sensors and a control system. The application of artificial intelligence could potentially predict the possible m...

With the proliferation of deep learning (DL) techniques in biomedical applications, the need for large-scale and diverse datasets has become more and more apparent. However, obtaining labeled biomedical data is often challenging. Concerns such as patient privacy, data sharing issues, ethical questions, and the lack of data – either due to the bias...

Abstract: Hepatitis C is an infectious disease which is caused by the Hepatitis C virus (HCV) and the virus primarily affects the liver. Based on the publicly available dataset used in this paper the idea is to develop a mathematical equation that could be used to detect HCV patients with high accuracy based on the enzymes, proteins, and biomarker...

Fire is usually detected with fire detection systems that are used to sense one or more products resulting from the fire such as smoke, heat, infrared, ultraviolet light radiation, or gas. Smoke detectors are mostly used in residential areas while fire alarm systems (heat, smoke, flame, and fire gas detectors) are used in commercial, industrial and...

Malicious websites are web locations that attempt to install malware, which is the general term for anything that will cause problems in computer operation, gather confidential information, or gain total control over the computer. In this paper, a novel approach is proposed which consists of the implementation of the genetic programming symbolic cl...

This article describes the implementation of the You Only Look Once (YOLO) detection algorithm for the detection of returnable packaging. The method of creating an original dataset and creating an augmented dataset is shown. The model was evaluated using mean Average Precision (mAP), F1score, Precision, Recall, Average Intersection over Union (Aver...

The value of the main ship particulars are key values to determine during initial design of a vessel, but they can be complex to determine, as they depend on a large number of factors. The presented research attempts to model the main particulars: length between perpendiculars (LPP), length overall (LOA), modulated breadth (B), depth (D), draught (...

Vaccinations are one of the most important steps in combat against viral diseases such as COVID-19. Determining the influence of the number of vaccinated patients on the infected population represents a complex problem. For this reason, the aim of this research is to model the influence of the total number of vaccinated or fully vaccinated patients...

In this paper, two-cylinder steam turbine, which operates in nuclear power plant is analyzed from the energy viewpoint. Along with the whole turbine, energy analysis is performed for each turbine cylinder (High Pressure Cylinder-HPC and Low Pressure Cylinder-LPC). A comparison of both cylinders shows that the dominant mechanical power producer is L...

Proceedings of the International Scientific Student Conference Ri-STEM.

While many discussions and observations have been made regarding the execution times of machine learning (ML) model training, not many researchers have shown concern regarding the execution times of trained models when the model are applied for inference. In this paper, the researchers observe the execution times of a realistic hybrid system consis...

The reaction to and the effect severity on the population of COVID-19 varied across different countries. This indicates that there are country-level factors which influenced the severity COVID-19 effect on the populace. The goal of this research is to determine some of these factors using Our World in Data COVID-19 dataset. The performance of the c...

In this paper, the influence of data scaling/normalizing techniques on the estimation accuracy of the ground state energies of molecules based on combination of C,H,N,O,P, and S atoms achieved by symbolic expressions obtained by applying genetic programming (GP) was investigated. For this investigation, a function with random selection of GP parame...

Over the past decade, improvements in image analysis methods and substantial advancements in processing power have allowed the development of powerful computer-aided analytical approaches to medical data. Tissue histology slides can now be scanned and preserved in digital form, thanks to the recent introduction of entire slide digital scanners. In...

One of the key challenges in medical image analysis is the curation of sufficiently large data sets. For these reasons, in this paper, two different approaches for image data set augmentation are presented. One approach is based on a pipeline that consists of various geometrical variations of original images. The second approach is based on the uti...

Coronavirus disease (COVID-19), since its appearance, has put a large burden on the global health system which have strived to mitigate the pandemic, but mortality of COVID-19 continues to increase. Many authors have employed machine learning (ML) algorithms in the investigation of COVID-19 in order to identify infected individuals, predict their c...

The use of artificial intelligence, especially machine learning methods in creating models that will be applied in clinical practice has reached its peak with the appearance of the COVID-19 pandemic. This study aims to determine the severity of the clinical condition of COVID-19 patients based on blood marker analysis. The study used data from 60 C...

In this paper, we shall be utilizing genetic programming (GP) to predict ground-state energies of molecules made up of C, H, N, O, P, and S (CHONPS) atoms. The GP was trained and tested on a publicly available dataset which consist of 16242 molecules where ground state energies were computed using the density functional theory (DFT). The optimal pa...

Cancer is one of the most discussed diseases in modern healthcare. Cancer rates vary by country, this indicates that there are factors that might inuence the occurrence of cancer depending on the country. In this paper, the authors present the dataset which consists of cancer rates (CR) for 42 countries, with 10 possible country-level factors-Healt...

Bladder cancer is one of the most common malignancies in men in Croatia. It is characterized by a high recurrence rate and high metastatic potential. For this reason, accurate and timely diagnosis is needed in order to treat bladder cancer as successfully as possible. Cystoscopy as a diagnostic method shows poorer accuracy of Carcinoma in situ (CIS...

Predicting the quality of the robot end-effector grasp quality during an industrial robot manipulator operation can be an extremely complex task. As is often the case with such complex tasks, Artificial Intelligence methods may be applied to attempt the creation of a model-if sufficient data exists. The presented dataset uses a publicly available d...

Determining the residuary resistance per unit weight of displacement is one of the key factors in the design of vessels. In this paper, the authors utilize two novel methods – Symbolic Regression (SR) and Gradient Boosted Trees (GBT) to achieve a model which can be used to calculate the value of residuary resistance per unit weight, of displacement...

This paper presents an energy and exergy analyses of two steam turbines from geothermal double flash power system. Along with the calculation of efficiencies and losses, in the exergy analysis is performed variation of the ambient temperature to investigate its influence on the obtained results. Low pressure turbine (LPT) produces higher real mecha...

In this paper is performed energy analysis of the gas turbine upgraded with heat regenerator. The analysis is performed by using air and combustion gases operating parameters measured in the real exploitation, therefore all the losses are considered during calculations (only the mechanical losses which has low influence on the overall energy balanc...

The diagnosis of oral squamous cell carcinoma is based on a histopathological examination, which is still the most reliable way of identifying oral cancer despite its high subjectivity. However, due to the heterogeneous structure and textures of oral cancer, as well as the presence of any inflammatory tissue reaction, histopathological classificati...

The calculation of inverse kinematics (IK) is a key part of industrial robot modeling, as it allows for the determination of the joint angles necessary to place the end-effector in the desired position. Still, analytically determining the IK equations is time-intensive, as it requires the solution of a complex equation system-and only grows more pr...

Detecting and identifying underground objects without excavation can be demanding, time-consuming, and at the same time, very challenging. Nowadays, with different approach i.e., by utilizing ground-penetrating radar (GPR), underground utilities such as pipes, metals, cables, concrete etc. can be observed and explored from the ground surface [1]. S...

Urinary bladder cancer is one of the most common cancers of the urinary tract. This cancer is characterized by its high metastatic potential and recurrence rate. Due to the high metastatic potential and recurrence rate, correct and timely diagnosis is crucial for successful treatment and care. With the aim of increasing diagnosis accuracy, artifici...

Since the outbreak of coronavirus disease-2019 (COVID-19), the whole world has taken interest in the mechanisms of its spread and development. Mathematical models have been valuable instruments for the study of the spread and control of infectious diseases. For that purpose, we propose a two-way approach in modeling COVID-19 spread: a susceptible,...

In this paper, an approach for urinary bladder cancer diagnosis from computer tomography (CT) images based on the application of convolutional neural networks (CNN) is presented. The image data set that consists of three main parts (frontal, horizontal, and sagittal plane) is used. In order to classify images, pre-defined CNN architectures are used...

The fact that Artificial Intelligence (AI) based algorithms exhibit a high performance on image classification tasks has been shown many times. Still, certain issues exist with the application of machine learning (ML) artificial neural network (ANN) algorithms. The best known is the need for a large amount of statistically varied data, which can be...

The collection of image data is an extremely common procedure in clinical practice today. Many of the diagnostic approaches generate such data-computed tomography (CT), X-ray radiography, magnetic resonance imaging (MRI), and others. This data collection process allows for the use of computer vision approaches to be applied with the goal of analysi...

Simplified Molecular Input Line Entry System (SMILES) is a type of chemical notation. The SMILES format allows the representation of chemical structures in a shape easily readable by computer programs. This allows many techniques, such as Artificial Neural Networks (ANNs) to be applied on the SMILES formatted data. One of the highest-performing ANN...

Background and objectives: Although ML has been studied for different epidemiological and clinical issues as well as for survival prediction of COVID-19, there is a noticeable shortage of literature dealing with ML usage in prediction of disease severity changes through the course of the disease. In that way, predicting disease progression from mi...

In this paper is performed energy and exergy analysis of waste heat recovery closed-cycle gas turbine system. Analyzed system can use waste heat from various main propulsors (gas turbines or internal combustion engines). Basically, the observed system operates by using CO 2 , what was the baseline for the analysis. It is investigated did the observ...

The importance of error detection is high, especially in modern manufacturing processes where assembly lines operate without direct supervision. Stopping the faulty operation in time can prevent damage to the assembly line. Public dataset is used, containing 15 classes, 2 types of faultless operation and 13 types of faults, with 463 force and torsi...

INTRODUCTION: As a result of this global health crisis caused by the COVID-19 pandemic, the medical industry is searching for innovations that have the potential to automate the diagnostic process of COVID-19 and serve as an assistive tool for clinicians. OBJECTIVES: X-ray images have shown to be useful in the diagnosis of COVID-19. The goal of th...

This paper presents an exergy analysis of the whole turbine, turbine cylinders and cylinder parts in four different operating regimes. Analyzed turbine operates in nuclear power plant while three of four operating regimes are obtained by using optimization algorithms-SA (Simplex Algorithm), GA (Genetic Algorithm) and IGSA (Improved Genetic-Simplex...

Inverse kinematics is one of the key parts of any industrial robotic manipulator modeling. Solving the inverse kinematics of a robotic manipulator in the classical analytical manner is fairly complex and error-prone. While previous research has shown the possibility of AI application for inverse kinematics solutions, such models have certain pitfal...

Since the outbreak of new coronavirus COVID-19, measures for ending the global pandemic such as social distancing and contact tracing have been proposed worldwide. We propose a SEIRD model to predict the development of epidemic, which can contribute to effective planning to control it. Based on official statistical data for Belgium, we calculated t...

This paper presents an exergy analysis of the whole turbine, turbine cylinders and cylinder parts in four different operating regimes. Analyzed turbine operates in nuclear power plant while three of four operating regimes are obtained by using optimization algorithms-SA (Simplex Algorithm), GA (Genetic Algorithm) and IGSA (Improved Genetic-Simplex...

This paper presents exergy analysis of the main steam condenser, which operates in nuclear power plant. The analysis is performed in four main condenser operating regimes (loads) for a variety of the ambient temperatures. It is found that the main steam condenser has the lowest exergy destruction (equal to 72091.56 kW) and the highest exergy effici...

RI-STEM-2021 is an international scientific student conference. The goal of the conference is to provide students of pre-graduate, graduate and post-graduate levels with experience in preparing, writing, and publishing scientific research in a form of a conference paper. The first RI-STEM was held on 10th June 2021 in Rijeka, Croatia (Online) wit...

The computational complexity of research tasks is ever growing, which is something that is extremely apparent in the field of Artificial Intelligence. These computational tasks require High Performance Computers (HPC), which may either be rented, per Infrastructure as a Service (IaaS) paradigm, or purchased in entirety and installed locally. One lo...