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DISTANCE BETWEEN SPECIES BY CONFUSION OPERATORS OF MULTI-CLASS CLASSIFIERS

UPB Scientific Bulletin, Series A: Applied Mathematics and Physics 2025年第1期2025卷 171-182页

作者： Tarbă, Nicolae Irimescu, Ionela N. Pleavă, Ana M. Scarlat, Eugen N. Mihăilescu, Mona Doctoral School Computer Science and Engineering Department Faculty of Automatic Control and Computers National University of Science and Technology POLITEHNICA Bucharest Romania Applied Sciences Doctoral School National University of Science and Technology POLITEHNICA Bucharest Romania CAMPUS Research Center National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept National University of Science and Technology POLITEHNICA Bucharest Romania Physics Dept Research Center for Applied Sciences in Engineering National University of Science and Technology POLITEHNICA Bucharest Romania

We introduce a method to evaluate the similarities between classes of objects based on the confusion matrices coming from the multi-class machine learning (ML) predictors that operate in the vector space generated by the classes. Operation in the confusion domain allows us to use the distance as evaluation metric of the closeness of the relevant properties carried by the classes. We applied the method to semiquantitatively evaluate the effects of X-ray and carbon ion radiation on cultured SW1353 chondrosarcoma cells with respect to the non-irradiated reference. We prove that it is possible to draw useful information on the strength of cells nuclei changes. © 2025, Politechnica University of Bucharest. All rights reserved.

关键词： Radiation effects

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Analog, Programmable Switched Capacitor FIR Filter Based on Rotator Architecture Implemented in CMOS Technology 26

Analog, Programmable Switched Capacitor FIR Filter Based on ...

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26th IEEE Signal Processing: Algorithms, Architectures, Arrangements, and Applications, SPA 2023

作者： Pawlowski, Pawel Dlugosz, Rafal Radkowski, Marek Watly, Mateusz Dabrowski, Adam Poznań University of Technology Division of Signal Processing and Electronic Systems Faculty of Control Robotics and Electrical Engineering Institute of Automatic Control and Robotics Poznań60-965 Poland Bydgoszcz University of Science and Technology Faculty of Telecommunication Computer Science and Electrical Engineering Bydgoszcz85-796 Poland

ISBN: (纸本)9798350304985

The paper presents project and its verification of a prototype integrated circuit containing an analog, programmable finite impulse response (FIR) filter, implemented in CMOS 350 nm technology. The structure of the filter is based on the switched capacitor technique. In circuits of this type, one of main challenges is an efficient implementation of filter coefficients, which result from several factors described in this work. When implementing such filters as programmable circuits, the values of their coefficients have to be limited to a selected range, i.e. a given resolution in bits. In the implemented prototype filter, the filter coefficients are represented by 6 bits in sign-magnitude notation, so they can take 63 different values only. In such filters, it is not possible to directly implement any frequency response of the filter. Each time, it is necessary to properly round the theoretical values of the coefficients so that they fit into the available range of discrete values resulting from the implementation. The authors of the work designed an algorithm that allows such matching. The paper also presents results of measurements of the prototype chip. © 2023 Division of Signal Processing and Electronic Systems, Poznan University of Technology (DSPES PUT).

关键词： FIR filters

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GaitPT: Skeletons Are All You Need For Gait Recognition

arXiv

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arXiv 2023年

作者： Catruna, Andy Cosma, Adrian Radoi, Emilian Faculty of Automatic Control and Computer Science University Politehnica of Bucharest Romania

The analysis of patterns of walking is an important area of research that has numerous applications in security, healthcare, sports and human-computer interaction. Lately, walking patterns have been regarded as a unique fingerprinting method for automatic person identification at a distance. In this work, we propose a novel gait recognition architecture called Gait Pyramid Transformer (GaitPT) that leverages pose estimation skeletons to capture unique walking patterns, without relying on appearance information. GaitPT adopts a hierarchical transformer architecture that effectively extracts both spatial and temporal features of movement in an anatomically consistent manner, guided by the structure of the human skeleton. Our results show that GaitPT achieves state-of-the-art performance compared to other skeleton-based gait recognition works, in both controlled and in-the-wild scenarios. GaitPT obtains 82.6% average accuracy on CASIA-B, surpassing other works by a margin of 6%. Moreover, it obtains 52.16% Rank-1 accuracy on GREW, outperforming both skeleton-based and appearance-based *** Codes 68U10 © 2023, CC BY-NC-ND.

关键词： Human computer interaction

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TCIP: Transformed Colour Intensity Profiles analysis for fault detection in power line insulators

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Multimedia Tools and Applications 2025年第8期84卷 4503-4534页

作者： Tomaszewski, Michal Gasz, Rafal Kasana, Singara Singh Osuchowski, Jakub Singh, Simranjit Zator, Slawomir Department of Computer Science Faculty of Electrical Engineering Automatic Control and Informatics Opole University of Technology Prószkowska 76 Opole45-758 Poland Department of Computer Science and Information Technology Central University of Haryana Haryana Mahendergarh123031 India Department of Information Technology Dr B. R. Ambedkar National Institute of Technology Punjab Jalandhar India Department of Safety Engineering and Technical Systems Faculty of Production Engineering and Logistics Opole University of Technology Prószkowska 76 Opole45-758 Poland

In response to the escalating demand for electricity, the aging process and inherent failures in power lines have become unavoidable challenges in their operational integrity. This research addresses the imperative need for a robust method to detect damage in power insulator disc images, introducing a novel feature extraction technique grounded in color intensity profile transformation and ensemble learning. For the purposes of the research, a specific dataset was developed based on publicly available images of power insulators. The collection consists of 9232 images of insulator discs which included 2184 images of damaged discs. The discernible damages include breakages and burnouts. Two distinct analysis variants were employed. In the first variant (V1), two classification groups were selected: disc with damages and disc without damages. In the second variant (V2), three classification groups were selected: discs without damage, broken discs, and burnout discs. The described research was divided into two successive stages. In the first of them (S1), the transformed color intensity profiles for the prepared data set were built and various machine learning models for their classification were trained and evaluated. In the next stage (S2), previously developed, highest efficient machine learning models, were used to make the detection of various damaged types of overhead line insulator discs. For the first stage of research high-performance results and a high value of the F1 score parameters were obtained (F1 score = 0.999 for the first variant (S1V1) and F1 score = 0.992 for the second variant (S1V2). In the second stage of research and the first variant (S2V1), the highest result of the F1 score was 0.932 and for the second variant (S2V2) F1 score was 0.930. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Feature extraction

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Split Cost Function based Single-Horizon Finite-Set Model Predictive control for Boost Converter with Loading Current Estimation

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IEEE Journal of Emerging and Selected Topics in Power Electronics 2025年

作者： Tatari, Fatemeh Rezayof Bizhani, Hamed Iwanski, Grzegorz Warsaw University of Technology Faculty of Electrical Engineering Warsaw Poland Kielce University of Technology Faculty of Electrical Engineering Automatic Control and Computer Science Kielce Poland

This paper presents a robust single-horizon finite-set model predictive control (FS-MPC) method for controlling the output voltage of boost converters. Unlike the long-horizon FS-MPC approach, which addresses the non-minimum phase (NMP) behavior of the converter by extending the prediction horizon (thereby increasing computational effort), the proposed method ensures stable voltage regulation by incorporating inductor current regulation into the cost function. To achieve this, the desired inductor current is calculated based on input-output power balance theory. Unlike recent studies that require an additional sensor to measure the loading current, this paper develops a loading current estimation approach to eliminate the need for extra current sensors, thereby enhancing the robustness of the proposed FS-MPC method. Additionally, over-current protection, which is typically absent in conventional FS-MPC used for direct voltage regulation, is also incorporated into the proposed method. The conventional cost function is also modified to tackle the NMP behavior more effectively. The performance of the proposed method in regulating the output voltage is evaluated through simulation results. Finally, its effectiveness across a wide range of output power and various load characteristics, including resistive, constant power, and constant current loads, is validated via experimental results. The results demonstrate that the proposed method is not only able to eliminate the overshoot and undershoot, but can also improve the settling time by 41% compared to a well-tuned conventional cascaded PI controller. In addition, the proposed method can reduce the computational burden by 84% compared to the conventional long-horizon FS-MPC approach. © 2013 IEEE.

关键词： Cost functions

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Pneumonia Detection from X-ray Images Using Convolutional Neural Networks

Pneumonia Detection from X-ray Images Using Convolutional Ne...

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International Conference on control Systems and computer science (CSCS)

作者： Viorel Dediu Andreea Udrea Department of Automatic Control and Systems Engineering Faculty of Automatic Control and Computer Science Univesity Politehnica of Bucharest Bucharest Romania

Pneumonia is one of the top causes of death in Romania and early detection of this disease improves the recovery chances and shortens the length of hospitalization. In this work, we develop a solution for automatic pneumonia detection based on convolutional neural networks. Four network models are investigated. They are trained on 4.163 images from a public dataset and tested on 530 images. The best results are obtained by one of the proposed models conducting to a sensitivity of 98.72%, an accuracy of 89.81%, and ROC 93.46%. Thus, this research proposes a lightweight screening tool that can help triaging the patients with pneumonia.

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Research on path planning algorithm of takeaway robots for terminal delivery

Research on path planning algorithm of takeaway robots for t...

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2nd International Conference on Mechatronic Automation and Electrical Engineering (ICMAEE 2024)

作者： Yuhang Wan Faculty of Automatic Control Electronics and Computer Science Silesian Technical University Gliwice 44-100 Poland

ISBN: (数字)9781837242672

Takeaway delivery has become an important part of urban life. However, terminal deliveries are often blocked by security measures that often prevent them from arriving on time. Designing a takeaway delivery robot can solve this problem to a large extent. In this paper, path planning algorithm level of designing a takeaway robot is researched. In this paper, the research is carried out by closely focusing on the current stage of the path planning algorithm related difficulties. Three typical algorithms are selected for simulation testing within the scope of graph search algorithms. These three algorithms are Dijkstra algorithm, A* algorithm and rapidly-exploring random tree (RRT) algorithm. The final comparison is made with the simulation test results. And to find the optimal path planning algorithm for takeaway delivery robots within the range of graph search algorithms. This paper provides a reference for the path planning algorithm level of takeaway delivery robot design. At the same time, it helps to improve the delivery service of takeaway terminal.

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How capable are state-of-the-art language models to cope with sarcasm? 24

How capable are state-of-the-art language models to cope wit...

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24th International Conference on control Systems and computer science, CSCS 2023

作者： Baroiu, Alexandru -Costin Trausan-Matu, Stefan Politehnica University of Bucharest Faculty of Automatic Control and Computer Science Bucharest Romania Romanian Academy Research Institute for Artificial Intelligence 'Mihai Drǎganescu' Academy of Romanian Scientists Bucharest Romania

ISBN: (纸本)9798350313390

Sarcasm detection has established itself as one of the more difficult Natural Language Processing tasks, due to the complex nature of sarcasm. This paper aims to benchmark the performance of state-of-the-art models like BERT, RoBERTa, ALBERT and GPT-3 when faced with this task. The dataset selected is MUStARD, which has increased in popularity in recent years, especially for multimodal tasks, and is one of the most qualitative and data rich dataset. An untuned GPT-3 based model was selected as the baseline and all the other models were fine-tuned using the textual data present in MUStARD, mainly the context and utterance information. The best performer was found to be the GPT-3 fine-tuned model, with an F1 score of 77. This is in line with the reported feats of GPT-3 based models that have popularized in recent months and reaffirms the superiority of GPT-3. Future avenues of research are then presented and explored, and the conclusions are drawn. © 2023 IEEE.

关键词： Benchmarking

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Applying NoSQL Data Adapter with the Learning Paths mechanism for better knowledge transfer in the age of distance learning 26

Applying NoSQL Data Adapter with the Learning Paths mechanis...

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26th International Conference on Knowledge-Based and Intelligent Information and Engineering Systems, KES 2022

作者： Werner, Aleksandra Faculty of Automatic Control Electronics and Computer Science Silesian University of Technology Akademicka 16 Str. Gliwice44-100 Poland

Database technology applies to many engineering problems. Hence it is the subject of study at many university majors. Since teaching practical usage of theory at a distance is difficult or even impossible, we present novel mechanisms that significantly enrich e-learning platform functionalities in individualized learning of databases installed on the teacher-managed server. The crucial component of our proposal, Data Adapter, allows for interactive querying and manipulating of the NoSQL databases through an e-learning platform. The Adapter is complemented by the Learning Paths component, which enables teachers the creation of individualized didactic paths for students with special educational needs. The e-learning platform load tests confirm that new activities do not substantially affect the comfort of students' work. Its impact on learning effectiveness was verified by rating the competence test for the group of 104 course participants. Half of them were the participants of the e-learning NoSQL course and used the developed mechanisms, while the remaining, control, group was taught with the conventional methods. The research shows that the proposal successfully improves teaching modern NoSQL languages. The scores improvement in the e-learning group of students compared to results in the control group is noticeable, and observed differences are statistically significant. © 2022 The Authors. Published by Elsevier B.V.

关键词： Students

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Creating a personality leisure-time model using genetic algorithms, behavioral psychology, and a happiness dataset

Creating a personality leisure-time model using genetic algo...

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International Conference on control Systems and computer science (CSCS)

作者： Ciprian-Ionut Nutescu Mariana Mocanu Faculty of Automatic Control and Computer Science University Politehnica Bucharest Bucharest Romania

In this paper, we proposed a genetic algorithm based on behavioral psychology developed by Carl Gustav Jung (16 Personalities model), in which we describe the person’s behavioral leisure and ludic behavioral features regarding his personality. The model used for inference is based on 40 years of psychology research and studies from the book “The 16 Personalities types that determinate how we live, love and work” by Otto Kroger and Janet M. Thuesen, published in 1988. To generate the leisure model, we are using genetic algorithms. To improve the leisure model, we are reinforcing it using weight-based fitness functions with inference extracted from the HappyDB dataset. In this dataset, persons around the world express the most valuable/happy moments in their life. The leisure model describes how they would prefer spending their time and how this will bring the most enjoyment and reward (human reward psychological model).

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