Nauki Techniczne

Bulletin of the Polish Academy of Sciences Technical Sciences

Opis

The Bulletin of the Polish Academy of Sciences Technical Sciences is published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences, since the beginning of the existence of the PAS in 1952. The journal is peer‐reviewed and is published both in printed and electronic form. It is established for the publication of original high quality papers from multidisciplinary Engineering sciences with the following topics preferred:

Artificial and Computational Intelligence,
Biomedical Engineering and Biotechnology,
Civil Engineering,
Control, Informatics and Robotics,

Electronics, Telecommunication and Optoelectronics,
Mechanical and Aeronautical Engineering, Thermodynamics,
Material Science and Nanotechnology,
Power Systems and Power Electronics.

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Journal Metrics:

JCR Impact Factor 2022:	1.2
5 Year Impact Factor 2020:	1.490
CiteScore 2022:	2.8
SCImago Journal Rank (SJR) 2022:	0.285
Source Normalized Impact per Paper (SNIP) 2022:	0.543
Ministry of Education and Science:	100 points

Abbreviated title: Bull. Pol. Acad. Sci. Tech. Sci.

ISSN

ISSN 2300-1917

Editorial Board 2023-2025

Editor-in-Chief:

A. Rogalski, Military University of Technology

Honorary (Past) Editor-in Chief:

T. Kaczorek, Warsaw University of Technology

M.P. Kaźmierkowski, Warsaw University of Technology

Deputy Editor-in-Chief:

B. Błachowski, Institute of Fundamental Technological Research PAN

M. Mrozowski, Gdansk University of Technology

Board of Topical Co-editors:

Artificial and Computational Intelligence

S. Osowski, B. Sawicki and T. Leś, Warsaw University of Technology

Biomedical Engineering and Biotechnology

D. Pijanowska, Institute of Biocybernetics and Biomedical Engineering PAN

Civil Engineering

L. Czarnecki, Building Research Institute, ITB, Warsaw

Ł. Sadowski, Wroclaw University of Science and Technology

Control, Robotics and Informatics

J. Klamka and A. Babiarz, Silesian Technical University

J. Stefanowski, Poznan University of Technology

Electronics, Telecommunication and Optoelectronics

M. Mrozowski and A. Lamęcki, Gdansk University of Technology

Mechanical and Aeronautical Engineering, Thermodynamics

B. Błachowski, Institute of Fundamental Technological Research PAN

G. Zboiński, Institute of Fluid-Flow Machinery PAN and University of Warmia and Mazury in Olsztyn

Materials Science and Nanotechnology

B. Major and P. Czaja, Institute of Metallurgy and Materials Science PAN

Power Systems and Power Electronics

J. Rąbkowski and M. Jasiński, Warsaw University of Technology

International Editorial Advisory Board

R. Asthana, University of Wisconsin-Stout, Menomonie, USA

Xu Binshi, China Association of Plant Engineering, Beijing, P.R. China

F. Blaabjerg, Aalborg University, Denmark

C. Cecati, University of L’Aquila, Italy

A. Cichocki, RIKEN Institute, Tokyo, Japan

M. David, National Polytechnique de Toulouse, France

R. Ebner, Materials Centre Leoben, Leoben, Austria

E. Fornasini, University of Padova, Padova, Italy

L.G. Franquelo, University of Sevilla, Spain

M. Gad-el-Hak, Virginia Commonwealth University, Richmond, USA

M. Giersig, Free University of Berlin, Germany

D. van Gemert, Catholic University Leuven, KU Leuven, Belgium

L. Keviczky, Hungarian Academy of Sciences, Budapest, Hungary

V. Kučera, Czech Technical University in Prague, Prague, Czech Republic

R. Kennel, Technical University Munich, Germany

T.A. Kowalewski, Institute of Fundamental Technological Research PAN

E. Levi, Liverpool John Moore University, UK

G. Maier, Technical University of Milan, Milan, Italy

K.F. Man, City University of Hong Kong,

R. Maniewski, Institute of Biocybernetics and Biomedical Engineering PAN

H.A. Mang, Austrian Academy of Sciences, Vienna, Austria

H. Mihashi, Tohoku University, Aoba-ku, Sendai, Japan

S. Mindess, University of British Columbia, Vancouver, Canada

D.A. Mlynski, University of Karlsruhe, Karlsruhe, Germany

A.S. Nowak, University of Michigan, Ann Arbor, USA

K. Ohnishi, Keio University, Yokohama, Japan

A. Öberg, Linköping University, Linköping, Sweden

W. Pedrycz, University of Alberta, Canada

M. Razeghi, Northwestern University, Evanston, USA

J. Rodriguez, University of Andres Bello, Santiago, Chile

J.V. Sloten, Catholic University Leuven, Leuven, Belgium

B.M. Wilamowski, University of Auburn, Alabama, USA

A.L. Yarin, University of Illinois at Chicago, USA

Du Xiangwan, Chinese Academy of Engineering, China

J. Żurada, Department of Computer Engineering, University of Louisville, USA

Editorial Office:

Pałac Kultury i Nauki

Wydział IV Nauk Technicznych PAN

Pl. Defilad 1

PL 00-901 Warszawa

Managing Editor:

Renata Podraza, e-mail: Renata.Podraza@pan.pl

Finance:

Katarzyna Łasak, e-mail: Katarzyna.Lasak@pan.pl

The Bulletin of the Polish Academy of Sciences Technical Sciences is an open access journal with all content available with no charge in full text version.

The journal content is available under the licencse CC BY 4.0 https://creativecommons.org/licenses/by/4.0/.

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Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3

1 Digital twin-oriented dynamic optimization of multi-process route based on improved hybrid ant colony algorithm

Zhaoming Chen , Jinsong Zou , Wei Wang

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e148875 | DOI: 10.24425/bpasts.2024.148875

Słowa kluczowe: digital twin multi-process route intuitionistic fuzzy information adaptive ant colony algorithm optimization

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Abstrakt

To improve the dynamic adaptability and flexibility of the process route during manufacturing, a dynamic optimization method of the multi-process route based on an improved ant colony algorithm driven by digital twin is proposed. Firstly, based on the analysis of the features of the manufacturing part, the machining methods of each process are selected, and the fuzzy precedence constraint relationship between machining metas and processes is constructed by intuitionistic fuzzy information. Then, the multi-objective optimization function driven by the digital twin is established with the optimization objectives of least manufacturing cost and lowest carbon emission, also the ranking of processing methods is optimized by an improved adaptive ant colony algorithm to seek the optimal processing sequence. Finally, the transmission shaft of some equipment is taken as an engineering example for verification analysis, which shows that this method can obtain a process route that gets closer to practical production.

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Autorzy i Afiliacje

Zhaoming Chen

1 2

e-mail:

ORCID:

Jinsong Zou

Wei Wang

e-mail:

ORCID:

Chongqing University, Chongqing, China
Chongqing School, University of Chinese Academy of Sciences, Chongqing, China
Chongqing Institute of Green and Intelligent Technology, Chinese Academy of Sciences, Chongqing, China

2 FedAssess: analysis for efficient communication and security algorithms over various federated learning frameworks and mitigation of label-flipping attack

R Anusuya , D Karthika Renuka

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e148944 | DOI: 10.24425/bpasts.2024.148944

Słowa kluczowe: federated learning privacy in federated learning deep learning attacks in federated learning label-flipping attack in FL

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Abstrakt

. Federated learning is an upcoming concept used widely in distributed machine learning. Federated learning (FL) allows a large number of users to learn a single machine learning model together while the training data is stored on individual user devices. Nonetheless, federated learning lessens threats to data privacy. Based on iterative model averaging, our study suggests a feasible technique for the federated learning of deep networks with improved security and privacy. We also undertake a thorough empirical evaluation while taking various FL frameworks and averaging algorithms into consideration. Secure multi party computation, secure aggregation, and differential privacy are implemented to improve the security and privacy in a federated learning environment. In spite of advancements, concerns over privacy remain in FL, as the weights or parameters of a trained model may reveal private information about the data used for training. Our work demonstrates that FL can be prone to label-flipping attack and a novel method to prevent label-flipping attack has been proposed. We compare standard federated model aggregation and optimization methods, FedAvg and FedProx using benchmark data sets. Experiments are implemented in two different FL frameworks – Flower and PySyft and the results are analyzed. Our experiments confirm that classification accuracy increases in FL framework over a centralized model and the model performance is better after adding all the security and privacy algorithms. Our work has proved that deep learning models perform well in FL and also is secure.

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Autorzy i Afiliacje

R Anusuya

e-mail:

ORCID:

D Karthika Renuka

e-mail:

ORCID:

Department of Information Technology, PSG College of Technology, Coimbatore, TN 641004, India

3 A novel artificial intelligence-based hybrid system to improve breast cancer detection using DCE-MRI

İsmail Akgül , Volkan Kaya , Erdal Karavaş , Sonay Aydin , Ahmet Baran

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149172 | DOI: 10.24425/bpasts.2024.149172

Słowa kluczowe: artificial intelligence artificial neural network deep learning DCE-MRI breast cancer detection and classification

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Abstrakt

The interpretation of breast magnetic resonance imaging (MRI) in the healthcare field depends on the good knowledge and experience of radiologists. Recent developments in artificial intelligence (AI) have shown advances in the field of radiology. However, the desired levels have not been reached in the field of radiology yet. In this study, a novel model structure is proposed to characterize the diagnostic performance of AI technology for individual breast dynamic contrast material–enhanced (DCE) MRI sequences. In the proposed model structure, Inception-v3, EfficientNet-B3, and DenseNet-201 models were used as hybrids together with the Yolo-v3 algorithm to detect breast and cancer regions. In the proposed model, DCE-MRI sequences (T2, ADC, Diffusion, Non-Contrast Fat Non-Suppressed T1, Non-Contrast Fat Suppressed T1, Contrast Fat Suppressed T1, and Subtraction T1) were evaluated separately and validation was made, thus providing a unique perspective. According to the validation results, the model structure with the best performance was determined as Yolo-v3 + DenseNet-201. With this model structure, 92.41% accuracy, 0.5936 loss, 92.44% sensitivity, and 92.44% specificity rates were obtained. In addition, it was determined that the results obtained without using contrast material in the best model were 91.53% accuracy, 0.9646 loss, 92.19% sensitivity, and 92.19% specificity. Therefore, it is predicted that the need for contrast material use can be reduced with the help of this model structure.

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Autorzy i Afiliacje

İsmail Akgül

e-mail:

ORCID:

Volkan Kaya

e-mail:

ORCID:

Erdal Karavaş

e-mail:

ORCID:

Sonay Aydin

e-mail:

ORCID:

Ahmet Baran

e-mail:

ORCID:

Department of Computer Engineering, Faculty of Engineering and Architecture, Erzincan Binali Yıldırım University, Türkiye
Department of Radiology, Faculty of Medicine, Bandırma Onyedi Eylül University, Balıkesir, Türkiye
Department of Radiology, Faculty of Medicine, Erzincan Binali Yıldırım University, Erzincan, Türkiye

4 Implications of lithium-ion cell temperature estimation methods for intelligent battery management and fast charging systems

Ahmed Abd El Baset Abd El Halim , Ehab Hassan Eid Bayoumi , Walid El-Khattam , Amr Mohamed Ibrahim

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149171 | DOI: 10.24425/bpasts.2024.149171

Słowa kluczowe: BMS fast charging lithium-ion batteries machine learning thermal testing techniques

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Abstrakt

This article examines in depth the most recent thermal testing techniques for lithium-ion batteries (LIBs). Temperature estimation circuits can be divided into six divisions based on modeling and calculation methods, including electrochemical computational modeling, equivalent electric circuit modeling (EECM), machine learning (ML), digital analysis, direct impedance measurement and magnetic nanoparticles as a base. Complexity, accuracy and computational cost-based EECM circuits are feasible. The accuracy, usability and adaptability of diagrams produced using ML have the potential to be very high. However, none of them can anticipate the low-cost integrated BMS in real time due to their high computational costs. An appropriate solution might be a hybrid strategy that combines EECM and ML.

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Autorzy i Afiliacje

Ahmed Abd El Baset Abd El Halim

e-mail:

ORCID:

Ehab Hassan Eid Bayoumi

Walid El-Khattam

Amr Mohamed Ibrahim

Energy and Renewable Energy Department, Faculty of Engineering, Egyptian Chinese University, 14 Abou Ghazalh, Mansheya El-Tahrir,Ain Shams, Cairo, Egypt
Department of Mechanical Engineering, Faculty of Engineering, The British University in Egypt, El Sherouk City, Cairo, Egypt
Department of Electric Power and Machines, Faculty of Engineering, Ain Shams University, Cairo, Egypt

5 Damage detection in concrete structures with impedance data and machine learning

Asraar Anjum , Meftah Hrairi , Abdul Aabid , Norfazrina Yatim , Maisarah Ali

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149178 | DOI: 10.24425/bpasts.2024.149178

Słowa kluczowe: concrete structures damage piezoelectric materials electromechanical impedance machine learning

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Abstrakt

This study aims to evaluate the effectiveness of machine learning (ML) models in predicting concrete damage using electromechanical impedance (EMI) data. From numerous experimental evidence, the damaged mortar sample with surface-mounted piezoelectric (PZT) material connected to the EMI response was assessed. This work involved the different ML models to identify the accurate model for concrete damage detection using EMI data. Each model was evaluated with evaluation metrics with the prediction/true class and each class was classified into three levels for testing and trained data. Experimental findings indicate that as damage to the structure increases, the responsiveness of PZT decreases. Therefore, we examined the ability of ML models trained on existing experimental data to predict concrete damage using the EMI data. The current work successfully identified the approximately close ML models for predicting damage detection in mortar samples. The proposed ML models not only streamline the identification of key input parameters with models but also offer cost-saving benefits by reducing the need for multiple trials in experiments. Lastly, the results demonstrate the capability of the model to produce precise predictions.

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Autorzy i Afiliacje

Asraar Anjum

Meftah Hrairi

e-mail:

ORCID:

Abdul Aabid

e-mail:

ORCID:

Norfazrina Yatim

e-mail:

ORCID:

Maisarah Ali

Department of Mechanical and Aerospace Engineering, Faculty of Engineering, International Islamic University Malaysia,P.O. Box 10, 50728, Kuala Lumpur, Malaysia
Department of Engineering Management, College of Engineering, Prince Sultan University, PO BOX 66833, Riyadh 11586, Saudi Arabia
Department of Civil Engineering, Faculty of Engineering, International Islamic University Malaysia, P.O. Box 10, 50728, Kuala Lumpur, Malaysia

6 GNSS multipath error in the context of the reliability of companion robots

Karolina Krzykowska-Piotrowska , Emilia Grabka , Ewa Dudek , Adam Rosiński , Kamil Maciuk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149235 | DOI: 10.24425/bpasts.2024.149235

Słowa kluczowe: companion robot reliability operation navigation

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Abstrakt

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Autorzy i Afiliacje

Karolina Krzykowska-Piotrowska

e-mail:

ORCID:

Emilia Grabka

Ewa Dudek

e-mail:

ORCID:

Adam Rosiński

e-mail:

ORCID:

Kamil Maciuk

e-mail:

ORCID:

Warsaw University of Technology, Faculty of Transport, ul. Koszykowa 75, 00-662 Warsaw, Poland
AGH University of Krakow, ul. Mickiewicza 30, 30-059 Kraków, Poland

7 The use of computed tomography and scanning microscopy methods for assessing the alkaline reactivity of aggregate

Justyna Zapała-Sławeta

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149814 | DOI: 10.24425/bpasts.2024.149814

Słowa kluczowe: alkali-silica-reaction microstructure degradation computed tomography SEM-EDS

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Abstrakt

The reaction of alkalis with aggregate containing reactive forms of silica (ASR) plays a significant role in shaping the durability of concrete, as the strongly hygroscopic reaction products generated lead to internal stress, causing its expansion and cracking. This study presents an extended analysis of corrosive processes occurring in mortars with reactive natural aggregate from Poland, using computed tomography and scanning microscopy methods. Numerous cracks in the grains and the surrounding cementitious matrix were observed, indicating a high degree of advancement of corrosive processes. Over time, the proportion of pores with reduced sphericity increased, indicating ongoing degradation of the mortars. The usefulness of computed tomography in studying the progress of ASR was demonstrated. Scanning microscopy confirmed that the cause of mortar degradation is the formed ASR gel with a typical composition, located within the volume of reactive grains, cracks propagating into the cementitious matrix, and accumulated in air voids.

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Autorzy i Afiliacje

Justyna Zapała-Sławeta

e-mail:

ORCID:

Faculty of Civil Engineering and Architecture, Kielce University of Technology, Al. Tysi ˛aclecia Panstwa Polskiego 7, 25-314 Kielce, Poland

8 Genetic programming for estimating passenger car equivalent in unsignalized intersections

Aarohi Kumar Munshi , Ashish Kumar Patnaik

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149180 | DOI: 10.24425/bpasts.2024.149180

Słowa kluczowe: passenger car rquivalent (PCE) unsignalized intersection slow-moving three-wheelers (SM3W) urban traffic sustainable mode genetic programming

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Abstrakt

The study concentrates on two different genetic programming approaches for determining passenger car equivalent (PCE) values and observing the impact on capacity estimation at urban unsignalized intersections. Considering heterogeneous traffic conditions, a new PCE value is introduced to encompass sustainable modes of public transit vehicles, specifically slow-moving three-wheelers (SM3W), commonly known as E-Rickshaws. Since PCE value is considered an important parameter for capacity calculations, the present study considered 14 unsignalized intersections located in Ranchi city of India. An automatic plate recognition system is employed to have the count of vehicular traffic. The methodologies include age-layered population structure genetic programming (ALPSGP), and the offspring selection genetic programming (OSGP) approach that incorporates static and dynamic variables. Based on the significance test and ranking of the genetic programming (GP) models, the OSGP model is recommended as the most appropriate model for heterogeneous traffic. Sensitivity analysis reported that lagging headway (��) is the most contributing factor in PCE estimation. The PCE value of SM3W is found to be 0.81 and that could be incorporated as a new classification of vehicles in Indo-HCM. It is observed that evaluated capacity based on PCE values of OSGP performed admirably in both normal and congested traffic situations.

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Autorzy i Afiliacje

Aarohi Kumar Munshi

Ashish Kumar Patnaik

e-mail:

ORCID:

Department of Civil & Environmental Engineering, Birla Institute of Technology Mesra, India

9 Time parameters verification of a numerical simulator of an automated store warehouse

Sebastian Rzydzik , Piotr Kroczek

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149816 | DOI: 10.24425/bpasts.2024.149816

Słowa kluczowe: automated store warehouse vending machine numerical simulator digital twin

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Abstrakt

The intelligent automated store warehouse (iZMS) research and development project was created to meet the expectations of a modern automatic store. The project concerns the development of the concept and pilot implementation of an automated store warehouse adapted to the autonomous and automatic sales of goods selected by retail chains. One of the aims of the iZMS project is to develop a scalable solution that allows for the simple adaptation of the iZMS to the needs of a potential customer, considering their requirements in terms of the quantity and variety of assortment offered within the iZMS. An important requirement in the use of the iZMS system is minimizing the customer waiting time for purchased products. This problem is related, among others, to the placement of products on the shelves of racks and will be solved in the optimizing process. Running optimization tasks requires a simulator that will mimic the features of a physical device faster than in real time to generate many proposals of the allocation of goods on storage racks in the shortest possible time and choose the best one, guaranteeing the shortest picking time of a representative basket of goods. A numerical simulator was developed to model the physical structures of food storage equipment and then simulate the sales process. Among the results obtained, the most important are the time parameters of individual operations,which will be used to optimize the placement of goods on storage racks. After analyzing the needs resulting from the usage of the iZMS system, we decided to develop a dynamic, deterministic simulator with discrete objects and perform the simulation with a controlled time increment and, in some cases, utilize elements of event-driven simulation, in which the flow of goods is simulated with first-in, first-out (FIFO) queues. Finally, verification of the numerical simulator with a physical model confirmed that it could be employed in optimization processes.

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Autorzy i Afiliacje

Sebastian Rzydzik

e-mail:

ORCID:

Piotr Kroczek

Faculty of Mechanical Engineering, Silesian University of Technology, ul. Konarskiego 18A, 44-100 Gliwice, Poland
HemiTech sp. z o.o., ul. Piastowska 2, 44-122 Gliwice, Poland

10 Varying coefficients in parallel shared-memory variational splitting solvers for non-stationary Maxwell equations

Marcin Łoś , Maciej Woźniak , Maciej Paszynski

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149179 | DOI: 10.24425/bpasts.2024.149179

Słowa kluczowe: partial differential equations finite element method Maxwell equations variational splitting MRI scan data

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Abstrakt

Direction-splitting implicit solvers employ the regular structure of the computational domain augmented with the splitting of the partial differential operator to deliver linear computational cost solvers for time-dependent simulations. The finite difference community originally employed this method to deliver fast solvers for PDE-based formulations. Later, this method was generalized into so-called variational splitting. The tensor product structure of basis functions over regular computational meshes allows us to employ the Kronecker product structure of the matrix and obtain linear computational cost factorization for finite element method simulations. These solvers are traditionally used for fast simulations over the structures preserving the tensor product regularity. Their applications are limited to regular problems and regular model parameters. This paper presents a generalization of the method to deal with non-regular material data in the variational splitting method. Namely, we can vary the material data with test functions to obtain a linear computational cost solver over a tensor product grid with non-regular material data. Furthermore, as described by the Maxwell equations, we show how to incorporate this method into finite element method simulations of non-stationary electromagnetic wave propagation over the human head with material data based on the three-dimensional MRI scan.

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Autorzy i Afiliacje

Marcin Łoś

e-mail:

ORCID:

Maciej Woźniak

e-mail:

ORCID:

Maciej Paszynski

e-mail:

ORCID:

AGH University of Krakow, al. Mickiewicza 30, 30-059 Krakow, Poland

11 On applications of quasi-Abelian Cayley graphs to Denial-of-Service protection

Ewa Girejko , Agnieszka B. Malinowska

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | No. 3 | e149232 | DOI: 10.24425/bpasts.2024.149232

Słowa kluczowe: multi-agent systems Denial-of-Service attack asymptotic stability switched systems quasi-Abelian Cayley graphs

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Abstrakt

This paper addresses the problem of designing secure control for networked multi-agent systems (MASs) under Denial-of-Service (DoS) attacks. We propose a constructive design method based on the interaction topology. The MAS with a non-attack communication topology, modelled by quasi-Abelian Cayley graphs subject to DoS attacks, can be represented as a switched system. Using switching theory, we provide easily implementable sufficient conditions for the networked MAS to remain asymptotically stable despite DoS attacks. Our results are applicable to both continuous-time and discrete-time systems, as well as to discrete-time systems with variable steps or systems that combine discrete and continuous times.

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Autorzy i Afiliacje

Ewa Girejko

e-mail:

ORCID:

Agnieszka B. Malinowska

e-mail:

ORCID:

Bialystok University of Technology,Wiejska 45, 15-351 Białystok, Poland

12 CNC machine control using deep reinforcement learning

Dawid Kalandyk , Bogdan Kwiatkowski , Damian Mazur

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e148940 | DOI: 10.24425/bpasts.2024.148940

Słowa kluczowe: deep reinforcement learning cnc machining machining optimization

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Abstrakt

Optimization of industrial processes such as manufacturing or processing of specific materials constitutes a point of interest for many researchers, and its application can lead not only to speeding up the processes in question, but also to reducing the energy cost incurred during them. This article presents a novel approach to optimizing the spindle motion of a computer numeric control (CNC) machine. The proposed solution is to use deep learning with reinforcement to map the performance of the reference points realization optimization (RPRO) algorithm used in the industry. A detailed study was conducted to see how well the proposed method performs the targeted task. In addition, the influence of a number of different factors and hyperparameters of the learning process on the performance of the trained agent was investigated. The proposed solution achieved very good results, not only satisfactorily replicating the performance of the benchmark algorithm, but also speeding up the machining process and providing significantly higher accuracy.

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Autorzy i Afiliacje

Dawid Kalandyk

e-mail:

ORCID:

Bogdan Kwiatkowski

e-mail:

ORCID:

Damian Mazur

e-mail:

ORCID:

Doctoral School of the Rzeszów University of Technology, Powstanców Warszawy Ave. 12, 35-959 Rzeszów, Poland
Department of Electrical and Computer Engineering Fundamentals, Rzeszow University of Technology, W. Pola str. 2, 35-959 Rzeszów, Poland

13 Synergistic toughening and strengthening of an epoxy resin modified by simultaneous use of two different modifiers

Anita Białkowska , Patryk Suroń , Wojciech Kucharczyk , Barbora Hanulikova , Mohamed Bakar

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149176 | DOI: 10.24425/bpasts.2024.149176

Słowa kluczowe: epoxy resin hybrid composites mechanical and thermal properties structure morphology

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Abstrakt

The present work investigates the effect of modifying an epoxy resin using two different modifiers. The mechanical and thermal properties were evaluated as a function of modifier type and content. The structure and morphology were also analyzed and related to the measured properties. Polyurethane (PUR) was used as a liquid modifier, while Cloisite Na+ and Nanomer I.28E are solid nanoparticles. Impact strength (IS) of hybrid nanocomposites based on 3.5 wt% PUR and 2 wt% Cloisite or 3.5 wt% PUR and 1 wt% Nanomer was maximally increased by 55% and 30%, respectively, as compared to the virgin epoxy matrix, exceeding that of the two epoxy/nanoparticle binaries but not that of the epoxy/PUR binary. Furthermore, a maximum increase in IS of approximately 20% as compared to the pristine matrix was obtained with the hybrid epoxy nanocomposite containing 0.5 wt% Cloisite and 1 wt% Nanomer, including a synergistic effect, due most likely to specific interactions between the nanoparticles and the epoxy matrix. The addition of polyurethane and nanoclays increased the thermal stability of epoxy composites significantly. However, DSC results showed that the addition of flexible polyurethane chains decreased the glass transition temperatures, while the softening point and the service temperature range of epoxy nanocomposites containing nanofillers were increased. FTIR analysis confirmed the occurrence of interaction between the epoxy matrix and added modifiers. All SEM micrographs showed significant roughness of the fracture surfaces with the formation of elongated platelets, explaining the increase in mechanical properties of the epoxy matrix.

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Autorzy i Afiliacje

Anita Białkowska

Patryk Suroń

Wojciech Kucharczyk

Barbora Hanulikova

Mohamed Bakar

e-mail:

ORCID:

Casimir Pulaski University of Radom, Poland
Tomas Bata University in Zlin, Czech Republic
Independent Researcher

14 The effect of magnesium and copper addition on the microstructure, mechanical properties, and corrosion rate of as-cast biodegradable zinc alloys

Magdalena Gieleciak , Karol Janus , Łukasz Maj , Paweł Petrzak , Magdalena Bieda , Anna Jarzębska

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149175 | DOI: 10.24425/bpasts.2024.149175

Słowa kluczowe: biodegradable zinc alloys alloying additives mechanical properties microstructure corrosion rate

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Abstrakt

Microstructure, mechanical, and corrosion properties of as-cast pure zinc and its binary and ternary alloys with magnesium (Mg), and copper (Cu) additions were investigated. Analysis of microstructure conducted by scanning electron microscopy revealed that alloying additives contributed to decreasing average grain size compared to pure zinc. Corrosion rate was calculated based on immersion and potentiodynamic tests and its value was lower for materials with Cu content. Moreover, it was shown that the intermetallic phase, formed as a result of Mg addition, constitutes a specific place for corrosion. It was observed that a different type of strengthening was obtained depending on the additive used. The presence of the second phase with Mg improved the tensile strength of the Zn-based materials, while Cu dissolved in the solution had a positive effect on their elongation.

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Autorzy i Afiliacje

Magdalena Gieleciak

e-mail:

ORCID:

Karol Janus

1 2

Łukasz Maj

Paweł Petrzak

Magdalena Bieda

Anna Jarzębska

e-mail:

ORCID:

Institute of Metallurgy and Materials Science, Polish Academy of Sciences, Krakow, Poland
Faculty of Foundry Engineering, AGH University of Science and Technology, Krakow, Poland

15 Investigation of HgCdTe avalanche photodiodes for HOT condition

Tetiana Manyk , Jan Sobieski , Kacper Matuszelański , Jarosław Rutkowski , Piotr Martyniuk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149173 | DOI: 10.24425/bpasts.2024.149173

Słowa kluczowe: HgCdTe APD LWIR MWIR

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Abstrakt

The performance of long-wave infrared (LWIR) �� = 0.22 HgCdTe avalanche photodiodes (APDs) was presented. The dark currentvoltage characteristics at temperatures 200 K, 230 K, and 300 K were measured and numerically simulated. Theoretical modeling was performed by the numerical Apsys platform (Crosslight). The effects of the tunneling currents and impact ionization in HgCdTe APDs were calculated. Dark currents exhibit peculiar features which were observed experimentally. The proper agreement between the theoretical and experimental characteristics allowed the determination that the material parameters of the absorber were reached. The effect of the multiplication layer profile on the detector characteristics was observed but was found to be insignificant.

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Autorzy i Afiliacje

Tetiana Manyk

e-mail:

ORCID:

Jan Sobieski

1 2

e-mail:

ORCID:

Kacper Matuszelański

Jarosław Rutkowski

e-mail:

ORCID:

Piotr Martyniuk

e-mail:

ORCID:

Institute of Applied Physics, Military University of Technology, ul. Kaliskiego 2, 00-908 Warsaw, Poland
Vigo Photonics S.A., ul. Poznanska 129/133, 05-850 Ożarów Mazowiecki, Poland

16 Analysis of the general index of modelling in interior lighting

Piotr Pracki , Paulina Komorzycka

Bulletin of the Polish Academy of Sciences Technical Sciences | 2024 | 72 | 3 | e149233 | DOI: 10.24425/bpasts.2024.149233

Słowa kluczowe: electric lighting interior lighting directionality of light modelling regression

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Abstrakt

Directionality of light and modelling effects impact lighting quality in interiors. Modelling effects depend on the photometric characteristics of luminaires and their layout but also interior size and reflectance. This research aims to evaluate lighting design limitations and the characteristics of the impact of interior and luminaires on modelling effects, as well as elaborate a prediction method of modelling effects in interior lighting. The general index of modelling was used for the analysis of modelling effects in interiors. The implementation of the research objectives was based on simulation and statistical analysis. 432 situations, varied interior size, and reflectance, the lighting class, luminaire downward luminous intensity distribution, and layout were considered. The results show that achieving the required range of the general index of modelling in interior lighting is substantially limited. The general index of modelling is impacted the most by the layout of luminaires. The elaborated multiple linear regression models can have a practical use for interior lighting design and analysis in terms of obtaining the required range of the general index of modelling.

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