Applied sciences

Bulletin of the Polish Academy of Sciences Technical Sciences

Description

The Bulletin of the Polish Academy of Sciences Technical Sciences has been published bimonthly by the Division IV Engineering Sciences of the Polish Academy of Sciences since the establishment of PAS in 1952. The journal is peer-reviewed and issued in electronic format. It aims to publish original, high-quality papers from multidisciplinary engineering sciences, with preferred topics including:

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.

Submit your article

Journal Metrics:

JCR Impact Factor 2024:	1.1
5 Year Impact Factor 2023:	1.0
CiteScore 2024:	2.7
SCImago Journal Rank (SJR) 2023:	0.271
Source Normalized Impact per Paper (SNIP) 2023:	0.517
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

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

Biomedical Engineering and Biotechnology

P. Ładyżyński, 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, Gdansk University of Technology

P. Kryszkiewicz, Poznan 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

P. Zięba 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/.

Volumes
Instructions for authors
Additional info

Select number

Content

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4

1 Contents 4/2023

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4

Download PDF Download RIS Download Bibtex

2 Application of fuzzy type II multi-layer Kalman filter for parameters identification of two-mass drive system

Kacper Śleszycki , Karol Wróbel , Krzysztof Szabat , Seiichiro Katsura

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e146107 | DOI: 10.24425/bpasts.2023.146107

Keywords: electrical drives torsional vibration state estimation Kalman filter multi-layer estimator

Download PDF Download RIS Download Bibtex

Abstract

The paper describes a novel online identification algorithm for a two-mass drive system. The multi-layer extended Kalman Filter (MKF) is proposed in the paper. The proposed estimator has two layers. In the first one, three single extended Kalman filters (EKF) are placed. In the second layer, based on the incoming signals from the first layer, the final states and parameters of the two-mass system are calculated. In the considered drive system, the stiffness coefficient of the elastic shaft and the time constant of the load machine is estimated. To improve the quality of estimated states, an additional system based on II types of fuzzy sets is proposed. The application of fuzzy MKF allows for a shorter identification time, as well as improves the accuracy of estimated parameters. The identified parameters of the two-mass system are used to calculate the coefficients of the implemented control structure. Theoretical considerations are supported by simulations and experimental tests.

Go to article

Authors and Affiliations

Kacper Śleszycki

e-mail:

ORCID:

Karol Wróbel

e-mail:

ORCID:

Krzysztof Szabat

e-mail:

ORCID:

Seiichiro Katsura

e-mail:

ORCID:

Wrocław University of Science and Technology, Institute of Electrical Machines, Drives and Measurements, Wrocław, Poland
Keio University, Department of System Design Engineering, Tokyo, Japan

3 Anonymous traffic classification based on three-dimensional Markov image and deep learning

Xin Tang , Huanzhou Li , Jian Zhang , Zhangguo Tang , Han Wang , Cheng Cai

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e145676 | DOI: 10.24425/bpasts.2023.145676

Keywords: anonymous network traffic classification three-dimensional Markov image output self-attention deep learning

Download PDF Download RIS Download Bibtex

Abstract

Illegal elements use the characteristics of an anonymous network hidden service mechanism to build a dark network and conduct various illegal activities, which brings a serious challenge to network security. The existing anonymous traffic classification methods suffer from cumbersome feature selection and difficult feature information extraction, resulting in low accuracy of classification. To solve this problem, a classification method based on three-dimensional Markov images and output self-attention convolutional neural network is proposed. This method first divides and cleans anonymous traffic data packets according to sessions, then converts the cleaned traffic data into three-dimensional Markov images according to the transition probability matrix of bytes, and finally inputs the images to the output self-attention convolution neural network to train the model and perform classification. The experimental results show that the classification accuracy and F1-score of the proposed method for Tor, I2P, Freenet, and ZeroNet can exceed 98.5%, and the average classification accuracy and F1-score for 8 kinds of user behaviors of each type of anonymous traffic can reach 93.7%. The proposed method significantly improves the classification effect of anonymous traffic compared with the existing methods.

Go to article

Authors and Affiliations

Xin Tang

1 2

Huanzhou Li

1 2

Jian Zhang

1 2

Zhangguo Tang

1 2

Han Wang

1 2

Cheng Cai

1 2

School of Physics and Electronic Engineering, Sichuan Normal University, Chengdu 610101, Sichuan, China
Institute of Network and Communication Technology, Sichuan Normal University, Chengdu 610101, Sichuan, China

4 Research on communication emitter identification based on semi-supervised dimensionality reduction in complex electromagnetic environment

Wei Ge , Lin Qi , Lin Tong , Jun Zhu , Jing Zhang , Dongyang Zhao , Ke Li

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e145766 | DOI: 10.24425/bpasts.2023.145766

Keywords: communication emitter identification feature extraction dimensionality reduction VMD ESDA

Download PDF Download RIS Download Bibtex

Abstract

The individual identification of communication emitters is a process of identifying different emitters based on the radio frequency fingerprint features extracted from the received signals. Due to the inherent non-linearity of the emitter power amplifier, the fingerprints provide distinguishing features for emitter identification. In this study, approximate entropy is introduced into variational mode decomposition, whose features performed in each mode which is decomposed from the reconstructed signal are extracted while the local minimum removal method is used to filter out the noise mode to improve SNR. We proposed a semi-supervised dimensionality reduction method named exponential semi-supervised discriminant analysis in order to reduce the high-dimensional feature vectors of the signals, and LightGBM is applied to build a classifier for communication emitter identification. The experimental results show that the method performs better than the state-of-the-art individual communication emitter identification technology for the steady signal data set of radio stations with the same plant, batch and model.

Go to article

Authors and Affiliations

Wei Ge

1 2

e-mail:

ORCID:

Lin Qi

1 2

e-mail:

ORCID:

Lin Tong

1 2

Jun Zhu

1 2

Jing Zhang

1 2

Dongyang Zhao

Ke Li

1 2

e-mail:

ORCID:

School of Information & Computer Science, Anhui Agricultural University, Hefei, Anhui, 230036, China
Information Materials and Intelligent Sensing Laboratory of Anhui Province, Anhui University, Hefei, Anhui, 230601, China
Shenzhen Institute for Advanced Study, University of Electronic Science and Technology of China, ShenZhen, GuangDong, 518000, China

5 Existence, uniqueness and parameter perturbation analysis results of a fractional integro-differential boundary problem

Nan Zhang , Lingling Zhang , Mercy Ngungu , Adejimi Adeniji , Emmanuel Addai

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e145938 | DOI: 10.24425/bpasts.2023.145938

Keywords: existence and uniqueness stability analysis parameter perturbation fractional differential equation integro-differential boundary condition

Download PDF Download RIS Download Bibtex

Abstract

In the formulation, the existence, uniqueness and stability of solutions and parameter perturbation analysis to Riemann-Liouville fractional differential equations with integro-differential boundary conditions are discussed by the properties of Green’s function and cone theory. First, some theorems have been established from standard fixed point theorems in a proper Banach space to guarantee the existence and uniqueness of positive solution. Moreover, we discuss the Hyers-Ulam stability and parameter perturbation analysis, which examines the stability of solutions in the presence of small changes in the equation main parameters, that is, the derivative order η, the integral order β of the boundary condition, the boundary parameter ξ , and the boundary value τ. As an application, we present a concrete example to demonstrate the accuracy and usefulness of the proposed work. By using numerical simulation, we obtain the figure of unique solution and change trend figure of the unique solution with small disturbances to occur in different kinds of parameters.

Go to article

Authors and Affiliations

Nan Zhang

e-mail:

ORCID:

Lingling Zhang

e-mail:

ORCID:

Mercy Ngungu

Adejimi Adeniji

Emmanuel Addai

College of Mathematics, Taiyuan University of Technology, 030024, TaiYuan, Shanxi, ChinaCollege of Mathematics, Taiyuan University of Technology, 030024, TaiYuan, Shanxi, China
College of Mathematics, Taiyuan University of Technology, 030024, TaiYuan, Shanxi, China
Human Sciences Research Council (HSRC), South Africa
Tshwane university of Technology, South Africa

6 Influence of modelling phase transformations with the use of LSTM network on the accuracy of computations of residual stresses for the hardening process

Joanna Wróbel , Adam Kulawik

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e145681 | DOI: 10.24425/bpasts.2023.145681

Keywords: RNN network hardening process temperature phase transformations in the solid state effective stresses numerical modelling

Download PDF Download RIS Download Bibtex

Abstract

Replacing mathematical models with artificial intelligence tools can play an important role in numerical models. This paper analyses the modeling of the hardening process in terms of temperature, phase transformations in the solid state and stresses in the elastic-plastic range. Currently, the use of artificial intelligence tools is increasing, both to make greater generalizations and to reduce possible errors in the numerical simulation process. It is possible to replace the mathematical model of phase transformations in the solid state with an artificial neural network (ANN). Such a substitution requires an ANN network that converts time series (temperature curves) into shares of phase transformations with a small training error. With an insufficient training level of the network, significant differences in stress values will occur due to the existing couplings. Long-Short-Term Memory (LSTM) networks were chosen for the analysis. The paper compares the differences in stress levels with two coupled models using a macroscopic model based on CCT diagram analysis and using the Johnson-Mehl-Avrami-Kolmogorov (JMAK) and Koistinen-Marburger (KM) equations, against the model memorized by the LSTM network. In addition, two levels of network training accuracy were also compared. Considering the results obtained from the model based on LSTM networks, it can be concluded that it is possible to effectively replace the classical model in modeling the phenomena of the heat treatment process.

Go to article

Authors and Affiliations

Joanna Wróbel

Adam Kulawik

e-mail:

ORCID:

Department of Computer Science, Czestochowa University of Technology, Dabrowskiego 73, 42-201 Czestochowa, Poland

7 Smart network anomaly detection software architecture for network-enabled ubiquitous devices

Mariusz Pelc , Dawid Galus , Mariusz Gola , Aleksandra Kawala-Sterniuk

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e146285 | DOI: 10.24425/bpasts.2023.146285

Keywords: network anomaly/threats detection smart systems policy-based computing

Download PDF Download RIS Download Bibtex

Abstract

In this paper we present an architecture for run-time reconfiguration of network-enabled ubiquitous devices. The whole idea is based on a policy-based system where the whole decision-making (e.g. anomaly detection-related) logic is provided in a form of an externally loaded policy file. The architecture is verified through real-life implementation on an embedded system whose sensitivity can be easily modified should a need arise in run-time without affecting network device/segment (and thus potentially a number of network services) so that they continue working while the re-configuration process is triggered.

Go to article

Authors and Affiliations

Mariusz Pelc

1 2

e-mail:

ORCID:

Dawid Galus

e-mail:

ORCID:

Mariusz Gola

e-mail:

ORCID:

Aleksandra Kawala-Sterniuk

e-mail:

ORCID:

Faculty of Electrical Engineering, Automatic Control and Informatics, Opole University of Technology, Opole, Poland
School of Computing and Mathematical Sciences, University of Greenwich, London, UK

8 Investigations of the turbulent thermo-fluid performance in a circular heat exchanger with a novel flow deflector-type baffle plate

Md Atiqur Rahman , Sushil Kumar Dhiman

Bulletin of the Polish Academy of Sciences Technical Sciences | 2023 | 71 | 4 | e145939 | DOI: 10.24425/bpasts.2023.145939

Keywords: thermo-fluid performance flow resistance swirl flow re-circulation trapezoidal deflector inclination angle

Download PDF Download RIS Download Bibtex

Abstract

An axial flow tubular heat exchanger has been experimentally investigated to augment the heat transfer rate with a novel swirl flow of air past the heated tubes. The novel design has been based on circular baffle plates provided with trapezoidal air deflectors of various inclination angles. The arrangement of tubes is kept the same throughout the experiment, in accordance with the longitudinal airflow direction. The tubes maintained a constant heat flux condition over the surface. Four deflectors with equal inclination angles were developed on each baffle plate, generating air swirl inside a circular duct carrying the heated tubes that increase air-side turbulence and, consequently, the surface heat transfer rate. The baffle plates were placed equidistant from each other at variable pitch ratios. The Reynolds number was kept in the range of 16000– 2800