Wyniki wyszukiwania - BazTech

1

The Impact of the KPI System on Employee Motivation to Improve Skills and Work Effectiveness in a Ship Management Company

Łączyński Tomasz, Przybyłowski Piotr

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2025

|

Vol. 19 No. 1

69--73

EN

The aim of this article is to analyse the impact of the KPI (Key Performance Indicators) system on employee motivation in terms of developing competences and improving work effectiveness. The research was conducted on a sample of 114 employees using a questionnaire based on a Likert scale. The one-factor ANOVA technique was used to analyse the results. The results clearly showed that high awareness of the role of the KPI system, regular feedback, knowledge of goals and appropriate support and resources have a significant impact on the level of employee motivation to develop their own skills and improve work performance. The article discusses both theoretical aspects and practical implications of the results that can constitute a basis for improving the quality of management based on KPI indicators in a ship management company.

2

An Assessment of Long-term Spatial Agnosticism of GNSS Positioning Degradation Risks Due to Ionospheric Conditions

Sikirica Nenad, Hedji Ivan, Mikša Marko, Brčić David, Ciriković Enes, Filjar Renato

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2025

|

Vol. 19 No. 1

85--89

EN

The Global Navigations Satellite Systems (GNSS) have been evolved into an essential infrastructure of modern civilisation, a public goods, and enabler of rapidly growing number of technology and socio-economic applications. However, GNSS applications often lack fundamental details on GNSS Positioning, Navigation, and Timing (PNT services performance to define and determine their Quality of Service (QoS). The lack of alignment with the core GNSS PNT deprives GNSS applications of assessing the risks of the GNSS PNT utilisation, thus leaving GNSS applications unable to prepare alternatives and mitigate the causes of GNSS PNT performance disruptions. Here we contributed to solution of the problem with the introduction and long-term performance assessment of the risk model of ionospheric-caused GNSS positioning degradation. Called the Probability of Occurrence (PoO), our team defined the risk model of GNSS positioning degradation caused by ionospheric conditions based on the long term observations of occurrences of degraded GNSS positioning performance. In the process of the GNSS risk model validation, the long-term PoO risk models are developed using the annual 2014 stationary GNSS horizontal positioning error observations derived from the GNSS pseudoranges collected at the International GNSS Service (IGS) reference stations situated in polar (Iqaluit, Canada) and sub-equatorial regions (Darwin, Australia). Two GNSS risk models are compared for similarity using statistical methods of Hausdorff distance and Cramér–von Mises statistical test. Research results show that two GNSS risk models are spatially agnostic, since no significant difference in two long-term GNSS risk models is found. The research results supports the conclusion of generality of the PoO GNSS risk model, and its ability to serve GNSS applications developers, operators, and users in determination of the QoS of particular GNSS applications.

3

The importance of smart technology solutions for sustainable logistics in Poland

Pyra Mariusz, Paužuolienė Jurgita, Kaveckė Ieva

LogForum

|

2025

|

Vol. 21, no 1

35--46

EN

Background: This article examines the impact of smart technology implementation on sustainable development practices within Polish logistics companies. In recent years, technologies supporting the optimization of logistics processes-such as route planning systems, real-time data analysis, and warehouse automation-have become increasingly important. The adoption of these technologies enables companies to manage resources more efficiently, while also reducing emissions and energy consumption. The main objective of this article is to investigate whether the adoption of such technologies correlates with higher levels of pro-environmental activities and greater commitment to corporate social responsibility (CSR), taking into account the specific characteristics of the Polish logistics market. Methods: The study employed descriptive statistics, Spearman's rank correlation, linear regression, Fisher's Z-transformation, and tests of normality and homogeneity of variance. Data were collected from 60 logistics companies, and selected through stratified random sampling based on company size, market of operation, and years of operation in the market. Indicators of technology use and sustainability were calculated to assess the extent of technology adoption and companies' commitment to sustainability. Building on this, statistical tests were performed to assess the strength and significance of the relationship between technology adoption and sustainability practices. Additionally, difference-in-differences analyses were conducted between subgroups identified by company size and business scope to assess the impact of these characteristics on the relationship between technology adoption and sustainability. Results: The analysis revealed a statistically significant positive correlation between the adoption of smart technologies and sustainability efforts. Companies operating in international markets, as well as those with more advanced technology implementations, demonstrated stronger sustainability performance. Regression analysis showed that the deployment of technology was a significant predictor of variation in sustainability practices among the surveyed companies. Further subgroup analysis suggested that the relationship between technology deployment and sustainability was stronger in larger companies and those with international operations. Conclusions: The findings suggest that smart technologies are playing a key role in enhancing the sustainability of the logistics sector in Poland, with their impact likely to be more pronounced in larger and internationally operating companies. For policymakers, this highlights the potential benefits of investing in technology to support sustainability goals and emphasizes the need for strategies tailored to the specific characteristics of companies.

4

Prediction and control of ground vibrations due to blasting activities in aggregate mines

Bulushi Iddi Ramadhani, Deressa Geleta Warkisa, Choudhary Bhanwar Singh

Journal of Sustainable Mining

|

2025

|

Vol. 24, iss. 2

267--281

EN

Predicting and controlling ground vibrations from blasting is crucial for protecting structures andminimizing environmental impacts. This study investigates how explosive quantity and scaled distances affect peak particle velocity and establishes empirical equations to estimate this velocity at different distances from the blast area. The study found that the maximum charge per delay at a peak particle velocity of 10 mm/s was reduced to 13.46% as the delay timing was increased from 0 to 25 ms and 9.99% from 0 to 50 ms delay timing. The reduction of maximum charge with increasing delay timing leads to the reduction of ground vibration. The developed model is validated with statistical analysis and field data, offering practical tools for optimizing blast designs to reduce ground vibrations. Blast monitoring data showed that over 98% of events had frequencies above 8 Hz, leading the study to use peak particle velocity thresholds of 10 mm/s and 15 mm/s. The statistical analysis showed a strong correlation between predicted and observed peak particle velocity for delay durations. The coefficient of determination was 0.83, 0.89, and 0.90 for 0, 25 ms, and 50 ms delay timings, respectively, underscoring the precision and reliability of the predictive models.

5

Analysis of Groundwater Temperature in Urban Conditions - the Case of Wrocław, Poland

Hajnrych Monika, Blachowski Jan, Worsa-Kozak Magdalena

Civil and Environmental Engineering Reports

|

2025

|

Vol. 35, no. 1

213--229

EN

With increasing urbanization, it is becoming important to study the impact of human activity and climate change on the underground environment, including groundwater temperatures. The subsurface urban heat island (SubUHI) is one of the effects of these changes, which consists in increasing the temperature of soil and groundwater in urban areas. This article analyses groundwater temperatures in Wrocław in 2022–2024. The research was conducted at 19 measurement points. The average groundwater temperature was 12.7°C, with values from 8.9°C to 25.4°C. The highest temperatures were recorded in the city center, and the lowest on its western outskirts. Spatial analysis showed higher temperatures in the city center, related to the influence of underground infrastructure and artificial surfaces. At a depth of 15 meters, the influence of external factors on groundwater temperature disappeared. The results indicate the need for further research on local factors influencing groundwater temperature, which may be important for water resource management in cities.

6

Identification of threats affecting the risk of urban regeneration of post-industrial areas

Apollo Magdalena, Rzepecki Łukasz

Archives of Civil Engineering

|

2025

|

Vol. 71, nr 1

327--345

EN

One of the main problems of highly urbanized areas is progressively degrading land. This process is mainly caused by the closure of enterprises that have failed to adapt to the realities of the economy and the lack of investment. Post-industrial areas are usually large, diverse, and polluted complexes that may have historical and locational value. Currently, there is a growing interest among European city authorities in this type of land, which can be revitalized to create, i.e., leisure and recreation areas. The need to preserve cultural values, while adapting the space to the new reality, requires verification of risk factors affecting the urban regeneration process. In this article, the authors attempt to create a ranking of the risk factors of post-industrial area urban regeneration. A statistical analysis was conducted preceded by the collection of data in the form of assessments of the probability and severity of the identified urban regeneration risk factors. This ranking was created to identify the key factors for urban regeneration risk estimation. The analysis conducted revealed that the most significant urban regeneration risk factors are related to, i.e., poor technical condition of buildings and structures, environmental degradation, as well as logistical problems.

PL

Jednym z głównych problemów obszarów wysoce zurbanizowanych jest pojawianie się terenów, które ulegają stopniowej degradacji. Proces ten spowodowany jest przede wszystkim likwidacją przedsiębiorstw, które nie zdołały przystosować się do realiów gospodarki oraz brakiem nakładów inwestycyjnych. Obszary poprzemysłowe to zwykle duże, zróżnicowane i zanieczyszczone kompleksy związane głównie z przemysłem lekkim i ciężkim posiadające często walory historyczne i lokalizacyjne. Obecnie zauważa się wzrost zainteresowania władz europejskich miast tego typu terenami, które mogą zostać zrewitalizowane, tworząc m.in. miejsca wypoczynku i rekreacji. Szczególnym przypadkiem obszarów poprzemysłowych są całe dzielnice miast, które oprócz struktur przemysłowych pełnią także funkcje mieszkaniowe czy usługowe. Przykładem tego rodzaju struktury jest Letnica, będąca dzielnicą Gdańska. Pomimo dogodnej lokalizacji, występowały tu stagnacja gospodarcza, problemy infrastrukturalne, przestrzenne i społeczne. Jednym z poważniejszych problemów Letnicy była degradacja w wymiarze technicznym. Zespół robotniczej zabudowy mieszkaniowej, wzniesiony na przełomie XIX i XX wieku, oraz infrastruktura przed rozpoczęciem rewitalizacji znajdowała się w bardzo złym stanie technicznym. Ponad 60% wszystkich budynków dzielnicy posiadała wartości kulturowe, które ulegały stopniowemu niszczeniu i zanikały ze względu na brak działań renowacyjnych. Konieczność zachowania wartości kulturowych, a jednocześnie przystosowania przestrzeni do nowej rzeczywistości, zmusza do weryfikacji zagrożeń mających wpływ na proces rewitalizacji. W artykule autorzy podejmują próbę utworzenia rankingu zagrożeń rewitalizacji obszaru poprzemysłowego. Przeprowadzono analizę statystyczną poprzedzoną zebraniem danych w postaci ocen prawdopodobieństwa oraz skutków zaistnienia zidentyfikowanych czynników ryzyka rewitalizacji. Ranking ten utworzono w celu wskazania czynników, które są kluczowe w kontekście szacowania ryzyka rewitalizacji. Biorąc pod uwagę przeprowadzoną analizę statystyczną należy stwierdzić, że powstały ranking odzwierciedla rzeczywisty poziom istotności poszczególnych czynników ryzyka rewitalizacji obszaru poprzemysłowego. Wyniki przeprowadzonych badań wskazują ponadto, iż zakłócenia w realizacji zadań budowlanych spowodowane są m.in. następującymi przyczynami: · napięty harmonogram i ograniczony czas realizacji procesów budowlanych,· problemy z komunikacją i przepływem aktualnych oraz wiarygodnych informacji, · realizacja nietypowych robót i unikatowych rozwiązań, · problemy logistyczne wynikające z jednoczesnej obecności na placu budowy inwestora, wykonawcy, podwykonawcy, mieszkańców dzielnicy. Genezą większości zaistniałych problemów okazał się brak dogłębnej analizy źródeł i czynników ryzyka. Niektóre spośród przyczyn skutkujących opóźnieniami działań podejmowanych na placu budowy i zwiększeniem kosztów, były efektem niemożliwych do przewidzenia błędów popełnionych na etapie planowania. Pozostałe spowodowane były tzw. „czynnikiem ludzkim”, przejawiającym się między innymi zaniedbaniami, niedopatrzeniami, brakiem kompetencji oraz przekazywaniem nieaktualnych i nie w pełni zweryfikowanych informacji.

7

Planning the natural development of a peripheral vertex on the example of a regional airport in Central Europe

Wawrzosek Jacek, Zarajczyk Janusz, Ignaciuk Szymon

Advances in Science and Technology. Research Journal

|

2025

|

Vol. 19, no. 7

377--393

EN

In this paper, a young airport in Central Europe is presented as a peripheral node of a complex network, subject to Luce's natural laws of development. Research conducted since the late 1990s has focused on creating models that apply to the entire network. Even the development of the most important nodes of a complex network, the so-called hubs, is considered as a consequence of the topology of the entire network. The paper considers what laws and models can be applied to a single, peripheral network node, compared to the widely used exponential models. The presented analysis of the dynamics of the scheduled traffic at the Lublin Airport allows for forecasting its further development. Thus, the methods proposed here for the case study of a regional airport enable us to specify a forecast for the further development of any peripheral vertex of a complex network of a transportation system. On the basis of this analysis, it was pointed out, among others, that seasonality expressing the dynamics of a complex network, so far expressed in statistics using the time series method can also be approached in the Elliot waves terminology and used to predict the profitability of a regional airport. It was also established, that since 2015 the regional demand for civil aviation operations in the General Aviation category has been saturated at the Lublin Airport, reaching the level of 1750 operations per year.

8

Monte Carlo validation of the pairwise comparisons method accuracy improvement for 3D objects

Koczkodaj Waldemar W., Kułakowski Konrad, Lau Meng Cheng, Pedrycz Witold, Pigazzini Alexander, Song Yingli, Strzałka Dominik, Żądło Tomasz

Advances in Science and Technology. Research Journal

|

2025

|

Vol. 19, no. 6

194--202

EN

A Monte Carlo study of the pairwise comparisons method has been designed to validate the accuracy improvement by the pairwise comparisons method for 3D objects. For this, not-so-irregular objects were randomly selected. It is important to emphasize that this study focuses on testing the accuracy of the method rather than the users’ skills. The users’ inability to assess the volume of unrestricted random objects (e.g., a porcupine) would only deviate the results. As a side product, semi-randomly generated 3D objects can also be useful in many other research areas, such as software validation and verification, microeconomics (consumer preferences for products), computer entertainment, and even agriculture (selecting of fruits and vegetables). Further generalizations incorporating additional dimensions, as a comparison of different investment opportunities, can be useful, for example in enhancing financial decision-making processes.

9

Scale effects and spatial distribution characteristics of 3D roughness of natural rock fracture surfaces: statistical analysis

Huan Jiuyang, He Mingming, Wan Zhiwen, Li Meishu, Pan Hengfei, Hu Mengdie

Acta Geophysica

|

2025

|

Vol. 73, no. 1

83--103

EN

The roughness feature of a natural rock fracture surface is an important factor affecting the shear and poromechanical behavior of rock. The scale effect and spatial distribution characteristics of the fracture surface roughness are notable challenges at rock engineering sites. In this article, morphological data of a large-scale field rock fracture surface were collected using a 3D scanner. Then, the original surface was divided into several small fracture surfaces. With the use of a 2D roughness statistical index, the 2D roughness (JRC2D) of the fracture profile was evaluated. The 3D roughness (JRC3D) of the fracture surface along different directions was obtained via the weighted averaging method. Based on four oblique analysis schemes, the elevation statistical trend and roughness scale effect of fracture surfaces with different widths were examined. With increasing fracture size, the average elevation (^) and the standard deviation of elevation (a) showed different typical change patterns. The impact of size variation on the fracture surface roughness includes four types and exhibits significant anisotropy. Based on small fissure surfaces without mutual coverage, the spatial distribution characteristics of the fracture roughness were analyzed and were proven to exhibit high dispersion and anisotropy. With increasing width of the analyzed small fracture, the roughest position on the fracture surface basically remained the same, but there was a significant change in roughness anisotropy.

10

Stochastic fire brigade intervention model

Kuziora Łukasz, Gałaj Jerzy

Zeszyty Naukowe SGSP / Szkoła Główna Służby Pożarniczej

|

2024

|

Nr 91 (tom 1)

107--131

EN

The article is a continuation of a previously published paper, which, based on an analysis of available global literature, provides an overview of firefighting operational models. It outlines the concept of a stochastic model, which was implemented in the Aamks software to assess the fire risk of buildings, developed several years ago and systematically further expanded at the Fire University. It consists of four main time modules: the time of notifying about a fire, the time from receiving information about an incident until the moment of dispatch, the time of arriving at the scene of the incident and the time from the moment of arrival to the moment of starting firefighting activities. Their majority were determined in a probabilistic way, while some of them, such as the fire monitoring notification system and selected elements of the final stage, were assessed in a deterministic way. The paper discusses methods of their estimation, particularly in terms of the used data. The developed model consists of two main action phases, each subdivided into smaller stages, the sum of which gives the time taken to undertake extinguishing actions. This time is presented as a probability distribution. The first phase, i.e. the notification of the incident, is variable and depends on the equipment of the building with detection devices. As a result of the variability of the first phase of action, three different but invariable paths have been identified. The results in the form of extinguishing action times, along with the probabilities for each variant, are presented in three result tables at the end of the article.

11

Analysis of thermal energy consumption management of energy-intensive enterprises

Widera Katarzyna, Gąsior Rafał, Smoliński Adam

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2024

|

z. 202

591--604

EN

Purpose: The purpose of this study is to analyze and evaluate the consumption of thermal energy in a coal mining enterprise with separate business units, in the context of securing energy reserves and effectively managing the consumption of this energy. Design/methodology/approach: Based on the aggregation and analysis of historical data of thermal energy consumption, the method of statistical analysis of aggregated data from individual business units of the coal mining company was applied. Findings: The applied statistical analysis of the aggregate data made it possible to verify the planned short- and long-term activities for each group of facilities of the coal mining company. Research limitations/implications: The further direction of the research requires verification of the obtained results of the statistical analysis, after completing the data of thermal energy consumption in the following years and correlating the obtained results with the introduced pro¬efficiency measures in the enterprise so as to clarify the division of the enterprise's facilities into individual groups. Practical implications: Statistical analysis of thermal energy consumption, can become an effective tool to support the process of managing pro-efficiency measures in mining enterprises with separate business units. Social implications: The right approach of coal mining companies to thermal energy analysis and management can contribute to securing energy reserves for the local environment in which the company operates. Originality/value: The presented classification of facilities into groups A, B and C and the use of statistical analysis to verify the introduced measures to reduce thermal energy consumption have not yet been introduced and tested in the Polish coal mining industry.

12

Analysis of lean manufacturing knowledge correlation models for India and the USA

Podloch Iwo, Kocjan Jakub, Nowacki Krzysztof

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2024

|

z. 198

427--439

EN

Purpose: This article presents the findings of a statistical study that used surveys to collect data from English-speaking countries and India, where English is widely used as a common language. The surveys aimed to understand the knowledge, attitudes, and awareness of production management systems among employees at selected plants of a multinational automotive corporation. Statistical analysis was used to identify relationships within the "knowledge" subgroup of the data, and a detailed expert study was conducted based on the results. The study not only describes the identified correlations but also provides recommendations on how to enhance the performance of areas with low knowledge scores by leveraging these correlation. Design/methodology/approach: Based on responses collected in a survey based on the Lickert scale in research groups. Using scale reliability analysis with the -Cronbach test and the Nunali criterion reliability, statistically significant pairs of correlations were defined and subjected to further expert analysis. Findings: Based on the correlation analysis, a higher level of understanding of Lean Manufacturing issues was noticed in India than in the USA, and in both study groups there was a relationship proving that the use of Lean tools was perceived not as work improvement but as additional work.

13

Review of ocean wave’s uncertainties for navigators

Žiha Kalman

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2024

|

Vol. 18 No. 4

873--882

EN

The uncertainties of marine environments lastingly challenge navigation and safety of sea transportation. Therefore, the article tackles the extraction, assessment, and analysis as well as the perceptive presentations of probabilistic uncertainties of the random wind waves ocean-wide. The link of the probabilistic uncertainties and statistical variabilities is accomplished in the article by using the reported Global Wave Statistics of coherent and controlled wind wave data visually observed from ships in normal service. The probabilistic uncertainty is defined in the information theory most coherently with the human experience of randomness by the information entropy. The article reveals expressions, tables, graphs, and charts of information entropy which objectively express the uncertainties of observed wind wave directions, heights, and periods in all principal ocean areas. The combinations of areal entropy provide uncertainties of wider ocean zones, sectors, and shipping routes for the assessment of all-around exposures of ships and other objects in service at seas to random wind wave effects appropriately to sea-men’s experience of randomness.

14

Create a statistical model to show the relationship between the types and numbers of ships used green fuel frequenting Saudi ports and their impact on port profitability

Elentably Akram, van Essen Pieter, Fahad Ayman Bin, Aljahdly Bassam Bin Saleh

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2024

|

Vol. 18 No. 3

511--517

EN

The shipping industry's significant contribution to global air pollution, estimated at 13% of man-made carbon dioxide emissions, has spurred shipping companies to embrace green fuels like LNG and biofuels. However, their higher costs pose a challenge to their adoption. This study presents a statistical model that demonstrates the relationship between green fuel use by ships visiting Saudi ports and port profitability. Leveraging data from the Saudi Ports Authority and the International Maritime Organization, the model establishes a positive correlation between green fuel usage and port profitability. This correlation stems from green fuel's environmental benefits, which translate into lower operating costs and increased revenues for ports. The model empowers port authorities in making informed decisions to attract vessels utilizing green fuels. By promoting the adoption of sustainable practices, ports can not only enhance their environmental standing but also improve their financial resilience.

15

Analysis of computer network statistics for identifying stability-disrupting information flows in military local networks

Tanriverdiyev Elshan

Studia Bezpieczeństwa Narodowego

|

2024

|

R. 14, Nr 34

77--89

EN

The increasing complexity and scope of military computer networks necessitate robust methods to ensure network stability and security. This study presents a comprehensive analysis of computer network statistics in military local networks to develop a method for detecting information flows that disrupt stability. By leveraging advanced statistical techniques and machine learning algorithms, this research aims to enhance the cybersecurity posture of military local networks globally. Military networks are vital for communication, data exchange, and operational coordination. However, the dynamic nature of network traffic and the persistent threat of cyberattacks pose significant challenges to maintaining network stability. Traditional monitoring techniques often fail to meet the unique requirements of military networks, which demand high levels of security and rapid response capabilities. This study employs a multi-faceted approach to detect anomalies in network traffic, utilizing statistical methods such as Z-score analysis, Principal Component Analysis (PCA), and Autoregressive Integrated Moving Average (ARIMA) models. Machine learning techniques, including SupportVector Machines (SVM), Random Forests, Neural Networks, K-means clustering, and Reinforcement Learning, are also applied to identify patterns indicative of stability-disrupting information flows. The integration of statistical and machine learning methods forms a hybrid model that enhances anomaly detection, providing a robust framework for network security. The research problem is formulated as follows: does data collection include comprehensive network traffic data from various segments of military local area networks, including packet flows, transmission rates, and error rates over a specified period? Statistical analysis identifies patterns in the network traffic, which are then used to train machine learning models to classify normal and abnormal traffic. The research hypothesis states that machine learning models achieve high accuracy in detecting stability-disrupting information flows, with a precision rate exceeding 90%. The models identified several instances of stability-disrupting events, correlating these with known security incidents to validate the effectiveness of the detection method. This study underscores the importance of continuous monitoring and analysis of network statistics to ensure stability and security. The proposed method can be integrated with existing network monitoring and intrusion detection systems, providing a comprehensive approach to network security. Future research can build on these findings to develop more sophisticated models and explore additional factors influencing network stability, including the incorporation of advanced machine learning techniques, such as deep learning, and the exploration of other network metrics, like latency and packet loss. This comprehensive approach aims to enhance the security and operational reliability of military local networks.

PL

Rosnąca złożoność i zakres wojskowych sieci komputerowych wymagają solidnych metod zapewniających stabilność i bezpieczeństwo sieci. Celem niniejszej pracy jest przedstawienie kompleksowej analizy statystyk sieci komputerowych w lokalnych sieciach wojskowych w celu opracowania metody wykrywania przepływów informacji, które zakłócają stabilność. Wykorzystując zaawansowane techniki statystyczne i algorytmy uczenia maszynowego, niniejsze badanie ma na celu poprawę postawy cyberbezpieczeństwa lokalnych sieci wojskowych na całym świecie. Sieci wojskowe są niezbędne do komunikacji, wymiany danych i koordynacji operacyjnej. Jednak dynamiczna natura ruchu sieciowego i ciągłe zagrożenie cyberatakami stanowią poważne wyzwanie dla utrzymania stabilności sieci. Tradycyjne techniki monitorowania często nie spełniają unikalnych wymagań sieci wojskowych, które wymagają wysokiego poziomu bezpieczeństwa i możliwości szybkiego reagowania. W niniejszym badaniu zastosowano wieloaspektowe podejście do wykrywania anomalii w ruchu sieciowym, wykorzystując metody statystyczne, takie jak analiza Z-score, analiza głównych składowych (PCA) i modele autoregresyjnej zintegrowanej średniej ruchomej (ARIMA). Techniki uczenia maszynowego, w tym maszyny wektorów nośnych (SVM), lasy losowe, sieci neuronowe, klasteryzacja K-means i uczenie wzmacniające, są również stosowane w celu identyfikacji wzorców wskazujących na przepływy informacji zakłócające stabilność. Integracja metod statystycznych i uczenia maszynowego tworzy hybrydowy model, który wzmacnia wykrywanie anomalii, zapewniając solidne ramy dla bezpieczeństwa sieci. Problem badawczy sformułowano w następujący sposób: czy zbieranie danych obejmuje kompleksowe dane o ruchu sieciowym z różnych segmentów wojskowych sieci lokalnych, w tym przepływy pakietów, szybkości transmisji i wskaźniki błędów w określonym okresie? Analiza statystyczna identyfikuje wzorce w ruchu sieciowym, które są następnie wykorzystywane do trenowania modeli uczenia maszynowego w celu klasyfikowania normalnego i nieprawidłowego ruchu. Hipoteza badawcza stwierdza, że modele uczenia maszynowego osiągają wysoką dokładność w wykrywaniu przepływów informacji zakłócających stabilność, ze współczynnikiem precyzji przekraczającym 90%. Modele zidentyfikowały kilka przypadków zdarzeń zakłócających stabilność, korelując je ze znanymi incydentami bezpieczeństwa w celu sprawdzenia skuteczności metody wykrywania. Niniejsze badanie podkreśla znaczenie ciągłego monitorowania i analizy statystyk sieci w celu zapewnienia stabilności i bezpieczeństwa. Proponowaną metodę można zintegrować z istniejącymi systemami monitorowania sieci i wykrywania włamań, zapewniając kompleksowe podejście do bezpieczeństwa sieci. Przyszłe badania mogą opierać się na tych ustaleniach, aby opracować bardziej wyrafinowane modele i zbadać dodatkowe czynniki wpływające na stabilność sieci, w tym włączenie zaawansowanych technik uczenia maszynowego, takich jak głębokie uczenie, oraz eksplorację innych metryk sieciowych, takich jak opóźnienie i utrata pakietów. To kompleksowe podejście ma na celu zwiększenie bezpieczeństwa i niezawodności operacyjnej wojskowych sieci lokalnych.

16

Wpływ popiołów lotnych na właściwości fizyczne zapraw w ujęciu statystycznym

Marczewska Julia, Jaworska-Wędzińska Monika, Jasińska Iga

Przegląd Budowlany

|

2024

|

R. 95, nr 7

171--174

PL

Unia Europejska nakłada surowe wymagania środowiskowe związane z ograniczeniem emisji CO2 do atmosfery. W artykule przedstawiono wyniki badań wytrzymałości na ściskanie zapraw cementowych po 28 dniach dojrzewania i po 170 dniach przebywania próbek w roztworze Na2SO4. Skład zapraw był opracowany na podstawie trójkąta Gibbsa, w którym zastosowano różną ilość popiołów lotnych. Uzyskane wyniki badań poddano analizie statystycznej w oparciu o simplexowy plan eksperymentów dla mieszanin trójskładnikowych. Przedstawione obliczenia statystyczne wykonano w środowisku obliczeniowym R w wersji 3.3.1. Badania statystyczne potwierdziły istotny wpływ popiołów lotnych na trwałość zapraw.

EN

The European Union imposes strict environmental requirements related to the reduction of CO2 emissions into the atmosphere. The article presents the results of testing the compressive strength of cement mortars after 28 days of curing and after 170 days of the samples remaining in the Na2SO4 solution. The composition of the mortars was developed on the basis of the Gibbs triangle, in which different amounts of fly ash were used. The obtained test results were subjected to statistical analysis based on a simplex experimental plan for three-component mixtures. The presented statistical calculations were performed in the R computing environment, version 3.3.1. Statistical tests confirmed the significant impact of fly ash on the durability of mortars.

17

Application of Point-Based Characteristics of Vibration Signals in the Detection of Railway Rail Damage

Łomżyńska Adrianna, Nowak Malwina Magdalena, Strugarek Klaudia, Ludwiczak Aleksander, Klekowicki Mikołaj, Szymański Grzegorz Marek

Problemy Kolejnictwa

|

2024

|

Z. 203

111--121

EN

This study investigates the application of vibration signal characteristics for the detection of railway track damage. The analysis focuses on vibrations generated by the bogie system during traversal of track sections under two distinct technical conditions. A comprehensive review of rail infrastructure and maintenance methodologies is provided, emphasizing the use of advanced diagnostic tools by track maintenance organizations. The research employs a point-based analysis of dimensional and dimensionless features of vibration signals. The results confirm the effectiveness of utilizing vibration signals recorded from a moving vehicle to identify track damage that may cause decrease of vehicle’s exploitation period.

18

The importance of selected demographic factors in municipal waste management

Klufová Renata, Skibiński Andrzej

Polish Journal of Management Studies

|

2024

|

Vol. 29, No. 1

161--181

EN

The publication presents the possibilities of using selected demographic variables as a source of knowledge to predict the amount of municipal waste. This may be important in the adaptation process of selecting the optimal technology for recycling and waste disposal. Therefore, the study aimed to determine the relationship of selected demographic variables with the generation of municipal waste based on the example of a pilot proprietary survey conducted in the Czech Republic. Advanced statistical methods were used in the pilot study to verify the research hypotheses. The presented research results clearly show that many parameters characterizing socio-demographic factors, such as age, disposable income or type of inhabited real estate, may be of great importance, affecting the amount of municipal waste and the effectiveness of its selective collection. In addition, the use of multivariate statistical analysis based on the CATPCA method made it possible to show in more detail the relationship between the age of the respondent and their approach to waste management.

PL

W publikacji przedstawiono możliwości wykorzystania wybranych zmiennych demograficznych jako źródła wiedzy do prognozowania ilości odpadów komunalnych. Może to mieć znaczenie w procesie adaptacyjnym wyboru optymalnej technologii recyklingu i unieszkodliwiania odpadów. Dlatego też celem badań było określenie związku wybranych zmiennych demograficznych z wytwarzaniem odpadów komunalnych na przykładzie pilotażowego, autorskiego badania ankietowego przeprowadzonego w Czechach. W badaniu pilotażowym wykorzystano zaawansowane metody statystyczne w celu weryfikacji postawionych hipotez badawczych. Zaprezentowane wyniki badań wyraźnie pokazują, że wiele parametrów charakteryzujących czynniki społeczno-demograficzne, takich jak wiek, dochód do dyspozycji czy rodzaj zamieszkałej nieruchomości, może mieć ogromne znaczenie, wpływając na ilość odpadów komunalnych i efektywność ich selektywnej zbiórki. Dodatkowo zastosowanie wieloczynnikowej analizy statystycznej opartej na metodzie CATPCA pozwoliło na bardziej szczegółowe ukazanie zależności pomiędzy wiekiem respondenta a jego podejściem do gospodarki odpadami.

19

Reliability of selected components of the pzl m28 bryza aircraft

Świergolik Szymon

Journal of KONBiN

|

2024

|

Vol. 54, iss. 3

117--146

PL

Rosnąca liczba operacji lotniczych, a co za tym idzie, zwiększone prawdopodobieństwo wystąpienia sytuacji niepożądanych wzmaga potrzebę prowadzenia badań nad aspektami niezawodności statków powietrznych. Niniejszy artykuł poświęcony jest niezawodności wybranych zespołów statku powietrznego PZL M28 Bryza, szeroko stosowanego w lotnictwie wojskowym i cywilnym. W artykule przedstawiono obiekt badań – samolot PZL M28 Bryza oraz metodykę badań, która miała na celu ocenę niezawodności jego kluczowych zespołów. Badania skupiają się na analizie awaryjności zespołów, takich jak: układ napędowy, płatowiec, urządzenia radioelektroniczne oraz osprzęt, z wykorzystaniem danych eksploatacyjnych. Wyniki pozwalają lepiej zrozumieć krytyczne aspekty wpływające na niezawodność samolotu PZL M28 Bryza, co jest istotne dla poprawy bezpieczeństwa i wydajności przeprowadzanych operacji lotniczych.

EN

The increasing number of flight operations, and the resulting increased likelihood of adverse situations, intensifies the need for research into aspects of aircraft reliability. This article is devoted to the reliability of selected assemblies of the PZL M28 Bryza aircraft, widely used in military and civil aviation. The article presents the research object, the PZL M28 Bryza aircraft, and the research methodology to assess the reliability of its key assemblies. The research focuses on analyzing the failure rate of such assemblies as the propulsion system, airframe, radioelectronic devices and on-board systems, using in-service data. The results provide a better understanding of the critical aspects affecting the reliability of the PZL M28 Bryza aircraft, which is important for improving the safety and efficiency of flight operations conducted.

20

Statistical Analysis of Urban Non-Point Source Pollution and Nitrate Contamination in the Groundwater at Thuckalay, Kanyakumari District, South India

Ramesh Bhagavathi Krishnan, Vanitha Sankararajan

Journal of Ecological Engineering

|

2024

|

Vol. 25, nr 6

271--291

EN

A statistical analysis of nitrate contamination in the groundwater at the Thuckalay area of Padmanabhapuram town, South India, is conducted using data collected from 2000 to 2019 that includes rainfall, groundwater level, and groundwater quality. The findings indicate that there was a rise in nitrate contamination in the groundwater between 2001 and 2011. This increase can be attributed directly to the 6.69% increase in population and the corresponding increase of 108.79 hectares in residential areas, which accounts for the 17% expansion. The elevated concentrations of EC (1830 µS/cm), Cl (511 mg/L), Na (210 mg/L), NO3 (150 mg/L), TH (420 mg/L), and precipitation (1,184) in 2011 may have an impact on the non-point source contamination in the subject area, which is caused by flowing water bodies. An investigation was conducted into the sources and regulating factors of elevated nitrate levels through the utilisation of cross plots and fitted line plots of NO3 in conjunction with other chosen hydrochemical parameters. Nitrate contamination of the groundwater is indicated by a positive Pearson correlation coefficient between NO3 and Ca, Cl, EC, Na, SAR, SO4, TH, TA, and WL. Furthermore, a nitrate pollution index greater than three signifies a higher degree of pollution during the years 2005, 2010, 2011, 2013 and 2014. The primary sources of nitrate contamination in the vicinity of the study area were human and animal refuse that was disposed of in open areas. This may be the result of increased fertiliser application on agricultural land. Restoring groundwater quality in the studied area is possible through periodic monitoring, regulation of polluting sources, and implementation of a natural, cost-effective redevelopment technique.