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Authors - 9566
Shynara Sarkambayeva
55682792800
Satyanand Singh
59195600100
L. D. Brassó
57222729386
Muhammad Suleman
57196800921
Publications - 6289
Advanced Examination Systems: Applying Fuzzy Logic and Machine Learning Methods in Education
Publication Name: Iccc 2025 IEEE 12th International Joint Conference on Cybernetics and Computational Cybernetics Cyber Medical Systems Proceedings
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: 231-235
Description:
In our paper, we present an innovative educational assessment system that attempts to overcome the limitations of traditional educational evaluation methods by applying machine learning, artificial intelligence, fuzzy logic, and advanced mathematical techniques. This system can provide a more objective and personalized assessment of students' knowledge. Current examination systems in educational institutions are outdated and do not meet modern societal and technological requirements. A central element of the system is the application of fuzzy logic, which allows for handling uncertainties in knowledge assessment. Using the FP-growth algorithm and the fuzzy analytical hierarchy process (AHP) aids in optimizing the evaluation process and enables a more profound analysis of students' performance. During the system's development, we aim to adaptively manage the difficulty level of questions, taking into account students' prior performance and individual capabilities. The study highlights the security risks and efficiency issues of current 'manual' question compilation methods. The new system aims to minimize these risks while improving the quality of education and reducing the workload of educators.
Open Access: Yes
Traffic Modelling and Emission Calculation: Integration of the COPERT Method into the PTV-VISUM Software
Publication Name: Applied Sciences Switzerland
Publication Date: 2026-01-01
Volume: 16
Issue: 2
Page Range: Unknown
Description:
The environmental impacts of road transport, in particular air pollution and noise, are receiving increasing attention in urban and regional planning, as they can not only predict vehicle movements but also provide detailed information on traffic volumes and speed distributions, which are indispensable for effective regulation, targeted interventions and health-conscious urban planning. This study presents an emission calculation module that can be integrated into traffic models and provides detailed estimates of pollutants emitted by road vehicles. The developed module builds on the COPERT methodology, which accounts not only for exhaust emissions such as (Formula presented.), (Formula presented.) and PM, but also for non-exhaust emissions from brake wear, tyre wear, road abrasion and evaporation. The presented system has an open architecture, enabling further customisation, particularly when local measured data are available. This contributes to building a stronger, data-driven link between transport planning and environmental protection.
Open Access: Yes
DOI: 10.3390/app16020567
Design and Implementation of a Modular Smart Home System Using ESP32 and Apple HomeKit Integration
Publication Name: Sisy 2025 IEEE 23rd International Symposium on Intelligent Systems and Informatics Proceedings
Publication Date: 2025-01-01
Volume: Unknown
Issue: Unknown
Page Range: 125-130
Description:
This paper presents a modular smart home system integrating ESP32 microcontrollers with Apple HomeKit ecosystem to address scalability and data retention challenges in residential IoT deployments. The proposed solution employs the HomeSpan library for HomeKit-Compatible accessories, enabling secure local communication while maintaining compatibility with Apple's Home application. The key scientific contribution lies in the hybrid architecture combining real-time HomeKit control with a dedicated REST API server featuring SSL encryption and API-key authentication for historical data collection. The system addresses Apple Home app's limitation of lacking data retention capabilities through automated 5-minute data transmission intervals to a secure MariaDB database. Performance evaluation demonstrates stable operation across multiple sensor types (DHT22, PIR motion sensors) and actuators with modular deployment flexibility. Comparative analysis shows improved data persistence and analytics capabilities over standard HomeKit implementations while maintaining the security benefits of local communication protocols. The implementation achieves practical IoT deployment suitable for residential environments with enhanced comfort, safety, and energy efficiency monitoring capabilities.
Open Access: Yes
Data-driven linear parameter-varying modelling of the steering dynamics of an autonomous car
Publication Name: IFAC Papersonline
Publication Date: 2021-07-01
Volume: 54
Issue: 8
Page Range: 20-26
Description:
Developing automatic driving solutions and driver support systems requires accurate vehicle specific models to describe and predict the associated motion dynamics of the vehicle. Despite of the mature understanding of ideal vehicle dynamics, which are inherently nonlinear, modern cars are equipped with a wide array of digital and mechatronic components that are difficult to model. Furthermore, due to manufacturing, each car has its personal motion characteristics which change over time. Hence, it is important to develop data-driven modelling methods that are capable to capture from data all relevant aspects of vehicle dynamics in a model that is directly utilisable for control. In this paper, we show how Linear Parameter-Varying (LPV) modelling and system identification can be applied to reliably capture personalised model of the steering system of an autonomous car based on measured data. Compared to other nonlinear identification techniques, the obtained LPV model is directly utilisable for powerful controller synthesis methods of the LPV framework.
Open Access: Yes
Effect of gibberellins on growth and biochemical constituents in Chlorella minutissima (Trebouxiophyceae)
Publication Name: South African Journal of Botany
Publication Date: 2019-11-01
Volume: 126
Issue: Unknown
Page Range: 92-98
Description:
A hormonal network regulates growth processes and stress responses in vascular plants. There is evidence for a similar hormonal network in microalgae. This study investigated the effect of exogenous gibberellins (GAs) on Chlorella minutissima Fott et Nováková growth and biochemical composition. Two bioactive GAs i.e. GA3 and GA4 were applied at 10−8–10−5 M. Growth was monitored until cultures were harvested on day 7 when in an exponential growth phase. Primary metabolites (protein, chlorophyll and carotenoids) were quantified and endogenous GAs and phenolic acids were identified and quantified. GA3 had little beneficial effect on growth in C. minutissima while GA4 was inhibitory. GA application had little effect on the protein, chlorophyll and total carotenoid content. Analysis of the GA content suggested that GA3 was not readily taken up by the cells while GA4 was absorbed but not further metabolised. This high accumulation of GA4 could account for its inhibitory effect. Three phenolics acids were detected in C. minutissima i.e. p-hydroxybenzoic acid > salicylic acid > protocatechuic acid. Their concentrations were not affected by GA treatments or GA-type. The physiological role of GAs in microalgae is still unclear and further studies are required to gain clearer insight into uptake rates, metabolism and function.
Open Access: Yes
The role of purpose in life as reflected in the indicators of body composition, fitness and quality of life in women working in the social sector
Publication Name: Orvosi Hetilap
Publication Date: 2021-07-01
Volume: 62
Issue: 27
Page Range: 1089-1098
Description:
Introduction: Professionals working in the social sector typically do significant overwork in rather unfavourable working conditions. Although the purpose in life is proved to determine the areas of career, health awareness, and the quality of life, the latter has not yet been confirmed among social workers. Objective: The purpose of this research is to demonstrate body composition and fitness status as well as the quality of life of female employees (n = 127) at a social institution, furthermore the decisive role purpose of life plays in these indicators. Method: Data were collected through questionnaires, tests, body composition analyses, and fitness status tests, and were assessed by t-test, analysis of variance and regression analysis. Results: Body composition of the participants indicates a generally overweight status, while fitness status, quality of life, and purpose of life are within the acceptable range, however, all with notable range values. Those with a higher-level purpose of life demonstrate better fitness indicators and higher quality of life. In terms of body composition, fitness, and quality of life, only a minor difference was found between those who do intellectual and physical type of work. Those who took sick leave demonstrated a lower level of fitness and quality of life compared to those who did not take any sick leave. Body composition and fitness status have proven to deteriorate with age. Conclusion: Previous research findings can be confirmed by stating that neither the body composition and fitness indicators, nor the quality-of-life level of social workers are optimal. The determining role of purpose in life has been proven in substantial aspects in this study. One of the focus areas of enhancing purpose in life is the workplace, where major positive impacts can be achieved in terms of the physical and mental health, well-being, and work performance.
Open Access: Yes
Artificial intelligence-based expert weighted quantum picture fuzzy rough sets and recommendation system for metaverse investment decision-making priorities
Publication Name: Artificial Intelligence Review
Publication Date: 2024-10-01
Volume: 57
Issue: 10
Page Range: Unknown
Description:
There should be some improvements to increase the performance of Metaverse investments. However, businesses need to focus on the most important actions to provide cost effectiveness in this process. In summary, a new study is needed in which a priority analysis is made for the performance indicators of Metaverse investments. Accordingly, this study aims to evaluate the main determinants of the performance of the metaverse investments. Within this context, a novel model is created that has four different stages. The first stage is related to the prioritizing the experts with artificial intelligence-based decision-making method. Secondly, missing evaluations are estimated by expert recommendation system. Thirdly, the criteria are weighted with Quantum picture fuzzy rough sets-based (QPFR) M-Step-wise Weight Assessment Ratio Analysis (SWARA). Finally, investment decision-making priorities are ranked by QPFR VIKOR (Vlse Kriterijumska Optimizacija Kompromisno Resenje). The main contribution of this study is the integration of the artificial intelligence methodology to the fuzzy decision-making approach for the purpose of computing the weights of the decision makers. Owing to this condition, the evaluations of these people are examined according to their qualifications. This situation has a positive contribution to make more effective evaluations. Organizational effectiveness is found to be the most important factor in improving the performance of metaverse investments. Similarly, it is also identified that it is important for businesses to ensure technological improvements in the development of Metaverse investments. On the other side, the ranking results indicate that regulatory framework is the most critical alternative in this regard.
Open Access: Yes
The Impact of the Difficult Economic Situation on the Operation of Slovak Companies in the Shadow of War
Publication Name: Journal of Ecohumanism
Publication Date: 2024-09-20
Volume: 3
Issue: 7
Page Range: 2213-2230
Description:
Purpose: The purpose of this study is to examine the organizational and human resource (HR) responses to the challenging economic conditions caused by the war and the COVID-19 pandemic. Given the limited evidence available on how organizations adapt to such crises, this research aims to develop a conceptual model and empirically investigate the influence of two specific factors: organizational size and direct economic ties with the Russian and Ukrainian markets.This study employs a mixed-method approach, combining both theoretical and empirical research. A conceptual model was first developed to outline potential organizational reactions to crisis conditions. The empirical part of the study involved data collection from 128 organizations, including companies and institutions, in Slovakia. The analysis was conducted to test two hypotheses regarding how organizational size and economic connections with the Russian and Ukrainian markets affect organizational and HR responses in times of war.The findings of the study indicate that neither organizational size nor direct economic linkages with the Russian and Ukrainian markets significantly influenced the responses of the organizations studied to the economic difficulties caused by the war. This suggests that other factors may play a more critical role in shaping organizational and HR strategies in response to crises.For theory, this study contributes to the existing literature by challenging the assumption that organizational size and direct economic ties to conflict-affected markets are primary determinants of organizational responses to crisis. For practice, the findings suggest that managers and HR professionals need to consider a broader range of factors beyond size and market exposure when developing strategies to cope with economic disruptions caused by global crises.This research is original in its focus on the specific impacts of war and pandemic-induced economic conditions on organizations in Slovakia. The study provides valuable insights into how organizations navigate crises, expanding the understanding of crisis management and organizational adaptability. It adds value by highlighting the need for more comprehensive models that consider a wider array of factors influencing organizational behavior in times of global economic disruption.
Open Access: Yes
Generalized Objective Function to Ensure Robust Evaluation for Evolutionary Storage Location Assignment Algorithms
Publication Name: Communications in Computer and Information Science
Publication Date: 2023-01-01
Volume: 1864 CCIS
Issue: Unknown
Page Range: 546-559
Description:
The efficiency of warehouse operations can be measured by various indicators, but the main one is the lead time, which is heavily influenced by the order picking, as this is the most time- and labor-intensive process in the warehouse operation. In order to reduce lead times, many researchers are working on the topic of Storage Location Assignment Problem (SLAP) The optimized SLA is designed to improve picking efficiency, so that the picker does not have to travel long distances unnecessarily in a picker-to-parts system. During the optimization process, it is necessary to evaluate the SLA in an appropriate way, on the basis of which it is possible to measure whether the objectives are approximated by the results or not. It is also very important to evaluate regularly the SLA during the period after optimization to get an up-to-date information about the assignment of the storage items. The results of regular evaluations can be used to check whether the SLA is effective and lead times are good or whether optimization and reassignment is necessary. Based on studies and experience, SLAs are reassessed and optimized following significant inefficiencies, resulting in relocation tasks and additional work and costs for warehouses. The authors’ research concept includes avoiding large-scale relocation tasks by continuously review the SLA. While other studies evaluate the optimized SLA by running picking lists, but it usually would be necessary to get information about the assignment of the entire warehouse. Furthermore, since assigning thousands of items to thousands of positions is a huge combinational problem, evolutionary algorithm would be necessary to apply. It is also requiring time-effective and generalized individual evolution method to make us possible tactical SLA optimization. The aim of this paper is to describe a novel generalized SLA evaluation method where each of the located items is evaluated to obtain a more accurate optimization result. Furthermore, unlike other research, the aim is to ensure that the optimization concept and the evaluation method are not only specified for one warehouse but can be used in other warehouses as well.
Open Access: Yes
