Showing papers in "Acta Polytechnica Hungarica in 2021"

Robotics and Intelligent Systems Against a Pandemic

Abstract: The outbreak of the novel coronavirus and its disease COVID-19 presents an unprecedented challenge for humanity. Intelligent systems and robotics particularly are helping the fight against COVID-19 several ways. Potential technology-driven solutions in this accelerating pandemic include, but are not limited to, early detection and diagnosis, assistive robots, indoor and outdoor disinfection robots, public awareness and patrolling, contactless last-mile delivery services, micro- and nano-robotics and laboratory automation. This article sheds light on the roles robotics and automation can play in fighting this disastrous pandemic and highlights a number of potential applications to transform this challenge into opportunities. The article also highlights the ethical implications of robotics and intelligent systems during the emergency side and in the post-pandemic world.

Predictive Machine Learning Approach for Complex Problem Solving Process Data Mining

Abstract: Problem-solving is considered to be an essential everyday skill, in professional as well as in personal situations. In this paper, we investigate whether a predictive model for a problem-solving process based on data mining techniques can be derived from raw logfiles recorded by a computer-based assessment system. Modern informatics-based education relies on electronic assessment systems for evaluating knowledge and skills. OECD’s PISA 2012 computer-based assessment database was used, which contains a rich problem-solving dataset. The dataset consists of detailed action logs and results for several problem-solving tasks. Two feature sets were extracted from the selected PISA 2012 Climate Control problem solving task: a set of time-based features and a set of features indicating the employment of the VOTAT problem-solving strategy. We evaluated both feature sets with six machine learning algorithms in order to predict the outcome of the problem-solving process, compared their performance and analyzed which algorithms yield better results with respect to the observed feature set. The approach presented in this paper can be used as a potential tool for better understanding of problem-solving patterns, and also for implementing interactive e-learning systems for training problem solving skills.

Sensory Integration in Deep Neural Networks

Abstract: Two unimodal deep networks and one multimodal deep network are created to test for possible mechanisms of sensory integration that may shed more light on how sensory integration is carried out in biological organisms. One unimodal network is provided with pictures and the other with mel-spectrograms created from sounds. Adapted pre-trained VGG16 network was used for unimodal networks. After training consisting of 30 epochs and repeated for 100 runs the unimodal networks achieved an average accuracy of 0.57 and 0.73 respectively. The multimodal network received processed features from both unimodal networks and after training consisting of 30 epochs and repeated for 100 runs outperformed both unimodal networks with the average accuracy of 0.79. Next, noise was applied to the test data to see how unimodal and multimodal networks compare in noisy environments. Unimodal networks achieved an average accuracy of 0.63 and 0.69 respectively. Again, the multimodal network outperformed both unimodal networks with an average accuracy of 0.73. Pre-trained networks were used and limited training data were provided to the networks to simulate conditions similar to animal brains.

Secure Remote User Authentication Scheme on Health Care, IoT and Cloud Applications: A Multilayer Systematic Survey

Abstract: Secure remote user authentication is an authentication technique in which the remote server authorizes the identity of the user through an insecure communication network. Since then diverse remote user authentication schemes have been proposed, but each category has its advantages and disadvantages. Besides its strength and weakness, remote user authentication systems have a great impact on real-time applications such as E-health applications, telemedicine applications, Internet of Things (IoT), Cloud, and Multi-server applications. The implementation of the Tele Medicine Information System (TMIS) over public networks continues to disclose confidential information to unauthorized entities. Similarly, remote user authentication techniques have become essential in accelerating IoT as well. Security is a major concern in IoT because it allows secure access to remote services. Cloud computing services and a Multi-server environment share data among different end-users through the internet which also needs security as its paramount concern. Although intensive efforts were made in designing remote user authentication scheme for health care, IoT, Multi-server and cloud applications, the majority of these applications suffers either from security attacks or lagging of critical features. This paper presents an analytical and comprehensive survey of various remote user authentication techniques and categorizes them based on different applications. Furthermore, the state of art recent remote user authentication techniques have been compared, their advantages, key features, computational cost, storage cost, and communication cost are highlighted.

Cyber Threats and Cyber Deception in Hybrid Warfare

Abstract: Paper deals with the design of the model of hybrid threats and cyber deception platform and solution for cyber threat detection. National networks face a broad range of cyber threats. It includes advanced and persistent peril that can evade commercially available detection tools and defeat generic security measures. Cyber attacks are becoming more intense and complex as they reflect an increasing level of sophistication, e. g. by advanced persistent threat (APT) activity. This environment of menace is of a global nature when transcending geographic boundaries and characterized by the emerging development of offensive cyber capabilities that are an inherent part of conflicts. Deception methods and techniques are being successfully employed by attackers to breach networks and remain undetected in the physical and in the virtual worlds. However, in the world of cyber security, deception as a tactic and element of a more robust defensive strategy has been still largely underexploited. The broad concepts of deception within cyber security were introduced decades ago. Still, these were technological solutions focused on providing technical capabilities to distract, mislead or misdirect the attacker. Only recently has the focus shifted on to how to shape the attackers’ sense-making of what is happening as they illegitimately explore networks. In this way, Cyber Deception nowadays provides an opportunity to scare, deter, and retaliate against those that violate organizations’ systems. In connection with the foregoing authors created and presented the novel model of hybrid threats in hybrid warfare as a combination of multiple conventional and unconventional tools of warfare. Authors investigate the cyber deception platform and industrial model and solution for threat detection using deception-

Fuzzy Logic Model to Assess Desertification Intensity Based on Vulnerability Indices

Abstract: Executive practices on desertification control should be based on recognizing the current desertification state and its severity. So, it is essential to assess the ways to give zoning based on logic, active principles, and theoretical foundation for the management of desert regions. For this aim, 30 useful indices on desertification were determined in two human and natural sections. The significance of indices relative to each other and each index's importance per work unit was determined using the Delphi method. The Bonissone method in the framework of the Fuzzy Multiple Attribute Decision Making (FMADM) method was used to combine indices and determine desertification intensity in each working unit. Then, data were converted to the Fuzzy layer using Chen and Wang method, and Fuzzy analysis was performed on data. Finally, Fuzzy data were changed to nonFuzzy, and desertification intensity was estimated. The results showed that 9.35% of the study area was in a very high class regarding desertification intensity and 9.36% of the region was in relatively high class. Desertification with moderate intensity (50.64%) and a relatively moderate intensity (29.45%) had the most shares in the study area, respectively. The quantitative value of desertification potential in the whole area from all of the components was obtained as 0.083, relatively high. This study shows the efficiency and ease of Fuzzy logic application for assessing desertification intensity.

The Methods and IT-Tools Used in Higher Education Assessed in the Characteristics and Attitude of Gen Z

Abstract: In the era of digital transformation, some questions occur whether the teaching methods used in higher education are suitable for the students belonging to generation Z or these methods are appropriate enough to make them more attentive or motivated. The diverse methods of information technology have already spread into university education and a pedagogical paradigm shift can be perceived. The latest methodology, like project method, e-learning, BYOD, gamification, MOOC are available in higher education as well; however, it is a question to what extent teachers apply these methods in their teaching process. The new techniques not only make the students more motivated but also enhance them with those sorts of skills that are indispensable to be successful in the field of labor. The research was aimed to find answers about how much engineer students are satisfied with the training they are given in higher education in the 21 Century, what kind of attitude they have towards educational technology.

Towards Fast and Understandable Computations: Which “And”- and “Or”-Operations Can Be Represented by the Fastest (i.e., 1-Layer) Neural Networks? Which Activations Functions Allow Such Representations?

Abstract: We want computations to be fast, and we want them to be understandable. As we show, the need for computations to be fast naturally leads to neural networks, with 1-layer networks being the fastest, and the need to be understandable naturally leads to fuzzy logic and to the corresponding “and”and “or”-operations. Since we want our computations to be both fast and understandable, a natural question is: which “and”and “or”-operations of fuzzy logic can be represented by the fastest (i.e., 1-layer) neural network? And a related question is: which activation functions allow such a representation? In this paper, we provide an answer to both questions: the only “and”and “or”-operations that can be thus represented are max(0,a+ b− 1) and min(a+ b,1), and the only activations functions allowing such a representation are equivalent to the rectified linear function – the one used in deep learning. This result provides an additional explanation of why rectified linear neurons are so successful. With also show that with full 2-layer networks, we can compute practically any “and”and “or”-operation.

Responses to the challenges of fast digital conversion, in the light of international research results - A comparative look at virtual spaces

Abstract: In order to assure effectiveness, digital instruction prioritizes digital devices and systems over traditional technological and methodological solutions. In the current digital age and the way of life defined by digital culture, digital skills and competences become highly appreciated. Also, innovative methodological solutions, promoting the long term maintenance of attention and motivation, become key factors in remote learning or digitally scheduled education. Furthermore, the emergence of additional digital gaps, triggers newer digital paradigm shifts, gaining special importance during such exigencies, as a pandemic. An effective response or potential remedy, to this situation, is offered by digital pedagogy. Digital pedagogy faced substantial challenges during the first wave of the COVID-19 pandemic, imposing demanding tasks on all participants, within the education sector. Our study introduces the results of a quantitative, multivariable, empirical inquiry, entailing a comparative analysis of data obtained from a survey of the pedagogue attitudes and digital tool systems for three selected countries. © 2021, Budapest Tech Polytechnical Institution. All rights reserved.

Impact of Tax Benefits and Earnings Management on Capital structures Across V4 Countries

Abstract: The issue of capital structure is among the most commonly discussed fields within Corporate Finance Theory. By optimizing the capital structure, it is possible to achieve an increase in the company value and increase the company flexibility and competitiveness. Economists have, for more than half a century, seen tax benefits (tax shields) as a capital structure determinant. Nonetheless, leverage is also influenced by earnings management, which can significantly reduce information asymmetry, between stakeholders when used correctly. This paper examines the influence of the tax shield and earnings management on a corporate capital structure, in V4 countries. In order to determine the influence of the tax shield and earnings management, panel data model was used. Net sample consisted of 10627 companies from the V4 countries from 2014-2017. The results of the model indicate that corporate behavior in the area of capital structure follows Pecking order; short-term trade credit is the most commonly used liability. The interest tax shield is of little importance for deciding between debt and equity, while the non-debt tax shield is negatively correlated with debt. Furthermore, an inverse correlation between debt and earnings management, as measured by the modified Jones model, indicates that debt monitoring, reduces agent costs and reduces the application of earnings management techniques.

Sustainability of human resource management processes through employee motivation and job satisfaction

Abstract: Small and medium-sized enterprises form a significant part of the economy of each country with the greatest potential for growth and the impact on stabilizing the economy. Their success or failure depends not only on know-how, capital, or machinery, but also on human resources, one of the competitive advantages and a critical factor of success. In order to achieve success and ensure the sustainability of business processes, the focus is on employee motivation and employee satisfaction, with an emphasis on effective management as multicultural workers' groups are becoming the current trend in logistics companies. Using Tukey's HSD post-hoc test and ANOVA, differences in the perception of motivation and job satisfaction of employees are identified. As part of the post-hoc analysis, the observed dependencies of the mean values of importance and satisfaction with the effect of selected motivation factors are examined in more detail. Based on the results, the fact that employee motivation in logistics companies in Slovakia and the Czech Republic is different, can be concluded. In addition, it varies according to the size of the enterprise. These findings are important for the members of management because of the globalization of economies and multiculturalism of workers‘ teams in both logistics and also other enterprises. Finding a variety of preferences for motivational needs and job satisfaction does not make it possible to develop unified motivation programs. The needs of employees regarding the size of the enterprise and also the country of origin must be taken into account by the management of an enterprise.

Hybrid SLAM-based Exploration of a Mobile Robot for 3D Scenario Reconstruction and Autonomous Navigation

Abstract: SLAM can be categorized into two groups: laser-based SLAM and visual-based SLAM. They are used to identify surrounded objects of a robot. This paper proposes a combination of visual-based SLAM algorithm and laser-based SLAM. The purpose is to reduce effort but still provides the high quality 3D-reconstructed map. First, this paper presents visual-based SLAM and laser-based SLAM separately. Then, two techniques are integrated into one system. In addition, bi-direction RRT* path planning algorithm is developed to create a feasible and optimal trajectory. A self-tuning Fuzzy-PID controller also is introduced for driving the robot to follow the trajectory precisely. The simulations and real experiments are conducted in order to illustrate the superiority of the proposed approach.

Practical Application Possibilities for 3D Models Using Low-resolution Thermal Images

Abstract: Everyday used cheap thermal cameras can only take low-resolution images. Low-resolution images can be used as the input data of photogrammetry procedures with difficulty or cannot be used at all, as little information is stored of the actual object. Based on the little amount of information, conventional procedures are not capable of identifying a correlation between individual images. Intensity also differs between individual pixels compared to conventional RGB images, thus gradient-based solutions fail to be successful. A method has been developed, which can be used to create thermal image orthophotos from thermal images combined with RGB images. The procedure can result in several output images, from which the most important is the false color thermal image, which is within the visible light spectrum, as on it the original object and the amount of thermal radiation are both visible. Another advantage of the procedure is that not only the information of the visible light spectrum can be visualized but also the data which is invisible to the naked eye.

A convergence analysis of the Nelder-Mead simplex method

Abstract: We give a sufficient condition for a certain type of convergence behavior of the Nelder-Mead simplex method and apply this result to several examples. We also give two related examples for the case of repeated shrinking which indicates a kind of local character of the method.

Reliability, Maintainability, and Availability Analysis of a Computerized Numerical Control Machine Tool Using Markov Chains

Abstract: Reliability, maintainability, and availability analysis of Computerized Numerical Control Machine Tools (CNCMT) is vital as they are widely used in manufacturing industries for mass production. This paper proposes a generalized framework for TimeBetween-Failure (TBF) and Time-To-Repair (TTR) data analysis, integrated with Markov chains for estimating the system’s Steady State Availability (SSA). A case study of a typical CNCMT illustrates the applicability and the effectiveness of the proposed framework. The effect of variation of sub-systems' failure and repair rates on the availability of the CNCMT is studied. The critical sub-systems from reliability, maintainability, and availability point of view are identified. The analysis reveals that the CNCMT’s failure and repair rates are nearly constant and the CNCMT fails four times per year. The Lubrication Sub-system (LS) is the utmost severe sub-system as far as maintainability aspect is concerned and Turret Sub-system (TS) is the utmost severe sub-system from a reliability perspective.

Three-Dimensional Modeling and Analysis of Mechanized Excavation for Tunnel Boring Machines

Abstract: Urban train infrastructures are very important for reliable urban mobility. This paper proposes a three-dimensional modeling of mechanized drilling corridors. Drilling in urban areas is always a risky and complex project. One of the most important issues during the construction of subway tunnels is the investigation of the impact of drilling steps on the ground subsidence and impact on existing structures. For this purpose, different types of mechanized drilling methods are often used, resulting in a considerable reduction in the displacements caused by tunnel drilling. In this study, part of the route of an urban train tunnel, that passes under a traffic interchange, is examined. The shear strength capacity of the slab pile was calculated, using the relevant equations, and then, the modeling of the soil mass was performed, using the PLAXIS 3D finite element program. The proposed depth of the tunnel construction, by the consulting company, is 18 meters. Due to drilling problems, D. Mohammadzadeh S. et al. Three-Dimensional Modeling and Analysis of Mechanized Excavation for Tunnel Boring Machines – 214 – a depth of 14 meters has been suggested as an alternative. Analysis of both the depths of 14 and 18 meters, showed that the displacements at both depths, were approximately the same. However, the impact of the tunnel, on the capacity of the piles' tip, at a depth of 18 meters, is greater than at the depth of 14 meters. Thus, the suggested optimum depth is 14 meters, which is more suitable, than the initial suggested depth of 18 meters.

Fuzzy-Terminal Sliding Mode Control of a Flexible Link Manipulator

Abstract: In this study, a terminal sliding mode controller is introduced, for trajectory tracking control, of a flexible link robot manipulator. Two important parameters are considered; angle of the link and tip deflection. To demonstrate the effectiveness of the developed controller, control gain parameters in the sliding mode controller are determined by using Fuzzy Logic Control law. Another important feature of the developed controller is that it is robust against external disturbances. Stability analysis of the system is guaranteed by the Lyapunov theory. Trajectory tracking errors, angles and tip deflection of the links are investigated for two different trajectories. When the results are examined, it is seen that the developed controller, with fuzzy logic, is effective, even if there are external disturbances and parametric uncertainties in the system.

Polyhedrons vs. Curved Surfaces with Mental Cutting: Impact of Spatial Ability

Abstract: This study aims to determine and compare first-year engineering students’ mental cutting ability, into two new parts, among the students of two universities in Tehran and Debrecen, concerning final mathematical exams and their gender, in order to understand whether the students of the two universities have sufficient spatial abilities. For that purpose; the Mental Cutting Test is applied to first-year engineering students to determine their mental cutting ability, in a current situation. In our research, we separate the tests into two parts, “Polyhedrons” and “Curved Surfaces”. The separate tests results have been statistically evaluated and conclusions formulated. According to obtained data, the results are: First-year engineering female students of Debrecen and male students of Tehran, are more successful at Curved Surfaces than Polyhedrons; in addition, male students of Debrecen and female students of Tehran are more successful at Polyhedrons than Curved Surfaces. There is a significant correlation between the male students Polyhedrons and Curved Surfaces solutions, in both countries, but not for the female population.

Learner experiences related to digital education schedules in light of empirical data

Abstract: In this work, I briefly introduce the theoretical foundations and main aspects of electronic learning, in order to explore and evaluate the instruction schemes implemented as a result of the digital transformation. I base my findings on the analysis of a questionnaire-based survey administered to a sample of students. My research aims at examining the efficiency of the implementation of digital instruction and the accompanying challenges at various levels of the education sphere. I was interested in students’ Information and Communications Technology (ICT) preferences and usage habits and whether or not they possess vital digital competences in their own view. The digitally scheduled education programs introduced in response to the COVID-19 pandemic could not fully reach a level required for effective learning according to research findings. The responses revealed that several schools did not implement uniform systems, the educational materials were not suitable for independent learning, the given materials did not have a modular structure, the respective texts did not reflect a system oriented perspective, and it was proven that neither students nor teachers possessed digital literacy skills considered to be currently vital. The most important result of this statistical analysis entails that those students were more successful in the digital home-based education, who spent more time with Information and Communications Technology (ICT) use, regularly played with or used experience-oriented software and relied on smart devices for most of their studies. © 2021, Budapest Tech Polytechnical Institution. All rights reserved.