Jarosław Adam Miszczak

Jarosław Adam Miszczak

The emergence of cooperation in the groups of interacting agents is one of the most fascinating phenomena observed in many complex systems studied in social science and ecology, even in the situations where one would expect the agent to use a free-rider policy. This is especially surprising in the situation where no external mechanisms based on reputation or punishment are present. One of the possible explanations of this effect is the inhomogeneity of the various aspects of interactions, which can be used to clarify the seemingly paradoxical behaviour. In this work we demonstrate that the diversity of interaction networks helps to some degree explaining the emergence of cooperation. We extend the model of spatial interaction diversity by enabling the evaluation of the interaction groups. We show that the process of the reevaluation of the interaction group facilitates the emergence of cooperation. Furthermore, we also observe that a significant participation of agents switching their interaction neighbourhoods has a negative impact on the formation of cooperation. The introduced scenario can help to understand the formation of cooperation in the systems where no additional mechanisms for controlling agents are included.

Mateusz Żarski, Jarosław Adam Miszczak

Quick and accurate assessment of the damage state of buildings after natural disasters is crucial for undertaking properly targeted rescue and subsequent recovery operations, which can have a major impact on the safety of victims and the cost of disaster recovery. The quality of such a process can be significantly improved by harnessing the potential of machine learning methods in computer vision. This paper presents a novel damage assessment method using an original multi-step feature fusion network for the classification of the damage state of buildings based on pre- and post-disaster large-scale satellite images. We introduce a novel convolutional neural network (CNN) module that performs feature fusion at multiple network levels between pre- and post-disaster images in the horizontal and vertical directions of CNN network. An additional network element - Fuse Module - was proposed to adapt any CNN model to analyze image pairs in the issue of pair classification. We use, open, large-scale datasets (IDA-BD and xView2) to verify, that the proposed method is suitable to improve on existing state-of-the-art architectures. We report over a 3 percentage point increase in the accuracy of the Vision Transformer model.

Bartosz Wójcik, Mateusz Żarski, Kamil Książek et al.

In recent years, a lot of attention is paid to deep learning methods in the context of vision-based construction site safety systems, especially regarding personal protective equipment. However, despite all this attention, there is still no reliable way to establish the relationship between workers and their hard hats. To answer this problem a combination of deep learning, object detection and head keypoint localization, with simple rule-based reasoning is proposed in this article. In tests, this solution surpassed the previous methods based on the relative bounding box position of different instances, as well as direct detection of hard hat wearers and non-wearers. The results show that the conjunction of novel deep learning methods with humanly-interpretable rule-based systems can result in a solution that is both reliable and can successfully mimic manual, on-site supervision. This work is the next step in the development of fully autonomous construction site safety systems and shows that there is still room for improvement in this area.

Mateusz Żarski, Bartosz Wójcik, Jarosław Adam Miszczak

Monitoring the technical condition of infrastructure is a crucial element to its maintenance. Currently applied methods are outdated, labour-intensive and inaccurate. At the same time, the latest methods using Artificial Intelligence techniques are severely limited in their application due to two main factors -- labour-intensive gathering of new datasets and high demand for computing power. We propose to utilize custom made framework -- KrakN, to overcome these limiting factors. It enables the development of unique infrastructure defects detectors on digital images, achieving the accuracy of above 90%. The framework supports semi-automatic creation of new datasets and has modest computing power requirements. It is implemented in the form of a ready-to-use software package openly distributed to the public. Thus, it can be used to immediately implement the methods proposed in this paper in the process of infrastructure management by government units, regardless of their financial capabilities.

Adam Glos, Jarosław Adam Miszczak

In this paper we demonstrate that the efficiency of quantum algorithms can be significantly altered by malicious manipulation of the input data. We exemplify the possibility of attacks on quantum spatial search based on Szegedy walk. We achieve this by proposing a framework suitable for analysing efficiency of attacks on quantum search algorithms. We provide the analysis of proposed attacks for different models of random graphs.

Piotr Zawadzki, Jarosław Adam Miszczak

The existence of an undetectable eavesdropping of dense coded information has been already demonstrated by Pavičić for the quantum direct communication based on the ping-pong paradigm. However, a) the explicit scheme of the circuit is only given and no design rules are provided, b) the existence of losses is implicitly assumed, c) the attack has been formulated against qubit based protocol only and it is not clear whether it can be adapted to higher dimensional systems. These deficiencies are removed in the presented contribution. A new generic eavesdropping scheme built on a firm theoretical background is proposed. In contrast to the previous approach, it does not refer to the properties of the vacuum state, so it is fully consistent with the absence of losses assumption. Moreover, the scheme applies to the communication paradigm based on signal particles of any dimensionality. It is also shown that some well known attacks are special cases of the proposed scheme.

Jarosław Adam Miszczak

We provide a complete work-flow, based on the language of quantum information theory, suitable for processing data for the purpose of pattern recognition. The main advantage of the introduced scheme is that it can be easily implemented and applied to process real-world data using modest computation resources. At the same time it can be used to investigate the difference in the pattern recognition resulting from the utilization of the tensor product structure of the space of quantum states. We illustrate this difference by providing a simple example based on the classification of 2D data.

Jarosław Adam Miszczak, Piotr Zawadzki

We introduce a general approach for the analysis of a quantum direct communication protocol. The method is based on the investigation of the superoperator acting on a joint system of the communicating parties and the eavesdropper. The introduced method is more versatile than the approaches used so far as it permits to incorporate different noise models in a unified way. Moreover, it make use of a well grounded theory of quantum discrimination for the purpose of estimating the eavesdropper's information gain.

Piotr Zawadzki, Zbigniew Puchała, Jarosław Adam Miszczak

In this paper we propose an extended version of the ping-pong protocol and study its security. The proposed protocol incorporates the usage of mutually unbiased bases in the control mode. We show that, by increasing the number of bases, it is possible to improve the security of this protocol. We also provide the upper bounds on eavesdropping average non-detection probability and propose a control mode modification that increases the attack detection probability.