István Harmati
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Breast Cancer Surgical Specimens: A Marking Challenge and a Novel Solution—A Prospective, Randomized Study Open
Background: Accurate orientation of resected breast specimens is essential for proper pathological evaluation and margin assessment. Misorientation may compromise analysis, lead to imprecise re-excisions, and increase the risk of local rec…
Breast Cancer Surgical Specimens: A Marking Challenge and a Novel Solution—A Prospective, Randomized Study Open
Background: Accurate orientation of resected breast specimens is crucial for proper pathological evaluation and reliable margin assessment. Misorientation can compro-mise margin analysis, potentially leading to imprecise re-excisions and i…
Breast Cancer Surgical Specimens: A Marking Challenge and a Novel Solution – A Prospective, Randomized Study Open
Background: Accurate orientation of resected breast specimens is crucial for proper pathological evaluation and reliable margin assessment. Misorientation can compromise margin analysis, potentially leading to imprecise re-excisions and in…
The structure of the Hungarian insurance market and the invariant distribution of market shares Open
The Hungarian economy exhibits a notable underinsurance phenomenon, with insurance penetration at a mere 2.8%, significantly lower than the European Union average of 8%. This situation indicates substantial growth potential within the Hung…
Sales strategies with a probabilistic business model of an insurance company: The role of updating and targeting Open
The major goal of decisions made by a business organization is to enhance business performance. These days, owners, managers and other stakeholders are seeking for opportunities of modelling and automating decisions by analysing the most r…
Path planning for multiagent system in a sensing field with obstacles and multiple base stations Open
In large area data collection, wireless long-distance data transmission through sensor network reduces network lifetime due to large energy consumption. Therefore, this paper presents a path planning problem for a multiagent system to peri…
OWA operators in the insurance industry Open
In this paper, we examine a possible application of ordered weighted average (OWA for short) aggregation operators in the insurance industry. Aggregation operators are essential tools in decision-making when a single value is needed instea…
Non-Palpable Breast Cancer: A Targeting Challenge–Comparison of Radio-Guided vs. Wire-Guided Localization Techniques Open
Background: The incidence of non-palpable breast cancer is increasing due to widespread screening and neo-adjuvant therapies. Among the available tumor localization techniques, radio-guided occult lesion localization (ROLL) has largely rep…
Non-Palpable Breast Cancer: A Targeting Challenge – Comparison of Radio-Guided vs Wire Wire-Guided Localization Techniques Open
The incidence of non-palpable breast cancer is increasing due to widespread screening and neoadjuvant therapies. Among the available tumor localization techniques, radio-guided occult lesion localization (ROLL) has largely replaced wire-gu…
Improving Reinforcement Learning Exploration by Autoencoders Open
Reinforcement learning is a field with massive potential related to solving engineering problems without field knowledge. However, the problem of exploration and exploitation emerges when one tries to balance a system between the learning …
Path Planning for Data Collection Multiagent System with Priority and Moving Nodes in a Sensing Field with Obstacles Open
Nowadays there is a more and more common need for one-off data collection in a specified area. For example, in case of searching for the survivors of disasters or wars, or for skiers who get into trouble. The simplest way of collecting suc…
The Emergency Braking Game: a game theoretic approach for maneuvering in a dense crowd of pedestrians Open
We introduce an algorithm that maneuvers a vehicle through an area with randomly moving pedestrians. In non-critical situations, our strategy is to avoid pedestrians by steering, whereas dangerously moving pedestrians are avoided by brakin…
Improving Multiagent Actor-Critic Architectures, with Opponent Approximation and Dropout for Control Open
In the domain of reinforcement learning, solution proposals to multiagent problems are evolving.We propose a new algorithm, MADDPGX, to handle the problem of higher uncertainty created by other agents' actions by an enemy actor approximato…
Optimal strategies of a pursuit-evasion game with three pursuers and one superior evader Open
We attempt to solve the pursuit-evasion game of a faster evader being surrounded by three pursuers. The complexity of the game under study stems from the holonomic motion of the agents. This game has not been solved either in the sense of …
Path planning for data collection robot in sensing field with obstacles Open
Using mobile robots to collect data from wireless sensor network can reduce energy dissipation and this way improves network lifetime. Our problem is to plan paths for unicycle robots to visit a set of sensor nodes and download data on a s…
On stability of maximal entropy OWA operator weights Open
The maximal entropy OWA operator (MEOWA) weights can be obtained by solving a nonlinear programming problem with a linear constraint for the level of orness. Since the exact MEOWA weights are not known for the general case we can only find…
Global stability of fuzzy cognitive maps Open
Complex systems can be effectively modelled by fuzzy cognitive maps. Fuzzy cognitive maps (FCMs) are network-based models, where the connections in the network represent causal relations. The conclusion about the system is based on the lim…
Lane-changing decision modelling in congested traffic with a game theory-based decomposition algorithm Open
This study presents a cellular lane-changing model where the traffic lanes are discretized into cells and formulates the lane-changing process as a multi-player non-zero-sum non-cooperative game in a connected environment where the real-ti…
Vision-based reinforcement learning for lane-tracking control Open
The present study focused on vision-based end-to-end reinforcement learning in relation to vehicle control problems such as lane following and collision avoidance. The controller policy presented in this paper is able to control a small-sc…
A2CM: a new multi-agent algorithm Open
Reinforcement learning is currently one of the most researched fields of artificial intelligence. New algorithms are being developed that use neural networks to compute the selected action, especially for deep reinforcement learning. One s…
Monitoring multi-respiratory indices via a smart nanofibrous mask filter based on a triboelectric nanogenerator Open
Respiratory parameters, such as respiratory rate (RR), inhalation time (tin), exhalation time (tex), and their ratio (IER=tin/tex), are of great importance to indicate clinical differences between healthy people and those with respiratory …
Revisiting a Three-Player Pursuit-Evasion Game Open
We consider the game of a holonomic evader passing between two holonomic pursuers. The optimal trajectories of this game are known. We give a detailed explanation of the game of kind’s solution and present a computationally efficient way t…
Dynamics of Fuzzy-Rough Cognitive Networks Open
Fuzzy-rough cognitive networks (FRCNs) are interpretable recurrent neural networks, primarily designed for solving classification problems. Their structure is simple and transparent, while the performance is comparable to the well-known bl…
A Simplified Pursuit-evasion Game with Reinforcement Learning Open
In this paper we visit the problem of pursuit and evasion and specifically, the collision avoidance during the problem. Two distinct tasks are visited: the first is a scenario when the agents can communicate with each other online, meanwhi…