Paweł Golec

Bio: Paweł Golec is an academic researcher from Wrocław University of Economics. The author has contributed to research in topics: Digital image processing & Decision support system. The author has an hindex of 1, co-authored 5 publications receiving 1 citations.

Gesture Detection in Digital Image Processing based on the Use of Convolutional Neuronal Networks

Abstract: The paper presents empirical findings obtained from tests of an image detection system utilizing the YOLO network. Operating principles of the system are discussed, starting from simple convolutional networks, through R-CNN networks, and culminating in the use of the YOLO technology. The second part provides an examination of findings obtained from a system constructed on a custom dataset. Details are provided of the training process employed, together with the examination of accuracies for all pictures as well as for different classes. The main objective of the paper was to present the development of a system offering real-time gesture detection from camera feed images. Potential applications of the postulated gesture recognition system include toy control systems, photography, and broadly defined office assistance.

Data Quality Management in ERP Systems - Accounting Case.

Abstract: ERP systems process data obtained from heterogeneous sources and therefore the data are characterized by different quality. In order to effectively support management, ERP systems must be based on high-quality data. This is a prerequisite for making decisions within the company. The aim of this paper is to analyse the problems of data quality management in ERP systems and its main contribution is to develop procedures for data quality management in data processing, especially accounting data. The basic outcome of the conducted research is the systematization of the knowledge concerning the data allowing for making quick and effective economic decisions. Based on the results of the research it was concluded that a large number of data control procedures embedded in the ERP allows for ensuring appropriate data quality.

The use of cognitive agent programs in management support

Abstract: A modern economy, based on information and knowledge, forces organizations to use IT tools that support management processes. The authors presented the concept of using cognitive agent programs to support management. These programs are able to track economic phenomena and processes taking place in the organization and its environment, conduct an in-depth analysis of information, draw conclusions and take specific actions. The features of cognitive agents allow organizations to gain a competitive advantage by making the right decisions faster at the operational, tactical and strategic level and by limiting the impact of such human characteristics as emotions or fatigue on task execution. The first part of the article outlines a characterisation of cognitive agent programs. The management areas in which cognitive agents can be used are then analysed and presented. The final part of the article provides conclusions and further research work.

The Role of Algorithmic Trading in Stock Liquidity and Commonality in Electronic Limit Order Markets

Abstract: In investigating the effects of algorithmic trading on stock market liquidity and commonality in liquidity in different market conditions in an electronic limit order market, we find algorithmic trading increases stock liquidity by narrowing quoted and effective bid-ask spreads. Furthermore, algorithmic trading decreases commonality in liquidity; this finding is robust across a variety of liquidity measures. We also find algorithmic trading narrows the quoted and effective spreads to a much lesser extent following extreme market conditions, particularly after large stock market declines. However, the effect of algorithmic trading on commonality in liquidity does not differ following large market declines.