The preprocessing of data is an important task in rough set theory as well as in Entropy. The discretization of data as part of the preprocessing of data is a very influential process. Is there a connection between the segmentation of the data histogram and data discretization? The authors propose a novel data segmentation technique based on a histogram with regard to the quality of a data discretization. The significance of a cut’s position has been researched on several groups of histograms. A data set reduct was observed with respect to the histogram type. Connections between the data histograms and cuts, reduct and the classification rules have been researched. The result is that the reduct attributes have a more irregular histogram than attributes out of the reduct. The following discretization algorithms were used: the entropy algorithm and the Maximal Discernibility algorithm developed in rough set theory. This article presents the Cuts Selection Method based on histogram segmentation, reduct of data and MD algorithm of discretization. An application on the selected database shows that the benefits of a selection of cuts relies on histogram segmentation. The results of the classification were compared with the results of the Naïve Bayes algorithm.

Agile meetings are an essential part of modern software development, but they often face challenges such as lack of focus, communication problems, technological difficulties, and the like. Previous research has often addressed individual issues of agile meetings but has not provided sufficiently integrated or practical models to comprehensively address these challenges. This research fills this gap, developing a theoretical model that not only identifies key issues but systematically links them to provide a deeper understanding of their impact on meeting effectiveness.In this paper, we present a theoretical model that depicts intra-team problems in agile meetings developed through a systematic literature review (SLR). After initial development, the model was validated and improved through the qualitative analysis of semi-structured interviews with IT experts. This research aimed to confirm the coverage and relevance of the content of the preliminary model, as well as to identify the need for modification. The results of the interviews suggest that the presented model is adequate but that there is a need for potential improvement. IT experts agreed with the items in the model, and some of them suggested improvements. The model is promising because it illustrates the key issues that influence the effectiveness of agile meetings in a promising way. IT experts agreed on the items in the model, and some of them suggested improving the model.

The development and adoption of microservices, as one of the most promising directions for developing heterogeneous distributed software systems, have been driven by dynamic changes in business and technology. In addition to the development of new applications, a significant aspect of microservices is the migration from legacy monolithic systems to microservice architectures. Such development trends are accompanied by an increase in the number of primary and secondary publications addressing microservices, highlighting the need to systematize research at a higher level. The objective of this study is to comprehensively analyze secondary studies in the field of microservices from the following five aspects: (1) publishing trends, (2) quality trends of secondary studies, (3) research trends, (4) domains of implementation, and (5) future research directions. The study follows the guidelines for conducting a systematic literature review. The findings were derived from 44 secondary studies published in the period from January 2016 to January 2023. These studies were organized and analyzed to address the five proposed research questions pertaining to the study objectives. The findings suggest that the most promising research directions are related to the development, implementation, and validation of new approaches, methods, and tools that encompass all the phases of the life cycle. Additionally, these research directions have applications in a variety of business and human life domains. Recommendations for further literature reviews relate to improvement of quality assessment of selected studies, more detailed review of architecture quality attributes, inquiry of human factor issues, and certain maintenance and operation issues. From the methodological aspect, recommendations relate to using social science qualitative methods for more detailed analysis of selected studies, and inclusion of gray literature that will bring the real experience of experts from industry.

Digital image processing was recently proved to be successfully approached by variational tools, which extend the Casseles-Kimmel-Sapiro weighted length problem. Such tools essentially lead to the socalled Geodesic Active Flow (GAF) process, which relies on the derived mean curvature flow PDE. This prolific process is valuable due to both the provided numeric mathematical insight, which requires specific nontrivial choices for implementing the related algorithms, and the variety of possible underlying specific geometric structures. A natural Finsler extension of Randers type was recently developed by the authors, which emphasizes the anisotropy given by the straightforward gradient, while considering a particular scaling of the Lagrangian. The present work develops to its full extent the GAF process to the Randers Finslerian framework: the evolution equations of the model are determined in detail, Matlab simulations illustrate the obtained theoretic results and conclusive remarks are drawn. Finally, open problems regarding the theoretic model and its applicative efficiency are stated.

The systems for localization of resources in indoor environments based on Received Signal Strength Indicator (RSSI) are widely used today. Since satellite navigation systems, such as GPS or GLONASS, have certain difficulties in the indoor environments, the signals of deployed wireless devices, such as sensor nodes, access points etc, are used for localization instead. Those systems are known as Indoor Positioning System (IPS). Those systems are used for resource tracking and positioning in places such as airports, railway stations, shopping malls, warehouses, production facilities, construction sites, and healthcare institutions. The Bluetooth Low Energy is one of the wireless technologies that can be used with great efficiency for indoor localization. It offers easy and economic implementation on mobile devices such as smart phones and tablets. There are many techniques used for determination of position. In a number of methods, such as ROCRSSI or MinMax, the distance from the wireless nodes is used for calculating the location. In those systems the main challenge is to accurately estimate distance from the device based on signal strength. In this paper, usability of various software tools for modelling the distance estimation based on RSSI is discussed. Those software tools are Microsoft Access, R Studio, Octave, and Python.