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Charles University, Czech Republic

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16 Papers

Increasing Business Opportunities for Drone Services

Topics: B2C/B2B Considerations; Service-oriented Enterprise ; Industrial/Manufacturing

Authors: S. Brezani ¹ , R. Hrasko ¹ , D. Vanco ¹ and P. Vojtas ^{2

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Affiliations: ¹ Globesy ltd., Framborska 58, Zilina, Slovak Republic , ² Dpt. Software Engineering, Charles University, Malostranke nam. 25, Prague, Czech Republic

Digital Object Identifier: 10.5220/0010566900930100

Proceedings of ICE-B 2021, ISBN: 978-989-758-527-2

Quick Abstract

We describe our UAV imaging research and development from a business perspective. Our main goal is to increase business opportunities for our drone services. We build on experiences from an already deployed drone service provided by our IT company. The application is using a commercial tool for processing photogrammetry. Its advantage is accuracy, but the main disadvantage is the time needed for annotation by a trained human operator. Our methodology is based on user studies and knowledge gained in communicating with potential customers at IT trade fairs and exhibitions. We analyse the duration and automation of the service as key factors. We consider two types of higher automation of the solution. First is the automation of annotation - less accurate, without human intervention. The second is automation in flight planning and implementation. The use of other drone peripherals or hybrid drones can also create new types of services. In particular, there is a demand for immediate execution of on-site flight imaging without any pre-calibration. Our considerations, expanding our services, also include various inspections or direct involvement in industrial processes. Some improvements were tested on an experimental prototype. The results indicate improvement making services cheaper and faster.

Automatic Train Operation: History and Open Questions

Topics: Intelligent Infrastructure and Guidance Systems; Information Systems and Technologies

Authors: Aleš Lieskovský ¹ , Ivo Myslivec ¹ and Michal Žemlička ²

Affiliations: ¹ Závod Technika, A ŽD Praha, s.r.o., Žirovnická 3146/2, Praha 10, Czech Republic , ² Závod Technika, A ŽD Praha, s.r.o., Žirovnická 3146/2, Praha 10, Czech Republic, Department of Informatics, Jan Evangelista Purkyně University, České mládeže 8, Ústí nad Labem, Czech Republic, Department of Software and Computer Science Education, Charles University, Praha, Czech Republic

Digital Object Identifier: 10.5220/0009418002600267

Proceedings of VEHITS 2020, ISBN: 978-989-758-419-0

Quick Abstract

The paper presents the concept of automatic train operation. We give here short description of its functionality and remember some points from its history. There is an overview of various future development as well as proposals for improvement of some existing, especially mainline, solutions. There are presented also some observations from decades of practical use of automatic train operation in the Czech Republic. Selected challenges are presented and discussed.

Indexing Patterns in Graph Databases

Topics: Nosql Databases; Database Architecture and Performance

Authors: Jaroslav Pokorný ¹ , Michal Valenta ² and Martin Troup ²

Affiliations: ¹ Faculty of Mathematics and Physics, Charles University, Prague and Czech Republic , ² Faculty of Information Technology, Czech Technical University, Prague and Czech Republic

Digital Object Identifier: 10.5220/0006826903130321

Proceedings of DATA 2018, ISBN: 978-989-758-318-6

Quick Abstract

Nowadays graphs have become very popular in domains like social media analytics, healthcare, natural sciences, BI, networking, graph-based bibliographic IR, etc. Graph databases (GDB) allow simple and rapid retrieval of complex graph structures that are difficult to model in traditional IS based on a relational DBMS. GDB are designed to exploit relationships in data, which means they can uncover patterns difficult to detect using traditional methods. We introduce a new method for indexing graph patterns within a GDB modelled as a labelled property graph. The index is organized in a tree structure and stored in the same database where the database graph. The method is analysed and implemented for Neo4j GDB engine. It enables to create, use and update indexes that are used to speed-up the process of matching graph patterns. The paper provides a comparison between queries with and without using indexes.

Related Ontology Subjects/Areas/Topics (4)

Data Engineering		Databases and Data Security		Nosql Databases
Database Architecture and Performance

Automated Dynamic Formation of Component Ensembles - Taking Advantage of Component Cooperation Locality

Topic: Component-Based Software Engineering

Authors: Filip Krijt , Zbynek Jiracek , Tomas Bures , Petr Hnetynka and Frantisek Plasil

Affiliation: Charles University, Czech Republic

Digital Object Identifier: 10.5220/0006273705610568

Proceedings of MODELSWARD 2017, ISBN: 978-989-758-210-3

Quick Abstract

Smart cyber-physical systems (sCPS) is a growing research field focused on scenarios where a set of autonomous software-hardware entities (components) is cooperating via network communication to achieve a type of swarm or cloud intelligence. Typically the components’ cooperation is designed at a low level of abstraction and their behavior validated via simulations. As a remedy, a declarative language capable of specifying high-level component ensembles has been proposed in recent work. By capturing component functionality and the cooperation constraints, a specification serves both for generating platform-specific implementation and as a model@run.time to support self-adaption via dynamic formation of ensembles. However, for a particular specification, multiple possible architectural configurations exist with various impact on the system. Given their typically large number, we select the best one via an SMT solver. In this paper, we show that scalability of such approach can be supported by exploiting the effect of locality in component cooperation and by hoisting specific domain knowledge to the level of architecture.

Related Ontology Subjects/Areas/Topics (4)

Applications and Software Development		Model-Driven Software Development		Software Engineering
Component-Based Software Engineering

Data Preprocessing of eSport Game Records - Counter-Strike: Global Offensive

Topics: Information Quality; Information Integration; Data Integrity; Organizational Concepts and Practices; Data Management for Analytics

Authors: David Bednárek , Martin Krulis , Jakub Yaghob and Filip Zavoral

Affiliation: Charles University, Czech Republic

Digital Object Identifier: 10.5220/0006475002690276

Proceedings of DATA 2017, ISBN: 978-989-758-255-4

Quick Abstract

Electronic sports or pro gaming have become very popular in this millenium and the increased value of this new industry is attracting investors with various interests. One of these interest is game betting, which requires player and team rating, game result predictions, and fraud detection techniques. In our work, we focus on preprocessing data of Counter-Strike: Global Offensive game in order to employ subsequent data analysis methods for quantifying player performance. The data preprocessing is difficult since the data format is complex and undocumented, the data quality of available sources is low, and there is no direct way how to match players from the recorded files with players listed on public boards such as HLTV website. We have summarized our experience from the data preprocessing and provide a way how to establish a player matching based on their metadata.

Related Ontology Subjects/Areas/Topics (18)

Artificial Intelligence	Databases and Data Security	Integration/Interoperability
Collaboration and e-Services	e-Business	Knowledge Engineering and Ontology Development
Data Engineering	Enterprise Information Systems	Knowledge-Based Systems
Data Integrity	Information and Systems Security	Ontologies and the Semantic Web
Data Management and Quality	Information Integration	Organizational Concepts and Best Practices
Data Management for Analytics	Information Quality	Symbolic Systems

The Benefit of Control Knowledge and Heuristics During Search in Planning

Topics: Planning and Scheduling; Knowledge Representation and Reasoning; State Space Search

Authors: Jindřich Vodrážka and Roman Barták

Affiliation: Charles University in Prague, Czech Republic

Digital Object Identifier: 10.5220/0005828005520559

Proceedings of ICAART 2016, ISBN: 978-989-758-172-4

Quick Abstract

The overall performance of classical planner depends heavily on the domain model which can be enhanced by adding control knowledge and heuristics. Both of them are known techniques which can boost the search process in exchange for some computational overhead needed for their repeated evaluation. Our experiments show that the gain from usage of heuristics and control knowledge is evolving throughout the search process and also depends on the type of search algorithm. We demonstrate the idea using the branch-and-bound and iterative deepening search techniques, both implemented in the Picat planning module.

Related Ontology Subjects/Areas/Topics (9)

Artificial Intelligence	Intelligent Control Systems and Optimization	Simulation and Modeling
Formal Methods	Knowledge Representation and Reasoning	State Space Search
Informatics in Control, Automation and Robotics	Planning and Scheduling	Symbolic Systems

Database Architectures: Current State and Development

Topics: Information Integration; Semi-Structured and Unstructured Data; Big Data; Architectural Concepts; Data Management for Analytics; Nosql Databases; Database Architecture and Performance

Authors: Jaroslav Pokorny ¹ and Karel Richta ²

Affiliations: ¹ Charles University, Czech Republic , ² Czech Technical University, Czech Republic

Digital Object Identifier: 10.5220/0005512001520161

Proceedings of DATA 2015, ISBN: 978-989-758-103-8

Quick Abstract

The paper presents shortly a history and development of database management tools in last decade. The movement towards a higher database performance and database scalability is discussed in the context to requirements of practice. These include Big Data and Big Analytics as driving forces that together with a progress in hardware development led to new DBMS architectures. We describe and evaluate them mainly in terms of their scalability. We focus also on a usability of these architectures which depends strongly on application environment. We also mention more complex software stacks containing tools for management of real-time analysis and intelligent processes.

Related Ontology Subjects/Areas/Topics (20)

Architectural Concepts	Data Management for Analytics	Knowledge Engineering and Ontology Development
Artificial Intelligence	Database Architecture and Performance	Knowledge-Based Systems
Big Data	Databases and Data Security	Nosql Databases
Business Analytics	e-Business	Ontologies and the Semantic Web
Collaboration and e-Services	Enterprise Information Systems	Semi-Structured and Unstructured Data
Data Engineering	Information Integration	Symbolic Systems
Data Management and Quality	Integration/Interoperability

e-Shop User Preferences via User Behavior

Topics: Web Services; Entertainment; Quality-Of-Service; Business Performance; Transaction Support; Goal Setting and Setting; Technologies and Tools

Authors: Peter Vojtáš and Ladislav Peška

Affiliation: Charles University, Czech Republic

Digital Object Identifier: 10.5220/0005102300680075

Proceedings of ICE-B 2014/ICETE, ISBN: 978-989-758-043-7

Quick Abstract

We deal with the problem of using user behavior for business relevant analytic task processing. We describe our acquaintance with preference learning from behavior data from an e-shop. Based on our experience and problems we propose a model for collecting (java script tracking) and processing user behavior data. We present several results of offline experiments on real production data. We show that mere data on users (implicit) behavior are sufficient for improvement of prediction of user preference. As a future work we present richer data on time dependent user behavior.

Related Ontology Subjects/Areas/Topics (26)

Applications	Entertainment	Software Engineering Methods and Techniques
Business Performance	Goal Setting and Setting	Sustainable e-Business
Cloud Computing	Logistics	Technologies and Tools
Collaboration and e-Services	Mobile Software and Services	Technology Platforms
Data Communication Networking	Ontologies and the Semantic Web	Telecommunications
Data Engineering	Quality-Of-Service	Transaction Support
e-Business	Services Science	Web Services
Enterprise Engineering	Software Agents and Internet Computing	Wireless Information Networks and Systems
Enterprise Information Systems	Software Engineering

Highly Scalable Sort-merge Join Algorithm for RDF Querying

Topics: Query Processing and Optimization; Nosql Databases; Database Architecture and Performance

Authors: Zbyněk Falt , Miroslav Čermák and Filip Zavoral

Affiliation: Charles University, Czech Republic

Digital Object Identifier: 10.5220/0004489702930300

Proceedings of DATA 2013, ISBN: 978-989-8565-67-9

Quick Abstract

In this paper, we introduce a highly scalable sort-merge join algorithm for RDF databases. The algorithm is designed especially for streaming systems; besides task and data parallelism, it also tries to exploit the pipeline parallelism in order to increase its scalability. Additionally, we focused on handling skewed data correctly and efficiently; the algorithm scales well regardless of the data distribution.

Related Ontology Subjects/Areas/Topics (5)

Data Engineering		Databases and Data Security		Query Processing and Optimization
Database Architecture and Performance		Nosql Databases

Planning and Reactive Agents in Dynamic Game Environments - An Experimental Study

Topics: Planning and Scheduling; Reactive AI; Task Planning and Execution

Authors: Roman Barták , Cyril Brom , Martin Černý and Jakub Gemrot

Affiliation: Charles University in Prague, Czech Republic

Digital Object Identifier: 10.5220/0004254202340240

Proceedings of ICAART 2013, ISBN: 978-989-8565-38-9

Quick Abstract

Many contemporary computer games can be described as dynamic real-time simulations inhabited by autonomous intelligent virtual agents (IVAs) where most of the environmental structure is immutable and navigating through the environment is one of the most common activities. Though controlling the behaviour of such agents seems perfectly suited for action planning techniques, planning is not widely adopted in existing games. This paper contributes to discussion whether the current academic planning technology is ready for integration to existing games and under which conditions. The paper compares reactive techniques to classical planning in handling the action selection problem for IVAs in game-like environments. Several existing classical planners that occupied top positions in the International Planning Competition were connected to the virtual environment of Unreal Development Kit via the Pogamut platform. Performance of IVAs employing those planners and IVAs with reactive architecture was measured on a class of game-inspired maze-like test environments under different levels of external interference. It was shown that agents employing classical planning techniques outperform reactive agents if the size of the planning problem is small or if the environment changes are either hostile to the agent or not very frequent.

Related Ontology Subjects/Areas/Topics (11)

Agents	Intelligent Control Systems and Optimization	Soft Computing
Artificial Intelligence	Planning and Scheduling	Symbolic Systems
Formal Methods	Reactive AI	Task Planning and Execution
Informatics in Control, Automation and Robotics	Simulation and Modeling