Involving environmental informatics in Croatian technical studies

Cilj rada je istražiti stupanj znanja studenata o informatici okoliša. Istraživanje obuhvaća veliki uzorak studenata koji su anonimni a odgovorili su na svih 10 pitanja iz ankete koja se odnose na informatiku okoliša. Rezultati ankete statistički su analizirani čime je stvorena osnova za zaključivanje o razini znanja studenata tehničkog područja o informatici okoliša. Rezultati nisu zadovoljavajući pa je istraživanje prošireno i na njihove sveučilišne nastavnike da bi se istražio uzrok postignutih rezultata. Istraživanje je pokazalo da se premalo koriste metode i algoritmi za upravljanje podacima kao što su strukture podataka, rudarenje i pohranjivanje podataka, te posebne statističke metode i algoritmi za modeliranje poslovnih pravila za prikupljanje i upravljanje podacima. Uloga velikih skupova podataka (eng. big data) u promatranom području je značajna zbog česte pojave vremenskih serija u podacima i metode komparacije promatranih sustava post hoc analize kada rudarenje podataka nije dostupno, a posebno kada se želi prepoznati uzorak ponašanja promatranih sustava i njihovih komponenata.The paper presents research degree students\u27 knowledge about the Environmental Informatics. The research covered a sample of 31 students who anonymously responded to 10 survey questions about the environmental informatics. The survey results were statistically analysed to arrive at the conclusions about the students\u27 knowledge in the technical field of Environmental Informatics. The results are not satisfying, so the survey was expanded by surveying their university teachers, to investigate the reason for the given results. Research shows the insufficient use of methods and algorithms for data management such as data structures, data mining and storage, and special statistical methods and algorithms for business rules modelling for the collection and manipulation of data. The role of big data in this area is important to manage a time series of data, and a comparative analysis of the observed systems post hoc analysis of data mining is not available, especially when it comes to recognising the behaviour of systems and their components

Comparison of the Information Technology Development in Slovakia and Hungary

Nowadays the role of information is increasingly important, so every company has to provide the efficient procurement, processing, storage and visualization of this special resource in hope to stay competitive. More and more enterprises introduce Enterprise Resource Planning System to be able to perform the listed functions. The article illustrates the usage of these systems in Hungary and Slovakia, as well as tests the following presumption: the level of Information Technology (IT) development is lower in Hungary than our northern neighbor

A Review on the Application of Natural Computing in Environmental Informatics

Natural computing offers new opportunities to understand, model and analyze the complexity of the physical and human-created environment. This paper examines the application of natural computing in environmental informatics, by investigating related work in this research field. Various nature-inspired techniques are presented, which have been employed to solve different relevant problems. Advantages and disadvantages of these techniques are discussed, together with analysis of how natural computing is generally used in environmental research.Comment: Proc. of EnviroInfo 201

Storage Solutions for Big Data Systems: A Qualitative Study and Comparison

Big data systems development is full of challenges in view of the variety of application areas and domains that this technology promises to serve. Typically, fundamental design decisions involved in big data systems design include choosing appropriate storage and computing infrastructures. In this age of heterogeneous systems that integrate different technologies for optimized solution to a specific real world problem, big data system are not an exception to any such rule. As far as the storage aspect of any big data system is concerned, the primary facet in this regard is a storage infrastructure and NoSQL seems to be the right technology that fulfills its requirements. However, every big data application has variable data characteristics and thus, the corresponding data fits into a different data model. This paper presents feature and use case analysis and comparison of the four main data models namely document oriented, key value, graph and wide column. Moreover, a feature analysis of 80 NoSQL solutions has been provided, elaborating on the criteria and points that a developer must consider while making a possible choice. Typically, big data storage needs to communicate with the execution engine and other processing and visualization technologies to create a comprehensive solution. This brings forth second facet of big data storage, big data file formats, into picture. The second half of the research paper compares the advantages, shortcomings and possible use cases of available big data file formats for Hadoop, which is the foundation for most big data computing technologies. Decentralized storage and blockchain are seen as the next generation of big data storage and its challenges and future prospects have also been discussed