43 research outputs found

    Infrastructure for collaborating data-researchers in a smart grid pilot

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    A large amount of stakeholders are often involved in Smart Grid projects. Each partner has its own way of storing, representing and accessing its data. An integrated data storage and a joint online analytical mining infrastructure is needed to limit the amount of duplicated work and to raise the overall security of the system. The proposed infrastructure is composed of standard application software and an in-house developed data analysis tool that allows researchers to add and share their own functionality without compromising security

    Data Mining in the industry

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    The monograph proposes a suitable process application for a knowledge discovery process in industry databases. The entire process was divided into distinct stages. First, the subject matter to be resolved by employing the knowledge discovery process was identified. Next, the data of the production system was analysed. Several mining models, in which various methods and techniques of data mining in dependence on analyzed data and subject matter investigated, were developed. In order to examine how interesting and useful the knowledge discovered was, it was applied to a production system, whose data operated as input data to the process of KDD. The results achieved proved that the knowledge discovered was useful and a modified simulation model achieved the predicted behaviour. Finally, the proposal of the process application methodology of knowledge discovery in industry databases is discussed. This methodology describes the particular steps of implementing the process of KDD. The proposed methodology can help identify specific requirements and potential problems in the process stages that might be encountered in the course of its application in the industry

    Dynamic Behavioral Analysis of Malicious Software with Norman Sandbox

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    Current signature-based Anti-Virus (AV) detection approaches take, on average, two weeks from discovery to definition update release to AV users. In addition, these signatures get stale quickly: AV products miss between 25%-80% of new malicious software within a week of not updating. This thesis researches and develops a detection/classification mechanism for malicious software through statistical analysis of dynamic malware behavior. Several characteristics for each behavior type were stored and analyzed such as function DLL names, function parameters, exception thread ids, exception opcodes, pages accessed during faults, port numbers, connection types, and IP addresses. Behavioral data was collected via Norman Sandbox for storage and analysis. We proposed to find which statistical measures and metrics can be collected for use in the detection and classification of malware. We conclude that our logging and cataloging procedure is a potentially viable method in creating behavior-based malicious software detection and classification mechanisms

    Dynamic Behavioral Analysis of Malicious Software with Norman Sandbox

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    Current signature-based Anti-Virus (AV) detection approaches take, on average, two weeks from discovery to definition update release to AV users. In addition, these signatures get stale quickly: AV products miss between 25%-80% of new malicious software within a week of not updating. This thesis researches and develops a detection/classification mechanism for malicious software through statistical analysis of dynamic malware behavior. Several characteristics for each behavior type were stored and analyzed such as function DLL names, function parameters, exception thread ids, exception opcodes, pages accessed during faults, port numbers, connection types, and IP addresses. Behavioral data was collected via Norman Sandbox for storage and analysis. We proposed to find which statistical measures and metrics can be collected for use in the detection and classification of malware. We conclude that our logging and cataloging procedure is a potentially viable method in creating behavior-based malicious software detection and classification mechanisms

    Usporedba alata za vizualizaciju podataka

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    Informacija se u modernom poslovanju smatra resursom. Kvaliteta poslovne odluke u pozitivnom je korelacijskom odnosu sa kvalitetom dostupnih informacija. Poslovna inteligencija proces je prikupljanja relevantnih i dostupnih informacija informacija te se danas smatra jednom od osnovnih konkurentskih prednosti. Višedimenzijske podatkovne strukture temelj su moderne poslovne inteligencije. Analize provedene nad takvim podacima često generiraju više novih pitanja nego što daju odgovora. Zbog ove problematike, moderna analitička rješenja usmjerena su na vizualizaciju podataka kako bi korisnik što brže mogao saznati esenciju nekog niza podataka. Tržište je danas puno alata za vizualizaciju podataka, a ovaj diplomski rad komparira najpopularnija rješenja. U nizu alata odabrani su Tableau i Power BI kao tržišni predvodnici te su detaljno uspoređeni prema funkcionalnostima ali i empirijski. Ovaj diplomski rad pokušava dati odgovor na pitanje koje rješenje je najprimjerenije za određenog korisnika, odnosno organizaciju.Information is being considered as a resource in modern business. The quality of a business decision is in a positive correlation with the quality of available information. Business intelligence is a process of collecting relevant and accessible information and is one of the core competitive advantages in the modern market. Multi-dimensional data structures are the foundation of modern business intelligence. Analysis of such data often generates more questions than answers which creates a problem for the decision maker. Therefore, modern analytical solutions are more focused on data visualization than ever before. Using visual techniques, user can find out the essence of a certain data within seconds. There are a lot of tools that support data visualization in the modern market. Tableau and Power BI were chosen as market leaders, and were compared in detail regarding their functionalities. User experience experiment was also carried out to see which of these two performs better. This master thesis is trying to help users choose which visualization tool is the most appropriate for them or their organization

    Usporedba alata za vizualizaciju podataka

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    Informacija se u modernom poslovanju smatra resursom. Kvaliteta poslovne odluke u pozitivnom je korelacijskom odnosu sa kvalitetom dostupnih informacija. Poslovna inteligencija proces je prikupljanja relevantnih i dostupnih informacija informacija te se danas smatra jednom od osnovnih konkurentskih prednosti. Višedimenzijske podatkovne strukture temelj su moderne poslovne inteligencije. Analize provedene nad takvim podacima često generiraju više novih pitanja nego što daju odgovora. Zbog ove problematike, moderna analitička rješenja usmjerena su na vizualizaciju podataka kako bi korisnik što brže mogao saznati esenciju nekog niza podataka. Tržište je danas puno alata za vizualizaciju podataka, a ovaj diplomski rad komparira najpopularnija rješenja. U nizu alata odabrani su Tableau i Power BI kao tržišni predvodnici te su detaljno uspoređeni prema funkcionalnostima ali i empirijski. Ovaj diplomski rad pokušava dati odgovor na pitanje koje rješenje je najprimjerenije za određenog korisnika, odnosno organizaciju.Information is being considered as a resource in modern business. The quality of a business decision is in a positive correlation with the quality of available information. Business intelligence is a process of collecting relevant and accessible information and is one of the core competitive advantages in the modern market. Multi-dimensional data structures are the foundation of modern business intelligence. Analysis of such data often generates more questions than answers which creates a problem for the decision maker. Therefore, modern analytical solutions are more focused on data visualization than ever before. Using visual techniques, user can find out the essence of a certain data within seconds. There are a lot of tools that support data visualization in the modern market. Tableau and Power BI were chosen as market leaders, and were compared in detail regarding their functionalities. User experience experiment was also carried out to see which of these two performs better. This master thesis is trying to help users choose which visualization tool is the most appropriate for them or their organization

    Usporedba alata za vizualizaciju podataka

    Get PDF
    Informacija se u modernom poslovanju smatra resursom. Kvaliteta poslovne odluke u pozitivnom je korelacijskom odnosu sa kvalitetom dostupnih informacija. Poslovna inteligencija proces je prikupljanja relevantnih i dostupnih informacija informacija te se danas smatra jednom od osnovnih konkurentskih prednosti. Višedimenzijske podatkovne strukture temelj su moderne poslovne inteligencije. Analize provedene nad takvim podacima često generiraju više novih pitanja nego što daju odgovora. Zbog ove problematike, moderna analitička rješenja usmjerena su na vizualizaciju podataka kako bi korisnik što brže mogao saznati esenciju nekog niza podataka. Tržište je danas puno alata za vizualizaciju podataka, a ovaj diplomski rad komparira najpopularnija rješenja. U nizu alata odabrani su Tableau i Power BI kao tržišni predvodnici te su detaljno uspoređeni prema funkcionalnostima ali i empirijski. Ovaj diplomski rad pokušava dati odgovor na pitanje koje rješenje je najprimjerenije za određenog korisnika, odnosno organizaciju.Information is being considered as a resource in modern business. The quality of a business decision is in a positive correlation with the quality of available information. Business intelligence is a process of collecting relevant and accessible information and is one of the core competitive advantages in the modern market. Multi-dimensional data structures are the foundation of modern business intelligence. Analysis of such data often generates more questions than answers which creates a problem for the decision maker. Therefore, modern analytical solutions are more focused on data visualization than ever before. Using visual techniques, user can find out the essence of a certain data within seconds. There are a lot of tools that support data visualization in the modern market. Tableau and Power BI were chosen as market leaders, and were compared in detail regarding their functionalities. User experience experiment was also carried out to see which of these two performs better. This master thesis is trying to help users choose which visualization tool is the most appropriate for them or their organization

    An OLAP-GIS System for Numerical-Spatial Problem Solving in Community Health Assessment Analysis

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    Community health assessment (CHA) professionals who use information technology need a complete system that is capable of supporting numerical-spatial problem solving. On-Line Analytical Processing (OLAP) is a multidimensional data warehouse technique that is commonly used as a decision support system in standard industry. Coupling OLAP with Geospatial Information System (GIS) offers the potential for a very powerful system. For this work, OLAP and GIS were combined to develop the Spatial OLAP Visualization and Analysis Tool (SOVAT) for numerical-spatial problem solving. In addition to the development of this system, this dissertation describes three studies in relation to this work: a usability study, a CHA survey, and a summative evaluation.The purpose of the usability study was to identify human-computer interaction issues. Fifteen participants took part in the study. Three participants per round used the system to complete typical numerical-spatial tasks. Objective and subjective results were analyzed after each round and system modifications were implemented. The result of this study was a novel OLAP-GIS system streamlined for the purposes of numerical-spatial problem solving.The online CHA survey aimed to identify the information technology currently used for numerical-spatial problem solving. The survey was sent to CHA professionals and allowed for them to record the individual technologies they used during specific steps of a numerical-spatial routine. In total, 27 participants completed the survey. Results favored SPSS for numerical-related steps and GIS for spatial-related steps.Next, a summative within-subjects crossover design compared SOVAT to the combined use of SPSS and GIS (termed SPSS-GIS) for numerical-spatial problem solving. Twelve individuals from the health sciences at the University of Pittsburgh participated. Half were randomly selected to use SOVAT first, while the other half used SPSS-GIS first. In the second session, they used the alternate application. Objective and subjective results favored SOVAT over SPSS-GIS. Inferential statistics were analyzed using linear mixed model analysis. At the .01 level, SOVAT was statistically significant from SPSS-GIS for satisfaction and time (p < .002).The results demonstrate the potential for OLAP-GIS in CHA analysis. Future work will explore the impact of an OLAP-GIS system in other areas of public health

    CIRA annual report FY 2016/2017

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    Reporting period April 1, 2016-March 31, 2017
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