91. Phase equilibrium measurements and data correlation for the ternary system oleic acid + 1-octanol + carbon dioxideChiara Giulia Laudani, Mateja Primožič, Željko Knez, Maja Leitgeb, 2009, izvirni znanstveni članek Opis: A study of the high-pressure phase equilibria in the ternary system oleic acid/1- octanol/supercritical CO2 was performed to obtain information for optimization of enzymatic synthesis of n-octyl oleate. Equilibrium data were measured at temperatures of 308.15, 323.15 and 343.15 K over a pressure range from 1 to 25 MPa. Two different apparatuses: a Variable Volume View Cell and a Batch Stirred Tank were used employing synthetic and static-analytic measurement methods, respectively. The measured solubility of dense CO2 in the binary liquid mixture oleic acid/1-octanol covered the range from 0.0781 to 0.7686 of CO2 molar fraction. CO2 solubility increased with increasing pressure up to 10 MPa. At higher pressures, no significant increase was observed. The Soave-Redlich-Kwong equation-of-state (SRK-EoS) with quadratic mixing rules was successfully used for data correlation in the whole P-T-x region studied.
Ključne besede: data correlation, 1-octanol, oleic acid, supercritical carbon dioxide, Soave-Redlich-Kwong equation-of-state, vapor-liquid equilibria
Objavljeno v DKUM: 05.07.2017; Ogledov: 1558; Prenosov: 118
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92. A flexible microcontroller-based data acquisition deviceDarko Hercog, Bojan Gergič, 2014, izvirni znanstveni članek Opis: This paper presents a low-cost microcontroller-based data acquisition device. The key component of the presented solution is a configurable microcontroller-based device with an integrated USB transceiver and a 12-bit analogue-to-digital converter (ADC). The presented embedded DAQ device contains a preloaded program (firmware) that enables easy acquisition and generation of analogue and digital signals and data transfer between the device and the application running on a PC via USB bus. This device has been developed as a USB human interface device (HID). This USB class is natively supported by most of the operating systems and therefore any installation of additional USB drivers is unnecessary. The input/output peripheral of the presented device is not static but rather flexible, and could be easily configured to customised needs without changing the firmware. When using the developed configuration utility, a majority of chip pins can be configured as analogue input, digital input/output, PWM output or one of the SPI lines. In addition, LabVIEW drivers have been developed for this device. When using the developed drivers, data acquisition and signal processing algorithms as well as graphical user interface (GUI), can easily be developed using a well-known, industry proven, block oriented LabVIEW programming environment.
Ključne besede: data acquisition, DAQ, microcontroller, analogue-to-digital converter, ADC, USB, HID, LabVIEW, GUI, data logging
Objavljeno v DKUM: 22.06.2017; Ogledov: 1462; Prenosov: 399
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93. Predictions of experimentally observed stochastic ground vibrations induced by blastingSrđan Kostić, Matjaž Perc, Nebojša Vasović, Slobodan Trajković, 2013, izvirni znanstveni članek Opis: In the present paper, we investigate the blast induced ground motion recorded at the limestone quarry “Suva Vrela” near Kosjerić, which is located in the western part of Serbia. We examine the recorded signals by means of surrogate data methods and a determinism test, in order to determine whether the recorded ground velocity is stochastic or deterministic in nature. Longitudinal, transversal and the vertical ground motion component are analyzed at three monitoring points that are located at different distances from the blasting source. The analysis reveals that the recordings belong to a class of stationary linear stochastic processes with Gaussian inputs, which could be distorted by a monotonic, instantaneous, time-independent nonlinear function. Low determinism factors obtained with the determinism test further confirm the stochastic nature of the recordings. Guided by the outcome of time series analysis, we propose an improved prediction model for the peak particle velocity based on a neural network. We show that, while conventional predictors fail to provide acceptable prediction accuracy, the neural network model with four main blast parameters as input, namely total charge, maximum charge per delay, distance from the blasting source to the measuring point, and hole depth, delivers significantly more accurate predictions that may be applicable on site. We also perform a sensitivity analysis, which reveals that the distance from the blasting source has the strongest influence on the final value of the peak particle velocity. This is in full agreement with previous observations and theory, thus additionally validating our methodology and main conclusions.
Ključne besede: blasting, vibrations, surrogate data, deterministic chaos, stochasticity
Objavljeno v DKUM: 19.06.2017; Ogledov: 1069; Prenosov: 342
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94. Prediction of wine sensorial quality by routinely measured chemical propertiesAdriána Bednárová, Roman Kranvogl, Darinka Brodnjak-Vončina, Tjaša Jug, 2014, izvirni znanstveni članek Opis: The determination of the sensorial quality of wines is of great interest for wine consumers and producers since it declares the quality in most of the cases. The sensorial assays carried out by a group of experts are time-consuming and expensive especially when dealing with large batches of wines. Therefore, an attempt was made to assess the possibility of estimating the wine sensorial quality with using routinely measured chemical descriptors as predictors. For this purpose, 131 Slovenian red wine samples of different varieties and years of production were analysed and correlation and principal component analysis were applied to find inter-relations between the studied oenological descriptors. The method of artificial neural networks (ANNs) was utilised as the prediction tool for estimating overall sensorial quality of red wines. Each model was rigorously validated and sensitivity analysis was applied as a method for selecting the most important predictors. Consequently, acceptable results were obtained, when data representing only one year of production were included in the analysis. In this case, the coefficient of determination (R2) associated with training data was 0.95 and that for validation data was 0.90. When estimating sensorial quality in categorical form, 94 % and 85 % of correctly classified samples were achieved for training and validation subset, respectively.
Ključne besede: overall sensorial quality, prediction, Slovenian wine, artificial neural networks, multivariate data analysis
Objavljeno v DKUM: 03.04.2017; Ogledov: 1602; Prenosov: 403
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95. Big data for business ecosystem playersIgor Perko, Peter Ototsky, 2016, izvirni znanstveni članek Opis: In the provided research, some of the Big Data most prospective usage domains connect with distinguished player groups found in the business ecosystem. Literature analysis is used to identify the state of the art of Big Data related research in the major domains of its use—namely, individual marketing, health treatment, work opportunities, financial services, and security enforcement. System theory was used to identify business ecosystem major player types disrupted by Big Data: individuals, small and mid-sized enterprises, large organizations, information providers, and regulators. Relationships between the domains and players were explained through new Big Data opportunities and threats and by players’ responsive strategies. System dynamics was used to visualize relationships in the provided model.
Ključne besede: business ecosystems, Big Data, information providers, system dynamics
Objavljeno v DKUM: 03.04.2017; Ogledov: 1279; Prenosov: 372
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96. Correlates of depression in the slovenian working populationZalika Klemenc-Ketiš, Borut Peterlin, 2013, izvirni znanstveni članek Opis: This multicentre, cross-sectional observational study aimed to determine the prevalence of depression among the working population of Slovenia and identify factors correlating with higher prevalence of depression. It was conducted in three occupational medicine practices within major Slovenian primary health care centres. The study population consisted of 1,474 respondents [73.7 % of the invited participants, 889 (60.3 %) men and 585 (39.7 %) women with mean age of (40.5±9.8) years] who visited these practices for their regular check-ups from November 2010 to June 2012 and were asked to fill in a self-developed questionnaire and score depression on the Zung’s self-rating depression scale. According to the rating, 50 (3.4 %) respondents suffered from depression. In the multivariate analysis, depression correlated with the following independent variables: self-perceived exposure to chronic stress, positive family history of depression, and primary school education.
Ključne besede: mental diseases, primary health care, cross-sectional study, demographic data, family history
Objavljeno v DKUM: 30.03.2017; Ogledov: 1420; Prenosov: 355
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97. Algorithms for association rule learningRenata Akhmetshakirova, 2017, diplomsko delo Opis: One of the most popular methods of knowledge discovery in databases is the extraction of association rules. There are many different algorithms for association rule learning , which differ in space and time complexity. To perform a comparative analysis, we have implemented Apriori, Eclat and FP-growth algorithms and compared their time and memory consumption using synthetic and real databases. The analysis has shown that the FP-growth algorithm is the most efficient in the majority of cases.
Ključne besede: association rules, data mining, Apriori, Eclat, FP-growth
Objavljeno v DKUM: 24.02.2017; Ogledov: 2385; Prenosov: 108
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98. PRAVNI VIDIKI VELIKEGA PODATKOVJA (BIG DATA)Hana Kosi, 2016, diplomsko delo Opis: Ljudje vsakodnevno z uporabo mobilnih aplikacij, brskanjem po spletu in celo pri nakupovanju v trgovini največkrat nezavedno in prostovoljno delimo svoje osebne podatke. Ker se vse več spletnih podjetij in drugih organizacij za lažje in boljše delovanje ukvarja z zbiranjem in obdelovanjem osebnih podatkov, se postavlja vedno pomembnejše vprašanje varstva osebnih podatkov. Prvi pravno zvezujoči mednarodni sporazum na področju varstva osebnih podatkov je oblikoval Svet Evrope in ga leta 1981 predstavil kot Konvencijo o varstvu posameznika glede na avtomatsko obdelavo osebnih podatkov. Evropska unija je v zadnjih 30. letih zaradi vedno naprednejše informacijske tehnologije na tem področju oblikovala obsežno zakonodajo, katere najpomembnejši dokumenti v povezavi z varstvom podatkov so Direktiva 95/46/ES o varstvu posameznikov pri obdelavi osebnih podatkov in o prostem pretoku takih podatkov in Listina Evropske unije o temeljnih pravicah, zadnje spremembe pa sta prinesli Uredba (EU) 2016/679 o varstvu posameznikov pri obdelavi osebnih podatkov in o prostem pretoku takih podatkov ter o razveljavitvi Direktive 95/46/ES in Direktiva (EU) 2016/680 o varstvu posameznikov pri obdelavi osebnih podatkov, ki jih pristojni organi obdelujejo za namene preprečevanja, preiskovanja, odkrivanja ali pregona kaznivih dejanj ali izvrševanja kazenskih sankcij, in o prostem pretoku takih podatkov ter o razveljavitvi Okvirnega sklepa Sveta 2008/977/PNZ.
Zbiranje in obdelovanje podatkov igra pomembno vlogo tudi z vidika konkurence, natančneje pri oblikovanju tržne moči posameznih podjetij in vstopnih ovir, ki jih ta podjetja ustvarjajo za majhna in še ne uveljavljena podjetja. Na tem področju sta francoski in nemški organ za konkurenco maja letos objavila skupno poročilo o velikem podatkovju in konkurenčnem pravu, ki vsebuje raziskavo o tem, na katere načine lahko podatki postanejo vir tržne moči in kako lahko dostop do podatkov s povečanjem preglednosti trga izkrivlja konkurenco, vsebuje pa tudi predstavitev ravnanja s podatki, ki lahko kršijo konkurenčno zakonodajo. V želji po boljši in lažji dostopnosti do podatkov podjetja posegajo po številnih protikonkurenčnih ravnanjih, kot so združevanje podjetij in izključujoča ravnanja, kamor spadajo zavrnitev dostopa, diskriminatoren dostop do podatkov, izključujoči dogovori in vezane prodaje ter navzkrižna uporaba podatkovnih nizov, podatki pa so lahko tudi sredstvo cenovne diskriminacije.
Ključne besede: veliko podatkovje, varstvo zasebnosti, varstvo osebnih podatkov, konkurenca, zakonodaja Evropske unije, Big Data
Objavljeno v DKUM: 02.12.2016; Ogledov: 19480; Prenosov: 241
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99. UPORABA VELIKE KOLIČINE PODATKOV ZA POTREBE INFORMACIJSKIH REŠITEV UPRAVLJANJA ODNOSOV S STRANKAMIJernej Omulec, 2016, magistrsko delo Opis: Številna podjetja se že poslužujejo upravljanja odnosov s strankami in CRM-rešitev. CRM lahko definiramo kot upravljavsko filozofijo, kjer se cilji podjetja najlažje dosežejo skozi identificiranje in zadovoljevanje potrošniških želj (tako izjavljenih kot tudi neizjavljenih) in potreb. CRM pomaga pri profiliranju potencialnih strank, razumevanju njihovih potreb in grajenju odnosov, tako da se jim ponudi najprimernejši izdelek.
Na drugi strani pa imamo Big Data, ki sicer po podjetjih še ni tako razširjena zadeva kot CRM, vendar vedno bolj pridobiva na popularnosti. Big Data so nizi podatkov, katerih obseg presega sposobnosti zajema, hranjenja, upravljanja in analiziranja s pomočjo klasičnih programskih rešitev.
Uvedba CRM-rešitve in integracija Big Data sami po sebi pa ne bosta prinesli dobička. Za izboljšanja delovanja podjetja, poslovnega izida in prihodkov potrebujemo ljudi, ki bodo dana orodja in podatke znali analizirati in izkoristiti v svoj prid. Ne smemo pozabiti ene precej pomembne stvari. Lahko uvedemo najboljšo in najdražjo rešitev in nam ta ne bo prav nič koristila, če je sami ne bomo znali maksimalno izkoristiti. CRM-rešitve in Big Data sta samo pripomočka, ki nam precej olajšata razumevanje strank, vendar sama po sebi ne bosta storila ničesar.
Ključne besede: Big Data, velike količine podatkov, CRM, upravljanje odnosov s strankami, Salesforce, Datameer.
Objavljeno v DKUM: 24.10.2016; Ogledov: 1413; Prenosov: 198
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