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Linearna regresija najčešći je oblik regresijske analize. Ako su pretpostavke normalnosti, homogenosti i nezavisnosti slučajnih grešaka ispunjene, metoda najmanjih kvadrata daje egzaktne rezultate. U praksi su pretpostavke često oslabljene ili čak nedostižne, čime se traži alternativa u procjeni koeficijenata. Metode ponovnog uzorkovanja koje se zasnivaju na zakonu velikih brojeva nameću se kao moguće potencijalno rješenje. U ovom radu proučava se bootstrap metoda, koja polazi od ideje da statistički uzorak već sadrži sve dostupne informacije o nekoj funkciji distribucije F te ponovnim uzorkovanjem dobiva se uzorak koji pripada toj istoj distribuciji. U središtu interesa su dva algoritma - metoda uzorkovanja podataka i metoda uzorkovanja grešaka. U prvom poglavlju iznose se osnovni pojmovi teorije vjerojatnosti te se predstavlja bootstrap metoda. U drugom poglavlju definiran je jednostavan model linearne regresije te je iznesena ideja bootstrap metode za distribuciju procjenitelja. Treće poglavlje je proširivanje drugog poglavlja na višedimenzionalan slučaj. Također, predstavljen je pojam predikcije te uloga bootstrap metode u tom pogledu. U četvrtom poglavlju izloženi su praktični rezultati dobiveni raznim simulacijama u programskom jeziku R. Dodatak na kraju rada je peto poglavlje, gdje se nalazi kod korišten za provođenje simulacija. Linear regression is the most common form of regression analysis. If the assumptions of normality, homogeneity and independence of random errors are satisfied, the least square method gives exact results. In practice, assumptions are often difficult to reach or even elusive, which requires looking for an alternative. Resampling methods, based on the law of large numbers, are offered as a possible potential solution. In this paper, the bootstrap method is studied, which is based on the idea that a statistical sample already contains all available information about a distribution function F, so by resampling, we get a sample that belongs to that same distribution. Two algorithms are particularly discussed – the data resampling method and the errors resampling method. In the first chapter, the basic concepts of probability theory and the bootstrap method are presented. In the second chapter, a simple linear regression model is defined and the idea of the bootstrap method for the distribution of estimators is exposed. The third chapter is an extension of the second chapter to a multidimensional case. Also, the concept of prediction and the role of the bootstrap method in this respect are presented. In the fourth chapter, the practical results obtained by conducting various simulations in the R programming language are exposed. The code used to perform the simulations is presented at the end of the paper, in the fifth chapter.

U radu su prikazane osnove Metode najmanjih kvadrata, počevši od regresijske analize. Metodu najmanjih kvadrata postavio je 1795. g. Carl Friedrich Gauss. U praktičnom dijelu izvršena su mjerenja promjene dužine opruge u zavisnosti od opterećenja. Oprugu, kao i zakon elastičnosti postavio je Robert Hooke, pa se i zakon zove po njemu – Hookove zakon. Dobivene vrijednosti ucrtane su u graf, koji predstavlja početak dijagrama naprezanja. Linearna funkcija koja najbolje odgovara dobivenim točkama izračunata je ručno Metodom najmanjih kvadrata. Dobiveni koeficijenti pravca provjereni su korištenjem aplikacije Statistica. The paper presents the basics of the Method of Least Squares, starting with regression analysis. The method of least squares was established in 1795 by Mr. Carl Friedrich Gauss. In the practical part, measurements were made of the change in spring length depending on the load. The spring, as well as the law of elasticity, was established by Robert Hooke, so the law is named after him - Hooke's law. The obtained values are plotted in a graph, which represents the beginning of the stress diagram. The linear function that best fits the obtained points was calculated manually by the Method of Least Squares. The obtained direction coefficients were checked using the Statistica application.

U ovom se istraživanju ispituje model kolotraženja koji je prikladniji za savitljive kolničke konstrukcije na cestama s malim volumenom prometa u Indiji. Kolotrazi na cesti izravno utječu na različite aspekte kao što su svojstva kolnika, sigurnost, udobnost vožnje i trajanje putovanja. Sukladno tome, ovo je istraživanje provedeno na 173 probne dionice cesta s malim volumenom prometa, a matematički model kolotraženja razvijen je pomoću višestruke regresijske analize. U modelu je kolotraženje varijabla odgovora, a broj gospodarskih vozila po danu, oborine, nosivost posteljice (kao modificirani strukturni broj) i starost kolnika su eksplanatorne varijable. Model je statistički potvrđen i primijenjen za predviđanje kolotraga na cesti, a učinkovitost predviđanja je potvrđena. Pogreška između terenskih podataka i procijenjenih vrijednosti je unutar 5 %., This study considers a road rutting model better-suited for the flexible pavements in the low-volume roads of India. The rutting on a road directly affects various aspects such as the pavement performance, safety, driving comfort, and travel time. Accordingly, this study is conducted on 173 test sections of low-volume roads, and a mathematical rutting model is developed using a multiple regression analysis. In the model, the rutting is the response variable, whereas the commercial vehicles per day, rainfall, subgrade strength (as a modified structural number), and pavement age are the explanatory variables. The model is statistically validated and used to forecast road rutting and the effectiveness of the rutting prediction is confirmed. The error between the field data and estimated values is within 5 %.

Svrha rada jest istražiti kako „velikih pet“ obilježja ličnosti utječu na stilove odlučivanja potrošača o kupnji digitalnih proizvoda. Empirijski podaci prikupljeni su anketnim istraživanjem na uzorku koji su činila 302 ispitanika. Prikupljeni podaci obrađeni su primjenom eksplorativne faktorske analize, izračunom Cronbachovih alfa koeficijenata, primjenom višestruke regresijske analize i metoda deskriptivne statistike. Rezultati istraživanja pokazuju da svih pet obilježja ličnosti utječe na ukupno šest stilova odlučivanja o kupnji digitalnih proizvoda. Istraživanja utjecaja obilježja ličnosti potrošača na njihov stil odlučivanja o kupnji, osobito u kontekstu digitalnih proizvoda, još uvijek nisu dovoljno zastupljena u znanstvenoj literaturi pa nalazi provedenog istraživanja pridonose dubljem razumijevanju ovog aspekta potrošačkog ponašanja. Stoga se spoznaje dobivene istraživanjem mogu smatrati korisnim i za razvoj teorije i za poslovnu praksu.

Dosadašnja istraživanja dovela su do zaključka da se veliki broj prometnih nesreća događa na prijelazu s pravca u horizontalnu krivinu, što upućuje na to da se među uzrocima prometnih nesreća, uz pogreške samih vozača mogu razmatrati i geometrijske karakteristike ceste. S ciljem povećanja razine sigurnosti u prometu provode se nove analize i istraživanja. U radu su prikazani postojeći modeli koji su obrađivali fenomen usporenja na prijelazu s pravca u horizontalnu krivinu na temelju podataka o geometrijskim karakteristikama ceste. Obradom podataka mjerenih od strane 20 vozača na dionici Vrlika – Sinj, izrađeni su regresijski modeli intenziteta usporenja vozila, napravljena je usporedba s nekim od postojećih modela te su doneseni zaključci o utjecaju geometrijskih karakteristika ceste na intenzitet usporenja vozila., Previous research has led to the conclusion that a large number of traffic accidents occur at the transition from an approach tangent to a horizontal curve, which indicates that among the causes of traffic accidents, in addition to the mistakes of the drivers themselves, the geometric characteristics of the road can also be considered. With the aim of increasing the level of traffic safety, new analyses and research are being carried out. The paper presents some previous models that processed the phenomenon of deceleration at the transition from an approach tangent to a horizontal curve based on data on the geometric characteristics of the road. By processing the data measured by 20 drivers on the section Vrlika - Sinj, regression models of the intensity of vehicle deceleration were created, a comparison was made with some of the existing models, and conclusions were drawn about the influence of the geometric characteristics of the road on the intensity of vehicle deceleration.

U ovom radu najprije smo objasnili što je regresijska analiza i koji je njezin glavni cilj te pokazali koje su glavne razlike između linearne i logističke regresijske analize. Zatim smo definirali logistički model, objasnili metodu maksimalne vjerodostojnosti koju koristimo za procjenu parametara, pokazali na koji način pronalazimo najbolji model te kako interpretiramo parametre modela. Također smo definirali i ROC krivulju te objasnili njezino značenje. Sve to smo zatim primijenili i na praktičnom primjeru. Glavni cilj nam je bio pronaći koje varijable i koliko statistički značajno utječu na to da dijabetička polineuropatija bude bolna u odnosu na bezbolnu. Koristili smo bazu koja sadrži 22 varijable (zdrastveni podaci) o 100 pacijenata. Analizu smo proveli primjenom U ovom radu najprije smo objasnili što je regresijska analiza i koji je njezin glavni cilj te pokazali koje su glavne razlike izmedu linearne i logističke regresijske analize. Zatim smo definirali logistički model, objasnili metodu maksimalne vjerodostojnosti koju koristimo za procjenu parametara, pokazali na koji način pronalazimo najbolji model te kako interpretiramo parametre modela. Također smo definirali i ROC krivulju te objasnili njezino značenje. Sve to smo zatim primijenili i na praktičnom primjeru. Glavni cilj nam je bio pronaći koje varijable i koliko statistički značajno utječu na to da dijabetička polineuropatija bude bolna u odnosu na bezbolnu. Koristili smo bazu koja sadrži 22 varijable (zdrastveni podaci) o 100 pacijenata. Analizu smo proveli primjenom univarijatne i multivarijatne logističke regresije te stepwise selekcijom. Zaključak je da su statistički najznačajnije varijable Tramadol (lijek) i PF (fizičko funkcioniranje).m. Zaključak je da su statistički najznačajnije varijable Tramadol (lijek) i PF (fizičko funkcioniranje). In this thesis it was first explained what is regression analysis and what is its main goal, it was also shown what are the main differences between linear and logistic regression analysis. Then the logistic model was defined, maximum likelihood method was explained which is used for parameters estimation, it was shown in which way the best model is found and how model parameters are interpreted. Also, ROC curve was defined and its meaning was explained. All of that was applied on practical example. Main goal was to found which variables and statistically to which extent they influence on diabetic polyneuropathy to be painful or painless. Database with 22 variables (health data) for 100 patient records was used. Analysis was carried out by applying univariate and multivariate logistic regression and the stepwise selection. It was concluded that the most statistically significant variables are Tramadol (medicament) and PH (physical functioning).

V magistrski nalogi smo analizirali vpliv avtoceste na cene stanovanj v jugovzhodni Sloveniji. V analizi smo uporabili podatke evidence trga nepremičnin, registra nepremičnini ter osi državnih cest za obdobje 2007 do 2020. Analizo vpliva oddaljenosti avtoceste in priključkov na avtocesto na ceno stanovanj smo izvedli s pomočjo statističnega modeliranja ter preizkušanja domnev. Analizirali smo stanovanja v skupno petindvajsetih občinah, od tega v devet obravnavanih občinah, tj. v občinah, preko katerih poteka avtocesta, ter v šestnajstih neposrednih sosednjih, t.i. kontrolnih, občinah. Izvedli smo tudi analizo lokacije prodaje stanovanja glede na oddaljenost od avtoceste in avtocestnega priključka. The master's thesis analysed the influence of the motorway on housing prices in south-eastern Slovenia. Data from real estate market records, the real estate register and the national road axis for the period 2007 to 2020 were used for the analyses. Statistical modelling and hypothesis testing were used to analyse the effects of highway distance and highway access on housing prices. We analysed housing sales in a total of twenty-five municipalities. Nine of these are crossed by the highway and sixteen of these are neighbouring municipalities. We also conducted an analysis of the location of housing sales by distance from the motorway and motorway access points.

Dosadašnja istraživanja dovela su do zaključka da se veliki broj prometnih nesreća događa na prijelazu s pravca u horizontalnu krivinu, što upućuje na to da se među uzrocima prometnih nesreća, uz pogreške samih vozača mogu razmatrati i geometrijske karakteristike ceste. S ciljem povećanja razine sigurnosti u prometu provode se nove analize i istraživanja. U radu su prikazani postojeći modeli koji su obrađivali fenomen usporenja na prijelazu s pravca u horizontalnu krivinu na temelju podataka o geometrijskim karakteristikama ceste. Obradom podataka mjerenih od strane 20 vozača na dionici Vrlika – Sinj, izrađeni su regresijski modeli intenziteta usporenja vozila, napravljena je usporedba s nekim od postojećih modela te su doneseni zaključci o utjecaju geometrijskih karakteristika ceste na intenzitet usporenja vozila. Previous research has led to the conclusion that a large number of traffic accidents occur at the transition from an approach tangent to a horizontal curve, which indicates that among the causes of traffic accidents, in addition to the mistakes of the drivers themselves, the geometric characteristics of the road can also be considered. With the aim of increasing the level of traffic safety, new analyses and research are being carried out. The paper presents some previous models that processed the phenomenon of deceleration at the transition from an approach tangent to a horizontal curve based on data on the geometric characteristics of the road. By processing the data measured by 20 drivers on the section Vrlika - Sinj, regression models of the intensity of vehicle deceleration were created, a comparison was made with some of the existing models, and conclusions were drawn about the influence of the geometric characteristics of the road on the intensity of vehicle deceleration.

Košarka je vrlo dinamična sportska igra. Brze i precizne kretnje svakog igrača nužne kako bi mogao pratiti ritam današnje košarke. Skok šut je definitivno element košarkaške igre koji je među najbitnijima u košarci pa tako i vrijeme trajanja njegova izvođenja radi mogućnosti upućivanja lopte prije dolaska obrambenog igrača, a najizvođeniji je upravo šut za 3 poena. Cilj ovog istraživanja je bio utvrditi imaju li određeni kinematički i kinetički parametri utjecaj na vrijeme trajanja skok šuta za tri poena. Istraživanje je provedeno na 13 košarkaša (dob: 15,54 ± 0,88 godina, visina: 188,99 ± 5,32 cm, težina: 73,02 ± 10,36 kg) koji su izveli 65 šuteva za 3 poena. Šutevi su analizirani pomoću Xsens (Awinda) sustava, 94 Fifty Smart Sensor Basketball i NOVEL uložaka za mjerenje sile, te su promatrane varijable (VCTPL, VIL, KRSŠ, F_D i F_L) pokazale značajan utjecaj (r2 =0,60) na varijablu vrijeme trajanja šuta (VTŠ) nakon provedene regresijske analize. Basketball is a very dynamic sports game. Fast and precise movements of each player are necessary to be able to follow the rhythm of today's basketball. Jump shot is definitely a skill in basketball that is among the most important in basketball, and so is the duration time of its execution due to the opportunity of shooting the ball before the arrival of a defensive player, and the most performed is the 3 point shot. The aim of this study was to determine whether certain kinematic and kinetic parameters have an impact on the duration of a three-point jump shot. The research was conducted on 13 basketball players (age: 15,54 ± 0,88 years, hight: 188,99 ± 5,32 cm, weight: 73,02 ± 10,36 kg) who performed 65 shots for 3 points. Shots were analyzed using the Xsens (Awinda) system, 94 Fifty Smart Sensor Basketball and NOVEL force measuring insoles, and the observed variables (VCTPL, VIL, KRSŠ, F_D and F_L) showed a significant effect (r2 = 0.60) on the variable duration of the shot (VTŠ) after the regression analysis.

This work investigates the evenness of fabric drying in a household heat pump tumble dryer. The evenness of drying was defined as the standard deviation of the fraction of water, evaporated from each fabric item. Drying experiments were performed according to the IEC 61121 standard, which was also followed to determine quantities and types of cotton fabric items (towels, pillowcases and sheets) within each load. Regression analysis was performed to develop models for evenness of drying as a function of load mass and drum speed. Similarities between the tumble dryer energy efficiency parameters and the evenness of drying were analyzed. A high level of agreement was determined between responses of energy efficiency, drying time and evenness of drying to changes in drum speed. Effects of load mass were however more complex and were reflected in a non-linear response of evenness of drying to changes in load mass – the best evenness of drying could be obtained at 2 kg load, followed by 6 kg and 4 kg load. Load composition was determined as an important factor affecting the evenness of drying. At larger loads, a sheet or a pillowcase in average contributed more to the un-evenness of drying than a towel. The presence of sheets and probably the ratio of sheets to other item types in the load were determined as the most probable factors that negatively affected the evenness of drying.

Nowadays, most mining and quarrying industries utilize a diamond wire saw machine for bench cutting operations. This method uses a metal wire or cable assembled by diamond beads to cut the hard stone into large blocks. Many parameters classified into controllable and uncontrollable parameters affect the performance of the diamond wire saw cutting method. The uncontrollable parameters are related to rock engineering properties, and controllable parameters are related to operational aspects and machine performance. The diamond wire sawing process’s production rate is one of the most critical parameters influencing the design optimization and quarrying cost estimation. The cutting rate and wear rate of diamond beads are the most important factors to evaluate quarries’ production performance. This study aims to determine the effects of different controllable and uncontrollable parameters on different quarries’ production rates. Rock engineering properties like strength, hardness, and abrasivity, and operational aspects, such as cutting angle and drive wheel diameters, are considered as the main factors affecting the production performance of the diamond wire saw method. To discover the influence of these parameters, a detailed investigation in ten quarry operations was carried out. The relation between cutting rate and diamond bead wear with different parameters is estimated. It was observed that different controllable and uncontrollable parameters could increase or decrease the cutting rate and diamond bead wearing. Furthermore, using simple and multiple regression analysis, performance prediction of the cutting rate and wearing of diamond beads was developed, and the best equations were proposed., Danas se u najvećemu broju rudnika i kamenoloma upotrebljava dijamantna žična pila za razne operacije na čelima radilišta. Uporabom metalne žice (ili kabela) na koju su dodani dijamantni zupci mogu se rezati veliki blokovi arhitektonsko-građevnoga kamena. Pri tomu rezanje ovisi o nizu parametara od kojih se neki mogu, a neki ne mogu kontrolirati. Oni koji se ne mogu kontrolirati jesu inženjerska svojstva stijena, a oni koji se mogu kontrolirati jesu operativne varijable i svojstva stroja. Iznos rezanja/proizvodnje najkritičnija je varijabla prema utjecaju na iznos proizvodnje. Svojstva stijena kao čvrstoća, tvrdoća i abrazivnost te operativne vrijednosti poput kuta rezanja, promjera pogonskoga kotača najvažnije su varijable koje utječu na proizvodnju žičnih pila. Procijenjen je odnos između brzine rezanja i trošenja dijamantnih zubaca i opaženo je kako različite varijable utječu na povećanje ili smanjivanje iznosa proizvodnje. Analizirane su metodama jednostavne i višestruke regresije, uključivši sve spomenute varijable, te su predložene jednadžbe kojima se opisuju opažene pojave.

Introduction: Over the last decade, the criminal justice system among the European countries deals with a new group of people, the undocumented people. In the criminal field, most of the suspected claimed to be under the minor legal age according to the type of crime. The government of each European country is committed to protecting the children and vulnerable people. There are serious safety concerns since adults falsely claim to be minors and legal systems oppose to such claims. In this study, we have used different age assessment methods and some of them without accuracy. Objective: To meet the general considerations we developed a study using the current dental age assessment methods. Hence, for the Portuguese population, this study aims to validate the European regression formula between the ages of 6 and 15 years of age; to estimate the cut-off point for the age of 12 years, and to compare the quantitative approach of European regression formula with Demirjian’s qualitative approach for age estimation. Materials and Methods: 483 orthopantomograms were analysed using the European formula and Demirjian scoring stages. A new method, Model 2, was designed to better suit the Portuguese population. Results: The European formula: average age underestimation of 4.88 for the third quadrant and 4.04 months for the fourth quadrant; and a mean absolute error (MAE) of 10.93 and 10.68 months respectively. Demirjian method: average overestimation of 8.70 months, MAE of 12.85 months. In Model 2: MAE of 9.37 months for the third quadrant, and 9.28 months for the fourth quadrant. Both European formula and Demirjian method had an area under ROC curves results above 0.93. Discrepancy of sensitivity between methods for the specific cut-off point: 11.48. The results obtained in this study can be extrapolated to 87.33% of the Portuguese population. Conclusions: The European regression formula can be applied for the Portuguese population, and seems to be more accurate than Demirjian’s methodology in this population. Nevertheless, both European regression formula and Demirjian method present similarly suitable results in the classification of 12 years of age, although there is a noticeable discrepancy favouring the European regression formula. The European Formula when applied for criminal age assessment, independently of population, is mandatory to indicate to the judicial institutions, the sensitivity of the results., Uvod: Tijekom posljednjega desetljeća kaznenopravni sustav europskih zemalja bavi se novom skupinom ljudi – osobama bez dokumenata. Kada je riječ o kaznenome djelu, većina osumnjičenih tvrdila je da je prema vrsti kaznenoga djela maloljetna. Vlada svake europske zemlje dužna je štititi djecu i ranjive osobe. No pojavljuju se ozbiljni sigurnosni problemi zato što odrasli lažno tvrde da su maloljetnici, a pravni se sustavi protive takvim tvrdnjama. U ovoj studiji koristili smo se različitim metodama procjene dobi, a neke od njih nisu točne. Cilj: Kako bismo zadovoljili opća razmatranja, u studiji smo se koristili trenutačnim metodama procjene dentalne dobi. Zato, kada je riječ o portugalskom stanovništvu, ovoj je studiji svrha potvrditi europsku regresijsku formulu za dob od 6 do 15 godina, procijeniti graničnu točku za dob od 12 godina i usporediti kvantitativni pristup europske regresijske formule s Demirjianovim kvalitativnim pristupom za procjenu dobi. Materijal i metode: Europskom formulom i Demirjianovim stupnjevima bodovanja analizirana su 483 ortopantomograma. Nova metoda – model 2, dizajnirana je tako da bolje odgovara portugalskom stanovništvu. Rezultati: Europska formula: podcjenjivanje prosječne dobi od 4,88 za treći kvadrant i 4,04 mjeseca za četvrti kvadrant i srednja apsolutna pogreška (MAE) od 10,93 mjeseca, odnosno 10,68 mjeseci. Demirjianova metoda: prosječno precjenjivanje od 8,70 mjeseci, MAE od 12,85 mjeseci. U modelu 2: MAE od 9,37 mjeseci za treći kvadrant i 9,28 mjeseci za četvrti. I europska formula i Demirjianova metoda imale su rezultate površine ispod ROC krivulja iznad 0,93. Razlika u osjetljivosti između metoda za određenu graničnu točku: 11,48. Rezultati dobiveni u ovoj studiji mogu se ekstrapolirati na 87,33 % portugalske populacije. Zaključci: Europska regresijska formula može se primijeniti na portugalsku populaciju i čini se da je u toj populaciji točnija od Demirjianove metodologije. Ipak, i europska regresijska formula i Demirjianova metoda daju slične prikladne rezultate u klasifikaciji dobi od 12 godina, iako postoji primjetno odstupanje u korist europske regresijske formule. Europska formula, kada se primjenjuje za procjenu kaznene dobi, neovisno o populaciji, obvezna je jer upozorava pravosudne institucije na osjetljivost rezultata.

Cilj ovog rada je modelirati ekstrakcijsko razdvajanje aromata i alifata s polarnim otapalom, smjesom tetraetilenglikola i vode. Iz literature su uzeti potrebni eksperimentalni podatci o ravnoteži kapljevina-kapljevina za osam različitih sustava u temperaturnom području od 60 °C do 140 °C. Pri modeliranju modelima koeficijenta aktivnosti NRTL i UNIQUAC primijenio se pseudo-trokomponentni pristup. Parametri modela određeni su regresijskom analizom, a dobiveni skupovi parametara provjereni su testom termodinamičke konzistentnosti. Rezultati pokazuju da se pseudo-trokomponentni pristup može uspješno primijeniti na modeliranje takvih sustava te je iz dobivenih parametara modela moguće proračunavati ravnotežne sastave faza i predviđati fazno ponašanje tih sustava. Ravnotežni sastavi faza izračunati su i prediktivnim modelom UNIFAC radi usporedbe s korelativnim modelima. Dobiveni rezultati slični su onima kao kod modela UNIQUAC i NRTL iako je postignuto nešto lošije slaganje eksperimenta i modela. In this thesis, extraction separation of aromatic and aliphatic compounds with a polar solvent, a mixture of tetraethlyene glycol and water, is modeled. Liquid-liquid equilibrium (LLE) experimental data were taken from literature for eight different systems in the temperature range from 60 °C to 140 °C. The pseudo-three-component approach was used along with NRTL and UNIQUAC activity coefficient models. The model parameters were determined with regression analysis and thus obtained parameter sets were checked for thermodynamic consistency. The results show that the pseudo-three-component approach can be successfully used for LLE calculations in such systems using regressed NRTL and UNIQUAC parameters. UNIFAC calculations of tie lines were also done to compare the results with those of the correlative models. UNIFAC results were similar to those obtained by NRTL and UNIQUAC although with somewhat worse fit between experiment and model.

Zavzetost predstavlja pozitivno delovno naravnanost posameznika, kjer je pristna njegova pripravljenost k prispevanju uspeha organizacije. Govorimo tako o pozitivnem odnosu zaposlenih do organizacije in njenih vrednot kot tudi z delom prepletenim stanjem duha, kjer sta značilna predanost in zagnanost. Da bi dosegli čim višjo zavzetost zaposlenega na delovnem mestu, je treba raziskati vplivajoče dejavnike. Namen magistrskega dela je odkriti dejavnike, ki vplivajo na zavzetost zaposlenih v upravnih enotah v Republiki Sloveniji, ter izmeriti stopnjo zavzetosti in jo primerjati s stopnjo zavzetosti zaposlenih v Avstriji. Prav tako je namen izoblikovati prispevek, ki bo vodilnim v organizaciji pripomogel k ustreznem načinu ukrepanja pri dvigu stopnje zavzetosti zaposlenih. V magistrskem delu je predstavljen podroben pregled literature in analize raziskav domačih in tujih avtorjev s predstavitvijo zavzetosti in njenih dejavnikov. Uporabljena je bila faktorska in regresijska analiza ter opisna statistika za obdelavo pridobljenih rezultatov. S faktorsko analizo smo na podlagi rezultatov pridobili na novo nastale dimenzije zavzetosti zaposlenih kot tudi na novo nastala dejavnika zavzetosti. Z linearno regresijsko analizo smo preverjali vpliv dejavnikov na dimenzije zavzetosti. Ugotovili smo, da na dimenziji zagnanost/vitalnost in predanost vplivata dejavnika osnovne potrebe in spodbujanje in usmerjanje, med tem, ko na dimenzijo vpetost/vpletenost vpliva dejavnikov ni moč zaznati. Rezultati t-testa, ANOVE in aritmetičnih sredin so pokazali statistično značilen vpliv socio-demografske spremenljivke število let zaposlenega v organizaciji z njegovo zavzetostjo. Ugotovili smo, da so zaposleni v upravnih enotah v Avstriji bolj zavzeti za svoje delo kot zaposleni v upravnih enotah v Sloveniji. Na podlagi ugotovljenih rezultatov so podana priporočila in predlogi izboljšav za povečanje stopnje zavzetosti zaposlenih v upravnih enotah. Poleg navedenega so podane ugotovitve in omejitve raziskave ter možnost mednarodnega primerjanja kot tudi možnost ponovnega izvajanja raziskave. Engagement represents the positive work attitude of the individual, where his willingness to contribute to the success of the organization is genuine. We are talking about the positive attitude of employees towards the organization and its values, as well as the state of mind intertwined with work, which is characterized by dedication and enthusiasm. In order to achieve the highest possible engagement of the employee in the workplace, it is necessary to investigate the influencing factors. The purpose of the master's thesis is to discover the factors that affect the engagement of employees in administrative units in the Republic of Slovenia and to measure the level of engagement and compare it with the level of engagaement of employees in Austria. It is also intended to create a contribution that will help leaders in the organization to take appropriate action to increase the level of employee engagement. In the master's thesis, a detailed review of the literature and analysis of research by domestic and foreign authors is presented, with a presentation of engagement and its factors. Factor analysis, regression analysis and descriptive statistics were used to process the obtained results. Based on the results of the factor analysis, we obtained the newly created dimensions of employee engagement as well as the newly emerged engagement factors. The influence of factors on the dimensions of engagement was checked by linear regression analysis. We found that the vigor and dedication dimensions are influenced by two factors, basic need and encouragement and guidance, while the absorption dimension is not affected by them. The results of the t-test, ANOVA and arithmetic means showed a statistically significant influence of the socio-demographic variable the number of years of the employee in the organization with his engagement. We found that employees in administrative units in Austria are more engaged to their work than employees in administrative units in Slovenia. Based on the established results we have prepared recommendations and suggestions for improvements to increase the level of engagement of employees in administrative units. In addition to the above, we have prepared the findings and limitations of the research, as well as the possibility of international comparison and the possibility of re-conducting the research.

In this paper, six novel mathematical models based on semi-empirical calculus are proposed and applied to characterise the oven-drying process of cement mortar composites reinforced with cellulosic fibres (CMCRCFs). The drying experiments were carried out on four levels of oven-drying temperatures (70, 85, 105, and 120 °C), with four different cellulosic fibres content (0, 5, 10, and 20 %). Obtained results were compared to those derived by regression analysis of six most typically used mathematical drying models (Newton, Page, Page modified1, Page modified2, Handerson Pabis, and Logarithmic) in addition to six proposed models. The regression accuracy of the drying process was evaluated by the coefficient of determination (R2), low mean square error (MSE), low root mean squared error (RMSE), and mean absolute error (MAE). Additional criteria were used to ensure more validity of the selected models. The obtained values indicate a highly accurate fit of the proposed model MR9, meaning that the proposed model can clearly interpret the experimental drying data and predict the dry state of CMCRCFs., U ovom radu predloženo je i primijenjeno šest novih matematičkih modela temeljenih na poluempirijskom proračunu za karakterizaciju procesa sušenja u pećnici kompozita cementne žbuke ojačane celuloznim vlaknima (CMCRCF). Pokusi sušenja provedeni su pri četiri razine temperature sušenja u pećnici (70, 85, 105 i 120 °C) s četiri različita udjela celuloznih vlakana (0, 5, 10 i 20 %). Dobiveni rezultati uspoređeni su s onima dobivenim regresijskom analizom šest najčešće primjenjivanih matematičkih modela sušenja (Newton, Page, Page modified1, Page modified2, Handerson Pabis i Logarithmic) uz šest predloženih modela. Regresijska točnost procesa sušenja procijenjena je koeficijentom determinacije (R2), srednjom kvadratnom pogreškom (MSE), korijenom srednje kvadratne pogreške (RMSE) i srednjom apsolutnom pogreškom (MAE). Primijenjeni su i dodatni kriteriji da bi se osigurala veća valjanost odabranih modela. Dobivene vrijednosti pokazuju dobro slaganje predloženog modela MR9 s eksperimentalnim vrijednostima, što znači da predloženi model može jasno interpretirati eksperimentalne podatke o sušenju i predvidjeti suho stanje CMCRCF-a.

Utična hibridna električna vozila (engl. Plug-in Hybrid Electric Vehicle, PHEV) predstavljaju jednu od ključnih tranzicijskih tehnologija prema energetski učinkovitom, čistom, tihom i održivom transportu u budućnosti. Budući da su vozni ciklusi vezani uz uvjete vožnje i ponašanje vozača, oni su od ključnog značaja za procjenu potrošnje energije i emisija štetnih plinova, te se naširoko koriste kod projektiranja i parametriranja strukture PHEV pogona i njegove upravljačke strategije. Većina studija vezanih uz PHEV kao i druge tipove vozila temelje se na certifikacijskim voznim ciklusima, koji ne uzimaju u obzir realne uvjete vožnje uključujući nagib ceste, već se temelje na "umjetno" generiranom profilu brzine vozila u ovisnosti o vremenu. Međutim, za potrebe projektiranja i ispitivanja sustava upravljanja vozilom trebali bi se koristiti realistični vozni ciklusi, koji odražavaju stvarno ponašanje u vožnji i uvjete na cesti. U tom smislu, glavni cilj ovog rada usmjeren je na sintezu i validaciju realističnih voznih ciklusa predstavljenih vremenskim profilima brzine i ubrzanja vozila te nagiba ceste, koji su izvedeni iz snimljenih GPS podataka praćenja vozila. U radu se prvo uspostavlja stohastički model voznih ciklusa temeljen na Markovljevim lancima, koji uključuje kombinacije diskretnih vrijednosti brzine vozila, akceleracije vozila, nagiba ceste i vremenske promjene nagiba ceste kao Markovljeva stanja. U tu svrhu prikupljen je bogat skup voznih ciklusa gradskih autobusa u gradu Dubrovniku. Zatim se slučajnim uzorkovanjem višedimenzionalne matrice prijelaznih vjerojatnosti (engl. Transition Probability Matrix, TPM) generira veliki skup sintetičkih voznih ciklusa. Kako bi se smanjio zahtjev za memorijom, a istovremeno poboljšala računalna učinkovitost, predlaže se programska implementacija TPM u obliku rijetke matrice temeljene na rječniku ključeva. K tome, razmatra se postupak uključivanja mase putnika u sintezu voznih ciklusa temeljen na događajima zaustavljanja vozila. Zagušenje prometa uzima se u obzir kroz tvorbu zasebnih TPM za svaku kategoriju zagušenosti prometa, koja se provodi klasteriranjem snimljenih voznih ciklusa s obzirom na uspostavljene kriterije zagušenja prometa. Za potrebe validacije sintetičkih voznih ciklusa predlaže se neuronska mreža koja za dani vozni ciklus predviđa potrošnju goriva. Kao podrška validaciji sintetičkih voznih ciklusa, uzimaju se u obzir brojne statističke značajke iz vremenske i frekvencijske domene, uključujući jedinstvene pokazatelje unakrsne korelacije brzine i ubrzanja vozila te nagiba ceste. Značaj svake nominirane statističke značajke i njezin utjecaj na potrošnju goriva raščlanjuje se pomoću linearne regresijske analize i LASSO (engl. Least Absolute Shrinkage and Selection Operator) metode odabira značajki. Za jednoznačnu, jednokriterijsku validaciju sintetičkih voznih ciklusa u odnosu na skup snimljenih voznih ciklusa predlaže se regresijski model koji uključuje samo nekoliko najrelevantnijih statističkih značajki kao ulaze i potrošnju goriva kao izlaz. Također se kao potencijalno daljnje unaprjeđenje ispituje metoda validacije voznih ciklusa temeljem višestrukih kriterija. Predloženi pristupi validacije temelje se na minimiziranju odstupanja statističkih značajki sintetičkih voznih ciklusa u odnosu na očekivane vrijednosti snimljenih voznih ciklusa. Konačno, u radu se predlažu deterministički i stohastički modeli za predviđanje brzine vozila na horizontu u budućnosti, a s tim povezanim i značajki voznih ciklusa relevantnih za potrebe modelskog prediktivnog upravljanja PHEV pogonom. Prediktivni modeli temelje se na višeslojnoj unaprijednoj neuronskoj mreži, koja se parametrira korištenjem podatka o trenutnoj poziciji vozila, trenutnoj brzini ili povijesti brzina vozila, dobu dana i dana u tjednu, a kao izlaz daje sekvencu brzina vozila na pomičnom vremenskom horizontu. Točnost predviđanja brzine vozila demonstrira se na izdvojenom skupu snimljenih voznih ciklusa. Plug-in Hybrid Electric Vehicles (PHEV) represent a key enabling technology to make the transport system more efficient, cleaner, quieter, and less dependent on oil reserves. Since driving cycles are related to driving conditions and driver behaviour, they are crucial for estimating energy consumption and pollutant emissions, and they are widely used in designing and parameterising the structure of PHEV powertrain and its control strategy. Nowadays, various studies related to PHEVs, as well as other vehicle types, are usually based on certification driving cycles, which do not take into account realistic driving conditions including road slope, but are rather based on “artificially” generated vehicle velocity-time profiles. However, for the purposes of designing and testing a vehicle control system, realistic driving cycles should be used, which reflect the actual driving behavior and road conditions. In this sense, the main aim of this thesis is focused on the synthesis and validation of realistic driving cycles represented by vehicle velocity, acceleration and road slope time profiles, which are derived from recorded GPS vehicle tracking data. The thesis first establishes a stochastic model of driving cycles based on Markov chains, which includes combinations of discrete values of vehicle velocity, vehicle acceleration, road slope and road slope time derivative as Markov states. For this purpose, a rich set of driving cycles of city buses operating in the city of Dubrovnik has been collected. By random sampling of a multidimensional transition probability matrix (TPM), a large set of synthetic driving cycles is generated. To reduce the memory requirement while improving computational efficiency, the implementation of TPM in the form of a sparse matrix based on a dictionary of keys (DOK) is proposed. In addition, including of passengers' mass into driving cycle synthesis process is considered based on vehicle stopping events. Traffic congestion is taken into account through the formation of separate TPMs for each traffic congestion category, which is carried out through clustering of recorded driving cycles based on established traffic congestion criteria. For the purpose of synthetic driving cycles validation, a dedicated neural network (NN) is proposed, which predicts the vehicle fuel consumption for a given driving cycle. The NN approach is based on driving cycle time series input data arranged in a form of fixed‐dimension histogram of counted discrete values of vehicle velocity, acceleration, and road slope. In support of validation of synthetic driving cycles, a rich set of statistical features from the time and frequency domains are considered, including unique indicators of cross-correlation of vehicle velocity, vehicle acceleration, and road slope. The significance of each nominated statistical feature and its impact on fuel consumption is analyzed by using a linear regression analysis and Least Absolute Shrinkage and Selection Operator (LASSO) feature selection method. For unambiguous, single-criteria validation of synthetic driving cycles with respect to recorded driving cycles, a reduced-order LASSO regression model is proposed that takes only a few most significant statistical features as inputs and gives fuel consumption as output. The driving cycle validation method based on multiple criteria is also examined as a potential further improvement. The proposed validation approaches are based on minimizing the deviation of statistical features of synthetic driving cycles from the mean/expected values of recorded driving cycles. Finally, the thesis proposes deterministic and stochastic models for predicting vehicle velocity on receding time horizon, and accordingly driving cycle features relevant for model predictive control of PHEV. Predictive models are based on a feedforward multilayer neural networks, which are trained by using the data on current vehicle position, current vehicle velocity or velocity history, time of day, and weekday, and as an output give sequence of vehicle velocities on the receding time horizon. The accuracy of vehicle velocity prediction is demonstrated on a separate set of recorded driving cycles. The main aim of the thesis is to propose a systematic procedure of multi-dimensional driving cycle synthesis, which utilizes driving data recorded using a vehicle telemetry tracking system and at the end results in a minimum number of representative synthetic driving cycles for a wide range of driving conditions. The thesis is organized in eight chapters, whose content is summarized in what follows. Chapter 1, „Introduction“ outlines the motivation for the conducted research, presents the literature overview, and provides the main hypothesis and an overview of the thesis. Chapter 2, „Recording, pre-processing and analysis of driving cycles“ describes the procedure of driving data recording by utilizing GPS/GPRS vehicle tracking devices for the case of a city bus fleet. Pre-processing of recorded driving data is carried out in terms of extracting driving cycles defined by recorded data between end stations of a certain route, filtering of driving cycles with respect to various criteria, reconstruction of precise road slope profiles using regression method based on Gaussian processes, and categorization of driving cycles in accordance to a traffic congestion index. A comprehensive analysis of interdependence of vehicle velocity, acceleration, road slope, and passengers mass is performed to determine whether the synthesis of driving cycles should be carried out jointly with respect to velocity, acceleration, road slope and passengers mass' states or the road slope and passengers' mass can be modeled independently of velocity and acceleration. Chapter 3, „Synthesis of multidimensional driving cycles“ proposes a method for synthesis of multidimensional driving cycles based on Markov chains. Different ways of realizing the transition probability matrix (TPM) are considered along with related implementation aspects, including computational efficiency analysis. It is proposed to adopt a stochastic driving cycle model represented by an 8D TPM using vehicle velocity, acceleration, road slope, and road slope time derivative states, and based on this model a rich set of synthetic driving cycles is generated. An independent, vehicle stopping event-based synthesis method of passengers’ mass profiles is also proposed. Traffic congestion is considered through the formation of separate TPMs for three levels of congestion (light, medium, and heavy). The chapter concludes with a preliminary analysis of validity of the generated synthetic driving cycles, based on a comparison of distributions of characteristic statistical features between synthetic and recorded driving cycles. Chapter 4, „Regression model for predicting fuel consumption“ establishes a regression model for predicting fuel consumption based on appropriately formed input features of synthetic driving cycles and corresponding neural network (NN). The emphasis is on including a road slope feature when designing the model inputs to improve prediction accuracy. The proposed regression models are trained, validated, and tested on an augmented dataset of combined driving cycles, which are derived through random addition of recorded microcycles whose length corresponds to resolution of fuel consumption measurement. A comparative analysis of fuel consumption prediction accuracy is performed between NN and simpler, linear-in-parameter polynomial regression models, for the case with included and excluded road slope information. In addition, several methods for fine-tuning of NN models are conducted and described in detail, which are related to dimensionality reduction, finding the most appropriate architecture, determining the optimal learning rate, and regularizing the NN. Although the proposed regression model for predicting fuel consumption can be applied to various transport-related studies, in this thesis it is used for determining the fuel consumption related to a set of synthetic driving cycles generated in third chapter for the purpose of their validation. Chapter 5, „Multi-criteria validation of driving cycles“ deals with validation of multidimensional synthetic driving cycles generated in the third chapter. A rich set of driving cycle-related statistical features are nominated to describe different driving patterns, which in addition to general statistical indices includes frequency domain ones and cross-correlation of vehicle speed, vehicle acceleration and road slope features. A comparative analysis of the characteristic statistical features calculated for each recorded and synthetic driving cycle is performed to verify that the distributions of the statistical features for the synthetic driving cycles resembles well those obtained for the recorded driving cycles. For the needs of unambiguous validation of driving cycles, several lumped indicators of driving cycle representativeness are derived, which are based on consolidation of individual statistical features or similarity index between two vectors/matrices used to model driving cycles. The selection of the most appropriate representativeness indicator for the final validation of driving cycles is carried out based on correlation analysis in relation to fuel consumption deviation from the mean value of concatenated recorded driving cycles. Finally, a multi-criteria validation procedure is proposed, which highlights and analyzes several most representative driving cycles from the Pareto frontier of lumped representativeness indicators. Chapter 6, „Feature selection-supported validation of driving cycles“ deals with feature selection techniques based on linear regression analysis and least absolute shrinkage and selection operator (LASSO), which serves to determine the relevance of each nominated statistical feature. The competitiveness of the fuel consumption prediction accuracy of linear and LASSO regression models of reduced order is examined in relation to baseline neural network model established in the fourth chapter. The procedure of extracting representative synthetic driving cycles based on LASSO-predicted fuel consumption is presented and compared with the Euclidean distance lumped indicator-based approach. To further improve the process of unambiguous validation of synthetic driving cycles, a dual-criterion validation method based on both Euclidean distance and LASSO-predicted fuel consumption is examined, as well. Chapter 7, „Prediction of driving cycle features“ first describes the process of data preparation for learning, validation, and testing of a vehicle velocity prediction models. Next, static stochastic and deterministic deep feedforward neural network prediction models are proposed, where the former predicts the vehicle velocity distribution along the route, while the latter predicts the vehicle velocity profile on receding time horizon. A comprehensive analysis of the prediction accuracy of the developed predictive models is performed based on test dataset and considering different forecast quality indicators. Deterministic model is additionally examined in terms of influence of each input variable candidates (current vehicle position, current velocity or history of vehicle velocities, time of day, and weekday), velocity history length, and prediction horizon length on the accuracy of vehicle velocity profile prediction. Finally, a dynamic stochastic model is proposed, which combines the properties of both previously developed predictive models, in terms of predicting expectations and standard deviations of velocity patterns on the receding time horizon. Chapter 8, „Conclusion“ outlines the main results, guidelines for future research, and the following major contributions of the doctoral thesis: 1) Driving cycle model based on Markov chains, which in addition to vehicle velocity and acceleration as the Markov states accounts for the road slope, vehicle mass, and traffic congestion features; 2) Validation of driving cycle model based on recorded fuel consumption data and fuel consumption predictions obtained by using a neural network parameterized based on the driving cycle model features; 3) Stochastic model for predicting driving cycle statistical features meant to be applied in stochastic model predictive control of PHEV.

Sve većim brojem prometnih nesreća te razvojem nove tehnologije u svijetu se vrše različita istraživanja i analize u svrhu povećanja sigurnosti prometa na cestama. U ovom radu prikazani su dosadašnji modeli analize ubrzanja vozila na prijelazu iz horizontalne krivine na pravac, na temelju kojih je provedeno istraživanje prikazano u radu. Statističkom obradom kontinuirano snimljenih brzina reprezentativnog uzorka vozača, izrađeni su regresijski modeli ubrzanja vozila te su doneseni zaključci o utjecaju pojedinih geometrijskih karakteristika trase ceste na intenzitet ubrzanja vozila., With raising numbers of traffic accidents and with the development of new technologies in the world there have been a various research and analysis aiming to increase traffic safety. This paper presents models of vehicle acceleration analysis at the transition from horizontal curvature to tangent section used so far, which were the base of conducted research. By statistical processing of continuously recorded speeds of a representative sample of drivers, regression models of vehicle acceleration were made and conclusions were made on the influence of certain geometrical characteristics of the road route on the intensity of vehicle acceleration.

Student motivation represents an important factor in their academic performance. The present study explored university students' academic motivation across the academic year and its relationship with psychological need satisfaction in the study context and academic adjustment. Deci and Ryan's SelfDetermination Theory (SDT) presents a theoretical framework of this study. 124 students participated in both waves of data collection. They answered the Academic Motivation Scale, College Version (AMS-C 28) in the fall of the academic year, and seven months later they answered the question about their certainty of study choice and completed again the AMS-C 28. Additionally, they answered the items about their psychological need satisfaction (autonomy, competence, relatedness) in the current academic year and the items about their satisfaction with the study. The results showed that all forms of academic motivation (as distributed along the SDT motivational continuum) remained highly stable within one academic year. More autonomous motivational orientation related to higher perceived satisfaction of psychological needs. Furthermore, it significantly predicted students' satisfaction with the study and certainty about the study choice. When students'satisfaction of psychological needs in the current academic year was entered into the regression model, it predicted satisfaction with the study and certainty in study choice over and above the students' level of autonomous motivation. The study showed the importance of creating learning environments that respond to students' psychological study needs., Motivacija studenata predstavlja važan čimbenik školskoga postignuća. Ovim je istraživanjem ispitana akademska motivacija studenata tijekom akademske godine i njezin odnos sa zadovoljenjem psiholoških potreba u kontekstu studiranja te s akademskom prilagodbom. Teorijski okvir ovog istraživanja predstavlja teorija samoodređenja (SDT) Decija i Ryana. U obje su točke mjerenja sudjelovala 124 studenta. Na početku akademske godine studenti su ispunili Skalu akademske motivacije, verziju za studente (AMS-C 28), a sedam mjeseci kasnije odgovorili su na pitanje o svojoj sigurnosti izborom studija te ponovno ispunili AMS-C 28. Pored toga, procijenili su stupanj zadovoljenosti psiholoških potreba (za autonomijom, kompetencijom i povezanošću) u tekućoj akademskoj godini te svoje zadovoljstvo studijem. Rezultati su pokazali da su svi oblici akademske motivacije (raspoređeni po motivacijskom kontunuumu SDT-a) tijekom akademske godine ostali vrlo stabilni. Viša autonomna motivacijska orijentacija bila je povezana s većim percipiranim zadovoljenjem psiholoških potreba te je bila značajan prediktor zadovoljstva studenata studijem i sigurnosti u izbor studija. Kada je zadovoljenje psiholoških potreba studenata u tekućoj akademskoj godini uneseno u regresijski model, predviđalo je zadovoljstvo studijem i sigurnost u izbor studija povrh autonomne motivacije studenata. Istraživanje je uputilo na važnost stvaranja okruženja za učenje koje je responsivno na psihološke potrebe studenata vezane uz studij.

Davčna morala postaja vse pomembnejša tematika današnjega družbenega sistema. Pomembna je predvsem z vidika države, saj je tudi od nje odvisno, koliko prihodkov bo imela država iz naslova pobranih davkov. Precejšen izziv predstavlja odkrivanje dejavnikov, ki vplivajo na davčno moralo, še posebej med podjetniki. Glavni namen magistrskega dela je na podlagi preteklih raziskav odkriti in oceniti dejavnike davčne morale pri podjetnikih v Sloveniji ter jo tudi izmeriti. V magistrskem delu sta bila uporabljena podroben pregled in analiza preteklih raziskav ter literature. Za obdelavo pridobljenih podatkov smo uporabili opisno statistiko, faktorsko analizo ter regresijsko analizo. Oblikovali smo merski instrument, s katerim smo odkrili statistično vplivne dejavnike ter izmerili davčno moralo. Pripravili smo priporočilo, ki bi lahko pripomoglo k zvišanju davčne morale. Glede na odziv odgovorov zaznavamo, da podjetniki niso zainteresirani za anketiranje tovrstne tematike. V raziskavi je bilo ugotovljeno, da je med slovenskimi podjetniki davčna morala zelo visoka, nanjo pa vplivajo trije dejavniki, obravnava davkoplačevalcev, upravičenost utajevanja ter priložnost utajevanja. Med najbolj vplivnimi je dejavnik upravičenost utajevanja. Raziskava za oblast podaja ugotovitve ter predloge, ki jih lahko oblast upošteva pri ustvarjanju ter izvajanju politike. Ob upoštevanju predlogov bo pripomogla k dvigu davčne morale. Na znanstvenem področju ponuja širok spekter zbrane literature na enem mestu. Podaja ugotovitve ter poudarja omejitve, ki se jim lahko v prihodnjem raziskovanju izognemo. Ponuja konkretno začetno točko za ponovno izvajanje raziskave, ki jo je možno dvigniti na višjo raven in jo mednarodno primerjati. Tax morale is becoming an increasingly important topic of today's social system, particularly from the point of view of the state. However, a considerable challenge is the identification of factors affecting tax morale, particularly among entrepreneurs. The main purpose of the master's thesis is to identify and assess the factors of tax morale among entrepreneurs in the Slovenia, as well as to measure the tax morale among entrepreneurs based on past research. The master's thesis used a detailed overview and analysis of past research and literature. Descriptive statistics, factor analysis and regression analysis were used for data processing. A measuring instrument was created to identify influential factors and measure tax morale. A recommendation has also been prepared, containing measures that could help to increase tax morale. Based on the responses, it seems that entrepreneurs are not interested in surveys on this topic. The survey found that tax morale is very high among Slovenian entrepreneurs. Only three factors were found to be influential, i.e. “treatment of taxpayers”, “justification of evasion” and “opportunity for evasion”, with “justification of evasion” being the most influential factor. The survey provides findings and suggestions that the authorities can take into account when creating and implementing the tax policy. By taking the proposals into account, it will help to raise the tax morale. For scientists, the survey offers a wide range of literature collected in one place. It also provides findings and highlights the limitations that can be avoided in future research. In doing so, it offers a concrete starting point for the re-implementation of the survey, which can be raised to a higher level and compared internationally.

V doktorskem delu so raziskani vplivi parametrov zraka na vstopu v boben na proces sušenja v sušilnem stroju z odprtim pretočnim sistemom. Izdelani so bili regresijski modeli za izračun specifičnega časa sušenja, hitrosti uparjanja vlage in produkta snovske prestopnosti in površine perila. Večji pretok, višja temperatura ter manjša relativna vlažnost sušilnega zraka povečajo masni tok vlage iz perila, kar skrajša specifični čas sušenja. Sušilni stroj s toplotno črpalko z zaprtim pretočnim sistemom je bil ovrednoten z vidika rabe električne energije in časa sušenja v odvisnosti od hitrosti ventilatorja, hitrosti bobna, mase perila in mase hladiva. Povečanje hitrosti bobna, mase perila in hladiva ima pozitiven vpliv na specifično rabo električne energije in čas sušenja. Vpliv kinematike perila na učinkovitost sušilnega stroja s toplotno črpalko je bil raziskan v odvisnosti od mase perila, hitrosti bobna in faze sušenja, ki je določena z relativno maso kondenzata. Kinematika perila je bila posneta s hitro kamero in ovrednotena z vizualizacijsko metodo. Homogena porazdelitev perila in zmanjšanje vozlanja oziroma lokalnega kopičenja perila poveča površino perila v stiku s sušilnim zrakom, kar izboljša prenos vlage iz perila, učinkovitost in kakovost sušenja. This work investigates the influence of drum inlet air parameters on a drying process in an open-cycle tumble dryer. Regression models were developed to determine the specific drying time, moisture evaporation rate and area-mass transfer coefficient. A higher volume flow rate and temperature and a lower relative humidity of the drying air increase the moisture evaporation rate, which decreases the specific drying time. A closed-cycle heat pump dryer was evaluated for energy consumption and drying time as a function of fan speed, drum speed, load mass, and refrigerant mass. An increase in drum speed, load mass and refrigerant mass has a positive effect on specific energy consumption and specific drying time. Furthermore, clothes kinematics and its effect on the heat pump dryer performance were examined in relation to the load mass, drum speed and drying stage, defined by a relative condensate mass. Clothes kinematics in the drum was recorded using a high-speed camera and evaluated by visualization method. Homogenous clothes distribution and reduction of tangling or local accumulation of clothes increase the contact area between the clothes and the drying air, which improves the moisture evaporation rate, drying efficiency and drying quality.

Fokus ovog diplomskog rada su promjene nastale na zemljišnom pokrovu Osječkobaranjske županije i Baranjske županije između 1992. i 2011. Snimke na kojima se temelji analiza preuzete su sa web stranica Earth explorer (USGS) i klasificirane su u ArcGIS 10.3.1 gdje je i provedena procjena točnosti istih pomoću matrice konfuzije i kapa koeficijenta. Nakon provedene klasifikacije i usporedbe snimaka utvrđeni su procesi promjene zemljišnog pokrova. U Osječko-baranjskoj županiji izdvajaju se: ekstenzifikacija, intenzifikacija i degradacija, a u Baranjskoj županiji: intenzifikacija, reforestacija i urbanizacija. Kako bi se objasnili uzročnici promjena zemljišnog pokrova napravljena je regresijska analiza pomoću Spatial Statistics Tools-a na temelju fizičko-geografskih (nagib zemljišta, nadmorska visina), socioekonomskih (udio zaposlenih, udio starijih, udio visokoobrazovanih) i demografskih (indeks starosti, promjene broja stanovnika, gustoća stanovnika) varijabli. Uz OSL i GWR modele pojedinih promjena zemljišnog pokrova napravljen je ukupni (GWR) model promjene koji ukazuje da navedene varijbale najviše objašnjavaju procese nastale na zapadu i sjeverozapadu Osječkobaranjske županije, odnosno istoku Baranjske županije. Focus of this thesis is change in land cover of Osijek-Baranja county and Baranya county between 1992. and 2011. Images on which analysis is based upon were downloaded from the web pages of Earth Explorer, United States Geological Survey and classified in ArcGIS 10. 3. 1. In this software was also made accuracy assessment based on error matrix and kappa coefficient. After classification and comparison of images the land cover changes were confirmed. In Osijek-Baranja county most dominate ones were: extensification, intensification and degradation. As for Baranya county there were intensification, reforestation and urbanisation. To determine what causes these changes the Spatial Statistics Tools were used based on physical-geographic (slope, elevation), socioeconomic (employment ratio, elderly ratio, highly educated ratio) and demographic (age index, population change, population density) variables. After making OSL and GWR models for each land cover change, there was model made for total land cover change based on all of the variables. It showed that the variables best explained land cover changes in west and north west parts of Osijek-Baranja county and east parts of Baranya county.

U ovom radu dan je jedan drugi aspekt provođenja regresijske analize. Konkretno, linearnoj i polinomijalnoj regresiji pristupili smo na nešto slikovitiji način, koristeći geometrijski pristup. Kako bismo to izveli, od krucijalne važnosti bili su nam vektori koji su nam omogućili povezivanje znanja iz područja linearne algebre i područja statistike. Naime, podatke s kojima radimo, kao i sam model zapisivali smo u vektorskom obliku. Prilikom provođenja statističke analize, klasičan izračun modelom prilagođene vrijednosti zamijenili smo izračunom ortogonalne projekcije vektora opažanja na prostor razapet samim modelom. Svojstva ortogonalne projekcije poslužila su nam i prilikom provođenja statističkih testova te računanja testne statistike. Dakle, uobičajenim izrazima koje u regresijskoj analizi inače koristimo dodali smo jednu novu interpretaciju te pokazali da je to zaista ekvivalentno. Upravo ta mogućnost sagledavanja problema te pristupa njegovu rješavanju s više točaka gledišta koje vode istom rješenju jedna je od ljepota matematike koja nam omogućuje povezivanje znanja iz različitih područja te pomaže razjasniti eventualne nedoumice. In this thesis, another aspect of conducting regression analysis is given. In particular, we approached linear and polynomial regression in a somewhat more illustrative way, using a geometric approach. To achieve this, the vectors that enable us to connect knowledge from the field of linear algebra and the field of statistics were of crucial importance to us. Namely, the data we work with, as well as the model itself, were written in vector form. When performing statistical analysis, we replaced the classical calculation of model fitted values by calculating the orthogonal projection of the observation vector on the model space. The properties of orthogonal projection also served us when conducting statistical tests and calculating test statistics. So, we added a new interpretation to the common expressions we usually use in regression analysis and showed that it is really equivalent. It is this possibility of perceiving the problem and approaching its solution from several points of view that leads to the same solution which is one of the beauties of mathematics that enables us to connect knowledge from different fields and helps to clarify possible doubts.

Turizam je sustav koji neizostavno prati tehnološki napredak ostalih područja društvenog i gospodarskog života, pogotovo u domeni dostupnosti svih elemenata turističkog proizvoda koje nudi njegova osnovna jedinica – turistička destinacija. Slijedom sklonosti i potrebe korištenja mobilnih digitalnih alata i usluga od strane posjetitelja u svrhu boljeg snalaženja, sve se više nameće koncept tzv. pametne destinacije. Međutim, kako digitalne aplikacije sve više zasićuju svakodnevnicu i prijete saturaciji realnog i kvalitetnog života, nameće se potreba selektivnog pristupa i u domenu destinacijskog upravljanja kroz upravljanje iskustvom i zadovoljstvom posjetitelja. Metodom usmjerenog anketnog upitnika provedeno je istraživanje na više turistički frekventnih lokacija u destinaciji, čiji je cilj bio, od pet najistaknutijih, istražiti važnost i participaciju pojedinačnih mobilnih aplikacija u unapređenju iskustva posjetitelja. Provedbom korelacijske i regresijske analize došlo se do rezultata, koje aplikacije najznačajnije participiraju u unapređenju iskustva posjetitelja. Značaj ovog istraživanja ogleda se u oblikovanju novog alata za adaptabilno i selektivno uvođenje novih mobilnih aplikacija u funkciji lakšeg snalaženja posjetitelja u destinaciji a time i učinkovitijeg upravljanja njihovim iskustvom.

Tourism is a system that inevitably follows the technological advancement of other areas of social and economic life, especially in the domain of accessibility of all elements of tourist product offered by its basic unit - a tourist destination. Due to the inclination and the need to use mobile digital tools and services for visitors to better manage, the concept of the so-called “smart destination” is becoming increasingly important. However, as digital applications become increasingly saturated with everyday life and threaten the saturation of real and quality life, there is a need for selective access also in the domain of destination management through experience management and visitor satisfaction. Using the methodology of the survey questionnaire a survey has conducted on several tourist frequency locations in the destination, whose aim was to investigate the importance and participation of individual mobile applications in improving the visitor experience, among them the five most prominent. By applying correlation and regression analysis, results have been achieved, which applications most importantly participate in improving the visitor experience. The significance of this research is reflected in the design of a new tool for adaptive and selective introduction of new mobile applications in order to better target visitors in a destination and thus more effectively manage their experience., Turizam je sustav koji neizostavno prati tehnološki napredak ostalih područja društvenog i gospodarskog života, pogotovo u domeni dostupnosti svih elemenata turističkog proizvoda koje nudi njegova osnovna jedinica – turistička destinacija. Slijedom sklonosti i potrebe korištenja mobilnih digitalnih alata i usluga od strane posjetitelja u svrhu boljeg snalaženja, sve se više nameće koncept tzv. pametne destinacije. Međutim, kako digitalne aplikacije sve više zasićuju svakodnevnicu i prijete saturaciji realnog i kvalitetnog života, nameće se potreba selektivnog pristupa i u domenu destinacijskog upravljanja kroz upravljanje iskustvom i zadovoljstvom posjetitelja. Metodom usmjerenog anketnog upitnika provedeno je istraživanje na više turistički frekventnih lokacija u destinaciji, čiji je cilj bio, od pet najistaknutijih, istražiti važnost i participaciju pojedinačnih mobilnih aplikacija u unapređenju iskustva posjetitelja. Provedbom korelacijske i regresijske analize došlo se do rezultata, koje aplikacije najznačajnije participiraju u unapređenju iskustva posjetitelja. Značaj ovog istraživanja ogleda se u oblikovanju novog alata za adaptabilno i selektivno uvođenje novih mobilnih aplikacija u funkciji lakšeg snalaženja posjetitelja u destinaciji a time i učinkovitijeg upravljanja njihovim iskustvom.