Framework for Federated Learning Open Models in e-Government Applications

Using open data and artificial intelligence in providing innovative public services is the focus of the third generation of e-Government and supporting Internet and Communication Technologies systems. However, developing applications and offering open services based on (open) machine learning models requires large volumes of private, open, or a combination of both open and private data for model training to achieve sufficient model quality. Therefore, it would be beneficial to use both open and private data simultaneously to fully use the potential that machine learning could grant to the public and private sectors. Federated learning, as a machine learning technique, enables collaborative learning among different parties and their data, being private or open, creating shared knowledge by training models on such partitioned data without sharing it between parties in any step of the training or inference process. This paper provides a practical layout for developing and sharing machine learning models in a federative and open manner called Federated Learning Open Model. The definition of the Federated Learning Open Model concept is followed by a description of two potential use cases and services achieved with its usage, one being from the agricultural sector with the horizontal dataset partitioning and the latter being from the financial sector with a dataset partitioned vertically

Nagrađivanje zaposlenika u malim poduzećima: stanje i uloga iz perspektive menadžera

Upravljanje nagrađivanjem važna je funkcija upravljanja ljudskim potencijalima. U cilju jačanja tržišne konkurentnosti, privlačenja i zadržavanja ključnih zaposlenika i mala poduzeća moraju posvetiti odgovarajuću pozornost kompenzacijama zaposlenih. U malim je poduzećima upravljanje ljudskim potencijalima, pa time i nagrađivanje, manje formalizirano te se dostupne teorijske spoznaje o upravljanju nagrađivanjem koje vrijede za velika poduzeća ne mogu bezuvjetno primijeniti i na mala poduzeća. U malim poduzećima menadžeri/vlasnici samostalno formuliraju odgovarajuće pakete kompenzacija koji bi trebali imati učinak na privlačenje, motiviranje i zadržavanje zaposlenika. U cilju utvrđivanja stanja i uloge nagrađivanja u malim poduzećima provedeno je istraživanje među menadžerima malih poduzeća u Bosni i Hercegovini. Opće je mišljenje ispitanika da kompenzacije uglavnom nisu ključan element u privlačenju i zadržavanju zaposlenika u malim poduzećima. Ipak, postoje razlike s obzirom na poziciju ispitanika. Naime, svijest o važnosti kompenzacija veća je kod direktora malih poduzeća koji nisu ujedno i vlasnici poduzeća. Dodatna analiza različitih kategorija materijalnog i nematerijalnog nagrađivanja u poticanju motivacije i zadovoljstva zaposlenika u malom poduzeću pokazala je da je prema mišljenju ispitanika visina osnovne plaće ključan faktor u poticanju motivacije i zadovoljstva zaposlenika. Pored materijalnog nagrađivanja u vidu osnovne plaće odgovarajuće visine, ispitanici pridaju tek neznatno manju važnost kvaliteti radnog života i delegiranju odgovornosti, odnosno kategorijama nematerijalnog nagrađivanja. Iako menadžeri malih poduzeća ne smatraju da su kompenzacije presudne za motivaciju zaposlenika, svjesni su važnosti pojedinačnih kompenzacija, kako materijalnih, tako i onih nematerijalnih

The Correlation between Iron Deficiency and Recurrent Aphthous Stomatitis: A Literature Review

Aphthous lesions of the oral mucosa are a very common symptom and can be seen in both family medicine practice, dental medicine practice, and dermatology or otorhinolaryngology clinics. Some patients develop a chronic recurrent condition, which is clinically known as recurrent aphthous stomatitis (RAS). These ulcers are round, clearly defined, and can be visible on the movable part of the oral mucosa, with variations in size. A prodromal symptom like the burning or stinging sensation can precede the appearance of lesions. The main reason why patients seek medical help is oropharyngeal pain with lack of appetite. The exact etiopathogenesis of RAS remains unknown. Immune disorders, nutritional deficiencies, allergies, mechanical injuries, and even psychological disorders are being studied as potential causes of this condition. Some authors claim that iron deficiency may be a possible causative factor of RAS due to its role in DNA synthesis, mitochondrial function, and enzymatic activity. In iron deficiency, epithelial cells turn over more rapidly and produce an immature or atrophic mucosa. Such mucosa is vulnerable and can be a fertile soil for chronic inflammation and development of aphthae. Finally, our goals were to describe the clinical aspects and etiology of RAS, as well as to determine whether RAS may be related to iron deficiency, in order to identify potential patients with iron deficiency in everyday work

Connection between knowledge of oral hygiene and dental status of the elderly in Požeško-slavonska County

Timely visits to the dentist are extremely important for the preservation of dental health. Given the biological predisposition of teeth decay with age, it is important to act preventively in order to minimize the adverse effects of age on dental health. Aim: The aim of this study is to establish the correlation between the various factors related to oral health and dental status in older age and to examine the differences in dental status between retirement home residents and those living at home. Materials and methods: The data were collected through a survey consisting of 39 questions. The sample consisted of 110 participants located in the Požega HPP and the Home for the Elderly and Infirm in Požega, 42.7% of which were men and 57.3% women. The study used the selection criterion of persons over the age of 65. The average age in the sample was 77.35 years (SD = 7.18) ranging from 65 to 97 years of age. The data were collected in the period from January 2018 to July 2018. The participants were divided into two groups, those living in the Požega Nursing Home and those living in their own household but were hospitalized once in the Požega County Hospital. Results: The obtained results showed that participants have different dental problems that were partially related to their knowledge of oral hygiene. This paper emphasizes the importance of additional training and education for the elderly population in order to preserve and improve the quality of their dental health. Conclusion: The results of this study suggest that participants, in average, were less concerned about their dental health, which was confirmed by the small number of healthy teeth. There was a partial correlation between the knowledge about oral hygiene and the dental status of elderly people in Požega-Slavonia County, i.e. their knowledge was related only to some aspects of their dental status. According to the results obtained, it is important to organize training for the elderly about the importance of timely interventions when dental health is in question, as well as to further educate them about the harmful factors when it comes to the preservation of their dental health

Connection between knowledge of oral hygiene and dental status of the elderly in Požeško-slavonska County

Timely visits to the dentist are extremely important for the preservation of dental health. Given the biological predisposition of teeth decay with age, it is important to act preventively in order to minimize the adverse effects of age on dental health. Aim: The aim of this study is to establish the correlation between the various factors related to oral health and dental status in older age and to examine the differences in dental status between retirement home residents and those living at home. Materials and methods: The data were collected through a survey consisting of 39 questions. The sample consisted of 110 participants located in the Požega HPP and the Home for the Elderly and Infirm in Požega, 42.7% of which were men and 57.3% women. The study used the selection criterion of persons over the age of 65. The average age in the sample was 77.35 years (SD = 7.18) ranging from 65 to 97 years of age. The data were collected in the period from January 2018 to July 2018. The participants were divided into two groups, those living in the Požega Nursing Home and those living in their own household but were hospitalized once in the Požega County Hospital. Results: The obtained results showed that participants have different dental problems that were partially related to their knowledge of oral hygiene. This paper emphasizes the importance of additional training and education for the elderly population in order to preserve and improve the quality of their dental health. Conclusion: The results of this study suggest that participants, in average, were less concerned about their dental health, which was confirmed by the small number of healthy teeth. There was a partial correlation between the knowledge about oral hygiene and the dental status of elderly people in Požega-Slavonia County, i.e. their knowledge was related only to some aspects of their dental status. According to the results obtained, it is important to organize training for the elderly about the importance of timely interventions when dental health is in question, as well as to further educate them about the harmful factors when it comes to the preservation of their dental health

Preporučiteljski sustavi svjesni konteksta namijenjeni autorima sadržaja u e-učenju

The goal of this thesis is to research context dimensions and characteristics of context-aware recommender systems designed for authoring of e-learning content. Building on characteristics of available content models, the context model is proposed, comprising context dimensions from (i) learning management system and course context, (ii) author’s profile and (iii) context inferred from already used learning objects, which includes their structure, pedagogical roles, domain topics and layout features. Based on this model, the recommender system structure is proposed, with algorithms for analyzing content and inferring context data which can be grouped in three subtypes: (i) domain keywords and concepts, (ii) context dimensions for structure, layout and pedagogical roles, and (iii) author’s feedback. Following the analysis, data is converted to three matrices, to be used in further algorithms. Recommended learning objects are obtained from popular Web2.0 content providers according to content keywords. Received results are additionally analyzed in contextual post-filtering phase, according to relevant context dimensions and implicit author’s feedback. Implementation of model and recommender system is developed in the popular learning management system Moodle, as AREC recommender block, providing content recommendations to authors. Evaluation, based on publicly available and free content, shows that using context data improves recommendation process, which would otherwise depend only on content-based recommendation from content providers. During evaluation discussion, several open issues in model and system proposal, as well as in reusing e-learning content, are noted and discussed, with possible solutions offered.Cilj ove disertacije je istraživanje dimenzija konteksta i značajki preporučiteljskih sustava svjesnih konteksta namijenjenih autorima sadržaja u e-učenju. Nadograđujući na značajke postojećih modela sadržaja, predložen je model konteksta, koji se sastoji od dimenzija konteksta iz (i) sustava za upravljanje učenjem i konteksta kolegija, (ii) profila autora i (iii) konteksta izvedenog iz već korištenih objekata učenja, koji sadrži njihovu strukturu, pedagoške uloge, teme domene i posebnosti izgleda. Na temelju ovoga modela predložena je struktura preporučiteljskog sustava, s algoritmima za analizu sadržaja i izvođenje podataka iz konteksta koje je moguće grupirati u tri podtipa: (i) ključne riječi i koncepti domene, (ii) dimenzije konteksta za strukturu, izgled i pedagoške uloge, te (iii) povratna informacija autora. Nakon analize, podaci su pretvoreni u tri matrice, za uporabu u narednim algoritmima. Preporučeni objekti učenja dobiveni su iz popularnih Web2.0 pružatelja sadržaja prema ključnim riječima sadržaja. Dobiveni rezultati dodatno su analizirani u fazi kontekstualnog naknadnog filtriranja, prema relevantnim dimenzijama konteksta i implicitnom autorovom povratnom informacijom. Izvedba modela i preporučiteljskog sustava ostvarena je u popularnom sustavu za upravljanje učenjem Moodle, kao blok „AREC preporučitelj“, koji autorima pruža preporuke sadržaja. Vrednovanje, temeljeno na javno dostupnom, slobodnom sadržaju, pokazuje da uporaba kontekstnih podataka poboljšava proces preporučivanja, koji bi inače ovisio samo o preporukama temeljenim na sadržaju pružatelja sadržaja. U raspravi o vrednovanju, navedeno je i obrazloženo nekoliko otvorenih općenitih poteškoća vezanih za prijedlog modela i sustava, te uz ponovnu uporabu sadržaja u e-učenju, uz prijedloge mogućih rješenja

Preporučiteljski sustavi svjesni konteksta namijenjeni autorima sadržaja u e-učenju

The goal of this thesis is to research context dimensions and characteristics of context-aware recommender systems designed for authoring of e-learning content. Building on characteristics of available content models, the context model is proposed, comprising context dimensions from (i) learning management system and course context, (ii) author’s profile and (iii) context inferred from already used learning objects, which includes their structure, pedagogical roles, domain topics and layout features. Based on this model, the recommender system structure is proposed, with algorithms for analyzing content and inferring context data which can be grouped in three subtypes: (i) domain keywords and concepts, (ii) context dimensions for structure, layout and pedagogical roles, and (iii) author’s feedback. Following the analysis, data is converted to three matrices, to be used in further algorithms. Recommended learning objects are obtained from popular Web2.0 content providers according to content keywords. Received results are additionally analyzed in contextual post-filtering phase, according to relevant context dimensions and implicit author’s feedback. Implementation of model and recommender system is developed in the popular learning management system Moodle, as AREC recommender block, providing content recommendations to authors. Evaluation, based on publicly available and free content, shows that using context data improves recommendation process, which would otherwise depend only on content-based recommendation from content providers. During evaluation discussion, several open issues in model and system proposal, as well as in reusing e-learning content, are noted and discussed, with possible solutions offered.Cilj ove disertacije je istraživanje dimenzija konteksta i značajki preporučiteljskih sustava svjesnih konteksta namijenjenih autorima sadržaja u e-učenju. Nadograđujući na značajke postojećih modela sadržaja, predložen je model konteksta, koji se sastoji od dimenzija konteksta iz (i) sustava za upravljanje učenjem i konteksta kolegija, (ii) profila autora i (iii) konteksta izvedenog iz već korištenih objekata učenja, koji sadrži njihovu strukturu, pedagoške uloge, teme domene i posebnosti izgleda. Na temelju ovoga modela predložena je struktura preporučiteljskog sustava, s algoritmima za analizu sadržaja i izvođenje podataka iz konteksta koje je moguće grupirati u tri podtipa: (i) ključne riječi i koncepti domene, (ii) dimenzije konteksta za strukturu, izgled i pedagoške uloge, te (iii) povratna informacija autora. Nakon analize, podaci su pretvoreni u tri matrice, za uporabu u narednim algoritmima. Preporučeni objekti učenja dobiveni su iz popularnih Web2.0 pružatelja sadržaja prema ključnim riječima sadržaja. Dobiveni rezultati dodatno su analizirani u fazi kontekstualnog naknadnog filtriranja, prema relevantnim dimenzijama konteksta i implicitnom autorovom povratnom informacijom. Izvedba modela i preporučiteljskog sustava ostvarena je u popularnom sustavu za upravljanje učenjem Moodle, kao blok „AREC preporučitelj“, koji autorima pruža preporuke sadržaja. Vrednovanje, temeljeno na javno dostupnom, slobodnom sadržaju, pokazuje da uporaba kontekstnih podataka poboljšava proces preporučivanja, koji bi inače ovisio samo o preporukama temeljenim na sadržaju pružatelja sadržaja. U raspravi o vrednovanju, navedeno je i obrazloženo nekoliko otvorenih općenitih poteškoća vezanih za prijedlog modela i sustava, te uz ponovnu uporabu sadržaja u e-učenju, uz prijedloge mogućih rješenja

Preporučiteljski sustavi svjesni konteksta namijenjeni autorima sadržaja u e-učenju

The goal of this thesis is to research context dimensions and characteristics of context-aware recommender systems designed for authoring of e-learning content. Building on characteristics of available content models, the context model is proposed, comprising context dimensions from (i) learning management system and course context, (ii) author’s profile and (iii) context inferred from already used learning objects, which includes their structure, pedagogical roles, domain topics and layout features. Based on this model, the recommender system structure is proposed, with algorithms for analyzing content and inferring context data which can be grouped in three subtypes: (i) domain keywords and concepts, (ii) context dimensions for structure, layout and pedagogical roles, and (iii) author’s feedback. Following the analysis, data is converted to three matrices, to be used in further algorithms. Recommended learning objects are obtained from popular Web2.0 content providers according to content keywords. Received results are additionally analyzed in contextual post-filtering phase, according to relevant context dimensions and implicit author’s feedback. Implementation of model and recommender system is developed in the popular learning management system Moodle, as AREC recommender block, providing content recommendations to authors. Evaluation, based on publicly available and free content, shows that using context data improves recommendation process, which would otherwise depend only on content-based recommendation from content providers. During evaluation discussion, several open issues in model and system proposal, as well as in reusing e-learning content, are noted and discussed, with possible solutions offered.Cilj ove disertacije je istraživanje dimenzija konteksta i značajki preporučiteljskih sustava svjesnih konteksta namijenjenih autorima sadržaja u e-učenju. Nadograđujući na značajke postojećih modela sadržaja, predložen je model konteksta, koji se sastoji od dimenzija konteksta iz (i) sustava za upravljanje učenjem i konteksta kolegija, (ii) profila autora i (iii) konteksta izvedenog iz već korištenih objekata učenja, koji sadrži njihovu strukturu, pedagoške uloge, teme domene i posebnosti izgleda. Na temelju ovoga modela predložena je struktura preporučiteljskog sustava, s algoritmima za analizu sadržaja i izvođenje podataka iz konteksta koje je moguće grupirati u tri podtipa: (i) ključne riječi i koncepti domene, (ii) dimenzije konteksta za strukturu, izgled i pedagoške uloge, te (iii) povratna informacija autora. Nakon analize, podaci su pretvoreni u tri matrice, za uporabu u narednim algoritmima. Preporučeni objekti učenja dobiveni su iz popularnih Web2.0 pružatelja sadržaja prema ključnim riječima sadržaja. Dobiveni rezultati dodatno su analizirani u fazi kontekstualnog naknadnog filtriranja, prema relevantnim dimenzijama konteksta i implicitnom autorovom povratnom informacijom. Izvedba modela i preporučiteljskog sustava ostvarena je u popularnom sustavu za upravljanje učenjem Moodle, kao blok „AREC preporučitelj“, koji autorima pruža preporuke sadržaja. Vrednovanje, temeljeno na javno dostupnom, slobodnom sadržaju, pokazuje da uporaba kontekstnih podataka poboljšava proces preporučivanja, koji bi inače ovisio samo o preporukama temeljenim na sadržaju pružatelja sadržaja. U raspravi o vrednovanju, navedeno je i obrazloženo nekoliko otvorenih općenitih poteškoća vezanih za prijedlog modela i sustava, te uz ponovnu uporabu sadržaja u e-učenju, uz prijedloge mogućih rješenja

In Search of a Smile: SMIL Indexing System for Multimedia Learning

In today's world of education, new methods and services are appearing every day. This paper proposes the usage of educational material "mashup", created in SMIL (Synchronized Multimedia Integration Language) format. A multi-user Web application for indexing and sharing SMIL presentations is described. Presentations, located on remote servers, are fetched using different protocols, analyzed and indexed using a full-text search method. Each result gives not only "the place" but also "the time" of spoken word or phrase in the course. Afterwards, the lectures can be grouped based on their content, shared and combined together into personalized Search boxes for specific courses. The placement of Search boxes on any course Web page or LMS is done by client-side technologies, which eliminates tweaking of learning systems and usage of server-side programming. An example of usage at the University of Zagreb, Faculty of Electrical Engineering and Computing is described, together with the research results obtained