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Narrative of Romance in Ružica Zagorska's Novel Pobjeda ljubavi (Victory of Love)
No full textU radu se analiziraju obilježja književnog žanra romanse na primjeru romana Pobjeda ljubavi te se roman interpretira u okviru nakladničke cjeline Biblioteka moje kćeri koju nakladnik Stjepan Kugli objavljuje od 1922. godine i u kojoj je objavljen i analizirani roman. Djevojke u adolescentskoj dobi, čitajući knjige prilagođene upravo njima, dolaze do spoznaje što je sentimentalnost odnosno sentimentalno pripovijedanje
Image classification using supervised machine learning
No full textPrisutnost tehnologije u svakom aspektu života postala je gotovo neizostavna. Tehnološki napredak transformira način na koji živimo i utječe na naše razumijevanje i interpretaciju svijeta oko nas. Posebno se očituje napredak u području strojnog učenja koje je zahvatilo sve slojeve znanosti i većinu industrija, posebno modnu industriju. Stoga primjena nadziranog strojnog
učenja u klasifikaciji slika s naglaskom na kulturno specifične haljine iz različitih regija svijeta postaje važna. Ovim pristupom želi se doprinijeti boljem razumijevanju i kategorizaciji kulturno specifičnih odjevnih tradicija, s potencijalnim primjenama u modnoj industriji, obrazovanju i promicanju kulturne raznolikosti. Cilj ovog rada bio je razviti model za klasifikaciju slika koji može prepoznati i klasificirati raznovrsne haljine prema njihovom podrijetlu. Razvijen je model za klasifikaciju slika koristeći
skup podataka koji sadrži slike kulturno raznolikih haljina iz Skandinavije, Mediterana, Ujedinjenih Arapskih Emirata i središnje Europe. Model je treniran na različitom broju epoha (50 i 100) kako bi se usporedili rezultati i performanse modela s obzirom na broj epoha. Analiza performansi modela u odnosu na broj epoha, pokazuje da model treniran na većem broju epoha
(100) postiže neznatna poboljšanja u odnosu na model treniran na manjem broju epoha (50). Veći broj epoha (100) poboljšava performanse u klasifikaciji slika haljina karakterističnih za Ujedinjene Arapske Emirate i Skandinaviju, dok negativno utječe na klasifikaciju slika haljina karakterističnih za središnju Europu i Mediteran. I model treniran na 50 epoha i model treniran na 100 epoha ima poteškoća u klasificiranju slika haljina karakterističnih za središnju Europu, dok najbolje rezultate postiže u klasifikaciji slika haljina karakterističnih za Mediteran. Za postizanje optimalnih rezultata potrebno je daljnje podešavanje broja epoha i drugih hiperparametara. Također, povećanje broja i raznolikosti skupa podataka, s ciljem boljeg
odražavanja različitih uvjeta i karakteristika haljina, može značajno unaprijediti sposobnost modela da točno klasificira slike u sve kategorije.The presence of technology in every aspect of life has become almost inevitable. Technological progress is transforming the way we live and influencing our understanding and interpretation of the world around us. The progress in the field of machine learning, which has affected all layers of science and most industries, especially the fashion industry, is particularly evident. Therefore, the application of supervised machine learning in image classification with a focus on culturally specific dresses from different regions of the world becomes important. This approach aims to contribute to a better understanding and categorization of culturally specific clothing traditions, with potential applications in the fashion industry, education and the promotion of cultural diversity. The aim of this paper was to develop a model for image classification that can recognize and classify various dresses according to their origin. An image classification model was developed, using a dataset containing images of culturally diverse dresses from Scandinavia, the Mediterranean, the United Arab Emirates, and Central Europe. The model was trained on different numbers of epochs (50 and 100) to compare the results and performance of the model with respect to the number of epochs. The analysis of the performance of the model in relation to the number of epochs shows that the model trained on a larger number of epochs (100) achieves slight improvements compared to the model trained on a smaller number of epochs (50). A larger number of epochs (100) improves the performance in the classification of dress images characteristic of the United Arab Emirates and Scandinavia, while negatively affectting the classification of dress images characteristic of Central Europe and the Mediterranean. Both the model trained on 50 epochs and the model trained on 100 epochs have difficulties in classifying images of dresses characteristic of Central Europe, while they achieve the best results in classification of images of dresses characteristic of the Mediterranean. To achieve optimal results, further adjustment of the number of epochs and other hyperparameters is necessary. Also, increasing the number and diversity of the dataset, with the aim of better
reflecting the different conditions and characteristics of the dresses, can significantly improve the model's ability to accurately classify images into all categories
Image classification using supervised machine learning
No full textPrisutnost tehnologije u svakom aspektu života postala je gotovo neizostavna. Tehnološki napredak transformira način na koji živimo i utječe na naše razumijevanje i interpretaciju svijeta oko nas. Posebno se očituje napredak u području strojnog učenja koje je zahvatilo sve slojeve znanosti i većinu industrija, posebno modnu industriju. Stoga primjena nadziranog strojnog
učenja u klasifikaciji slika s naglaskom na kulturno specifične haljine iz različitih regija svijeta postaje važna. Ovim pristupom želi se doprinijeti boljem razumijevanju i kategorizaciji kulturno specifičnih odjevnih tradicija, s potencijalnim primjenama u modnoj industriji, obrazovanju i promicanju kulturne raznolikosti. Cilj ovog rada bio je razviti model za klasifikaciju slika koji može prepoznati i klasificirati raznovrsne haljine prema njihovom podrijetlu. Razvijen je model za klasifikaciju slika koristeći
skup podataka koji sadrži slike kulturno raznolikih haljina iz Skandinavije, Mediterana, Ujedinjenih Arapskih Emirata i središnje Europe. Model je treniran na različitom broju epoha (50 i 100) kako bi se usporedili rezultati i performanse modela s obzirom na broj epoha. Analiza performansi modela u odnosu na broj epoha, pokazuje da model treniran na većem broju epoha
(100) postiže neznatna poboljšanja u odnosu na model treniran na manjem broju epoha (50). Veći broj epoha (100) poboljšava performanse u klasifikaciji slika haljina karakterističnih za Ujedinjene Arapske Emirate i Skandinaviju, dok negativno utječe na klasifikaciju slika haljina karakterističnih za središnju Europu i Mediteran. I model treniran na 50 epoha i model treniran na 100 epoha ima poteškoća u klasificiranju slika haljina karakterističnih za središnju Europu, dok najbolje rezultate postiže u klasifikaciji slika haljina karakterističnih za Mediteran. Za postizanje optimalnih rezultata potrebno je daljnje podešavanje broja epoha i drugih hiperparametara. Također, povećanje broja i raznolikosti skupa podataka, s ciljem boljeg
odražavanja različitih uvjeta i karakteristika haljina, može značajno unaprijediti sposobnost modela da točno klasificira slike u sve kategorije.The presence of technology in every aspect of life has become almost inevitable. Technological progress is transforming the way we live and influencing our understanding and interpretation of the world around us. The progress in the field of machine learning, which has affected all layers of science and most industries, especially the fashion industry, is particularly evident. Therefore, the application of supervised machine learning in image classification with a focus on culturally specific dresses from different regions of the world becomes important. This approach aims to contribute to a better understanding and categorization of culturally specific clothing traditions, with potential applications in the fashion industry, education and the promotion of cultural diversity. The aim of this paper was to develop a model for image classification that can recognize and classify various dresses according to their origin. An image classification model was developed, using a dataset containing images of culturally diverse dresses from Scandinavia, the Mediterranean, the United Arab Emirates, and Central Europe. The model was trained on different numbers of epochs (50 and 100) to compare the results and performance of the model with respect to the number of epochs. The analysis of the performance of the model in relation to the number of epochs shows that the model trained on a larger number of epochs (100) achieves slight improvements compared to the model trained on a smaller number of epochs (50). A larger number of epochs (100) improves the performance in the classification of dress images characteristic of the United Arab Emirates and Scandinavia, while negatively affectting the classification of dress images characteristic of Central Europe and the Mediterranean. Both the model trained on 50 epochs and the model trained on 100 epochs have difficulties in classifying images of dresses characteristic of Central Europe, while they achieve the best results in classification of images of dresses characteristic of the Mediterranean. To achieve optimal results, further adjustment of the number of epochs and other hyperparameters is necessary. Also, increasing the number and diversity of the dataset, with the aim of better
reflecting the different conditions and characteristics of the dresses, can significantly improve the model's ability to accurately classify images into all categories
Image classification using supervised machine learning
No full textPrisutnost tehnologije u svakom aspektu života postala je gotovo neizostavna. Tehnološki napredak transformira način na koji živimo i utječe na naše razumijevanje i interpretaciju svijeta oko nas. Posebno se očituje napredak u području strojnog učenja koje je zahvatilo sve slojeve znanosti i većinu industrija, posebno modnu industriju. Stoga primjena nadziranog strojnog
učenja u klasifikaciji slika s naglaskom na kulturno specifične haljine iz različitih regija svijeta postaje važna. Ovim pristupom želi se doprinijeti boljem razumijevanju i kategorizaciji kulturno specifičnih odjevnih tradicija, s potencijalnim primjenama u modnoj industriji, obrazovanju i promicanju kulturne raznolikosti. Cilj ovog rada bio je razviti model za klasifikaciju slika koji može prepoznati i klasificirati raznovrsne haljine prema njihovom podrijetlu. Razvijen je model za klasifikaciju slika koristeći
skup podataka koji sadrži slike kulturno raznolikih haljina iz Skandinavije, Mediterana, Ujedinjenih Arapskih Emirata i središnje Europe. Model je treniran na različitom broju epoha (50 i 100) kako bi se usporedili rezultati i performanse modela s obzirom na broj epoha. Analiza performansi modela u odnosu na broj epoha, pokazuje da model treniran na većem broju epoha
(100) postiže neznatna poboljšanja u odnosu na model treniran na manjem broju epoha (50). Veći broj epoha (100) poboljšava performanse u klasifikaciji slika haljina karakterističnih za Ujedinjene Arapske Emirate i Skandinaviju, dok negativno utječe na klasifikaciju slika haljina karakterističnih za središnju Europu i Mediteran. I model treniran na 50 epoha i model treniran na 100 epoha ima poteškoća u klasificiranju slika haljina karakterističnih za središnju Europu, dok najbolje rezultate postiže u klasifikaciji slika haljina karakterističnih za Mediteran. Za postizanje optimalnih rezultata potrebno je daljnje podešavanje broja epoha i drugih hiperparametara. Također, povećanje broja i raznolikosti skupa podataka, s ciljem boljeg
odražavanja različitih uvjeta i karakteristika haljina, može značajno unaprijediti sposobnost modela da točno klasificira slike u sve kategorije.The presence of technology in every aspect of life has become almost inevitable. Technological progress is transforming the way we live and influencing our understanding and interpretation of the world around us. The progress in the field of machine learning, which has affected all layers of science and most industries, especially the fashion industry, is particularly evident. Therefore, the application of supervised machine learning in image classification with a focus on culturally specific dresses from different regions of the world becomes important. This approach aims to contribute to a better understanding and categorization of culturally specific clothing traditions, with potential applications in the fashion industry, education and the promotion of cultural diversity. The aim of this paper was to develop a model for image classification that can recognize and classify various dresses according to their origin. An image classification model was developed, using a dataset containing images of culturally diverse dresses from Scandinavia, the Mediterranean, the United Arab Emirates, and Central Europe. The model was trained on different numbers of epochs (50 and 100) to compare the results and performance of the model with respect to the number of epochs. The analysis of the performance of the model in relation to the number of epochs shows that the model trained on a larger number of epochs (100) achieves slight improvements compared to the model trained on a smaller number of epochs (50). A larger number of epochs (100) improves the performance in the classification of dress images characteristic of the United Arab Emirates and Scandinavia, while negatively affectting the classification of dress images characteristic of Central Europe and the Mediterranean. Both the model trained on 50 epochs and the model trained on 100 epochs have difficulties in classifying images of dresses characteristic of Central Europe, while they achieve the best results in classification of images of dresses characteristic of the Mediterranean. To achieve optimal results, further adjustment of the number of epochs and other hyperparameters is necessary. Also, increasing the number and diversity of the dataset, with the aim of better
reflecting the different conditions and characteristics of the dresses, can significantly improve the model's ability to accurately classify images into all categories
Analysis of information using the national branding index in the Republic of Croatia
No full textJedinstvenost i prepoznatljivost karakteristike su gotovo svake države na svijetu. Komunikacija
nacionalnog brenda predstavlja važan segment u prepoznatljivosti zemlje te utječe na
poslovanje, turizam, investicije, itd. Stoga analiza informacija kojima se procjenjuje razina
nacionalnog brendiranja predstavlja važan korak u mjerenju napretka ostvarenog nacionalnim
brendiranjem.
Cilj ovog rada bio je provesti analizu informacija o Hrvatskoj kao nacionalnom brendu
primjenom Indeksa nacionalnog brendiranja Republike Hrvatske kroz šest dimenzija: Ljudi,
Upravljanje, Izvoz, Turizam, Ulaganja i imigracije, Kultura i baština. Mogući nedostaci kod
provedenog istraživanja su dominacija dobi od 19 do 25 godina u odnosu na ostale dobne
skupine koje su pristupile istraživanju, premali broj ispitanika koji su sudjelovali u istraživanju
ali i neodgovaranje svih ispitanika na sva postavljena pitanja. Upitnik je ispunilo 342 ispitanika,
od čega 167 domaćeg stanovništva i 175 stranog. Prevladavala je dob od 19 do 25 godina i kod
domaćih ispitanika (60%) i kod stranih (66%). Rezultati istraživanja pokazuju da se percepcija
domaćih i stranih ispitanika od prilike podudara što i dokazuju prosječne ocjene koje iznose od
domaćih ispitanika 4,85 i od stranih 4,85. Prosječne ocjene domaćih i stranih ispitanika su
jednake no ocjene se međusobno razlikuju za svaku dimenziju posebno. Također Hrvatska je
sa svojom prosječnom ocjenom od 4,85 zauzela srednju poziciju. Navedeni rezultati ukazuju
na to da Hrvatska nije loše percipirana od strane domaćih i stranih ispitanika te da svakako ima
veliki potencijal za napredak.Uniqueness and recognizability are the characteristics of almost every country in the world.
The communication of the national brand represents an important segment in the recognition
of the country and affects business, tourism, investments, etc. Therefore, the analysis of
information that is used to assess the level of national branding represents an important step in
measuring the progress made by national branding.
The aim of this paper was to analyze information about Croatia as a national brand by applying
the National Branding Index of the Republic of Croatia through six dimensions: People,
Management, Exports, Tourism, Investments and immigration, Culture and heritage. Possible
shortcomings of the conducted research are the predominance of the age group from 19 to 25
years old compared to the other age groups that participated in the research, the insufficient
number of respondents who participated in the research, but also the failure of all respondents
to answer all the questions. The questionnaire was completed by 342 respondents, of which
167 were local and 175 were foreign. The age of 19 to 25 years prevailed for both domestic
respondents (60%) and foreign respondents (66%). The results of the research shows that the
perception of domestic and foreign respondents are about the same, which is evidenced by the
average ratings of 4,85 from domestic respondents and 4.85 from foreign respondents. The
average scores of domestic and foreign respondents are equal, but they differ from each other
for each dimension separately. Also, Croatia, with its average rating of 4.85 took a middle
position. The above results indicate that Croatia is not badly perceived by domestic and foreign
respondents and that it certainly has great potential for progress
Narrative of Romance in Ružica Zagorska's Novel Pobjeda ljubavi (Victory of Love)
No full textU radu se analiziraju obilježja književnog žanra romanse na primjeru romana Pobjeda ljubavi te se roman interpretira u okviru nakladničke cjeline Biblioteka moje kćeri koju nakladnik Stjepan Kugli objavljuje od 1922. godine i u kojoj je objavljen i analizirani roman. Djevojke u adolescentskoj dobi, čitajući knjige prilagođene upravo njima, dolaze do spoznaje što je sentimentalnost odnosno sentimentalno pripovijedanje
Narrative of Romance in Ružica Zagorska's Novel Pobjeda ljubavi (Victory of Love)
No full textU radu se analiziraju obilježja književnog žanra romanse na primjeru romana Pobjeda ljubavi te se roman interpretira u okviru nakladničke cjeline Biblioteka moje kćeri koju nakladnik Stjepan Kugli objavljuje od 1922. godine i u kojoj je objavljen i analizirani roman. Djevojke u adolescentskoj dobi, čitajući knjige prilagođene upravo njima, dolaze do spoznaje što je sentimentalnost odnosno sentimentalno pripovijedanje
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Get PDF“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
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