Iskanje po katalogu digitalne knjižnice

Opis: Since the discovery of the Differential Evolution algorithm, new and improved versions have continuously emerged. In this paper, we review selected algorithms based on Differential Evolution that have been proposed in recent years. We examine the mechanisms integrated into them and compare the performance of algorithms. To compare their performances, statistical comparisons were used as they enable us to draw reliable conclusions about the algorithms’ performances. We use the Wilcoxon signed-rank test for pairwise comparisons and the Friedman test for multiple comparisons. Subsequently, the Mann–Whitney U-score test was added. We conducted not only a cumulative analysis of algorithms, but we also focused on their performances regarding the function family (i.e., unimodal, multimodal, hybrid, and composition functions). Experimental results of algorithms were obtained on problems defined for the CEC’24 Special Session and Competition on Single Objective Real Parameter Numerical Optimization. Problem dimensions of 10, 30, 50, and 100 were analyzed. In this paper, we highlight promising mechanisms for further development and improvements based on the study of the selected algorithms.
Ključne besede: global optimization, differential evolution, benchmark suite, mechanisms, statistical tests, performance
Objavljeno v DKUM: 19.05.2025; Ogledov: 0; Prenosov: 4
Celotno besedilo (313,93 KB)

Opis: With the transition to neural architectures, machine translation achieves very good quality for several resource-rich languages. However, the results are still much worse for languages with complex morphology, especially if they are low-resource languages. This paper reports the results of a systematic analysis of adding morphological information into neural machine translation system training. Translation systems presented and compared in this research exploit morphological information from corpora in different formats. Some formats join semantic and grammatical information and others separate these two types of information. Semantic information is modeled using lemmas and grammatical information using Morpho-Syntactic Description (MSD) tags. Experiments were performed on corpora of different sizes for the English–Slovene language pair. The conclusions were drawn for a domain-specific translation system and for a translation system for the general domain. With MSD tags, we improved the performance by up to 1.40 and 1.68 BLEU points in the two translation directions. We found that systems with training corpora in different formats improve the performance differently depending on the translation direction and corpora size.
Ključne besede: neural machine translation, POS tags, MSD tags, inflected language, data sparsity, corpora size
Objavljeno v DKUM: 28.03.2025; Ogledov: 0; Prenosov: 11
Celotno besedilo (448,16 KB)
Gradivo ima več datotek! Več...

Opis: Sequence-to-sequence models have been applied to many challenging problems, including those in text and speech technologies. Normalization is one of them. It refers to transforming non-standard language forms into their standard counterparts. Non-standard language forms come from different written and spoken sources. This paper deals with one such source, namely speech from the less-resourced highly inflected Slovenian language. The paper explores speech corpora recently collected in public and private environments. We analyze the efficiencies of three sequence-to-sequence models for automatic normalization from literal transcriptions to standard forms. Experiments were performed using words, subwords, and characters as basic units for normalization. In the article, we demonstrate that the superiority of the approach is linked to the choice of the basic modeling unit. Statistical models prefer words, while neural network-based models prefer characters. The experimental results show that the best results are obtained with neural architectures based on characters. Long short-term memory and transformer architectures gave comparable results. We also present a novel analysis tool, which we use for in-depth error analysis of results obtained by character-based models. This analysis showed that systems with similar overall results can differ in the performance for different types of errors. Errors obtained with the transformer architecture are easier to correct in the post-editing process. This is an important insight, as creating speech corpora is a time-consuming and costly process. The analysis tool also incorporates two statistical significance tests: approximate randomization and bootstrap resampling. Both statistical tests confirm the improved results of neural network-based models compared to statistical ones.
Ključne besede: low-resource language, applications, spoken language, normalization, character unit, subword unit, statistical model, long short-term memory, transformer, error analysis
Objavljeno v DKUM: 31.01.2025; Ogledov: 0; Prenosov: 12
Celotno besedilo (437,99 KB)
Gradivo ima več datotek! Več...

Opis: Magistrsko delo obravnava različne algoritme stiskanja tekstovnih datotek in analizira, ali jezik, v katerem je zapisana vhodna datoteka, vpliva na uspešnost stiskanja z izbranimi algoritmi. Preučeni in predstavljeni bodo izbrani algoritmi stiskanja, ugotovljene prednosti uporabe izbranih algoritmov stiskanja tekstovnih datotek, določene entropije analiziranih jezikov na ravni znakov, izvedeni praktični testi izbranih algoritmov stiskanja tekstovnih datotek s testnimi vzorci različnih jezikov, analizirano in ugotovljeno, ali jezik v izbranih testnih vzorcih vpliva na uspešnost posameznih algoritmov stiskanja tekstovnih datotek. Delo bo iskalo povezave med entropijo jezika in uspešnostjo stiskanja. Na koncu bo na primeru Huffmanovega algoritma, ki kodira posamezne znake, preverjeno, ali kodiranje daljših nizov izboljša učinkovitost kodiranja.
Ključne besede: naravni jezik, entropija jezika, algoritmi stiskanja, algoritem LZW, tekstovne datoteke
Objavljeno v DKUM: 23.12.2024; Ogledov: 0; Prenosov: 28
Celotno besedilo (2,04 MB)

Opis: V magistrskem delu smo opisali čedalje večjo problematiko glede ohranjanja zdravja in kakovosti življenja starejših oseb ter predstavili potrebo po zaznavanju aktivnosti dnevnega življenja. V ta namen smo zasnovali dva različna sistema senzorskih omrežij. K obema sistemoma smo dodali podatkovno bazo na oddaljenem računalniku za zajemanje podatkov. Eden od sistemov senzorskega omrežja deluje na komunikaciji RF, medtem ko drugi na komunikaciji WiFi. Njuno delovanje smo preverili v testnem okolju. Ker sta omrežji napajani z baterijo, smo opravili meritve porabe toka ter napajalne napetosti. Rezultate smo predstavili v zaključku magistrskega dela.
Ključne besede: senzorsko omrežje, aktivnosti dnevnega življenja, modul RF, modul WiFi, protokol MQTT
Objavljeno v DKUM: 01.03.2024; Ogledov: 363; Prenosov: 40
Celotno besedilo (3,33 MB)