Cross-lingual alignments of ELMo contextual embeddings

Building machine learning prediction models for a specific NLP task requires sufficient training data, which can be difficult to obtain for less-resourced languages. Cross-lingual embeddings map word embeddings from a less-resourced language to a resource-rich language so that a prediction model trained on data from the resource-rich language can also be used in the less-resourced language. To produce cross-lingual mappings of recent contextual embeddings, anchor points between the embedding spaces have to be words in the same context. We address this issue with a novel method for creating cross-lingual contextual alignment datasets. Based on that, we propose several cross-lingual mapping methods for ELMo embeddings. The proposed linear mapping methods use existing Vecmap and MUSE alignments on contextual ELMo embeddings. Novel nonlinear ELMoGAN mapping methods are based on GANs and do not assume isomorphic embedding spaces. We evaluate the proposed mapping methods on nine languages, using four downstream tasks: named entity recognition (NER), dependency parsing (DP), terminology alignment, and sentiment analysis. The ELMoGAN methods perform very well on the NER and terminology alignment tasks, with a lower cross-lingual loss for NER compared to the direct training on some languages. In DP and sentiment analysis, linear contextual alignment variants are more successful.Comment: 30 pages, 5 figure

FinEst BERT and CroSloEngual BERT: less is more in multilingual models

Large pretrained masked language models have become state-of-the-art solutions for many NLP problems. The research has been mostly focused on English language, though. While massively multilingual models exist, studies have shown that monolingual models produce much better results. We train two trilingual BERT-like models, one for Finnish, Estonian, and English, the other for Croatian, Slovenian, and English. We evaluate their performance on several downstream tasks, NER, POS-tagging, and dependency parsing, using the multilingual BERT and XLM-R as baselines. The newly created FinEst BERT and CroSloEngual BERT improve the results on all tasks in most monolingual and cross-lingual situationsComment: 10 pages, accepted at TSD 2020 conferenc

Decoupling management and technological innovations: Resolving the individualism-collectivism controversy

This study aims to resolve the contradictory previous research findings on the relationship between individualism–collectivism and innovation. We draw on innovation theory and relate to the difference between non-technological (management) and technological innovation types as well as to the distinction between exploration and exploitation (invention and commercialization of technological innovations). Using Community Innovation Survey (CIS) 2006 micro data for innovation at the organizational level in 13 countries – along with Hofstede (1980, 2001), GLOBE (2005), and Schwartz (2006) scores for individualism–collectivism – we apply Hierarchical Linear Modeling (HLM). The results indicate that individualism is positively related to the invention phase, whereas collectivism is beneficial for the commercialization of innovative ideas. Furthermore, in collectivistic cultures, management innovation plays a more important stimulating role in enhancing technological innovation than it does in individualistic ones. This provides the managers with an idea of when innovation processes in their companies would be more favorable versus detrimental

Feature construction using explanations of individual predictions

Feature construction can contribute to comprehensibility and performance of machine learning models. Unfortunately, it usually requires exhaustive search in the attribute space or time-consuming human involvement to generate meaningful features. We propose a novel heuristic approach for reducing the search space based on aggregation of instance-based explanations of predictive models. The proposed Explainable Feature Construction (EFC) methodology identifies groups of co-occurring attributes exposed by popular explanation methods, such as IME and SHAP. We empirically show that reducing the search to these groups significantly reduces the time of feature construction using logical, relational, Cartesian, numerical, and threshold num-of-N and X-of-N constructive operators. An analysis on 10 transparent synthetic datasets shows that EFC effectively identifies informative groups of attributes and constructs relevant features. Using 30 real-world classification datasets, we show significant improvements in classification accuracy for several classifiers and demonstrate the feasibility of the proposed feature construction even for large datasets. Finally, EFC generated interpretable features on a real-world problem from the financial industry, which were confirmed by a domain expert.Comment: 54 pages, 10 figures, 22 table

Kako je epidemija COVID-19 utjecala na upotrebu i tržište droga u Sloveniji?

The purpose of our study was to explore the effect of the COVID-19 epidemic on drug use, the drug market and the availability of help and support in Slovenia. Through an online questionnaire, we collected a non-representative sample of 680 people who used drugs before and during the epidemic in 2020. The results showed the use of illicit drugs and alcohol has reduced. A significant increase in the frequency of use has only been detected in marijuana. The most prominent changes in the drug market were the reduced number of drug dealers and lower availability of certain drugs. Accessibility to drug services has been reduced and respondents also had significant financial consequences due to loss of work. Due to decreased availability of sources of support at the time of the epidemic, adjustments to services for drug users are necessary before the end of the COVID-19 pandemic in terms of promoting online interventions and maintaining contact with users when the services are not physically accessible.Svrha našeg istraživanja bila je istražiti kako je epidemija COVID-19 utjecala na upotrebu droga i tržište droga u Sloveniji. Internetskim upitnikom obuhvatili smo nereprezentativni uzorak od 680 ljudi koji su konzumirali droge prije i tijekom epidemije 2020. Upotreba ilegalnih droga i alkohola smanjena je. Značajno povećanje učestalosti upotrebe zabilježeno je samo s marihuanom. Najistaknutije promjene na tržištu droga bile su pad dilera i manja dostupnost odre- đenih droga. Pristup uslugama za korisnike droga smanjen je, a ispitanici su imali i znatne financijske posljedice zbog gubitka posla. Zbog slabe dostupnosti izvora podrške u vrijeme epidemije, prilagodbe pružatelja usluga korisnicima droga potrebne su prije kraja pandemije, u smislu promicanja internetskih intervencija i održavanja kontakta s korisnicima kada usluge nisu fizički dostupne

COMPUTER SYSTEMS FOR MULTIMEDIA STIMULI GENERATION IN PSYCHOTHERAPY

Učinkovit, točan i brz postupak generiranja multimedijskih pobuda, implementiran kao računalni sustav, je izrazito koristan domenskim stručnjacima iz područja psihologije, psihijatrije i neuroznanosti u odabiru i prikazivanju sekvenci pobuda, te kao pomoć pri estimaciji kognitivnih i afektivnih parametara ispitanika. Prvenstveni cilj ovog rada je predstaviti računalni sustav za generiranje multimedijskih pobuda i neurofeedback kojeg su razvili autori. Računalni sustav koristi se u sprezi s afektivnim bazama afektivne multimedije, a namijenjen je za istraživanje emocija i pažnje, te za neke oblike psihoterapije s bihevioralnom komponentom. Računalni sustav generatora multimedijskih pobuda ispitan je u eksperimentu elicitacije emocija u virtualnoj stvarnosti sa 6 ispitanika. Pri tome je korišten eMotiv EPOC+ 14-kanalni mobilni EEG i HTC Vive uređaj za virtualnu stvarnost. Slikovne pobude preuzete su iz baze afektivne multimedije NAPS te su generirane dvije sekvence s ukupno 20 slika za elicitaciju osnovnih emocija tuge i sreće. Rezultati eksperimenta potvrđuju ispravnost dizajna i implementacije računalnog sustava generatora multimedijskih pobuda.Effective, accurate and fast process of multimedia stimuli generation, implemented as a computer system, is very useful to domain specialists in the fields of psychology, psychiatry and neuroscience in selecting and displaying excitation sequences, and as an aid in estimating the cognitive and affective parameters of the subject. The primary purpose of this paper is to present a computer system for multimedia stimuli generation and neurofeedback developed by the authors. The computer system is used with affective multimedia databases and is intended for research of emotions and attention, and for some types of psychotherapy with a behavioral component. The computer system was tested in an emotion elicitation experiment in virtual reality environment with 6 subjects. The eMotiv EPOC + 14-channel mobile EEG and HTC Vive virtual reality device were used. The pictorial stimuli were downloaded from the NAPS affective multimedia database and two sequences were generated with a total of 20 pictures to elicit the basic emotions of sadness and happiness. The results of the experiment confirm the correctness of the design and implementation of the computer system of the multimedia stimuli generator

Lateralizacija glasnice - primjer

Respiracijska insuficijencija uzrokovana parezom ili paralizom obje glasnice najčešće je posljedica kirurških intervencija, tj. jatrogene je etiologije i predstavlja životno ugrožavajuće hitno stanje. Možemo ga tretirati različitim postupcima, a lateralizacija glasnice jedna je od manje invazivnih metoda, što ju čini povoljnijom terapijskom opcijom za bolesnika. Riječ je o postupku koji se može izvoditi vanjsko-unutarnjim ili unutarnje-vanjskim pristupom. U našem primjeru prikazan je slučaj obostrane paralize glasnica, primarno u hitnoći zbrinute traheotomijom. U cilju bržeg dekanilmana, nakon 3 dana učinjena je lateralizacija lijeve glasnice vanjsko-unutarnjim pristupom, metodom trostrukoga uboda. Prilikom postupka, za uvođenje konca korištena je epiduralna igla, a uvedeni konci poput omče obuhvatili su lijevu glasnicu, te su učvršćeni čvorom površno, na koži vrata. Time je lijeva glasnica zadržana u lateraliziranom položaju i omogućena je respiracija po dekanilmanu. U raspravi prikazujemo druge modalitete i instrumente koji se mogu koristiti za ovaj postupak

Drvenaste invazivne vrste gradskih područja u Karlovcu

Sadnja i sakupljanje alohtone vegetacije u urbanim prostorima pejzažne arhitekture odražavalo je u povijesti status vlasnika i žitelja toga prostora. Danas se pojedine vrste nalaze na popisima invazivnih vrsta koje ugrožavaju ili potencijalno mogu ugroziti prirodna staništa. Analizom biljnih vrsta i determinacijom drvenastih vrsta u karlovačkim perivojima i različitim nasadima povijesne jezgre pod zaštitom Ministarstva kulture utvrđene su vrste Ailanthus altissima (Mill.) Swingle, Acer negundo L. i Robinia pseudoacacia L. Pronađene jedinke realno ne predstavljaju žarišta i potencijalna mjesta širenja ni vegetativno, niti generativno, zbog kvalitetnoga održavanja travnjaka i zelenih površina u vlasništvu Grada. Potencijalnu opasnost mogu izazvati privatne parcele i zapušteni objekti. Također kroz planove gradske tvrtke, trend je uklanjanje takvih vrsta te sadnja i uređenje perivoja pretežito autohtonim vrstama. Moguća problematika ostaje u nedovoljnom obrađivanju, deponiranju i kompostiranju dijelova biljaka čime se otvara put prirodnim staništima