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Digital Competition in Different Sectors of the Economy
Get PDFThe introduction of information and communication technologies (ICT) into different sectors of the economy has led to the emergence of the digital economy, defined by the “fourth industrial revolution”. Digital competition in different sectors of the Ukrainian economy is mainly seen in the creation of digital services, while global practice demonstrates the modernization of enterprises based on digitalization of production, the sales sphere and so on.Digitization and its competition in different spheres of the national economy is studied here. Namely, it is determined that nowadays digitization of the real sector of Ukraine\u27s economy in the form of innovative production is not observed at the moment, but digitalization is more represented in the financial sector. Taking into account the current structure of the financial market in Ukraine, it was found that digitalization processes have largely affected the banking sector, which is embodied in the presence of developed Internet banking. It is found that the stock market in Ukraine currently lags far behind the banking sector in terms of the introduction of digital technologies
Machine learning algorithm application in trip planning
Get PDFThis article explores how machine learning can be applied in efficiently solving a variation of the Travelling Salesman Problem (TSP) in the context of air travel tourism. Large number of cities create too many trip route combinations to be efficiently evaluated in real time. The method proposed uses a feedforward neural network to narrow down the number of trip route combinations, while a more traditional algorithm based on dynamic programming is then able to select the best trip offers. It was shown that the method could be applied in practice to achieve almost real-time generation of best possible trip offers while evaluating a large amount of real-world flight data
Bendrinės lietuvių kalbos skiemenavimas sonoringumo teorijos požiūriu
Get PDFThe article discusses the research which aims to ascertain whether the sonority of sounds could be used to determine boundaries of syllables in consonant clusters and if this principle is commonly employed by a sample of language users. The research consists of a) the overview of more significant foreign authors’ works, which is then used to identify the theoretic hierarchy of consonant clusters in Lithuanian, b) the exploratory analysis of consonant sonority, c) the investigation of sonority in consonant clusters, d) the research of tendencies in language users’ syllabification. The results have revealed that after establishing the hierarchy of consonant clusters in Lithuanian and applying the principle of syllabification by sonority, one fifth of the consonant clusters in the empirical data base is impossible to syllabify. Neither predicted phonetic syllable, nor the phonological syllable is commonly employed by the language users. The users are likely to assign at least one consonant of a cluster to a preceding syllable, while only the last consonant of polynomial clusters is assigned to the onset of a later syllable. Fricative consonants in consonant clusters are assigned to the coda of a previous syllable.Straipsnyje aprašomo tyrimo tikslas – išsiaiškinti, ar gali būti pritaikomas garsų sonoringumo principas nustatant skiemenų ribą bendrinės lietuvių kalbos priebalsių samplaikose ir ar šį principą remia kalbos vartotojų skiemenavimo polinkiai. Tyrimą sudaro: a) reikšmingesnių užsienio autorių darbų apžvalga ir ja paremtos teorinės lietuvių kalbos priebalsių sonoringumo hierarchijos nustatymas, b) žvalgomoji lietuvių kalbos priebalsių sonoringumo analizė, c) priebalsinių samplaikų sonoringumo nagrinėjimas, d) kalbos vartotojų skiemenavimo polinkių tyrimas. Rezultatai rodo, kad nustačius bendrinės lietuvių kalbos priebalsių sonoringumo hierarchiją ir pritaikius skiemenavimo pagal sonoringumą principus, beveik penktadalio empirinėje medžiagoje rastų priebalsių samplaikų negalima suskiemenuoti. Vartotojų skiemenavimo polinkiai neremia nei prognozuoto fonetinio, nei fonologinio skiemens ribų. Vartotojai yra linkę ankstesniam skiemeniui priskirti bent vieną samplaikos priebalsį, tolesnio skiemens pratarui priskirti tik paskutinį daugianarės samplaikos priebalsį, priebalsių samplaikose esantį pučiamąjį priebalsį priskirti ankstesnio skiemens ištarui
Probleminiai gydytojo ar kito sveikatos priežiūros specialisto baudžiamosios atsakomybės už neatsargiai padarytą žalą paciento gyvybei arba sveikatai pagal Lietuvos Respublikos baudžiamuosius įstatymus aspektai
Get PDFĮmonių bankroto prognozavimas naudojant gilųjį mokymą
Get PDFŠiame straipsnyje pristatomi sukurti giliojo mokymosi modeliai skirti įmonių bankroto prognozavimui. Tyrimo metu, naudojant Lietuvos įmonių duomenis, sukurti du modeliai: daugiasluoksnis perceptronas ir konvoliucinis neuroninis tinklas. Modelių apmokymui ir hiperparametrų validavimui, buvo naudojami subalansuoti duomenų poaibiai. Siekiant įvertinti modelių gebėjimą atskirti bankroto atvejus išbalansuotoje duomenų aibėje, modelių testavimui buvo naudojamas poaibis, kuriame buvo išlaikytas pradinio duomenų rinkinio klasių disbalansas. Gauti rezultatai parodė, kad sukurti giliojo mokymosi modeliai atpažįsta bankroto atvejus duomenų aibėje su dideliu klasių disbalansu
Analysis of Economic Activity of Foreign Direct Investors in Latvia
Get PDFThe aim of this article is to investigate the activity of foreign direct investors in Latvia and find out the main source of financing for foreign investors - new investments or reinvested earnings. To achieve the set goal, the methodology of the Sixth Edition of the International Monetary Fund\u27s Balance of Payments and International Investment Position Manual was used to define the types of foreign direct investment (FDI). This methodology was adapted to Latvian data. At the request of the author, Lursoft IT Ltd selected business data on all registered companies with foreign capital in Latvia since 2005 and aggregate data were used in the analysis. Foreign direct investment in Latvia flows mainly in the form of reinvested earnings, due to the profit earned from operating activities in Latvia. While new investments or greenfield investments in equity is lower compared to the amount of reinvested earnings