New VILNIUS TECH eBook

January 27, 2025
New VILNIUS TECH eBook:
Rimutė Raudeliūnienė, Irena Danilevičienė
Apskaita verslo sprendimams“ 
"Accounting for Business Decisions". The book is written in Lithuanian.

The textbook offers a comprehensive and systematic overview of financial accounting, covering its concept, essence, functions, objectives, and the specifics of organizing the accounting process. It explores the primary levels of financial accounting regulation, emphasizing their unique characteristics, and examines key normative documents, international accounting standards, and EU directives that govern accounting practices, highlighting their relevance and benefits. Additionally, the Lithuanian financial reporting standards and the procedures for recording and evaluating economic transactions are thoroughly analyzed.

The section on long-term assets addresses their nature, classifications, and specific accounting procedures, including the registration and acquisition cost of tangible fixed assets, methods for calculating and recording depreciation, and processes related to asset utilization, reconstruction, repair, revaluation, and disposal. The amortization and disposal of intangible fixed assets are also covered in detail.

The textbook delves into inventory accounting, explaining the composition and balance sheet valuation of inventory, along with valuation methodologies, acquisition and production cost calculation, and net realizable value. It discusses inventory write-down accounting, acceptance procedures, recording, and documentation of issuance transactions. Furthermore, methods for accounting inventory usage, valuation techniques, and the accounting specifics for raw materials, purchased goods for resale, work-in-progress, and finished products are explored.

Accounts receivable are analyzed as a key component of current assets, with a detailed examination of their classification and the specifics of their recognition and registration in accounting. The section on liabilities defines their essence, structure, and classification, and addresses the accounting of accrued expenses, deferred income, and other related specifics.

The concept and structure of equity are comprehensively explained, with a focus on the prerequisites for forming share capital, regulations governing reserve creation, and the accounting for share capital increases and decreases. Reserve accounting and the treatment of changes in retained earnings or accumulated losses are also systematically presented.

The section on wages defines the nature of compensation and describes various remuneration forms and systems, alongside the legal framework regulating payroll. Examples of liabilities related to employment relationships, including payroll calculations, deductions, and accounts, are provided in alignment with legal provisions.

Revenue accounting is analyzed through an in-depth explanation of revenue recognition and valuation principles, revenue classification, and the specific procedures for recording different types of revenue. Similarly, expense accounting is discussed, with an emphasis on recognition principles, expense types, and the accounting treatment of cost of sales, selling, general and administrative expenses, other operating costs, financial and investment expenses, and income tax expenses.

Finally, the textbook highlights the importance and role of financial statements, systematically analyzing the principles and requirements for the preparation of annual financial reports, ensuring compliance with relevant standards and regulations.

eBook edition   >>>

* Institutional users are granted cost-free access to the e-books by logging onto the University's computer network, whether on-site or remotely through a Virtual Private Network (VPN). 

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VILNIUS TECH Library invites you to follow the published new dissertations. The dissertation „Research and application of machine learning methods for migraine attack prediction“ prepared at VILNIUS TECH by Viroslava Kapustynska. The dissertation was prepared in 2021–2026. Scientific consultant – Prof. Dr Šarūnas Paulikas. The dissertation was defended at the public meeting of the Dissertation Defense Council of the Scientific Field of Electrical and Electronic Engineering in the Aula Doctoralis Meeting Hall of Vilnius Gediminas Technical University at 2 p.m. on 9 June 2026. Migraine is a complex neurological disorder characterized by strong inter- and intra-individual variability, which makes early forecasting difficult using only clinical observations. Wearable biosensors combined with machine learning offer new opportunities to detect subtle physiological changes that may precede migraine attacks and to develop individualized prediction models. This dissertation investigates migraine analysis and next-day prediction using physiological recordings collected under real-life monitoring conditions. Data were obtained with the Empatica Embrace Plus wearable device and include electrodermal activity, pulse rate, skin temperature, and movement-related signals. The analysis focuses on nocturnal recordings, since the night period provides a more stable physiological context with fewer external disturbances. Nights were standardized using sleep-based contextual selection and consistent night-level rules. The experimental framework is organized in two stages. In the first stage, a window-level binary classification task is used as an exploratory methodological analysis to examine how design choices influence model performance. Night recordings are segmented into analysis frames ranging from 5 to 120 minutes, statistical features are extracted, and the influence of signal preprocessing and feature representation is evaluated across several classifier families, including Random Forest, XGBoost, histogram-based gradient boosting, support vector machines, and k-nearest neighbors. In the second stage, the research evaluates next-day migraine prediction based on whole-night recordings. This stage refines the experimental methodology to obtain more reliable estimates of predictive performance under a stricter validation framework. The analysis focuses on the effect of temporal aggregation while comparing the same classifier families under consistent evaluation conditions. The results demonstrate considerable variability across participants in achievable prediction performance and optimal modeling configurations. Shorter analysis frames generally preserve informative short-term physiological changes, whereas longer windows tend to smooth these variations. Signal preprocessing shows a window-dependent effect and does not consistently improve performance. Overall, the results highlight the importance of temporal resolution, rigorous validation, and individualized modeling for wearable-based migraine prediction systems. Doctoral dissertation readers can search via VILNIUS TECH Virtual Library.
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