03279nam 2200481 450 991081204870332120230629090623.03-482-00552-4(CKB)4100000009148637(MiAaPQ)EBC6017418(Au-PeEL)EBL6017418(OCoLC)1193132231(EXLCZ)99410000000914863720230629d2019 uy 0gerurcnu||||||||txtrdacontentcrdamediacrrdacarrierIFRS essentials /Norbert Lüdenbach, Dieter Christian5. Auflage.Herne :NWB Ausbildung,2019.1 online resource (568 pages)NWB Studium Betriebswirtschaft3-482-59835-5 Intro -- Rahmenkonzept -- IAS1 Darstellung des Abschlusses -- IAS2 Vorräte -- IAS7 Kapitalflussrechnung -- IAS8 Bilanzierungsmethoden, Schätzungsänderungen und Fehler -- IAS 10 Ereignisse nach der Berichtsperiode -- IAS 12 Steuern vom Einkommen und vom Ertrag -- IAS 16 Sachanlagen -- IAS 19 Leistungen an Arbeitnehmer/IAS 26 Bilanzierung und Berichterstattung von Altersversorgungsplänen -- IAS 20 Öffentliche Zuwendungen -- IAS 21 Die Auswirkungen von Wechselkursänderungen -- IAS 23 Fremdkapitalkosten -- IAS 24 Angaben zu nahe stehenden Parteien -- IAS 26 Bilanzierung und Berichterstattung von Altersversorgungsplänen -- IAS 27 Einzelabschlüsse -- IAS 28 Anteile an Gemeinschafts- und assoziierten Unternehmen -- IAS 29 Rechnungslegung in Hochinflationsländern -- IAS 32 Finanzinstrumente: Darstellung -- IAS 33 Ergebnis je Aktie -- IAS 34 Zwischenberichterstattung -- IAS 36 Wertminderung von Vermögenswerten -- IAS 37 Rückstellungen, Eventualschulden und Eventualforderungen -- IAS 38 Immaterielle Vermögenswerte -- IAS 40 Anlageimmobilien -- IAS 41 Landwirtschaft -- IFRS1 Erstmalige Anwendung der IFRS -- IFRS2 Anteilsbasierte Vergütungen -- IFRS3 Unternehmenszusammenschlüsse -- IFRS4 Versicherungsverträge -- IFRS5 Zum Verkauf gehaltene langfristige Vermögenswerte und aufgegebene Geschäftsbereiche -- IFRS6 Erkundung und Evaluierung von Bodenschätzen -- IFRS7 Finanzinstrumente: Angaben -- IFRS8 Operative Segmente -- IFRS9 Finanzinstrumente -- IFRS 10 Konzernabschlüsse -- IFRS 11 Gemeinsame Vereinbarungen -- IFRS 12 Angaben zu Beteiligungen an anderen Unternehmen -- IFRS 13 Ermittlung beizulegender Zeitwerte -- IFRS 14 Regulatorische Abgrenzungsposten -- IFRS 15 Erlöse aus Vertr!gen mit Kunden -- IFRS 16 Leasingverhältnisse -- IFRS 17 Versicherungsverträge.NWB Studium Betriebswirtschaft.AccountingStandardsFinancial statementsStandardsInternational business enterprisesAccountingStandardsAccountingStandards.Financial statementsStandards.International business enterprisesAccountingStandards.657.0218Lüdenbach Norbert1955-953450Christian Dieter1977-MiAaPQMiAaPQMiAaPQBOOK9910812048703321IFRS essentials4094862UNINA05133nam 22005295 450 99664796970331620250304115229.09783031824845(electronic bk.)978303182483810.1007/978-3-031-82484-5(MiAaPQ)EBC31942148(Au-PeEL)EBL31942148(CKB)37771980000041(DE-He213)978-3-031-82484-5(OCoLC)1511106008(EXLCZ)993777198000004120250304d2025 u| 0engurcnu||||||||txtrdacontentcrdamediacrrdacarrierMachine Learning, Optimization, and Data Science 10th International Conference, LOD 2024, Castiglione della Pescaia, Italy, September 22–25, 2024, Revised Selected Papers, Part II /edited by Giuseppe Nicosia, Varun Ojha, Sven Giesselbach, M. Panos Pardalos, Renato Umeton1st ed. 2025.Cham :Springer Nature Switzerland :Imprint: Springer,2025.1 online resource (606 pages)Lecture Notes in Computer Science,1611-3349 ;15509Print version: Nicosia, Giuseppe Machine Learning, Optimization, and Data Science Cham : Springer,c2025 9783031824838 -- Exploring Explainable Machine Learning for Enhanced Ship Performance Monitoring. -- Identifying Potential Key Point of Sale Customers Using Network Centrality. -- Hyperparameter Optimization for Driving Strategies Based on Reinforcement Learning. -- Predicting Multiple Sclerosis Worsening Using Stratification Based and Time Dependent Variables Extracted from Routine Visits Data. -- Predicting University Dropout Rates Using Machine Learning: UniCt case. -- Investigating on Gradient Regularization for Testing Neural Networks. -- SKIE SRL: Structured Key Information Extraction from Business Documents using Statistical Relational Learning. -- Leveraging LLM powered Systems to Accelerate Mycobacterium tuberculosis Research Step One: From Documents to the Vectorstore. -- Vegvisir: Probabilistic model (VAE) for viral T cell epitope prediction. -- Tiny Long Short Term Memory Model for Resource Constrained Prediction of Battery Cycle Life. -- Compact Artificial Neural Network Models for Predicting Protein Residue RNA Base Binding. -- FWin transformer for dengue prediction under climate and ocean influence. -- ENGinnSAND: A Reference Dataset for Monocular Depth Prediction of Line Structures. -- Topological Layering of Mouse Brain Activity in Light Sheet Microscopy Datasets. -- A Constraint Based Savings Algorithm for the Traveling Salesman Problem. -- Gaussian process interpolation with conformal prediction: methods and comparative analysis. -- Using embeddings of pre trained models for cross database dysarthria detection: supervised vs. self supervised approach. -- Personality Profiling for Literary Character Dialogue Agents with Human Level Attributes. -- Integrating Logit Space Embeddings for Reliable Out of Distribution Detection. -- A Computational Framework for Identifying Salient Moments in Motion Capture Data. -- Machine Learning for the Evaluation of the Nephrops Norvegicus Population. -- Enhancing Cluster Based Topic Models through Parametric Dimensionality Reduction with Transformer Encoders. -- Enhancing Arrhythmia Detection Using an Ensemble of Transformer Models for Heartbeat Classification. -- Rapidly Computing Approximate Graph Convex Hulls via FastMap. -- Deep Gaussian mixture model for unsupervised image segmentation. -- Address Classification in E commerce Logistics Using Federated Learning.The three-volume set LNAI 15508-15510 constitutes the refereed proceedings of the 10th International Conference on Machine Learning, Optimization, and Data Science, LOD 2024, held in Castiglione della Pescaia, Italy, during September 22–25, 2024. This year, in the LOD Proceedings decided to also include the papers of the fourth edition of the Symposium on Artificial Intelligence and Neuroscience (ACAIN 2024). The 79 full papers included in this book were carefully reviewed and selected from 127 submissions. The LOD 2024 proceedings focus on machine learning, deep learning, AI, computational optimization, neuroscience and big data that includes invited talks, tutorial talks, special sessions, industrial tracks, demonstrations and oral and poster presentations of refereed papers.Lecture Notes in Computer Science,1611-3349 ;15509Artificial intelligenceArtificial IntelligenceArtificial intelligence.Artificial Intelligence.006.3Nicosia Giuseppe241374Ojha Varun1726448Giesselbach Sven1736135Pardalos M. Panos1789844Umeton Renato1726451MiAaPQMiAaPQMiAaPQ996647969703316Machine Learning, Optimization, and Data Science4325960UNISA