Computer science Books
Springer International Publishing ManyValued Semantics and Modal Logics Essays in
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£98.99
Springer Spektrum Einführung in die Bioinformatik in der
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£34.19
Springer Text Speech and Dialogue
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£44.99
Springer Text Speech and Dialogue
Book Synopsis.- Speech..- Retrieval Augmented Spoken Language Generation for Transport Domain..- Adapting Audiovisual Speech Synthesis to Estonian..- Dysphonia Diagnosis Using Self-Supervised Speech Models in Mono- and Cross-Lingual Settings..- Sentences vs Phrases in Neural Speech Synthesis..- Zero-Shot vs. Few-Shot Multi-Speaker TTS Using Pre-trained Czech SpeechT5 Model..- Deep Speaker Embeddings for Speaker Verification of Children..- Improved Alignment for Score Combination of RNN-T and CTC Decoder for Online Decoding..- Attention to Phonetics: A Visually Informed Explanation of Speech Transformers..- Effects of Training Strategies and the Amount of Speech Data on the Quality of Speech Synthesis..- Stream-Based Active Learning for Speech Emotion Recognition via Hybrid Data Selection and Continuous Learning..- Data Alignment and Duration Modelling in VITS..- Multiword Expressions Resources for Italian: Presenting a Manually Ann
£53.99
Springer Emerging AI Applications in Earth Sciences
Book SynopsisChapter 1 Introduction to AI and IoT in the field of Earth Sciences.- Chapter 2. Growing Beyond the Earth: The Potential of Extra-Terrestrial Agriculture from Earth to Space.- Chapter 3. A Spatiotemporal Urban Growth Assessment in Bhopal, India from 1992 To 2042 using Machine Learning Algorithms.- Chapter 4. Emerging Areas and Applications in the Field of Earth Sciences.- Chapter 5. Integrating Deep Learning and IoT for Enhanced Monitoring and Sustainable Mining Practices.- Chapter 6. AI-Driven Insights into Fault Movements and Earthquake Dynamics.- Chapter 7. Harnessing Ai for Seismic Hazard Detection and Prediction: Innovations and Challenges.- Chapter 8. AI Techniques for Remote Monitoring.- Chapter 9. Role of AI in Estimating Potential Aftershocks During Earthquake.- Chapter 10. Advancements in Ozone Monitoring: Leveraging AI and ML for Environmental Protection.- Chapter 11. Quantum Computing in the Field of Earth Sciences.- Chapter 12. Machine Learning Approaches for Yield Prediction and Crop Management Optimization: A SLR.- Chapter 13. Resource Allocation in agriculture and Water Management fields.- Chapter 14. Optimising Crop Yields with Machine learning: Techniques and Applications.- Chapter 15. AI Trends Concerning Patterns, Anomalies, and Correlations for Predicting Earthquake Patterns.- Chapter 16. Future Trends and Challenges of AI And IoT for Earth Sciences.
£161.99
Springer Computational Complexity and Local Algorithms
Book Synopsis-. On defining PPT-search problems.- -. Multi-pseudodeterministic algorithms.- On counting t-cliques Mod 2.- On coarse and fine approximate counting of t-cliques.- On the complexity of enumerating ordered sets.- On the Cook-Mertz Tree Evaluation procedure.- Solving Tree Evaluation in o(log n · log log n) space.- On parallel repetitions of interactive proof systems.- On locally-characterized expander graphs (a survey).- On the Locally Testable Code of Dinur et al. (2021).- On the lower bound on the length of relaxed Locally Decodable Codes.- On the relaxed LDC of BGHSV: A survey that corrects the record.- On the complexity of estimating the Effective Support Size.- Robust Self-Ordering versus Local Self-Ordering.- On Testing Hamiltonicity in the Bounded Degree Graph Model.- Testing Isomorphism in the Bounded-Degree Graph Model.- On Testing Isomorphism to a fixed graph in the Bounded-Degree Graph Model.- On Testing Asymmetry in the Bounded Degree Graph Model.- On the query complexity of testing local graph properties in the Bounded-Degree Graph Model.- Testing in the bounded-degree graph model with degree bound two.- On properties that are non-trivial to test.- One-Sided Error Testing of Monomials and Affine Subspaces.- On testing group properties.
£58.49
Springer Research in Computational Molecular Biology
Book SynopsisOrientation-Aware Graph Neural Networks for Protein Structure Representation Learning.- Active Learning for Protein Structure Prediction.- Sequence-based TCR-Peptide Representations Using Cross-Epitope Contrastive Fine-tuning of Protein Language Models.- DualGOFiller: A Dual-Channel Graph Neural Network with Contrastive Learning for Enhancing Function Prediction in Partially Annotated Proteins.- Detecting antimicrobial resistance through MALDI-TOF mass spectrometry with statistical guarantees using conformal prediction.- Hierarchical Spatio-Temporal State-Space Modeling for fMRI Analysis.- A Phylogenetic Approach to Genomic Language Modeling.- Dynamic Programming Algorithms for Fast and Accurate Cell Lineage Tree Reconstruction from CRISPR-based Lineage Tracing Data.- Old dog, new tricks: Exact seeding strategy improves RNA design performances.- Scalable and Interpretable Identification of Minimal Undesignable RNA Structure Motifs with Rotational Invariance.- An Exact and Fast SAT Formulation for the DCJ Distance.- Improved pangenomic classification accuracy with chain statistics.- Dynamic μ-PBWT: Dynamic Run-length Compressed PBWT for Biobank Scale Data.- Prokrustean Graph: A substring index for rapid k-mer size analysis.- Rag2Mol: Structure-based drug design based on Retrieval Augmented Generation.- Rewiring protein sequence and structure generative models to enhance protein stability prediction.- Learning a CoNCISE language for small molecule binding and function.- An adversarial scheme for integrating multi-modal data on protein function.- Decoding the Functional Interactome of Non-Model Organisms with PHILHARMONIC.- The tree labeling polytope: a unified approach to ancestral reconstruction problems.- ScisTree2: An Improved Method for Large-scale Inference of Cell Lineage Trees and Genotype Calling from Noisy Single Cell Data.- OMKar: optical map based automated karyotyping of genomes to identify constitutional disorders.- TarDis: Achieving Robust and Structured Disentanglement of Multiple Covariates.- devider: long-read reconstruction of many diverse haplotypes.- Pharming: Joint Clonal Tree Reconstruction of SNV and CNA Evolution from Single-cell DNA Sequencing of Tumors.- GEM-Finder: dissecting GWAS variants via long-range interacting cis-regulatory elements with differentiation-specific genes.- Learning multi-cellular representations of single-cell transcriptomics data enables characterization of patient-level disease states.- cfDecon: Accurate and interpretable methylation based cell type deconvolution for cell-free DNA.- Inferring cell differentiation maps from lineage tracing data.- Alignment-free estimation of read to genome distances and its applications.- ML-MAGES: A machine learning framework for multivariate genetic association analyses with genes and effect size shrinkage.- TX-Phase: Secure Phasing of Private Genomes in a Trusted Execution Environment.- Hyper-k-mers: efficient streaming k-mers representation.- Characterizing the Solution Space of Migration Histories of Metastatic Cancers with MACH2.- Causal Disentanglement of Treatment Effects in Single-cell RNA Sequencing through Counterfactual Inference.- Integration and querying of multimodal single-cell data with PoE-VAE.- ralphi: a deep reinforcement learning framework for haplotype assembly.- GeneCover: A Combinatorial Approach for Label-free Marker Gene Selection.- Joint imputation and deconvolution of gene expression across spatial transcriptomics platforms.- ScatTR: Estimating the Size of Long Tandem Repeat Expansions from Short-Reads.- Learning Latent Trajectories in Developmental Time Series with Hidden-Markov Optimal Transport.- Unified integration of spatial transcriptomics across platforms.- Tree reconstruction guarantees from CRISPR-Cas9 lineage tracing data using Neighbor-Joining.- mcRigor: a statistical method to enhance the rigor of metacell partitioning in single-cell data analysis.- TissueMosaic enables cross-sample differential analysis of spatial transcriptomics datasets through self-supervised representation learning.- Accurate Detection of Tandem Repeats from Error-Prone Sequences with EquiRep.- ALPINE: an interpretable approach for decoding phenotypes from multi-condition sequencing data.- Synthetic control removes spurious discoveries from double dipping in single-cell and spatial transcriptomics data analyses.- Integer programming framework for pangenome-based genome inference.- A Partition Function Algorithm to Evaluate Inferred Subclonal Structures in Single-Cell Sequencing Data.- Untying Rates of Gene Gain and Loss Leads to a New Phylogenetic Approach.- Learning maximally spanning representations improves protein function annotation.- Optimal marker genes for c-separated cell types.- Bayesian Aggregation of Multiple Annotations Enhances Rare Variant Association Testing.- Steamboat: Attention-Based Multiscale Delineation of Cellular Interactions in Tissues.
£58.49
Springer Computational Intelligence Methods for
Book Synopsis.- A Network Approach to Aquatic Food Web Dynamics..- Leveraging Diffuser Data Augmentation to enhance ViT-based performance on Dermatoscopic Melanoma Images Classification..- Thyroid Nodule Diagnosis Using a New Supervised Autoencoder Neural net work with multi-categorical medical data..- Can smoothing methods recognize the patterns of the hazard function in complex clinical scenarios? A simulation study using discrete-time survival models..- Nested Named Entity Recognition in Chinese Electronic Medical Records..- Transformers for Interpretable Classification of Histopathological Images..- Breast Cancer Malignancy Prediction Through Explainable Models based on a Multimodal Signature of Features..- Exploring the Conformational Odorant Space in the Olfactory Re-ceptor Binding Region..- Synergy between mechanistic modelling and Ensemble Feature Selection ap proaches to explore multiscale biological Heterogeneity..- Homophily of large weighted networks in a data streaming setting..- Living along COVID-19: assessing contention policies through Agent-Based Models..- Stochastic modeling and dosage optimization of a cancer vaccine exploiting the EpiMod Framework..- Extension of the GreatMod modeling framework to simulate non-Markovian processes with general-distributed events..- Identifying Damage-Related Features in scRNA-seq Data..- A benchmark study of gene fusion prioritization tools..- Improving the reliability of tree-based feature importance via consensus signals..- Interpretable Machine Learning for Automated Cellular Population Analysis in Flow Cytometry..- Pre-trained Models Based on Primary Sequence to Classify Antibody Bind ing to Protein and Non-Protein Targets with 80% Accuracy..- Inferring breast cancer subtype associations using an original omics integra tion based on Non-negative Matrix Tri-Factorization..- Screening the bioactivity of the P450 enzyme by spiking neural networks..- Enhancing functional interpretability in gene expression analysis through biologically-guided feature selection..- Extraction of Attributes from Electrodermal Activity Signals Applying Time Series Fuzzy Granulation for Classification of Academic Stress Perception in Different Scenarios..- Transfer Learning and AutoML as a Support for the Pneumonia Diagnosis using Chest X-ray scan.
£80.99
Springer Designing for Tomorrow Innovation and Equity in
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£161.99
Peter Lang AG Bienvenue au 21 e siècle: Évaluation des
Book SynopsisChaque jour, chaque semaine, chaque année, des données reliées à l'évaluation des apprentissages sont récoltées par des enseignants, des écoles et des ministères. Traditionnellement, ces données ont été récoltées avec un support dit papier-crayon, mais cette technologie est en voie d'être supplantée par la technologie informatique et le support écran-clavier. Il s'agit d'un constat inéluctable et ce nouveau support ouvre la porte à une exploitation des données qu'il était difficile d'imaginer il y a dix ans à peine, avec un potentiel de transformation radicale du processus d'évaluation des apprentissages et des apprentissages eux-mêmes. Dans la lignée de leurs ouvrages précédents sur le même thème, les auteurs exposent ici différentes facettes propres à l'évaluation des apprentissages à l'aide des technologies de l'information et de la communication. Ce thème est abordé en quatre parties : la complexité de nouvelles approches pour récolter des données pour l'évaluation, les dispositifs numériques en ligne, les outils pour l'analyse de séquences filmées et enfin la modélisation de données pour l'évaluation.
£64.53
Peter Lang AG, Internationaler Verlag der Wissenschaften Schulentwicklung: Bildungspolitische
Book SynopsisDie hier durchgeführte Querschnittsstudie evaluiert erstmalig, ob Schulen sich erfolgreich eigenständig wie bildungspolitisch gefordert , in sogenannte problemlösende Organisationseinheiten transformieren können, um ihren Unterricht im Rahmen der Schulentwicklung kontinuierlich weiterzuentwickeln. Die Ergebnisse dieser Studie stellen hierbei vor allem die Nachhaltigkeit von Schulentwicklung in Frage, da weder die Lehrpersonen noch Schulleitungsmitglieder an den evaluierten Berufsfachschulen der Meinung waren, dass Schulentwicklung den Unterricht und die beruflichen Fähigkeiten der Einzellehrperson überhaupt beeinflusst. Begründet liegt dieses Ergebnis u.a. in der von den Schulen vorgenommenen Implementierungsstrategie. So wird das Lehrerkollegium allgemein zu wenig in Entscheidungsprozesse involviert und beispielsweise nur unzureichend über den Zielerreichungsgrad und Maßnahmen abgeschlossener Schulentwicklungsprojekte informiert.
£58.10
Peter Lang AG, Internationaler Verlag der Wissenschaften Learning second language pragmatics beyond
Book SynopsisThe volume Learning second language pragmatics beyond traditional contexts is a collection of studies dealing with the acquisition of second language pragmatic competence in different learning contexts. Such contexts brought together include technology-mediated contexts (e.g. computer-mediated communication, emails), emerging institutional settings in the European context (e.g. CLIL, English-medium instruction, the multilingual classroom), study abroad settings, and natural contexts (e.g. au-pairing, media contact). Altogether, the contributions attempt to move forward the field of second language pragmatics by accounting for learning settings that have gained importance in the current era of globalization and multiculturalism.Table of ContentsTechnology-mediated contexts – Emerging institutional settings in the European context – Study abroad contexts – Natural contexts
£54.86
Diaphanes AG Natures of Data – A Discussion between
Book SynopsisComputer-based technologies for the production and analysis of data have been an integral part of biological research since the 1990s at the latest. This not only applies to genomics and its offshoots but also to less conspicuous subsections such as ecology. But little consideration has been given to how this new technology has changed research practically. How and when do data become questionable? To what extent does necessary infrastructure influence the research process? What status is given to software and algorithms in the production and analysis of data? These questions are discussed by the biologists Philipp Fischer and Hans Hofmann, the philosopher Gabriele Gramelsberger, the historian of science and biology Hans-Jörg Rheinberger, the science theorist Christoph Hoffmann, and the artist Hannes Rickli. The conditions of experimentation in the digital sphere are examined in four chapters—“Data,” “Software,” “Infrastructure,” and “in silico”—in which the different perspectives of the discussion partners complement one another. Rather than confirming any particular point of view, Natures of Data deepens understanding of the contemporary basis of biological research.
£24.70
De Gruyter Computational Technologies: Advanced Topics
Book SynopsisThis book discusses questions of numerical solutions of applied problems on parallel computing systems. Nowadays, engineering and scientific computations are carried out on parallel computing systems, which provide parallel data processing on a few computing nodes. In the development of up-to-date applied software, this feature of computers must be taken into account for the maximum efficient usage of their resources. In constructing computational algorithms, we should separate relatively independent subproblems in order to solve them on a single computing node.
£40.95
De Gruyter A Course in Mathematical Cryptography
Book SynopsisCryptography has become essential as bank transactions, credit card infor-mation, contracts, and sensitive medical information are sent through inse-cure channels. This book is concerned with the mathematical, especially algebraic, aspects of cryptography. It grew out of many courses presented by the authors over the past twenty years at various universities and covers a wide range of topics in mathematical cryptography. It is primarily geared towards graduate students and advanced undergraduates in mathematics and computer science, but may also be of interest to researchers in the area. Besides the classical methods of symmetric and private key encryption, the book treats the mathematics of cryptographic protocols and several unique topics such as Group-Based Cryptography Gröbner Basis Methods in Cryptography Lattice-Based Cryptography
£43.22
De Gruyter Actuarial Data Science: Maschinelles Lernen in
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£47.02
Walter de Gruyter Erp-Systeme: Architektur, Management Und
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£44.55
De Gruyter Fitness Landscape, Red Queen, Evolutionary
Book SynopsisThis two-volume work focuses on the mathematical aspects of Darwinian evolution starting from the basic model of stochastic evolution of a single isolated locus in the presence of mutation to the multi–locus models of sexual and asexual populations. Volume 2 discusses the inference of fi tness landscape from DNA sequence data, discovery of the evolutionary roles of enygmatic traits, co-evolution of adversarial species, and various applications to virus evolution.
£194.69
De Gruyter Data Science: Time Complexity, Inferential
Book SynopsisThe amount of new information is constantly increasing, faster than our ability to fully interpret and utilize it to improve human experiences. Addressing this asymmetry requires novel and revolutionary scientific methods and effective human and artificial intelligence interfaces. By lifting the concept of time from a positive real number to a 2D complex time (kime), this book uncovers a connection between artificial intelligence (AI), data science, and quantum mechanics. It proposes a new mathematical foundation for data science based on raising the 4D spacetime to a higher dimension where longitudinal data (e.g., time-series) are represented as manifolds (e.g., kime-surfaces). This new framework enables the development of innovative data science analytical methods for model-based and model-free scientific inference, derived computed phenotyping, and statistical forecasting. The book provides a transdisciplinary bridge and a pragmatic mechanism to translate quantum mechanical principles, such as particles and wavefunctions, into data science concepts, such as datum and inference-functions. It includes many open mathematical problems that still need to be solved, technological challenges that need to be tackled, and computational statistics algorithms that have to be fully developed and validated. Spacekime analytics provide mechanisms to effectively handle, process, and interpret large, heterogeneous, and continuously-tracked digital information from multiple sources. The authors propose computational methods, probability model-based techniques, and analytical strategies to estimate, approximate, or simulate the complex time phases (kime directions). This allows transforming time-varying data, such as time-series observations, into higher-dimensional manifolds representing complex-valued and kime-indexed surfaces (kime-surfaces). The book includes many illustrations of model-based and model-free spacekime analytic techniques applied to economic forecasting, identification of functional brain activation, and high-dimensional cohort phenotyping. Specific case-study examples include unsupervised clustering using the Michigan Consumer Sentiment Index (MCSI), model-based inference using functional magnetic resonance imaging (fMRI) data, and model-free inference using the UK Biobank data archive. The material includes mathematical, inferential, computational, and philosophical topics such as Heisenberg uncertainty principle and alternative approaches to large sample theory, where a few spacetime observations can be amplified by a series of derived, estimated, or simulated kime-phases. The authors extend Newton-Leibniz calculus of integration and differentiation to the spacekime manifold and discuss possible solutions to some of the "problems of time". The coverage also includes 5D spacekime formulations of classical 4D spacetime mathematical equations describing natural laws of physics, as well as, statistical articulation of spacekime analytics in a Bayesian inference framework. The steady increase of the volume and complexity of observed and recorded digital information drives the urgent need to develop novel data analytical strategies. Spacekime analytics represents one new data-analytic approach, which provides a mechanism to understand compound phenomena that are observed as multiplex longitudinal processes and computationally tracked by proxy measures. This book may be of interest to academic scholars, graduate students, postdoctoral fellows, artificial intelligence and machine learning engineers, biostatisticians, econometricians, and data analysts. Some of the material may also resonate with philosophers, futurists, astrophysicists, space industry technicians, biomedical researchers, health practitioners, and the general public.
£75.05
Walter de Gruyter Erp Und Scm: Enterprise Resource Planning Und
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£62.10
Walter de Gruyter Einführung in Die Wirtschaftsinformatik: Ein
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£28.02
De Gruyter Linguistische Methodenreflexion im Aufbruch
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£95.48
de Gruyter Discrete Mathematics
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£39.20
de Gruyter Algorithmische Graphentheorie
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£53.24
de Gruyter Data Mining
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£59.46
de Gruyter ComputerAided Drug Design
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£54.40
De Gruyter InformationOriented Logic
£62.80
de Gruyter Products of Automata
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£134.09
de Gruyter Siegfried Matthies Galina W. Vinel Kurt Helming
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£117.50
de Gruyter Siegfried Matthies Galina W. Vinel Kurt Helming
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£117.50
de Gruyter Kommunikationsprotokolle
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£134.09
de Gruyter Compiler Und Interpreter Für Höhere
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£134.09
de Gruyter Digitalgrafik
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£134.09
de Gruyter Visuelle Sensoren
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£134.09
de Gruyter Lokale Netze
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£134.09
de Gruyter Automaten Und Funktoren
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£134.09
de Gruyter Vom Wesen Der Information Der
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£134.09
de Gruyter Ökonomische Kybernetik Und Anwendung in Der
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£134.09
de Gruyter Automatengraphen
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£134.09
de Gruyter Representation and Processing of Natural Language
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£117.50
de Gruyter Theoretische Grundlagen Der Digitalen
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£134.09
de Gruyter Information II. Ergänzungsband Zur Vielfalt Und
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£134.09
de Gruyter The Concept of Fuzziness in Automata and Language
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£134.09
de Gruyter Completeness Problems in the Structural Theory of
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£111.62
de Gruyter Nonlinear Timediscrete Systems
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£111.62
de Gruyter Abstrakte Rechnermodelle
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£134.09
De Gruyter Dynamical Networks
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£111.62
de Gruyter Nichtmetrische Klassifizierung Von Informationen
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£134.09
