Algorithms and data structures Books

Book SynopsisThis book constitutes the refereed proceedings of the 21st International Conference on Software Engineering and Formal Methods, SEFM 2023, held in Eindhoven, The Netherlands, during November 6-10, 2023. The 18 regular papers presented in this book, together with 1 invited paper and 1 tool paper, were carefully reviewed and selected from 41 submissions. The SEFM conference series aims to bring together researchers and practitioners from academia, industry and government, to advance the state of the art in formal methods, to facilitate their uptake in the software industry, and to encourage their integration within practical software engineering methods and tools.Table of ContentsRefinements for Open Automata.- The Cubicle Fuzzy Loop : A Fuzzing-Based Extension for the Cubicle Model Checker.- Guiding Symbolic Execution with A-star.- Robustness Testing of Software Verifiers.- Decoupled Fitness Criteria for Reactive Systems.- Capturing Smart Contract Design with DCR Graphs.- An Active Learning Approach to Synthesizing Program Contracts.- Ranged Program Analysis via Instrumentation.- Attack time analysis in dynamic attack trees via integer linear programming.- SSCalc A Calculus for Solidity Smart Contracts.- ATM: a Logic for Quantitative Security Properties on Attack Trees.- Refactoring of Multi-Instance BPMN Processes with Time and Resources.- Verified Scalable Parallel Computing with Why3.- Exact and Efficient Bayesian Inference for Privacy Risk Quantification.- A Formalization of Heisenbugs and Their Causes.- Verifying Read-Copy Update under RC11.- QNNRepair: Quantized Neural Network Repair.- Timeout Prediction for Software Analyses.- PART Tool Papers.- PMC-VIS: An Interactive Visualization Tool for Probabilistic Model Checking.

Read more less

Book SynopsisThis book constitutes the refereed proceedings of the 42nd International Conference on Conceptual Modeling, ER 2023, held in Lisbon, Portugal, during November 6-9, 2023. The 21 full papers were carefully reviewed and selected from 121 submissions. Additionally, the book contains 4 keynote speeches and 3 tutorials, and one invited paper corresponding to one of the keynote speeches. The papers cover a broad spectrum of classical and modern topics on conceptual modeling, including research and practice in the theories of concepts and ontologies, techniques for transforming conceptual models into effective implementations, and methods and tools for developing and communicating conceptual models.Table of Contents​Invited Paper.- Stochastic LLMs do not Understand Language: Towards Symbolic, Explainable and Ontologically Based LLMs.- The Conceptual Modeling Task.- A Survey of Ethical Reasoning Methods, their Metamodels, and a Theory on their Application to Conceptual Modelling.- Use of Competency Questions in Ontology Engineering: a Survey.- How Inclusive is Conceptual Modeling? A Systematic Review of Literature and Tools for Disability-aware Conceptual Modeling.- The Meta Level.- A Terminological and Semiotic Review of the Digital Object Concept.- The Ontology for Conceptual Characterization of Ontologies.- ProMoTe: A Data Product Model Template for Industry.- Model-Based Analysis and Implementation.- Using a Conceptual Model in Plug-and-play SQL.- Sanity-Checking Multiple Levels of Classification – A Formal Approach with a ConceptBase Implementation.- A Safari for Deviating GoF Pattern Definitions and Examples on the Web.- Process Mining and Abstraction.- Object-Centric Alignments.- Transforming Event Knowledge Graph to Object-Centric Event Logs: A Comparative Study for Multi-dimensional Process Analysis.- Ontology-Based Abstraction of Bot Models in Robotic Process Automation.- Modeling Events and Processes.- Shards of Knowledge – Modeling Attributions for Event-Centric Knowledge Graphs.- A Characterisation of Ambiguity in BPM.- Dealing with the evolution of event-based choreographies of BPMN fragments: definition and proof of concept.- Conceptual Modeling in Context.- Safety Analysis of Human Robot Collaborations with GRL Goal Models.- A Domain-Specific Visual Modeling Language for Augmented Reality Applications Using WebXR.- An Ontology for Context Modeling in Smart Spaces.- Applications of Conceptual Modeling.- A Reference Meta-Model to Understand DNA Variant Interpretation Guidelines.- A Conceptual Modeling Approach for Risk Assessment and Mitigation in Collision-free UAV Routing for Beyond-the-Visual-Line-of-Sight Flights.- QuantumShare: Towards An Ontology for Bridging the Quantum Divide.

Read more less

Book SynopsisThe two-volume set LNCS 14461 and LNCS 14462 constitutes the refereed proceedings of the 17th International Conference on Combinatorial Optimization and Applications, COCOA 2023, held in Hawaii, HI, USA, during December 15–17, 2023. The 73 full papers included in the proceedings were carefully reviewed and selected from 117 submissions. They were organized in topical sections as follows: Part I: Optimization in graphs; scheduling; set-related optimization; applied optimization and algorithm; Graph planer and others;Part II: Modeling and algorithms; complexity and approximation; combinatorics and computing; optimization and algorithms; extreme graph and others; machine learning, blockchain and others.Table of ContentsModeling and Algorithms.- ​Differentiable Discrete Optimization using Dataless Neural Networks.- When Advertising meets Assortment Planning: Joint Advertising and Assortment Optimization under Multinomial Logit Model.- Twin-treewidth: A single-exponential logic-based approach.- Highway Preferential Attachment Models for Geographic Routing.- Complexity and Approximation.- Restricted Holant Dichotomy on Domains 3 and 4.- Earliest Deadline First is a $2$-approximation for DARP with Time Windows.- Improved approximation for broadcasting in k-Path Graphs.- The fine-grained complexity of approximately counting proper connected colorings (extended abstract).- Combinatorics and Computing.- Strong edge coloring of subquartic graphs.- Two multicolor Ramsey numbers involving bipartite graphs.- Mechanism Design for Time-Varying Value Tasks in High-Load Edge Computing Markets.- Computing random r-orthogonal Latin squares.- Optimization and Algorithms.- A Two-stage Seeds Algorithm for Competitive Influence Maximization considering User Demand.- Practical Attribute-Based Multi-Keyword Search Scheme with Sensitive Information Hiding for Cloud Storage Systems.- Testing Higher-order Clusterability on graphs.- The $2$-mixed-center color spanning problem.- A Dynamic Parameter Adaptive Path Planning Algorithm.- On the Mating Between a Polygonal Curve and a Convex Polygon.- A Faster Parameterized Algorithm for Bipartite 1-Sided Vertex Explosion.- Multi-Winner Approval Voting with Grouped Voters.- EFX Allocation to Chores Over Small Graph.- Extreme Graph and Others.- Zero-visibility Cops and Robber game on Cage graph.- Online Facility Assignment for General Layout of Servers on a Line.- Guarding Precise and Imprecise Polyhedral Terrains with Segments.- The Bag-Based Search: A meta-algorithm to construct tractable logical circuits for graphs based on tree decomposition.- On Problems Related to Absent Subsequences.- Some Combinatorial Algorithms on the Dominating Number of Anti-Rank k Hypergraphs.- Parameterized and exact-exponential algorithms for the read-once integer refutation problem in UTVPI constraints.- Critical $(P_5,dart)$-Free Graphs.- Graph Clustering through Users' Properties and Social Influence.- Machine Learning, Blockchain and Others.- Incorporating Neural Point Process-based Temporal Feature for Rumor Detection.- Improving Contraction Hierarchies by Combining with All-Pairs Shortest Paths Problem Algorithms.- Information Theory of Blockchain Systems.- Machine Learning with Low Resource Data from Psychiatric Clinics.- Single Image Dehazing Based on Dynamic Convolution and Transformer.- Reinforcement Learning for Combating Cyberbullying in Online Social Networks.

Read more less

Book SynopsisThis book constitutes the refereed proceedings of the 8th International Conference on Advances in Computing and Data Sciences, ICACDS 2024, held in Velizy, France, during May 910, 2024. The 28 full papers present here, were carefully reviewed and selected from 174 submissions.

Read more less

Book SynopsisThis is a graduate textbook of advanced tutorials on the theory of cryptography and computational complexity. In particular, the chapters explain aspects of garbled circuits, public-key cryptography, pseudorandom functions, one-way functions, homomorphic encryption, the simulation proof technique, and the complexity of differential privacy. Most chapters progress methodically through motivations, foundations, definitions, major results, issues surrounding feasibility, surveys of recent developments, and suggestions for further study.This book honors Professor Oded Goldreich, a pioneering scientist, educator, and mentor. Oded was instrumental in laying down the foundations of cryptography, and he inspired the contributing authors, Benny Applebaum, Boaz Barak, Andrej Bogdanov, Iftach Haitner, Shai Halevi, Yehuda Lindell, Alon Rosen, and Salil Vadhan, themselves leading researchers on the theory of cryptography and computational complexity. The book is appropriate for graduate tutorials and seminars, and for self-study by experienced researchers, assuming prior knowledge of the theory of cryptography.Table of ContentsGarbled Circuits as Randomized Encodings of Functions: A Primer.- The Complexity of Public-Key Cryptography.- Pseudorandom Functions: Three Decades Later.- The Many Entropies in One-Way Functions.- Homomorphic Encryption.- How to Simulate It: A Tutorial on the Simulation Proof Technique.- The Complexity of Differential Privacy.

Read more less

Book SynopsisCovering all the essential components of Unix/Linux, including process management, concurrent programming, timer and time service, file systems and network programming, this textbook emphasizes programming practice in the Unix/Linux environment. Systems Programming in Unix/Linux is intended as a textbook for systems programming courses in technically-oriented Computer Science/Engineering curricula that emphasize both theory and programming practice. The book contains many detailed working example programs with complete source code. It is also suitable for self-study by advanced programmers and computer enthusiasts.Systems programming is an indispensable part of Computer Science/Engineering education. After taking an introductory programming course, this book is meant to further knowledge by detailing how dynamic data structures are used in practice, using programming exercises and programming projects on such topics as C structures, pointers, link lists and trees.This book provides a wide range of knowledge about computer systemsoftware and advanced programming skills, allowing readers to interface with operatingsystem kernel, make efficient use of system resources and develop application software.It also prepares readers with the needed background to pursue advanced studies inComputer Science/Engineering, such as operating systems, embedded systems, databasesystems, data mining, artificial intelligence, computer networks, network security,distributed and parallel computing.Table of ContentsChapter 1. Introduction to Unix/Linux.- Chapter 2. Programming Background.- Chapter 3 Process Management in Unix/Linux.- Chapter 4 Concurrent Programming.- Chapter 5 Timers and Time Service.- Chapter 6 Signals and Signal Processing.- Chapter 7 File Operations.- Chapter 8 System Calls for File Operations.- Chapter 9 Library I/O FunctionsChapter 10 Sh Programming.- Chapter 11 EXT2 File System.- Chapter 12. Block Device I/O and Buffer Management.- Chapter 13 TCP/IP and Network Programming.

Read more less

Book SynopsisDie Komplexitätstheorie untersucht den algorithmischen Aufwand zur Lösung von Problemen mit Hilfe einer Maschine. Dabei werden Rechnermodelle wie Turing-Maschinen oder Registermaschinen verwendet, um von speziellen Architektur- und Implementationsdetails unabhängige Ergebnisse zu gewinnen.Table of Contents1 Das TM-Modell.- 1.0 Vorbemerkungen.- 1.0.1 Mengen.- 1.0.2 Graphen.- 1.0.3 Strings, Sprachen.- 1.1 Turing-Maschinen.- 1.1.1 Das allgemeine Modell.- 1.1.2 Verschiedene Speichertypen.- 1.1.3 Beispiele für die Arbeitsweise von TM.- 1.1.4 Berechenbarkeit.- 1.1.5 Nichtdeterministische Berechnungen.- 1.2 Das Rechnen mit TM.- 1.2.1 Elementare Techniken.- 1.2.2 Simulation, Band- und Kopf-Reduktion.- 1.2.3 Universelle Maschinen.- 1.3 Mathematische Grundlagen.- 1.3.1 Notation.- 1.3.2 Asymptotisches Wachstum.- 1.3.3 Wachstumsordnungen.- 1.3.4 Rekursionsgleichungen.- 1.4 Die Komplexität von TM.- 1.4.1 Schranken, Maße und Konstruierbarkeit.- 1.4.2 Komplexitätsklassen.- 1.4.3 Diagonalisierung.- 1.4.4 Bandkompression.- 1.4.5 Lineare Beschleunigung.- 1.5 Übungsaufgaben.- 1.6 Bemerkungen und Literaturhinweise.- 2 Weitere Maschinenmodelle.- 2.1 Registermaschinen.- 2.1.1 Das RAM-Modell.- 2.1.2 Komplexitätsmaße für RAMs.- 2.1.3 Simulation von RAMs durch TM.- 2.1.4 Simulation von TM durch RAMs.- 2.2 Schaltkreis-Familien.- 2.2.1 Boolesche Funktionen und Schaltkreise.- 2.2.2 Schaltkreiskomplexität.- 2.2.3 Uniformität.- 2.2.4 Simulation von Schaltkreisfamilien durch TM.- 2.2.5 Simulation von TM durch Schaltkreisfamilien.- 2.2.6 Universelle Schaltkreise.- 2.3 Arithmetische Modelle, Entscheidungsgraphen.- 2.3.1 Arithmetische RAMs und Schaltkreise.- 2.3.2 Entscheidungsbaum-Modelle.- 2.4 Übungsaufgaben.- 2.5 Bemerkungen und Literaturhinweise.- 3 Hierarchie-Sätze.- 3.1 Untere Schranken und Komplexitätslücken.- 3.1.1 Logarithmische Platzschranke.- 3.1.2 Quadratische Zeitschranke für 1-Band Maschinen.- 3.1.3 Komplexitätslücke bei zeitbeschränkten 1-Band TM.- 3.1.4 Komplexitätslücke bei kleinen Platzschranken.- 3.2 Deterministische Hierarchien.- 3.2.1 Allgemeiner Hierarchiesatz.- 3.2.2 Zeithierarchien.- 3.2.3 Platzhierarchien.- 3.3 Translation.- 3.4 Nichtdeterministische Hierarchien.- 3.4.1 Komplementabschluß von nichtdeterministischem Platz.- 3.4.2 Nichtdeterministischer Platzhierarchiesatz.- 3.4.3 Nichtdeterministischer Zeithierarchiesatz.- 3.5 Das Komplexitätsmaß Reversal.- 3.5.1 Reversalbeschränkte TM.- 3.5.2 Vergleich von Time und Reversal.- 3.5.3 Vergleich von Space und Reversal.- 3.5.4 Bandreduktion und Reversal für NTM.- 3.6 Abstrakte Komplexitätstheorie.- 3.6.1 Allgemeines Gap-Theorem.- 3.6.2 Speedup-Theorem.- 3.6.3 Union-Theorem.- 3.6.4 Abstrakte Komplexitätsmaße.- 3.7 Übungsaufgaben.- 3.8 Bemerkungen und Literaturhinweise.- 4 Vergleich von Speicherstrukturen.- 4.1 Ein allgemeines Speichermodell.- 4.1.1 On-line versus off-line.- 4.1.2 Konstruierbare Speicher.- 4.1.3 Lineare Bandsimulation konstruierbarer Speicher.- 4.2 1-dimensionale Speicher.- 4.2.1 Bandreduktion für NTM.- 4.2.2 Simulation von Mehrkopf-Maschinen.- 4.2.3 TM mit separatem Einweg-Eingabeband.- 4.2.4 1 versus 2 Bänder bei Zweiweg-Eingabe.- 4.3 Untere Schranken für Speicherzugriffe.- 4.3.1 Kolmogorov-Komplexität von Strings.- 4.3.2 Der Einfluß des Radius.- 4.4 Obere Schranken für Speicherzugriffe.- 4.4.1 Einbettung von Graphen.- 4.4.2 Kompaktifizierung.- 4.4.3 Schnelle Simulationen.- 4.5 Übungsaufgaben.- 4.6 Bemerkungen und Literaturhinweise.- 5 Zeit- versus Platzkomplexität.- 5.1 Time-Space-Relationen für 1-Band TM.- 5.1.1 Simulation platzbeschränkter 1-Band DTM.- 5.1.2 Simulation platzbeschränkter 1-Band NTM.- 5.1.3 Mehrdimensionale 1-Band TM.- 5.2 Das Pebble-Game.- 5.2.1 Berechnungsgraphen.- 5.2.2 Superkonzentratoren.- 5.2.3 Schichtungen von Graphen.- 5.3 Platzeffiziente Simulation von TM und RAMs.- 5.3.1 Lineare Speicher.- 5.3.2 Nichtlineare Speicher.- 5.3.3 Auxiliary Pushdown TM.- 5.4 Simultane Ressource-Schranken.- 5.4.1 Schaltkreisweite.- 5.4.2 Vergleich der Ressourcen von TM und Schaltkreisen.- 5.5 Übungsaufgaben.- 5.6 Bemerkungen und Literaturhinweise.- 6 Sequentielle Komplexitätsklassen.- 6.1 Einführung.- 6.1.1 Notation.- 6.1.2 Zeit-Platz-Hierarchie.- 6.1.3 Reduzierbarkeit, Vollständigkeit.- 6.2 Die Klassen von L bis P.- 6.2.1 Labyrinth-Probleme zur Charakterisierung von L und NL.- 6.2.2 P -vollständige Probleme.- 6.3 NP-vollständige Probleme.- 6.3.1 Das Erfüllbarkeitsproblem.- 6.3.2 Selbstreduzierbarkeit.- 6.3.3 Erfüllbarkeit für 3-CNF.- 6.3.4 Graphenprobleme: Cliquen, Kreise und Überdeckungen.- 6.3.5 Das Färbungsproblem für Graphen.- 6.3.6 Diskrete Optimierung.- 6.3.7 NP -Vollständigkeit im strengen Sinne.- 6.3.8 Obere Schranken und Parameterkomplexität.- 6.4 Von NP bis PSP ACE.- 6.4.1 Die Struktur von NP.- 6.4.2 Die Relation zwischen NP und co-NP.- 6.4.3 UP, Einweg-Funktionen und Kryptologie.- 6.4.4 PSP ACE -Vollständigkeit.- 6.5 Linguistische Klassifikationen.- 6.5.1 Formale Grammatiken.- 6.5.2 Die Chomsky-Hierarchie.- 6.5.3 Kontextfreie Sprachen und Log CFL.- 6.5.4 Reguläre Ausdrücke.- 6.6 Übungsaufgaben.- 6.7 Bemerkungen und Literaturhinweise.- Stichwortverzeichnis.- Symbolverzeichnis.- Zeitschriftenverzeichnis.- Konferenzverzeichnis.- Verzeichnis von Fachorganisationen.

Read more less

Book SynopsisDieser Band behandelt numerische Algorithmen, die in der traditionellen Schulmathematik eine wichtige Rolle spielen. Ziel ist es dabei, nicht nur die einzelnen Algorithmen kennenzulernen, sondern zugleich auch die Methodik, die zur Elementarisierung mathematischer Probleme und zur Lösung in endlich vielen Schritten führt. Darüber hinaus werden nichtnumerische Such-, Sortier- und Simulationsalgorithmen dargestellt, die sich in der Schule in spielerischer und kreativer Weise behandeln lassen. Für die konkreten Lösungen einer mathematischen Aufgabe ist immer ein Algorithmus erforderlich. Vom Euklidischen Algorithmus zur Ermittlung des größten gemeinsamen Teilers zweier natürlicher Zahlen bis zur Lösung linearer Gleichungssysteme mit dem Gaußschen Algorithmus sind Algorithmen unverzichtbar. Die zweite, durchgesehene und erweiterte Auflage dieses Hochschullehrbuches enthält zusätzliche Beispiele, Lösungen und Aufgaben.Table of Contents1 Einführung.- 1.1 Was ist ein Algorithmus?.- 1.2 Zielsetzung.- 1.3 Beispiel 1 Potenzierung.- 1.4 Beispiel 2 Russisches Roulette.- 1.5 Folgerungen und Ausblick.- 2 Numerische Algorithmen.- 2.1 Teilbarkeitslehre in N.- 2.1.1 Teilbarkeit und Teilermengen.- 2.1.2 Größter gemeinsamer Teiler und kleinstes gemeinsames Vielfaches.- 2.1.3 Primzahleigenschaft.- 2.1.4 Primzahltabelle von 2 bis n.- 2.1.5 Zerlegung einer natürlichen Zahl in Primfaktoren.- 2.2 Stellenwertsysteme in Q.- 2.2.1 Darstellung natürlicher Zahlen in Stellenwertsystemen.- 2.2.2 Darstellung rationaler Zahlen in Stellenwertsystemen.- 2.2.3 Teilbarkeit und Teilbarkeitskriterien.- 2.3 Iterationen in Q.- 2.3.1 Quadratwurzeliteration (Halbierungsverfahren).- 2.3.2 Nullstellenbestimmung.- 2.3.3 Nullstelle einer kubischen Gleichung.- 2.3.4 Quadratwurzelnäherung nach Newton-Heron.- 3 Nichtnumerische Algorithmen.- 3.1 Suchvorgänge.- 3.1.1 Suchen eines Elementes in einer geordneten Liste.- 3.1.2 Einordnen eines Elementes in eine geordnete Liste.- 3.1.3 Zweidimensionales Suchen (Kobold).- 3.1.4 Damen-Problem.- 3.2 Sortiervorgänge.- 3.2.1 Minimales Element einer Liste.- 3.2.2 Sortieren einer Liste von n Wörtern mit der Austauschmethode.- 3.2.3 Sortieren einer Liste von n Wörtern mit der Sprudelmethode.- 3.2.4 Sortieren einer Liste von n Wörtern mit Quicksort.- 3.2.5 Sortieren durch Mischen.- 3.2.6 Türme von HANOI.- 4 Anhang: Arbeiten mit Visual-BASIC.- 4.1 EXCEL-Tabelle und Programm-Modul(e).- 4.2 EXCEL-Tabelle mit variabler Ein- und Ausgabe.- Literaturhinweise.- Stichwortverzeichnis.

Read more less

Book SynopsisAt its core, information security deals with the secure and accurate transfer of information. While information security has long been important, it was, perhaps, brought more clearly into mainstream focus with the so-called “Y2K” issue. Te Y2K scare was the fear that c- puter networks and the systems that are controlled or operated by sofware would fail with the turn of the millennium, since their clocks could lose synchronization by not recognizing a number (instruction) with three zeros. A positive outcome of this scare was the creation of several Computer Emergency Response Teams (CERTs) around the world that now work - operatively to exchange expertise and information, and to coordinate in case major problems should arise in the modern IT environment. Te terrorist attacks of 11 September 2001 raised security concerns to a new level. Te - ternational community responded on at least two fronts; one front being the transfer of reliable information via secure networks and the other being the collection of information about - tential terrorists. As a sign of this new emphasis on security, since 2001, all major academic publishers have started technical journals focused on security, and every major communi- tions conference (for example, Globecom and ICC) has organized workshops and sessions on security issues. In addition, the IEEE has created a technical committee on Communication and Information Security. Te ?rst editor was intimately involved with security for the Athens Olympic Games of 2004.Trade ReviewAus den Rezensionen: “... Besonderes Augenmerk gilt dabei dem Wechselspiel zwischen Kommunikation und dem Bereich der Informationssicherheit. ... herausgegriffene Themen illustrieren die Relevanz des Buchs. … Verschiedene HIPs werden vorgestellt und verglichen Weitere Beitrage befassen sich mit Phishing Attacken bzw mit Authentifikationen mittels biometrischer Methoden. ... Die Beitrage sind theoretisch fundiert und oft praxisbezogen. … Das Buch eignet sich deshalb gut als Einstiegslektüre für Studierende oder für Informatiker, die sich nur am Rande für die Sicherheitsthematik interessieren. Für Experten ist das Buch eine wertvolle, vielseitige Inspirationsquelle.“ (in: Bulletin electrosuisse, 2/July/2010, Issue 7, S. 121)Table of ContentsPart A Fundamentals and Cryptography A Framework for System Security .- Public-Key Cryptography.- Elliptic Curve Cryptography.- Cryptographic Hash Functions.- Block Cipher Cryptanalysis.- Chaos-Based Information Security.- Bio-Cryptography.- Quantum Cryptography.- Part B Intrusion Detection and Access Control Intrusion Detection and Prevention Systems.- Intrusion Detection Systems.- Intranet Security via Firewalls.- Distributed Port Scan Detection.- Host-Based Anomaly Intrusion Detection.- Security in Relational Databases.- Anti-Bot Strategies Based on Human Interactive Proofs.- Access and Usage Control in GRID Systems.- Secure Human Identification.- Part C Networking Peer-to-Peer Botnets.- Security of Service Networks.- SCADA Security.- Mobile Ad-Hoc Network Routing.- Security Approach for Ad–Hoc Networks.- Phishing: Attacks and Countermeasures´.- Part D Optical Networking Chaos-Based Secure Optical Communications.- Chaos Applications in Optical Communications.- Part E Wireless Networking Security in Wireless Sensor Networks.- Secure routing in Wireless Sensor Networks.- Security Via Surveillance and Monitoring.- Security and QoS in Wireless Networks.- Part F Software Low-Level Software Security by Example.- Software Reverse Engineering.- Trusted Computing.- Security via Trusted Communications.- Viruses and Malware.- Designing a Secure Programming Language.- Part G Forensics and Legal Issues Fundamentals of Digital Forensic Evidence.- Multimedia Forensics for Detecting Forgeries.- Technological and Legal Aspects of CIS Subject Index

Read more less

Book SynopsisThis book constitutes the refereed proceedings of the 13th Algorithms and Data Structures Symposium, WADS 2013, held in London, ON, Canada, August 2013. The Algorithms and Data Structures Symposium - WADS (formerly "Workshop on Algorithms and Data Structures") is intended as a forum for researchers in the area of design and analysis of algorithms and data structures. The 44 revised full papers presented in this volume were carefully reviewed and selected from 139 submissions. The papers present original research on algorithms and data structures in all areas, including bioinformatics, combinatorics, computational geometry, databases, graphics, and parallel and distributed computing.Table of ContentsAlgorithms and data structures in bioinformatics.- Algorithms and data structures in combinatorics.- Algorithms and data structures in computational geometry.- Algorithms and data structures in databases.- Algorithms and data structures in graphics.- Parallel and distributed computing.

Read more less

Book SynopsisComputer science is the science of the future, and already underlies every facet of business and technology, and much of our everyday lives. In addition, it will play a crucial role in the science the 21st century, which will be dominated by biology and biochemistry, similar to the role of mathematics in the physical sciences of the 20th century. In this award-winning best-seller, the author and his co-author focus on the fundamentals of computer science, which revolve around the notion of the algorithm. They discuss the design of algorithms, and their efficiency and correctness, the inherent limitations of algorithms and computation, quantum algorithms, concurrency, large systems and artificial intelligence. Throughout, the authors, in their own words, stress the ‘fundamental and robust nature of the science in a form that is virtually independent of the details of specific computers, languages and formalisms'. This version of the book is published to celebrate 25 years since its first edition, and in honor of the Alan M. Turing Centennial year. Turing was a true pioneer of computer science, whose work forms the underlying basis of much of this book. Trade ReviewFrom the reviews of the third edition:“This book should be on any short list for a central course in computer science. It is designed to provide a uniform background on which all students might draw. It has a good-humored, easy style, which would make any reader unwilling to close the book after opening it anywhere. All computer scientists should have this book. … the bibliography is organized in a convenient chapter-by-chapter form, which makes the book useful for advanced work, and the exercises will help instructors identify capable students.” (Harvey Cohn, ACM Computing Reviews, August, 2012)“This is a reprint of the 3rd edition on the occasion of the 25th year of the existence of the book; it is also intended to honor Alan Turing’s 100th birthday. … it is highly readable, even if one is largely acquainted with the field. It is very well written, containing many illustrative examples, suited also for the non-specialist.” (Gunther Schmidt, Zentralblatt MATH, Vol. 1243, 2012)Table of ContentsPreliminaries.- and Historical Review.- Algorithms and Data.- Programming Languages and Paradigms.- Methods and Analysis.- Algorithmic Methods.- The Correctness of Algorithms.- The Efficiency of Algorithms.- Limitations and Robustness.- Inefficiency and Intractability.- Noncomputability and Undecidability.- Algorithmic Universality and Its Robustness.- Relaxing the Rules.- Parallelism, Concurrency, and Alternative Models.- Probabilistic Algorithms.- Cryptography and Reliable Interaction.- The Bigger Picture.- Software Engineering.- Reactive Systems.- Algorithmics and Intelligence.

Read more less

Book Synopsis

Read more less

Book SynopsisDas an Studienanfänger der Mathematik gerichtete Lehrbuch bietet eine breit angelegte Einführung in verschiedene Facetten der computerorientierten Mathematik. Es ermöglicht eine frühzeitige und wertvolle Auseinandersetzung mit computerorientierten Methoden, Denkweisen und Arbeitstechniken innerhalb der Mathematik.Hierzu werden grundlegende mathematische Teilgebiete behandelt, die eine enge Beziehung zu computerorientierten Aspekten haben: Graphen, mathematische Algorithmen, Rekursionsgleichungen, computerorientierte lineare Algebra, Zahlen, Polynome und ihre Nullstellen. Anhand des mathematischen Kernstrangs werden Einblicke in die Modellierung, Analyse und algorithmische Aufbereitung fundamentaler mathematischer Sachverhalte gegeben. Eine Besonderheit des Buches ist die Verwendung des sich immer stärker in Forschung und Lehre verbreitenden, frei verfügbaren Software-Systems Sage.Das Buch eignet sich besonders gut zur Komplementierung der klassischen Grundvorlesungen in Analysis und linearer Algebra.Trade Review“... Jedes Kapitel wird durch theoretisch ausgestaltete Übungsaufgaben sowie weiterführende Anmerkungen mit Quellenangaben direkt am Kapitelende komplettiert. ... Insgesamt ist dies ein gelungenes Lehrbuch zur computerorientierten Mathematik, das sowohl für eine Vorlesung für Erstsemester als auch als Hintergrundliteratur für ein Computerpraktikum zu Studienbeginn sehr gut geeignet ist ...” (Anne Frühbis-Krüger, in: Computer Algebra, Heft 58, März 2016)Table of ContentsEinleitung und Überblick.- Grundlegende Begriffe und Techniken.- Das Software-System Sage.- Graphen.- Einstieg in die Mathematik mit Sage.- Algorithmen und Rekursion.- Grundlegende mathematische Algorithmen.- Rechnen mit komplexen Zahlen.- Computerorientierte lineare Algebra.- Polynome und ihre Nullstellen.- Computerorientierte Fallstudien natürlicher Zahlen.- Anhang: Analysis, Lineare Algebra, Notation, Liste der verwendeten Sage-Befehle.

Read more less

Book SynopsisDieses Buch bietet einen historisch orientierten Einstieg in die Algorithmik, also die Lehre von den Algorithmen, in Mathematik, Informatik und darüber hinaus. Besondere Merkmale und Zielsetzungen sind: Elementarität und Anschaulichkeit, die Berücksichtigung der historischen Entwicklung, Motivation der Begriffe und Verfahren anhand konkreter, aussagekräftiger Beispiele unter Einbezug moderner Werkzeuge (Computeralgebrasysteme, Internet). Als Zusatzmedien werden computer- und internetspezifische Interaktions- und Visualisierungsmöglichkeiten (kostenlos) zur Verfügung gestellt. Das Werk wendet sich an Studierende und Lehrende an Schulen und Hochschulen sowie an Nichtspezialisten, die an den Themen "Computer/Algorithmen/Programmierung" einschließlich ihrer historischen und geisteswissenschaftlichen Dimension interessiert sind.Table of ContentsEinleitung.- Begriffsbestimmungen.- Historische Bezüge.- Fundamentale heuristische Strategien des algorithmischen Problemlösens.- Effizienz von Algorithmen.- Korrektheit von Algorithmen, Korrektheit von Computerergebnissen.- Grenzen der Algorithmisierbarkeit, Grenzen des Computers.- Programmierung.- Informationstheorie, Codierung und Kryptographie.- Evolutionäre Algorithmen und neuronale Netze.

Read more less

Book SynopsisDas Buch bietet ein ausgewogenes Verhältnis zwischen Theorie und praktischen Anwendungen des berechnenden Ingenieurswesens. Es illustriert sowohl die mathematischen Modelle im Computational Engineering, wie auch die zugehörigen Simulationsmethoden für die verschiedenen Ingenieursanwendungen und benennt geeignete Softwarepakete. Die umfangreichen Beispiele aus der berechnenden Ingenieurswissenschaft, welche Wärme- und Massentransport, Plasmasimulation und hydrodynamische Transportprobleme einschließen, geben dem Leser einen Überblick zu den aktuellen Themen und deren praktische Umsetzung in spätere Simulationsprogramme. Übungsaufgaben und prüfungsrelevante Fragen schließen die einzelnen Kapitel ab.Table of ContentsEinführung in Computational Engineering - Theoretischer Überblick zu den numerischen Verfahren - Theoretischer Überblick zu den Modellen - Schwerpunkt: Numerische Verfahren im Bereich der Transportmodelle - Schwerpunkt: Multiskalenmodelle und deren Multiskalenlöser - Algorithmische Umsetzung der theoretischen Verfahren - Praktische Anwendung in ingenieurswissenschaftlichen Problemstellungen.

Read more less

Book SynopsisThe LNCS journal Transactions on Large-Scale Data and Knowledge-Centered Systems focuses on data management, knowledge discovery, and knowledge processing, which are core and hot topics in computer science. Since the 1990s, the Internet has become the main driving force behind application development in all domains. An increase in the demand for resource sharing (e.g., computing resources, services, metadata, data sources) across different sites connected through networks has led to an evolution of data- and knowledge-management systems from centralized systems to decentralized systems enabling large-scale distributed applications providing high scalability.This, the 50th issue of Transactions on Large-Scale Data and Knowledge-Centered Systems, contains five fully revised selected regular papers. Topics covered include data anonymization, quasi-identifier discovery methods, symbolic time series representation, detection of anomalies in time series, data quality management in biobanks, and the use of multi-agent technology in the design of intelligent systems for maritime transport.Table of ContentsA Parallel Quasi-identifier Discovery Scheme for Dependable Data Anonymisation.- Towards Symbolic Time Series Representation Improved by Kernel Density Estimators.- Anomaly Detection in Time Series.- Designing Intelligent Marine Framework Based on Complex Adaptive System Principle.- Data Item Quality for Biobanks.

Read more less

Book SynopsisDavid Trachtenherz entwickelt einen Lösungsansatz zur eigenschaftsorientierten Beschreibung der logischen Architektur eingebetteter Systeme, der eine präzise deklarative Spezifikation funktionaler Eigenschaften mit wählbarem Grad der Abstraktion für unterschiedliche Entwicklungsphasen und -ebenen ermöglicht.Table of ContentsLogische Architektur; Formale Grundlagen; Grundlagen eigenschaftsorientierter Architekturbeschreibung; Anschauliche Darstellung eigenschaftsorientierter Architekturspezifikation; Fallstudie ; Ströme und temporale Logik in Isabelle/HOL

Read more less

Book SynopsisThis book is a compilation of the entire research work on the topic of Complex Binary Number System (CBNS) carried out by the author as the principal investigator and members of his research groups at various universities during the years 2000-2012. Pursuant to these efforts spanning several years, the realization of CBNS as a viable alternative to represent complex numbers in an “all-in-one” binary number format has become possible and efforts are underway to build computer hardware based on this unique number system. It is hoped that this work will be of interest to anyone involved in computer arithmetic and digital logic design and kindle renewed enthusiasm among the engineers working in the areas of digital signal and image processing for developing newer and efficient algorithms and techniques incorporating CBNS.Trade ReviewFrom the reviews:“This is a monograph presenting the results of a dozen or so years research of the author devoted to purely binary representation of complex numbers and design of circuits for arithmetic operations on them. … The topic of this book may be recommended as a facultative lecture for academic courses on digital arithmetic.” (Antoni Michalski, Zentralblatt MATH, Vol. 1262, 2013)Table of ContentsIntroduction.- Conversion Algorithms.- Arithmetic Algorithms.- Arithmetic Circuits Designs.- Complex Binary Associative Processor Design.- Conclusion and Further Research.

Read more less

Book SynopsisThis book constitutes the post-conference proceedings of the 4th International Conference on Advances in Computing and Data Sciences, ICACDS 2020, held in Valletta, Malta, in April 2020.*The 46 full papers were carefully reviewed and selected from 354 submissions. The papers are centered around topics like advanced computing, data sciences, distributed systems organizing principles, development frameworks and environments, software verification and validation, computational complexity and cryptography, machine learning theory, database theory, probabilistic representations.* The conference was held virtually due to the COVID-19 pandemic.Table of ContentsAdvanced computing.- data sciences.

Read more less

Book SynopsisThis book presents best selected research papers presented at the International Conference on Computer Networks, Big Data and IoT (ICCBI 2020), organized by Vaigai College Engineering, Madurai, Tamil Nadu, India, during 15–16 December 2020. The book covers original papers on computer networks, network protocols and wireless networks, data communication technologies and network security. The book is a valuable resource and reference for researchers, instructors, students, scientists, engineers, managers and industry practitioners in those important areas.Table of ContentsMaximizing Network Lifetime in WSN using Ant Colony Algorithm.- Deep Ensemble Approach for Question Answer System.- Information Sharing Over Social Media Analysis Using Centrality Measure.- Indoor Mobile Robot Navigation using Deep Convolutional Neural Network.- Etaheuristic Enabled Shortest Path Selection for IoT based Wireless Sensor Network.- Generation of Random Binary Sequence using Adaptive Row-Column Approach and Synthetic Colour Image.- A Study of Mobile Adhoc Network and its Performance Optimizaiton Algorithm.- Sentimental Analysis on Twitter Data of Political Domain.- Big Social Media Analytics: Applications and Challenges.- Intelligent Computing Application for Cloud Enhancing Health Care Services.- Corona Virus Detection and Classification using X-Rays and CT Scans with Machine Learning Techniques.- Security Issues and Solutions in E-Health and Telemedicine.- Accident Alert System with False Alarm Switch.- A Deep Learning Approach to Detect Lumpy Skin Disease in Cows.- Algorithmic Trading using Machine Learning and Neural Network.- Analysis on Intrusion Detection System using Machine Learning Techniques.- Content Related Feature Analysis for Fake Online Consumer Review Detection.- Approaches in Assistive Technology: A Survey on Existing Assistive Wearable Technology for The Visually-Impaired.- Filter Bank Multicarrier Systems using Gaussian Pulse based Filter Design for 5G Technologies.- Data Streaming Architecture for Visualizing Cryptocurrency Temporal Data.- Integration of IoT and SDN to Mitigate DDoS with RYU Controller.- A Framework for monitoring Patient’s Vital Signs with Internet-of-Things and Blockchain Technology.- Network Intrusion Detection using Cross Bagging based Stacking Model.- Performance Study of Free Space Optical System under Varied Atmospheric Conditions.- Review on Energy Efficient Routing Protocols in WSN.Comparative Analysis of Traffic and Congestion in Software Defined Networks.- Automatic Vehicle Service Monitoring and Tracking System using IoT and Machine Learning.

Read more less

Book SynopsisThis two-volume book provides an insight into the 10th International Conference on Soft Computing for Problem Solving (SocProS 2020). This international conference is a joint technical collaboration of Soft Computing Research Society and Indian Institute of Technology Indore. The book presents the latest achievements and innovations in the interdisciplinary areas of soft computing. It brings together the researchers, engineers and practitioners to discuss thought-provoking developments and challenges, in order to select potential future directions. It covers original research papers in the areas including but not limited to algorithms (artificial immune system, artificial neural network, genetic algorithm, genetic programming and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). The book will be beneficial for young as well as experienced researchers dealing across complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.Table of ContentsA deep semi-supervised approach for multi-label land-cover classification under scarcity of labelled images.- Role of individual samples in Modified Possibilistic c-Means classifier for handling heterogeneity within mustard crop.- Specially Structured Flow Shop Scheduling Models with processing times as Trapezoidal Fuzzy Numbers to optimize Waiting time of Jobs.- Potential Fishing Zone Characterization in the Indian Ocean by Machine Learning Approach.- A novel method to optimize interval length for intuitionistic fuzzy time series.- Low Altitude Unmanned Aerial Vehicle For Real Time Green House Plant Disease Monitoring Using Convolutional Neural Network.

Read more less

Book SynopsisThis book aims to address emerging challenges in the field of agriculture and natural resource management using the principles and applications of data science (DS). The book is organized in three sections, and it has fourteen chapters dealing with specialized areas. The chapters are written by experts sharing their experiences very lucidly through case studies, suitable illustrations and tables. The contents have been designed to fulfil the needs of geospatial, data science, agricultural, natural resources and environmental sciences of traditional universities, agricultural universities, technological universities, research institutes and academic colleges worldwide. It will help the planners, policymakers and extension scientists in planning and sustainable management of agriculture and natural resources. The authors believe that with its uniqueness the book is one of the important efforts in the contemporary cyber-physical systems.Table of ContentsData Science: Principles and Concepts in Data Analysis and Modelling.- Data Science: Tools, Techniques and Potential Applications in Earth Observation Studies.- Data Science in Agriculture and Natural Resource Management: An Overview.- Applications of Reinforcement Learning and Recurrent Neural Network Based Deep Learning Frameworks in Agriculture.- Precision Farming Using Emerging Technologies.- An Architecture for Quality Centric Crop Production.- Integrating UAV and Field Sensor Data for Better Decision Making in Broadacre Cropping Systems.- Object Based Crop Classification for Precision Farming.- Disruptive Innovations in Precision Agriculture - Towards BD Analytics for Better GeoFarmatics.- A Paradigm-shift in Global Cropland Maps and Products for Food and Water Security in the Twenty-first Century: Petabyte Scale Satellite Big-data Analytics, Machine Learning, and Cloud Computing.- Big Data Analytics for Climate Resilient Supply Chains: Opportunities and Way Forward.- Mapping Croplands Using Machine Learning Algorithms and Spectral Matching Techniques.- Applications of Computer Vision in Precision Agriculture.- Innovative Geoportal Platforms for Sustainable Management of Natural Resources.

Read more less

Book SynopsisDeep Learning models are at the core of artificial intelligence research today. It is well known that deep learning techniques are disruptive for Euclidean data, such as images or sequence data, and not immediately applicable to graph-structured data such as text. This gap has driven a wave of research for deep learning on graphs, including graph representation learning, graph generation, and graph classification. The new neural network architectures on graph-structured data (graph neural networks, GNNs in short) have performed remarkably on these tasks, demonstrated by applications in social networks, bioinformatics, and medical informatics. Despite these successes, GNNs still face many challenges ranging from the foundational methodologies to the theoretical understandings of the power of the graph representation learning.This book provides a comprehensive introduction of GNNs. It first discusses the goals of graph representation learning and then reviews the history, current developments, and future directions of GNNs. The second part presents and reviews fundamental methods and theories concerning GNNs while the third part describes various frontiers that are built on the GNNs. The book concludes with an overview of recent developments in a number of applications using GNNs. This book is suitable for a wide audience including undergraduate and graduate students, postdoctoral researchers, professors and lecturers, as well as industrial and government practitioners who are new to this area or who already have some basic background but want to learn more about advanced and promising techniques and applications.Table of ContentsChapter 1. Representation Learning.- Chapter 2. Graph Representation Learning.- Chapter 3. Graph Neural Networks.- Chapter 4. Graph Neural Networks for Node Classification.- Chapter 5. The Expressive Power of Graph Neural Networks.- Chapter 6. Graph Neural Networks: Scalability.- Chapter 7. Interpretability in Graph Neural Networks.- Chapter 8. "Graph Neural Networks: Adversarial Robustness".- Chapter 9. Graph Neural Networks: Graph Classification.- Chapter 10. Graph Neural Networks: Link Prediction.- Chapter 11. Graph Neural Networks: Graph Generation.- Chapter 12. Graph Neural Networks: Graph Transformation.- Chapter 13. Graph Neural Networks: Graph Matching.- Chapter 14. "Graph Neural Networks: Graph Structure Learning". Chapter 15. Dynamic Graph Neural Networks.- Chapter 16. Heterogeneous Graph Neural Networks.- Chapter 17. Graph Neural Network: AutoML.- Chapter 18. Graph Neural Networks: Self-supervised Learning.- Chapter 19. Graph Neural Network in Modern Recommender Systems.- Chapter 20. Graph Neural Network in Computer Vision.- Chapter 21. Graph Neural Networks in Natural Language Processing.- Chapter 22. Graph Neural Networks in Program Analysis.- Chapter 23. Graph Neural Networks in Software Mining.- Chapter 24. "GNN-based Biomedical Knowledge Graph Mining in Drug Development".- Chapter 25. "Graph Neural Networks in Predicting Protein Function and Interactions".- Chapter 26. Graph Neural Networks in Anomaly Detection.- Chapter 27. Graph Neural Networks in Urban Intelligence.

Read more less

Book SynopsisThis book introduces important results and techniques in property testing, where the goal is to design algorithms that decide whether their input satisfies a predetermined property in sublinear time, or even in constant time – that is, time is independent of the input size. This book consists of three parts. The first part provides an introduction to the foundations of property testing. The second part studies the testing of specific properties on strings, graphs, functions, and constraint satisfaction problems. Vectors and matrices over real numbers are also covered. The third part is more advanced and explains general conditions, including full characterizations, under which properties are constant-query testable. The first and second parts of the book are intended for first-year graduate students in computer science. They should also be accessible to undergraduate students with the adequate background. The third part can be used by researchers or ambitious graduate students who want to gain a deeper theoretical understanding of property testing.Table of ContentsChapter 1: Introduction.- Chapter 2: Basic Techniques.- Chapter 3: Strings.- Chapter 4: Graphs in the Adjacency Metrix Model.- Chapter 5: Graphs in the Bounded-Degree Model.- Chapter 6: Functions over Hypercubes.- Chapter 7: Massively Parameterized Model.- Chapter 8: Vectors and Matrices over the Reals.- Chapter 9: Graphs in the Adjacency Matrix Model.- Chapter 10: Graphs in the Bounded-Degree Model.- Chapter 11: Affine-Invariant Properties of Functions.- Chapter 12: Linear Properties of Functions.- Chapter 13: Massively Parameterized Model.

Read more less

Book SynopsisThis book focuses on research aspects of ensemble approaches of machine learning techniques that can be applied to address the big data problems. In this book, various advancements of machine learning algorithms to extract data-driven decisions from big data in diverse domains such as the banking sector, healthcare, social media, and video surveillance are presented in several chapters. Each of them has separate functionalities, which can be leveraged to solve a specific set of big data applications. This book is a potential resource for various advances in the field of machine learning and data science to solve big data problems with many objectives. It has been observed from the literature that several works have been focused on the advancement of machine learning in various fields like biomedical, stock prediction, sentiment analysis, etc. However, limited discussions have been carried out on application of advanced machine learning techniques in solving big data problems. Table of ContentsDeep Learning for Supervised Learning.- Deep Learning for Unsupervised Learning.- Support Vector Machine for Regression.- Support Vector Machine for Classification.- Decision Tree for Regression.- Higher Order Neural Networks.- Competitive Learning.- Semi-supervised Learning.- Multi-objective Optimization Techniques.- Techniques for Feature Selection/Extraction.- Techniques for Task Relevant Big Data Analysis.- Techniques for Post Processing Task in Big Data Analysis.- Customer Relationship Management.

Read more less

Book SynopsisThis book addresses several knowledge discovery problems on multi-sourced data where the theories, techniques, and methods in data cleaning, data mining, and natural language processing are synthetically used. This book mainly focuses on three data models: the multi-sourced isomorphic data, the multi-sourced heterogeneous data, and the text data. On the basis of three data models, this book studies the knowledge discovery problems including truth discovery and fact discovery on multi-sourced data from four important properties: relevance, inconsistency, sparseness, and heterogeneity, which is useful for specialists as well as graduate students. Data, even describing the same object or event, can come from a variety of sources such as crowd workers and social media users. However, noisy pieces of data or information are unavoidable. Facing the daunting scale of data, it is unrealistic to expect humans to “label” or tell which data source is more reliable. Hence, it is crucial to identify trustworthy information from multiple noisy information sources, referring to the task of knowledge discovery. At present, the knowledge discovery research for multi-sourced data mainly faces two challenges. On the structural level, it is essential to consider the different characteristics of data composition and application scenarios and define the knowledge discovery problem on different occasions. On the algorithm level, the knowledge discovery task needs to consider different levels of information conflicts and design efficient algorithms to mine more valuable information using multiple clues. Existing knowledge discovery methods have defects on both the structural level and the algorithm level, making the knowledge discovery problem far from totally solved.Table of ContentsChapter 1 Introduction 1.1 Knowledge Discovery 1.2 Main Challenges 1.3 Book Overview Chapter 2 Functional-dependency-based truth discovery for isomorphic data 2.1 Handling independent constraints 2.2 Handling inter-related constraints 2.3 Inter-source data aggregation 2.4 Update source weights Chapter 3 Denial-constraint-based truth discovery for isomorphic data Describe the truth discovery strategies for isomorphic data based on denial constraints 4.1 Denial constraint transformation 4.2 Optimized solution 4.3 Scalable strategies Chapter 4 Pattern discovery for heterogeneous data 4.1 Problem definition for multi-source heterogeneous data 4.2 Optimization framework 4.3 PatternFinder algorithm 4.4 The optimized grouping strategy Chapter 5 Deep fact discovery for text data 5.1 Fact extraction via mining patterns 5.2 The CNN-LSTM architecture 5.3 The fact encoder and pattern embedding 5.4 Training and inference

Read more less

Book SynopsisThis textbook explains the fundamentals of Markov Chain Monte Carlo (MCMC) without assuming advanced knowledge of mathematics and programming. MCMC is a powerful technique that can be used to integrate complicated functions or to handle complicated probability distributions. MCMC is frequently used in diverse fields where statistical methods are important – e.g. Bayesian statistics, quantum physics, machine learning, computer science, computational biology, and mathematical economics. This book aims to equip readers with a sound understanding of MCMC and enable them to write simulation codes by themselves. The content consists of six chapters. Following Chap. 2, which introduces readers to the Monte Carlo algorithm and highlights the advantages of MCMC, Chap. 3 presents the general aspects of MCMC. Chap. 4 illustrates the essence of MCMC through the simple example of the Metropolis algorithm. In turn, Chap. 5 explains the HMC algorithm, Gibbs sampling algorithm and Metropolis-Hastings algorithm, discussing their pros, cons and pitfalls. Lastly, Chap. 6 presents several applications of MCMC. Including a wealth of examples and exercises with solutions, as well as sample codes and further math topics in the Appendix, this book offers a valuable asset for students and beginners in various fields. Table of ContentsChapter 1: Introduction.- Chapter 2: What is the Monte Carlo method?.- Chapter 3: General Aspects of Markov Chain Monte Carlo.- Chapter 4: Metropolis Algorithm.- Chapter 5: Other Useful Algorithms.- Chapter 6: Applications of Markov Chain Monte Carlo.

Read more less

Book SynopsisThis book features high-quality, peer-reviewed research papers presented at the Fifth International Conference on Smart Technologies in Data Science and Communication (SMARTDSC 2022), held Koneru Lakshmaiah Education Foundation, Guntur, Andhra Pradesh, India, on 16 – 17 June 2022. It includes innovative and novel contributions in the areas of data analytics, communication and soft computing. Table of ContentsA Graph based model for Discovering Host-based hook Attacks.- E-Health Care Patient Information Retrieval and Monitoring System Using SVM.- Number Plate Recognition using Optical Character Recognition (OCA) and Connected Component Analysis (CCA).- Cartoonify an Image with Open cv using Python.- Web Design as an Important Factor in the Success of a Website.- Earlier Selection of Routes for Data Transfer in both Wired and Wireless Networks.

Read more less

Book SynopsisThis book focuses on improving the performance (convergence rate, communication efficiency, computational efficiency, etc.) of algorithms in the context of distributed optimization in networked systems and their successful application to real-world applications (smart grids and online learning). Readers may be particularly interested in the sections on consensus protocols, optimization skills, accelerated mechanisms, event-triggered strategies, variance-reduction communication techniques, etc., in connection with distributed optimization in various networked systems. This book offers a valuable reference guide for researchers in distributed optimization and for senior undergraduate and graduate students alike.Table of ContentsChapter 1. Distributed Nesterov-Like Accelerated Algorithms in Networked Systems with Directed Communications.- Chapter 2. Distributed Stochastic Projected Gradient Algorithms for Composite Constrained Optimization in Networked Systems.- Chapter 3. Distributed Proximal Stochastic Gradient Algorithms for Coupled Composite Optimization in Networked Systems.- Chapter 4. Distributed Subgradient Algorithms Based on Event-Triggered Strategy in Networked Systems.- Chapter 5. Distributed Accelerated Stochastic Algorithms Based on Event-Triggered Strategy in Networked Systems.- Chapter 6. Event-Triggered Based Distributed Optimal Economic Dispatch in Smart Grids.- Chapter 7. Fast Distributed Optimal Economic Dispatch in Dynamic Smart Grids with Directed Communications.- Chapter 8. Accelerated Distributed Optimal Economic Dispatch in Smart Grids with Directed Communications.- Chapter 9. Privacy Preserving Distributed Online Learning with Time-Varying and Directed Communications.

Read more less

Book SynopsisThis book includes an extended version of selected papers presented at the 11th Industry Symposium 2021 held during January 7–10, 2021. The book covers contributions ranging from theoretical and foundation research, platforms, methods, applications, and tools in all areas. It provides theory and practices in the area of data science, which add a social, geographical, and temporal dimension to data science research. It also includes application-oriented papers that prepare and use data in discovery research. This book contains chapters from academia as well as practitioners on big data technologies, artificial intelligence, machine learning, deep learning, data representation and visualization, business analytics, healthcare analytics, bioinformatics, etc. This book is helpful for the students, practitioners, researchers as well as industry professional.Table of ContentsNLP for Sentiment Computation.- Productizing an Artificial Intelligence solution for Intelligent Detail Extraction- Synergy of Symbolic and Sub-symbolic Artificial Intelligence techniques.- Digital Consumption Pattern and Impacts of Social Media: Descriptive Statistical Analysis.- Applicational Statistics in Data Science & Machine Learning.- Evolutionary algorithms based machine learning models.- Application to Predict the Impact of COVID-19 in India using Deep Learning.- Role of Data Analytics in Bio Cyber Physical Systems.- Evolution of Sentiment Analysis : Methodologies and Paradigms.- Healthcare Analytics: An advent to mitigate the risks and impacts of a Pandemic.- Image Classification for Binary Classes using Deep Convolutional Neural Network: An Experimental Study.

Read more less

Book SynopsisThe 7-volume set LNCS 14487-14493 constitutes the proceedings of the 23rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2023, which took place in Tianjin, China, during October, 2023. The 145 full papers included in this book were carefully reviewed and selected from 439 submissions.

Read more less

Book SynopsisThe 7-volume set LNCS 14487-14493 constitutes the proceedings of the 23rd International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2023, which took place in Tianjin, China, during October, 2023. The 145 full papers included in this book were carefully reviewed and selected from 439 submissions.

Read more less

Book SynopsisThis open access book discusses the theory and methods of hypergraph computation. Many underlying relationships among data can be represented using graphs, for example in the areas including computer vision, molecular chemistry, molecular biology, etc. In the last decade, methods like graph-based learning and neural network methods have been developed to process such data, they are particularly suitable for handling relational learning tasks. In many real-world problems, however, relationships among the objects of our interest are more complex than pair-wise. Naively squeezing the complex relationships into pairwise ones will inevitably lead to loss of information which can be expected valuable for learning tasks. Hypergraph, as a generation of graph, has shown superior performance on modelling complex correlations compared with graph. Recent years have witnessed a great popularity of researches on hypergraph-related AI methods, which have been used in computer vision, social media analysis, etc. We summarize these attempts as a new computing paradigm, called hypergraph computation, which is to formulate the high-order correlations underneath the data using hypergraph, and then conduct semantic computing on the hypergraph for different applications. The content of this book consists of hypergraph computation paradigms, hypergraph modelling, hypergraph structure evolution, hypergraph neural networks, and applications of hypergraph computation in different fields. We further summarize recent achievements and future directions on hypergraph computation in this book.Table of Contents

Read more less

Book SynopsisThis book systematically introduces the competitions in the field of algorithm and machine learning. The first author of the book has won 5 championships and 5 runner-ups in domestic and international algorithm competitions.Firstly, it takes common competition scenarios as a guide by giving the main processes of using machine learning to solve real-world problems, namely problem modelling, data exploration, feature engineering, model training. And then lists the main points of difficulties, general ideas with solutions in the whole process. Moreover, this book comprehensively covers several common problems in the field of machine learning competitions such as recommendation, temporal prediction, advertising, text computing, etc. The authors, also knew as "competition professionals”, will explain the actual cases in detail and teach you various processes, routines, techniques and strategies, which is a rare treasure book for all competition enthusiasts. It is very suitable for readers who are interested in algorithm competitions and deep learning algorithms in practice, or computer-related majors.Table of ContentsChapter 1 First Sight.- Chapter 2 Problem Modeling.- Chapter 3 Data Exploration.- Chapter 4 Characteristic Engineering.- Chapter 5 Model Training .- Chapter 6 Model Fusion.- Chapter 7 User Portrait.- Chapter 8 Actual Combat Case: Elo Merchant.- Chapter 9 time sequence.- Chapter 10 Practical Cases: Global Urban.- Chapter 11 Practical Case: Corporaci .-Corporación Favorita Grocery Sales Forecasting.- Chapter 12 Computing Advertising.- Chapter 13 Practical Cases: Tencent 2018 Advertising Algorithm Contest-Similarity Crowd Expansion.- Chapter 14: TalkingData AdTracking Fraud Detection Challenge.- Chapter 15 Natural Language Processing.- Chapter 16 Practical Case: Quora Question Pairs.

Read more less

Book SynopsisThis volume LNCS 14252 constitutes the refereed proceedings of 25th International Conference on Information and Communications Security, ICICS 2023, held in Tianjin, China, during November 18–20, 2023. The 38 full papers presented together with 6 short papers were carefully reviewed and selected from 181 submissions. The conference focuses on: Symmetric-Key Cryptography; Public-Key Cryptography; Applied Cryptography; Authentication and Authorization; Privacy and Anonymity; Security and Privacy of AI; Blockchain and Cryptocurrencies; and System and Network Security. Table of Contents​Symmetric-Key Cryptography.- SAT-aided Differential Cryptanalysis of Lightweight Block Ciphers Midori, MANTIS and QARMA.- Improved Related-Key Rectangle Attack against the Full AES-192.- Block Ciphers Classification Based on Randomness Test Statistic Value via LightGBM.- Cryptanalysis of Two White-Box Implementations of the CLEFIA Block Cipher.- PAE: Towards More Efficient and BBB-secure AE From a Single Public Permutation.- Public-Key Cryptography.- A Polynomial-time Attack on G2SIDH.- Improvements of Homomorphic Secure Evaluation of Inverse Square Root.- Oblivious Transfer from Rerandomizable PKE.- Forward Secure Lattice-based Ring Signature Scheme in the Standard Model.- Applied Cryptography.- Secure Multi-Party Computation with Legally-Enforceable Fairness.- On-demand Allocation of Cryptographic Computing Resource with Load Prediction.- Private Message Franking with After Opening Privacy.- Semi-Honest 2-Party Faithful Truncation from Two-Bit Extraction.- Outsourcing Verifiable Distributed Oblivious Polynomial Evaluation from Threshold Cryptography.- Authentication and Authorization.- PiXi: Password Inspiration by Exploring Information.- Security Analysis of Alignment-Robust Cancelable Biometric Scheme for Iris Verification.- A Certificateless Conditional Anonymous Authentication Scheme for Satellite Internet of Things.- BLAC: A Blockchain-based Lightweight Access Control Scheme in Vehicular Social Networks.- Privacy and Anonymity.- Link Prediction-Based Multi-Identity Recognition of Darknet Vendors.- CryptoMask: Privacy-preserving Face Recognition.- Efficient Private Multiset ID Protocols.- Zoomer: A Website Fingerprinting Attack against Tor Hidden Services.- An Enhanced Privacy-preserving Hierarchical Federated Learning Framework for IoV.- Security and Privacy of AI.- Revisiting the Deep Learning-based Eavesdropping Attacks via Facial Dynamics from VR Motion Sensors.- Multi-scale Features Destructive Universal Adversarial Perturbations.- Pixel-Wise Reconstruction of Private Data in Split Federated Learning.- Neural Network Backdoor Attacks Fully Controlled by Composite Natural Utterance Fragments.- Black-Box Fairness Testing with Shadow Models.- Graph Unlearning using Knowledge Distillation.- AFLOW: Developing Adversarial Examples under Extremely Noise-limited Settings.- Learning to Detect Deepfakes via Adaptive Attention and Constrained Difference.- A Novel Deep Ensemble Framework for Online Signature Verification Using Temporal and Spatial Representation.- Blockchain and Cryptocurrencies.- SCOPE: A Cross-Chain Supervision Scheme for Consortium Blockchains.- Subsidy Bridge: Rewarding Cross-blockchain Relayers with Subsidy.- Towards Efficient and Privacy-Preserving Anomaly Detection of Blockchain-based Cryptocurrency Transactions.- Blockchain based Publicly Auditable Multi-Party Computation with Cheater Detection.- BDTS: Blockchain-based Data Trading System.- Illegal Accounts Detection on Ethereum using Heterogeneous Graph Transformer Networks.- System and Network security.- DRoT: A Decentralised Root of Trust for Trusted Networks.- Finding Missing Security Operation Bugs via Program Slicing and Differential Check.- TimeClave: Oblivious In-enclave Time series Processing System.- Efficient and Appropriate Key Generation Scheme in Different IoT Scenarios.- A Fake News Detection Method Based on A Multimodal Cooperative Attention Network.

Read more less

Book Synopsis

Read more less

Book SynopsisOffers the major concepts, techniques and applications of sparse representation. This book presents the standard representations with Fourier, wavelet and time-frequency transforms, and the construction of orthogonal bases with fast algorithms.Trade Review"There is no question that this revision should be published. Mallat’s book is the undisputed reference in this field – it is the only one that covers the essential material in such breadth and depth." --Laurent Demanet, Stanford UniversityTable of ContentsPrefaceNotationsSparse RepresentationsFourier KingdomDiscrete RevolutionTime Meets FrequencyFramesWavelet ZoomWavelet BasesWavelet Packet and Local Cosine BasesApproximations in BasesCompressionDenoisingSparse in Redundant DictionariesMathematical Complements

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less

a huge range and FREE tracked UK delivery on ALL orders.

Read more less