Электронный каталог

    Temperature dependent magnetic properties and FORC probing of NiMn nanowire arrays / Samardak, Vadim YurievichOgnev, Aleksey V.Samardak, Aleksey Yurievich [и др.] // Четвертая Азиатская школа-конференция по физике и технологии наноструктурированных материалов : материалы школы-конференции, 23-28 сентября 2018 г., Владивосток : [на англ. яз.]. - Владивосток : Изд-во Дальневосточного федерального университета, 2018. - С. 188. - (RuSLFEFU А 355 620.2)

Рубрики: статья из сборника

Кл.слова (ненормированные):
ДВФУ (труды преподавателей) -- магнитные свойства -- наноструктуры -- нановолокна

Доп.точки доступа:
Samardak, Vadim Yurievich
Ognev, Aleksey V.
Samardak, Aleksey Yurievich
Noshahr, A. S.
Nasipouri, F.
Samardak, Aleksandr Sergeevich

Temperature dependent magnetic properties and FORC probing of NiMn nanowire arrays [Текст] / Samardak, Vadim YurievichOgnev, Aleksey V.Samardak, Aleksey Yurievich [и др.] // Четвертая Азиатская школа-конференция по физике и технологии наноструктурированных материалов : материалы школы-конференции, 23-28 сентября 2018 г., Владивосток : [на англ. яз.]. - Владивосток : Изд-во Дальневосточного федерального университета, 2018. - С. 188

DDC 500.5
N 27
NATO Advanced Research Workshop on Critical Space Infrastructure: From Vulnerabilities and Threats to Resilience ((2019 : ; Norfolk, Va.)).
    Space infrastructures [[electronic resource] /] / edited by Unal Tatar [and more]. - Amsterdam : : IOS Press,, 2020. - 1 online resource (410 p.). - (NATO Science for Peace and Security Series - d: Information and Communication Security Ser. ; ; v.57). - URL: https://library.dvfu.ru/lib/document/SK_ELIB/9ABF1380-B3D0-4912-9B26-4FC8348084ED. - ISBN 9781643680736. - ISBN 1643680730
Description based upon print version of record. "Proceedings of the NATO Advanced Research Workshop on Critical Space Infrastructure: From Vulnerabilities and Threats to Resilience, Norfolk, Virginia, USA, 21-22 May 2019."
Параллельные издания: Print version: : Tatar, U. Space Infrastructures: from Risk to Resilience Governance. - Amsterdam : IOS Press, Incorporated,c2020. - ISBN 9781643680729
    Содержание:
Intro -- Title Page -- Preface -- Contents -- I. Governance of Space Critical Infrastructures -- Critical Space Infrastructures: Perspectives and a Critical Review -- Critical Space Infrastructures -- A Comparison with Terrestrial CI -- Space and Cyberspace as Global Commons and as Property -- Complex System Governance: Advancing Prospects for Critical Space Infrastructure Applications -- From Flag to Hashtag: Space 2.0 -- Critical Space Infrastructure: Contributions of Complex System Governance -- II. Cybersecurity of Space Infrastructures
Cybersecurity Implications of Commercial Off The Shelf (COTS) Equipment in Space Infrastructure -- Satellites Under Attack: An Evaluation of a Mock Cyberoperation in Space Under International Law -- Space Infrastructure Security Through the Lens of Plan-Do-Check-Act (PDCA) Cybersecurity Framework -- A Mixed Public-Private Partnership Approach for Cyber Resilience of Space Technologies -- Addressing Cyber-Security and Privacy in a Multi-Actor Energy Environment Using Unbundled Smart Meter Architecture -- War in Space -- III. Risk, Resiliency, and Complexity of Space Infrastructures
The Impact of Human Assurance on Satellite Operations -- Fuzzy Analytic Hierarchy Process-Based Risk Assessment Methodology for Solar Arrays of GEO Satellites -- Resilience of Critical Infrastructure Index Design Between Diversification and Uniformization -- Resilience in Design of Multi-Satellite Systems -- Dependency of the Critical Infrastructures from Energy Sector on Geomagnetic Storms and Electrical Properties of the Geological Basement -- IV. Emerging Technologies for Space Infrastructures: Blockchain, Artificial Intelligence, Quantum Computing
A Sand Resource Governance Framework That Employs Satellite Imagery and Blockchain Technology -- Critical Space Infrastructures and Quantum Computing -- Artificial Intelligence: The Nexus Between Neural Networks and Space Critical Infrastructures -- Blockchain and Space-Perfect Match or Red Herring? -- V. Application Domains for Critical Space Systems -- The Use of Geoinformatics for Combining In Situ and Satellite-Derived Data for the Assessment of Land Degradation in Trinidad -- GNSS and Earth Observation Services Disruption, Between Collapse and Myth
Pilots' Role in the Critical Infrastructure of Aviation -- Critical Space Infrastructure of the Health System in Romania -- Overview and Brief Analysis -- VI. National Approaches and Applications for Critical Space Infrastructures -- Vital Outer Space Infrastructures: Romania's Pursuits and Achievements -- Implementing Agile Project Management in the U.S. Department of Defense -- SST and NEO Related Activities in Romania -- An Overview of Institutional and Legal Framework -- Curriculum Improvement Challenges in the Geospatial Occupational Profile Sector in Romania -- Subject Index -- Author Index

Space infrastructures [[electronic resource] /] / edited by Unal Tatar [and more]., 2020. - 1 online resource (410 p.). с. (Введено оглавление)

DDC 005.133
J 22
Jamro, Marcin.
    C# Data Structures and Algorithms [[electronic resource] :] : Explore the possibilities of C# for developing a variety of efficient applications. / Marcin. Jamro. - 1788833738. - Birmingham : : Packt Publishing,, 2018. - 1 online resource (287 p.) ( час. мин.), 1788833738. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/7C4244C4-3708-40D1-BF46-6CEC3759E2A4. - ISBN 9781788834681 (electronic bk.). - ISBN 1788834682 (electronic bk.). - ISBN 1788833732. - ISBN 9781788833738
Description based upon print version of record.
Параллельные издания: Print version: : Jamro, Marcin C# Data Structures and Algorithms : Explore the possibilities of C# for developing a variety of efficient applications. - Birmingham : Packt Publishing,c2018
    Содержание:
Cover; Title Page; Copyright and Credits; Packt Upsell; Contributors; Table of Contents; Preface; Chapter 1: Getting Started; Programming language; Data types; Value types; Structs; Enumerations; Reference types; Strings; Object; Dynamic; Classes; Interfaces; Delegates; Installation and configuration of the IDE; Creating the project; Input and output; Reading from input; Writing to output; Launching and debugging; Summary; Chapter 2: Arrays and Lists; Arrays; Single-dimensional arrays; Example - month names; Multi-dimensional arrays; Example - multiplication table; Example - game map
Jagged arraysExample - yearly transport plan; Sorting algorithms; Selection sort; Insertion sort; Bubble sort; Quicksort; Simple lists; Array list; Generic list; Example - average value; Example - list of people; Sorted lists; Example - address book; Linked lists; Example - book reader; Circular-linked lists; Implementation; Example - spin the wheel; Summary; Chapter 3: Stacks and Queues; Stacks; Example - reversing words; Example - Tower of Hanoi; Queues; Example - call center with a single consultant; Example - call center with many consultants; Priority queues
Example - call center with priority supportSummary; Chapter 4: Dictionaries and Sets; Hash tables; Example - phone book; Dictionaries; Example - product location; Example -- user details; Sorted dictionaries; Example -- definitions; Hash sets; Example -- coupons; Example -- swimming pools; Sorted"" sets; Example -- removing duplicates; Summary; Chapter 5: Variants of Trees; Basic trees; Implementation; Node; Tree; Example - hierarchy of identifiers; Example - company structure; Binary trees; Implementation; Node; Tree; Example - simple quiz; Binary search trees; Implementation; Node; Tree; Lookup
InsertionRemoval; Example - BST visualization; AVL trees; Implementation; Example - keep the tree balanced; Red-black trees; Implementation; Example - RBT-related features; Binary heaps; Implementation; Example - heap sort; Binomial heaps; Fibonacci heaps; Summary; Chapter 6: Exploring Graphs; Concept of graphs; Applications; Representation; Adjacency list; Adjacency matrix; Implementation; Node; Edge; Graph; Example - undirected and unweighted edges; Example - directed and weighted edges; Traversal; Depth-first search; Breadth-first search; Minimum spanning tree; Kruskal's algorithm
Prim's algorithmExample - telecommunication cable; Coloring; Example - voivodeship map; Shortest path; Example - game map; Summary; Chapter 7: Summary; Classification of data structures; Diversity of applications; Arrays; Lists; Stacks; Queues; Dictionaries; Sets; Trees; Heaps; Graphs; The last word; Other Books You May Enjoy; Index

Jamro, Marcin. C# Data Structures and Algorithms [[electronic resource] :] : Explore the possibilities of C# for developing a variety of efficient applications. / Marcin. Jamro, 2018. - 1 online resource (287 p.) с. (Введено оглавление)

DDC 006.37
E 76
Escrivá, David Millán.
    OpenCV 4 Computer Vision Application Programming Cookbook. / David Millán. Escrivá, Laganiere, Robert. - [Place of publication not identified] : : 2019., Б. г. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/B700133F-76C9-4D0F-8FD1-3B8A0D362E98. - ISBN 9781789345285 (electronic bk.). - ISBN 1789345286 (electronic bk.)
Vendor-supplied metadata.
Параллельные издания: Print version: : Millán Escrivá, David. OpenCV 4 Computer Vision Application Programming Cookbook : Build Complex Computer Vision Applications with OpenCV and C++, 4th Edition. - Birmingham : Packt Publishing, Limited, ©2019. - ISBN 9781789340723
    Содержание:
Cover; Title Page; Copyright and Credits; About Packt; Contributors; Table of Contents; Preface; Chapter 1: Playing with Images; Installing the OpenCV library; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Using Qt for OpenCV developments; The OpenCV developer site; See also; Loading, displaying, and saving images; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Clicking on images; Drawing on images; Running the example with Qt; See also; Exploring the cv::Mat data structure; How to do it ... ; How it works ... ; There's more ... ; The input and output arrays
See alsoDefining regions of interest; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Using image masks; See also; Chapter 2: Manipulating the Pixels; Accessing pixel values; Getting ready; How to do it ... ; How it works ... ; There's more ... ; The cv::Mat_ template class; See also; Scanning an image with pointers; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Other color reduction formulas; Having input and output arguments; Efficient scanning of continuous images; Low-level pointer arithmetics; See also; Scanning an image with iterators; Getting ready
How to do it ... How it works ... ; There's more ... ; See also; Writing efficient image-scanning loops; How to do it ... ; How it works ... ; There's more ... ; See also; Scanning an image with neighbor access; Getting ready; How to do it ... ; How it works ... ; There's more ... ; See also; Performing simple image arithmetic; Getting ready; How to do it ... ; How it works ... ; There's more ... ; Overloaded image operators; Splitting the image channels; Remapping an image; How to do it ... ; How it works ... ; See also; Chapter 3: Processing Color Images with Classes; Comparing colors using the strategy design pattern
How to do it ... How it works ... ; There's more ... ; Computing the distance between two color vectors; Using OpenCV functions; The functor or function object; The OpenCV base class for algorithms; See also; Segmenting an image with the GrabCut algorithm; How to do it ... ; How it works ... ; See also; Converting color representations; Getting ready; How to do it ... ; How it works ... ; See also; Representing colors with hue, saturation, and brightness; How to do it ... ; How it works ... ; There's more ... ; Using colors for detection -- skin tone detection; Chapter 4: Counting the Pixels with Histograms
Computing the image histogramGetting started; How to do it ... ; How it works ... ; There's more ... ; Computing histograms of color images; See also; Applying lookup tables to modify the image's appearance; How to do it ... ; How it works ... ; There's more ... ; Stretching a histogram to improve the image contrast; Applying a lookup table on color images; Equalizing the image histogram; How to do it ... ; How it works ... ; Backprojecting a histogram to detect specific image content; How to do it ... ; How it works ... ; There's more ... ; Backprojecting color histograms

Escrivá, David Millán. OpenCV 4 Computer Vision Application Programming Cookbook. [Электронный ресурс] / David Millán. Escrivá, Laganiere, Robert. - 1 online resource. с. (Введено оглавление)

DDC 468
O-45
Oliva, Miguel A. Aijón,
    Constructing us : : the first and second persons in Spanish media discourse / / Miguel A. Aijón Oliva. - 1515/9783110643442. - Berlin : : De Gruyter,, ©2019. - 1 online resource ( час. мин.), 1515/9783110643442. - (Beihefte zur Zeitschrift für romanische Philologie ; ; 435). - In English. - Includes bibliographical references. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/1A3E403B-12A8-4FCD-9103-358B8F724F42. - ISBN 3110643448 (pdf). - ISBN 9783110635645 (electronic bk.). - ISBN 311063564X (electronic bk.). - ISBN 9783110640779 (epub). - ISBN 3110640775 (epub). - ISBN 9783110643442 (electronic bk.)
Print version record
Параллельные издания: Print version: : OLIVA, MIGUEL A. AIJN. CONSTRUCTING US. - [Place of publication not identified] : DE GRUYTER, 2019. - ISBN 311063564X
    Содержание:
Linguistic choice and the construction of meaning -- Variable grammar: the continuum of syntactic functions -- The first and second persons: discourse in grammar -- The singular first person: the speaker -- The plural first person: more than the speaker -- The singular second person: the addressee -- The plural second person: the audience -- The displaced second persons: addressees and audiences far away -- The construction of style across textual genres -- The construction of style across participant identities -- Conclusions -- References

Oliva, Miguel A. Aijón, Constructing us : [Электронный ресурс] : the first and second persons in Spanish media discourse / / Miguel A. Aijón Oliva, ©2019. - 1 online resource с. (Введено оглавление)

DDC 006.3015
F 25
Farrell, Peter, (1966-).
    The statistics and calculus workshop : a comprehensive introduction to mathematics in Python for artificial intelligence applications / / Peter Farrell [and five others]. - Birmingham : : Packt Publishing,, 2020. - 1 online resource. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/49180D55-AA15-4935-86A3-82CCF72C7E8B. - ISBN 9781800208360 (electronic book). - ISBN 1800208367 (electronic book)
Параллельные издания: Print version: :
    Содержание:
Cover -- FM -- Copyright -- Table of Contents -- Preface -- Chapter 1: Fundamentals of Python -- Introduction -- Control Flow Methods -- if Statements -- Exercise 1.01: Divisibility with Conditionals -- Loops -- The while Loop -- The for Loop -- Exercise 1.02: Number Guessing Game -- Data Structures -- Strings -- Lists -- Exercise 1.03: Multi-Dimensional Lists -- Tuples -- Sets -- Dictionaries -- Exercise 1.04: Shopping Cart Calculations -- Functions and Algorithms -- Functions -- Exercise 1.05: Finding the Maximum -- Recursion -- Exercise 1.06: The Tower of Hanoi -- Algorithm Design
Exercise 1.07: The N-Queens Problem -- Testing, Debugging, and Version Control -- Testing -- Debugging -- Exercise 1.08: Testing for Concurrency -- Version Control -- Exercise 1.09: Version Control with Git and GitHub -- Activity 1.01: Building a Sudoku Solver -- Summary -- Chapter 2: Python's Main Tools for Statistics -- Introduction -- Scientific Computing and NumPy Basics -- NumPy Arrays -- Vectorization -- Exercise 2.01: Timing Vectorized Operations in NumPy -- Random Sampling -- Working with Tabular Data in pandas -- Initializing a DataFrame Object -- Accessing Rows and Columns
Manipulating DataFrames -- Exercise 2.02: Data Table Manipulation -- Advanced Pandas Functionalities -- Exercise 2.03: The Student Dataset -- Data Visualization with Matplotlib and Seaborn -- Scatter Plots -- Line Graphs -- Bar Graphs -- Histograms -- Heatmaps -- Exercise 2.04: Visualization of Probability Distributions -- Visualization Shorthand from Seaborn and Pandas -- Activity 2.01: Analyzing the Communities and Crime Dataset -- Summary -- Chapter 3: Python's Statistical Toolbox -- Introduction -- An Overview of Statistics -- Types of Data in Statistics -- Categorical Data
Exercise 3.01: Visualizing Weather Percentages -- Numerical Data -- Exercise 3.02: Min-Max Scaling -- Ordinal Data -- Descriptive Statistics -- Central Tendency -- Dispersion -- Exercise 3.03: Visualizing Probability Density Functions -- Python-Related Descriptive Statistics -- Inferential Statistics -- T-Tests -- Correlation Matrix -- Exercise 3.04: Identifying and Testing Equality of Means -- Statistical and Machine Learning Models -- Exercise 3.05: Model Selection -- Python's Other Statistics Tools -- Activity 3.01: Revisiting the Communities and Crimes Dataset -- Summary
Chapter 4: Functions and Algebra with Python -- Introduction -- Functions -- Common Functions -- Domain and Range -- Function Roots and Equations -- The Plot of a Function -- Exercise 4.01: Function Identification from Plots -- Function Transformations -- Shifts -- Scaling -- Exercise 4.02: Function Transformation Identification -- Equations -- Algebraic Manipulations -- Factoring -- Using Python -- Exercise 4.03: Introduction to Break-Even Analysis -- Systems of Equations -- Systems of Linear Equations -- Exercise 4.04: Matrix Solution with NumPy -- Systems of Non-Linear Equations

Farrell, Peter,. The statistics and calculus workshop [Электронный ресурс] : a comprehensive introduction to mathematics in Python for artificial intelligence applications / / Peter Farrell [and five others]., 2020. - 1 online resource с. (Введено оглавление)

DDC 004.35
P 25
ParCo2019 ((2019 : ; Prague, Czech Republic),).
    Parallel computing : : technology trends / / edited by Ian Foster (Argonne National Laboratory and University of Chicago, Chicago, USA), Gerhard R. Joubert (Technical University Clausthal, Clausthal-Zellerfeld, Germany), Luděk Kučera (Charles University, Prague, Czech Republic), Wolfgang E. Nagel (Technical University Dresden, Dresden, Germany) and Frans Peters (formerly Philips Research, Eindhoven, Netherlands). - Amsterdam ; ; Washington, DC : : IOS Press,, ©2020. - 1 online resource (xvii, 785 pages). - (Advances in parallel computing, ; v. 36). - Includes bibliographical references and indexes. - URL: https://library.dvfu.ru/lib/document/SK_ELIB/FCC8F63F-3BB5-441E-BCF2-00CCA0051956. - ISBN 9781643680712 (electronic bk.). - ISBN 1643680714 (electronic bk.)
Conference: "ParCo2019, held in Prague, Czech Republic, from 10-13 September 2019, ..."--Back cover. Online resource; title from PDF title page (EBSCO, viewed July 6, 2020).
Параллельные издания: Print version: : Parallel computing. - Amsterdam : IOS Press, [2020]. - ISBN 9781643680705
    Содержание:
Intro -- Title Page -- Preface -- Conference Organisation -- Contents -- Opening -- Four Decades of Cluster Computing -- Invited Talks -- Will We Ever Have a Quantum Computer? -- Empowering Parallel Computing with Field Programmable Gate Arrays -- Main Track -- Deep Learning Applications -- First Experiences on Applying Deep Learning Techniques to Prostate Cancer Detection -- Deep Generative Model Driven Protein Folding Simulations -- Economics -- A Scalable Approach to Econometric Inference -- Cloud vs On-Premise HPC: A Model for Comprehensive Cost Assessment -- GPU Computing Methods
GPU Architecture for Wavelet-Based Video Coding Acceleration -- GPGPU Computing for Microscopic Pedestrian Simulation -- High Performance Eigenvalue Solver for Hubbard Model: Tuning Strategies for LOBPCG Method on CUDA GPU -- Parallel Smoothers in Multigrid Method for Heterogeneous CPU-GPU Environment -- Load Balancing Methods -- Progressive Load Balancing in Distributed Memory. Mitigating Performance and Progress Variability in Iterative Asynchronous Algorithms -- Learning-Based Load Balancing for Massively Parallel Simulations of Hot Fusion Plasmas
Load-Balancing for Large-Scale Soot Particle Agglomeration Simulations -- On the Autotuning of Task-Based Numerical Libraries for Heterogeneous Architectures -- Parallel Algorithms -- Batched 3D-Distributed FFT Kernels Towards Practical DNS Codes -- On Superlinear Speedups of a Parallel NFA Induction Algorithm -- A Domain Decomposition Reduced Order Model with Data Assimilation (DD-RODA) -- Predicting Performance of Classical and Modified BiCGStab Iterative Methods -- Parallel Applications -- Gadget3 on GPUs with OpenACC -- Exploring High Bandwidth Memory for PET Image Reconstruction
Parallel Architecture -- The Architecture of Heterogeneous Petascale HPC RIVR -- Design of an FPGA-Based Matrix Multiplier with Task Parallelism -- Application Performance of Physical System Simulations -- Parallel Methods -- A Hybrid MPI+Threads Approach to Particle Group Finding Using Union-Find -- Parallel Performance -- Improving the Scalability of the ABCD Solver with a Combination of New Load Balancing and Communication Minimization Techniques -- Characterization of Power Usage and Performance in Data-Intensive Applications Using MapReduce over MPI
Feedback-Driven Performance and Precision Tuning for Automatic Fixed Point Exploitation -- Parallel Programming -- A GPU-CUDA Framework for Solving a Two-Dimensional Inverse Anomalous Diffusion Problem -- Parallelization Strategies for GPU-Based Ant Colony Optimization Applied to TSP -- DBCSR: A Blocked Sparse Tensor Algebra Library -- Acceleration of Hydro Poro-Elastic Damage Simulation in a Shared-Memory Environment -- BERTHA and PyBERTHA: State of the Art for Full Four-Component Dirac-Kohn-Sham Calculations -- Prediction-Based Partitions Evaluation Algorithm for Resource Allocation

Parallel computing : [Электронный ресурс] : technology trends / / edited by Ian Foster (Argonne National Laboratory and University of Chicago, Chicago, USA), Gerhard R. Joubert (Technical University Clausthal, Clausthal-Zellerfeld, Germany), Luděk Kučera (Charles University, Prague, Czech Republic), Wolfgang E. Nagel (Technical University Dresden, Dresden, Germany) and Frans Peters (formerly Philips Research, Eindhoven, Netherlands)., ©2020. - 1 online resource (xvii, 785 pages) с. (Введено оглавление)