Havlin
•
0 likes•657 views
1) Theoretical physics theories are more valid if they can predict new phenomena that can be tested, rather than just explaining existing phenomena. 2) The document presents three examples from network science that demonstrate both explanation and prediction: (i) predicting epidemic spreading, (ii) predicting abrupt breakdown of interconnected networks, and (iii) predicting El Niño events. 3) Research on coupled networks found that the robustness of interconnected networks decreases abruptly rather than continuously as networks become more complex, moving from a second-order transition to a first-order transition with cascading failures.
Report
Share
Report
Share
Download to read offline
Recommended
Basics Of Neural Network Analysis
This document provides an overview of neural network analysis, including what neural networks are, their advantages and disadvantages, and two common types - multilayer perceptron and Kohonen networks. It describes how neural networks are trained using cases with input and output data, and how the network parameters are adjusted during training to best fit the data. The training process involves using a portion of cases for training, another portion for verification, and the remainder for testing the network.
Modeling Stochasticity and Gap Junction Dynamics: Integrate and Fire Model
In this presentation, we describe a mathematical model for modeling the stochasticity of firing neurons based on a modified integrate and fire model that incorporates gap junction potential.
Perceptron algorithm
The document discusses the perceptron algorithm, which is a simple neural network used for binary classification. It was invented in 1957 and works by computing weighted inputs and applying a threshold activation function. The perceptron learns by adjusting its weights during the training process. It is computationally efficient but can only learn linearly separable problems and not more complex nonlinear relationships.
Integrate and Fire based neuron model
This gives a brief introduction to integrate and Fire neuron model and one of it's variant simulation
Neural Networks and Deep Learning: An Intro
This document provides an overview of neural networks and deep learning. It describes how artificial neurons are arranged in layers to form feedforward neural networks, with information fed from the input layer to subsequent hidden and output layers. Networks are trained using gradient descent to adjust weights between layers to minimize error. Convolutional neural networks are also discussed, which apply convolution and pooling operations to process visual inputs like images for tasks such as image classification. CNNs have achieved success in applications involving computer vision, natural language processing, and more.
Adaptive Resonance Theory
This presentation gives brief overview of adaptive resonance theory, it's structure, working and uses.
AINL 2016: Skornyakov
This document describes a neural network model for detecting paraphrases. It discusses the dataset used, which contains pairs of news headlines labeled as paraphrases or not. Various feature engineering techniques are explored, including different ways of transforming text into sequences and calculating distances between the sequences. Evaluation is done using cross-validation and on the public leaderboard. Results show the model performs similarly on standard and non-standard feature sets, indicating the optimal choice of features is more important than the number of features.
Recurrent Neural Network Wavefunctions
March meeting presentation 2020
You can check out the article online for more details: https://arxiv.org/abs/2002.02973
Abstract: A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has precipitated many spectacular advances in natural language processing and neural machine translation. This architecture also makes a good candidate for a variational wavefunction, where the RNN parameters are tuned to learn the approximate ground state of a quantum Hamiltonian. In this paper, we demonstrate the ability of RNNs to represent several many-body wavefunctions, optimizing the variational parameters using a stochastic approach. Among other attractive features of these variational wavefunctions, their autoregressive nature allows for the efficient calculation of physical estimators by providing perfectly uncorrelated samples. We demonstrate the effectiveness of RNN wavefunctions by calculating ground state energies, correlation functions, and entanglement entropies for several quantum spin models of interest to condensed matter physicists in one and two spatial dimensions.
Recommended
Basics Of Neural Network Analysis
This document provides an overview of neural network analysis, including what neural networks are, their advantages and disadvantages, and two common types - multilayer perceptron and Kohonen networks. It describes how neural networks are trained using cases with input and output data, and how the network parameters are adjusted during training to best fit the data. The training process involves using a portion of cases for training, another portion for verification, and the remainder for testing the network.
Modeling Stochasticity and Gap Junction Dynamics: Integrate and Fire Model
In this presentation, we describe a mathematical model for modeling the stochasticity of firing neurons based on a modified integrate and fire model that incorporates gap junction potential.
Perceptron algorithm
The document discusses the perceptron algorithm, which is a simple neural network used for binary classification. It was invented in 1957 and works by computing weighted inputs and applying a threshold activation function. The perceptron learns by adjusting its weights during the training process. It is computationally efficient but can only learn linearly separable problems and not more complex nonlinear relationships.
Integrate and Fire based neuron model
This gives a brief introduction to integrate and Fire neuron model and one of it's variant simulation
Neural Networks and Deep Learning: An Intro
This document provides an overview of neural networks and deep learning. It describes how artificial neurons are arranged in layers to form feedforward neural networks, with information fed from the input layer to subsequent hidden and output layers. Networks are trained using gradient descent to adjust weights between layers to minimize error. Convolutional neural networks are also discussed, which apply convolution and pooling operations to process visual inputs like images for tasks such as image classification. CNNs have achieved success in applications involving computer vision, natural language processing, and more.
Adaptive Resonance Theory
This presentation gives brief overview of adaptive resonance theory, it's structure, working and uses.
AINL 2016: Skornyakov
This document describes a neural network model for detecting paraphrases. It discusses the dataset used, which contains pairs of news headlines labeled as paraphrases or not. Various feature engineering techniques are explored, including different ways of transforming text into sequences and calculating distances between the sequences. Evaluation is done using cross-validation and on the public leaderboard. Results show the model performs similarly on standard and non-standard feature sets, indicating the optimal choice of features is more important than the number of features.
Recurrent Neural Network Wavefunctions
March meeting presentation 2020
You can check out the article online for more details: https://arxiv.org/abs/2002.02973
Abstract: A core technology that has emerged from the artificial intelligence revolution is the recurrent neural network (RNN). Its unique sequence-based architecture provides a tractable likelihood estimate with stable training paradigms, a combination that has precipitated many spectacular advances in natural language processing and neural machine translation. This architecture also makes a good candidate for a variational wavefunction, where the RNN parameters are tuned to learn the approximate ground state of a quantum Hamiltonian. In this paper, we demonstrate the ability of RNNs to represent several many-body wavefunctions, optimizing the variational parameters using a stochastic approach. Among other attractive features of these variational wavefunctions, their autoregressive nature allows for the efficient calculation of physical estimators by providing perfectly uncorrelated samples. We demonstrate the effectiveness of RNN wavefunctions by calculating ground state energies, correlation functions, and entanglement entropies for several quantum spin models of interest to condensed matter physicists in one and two spatial dimensions.
Aps tutorial 2011_yulin_chen
This document provides a tutorial on direct probing of the electronic structures of topological insulators using angle-resolved photoemission spectroscopy (ARPES). It begins with an introduction to topological insulators and their unique surface state properties. It then discusses how ARPES can be used as a k-space microscope to visualize electronic band structures and distinguish bulk and surface states. The document concludes by showcasing recent ARPES results revealing the topological insulator state in the material Bi2Te3.
Kent_2007
This document summarizes a presentation given by Mikhail Kopytine at Kent State University on April 10, 2007 about recent developments in relativistic heavy ion collision experiments at RHIC. The presentation covered the motivation for studying Au+Au collisions at RHIC, which aim to recreate and study the quark-gluon plasma phase of quantum chromodynamics. It discussed theoretical approaches to modeling the quark-gluon plasma and experimental strategies at RHIC experiments like STAR and PHENIX. Key diagnostics discussed included perturbative probes like high pT particles and collective flow measurements.
Precision Electroweak Experiments with Leptons and Nuclei
Invited plenary presentation at the Lepton Photon 2017 conference at Sun Yat-Sen University in Guangzhou, China.
004
1. The document discusses gamma-ray pre-equilibrium emission from 40Ca+48Ca and 40Ca+46Ti collisions at energies ranging from 10-25 MeV/A.
2. CoMD calculations are able to provide a unified description of pre-equilibrium phenomena by evaluating the average fluctuating dynamics.
3. The parameter φch, which represents the ratio between average and fluctuating dynamics, is found to change rapidly when multifragmentation processes occur, indicating a change in the fundamental properties of hot reaction sources.
004
1. The document discusses gamma-ray pre-equilibrium emission from 40Ca+48Ca and 40Ca+46Ti collisions at energies ranging from 10-25 MeV/A.
2. CoMD calculations are able to provide a unified description of pre-equilibrium phenomena by evaluating the average fluctuating dynamics.
3. The parameter φch, which represents the ratio between average and fluctuating dynamics, is found to change rapidly when multifragmentation processes occur, indicating a change in the fundamental properties of hot reaction sources.
Lecture 3: Fundamental Limitations of Solar Cells
Key Question: Why can't a solar cell convert incident light into electrical power with 100% efficiency.
Report
This document summarizes a research project that involves building a toy model of particle collisions using C++ and ROOT. The model simulates collisions by sampling probability distributions measured in real collisions. It generates particles and assigns them properties like momentum and angle. It also models physical processes like jet production and elliptic flow. The goal is to study how properties of particles like jets are affected by a quark-gluon plasma and vice versa. The model allows tuning parameters to learn about collision interactions and switch physics processes on or off.
Power point slides_chapter_03
1) The document provides an overview of elementary quantum physics concepts including the photoelectric effect, blackbody radiation, quantum tunneling, the hydrogen atom model, electron spin, and selection rules for photon emission and absorption.
2) Key topics covered include Planck's quantization of energy, De Broglie's matter waves, Heisenberg's uncertainty principle, Schrodinger's equation, and the quantization of angular momentum.
3) Experiments are described that provided evidence for the quantum nature of light and matter, including the photoelectric effect, Compton scattering, electron diffraction, and scanning tunneling microscopy.
Visualizing Radiation Physics Concepts with photon electron particle tracks
This document describes advanced computer simulation and visualization tools to enhance understanding of core medical physics concepts. It presents two tools: 1) A Monte Carlo code called Athena that explicitly visualizes radiation physics processes to illustrate their connection to clinical physics. 2) A particle simulator that models particles in electromagnetic fields to illustrate devices like linear accelerators. The tools help elucidate physics by breaking processes into layers, develop physical insight, and reduce commissioning errors for safer patient treatment.
Introduction to Modern Methods and Tools for Biologically Plausible Modelling...
This document provides an overview of modern methods and tools for biologically plausible modeling of neural structures in the brain. It discusses modeling at different levels, from the system level looking at the brain as a whole, down to the subcellular and molecular levels examining individual neurons and ion channels. At each level, it outlines key research methods used to study the brain experimentally and different modeling approaches, including population and dynamical models, formal neural networks, and detailed single-cell models. The document also reviews seminal work in neuroscience like Hodgkin and Huxley's equations for modeling ion channel dynamics and spike generation in neurons.
Further discriminatory signature of inflation
These are the slides of the talk I gave on discriminating between models of inflation using space based gravitational wave detectors, at KEK in Tskuba University, Japan.
NNBAR SESAPS PRESENTATION FINAL
1) DUNE aims to resolve the matter-antimatter asymmetry by searching for neutron-antineutron oscillations, a baryon number violating process.
2) Simulations of atmospheric neutrino backgrounds that could mimic the signal are underway using GENIE to determine the viability of detecting oscillations above background levels.
3) If viable, the analysis will consider effects of cosmogenic muons and fast neutrons, with generators for neutron-antineutron interactions in argon under construction.
Neutron Skin Measurements at Mainz
Extract of a longer presentation on the neutron skin measurement program at the Institute of Nuclear Physics, Mainz (Germany)
DIAS
1) The document discusses the history and current state of dark matter research, from early evidence from galaxy rotation curves and galaxy cluster masses to modern direct detection experiments.
2) The DarkSide collaboration is running the DarkSide-50 experiment at Gran Sasso laboratory to directly detect dark matter using an underground liquid argon time projection chamber.
3) Future experiments like DarkSide-20k aim to reach the "neutrino floor" and probe dark matter candidates down to neutrino interaction cross sections over the next decade.
Serie de dyson
This document reviews research on the convergence of perturbation series in quantum field theory. It discusses Dyson's argument that perturbation series in quantum electrodynamics (QED) have zero radius of convergence due to vacuum instability when the coupling constant is negative. Large-order estimates show that perturbation series coefficients grow factorially fast in quantum mechanics and field theories. Finally, it describes the method of Borel summation, which may allow extracting the exact physical quantity from a divergent perturbation series through a unique mapping.
Computational Spectroscopy in G03
Tutorial in calculation of IR & NMR spectra (i.e. measuring nuclear vibrations and spins) using the GAUSSIAN03 computational chemistry package.
Following an introduction to spectroscopy in general, each of the two measurement types is presented in sequence. For each one, we review the theory before presenting the calculation scheme. We then present the relative strengths and limitations (with respect to other measurements), and then compare the calculation method with experimentation. We close each of the two subjects with an advanced topic: Raman IR spectroscopy (and depolarization ratio), and indirect dipole coupling (a.k.a. spin-spin coupling). I've also made the last part available as a standalone presentation: http://www.slideshare.net/InonSharony/nmr-spinspin-splitting-using-gaussian03.
Vibration energy harvesting under uncertainty
The document summarizes research on vibration energy harvesting under uncertainty. It discusses piezoelectric energy harvesting using cantilever beams and focuses on harvesting from single frequencies at resonance. It notes that most previous work assumes certain input but uncertainty exists in real environments. The document outlines sources of uncertainty in excitation and system parameters and presents linear and nonlinear models of piezoelectric energy harvesters. It transforms models into the frequency domain to analyze optimal harvester design under Gaussian excitation without an inductor.
Searches with LHC
The document summarizes potential discoveries at the LHC beyond the Standard Model. It discusses:
1) Searches for new constituents like excited neutrinos that may appear as single particles produced via Z, W, or gamma decays.
2) Searches for new quark singlets with charges of -1/3 that could be discovered if pair produced and decaying to bosons and jets.
3) Searches for new up-type quark doublets that could be discovered if pair produced and decaying to W bosons and jets. The document outlines possible mass ranges and luminosities needed for discovery.
4) It notes how new quark discoveries could enhance the search for the Higgs boson
Chemical dynamics and rare events in soft matter physics
Talk for the Trinity Math Society Symposium. First summarises the approximations leading from Dirac equation to molecular description and then the synthesis towards non-equilibrium statistical mechanics. The relaxation approach to projection of a molecular system to a Markov jump process is discussed.
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
More Related Content
Similar to Havlin
Aps tutorial 2011_yulin_chen
This document provides a tutorial on direct probing of the electronic structures of topological insulators using angle-resolved photoemission spectroscopy (ARPES). It begins with an introduction to topological insulators and their unique surface state properties. It then discusses how ARPES can be used as a k-space microscope to visualize electronic band structures and distinguish bulk and surface states. The document concludes by showcasing recent ARPES results revealing the topological insulator state in the material Bi2Te3.
Kent_2007
This document summarizes a presentation given by Mikhail Kopytine at Kent State University on April 10, 2007 about recent developments in relativistic heavy ion collision experiments at RHIC. The presentation covered the motivation for studying Au+Au collisions at RHIC, which aim to recreate and study the quark-gluon plasma phase of quantum chromodynamics. It discussed theoretical approaches to modeling the quark-gluon plasma and experimental strategies at RHIC experiments like STAR and PHENIX. Key diagnostics discussed included perturbative probes like high pT particles and collective flow measurements.
Precision Electroweak Experiments with Leptons and Nuclei
Invited plenary presentation at the Lepton Photon 2017 conference at Sun Yat-Sen University in Guangzhou, China.
004
1. The document discusses gamma-ray pre-equilibrium emission from 40Ca+48Ca and 40Ca+46Ti collisions at energies ranging from 10-25 MeV/A.
2. CoMD calculations are able to provide a unified description of pre-equilibrium phenomena by evaluating the average fluctuating dynamics.
3. The parameter φch, which represents the ratio between average and fluctuating dynamics, is found to change rapidly when multifragmentation processes occur, indicating a change in the fundamental properties of hot reaction sources.
004
1. The document discusses gamma-ray pre-equilibrium emission from 40Ca+48Ca and 40Ca+46Ti collisions at energies ranging from 10-25 MeV/A.
2. CoMD calculations are able to provide a unified description of pre-equilibrium phenomena by evaluating the average fluctuating dynamics.
3. The parameter φch, which represents the ratio between average and fluctuating dynamics, is found to change rapidly when multifragmentation processes occur, indicating a change in the fundamental properties of hot reaction sources.
Lecture 3: Fundamental Limitations of Solar Cells
Key Question: Why can't a solar cell convert incident light into electrical power with 100% efficiency.
Report
This document summarizes a research project that involves building a toy model of particle collisions using C++ and ROOT. The model simulates collisions by sampling probability distributions measured in real collisions. It generates particles and assigns them properties like momentum and angle. It also models physical processes like jet production and elliptic flow. The goal is to study how properties of particles like jets are affected by a quark-gluon plasma and vice versa. The model allows tuning parameters to learn about collision interactions and switch physics processes on or off.
Power point slides_chapter_03
1) The document provides an overview of elementary quantum physics concepts including the photoelectric effect, blackbody radiation, quantum tunneling, the hydrogen atom model, electron spin, and selection rules for photon emission and absorption.
2) Key topics covered include Planck's quantization of energy, De Broglie's matter waves, Heisenberg's uncertainty principle, Schrodinger's equation, and the quantization of angular momentum.
3) Experiments are described that provided evidence for the quantum nature of light and matter, including the photoelectric effect, Compton scattering, electron diffraction, and scanning tunneling microscopy.
Visualizing Radiation Physics Concepts with photon electron particle tracks
This document describes advanced computer simulation and visualization tools to enhance understanding of core medical physics concepts. It presents two tools: 1) A Monte Carlo code called Athena that explicitly visualizes radiation physics processes to illustrate their connection to clinical physics. 2) A particle simulator that models particles in electromagnetic fields to illustrate devices like linear accelerators. The tools help elucidate physics by breaking processes into layers, develop physical insight, and reduce commissioning errors for safer patient treatment.
Introduction to Modern Methods and Tools for Biologically Plausible Modelling...
This document provides an overview of modern methods and tools for biologically plausible modeling of neural structures in the brain. It discusses modeling at different levels, from the system level looking at the brain as a whole, down to the subcellular and molecular levels examining individual neurons and ion channels. At each level, it outlines key research methods used to study the brain experimentally and different modeling approaches, including population and dynamical models, formal neural networks, and detailed single-cell models. The document also reviews seminal work in neuroscience like Hodgkin and Huxley's equations for modeling ion channel dynamics and spike generation in neurons.
Further discriminatory signature of inflation
These are the slides of the talk I gave on discriminating between models of inflation using space based gravitational wave detectors, at KEK in Tskuba University, Japan.
NNBAR SESAPS PRESENTATION FINAL
1) DUNE aims to resolve the matter-antimatter asymmetry by searching for neutron-antineutron oscillations, a baryon number violating process.
2) Simulations of atmospheric neutrino backgrounds that could mimic the signal are underway using GENIE to determine the viability of detecting oscillations above background levels.
3) If viable, the analysis will consider effects of cosmogenic muons and fast neutrons, with generators for neutron-antineutron interactions in argon under construction.
Neutron Skin Measurements at Mainz
Extract of a longer presentation on the neutron skin measurement program at the Institute of Nuclear Physics, Mainz (Germany)
DIAS
1) The document discusses the history and current state of dark matter research, from early evidence from galaxy rotation curves and galaxy cluster masses to modern direct detection experiments.
2) The DarkSide collaboration is running the DarkSide-50 experiment at Gran Sasso laboratory to directly detect dark matter using an underground liquid argon time projection chamber.
3) Future experiments like DarkSide-20k aim to reach the "neutrino floor" and probe dark matter candidates down to neutrino interaction cross sections over the next decade.
Serie de dyson
This document reviews research on the convergence of perturbation series in quantum field theory. It discusses Dyson's argument that perturbation series in quantum electrodynamics (QED) have zero radius of convergence due to vacuum instability when the coupling constant is negative. Large-order estimates show that perturbation series coefficients grow factorially fast in quantum mechanics and field theories. Finally, it describes the method of Borel summation, which may allow extracting the exact physical quantity from a divergent perturbation series through a unique mapping.
Computational Spectroscopy in G03
Tutorial in calculation of IR & NMR spectra (i.e. measuring nuclear vibrations and spins) using the GAUSSIAN03 computational chemistry package.
Following an introduction to spectroscopy in general, each of the two measurement types is presented in sequence. For each one, we review the theory before presenting the calculation scheme. We then present the relative strengths and limitations (with respect to other measurements), and then compare the calculation method with experimentation. We close each of the two subjects with an advanced topic: Raman IR spectroscopy (and depolarization ratio), and indirect dipole coupling (a.k.a. spin-spin coupling). I've also made the last part available as a standalone presentation: http://www.slideshare.net/InonSharony/nmr-spinspin-splitting-using-gaussian03.
Vibration energy harvesting under uncertainty
The document summarizes research on vibration energy harvesting under uncertainty. It discusses piezoelectric energy harvesting using cantilever beams and focuses on harvesting from single frequencies at resonance. It notes that most previous work assumes certain input but uncertainty exists in real environments. The document outlines sources of uncertainty in excitation and system parameters and presents linear and nonlinear models of piezoelectric energy harvesters. It transforms models into the frequency domain to analyze optimal harvester design under Gaussian excitation without an inductor.
Searches with LHC
The document summarizes potential discoveries at the LHC beyond the Standard Model. It discusses:
1) Searches for new constituents like excited neutrinos that may appear as single particles produced via Z, W, or gamma decays.
2) Searches for new quark singlets with charges of -1/3 that could be discovered if pair produced and decaying to bosons and jets.
3) Searches for new up-type quark doublets that could be discovered if pair produced and decaying to W bosons and jets. The document outlines possible mass ranges and luminosities needed for discovery.
4) It notes how new quark discoveries could enhance the search for the Higgs boson
Chemical dynamics and rare events in soft matter physics
Talk for the Trinity Math Society Symposium. First summarises the approximations leading from Dirac equation to molecular description and then the synthesis towards non-equilibrium statistical mechanics. The relaxation approach to projection of a molecular system to a Markov jump process is discussed.
Similar to Havlin (20)
Precision Electroweak Experiments with Leptons and Nuclei
Precision Electroweak Experiments with Leptons and Nuclei
Visualizing Radiation Physics Concepts with photon electron particle tracks
Visualizing Radiation Physics Concepts with photon electron particle tracks
Introduction to Modern Methods and Tools for Biologically Plausible Modelling...
Introduction to Modern Methods and Tools for Biologically Plausible Modelling...
Chemical dynamics and rare events in soft matter physics
Chemical dynamics and rare events in soft matter physics
Recently uploaded
Building Production Ready Search Pipelines with Spark and Milvus
Spark is the widely used ETL tool for processing, indexing and ingesting data to serving stack for search. Milvus is the production-ready open-source vector database. In this talk we will show how to use Spark to process unstructured data to extract vector representations, and push the vectors to Milvus vector database for search serving.
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on integration of Salesforce with Bonterra Impact Management.
Interested in deploying an integration with Salesforce for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Are you ready to revolutionize how you handle data? Join us for a webinar where we’ll bring you up to speed with the latest advancements in Generative AI technology and discover how leveraging FME with tools from giants like Google Gemini, Amazon, and Microsoft OpenAI can supercharge your workflow efficiency.
During the hour, we’ll take you through:
Guest Speaker Segment with Hannah Barrington: Dive into the world of dynamic real estate marketing with Hannah, the Marketing Manager at Workspace Group. Hear firsthand how their team generates engaging descriptions for thousands of office units by integrating diverse data sources—from PDF floorplans to web pages—using FME transformers, like OpenAIVisionConnector and AnthropicVisionConnector. This use case will show you how GenAI can streamline content creation for marketing across the board.
Ollama Use Case: Learn how Scenario Specialist Dmitri Bagh has utilized Ollama within FME to input data, create custom models, and enhance security protocols. This segment will include demos to illustrate the full capabilities of FME in AI-driven processes.
Custom AI Models: Discover how to leverage FME to build personalized AI models using your data. Whether it’s populating a model with local data for added security or integrating public AI tools, find out how FME facilitates a versatile and secure approach to AI.
We’ll wrap up with a live Q&A session where you can engage with our experts on your specific use cases, and learn more about optimizing your data workflows with AI.
This webinar is ideal for professionals seeking to harness the power of AI within their data management systems while ensuring high levels of customization and security. Whether you're a novice or an expert, gain actionable insights and strategies to elevate your data processes. Join us to see how FME and AI can revolutionize how you work with data!
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
A Mix Chart displays historical data of numbers in a graphical or tabular form. The Kalyan Rajdhani Mix Chart specifically shows the results of a sequence of numbers over different periods.
Operating System Used by Users in day-to-day life.pptx
Dive into the realm of operating systems (OS) with Pravash Chandra Das, a seasoned Digital Forensic Analyst, as your guide. 🚀 This comprehensive presentation illuminates the core concepts, types, and evolution of OS, essential for understanding modern computing landscapes.
Beginning with the foundational definition, Das clarifies the pivotal role of OS as system software orchestrating hardware resources, software applications, and user interactions. Through succinct descriptions, he delineates the diverse types of OS, from single-user, single-task environments like early MS-DOS iterations, to multi-user, multi-tasking systems exemplified by modern Linux distributions.
Crucial components like the kernel and shell are dissected, highlighting their indispensable functions in resource management and user interface interaction. Das elucidates how the kernel acts as the central nervous system, orchestrating process scheduling, memory allocation, and device management. Meanwhile, the shell serves as the gateway for user commands, bridging the gap between human input and machine execution. 💻
The narrative then shifts to a captivating exploration of prominent desktop OSs, Windows, macOS, and Linux. Windows, with its globally ubiquitous presence and user-friendly interface, emerges as a cornerstone in personal computing history. macOS, lauded for its sleek design and seamless integration with Apple's ecosystem, stands as a beacon of stability and creativity. Linux, an open-source marvel, offers unparalleled flexibility and security, revolutionizing the computing landscape. 🖥️
Moving to the realm of mobile devices, Das unravels the dominance of Android and iOS. Android's open-source ethos fosters a vibrant ecosystem of customization and innovation, while iOS boasts a seamless user experience and robust security infrastructure. Meanwhile, discontinued platforms like Symbian and Palm OS evoke nostalgia for their pioneering roles in the smartphone revolution.
The journey concludes with a reflection on the ever-evolving landscape of OS, underscored by the emergence of real-time operating systems (RTOS) and the persistent quest for innovation and efficiency. As technology continues to shape our world, understanding the foundations and evolution of operating systems remains paramount. Join Pravash Chandra Das on this illuminating journey through the heart of computing. 🌟
Introduction of Cybersecurity with OSS at Code Europe 2024
I develop the Ruby programming language, RubyGems, and Bundler, which are package managers for Ruby. Today, I will introduce how to enhance the security of your application using open-source software (OSS) examples from Ruby and RubyGems.
The first topic is CVE (Common Vulnerabilities and Exposures). I have published CVEs many times. But what exactly is a CVE? I'll provide a basic understanding of CVEs and explain how to detect and handle vulnerabilities in OSS.
Next, let's discuss package managers. Package managers play a critical role in the OSS ecosystem. I'll explain how to manage library dependencies in your application.
I'll share insights into how the Ruby and RubyGems core team works to keep our ecosystem safe. By the end of this talk, you'll have a better understanding of how to safeguard your code.
Artificial Intelligence for XMLDevelopment
In the rapidly evolving landscape of technologies, XML continues to play a vital role in structuring, storing, and transporting data across diverse systems. The recent advancements in artificial intelligence (AI) present new methodologies for enhancing XML development workflows, introducing efficiency, automation, and intelligent capabilities. This presentation will outline the scope and perspective of utilizing AI in XML development. The potential benefits and the possible pitfalls will be highlighted, providing a balanced view of the subject.
We will explore the capabilities of AI in understanding XML markup languages and autonomously creating structured XML content. Additionally, we will examine the capacity of AI to enrich plain text with appropriate XML markup. Practical examples and methodological guidelines will be provided to elucidate how AI can be effectively prompted to interpret and generate accurate XML markup.
Further emphasis will be placed on the role of AI in developing XSLT, or schemas such as XSD and Schematron. We will address the techniques and strategies adopted to create prompts for generating code, explaining code, or refactoring the code, and the results achieved.
The discussion will extend to how AI can be used to transform XML content. In particular, the focus will be on the use of AI XPath extension functions in XSLT, Schematron, Schematron Quick Fixes, or for XML content refactoring.
The presentation aims to deliver a comprehensive overview of AI usage in XML development, providing attendees with the necessary knowledge to make informed decisions. Whether you’re at the early stages of adopting AI or considering integrating it in advanced XML development, this presentation will cover all levels of expertise.
By highlighting the potential advantages and challenges of integrating AI with XML development tools and languages, the presentation seeks to inspire thoughtful conversation around the future of XML development. We’ll not only delve into the technical aspects of AI-powered XML development but also discuss practical implications and possible future directions.
HCL Notes and Domino License Cost Reduction in the World of DLAU
Webinar Recording: https://www.panagenda.com/webinars/hcl-notes-and-domino-license-cost-reduction-in-the-world-of-dlau/
The introduction of DLAU and the CCB & CCX licensing model caused quite a stir in the HCL community. As a Notes and Domino customer, you may have faced challenges with unexpected user counts and license costs. You probably have questions on how this new licensing approach works and how to benefit from it. Most importantly, you likely have budget constraints and want to save money where possible. Don’t worry, we can help with all of this!
We’ll show you how to fix common misconfigurations that cause higher-than-expected user counts, and how to identify accounts which you can deactivate to save money. There are also frequent patterns that can cause unnecessary cost, like using a person document instead of a mail-in for shared mailboxes. We’ll provide examples and solutions for those as well. And naturally we’ll explain the new licensing model.
Join HCL Ambassador Marc Thomas in this webinar with a special guest appearance from Franz Walder. It will give you the tools and know-how to stay on top of what is going on with Domino licensing. You will be able lower your cost through an optimized configuration and keep it low going forward.
These topics will be covered
- Reducing license cost by finding and fixing misconfigurations and superfluous accounts
- How do CCB and CCX licenses really work?
- Understanding the DLAU tool and how to best utilize it
- Tips for common problem areas, like team mailboxes, functional/test users, etc
- Practical examples and best practices to implement right away
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for life science domain, where you retriever information from biomedical knowledge graphs using LLMs to increase the accuracy and performance of generated answers
AWS Cloud Cost Optimization Presentation.pptx
This presentation provides valuable insights into effective cost-saving techniques on AWS. Learn how to optimize your AWS resources by rightsizing, increasing elasticity, picking the right storage class, and choosing the best pricing model. Additionally, discover essential governance mechanisms to ensure continuous cost efficiency. Whether you are new to AWS or an experienced user, this presentation provides clear and practical tips to help you reduce your cloud costs and get the most out of your budget.
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Simplify your search for a reliable Python development partner! This list presents the top 10 trusted US providers offering comprehensive Python development services, ensuring your project's success from conception to completion.
Presentation of the OECD Artificial Intelligence Review of Germany
Consult the full report at https://www.oecd.org/digital/oecd-artificial-intelligence-review-of-germany-609808d6-en.htm
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
Predictive maintenance is a proactive approach that anticipates equipment failures before they happen. At the forefront of this innovative strategy is Artificial Intelligence (AI), which brings unprecedented precision and efficiency. AI in predictive maintenance is transforming industries by reducing downtime, minimizing costs, and enhancing productivity.
Generating privacy-protected synthetic data using Secludy and Milvus
During this demo, the founders of Secludy will demonstrate how their system utilizes Milvus to store and manipulate embeddings for generating privacy-protected synthetic data. Their approach not only maintains the confidentiality of the original data but also enhances the utility and scalability of LLMs under privacy constraints. Attendees, including machine learning engineers, data scientists, and data managers, will witness first-hand how Secludy's integration with Milvus empowers organizations to harness the power of LLMs securely and efficiently.
Columbus Data & Analytics Wednesdays - June 2024
Columbus Data & Analytics Wednesdays, June 2024 with Maria Copot 20
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Sidekick Solutions uses Bonterra Impact Management (fka Social Solutions Apricot) and automation solutions to integrate data for business workflows.
We believe integration and automation are essential to user experience and the promise of efficient work through technology. Automation is the critical ingredient to realizing that full vision. We develop integration products and services for Bonterra Case Management software to support the deployment of automations for a variety of use cases.
This video focuses on automated letter generation for Bonterra Impact Management using Google Workspace or Microsoft 365.
Interested in deploying letter generation automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Recently uploaded (20)
Building Production Ready Search Pipelines with Spark and Milvus
Building Production Ready Search Pipelines with Spark and Milvus
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Energy Efficient Video Encoding for Cloud and Edge Computing Instances
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Salesforce Integration for Bonterra Impact Management (fka Social Solutions A...
Driving Business Innovation: Latest Generative AI Advancements & Success Story
Driving Business Innovation: Latest Generative AI Advancements & Success Story
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
How to Interpret Trends in the Kalyan Rajdhani Mix Chart.pdf
WeTestAthens: Postman's AI & Automation Techniques
WeTestAthens: Postman's AI & Automation Techniques
Operating System Used by Users in day-to-day life.pptx
Operating System Used by Users in day-to-day life.pptx
Introduction of Cybersecurity with OSS at Code Europe 2024
Introduction of Cybersecurity with OSS at Code Europe 2024
HCL Notes and Domino License Cost Reduction in the World of DLAU
HCL Notes and Domino License Cost Reduction in the World of DLAU
GraphRAG for Life Science to increase LLM accuracy
GraphRAG for Life Science to increase LLM accuracy
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Your One-Stop Shop for Python Success: Top 10 US Python Development Providers
Presentation of the OECD Artificial Intelligence Review of Germany
Presentation of the OECD Artificial Intelligence Review of Germany
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
leewayhertz.com-AI in predictive maintenance Use cases technologies benefits ...
Generating privacy-protected synthetic data using Secludy and Milvus
Generating privacy-protected synthetic data using Secludy and Milvus
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Deep Dive: AI-Powered Marketing to Get More Leads and Customers with HyperGro...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Letter and Document Automation for Bonterra Impact Management (fka Social Sol...
Havlin
- 1. SHLOMO HAVLIN Bar-Ilan University Explain or Predict 1. Explaining and understanding a physical phenomena usually leads to predictions: Examples: the Higgs Boson, photo electric …. 2. Theory without predictions of new phenomena and the possibility of testing the predictions is usually not regarded as a valid theory! 3. I will present three examples from my current field: (i) Early predicting of epidemic spreading (ii) Abrupt breakdown of a system of systems represented as “network of networks” (iii) Early prediction of El-Nino events (Unpublished) Explain AND Predict
- 2. Based on theoretical paper of Cohen, Havlin and ben-Avraham, PRL 91, 247901 (2003)
- 4. Single and coupled networks: Robustness ER Remove randomly (or targeted) a fraction 1 − p nodes P∞ Size of the largest connected component (cluster) pc Breakdown threshold Giant component and breakdown thresholds are predicted 1 Single ER for these models P∞ = p[1 − exp(− k P∞ )] Coupled P∞ Single networks: Continuous abrupt Continuous transition Cascades, Sudden Coupled networks: breakdown New paradigm-Abrupt transition 0 0 pc p pc 1 Cascading Failures
- 5. Network of Networks (tree) n=5 For ER, ki = k full coupling , ALL loopless topologies (chain, star, tree): P∞ = p[1 − exp(− k P∞ )] n P∞ n=1 known ER- 2nd order n=1 n=5 pc = 1/ k n=2 Vulnerability increases significantly with n Buldyrev et al Nature (2010) Gao et al PRL (2011)