Paper Introduction: Combinatorial Model and Bounds for Target Set SelectionYu Liu
Ā
The paper Combinatorial Model and Bounds for Target Set Selection by Eyal Ackerman, Oren Ben-Zwi, Guy Wolfovitz:
1. a combinatorial model for the dynamic activation process of
influential networks;
2. representing Perfect Target Set Selection Problem and its
variants by linear integer programs;
3. combinatorial lower and upper bounds on the size of the
minimum Perfect Target Set
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijujournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical
methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work
piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard
formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations.
Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil
voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This
mathematical model is useful for coil design and optimization of induction heating process.
Paper Introduction: Combinatorial Model and Bounds for Target Set SelectionYu Liu
Ā
The paper Combinatorial Model and Bounds for Target Set Selection by Eyal Ackerman, Oren Ben-Zwi, Guy Wolfovitz:
1. a combinatorial model for the dynamic activation process of
influential networks;
2. representing Perfect Target Set Selection Problem and its
variants by linear integer programs;
3. combinatorial lower and upper bounds on the size of the
minimum Perfect Target Set
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijujournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic vector potential formulation is done and finite element method (FEM) is used to solve the field equations. Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil voltage, work piece power are compared and found that they are in good agreement. Analytically and numerically obtained coil voltages at different frequencies are validated by experimental results. This mathematical model is useful for coil design and optimization of induction heating process.
Analytical, Numerical and Experimental Validation of Coil Voltage in Inductio...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical
methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work
piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard
formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations.
Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil
voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This
mathematical model is useful for coil design and optimization of induction heating process.
In this work, we study Hā control wind turbine fuzzy model for finite frequency(FF) interval. Less conservative results are obtained by using Finslerās lemma technique, generalized Kalman Yakubovich Popov (gKYP), linear matrix inequality (LMI) approach and added several separate parameters, these conditions are given in terms of LMI which can be efficiently solved numerically for the problem that such fuzzy systems are admissible with Hā disturbance attenuation level. The FF Hā performance approach allows the state feedback command in a specific interval, the simulation example is given to validate our results.
Photophysical properties of light harvesting molecules: three different approaches (of increasing complexity and accuracy) to foresee the harvesting behaviour are reviewed with a highly didactic flow. Design principles are highlighted.
A supplementary document explaining the details is available among my uploads.
This set of slides collects a self-made research I did for a photochemistry course. I don't own part of the shown material and references for many public images are collected at the end of the presentation.
A Generalized Sampling Theorem Over Galois Field Domains for Experimental Des...csandit
Ā
In this paper, the sampling theorem for bandlimited functions over
domains is
generalized to one over ā
domains. The generalized theorem is applicable to the
experimental design model in which each factor has a different number of levels and enables us
to estimate the parameters in the model by using Fourier transforms. Moreover, the relationship
between the proposed sampling theorem and orthogonal arrays is also provided.
KEY
(If visualization is slow, please try downloading the file.)
Part 2 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
Transformations of continuous-variable entangled states of lightOndrej Cernotik
Ā
Gaussian states and Gaussian transformations represent an interesting counterpart to two-level photonic systems in the field of quantum information processing. On the theoretical side, Gaussian states are easily described using first and second moments of the quadrature operators; from the experimental point of view, Gaussian operations can be implemented using linear optics and optical parametric amplifiers. The biggest advantage compared to two-level photonic systems, is deterministic generation of entangled states in parametric amplifiers and highly efficient homodyne detection. In this presentation, we propose new protocols for manipulation of entanglement of Gaussian states.
Firstly, we study entanglement concentration of split single-mode squeezed vacuum states by photon subtraction enhanced by local coherent displacements. These states can be obtained by mixing a single-mode squeezed vacuum state with vacuum on a beam splitter and are, therefore, generated more easily than two-mode squeezed vacuum states. We show that performing local coherent displacements prior to photon subtraction can lead to an enhancement of the output entanglement. This is seen in weak-squeezing approximation where destructive quantum interference of dominant Fock states occurs, while for arbitrarily squeezed input states, we analyze a realistic scenario, including limited transmittance of tap-off beam splitters and limited efficiency of heralding detectors.
Next, motivated by results obtained for bipartite Gaussian states, we study symmetrization of multipartite Gaussian states by local Gaussian operations. Namely, we analyze strategies based on addition of correlated noise and on quantum non-demolition interaction. We use fidelity of assisted quantum teleportation as a figure of merit to characterize entanglement of the state before and after the symmetrization procedure. Analyzing the teleportation protocol and considering more general transformations of multipartite Gaussian states, we show that the fidelity can be improved significantly.
Polynomial matrices can help to elegantly formulate many broadband multi-sensor / multi-channel processing problems, and represent a direct extension of well-established narrowband techniques which typically involve eigen- (EVD) and singular value decompositions (SVD) for optimisation. Polynomial matrix decompositions extend the utility of the EVD to polynomial parahermitian matrices, and this talk presents a brief overview of such polynomial matrices, characteristics of the polynomial EVD (PEVD) and iterative algorithms for its solution. The presentation concludes with some surprising results when applying the PEVD to subband coding and broadband beamforming.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Kinetic pathways to the isotropic-nematic phase transformation: a mean field ...Amit Bhattacharjee
Ā
Here we illustrate the classic Ginzburg-Landau-de Gennes theory of isotropic nematic phase transition and show how fluctuations as well as deterministic kinetics can lead to phase equilibria.
In this work, we study Hā control wind turbine fuzzy model for finite frequency(FF) interval. Less conservative results are obtained by using Finslerās lemma technique, generalized Kalman Yakubovich Popov (gKYP), linear matrix inequality (LMI) approach and added several separate parameters, these conditions are given in terms of LMI which can be efficiently solved numerically for the problem that such fuzzy systems are admissible with Hā disturbance attenuation level. The FF Hā performance approach allows the state feedback command in a specific interval, the simulation example is given to validate our results.
Photophysical properties of light harvesting molecules: three different approaches (of increasing complexity and accuracy) to foresee the harvesting behaviour are reviewed with a highly didactic flow. Design principles are highlighted.
A supplementary document explaining the details is available among my uploads.
This set of slides collects a self-made research I did for a photochemistry course. I don't own part of the shown material and references for many public images are collected at the end of the presentation.
A Generalized Sampling Theorem Over Galois Field Domains for Experimental Des...csandit
Ā
In this paper, the sampling theorem for bandlimited functions over
domains is
generalized to one over ā
domains. The generalized theorem is applicable to the
experimental design model in which each factor has a different number of levels and enables us
to estimate the parameters in the model by using Fourier transforms. Moreover, the relationship
between the proposed sampling theorem and orthogonal arrays is also provided.
KEY
(If visualization is slow, please try downloading the file.)
Part 2 of a tutorial given in the Brazilian Physical Society meeting, ENFMC. Abstract: Density-functional theory (DFT) was developed 50 years ago, connecting fundamental quantum methods from early days of quantum mechanics to our days of computer-powered science. Today DFT is the most widely used method in electronic structure calculations. It helps moving forward materials sciences from a single atom to nanoclusters and biomolecules, connecting solid-state, quantum chemistry, atomic and molecular physics, biophysics and beyond. In this tutorial, I will try to clarify this pathway under a historical view, presenting the DFT pillars and its building blocks, namely, the Hohenberg-Kohn theorem, the Kohn-Sham scheme, the local density approximation (LDA) and generalized gradient approximation (GGA). I would like to open the black box misconception of the method, and present a more pedagogical and solid perspective on DFT.
Transformations of continuous-variable entangled states of lightOndrej Cernotik
Ā
Gaussian states and Gaussian transformations represent an interesting counterpart to two-level photonic systems in the field of quantum information processing. On the theoretical side, Gaussian states are easily described using first and second moments of the quadrature operators; from the experimental point of view, Gaussian operations can be implemented using linear optics and optical parametric amplifiers. The biggest advantage compared to two-level photonic systems, is deterministic generation of entangled states in parametric amplifiers and highly efficient homodyne detection. In this presentation, we propose new protocols for manipulation of entanglement of Gaussian states.
Firstly, we study entanglement concentration of split single-mode squeezed vacuum states by photon subtraction enhanced by local coherent displacements. These states can be obtained by mixing a single-mode squeezed vacuum state with vacuum on a beam splitter and are, therefore, generated more easily than two-mode squeezed vacuum states. We show that performing local coherent displacements prior to photon subtraction can lead to an enhancement of the output entanglement. This is seen in weak-squeezing approximation where destructive quantum interference of dominant Fock states occurs, while for arbitrarily squeezed input states, we analyze a realistic scenario, including limited transmittance of tap-off beam splitters and limited efficiency of heralding detectors.
Next, motivated by results obtained for bipartite Gaussian states, we study symmetrization of multipartite Gaussian states by local Gaussian operations. Namely, we analyze strategies based on addition of correlated noise and on quantum non-demolition interaction. We use fidelity of assisted quantum teleportation as a figure of merit to characterize entanglement of the state before and after the symmetrization procedure. Analyzing the teleportation protocol and considering more general transformations of multipartite Gaussian states, we show that the fidelity can be improved significantly.
Polynomial matrices can help to elegantly formulate many broadband multi-sensor / multi-channel processing problems, and represent a direct extension of well-established narrowband techniques which typically involve eigen- (EVD) and singular value decompositions (SVD) for optimisation. Polynomial matrix decompositions extend the utility of the EVD to polynomial parahermitian matrices, and this talk presents a brief overview of such polynomial matrices, characteristics of the polynomial EVD (PEVD) and iterative algorithms for its solution. The presentation concludes with some surprising results when applying the PEVD to subband coding and broadband beamforming.
UCSD NANO 266 Quantum Mechanical Modelling of Materials and Nanostructures is a graduate class that provides students with a highly practical introduction to the application of first principles quantum mechanical simulations to model, understand and predict the properties of materials and nano-structures. The syllabus includes: a brief introduction to quantum mechanics and the Hartree-Fock and density functional theory (DFT) formulations; practical simulation considerations such as convergence, selection of the appropriate functional and parameters; interpretation of the results from simulations, including the limits of accuracy of each method. Several lab sessions provide students with hands-on experience in the conduct of simulations. A key aspect of the course is in the use of programming to facilitate calculations and analysis.
Kinetic pathways to the isotropic-nematic phase transformation: a mean field ...Amit Bhattacharjee
Ā
Here we illustrate the classic Ginzburg-Landau-de Gennes theory of isotropic nematic phase transition and show how fluctuations as well as deterministic kinetics can lead to phase equilibria.
ANALYTICAL, NUMERICAL AND EXPERIMENTAL VALIDATION OF COIL VOLTAGE IN INDUCTIO...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical
methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work
piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard
formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations.
Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil
voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This
mathematical model is useful for coil design and optimization of induction heating process.
ANALYTICAL, NUMERICAL AND EXPERIMENTAL VALIDATION OF COIL VOLTAGE IN INDUCTIO...ijeljournal
Ā
This paper presents, mathematical model of induction heating process by using analytical and numerical
methods. In analytical method, series equivalent circuit (SEC) is used to represent induction coil and work
piece. Induction coil and workpiece parameters (resistance and reactance) are calculated by standard
formulas along with Nagaoka correction factors and Bessel functions. In Numerical method, magnetic
vector potential formulation is done and finite element method (FEM) is used to solve the field equations.
Analytically and numerically computed parameters such as equivalent coil resistance, reactance, coil
voltage, work piece power are compared and found that they are in good agreement. Analytically and
numerically obtained coil voltages at different frequencies are validated by experimental results. This
mathematical model is useful for coil design and optimization of induction heating process.
I am Alex N. I am a Physical Chemistry Exam Helper at liveexamhelper.com. I hold a Masters' Degree in Physical Chemistry, from Leeds Trinity University. I have been helping students with their exams for the past 10 years. You can hire me to take your exam in Physical Chemistry.
Visit liveexamhelper.com or email info@liveexamhelper.com. You can also call on +1 678 648 4277 for any assistance with the Physical Chemistry exam.
Development of Improved Diode Clamped Multilevel Inverter Using Optimized Sel...eeiej_journal
Ā
In this paper the role of Selective Harmonic Elimination (SHE) is presented for diode clamped twelve-level multilevel inverter (DCMLI) based on dog leg optimization algorithm. Non-linear equations has been solved to eliminate specific low order harmonics, using the developed DOP algorithm, while at the same time the fundamental component is retained efficiently. The non-linear nature of transcendental equation provide multiple or even no solution for a particular modulation index. The proposed optimization method solving the nonlinear transcendental equations providing all possible solutions. The paper also showing the comparison between different modulation techniques including the proposed method. The entire system has been simulated using MATLAB/Simulink. Simulation results confirm the effectiveness with negligible
THD.
Harmonic elimination at the fundamental frequency is very much appropriate for high and medium range of power generation and applications. This paper considers a new technique for selective harmonic elimination (SHE), in which the total harmonic distortion (THD) is minimized when compared with that of the conventional one. With this technique, the harmonics at lower order are eliminated, which are more predominant than the higher ones.Cascaded H-Bridge inverter fed by a single DC is considered which is simulated with the switching angles generated by both the conventional method of SHE and the new method of SHE. The simulated results of the load voltage and the waveforms of the harmonic analysis are shown. The THD values are compared for the two techniques. The experimental results are also shown for the new technique. The switching angles are generated with the help of field programmable gated array (FPGA) in the hardware. The value of experimental THD of voltage is compared with that of simulated THD and the comparison prove that the results are satisfactory.
In developing electric motors in general and induction motors in particular
temperature limit is a key factor affecting the efficiency of the overall design. Since
conventional loading of induction motors is often expensive, the estimation of temperature
rise by tools of mathematical modeling becomes increasingly important. Excepting for
providing a more accurate representation of the problem, the proposed model can also
reduce computing costs. The paper develops a three-dimensional transient thermal model in
polar co-ordinates using finite element formulation and arch shaped elements. A
temperature-time method is employed to evaluate the distribution of loss in various parts of
the machine. Using these loss distributions as an input for finite element analysis, more
accurate temperature distributions can be obtained. The model is applied to predict the
temperature rise in the stator of a squirrel cage 7.5 kW totally enclosed fan-cooled induction
motor. The temperature distribution has been determined considering convection from the
back of core surface, outer air gap surface and annular end surface of a totally enclosed
structure.
Interpretation of local oriented microstructures by a streamline approach to ...Fabian Wein
Ā
This presentation was held at the conference OPT-I 2014 in Kos, Greece.
It demonstrates a method to interprete material design optimization results with rotated anisotropic cells.
Topology Optimization Using the SIMP MethodFabian Wein
Ā
This is a talk I held internally about the SIMP topology optimization method. It coveres only standard linear elasticity - not the more advanced stuff I do in my research.
PHP Frameworks: I want to break free (IPC Berlin 2024)Ralf Eggert
Ā
In this presentation, we examine the challenges and limitations of relying too heavily on PHP frameworks in web development. We discuss the history of PHP and its frameworks to understand how this dependence has evolved. The focus will be on providing concrete tips and strategies to reduce reliance on these frameworks, based on real-world examples and practical considerations. The goal is to equip developers with the skills and knowledge to create more flexible and future-proof web applications. We'll explore the importance of maintaining autonomy in a rapidly changing tech landscape and how to make informed decisions in PHP development.
This talk is aimed at encouraging a more independent approach to using PHP frameworks, moving towards a more flexible and future-proof approach to PHP development.
UiPath Test Automation using UiPath Test Suite series, part 3DianaGray10
Ā
Welcome to UiPath Test Automation using UiPath Test Suite series part 3. In this session, we will cover desktop automation along with UI automation.
Topics covered:
UI automation Introduction,
UI automation Sample
Desktop automation flow
Pradeep Chinnala, Senior Consultant Automation Developer @WonderBotz and UiPath MVP
Deepak Rai, Automation Practice Lead, Boundaryless Group and UiPath MVP
Essentials of Automations: Optimizing FME Workflows with ParametersSafe Software
Ā
Are you looking to streamline your workflows and boost your projectsā efficiency? Do you find yourself searching for ways to add flexibility and control over your FME workflows? If so, youāre in the right place.
Join us for an insightful dive into the world of FME parameters, a critical element in optimizing workflow efficiency. This webinar marks the beginning of our three-part āEssentials of Automationā series. This first webinar is designed to equip you with the knowledge and skills to utilize parameters effectively: enhancing the flexibility, maintainability, and user control of your FME projects.
Hereās what youāll gain:
- Essentials of FME Parameters: Understand the pivotal role of parameters, including Reader/Writer, Transformer, User, and FME Flow categories. Discover how they are the key to unlocking automation and optimization within your workflows.
- Practical Applications in FME Form: Delve into key user parameter types including choice, connections, and file URLs. Allow users to control how a workflow runs, making your workflows more reusable. Learn to import values and deliver the best user experience for your workflows while enhancing accuracy.
- Optimization Strategies in FME Flow: Explore the creation and strategic deployment of parameters in FME Flow, including the use of deployment and geometry parameters, to maximize workflow efficiency.
- Pro Tips for Success: Gain insights on parameterizing connections and leveraging new features like Conditional Visibility for clarity and simplicity.
Weāll wrap up with a glimpse into future webinars, followed by a Q&A session to address your specific questions surrounding this topic.
Donāt miss this opportunity to elevate your FME expertise and drive your projects to new heights of efficiency.
Key Trends Shaping the Future of Infrastructure.pdfCheryl Hung
Ā
Keynote at DIGIT West Expo, Glasgow on 29 May 2024.
Cheryl Hung, ochery.com
Sr Director, Infrastructure Ecosystem, Arm.
The key trends across hardware, cloud and open-source; exploring how these areas are likely to mature and develop over the short and long-term, and then considering how organisations can position themselves to adapt and thrive.
"Impact of front-end architecture on development cost", Viktor TurskyiFwdays
Ā
I have heard many times that architecture is not important for the front-end. Also, many times I have seen how developers implement features on the front-end just following the standard rules for a framework and think that this is enough to successfully launch the project, and then the project fails. How to prevent this and what approach to choose? I have launched dozens of complex projects and during the talk we will analyze which approaches have worked for me and which have not.
GDG Cloud Southlake #33: Boule & Rebala: Effective AppSec in SDLC using Deplo...James Anderson
Ā
Effective Application Security in Software Delivery lifecycle using Deployment Firewall and DBOM
The modern software delivery process (or the CI/CD process) includes many tools, distributed teams, open-source code, and cloud platforms. Constant focus on speed to release software to market, along with the traditional slow and manual security checks has caused gaps in continuous security as an important piece in the software supply chain. Today organizations feel more susceptible to external and internal cyber threats due to the vast attack surface in their applications supply chain and the lack of end-to-end governance and risk management.
The software team must secure its software delivery process to avoid vulnerability and security breaches. This needs to be achieved with existing tool chains and without extensive rework of the delivery processes. This talk will present strategies and techniques for providing visibility into the true risk of the existing vulnerabilities, preventing the introduction of security issues in the software, resolving vulnerabilities in production environments quickly, and capturing the deployment bill of materials (DBOM).
Speakers:
Bob Boule
Robert Boule is a technology enthusiast with PASSION for technology and making things work along with a knack for helping others understand how things work. He comes with around 20 years of solution engineering experience in application security, software continuous delivery, and SaaS platforms. He is known for his dynamic presentations in CI/CD and application security integrated in software delivery lifecycle.
Gopinath Rebala
Gopinath Rebala is the CTO of OpsMx, where he has overall responsibility for the machine learning and data processing architectures for Secure Software Delivery. Gopi also has a strong connection with our customers, leading design and architecture for strategic implementations. Gopi is a frequent speaker and well-known leader in continuous delivery and integrating security into software delivery.
LF Energy Webinar: Electrical Grid Modelling and Simulation Through PowSyBl -...DanBrown980551
Ā
Do you want to learn how to model and simulate an electrical network from scratch in under an hour?
Then welcome to this PowSyBl workshop, hosted by Rte, the French Transmission System Operator (TSO)!
During the webinar, you will discover the PowSyBl ecosystem as well as handle and study an electrical network through an interactive Python notebook.
PowSyBl is an open source project hosted by LF Energy, which offers a comprehensive set of features for electrical grid modelling and simulation. Among other advanced features, PowSyBl provides:
- A fully editable and extendable library for grid component modelling;
- Visualization tools to display your network;
- Grid simulation tools, such as power flows, security analyses (with or without remedial actions) and sensitivity analyses;
The framework is mostly written in Java, with a Python binding so that Python developers can access PowSyBl functionalities as well.
What you will learn during the webinar:
- For beginners: discover PowSyBl's functionalities through a quick general presentation and the notebook, without needing any expert coding skills;
- For advanced developers: master the skills to efficiently apply PowSyBl functionalities to your real-world scenarios.
Slack (or Teams) Automation for Bonterra Impact Management (fka Social Soluti...Jeffrey Haguewood
Ā
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 the notifications, alerts, and approval requests using Slack for Bonterra Impact Management. The solutions covered in this webinar can also be deployed for Microsoft Teams.
Interested in deploying notification automations for Bonterra Impact Management? Contact us at sales@sidekicksolutionsllc.com to discuss next steps.
Kubernetes & AI - Beauty and the Beast !?! @KCD Istanbul 2024Tobias Schneck
Ā
As AI technology is pushing into IT I was wondering myself, as an āinfrastructure container kubernetes guyā, how get this fancy AI technology get managed from an infrastructure operational view? Is it possible to apply our lovely cloud native principals as well? What benefitās both technologies could bring to each other?
Let me take this questions and provide you a short journey through existing deployment models and use cases for AI software. On practical examples, we discuss what cloud/on-premise strategy we may need for applying it to our own infrastructure to get it to work from an enterprise perspective. I want to give an overview about infrastructure requirements and technologies, what could be beneficial or limiting your AI use cases in an enterprise environment. An interactive Demo will give you some insides, what approaches I got already working for real.
Smart TV Buyer Insights Survey 2024 by 91mobiles.pdf91mobiles
Ā
91mobiles recently conducted a Smart TV Buyer Insights Survey in which we asked over 3,000 respondents about the TV they own, aspects they look at on a new TV, and their TV buying preferences.
Accelerate your Kubernetes clusters with Varnish CachingThijs Feryn
Ā
A presentation about the usage and availability of Varnish on Kubernetes. This talk explores the capabilities of Varnish caching and shows how to use the Varnish Helm chart to deploy it to Kubernetes.
This presentation was delivered at K8SUG Singapore. See https://feryn.eu/presentations/accelerate-your-kubernetes-clusters-with-varnish-caching-k8sug-singapore-28-2024 for more details.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...Ramesh Iyer
Ā
In today's fast-changing business world, Companies that adapt and embrace new ideas often need help to keep up with the competition. However, fostering a culture of innovation takes much work. It takes vision, leadership and willingness to take risks in the right proportion. Sachin Dev Duggal, co-founder of Builder.ai, has perfected the art of this balance, creating a company culture where creativity and growth are nurtured at each stage.
Builder.ai Founder Sachin Dev Duggal's Strategic Approach to Create an Innova...
Ā
Local Optimal Polarization of Piezoelectric Material
1. Introduction Local Optimal Polarization Numerical Examples Summary
Local Optimal Polarization of Piezoelectric Material
Fabian Wein, M. Stingl
9th Int. Workshop on Direct and Inverse Problems in Piezoelectricity
30.09-02.10.2013
2. Introduction Local Optimal Polarization Numerical Examples Summary
Overview
General
linear continuum model
numerical approach based on ļ¬nite element method
PDE based optimization with high number of design variables
Optimization
optimization helps to understand systems better
manufacturability in mind
no real prototypes
3. Introduction Local Optimal Polarization Numerical Examples Summary
Structural Optimization = Topology Optimization + Material Design
Topology optimization
āwhere to put holesā/ material distribution
design of (piezoelectric) devices
macroscopic view
Material design
āassume you could have arbitrary material, what do you want?ā
realization might be another process
realizations might be metamaterials
4. Introduction Local Optimal Polarization Numerical Examples Summary
Motivation
stochastic orientation
Jayachandran, Guedes,
Rodrigues; 2011
Material Design
common homogeneous material seems to
be not optimal
Free Material Optimization ā why it does
not work
local optimal material ā new approach
5. Introduction Local Optimal Polarization Numerical Examples Summary
Standard Topology Optimization
distributes uniform polarized material/holes
āmacroscopic viewā
established in 2 1/2 dimensions (single layer)
scalar variable Ļe for each design element (= ļ¬nite element cell)
SIMP (solid isotropic material with penalization)
piezoelectric topology optimization KĀØogel, Silva; 2005
[cE
e ] = Ļe [cE
] [ee] = Ļe [e] [ĪµS
e ] = Ļe[ĪµS
], Ļe ā [Ļmin,1]
6. Introduction Local Optimal Polarization Numerical Examples Summary
Piezoelectric Free Material Optimization (FMO)
all tensor coeļ¬cients of every ļ¬nite element cell are design variable
[c] =
ļ£«
ļ£
c11 c12 c13
ā c22 c23
ā ā c33
ļ£¶
ļ£ø, [e] =
e11 e13 e15
e31 e33 e35
, [Īµ] =
Īµ11 Īµ12
ā Īµ22
properties
[c] and [Īµ] need to be symmetric positive deļ¬nite
[Īµ] only for sensor case (mechanical excitation) relevant
questions to be answered
[c] orthotropic?
[e] with only standard coeļ¬cients?
orientation of [c] and [e] coincides?
something like an optimal oriented polarization?
7. Introduction Local Optimal Polarization Numerical Examples Summary
FMO Problem Formulation (Actor)
min l u maximize compression
s.th. ĖK u = f, coupled state equation
Tr([c]e) ā¤ Ī½c, 1 ā¤ e ā¤ N, bound stiļ¬ness
Tr([c]e) ā„ Ī½c, 1 ā¤ e ā¤ N, enforce material
( [e]e 2)2
ā¤ Ī½e, 1 ā¤ e ā¤ N, bound coupling
[c]e āĪ½I 0, 1 ā¤ e ā¤ N. positive deļ¬niteness
realize positive deļ¬niteness by feasibility constraints
c11e āĪ½ ā¤ Īµ, 1 ā¤ e ā¤ N,
det2([c]e āĪ½I) ā¤ Īµ, 1 ā¤ e ā¤ N,
det3([c]e āĪ½I) ā¤ Īµ, 1 ā¤ e ā¤ N.
12. Introduction Local Optimal Polarization Numerical Examples Summary
Discussion of the FMO Results
objective
maximize vertical displacement of top electrode
observations
less vertical stiļ¬ness to support compression
in coupling tensor e33 is dominant
characteristic orientational polarization
standard material classes (orthotropic)
coinciding orientation for [c] and [e]
ill-posed problem (stiļ¬ness minimization)
inhomogeneity due to boundary conditions
boundary conditions
deformation
elasticity
coupling
13. Introduction Local Optimal Polarization Numerical Examples Summary
Electrode Design vs. Optimal Polarization
Electrode Design
pseudo polarization KĀØogel, Silva; 2005
[cE
e ] = [cE
], [ee] = [e], [ĪµS
e ] = Ļp[ĪµS
] Ļp ā [ā1,1]
(continuous) ļ¬ipping of polarization (+ topology optimization)
applied on single layer piezoelectric plates
only scales polarization, does not change angle
known to result in -1 and 1 full polarization (static)
erroneously called āoptimal polarizationā
14. Introduction Local Optimal Polarization Numerical Examples Summary
Optimal Orientation
parametrization by design angle Īø
[cE
] = Q(Īø) [c]Q(Īø) [e] = R(Īø) [e]Q(Īø) [ĪµS
] = R(Īø) [Īµ]R(Īø)
R =
cosĪø sinĪø
āsinĪø cosĪø
Q =
ļ£«
ļ£
R2
11 R2
12 2R11 R12
R2
21 R2
22 2R21 R22
R11 R21 R12 R22 R11 R22 +R12 R21
ļ£¶
ļ£ø
concurrent orientation of all tensors
corresponds to local polarization
15. Introduction Local Optimal Polarization Numerical Examples Summary
Numerical System
linear FEM system (static)
Kuu KuĻ
KuĻ āKĻĻ
u
Ļ
=
f
ĀÆq
, short ĖKu = f
Kā assembled by local ļ¬nite element matrices Kāe
Kāe constructed by [cE
e ](Īø), [ee](Īø) and [ĪµS
e ](Īø)
f is discrete force vector, corresponding to mesh nodes.
ĀÆq from applied electric potential (inhomogeneous Dirichlet B.C.)
f = 0 for sensor, ĀÆq = 0 for actuator
16. Introduction Local Optimal Polarization Numerical Examples Summary
Function
discrete solution vector u = u1x u1y u2x u2y ...Ļ1 Ļ2 ...
displacement (each direction) and electric potential at mesh nodes
generic function f identifying solution
f = u l
scalar product of solution with selection vector l = (0 ... 1 ...0)
f can be maximized or used to specify a restriction
vertical displacement of all upper electrode nodes
horizontal displacement of a corner
diagonal displacement of a given region
selection of electric potential at electrode
. . .
17. Introduction Local Optimal Polarization Numerical Examples Summary
Sensitivity Analysis
the gradient vector āf
āĪø determines for every Īøe the impact on f
sensitivity analysis based on adjoint approach
f = uT
l,
āf
āĪøe
= Ī»e
āKe
āĻe
ue with Ī» solving ĖKĪ» = āl
one adjoint system ĖKĪ» = āl to be solved for every function f
āKe
āĻe
easily found by product rule
numerically very eļ¬cient, independent of number of design variables
iteratively problem solution by ļ¬rst order optimizer (SNOPT, MMA)
18. Introduction Local Optimal Polarization Numerical Examples Summary
Problem Formulation
generic problem formulation
min
Īø
l u objective function
s.th. ĖK u = f, coupled state equation
lk u ā¤ ck, 0 ā¤ k ā¤ M, arbitrary constraints
Īøe ā [ā
Ļ
2
,
Ļ
2
], 1 ā¤ Īøe ā¤ N, box constraints
for sensor and actuator problem
full material everywhere
individual polarization angle in every cell
19. Introduction Local Optimal Polarization Numerical Examples Summary
Regularization
orientational optimization in elasticity known to have local optimima
restricts local change of angle
ļ¬ltering Bruns, Tortorelli; 2001
Īøe =
ā
Ne
i=1 w(xi )Īøi
ā
Ne
i=1 w(xi )
w(xi ) = max(0,R ā|xe āxi |)
local slope constraints Petersson, Sigmund; 1998
gslope(Īø) = |< ei ,āĪø(x) >| ā¤ cs i ā {1,...,DIM}
gslope(Īøe,i) = |Īøe āĪøi | ā¤ c,
20. Introduction Local Optimal Polarization Numerical Examples Summary
Example Problems
A BC
actuator problems
maximize compression C ā
maximize compression C ā and limit A ā and B ā
twist A ā and B ā
sensor problem
maximize electric potential at C
21. Introduction Local Optimal Polarization Numerical Examples Summary
maximize compression C ā
initial |u| optimized |u|
gain: 6.1% of integrated y-displacement of C nodes
C is ļ¬attened
probably no global optimum reached
22. Introduction Local Optimal Polarization Numerical Examples Summary
maximize compression C ā and limit A ā and B ā
loss: 4.9% of integrated y-displacement of C nodes
but A and C bounded to 50 % of initial x-displacement
23. Introduction Local Optimal Polarization Numerical Examples Summary
twist A ā and B ā
note Īø ā [āĻ
2 , Ļ
2 ]
electrode design might be more eļ¬ective for this case
24. Introduction Local Optimal Polarization Numerical Examples Summary
maximize electric potential at C
gain: 0.6 % in diļ¬erence of potential
possibly due to poor local optima
25. Introduction Local Optimal Polarization Numerical Examples Summary
Coupling Tensor vs. Stiļ¬ness Tensor
what is the impact of the transversal isotropic stiļ¬ness tensor?
assume isotropic stiļ¬ness tensor
gain: 4.7 % vs. 6.1 % with PZT-5A tensors
26. Introduction Local Optimal Polarization Numerical Examples Summary
Conclusion
General
local polarization works in principle
solutions might be far from global optimium
more feasible than piezoelectric Free Material Optimization
simple support would change everything
Applications
not to improve performance
exact tuning of devices
metamaterial not yet possible (e.g. auxetic material)
27. Introduction Local Optimal Polarization Numerical Examples Summary
Future Work
Examples
dynamic problems, shift of resonance frequencies possible?
metamaterials (e.g. auxetic material)
Mathematical
novel tensor based solver
very promising for elasticity
Technical Realization
polarization by local electric ļ¬eld
piezoelectric building blocks
. . . any suggestions?