Month: August 2024
Formula for moving a range of cells in one row to a new row
Hello All,
On the small sample inserted below, you will see that every student has a unique number in Column A and each student has two rows of data. I would like to move the data so that every student has only one row of data.
For example, the first student is student number 150 (A2 and A3). I would like to move the data from cell range G3:L3 to M2:R2. I want to do this for every student.
How do I do this? Thank you for your help!
Hello All, On the small sample inserted below, you will see that every student has a unique number in Column A and each student has two rows of data. I would like to move the data so that every student has only one row of data. For example, the first student is student number 150 (A2 and A3). I would like to move the data from cell range G3:L3 to M2:R2. I want to do this for every student. How do I do this? Thank you for your help! Read More
MD-102 Change Log
Hi
When the MD-102 exam changes on September 17, will the Learning Path also be changed on that day? If not, is there a timeline on when the learning path will be updated after exam change?
Hi When the MD-102 exam changes on September 17, will the Learning Path also be changed on that day? If not, is there a timeline on when the learning path will be updated after exam change? Read More
How to use Aspen Plus – Matlab Link?
Please help me I am new to Matlab and Aspen Plus but have basic knowledge so please guide in detail. Please tell me what steps do I follow to link Aspen file and Matlab.
The Matlab cod file is:
%% Created by Ing. Andrés Felipe Abril. Universidad Nacional de Colombia. Departamento de Ingeniería Química.
%% Linking
Aspen = actxserver(‘Apwn.Document.36.0’); %34.0 —> V8.8; 35.0 —> V9.0; and 36.0 —> V10.0
[stat,mess]=fileattrib; % get attributes of folder (Necessary to establish the location of the simulation)
Simulation_Name = ‘Reactive_Distillation’;% Aspeen Plus Simulation Name
Aspen.invoke(‘InitFromArchive2’,[mess.Name ” Simulation_Name ‘.bkp’]);
Aspen.Visible = 1; % 1 —> Aspen is Visible; 0 —> Aspen is open but not visible
Aspen.SuppressDialogs = 1; % Suppress windows dialogs.
Aspen.Engine.Run2(1); % Run the simulation
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
end
%% Example of Application
Reflux_Ratio = [1, 3, 5, 7];
for i = 1:length(Reflux_Ratio)
Aspen.Tree.FindNode("DataBlocksRC-101InputBASIS_RR").Value = Reflux_Ratio(i); % Column Reflux
Aspen.Reinit; % Reinit simulation
Aspen.Engine.Run2(1); %Run the simulation. (1) —> Matlab isnt busy; (0) Matlab is Busy;
time = 1;
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
time = time+1;
if time==15 % Control of simulation time.
Aspen.Engine.Stop;
end
end
Simulation_Convergency = Aspen.Tree.FindNode("DataResults SummaryRun-StatusOutputPCESSTAT").Value; % 1 Doesn’t Convergence; 0 Converge
if Simulation_Convergency == 0 && time < 10
Duty(i) = Aspen.Tree.FindNode("DataBlocksRC-101OutputREB_UTL_DUTY").Value; %Duty value of reactive column
else
Duty(i) = inf; % Its Penalized if simulation doesn’t converge;
end
end
%% Plotting
figure()
plot(Reflux_Ratio, Duty, ‘ok’);
Aspen.Close;
Aspen.Quit;Please help me I am new to Matlab and Aspen Plus but have basic knowledge so please guide in detail. Please tell me what steps do I follow to link Aspen file and Matlab.
The Matlab cod file is:
%% Created by Ing. Andrés Felipe Abril. Universidad Nacional de Colombia. Departamento de Ingeniería Química.
%% Linking
Aspen = actxserver(‘Apwn.Document.36.0’); %34.0 —> V8.8; 35.0 —> V9.0; and 36.0 —> V10.0
[stat,mess]=fileattrib; % get attributes of folder (Necessary to establish the location of the simulation)
Simulation_Name = ‘Reactive_Distillation’;% Aspeen Plus Simulation Name
Aspen.invoke(‘InitFromArchive2’,[mess.Name ” Simulation_Name ‘.bkp’]);
Aspen.Visible = 1; % 1 —> Aspen is Visible; 0 —> Aspen is open but not visible
Aspen.SuppressDialogs = 1; % Suppress windows dialogs.
Aspen.Engine.Run2(1); % Run the simulation
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
end
%% Example of Application
Reflux_Ratio = [1, 3, 5, 7];
for i = 1:length(Reflux_Ratio)
Aspen.Tree.FindNode("DataBlocksRC-101InputBASIS_RR").Value = Reflux_Ratio(i); % Column Reflux
Aspen.Reinit; % Reinit simulation
Aspen.Engine.Run2(1); %Run the simulation. (1) —> Matlab isnt busy; (0) Matlab is Busy;
time = 1;
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
time = time+1;
if time==15 % Control of simulation time.
Aspen.Engine.Stop;
end
end
Simulation_Convergency = Aspen.Tree.FindNode("DataResults SummaryRun-StatusOutputPCESSTAT").Value; % 1 Doesn’t Convergence; 0 Converge
if Simulation_Convergency == 0 && time < 10
Duty(i) = Aspen.Tree.FindNode("DataBlocksRC-101OutputREB_UTL_DUTY").Value; %Duty value of reactive column
else
Duty(i) = inf; % Its Penalized if simulation doesn’t converge;
end
end
%% Plotting
figure()
plot(Reflux_Ratio, Duty, ‘ok’);
Aspen.Close;
Aspen.Quit; Please help me I am new to Matlab and Aspen Plus but have basic knowledge so please guide in detail. Please tell me what steps do I follow to link Aspen file and Matlab.
The Matlab cod file is:
%% Created by Ing. Andrés Felipe Abril. Universidad Nacional de Colombia. Departamento de Ingeniería Química.
%% Linking
Aspen = actxserver(‘Apwn.Document.36.0’); %34.0 —> V8.8; 35.0 —> V9.0; and 36.0 —> V10.0
[stat,mess]=fileattrib; % get attributes of folder (Necessary to establish the location of the simulation)
Simulation_Name = ‘Reactive_Distillation’;% Aspeen Plus Simulation Name
Aspen.invoke(‘InitFromArchive2’,[mess.Name ” Simulation_Name ‘.bkp’]);
Aspen.Visible = 1; % 1 —> Aspen is Visible; 0 —> Aspen is open but not visible
Aspen.SuppressDialogs = 1; % Suppress windows dialogs.
Aspen.Engine.Run2(1); % Run the simulation
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
end
%% Example of Application
Reflux_Ratio = [1, 3, 5, 7];
for i = 1:length(Reflux_Ratio)
Aspen.Tree.FindNode("DataBlocksRC-101InputBASIS_RR").Value = Reflux_Ratio(i); % Column Reflux
Aspen.Reinit; % Reinit simulation
Aspen.Engine.Run2(1); %Run the simulation. (1) —> Matlab isnt busy; (0) Matlab is Busy;
time = 1;
while Aspen.Engine.IsRunning == 1 % 1 –> If Aspen is running; 0 —> If Aspen stop.
pause(0.5);
time = time+1;
if time==15 % Control of simulation time.
Aspen.Engine.Stop;
end
end
Simulation_Convergency = Aspen.Tree.FindNode("DataResults SummaryRun-StatusOutputPCESSTAT").Value; % 1 Doesn’t Convergence; 0 Converge
if Simulation_Convergency == 0 && time < 10
Duty(i) = Aspen.Tree.FindNode("DataBlocksRC-101OutputREB_UTL_DUTY").Value; %Duty value of reactive column
else
Duty(i) = inf; % Its Penalized if simulation doesn’t converge;
end
end
%% Plotting
figure()
plot(Reflux_Ratio, Duty, ‘ok’);
Aspen.Close;
Aspen.Quit; aspen plus MATLAB Answers — New Questions
how to model heat transfer to a pipe from furnace
Hello
I am trying to model a thermal fluid system where a furnace provides heat to pipe TL in simscape. at the moment, the mass flow rate of the fuel is 0, but i get the following errors:
At time 20.000000, one or more assertions are triggered. Temperature at port A must be less than or equal to Maximum valid temperature. The assertion comes from: Block path: pumpandpipe07082024/Pipe (TL)Assert location: o (location information is protected) o (location information is protected)
Ungroup 25 similar
Component:Simulink | Category:Model warning
An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘pumpandpipe07082024.Pipe_TL.segment.p_I’ in block ‘pumpandpipe07082024/Pipe (TL)’ at time 50.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances)Hello
I am trying to model a thermal fluid system where a furnace provides heat to pipe TL in simscape. at the moment, the mass flow rate of the fuel is 0, but i get the following errors:
At time 20.000000, one or more assertions are triggered. Temperature at port A must be less than or equal to Maximum valid temperature. The assertion comes from: Block path: pumpandpipe07082024/Pipe (TL)Assert location: o (location information is protected) o (location information is protected)
Ungroup 25 similar
Component:Simulink | Category:Model warning
An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘pumpandpipe07082024.Pipe_TL.segment.p_I’ in block ‘pumpandpipe07082024/Pipe (TL)’ at time 50.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances) Hello
I am trying to model a thermal fluid system where a furnace provides heat to pipe TL in simscape. at the moment, the mass flow rate of the fuel is 0, but i get the following errors:
At time 20.000000, one or more assertions are triggered. Temperature at port A must be less than or equal to Maximum valid temperature. The assertion comes from: Block path: pumpandpipe07082024/Pipe (TL)Assert location: o (location information is protected) o (location information is protected)
Ungroup 25 similar
Component:Simulink | Category:Model warning
An error occurred while running the simulation and the simulation was terminated
Caused by:
Derivative of state ‘pumpandpipe07082024.Pipe_TL.segment.p_I’ in block ‘pumpandpipe07082024/Pipe (TL)’ at time 50.0 is not finite. The simulation will be stopped. There may be a singularity in the solution. If not, try reducing the step size (either by reducing the fixed step size or by tightening the error tolerances) simscape, fluids, furnace MATLAB Answers — New Questions
Newton’s method gives NaN. Can someone improve my code?
Hello everybody. I’m using Newton’s method to solve a liner equation whose solution should be in [0 1]. Unfortunately, the coe I’m using gives NaN as a result for a specific combination of parameters and I would like to understand if I can improve the code I wrote for my Newton’s method. In the specific case I’m considering, I reach the maximum iterations even if the tolerance is very low.
function [x,n,ier] = newton(f,fd,x0,nmax,tol)
% Newton’s method for non-linear equations
ier = 0;
for n = 1:nmax
x = x0-f(x0)/fd(x0);
if abs(x-x0) <= tol
ier = 1;
break
end
x0 = x;
end
% % % % Script for solving NaN
mNAN= 16.1;
lNAN= 10^-4;
f= @(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN);
Fd= @(x) mNAN*(1+lNAN*exp(mNAN*x));
tolNaN=10^-1;
nmax=10^8;
AB0 = 0.5;
[amNAN,nNAN,ierNAN]=newton(f,Fd,AB0,nmax,tolNaN);
amNAN
Llimit=f(0)
Ulimit=f(1)
fplot(@(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN),[0 1.1])Hello everybody. I’m using Newton’s method to solve a liner equation whose solution should be in [0 1]. Unfortunately, the coe I’m using gives NaN as a result for a specific combination of parameters and I would like to understand if I can improve the code I wrote for my Newton’s method. In the specific case I’m considering, I reach the maximum iterations even if the tolerance is very low.
function [x,n,ier] = newton(f,fd,x0,nmax,tol)
% Newton’s method for non-linear equations
ier = 0;
for n = 1:nmax
x = x0-f(x0)/fd(x0);
if abs(x-x0) <= tol
ier = 1;
break
end
x0 = x;
end
% % % % Script for solving NaN
mNAN= 16.1;
lNAN= 10^-4;
f= @(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN);
Fd= @(x) mNAN*(1+lNAN*exp(mNAN*x));
tolNaN=10^-1;
nmax=10^8;
AB0 = 0.5;
[amNAN,nNAN,ierNAN]=newton(f,Fd,AB0,nmax,tolNaN);
amNAN
Llimit=f(0)
Ulimit=f(1)
fplot(@(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN),[0 1.1]) Hello everybody. I’m using Newton’s method to solve a liner equation whose solution should be in [0 1]. Unfortunately, the coe I’m using gives NaN as a result for a specific combination of parameters and I would like to understand if I can improve the code I wrote for my Newton’s method. In the specific case I’m considering, I reach the maximum iterations even if the tolerance is very low.
function [x,n,ier] = newton(f,fd,x0,nmax,tol)
% Newton’s method for non-linear equations
ier = 0;
for n = 1:nmax
x = x0-f(x0)/fd(x0);
if abs(x-x0) <= tol
ier = 1;
break
end
x0 = x;
end
% % % % Script for solving NaN
mNAN= 16.1;
lNAN= 10^-4;
f= @(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN);
Fd= @(x) mNAN*(1+lNAN*exp(mNAN*x));
tolNaN=10^-1;
nmax=10^8;
AB0 = 0.5;
[amNAN,nNAN,ierNAN]=newton(f,Fd,AB0,nmax,tolNaN);
amNAN
Llimit=f(0)
Ulimit=f(1)
fplot(@(x) mNAN*x+lNAN*exp(mNAN*x)-lNAN*exp(mNAN),[0 1.1]) transferred MATLAB Answers — New Questions
Challenge with Simulating Loader Mechanism with Closed Kinematic Loop
I’m currently working on simulating a loader mechanism that includes a closed kinematic loop in its arm, actuated by two jacks. From my research, I understand that conducting a full multibody simulation in systems with a closed kinematic loop while all joints are actuated is impossible. Therefore, one of the actuators must be converted to an unactuated joint (Here is the Link for reference).
To address this, I left the right jack of the loader unactuated in my simulation and forced the left side to stay in a specific position, effectively conducting a static analysis (inverse dynamic) and recording the calculated forces on other joints, such as those between the chassis and the arm. Something like pictue below:
Here is my challenge:
When simulating the arm with only one active jack, the forces generated on the unactuated side of the loader are not accurate because the unactuated jack does not apply any force to the mechanism, which it does in reality. Am I correct in this understanding?
If so, how do others typically address this issue in their simulations?
Any insights or suggestions on how to properly simulate this mechanism would be greatly appreciated!I’m currently working on simulating a loader mechanism that includes a closed kinematic loop in its arm, actuated by two jacks. From my research, I understand that conducting a full multibody simulation in systems with a closed kinematic loop while all joints are actuated is impossible. Therefore, one of the actuators must be converted to an unactuated joint (Here is the Link for reference).
To address this, I left the right jack of the loader unactuated in my simulation and forced the left side to stay in a specific position, effectively conducting a static analysis (inverse dynamic) and recording the calculated forces on other joints, such as those between the chassis and the arm. Something like pictue below:
Here is my challenge:
When simulating the arm with only one active jack, the forces generated on the unactuated side of the loader are not accurate because the unactuated jack does not apply any force to the mechanism, which it does in reality. Am I correct in this understanding?
If so, how do others typically address this issue in their simulations?
Any insights or suggestions on how to properly simulate this mechanism would be greatly appreciated! I’m currently working on simulating a loader mechanism that includes a closed kinematic loop in its arm, actuated by two jacks. From my research, I understand that conducting a full multibody simulation in systems with a closed kinematic loop while all joints are actuated is impossible. Therefore, one of the actuators must be converted to an unactuated joint (Here is the Link for reference).
To address this, I left the right jack of the loader unactuated in my simulation and forced the left side to stay in a specific position, effectively conducting a static analysis (inverse dynamic) and recording the calculated forces on other joints, such as those between the chassis and the arm. Something like pictue below:
Here is my challenge:
When simulating the arm with only one active jack, the forces generated on the unactuated side of the loader are not accurate because the unactuated jack does not apply any force to the mechanism, which it does in reality. Am I correct in this understanding?
If so, how do others typically address this issue in their simulations?
Any insights or suggestions on how to properly simulate this mechanism would be greatly appreciated! simscape, simulation, guide MATLAB Answers — New Questions
Enterprise Custom Field populated in PWA. Data is not populated in Desktop
I have created a resource Enterprise Custom Field called “Role”. The new field shows up on the “Edit Resource” page in PWA. I populate the field with a value (it is a text lookup type using the “Role” lookup table). When I open the resource in Project Desktop, the field is there, but the value I entered in PWA is not there. It is just empty. If I update the value in the Desktop, it stays. Why is the value not showing up in the desktop when I populate through PWA?
I have created a resource Enterprise Custom Field called “Role”. The new field shows up on the “Edit Resource” page in PWA. I populate the field with a value (it is a text lookup type using the “Role” lookup table). When I open the resource in Project Desktop, the field is there, but the value I entered in PWA is not there. It is just empty. If I update the value in the Desktop, it stays. Why is the value not showing up in the desktop when I populate through PWA? Read More
Reverting from (New) Outlook Need some advice.
As the title says I’m running away from the new outlook. But I have a few Questions:
1. I use office 365 and am going back to standard outlook, is it best to set my rules in the cloud/web site or locally? Will the cloud rules affect my local copy of outlook standard?
2. Are there any actual consequences from ditching the new outlook?
As the title says I’m running away from the new outlook. But I have a few Questions: 1. I use office 365 and am going back to standard outlook, is it best to set my rules in the cloud/web site or locally? Will the cloud rules affect my local copy of outlook standard?2. Are there any actual consequences from ditching the new outlook? Read More
New on Azure Marketplace: July 25-31, 2024
We continue to expand the Azure Marketplace ecosystem. For this volume, 142 new offers successfully met the onboarding criteria and went live. See details of the new offers below:
Get it now in our marketplace
AIMMO Core – Smart Curation: AIMMO Core’s AI-powered data curation service streamlines dataset curation by sending image files from the customer’s Azure Blob Storage to AI models using URLs, with the curated results viewable in a web viewer. The service operates directly within the customer’s Azure Storage, ensures data security, and saves time by eliminating the transfer of large data volumes for AI inference.
AlmaLinux 9.3 Generation 2: Rinne Labs offers a lightweight and secure AlmaLinux 9.3 image built from the official ISO for optimal performance. The image reduces storage requirements, optimizes system responsiveness, and is equipped with the latest security patches and updates. It is ideal for rapid deployment of web applications, efficient development and testing environments, stable and secure server infrastructure, data analytics, and machine learning.
AlmaLinux 9.3 Gen 2 Minimal: Rinne Labs offers a lightweight and secure AlmaLinux 9.3 image built from the official ISO with minimal size for faster boot times and reduced resource consumption. The image reduces storage requirements, optimizes system responsiveness, and is equipped with the latest security patches and updates. It is ideal for rapid deployment of web applications, efficient development and testing environments, stable and secure server infrastructure, data analytics, and machine learning.
Archibus: Archibus by Eptura is a web-based platform that optimizes workplace and building operations. It offers a comprehensive suite of tools for space management, asset management, risk and sustainability, capital projects and leases, and more. Archibus integrates with Microsoft Outlook, Teams, and Power BI, and is hosted on Microsoft Azure for select clients and FedRAMP compliant organizations.
Awssome White Label: This SaaS platform from WeTransact offers built-in order management, financial reporting, and marketplace integration maintenance for independent software vendors and enables them to list offers on multiple cloud marketplaces. With ongoing support and no hidden costs, Awssome White Label makes publishing quick and easy. Offers can go live in just days.
Bandit on Debian 11: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
Bandit on Oracle Linux 8.8: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
Bandit on Red Hat 8.7: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
Bandit on Ubuntu 20.04 LTS: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
Bandit on Ubuntu 22.04 LTS: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
Bandit on Ubuntu 24.04 LTS: Bandit is a Python code scanning tool that identifies potential security vulnerabilities. This pre-configured image from Apps4Rent optimized for Microsoft Azure simplifies deployment and provides a consistent environment across different compute resources. Key features include automated security analysis, comprehensive issue detection, and ease of use.
CA Gatekeeper: CA Gatekeeper allows for easy backup and restoration of tenant conditional access policies, with granular management capabilities and safeguards against accidental deletion and compliance issues. It also provides advanced management capabilities, such as change prevention, approval workflows, policy comparison, and user-friendly views of policy settings and changes.
CIS Level 1 Benchmarks for Microsoft Windows 11 Enterprise: This Azure-based virtual machine comes with a pre-configured Windows 11 Enterprise image that meets the Center for Internet Security (CIS) Level 1 compliance needs. CIS benchmarks provide guidelines for securing and configuring server settings to mitigate common security vulnerabilities and threats. Madarson IT images are always up to date, secure, and follow industry standards.
CIS Level 1 Benchmarks for Microsoft Windows Server 2022: This Azure-based virtual machine comes with the latest Microsoft Windows Server 2022 image pre-configured to meet the Center for Internet Security (CIS) Level 1 compliance needs. CIS benchmarks provide guidelines for securing and configuring server settings to mitigate common security vulnerabilities and threats. Madarson IT images are always up-to-date, secure, and built to work right out of the box.
CIS Level 2 Benchmarks for Microsoft Windows Server 2019: This Azure-based virtual machine is pre-configured with the Microsoft Windows Server 2019 image and meets the Center for Internet Security (CIS) Level 2 compliance needs. CIS benchmarks provide guidelines for securing and configuring server settings to mitigate security vulnerabilities and threats. Madarson IT images are always up to date, secure, and follow industry standards.
CIS Level 2 Benchmarks for Microsoft Windows Server 2022: This Azure-based virtual machine is pre-configured with the latest Microsoft Windows Server 2022 image and meets the Center for Internet Security (CIS) Level 2 compliance needs. CIS benchmarks provide guidelines for securing and configuring server settings to mitigate security threats. Madarson IT images are always up to date, secure, and follow industry standards.
Connected Worker (SaaS): Vassar Digital’s Connected Worker solution uses generative AI and LLMs with enterprise knowledge base to improve field operations and boost employee productivity. The platform enables you to elevate customer service, explore new revenue streams, and optimize profitability.
Dagster: Dagster is a cloud-native data orchestration platform that offers integrated lineage and observability, a declarative programming model, and reliable testability. With Azure integration, developers can use Azure Storage Accounts as part of their data pipeline. Dagster empowers developers to observe, optimize, and debug any pipeline on their data platform and collaborate across teams with an intuitive UI.
DataStax HCD (Hyper Converged Database): DataStax HCD is a cloud-native data infrastructure for AI data clouds, designed for enterprises investing in datacenter modernization and hyper converged infrastructure. Built on open-source Apache Cassandra, it is ideal for enterprise operators and architects driving on-premises datacenter modernization initiatives.
Debian 10 with Apache Subversion (SVN) Server: Virtual Pulse offers a pre-configured and cloud hardened Debian 10 with Apache Subversion (SVN) Server image for software developers to maintain current and previous versions of files. SVN is a centralized version control system that ensures atomic operations, retains full revision history, and supports a wide variety of users and projects.
Eclipse IDE for Java and Web on Windows Server 2022: Eclipse IDE is a free and open-source development platform for Java and other programming languages. Nuvemnest provides Eclipse IDE for Java and Web on Windows Server 2022 with a focus on customer-centric approach, expertise in cloud computing, and future-ready technology.
Eclipse IDE for Java on Windows Server 2016: Nuvemnest offers Eclipse IDE, an open-source development platform for Java and other programming languages that enables programmers to streamline the development of Java-based applications using a comprehensive suite of tools and integrations. The Eclipse IDE for Java and Web on Windows Server 2016 solution is built on top-notch technology, ensuring adaptability and sustainability.
Eclipse IDE for Java on Windows Server 2019: Eclipse IDE is a free and open-source development platform for Java and other programming languages. Nuvemnest provides Eclipse IDE for Java on Windows Server 2019 with a focus on customer-centric approach, expertise in cloud computing, and future-ready technology. No commercial licenses are offered.
Eclipse IDE for Java on Windows Server 2022: Eclipse IDE is a free and open-source development platform for Java and other programming languages. Nuvemnest provides Eclipse IDE for Java on Windows Server 2022 with a focus on customer-centric approach, expertise in cloud computing, and future-ready technology. No commercial licenses are offered.
Hybrid Setup for Nutanix Cluster: MDS/LiveRoute will provide you with hands-on assistance in deploying and configuring your Nutanix cluster on Microsoft Azure. Their expert guides will evaluate your environment and ensure efficient migration of your applications and data to Azure while minimizing downtime and disruption. The offer includes assessment, planning, and setup services.
Instant Kubernetes: K8 VM with Minikube: Unlock the power of Kubernetes with Techlatest.net’s cost-effective solution. It comes with Minikube and pre-installed kubectl, making it ideal for pre-production and educational purposes. Test multi-node clusters and explore various Kubernetes configurations without the need for a complex setup. Gain immediate access to the Minikube dashboard for resource management.
Jellyfin on AlmaLinux 8 – Streaming Media Server: Jellyfin Streaming Media Server on AlmaLinux 8 offers a customizable and secure media server solution for media enthusiasts and tech-savvy individuals. With seamless streaming, full customization, scalability, security, and a user-friendly interface, it provides a robust platform for managing and streaming your media library.
Jellyfin on AlmaLinux 9 – Streaming Media Server: Jellyfin on AlmaLinux 9 is a customizable, secure, and efficient media server that allows you to stream your media library in high definition across all your devices. With features like cross-platform support and a customizable interface, it’s perfect for media enthusiasts, families, and small businesses looking to centralize and control their media content.
Jellyfin on Debian 11 – Streaming Media Server: Jellyfin is a free, open-source media server that allows you to organize and stream your media collection with ease. With features like SyncPlay and support for Live TV and TV tuners, Jellyfin offers unparalleled flexibility and customization options. Deploy Debian 11 with Jellyfin Server to take control of your media journey.
Jellyfin on Debian 12 – Streaming Media Server: Jellyfin is an open-source multimedia software that allows you to organize and enjoy your media library from anywhere. It offers transcoding and media format support, customization options, and third-party plugins. With Jellyfin, you have full control over your data and privacy. Turn your home server into a multimedia center with Jellyfin on Debian 12.
Jellyfin on Linux Stream 8 – Streaming Media Server: Jellyfin on Linux Stream 8 is a reliable and high-performing media server solution for personal and professional use. It offers comprehensive media management, security, and community support. With Jellyfin, users can stream their media anytime, anywhere, and on any device.
Jellyfin on Linux Stream 9 – Streaming Media Server: Jellyfin Media Server on Linux Stream 9 is a flexible and secure solution for managing and streaming your digital content. It offers seamless media streaming, comprehensive media organization, customizable user experience, multi-platform support, and privacy and security features.
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Linux Stream 9 Minimal with Jitsi: Jitsi Meet is an open-source video-conferencing app that offers high functionality and secure end-to-end TLS encryption. It allows anonymous access, self-hosting, password protection, and low bandwidth settings. Virtual Pulse’s Linux Stream 9 Minimal image with Jitsi provides a seamless user experience for online classes, client conferences, family gatherings, and work meetings.
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Linux Stream 9 with Jellyfin Server: Jellyfin is a media server that organizes movies, TV shows, music, and images in one location accessible from any device. It fetches metadata and allows personalized user profiles with parental controls. Jellyfin is open source with security features for privacy. Improve your media experience with Virtual Pulse’s Linux Stream 9 image with Jellyfin Server available on Azure.
Linux Stream 9 with Webmin Server: Linux Stream 9 with Webmin Server offers a user-friendly interface for effortless server management. It allows you to add, modify, or delete users, manage file systems, and configure services from a centralized dashboard. The real-time monitoring tools keep an eye on server performance issues, and the built-in cron job manager enables you to automate recurring tasks. It supports popular databases like MySQL and PostgreSQL, making database management easy.
Mendel Hypercube: Hypercube from Mendel AI is an AI copilot suite that uses hypergraph technology to transform clinical analytics workflows for healthcare organizations. It includes features such as Hypercube Cohort for rapid patient cohort creation, Hypercube Charts for a comprehensive understanding of patient journeys, Hypercube Analyst for in-depth analysis, and Hypercube Redact for data privacy and compliance.
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Singledispatch on Oracle Linux 8.8: This offer from Apps4Rent provides a pre-configured image of singledispatch on Oracle Linux 8.8 optimized for Azure. The singledispatch decorator is used for function overloading in Python and provides a consistent environment for easy development and deployment. Key features include efficiency, compatibility, extensibility, ease of use, and high performance.
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Singledispatch on Ubuntu 22.04 LTS: Apps4Rent’s pre-configured Singledispatch image on Ubuntu 22.04 LTS optimized for Azure provides a consistent environment for easy development and deployment. The singledispatch decorator is used for function overloading in Python and offers efficiency, compatibility, extensibility, ease of use, and high performance. ease of use, and high performance.
Singledispatch on Ubuntu 24.04 LTS: Apps4Rent’s pre-configured Singledispatch image on Ubuntu 24.04 LTS optimized for Azure provides a consistent environment for easy development and deployment. The singledispatch decorator is used for function overloading in Python and offers efficiency, compatibility, extensibility, ease of use, and high performance. ease of use, and high performance.
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UDS Government: UDS Government from Virtual Cable is a virtualization solution for public administrations that provides secure and continuous access to all necessary applications and software from any location and device. It integrates desktop and application virtualization for both Windows and Linux in a single console, as well as remote access to physical devices. UDS Government simplifies deployment of new digital workspaces in high availability, customized for each user profile, with high security and privacy.
UDS Health: UDS Health from Virtual Cable is a virtualization solution for the healthcare sector that provides secure and continuous access to all applications and software used in hospitals, clinics, nursing homes, and primary care centers. It integrates desktop and application virtualization for both Windows and Linux in a single console, as well as remote access to physical devices. It can be deployed on-premises or in public, private, hybrid, or multi-cloud environments.
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Evaluate classification/regression performance against noisy annotation
Is there a way to evaluate classification/regression performance accounting of noisy annotations.
Let’s say I have a cat/dog detector and 1000 cat/dog test images. The 1000 images are human annotated, so it’s likely there are annotation errors, e.g. some bounding box may be incorrect and some class label may be wrong. Simply draw a confusion matrix or derive an IoU just compare the detector performance with the noisy data, and I don’t think such way is appropriate.
So my questions are
What’s the appropriate way to estimate the bbox and class error margin in the data set, given it’s not possible to go through each of them?
How to incorporate the above annotation error when reporting the performance of the cat/dog detector?
Thanks.Is there a way to evaluate classification/regression performance accounting of noisy annotations.
Let’s say I have a cat/dog detector and 1000 cat/dog test images. The 1000 images are human annotated, so it’s likely there are annotation errors, e.g. some bounding box may be incorrect and some class label may be wrong. Simply draw a confusion matrix or derive an IoU just compare the detector performance with the noisy data, and I don’t think such way is appropriate.
So my questions are
What’s the appropriate way to estimate the bbox and class error margin in the data set, given it’s not possible to go through each of them?
How to incorporate the above annotation error when reporting the performance of the cat/dog detector?
Thanks. Is there a way to evaluate classification/regression performance accounting of noisy annotations.
Let’s say I have a cat/dog detector and 1000 cat/dog test images. The 1000 images are human annotated, so it’s likely there are annotation errors, e.g. some bounding box may be incorrect and some class label may be wrong. Simply draw a confusion matrix or derive an IoU just compare the detector performance with the noisy data, and I don’t think such way is appropriate.
So my questions are
What’s the appropriate way to estimate the bbox and class error margin in the data set, given it’s not possible to go through each of them?
How to incorporate the above annotation error when reporting the performance of the cat/dog detector?
Thanks. annotation, classification, regression, noise, evaluation MATLAB Answers — New Questions
why my training results are repeated even after i run my code again and again ??
% ANN model for ukraine with all inputs
%% Data loading to the matlab environment
train_data = xlsread(‘Train_M.xlsx’);
input_train = xlsread(‘Train_M’,’input’);
X_train = input_train’;
target_train = xlsread(‘Train_M’,’target’);
T_train = target_train’;
test_data = xlsread(‘Test_M.xlsx’);
input_test = xlsread(‘Test_M’,’input’);
X_test = input_test’;
target_test = xlsread(‘Test_M’,’target’);
T_test = target_test’;
%% normalization of training and testing data
%for training
[Tr_i ps] = mapminmax(X_train,-1,1);
[Tr_t ps] = mapminmax(T_train,-1,1);
%for testing
[Tst_i pp] = mapminmax(X_test,-1,1);
[Tst_t pp] = mapminmax(T_test,-1,1);
%clear
%clc
%load Best_Dataset (need to save our datadivision for avoiding
%randomization)
%% GRNN model development
%% model formulation
spread = 0.42;
net = newgrnn(Tr_i,Tr_t,spread);
view(net);
%% prediction outputs of the model
y_tr = net(Tr_i);
y_tst = net(Tst_i);
%% renormalization process
% Model outputs(forecasted data)
Renorm_train_out = mapminmax(‘reverse’,y_tr,ps);
Renorm_test_out = mapminmax(‘reverse’,y_tst,pp);
%for model inputs(observed data)
Renorm_train_inp = mapminmax(‘reverse’,Tr_t,ps);
Renorm_test_inp = mapminmax(‘reverse’,Tst_t,pp);
%% performance of the ANN model
%Training performance and testing performance
plot(Renorm_test_inp,Renorm_test_out,’x’)%curves is ok
plot(Renorm_train_inp,Renorm_train_out,’x’)%curve is ok
%% statistical measure of the model
%% model performance command
mdl = fitlm(Renorm_test_inp,Renorm_test_out)%testing performance
mdl = fitlm(Renorm_train_inp,Renorm_train_out)%training performance
%% saving the trained model
save(‘GRNN_allinputs.mat’,’net’);
%% the results for the above code repeates.
R2 is 0.68, RMSE 10.8 – training
R2 is 0.639 ,RMSE 3.03 -testing
these results are again shown for the second run and so on
AM i missing something here ???
please help !!!!% ANN model for ukraine with all inputs
%% Data loading to the matlab environment
train_data = xlsread(‘Train_M.xlsx’);
input_train = xlsread(‘Train_M’,’input’);
X_train = input_train’;
target_train = xlsread(‘Train_M’,’target’);
T_train = target_train’;
test_data = xlsread(‘Test_M.xlsx’);
input_test = xlsread(‘Test_M’,’input’);
X_test = input_test’;
target_test = xlsread(‘Test_M’,’target’);
T_test = target_test’;
%% normalization of training and testing data
%for training
[Tr_i ps] = mapminmax(X_train,-1,1);
[Tr_t ps] = mapminmax(T_train,-1,1);
%for testing
[Tst_i pp] = mapminmax(X_test,-1,1);
[Tst_t pp] = mapminmax(T_test,-1,1);
%clear
%clc
%load Best_Dataset (need to save our datadivision for avoiding
%randomization)
%% GRNN model development
%% model formulation
spread = 0.42;
net = newgrnn(Tr_i,Tr_t,spread);
view(net);
%% prediction outputs of the model
y_tr = net(Tr_i);
y_tst = net(Tst_i);
%% renormalization process
% Model outputs(forecasted data)
Renorm_train_out = mapminmax(‘reverse’,y_tr,ps);
Renorm_test_out = mapminmax(‘reverse’,y_tst,pp);
%for model inputs(observed data)
Renorm_train_inp = mapminmax(‘reverse’,Tr_t,ps);
Renorm_test_inp = mapminmax(‘reverse’,Tst_t,pp);
%% performance of the ANN model
%Training performance and testing performance
plot(Renorm_test_inp,Renorm_test_out,’x’)%curves is ok
plot(Renorm_train_inp,Renorm_train_out,’x’)%curve is ok
%% statistical measure of the model
%% model performance command
mdl = fitlm(Renorm_test_inp,Renorm_test_out)%testing performance
mdl = fitlm(Renorm_train_inp,Renorm_train_out)%training performance
%% saving the trained model
save(‘GRNN_allinputs.mat’,’net’);
%% the results for the above code repeates.
R2 is 0.68, RMSE 10.8 – training
R2 is 0.639 ,RMSE 3.03 -testing
these results are again shown for the second run and so on
AM i missing something here ???
please help !!!! % ANN model for ukraine with all inputs
%% Data loading to the matlab environment
train_data = xlsread(‘Train_M.xlsx’);
input_train = xlsread(‘Train_M’,’input’);
X_train = input_train’;
target_train = xlsread(‘Train_M’,’target’);
T_train = target_train’;
test_data = xlsread(‘Test_M.xlsx’);
input_test = xlsread(‘Test_M’,’input’);
X_test = input_test’;
target_test = xlsread(‘Test_M’,’target’);
T_test = target_test’;
%% normalization of training and testing data
%for training
[Tr_i ps] = mapminmax(X_train,-1,1);
[Tr_t ps] = mapminmax(T_train,-1,1);
%for testing
[Tst_i pp] = mapminmax(X_test,-1,1);
[Tst_t pp] = mapminmax(T_test,-1,1);
%clear
%clc
%load Best_Dataset (need to save our datadivision for avoiding
%randomization)
%% GRNN model development
%% model formulation
spread = 0.42;
net = newgrnn(Tr_i,Tr_t,spread);
view(net);
%% prediction outputs of the model
y_tr = net(Tr_i);
y_tst = net(Tst_i);
%% renormalization process
% Model outputs(forecasted data)
Renorm_train_out = mapminmax(‘reverse’,y_tr,ps);
Renorm_test_out = mapminmax(‘reverse’,y_tst,pp);
%for model inputs(observed data)
Renorm_train_inp = mapminmax(‘reverse’,Tr_t,ps);
Renorm_test_inp = mapminmax(‘reverse’,Tst_t,pp);
%% performance of the ANN model
%Training performance and testing performance
plot(Renorm_test_inp,Renorm_test_out,’x’)%curves is ok
plot(Renorm_train_inp,Renorm_train_out,’x’)%curve is ok
%% statistical measure of the model
%% model performance command
mdl = fitlm(Renorm_test_inp,Renorm_test_out)%testing performance
mdl = fitlm(Renorm_train_inp,Renorm_train_out)%training performance
%% saving the trained model
save(‘GRNN_allinputs.mat’,’net’);
%% the results for the above code repeates.
R2 is 0.68, RMSE 10.8 – training
R2 is 0.639 ,RMSE 3.03 -testing
these results are again shown for the second run and so on
AM i missing something here ???
please help !!!! regression, general regression neural network, matlab, programming MATLAB Answers — New Questions
Formula Required
Hi All,
I need a formula for the following see attached Sheet.
Brief
Starting at 50klm distance the base rate is $1.50
Every 50klm more I want the rate to increase $0.25
I have it set up so when you enter the Distance (KLM) (sourced via Google Search)
The Quantity needs to rounds up to the next whole number according to Distance(KLM) entered
The rate increase needs to corresponds with Quantity total.
Any help would be appreciated. Thank you
Hi All, I need a formula for the following see attached Sheet. BriefStarting at 50klm distance the base rate is $1.50Every 50klm more I want the rate to increase $0.25 I have it set up so when you enter the Distance (KLM) (sourced via Google Search) The Quantity needs to rounds up to the next whole number according to Distance(KLM) enteredThe rate increase needs to corresponds with Quantity total. Any help would be appreciated. Thank you Read More
Formula for COUNTIFS combined with OR (I think)
Hello,
Please can someone help me with a formula for the following:
Column E is labelled “Priority” with drop down options of “High”, “Medium” or “Low” from a lookup table.
Column I is labelled “Status” with drop down options of “Complete”, “In Progress” or “Not Started” from a look up table.
I want to count in cell I2, how many priorities in column E are “high” AND column I has the status “In Progress” OR “Not Started” [i.e. a status that is not “Complete”].
I have created a COUNTIFS formula but cannot seem to apply a second criteria that excludes from the count any with the status “Complete”: =(COUNTIFS($E7:E13,”High”))
I can then adjust the same formula for “Medium” and “Low” priorities for cells I3 and I4 respectively.
Hello, Please can someone help me with a formula for the following: Column E is labelled “Priority” with drop down options of “High”, “Medium” or “Low” from a lookup table.Column I is labelled “Status” with drop down options of “Complete”, “In Progress” or “Not Started” from a look up table. I want to count in cell I2, how many priorities in column E are “high” AND column I has the status “In Progress” OR “Not Started” [i.e. a status that is not “Complete”]. I have created a COUNTIFS formula but cannot seem to apply a second criteria that excludes from the count any with the status “Complete”: =(COUNTIFS($E7:E13,”High”)) I can then adjust the same formula for “Medium” and “Low” priorities for cells I3 and I4 respectively. Read More
change background when using dropdown list
When picking items from a dropdown list that contains employees who have different color backgrounds based on their dept, I want the background for that item in the table to appear on my spreadsheet once I pick them for my sheet.
When picking items from a dropdown list that contains employees who have different color backgrounds based on their dept, I want the background for that item in the table to appear on my spreadsheet once I pick them for my sheet. Read More
Web Filtering / Monitoring for Android Devices
Hello all,
Does Intune offer a solution to filter and monitor web access on Android devices?
Basically block them from accessing naughty sites.
These are Corporate fully managed/KIOSK devices etc with MS edge loaded.
Don’t want to go down the white/allowed list route if possible as they used for multiple scenarios.
I am looking at the MS Defender app but unsure if It can do the job and how to set it up.
We have a solution for our Windows devices but isn’t compatible with Android.
Any help or suggestions welcome.
Hello all, Does Intune offer a solution to filter and monitor web access on Android devices? Basically block them from accessing naughty sites. These are Corporate fully managed/KIOSK devices etc with MS edge loaded. Don’t want to go down the white/allowed list route if possible as they used for multiple scenarios. I am looking at the MS Defender app but unsure if It can do the job and how to set it up. We have a solution for our Windows devices but isn’t compatible with Android. Any help or suggestions welcome. Read More
Store images in Kusto and visualize them with Power BI or Azure Data Explorer Dashboards
How to Visualize Images Stored in Kusto
Kusto is a fast and scalable database designed to ingest, store, and analyze large volumes of structured and semi-structured data. For non-structured data like images, Azure Storage is typically the best choice. Databases can reference image data on storage via a URL, meaning images are not directly stored in Kusto. However, there are scenarios where storing image data in Kusto is beneficial. However, there are scenarios where storing image data in Kusto is beneficial. In this blog post, we will explore when it makes sense to store images in Kusto, how to store them, and how to visualize this data using Azure Data Explorer dashboards or Power BI.
Although Kusto doesn’t support binary data types, there are still compelling reasons to store images in Azure Data Explorer. For dashboards and reports that require images, visualization tools might not support secure access to external storage. By leveraging identities and network segregation via managed private endpoints, storing all data in one location simplifies both access and security. However, it’s important to note that Kusto the best technology for storing large-scale images.
Kusto does not support binary data types, so images must be encoded in base64. This encoding converts the data into a non-human-readable string of 64 English characters. When storing an image in Kusto using base64, it is saved as a string.The default size limit for a string in Kusto is 1 MB (see Kusto Documentation for string datatype. By default, all columns in Kusto are indexed. For columns storing images, you should disable indexing and may need to increase the default size limit. Below is an example of creating an image table, disabling indexing, and increasing the string size limit to 2 MB using the the BigObject encoding type:
.create table image (file_name:string, img_original_base64 : string )
// This policy disables the index of the image column and overrides MaxValueSize property in the encoding Policy to 2 MB:
.alter column image.img_original_base64 policy encoding type=’BigObject’
The maximum size for a string in Kusto is 32 MB. For more details, refer to the documentation on the encoding policy.
You can use all available ingestion methods for the Kusto database, depending on the deployment (PaaS or SaaS). Ensure that the image data is converted to a binary string and encoded to base64, as described in the previous section. You can find a Python example in the Gist references at the end of this article.
Once you’ve ingested image data into a Kusto table, you might want to visualize it using Azure Data Explorer Dashboards. Markdown visuals are an effective way to display images. Typically, images are displayed from a storage location using the following markdown pattern:
For images stored in Kusto, the process is similar. Instead of linking to a storage location, you use the field containing the base64-encoded string of the image. Here’s how you can do it:
This method embeds the image directly into the dashboard using the base64-encoded string from your data. If you have multiple images to display you can make use of a function generating a markdown from a Kusto query. The function logic has been shared on stackoverflow by Daniel Dror:
let schema = t | getschema;
let headers = schema | project ColumnName | summarize make_list(ColumnName) | extend String = strcat(‘| ‘, strcat_array(list_ColumnName, ‘ | ‘), ‘ |’) | project String, Order=1;
let upper_divider = schema | project ColumnName, Sep = ‘—‘ | summarize Cols=make_list(Sep) | extend String = strcat(‘| ‘, strcat_array(Cols, ‘ | ‘), ‘ |’) | project String, Order=2;
let data = t | extend Cols=pack_array(*) | extend String = strcat(‘| ‘, strcat_array(Cols, ‘ | ‘), ‘ |’) | project String, Order=3;
headers
| union upper_divider
| union data
| order by Order asc
| summarize Rows=make_list(String)
| project array_strcat(Rows, ‘rn’)
}
With invoking this function, you can easily display a table of images in Azure Data Explorer dashboards. The following query is used in combination with a markdown visual:
| project file_name, img_original_base64
| extend ingestion_time=ingestion_time()
| summarize arg_max(ingestion_time, *) by file_name// remove duplicates
| extend image=strcat(“” )
| project file_name, image
| order by file_name desc
| invoke table_to_markdown()
This is an example how your data can be visualized using the markdown visualization:
Markdown visualization in Azure Data Explorer Dashboards
Power BI allows the integration of images from a database, a process that is well-documented in a Guy in a Cube YouTube video, which is referenced at the end of this article. By default, Power BI supports image URLs, but what if you want to display images stored as strings? Given Power BI’s limitation of a 32k string size, a creative workaround is necessary. This involves splitting the strings and then reconstructing them using DAX logic, a technique thoroughly explained in the aforementioned Guy in a Cube video.
To handle large image strings that exceed Power BI’s capacity, a split string function in Kusto can be employed. This function divides the image string representation into multiple rows, which is essential for visualization tools that have string size restrictions. Here’s how the function looks
//this is needed for visualization tools with limitation on string sizes
.create-or-alter function with (folder = “Gold layer”, docstring=”split image string representation to several rows if PowerBI string size limitation is hit”, skipvalidation = “true”) image_report ()
{
let max_length=32766; //maximum PowerBI string length
image
| project file_name, img_original_base64
| extend ingestion_time=ingestion_time()
| summarize arg_max(ingestion_time, *) by file_name // remove duplicates
| extend parts = range(0, strlen(img_original_base64) – 1, max_length)
| mv-expand parts // rows needed for each substring (1 if length < max_length)
| extend img_original_base64_part = substring(img_original_base64, toint(parts), max_length), order=toint(parts)/max_length
| project file_name, img_original_base64_part, order
}
Following the split, DAX logic is used to concatenate the substrings back into the final image:
This approach ensures that even with Power BI’s string size limitations, images can be effectively displayed by leveraging Kusto’s split string function and DAX’s concatenation capabilities.
The integration of images into Kusto and their visualization through Power BI or Azure Data Explorer Dashboards offers a unique approach to managing and displaying non-structured data. While Kusto is primarily designed for structured and semi-structured data, it can accommodate images through base64 encoding, albeit with some limitations due to the absence of binary data types. This method is particularly useful for dashboards and reports that require secure access to images without relying on external storage solutions.
The process involves encoding images into a base64 string, ingesting them into Kusto, and then utilizing visualization tools like Power BI to display the images. This approach ensures that all data, including images, can be securely accessed and managed in one centralized location, simplifying both access and security protocols.
However, it’s crucial to recognize that Kusto is not optimized for storing large-scale images, and this method should be reserved for scenarios where the benefits outweigh the limitations. By following the guidelines and techniques outlined in this blog post, users can effectively store and visualize images within Kusto, enhancing their data analysis and reporting capabilities in a secure and efficient manner.
Column encoding policy
Generate a markdown from a kusto query result, stackoverflow
Power BI Display images in a table, matrix, or slicer in a report
Using Images from a Data Base in Power BI, You Tube
Gist with code examples
Microsoft Tech Community – Latest Blogs –Read More
Networking improvements in Windows Server 2025
Windows Server 2025 is the most secure and performant release yet! Download the evaluation now!
Looking to migrate from VMware to Windows Server 2025? Contact your Microsoft account team!
Looking to migrate from VMware to Windows Server 2025? Contact your Microsoft account team!
The 2024 Windows Server Summit was held in March and brought three days of demos, technical sessions, and Q&A, led by Microsoft engineers, guest experts from Intel®, and our MVP community. For more videos from this year’s Windows Server Summit, please find the full session list here.
This article focuses on networking improvements in Windows Server 2025.
Host networking at the edge
It’s time for a closer look at what’s new and exciting in networking for Windows Server! Explore Network ATC, which simplifies deployment and network configuration management for Azure Stack HCI clusters. Get to know Network HUD and how it can perform real-time analysis of network issues and provides prescriptive alerts or auto-remediation of the issue when possible. Learn how to greatly improve networking performance with Accelerated Networking.
Software Defined Networking
Take a whirlwind tour of the most requested and exciting new core features for Software Defined Networking (SDN) in this jam-packed session of demos! We’ll share advancements in network security and Azure Kubernetes Service (AKS) integrations! If that isn’t enough, we’ll share great resources to help you learn and advance your skills fast. This is a session you won’t want to miss!
Microsoft Tech Community – Latest Blogs –Read More
Why do I get “Maximum variable size allowed on the device is exceeded.” error when running the “semanticseg” function on my image and custom network?
I am trying to run the "semanticseg" function on an image with size (8557×11377) and my own custom network, and I receive the error:
ERROR: Error using nnet.internal.cnngpu.convolveForward2D
Maximum variable size allowed on the device is exceeded.
I expect MATLAB to tile the image, run the semantic segmentation, and reassemble the tile, but I am receiving this error on a windows laptop with a GTX 1070 card.
The two questions I have are:
1) Why do I receive this error message?
2) I would like to know what the maximum allowed image size I can have with my own custom network when running the "semanticseg" function.I am trying to run the "semanticseg" function on an image with size (8557×11377) and my own custom network, and I receive the error:
ERROR: Error using nnet.internal.cnngpu.convolveForward2D
Maximum variable size allowed on the device is exceeded.
I expect MATLAB to tile the image, run the semantic segmentation, and reassemble the tile, but I am receiving this error on a windows laptop with a GTX 1070 card.
The two questions I have are:
1) Why do I receive this error message?
2) I would like to know what the maximum allowed image size I can have with my own custom network when running the "semanticseg" function. I am trying to run the "semanticseg" function on an image with size (8557×11377) and my own custom network, and I receive the error:
ERROR: Error using nnet.internal.cnngpu.convolveForward2D
Maximum variable size allowed on the device is exceeded.
I expect MATLAB to tile the image, run the semantic segmentation, and reassemble the tile, but I am receiving this error on a windows laptop with a GTX 1070 card.
The two questions I have are:
1) Why do I receive this error message?
2) I would like to know what the maximum allowed image size I can have with my own custom network when running the "semanticseg" function. convolveforward2d, semanticseg MATLAB Answers — New Questions
ANSYS Fluent and Simulink co-simulation in real time.
Hello,
I want to test a temperature and air flow pattern in a room in ANSYS Fluent but the same time i want a co-simulation with Simulink so that i can modify parameters in Simulink and observe the variation in Fluent. How to do that….??
thanxHello,
I want to test a temperature and air flow pattern in a room in ANSYS Fluent but the same time i want a co-simulation with Simulink so that i can modify parameters in Simulink and observe the variation in Fluent. How to do that….??
thanx Hello,
I want to test a temperature and air flow pattern in a room in ANSYS Fluent but the same time i want a co-simulation with Simulink so that i can modify parameters in Simulink and observe the variation in Fluent. How to do that….??
thanx ansys fluent and simulink co-simulation in real ti MATLAB Answers — New Questions
how to make the numbers on the matrix with alternative sign?
I want to create a matrix that the main diagonal of K are alternatively 2 and -2’s, the sub- and sup-diagonal of K alternatively
1 and -1’s, and everywhere else 0. The size of K is 2n by 2n.
Here is what I got so far.
x=ones(1,5);
y=ones(1,4);
x2=2*x;
y2=y*-1;
z=diag(x2,0)
[rows, columns] = size(z)
z(1:2*rows+2:end) = -z(1:2*rows+2:end)
b=diag(y2,+1)
d=diag(y2,-1)
g=z+b+dI want to create a matrix that the main diagonal of K are alternatively 2 and -2’s, the sub- and sup-diagonal of K alternatively
1 and -1’s, and everywhere else 0. The size of K is 2n by 2n.
Here is what I got so far.
x=ones(1,5);
y=ones(1,4);
x2=2*x;
y2=y*-1;
z=diag(x2,0)
[rows, columns] = size(z)
z(1:2*rows+2:end) = -z(1:2*rows+2:end)
b=diag(y2,+1)
d=diag(y2,-1)
g=z+b+d I want to create a matrix that the main diagonal of K are alternatively 2 and -2’s, the sub- and sup-diagonal of K alternatively
1 and -1’s, and everywhere else 0. The size of K is 2n by 2n.
Here is what I got so far.
x=ones(1,5);
y=ones(1,4);
x2=2*x;
y2=y*-1;
z=diag(x2,0)
[rows, columns] = size(z)
z(1:2*rows+2:end) = -z(1:2*rows+2:end)
b=diag(y2,+1)
d=diag(y2,-1)
g=z+b+d matrix manipulation MATLAB Answers — New Questions
