Category: News
Activate the automatic Office update (for M365 apps) via PowerShell
Hello,
We have installed M365 products for many customers and most of them have automatic updates enabled in their account settings. But not all. Since we don’t want to change over manually for our customers, we are looking for a way to do this via PowerShell.
In the article from Microsoft (https://learn.microsoft.com/de-de/microsoft-365/troubleshoot/updates/automatic-updates) registry keys are specified, but these neither set for devices with automatic updates nor for devices with deactivated updates.
Does anyone have a tip where to find the correct registry key or how else the automatic updates can be activated via PowerShell?
(Via GPO is not a solution because not all customers have an Active Directory, but the devices are entra-joined)
I look forward to ideas and suggestions.
Lisa
Hello, We have installed M365 products for many customers and most of them have automatic updates enabled in their account settings. But not all. Since we don’t want to change over manually for our customers, we are looking for a way to do this via PowerShell.In the article from Microsoft (https://learn.microsoft.com/de-de/microsoft-365/troubleshoot/updates/automatic-updates) registry keys are specified, but these neither set for devices with automatic updates nor for devices with deactivated updates.Does anyone have a tip where to find the correct registry key or how else the automatic updates can be activated via PowerShell?(Via GPO is not a solution because not all customers have an Active Directory, but the devices are entra-joined) I look forward to ideas and suggestions. Lisa Read More
No company Apps after signing in using company portal
Hi All
I really need your help on this issue, yesterday after playing with lots of settings I can’t figure out where is my mistake.
1. When I log in using Company Portal to enroll Android device (Personally-Owned with Work Profile), I can sign in without problems, with no Erros, but the device is not enrolled, and no apps shown.
2. Two days ago (before playing with multiple settings), I was able to log in with multiple test users accounts and apps was displayed normally.
3. I checked device policy and configuration policy and things seems OK.
4. After facing this problem, even did not apply Conditional access to the device group where this device belongs.
5. When I log in, I do not get to the setup access page where it starts to create profile and activate work profile and update device settings.
6. I even factory reset the Samsung s24 device but still the same.
7. Apps are assigned to the group where the device belongs.
8. One user even succeeded to enroll his device normally, so I added the testing user to that group and signed in, but it is still the same!!
9. I created two groups:
one for corporate owned devices with Work profile and devices works OK
Second for Personally owned devices with Work profile, one device enrolled and works, others not.
Definitely I am missing something, everything was not that complicated when I made the initial configuration.
Any suggestion where the problem could be?
Hi AllI really need your help on this issue, yesterday after playing with lots of settings I can’t figure out where is my mistake. 1. When I log in using Company Portal to enroll Android device (Personally-Owned with Work Profile), I can sign in without problems, with no Erros, but the device is not enrolled, and no apps shown.2. Two days ago (before playing with multiple settings), I was able to log in with multiple test users accounts and apps was displayed normally.3. I checked device policy and configuration policy and things seems OK.4. After facing this problem, even did not apply Conditional access to the device group where this device belongs.5. When I log in, I do not get to the setup access page where it starts to create profile and activate work profile and update device settings.6. I even factory reset the Samsung s24 device but still the same.7. Apps are assigned to the group where the device belongs.8. One user even succeeded to enroll his device normally, so I added the testing user to that group and signed in, but it is still the same!!9. I created two groups:one for corporate owned devices with Work profile and devices works OKSecond for Personally owned devices with Work profile, one device enrolled and works, others not. Definitely I am missing something, everything was not that complicated when I made the initial configuration. Any suggestion where the problem could be? Read More
Computing Euler Angles from MoCap Markers 3D Data
I have obtained 3D (x,y,z) data from a Motion Capture (MoCap) system using markers placed on the subject’s head and chin. The data is structured in the following format. I need to compute the Euler angles (yaw, pitch, and roll). Any assistanse in this matter would be greatly appreciated.
headFL = [data.HeadFL_X, data.HeadFL_Y, data.HeadFL_Z];
headFR = [data.HeadFR_X, data.HeadFR_Y, data.HeadFR_Z];
headBL = [data.HeadBL_X, data.HeadBL_Y, data.HeadBL_Z];
headBR = [data.HeadBR_X, data.HeadBR_Y, data.HeadBR_Z];
chin = [data.Chin_X, data.Chin_Y, data.Chin_Z];
headFL = [-97.507,-105.897,1594.74]
headFR = [-186.455,-9.66,1609.556]
headBL = [20.236,-15.579,1544.697]
headBR = [-86.745, 98.811,1557.386]
Chin = [-169.193,-74.004,1431.651]I have obtained 3D (x,y,z) data from a Motion Capture (MoCap) system using markers placed on the subject’s head and chin. The data is structured in the following format. I need to compute the Euler angles (yaw, pitch, and roll). Any assistanse in this matter would be greatly appreciated.
headFL = [data.HeadFL_X, data.HeadFL_Y, data.HeadFL_Z];
headFR = [data.HeadFR_X, data.HeadFR_Y, data.HeadFR_Z];
headBL = [data.HeadBL_X, data.HeadBL_Y, data.HeadBL_Z];
headBR = [data.HeadBR_X, data.HeadBR_Y, data.HeadBR_Z];
chin = [data.Chin_X, data.Chin_Y, data.Chin_Z];
headFL = [-97.507,-105.897,1594.74]
headFR = [-186.455,-9.66,1609.556]
headBL = [20.236,-15.579,1544.697]
headBR = [-86.745, 98.811,1557.386]
Chin = [-169.193,-74.004,1431.651] I have obtained 3D (x,y,z) data from a Motion Capture (MoCap) system using markers placed on the subject’s head and chin. The data is structured in the following format. I need to compute the Euler angles (yaw, pitch, and roll). Any assistanse in this matter would be greatly appreciated.
headFL = [data.HeadFL_X, data.HeadFL_Y, data.HeadFL_Z];
headFR = [data.HeadFR_X, data.HeadFR_Y, data.HeadFR_Z];
headBL = [data.HeadBL_X, data.HeadBL_Y, data.HeadBL_Z];
headBR = [data.HeadBR_X, data.HeadBR_Y, data.HeadBR_Z];
chin = [data.Chin_X, data.Chin_Y, data.Chin_Z];
headFL = [-97.507,-105.897,1594.74]
headFR = [-186.455,-9.66,1609.556]
headBL = [20.236,-15.579,1544.697]
headBR = [-86.745, 98.811,1557.386]
Chin = [-169.193,-74.004,1431.651] transferred MATLAB Answers — New Questions
How to write a point’s coordinates
How can I write coordinates of my extrema on a figure?
I tried using "text" command but I stiil can’t deal with the problemHow can I write coordinates of my extrema on a figure?
I tried using "text" command but I stiil can’t deal with the problem How can I write coordinates of my extrema on a figure?
I tried using "text" command but I stiil can’t deal with the problem coordinates-figure-write, coordinates-figure-write-plot, coordinates_figure_write_plot, coordinates_figure_write, plot MATLAB Answers — New Questions
how mixing pressure Pm is calculated in gas ejector model of Matlab
how mixing pressure Pm is calculated in gas ejector model of Matlabhow mixing pressure Pm is calculated in gas ejector model of Matlab how mixing pressure Pm is calculated in gas ejector model of Matlab simulink, gas ejector model MATLAB Answers — New Questions
Invalid training data Predictors must be a N-by-1 cell array of sequences
% Reshape training data for LSTM input and output
num_features = size(X_train, 2);
num_samples_per_day = 24; % Number of hours in a day
num_days_train = size(X_train, 1) / num_samples_per_day;
X_train_reshaped = cell(num_days_train, 1);
y_train_reshaped = cell(num_days_train, 1);
for a = 1:num_days_train
start_idx = (a – 1) * num_samples_per_day + 1;
end_idx = a * num_samples_per_day;
% Extract data for the current day
current_day_data = X_train(start_idx:end_idx, :);
current_day_target = y_train(start_idx:end_idx);
% Reshape data into a cell array of matrices [num_features x num_samples_per_day]
reshaped_data = num2cell(current_day_data’, 1);
X_train_reshaped{a} = reshaped_data;
% Reshape target values into a cell array of column vectors
reshaped_target = reshape(current_day_target, [], 1);
y_train_reshaped{a} = reshaped_target;
end
% Reshape validation data for LSTM input
num_days_val = size(X_val, 1) / num_samples_per_day;
X_val_reshaped = cell(num_days_val, 1);
y_val_reshaped = cell(num_days_val, 1);
for b = 1:num_days_val
start_idx = (b – 1) * num_samples_per_day + 1;
end_idx = b * num_samples_per_day;
% Extract data for the current day
current_day_data = X_val(start_idx:end_idx, :);
current_day_target = y_val(start_idx:end_idx);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Reshape target values into a column vector
reshaped_target = current_day_target’;
% Store reshaped data and target for the current day
X_val_reshaped{b} = reshaped_data;
y_val_reshaped{b} = reshaped_target;
end
% Reshape test data for LSTM input
num_days_test = size(X_test, 1) / num_samples_per_day;
X_test_reshaped = cell(num_days_test, 1);
for c = 1:num_days_test
start_idx = (c – 1) * num_samples_per_day + 1;
end_idx = c * num_samples_per_day;
% Extract data for the current day
current_day_data = X_test(start_idx:end_idx, :);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Store reshaped data for the current day
X_test_reshaped{c} = reshaped_data;
end
% Define hyperparameters for grid search
hidden_layers = [1, 2, 3];
num_hidden_units_range = [24, 48, 96, 192];
dropout_rates = [0.1, 0.2, 0.3, 0.4, 0.5];
learning_rates = [0.05, 0.01, 0.005, 0.001, 0.0005];
optimization_solvers_list = {‘adam’, ‘sgdm’, ‘rmsprop’};
num_epochs_range = [50, 100, 150, 200, 250];
% Build LSTM model
layers = [
sequenceInputLayer(num_features)
];
for m = 1:num_layers
layers = [
layers
lstmLayer(num_units, ‘OutputMode’, ‘sequence’)
dropoutLayer(dropout_rate)
];
end
% Connect the last LSTM layer to a fully connected layer
layers = [
layers
fullyConnectedLayer(num_units)
dropoutLayer(dropout_rate)
fullyConnectedLayer(24) % Output layer with 24 units for 24-hour GHI forecasting
regressionLayer % Output layer for regression tasks
];
% Set options for training
options = trainingOptions(optimizer, …
‘MaxEpochs’, num_epochs, …
‘MiniBatchSize’, 64, …
‘InitialLearnRate’, learning_rate, …
‘LearnRateSchedule’, ‘piecewise’, …
‘LearnRateDropPeriod’, 50, …
‘LearnRateDropFactor’, 0.1, …
‘ValidationData’, {X_val_reshaped, y_val_reshaped}, …
‘ValidationFrequency’, 10, …
‘ValidationPatience’, 20, …
‘Verbose’, 0, …
‘Plots’, ‘training-progress’);
% Train the LSTM model
lstm_model = trainNetwork(X_train_reshaped, y_train_reshaped, layers, options);
% Predict GHI using the trained model on validation data
y_pred_val = predict(lstm_model, X_val_reshaped);
% Denormalize predictions
y_pred_denormalized = y_pred_val * (max(features.GHI) – min(features.GHI)) + min(features.GHI);
% Calculate evaluation metrics
rmse_val = calculate_rmse(y_val, y_pred_val_denormalized);
mae_val = calculate_mae(y_val, y_pred_val_denormalized);
end
Error using trainNetwork (line 184)
Invalid training data. Predictors must be a N-by-1 cell array of sequences, where N is the number of sequences. All
sequences must have the same feature dimension and at least one time step.% Reshape training data for LSTM input and output
num_features = size(X_train, 2);
num_samples_per_day = 24; % Number of hours in a day
num_days_train = size(X_train, 1) / num_samples_per_day;
X_train_reshaped = cell(num_days_train, 1);
y_train_reshaped = cell(num_days_train, 1);
for a = 1:num_days_train
start_idx = (a – 1) * num_samples_per_day + 1;
end_idx = a * num_samples_per_day;
% Extract data for the current day
current_day_data = X_train(start_idx:end_idx, :);
current_day_target = y_train(start_idx:end_idx);
% Reshape data into a cell array of matrices [num_features x num_samples_per_day]
reshaped_data = num2cell(current_day_data’, 1);
X_train_reshaped{a} = reshaped_data;
% Reshape target values into a cell array of column vectors
reshaped_target = reshape(current_day_target, [], 1);
y_train_reshaped{a} = reshaped_target;
end
% Reshape validation data for LSTM input
num_days_val = size(X_val, 1) / num_samples_per_day;
X_val_reshaped = cell(num_days_val, 1);
y_val_reshaped = cell(num_days_val, 1);
for b = 1:num_days_val
start_idx = (b – 1) * num_samples_per_day + 1;
end_idx = b * num_samples_per_day;
% Extract data for the current day
current_day_data = X_val(start_idx:end_idx, :);
current_day_target = y_val(start_idx:end_idx);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Reshape target values into a column vector
reshaped_target = current_day_target’;
% Store reshaped data and target for the current day
X_val_reshaped{b} = reshaped_data;
y_val_reshaped{b} = reshaped_target;
end
% Reshape test data for LSTM input
num_days_test = size(X_test, 1) / num_samples_per_day;
X_test_reshaped = cell(num_days_test, 1);
for c = 1:num_days_test
start_idx = (c – 1) * num_samples_per_day + 1;
end_idx = c * num_samples_per_day;
% Extract data for the current day
current_day_data = X_test(start_idx:end_idx, :);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Store reshaped data for the current day
X_test_reshaped{c} = reshaped_data;
end
% Define hyperparameters for grid search
hidden_layers = [1, 2, 3];
num_hidden_units_range = [24, 48, 96, 192];
dropout_rates = [0.1, 0.2, 0.3, 0.4, 0.5];
learning_rates = [0.05, 0.01, 0.005, 0.001, 0.0005];
optimization_solvers_list = {‘adam’, ‘sgdm’, ‘rmsprop’};
num_epochs_range = [50, 100, 150, 200, 250];
% Build LSTM model
layers = [
sequenceInputLayer(num_features)
];
for m = 1:num_layers
layers = [
layers
lstmLayer(num_units, ‘OutputMode’, ‘sequence’)
dropoutLayer(dropout_rate)
];
end
% Connect the last LSTM layer to a fully connected layer
layers = [
layers
fullyConnectedLayer(num_units)
dropoutLayer(dropout_rate)
fullyConnectedLayer(24) % Output layer with 24 units for 24-hour GHI forecasting
regressionLayer % Output layer for regression tasks
];
% Set options for training
options = trainingOptions(optimizer, …
‘MaxEpochs’, num_epochs, …
‘MiniBatchSize’, 64, …
‘InitialLearnRate’, learning_rate, …
‘LearnRateSchedule’, ‘piecewise’, …
‘LearnRateDropPeriod’, 50, …
‘LearnRateDropFactor’, 0.1, …
‘ValidationData’, {X_val_reshaped, y_val_reshaped}, …
‘ValidationFrequency’, 10, …
‘ValidationPatience’, 20, …
‘Verbose’, 0, …
‘Plots’, ‘training-progress’);
% Train the LSTM model
lstm_model = trainNetwork(X_train_reshaped, y_train_reshaped, layers, options);
% Predict GHI using the trained model on validation data
y_pred_val = predict(lstm_model, X_val_reshaped);
% Denormalize predictions
y_pred_denormalized = y_pred_val * (max(features.GHI) – min(features.GHI)) + min(features.GHI);
% Calculate evaluation metrics
rmse_val = calculate_rmse(y_val, y_pred_val_denormalized);
mae_val = calculate_mae(y_val, y_pred_val_denormalized);
end
Error using trainNetwork (line 184)
Invalid training data. Predictors must be a N-by-1 cell array of sequences, where N is the number of sequences. All
sequences must have the same feature dimension and at least one time step. % Reshape training data for LSTM input and output
num_features = size(X_train, 2);
num_samples_per_day = 24; % Number of hours in a day
num_days_train = size(X_train, 1) / num_samples_per_day;
X_train_reshaped = cell(num_days_train, 1);
y_train_reshaped = cell(num_days_train, 1);
for a = 1:num_days_train
start_idx = (a – 1) * num_samples_per_day + 1;
end_idx = a * num_samples_per_day;
% Extract data for the current day
current_day_data = X_train(start_idx:end_idx, :);
current_day_target = y_train(start_idx:end_idx);
% Reshape data into a cell array of matrices [num_features x num_samples_per_day]
reshaped_data = num2cell(current_day_data’, 1);
X_train_reshaped{a} = reshaped_data;
% Reshape target values into a cell array of column vectors
reshaped_target = reshape(current_day_target, [], 1);
y_train_reshaped{a} = reshaped_target;
end
% Reshape validation data for LSTM input
num_days_val = size(X_val, 1) / num_samples_per_day;
X_val_reshaped = cell(num_days_val, 1);
y_val_reshaped = cell(num_days_val, 1);
for b = 1:num_days_val
start_idx = (b – 1) * num_samples_per_day + 1;
end_idx = b * num_samples_per_day;
% Extract data for the current day
current_day_data = X_val(start_idx:end_idx, :);
current_day_target = y_val(start_idx:end_idx);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Reshape target values into a column vector
reshaped_target = current_day_target’;
% Store reshaped data and target for the current day
X_val_reshaped{b} = reshaped_data;
y_val_reshaped{b} = reshaped_target;
end
% Reshape test data for LSTM input
num_days_test = size(X_test, 1) / num_samples_per_day;
X_test_reshaped = cell(num_days_test, 1);
for c = 1:num_days_test
start_idx = (c – 1) * num_samples_per_day + 1;
end_idx = c * num_samples_per_day;
% Extract data for the current day
current_day_data = X_test(start_idx:end_idx, :);
% Reshape data into a matrix [num_features x num_samples_per_day]
reshaped_data = current_day_data’;
% Store reshaped data for the current day
X_test_reshaped{c} = reshaped_data;
end
% Define hyperparameters for grid search
hidden_layers = [1, 2, 3];
num_hidden_units_range = [24, 48, 96, 192];
dropout_rates = [0.1, 0.2, 0.3, 0.4, 0.5];
learning_rates = [0.05, 0.01, 0.005, 0.001, 0.0005];
optimization_solvers_list = {‘adam’, ‘sgdm’, ‘rmsprop’};
num_epochs_range = [50, 100, 150, 200, 250];
% Build LSTM model
layers = [
sequenceInputLayer(num_features)
];
for m = 1:num_layers
layers = [
layers
lstmLayer(num_units, ‘OutputMode’, ‘sequence’)
dropoutLayer(dropout_rate)
];
end
% Connect the last LSTM layer to a fully connected layer
layers = [
layers
fullyConnectedLayer(num_units)
dropoutLayer(dropout_rate)
fullyConnectedLayer(24) % Output layer with 24 units for 24-hour GHI forecasting
regressionLayer % Output layer for regression tasks
];
% Set options for training
options = trainingOptions(optimizer, …
‘MaxEpochs’, num_epochs, …
‘MiniBatchSize’, 64, …
‘InitialLearnRate’, learning_rate, …
‘LearnRateSchedule’, ‘piecewise’, …
‘LearnRateDropPeriod’, 50, …
‘LearnRateDropFactor’, 0.1, …
‘ValidationData’, {X_val_reshaped, y_val_reshaped}, …
‘ValidationFrequency’, 10, …
‘ValidationPatience’, 20, …
‘Verbose’, 0, …
‘Plots’, ‘training-progress’);
% Train the LSTM model
lstm_model = trainNetwork(X_train_reshaped, y_train_reshaped, layers, options);
% Predict GHI using the trained model on validation data
y_pred_val = predict(lstm_model, X_val_reshaped);
% Denormalize predictions
y_pred_denormalized = y_pred_val * (max(features.GHI) – min(features.GHI)) + min(features.GHI);
% Calculate evaluation metrics
rmse_val = calculate_rmse(y_val, y_pred_val_denormalized);
mae_val = calculate_mae(y_val, y_pred_val_denormalized);
end
Error using trainNetwork (line 184)
Invalid training data. Predictors must be a N-by-1 cell array of sequences, where N is the number of sequences. All
sequences must have the same feature dimension and at least one time step. hyperparameters fine-tune MATLAB Answers — New Questions
Microsoft Defender for Office 365 For Zoho Email Solution
Hello All,
I am currently having a mix of email solution providers between O365 and Zoho ( Cloud Based Email Solution) just need to understand the below:
1. Can I protect my 3rd party email solution with MDO P1
2. What are the licensing components i need to look at and its architecture
Thank you.
Hello All,
I am currently having a mix of email solution providers between O365 and Zoho ( Cloud Based Email Solution) just need to understand the below:
1. Can I protect my 3rd party email solution with MDO P1
2. What are the licensing components i need to look at and its architecture
Thank you. Read More
Clarify the purpose of labelling features in Microsoft Defender for Cloud Apps and Purview
I find the lineup of Microsoft’s products, bundles and licenses confusing. The names seem to change regularly and it is difficult to know whether documentation is referring to old or new features.
I’m looking into sensitivity labels and what features are available for different license levels. The main features are provided in the Purview portal but there are other sensitivity label features in Microsoft Defender for Cloud Apps.
From my understanding, a user with an Office 365 E3 license will be licensed for the entry level Purview components (Information Protection, Data Loss Prevention, Data lifecycle management, eDiscovery and auditing, insider risk management). You need to step up to Office 365 E5 to get auto-labeling features.
Microsoft Defender for Cloud Apps also has some sensitivity labeling features. I believe this requires a Microsoft 365 E5 or a (Office 365 E5 + Enterprise Mobility + Security E5). Which means you would also have access to most of the Purview features.
What is the difference between the Microsoft Defender for Cloud Apps sensitivity label features compared to the Purview features for Microsoft 365 content? Is it just for labeling content in other cloud services like Box and Dropbox? I saw one article that says the Cloud Apps feature can only label 100 (SharePoint?) items per day.
I find the lineup of Microsoft’s products, bundles and licenses confusing. The names seem to change regularly and it is difficult to know whether documentation is referring to old or new features. I’m looking into sensitivity labels and what features are available for different license levels. The main features are provided in the Purview portal but there are other sensitivity label features in Microsoft Defender for Cloud Apps. From my understanding, a user with an Office 365 E3 license will be licensed for the entry level Purview components (Information Protection, Data Loss Prevention, Data lifecycle management, eDiscovery and auditing, insider risk management). You need to step up to Office 365 E5 to get auto-labeling features. Microsoft Defender for Cloud Apps also has some sensitivity labeling features. I believe this requires a Microsoft 365 E5 or a (Office 365 E5 + Enterprise Mobility + Security E5). Which means you would also have access to most of the Purview features. What is the difference between the Microsoft Defender for Cloud Apps sensitivity label features compared to the Purview features for Microsoft 365 content? Is it just for labeling content in other cloud services like Box and Dropbox? I saw one article that says the Cloud Apps feature can only label 100 (SharePoint?) items per day. Read More
Accessing app centric permission via API
Hi,
is there any way to access (get/set) app centric permissions from GraphAPI or any other API? Our usecase is that we want to set the configuration programatically and also assign groups to specific apps without using the admin.teams portal.
Best Regards
Lars
Hi, is there any way to access (get/set) app centric permissions from GraphAPI or any other API? Our usecase is that we want to set the configuration programatically and also assign groups to specific apps without using the admin.teams portal. Best Regards Lars Read More
“For loop” to plot graphs of functions
I’m trying to write a matlab (for loop) code to produce the graphs:
Q as a function of A,
F as a function of A,
Z as a function of A
from the known functions f1, f2 and f3
Z = f1 (A, F, Q)
F = f2 (A, Q, Z)
A = f3 (Z, Q).
I made several attempts that were unsuccessful, if anyone can help me I would thank you a lot.I’m trying to write a matlab (for loop) code to produce the graphs:
Q as a function of A,
F as a function of A,
Z as a function of A
from the known functions f1, f2 and f3
Z = f1 (A, F, Q)
F = f2 (A, Q, Z)
A = f3 (Z, Q).
I made several attempts that were unsuccessful, if anyone can help me I would thank you a lot. I’m trying to write a matlab (for loop) code to produce the graphs:
Q as a function of A,
F as a function of A,
Z as a function of A
from the known functions f1, f2 and f3
Z = f1 (A, F, Q)
F = f2 (A, Q, Z)
A = f3 (Z, Q).
I made several attempts that were unsuccessful, if anyone can help me I would thank you a lot. for loop MATLAB Answers — New Questions
Unable to create a STM32CubeMX Project using “Embedded Coder Support Package for STMicroelectronics STM32 Processors”
Hello Comunity,
I am trying to create new project for STM32F4xx based boards. But I can not create the create project biuld options in Simulink Hardware implementation. I have attached the screenshot of the error. I have followed the step shown in the msg and tried to do hardware setup. I have already installed required STM32 CubeMX(v6.4.0) and STM32CubeProgrammer(v2.6.0) as recommended by the simulink hardware support package andthe installation paths are also validated. I was able to complete the setup but still it pops up.Hello Comunity,
I am trying to create new project for STM32F4xx based boards. But I can not create the create project biuld options in Simulink Hardware implementation. I have attached the screenshot of the error. I have followed the step shown in the msg and tried to do hardware setup. I have already installed required STM32 CubeMX(v6.4.0) and STM32CubeProgrammer(v2.6.0) as recommended by the simulink hardware support package andthe installation paths are also validated. I was able to complete the setup but still it pops up. Hello Comunity,
I am trying to create new project for STM32F4xx based boards. But I can not create the create project biuld options in Simulink Hardware implementation. I have attached the screenshot of the error. I have followed the step shown in the msg and tried to do hardware setup. I have already installed required STM32 CubeMX(v6.4.0) and STM32CubeProgrammer(v2.6.0) as recommended by the simulink hardware support package andthe installation paths are also validated. I was able to complete the setup but still it pops up. embedded coder support package, stmicroelectronics, stm32f4xx based board, simulink, model configuration MATLAB Answers — New Questions
AKS Networking || Bring your own CNI plugin (BYOC)
Bring your own Container Network Interface (BYOCNI) plugin with Azure Kubernetes Service (AKS)
What is BYOCNI?
BYOCNI stands for Bring Your Own Container Network Interface. It allows advanced AKS users to deploy an AKS cluster with no CNI plugin preinstalled. Instead, you can install any third-party CNI plugin that works in Azure. This flexibility enables you to use the same CNI plugin used in on-premises Kubernetes environments or leverage advanced functionalities available in other CNI plugins.
Before diving into BYOCNI, ensure the following prerequisites are met:
– Use at least template version 2022-01-02-preview or 2022-06-01 for Azure Resource Manager (ARM) or Bicep.
– Have Azure CLI version 2.39.0 or later.
– The virtual network for the AKS cluster must allow outbound internet connectivity.
– Avoid using specific address ranges (e.g., 169.254.0.0/16, 172.30.0.0/16, 172.31.0.0/16, or 192.0.2.0/24) for Kubernetes service, pod address range, or cluster virtual network address range.
– The Identity used by the AKS cluster need to have least Network Contributor permissions on the subnet within your virtual network. Or you can use the custom role which has “Microsoft.Network/virtualNetworks/subnets/join/action and Microsoft.Network/virtualNetworks/subnets/read” permission.
– Subnet cannot be a delegated subnet used by AKS node pool.
– AKS doesn’t apply NSGs to its subnet or modify any of the NSGs associated with that subnet. If you add custom NSGs to the subnet, ensure the security rules allow traffic within the node CIDR range.
Deploy AKS cluster with no CNI plugin preinstalled:
You can deploy the AKS cluster with different Infrastructure as code (IAC) and CLI. We just need to pass network-plugin with the value as none. Refer the below snapping for the same.
1. Azure CLI:
2. Terraform:
3. ARM template:
4. Bicep:
Upon a successfully deployment you can see the AKS cluster is online, but all the nodes are not ready, you can check and verify the same on the azure poral as well as by running the kubectl commands as shown below,
Azure portal:
kubectl:
We can clearly see the reason:NetworkPluginNotReady in the blow snapping.
Now to make the nodes ready we need to install the network plugin. To do so you can leverage BYOCNI plugin third-party vendor such as Cilium, Flannel and Weave. Apart from these three there are so many other 3rd party plugins as well. You can run the below command to install the network plugin. In my Case I have used Flannel.
kubectl apply -f https://raw.githubusercontent.com/coreos/flannel/master/Documentation/kube-flannel.yml
After applying the above kubectl commands the nods are now in ready state as you can see below,
Portal:
Using kubectl:
Note:
Remember that Microsoft support cannot assist with CNI-related issues in clusters deployed with BYOCNI. For CNI-related support, consider using a supported AKS network plugin or seek support from the third-party vendor of your chosen CNI plugin. Support is still provided for non-CNI-related issues.
BYOCNI empowers you to tailor your AKS networking to your specific requirements.
Microsoft Tech Community – Latest Blogs –Read More
Problem with validation of the covariance matrix P in the steady state continuous Kalman filter
Hi I am trying to verify on simulations that the covariance matrix of the estimation errror is equal to the matrix P provided by the Riccati Solution of a continuous kalman filter. However when I use lsim to simulate and get the covariance of the estimator error vectors the results are different from P. But if I do P*Ts I can see the equivalence.
Why this factor Ts is appearing?
I am using the following code:
clear
close all
clc
% System
A = [-10 -20;35 -50];
B = [1; 1;];
C = [1 0];
D = 0;
Fs = 50000; % Frequency
Ts = 1/Fs; %
t = 0:Ts:10;
L = length(t);
W = [20 0;0 10];
V = 1;
rng(10,’twister’);
w = chol(W, ‘lower’)*randn(2,L);
v = chol(V, ‘lower’)*randn(1,L);
mw = mean(w,2);
mv = mean(v);
v = v – mean(v)*ones(1,length(v));
w = w – mw.*ones(2,length(v));
cov_w = cov(w’);
cov_v = cov(v);
[Lk,P] = lqe(A,eye(2),C,W,V);
% Augmented system with plant and Kalman filter
Aak = [A zeros(2,2); Lk*C A-Lk*C];
Bak = [B eye(2) zeros(2,1); B zeros(2,2) Lk];
sys_obs_mak = ss(Aak,Bak,eye(4),0);
u(1,:) = 1*heaviside(t);
[yk,t,xk] = lsim(sys_obs_mak,[u’ w’ v’],t,[0 0 0 0]); % Simulation
erro = xk(:,1:2)-xk(:,3:4);
cov_erro_lsim = cov(erro)
PTs = P*Ts
PHi I am trying to verify on simulations that the covariance matrix of the estimation errror is equal to the matrix P provided by the Riccati Solution of a continuous kalman filter. However when I use lsim to simulate and get the covariance of the estimator error vectors the results are different from P. But if I do P*Ts I can see the equivalence.
Why this factor Ts is appearing?
I am using the following code:
clear
close all
clc
% System
A = [-10 -20;35 -50];
B = [1; 1;];
C = [1 0];
D = 0;
Fs = 50000; % Frequency
Ts = 1/Fs; %
t = 0:Ts:10;
L = length(t);
W = [20 0;0 10];
V = 1;
rng(10,’twister’);
w = chol(W, ‘lower’)*randn(2,L);
v = chol(V, ‘lower’)*randn(1,L);
mw = mean(w,2);
mv = mean(v);
v = v – mean(v)*ones(1,length(v));
w = w – mw.*ones(2,length(v));
cov_w = cov(w’);
cov_v = cov(v);
[Lk,P] = lqe(A,eye(2),C,W,V);
% Augmented system with plant and Kalman filter
Aak = [A zeros(2,2); Lk*C A-Lk*C];
Bak = [B eye(2) zeros(2,1); B zeros(2,2) Lk];
sys_obs_mak = ss(Aak,Bak,eye(4),0);
u(1,:) = 1*heaviside(t);
[yk,t,xk] = lsim(sys_obs_mak,[u’ w’ v’],t,[0 0 0 0]); % Simulation
erro = xk(:,1:2)-xk(:,3:4);
cov_erro_lsim = cov(erro)
PTs = P*Ts
P Hi I am trying to verify on simulations that the covariance matrix of the estimation errror is equal to the matrix P provided by the Riccati Solution of a continuous kalman filter. However when I use lsim to simulate and get the covariance of the estimator error vectors the results are different from P. But if I do P*Ts I can see the equivalence.
Why this factor Ts is appearing?
I am using the following code:
clear
close all
clc
% System
A = [-10 -20;35 -50];
B = [1; 1;];
C = [1 0];
D = 0;
Fs = 50000; % Frequency
Ts = 1/Fs; %
t = 0:Ts:10;
L = length(t);
W = [20 0;0 10];
V = 1;
rng(10,’twister’);
w = chol(W, ‘lower’)*randn(2,L);
v = chol(V, ‘lower’)*randn(1,L);
mw = mean(w,2);
mv = mean(v);
v = v – mean(v)*ones(1,length(v));
w = w – mw.*ones(2,length(v));
cov_w = cov(w’);
cov_v = cov(v);
[Lk,P] = lqe(A,eye(2),C,W,V);
% Augmented system with plant and Kalman filter
Aak = [A zeros(2,2); Lk*C A-Lk*C];
Bak = [B eye(2) zeros(2,1); B zeros(2,2) Lk];
sys_obs_mak = ss(Aak,Bak,eye(4),0);
u(1,:) = 1*heaviside(t);
[yk,t,xk] = lsim(sys_obs_mak,[u’ w’ v’],t,[0 0 0 0]); % Simulation
erro = xk(:,1:2)-xk(:,3:4);
cov_erro_lsim = cov(erro)
PTs = P*Ts
P kalman filter MATLAB Answers — New Questions
How do I remove outliers in data so that vectors are of the same length for plotting?
Please see the attached excel file.
X = First column data
Y = Second column data
I have to ensure that both the vectors are of the same length for plotting and curve-fitting purpose. How do I get rid of the outliers in the Y-values such that the corresponding X-values are also lost?Please see the attached excel file.
X = First column data
Y = Second column data
I have to ensure that both the vectors are of the same length for plotting and curve-fitting purpose. How do I get rid of the outliers in the Y-values such that the corresponding X-values are also lost? Please see the attached excel file.
X = First column data
Y = Second column data
I have to ensure that both the vectors are of the same length for plotting and curve-fitting purpose. How do I get rid of the outliers in the Y-values such that the corresponding X-values are also lost? data import, plotting, signal processing, curve fitting MATLAB Answers — New Questions
Verify if my app has active connectivity with my databases?
Hi my apps are working but for example must display messages with the ticket fail and it doesn’t.
I’m attaching a picture when it worked well and a photo of what it does now.
How do I do to see that my app has everything it needs for its correct functioning?, Taking into account that it was working fine until before a Windows update that my server made, my database is SQL Server.
Hi my apps are working but for example must display messages with the ticket fail and it doesn’t.I’m attaching a picture when it worked well and a photo of what it does now.How do I do to see that my app has everything it needs for its correct functioning?, Taking into account that it was working fine until before a Windows update that my server made, my database is SQL Server. Read More
Azure Container Apps Newsletter – June 2024
Welcome to this month’s Azure Container Apps newsletter! We’ll share the latest news and community highlights for Container Apps every month here on the Apps on Azure blog.
Azure Container Apps monthly community live stream
Our next live stream is June 12, 2024 at 11:00AM PDT (18:00 UTC). Join us and our special guests to learn all about running untrusted code in sandboxes with dynamic sessions on Azure Container Apps.
Subscribe to the Azure Developers YouTube channel!
Community highlights
Some great content created by our amazing community:
Blogs
What Azure Container Apps Is Not: Clearing the Confusion
Azure Container Apps – Overview
Deploy 1Password SCIM Bridge on Azure Container Apps
Simplifying .NET microservices with Dapr and Azure Container Apps
Running a Playwright scheduled job with Azure Container Apps
Videos
Build Intelligent Apps with Serverless Containers on Azure Container Apps
From Day Zero To Production with Azure Container Apps
Goodbye Azure Kubernetes Service! Hello Azure Container Apps! – Johnny Hooyberghs
Azure Container Apps Docker Containers first deployment with Azure Front Door
Azure Container Apps uncovered: Scenarios, workloads, and portability
How to configure HTTP ingress in Azure Container Apps (playlist)
Working with Workload Profiles in Azure Container Apps
Build a multi-LLM chat application with Azure Container Apps
Azure Container Apps dynamic sessions
New: Secure Sandboxes at Scale with Azure Container Apps Dynamic Sessions
Bridging the chasm between your ML and app devs (Semantic Kernel)
Secure code execution in LlamaIndex with Azure Container Apps dynamic sessions
Integrating LangChain with Azure Container Apps dynamic sessions
Using Azure Container Apps dynamic sessions from Java
Read about all our Microsoft Build 2024 announcements!
For more, check out our product roadmap.
Get notified when we publish future newsletters, subscribe to the Apps on Azure blog. Connect with the Azure Container Apps team on GitHub, Twitter, and Discord.
Microsoft Tech Community – Latest Blogs –Read More
Is there any feasible method to automated labelling images for a deep learning task, which I have a lot of images to label which is not practically feasible to do manually
I am doing a medical imaging project with MRI images. I hope to develop a deep learning model for this task. But the data I collected is not labelled and I have to label them for each category. Can someone suggest me a method to automate this labelling process where it will be greatly save my time. Thanks in advance. !I am doing a medical imaging project with MRI images. I hope to develop a deep learning model for this task. But the data I collected is not labelled and I have to label them for each category. Can someone suggest me a method to automate this labelling process where it will be greatly save my time. Thanks in advance. ! I am doing a medical imaging project with MRI images. I hope to develop a deep learning model for this task. But the data I collected is not labelled and I have to label them for each category. Can someone suggest me a method to automate this labelling process where it will be greatly save my time. Thanks in advance. ! deep learning, image analysis, image processing, image labelling MATLAB Answers — New Questions
KQL Query email attachments
let domainList = externaldata(domain: string) [@”https://raw.githubusercontent.com/tsirolnik/spam-domains-list/master/spamdomains.txt“] with (format=”txt”);
let excludedDomains = datatable(excludeddomain :string) // Add as many domains you would like to exclude
[“126.com”,”163.com”,”dell.com”,”trustwave.com”,”microsoft.com”,”qq.com”,”accenture.com”,”hp.com”,”google.com”,”amazon.com”];
let Timeframe = 2d; // Choose the best timeframe for your investigation
let SuspiciousEmails = EmailEvents
| where Timestamp > ago(Timeframe)
| where EmailDirection == “Outbound” // Assuming you are looking into mails sent by your organization
| extend EmailDomain = tostring(split(RecipientEmailAddress, ‘@’)[1])
| join kind=inner (domainList) on $left.EmailDomain == $right.domain
| where not(EmailDomain in ([‘excludedDomains’]))
| project Timestamp, NetworkMessageId, SenderMailFromAddress, SenderFromAddress, SenderDisplayName, RecipientEmailAddress, EmailDomain, domain, Subject, LatestDeliveryAction;
SuspiciousEmails
| join (EmailEvents
| summarize count() by NetworkMessageId
| where count_ == 1
| project NetworkMessageId
)on NetworkMessageId
| sort by Timestamp desc
How can i show EmailAttachmentInfo, to show the FileName or Attachment that was being sent ?
let domainList = externaldata(domain: string) [@”https://raw.githubusercontent.com/tsirolnik/spam-domains-list/master/spamdomains.txt”] with (format=”txt”);let excludedDomains = datatable(excludeddomain :string) // Add as many domains you would like to exclude[“126.com”,”163.com”,”dell.com”,”trustwave.com”,”microsoft.com”,”qq.com”,”accenture.com”,”hp.com”,”google.com”,”amazon.com”];let Timeframe = 2d; // Choose the best timeframe for your investigationlet SuspiciousEmails = EmailEvents| where Timestamp > ago(Timeframe)| where EmailDirection == “Outbound” // Assuming you are looking into mails sent by your organization| extend EmailDomain = tostring(split(RecipientEmailAddress, ‘@’)[1])| join kind=inner (domainList) on $left.EmailDomain == $right.domain| where not(EmailDomain in ([‘excludedDomains’]))| project Timestamp, NetworkMessageId, SenderMailFromAddress, SenderFromAddress, SenderDisplayName, RecipientEmailAddress, EmailDomain, domain, Subject, LatestDeliveryAction;SuspiciousEmails| join (EmailEvents| summarize count() by NetworkMessageId| where count_ == 1| project NetworkMessageId)on NetworkMessageId| sort by Timestamp desc How can i show EmailAttachmentInfo, to show the FileName or Attachment that was being sent ? Read More
SAML causes significant process issues for IT
Hi,
Firstly I apologize if I’ve posted in the wrong section, I’m very new to the Microsoft forums/hubs? found navigating it very confusing for this particular subject anyway. Full disclosure, I’m not a specialist in the networking, server, authentication related fields, nor Active Directory/Azure for that matter.
I’m trying to identify a way to alleviate some process issues caused by SAML when authenticating users for key web-apps we use, two in particular, I’m not sure I’m at liberty to state what they are so I won’t for security reasons, but I can explain the current workflow.
System 1 Onboarding Workflow
1. In order to onboard a user for System1 you must…
Add them to the applicable AD groupSend an email to the user to request they loginOnce the user has logged in and provided they told us…We can assign permissions, reporting lines etc in System1
System 2 Onboarding Workflow
2. In order to onboard a user for System2 you must…
Add them to the applicable AD groupSend an email to the user to request they login Once the user has logged in and provided they told us…They would come back with an error message that means the admins of the system can now assign permissions/accessAdmins can then respond back to the user again to state they will now be able to login successfully
From my limited perspective and understanding, SAML waits for a user to attempt a login before anything happens, from an onboarding process perspective this is very time consuming and ineffective, especially considering the reliance on replies and huge number of onboarding requests we receive on a daily basis.
Thinking out loud to remove this problem, when a user is added to the AD group for that web-app, a process runs based on a detected change in users/groups and pushes that to the web-apps so no manual user login attempts are required, is it possible to do anything like this? or can you provide different solutions to this while still using SAML?
I should note that it is an absolute requirement users have access to these systems as soon as the day they join.
Fundamentally, the question I am asking is…
User registration in web-apps seems to require an SSO attempt by the user before that user appears in the web-apps user directory, is it possible to automate the web-app user registration so the manual user SSO attempt isn’t required?
Hi, Firstly I apologize if I’ve posted in the wrong section, I’m very new to the Microsoft forums/hubs? found navigating it very confusing for this particular subject anyway. Full disclosure, I’m not a specialist in the networking, server, authentication related fields, nor Active Directory/Azure for that matter. I’m trying to identify a way to alleviate some process issues caused by SAML when authenticating users for key web-apps we use, two in particular, I’m not sure I’m at liberty to state what they are so I won’t for security reasons, but I can explain the current workflow. System 1 Onboarding Workflow1. In order to onboard a user for System1 you must…Add them to the applicable AD groupSend an email to the user to request they loginOnce the user has logged in and provided they told us…We can assign permissions, reporting lines etc in System1 System 2 Onboarding Workflow2. In order to onboard a user for System2 you must…Add them to the applicable AD groupSend an email to the user to request they login Once the user has logged in and provided they told us…They would come back with an error message that means the admins of the system can now assign permissions/accessAdmins can then respond back to the user again to state they will now be able to login successfullyFrom my limited perspective and understanding, SAML waits for a user to attempt a login before anything happens, from an onboarding process perspective this is very time consuming and ineffective, especially considering the reliance on replies and huge number of onboarding requests we receive on a daily basis. Thinking out loud to remove this problem, when a user is added to the AD group for that web-app, a process runs based on a detected change in users/groups and pushes that to the web-apps so no manual user login attempts are required, is it possible to do anything like this? or can you provide different solutions to this while still using SAML? I should note that it is an absolute requirement users have access to these systems as soon as the day they join. Fundamentally, the question I am asking is…User registration in web-apps seems to require an SSO attempt by the user before that user appears in the web-apps user directory, is it possible to automate the web-app user registration so the manual user SSO attempt isn’t required? Read More
Embed existing app in teams tabs
I have an existing web app and I’d like to deploy a teams tab to the MS app store that simply embeds my app. I’m wondering if there is a way to avoid building an entirely separate app. I’d like to just add a manifest file to my existing repo and feed that to the teams client. Would this be possible?
I have an existing web app and I’d like to deploy a teams tab to the MS app store that simply embeds my app. I’m wondering if there is a way to avoid building an entirely separate app. I’d like to just add a manifest file to my existing repo and feed that to the teams client. Would this be possible? Read More