Margalla Orchards by DHA in Islamabad, Pakistan

 

(Source: Zameen.com)

Margalla Orchards by DHA was launched in 2015. Presently, its transfer is taking place in the office of Federal Government Employee Housing Society, but soon its transfer will start taking place in the DHA, Phase 5 office, which is the main office of DHA. It is near Park Road. Before August, the prices of 1 kanal plots (files) in this area were in the range of 80 lacs to 1 crores. Now, after being linked to DHA, the prices are in the range of 1.6 crore or near or above this, such as above 2 crores. Investment in any area in this place can be of good value. It is about 8500 kanals’ area. Immediately, in its neighbor is Park Enclave, where market rates are above 5 crores at a distance and 6 crores in the start. Comsats University is located in its front. It has different sectors, including A, B, C, etc. Within 3 years, the prices of plots in these sectors can be doubled.

Source:

Real Ustad - 𝐌𝐚𝐫𝐠𝐚𝐥𝐥𝐚 𝐎𝐫𝐜𝐡𝐚𝐫𝐝𝐬 𝐛𝐲 𝐃𝐇𝐀 𝐈𝐬𝐥𝐚𝐦𝐚𝐛𝐚𝐝 - 𝐄𝐯𝐞𝐫𝐲 𝐅𝐢𝐥𝐞 𝐢𝐬 𝐈𝐦𝐩𝐨𝐫𝐭𝐚𝐧𝐭 - https://www.youtube.com/watch?v=33zkpgH7Jdc

Day 10: A challenge to learn basics of Structural Equation Modeling (SEM) using lavaan and semPlot packages in R

 During the next 12 days, I will learn and repeat the basics of structural equation modeling (SEM) using lavaan and semPlot packages in R.

You can search my lavaan posts by typing: #UsmanZafarParacha_lavaan , and semPlot posts by typing: #UsmanZafarParacha_semPlot

=============

During this day, I loaded the essential libraries, and defined the SEM model using the following lines of codes:

 

# Load libraries

library(lavaan)

library(semPlot)

 

# Define the SEM model

model <- '

  # Direct effect of teacher experience on instructional methods

  InstructionalMethods ~ a * TeacherExperience

 

  # Direct effect of instructional methods on student performance

  StudentPerformance ~ b * InstructionalMethods

 

  # Direct effect of teacher experience on student performance

  StudentPerformance ~ c * TeacherExperience

 

  # Moderation: Classroom environment moderates the effect of instructional methods on student performance

  StudentPerformance ~ d * Interaction

 

  # Define indirect (mediation) effect

  indirect := a * b

 

  # Define total effect (direct + indirect effects)

  total := c + (a * b)

'

 

Then, a supposed data is generated using the following lines of codes:

 

# Generate sample data (if real data is not available)

set.seed(123)

n <- 300

data <- data.frame(

  TeacherExperience = rnorm(n, mean = 10, sd = 5),

  ClassroomEnvironment = rnorm(n, mean = 3, sd = 1),

  InstructionalMethods = rnorm(n, mean = 0, sd = 1),

  StudentPerformance = rnorm(n, mean = 75, sd = 10)

)

 

Then a relationship is created and interaction terms are established, as follows:

 

# Create relationships and interaction term

data$InstructionalMethods <- 0.5 * data$TeacherExperience + rnorm(n)

data$StudentPerformance <- 0.3 * data$TeacherExperience +

                           0.6 * data$InstructionalMethods +

                           0.4 * data$InstructionalMethods * data$ClassroomEnvironment +

                           rnorm(n)

data$Interaction <- data$InstructionalMethods * data$ClassroomEnvironment

 

Then we fit the model and visualized the SEM model using the following lines of codes:

 

# Fit the model

fit <- sem(model, data = data)

summary(fit, standardized = TRUE, fit.measures = TRUE)

 

# Visualize the SEM model

semPaths(fit,

         whatLabels = "std",

         layout = "tree",

         edge.color = "blue",

         sizeMan = 6,

         sizeLat = 8,

         fade = FALSE)

 

Source:

ChatGPT

Six important factors that can lead to increase in property rates and real estate business

 

The real estate market in Pakistan is going to go up during the next 4 to 6 months. The current account deficits in Pakistan would decrease that can help in improving the real estate market. This decrease can be linked to the amount/payment provided by IMF. Moreover, China, Saudi Arabia, and Russia are going to invest in Pakistan that can also help in improving economic stability. So, this foreign investment would help in the next few months.

Another point is that people from foreign countries would send money to Pakistan in the form of remittances that can also positively affect the real estate market. For instance, if we compare August from September, there has been about 29% increase in foreign remittances.

Another interesting thing is that inflation is very much controlled during the past several months. It is not increasing, and this is a positive sign. This helps people in thinking about things other than day to day operations, such as real estate.

It is also important to note that the devaluation of Pakistani Rupees in comparison to Dollar has stopped. Pakistani Rupee is very much stable at one place. This is interesting, as people may stop investing in money trading and may stop investing in other options, such as real estate.

The interest rate is also an interesting and important factor. It is gradually decreasing that can also lead to increased investment in other options. In 2025, it is said that interest rate would come in single digit.

Pakistan’s exports are also increasing that can also result in increased investment in real estate. Exports result in more inflow of dollars, which is beneficial.

Source:

Asaan Home - Nobody Tells You About Pakistan's Real Estate Crisis | Which Projects are Profiting BIG Right Now! -  https://www.youtube.com/watch?v=K6eCIlrayrM  

Day 9: A challenge to learn basics of Structural Equation Modeling (SEM) using lavaan and semPlot packages in R

 

During the next 12 days, I will learn and repeat the basics of structural equation modeling (SEM) using lavaan and semPlot packages in R.

You can search my lavaan posts by typing: #UsmanZafarParacha_lavaan , and semPlot posts by typing: #UsmanZafarParacha_semPlot

=============

During this day, I loaded essential libraries, and defined the SEM model, using the following lines of codes:

# Load the libraries

library(lavaan)

library(semPlot)

 

# Define the SEM model

model <- '

  # Direct effects

  Housing_Demand ~ Economic_Conditions

  Property_Prices ~ Housing_Demand

 

  # Moderation (interaction term between Housing Demand and Interest Rates)

  Property_Prices ~ Housing_Demand * Interest_Rates

'

 

Then develop a supposed dataset using the following:

# Simulate data for the model

set.seed(123) # For reproducibility

N <- 300 # Sample size

 

Economic_Conditions <- rnorm(N, mean = 0, sd = 1)

Housing_Demand <- 0.6 * Economic_Conditions + rnorm(N, mean = 0, sd = 1)

Interest_Rates <- runif(N, min = 2, max = 5)  # Random interest rates between 2% and 5%

Property_Prices <- 0.8 * Housing_Demand + 0.4 * Housing_Demand * Interest_Rates + rnorm(N, mean = 0, sd = 1)

 

# Combine data into a dataframe

data <- data.frame(Economic_Conditions, Housing_Demand, Interest_Rates, Property_Prices)

 

Then I fit the SEM model using lavaan, as follows:

 

# Fit the SEM model

fit <- sem(model, data = data)

 

# Display the summary of the SEM model

summary(fit, fit.measures = TRUE, standardized = TRUE)

 

Eventually, the model is visualized using semPlot, as follows:

# Plot the SEM model

semPaths(fit, "std", whatLabels = "std", edge.label.cex = 1.2, layout = "tree",

         style = "lisrel", residuals = FALSE, intercepts = FALSE)

 

Source:
ChatGPT

Day 30: Blender tutorial for making illustrations – Upload and Share Your First Video

1. Finalize Your Video File

Before you upload your video, make sure it is in the correct format for YouTube. The most common format is MP4, which provides a good balance between file size and quality. You should have done this on Day 29, but double-check the following:

• Resolution: YouTube recommends 1080p (1920x1080) for standard videos.
• Frame rate: Use a consistent frame rate (e.g., 30fps).
• Aspect ratio: Standard aspect ratio is 16:9.

If everything is correct, you’re ready to proceed with the upload.

2. Log in to Your YouTube Account

• Visit YouTube Studio.
• Sign in using your Google account credentials.

3. Navigate to the Video Upload Section

• Once logged in, click the Create button (a camera icon with a plus sign), located at the top-right corner of the page.
• Select Upload Videos from the dropdown menu.

4. Upload Your Video

• Drag and Drop your video file into the upload area or click Select Files to browse for it manually on your computer.
• Wait for the video to upload. During the upload process, YouTube will show a progress bar.

5. Title Your Video

Choose a title that is SEO-friendly and accurately describes your content. Since your video is an illustrative educational video, include keywords such as "illustrative", "educational", and the topic covered in the video.

Example: "Illustrative Flowchart on Cell Division – Educational Video Tutorial"

6. Write a Description

The description is crucial for both viewers and search engines. Write a detailed and engaging description that explains what the video is about and what the audience will learn.

Example:

• Start with a short, attention-grabbing intro about the video.
• Mention the key concepts covered in the video.
• Add relevant keywords for SEO purposes.
• Include timestamps if the video has multiple sections.
• Finally, add any links to related content, including your social media or Patreon link.

7. Set Your Video Thumbnail

You can upload a custom thumbnail for your video, which is the image viewers will see before clicking on the video. A well-designed thumbnail can significantly increase click-through rates. Make sure it:

• Is visually appealing and informative.
• Reflects the content of your video (e.g., flowchart, illustrations).
• Has large, readable text if necessary.
• Is 1280x720 pixels in resolution.

8. Add Tags

Tags help YouTube understand the content of your video and recommend it to the right audience. Use tags related to the video's content.

• Example tags: "illustration", "Blender tutorial", "educational video", "flowchart", "Quranic content".

9. Select Playlists (Optional)

If you have playlists on your channel (e.g., educational series), you can add the video to relevant playlists. This helps organize your content and improve viewer retention.

10. Audience Settings

Select whether your video is made for kids or not. If your video is for a general audience, select "No, it’s not made for kids" unless the video content specifically targets children.

11. Set Video Visibility

YouTube allows you to choose when and how your video becomes visible:

• Public: The video is immediately visible to everyone.
• Private: Only you and people you invite can view the video.
• Unlisted: Only people with the link can view it.
• Scheduled: You can set a specific date and time for the video to go public.

If you want your video to be immediately available, choose Public.

12. Add End Screens and Cards (Optional)

End screens and cards can help promote other content on your channel. You can:

• Add related videos to the end screen.
• Suggest other playlists.
• Direct viewers to your Patreon or other social media.

13. Review and Publish

• Once you’ve filled out all the details, review them to ensure everything is correct.
• Click Publish (or Schedule if you selected that option).

14. Share Your Video

After publishing, share your video to increase its reach:

• Share on social media: Post on platforms like Twitter, Facebook, Instagram, and LinkedIn.
• Embed on your website or blog if you have one.
• Send to your email list if you have subscribers.
• Post the link in relevant online communities or forums where people might find the video valuable.

15. Monitor Video Performance

After uploading, keep an eye on the video’s performance in YouTube Studio:

• Check for views, likes, comments, and engagement statistics.
• Respond to comments to engage with your audience.

Some of the valuable societies in/near Islamabad, Pakistan

 

In Pakistan, there are some of the housing projects that may experience an increase in rates. Among the top-rated are those located near Chakri Road. These projects either experience the rates at a good level as that of previous level, or at a profit level. Among the different large projects facing good developments near Chakri Road are Capital Smart City. Another project is Phase 2, Faisal Town, in which one of the high level of developments has already been started. They are also legitimate developers, so the chances of higher rates are good. Blue World City project may also experience an increase in the rates of plots. Considering Islamabad, Park View City is experiencing good results. Overseas block in this area may experience good profits, especially those which moves from non-balloting to balloting. In the Gujjar Khan, New Metro City may also experience the return of good amount within the next six months to one year. It is also important to note that plots that are present on ground are already in good amount, while some of the plots which are only in files could be in negatives. Societies that are developing are experiencing good profits. For instance, in Faisal Hills, almost every file is in profit, as it is going through good development.

Source:

PROPERTY NAAMA - Rawalpindi & Islamabad Housing Society Next Year Profit & Loss Comparison | Market Analysis 2024 - https://www.youtube.com/watch?v=yx2w2M9N7Ds

Day 8: A challenge to learn basics of Structural Equation Modeling (SEM) using lavaan and semPlot packages in R

 

During the next 12 days, I will learn and repeat the basics of structural equation modeling (SEM) using lavaan and semPlot packages in R.

You can search my lavaan posts by typing: #UsmanZafarParacha_lavaan , and semPlot posts by typing: #UsmanZafarParacha_semPlot

=============

During this day, I loaded the essential libraries and prepared a data, using the following lines of codes:

 

# Load the required libraries

library(lavaan)

library(semPlot)

library(psych)

 

# Simulate data

set.seed(123)  # For reproducibility

n <- 300  # Number of samples

 

# Latent variables

Knowledge <- rnorm(n, mean = 0, sd = 1)

Attitudes <- 0.5 * Knowledge + rnorm(n, mean = 0, sd = 1)

Behavior <- 0.7 * Knowledge + 0.4 * Attitudes + rnorm(n, mean = 0, sd = 1)

 

# Observed indicators for each latent variable

Know1 <- 0.8 * Knowledge + rnorm(n, mean = 0, sd = 0.5)

Know2 <- 0.9 * Knowledge + rnorm(n, mean = 0, sd = 0.5)

Know3 <- 0.7 * Knowledge + rnorm(n, mean = 0, sd = 0.5)

 

Att1 <- 0.8 * Attitudes + rnorm(n, mean = 0, sd = 0.5)

Att2 <- 0.9 * Attitudes + rnorm(n, mean = 0, sd = 0.5)

Att3 <- 0.7 * Attitudes + rnorm(n, mean = 0, sd = 0.5)

 

Beh1 <- 0.8 * Behavior + rnorm(n, mean = 0, sd = 0.5)

Beh2 <- 0.9 * Behavior + rnorm(n, mean = 0, sd = 0.5)

Beh3 <- 0.7 * Behavior + rnorm(n, mean = 0, sd = 0.5)

 

# Create a data frame

data <- data.frame(Know1, Know2, Know3, Att1, Att2, Att3, Beh1, Beh2, Beh3)

 

The above code shows three observed variables for each latent factor. For example,

Knowledge: Know1, Know2, Know3

Attitudes: Att1, Att2, Att3

Behavior: Beh1, Beh2, Beh3

Then the SEM model is specified, using the following lines of codes:

 

# SEM model specification

model <- '

  # Measurement model

  Knowledge =~ Know1 + Know2 + Know3

  Attitudes =~ Att1 + Att2 + Att3

  Behavior  =~ Beh1 + Beh2 + Beh3

 

  # Structural model

  Attitudes ~ Knowledge

  Behavior  ~ Knowledge + Attitudes

'

The SEM model is fitted using lavaan, and visualized using the semPaths, as follows:

 

# Fit the SEM model

fit <- sem(model, data = data)

 

# Summarize the results

summary(fit, fit.measures = TRUE, standardized = TRUE)

 

# Plot the SEM path diagram

semPaths(fit, "std", layout = "tree", residuals = TRUE, nCharNodes = 7, edge.label.cex = 1.2)

 

Source:
ChatGPT