github for Python https://github.com/aurmc2018/hello-world.git
github for TANSCHE https://github.com/TANSCHEC/sirf.git
githubfor CAAI https://github.com/immbizsoft/caai-ai.git
Thursday, 27 March 2025
Saturday, 15 February 2025
Angular 18 Navigation for iMMSS
🚀 Setting Up Angular Routing - The Fun Way! 😆
Hey there, future Angular ninjas! 🥷 If you’re new to Angular and struggling with routing, don’t worry! We’ve got a simple, fun guide that even your lazy friend who never codes can follow. Let's go! 🎉
Step 1: Unlock the Terminal Superpowers ⚡
Open your terminal and type this magic spell:
Set-ExecutionPolicy Unrestricted -Scope CurrentUser
(If your computer starts talking back, run away! Just kidding 😜, this just allows scripts to run.)
Step 2: Summon a New Angular App 🏗️
ng new routing
Now, check if the server is alive:
ng serve
If everything is working, you should see some Angular awesomeness at localhost:4200. 🎯
Step 3: Create Pages Like a Pro 📄
Run these one by one in the terminal to create your components:
ng g c home
ng g c contact
ng g c about
ng g c services
Boom 💥! You just made pages like a coding boss.
Step 4: The Magic Routing Spell 🧙♂️
Open app.routes.ts and change its contents to this:
import { Routes } from '@angular/router';
import { HomeComponent } from './home/home.component';
import { ContactComponent } from './contact/contact.component';
import { AboutComponent } from './about/about.component';
import { ServicesComponent } from './services/services.component';
export const routes: Routes = [
{path:"home", component:HomeComponent},
{path:"contact", component:ContactComponent},
{path:"about", component:AboutComponent},
{path:"services", component:ServicesComponent},
];
Now your app knows where to go when you click a link! 🗺️
Step 5: Delete and Replace 🗑️➡️📜
Go to app.component.html, erase everything, and add this:
<h1>Testing Routing</h1>
<router-outlet></router-outlet>
Run:
ng serve
Now, check in your browser:
localhost:4200localhost:4200/homelocalhost:4200/contactlocalhost:4200/aboutlocalhost:4200/services
Enjoy watching the URLs change like magic! 🎩✨
Step 6: Auto-Redirect to Home 🏠
Modify app.routes.ts again:
{path:"", redirectTo:"/home", pathMatch:'full'},
Now, when someone opens your app, they go straight to /home. No confusion, just pure routing genius! 🧠
Step 7: Add a Navigation Menu 🧭
Modify app.component.ts first:
import { RouterLink, RouterOutlet } from '@angular/router';
imports: [RouterOutlet, RouterLink],
Now, in app.component.html, add this stylish navbar:
<h1>Testing Routing</h1>
<nav>
<a routerLink="/home">Home</a> |
<a routerLink="/contact">Contact</a> |
<a routerLink="/services">Services</a> |
<a routerLink="/about">About</a> |
</nav>
<router-outlet />
Check it in your browser and feel like a pro! 🤩
Step 8: Highlight Active Links 🔥
Modify app.component.html to add active styling:
<h1>Testing Routing</h1>
<nav>
<a routerLink="/home" routerLinkActive="active-home">Home</a> |
<a routerLink="/contact" routerLinkActive="active-contact">Contact</a> |
<a routerLink="/services" routerLinkActive="active-services">Services</a> |
<a routerLink="/about" routerLinkActive="active-link">About</a> |
</nav>
<router-outlet />
Now, create a style sheet to make it pop! 🎨
.active-link {
color: red;
}
.active-home {
color:aqua;
}
.active-about {
color:blue;
}
.active-services {
color: rgb(238, 47, 255);
}
.active-contact {
color:rgb(38, 236, 203);
}
Bam! Your links change colors when clicked! 🌈
STEP 9 :
Create Docker file with the followingcontents
FROM node:latest
WORKDIR /usr/src/app
COPY . /usr/src/app
RUN npm install -g @angular/cli
RUN npm install
CMD ["ng", "serve", "--host", "0.0.0.0"]
docker build -t angular_practice
docker run -p 8080:4200 angular_practice
➜ Local: http://localhost:4200/
➜ Network: http://172.17.0.3:4200/
➜ Network: http://172.17.0.3:4200/
Bonus: Learn More 🎥
Watch this video if you’re stuck: 👉 Programmatic Navigation
Congratulations, you just built a routing system in Angular! 🎉 Now, go flex on your friends! 😎
Friday, 27 December 2024
Academic paper pipeline
The Complete AI-Powered Academic Paper Writing Pipeline: From Idea to Publication (2025 Guide)
#AcademicWriting #Research #AI
📍 STAGE 1: RESEARCH IDEATION & PLANNING
🧠 Step 1: Topic Exploration & Research Gap Identification
Tools:
• Iris.ai - Research mapping and gap analysis
• Semantic Scholar - Trend identification
• Connected Papers - Visual literature mapping
• ResearchRabbit - Citation network analysis
• Elicit.org - Research question formulation
🔍 Step 2: Literature Review
Tools:
• Scholarcy - Automated paper summarization
• Zotero - Reference management
• Paper Digest - Quick paper summaries
• SciSpace - PDF analysis and highlighting
• LitMaps - Literature visualization
📊 Step 3: Research Design Planning
Tools:
• ChatGPT - Methodology brainstorming
• Claude - Experimental design feedback
• R Studio AI - Statistical planning
• G*Power AI - Sample size calculation
• Protocol.io - Method documentation
📍 STAGE 2: PAPER DRAFTING
📝 Step 4: Paper Outlining
Tools:
• Writefull Structure - Section organization
• Paperpal Outline - Content planning
• Sciflow - Template-based outlining
• AcademicWriter - Structure suggestions
• Scrivener AI - Content organization
Strategy: Use journal guidelines alongside AI suggestions for optimal structure
✍️ Step 5: First Draft Writing
Tools:
• Writefull - Scientific writing assistance
• Academic Phrasebank AI - Standard phrases
• Grammarly Academic - Real-time writing feedback
• QuillBot Academic - Paraphrasing help
• Ludwig.guru - Academic language suggestions
Writing Workflow:
1. Create section drafts using AI assistance
2. Review and modify content
3. Check technical accuracy
4. Verify citations
5. Polish language
📊 Step 6: Figures & Visualizations
Tools:
• BioRender - Scientific illustrations
• Plotly AI - Interactive charts
• RAWGraphs - Data visualization
• Tableau AI - Complex data plots
• Adobe Illustrator AI - Figure design
📍 STAGE 3: REFINEMENT & EDITING
📌 Step 7: Content Editing
Tools:
• Paperpal - Technical editing
• Grammarly Premium - Style and grammar
• LanguageTool - Language refinement
• Hemingway Editor - Readability check
• ProWritingAid Academic - Deep analysis
Editing Checklist:
□ Technical accuracy
□ Logical flow
□ Citation completeness
□ Figure relevance
□ Methods clarity
🔍 Step 8: Technical Review
Tools:
• StatReviewer - Statistical check
• Penelope.ai - Technical consistency
• SciScore - Methods verification
• iThenticate - Plagiarism check
• Authzen - Author contribution check
Critical: Manual review of all AI suggestions is essential
📑 Step 9: Reference Management
Tools:
• EndNote - Citation organization
• Mendeley Cite - Reference formatting
• Zotero AI - Bibliography management
• CiteDrive - BibTeX management
• ReadCube - Reference library organization
Tip: Double-check all AI-generated citations against original sources
Thursday, 19 December 2024
Green Energy - House Construction
With Minimum Meterological data, how i can build model for Green Energy new construction
With minimal meteorological data, you can still build a basic model for green energy construction using these steps:
Identify Key Data: Focus on crucial weather parameters:
- Solar: Solar radiation or sunlight hours (for solar panels).
- Wind: Wind speed and direction (for wind turbines).
- Temperature: Helps estimate energy efficiency.
- Precipitation: Affects solar efficiency or rainwater harvesting.
Collect Data: Use historical or open-source meteorological data from sources like:
- NASA POWER dataset
- Government weather portals
- Local weather stations
Simplify Energy Models:
- Solar Energy: Use models like PVWatts to estimate solar power output based on sunlight.
- Wind Energy: Apply the Power Law to estimate wind turbine energy output with basic wind speed data.
Site-Specific Adjustments:
- Use elevation, terrain, and shading data from tools like Google Earth or GIS tools.
Build Predictive Model:
- Use simple algorithms like Linear Regression to predict energy output.
- For software, use Python with libraries like Pandas, Scikit-learn, and NumPy.
Validate & Optimize: Compare model results with small-scale installations for accuracy.
This approach works as a basic starting point.
You said:
i have min, max tempearture in a particular place. How i can build model. Explain in step by step with use case for a typical class room for 60 students
ChatGPT
with minimum and maximum temperature data, you can build a model to estimate energy needs for maintaining a comfortable classroom for 60 students. Here's a step-by-step approach:
Objective:
Model the cooling or heating energy required to maintain a comfortable temperature (e.g., 24°C) in a classroom with 60 students.
Step 1: Define the Use Case
- Classroom dimensions: Assume typical size, e.g., 10m x 8m x 3m = 240 cubic meters.
- Occupancy: 60 students.
- Comfort Temperature: 24°C (standard indoor comfort).
- Given Data: Minimum and maximum temperatures for the location.
Step 2: Estimate Heat Load
The heat load includes factors that increase room temperature:
External Temperature Influence:
- Use the average temperature:
Heat Gain from Occupants:
- Each person generates around 100W of heat.
For 60 students:
- Each person generates around 100W of heat.
External Heat Transfer (Walls and Windows):
- Simplify using the U-value (thermal transmittance) of walls/windows.
- Heat transfer:
- U: Thermal transmittance (e.g., 1.5 W/m²K for walls).
- A: Area (walls, windows, roof).
- ΔT: Difference between outside and desired indoor temperature.
Step 3: Total Heat Load Calculation
Add all sources of heat load:
This gives the energy required to cool or heat the classroom.
Step 4: Model the Energy Requirement
- If average temperature > 24°C → Cooling needed.
- If < 24°C → Heating needed.
Energy Consumption can be calculated using:
Step 5: Use Case with Assumptions
Example Scenario:
- Min Temp = 28°C, Max Temp = 36°C → (Cooling needed).
- Classroom: 10m x 8m x 3m.
- Occupants: 60 students.
- Comfort Temp: 24°C.
- Operating hours: 6 hours/day.
- U-value = 1.5 W/m²K for walls.
- Total surface area (walls + roof): 150m².
1. Heat from students:
2. Heat transfer through walls:
3. Total Heat Load:
4. Energy Consumption:
For 6 hours:
Step 6: Build the Model in Python
Use Python to automate this calculation. Here’s a simple script:
Results
Total Heat Load: 7800.00 W
Daily Energy Consumption: 46.80 kWh
Step 7: Insights
- You can use this model to size AC systems or heating units.
- Compare energy requirements for different locations (changing temperatures).
- Use this to assess energy costs or design energy-efficient classrooms.
Let me know if you need further tweaks, bro! 🚀
How much AC i have to provide. Please advise for some use cases in hot climate regions like Ramnad in Tamilnadu
ChatGPT said:
In hot climate regions like Ramanathapuram (Ramnad) in Tamil Nadu, where temperatures often exceed 35-40°C, you need to size the AC units properly. Here's a step-by-step guide with use cases for a typical classroom:
Step 1: Cooling Load Estimation
Cooling load is the amount of heat that needs to be removed to maintain a comfortable 24°C.
Key Heat Sources:
- External heat gain: Through walls, roof, windows.
- Internal heat gain: Students, lights, and other equipment.
Simplified Formula:
For a classroom, use 1 ton of AC for every 12,000 BTU/hr cooling load.
1 Ton = 3.517 kW (energy).Cooling load can be calculated as:
Step 2: Typical Classroom in Ramnad
Let’s assume:
- Classroom Size = 10m x 8m x 3m (standard dimensions).
- 60 students (100W per student).
- Lights: Assume 10 lights at 50W each.
- High external temperatures: Min = 30°C, Max = 40°C.
Comfort Temp = 24°C.
Step 3: Cooling Load Calculation
Heat Gain from Students:
Heat Gain from Lights:
External Heat Gain (Walls + Roof):
Assume:- Total Area (walls + roof) = 150m².
- U-value = 1.5 W/m²K (standard wall insulation).
- Temperature Difference (ΔT): Max Temp - Comfort Temp = .
Total Cooling Load:
Convert to BTU/hr:
Step 4: AC Sizing
1 Ton of AC = 12,000 BTU/hr.
For 34,500 BTU/hr:
Step 5: Use Cases for Hot Climate
Use Case 1: Basic Classroom in Ramnad
- AC Capacity: 3 Tons (Split AC or Cassette AC).
- Configuration: Use 2 x 1.5 Ton ACs for better air distribution.
Use Case 2: Large Classroom or Higher Load
- If room size increases to 12m x 10m x 3m or more students (e.g., 80 students):
- Cooling load increases to ~4-5 Tons.
- Use 2 x 2 Ton ACs or 1 centralized 5 Ton unit.
Use Case 3: Energy-Efficient Classroom
To reduce AC load:
- Use insulation on walls/roof.
- Install cool roofing to reduce heat gain.
- Use blinds or reflective glass for windows.
- Opt for ceiling fans + AC to reduce AC usage.
Final Recommendation for Ramnad
For a 60-student classroom:
- Install 3 Tons of AC (2 x 1.5 Ton units).
- Choose Inverter ACs for energy efficiency.
This ensures comfort even in peak summer temperatures, bro! 🌞 Let me know if you need cost estimates or further tweaks. 🚀
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