Universities sometimes promote Assistant Professors directly to Professor (skipping Associate) or recruit directly to Professor roles by assessing outstanding research/teaching (UGC guidelines allow direct recruitment to Professor

Co,Pos...............

 

                

..................Operating System CO1 to CO6" refers to the typical Course Outcomes (COs) for an OS subject, covering foundational concepts (CO1), processes/scheduling (CO2, CO3), memory/file management (CO4, CO5), and advanced topics like Linux/mobile OS (CO6), explaining key OS functions from basics to practical implementations like < process scheduling, memory allocation, file systems, and security. 

Here's a breakdown of common COs for Operating Systems:

• CO1: Introduction to OS
  • Understanding basic concepts, history, functions, and types (batch, multiprogramming, real-time, distributed) of operating systems.
• CO2: Processes & CPU Scheduling
  • Learning about processes, threads, process coordination, and various CPU scheduling algorithms (FCFS, SJF, Priority, Round Robin).
• CO3: Process Synchronization & Deadlocks
  • Analyzing process synchronization mechanisms (semaphores, monitors) and techniques for handling deadlocks.
• CO4: Memory Management
  • Understanding memory allocation (contiguous, non-contiguous), virtual memory, paging, and segmentation.
• CO5: File Systems & I/O
  • Studying file system structures, disk scheduling, I/O management, and device management.
• CO6: Advanced Topics
  • Exploring security, protection, networking basics, distributed systems, real-time systems, or specific OSs like Linux/Android. 

These COs progress from foundational knowledge (CO1) to detailed analysis and application (CO4, CO5, CO6), guiding students through the core components of modern operating systems. 

Food and Beverage Calorie Prediction with Neural Networks...... total 12 pages..........."Under peer review" SpringerNature..........

 

Food and Beverage Calorie Prediction with Neural Networks

Raman kumar mandal^l   karingula Venudhar ²

Ramanjaneyulu Dayinaboyina Associate Professor , Dept of AIML , CMR College of  Engineering and Technology,

Kandlakoya medchal Hyderabad , Telangana, India

 

 

¹Assistant professor Department of IT, CMR College of  Engineering and Technology,

Kandlakoya medchal Hyderabad , Telangana, India

 

 

 

 

Abstract.This observe introduces a revolutionary approach for enhancing nutritional monitoring and selling healthful consuming behaviour via deep analyzing technology. The primary objective is to correctly come across several meals objects and estimate their calorie content cloth in actual-time, offering customers a smart and customized technique to nutritional tracking performed using Python, the gadget makes use of the cellular net architecture for food category and calorie estimation. The proposed gadget methods meals snap shots through a web based totally interface, figuring out gadgets hastily and supplying customers with a accurate calorie estimate. This machine empowers people with treasured insights into their nutritional behaviour, permitting them to song meals intake, set dietary dreams, and make knowledgeable picks. via way of leveraging deep studying for green and correct calorie estimation, this approach offers a transformative solution for nutritional control. With its excessive precision, real-time evaluation, and clever nutritional monitoring, this system has the ability to redefine how humans monitor and optimize their dietary conduct, fostering greater healthy lifestyles and average well-being.

 

Keywords:: Deep Learning, Food Calorie Estimation, Image Processing, CNN, Multi-Label Classification, Computer Vision

 

1       Introduction

Rapid advances in computer vision and deep learning have had a major impact on a wide range of areas including healthcare and nutrition the key uses are food detection and calorie estimation and it is estimated that a key role plays in intelligent nutrition monitoring accurate food identification and estimation of calorie content can help individuals make healthy nutrition decisions and promote a healthier lifestyle increased smartphone use and growing nutritional concerns have encouraged research into efficient and accurate calorie estimation systems these approaches are highly susceptible to variations in lighting conditions location and food presentation style furthermore many existing systems related to reporting on food categories are limited and lack actual calorie assessment skills this makes them ineffective for widespread use to address these challenges this study uses deep learning techniques particularly mobilenet architecture to improve the accuracy of food detection mobilenet is a lightweight and efficient model suitable for mobile applications .

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total 12 pages.

NOW A DAYS PROBLEM IS WITHOUT KNOWING UGC AICTE RULES................. MANY PEOPLE.not knowing............................

 

Mr.Ram.A.Dayinaboyina.........................

 

Mr ram.a.dayinaboyina..........

 

Mr.Ram.A.Dayinaboyina..............................

 

AI FAILS IN SOME SITUATIONS .............

 

Ternary Operator in Python............

              The ternary operator in Python allows us to perform conditional checks and assign values or perform operations on a single line. It is also known as a conditional expression because it evaluates a condition and returns one value if the condition is True and another if it is False.

ex 1:-

n = 5

res = "Even" if n % 2 == 0 else "Odd"

print(res)

ex 2:- 

n = -5

res = "Positive" if n > 0 else "Negative" if n < 0 else "Zero"

print(res)

sri ram.a.dayinaboyina today..................

S.R.M.C P......PORUR. DEPT OF Optometry and Vision Sciences

 

Agentic AI & Build Agents ............................

 

from R G I A HYD.........................

 

Mr ram..........................

 

at intl airport.........................

 

Mr ram.a.dayinaboyina university house

 

applications

 

working on SCI AIML Paper.................................springer berlin/heidelberg Scientific Reports - Receipt of Manuscript 'Crop Yield Prediction...' Inbox Springer Nature Thu 6 Nov, 18:27 (5 days ago) to me Ref: Submission ID bb9cb447-6a22-4579-a78c-478bdf8e1112 Dear Dr Ramanjaneyulu, Please note that you are listed as a co-author on the manuscript "Crop Yield Prediction in Diverse Environmental Conditions Using Ensemble Learning", which was submitted to Scientific Reports on 06 November 2025 UTC. If you have any queries related to this manuscript please contact the corresponding Peer Review Advisors, who is solely responsible for communicating with the journal. Kind regards, Peer Review Advisors Scientific Reports

 

Mr D.R today ....................................

 

THE HONEYMOON PERIOD IS OVER ...........................................

The phrase "the honeymoon period is over" means a new relationship has transitioned from the initial, intense phase of idealization and infatuation into a more realistic and comfortable stage. This is a natural and often healthy progression where you start to see your partner's imperfections, and the relationship moves toward building a lasting, mature connection, although it can also involve navigating more conflict and less excitement. 

Signs that the honeymoon period is over

• Idealization fades: 

  You begin to see your partner's flaws and "imperfections" that you didn't notice before. 
• Conflicts increase: 

  The relationship may experience more arguments or disagreements as real-life issues arise. 
• Daily life becomes the norm: 

  The intense, blissful feeling decreases, and you both settle into a more routine dynamic. 
• Intimacy changes: 

  Sex may decrease, or a more casual, comfortable level of intimacy replaces the constant passion. 
• Annoying quirks surface: 

  What you once found endearing or cute about your partner may now start to irritate you. 

How to navigate this transition

• Focus on communication: 

  Have open and honest conversations about your feelings, needs, and any issues that arise. 
• Continue to date each other: 

  Intentionally plan dates and activities, just as you did in the beginning, to maintain excitement and connection. 
• Introduce novelty: 

  Try new things together to keep stimulating your brains' reward systems, which can help recreate some of the initial spark. 
• Allow for space: 

  It's healthy to have some alone time, as it allows you to recharge and miss each other, which can strengthen your connection when you reunite. 
• Accept imperfections: 

  Understand that this shift is a normal part of a healthy, long-term relationship, not necessarily a sign of a broken one