Tuesday, 30 June 2020

Top 10 most read posts (June 2020) on Computing in Northamptonshire Blog



All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Saturday, 27 June 2020

Heuristic Optimization for Microload Shedding in Generation Constrained Power Systems - IEEE

Heuristic Optimization for Microload Shedding in Generation Constrained Power Systems

Julius Quarshie AzasooTriantafyllos KanakisAli Al-SherbazMichael Opoku Agyeman

J. Q. Azasoo, T. Kanakis, A. Al-Sherbaz and M. O. Agyeman, "Heuristic Optimization for Microload Shedding in Generation Constrained Power Systems," in IEEE Access, vol. 8, pp. 13294-13304, 2020, doi: 10.1109/ACCESS.2020.2965819.

Abstract

While the causes of power system outages are often complex and multi-faceted, an apparent deficit in generation compared to a known demand for electricity could be more alarming. A sudden hike in demand at any given time may ultimately result in the total failure of an electricity network. In this paper, algorithms to efficiently allocate the available generation is investigated. Dynamic programming based algorithms are developed to achieve this constraint by uniquely controlling home appliances to reduce the overall demands for electricity by the consumers on the grid in context. To achieve this, heuristic optimization method (HOM) based on the consumers’ comfort and the benefits to the electricity utility is proposed. This is then validated by simulating microload management in generation constrained power systems. Three techniques; General Shedding (GS), Priority Based Shedding (PBS) and Excess Reuse Shedding (ERS) techniques were studied for effecting efficient microload shedding. The research is aimed at reducing the burden imposed on the consumers in a generation constrained power system by the traditional load shedding approach. Additionally, the reduction of the excess curtailment is a prime objective in this paper as it helps the utility companies to reduce wastage and ultimately reduce losses resulting from over shedding. Reducing the peak-to-average ratios (PAR) on the entire network in context as a critical factor in the determination of the efficiency of an electricity network is also investigated. In the long run, the PAR affects the price charged to the final consumer. Simulation results show the associated benefits that include effectiveness, deployability, and scalability of the proposed HOM to reduce these burdens.








All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Monday, 22 June 2020

junkbots: School Outreach 2

Junkbots session 3: Move the robot but now there are rocks in the way.

 

What is the Junkbots project

The Junkbots project has been running for a number of years as an initiative to bring sustainability, computing and engineering together by building bots out of junk; details of the project can be found at. https://junkbots.blogspot.com/ . Junkbots is an extension of the Research into the teaching problem-solving going on at the University of Northampton please feel to visit https://computingnorthampton.blogspot.com/2019/01/problem-solving-research-outputs-and.html for more details.

 

What are we going to do?

·       Play with a Scratch robot on the screen!

·       Build on the routines from the previous session.

·       Look at example of what happens when the junkbot and the rock met.

·       Adding key press to control the code to guide the junkbot around.

·       Extend your solution


 

Activity 1: Reminder of the blocks we used previously? https://computingnorthampton.blogspot.com/2020/05/junkbots-school-outreach-1.html


This means when the green flag is pressed do whatever follows.

 

 

 


This means place our robot (go to block) to point on the screen roughly in the centre of the screen.

 

Do you want a challenge: What do think would happen if instead 0 and 0 in the white spaces in the go to block, we put in 50 and 50? Have a guess.

 

 

 

This means stop the scratch program for 1 second and then carry on.

 

 

 

We can use this block to move the robot 50 steps on the screen in the direction it is facing.

 



We can use this block to turn the robot to the right 45 degrees.

 


We are also going to look at two more ‘things’ today: one new block and a new type of blocks to make our programming easier – the control blocks.

 

 


We can use this block to change the direction the robot faces.

 

 


When we click on the control button at the side we see several more blocks we can use.

 

One of these we have played with before the wait block.

 

The other two we are going to use today in later activities.

 

When we want to repeat a combination of blocks so many times, we can use the middle block and then change the 10 to the number of times we want to repeat.

 

If we want it repeat something forever (or until we stop the program with the red button) we can use the last block.

 

 



Sometimes we want to change what the program does when something happens.

 

We will look at three types of instructions

-     If this ‘thing’ happens then do this.

-     If this ‘thing’ happens then do this else to this other thing

-     When a key is pressed do this.

 

  

 


Activity 2: Have a go at guessing what it is going to do?

 

Follow this link to a new Scratch project https://scratch.mit.edu/projects/405642711

 

 

Challenge 1: Press the green flag and see what it does.  THEN press the green flag and see what it does.

Tell others what you saw it do?

 

Challenge 2: Now go in the Scratch code for the rock (it should look like the scratch program shown next to this).

- describe what you think this does?

- tell others why do you think the if block is inside a forever block?

 

 

 

 

Activity 3: Modify and Make

 

·       Staying with the same scratch code you might have noticed that the junkbot doesn’t always hit the rock.

·       We are going change this so we can guide the junkbot to hit the rocks.

·       Go to the code for the junkbot/robot/rcx.

·       Challenge 3: Add instructions to move the junkbot by pressing the arrow keys. In the picture you can see two events blocks one group of blocks says what happens when the up key is pressed then other when the right key is pressed.

·       Add blocks to make the down and left keys move the junkbot down or left.

 

 

 

 

 

 


 

 

 

 

 

Activity 4: Modify and make play

 

·       Lets get it to add more blocks either using the program you have developed or https://scratch.mit.edu/projects/405650433

·       Go to the stage code you will see a block saying create clone of Rocks every time this block is used a new rock is added to the screen.

·       Challenge 4: Can you change the code so 20 rocks are put on the screen and now create a game where you have to hit every rock.

·       Challenge 5 – looking at other scratch examples (for example https://projects.raspberrypi.org/en/projects/ghostbusters/4) could you add a scoring system to this game.

 

 

 

 

 

 



All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Saturday, 20 June 2020

Keynote speech- Why everyone should learn a bit about ML

I recently had the honour of a providing a keynote speech for a conference  in Iraq (virtually) at the New Trends in Information and Communications Technology Applications conference http://www.uoitc.edu.iq/ntict2019/home.html

The recording is below:



All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Tuesday, 9 June 2020

Predictive Learning Analytics in Higher Education: Factors, Methods and Challenges

Predictive Learning Analytics in Higher Education: Factors, Methods and Challenges

Ghaith Al-Tameemi, James Xue, Suraj Ajit, Triantafyllos Kanakis, Israa Hadi

 

Abstract

In higher education institutions, a high number of studies show that the use of predictive learning analytics can positively impact student retention and the other aspects which lead to student success. Predictive learning analytics examines the learning data for intervening or improving the process itself that positively reflects on student performance. In our survey, we are considering the most recent research papers focusing on predictive learning analytics and how that affects the final student outcome in educational institutions. The process of predictive learning analytics, such as data collection, data preprocessing, data mining, and others, has been illustrated in detail. We have identified factors that affect student performance. Several machine learning approaches have also been compared to provide a clear view of the most suitable algorithms and tools used for implementing the learning analytics

IEEE

IEEE International Conference on Advances in Computing and Communication Engineering - Las Vegas, United States

22 Jun 2020  24 Jun 2020


Cite: Al-Tameemi, G, Xue, J, Ajit, S, Kanakis, T & Hadi, I 2020, Predictive Learning Analytics in Higher Education: Factors, Methods and Challenges. in Predictive Learning Analytics in Higher Education: Factors, Methods and Challenges. IEEE, 6th IEEE International Conference on Advances in Computing and Communication Engineering, Las Vegas, United States, 22/06/20.



All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Saturday, 6 June 2020

Towards a Paradigm Change in Group and Peer Assessment in Software Engineering Education

Towards a Paradigm Change in Group and Peer Assessment in Software Engineering Education
Paul Vossen*, Suraj Ajit*

 

*Corresponding author for this work

 

Abstract

Conventional approaches to group and peer assessment are invariably based on highly questionable assumptions about educational measurement and how to weight and aggregate multiple scores into an overall judgement of outcome and performance. In this paper, we propose an alternative approach based on a sound theory of educational scoring and rating. Our approach is particularly relevant for software engineering education where group projects with multiple types of outcomes are used to assess individual students. We will also present recent progress with two experimental tools incorporating our novel approach and compare the latter with some well-known tools based on conventional approaches. We will focus on explaining the reasons for and benefits of adopting this paradigm-changing approach to group-peer marking.

Proceedings of the 32nd IEEE International Conference on Software Engineering Education & Training (CSEE&T 2020)

Pages 1-8


https://ase.in.tum.de/cseet2020/





All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon

Monday, 1 June 2020

Top 10 viewed posts on Computing in Northampton in May 2020


All views and opinions are the author's and do not necessarily reflected those of any organisation they are associated with. Twitter: @scottturneruon