Saturday, 4 May 2019

Software defined cognitive networking: supporting intelligent online video streaming

Mu, M. (2018). Software defined cognitive networking: supporting intelligent online video streaming2018 15th IEEE Annual Consumer Communications & Networking Conference (CCNC)https://doi.org/10.1109/CCNC.2018.8319167

Abstract
Adaptive media such as HTTP adaptive streaming (HAS) is becoming a standard tool for online video distribution. The non-cooperative competition of network resources between a growing number of adaptive video applications has a significant detrimental impact on user experience and network efficiency. Existing network infrastructures often prioritise fast packet forwarding, which do not always contribute to the improved user experience. Future network management must leverage application and user-level cognitive factors to allocate scarce network resources effectively and intelligently. Our software defined cognitive networking (SDCN) project, supported by the Research Councils UK, aims at incorporating new developments in human cognition, media technology and communication networks to ensure the user experience, user-level fairness and network efficiency of online adaptive media using software defined networking-assisted and QoE-aware resource management.


To read goto: https://pure.northampton.ac.uk/en/publications/software-defined-cognitive-networking-supporting-intelligent-onli-2

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

Friday, 3 May 2019

10 most popular posts in April 2019 on computing in Northamptonshire



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

Wednesday, 24 April 2019

Even more experiments with Neural Networks

For a while I have been looking at teaching Artificial Neural Networks (https://computingnorthampton.blogspot.com/2018/04/further-experiments-in-teaching-neural.html) but what was missing, I think, is a physical aspect and in response to a question from Carl Simmons (@Activ8Thinking) about has anyone built a microbit simple neuron. I set out to build a neuron (then a small network of neurons) based around the microbit.


Quick Overview


  • Inputs are going to be binary
  • Weighted sum is bias+W1*input1+w2*input2
  • If weighted sum>=0 then the output is True (T on the LEDs) or '1'
  • If weighted sum<0 false="" font="" is="" leds="" on="" or="" output="" the="" then="">



First attempt - A simple gate using the buttons A and B

So first attempt uses the A and B buttons on the Microbit as the two inputs and it produces T for true and F for false on the LEDs. So the weights produce an AND if the bias is changed from -2 to -1 you get an OR.





More Physical Solution for Single Neuron


So in this case the buttons are removed and P0 and P1 formed the inputs the weights are the same as in the previous example with the bias of -2 being used to produce a AND gate. Programming-wise this is a simpler solution than the previous one, no converting button presses into inputs.




Figures below show the 'neuron' in action.


First, one shows the case when both inputs are '0' ie. not connected to 3v connection. The output is False (F on the LEDs)



This figure shows when only one input is '1', the output is False.



Finally what happens when both inputs are '1', the output goes to True (T on the LEDs).




Where next?

The XOR - it needs a network of neurons
Essentially for the two input case, if the two inputs are different then the output is True. 

The figure below shows the arrangement of the connections; pin 2 is the output of the neurons. The two micro:bits/neurons on the left of the picture taking in the two inputs, the same inputs go to these two neurons; the output from these neurons are the two inputs to the output neuron on the right.




figure 1

The micro:bit objects used in Figure 1 were produced using the micro:bit Frtzing diagram available at https://github.com/microbit-foundation/dev-docs/issues/36 thanks to David Whale (@whalleygeek ) for these.


Neuron 1

This is the top left neurone in figure 1. This neurone is set to produce an output of TRUE (pin 2 going high) when the first input goes low and the second input goes high. The code for it is shown below.




Neuron 2

This is the bottom left neuron in figure 1. This neurone is set to produce an output of TRUE (pin 2 going high) when the first input goes high and the second input goes low. The code for it is shown below.



Output Neuron

Neuron 1
This is the right-hand neurone in figure 1. This neurone is set to produce an output of TRUE (pin 2 going high) when either inputs (outputs from neurons 1 and 2) goes high - in other words acting as an OR gate . The code for it is shown below. 

The overall effect is when the two inputs to the network are high/TRUE then the output of the network (this neuron) is TRUE.




In Action

The wiring is messy but the effect is possible to see in these images. The top neuron is the output neuron.
figure 2: inputs to the network (input 1 low and input 2 high)
Figure 3: inputs to the network (input 1 high and input 2 low)

figure 4: inputs to the network (both inputs the same)
6. Room for expansion
The neurons were 'trained' in this case by selecting the weights by hand, an improvement would be to get them to learn. How to do this on a micro:bit takes a bit more thinking about, but I would be interested in seeing how others solve that problem.







All opinions in this blog are the Author's and should not in any way be seen as reflecting the views of any organisation the Author has any association with. Twitter @scottturneruon




Friday, 12 April 2019

Junkbots goes to Duston



via GIPHY

The junkbots project went to Duston Eldean Primary School, Northampton on 3rd April 2019, as part of their STEAM Week.

Each group built a drawing bot from vibrating motors, pens, sometimes a Kinder Egg plastic case (I was asked who eat all the chocolate - I admitted it was me)...and lots of tape. Details on the whole process and how to do it go to Crumble Based Junk Eggbot .

Structure of the session


  • 5 minutes the whole group is together and volunteers come up, face the group and hold the motor - when it is turned on the motor vibrates and often gets a reaction.
  • 10-20 minutes build in smaller groups the drawing bot and get it scribbling.
  • Remaining time put the crumble controller between the battery and the motor. Details on how to do this go to Crumble Based Junk Eggbot .











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

Sunday, 31 March 2019

10 most popular posts in March on Computing in Northamptonshire

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

Friday, 29 March 2019

Merged Futures - the AR/VR event


Merged Futures is a free, one-day Digital Northampton event bringing together experts in emerging technologies to showcase the great work taking place in Northamptonshire. Taking place on  Friday 14 June, 10:00am - 6:00pm at the new Waterside Campus, University of Northampton.

It will explore the potential to further develop and innovate for the benefit of our businesses, students and residents in Northamptonshire and beyond. Merged Futures will showcase the digital talent on offer in Northampton and how it can be harnessed to unlock the potential of the local digital economy in the county.


The target audience is anyone interested in finding out how and why emerging technologies such as AI (Artificial Intelligence), AR (Augmented Reality), VR (Virtual Reality) and IoT (Internet of Things) can benefit Northamptonshire, from business leaders to local residents.


The event will connect digital companies and educators with those interested in implementing digital transformation in their business or organisation.

As well as presentations at the event on subjects including VR and IoT, there will be interactive demos covering a range of technologies such as AR and AI.


Taking place at
Learning Hub, 
Waterside Campus, 
University of Northampton, 
NN1 5PH


To book go to https://www.digitalnorthampton.com/mergedfutures and it is free!

To find out more about Digital Northampton go to https://www.digitalnorthampton.com/ 

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

Saturday, 23 March 2019

Fuzzy scoring theory applied to team-peer assessment

Vossen, PH & Ajit, S 2018, 'Fuzzy scoring theory applied to team-peer assessment: additive vs. multiplicative scoring models on the signed or unsigned unit intervalAdvances in Intelligent Systems and Computing.





Abstract
Teamwork in educational settings for learning and assessment has a long tradition. The reasons, goals and methods for introducing teamwork in courses may vary substantially. However, in the end, teamwork must be assessed at the group level as well as on the student level. The lecturer must be able to give students credit points or formal grades for their joint output (product) as well as for their cooperation in the team (process). Schemes for such multicriteria quantitative assessments appear difficult to define in a plausible way. Over the last five decades, plenty proposals for assessing teamwork processes and products on team and student level have been given using diverse scoring schemes. There is a broad field of empirical research and practical advice about how team-based educational assessment might be set up, implemented, improved, and accepted by staff and students. However, the underlying methodological problems with respect to the merging of several independent measurements has been severely underestimated. Here, we offer an entirely new paradigm and taxonomy of teamwork-based assessment following a rigorous fuzzy-algebraic approach based on two core notions: quasi-arithmetic means, and split-join-invariance. We will show how our novel approach solves the problem of team-peer-assessment by means of appropriate software tools.

To read more goto: https://pure.northampton.ac.uk/en/publications/fuzzy-scoring-theory-applied-to-team-peer-assessment-additive-vs--2


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