Week 6 (24.11-30.11.24): Big Data

Big data is a vague term for a massive phenomenon that has rapidly become an obsession with entrepreneurs, scientists, governments and the media. It is the hottest topic in IT next to the cloud. Moreover, these two ideas are closely related as the massive growth in the quantity of data has been generated through cloud computing.


The continuous increase in the volume and detail of data captured by organizations, such as the rise of social media, Internet of Things (IoT) and multimedia, has produced an overwhelming flow of data in either structured or unstructured format. Data creation is occurring at a record rate, referred to herein as big data, and has emerged as a widely recognized trend. Big data has gained attention from the academia, government and industry.


Big data can be characterized by three aspects:
(a)data are numerous,
(b)data cannot be categorized into regular relational databases,
(c)data are generated, captured, and processed rapidly.


Moreover, big data is transforming healthcare, science, engineering, finance, business, and eventually, the society. The advancements in data storage and mining technologies allow for the preservation of increasing amounts of data described by a change in the nature of data held by organizations. The rate at which new data are being generated is staggering. A major challenge for researchers and practitioners is that this growth rate exceeds their ability to design appropriate cloud computing platforms for data analysis and update intensive workloads.


Please read the following article and answer the questions.


R. L. Villars, C. W. Olofson, M. Eastwood, Big data: what it is and why you should care, White Paper, IDC, 2011, MA, USA.

http://sites.amd.com/fr/Documents/IDC_AMD_Big_Data_Whitepaper.pdf


1. We gather more and more data, but does it provide in your opinion much more useful information?
2. What IT challenges related to big data can you think of?
3. Do you see any threats related to big data?

Week 5 (17.11-23.11.14): Business Intelligence and Pharmaceuticals

   The pharmaceutical industry is in the midst of fundamental changes. The changes have been brought on by the increasing concerns over expiry of patents for major blockbuster drugs, weak product pipelines, heightened awareness of drug safety, globalisation, competition from generics and growing value considerations with regards to access to and reimbursement of new speciality therapeutics. These issues, and more, have forced top pharmaceutical companies to change their current course, in search of a stable and sustainable path that can help them maintain and improve their current profitability levels

BI solutions are implemented in different parts of the organisation under the common direction of the CIO. Having been successful in achieving operational excellence and improving the research / clinical performance of the companies, these solutions have been increasingly adopted, albeit at a varied pace, by pharmaceutical organisations.

http://www2.microstrategy.com/download/files/whitepapers/open/business-intelligence-and-pharmaceuticals.pdf

I would like to ask you the following questions:

-  How do you see the future of Pharmaceutical Industry without using BI ?

- Have you  participated in a BI project ? 

- What do you think about the BI ?

Week 5 (17.11-23.11.14): The Future of Higher Education

I would like to discuss a subject of the future of higher education. I will support myself by using following article: http://www.educause.edu/library/resources/future-higher-education-0.
From time to time there is a need to discuss is the traditional behavior need to be changed? Is it efficient? Few years ago on the internet appears new trend: Massive open online course (MOOC). A new communication of transferring knowledge is founded on internet. What special about it? In the past universities support themselves by using learning management system LMS in addition of the traditional classroom curses. Students could download materials and other resources, communicate with other students and upload they work on teachers server. Now they can do the same by enrolling to one of MOOC platform. They don't need to meet age or any other criteria. As long as they understand material and upload they work they are graded by teachers and finally they receive accomplishment certificate. Will this revolutionize current education system? For now hundred of thousand students are using this outstanding system.
I understand that there is a lot of long pages to read so I composed my questions in way that they can be answered without need of deeper read of this article but i strongly recommend to do it. Especially if you are interested in future trends of higher education changes.
Please answer the questions:

• Actually the teaching method doesn’t differ much from the methods used  by first universities in 800 AD - young people gather with an older teacher who shares wisdom. Will XXI-st century bring fundamental change in the education system?
• Have you ever used MOOC (Massive open online course)?
• Are courses on the EDUX platform a good step into the  future education? What do they lack?
• Do you think it is a good idea to change the examiner's role with artificial program to check knowledge and skills of student?

Week 4(10.11 - 16.11 2014) Homoiconicity

Do you have an interest in C/C++ macros ? or LLVM ? or Parser/Lexer stuff?

If you do have or had any interest in one of the above terms / subjects, you might would like to know what actually 'homoiconicity' is.  Since the term is not the one that has many concerned developers arguing on it, here is a definition from Wikipedia;

"In computer programming, homoiconicity is a property of some programming languages in which the program structure is similar to its syntax, and therefore the program's internal representation can be inferred by reading the text's layout"

I picked this subject mostly because of it's importance on my research area. I always believed the power of (spoken, programming.. any!) language and the way it helps to develop the ideas, dreams, and the future. During my masters studies, once we were arguing about the English Language and how it re-shapes all over in time. Imagine a blog writer is trying to put an article on quantum entanglement with a language frozen hundreds of years ago. No way right ?

Homoiconicity, Lazyness and First-Class Macros
http://ww2.cs.mu.oz.au/~todavies/lookup.pdf

Homoiconicity - Wikipedia
http://en.wikipedia.org/wiki/Homoiconicity

IO language
http://iolanguage.org/

My questions are;

What is your 'favorite' programming language and why? (not the one that your company wants you to use)

How that programming language allows you to reshape?

What is your opinion on homoiconic approach?

Week 4 (10.11-16.11.14) Artificial Neural Networks in Medical Diagnosis

The next scientific paper is "Artificial Neural Networks in Medical Diagnosis" by Qeethara Kadhim Al-Shayea. You can find it here http://ijcsi.org/papers/IJCSI-8-2-150-154.pdf. The paper consists of 4 pages, whereas you need to read 3, the rest are figures, tables and references. Nevertheless, I compiled it into short description.
Please, keep it in mind that there are 3 posts this week. Dont`t wait till the end of week. 

Artificial neural network (ANN) are finding many uses nowadays, especially in the field of classification, pattern`s recognition and predicting problems. This powerful tool found medical diagnosis application too. Two medical cases are studied in the paper. The first one is acute nephritis disease, whereas the second one hearth disease. The paper consists of 4 parts including: introduction, ANN general description, experimental results and conclusions.

Scanning the introduction eleven short summaries of ANN medical application, ranging from heart to liver disease, are described. It can be seen that scientist researched application of different ANN models (e.g. supervised, unsupervised, MLP-multilayer perception) and their combination or comparison to a computing methods, technique (e.g. generalized regression, fuzzy approach, genetic algorithms).

The basics of ANN origin and proposed diagnosis model are shown in the second chapter. For example, we are finding out that ANN is a computational model, network of highly interconnecting parallel processing elements (neurons) inspired by human brain. Scientist proposed feed-forward ANN (in this type of network information always moves one direction - never goes backward) for classification, forecasting and solving considered medical problem. 

The goal of scientist was to create two neural network model to perform diagnosis of acute nephritis and heart disease. The data set contained 120 samples (symptoms, images, signals), whereas 90 to train the model and 30 for model testing. He evaluated model based on neural network Matlab toolbox. The summary of experimental results is that scientist got very good results - network was able to classify 99% testing cases in acute nephritis disease and 95% in heart disease.

So, let`s start the discussion.

1. Do you regard ANN application in medical diagnosis right?

2. In you opinion ANN should only support doctors in medical diagnosis or could work as a stand-alone on-line application?

3. Having read undermentioned text give your opinion (3 sentences only).

In the future there will be an on-line application connected with your home input devices. You will be able to take a temperature, do a blood test, input symptoms through the input devices. Then the on-line doctor will make a diagnosis, prescribe medicines or give you a hospital referral.

Week 3 (03.11-09.11.14): Mobile Learning

Keeping the educational theme of most recent articles on this blog, I've chosen a bulletin titled "The Future of Mobile Learning" by Rick Oller. It can be found on Educase: https://net.educause.edu/ir/library/pdf/ERB1204.pdf

As the title points out, it is mainly about "learning by means of wireless technological devices that can be pocketed and utilized wherever the learner's device is able to receive unbroken transmission signals". After the definition of m-learning we can read about some statistical data of the method's use by institutions around the globe. Later it is deducted that the method is becoming increasingly popular and that students find mobile devices extremely helpful in supplementing their academic work. What follows are the author's predictions about the future of mobile learning with tendencies to incorporate augmented reality, location-based learning and other. The author concludes that there is still much to be done in the area of mobile learning and that teachers must be willing to give it a try because sooner or later it will become a game changing educational method.


The article is pretty short so I suggest you give it a read for more details or the parts that I haven't mentioned.

Additionally I would like to ask you the following questions:

• Have you heard or participated in any project involving mobile learning? Is it used in Poland at all?
  
• Do you think that mobile learning is over-hyped or is it really much better than current learning methods? What subjects it would fit the best?
• And for my last two questions I'll let you chose two that you find interesting from the article's "Key Questions to Ask" section.