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Knowledge Discovery - Science topic
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Questions related to Knowledge Discovery
From the announcements of politicians, it appears that in a few years manned expeditions to the Moon will resume. On the Earth's moon, bases will be established for the preparation of a man's expedition to Mars, which may already be carried out in a dozen or so years. Manned expeditions to Mars in the perspective of a dozen or so years have already announced the US and China.
So there is a rivalry in the field of who will first make a manned trip to Mars. Will it be a similar competition as in the 1970s between the US and the USSR in the area of the then competing programs of the planned and implemented manned expedition to the Moon.
Or maybe a manned expedition to Mars will not be a competition between the biggest economic and technological powers of the world? Perhaps these planned further cosmic manned expeditions will be international expeditions, will be implemented as part of international cooperation and co-operation, and the crew of cosmonauts will be a crew composed of representatives of various countries?
What is your opinion on this matter? Should a manned space expedition to Mars be conducted as part of the international competition between competing countries or rather as part of international cooperation and cooperation?
Do you agree with me on the above matter?
In the context of the above issues, I am asking you the following question:
Is the planned space manned expedition to Mars a result of the rivalry between economic powers or their cooperation?
Please reply
I invite you to the discussion
Thank you very much
Best wishes
Do you think that man will ever leave our solar system?
Please, answer, comments.
I invite you to the discussion.
Best wishes
PhD degree is a highest recognized degree, currently considered as one of the requirements for several jobs like academic, scientific, managerial and other positions that are highly paid and respected in the scientific society.
Therefore, there is a obvious race to pursue PhD from the best of the eligible universities and to land up in a well established lab, to publish as much papers as possible and finally get PhD degree in shortest possible span of time.
Do you think it is wrong ? There is nothing wrong in competing with the above objectives but what I feel is all concerned about the blind race which eventually limits the quest for learning, enjoying the pursuit of knowledge discovery, being creative, confident and end-up with the self discovery.
Thus, this tricky race has lead to increased stress, anxiety and depression among research students. Most of the time, I realized that even after the PhD degree, people end-up breeding egos rather than humility which lands them to the mediocracy. However, this mediocracy keeps them moving up the ladder. Actually, each PhD journey is unique and should not be subjected to the comparison to other PhD's.
What is your overview of the current state of the PhD's ?
What technologies, currently considered surrealistic and possibly achievable in the future, could revolutionize technological progress and could solve key global problems of humanity?
For example, imagine if nuclear fusion technology was developed at a nuclear power plant, in which nuclear material would neutralize toxic waste in this way.
Or if power plants were built, in which hydrogen would be burned in oxygen in a controlled way and in this way electricity would be produced and the whole power plant would be built in the formula of a new generation steam engine, with water vapor arising in the process of the said hydrogen combustion in oxygen.
If it were possible, this type of technological solutions currently considered surreal and unreal could solve global problems being a derivative of the increase in greenhouse gas emissions, the ever-accelerating process of global warming and the growing demand for electricity.
What proposals do you have, surrealistic concepts for the surreal technologies of the future?
What do you think about this topic?
What's your opinion on this topic?
Do you agree with me on the above matter?
What technologies, currently considered surrealistic and possibly achievable in the future, could revolutionize technological progress and could solve key global problems of humanity?
What other ideas do you know about surrealistic technologies, known for example from science fiction novels and films, which if they became real, could they solve various key global problems of humanity?
Please reply
I invite you to the discussion
Our previous research suggested that experts’ perceptions related to the existence of expertise in standardization in small and medium enterprises (SMEs) significantly differ.
While some experts argued that expertise resides in all SMEs, others strongly suggested that expertise does not exist in SMEs. Assuming that owners and managers of SMEs must have had some level of expertise that enabled them to start their business activities and successfully carry them forward, given their lack of resources and capabilities, the question still remains - does expertise in standardization exist in SMEs?
What do you think - does expertise in standardization actually exist in SMEs?
Many approaches propose combined alternatives in this sense. For instance, using logic programing (Prolog), rough sets, and other more joined with models. However, it would be interesting to understand more practical strategies that promote a way of extracting the rules of inferences produced in the tree-based models.
As we know, most of the researchers use manual validation by the experts for the unlabeled User Reviews for a specific domain , but is there a new way? Because I worked with big sized dataset and using experts will be difficult?
if anyone use a new performance measure or a new way for validation, plz inform me .
Thanks in advance.
As we know, most of the researchers use manual validation by the experts on a domain, but is there a new way? or any benchmark, if anyone has a benchmark dataset for this task in any domain plz provides to me if possible. Thanks in advance.
I'm doing my dissertation on designing a model on Big Data knowledge discovery. I have used a questionnaire to gather the model components. now I want to know how can I validate the extracted model?
Should the instruments of motivating scientists and employees of companies to come up with new ideas, research concepts and innovations be improved in management processes?
Yes, in my opinion every scientific concept, idea, innovative solution, technological improvement, streamlining improvements, etc. after implementation into production should be properly rewarded. Every originator, inventor, etc. should receive a salary. It is necessary in a modern growing economy. In addition, instruments of motivating originators, scientists, also people employed in companies in various positions, should be constantly perfected to create well-designed financial instruments and / or non-financial remuneration for ideas, ideas, innovations, patents, improvement solutions, technological improvements, etc. implemented with positive effects. It is necessary that new ideas, ideas, innovations, etc. are created as much as possible and that they are implemented on a production scale. In the 21st century, especially pro-ecological innovations are particularly sought-after and necessary. In this way, the scope of cooperation, relationship between science and business is increased, and this is necessary in modern knowledge-based economies.
In the light of the above, encouraging discussion, I turn to you with the following question:
Should employee motivation instruments be invented in the management processes to come up with new ideas, research concepts and innovations?
Do you know the latest concepts of improving the instruments of motivating scientists and employees of companies to come up with new ideas, research concepts, innovations, ...?
Please, answer, comments. I invite you to the discussion.
I wish you the best in New Year 2019.
Best wishes
What are the procedures that we can implement in Transformation step?
The difference between these two designations lies in the type of approach used: artificial intelligence for Knowledge Discovery in Databases (KDD) with the use of heuristics from symbolic learning, statistics for Data Mining (DM) considered as an industrialization data analysis techniques.
there are different knowledge discovery can be implement in smart meter measurement. Are you interested in this type of analytic? or visulazation
Medical data mining has great potential for exploring the hidden patterns in the data sets of the medical domain. These patterns can be utilized for clinical diagnosis. However, the available raw medical data are widely distributed, heterogeneous in nature, and voluminous. These data need to be collected in an organized form. This collected data can be then integrated to form a hospital information system. Data mining technology provides a user-oriented approach to novel and hidden patterns in the data. Data mining and statistics both strive towards discovering patterns and structures in data. Statistics deals with heterogeneous numbers only, whereas data mining deals with heterogeneous fields. We identify a few areas of healthcare where these techniques can be applied to healthcare databases for knowledge discovery. In this paper we briefly examine the impact of data mining techniques, including artificial neural networks, on medical diagnostics.
is there any article discuses the correlation and linkage between them ?
Hi,
I'm looking for a free tool to recognize the terminology concepts in technical domains such as computer science and engineering.
Is there any available dictionary, gold standard or such a tool to do that? why there is no much research in this direction?
Thank you,
if so will this research challenge be tightly coupled with knowledge discovery. its well known that a picture is worth a thousand words. therefore there is a need for automated interpretation methods to aid end users who are illiterate as it were
Also a list of researchers working in this area can be listed. thanks
For example, the range of knowledge generated while doing your Phd thesis.
Information credibility depends on some of the information quality attributes; mainly accuracy, relevance, coherence and authenticity. Credibility is classified as presumed, reputed, surface, or experienced property. Credibility is gained and lost based on the quality of information being delivered as well as perception and interpretation of information. With current explosive rate of data generated by different business processes as well as magnitude of published information on the web internet information are identified as resources. These resources lack quality verification mechanisms. Achieving higher levels of information quality assurance requires formalization of information architecture and organization processes. Do you agree? If so, how should we resolve this problem?
What are the possible ways of knowledge discovery from extracted gene disease associations from biomedical text
The user contributions in the form of data and information are processed by using crowd-sourced human computations to generate knowledge in a knowledge management system.
Need pointers to similar research and any formal approaches to describe the process of knowledge creation in community crowds.
Dear RG members?
Does someone know guidelines for identifying Knowledge Gaps in Health Research?
In the literature, there are some systematic reviews about the knowledge gasps in some areas (e.g. cardiovascular diseases); but there are not clear guidelines about how to identify those knowledge gaps.
Thank you.
I am interested in datasets for knowledge discovery from data streams.
It would be valuable to obtain a real datasets, but artificial are fine for me as well. I am aware of: http://www.liaad.up.pt/kdus/products/datasets-for-concept-drift.
After several decades of exponential growth of studies on complexity, it seems to me that society remains on the sidelines, as if all research and serious advances were considered a mere academic debate far from people's real needs. What should the complexity research community do to permeate society?
Dear All, I need little help at starting my research work, I want to develop knowledge based event detection system from social media big data based on text messages and spatio-temporal information, I mean the system should have ability to tell about what is happening? what and where? in some region for example in London, The system should tell about for example emergency situation, fire, earthquake, traffic jam, raining, disease, volleyball or football match etc.
so my question, is it possible to detect such things from social media? for example from twitter.
if yes, then what kind of data mining and machine learning algorithms which i have need to use it for starting my research work? please can anyone help me in my question. Thank you in advance for your answer.
Best Regards,
Siraj
Does anybody have an example of research conducted in one area of science that when cross pollinated with research outputs from a different field of research, led to a breakthrough in a completely new area.
I am specifically looking for examples of research being conducted in two completely different areas and with no obvious connection that when brought together, by whatever means, led to a new discovery, process, or solution to an outstanding problem.
Hi guys,
I'm still newbie in big data analysis.
I'm currently looking to do incomplete data analysis for the big data in R rattle package.
I refer this book for my reference to do an analysis but it is not specifically focus on the big data.
I wish to get your knowldege sharing or opinion to do analysis the big data:
1) Any recommended data set that pretty enough with the big data size?
2) What is best size of data set that we should considered as a big dataset?
3) Any the best recommended tutorial to practice for the incomplete big data analysis ?
Thank you in advance
At the moment, I was able to find these papers:
1. Prototype a Knowledge Discovery Infrastructure by Implementing Relational Grid Monitoring Architecture (R-GMA) on European Data Grid (EDG) by Frank Wang, Na Helian, Yike Guo, Steve Thompson, John Gordon.
2. Knowledge grid-based problem-solving platform by Lu Zhen, Zuhua Jiang,Jun Liang.
Thank you in advance for any help.
Dear all
how can I find medical rule bases(knowledge base)?Is their implemented languages important for dealing with?what are they?
Hi all, we're considering different libraries and approaches for the construction of large sized graphs (using Twitter data) - upon construction graph algorithms will be evaluated, so the purpose is more for knowledge discovery rather than visualization.
Currently, it takes 4 hours to generate a graph for a twitter data set that has 21 days worth of twitter data.
1. Which would you recommend, Node4J or Jung, for this purpose?
2. Would HaDoop be a good choice to spread the construction task across different machines in order to save time?
3. How can we store a very large graph in memory , and how can it be made persistent?
I am looking for such a tool that shows me the value of a certain built feature on a desired part of the corpus. I need to not only visualize this but also get the distribution of every feature across the corpus (maybe in vector form) as output, so that I can analyze it faster by code, rather than manually.
Anyone know of any tool or resource even a bit similar to what I am looking for?
Thanks in advance.
I would be grateful if someone could point me to references for algorithms/approaches/techniques.
I've done some research on the topic and, so far, it was possible to identify that the following patterns have been thoroughly explored:
1) Sequence Mining. Example: "A-B-C-D happened in 10% of the database". This can also include a time constraint between events.
2) Temporal Association Rules: "A,B,C->D (30%, 20%) between 7am and 10am". In this case, the temporal information is used to "slice" the database in n-parts, which are then used to extract traditional association rules.
My first impression is that many recent researchers are focused on efficiently performing either 1 or 2, or porting them to data stream environments. I am wondering if there are any other patterns that can be obtained from timestamped data, for instance, "A,B->C (20%, 30%)", such that A and B happens in any order in a time window of at least 10 hours and at maximum 20 hours before C.
If nothing similar exists, is it worth the effort to develop a new data mining method to extract patterns similar to this?
Also, if you know about any open datasets with the following characteristics, please let me know. I've tried UCI repository, but no success so far.
Events with their respectives timestamps for many individuals or sensors. Example:
1 A (2012-02-20) B (2012-03-23) C (2013-01-20)
2 B (2003-04-30) D (2004-03-20)
3 B (2010-09-10) A (2010-10-01) C (2010-10-02)
There are many experienced prof. on this network. I need your guidance for effective teaching . Hope your sharing experience will helps not only me but also many lecturer.
Opinions, recommendations and success stories can be beneficial for many. Can it be helpful for sharing tacit knowledge?
