icorg.org - ICORG - DomainsData

Success! Domain icorg.org was analyzed on Saturday 12. November 2016!

DomainsData.org: ICORG

Title:

ICORG
Age:

16 years old
Alexa Rank:
Total Sites Linking In (Alexa):

29
Domain's IP Country:

United States
Status Code:

OK
IP Address:

216.120.228.13
Description:
Keywords:

icorg.org Whois Information:

1.

Domain Name:

icorg.org
2.

Domain Age:

16 years old
3.

Name Server 1:

ns1.bitra.biz
4.

Name Server 2:

ns2.bitra.biz
5.

Created:

Friday 26. November 1999
6.

Expires:

Sunday 26. November 2017
7.

Domain Registrar:

PDR Ltd. d/b/a PublicDomainRegistry.com

Website Important Html Tags:

TAG
TEXT
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Iyyanki. V. Murali Krishna
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Dr. Raja Ramanna
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Curriculum Vitae
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IGSRM
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Talk Inst of Engineers
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Executive Summary
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Image Fusion - Issues and Research Trends
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IYYANKI V MURALI KRISHNA
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M Tech(IIT-Madras) PhD (IISc-Bangalore) FIE, FIS, FAPASc, FICDM, MIEEE, FIGU
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www.icorg.org
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[email protected]
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Guided / Co-Guided 26 PhDs and 152 M Tech / MCA/ M Sc / MS in the area of Geospatial Technology and Management corresponding to the following faculties:
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Engineers have a prominent role in the knowledge economy. Technology change in terms of technological convergence and knowledge management is a major engineering challenge. Innovation of new products and processes form the core of new knowledge.
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Changing technologies and path breaking technological developments will have to be subjugated in all engineering disciplines. Technological change, as given in the Wikipedia, is the overall process of invention, innovation and diffusion of technology or processes. The technological change is the outcome of the engineering challenges consisting of a set of missions viz., invention, improvement and diffusion of technologies. These missions could further be explicated on the lines of content given in Wikipedia as follows
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In short, technological change is perceived currently as an inevitable outcome and noticeable rejoinder for engineering challenges, which is centered around convergence of both superior and supplementary technologies.
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Technological convergence is the tendency that as technology changes, different technological systems sometimes evolve toward performing similar tasks. For example the Digital convergence refers to the convergence of four diligences into one business, information technologies, telecommunication, consumer electronics and entertainment. Previously separate technologies such as voice (telephone), data, and video can now share resources and intermingle with each other synergistically. This is a unique example of technological convergence in other words an output requiring the engineering challenges. Specifically this involves the converging of previously distinct media such as telephone and data comunications into common interfaces on single devices, such as most smart phones which can make phone calls and search the web.
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The technological convergence is one way or other manyntimes an unexpected off-shoot of technology forecast. Here it is worth quoting the Moor's law for better appreciating the concept of technological convergence visa vis engineering challenges. Gordon E. Moore, who was working as the director of research and development (R&D) at Fairchild Semiconductor, was asked to predict what was going to happen in the semiconductor components industry over the next ten years. His response was a brief article entitled, "Cramming more components onto integrated circuits" in the thirty-fifth anniversary issue of Electronics magazine, which was published on April 19, 1965. Dr Moore speculated that by 1975 it would be possible to contain as many as 65,000 components on a single quarter-inch semiconductor. His reasoning was a log-linear relationship between device complexity (higher circuit density at reduced cost) and time. At the 1975 IEEE International Electron Devices Meeting Moore revised the forecast rate Semiconductor complexity would continue to double annually until about 1980 after which it would decrease to a rate of doubling approximately every two years. He outlined several contributing factors for this exponential behavior .Simultaneous evolution to finer minimum dimensions and what Moore called "circuit and device cleverness"
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Shortly after 1975, this was popularized as "Moore's law" stating that integrated circuits would double in performance every 18 months. Predictions of similar increases in computer power had existed years prior to this. It is reported that Intel offered US$ 10,000 some time during 2005, to purchase a copy of the original Electronics issue in which Moore's article appeared. Although Moore's law initially was made in the form of an observation and forecast the more widely it became accepted, the more it served as a goal for the industry. This drove both marketing and engineering departments of semiconductor manufacturers to focus enormous energy aiming for the specified increase in processing power that it was presumed one or more of their competitors would soon attain. In this regard, it may be viewed as a self-fulfilling prophecy.
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While talking about knowledge prophecy the issues for acquiring knowledge are equally important and there are specific instances where problem based learning yielded significant results. This process could help to meet the engineers capable of meeting current challenges in a more effective manner. In problem solving, arriving at decisions based on prior knowledge and reasoning is important while in problem based learning, the process of acquiring new knowledge based on recognition of a need to learn is important. In problem based learning, small groups of engineers are presented with contextual situations and asked to define the problem, decide what skills and resources are necessary to investigate the problem and then pose possible solutions. PBL starts with the problems rather than with exposition of disciplinary knowledge. Students acquire knowledge skills and understanding through a staged sequence of problems presented in sequence. However, not all studies have found in favour of problem based learning.
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People are investing in systems to capture, organize, and disseminate information, and then call it knowledge. But knowledge, by definition, cannot be converted into an object and given from one person to another without established flowing mechansims. Much of the confusion and disappointment concerning knowledge management stems from confusion between information and knowledge since not even KM experts link knowledge to action. There is no clarity. Knowledge only diffuses when there are learning processesThere is a discussion going on at the moment on Linked-Â-In, about the definition of knowledge, with several people arguing that a definition of knowledge is fundamental to knowledge management. Here reproduce the quoted example of a map of mineral data, which is to be used to site a gold mine:
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Currently, no universally accepted definition of knowledge management exists, but there are some basic concepts to be explored, and considered. Simply put, knowledge management undertakes to identify what is in essence a human asset buried in the minds and hard drives of engineers working in an organization. Knowledge management also requires a system that will allow the creation of new knowledge, a dissemination system that will reach every engineer, with the ability to package knowledge as value-added in products, services and systems. However, knowledge management goes far beyond the storage and manipulation of data, or even of information. There are two kinds of knowledge: tacit, which is hard to articulate, versus explicit knowledge, which can be expressed in words and numbers and can be easily communicated and shared in hard form, as scientific formulas, codified procedures, or universal principles. Tacit or unarticulated knowledge is more personal, experiential, context specific, and hard to formalize. This kind of knowledge is difficult to communicate or share with others, and is generally inside the heads of individuals and teams. Since knowledge may be an organization's only sustainable competitive advantage, it is very important to capture tacit knowledge and transfer it. It is the engieering challenge
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Knowledge is considered as discussed in various artciles as available in cyberspace as intangible, dynamic, and difficult to measure, but without it no developmental engineering institution can sustain. In fact, flows of knowledge is an indicator of institution's capacity to learn. The knowledge economy generally could be considered as different from the customary economy in several key respects: the economics is not of scarcity, but rather of abundance, and unlike most resources that deplete when used, information and knowledge can be distributed, and actually grows through such synergy.

icorg.org IP Information:

1.

Ip Address:

216.120.228.13
2.

Country:

United States
3.

Status Code:

OK
4.

Region Name:

New York
5.

City Name:

Clifton Park
6.

Zip Code:

12065
7.

Speed test:

72.1 ms

icorg.org Alexa Information:

5 Websites linking to icorg.org:
angelfire.com
members.tripod.com
isprs.org
bitra.com
bitratraining.com

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Top Keywords from Search Engines:
g.murali krishna web designer visakhapatnam, data science is training in hyderabad is considered as the most emerging field these days to become data scientist experts. it is considered as the interdisciplinary field that processes various systems to extract required data from the databases.

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