The relationship between artificial intelligence and psychological theoriesEr. rahul abhishek
Psychology is one of the parent elements of artificial
intelligence or we can also say that it is the main source for
artificial intelligence. In this paper we are discussing about the
theories of psychology used in AI. Since psychology is the study
of human brain and its nature and AI is the branch which deals
with the intelligence in machine, so for understanding the
intelligence of a machine we have to compare with human
intelligence because AI means the intelligence shown by a
machine like a human being.
The technologies of ai used in different corporate worldEr. rahul abhishek
Artificial intelligence (AI) is making its way back into the mainstream of corporate technology, this time at the core of business systems which are providing competitive advantage in all sorts of industries, including electronics, manufacturing, software, medicine, entertainment, engineering and communications, designed to leverage the capabilities of humans rather than replace them, today’s AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world. Some AI enabled applications are information distribution and retrieval, database mining, product design, manufacturing, inspection, training, user support, surgical planning, resource scheduling, and complex resource management.
The relationship between artificial intelligence and psychological theoriesEr. rahul abhishek
Psychology is one of the parent elements of artificial
intelligence or we can also say that it is the main source for
artificial intelligence. In this paper we are discussing about the
theories of psychology used in AI. Since psychology is the study
of human brain and its nature and AI is the branch which deals
with the intelligence in machine, so for understanding the
intelligence of a machine we have to compare with human
intelligence because AI means the intelligence shown by a
machine like a human being.
The technologies of ai used in different corporate worldEr. rahul abhishek
Artificial intelligence (AI) is making its way back into the mainstream of corporate technology, this time at the core of business systems which are providing competitive advantage in all sorts of industries, including electronics, manufacturing, software, medicine, entertainment, engineering and communications, designed to leverage the capabilities of humans rather than replace them, today’s AI technology enables an extraordinary array of applications that forge new connections among people, computers, knowledge, and the physical world. Some AI enabled applications are information distribution and retrieval, database mining, product design, manufacturing, inspection, training, user support, surgical planning, resource scheduling, and complex resource management.
Learning of robots by using & sharing the cloud computing techniquesEr. rahul abhishek
Robots are shaping a new era in the technology, many
algorithms has been developed for their learning which
they can apply to find the solution for the problems that
they are facing. That is, we have tried to provide them a
basic intelligence (like recognition, collision avoidance,
etc.). But besides that basic intelligence we are interested
in developing an intelligent system in which robots will
use their experiences and share it with each other just like
humans, who have got all its intelligence by his
experience and imaginations and sharing it with each
other. To implement this intelligent system we can use a
local server (word interchangeable to database) that will
be restricted to a robot only and a Cloud (global) server
where the authorized robots can upload their experiences
which can be used by every robot (which is authorized to
that server) to solve their problems.
In this paper, we discussed about the use of Artificial
Intelligence (AI) along with robots in which we took a
robot with java & artificial intelligence program and it
will perform some action according to the condition and
need of the surrounding. AI is the branch derived from the
computer science which works as like a human being we
focused this artificial human intelligence in our paper. We
can explain AI as a science and engineering of making
intelligence machines. The robots have proven that they
are beneficial to human life in various fields. But to
access these benefits we should require some high level of
intelligence that works as a human being and this high
level of intelligence can only be obtained by the artificial
intelligence.
In this paper, we discussed about the approach of Artificial Intelligence (AI) towards thermal imaging. At first we are going to discuss about AI, thermal imaging and at last but not the least about their approaches.
Since AI is one of the branches of computer science which aims at building machines that can think, feel and take decisions just like humans do. It is used in Expert systems, thermal imaging, Robotics, Neuroscience, Gaming, and in many more fields. It can be classified into two types first one is strong artificial intelligence and other is weak artificial intelligence.
Thermal imaging is the process which uses an infrared imaging and measurement camera to “see” and “measure” thermal energy emitted from an object. Thermal or infrared energy cannot be visible through naked eyes but with the help of thermal imaging we can now see and measure the infrared radiation. It has its wider application in industries, national army, different types of mines etc.
In this paper we are going to show the interrelationship between artificial intelligence (AI) and the thermal imaging. It is widely or say completely related to each other. Their function, operation and co-relation are described further in this paper.
Knowledge or Rule based Expert systems systems are widely used in engineering applications and in problem-solving. Rapid development today has brought with it environmental problems that cause loss or destruction of natural resources. Environmental impact assessment (EIA) has been acknowledged as a powerful planning and decisionmaking tool to assess new development projects. It requires qualified personnel with special expertise and responsibility in their domain. Rule-based EIA systems incorporate expert’s knowledge and act as a device-giving system. The system has an advantage over human experts and can significantly reduce the complexity of a planning task like EIA.
Uncertainty classification of expert systems a rough set approachEr. rahul abhishek
In this paper, we discussed about the un certainity classifications of the Expert Systems using a Rough Set Approach. It is a Softcomputing technique using this we classified the types of Expert Systems. An expert system has a unique structure, different from traditional programs. It is divided into two parts, one fixed, independent of the expert system: the inference engine, and one variable: the knowledge base. To run an expert system, the engine reasons about the knowledge base like a human. In the 80's a third part appeared: a dialog interface to communicate with users. This ability to conduct a conversation with users was later called "conversational". Rough set theory is a technique deals with uncertainty.
Inteligent computing relating to cloud computing.finalEr. rahul abhishek
This paper contends that the real understanding of natural language and the fulfillment of cloud computing cannot be reached without dealing with the significant sentimental factor. This paper points out that the achievement and enjoyment of cloud computing is highly reliant on break throughs in advanced intelligence. In this paper, advanced intelligence refers to the high level of interaction between natural intelligence and artificial intelligence.
We introduce intelligent computing language in the software so that machines can take decisions autonomously and in real time. By applying artificial intelligence to the cloud, we are hoping to develop a system through which computers can manage themselves. For example, computer scientists are looking to develop software that follows computers’ power consumption and regulates their operation according to the specific needs at any given time, thus reducing energy expenditure.
Implanting artificial intelligence into codes that will run in the cloud to improve efficiency is one of the strong research lines. Its part of a drive to create applications, executed in the cloud that goes beyond basic automation to anticipate situations and take decisions in real time over the Internet. We introduce intelligent computing language in the software so that machines can take decisions autonomously and in real time.
Inteligent computing relating to cloud computing.final
Quality Analyst related job
1. A rough notes for Quality Analyst interview
Er. Rahul Abhishek
Quality Analyst
rahulmithu.abhishek@gmail.com
1- What is Quality?
Quality is a back bone of any organization which help to grow in market for long
term.
Quality is something which understand customer’s need & can fulfill their
requirements.
It is something which meets customer’s expectation & increase customer’s
satisfaction.
It help to increase customer’s faith on the product.
2- Why you want to join as a QA?
As quality is back bone of organization it will help me as well as organization to
grow.
As the job is process oriented it will give me the opportunity to do try several things
at the time.
In a single moment I can apply number of works at a time in which I am good, such
as - the needed documents, test the application, write test plans and test cases,
prepare reports and retest them once again if the need arises & also provide
feedbacks.
My favorite task would be reducing defects. The more defects I find while working,
the happier I will be.
3- What are the basic Quality tools?
There are 7 basic Quality tools use
Cause-and-effect diagram (also known as the "fishbone" or Ishikawa diagram)
Check sheet
Control chart
Histogram
Pareto chart
Scatter diagram
Stratification (alternately, flow chart or run chart)
4- Define the basic tools of quality.
Cause-and-effect diagram (also known as the "fishbone" or Ishikawa diagram):-
It’s the method of problem solving used for identify the root cause of the fault or
problems.
Causes are usually grouped into major categories to identify these sources of variation. The
categories typically include
2. People: Anyone involved with the process
Methods: How the process is performed and the specific requirements for doing it,
such as policies, procedures, rules, regulations and laws
Machines: Any equipment, computers, tools, etc. required to accomplish the job
Materials: Raw materials, parts, pens, paper, etc. used to produce the final product
Measurements: Data generated from the process that are used to evaluate its quality
Environment: The conditions, such as location, time, temperature, and culture in
which the process operates.
Check the fig.1. Below
Check sheet:-
A structured, prepared form for collecting and analyzing data; a generic tool that can be
adapted for a wide variety of purposes. When the information is quantitative, the check sheet
is sometimes called a tally sheet.
Control chart:-
It’s also known as process-behavior charts. It’s the graph used to study how a process changes
over time. Data are plotted in time order. This always has a central line for the average, an upper
line as upper control limit & a lower line for the lower control limit. These line are determined
from historical data.
Histogram:-
A histogram is a graphical representation of the distribution of numerical data. It is an estimate
of the probability distribution of a continuous variable (quantitative variable). It also the most
commonly used graph for showing frequency distributions, or how often each different value in a
set of data occurs.
Pareto chart:-
3. It’s the type of chart that contains both bars & a line graph, where individual’s values are
represented in descending order by bars & the cumulative total is represented by the lines. It’s
the tools which help us to prioritize the major defects from largest to lowest. It works on 80/20
rules, where 80 % of problems may be attributed to 20% of the causes.
Fig 2. Below
Scatter diagram:-
Graphs pairs of numerical data, one variable on each axis, to look for a relationship. It’s a
graph in which the values of two variable are plotted among two axis, the pattern of the
resulting points revealing any correlation present.
Stratification (alternately, flow chart or run chart):-
A technique that separates data gathered from a variety of sources so that patterns can be
seen (some lists replace “stratification” with “flowchart” or “run chart”).
Flow chart: - It’s a type of diagram that represent an algorithm, workflow or process,
showing the steps as boxes of various kinds & their order by connecting them with arrows. This
diagrammatical representation illustrates a solution model to a given problem.
Run chart: - It’s a line graph of data plotted over time. By collecting & charting data over
time, you can find trends or patterns in the process. Because they don’t use control limits. It
can’t tell that process is stable.
6. What are the policy?
CAP- Corrective Action Policy.
DAP- Disciplinary Action Policy.
ZTP- Zero Tolerance Policy.
References
https://en.wikipedia.org/wiki/Seven_Basic_Tools_of_Quality