Introduction to TCP/IP Networking Network Model TCP/IP Terms Host Names Internet Addresses Subnet Addresses Internet Addresses to host name mapping Quiz# 1 Routing TCP/IP Daemons TCP/IP Information files TCP/IP Local Information files ifconfig mkhosts route Quiz# 2 TCP installed links Internet Services Common internet services error messages Trouble shooting commands ping netstat Trouble shooting Techniques
Introduction to TCP/IP
Chapter 4 introduction to TCP/IP protocols. Objectives in this chapter: Identify and explain the functions of the core TCP/IP protocols; explain how the TCP/IP protocols correlate to layers of the OSI model, discuss addressing schemes for TCP/IP in IPv4 and IPv6 protocols,... Inviting you to refer.
The research of neural networks has experienced several ups and downs in the 20th
century. The last resurgence is believed to be initiated by several seminal works of Hopfield
and Tank in the 1980s, and this upsurge has persisted for three decades. The Hopfield
neural networks, either discrete type or continuous type, are actually recurrent neural
networks (RNNs). The hallmark of an RNN, in contrast to feedforward neural networks, is
the existence of connections from posterior layer(s) to anterior layer(s) or connections
among neurons in the same layer....
The Internet is now a household term in many countries. With otherwise serious people beginning to joyride
along the Information Superhighway, computer networking seems to be moving toward the status of TV sets and
microwave ovens. The Internet has unusually high media coverage, and social science majors are descending on
Usenet newsgroups, online virtual reality environments, and the Web to conduct research on the new "Internet
In the recent years the electrical power utilities are undergoing rapid restructuring process
worldwide. Indeed, with deregulation, advancement in technologies and concern about
the environmental impacts, competition is particularly fostered in the generation side
thus allowing increased interconnection of generating units to the utility networks. These
generating sources are called as distributed generators (DG) and defined as the plant which is
directly connected to distribution network and is not centrally planned and dispatched.
As you might imagine, Teach Yourself TCP/IP in 14 Days provides a rapid introduction to the TCP/IP protocols and to a few commonly used applications that are built on top of them. The discussion is very lucid and emphasizes the fundamental concepts behind a given protocol; it does a good job of not letting the mass of details obscure the reasoning. Each section ends with a quiz and series of questions (and answers), so you can test your knowledge of each topic. The book also includes useful sections on sample installations and a nice discussion of sockets. As an added...
Decision support systems (DSS) have evolved over the past four decades from
theoretical concepts into real world computerized applications. DSS architecture contains
three key components: a knowledge base, a computerized model, and a user interface. DSS
simulate cognitive decision-making functions of humans based on artificial intelligence
methodologies (including expert systems, data mining, machine learning, connectionism,
logistical reasoning, etc.) in order to perform decision support functions.
In recent years many successful machine learning applications have been developed, ranging
from data mining programs that learn to detect fraudulent credit card transactions, to
information filtering systems that learn user’s reading preferences, to autonomous vehicles
that learn to drive on public highways. At the same time, machine learning techniques such
as rule induction, neural networks, genetic learning, case-based reasoning, and analytic
learning have been widely applied to real-world problems.
Even since computers were invented many decades ago, many researchers have been
trying to understand how human beings learn and many interesting paradigms and
approaches towards emulating human learning abilities have been proposed. The ability of
learning is one of the central features of human intelligence, which makes it an important
ingredient in both traditional Artificial Intelligence (AI) and emerging Cognitive Science.
Artificial Intelligence (AI) is often referred to as a branch of science which deals with
helping machines find solutions to complex problems in a more human-like fashion. It is
generally associated with Computer Science, but it has many important links with other
fields such as Maths, Psychology, Cognition, Biology and Philosophy. The AI success is due
to its technology has diffused into everyday life. Neural networks, fuzzy controls, decision
trees and rule-based systems are already in our mobile phones, washing machines and
Face plays an important role in human communication. Facial expressions and gestures
incorporate nonverbal information which contributes to human communication. By
recognizing the facial expressions from facial images, a number of applications in the field of
human computer interaction can be facilitated. Last two decades, the developments, as well
as the prospects in the field of multimedia signal processing have attracted the attention of
many computer vision researchers to concentrate in the problems of the facial expression
This book presents several recent advances on Evolutionary Computation, specially
evolution-based optimization methods and hybrid algorithms for several applications, from
optimization and learning to pattern recognition and bioinformatics. Concerning evolutionbased
optimization methods, this book presents diverse versions of genetic algorithms,
genetic programming, and performance studies and analyses, as well as several particle
swarm optimizers and hybrid approaches using neural networks and artificial
immunological systems for multi-objective optimization....
Swarm Intelligence is a research field that studies the emergent collective intelligence
of self-organized and decentralized simple agents. It is based on the social behavior
that can be observed in nature, such as in flocks of birds, fish schools and bee hives,
where a group of individuals with limited capabilities are able to emerge with
intelligent solutions for complex problems.
Entitites or computer programs that learn from their environment and can act based on
what they have learned can be defined as intelligent agents. These agents can be as simple
as triggering an alarm in case of a fire or as complex as human beings. Intelligent agents and
their applications to solve real-world problems are getting smarter and diversified day by
This book is consisting of 24 chapters which are focusing on the basic and applied research regarding e‐learning systems. Authors made efforts to provide theoretical as well as practical approaches to solve open problems through their elite research work.
A multi-agent system (MAS) is a system composed of multiple interacting intelligent agents. Multi-agent systems can be used to solve problems which are difficult or impossible for an individual agent or monolithic system to solve. Agent systems are open and extensible systems that allow for the deployment of autonomous and proactive software components. Multi-agent systems have been brought up and used in several application domains.
Nowadays, embedded systems - computer systems that are embedded in various
kinds of devices and play an important role of specific control functions, have
permeated various scenes of industry. Therefore, we can hardly discuss our life or
society from now on without referring to embedded systems. For wide-ranging
embedded systems to continue their growth, a number of high-quality fundamental
and applied researches are indispensable.
It has been many decades, since Computer Science has been able to achieve tremendous recognition
and has been applied in various fields, mainly computer programming and software
engineering. Many efforts have been taken to improve knowledge of researchers, educationists
and others in the field of computer science and engineering. This book provides a further
insight in this direction. It provides innovative ideas in the field of computer science and
engineering with a view to face new challenges of the current and future centuries....
The education industry has obviously been influenced by the Internet revolution. Teaching and learning methods have changed significantly since the coming of the Web and it is very likely they will keep evolving many years to come thanks to it. A good example of this changing reality is the spectacular development of e-Learning.
Technology is a product of science and reflects our ability to interact with the
environment. As science developed in time and became too vast for any one person to
master, different technologies emerged, consequently, in their attempt to reach excellence.
Although originally meant to work together, for a long time technological sectors developed
independently pursuing their own goals. In the recent times, since the value of information
became predominant in all spheres of human activity inevitably the scope of one technology
overlapped with another one.