Functions are mappings from one Manifold to another. Discrete Functions are functions which can be represented using a finite number of values. Given the finite extent of computer memory, algorithms which compute a function that satisfies some special properties are computing a discrete function which approximates a continuous function. Computing the function involves writing a set of equations that may be solved for the values representing the function.
The algorithm ID3 (Quinlan) uses the method top-down induction of decision trees. Given a set of classified examples a decision tree is induced, biased by the information gain measure, which heuristically leads to small trees. The examples are given in attribute-value representation. The set of possible classes is finite. Only tests, that split the set of instances of the underlying example languages depending on the value of a single attribute are supported.
C programming is a craft that takes years to perfect. A reasonably sharp person can learn the basics of
C quite quickly. But it takes much longer to master the nuances of the language and to write enough
programs, and enough different programs, to become an expert. In natural language terms, this is the
difference between being able to order a cup of coffee in Paris, and (on the Metro) being able to tell anative Parisienne where to get off. This book is an advanced text on the ANSI C programming
language. It is intended for people who are already writing C programs, and who want to quickly pick
up some of the insights and techniques of experts.
Guided vehicles (GVs) are commonly used for the internal transportation of loads in warehouses, production plants and terminals. These guided vehicles can be routed with a variety of vehicle dispatching rules in an attempt to meet performance criteria such as minimizing the average load waiting times. In this research, we use simulation models of three companies to evaluate the performance of several real-time vehicle dispatching rules, in part described in the literature. It appears that there
is a clear difference in average load waiting time between the different dispatching rules in the different environments. Simple rules, based on load and vehicle proximity (distance-based) perform best for all cases. The penalty for this is a relatively high maximum load waiting time. A distance-based rule with time truncation, giving more priority to loads that have to wait longer than a time threshold, appears to yield the best possible overall performance. A rule that particularly considers load-waiting time performs poor overall. We also show that using little pre-arrival information of loads leads to a significant improvement in the performance of the dispatching rules without changing their performance ranking.
We consider the problem of target localization by a
network of passive sensors. When an unknown target emits an
acoustic or a radio signal, its position can be localized with multiple
sensors using the time difference of arrival (TDOA) information.
In this paper, we consider the maximum likelihood formulation
of this target localization problem and provide efficient convex
relaxations for this nonconvex optimization problem.We also propose
a formulation for robust target localization in the presence of
sensor location errors. Two Cramer-Rao bounds are derived corresponding
to situations with and without sensor node location errors.
Simulation results confirm the efficiency and superior performance
of the convex relaxation approach as compared to the
existing least squares based approach when large sensor node location
errors are present.
The CommScope InstaPATCH? 360 and ReadyPATCH? solutions utilize a
standards-compliant multi-fiber connector to provide high density termination
capability. The connector is called an MPO (Multi-fiber Push On) connector by
the standards. In many cases, multi-fiber connector products are referred to as
MTP connectors. This document is intended to clarify the difference between the two terms – MPO and MTP.
During the past years, there has been a quickly rising interest in radio access tech-
nologies for providing mobile as well as nomadic and fixed services for voice,
video, and data. The difference in design, implementation, and use between
telecom and datacom technologies is also getting more blurred. One example is
cellular technologies from the telecom world being used for broadband data and
wireless LAN from the datacom world being used for voice over IP.
Duringthe past years, there has been a quickly rising interest in radio access technologies for providing
mobile as well as nomadic and fixed services for voice, video, and data. This proves that the difference
in design, implementation, and use between telecom and datacom technologies is also becoming more
blurred. What used to be a mobile phone used for voice communication is today increasingly
becoming the main data communication device for end-users, providing web browsing, social
networking, and many other services.
An acronym for Multiple-In, Multiple-Out, MIMO communication sends the same data as several signals
simultaneously through multiple antennas, while still utilizing a single radio channel. This is a form of
antenna diversity, which uses multiple antennas to improve signal quality and strength of an RF link. The
data is split into multiple data streams at the transmission point and recombined on the receive side by
another MIMO radio configured with the same number of antennas. The receiver is designed to take
into account the slight time difference between receptions of each signal, any additional noise or
interference, and even lost signals.
Electrostatic discharge (ESD) is one of the most prevalent threats to the reliability
of electronic components. It is an event in which a finite amount of charge is trans-
ferred from one object (i.e., human body) to another (i.e., microchip). This process
can result in a very high current passing through the microchip within a very short
period of time, and, hence, more than 35% of chip damages can be attributed to an
ESD-related event. As such, designing on-chip ESD structures to protect integrated
circuits against the ESD stresses is a high priority in the semiconductor industry.
