The object detector described below has been initially proposed by
P.F. Felzenszwalb in [Felzenszwalb2010]. It is based on a
Dalal-Triggs detector that uses a single filter on histogram of
oriented gradients (HOG) features to represent an object category.
This detector uses a sliding window approach, where a filter is
applied at all positions and scales of an image. The first
innovation is enriching the Dalal-Triggs model using a
star-structured part-based model defined by a “root” filter
(analogous to the Dalal-Triggs filter) plus a set of parts filters
and associated deformation models. The score of one of star models
at a particular position and scale within an image is the score of
the root filter at the given location plus the sum over parts of the
maximum, over placements of that part, of the part filter score on
its location minus a deformation cost easuring the deviation of the
part from its ideal location relative to the root. Both root and
part filter scores are defined by the dot product between a filter
(a set of weights) and a subwindow of a feature pyramid computed
from the input image. Another improvement is a representation of the
class of models by a mixture of star models. The score of a mixture
model at a particular position and scale is the maximum over
components, of the score of that component model at the given
location.
The 4.0 kbit/s speech codec described in this paper is based on a
Frequency Domain Interpolative (FDI) coding technique, which
belongs to the class of prototype waveform Interpolation (PWI)
coding techniques. The codec also has an integrated voice
activity detector (VAD) and a noise reduction capability. The
input signal is subjected to LPC analysis and the prediction
residual is separated into a slowly evolving waveform (SEW) and
a rapidly evolving waveform (REW) components. The SEW
magnitude component is quantized using a hierarchical
predictive vector quantization approach. The REW magnitude is
quantized using a gain and a sub-band based shape. SEW and
REW phases are derived at the decoder using a phase model,
based on a transmitted measure of voice periodicity. The spectral
(LSP) parameters are quantized using a combination of scalar
and vector quantizers. The 4.0 kbits/s coder has an algorithmic
delay of 60 ms and an estimated floating point complexity of
21.5 MIPS. The performance of this coder has been evaluated
using in-house MOS tests under various conditions such as
background noise. channel errors, self-tandem. and DTX mode
of operation, and has been shown to be statistically equivalent to
ITU-T (3.729 8 kbps codec across all conditions tested.
Introduction
jSMPP is a java implementation (SMPP API) of the SMPP protocol (currently supports SMPP v3.4). It provides interfaces to communicate with a Message Center or an ESME (External Short Message Entity) and is able to handle traffic of 3000-5000 messages per second.
jSMPP is not a high-level library. People looking for a quick way to get started with SMPP may be better of using an abstraction layer such as the Apache Camel SMPP component: http://camel.apache.org/smpp.html
Travis-CI status:
History
The project started on Google Code: http://code.google.com/p/jsmpp/
It was maintained by uudashr on Github until 2013.
It is now a community project maintained at http://jsmpp.org
Release procedure
mvn deploy -DperformRelease=true -Durl=https://oss.sonatype.org/service/local/staging/deploy/maven2/ -DrepositoryId=sonatype-nexus-staging -Dgpg.passphrase=<yourpassphrase>
log in here: https://oss.sonatype.org
click the 'Staging Repositories' link
select the repository and click close
select the repository and click release
License
Copyright (C) 2007-2013, Nuruddin Ashr uudashr@gmail.com Copyright (C) 2012-2013, Denis Kostousov denis.kostousov@gmail.com Copyright (C) 2014, Daniel Pocock http://danielpocock.com Copyright (C) 2016, Pim Moerenhout pim.moerenhout@gmail.com
This project is licensed under the Apache Software License 2.0.
An optical fiber amplifier is a key component for enabling efficient transmission of
wavelength-divisionmultiplexed(WDM)signalsoverlongdistances.Eventhough
many alternative technologies were available, erbium-doped fiber amplifiers won
theraceduringtheearly1990sandbecameastandardcomponentforlong-haulopti-
caltelecommunicationssystems.However,owingtotherecentsuccessinproducing
low-cost, high-power, semiconductor lasers operating near 1450 nm, the Raman
amplifiertechnologyhasalsogainedprominenceinthedeploymentofmodernlight-
wavesystems.Moreover,becauseofthepushforintegratedoptoelectroniccircuits,
semiconductor optical amplifiers, rare-earth-doped planar waveguide amplifiers,
and silicon optical amplifiers are also gaining much interest these days.
In a cellular communication system, a service area or a geographical
region is divided into a number of cells, and each cell is served by an
infrastructure element called the base station through a radio interface.
Management of radio interface related resources is a critical design
component in cellular communications.
Computer science as an academic discipline began in the 1960’s. Emphasis was on
programming languages, compilers, operating systems, and the mathematical theory that
supported these areas. Courses in theoretical computer science covered finite automata,
regular expressions, context-free languages, and computability. In the 1970’s, the study
of algorithms was added as an important component of theory. The emphasis was on
making computers useful. Today, a fundamental change is taking place and the focus is
more on a wealth of applications. There are many reasons for this change. The merging
of computing and communications has played an important role. The enhanced ability
to observe, collect, and store data in the natural sciences, in commerce, and in other
fields calls for a change in our understanding of data and how to handle it in the modern
setting. The emergence of the web and social networks as central aspects of daily life
presents both opportunities and challenges for theory.
This design uses Common-Emitter Amplifier (Class A) with 2N3904 Bipolar Junction Transistor.
Use “Voltage Divider Biasing” to reduce the effects of varying β (= ic / ib) (by holding the Base voltage constant)
Base Voltage (Vb) = Vcc * [R2 / (R1 + R2)]
Use Coupling Capacitors to separate the AC signals from the DC biasing voltage (which only pass AC signals and block any DC component).
Use Bypass Capacitor to maintain the Q-point stability.
To determine the value of each component, first set Q-point close to the center position of the load line. (RL is the resistance of the speaker.)
