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.
Reconstruction- and example-based super-resolution
(SR) methods are promising for restoring a high-resolution
(HR) image from low-resolution (LR) image(s). Under large
magnification, reconstruction-based methods usually fail
to hallucinate visual details while example-based methods
sometimes introduce unexpected details. Given a generic
LR image, to reconstruct a photo-realistic SR image and
to suppress artifacts in the reconstructed SR image, we
introduce a multi-scale dictionary to a novel SR method
that simultaneously integrates local and non-local priors.
The local prior suppresses artifacts by using steering kernel regression to predict the target pixel from a small local
area. The non-local prior enriches visual details by taking
a weighted average of a large neighborhood as an estimate
of the target pixel. Essentially, these two priors are complementary to each other. Experimental results demonstrate
that the proposed method can produce high quality SR recovery both quantitatively and perceptually.
This book provides an overview of recent innovations and achievements in the broad areas of cyber-physical systems (CPS), including architecture, networking, systems, applications, security, and privacy. The book discusses various new CPS technologies from diverse aspects to enable higher level of innovation towards intelligent life. The book provides insight to the future integration, coordination and interaction between the physical world, the information world, and human beings. The book features contributions from renowned researchers and engineers, who discuss key issues from various perspectives, presenting opinions and recent CPS-related achievements.Investigates how to advance the development of cyber-physical systems
Provides a joint consideration of other newly emerged technologies and concepts in relation to CPS like cloud computing, big data, fog computing, and crowd sourcing
Includes topics related to CPS such as architecture, system, networking, application, algorithm, security and privacy
Abstract—In the future communication applications, users
may obtain their messages that have different importance levels
distributively from several available sources, such as distributed
storage or even devices belonging to other users. This
scenario is the best modeled by the multilevel diversity coding
systems (MDCS). To achieve perfect (information-theoretic)
secrecy against wiretap channels, this paper investigates the
fundamental limits on the secure rate region of the asymmetric
MDCS (AMDCS), which include the symmetric case as a special
case. Threshold perfect secrecy is added to the AMDCS model.
The eavesdropper may have access to any one but not more than
one subset of the channels but know nothing about the sources,
as long as the size of the subset is not above the security level.
The question of whether superposition (source separation) coding
is optimal for such an AMDCS with threshold perfect secrecy
is answered. A class of secure AMDCS (S-AMDCS) with an
arbitrary number of encoders is solved, and it is shown that linear
codes are optimal for this class of instances. However, in contrast
with the secure symmetric MDCS, superposition is shown to
be not optimal for S-AMDCS in general. In addition, necessary
conditions on the existence of a secrecy key are determined as a
design guideline.
Recently millimeter-wave bands have been postu-
lated as a means to accommodate the foreseen extreme bandwidth
demands in vehicular communications, which result from the
dissemination of sensory data to nearby vehicles for enhanced
environmental awareness and improved safety level. However, the
literature is particularly scarce in regards to principled resource
allocation schemes that deal with the challenging radio conditions
posed by the high mobility of vehicular scenarios
Recently millimeter-wave bands have been postu-
lated as a means to accommodate the foreseen extreme bandwidth
demands in vehicular communications, which result from the
dissemination of sensory data to nearby vehicles for enhanced
environmental awareness and improved safety level.
