2,803 research outputs found
Gene Expression based Survival Prediction for Cancer Patients: A Topic Modeling Approach
Cancer is one of the leading cause of death, worldwide. Many believe that
genomic data will enable us to better predict the survival time of these
patients, which will lead to better, more personalized treatment options and
patient care. As standard survival prediction models have a hard time coping
with the high-dimensionality of such gene expression (GE) data, many projects
use some dimensionality reduction techniques to overcome this hurdle. We
introduce a novel methodology, inspired by topic modeling from the natural
language domain, to derive expressive features from the high-dimensional GE
data. There, a document is represented as a mixture over a relatively small
number of topics, where each topic corresponds to a distribution over the
words; here, to accommodate the heterogeneity of a patient's cancer, we
represent each patient (~document) as a mixture over cancer-topics, where each
cancer-topic is a mixture over GE values (~words). This required some
extensions to the standard LDA model eg: to accommodate the "real-valued"
expression values - leading to our novel "discretized" Latent Dirichlet
Allocation (dLDA) procedure. We initially focus on the METABRIC dataset, which
describes breast cancer patients using the r=49,576 GE values, from
microarrays. Our results show that our approach provides survival estimates
that are more accurate than standard models, in terms of the standard
Concordance measure. We then validate this approach by running it on the
Pan-kidney (KIPAN) dataset, over r=15,529 GE values - here using the mRNAseq
modality - and find that it again achieves excellent results. In both cases, we
also show that the resulting model is calibrated, using the recent
"D-calibrated" measure. These successes, in two different cancer types and
expression modalities, demonstrates the generality, and the effectiveness, of
this approach
ARPA Whitepaper
We propose a secure computation solution for blockchain networks. The
correctness of computation is verifiable even under malicious majority
condition using information-theoretic Message Authentication Code (MAC), and
the privacy is preserved using Secret-Sharing. With state-of-the-art multiparty
computation protocol and a layer2 solution, our privacy-preserving computation
guarantees data security on blockchain, cryptographically, while reducing the
heavy-lifting computation job to a few nodes. This breakthrough has several
implications on the future of decentralized networks. First, secure computation
can be used to support Private Smart Contracts, where consensus is reached
without exposing the information in the public contract. Second, it enables
data to be shared and used in trustless network, without disclosing the raw
data during data-at-use, where data ownership and data usage is safely
separated. Last but not least, computation and verification processes are
separated, which can be perceived as computational sharding, this effectively
makes the transaction processing speed linear to the number of participating
nodes. Our objective is to deploy our secure computation network as an layer2
solution to any blockchain system. Smart Contracts\cite{smartcontract} will be
used as bridge to link the blockchain and computation networks. Additionally,
they will be used as verifier to ensure that outsourced computation is
completed correctly. In order to achieve this, we first develop a general MPC
network with advanced features, such as: 1) Secure Computation, 2) Off-chain
Computation, 3) Verifiable Computation, and 4)Support dApps' needs like
privacy-preserving data exchange
Toward Consistent Creation of Marine Information Overlays: Configuration of ESRI’s PLTS Nautical Solution
This project presents a set of tools to facilitate interoperability between an ArcGIS geodatabase model and the S-57 international standard for nautical data. Additionally configurations and workflows were developed for consistent creation of nautical data in accordance with said standard. Central to this interoperability are Marine Information Overlays (MIO), which are additional navigation information to the Electronic Nautical Chart database. MIO data is intended to provide safe and efficient ship routing. Semantic mapping between the marine objects in the S-57 standard and the MIO model preserves the essential components of each. Data interoperability is realized through the use of semantic mapping via a configured PLTS Nautical Solution import/export engine and standards are supported through the use of this software
Mass-Market Receiver for Static Positioning: Tests and Statistical Analyses
Nowadays, there are several low cost GPS receivers able to provide both pseudorange and carrier phase measurements in the L1band, that allow to have good realtime performances in outdoor condition. The present paper describes a set of dedicated tests in order to evaluate the positioning accuracy in static conditions. The quality of the pseudorange and the carrier phase measurements let hope for interesting results. The use of such kind of receiver could be extended to a large number of professional applications, like engineering fields: survey, georeferencing, monitoring, cadastral mapping and cadastral road. In this work, the receivers performance is verified considering a single frequency solution trying to fix the phase ambiguity, when possible. Different solutions are defined: code, float and fix solutions. In order to solve the phase ambiguities different methods are considered. Each test performed is statistically analyzed, highlighting the effects of different factors on precision and accurac
Modeling Algorithms in SystemC and ACL2
We describe the formal language MASC, based on a subset of SystemC and
intended for modeling algorithms to be implemented in hardware. By means of a
special-purpose parser, an algorithm coded in SystemC is converted to a MASC
model for the purpose of documentation, which in turn is translated to ACL2 for
formal verification. The parser also generates a SystemC variant that is
suitable as input to a high-level synthesis tool. As an illustration of this
methodology, we describe a proof of correctness of a simple 32-bit radix-4
multiplier.Comment: In Proceedings ACL2 2014, arXiv:1406.123
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Research on Voyage Navigation S/W Development Architecture Using Open Source Base GIS Modules
Recently, as the number of voyage accident is increasing, massive damage of human life and property is following depends on scale of accident. ECDIS is navigation equipment essential for safe sailing and clean marine environment. However, ECDIS S/W is relatively expensive, and ocean-related international organizations such as IMO and IHO are designing the programs mainly for medium and large ships. OPEN CPN, SeaClear are existing as product based on Open Source Project, however they are lack of functions to use in actual voyage. ECDIS development by making combination with modules based on open source could be an alternative to follow the standards and develop efficiently
TRIDEnT: Building Decentralized Incentives for Collaborative Security
Sophisticated mass attacks, especially when exploiting zero-day
vulnerabilities, have the potential to cause destructive damage to
organizations and critical infrastructure. To timely detect and contain such
attacks, collaboration among the defenders is critical. By correlating
real-time detection information (alerts) from multiple sources (collaborative
intrusion detection), defenders can detect attacks and take the appropriate
defensive measures in time. However, although the technical tools to facilitate
collaboration exist, real-world adoption of such collaborative security
mechanisms is still underwhelming. This is largely due to a lack of trust and
participation incentives for companies and organizations. This paper proposes
TRIDEnT, a novel collaborative platform that aims to enable and incentivize
parties to exchange network alert data, thus increasing their overall detection
capabilities. TRIDEnT allows parties that may be in a competitive relationship,
to selectively advertise, sell and acquire security alerts in the form of
(near) real-time peer-to-peer streams. To validate the basic principles behind
TRIDEnT, we present an intuitive game-theoretic model of alert sharing, that is
of independent interest, and show that collaboration is bound to take place
infinitely often. Furthermore, to demonstrate the feasibility of our approach,
we instantiate our design in a decentralized manner using Ethereum smart
contracts and provide a fully functional prototype.Comment: 28 page
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