1,527 research outputs found
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
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From M-ary Query to Bit Query: a new strategy for efficient large-scale RFID identification
The tag collision avoidance has been viewed as one of the most important research problems in RFID communications and bit tracking technology has been widely embedded in query tree (QT) based algorithms to tackle such challenge. Existing solutions show further opportunity to greatly improve the reading performance because collision queries and empty queries are not fully explored. In this paper, a bit query (BQ) strategy based Mary query tree protocol (BQMT) is presented, which can not only eliminate idle queries but also separate collided tags into many small subsets and make full use of the collided bits. To further optimize the reading performance, a modified dual prefixes matching (MDPM) mechanism is presented to allow multiple tags to respond in the same slot and thus significantly reduce the number of queries. Theoretical analysis and simulations are supplemented to validate the effectiveness of the proposed BQMT and MDPM, which outperform the existing QT-based algorithms. Also, the BQMT and MDPM can be combined to BQMDPM to improve the reading performance in system efficiency, total identification time, communication complexity and average energy cost
Strategy evolution on dynamic networks
Models of strategy evolution on static networks help us understand how
population structure can promote the spread of traits like cooperation. One key
mechanism is the formation of altruistic spatial clusters, where neighbors of a
cooperative individual are likely to reciprocate, which protects prosocial
traits from exploitation. But most real-world interactions are ephemeral and
subject to exogenous restructuring, so that social networks change over time.
Strategic behavior on dynamic networks is difficult to study, and much less is
known about the resulting evolutionary dynamics. Here, we provide an analytical
treatment of cooperation on dynamic networks, allowing for arbitrary spatial
and temporal heterogeneity. We show that transitions among a large class of
network structures can favor the spread of cooperation, even if each individual
social network would inhibit cooperation when static. Furthermore, we show that
spatial heterogeneity tends to inhibit cooperation, whereas temporal
heterogeneity tends to promote it. Dynamic networks can have profound effects
on the evolution of prosocial traits, even when individuals have no agency over
network structures.Comment: 45 pages; final versio
Safeguarding development aid against climate change: evaluating progress and identifying best practice
Official development assistance currently totals around US$130 billion per year, an order of magnitude greater than international climate finance. To safeguard development progress and secure the long-term effectiveness of these investments, projects must be designed to be resilient to climate change. This article reviews 250 projects for three countries from two development organisations and finds that between 2% and 30% of these may require action now to "future-proof" investments and policies. Both organisations show improvements in the recognition of climate change in projects, but many projects are still not future-proof
Designing a talents training model for cross-border e-commerce: a mixed approach of problem-based learning with social media
© 2019, Springer Science+Business Media, LLC, part of Springer Nature. Cross-border e-commerce has developed rapidly integrating the global economy. Research has presented some solutions for the challenges and barriers in cross-border e-commerce from the perspective of the enterprise. However, little is known about the requirements of cross-border e-commerce talents and how to train them. In this paper, we firstly conducted semi-structured interviews to acquire the requirements of cross-border e-commerce talents. Business and market knowledge, technical skills, analytical ability and business practical ability were found to be the four core requirements. Then, we integrated problem-based learning and social media to design a talents training model for cross-border e-commerce and did a program to evaluate effectiveness of the model. Finally, its effectiveness was evaluated from the four evaluation dimensions of attitude, perceived enjoyment, concentration and work intention. The talents training model was improved according to the suggestions
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Fast splitting based tag identification algorithm for anti-collision in UHF RFID System
Efficient and effective objects identification using Radio Frequency Identification (RFID) is always a challenge in large scale industrial and commercial applications. Among existing solutions, the tree based splitting scheme has attracted increasing attention because of its high extendibility and feasibility. However, conventional tree splitting algorithms can only solve tag collision with counter value equals to zero and usually result in performance degradation when the number of tags is large. To overcome such drawbacks, we propose a novel tree-based method called Fast Splitting Algorithm based on Consecutive Slot Status detection (FSA-CSS), which includes a fast splitting (FS) mechanism and a shrink mechanism. Specifically, the FS mechanism is used to reduce collisions by increasing commands when the number of consecutive collision is above a threshold. Whereas the shrink mechanism is used to reduce extra idle slots introduced by FS. Simulation results supplemented by prototyping tests show that the proposed FSA-CSS achieves a system throughput of 0.41, outperforming the existing UHF RFID solutions
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