245 research outputs found
Does China's overseas lending favor One Belt One Road countries?
The One Belt One Road initiative is found to promote China’s overseas lending in the belt road countries, especially for countries along the continental route. Such effect strengthens and persists for at least three years. Our findings show that launching a national strategy could be a decisive determinant of one country’s outbound loans
Does China's overseas lending favors One Belt One Road countries?
The One Belt One Road initiative is found to promote China’s overseas lending in the belt road countries, especially for countries along the continental route. Such effect strengthens and persists for at least three years. Our findings show that launching a national strategy could be a decisive determinant of one country’s outbound loans
A White-Box False Positive Adversarial Attack Method on Contrastive Loss-Based Offline Handwritten Signature Verification Models
In this paper, we tackle the challenge of white-box false positive
adversarial attacks on contrastive loss-based offline handwritten signature
verification models. We propose a novel attack method that treats the attack as
a style transfer between closely related but distinct writing styles. To guide
the generation of deceptive images, we introduce two new loss functions that
enhance the attack success rate by perturbing the Euclidean distance between
the embedding vectors of the original and synthesized samples, while ensuring
minimal perturbations by reducing the difference between the generated image
and the original image. Our method demonstrates state-of-the-art performance in
white-box attacks on contrastive loss-based offline handwritten signature
verification models, as evidenced by our experiments. The key contributions of
this paper include a novel false positive attack method, two new loss
functions, effective style transfer in handwriting styles, and superior
performance in white-box false positive attacks compared to other white-box
attack methods.Comment: 8 pages, 3 figure
Political Tensions and Corporate Cross-border Financing: Evidence from the China-U.S. Trade War
A growing body of literature has explored the effects of political tensions on international trade and consumers’ behavior. Still, little is known whether or to what extend it matters to corporations’ cross-border financing activities. This study fills such gap in the literature by investigating the impacts of the recent China-U.S. trade war on Chinese firms’ international syndicated loans. This quasi-nature experiment facilitates the difference-in-differences (DD) identification strategy and we use Chinese corporations seeking international borrowing as the treatment group and non-Chinese counterparties as the control group. Our analysis is taken at both the aggregate level and the deal level. Preliminary results suggest significant negative aggregate consequences, including the number of loan initiations as well as their amount. Deal level estimations exhibit the similar pattern: loan spreads and maturities were adversely affected; and sizes of syndicates became bigger and the probability of secured loan occurrence was higher for Chinese corporations. To substantiate the argument that the observed gloom was caused by the trade war, we adopt the triple difference-in-differences (DDD) estimation method by exploiting U.S. borrowers as an additional level of variation
Quantum NETwork: from theory to practice
The quantum internet is envisioned as the ultimate stage of the quantum
revolution, which surpasses its classical counterpart in various aspects, such
as the efficiency of data transmission, the security of network services, and
the capability of information processing. Given its disruptive impact on the
national security and the digital economy, a global race to build scalable
quantum networks has already begun. With the joint effort of national
governments, industrial participants and research institutes, the development
of quantum networks has advanced rapidly in recent years, bringing the first
primitive quantum networks within reach. In this work, we aim to provide an
up-to-date review of the field of quantum networks from both theoretical and
experimental perspectives, contributing to a better understanding of the
building blocks required for the establishment of a global quantum internet. We
also introduce a newly developed quantum network toolkit to facilitate the
exploration and evaluation of innovative ideas. Particularly, it provides dual
quantum computing engines, supporting simulations in both the quantum circuit
and measurement-based models. It also includes a compilation scheme for mapping
quantum network protocols onto quantum circuits, enabling their emulations on
real-world quantum hardware devices. We showcase the power of this toolkit with
several featured demonstrations, including a simulation of the Micius quantum
satellite experiment, a testing of a four-layer quantum network architecture
with resource management, and a quantum emulation of the CHSH game. We hope
this work can give a better understanding of the state-of-the-art development
of quantum networks and provide the necessary tools to make further
contributions along the way.Comment: 36 pages, 33 figures; comments are welcom
Continual Learning through Networks Splitting and Merging with Dreaming-Meta-Weighted Model Fusion
It's challenging to balance the networks stability and plasticity in
continual learning scenarios, considering stability suffers from the update of
model and plasticity benefits from it. Existing works usually focus more on the
stability and restrict the learning plasticity of later tasks to avoid
catastrophic forgetting of learned knowledge. Differently, we propose a
continual learning method named Split2MetaFusion which can achieve better
trade-off by employing a two-stage strategy: splitting and meta-weighted
fusion. In this strategy, a slow model with better stability, and a fast model
with better plasticity are learned sequentially at the splitting stage. Then
stability and plasticity are both kept by fusing the two models in an adaptive
manner. Towards this end, we design an optimizer named Task-Preferred Null
Space Projector(TPNSP) to the slow learning process for narrowing the fusion
gap. To achieve better model fusion, we further design a Dreaming-Meta-Weighted
fusion policy for better maintaining the old and new knowledge simultaneously,
which doesn't require to use the previous datasets. Experimental results and
analysis reported in this work demonstrate the superiority of the proposed
method for maintaining networks stability and keeping its plasticity. Our code
will be released
Research on student engagement in distance learning in sustainability science to design an online intelligent assessment system
Distance learning programs in sustainability science provide a structured curriculum that covers various aspects of sustainability. Despite the growing recognition of distance learning in higher education, existing literature has primarily focused on specific and detailed factors, without a comprehensive summary of the global themes, especially neglecting in-depth exploration of poor engagement factors. This study bridged this gap by not only examining detailed factors but also synthesizing the overarching themes that influenced student engagement. The aim of this study was to investigate the factors that impact student engagement in distance learning within higher education institutions across different countries. By developing a theoretical framework, three key aspects of student engagement in higher education were identified. A total of 42 students and 2 educators affiliated with universities participated in semi-structured interviews. The findings of this paper indicated that sociocultural, infrastructure, and digital equity factors were the main influencing factors of student engagement. Furthermore, a student engagement assessment system was developed using machine learning algorithms to identify students with low levels of engagement and conduct further analysis that considers the three aforementioned factors. The proposed automated approach holds the potential to enhance and revolutionize digital learning methodologies
Numerical investigation of particle dynamic behaviours in geophysical flows considering solid-fluid interaction
Solid-fluid interaction vitally influences the flow dynamics of particles in a geophysical flow. A coupled computational fluid dynamics and discrete element method (CFD-DEM) is used in this study to model multiphase geophysical flow as a mixture of fluid and solid phases. The two non-Newtonian fluids (i.e., Bingham and Hershcel-Bulkley fluids) and water mixed with particles are considered in the simulation, while dry granular flow with the same volume is simulated as a control test. Results revealed that the solid-fluid interaction heavily governs the particle dynamic behaviours. Specifically, compared to dry case, particles in three multiphase cases are characterized by larger flow mobility and greater shear rate while smaller basal normal force. In addition, a power-law distribution with a crossover to a generalized Pareto Distribution is recommended to fit the distribution of normalized interparticle contact force
Towards Control-Centric Representations in Reinforcement Learning from Images
Image-based Reinforcement Learning is a practical yet challenging task. A
major hurdle lies in extracting control-centric representations while
disregarding irrelevant information. While approaches that follow the
bisimulation principle exhibit the potential in learning state representations
to address this issue, they still grapple with the limited expressive capacity
of latent dynamics and the inadaptability to sparse reward environments. To
address these limitations, we introduce ReBis, which aims to capture
control-centric information by integrating reward-free control information
alongside reward-specific knowledge. ReBis utilizes a transformer architecture
to implicitly model the dynamics and incorporates block-wise masking to
eliminate spatiotemporal redundancy. Moreover, ReBis combines
bisimulation-based loss with asymmetric reconstruction loss to prevent feature
collapse in environments with sparse rewards. Empirical studies on two large
benchmarks, including Atari games and DeepMind Control Suit, demonstrate that
ReBis has superior performance compared to existing methods, proving its
effectiveness
A Survey of Source Code Search: A 3-Dimensional Perspective
(Source) code search is widely concerned by software engineering researchers
because it can improve the productivity and quality of software development.
Given a functionality requirement usually described in a natural language
sentence, a code search system can retrieve code snippets that satisfy the
requirement from a large-scale code corpus, e.g., GitHub. To realize effective
and efficient code search, many techniques have been proposed successively.
These techniques improve code search performance mainly by optimizing three
core components, including query understanding component, code understanding
component, and query-code matching component. In this paper, we provide a
3-dimensional perspective survey for code search. Specifically, we categorize
existing code search studies into query-end optimization techniques, code-end
optimization techniques, and match-end optimization techniques according to the
specific components they optimize. Considering that each end can be optimized
independently and contributes to the code search performance, we treat each end
as a dimension. Therefore, this survey is 3-dimensional in nature, and it
provides a comprehensive summary of each dimension in detail. To understand the
research trends of the three dimensions in existing code search studies, we
systematically review 68 relevant literatures. Different from existing code
search surveys that only focus on the query end or code end or introduce
various aspects shallowly (including codebase, evaluation metrics, modeling
technique, etc.), our survey provides a more nuanced analysis and review of the
evolution and development of the underlying techniques used in the three ends.
Based on a systematic review and summary of existing work, we outline several
open challenges and opportunities at the three ends that remain to be addressed
in future work.Comment: submitted to ACM Transactions on Software Engineering and Methodolog
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