Search Results

The thriving mobile app ecosystem encompasses a wide range of functionalities. However, within this ecosystem, a subset of apps provides illicit services such as gambling and pornography to pursue economic gains, collectively referred to as "underground ...

Synonym discovery is important in a wide variety of concept-related tasks, such as entity/concept mining and industrial knowledge graph (KG) construction. It intends to determine whether two terms refer to the same concept in semantics. Existing ...

In recent years, with the development of deep learning, text detection research has achieved good research results. However, there is still relatively little research on the detection of Uyghur text in natural scenes. Therefore, this paper ...

In this paper, we consider numerical approximations for the optimal partition problem using Lagrange multipliers. By rewriting it into constrained gradient flows, three and four steps numerical schemes based on the Lagrange multiplier approach are ...

As researchers today, we are witnessing a fundamental change in our technologically-enabled world due to the advent and diffusion of highly disruptive technologies such as generative Artificial Intelligence (AI), Augmented Reality (AR) and Virtual Reality ...

Gig platforms increasingly harness AI algorithms to manage workers, offering notable efficiency and scalability benefits. However, the rise of worker resistance, such as manipulating algorithms with fake data, poses challenges to these benefits. ...

• How gig workers perceive and react to the transparency in AI management is explored.
• An inverted U-shaped relationship between transparency and fairness perceptions in AI management is identified.
• Algorithmic transparency initially ...

Images and videos often suffer from issues such as motion blur, video discontinuity, or rolling shutter artifacts. Prior studies typically focus on designing specific algorithms to address individual issues. In this paper, we highlight that these ...

Existing vehicle re-identification methods rely on visual features to extract vehicle identity information. However, while individual visual features enable the model to learn limited semantic information, multimodal representations are difficult ...

In this work, we investigate short-packet communications in power beacon (PB)-assisted Internet-of-Things (IoT) networks, where an energy-constrained actuator first harvests energy from a dedicated PB, and then transmits confidential signals to a ...

Recently, the Shapley additive explanations models have been extensively studied to enhance explainability of artificial intelligence algorithms, while most of them simply use Shapley additive explanations to rank or measure the importance of ...

• The relation between fault characteristic frequencies and local interpretability Shapley values studied.
• It is newly found that Shapley values can be used to locate fault characteristic frequencies.
• A health indicator construction ...

Knowledge graphs (KG) can aggregate data and make information resources easier to calculate and understand. With tremendous advancements in knowledge graphs, they have been incorporated into plenty of software systems to assist various tasks. ...

Sign language is one of the most effective communication tools for people with hearing difficulties. Most existing works focus on improving the performance of sign language tasks on RGB videos, which may suffer from degraded recording conditions, ...

Large foundation models have recently emerged as a prominent focus of interest, attaining superior performance in widespread scenarios. Due to the scarcity of 3D data, many efforts have been made to adapt pre-trained transformers from vision to 3D ...

Artificial intelligence and intelligent algorithms have shown great potential in solving complex optimisation problems, especially in the path optimisation problem in the field of transportation. Aiming at the route planning problem in civil aviation ...

This paper investigates the free strategy choice of vertically differentiated duopoly software vendors considering the heterogeneous preferences of consumers for software product quality and price. We find that when consumers are inclined to be rational ...

Mutation testing is vital for ensuring software quality. However, the presence of equivalent mutants is known to introduce redundant cost and bias issues, hindering the effectiveness of mutation testing in practical use. Although numerous equivalent ...

Archetypal analysis is an unsupervised machine learning method that summarizes data using a convex polytope. In its original formulation, for fixed k, the method finds a convex polytope with k vertices, called archetype points, such that the ...

Hybrid Transactional and Analytical Processing (HTAP) brings great challenges to data storage systems. However, traditional approaches have struggled to dynamically adapt storage structures to data and complex workloads. Fortunately, machine ...

While intelligent virtual assistants like Siri, Alexa, and Google Assistant have become ubiquitous in modern life, they still face limitations in their ability to follow multi-step instructions and accomplish complex goals articulated in natural ...

The existing rain streaks removal methods provide better deraining results, but it cannot be implemented on the low-light images due to the poor visual quality. To solve this problem, this paper presents a novel rain streaks removal approach using ...${}^{\mathit{}}$