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In recent years, the integration of location-based services into social media platforms has seen a significant surge, coinciding with the growing challenges posed by the proliferation of fake news online. However, the influence of location data ...

• Our study challenges traditional in-group favouritism seen in Social Identity Theory.
• Urban biases emerged in our study, highlighting the importance of online equality.
• Participants expressed concerns about geolocation spoofing on ...

We propose a time-splitting sine-pseudospectral (TSSP) method for the biharmonic nonlinear Schrödinger equation (BNLS) and establish its optimal error bounds. In the proposed TSSP method, we adopt the sine-pseudospectral method for spatial ...

In this work, we present a video editing chatbot (VEC) that performs intelligent multimedia editing through natural language dialogue. VEC comprises three modules: instruction analysis, multimedia resources retrieval, and multimedia resources editing. It ...

This paper discusses the functional principle of the theory in detail based on the theory of diversified intelligence and constructs a teaching platform of diversified intelligence. Then, this platform is applied to teaching in different cities, and the ...

This demo presents a novel end-to-end framework that combines on-device large language models (LLMs) with smartphone sensing technologies to achieve context-aware and personalized services. The framework addresses critical limitations of current ...

As the number of applications installed on smartphones continues to grow, the task of effectively managing location privacy has become increasingly complex. In this paper, we explore the factors that influence users' privacy-preserving intentions and ...

Deep Cross-Modal Hashing (DCMH) has garnered significant attention in the field of cross-modal retrieval due to its advantages such as high computational efficiency and small storage space. However, existing DCMH methods still face certain ...

Traditional methods often require a large number of parallel corpora, that is, texts from one language and corresponding texts from another language. The acquisition and construction of this data is very expensive and time-consuming, which limits the ...

In most recent research, the traffic forecasting task is typically formulated as a spatio-temporal graph modeling problem. For spatial correlation, they typically learn the shared pattern (i.e., the most salient pattern) of traffic series and ...

• Node-specific GCN immensely enhances the capacity of the GCN.
• A spatio-temporal fusion module is proposed.
• A transformer-based global temporal correlation learning module is proposed.
• The results prove that our method is ...

High-performance computing (HPC) has become a strategic resource that drives innovation and economic growth. In addition, it is important to educate a workforce with advanced computational skills to maintain economic competitiveness. In this ...

• IAS-FET, an intelligent assistant system, was constructed in this work not only for the prediction of successful rate of in-vitro fertilization embryo transfer technology (IVF-ET) outcomes based on patients’ clinical features, but also ...

Among all of the assisted reproductive technology (ART) methods, in vitro fertilization-embryo transfer (IVF-ET) holds a prominent position as a key solution for overcoming infertility. However, its success rate hovers at a modest 30% ...

Driven by generative AI and the Internet, there is an increasing availability of a wide variety of images, leading to the significant and popular task of cross-domain image retrieval. To reduce annotation costs and increase performance, this paper ...

The wide application of big data not only provides convenience for the teaching between teachers and students, but also plays a great role in the education and training of college students. However, how to cultivate students' ability to learn English ...

In-betweening is a technique for generating transitions given start and target character states. The majority of existing works require multiple (often <inline-formula><tex-math notation="LaTeX">$\geq$</tex-math><alternatives><mml:math><mml:mo>&#x2265;</...

Oceanic eddies and fronts are plentiful in the global oceans. There are abundant frontal processes at the edges of eddies, meanwhile, eddies can be formed due to instability along the fronts. Moreover, they can both induce submesoscale processes ...

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• A data fusion dataset dubbed eddy-front category is constructed.
• An eddy-front generative adversarial network (EFGAN) is proposed.
• With EFGAN, five types of eddy-front coupling are estimated.
• The spatiotemporal variability of ...

In April 2022, Sina Weibo began to display users’ coarse location for the stated purpose of regulating their online community. However, this raised concerns about location privacy. Through sentiment analysis and Latent Dirichlet Allocation (LDA), ...

Named Entity Recognition (NER) is an important task in knowledge extraction, which targets extracting structural information from unstructured text. To fully employ the prior-knowledge of the pre-trained language models, some research works formulate the ...

High performance computing (HPC), typically used only in research until recently, is being integrated more into undergraduate curricula across disciplines. HPC resources are expensive but lend themselves easily to sharing among institutions. However, in ...

Unmanned Aerial Vehicle (UAV)-aided target tracking has been applied to many practical scenarios such as search and rescue missions. Edge computing has emerged as a promising solution to improve the performance of UAV-aided target tracking and to ...

We present two finite difference time domain methods for the biharmonic nonlinear Schrödinger equation (BNLS) by reformulating it into a system of second-order partial differential equations instead of a direct discretization, including a second-...${}^{\mathrm{}}{}^{\mathrm{}}$${}^{\mathrm{}}$${}^{\mathrm{}}$$$