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The purpose of this paper is to construct a newly efficient finite element method which named as modified finite element method, for Maxwell’s equation in Kerr-type nonlinear media. Because the efficient unconditional stable alternative direction ...

Using multi-modal data to learn region representations has gained popularity for its ability to reveal diverse socioeconomic features in cities. However, many studies focus solely on semantic features from points-of-interest (POIs), neglecting the issue ...

A crucial area of research in Human-AI Interaction focuses on understanding how the integration of AI into social systems influences human behavior, for example, how news-feeding algorithms affect people’s voting decisions. But little attention has ...

In multi‐access edge computing (MEC), computational task offloading of mobile terminals (MT) is expected to provide the green applications with the restriction of energy consumption and service latency. Nevertheless, the diverse statuses of a ...

Each mobile terminal operates under energy constraints, engaging in computational tasks during system time slots. Facilitating adherence to latency and energy consumption limits, mobile terminals can fragment tasks into subtasks and delegate them for ...

With the development of the Intelligent Transportation Systems, a great deal of work has been proposed to tackle traffic prediction tasks. Despite their good performance, most traffic prediction models are point estimation models, lacking the capability ...

Large language models (LLMs) such as ChatGPT have shown remarkable capabilities in code generation. Despite significant achievements, they rely on enormous training data to acquire a broad spectrum of open-domain knowledge. Besides, their evaluation ...

Knowledge tracing (KT) aims to monitor students’ evolving knowledge states through their learning interactions with concept-related questions, and can be indirectly evaluated by predicting how students will perform on future questions. In this ...

Persistent memory (pmem) products bring the persistence domain up to the memory level. Intel recently introduced the eADR feature that guarantees to flush data buffered in CPU cache to pmem on a power outage, thereby making the CPU cache a transient ...

Log-structured merge tree (LSM-tree) is a promising structure. LSM-tree-based relational databases gain wide popularity in production environments to serve web and big data applications. We take MyRocks for study and explore how to optimize it in ...$$$$

With the expansion and growth of cities, profiling urban areas with the advent of multi-modal urban datasets (e.g., points-of-interest and street view imagery) has become increasingly important in urban planing and management. Particularly, street view ...

Next location prediction is a crucial task in human mobility modeling, and is pivotal for many downstream applications like location-based recommendation and transportation planning. Although there has been a large body of research tackling this problem, ...

Recent years have witnessed deep learning techniques endowing modern audio systems with powerful capabilities. However, the latest studies have revealed its strong reliance on training data, raising serious threats from backdoor attacks. Different from ...

Semantic annotation for points of interest (POIs) is the process of annotating a POI with a category label, which facilitates many services related to POIs, such as POI search and recommendation. Most of the existing solutions extract features related to ...

Points of interest (POIs) carry a wealth of semantic information of varying locations in cities and thus have been widely used to enable various location-based services. To understand POI semantics, existing methods usually model contextual correlations ...

Weather forecasting is of great importance for human life and various real-world fields, e.g., traffic prediction, agricultural production, and tourist industry. Existing methods can be roughly divided into two categories: theory-driven (e.g., numerical ...

The cinematic metaverse aims to create a virtual space with the context of a film. Users can enter this space in the form of avatars, experiencing the cinematic plot firsthand in an immersive manner. This requires us to design a rational ...

This paper utilizes multiple graph topological information to generate different graph representations that can reflect the real relationships between avatars in the cinematic metauniverse more comprehensively. image image

Approximate Nearest Neighbor Search (ANNS) is a fundamental and critical component in many applications, including recommendation systems and large language model-based applications. With the advancement of multimodal neural models, which transform data ...

Data deduplication is a widely employed technique in backup systems to enhance storage efficiency by eliminating duplicate chunks. Delta compression is a technique that complements deduplication by removing redundant data between similar chunks. ...

• Adding delta compression to backup systems leads to low throughput due to extra I/Os.
• With minimal fragmentation, delta compression needs just a few extra I/Os.
• Sequential chunk referencing achieves significant compression by ...

Cognitive diagnosis is an intelligent education task that aims to learn students’ cognitive states on knowledge concepts based on historical answering logs over questions. Existing studies focus on modeling the interactions between students and ...

Recent years have witnessed enormous research efforts on WiFi sensing to enable intelligent services of Internet of Things. However, due to the omni-directional broadcasting manner of WiFi signals, the activity semantic underlying the signals can be ...