We propose FisheyeVR, a zooming interface in VR dynamically providing users a larger software FOV by zooming out to a shorter virtual focal length, trading in an acceptable visual distortion for more context. We conduct studies to (1) understand the ...

Automated live visual descriptions can aid blind people in understanding their surroundings with autonomy and independence. However, providing descriptions that are rich, contextual, and just-in-time has been a long-standing challenge in accessibility. ...

Context awareness is key to developing intelligent voice assistants that offer situated support for users performing various daily tasks, like cooking and machine use. Human Activity Recognition (HAR) with various sensors can be a powerful approach to ...

Developing chatbots as personal companions has long been a goal of artificial intelligence researchers. Recent advances in Large Language Models (LLMs) have delivered a practical solution for endowing chatbots with anthropomorphic language capabilities. ...

While audio description (AD) is the standard approach for making videos accessible to blind and low vision (BLV) people, existing AD guidelines do not consider BLV users’ varied preferences across viewing scenarios. These scenarios range from how-to ...

The recognition of Application Programming Interface (API) mentions in the software-related texts is a prerequisite task for extracting API-related knowledge. Previous studies have demonstrated the superiority of deep learning-based methods in ...

Renaming is one of the most popular software refactorings. Although developers may know what the new name should be when they conduct a renaming, it remains valuable for refactoring tools to recommend new names automatically so that developers can simply ...

Research efforts focused on Smart Building (SB) development have concentrated on the automation of resources within intelligent environments towards an enhanced experience for occupants. The process converts everyday manual activities into ...

Web services are very popular in constructing software systems on the internet. With the increasing number of web services with similar functionalities, quality of service (QoS) becomes a crucial concern in web service selection. However, QoS values of ...

In internet of things (IoT), the context awareness in resolving the access control aids to finer resolution in deciding whether to grant access or not. In this paper, our focus is on the context aware access control for IoT devices, specifically on ...

National Key Laboratory of General Artificial Intelligence, Beijing Institute for General Artificial Intelligence (BIGAI), China

Retrieving out-of-reach objects is a crucial task in virtual reality (VR). One of the most commonly used approaches for this ...

This paper proposes a software architecture model applied for context-aware monitoring of Smart Buildings(SB), and it works in two layers: Fog and Edge computing and uses the Multi-Agent System(MAS) and Federated Learning(FL). The objective of this ...

Cloud-based SCADA (Supervisory Control and Data Acquisition) systems enable seamless access to internet of things (IoT) operational data for employees at control facilities and operators working on the field for automated control and monitoring of ...

Integrated recommendation, which aims at jointly recommending heterogeneous items from different channels in a main feed, has been widely applied to various online platforms. Though attractive, integrated recommendation requires the ranking methods to ...

Identifying semantic types for attributes in relations, known as attribute semantic type (AST) identification, plays an important role in many data analysis tasks, such as data cleaning, schema matching, and keyword search in databases. However, ...

Artificial intelligence requires advanced technologies in various fields. In particular, natural language processing consists of various tasks because computers need to understand and process human languages. Knowledge graphs represent common sense as a ...

Data analysis is a crucial process in the field of data science that extracts useful information from any form of data. With the rapid growth of technology, more and more unstructured data, such as text and images, are being produced in large amounts. ...

Automatically fixing compilation errors can greatly raise the productivity of software development, by guiding the novice or AI programmers to write and debug code. Recently, learning-based program repair has gained extensive attention and became the ...

Self-adaptable system concerns on service adaptation whenever errors persist within the system. Changes in contextual information such as networks or sensors will affect the system’s effectiveness because the service adaptation process is not ...

Context-aware recommender systems were proposed and built to adapt the recommendations to different context situations. With the development of deep learning based recommendation techniques, the neural network models have also been utilized to improve ...