Related papers: FullBrain: a Social E-learning Platform
Recently, e-learning platforms have grown as a place where students can post doubts (as a snap taken with smart phones) and get them resolved in minutes. However, the significant increase in the number of student-posted doubts with high…
Intelligent power grid research, i.e. smart grid, involves many simultaneous users spread over a relatively large geographical area. A tool for advancing research and community education is presented utilizing large-scale visualization…
On LongMemEval-500, ZenBrain matches a long-context oracle's binary-judge accuracy to within 4.5 pp ($47.7\%$ vs. $52.2\%$; $91.3\%$) at $1/106^\text{th}$ of the per-query token cost (App. F.5-F.6, Fig. 2), and wins all 12 head-to-head…
Neuroscience research has expanded dramatically over the past 30 years by advancing standardization and tool development to support rigor and transparency. Consequently, the complexity of the data pipeline has also increased, hindering…
The integration of brain-computer interfaces (BCIs), in particular electroencephalography (EEG), with artificial intelligence (AI) has shown tremendous promise in decoding human cognition and behavior from neural signals. In particular, the…
Neural Signal Operated Intelligent Robots (NOIR) system is a versatile brain-robot interface that allows humans to control robots for daily tasks using their brain signals. This interface utilizes electroencephalography (EEG) to translate…
Recently, many content sites have started encouraging their users to engage in social activities such as adding buddies on Yahoo! Travel and sharing articles with their friends on New York Times. This has led to the emergence of {\em social…
This paper describes the dynamic seminar management system named 'e-Sem', developed according to the opensource software philosophy. Due to its dynamic management functionality, it can equally adapt to any education environment (Primary,…
Boosting sales of e-commerce services is guaranteed once users find more matching items to their interests in a short time. Consequently, recommendation systems have become a crucial part of any successful e-commerce services. Although…
The session-based recommendation (SBR) garners increasing attention due to its ability to predict anonymous user intents within limited interactions. Emerging efforts incorporate various kinds of side information into their methods for…
Todays, Intelligent and web-based E-Learning is one of the important area in E-Learning. This paper integrates an intelligent and web-based E-Learning with expert system technology to be able to model the learning styles of the learners…
AI-supported writing tools show strong potential for scaffolding students' learning of argumentative writing. Prior work has demonstrated the benefits of AI-supported cognitive scaffolds, such as idea exploration and argument refinement,…
Research on social-media platforms has tended to rely on textual analysis to perform research tasks. While text-based approaches have significantly increased our understanding of online behavior and social dynamics, they overlook features…
Modern machine learning systems need to be able to cope with constantly arriving and changing data. Two main areas of research dealing with such scenarios are continual learning and data stream mining. Continual learning focuses on…
BEIR is a benchmark dataset for zero-shot evaluation of information retrieval models across 18 different domain/task combinations. In recent years, we have witnessed the growing popularity of a representation learning approach to building…
The objectives of this ongoing research are to build Real-Time AI-Powered Educational Dashboard (RAED) as a decision support tool for instructors, and to measure its impact on them while making decisions. Current developments in AI can be…
The learning-to-rank problem aims at ranking items to maximize exposure of those most relevant to a user query. A desirable property of such ranking systems is to guarantee some notion of fairness among specified item groups. While fairness…
Sensemaking in unfamiliar domains can be challenging, demanding considerable user effort to compare different options with respect to various criteria. Prior research and our formative study found that people would benefit from reading an…
Recent advances in wearable devices and Internet-of-Things (IoT) have led to massive growth in sensor data generated in edge devices. Labeling such massive data for classification tasks has proven to be challenging. In addition, data…
Edge computing scenarios necessitate the development of hardware-efficient online continual learning algorithms to be adaptive to dynamic environment. However, existing algorithms always suffer from high memory overhead and bias towards…