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Clouds gather a vast volume of telemetry from their networked systems which contain valuable information that can help solve many of the problems that continue to plague them. However, it is hard to extract useful information from such raw…
Cyber-security solutions are traditionally static and signature-based. The traditional solutions along with the use of analytic models, machine learning and big data could be improved by automatically trigger mitigation or provide relevant…
Artificial intelligence has been integrated into nearly every aspect of daily life, powering applications from object detection with computer vision to large language models for writing emails and compact models for use in smart homes.…
Machine learning (ML) algorithms are showing a growing trend in helping the scientific communities across different disciplines and institutions to address large and diverse data problems. However, many available ML tools are…
Citizen science is transforming how cognitive scientists study the human mind, and video games are at the heart of this shift. By embedding experimental tasks into engaging, game-like experiences, researchers can reach large, diverse…
Increasingly, artificial intelligence (AI) and machine learning (ML) are used in eScience applications [9]. While these approaches have great potential, the literature has shown that ML-based approaches frequently suffer from results that…
Mobile sensing is an emerging technology that utilizes agent-participatory data for decision making or state estimation, including multimedia applications. This article investigates the structure of mobile sensing schemes and introduces…
Emergence of latest technologies has diverted the focus of people form Computer-Supported Collaborative Learning (CSCL) to mobile supported collaborative learning. MCL is highly demanded in educational organizations to substantiate the…
With few exceptions, the field of Machine Learning (ML) research has largely ignored the browser as a computational engine. Beyond an educational resource for ML, the browser has vast potential to not only improve the state-of-the-art in ML…
Mobile Crowdsensing has become main stream paradigm for researchers to collect behavioral data from citizens in large scales. This valuable data can be leveraged to create centralized repositories that can be used to train advanced…
The integration of artificial intelligence (AI) into mobile applications has significantly transformed various domains, enhancing user experiences and providing personalized services through advanced machine learning (ML) and deep learning…
Large-scale research endeavors can be hindered by logistical constraints limiting the amount of available data. For example, global ecological questions require a global dataset, and traditional sampling protocols are often too inefficient…
This paper aims to bring together the disciplines of social science (SS) and computer science (CS) in the design and implementation of a novel multidisciplinary framework for systematic, transparent, ethically-informed, and bias-aware…
Conversion of raw data into insights and knowledge requires substantial amounts of effort from data scientists. Despite breathtaking advances in Machine Learning (ML) and Artificial Intelligence (AI), data scientists still spend the…
With the advent of seamless connection of human, machine, and smart things, there is an emerging trend to leverage the power of crowds (e.g., citizens, mobile devices, and smart things) to monitor what is happening in a city, understand how…
In recent years many works have shown that unsupervised Machine Learning (ML) can help detect unusual objects and uncover trends in large astronomical datasets, but a few challenges remain. We show here, for example, that different methods,…
The rise of machine learning (ML) and its integration into software systems has drastically changed development practices. While software engineering traditionally focused on manually created code artifacts with dedicated processes and…
Recent years have witnessed the increasing popularity of mobile devices (such as iphone) due to the convenience that it brings to human lives. On one hand, rich user profiling and behavior data (including per-app level, app-interaction…
Citizen science often requires volunteers to perform low-skill tasks such as counting and documenting en- vironmental features. In this work, we contend that these tasks do not adequately meet the needs of citizen scientists motivated by…
The blockchain technology has potential applications in various areas such as smart-contracts, Internet of Things (IoT), land registry, supply chain management, storing medical data, and identity management. Although the Github currently…