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A common approach to the problem of predicting students' exam scores has been to base this prediction on the previous educational history of students. In this paper, we present a model that bases this prediction on students' performance on several tasks assigned throughout the duration of the course. In order to build our prediction model, we use data from a semi-automated peer-assessment system implemented...
The enormous amounts of data that are continuously recorded in electronic health record systems offer ample opportunities for data science applications to improve healthcare. There are, however, challenges involved in using such data for machine learning, such as high dimensionality and sparsity, as well as an inherent heterogeneity that does not allow the distinct types of clinical data to be treated...
We review strategies for applying statistical inference to system design and management. In design, inferred models act as surrogates for expensive simulators and enable qualitatively new studies. In management, inferred models predict outcomes from allocation and scheduling decisions, and identify conditions that make performance stragglers more likely.
Modeling Extract-Transform-Load (ETL) processes of a Data Warehousing System has always been a challenge. The heterogeneity of the sources, the quality of the data obtained and the conciliation process are some of the issues that must be addressed in the design phase of this critical component. Commercial ETL tools often provide proprietary diagrammatic components and modeling languages that are not...
The vigorous growth of big data has triggered both opportunities and challenges in business and industry. However, Web big data distributed in diverse sources with multiple data structures frequently conflict with each other, i.e. inconsistency in cross-source Web big data. In this paper, we propose a state-of-the-art architecture of auto-discovering inconsistency with Web big data. Our contributions...
Mathematical and uncertainty modelling is an important component of data fusion (the fusion of unprocessed sensor data) and information fusion (the fusion of processed or interpreted data). If uncertainties in the modelling process are not or are incorrectly accounted for, fusion processes may provide under- or overconfident results, or in some cases incorrect results. These are often owing to incorrect...
Research shows that people consistently reach more efficient solutions than those predicted by standard economic models, which assume people are selfish. Artificial intelligence, in turn, seeks to create machines that can achieve these levels of efficiency in human-machine interaction. However, as reinforced in this paper, people's decisions are systematically less efficient — i.e., less fair and...
Artificial agents are becoming artificial companions, interacting with the user on a long-term basis. This evolution brought new challenges to the affective computing domain, such as designing artificial agents with personalities to the benefits of the user. Endowing artificial agents with personality could help to increase the agent's believability, hence easing the interaction. This paper touches...
Wireless sensor networks (WSNs) are collection of sensor nodes that unite together to monitor an environment or a system. Due to abundant workload on node near the sink makes faster energy depletion than other nodes. Due to this, lifetime of WSNs to some amount, is resolved by the power consumption between sensor node & sink. Hence, CSMA/SF is used to reduce power consumption for sensing nodes...
Cloud computing is recently has emerged as a pattern for hosting and service delivery on internet and has rapidly become a hot topic in academic and commercial environments and has attracted many people. Nowadays, we are encountering various cloud service providers. One of important aspects in cloud computing is service level agreement which is a contract involving service agreement between client...
As Internet continues to influence our day to day activities like eCommerce, eGoverence, eEducation etc. the threat from hackers has also increased. Due to which many researcher thinking intrusion detection systems as fundamental line of defense. However, many commercially available intrusion detection systems are predominantly signature-based that are designed to detect known attacks. These systems...
GeoSocial Networks (GSNs) are becoming increasingly popular due to its power in providing high-performance and flexible service capabilities. More and more internet users have accepted this innovative service model. However, although GSNs have great business value for data analysis by integrated with location information, it may seriously compromise users' privacy in publishing the GSN data. In this...
A knowledge based system (KBS) has its advantage over conventional database systems in that it has the inference ability to deduce implicit knowledge from the explicitly stored information. KBS is however known to be labor intensive in its construction in the knowledge acquisition and elicitation phase. Researchers have tried to overcome this hindrance for more than four decades. Automatic creation...
The 3D face morphable model is applied in the hearing and speech rehabilitation for hearing-impaired children, put forward to 3D face morphable model is the core of special human-computer interaction model. Including 3D face, sound, vibration, air, video, gestures, etc., through the computer generate realistic 3D face expressions and motions, with corresponding voice vibration flow feedback information...
Computers are getting faster and faster; the operating systems are getting more sophisticated. Often, these improvements necessitate that we migrate existing software to the new platform. In an ideal world, the migrated software should run perfectly well on a new platform; however, in reality, when we try that, thousands of errors appear, errors that need correcting. As a result, software migration...
The SSD is adopted to improve the IO performanceof the storage system in the data center, the throughput allocation for clients is a challenging problem. We need to find a throughput allocation method, which can determine the throughput allocations of clients on each server, while both providing the fair allocations for clients and maximizing the utilization of system throughput resource in the entire...
The age of big data opens new opportunities in various fields. While the availability of a big dataset can be helpful in some scenarios, it introduces new challenges in digital forensics investigations. The existing tools and infrastructures cannot meet the expected response time when we investigate on a big dataset. Forensics investigators will face challenges while identifying necessary pieces of...
This paper proposes a novel distributed parallel EM modeling technique to speed up the process of neural network modeling for EM structures. Existing techniques for EM modeling usually need to repeatedly change the parameters of microwave devices and drive the EM simulator to obtain sufficient training and testing samples. As the complexity in EM modeling problem increases, traditional techniques...
Industrial control systems are an important part of critical infrastructures and their uninterrupted operation is important for many aspects of society. In recent years these systems have come under more scrutiny, as reports about attacks on them have become more frequent. There is therefore a need to better secure them, and the first step to achieve this is to identify the threat landscape for such...
Securing provenance has recently become an important research topic, resulting in a number of models for protecting access to provenance. Existing work has focused on graph transformation mechanisms that supply a user with a provenance view that satisfies both access control policies and validity constraints of provenance. However, it is not always possible to satisfy both of them simultaneously,...
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