Predicting student success is an important task in educational institutions, as it allows for targeted interventions and support systems to enhance educational outcomes. This paper explores the use of SHAP (SHapley Ad...
Predicting student success is an important task in educational institutions, as it allows for targeted interventions and support systems to enhance educational outcomes. This paper explores the use of SHAP (SHapley Additive exPlanations) model-agnostic method in understanding and interpreting student success prediction. The predictive model was built using Multi-Layer Perceptron neural network algorithm on a large public dataset. By shedding light on the underlying factors driving student success, this research contributes to the advancement of data-driven decision-making in education.
A particular problem in using artificial intelligence techniques in the sensor grid is the high power consumption. Remote sensors are usually limited by the amount of power available, thus our general goal is to minim...
A particular problem in using artificial intelligence techniques in the sensor grid is the high power consumption. Remote sensors are usually limited by the amount of power available, thus our general goal is to minimize it while preserving accurate experimentation results. Using emerging technologies like spiking neural networks and neuromorphic hardware, we can create sensor grids that perform data processing with preserving low power consumption. In this paper, we demonstrate a remote node with integrated visual sensor that works on less than 10mW of energy, while performing continuous scene monitoring, object detection and classification. The system has intelligent power management and the ability to send data wirelessly.
The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential a...
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ISBN:
(数字)9798350376449
ISBN:
(纸本)9798350376456
The integration and detection of AI (Artificial Intelligence) in a variety of fields, primarily education, are examined in this paper. With an emphasis on virtual assistants and their uses, it explores the potential and constraints of such technology. A study was conducted with students at the Technical University of Sofia, to assess their ability to distinguish between texts written by humans and AI. The results showcase that learners need to develop their critical analysis skills evidenced by their mixed expertise.
We deigned a spiking neural network that computes network weights in the temporal dimension. Such a network can be used for artificial intelligence and deep learning. We demonstrate circuits implementing blocks for bu...
We deigned a spiking neural network that computes network weights in the temporal dimension. Such a network can be used for artificial intelligence and deep learning. We demonstrate circuits implementing blocks for building such a network and then a training model. This enables creation of efficient Hessenstein-Reichardt detectors observed in motion detection networks in the nature. The proposed network allows reconfiguration across network layers algorithmically.
With the increasing number of IoT devices, there is a growing need for bandwidth to support their communication. Unfortunately, there is a shortage of available bandwidth due to preallocated bands for various services...
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作者：
Gupta, GopalPontelli, EnricoApplied Logic
Programming Languages and Systems Lab. Department of Computer Science University of Texas at Dallas Richardson TX 95083 United States Laboratory for Logic
Databases and Advanced Programming Department of Computer Science New Mexico State University Las Cruces NM 88003 United States
Domain Specific Languages (DSLs) are high level languages designed for solving problems in a particular domain, and have been suggested as means for developing reliable software systems. We present a (constraint) logi...
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In the paper, based on a comparative analysis of the methods of processing time-interval codes used as secondary surveillance radar information signals consisting of a different sequence of performing joint decoding o...
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In this paper is proposed optimization, scaling, performance evaluation and profiling of parallel multiple sequence alignment based on ClustalW algorithm on the supercomputer BlueGene/Q, so-called JUQUEEN, for the cas...
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In this paper is proposed optimization, scaling, performance evaluation and profiling of parallel multiple sequence alignment based on ClustalW algorithm on the supercomputer BlueGene/Q, so-called JUQUEEN, for the case study of the influenza virus sequences. For this purpose a parallel I/O interface for simultaneous and independent access to single file collectively has been designed and verified on the basis of parallel program implementation on the supercomputer JUQUEEN.
ThisvolumeconstitutestheproceedingsoftheSixthInternationalConferenceon Flexible Query Answering systems, FQAS 2004, held in Lyon, France, on June 24–26, 2004. FQAS is the premier conference for researchers and practi...
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ISBN:
(数字)9783540259572
ISBN:
(纸本)9783540221609
ThisvolumeconstitutestheproceedingsoftheSixthInternationalConferenceon Flexible Query Answering systems, FQAS 2004, held in Lyon, France, on June 24–26, 2004. FQAS is the premier conference for researchers and practitioners concerned with the vital task of providing easy, ?exible, and intuitive access to information for every type of need. This multidisciplinary conference draws on several research areas, including databases, information retrieval, knowledge representation, soft computing, multimedia, and human-computer interaction. With FQAS 2004, the FQAS conference series celebrated its tenth anniversary as it has been held every two years since 1994. The overall theme of the FQAS conferences is innovative query systems aimed at providing easy, ?exible, and intuitive access to information. Such systems are intended to facilitate retrieval from information repositories such as databases, libraries, and the Web. These repositories are typically equipped with standard query systems that are often inadequate for users. The focus of FQAS is the development of query systems that are more expressive, informative, cooperative, productive, and intuitive to use.
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