Our approach to the model-driven collaborative design of workflows for bioinformatic applications uses the jABC for model driven mediation and choreography to complement a Web service-based elementary service provisio...
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Our approach to the model-driven collaborative design of workflows for bioinformatic applications uses the jABC for model driven mediation and choreography to complement a Web service-based elementary service provision. jABC is a framework for service development based on lightweight process coordination. Users (product developers and system/software designers) develop services and applications by composing reusable building-blocks into (flow-)graph structures that can be animated, analyzed, simulated, verified, executed, and compiled. This way of handling the collaborative design of complex processes has proven to be effective and adequate for the cooperation of non-programmers (in this case biologists) and technical people, and it is now being rolled out in the operative practice
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.
This paper presents a methodology to design automatically a QFT (Quantitative Feedback Theory) robust controller for plants with model uncertainty. The method proposed has as objective to find a QFT robust controller ...
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This paper presents a methodology to design automatically a QFT (Quantitative Feedback Theory) robust controller for plants with model uncertainty. The method proposed has as objective to find a QFT robust controller that fulfills the control specifications for the whole set of plant models, without including parameter controller restrictions. The methodology is based on a global optimization and has been solved using a global mixed-integer nonlinear programming. The design of an active control for vibration attenuation in optical interferometers is used to validate the technique.
The semantics of the core features of XML Schema in terms of XQuery 1.0 and XPath 2.0 data model algebraically defined is given. The database state is represented as a many sorted algebra whose sorts are sets of data ...
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The semantics of the core features of XML Schema in terms of XQuery 1.0 and XPath 2.0 data model algebraically defined is given. The database state is represented as a many sorted algebra whose sorts are sets of data type values and different kinds of nodes and whose operations are data type operations and node accessors. The values of some node accessors, such as "parent", "children" and "attributes", define a document tree with a definite order of nodes. The values of other node accessors help to make difference between kinds of nodes, learn the names, types and values associated with the corresponding document entities, etc., i.e., provide primitive facilities for a query language. As a result, a document can be easily mapped to its implementation in terms of nodes and accessors defined on them.
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 paper focuses on the problem of technical social engineering attacks that encompass the manipulation of individuals to reveal sensitive information, execute actions, or breach security systems. These exploits freq...
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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.
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.
The Constraint Language for Lambda Structures (CLLS)is an expressive language of tree descriptions which combinesdominance constraints with powerful parallelism and bindingconstraints. CLLS was introduced as a uniform...
The Constraint Language for Lambda Structures (CLLS)is an expressive language of tree descriptions which combinesdominance constraints with powerful parallelism and bindingconstraints. CLLS was introduced as a uniform framework for definingunderspecified semantics representations of natural languagesentences, covering scope, ellipsis, and anaphora. This articlepresents saturation-based algorithms for processing the completelanguage of CLLS. It also gives an overview of previous results on questions of processing and complexity.
Because of the increased market opening and massive data collection brought about by globalization, the need of maintaining control over customs procedures has increased. However, the integration and processing of cus...
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