Abstract Music inpainting is a sub-task of automated music generation that aims to infill incomplete musical pieces help musicians in their composition process. Many methods have been developed for this task. However, we observe tendency each method be evaluated using different datasets and metrics the papers where they are presented. This lack standardization hinders an adequate comparison the...

We consider the problem of on-line prediction of real-valued labels, assumed bounded in absolute value by a known constant, of new objects from known labeled objects. The prediction algorithm’s performance is measured by the squared deviation of the predictions from the actual labels. No stochastic assumptions are made about the way the labels and objects are generated. Instead, we are given a ...

In this paper, the problem of the fault diagnosis of an advanced wind turbine benchmark will be addressed using analytical redundant relations (ARRs) and observers that considers uncertainty in a bounded context, using the so-called interval approach. The fault detection test is based on checking the consistency between the measurements and the model by finding if the formers are inside the int...

This paper addresses the design of an observer-based fault diagnosis scheme, which is applied to some of the sensors and actuators of a wind turbine benchmark model. The methodology is based on a modified sliding mode observer (SMO) that allows accurate reconstruction of multiple sensor or actuator faults occurring simultaneously. The faults are reconstructed using the equivalent output err...

This paper presents a detailed branch characterization of an Oracle based commercial on-line transaction processing workload, Oracle Database Benchmark (ODB), running on an IA32 processor. We ran a welltuned ODB on Simics, a full system simulator, to collect the instruction traces used in this study. We compare the branch behavior of ODB with the branch behaviors of gcc, gzip and mcf from the S...

With the emergence of XML as a standard for representing business data, new decision support applications are being developed. These XML data warehouses aim at supporting On-Line Analytical Processing (OLAP) operations that manipulate irregular XML data. To ensure feasibility of these new tools, important performance issues must be addressed. Performance is customarily assessed with the help of...

This paper presents a new approach to parallel motion planning for industrial robot arms with six degrees of freedom in an on-line given 3D environment. The method is based on the A*-search algorithm and needs no essential off-line computations. The algorithm works in an implicitly descrete configuration space. Collisions are detected in the cartesian workspace by hierarchical distance computat...

Cloud computing helps reduce costs, increase business agility and deploy solutions with a high return on investment for many types of applications, including data warehouses and on-line analytical processing. However, storing and transferring sensitive data into the cloud raises legitimate security concerns. In this paper, the authors’ propose a new multi-secret sharing approach for deploying d...

Many real world data processing tasks demand intelligent computational models with good e/ciency and adaptability in their on-line operations. Consequently, neural algorithms with constructive network structure and incremental learning ability are of increasing interest. In this paper we present an algorithm of evolving self-organizing map (ESOM), which features an evolving network structure an...