Search results for "computer.software_genre"

Visualization in comparative music research

2007

Computational analysis of large musical corpora provides an approach that overcomes some of the limitations of manual analysis related to small sample sizes and subjectivity. The present paper aims to provide an overview of the computational approach to music research. It discusses the issues of music representation, musical feature extraction, digital music collections, and data mining techniques. Moreover, it provides examples of visualization of large musical collections.

Machine learning for a combined electroencephalographic anesthesia index to detect awareness under anesthesia

2020

Spontaneous electroencephalogram (EEG) and auditory evoked potentials (AEP) have been suggested to monitor the level of consciousness during anesthesia. As both signals reflect different neuronal pathways, a combination of parameters from both signals may provide broader information about the brain status during anesthesia. Appropriate parameter selection and combination to a single index is crucial to take advantage of this potential. The field of machine learning offers algorithms for both parameter selection and combination. In this study, several established machine learning approaches including a method for the selection of suitable signal parameters and classification algorithms are a…

Machine Learning Methods for One-Session Ahead Prediction of Accesses to Page Categories

2004

This paper presents a comparison among several well-known machine learning techniques when they are used to carry out a one-session ahead prediction of page categories. We use records belonging to 18 different categories accessed by users on the citizen web portal Infoville XXI. Our first approach is focused on predicting the frequency of accesses (normalized to the unity) corresponding to the user’s next session. We have utilized Associative Memories (AMs), Classification and Regression Trees (CARTs), Multilayer Perceptrons (MLPs), and Support Vector Machines (SVMs). The Success Ratio (SR) averaged over all services is higher than 80% using any of these techniques. Nevertheless, given the …

Robust spatio-temporal descriptors for real-time SVM-based fall detection

2014

Real-time flaw detection on complex part: Study of SVM and hyperrectangle based method

2002

We present in this paper the study of two classifications methods used in order to control in real-time some industrials parts. We present the practical frame in which is made the operations, natures of the anomaly to be detected as well as the features extractions method. We tested two techniques of classification, with different algorithm complexities and performances. We compare the results obtained on various features spaces. We end by a combinatorial perspective of results of classification.

Optimal gossip algorithm for distributed consensus SVM training in wireless sensor networks

2009

In this paper, we consider the distributed training of a SVM using measurements collected by the nodes of aWireless Sensor Network in order to achieve global consensus with the minimum possible inter-node communications for data exchange. We derive a novel mathematical characterization for the optimal selection of partial information that neighboring sensors should exchange in order to achieve consensus in the network. We provide a selection function which ranks the training vectors in order of importance in the learning process. The amount of information exchange can vary, based on an appropriately chosen threshold value of this selection function, providing a desired trade-off between cla…

Training label cleaning with ant colony optimization for classification of remote sensing imagery

2015

This paper presents an original approach for improving performances of the supervised classifiers in remote sensing imagery by proposing a technique to refine a given training set using Ant Colony Optimization (ACO). The new method called ACO-Training Label Cleaning (ACO-TLC) applies ACO model for selection of the significant training samples from a given set of labeled vectors in order to optimize the quality of a supervised classifier. This means to retain the most informative samples and to remove the uncertain or misclassified training samples, which lead to classification errors. As a result of the selection process, we can obtain a purified training set. The proposed model is implemen…

Multiscale analyses and characterizations of surface topographies

2018

International audience; This work studies multiscale analyses and characterizations of surface topographies from the engineering and scientific literature with an emphasis on production engineering research and design. It highlights methods that provide strong correlations between topographies and performance or topographies and processes, and methods that can confidently discriminate topographies that were processed or that perform differently. These methods have commonalities in geometric characterizations at certain scales, which are observable with statistics and measurements. It also develops a semantic and theoretical framework and proposes a new system for organizing and designating …

Usability Challenges in Surgical Simulator Training

2009

Surgical virtual reality simulators have been taken into use in order to improve surgical skills training. Emergence of simulators increases the need for research and knowledge related to usability of medical simulators. In this study usability of laparoscopic surgical simulator was researched experimentally through combined analysis. Data was gathered with heuristic evaluation, questionnaires, and interviews as well as recorded simulator parameters. Results suggest that the surgical simulator could be more efficient learning and training tool if usability issues such as support and error prevention were reconsidered in more detail. There also seem to be grounds for connecting user support …

Integrated approach to the assessment of waste management systems within the SEA framework

2007

This paper addresses the problem of evaluating the environmental performances of Urban Waste Systems. Specifically, the paper refers to the crucial problem of environmentally analysing the Urban Waste System Management Process. The application of the Dashboard of Sustainability has been deliberately suggested. The method has been selected because of its intrinsic simplicity and because it can provide the simultaneous evaluation of indicators which refer to different fields, such as the Environment, Economics and Quality in Institutional Services. The method has been applied to the city of Palermo. The results obtained have been compared to a couple of ideal scenarios.