Search results for "RNR"
showing 10 items of 302 documents
Testing a spectral-based feature set for audio genre classification
2011
Automatic musical genre classification is an important information retrieval task since it can be applied for practical purposes such as the organization of data collections in the digital music industry. However, this task remains an open question because the current state of the art shows far from satisfactory outcomes in terms of classification performance. Moreover, the most common algorithms that are used for this task are not designed for modelling music perception. This study suggests a framework for testing different musical features for use in music genre classification and evaluates the performance of this task based on two musical descriptors. The focus of this study is on automa…
SIFT Texture Description for Understanding Breast Ultrasound Images
2014
Texture is a powerful cue for describing structures that show a high degree of similarity in their image intensity patterns. This paper describes the use of Self-Invariant Feature Transform (SIFT), both as low-level and high-level descriptors, applied to differentiate the tissues present in breast US images. For the low-level texture descriptors case, SIFT descriptors are extracted from a regular grid. The high-level texture descriptor is build as a Bag-of-Features (BoF) of SIFT descriptors. Experimental results are provided showing the validity of the proposed approach for describing the tissues in breast US images.
Clustering Algorithms for MRI
1991
Magnetic Resonance Imaging (MRI) plays a relevant role in the design of systems for computer assisted diagnosis. MR-images are multi-dimensional in nature; physicians have to combine several perceptual information images to perform the tissue classification needed for diagnosis. Automatic clustering methods help to discriminate relevant features and to perform a preliminary segmentation of the image; it can guide the final manual classification of body-tissues. Three clustering techniques and their integration in a MRI-system are described. Their performance and accuracy was evaluated on synthetic and real image-data. A comparison of our approach with the tissue-classification done by a rad…
Image classification based on 2D feature motifs
2013
The classification of raw data often involves the problem of selecting the appropriate set of features to represent the input data. In general, various features can be extracted from the input dataset, but only some of them are actually relevant for the classification process. Since relevant features are often unknown in real-world problems, many candidate features are usually introduced. This degrades both the speed and the predictive accuracy of the classifier due to the presence of redundancy in the candidate feature set. In this paper, we study the capability of a special class of motifs previously introduced in the literature, i.e. 2D irredundant motifs, when they are exploited as feat…
Translational repression and novel functions of Cth2 in the Saccharomyces cerevisiae response to iron deficiency
2020
El hierro (Fe) es un micronutriente y cofactor esencial para todos los organismos eucariotas. Las proteínas que incorporan hierro en su estructura lo hacen en forma de grupos hemo, centros Fe/S o centros de hierro y oxígeno, entre otros. Estos cofactores están implicados en numerosos procesos celulares como la respiración, la replicación y reparación del DNA, la biogénesis de ribosomas y la traducción de proteínas, la biosíntesis de ácidos nucleicos y lípidos, la fotosíntesis y el transporte de oxígeno. Pese a ser un metal abundante en la corteza terrestre, su forma oxidada Fe+3 es la más frecuente en un entorno oxidante y resulta insoluble a pH fisiológico. Esto hace de la deficiencia de h…
Multispectral filter arrays: Recent advances and practical implementation
2014
Thanks to some technical progress in interferencefilter design based on different technologies, we can finally successfully implement the concept of multispectral filter array-based sensors. This article provides the relevant state-of-the-art for multispectral imaging systems and presents the characteristics of the elements of our multispectral sensor as a case study. The spectral characteristics are based on two different spatial arrangements that distribute eight different bandpass filters in the visible and near-infrared area of the spectrum. We demonstrate that the system is viable and evaluate its performance through sensor spectral simulation. Multispectral filter arrays: Recent advan…
A novel heuristic memetic clustering algorithm
2013
In this paper we introduce a novel clustering algorithm based on the Memetic Algorithm meta-heuristic wherein clusters are iteratively evolved using a novel single operator employing a combination of heuristics. Several heuristics are described and employed for the three types of selections used in the operator. The algorithm was exhaustively tested on three benchmark problems and compared to a classical clustering algorithm (k-Medoids) using the same performance metrics. The results show that our clustering algorithm consistently provides better clustering solutions with less computational effort.
Support vector machine integrated with game-theoretic approach and genetic algorithm for the detection and classification of malware
2013
Abstract. —In the modern world, a rapid growth of mali- cious software production has become one of the most signifi- cant threats to the network security. Unfortunately, wides pread signature-based anti-malware strategies can not help to de tect malware unseen previously nor deal with code obfuscation te ch- niques employed by malware designers. In our study, the prob lem of malware detection and classification is solved by applyin g a data-mining-based approach that relies on supervised mach ine- learning. Executable files are presented in the form of byte a nd opcode sequences and n-gram models are employed to extract essential features from these sequences. Feature vectors o btained are…
It’s Not Only What You Say, But How You Say It : Investigating the Potential of Prosodic Analysis as a Method to Study Teacher’s Talk
2018
In this study, we introduce new insights into prosodic analyses as an emerging method to study what happens in classrooms interactions. We claim that the prosodic aspects (features of speech such as intonation, volume and pace) of talk are important, but under-represented in the learning sciences. These prosodic aspects may be used to complement, intensify or even reverse the linguistic content of speech. Thus far, most research on classrooms has focused on the content (what is said) rather than on understanding the meaning of the prosodic features (how it is said) of talk. In this study, we introduce prosodic analyses as a method to study classroom discussions. Our exploratory experiment f…
AI Ethics in Industry: A Research Framework
2019
Artificial Intelligence (AI) systems exert a growing influence on our society. As they become more ubiquitous, their potential negative impacts also become evident through various real-world incidents. Following such early incidents, academic and public discussion on AI ethics has highlighted the need for implementing ethics in AI system development. However, little currently exists in the way of frameworks for understanding the practical implementation of AI ethics. In this paper, we discuss a research framework for implementing AI ethics in industrial settings. The framework presents a starting point for empirical studies into AI ethics but is still being developed further based on its pr…