Search results for "computer.software_genre"
showing 10 items of 3858 documents
Classification of Satellite Images with Regularized AdaBoosting of RBF Neural Networks
2008
A Memetic-Neural Approach to Discover Resources in P2P Networks
2008
This chapter proposes a neural network based approach for solving the resource discovery problem in Peer to Peer (P2P) networks and an Adaptive Global Local Memetic Algorithm (AGLMA) for performing in training of the neural network. The neural network, which is a multi-layer perceptron neural network, allows the P2P nodes to efficiently locate resources desired by the user. The necessity of testing the network in various working conditions, aiming to obtain a robust neural network, introduces noise in the objective function. The AGLMA is a memetic algorithm which employs two local search algorithms adaptively activated by an evolutionary framework. These local searchers, having different fe…
Two-level branch prediction using neural networks
2003
Dynamic branch prediction in high-performance processors is a specific instance of a general time series prediction problem that occurs in many areas of science. Most branch prediction research focuses on two-level adaptive branch prediction techniques, a very specific solution to the branch prediction problem. An alternative approach is to look to other application areas and fields for novel solutions to the problem. In this paper, we examine the application of neural networks to dynamic branch prediction. We retain the first level history register of conventional two-level predictors and replace the second level PHT with a neural network. Two neural networks are considered: a learning vec…
A simulation of disagreement for control of rational cheating in peer review
2013
Understanding the peer review process could help research and shed light on the mechanisms that underlie crowdsourcing. In this paper, we present an agent-based model of peer review built on three entities - the paper, the scientist and the conference. The system is implemented on a BDI platform (Jason) that allows to define a rich model of scoring, evaluating and selecting papers for conferences. Then, we propose a programme committee update mechanism based on disagreement control that is able to remove reviewers applying a strategy aimed to prevent papers better than their own to be accepted (rational cheating). We analyze a homogeneous scenario, where all conferences aim to the same leve…
The sit up test to exhaustion as a test for muscular endurance evaluation
2015
Aims/Hypothesis The aim of this study was to examine the sit up test to exhaustion as a field test for muscular endurance evaluation in a sample of sedentary people of both sexes. Methods A cross-sectional study was performed. Three-hundred-eighty-one participants volunteered for the study (28.5 ± 10.0 years; 168.2 ± 8.9 cm; 65.1 ± 11.1 kg), of which 194 males (27.5 ± 10.2 years; 173.6 ± 7.0 cm; 71.2 ± 5.2 kg) and 187 females (29.6 ± 10.1 years; 162.6 ± 7.1 cm; 58.7 ± 8.9 kg). Each subject voluntarily and randomly performed: a sit up test (SUT), a push up test (PUT), and a free weight squat test (ST), all till exhaustion. A multiple regression analysis was adopted for data analysis. Subsequ…
3D Matrix-Based Visualization System of Association Rules
2017
With the growing number of mining datasets, it becomes increasingly difficult to explore interesting rules because of the large number of resultant and its nature complexity. Studies on human perception and intuition show that graphical representation could be a better illustration of how to seek information from the data using the capabilities of human visual system. In this work, we present and implement a 3D matrix-based approach visualization system of association rules. The main visual representation applies the extended matrix-based approach with rule-to-items mapping to general transaction data set. A novel method merging rules and assigning weight is proposed in order to reduce the …
Discovering representative models in large time series databases
2004
The discovery of frequently occurring patterns in a time series could be important in several application contexts. As an example, the analysis of frequent patterns in biomedical observations could allow to perform diagnosis and/or prognosis. Moreover, the efficient discovery of frequent patterns may play an important role in several data mining tasks such as association rule discovery, clustering and classification. However, in order to identify interesting repetitions, it is necessary to allow errors in the matching patterns; in this context, it is difficult to select one pattern particularly suited to represent the set of similar ones, whereas modelling this set with a single model could…
A KInetic Database for Astrochemistry (KIDA)
2012
We present a novel chemical database for gas-phase astrochemistry. Named the KInetic Database for Astrochemistry (KIDA), this database consists of gas-phase reactions with rate coefficients and uncertainties that will be vetted to the greatest extent possible. Submissions of measured and calculated rate coefficients are welcome, and will be studied by experts before inclusion into the database. Besides providing kinetic information for the interstellar medium, KIDA is planned to contain such data for planetary atmospheres and for circumstellar envelopes. Each year, a subset of the reactions in the database (kida.uva) will be provided as a network for the simulation of the chemistry of dense…
Traitement de données RGB et Lidar à extrêmement haute résolution: retombées de la compétition de fusion de données 2015 de l'IEEE GRSS - Partie A / …
2016
International audience; In this paper, we discuss the scientific outcomes of the 2015 data fusion contest organized by the Image Analysis and Data Fusion Technical Committee (IADF TC) of the IEEE Geoscience and Remote Sensing Society (IEEE GRSS). As for previous years, the IADF TC organized a data fusion contest aiming at fostering new ideas and solutions for multisource studies. The 2015 edition of the contest proposed a multiresolution and multisensorial challenge involving extremely high-resolution RGB images and a three-dimensional (3-D) LiDAR point cloud. The competition was framed in two parallel tracks, considering 2-D and 3-D products, respectively. In this paper, we discuss the sci…
Exploring the Validity of the Long-Term Data Record V4 Database for Land Surface Monitoring
2016
A new version of the long-term data record (LTDR)—Version 4—has been released recently by NASA. This database includes daily information for all advanced very high resolution radiometer channels, as well as ancillary data, from July 1981 up to present. This dataset is the longest available record of remotely sensed data useful for land surface monitoring, since it allows the daily estimation of vegetation indices, as well as the estimation of land surface temperature (LST). Here, we analyze the fitness of this database for land surface monitoring, especially as regards long-term trends and their validity. To that end, we estimated normalized difference vegetation index (NDVI), LST, as well …