Search results for "computer.software_genre"
showing 10 items of 3858 documents
Experimental Assessment of the Backoff Behavior of Commercial IEEE 802.11b Network Cards
2007
It has been observed that different IEEE 802.11 commercial cards produced by different vendors experience different performance, either when accessing alone the channel, as well as when competing against each other. These differences persist also when thorough measurement methodologies (such as RF shielding, laptop rotation, etc) are applied, and alignment of the environmental factors (same laptop models, traffic generators, etc) is carried out. This paper provides an extensive experimental characterization of the backoff operation of six commercial NIC cards. It suggests a relevant methodological approach, namely a repeatable, well defined, set of experiments, for such a characterization. …
A plant-wide energy model for wastewater treatment plants: application to anaerobic membrane bioreactor technology
2016
[EN] The aim of this study is to propose a detailed and comprehensive plant-wide model for assessing the energy demand of different wastewater treatment systems (beyond the traditional activated sludge) in both steady- and unsteady-state conditions. The proposed model makes it possible to calculate power and heat requirements (W and Q, respectively), and to recover both power and heat from methane and hydrogen capture. In order to account for the effect of biological processes on heat requirements, the model has been coupled to the extended version of the BNRM2 plant-wide mathematical model, which is implemented in DESSAS simulation software. Two case studies have been evaluated to assess t…
Accelerated dinuclear palladium catalyst identification through unsupervised machine learning.
2021
Although machine learning bears enormous potential to accelerate developments in homogeneous catalysis, the frequent need for extensive experimental data can be a bottleneck for implementation. Here, we report an unsupervised machine learning workflow that uses only five experimental data points. It makes use of generalized parameter databases that are complemented with problem-specific in silico data acquisition and clustering. We showcase the power of this strategy for the challenging problem of speciation of palladium (Pd) catalysts, for which a mechanistic rationale is currently lacking. From a total space of 348 ligands, the algorithm predicted, and we experimentally verified, a number…
How Do Viewers Spontaneously Segment Animated Diagrams of Mechanical and Biological Subject Matter?
2012
A challenges for learning from animated diagrams is to first parse the continuous flow of information into discrete event units. Inadequacies in this parsing process can prejudice the quality of the mental model constructed from the depiction. One approach that has been proposed for ameliorating such problems is for the designer to pre-segment the animation. However, the pre-segmentation techniques used tend to be either intuitive or based on an expert's understanding of the subject matter. Neither of these approaches takes proper account of the psychological processing that must occur for an external animation to be properly internalized. This poster reports a study of the processes that l…
Basic Chemometric Tools
2013
Abstract The authentication of protected designation of origin and other protected geographical indications for foods involves the need for a deep knowledge of these kinds of samples and the correct identification of appropriate markers that are suitable to be used for authentication purposes. For this, significance tests must be developed and applied to provide evidence in a fast and accurate way; from this, it seems clear that advances in analytical tools, to obtain data regarding food chemical composition, and chemometric data treatments must be continued to provide to the users powerful identification methodologies. In this sense, the objective must be to differentiate between foods pro…
Chaînage de bases de données anonymisées pour les études épidémiologiques multicentriques nationales et internationales : proposition d'un algorithme…
2009
Background: Compiling individual records coming from different sources is very important for multicenter epidemiological studies; however, European directives and other national legislation concerning nominal data processing must be respected. These legal aspects can be satisfied by implementing mechanisms that allow anonymization of patient data (such as hashing techniques). Moreover, for security reasons, official recommendations suggest using different cryptographic keys in combination with a cryptographic hash function for each study. Unfortunately, this type of anonymization procedure is in contradiction with common requirements in public health and biomedical research because it becom…
Benchmarking Wilms’ tumor in multisequence MRI data: why does current clinical practice fail? Which popular segmentation algorithms perform well?
2019
Wilms' tumor is one of the most frequent malignant solid tumors in childhood. Accurate segmentation of tumor tissue is a key step during therapy and treatment planning. Since it is difficult to obtain a comprehensive set of tumor data of children, there is no benchmark so far allowing evaluation of the quality of human or computer-based segmentations. The contributions in our paper are threefold: (i) we present the first heterogeneous Wilms' tumor benchmark data set. It contains multisequence MRI data sets before and after chemotherapy, along with ground truth annotation, approximated based on the consensus of five human experts. (ii) We analyze human expert annotations and interrater varia…
Learning the relevant image features with multiple kernels
2009
This paper proposes to learn the relevant features of remote sensing images for automatic spatio-spectral classification with the automatic optimization of multiple kernels. The method consists of building dedicated kernels for different sets of bands, contextual or textural features. The optimal linear combination of kernels is optimized through gradient descent on the support vector machine (SVM) objective function. Since a na¨ive implementation is computationally demanding, we propose an efficient model selection procedure based on kernel alignment. The result is a weight — learned from the data — for each kernel where both relevant and meaningless image features emerge after training. E…
Adaptative Image Flow in Collaborative Medical Telediagnosis Environments
2011
International audience; Telemedicine, the application of telecommunication in the medicine field, has been developed to meet major problems encountered in connecting doctors with patients and other medical staff. Having a robust and efficient telemedical system has always been a challenge. The system needs to make the members in different locations capable of sharing medical data efficiently and without errors. In this work, we present a telemedical system that overcomes these challenges.We deploy a collaborative system and adapt data to store, visualize, modify and transfer fluorescence images efficiently and robustly at the same time. We also make the system adaptive to communicate across…
A Color Image Database for Haze Model and Dehazing Methods Evaluation
2016
International audience; One of the major issues related to dehazing methods (single or multiple image based) evaluation is the absence of the haze-free image (ground-truth). This is also a problem when it concerns the validation of Koschmieder model or its subsequent dehazing methods. To overcome this problem, we created a database called CHIC (Color Hazy Image for Comparison), consisting of two scenes in controlled environment. In addition to the haze-free image, we provide 9 images of different fog densities. Moreover, for each scene, we provide a number of parameters such as local scene depth, distance from the camera of known objects such as Macbeth Color Checkers, their radiance, and t…