Search results for " Performance Evaluation"
showing 10 items of 11 documents
Remarks on IEEE 802.11 DCF performance analysis
2005
This letter presents a new approach to evaluate the throughput/delay performance of the 802.11 distributed coordination function (DCF). Our approach relies on elementary conditional probability arguments rather than bidimensional Markov chains (as proposed in previous models) and can be easily extended to account for backoff operation more general than DCF's one.
MAC Protocols for Wake-up Radio: Principles, Modeling and Performance Analysis
2018
[EN] In wake-up radio (WuR) enabled wireless sensor networks (WSNs), a node triggers a data communication at any time instant by sending a wake-up call (WuC) in an on-demand manner. Such wake-up operations eliminate idle listening and overhearing burden for energy consumption in duty-cycled WSNs. Although WuR exhibits its superiority for light traffic, it is inefficient to handle high traffic load in a network. This paper makes an effort towards improving the performance of WuR under diverse load conditions with a twofold contribution. We first propose three protocols that support variable traffic loads by enabling respectively clear channel assessment (CCA), backoff plus CCA, and adaptive …
Analyzing big datasets of genomic sequences: fast and scalable collection of k-mer statistics
2019
Abstract Background Distributed approaches based on the MapReduce programming paradigm have started to be proposed in the Bioinformatics domain, due to the large amount of data produced by the next-generation sequencing techniques. However, the use of MapReduce and related Big Data technologies and frameworks (e.g., Apache Hadoop and Spark) does not necessarily produce satisfactory results, in terms of both efficiency and effectiveness. We discuss how the development of distributed and Big Data management technologies has affected the analysis of large datasets of biological sequences. Moreover, we show how the choice of different parameter configurations and the careful engineering of the …
El rol del modelo de las competencias en la reconfiguración meritocrática de las pautas de negociación salarial en empresas argentinas: continuidades…
2020
The development of new models of work organization and the complementary advance of flexible guidelines for the use of the labor force had as a correlate a profound change in techniques for the evaluation of workers. Thus, the typical model of Fordism, based on qualifications, was replaced by a different one based on competencies, whereby the strong relationship of the former was abandoned with the determination of the technical knowledge required for each job to move to a system which the priority is placed in the individual attitude. The consequent individualization of performance evaluations can lead to a possible loss of objectivity. In this article we develop a theoretical comparison b…
Robust Adaptive Modulation and Coding (AMC) selection in LTE systems using reinforcement learning
2014
Adaptive Modulation and Coding (AMC) in LTE networks is commonly employed to improve system throughput by ensuring more reliable transmissions. Most of existing AMC methods select the modulation and coding scheme (MCS) using pre-computed mappings between MCS indexes and channel quality indicator (CQI) feedbacks that are periodically sent by the receivers. However, the effectiveness of this approach heavily depends on the assumed channel model. In addition CQI feedback delays may cause throughput losses. In this paper we design a new AMC scheme that exploits a reinforcement learning algorithm to adjust at run-time the MCS selection rules based on the knowledge of the effect of previous AMC d…
Technical and health governance aspects of the External Quality Assessment Scheme for the SARS-CoV-2 molecular tests: institutional experience perfor…
2022
Abstract Objectives Since December 2019, the worldwide public health has been threatened by a severe acute respiratory syndrome caused by Coronavirus-2. From the beginning, a turning point has been the identification of new cases of infection, in order to minimize the virus spreading among the population. For this reason, it was necessary introducing a panel of tests able to identify positive cases, which became crucial for all countries. Methods As a Regional Reference Centre, the CRQ Laboratory (Regional Laboratory for the Quality Control) developed and conducted an External Quality Assessment (EQA) panel of assay, so as to evaluate the quality of real-time reverse transcription polymeras…
Setting up of a machine learning algorithm for the identification of severe liver fibrosis profile in the general US population cohort
2022
Background: The progress of digital transformation in clinical practice opens the door to transforming the current clinical line for liver disease diagnosis from a late-stage diagnosis approach to an early-stage based one. Early diagnosis of liver fibrosis can prevent the progression of the disease and decrease liver-related morbidity and mortality. We developed here a machine learning (ML) algorithm containing standard parameters that can identify liver fibrosis in the general US population.Materials and methods: Starting from a public database (National Health and Nutrition Examination Survey, NHANES), representative of the American population with 7265 eligible subjects (control populati…
On the optimal design of multi-stage cascaded transistor amplifiers with noise, gain and mismatch constraints
2007
The problem of evaluating the optimal performances of cascaded, unbalanced, multi-stage transistor amplifiers is addressed. In particular, a theoretically rigorous approach is proposed for the determination of a family of Optimal Design Curves (ODC's) which express the best noise-gain tradeoff that can be achieved - at each frequency and device operating condition - when a simultaneous constraint on amplifier input VSWR is accounted for. Such curves can be used as a more meaningful starting point in practical amplifier design in place of the approximate calculations so far employed for target performance or optimization goals determination.
Performance Analysis in Spatially Correlated IEEE 802.11 Networks
2012
Wireless mesh networks are difficult to be characterized, especially under multi-hop traffic streams. The problem is that the local view of the channel and the correlation between the buffers of consecutive nodes in a stream path make complicated the identification of the contention level perceived by each station along the time. Such a figure is used in the models based on the so called decoupling assumption for evaluating the final scheduling of simultaneous channel access grants. In this paper we propose a simplified mesh network model focused on capturing the correlation due to the network topology and traffic routes rather than the access protocol state at each node. To this purpose, w…
Integration of a structural features-based preclassifier and a man-machine interactive classifier for a fast multi-stroke character recognition
2003
A transputer-based parallel machine for handwritten character recognition is proposed. An algorithm based on structural features and on a tree classifier was used to accomplish the pre-classification of the unknown sample in order to speed up the recognition process. The algorithm for the final classification is based on the description of the strokes through Fourier descriptors. The learning phase is accomplished through a man-machine interactive process. The proposed system can expand its knowledge base. A special representation of this knowledge base is proposed in order to record a great amount of data in a suitable way. A fast multistroke handwritten isolated character recognition syst…