Search results for "MBL"

Horse exploitation at the Late Upper Palaeolithic site of Oelknitz (Thuringia, Germany) with special reference to canine modifications

2012

Abstract The faunal assemblage from Structure 5 of the Magdalenian settlement Oelknitz (Thuringia, Germany) was analyzed. The fauna is dominated by horse. All stages of butchery from skinning to marrow extraction were performed within the horse assemblage. In addition to this, various stages of organic artifact production could be documented. Two fragmentary equid canine teeth were of particular interest. They are the only documented canines from Structure 5, which otherwise contained a large amount of teeth. Both canines show traces of human modification. They were cut out of the jaw while still in the alveole. On both canines, lateral incisions were performed at the cervix dentis and the …

A weighted distance-based approach with boosted decision trees for label ranking

2023

Label Ranking (LR) is an emerging non-standard supervised classification problem with practical applications in different research fields. The Label Ranking task aims at building preference models that learn to order a finite set of labels based on a set of predictor features. One of the most successful approaches to tackling the LR problem consists of using decision tree ensemble models, such as bagging, random forest, and boosting. However, these approaches, coming from the classical unweighted rank correlation measures, are not sensitive to label importance. Nevertheless, in many settings, failing to predict the ranking position of a highly relevant label should be considered more seriou…

Multi-layer intrusion detection system with ExtraTrees feature selection, extreme learning machine ensemble, and softmax aggregation

2019

Abstract Recent advances in intrusion detection systems based on machine learning have indeed outperformed other techniques, but struggle with detecting multiple classes of attacks with high accuracy. We propose a method that works in three stages. First, the ExtraTrees classifier is used to select relevant features for each type of attack individually for each (ELM). Then, an ensemble of ELMs is used to detect each type of attack separately. Finally, the results of all ELMs are combined using a softmax layer to refine the results and increase the accuracy further. The intuition behind our system is that multi-class classification is quite difficult compared to binary classification. So, we…

Preamble Transmission Prediction for mMTC Bursty Traffic : A Machine Learning based Approach

2020

The evolution of Internet of things (IoT) towards massive IoT in recent years has stimulated a surge of traffic volume among which a huge amount of traffic is generated in the form of massive machine type communications. Consequently, existing network infrastructure is facing challenges when handling rapidly growing traffic load, especially under bursty traffic conditions which may more often lead to congestion. By proactively predicting the occurrence of congestion, we can implement necessary means and conceivably avoid congestion. In this paper, we propose a machine learning (ML) based model for predicting successful preamble transmissions at a base station and subsequently forecasting th…

Cloud screening with combined MERIS and AATSR images

2009

This paper presents a cloud screening algorithm based on ensemble methods that exploits the combined information from both MERIS and AATSR instruments on board ENVISAT in order to improve current cloud masking products for both sensors. The first step is to analyze the synergistic use of MERIS and AATSR images in order to extract some physically-based features increasing the separability of clouds and surface. Then, several artificial neural networks are trained using different sets of input features and different sets of training samples depending on acquisition and surface conditions. Finally, outputs of the trained neural networks are combined at the decision level to construct a more ac…

Automatic Identification of Watermarks and Watermarking Robustness Using Machine Learning Techniques

2021

The goal of this article is to propose a framework for automatic identification of watermarks from modified host images. The framework can be used with any watermark embedding/extraction system and is based on models built using machine learning (ML) techniques. Any supervised ML approach can be theoretically chosen. An important part of our framework consists in building a stand-alone module, independent of the watermarking system, for generating two types of watermarks datasets. The first type of datasets, that we will name artificially datasets, is generated from the original images by adding noise with an imposed maximum level of noise. The second type contains altered watermarked image…

Solving type-2 Assembly Line Balancing Problem with Fuzzy Binary Linear Programming

2013

Human factor policy testing in the sequencing of manual mixed model assembly lines

2004

In this paper the human resource management in manual mixed model assembly U-lines is considered. The objective is to minimise the total conveyor stoppage time to achieve the full efficiency of the line. A model, that includes effects of the human resource, was developed in order to evaluate human factor policies impact on the optimal solution of this line sequencing problem. Different human resource management policies are introduced to cope with the particular layout of the proposed line. Several examples have been proposed to investigate the effects of line dimensions on the proposed management policies. The examples have been solved through a genetic algorithm. The obtained results conf…

MACC regional multi-model ensemble simulations of birch pollen dispersion in Europe

2015

Abstract. This paper presents the first ensemble modelling experiment in relation to birch pollen in Europe. The seven-model European ensemble of MACC-ENS, tested in trial simulations over the flowering season of 2010, was run through the flowering season of 2013. The simulations have been compared with observations in 11 countries, all members of the European Aeroallergen Network, for both individual models and the ensemble mean and median. It is shown that the models successfully reproduced the timing of the very late season of 2013, generally within a couple of days from the observed start of the season. The end of the season was generally predicted later than observed, by 5 days or more…

Polyandrous females produce sons that are successful at post-copulatory competition.

2014

Some of the genetic benefit hypotheses put forward to explain multiple male mating (polyandry) predict that sons of polyandrous females will have an increased competitive ability under precopulatory or post-copulatory competition via paternally inherited traits, such as attractiveness or fertilization efficiency. Here, we tested these predictions by comparing the competitive ability of sons of experimentally monandrous and polyandrous female bank voles (Myodes glareolus), while controlling for potential material and maternal effects. In female choice experiments, we found no clear preference for sons of either monandrous or polyandrous mothers. Moreover, neither male type was dominant over …