Search results for "computer.software_genre"
showing 10 items of 3858 documents
A low-cost embedded IDS to monitor and prevent Man-in-the-Middle attacks on wired LAN environments
2007
A man-in-the-middle (MitM) attack is, in the scope of a LAN, a technique where an attacker is able to redirect all traffic between two hosts of that same LAN for packet sniffing or data manipulation, without the end hosts being aware of it. Usually these attacks exploit security flaws in the implementation of the ARP protocol at hosts. Up to now, detecting such attacks required setting up a machine with special-purpose software for this task. As an additional problem, few intrusion detection systems (IDS) are able to prevent MitM attacks. In this work we present a low-cost embedded IDS which, when plugged into a switch or hub, is able to detect and/or prevent MitM attacks automatically and …
NATO Advanced Research Workshop on Explosives Detection
2019
As of 2017, there are an estimated 100 million abandoned land mines littered across 61 countries. Following the wars in Afghanistan, Libya, Syria, Yemen, and Ukraine, there has been a rise in casualties due to the triggering of previously-abandoned explosive devices. The above institutions combined specialties to develop a remotely-operable, multisensor, robotic device for the detection of land mines, UXO (1), and IEDs (2). The robotic detection device uses novel subsurface radar with imaging and target classification to differentiate between threatening landmines and innocuous clutter. The expected outcome of this research is the creation of a multi-sensor system on a semi-autonomous vehic…
The language of emotion in short blog texts
2008
Emotion is central to human interactions, and automatic detection could enhance our experience with technologies. We investigate the linguistic expression of fine-grained emotion in 50 and 200 word samples of real blog texts previously coded by expert and naive raters. Content analysis (LIWC) reveals angry authors use more affective language and negative affect words, and that joyful authors use more positive affect words. Additionally, a co-occurrence semantic space approach (LSA) was able to identify fear (which naive human emotion raters could not do). We relate our findings to human emotion perception and note potential computational applications.
Importancia de la música como medio de comunicación intercultural en el proceso educativo
2013
El objetivo de este artículo es mostrar cómo la naturaleza metodológica y estructural de la música lleva al educando a comprender, a apreciar la realidad cultural que le envuelve; puesto que la música es fruto de un intercambio de experiencias teórico-prácticas en diferentes zonas del mundo y su metodología de aprendizaje es activa y participativa, necesitando de la colaboración y el entendimiento entre los intérpretes. Todo ello lleva a considerar la música como imagen del tiempo y de la sociedad que la ha producido, y, debido a ello, se convierte en una herramienta idónea para trabajar la interculturalidad en el aula. Este artículo toma como base uno de los objetivos de la educación artís…
AnySeq: A High Performance Sequence Alignment Library based on Partial Evaluation
2020
Sequence alignments are fundamental to bioinformatics which has resulted in a variety of optimized implementations. Unfortunately, the vast majority of them are hand-tuned and specific to certain architectures and execution models. This not only makes them challenging to understand and extend, but also difficult to port to other platforms. We present AnySeq - a novel library for computing different types of pairwise alignments of DNA sequences. Our approach combines high performance with an intuitively understandable implementation, which is achieved through the concept of partial evaluation. Using the AnyDSL compiler framework, AnySeq enables the compilation of algorithmic variants that ar…
Designing the Business Conversation Corpus
2020
While the progress of machine translation of written text has come far in the past several years thanks to the increasing availability of parallel corpora and corpora-based training technologies, automatic translation of spoken text and dialogues remains challenging even for modern systems. In this paper, we aim to boost the machine translation quality of conversational texts by introducing a newly constructed Japanese-English business conversation parallel corpus. A detailed analysis of the corpus is provided along with challenging examples for automatic translation. We also experiment with adding the corpus in a machine translation training scenario and show how the resulting system benef…
Active and inactive quarantine in epidemic spreading on adaptive activity-driven networks
2020
We consider an epidemic process on adaptive activity-driven temporal networks, with adaptive behaviour modelled as a change in activity and attractiveness due to infection. By using a mean-field approach, we derive an analytical estimate of the epidemic threshold for SIS and SIR epidemic models for a general adaptive strategy, which strongly depends on the correlations between activity and attractiveness in the susceptible and infected states. We focus on strong social distancing, implementing two types of quarantine inspired by recent real case studies: an active quarantine, in which the population compensates the loss of links rewiring the ineffective connections towards non-quarantining …
Core of communities in bipartite networks
2017
We use the information present in a bipartite network to detect cores of communities of each set of the bipartite system. Cores of communities are found by investigating statistically validated projected networks obtained using information present in the bipartite network. Cores of communities are highly informative and robust with respect to the presence of errors or missing entries in the bipartite network. We assess the statistical robustness of cores by investigating an artificial benchmark network, the co-authorship network, and the actor-movie network. The accuracy and precision of the partition obtained with respect to the reference partition are measured in terms of the adjusted Ran…
Denoising Autoencoders for Fast Combinatorial Black Box Optimization
2015
Estimation of Distribution Algorithms (EDAs) require flexible probability models that can be efficiently learned and sampled. Autoencoders (AE) are generative stochastic networks with these desired properties. We integrate a special type of AE, the Denoising Autoencoder (DAE), into an EDA and evaluate the performance of DAE-EDA on several combinatorial optimization problems with a single objective. We asses the number of fitness evaluations as well as the required CPU times. We compare the results to the performance to the Bayesian Optimization Algorithm (BOA) and RBM-EDA, another EDA which is based on a generative neural network which has proven competitive with BOA. For the considered pro…
Cross-Sensor Adversarial Domain Adaptation of Landsat-8 and Proba-V images for Cloud Detection
2021
The number of Earth observation satellites carrying optical sensors with similar characteristics is constantly growing. Despite their similarities and the potential synergies among them, derived satellite products are often developed for each sensor independently. Differences in retrieved radiances lead to significant drops in accuracy, which hampers knowledge and information sharing across sensors. This is particularly harmful for machine learning algorithms, since gathering new ground truth data to train models for each sensor is costly and requires experienced manpower. In this work, we propose a domain adaptation transformation to reduce the statistical differences between images of two…