Multilingual Cross-domain Perspectives on Online Hate Speech

In this report, we present a study of eight corpora of online hate speech, by demonstrating the NLP techniques that we used to collect and analyze the jihadist, extremist, racist, and sexist content. Analysis of the multilingual corpora shows that the different contexts share certain characteristics in their hateful rhetoric. To expose the main features, we have focused on text classification, text profiling, keyword and collocation extraction, along with manual annotation and qualitative study.Comment: 24 page

Multi-objective optimization of building life cycle performance. A housing renovation case study in Northern Europe

While the operational energy use of buildings is often regulated in current energy saving policies, their embodied greenhouse gas emissions still have a considerable mitigation potential. The study aims at developing a multi-objective optimization method for design and renovation of buildings incorporating the operational and embodied energy demands, global warming potential, and costs as objective functions. The optimization method was tested on the renovation of an apartment building in Denmark, mainly focusing envelope improvements as roof and exterior wall insulation and windows. Cellulose insulation has been the predominant result, together with fiber cement or aluminum-based cladding and 2-layered glazing. The annual energy demand has been reduced from 166.4 to a range between 76.5 and 83.7 kWh/(m2 y) in the optimal solutions. The fact that the legal requirements of 70 kWh/(m2 y) are nearly met without building service improvements indicates that energy requirements can be fulfilled without compromising greenhouse gas emissions and cost. Since the method relies on standard national performance reporting tools, the authors believe that this study is a preliminary step towards more cost-efficient and low-carbon building renovations by utilizing multi-optimization techniques

Self-Supervised and Controlled Multi-Document Opinion Summarization

We address the problem of unsupervised abstractive summarization of collections of user generated reviews with self-supervision and control. We propose a self-supervised setup that considers an individual document as a target summary for a set of similar documents. This setting makes training simpler than previous approaches by relying only on standard log-likelihood loss. We address the problem of hallucinations through the use of control codes, to steer the generation towards more coherent and relevant summaries.Finally, we extend the Transformer architecture to allow for multiple reviews as input. Our benchmarks on two datasets against graph-based and recent neural abstractive unsupervised models show that our proposed method generates summaries with a superior quality and relevance.This is confirmed in our human evaluation which focuses explicitly on the faithfulness of generated summaries We also provide an ablation study, which shows the importance of the control setup in controlling hallucinations and achieve high sentiment and topic alignment of the summaries with the input reviews.Comment: 18 pages including 5 pages appendi

Use of supervised machine learning for GNSS signal spoofing detection with validation on real-world meaconing and spoofing data : part I

The vulnerability of the Global Navigation Satellite System (GNSS) open service signals to spoofing and meaconing poses a risk to the users of safety-of-life applications. This risk consists of using manipulated GNSS data for generating a position-velocity-timing solution without the user's system being aware, resulting in presented hazardous misleading information and signal integrity deterioration without an alarm being triggered. Among the number of proposed spoofing detection and mitigation techniques applied at different stages of the signal processing, we present a method for the cross-correlation monitoring of multiple and statistically significant GNSS observables and measurements that serve as an input for the supervised machine learning detection of potentially spoofed or meaconed GNSS signals. The results of two experiments are presented, in which laboratory-generated spoofing signals are used for training and verification within itself, while two different real-world spoofing and meaconing datasets were used for the validation of the supervised machine learning algorithms for the detection of the GNSS spoofing and meaconing

Differential limit on the extremely-high-energy cosmic neutrino flux in the presence of astrophysical background from nine years of IceCube data

We report a quasi-differential upper limit on the extremely-high-energy (EHE) neutrino flux above $5\times 10^{6}$ GeV based on an analysis of nine years of IceCube data. The astrophysical neutrino flux measured by IceCube extends to PeV energies, and it is a background flux when searching for an independent signal flux at higher energies, such as the cosmogenic neutrino signal. We have developed a new method to place robust limits on the EHE neutrino flux in the presence of an astrophysical background, whose spectrum has yet to be understood with high precision at PeV energies. A distinct event with a deposited energy above $10^{6}$ GeV was found in the new two-year sample, in addition to the one event previously found in the seven-year EHE neutrino search. These two events represent a neutrino flux that is incompatible with predictions for a cosmogenic neutrino flux and are considered to be an astrophysical background in the current study. The obtained limit is the most stringent to date in the energy range between $5 \times 10^{6}$ and $5 \times 10^{10}$ GeV. This result constrains neutrino models predicting a three-flavor neutrino flux of $E_\nu^2\phi_{\nu_e+\nu_\mu+\nu_\tau}\simeq2\times 10^{-8}\ {\rm GeV}/{\rm cm}^2\ \sec\ {\rm sr}$at$10^9\ {\rm GeV}$. A significant part of the parameter-space for EHE neutrino production scenarios assuming a proton-dominated composition of ultra-high-energy cosmic rays is excluded.Comment: The version accepted for publication in Physical Review

Trade and Domestic Production Networks. National Bank of Belgium Working Paper No. 344

We use Belgian data with information on domestic firm-to-firm sales and foreign trade transactions to study how international trade affects firm efficiency and real wages. The data allow us to accurately construct the domestic production network of the Belgian economy, revealing several new empirical facts about firms’ indirect exposure to foreign trade through their domestic suppliers and buyers. We use this data to develop and estimate models of domestic production networks and international trade. We first consider a model of trade with an exogenous network structure, which gives analytical solutions for the effects of a change in the price of foreign goods on firms’ production costs and real wages. To examine how gains-from-trade calculations change if buyer-supplier links are allowed to form or break in response to changes in the price of foreign goods, we next develop a model of trade with endogenous network formation. We take both models to the data and compare the empirical results to those we obtain using existing approaches. This comparison highlights the relevance of data on and modeling of domestic production networks in studies of international trade

Accessibility dynamics and regional cross-border cooperation (CBC) perspectives in the portuguese—spanish borderland

Accessibility plays a major role in achieving sustainable transport, and therefore urban and regional sustainability. The urban public transport system promotes mobility and realizes a large part of urban movements. Moreover, improving accessibility in order to promote sustainable transport requires the application of new concepts and indicators as a powerful tool in the process of creating a balanced urban transport system. In this regard, one of the main goals of this research is to present an overview of the relevant accessibility indicators and assessment of accessibility in regional Cross-Border Cooperation (CBC) in order to transcendence challenges and obstacles for sustainable transportation in these regions along of Portuguese-Spanish border. This paper focuses on the accessibility of cross-border cooperation scenarios along the border regions of Alto Alentejo (Portugal) and Badajoz (Spain) where the Case Study Research Method (CSR) made it possible to recognize accessibility as a key factor in territorial success. Also, accessibility analysis can assess improvements as well as regional imbalances. In addition, this methodology can be used to identify missing links, which requires new investments enabling long-term sustainability.info:eu-repo/semantics/publishedVersio

Monitoring movement in the smart city : opportunities and challenges of measuring urban bustle

One of the promises of the smart city concept is using real-time data to enhance policy making. In practice, such promises can turn out to be either very limited in what is actually possible or quickly trigger dystopian scenarios of tracking and monitoring. Today, many cities around the world already measure forms of urban bustle, i.e. how busy it is during specific periods of time. They do this for all kinds of purposes like optimising mobility flows, attracting tourism, monitoring safety during events or stimulating the local economy, and they employ divergent technologies: from analogue counting, over surveys, to more advanced near real-time tracking using mobile operator data. This fragmentation of approaches to measuring urban bustle creates some challenges for cities related to privacy, vendor lock-in, comparability of data, data quality and accuracy, historical and predictive analysis of data and so on. To tackle these challenges and formulate a standardised approach to measuring urban bustle, the thirteen largest cities in Flanders (Belgium), together with local technology vendors, co-created a “definition manual”; a document outlining indicators and relevant technologies for measuring urban bustle, as well as shared profile descriptions of residents and visitors of the city. This paper outlines the process and presents the results, an agreed-upon framework of standard profiles and indicators, which are useful to academics, public servants and technology companies involved in this topic