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Code-based cryptography is one of the main techniques enabling cryptographic primitives in a post-quantum scenario. In particular, the MDPC scheme is a basic scheme from which many other schemes have been derived. These schemes rely on iterative decoding in the decryption process and thus have a certain small probability p of having a decryption (decoding) error.In this paper we show a very fundam
This study explores the online communication strategies of anti-tourism movements to evaluate their potential contributions to place branding—a topic that has received limited scholarly attention. While prior research often views such movements as antagonistic to place branding efforts, we challenge this assumption. Through an analysis of nine movements across five countries, we apply the typology
Background Long-term pathological breathlessness is a life-limiting symptom that risks taking control of the individual’s life. We aimed to evaluate how locus of control (LOC), an individual’s perceived control of present and past life events, relates to breathlessness in a middle-aged general population. Methods A population-based, cross-sectional analysis of people aged 50–64 years was conducted
Peatlands store substantial amounts of carbon and are vulnerable to climate change. We present a modified version of the Organising Carbon and Hydrology In Dynamic Ecosystems (ORCHIDEE) land surface model for simulating the hydrology, surface energy, and CO2 fluxes of peatlands on daily to annual timescales. The model includes a separate soil tile in each 0.5° grid cell, defined from a global peat
With the inclusion of external software components in their software, vendors also need to identify and evaluate vulnerabilities in the components they use. A growing number of external components makes this process more time-consuming, as vendors need to evaluate the severity and applicability of published vulnerabilities. The CVSS score is used to rank the severity of a vulnerability, but in its
User generated content (UGC) makes up a significant portion of Internet traffic. As opposed to other content, UGC has so far been left outside over-the-top providing network operators content distribution networks (telco-CDN) due to the difficulty in determining optimised placement of such content. The side effect of this is that UGC content is not placed close to end users and therefore occupy un
Organizations and individuals maintain and use an ever increasing amount of computer systems, either deployed locally, or in the cloud.These systems often store and handle vast amounts of data, some of which is sensitive and should be kept private.Regardless of where the data is located, there is a need to prevent data from falling into the wrong hands.To this end, this dissertation presents contr
This thesis explores methods for generating proposition databases in a large-scale and multilingual setting. Our methods are centered on using semantic role labeling for extracting predicate-argument structures, and the subsequent transformation of such structures for knowledge base population and generation. By extending semantic role labeling with entity detection, we demonstrate how predicate-a
In this paper, we describe KOSHIK, an end-to-end framework to process the unstructured natural language content of multilingual documents. We used the Hadoop distributed computing infrastructure to build this framework as it enables KOSHIK to easily scale by adding inexpensive commodity hardware. We designed an annotation model that allows the processing algorithms to incrementally add layers of a
Inthispaper,wedescribeanovelsystemthatidentifiesrelationsbetweentheobjectsextractedfromanimage. We started from the idea that in addition to the geometric and visual properties of the image objects, we could exploit lexical and semantic information from the text accompanying the image. As experimental set up, we gathered a corpus of images from Wikipedia as well as their associated articles. We ext
Most question answering systems feature a step to predict an expected answer type given a question. Li and Roth \cite{li2002learning} proposed an oft-cited taxonomy to the categorize the answer types as well as an annotated data set. While offering a framework compatible with supervised learning, this method builds on a fixed and rigid model that has to be updated when the question-answering domai
The massive amounts of text data made available through the Google Books digitization project have inspired a new field of big-data textual research. Named culturomics, this field has attracted the attention of a growing number of scholars over recent years. However, initial studies based on these data have been criticized for not referring to relevant work in linguistics and language technology.
This paper describes a set of methods to link entities across images and text. As a corpus, we used a data set of images, where each image is commented by a short caption and where the regions in the images are manually segmented and labeled with a category. We extracted the entity mentions from the captions and we computed a semantic similarity between the mentions and the region labels. We also
A cross-national study, 49 samples in 38 nations, N=4,344, investigates whether national peace and conflict reflect ambivalent warmth-competence stereotypes: High-conflict societies (Pakistan) may need clearcut, unambivalent group images-distinguishing friends from foes. Highly peaceful countries (Denmark) also may need less ambivalence because most groups occupy the shared national identity, with
Vehicle traffic management is becoming more complex due to increased traffic density in cities. Novel solutions are necessary for emergency vehicles, which despite growing congestion must be able to quickly reach their destination. Emergency vehicles are usually equipped with transmitters to control the traffic lights on their path and warn other vehicles with sirens. Transmitters are operated man
The role of time-dependent freezing of ice nucleating particles (INPs) is evaluated with the “Aerosol–Cloud” (AC) model in 1) deep convection observed over Oklahoma during the Midlatitude Continental Convective Cloud Experiment (MC3E), 2) orographic clouds observed over North California during the Atmospheric Radiation Measurement (ARM) Cloud Aerosol Precipitation Experiment (ACAPEX), and 3) super
To train well-performing generalizing neural networks, sufficiently large and diverse datasets are needed. Collecting data while adhering to privacy legislation becomes increasingly difficult and annotating these large datasets is both a resource-heavy and time-consuming task. An approach to overcome these difficulties is to use synthetic data since it is inherently scalable and can be automatical
Properties of the Grain-128AEAD key re-introduction, as part of the cipher initialization, are analyzed and discussed. We consider and analyze several possible alternatives for key re-introduction and identify weaknesses, or potential weaknesses, in them. Our results show that it seems favorable to separate the state initialization, the key re-introduction, and the A/R register initialization into
