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The concept of culturomics was born out of the availability of massive amounts of textual data and the interest to make sense of cultural and language phenomena over time. Thus far however, culturomics has only made use of, and shown the great potential of, statistical methods. In this paper, we present a vision for a knowledge-based culturomics that complements traditional culturomics. We discuss

In this paper, we introduce a method to use written natural language instructions to program assembly tasks for industrial robots. In our application, we used a state-of-the-art semantic and syntactic parser together with semantically rich world and skill descriptions to create highlevel symbolic task sequences. From these sequences, we generated executable code for both virtual and physical robot

The market of connected devices, IoT devices in particular, is hotter than ever. Today, lightweight IoT devices are used in several sectors, such as smart cities, smart homes, healthcare, and the manufacturing industry.IoT solutions help increase productivity by predictive maintenance and resource management in the industry. Devices with voice interfaces are spreading rapidly in the home automatio

This paper addresses the need for secure storage in virtualized services in the cloud. To this purpose, we evaluate the security properties of Intel's Software Guard Extensions (SGX) technology, which provides hardware protection for general applications, for securing virtual Hardware Security Modules (vHSM). In order for the analysis to be comparable with analyses of physical HSMs, the evaluation

A key enabler for Industry 4.0 is Fifth Generation Wireless Specifications (5G), within which network slicing is a promising technique to ensure customized quality of service for specific end-user groups in industrial scenarios. Massive Multiple Input Multiple Output (MIMO) plays a significant role in 5G but network slicing for massive MIMO has not yet been addressed. In this paper, we propose a n

It is well known that load balancing in data centers can lead to unnecessary energy usage if all servers are kept active. Usingdynamic server provisioning, the number of servers that serve requests can be reduced by turning off idle servers and thereby savingenergy. However, such a scheme, usually increases the risk of instability of server queues. In this work, we analyze the trade-offbetween ene

Side-channel attacks on cryptographic algorithms targets the implementation of the algorithm. Information can leak from the implementation in several different ways and, in this paper, electromagnetic radiation from an FPGA is considered. We examine to which extent key information from an AES implementation can be deduced using a low-end oscilloscope. Moreover, we examine how the antenna's distanc

Grain-128AEAD is a stream cipher supporting authenticated encryptionwith associated data, and it is currently in round 2 of the NIST lightweight cryptostandardization process. In this paper we present and benchmark software implementations of the cipher, targeting constrained processors. The processors chosen arethe 8-bit (AVR) and 16-bit (MSP) processors used in the FELICS-AEAD framework.Both hig

In the implementation of post-quantum primitives, it is well known that all computations that handle secret information need to be implemented to run in constant time. Using the Fujisaki-Okamoto transformation or any of its different variants, a CPA-secure primitive can be converted into an IND-CCA secure KEM. In this paper we show that although the transformation does not handle secret informatio

The Learning with Errors (LWE) problem is one of the main mathematical foundations of post-quantum cryptography. One of the main groups of algorithms for solving LWE is the Blum-Kalai-Wasserman (BKW) algorithm. This paper presents new improvements for BKW-style algorithms for solving LWE instances. We target minimum concrete complexity and we introduce a new reduction step where we partially reduc

Named entity linking is the task of identifying mentions of named things in text, such as “Barack Obama” or “New York”, and linking these mentions to unique identifiers. In this paper, we describe Hedwig, an end-to-end named entity linker, which uses a combination of word and character BILSTM models for mention detection, a Wikidata and Wikipedia-derived knowledge base with global information aggr

Cryptography as it is used today relies on a foundational level on the assumptionthat either the Integer Factoring Problem (IFP) or the DiscreteLogarithm Problem (DLP) is computationally intractable. In the 1990s PeterShor developed a quantum algorithm that solves both problems in polynomialtime. Since then alternative foundational mathematical problems to replace IFPand DLP have been suggested. T

Radio based localization and tracking usually require multiple receivers/transmitters or a known floor plan. This paper presents a method for anchor free indoor positioning based on single antenna ultra wideband (UWB) measurements. By using time of arrival information from multipath propagation components stemming from scatterers with different, but unknown, positions we estimate the movement of t

In this paper, we describe a passage retrieval component for a questioning answering system and we evaluate its performance on Swedish documents. We used a corpus of questions and answers transcribed from the Swedish board game Kvitt eller dubbelt and, as source for the passages, we used the articles of the Swedish version of Wikipedia. We show that Wikipedia is a suitable knowledge source to answ

Semantic role labeling has become a key module of many language processing applications. To build an unrestricted semantic role labeler, the first step is to develop a comprehensive proposition bank. However, building such a bank is a costly enterprise, which has only been achieved for a handful of languages. In this paper, we describe a technique to build proposition banks for new languages using

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