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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
Things such as organizations, persons, or locations are ubiquitous in all texts circulating on the internet, particularly in the news, forum posts, and social media. Today, there is more written material than any single person can read through during a typical lifespan. Automatic systems can help us amplify our abilities to find relevant information, where, ideally, a system would learn knowledge
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
The class of information set decoding algorithms is the best known way of decoding general codes, i.e. codes that admit no special structure, in the Hamming metric. Stern's algorithm is the origin of the most efficient algorithms in this class. In this paper we consider the same decoding problem but for a channel with soft information. We give a version of Stern's algorithm for a channel with soft
Thermal comfort has direction implications for energy efficiency and sustainable development. From a global perspective, about 40% of total primary energy is used in buildings, contributing to more than 30% of CO2 emissions [1]. The fact that the common practices of clothing choices have impact on energy efficiency is ignored [2-3]. This paper analyzed and proposed clothing insulation required for
While educational research (EdR) and the Scholarship of Teaching and Learning (SoTL) are overlapping fields there remains considerable friction between the two. Shulman, (2011, p. 5), recounts a situation when an EdR colleague accused him “of contributing to the bastardization of the field by encouraging faculty members who were never trained to conduct educational or social science research to en
We develop fixed-point algorithms for the approximation of structured matrices with rank penalties. In particular we use these fixed-point algorithms for making approximations by sums of exponentials, i.e., frequency estimation. For the basic formulation of the fixed-point algorithm we show that it converges to the solution of a related minimization problem, namely the one obtained by replacing th
