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When robots are working in dynamic environments, close to humans lacking extensive knowledge of robotics, there is a strong need to simplify the user interaction and make the system execute as autonomously as possible, as long as it is feasible. For industrial robots working side-by-side with humans in manufacturing industry, AI systems are necessary to lower the demand on programming time and sys
Spectral estimation is an important classical problem that has received considerable attention in the signal processing literature. In this contribution, we propose a novel method for estimating the parameters of sums of complex exponentials embedded in additive noise from regularly or irregularly spaced samples. The method relies on Kronecker's theorem for Hankel operators, which enables us to fo
Several studies have shown the value of using proximity data to understand the social context of users. To simplify the use of social context in application development we have developed Proximates, a social context engine for mobile phones. It scans nearby Bluetooth peers to determine what devices are in proximity. We map Bluetooth MAC ids to user identities on existing social networks which then
We consider sequences of points obtained by projecting a given point B=B (0) back and forth between two manifolds and , and give conditions guaranteeing that the sequence converges to a limit . Our motivation is the study of algorithms based on finding the limit of such sequences, which have proved useful in a number of areas. The intersection is typically a set with desirable properties but for w
The association between marital status and generalized trust in other people was investigated. The public health survey in Skane 2008 is a cross-sectional study including 28,198 persons (55% participation rate) aged 18-80 in southern Sweden. Logistic regression models investigated associations between marital status and trust, adjusting for age, country of birth, education, emotional support, inst
Sparse sums of Lorentzians can give good approximations to functions consisting of linear combination of piecewise continuous functions. To each Lorentzian, two parameters are assigned: translation and scale. These parameters can be found by using a method for complex frequency detection in the frequency domain. This method is based on an alternating projection scheme between Hankel matrices and f
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
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
Abstract in Uncoded languages Tarptautiniai klimato kaitos susitarimai ir Europos Sąjungos teisės aktai veikia skirtingus valdymo lygmenis, įskaitant nacionalines teisės sistemas ir administravimo modelius. Disertacijoje iškeltas tyrimo klausimas – Kaip Lietuva, konkrečiai pramonės sektorius, įgyvendina šiltnamio efektą sukeliančių dujų (toliau – ŠESD) emisijų mažinimo reikalavimus, nustatytus KioInternational climate change agreements and the European Union legislation have an influence on different levels of governance, including national legal systems and administrative schemes. The following research question is addressed in the doctoral dissertation: “How does Lithuania, specifically the industrial sector, implement GHG reduction requirements under the Kyoto Protocol and the European
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
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
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
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
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
