pinecone/core-2020-05-10-deduplication huggingface dataset:
Mobile Communication Signatures of Unemployment

The mapping of populations socio-economic well-being is highly constrained by
the logistics of censuses and surveys. Consequently, spatially detailed changes
across scales of days, weeks, or months, or even year to year, are difficult to
assess; thus the speed of which policies can be designed and evaluated is
limited. However, recent studies have shown the value of mobile phone data as
an enabling methodology for demographic modeling and measurement. In this work,
we investigate whether indicators extracted from mobile phone usage can reveal
information about the socio-economical status of microregions such as districts
(i.e., average spatial resolution < 2.7km). For this we examine anonymized
mobile phone metadata combined with beneficiaries records from unemployment
benefit program. We find that aggregated activity, social, and mobility
patterns strongly correlate with unemployment. Furthermore, we construct a
simple model to produce accurate reconstruction of district level unemployment
from their mobile communication patterns alone. Our results suggest that
reliable and cost-effective economical indicators could be built based on
passively collected and anonymized mobile phone data. With similar data being
collected every day by telecommunication services across the world,
survey-based methods of measuring community socioeconomic status could
potentially be augmented or replaced by such passive sensing methods in the
future
On Profiling Bots in Social Media

The popularity of social media platforms such as Twitter has led to the
proliferation of automated bots, creating both opportunities and challenges in
information dissemination, user engagements, and quality of services. Past
works on profiling bots had been focused largely on malicious bots, with the
assumption that these bots should be removed. In this work, however, we find
many bots that are benign, and propose a new, broader categorization of bots
based on their behaviors. This includes broadcast, consumption, and spam bots.
To facilitate comprehensive analyses of bots and how they compare to human
accounts, we develop a systematic profiling framework that includes a rich set
of features and classifier bank. We conduct extensive experiments to evaluate
the performances of different classifiers under varying time windows, identify
the key features of bots, and infer about bots in a larger Twitter population.
Our analysis encompasses more than 159K bot and human (non-bot) accounts in
Twitter. The results provide interesting insights on the behavioral traits of
both benign and malicious bots
Lightweight Interactions for Reciprocal Cooperation in a Social Network
  Game

The construction of reciprocal relationships requires cooperative
interactions during the initial meetings. However, cooperative behavior with
strangers is risky because the strangers may be exploiters. In this study, we
show that people increase the likelihood of cooperativeness of strangers by
using lightweight non-risky interactions in risky situations based on the
analysis of a social network game (SNG). They can construct reciprocal
relationships in this manner. The interactions involve low-cost signaling
because they are not generated at any cost to the senders and recipients.
Theoretical studies show that low-cost signals are not guaranteed to be
reliable because the low-cost signals from senders can lie at any time.
However, people used low-cost signals to construct reciprocal relationships in
an SNG, which suggests the existence of mechanisms for generating reliable,
low-cost signals in human evolution.Comment: 13 pages, 2 figure
Generation of Spatially Embedded Random Networks to Model Complex
  Transportation Networks

Random networks are increasingly used to analyse complex transportation
networks, such as airline routes, roads and rail networks. So far, this
research has been focused on describing the properties of the networks with the
help of random networks, often without considering their spatial properties. In
this article, a methodology is proposed to create random networks conserving
their spatial properties. The produced random networks are not intended to be
an accurate model of the real-world network being investigated, but are to be
used to gain insight into the functioning of the network taking into
consideration its spatial properties, which has potential to be useful in many
types of analysis, e.g. estimating the network related risk. The proposed
methodology combines a spatial non-homogeneous point process for vertex
creation, which accounts for the spatial distribution of vertices, considering
clustering effects of the network and a hybrid connection model for the edge
creation. To illustrate the ability of the proposed methodology to be used to
gain insight into a real world network, it is used to estimate standard
structural statistics for part of the Swiss road network, and these are then
compared with the known values.Comment: 7 pages, 4 figures, 2 table
Methodology for evaluating the safety level of current accepted design solutions for limiting fire spread between buildings

External fire spread between buildings is internationally considered as a major concern for buildings in dense urban environments. While design guidelines differ between countries, the fundamental methods currently used for limiting the risk of fire spread between buildings are generally limited to specifying the minimum required separation distance for a given unprotected façade area, or conversely, limiting the maximum allowable unprotected façade area for a giv-en separation distance. The safety level associated with the current design guidelines is however unknown, making the implementation of innovative, saf-er and more cost-effective design solutions difficult. In order to assess the safe-ty target implicitly incorporated in currently accepted design solutions, a meth-odology is developed for evaluating the annual probability of reaching unac-ceptable radiation intensities at the opposite façade. As a case study, the meth-odology is applied to a design which is in agreement with the current UK re-quirements specified in BR 187. This case study exposes inconsistencies in the current design guidelines, indicating the need for developing explicit safety targets
Is This a Joke? Detecting Humor in Spanish Tweets

While humor has been historically studied from a psychological, cognitive and
linguistic standpoint, its study from a computational perspective is an area
yet to be explored in Computational Linguistics. There exist some previous
works, but a characterization of humor that allows its automatic recognition
and generation is far from being specified. In this work we build a
crowdsourced corpus of labeled tweets, annotated according to its humor value,
letting the annotators subjectively decide which are humorous. A humor
classifier for Spanish tweets is assembled based on supervised learning,
reaching a precision of 84% and a recall of 69%.Comment: Preprint version, without referra
Evaluating the social acceptability of voice based smartwatch search

There has been a recent increase in the number of wearable (e.g. smartwatch, interactive glasses, etc.) devices available. Coupled with this there has been a surge in the number of searches that occur on mobile devices. Given these trends it is inevitable that search will become a part of wearable interaction. Given the form factor and display capabilities of wearables this will probably require a different type of search interaction to what is currently used in mobile search. This paper presents the results of a user study focusing on users’ perceptions of the use of smartwatches for search. We pay particular attention to social acceptability of different search scenarios, focussing on in-put method, device form and information need. Our findings indicate that audience and location heavily influence whether people will perform a voice based search. The results will help search system developers to support search on smartwatches
Assessing the authors of online books in digital libraries using users affinity

Information quality generated by crowd-sourcing platforms is a major concern. Incomplete or inaccurate user-generated data prevent truly comprehensive analysis and might lead to inaccurate reports and forecasts. In this paper, we address the problem of assessing the authors of users generated published books in digital libraries. We propose to model the platform using an heterogeneous graph representation and to exploit both the users’ interests and the natural inter-users affinities to infer the authors of unlabelled books. We formalize the task as an optimization problem and integrate in the objective a prior of consistency associated to the networked users in order to capture the neighboors’ interests. Experiments conducted over the Babellio platform (http://babelio.com/), a French crowd-sourcing website for book lovers, achieved successful results and confirm the interest of considering an affinity-base
Characterization of Microstructure and Mechanical Properties of Direct Metal Laser Sintered 15–5 PH1 Stainless Steel Powders and Components

15–5 PH1 stainless steel powder is one of the common materials used for the DMLS process. In this study, both the powder and parts fabricated via DMLS have been characterized. The microstructure and elemental composition have been examined. The microhardness and surface roughness have also been measured. The results show that most powder particle are in spherical with a particle size of 5 ~ 60 μm. Chemical compositions of the powder compare well with the literature data. The thickness of rough surface is about 1 μm. The measured Rockwell hardness is HRC 42.9±0.3, which is also in good agreement with literature
Anticorrosion Performance of Solanum Aethiopicum on Steel-Reinforcement in Concrete Immersed in Industrial/Microbial Simulating-Environment

This paper investigates anticorrosion performance of Solanum aethiopicum leaf-extract on steel-reinforcement in concrete immersed in 0.5 M H2SO4, simulating industrial/microbial environment. For this, corrosion rate by linear polarisation resistance and corrosion potential as per ASTM C876-91 R99 were monitored from steel-reinforced concrete slabs admix ed with different Solanum aethiopicum leaf-extract concentrations and immersed in the acidic test-environment. Obtained test-data were subjected to statistical probability distributions for which compatibilities were tested using Kolmogorov-Smirnov goodness-of-fit statistics, as per ASTM G16-95 R04. These identified all datasets of corrosion test-data, from the steel-reinforced concrete samples, as coming from the Weibull probability distribution. Analysed results showed that Solanum aethiopicum leaf-extract reduced rebar corrosion condition from “high” to “low” corrosion risks of ASTM C876-91 R99. Also, the corrosion rate analyses identified 0.25% Solanum aethiopicum leaf-extract with optimal inhibition efficiency performance, η = 93.99%, while the other concentrations also exhibited good inhibition of steel-reinforcement corrosion in the test-environment
M2D: Monolog to Dialog Generation for Conversational Story Telling

Storytelling serves many different social functions, e.g. stories are used to
persuade, share troubles, establish shared values, learn social behaviors, and
entertain. Moreover, stories are often told conversationally through dialog,
and previous work suggests that information provided dialogically is more
engaging than when provided in monolog. In this paper, we present algorithms
for converting a deep representation of a story into a dialogic storytelling,
that can vary aspects of the telling, including the personality of the
storytellers. We conduct several experiments to test whether dialogic
storytellings are more engaging, and whether automatically generated variants
in linguistic form that correspond to personality differences can be recognized
in an extended storytelling dialog
Enterprise Modelling for the Masses – From Elitist Discipline to Common Practice

Enterprise modelling (EM) as a discipline has been around for several decades with a huge body of knowledge on EM in academic literature. The benefits of modelling and its contributions to organizational tasks are largely undisputed. Thus, from an inside-out perspective, EM appears to be a mature and established discipline. However, for initiating serious innovations this view is not sufficient. This position paper takes an outside-in perspective on enterprise modelling and argues that EM is far away from reaching its maximum potential. EM is typically done by a limited number of people in organizations inclined to methods and modelling. What is captured in models is only a fragment of what ought to be captured. Many people actually develop some kind of model in their local practice without thinking about it consciously. Exploiting the potential of this “grass roots modelling” could lead to groundbreaking innovations in EM. The aim is to investigate integration of the established, often systematic and formalized practices of modelling in enterprises with local practices of creating, using and communicating modellike artifacts or objects of relevance for the overall organization
A 3D visualization approach for process training in office environments

Process participants need to learn how to perform in the context of their business processes. Process training is challenging due to cognitive difficulties in relating process model elements to real world concepts. In this paper we present a 3D Virtual World (VW) process training approach for office environments. In this VW, process participants can experience a process in an immersive environment. They inter- act with VW representations of process elements in changing locations, based on process activities. By means of embodied 3D representation, deep immersion and engagement in this environment, enhancements in long term memory learning and episodic memory usage for knowledge retrieval are expected. Our illustration of an example process model shows the applicability of the approach. We list a number of future directions to extend the use and the benefits
An introduction to integrable techniques for one-dimensional quantum
  systems

This monograph introduces the reader to basic notions of integrable
techniques for one-dimensional quantum systems. In a pedagogical way, a few
examples of exactly solvable models are worked out to go from the coordinate
approach to the Algebraic Bethe Ansatz, with some discussion on the finite
temperature thermodynamics. The aim is to provide the instruments to approach
more advanced books or to allow for a critical reading of research articles and
the extraction of useful information from them. We describe the solution of the
anisotropic XY spin chain; of the Lieb-Liniger model of bosons with contact
interaction at zero and finite temperature; and of the XXZ spin chain, first in
the coordinate and then in the algebraic approach. To establish the connection
between the latter and the solution of two dimensional classical models, we
also introduce and solve the 6-vertex model. Finally, the low energy physics of
these integrable models is mapped into the corresponding conformal field
theory. Through its style and the choice of topics, this book tries to touch
all fundamental ideas behind integrability and is meant for students and
researchers interested either in an introduction to later delve in the advance
aspects of Bethe Ansatz or in an overview of the topic for broadening their
culture.Comment: 137 pages, with several figures. Minor corrections over the published
  version. Comments are always welcome
Implementation of Scan-to-BIM and FEM for the documentation and analysis of heritage timber roof structures

Current heritage analysis applications and documentation techniques for timber roof structures rely on manual measurements to provide the spatial data. Major implifications are made to document these structures efficiently. However, these simplified geometric models provide
less reliable results. Therefore, the need exists for more realistic models. Additionally, the exchangeability of information between varying parties is paramount. Hence, the construction elements should be defined
in a Building Information Model (BIM). This allows users to reuse the model, allowing the distribution of information throughout the project. The goal of our research is to create a realistic BIM model of a complex
heritage roof structure employing dense point clouds. The comparison of our complex geometric model to a traditional wire-frame model proves that our approach provides more reliable results in terms of geometry and structural behaviour. Our work covers the acquisition, the modelling and the structural analysis of timber roof structures.status: publishe
Building information modelling – A novel parametric modeling approach based on 3D surveys of historic architecture

Building Information Modelling (BIM) appears to be the best answer to simplify the traditional process of design, construction, management and maintenance. On the other hand, the intricate reality of the built heritage and the growing need to represent the actual geometry using 3D models collide with the new paradigms of complexity and accuracy, opening a novel operative perspective for restoration and conservation. The management of complexity through BIM requires a new management approach focused on the development of improve the environmental impact cost, reduction and increase in productivity and efficiency the Architecture, Engineering and Construction (AEC) Industry. This structure is quantifiable in morphological and typical terms by establishing levels of development and detail (LoDs) and changes of direction (ReversLoDs) to support the different stages of life cycle (LCM). Starting from different experiences in the field of HBIM, this research work proposes a dynamic parametric modeling approach that involves the use of laser scanning, photogrammetric data and advanced modelling for HBIM
AI Researchers, Video Games Are Your Friends!

If you are an artificial intelligence researcher, you should look to video
games as ideal testbeds for the work you do. If you are a video game developer,
you should look to AI for the technology that makes completely new types of
games possible. This chapter lays out the case for both of these propositions.
It asks the question "what can video games do for AI", and discusses how in
particular general video game playing is the ideal testbed for artificial
general intelligence research. It then asks the question "what can AI do for
video games", and lays out a vision for what video games might look like if we
had significantly more advanced AI at our disposal. The chapter is based on my
keynote at IJCCI 2015, and is written in an attempt to be accessible to a broad
audience.Comment: in Studies in Computational Intelligence Studies in Computational
  Intelligence, Volume 669 2017. Springe
Field of research in sustainable manufacturing

Sustainability has raised significant attention in manufacturing research over the last decades and has become a significant driver of the development of innovative technologies and management concepts. The current chapter aims to provide a structured overview of the wide field of research in sustainable manufacturing with a particular focus on manufacturing technology and management. It intends to describe the role of manufacturing in sustainability, outline the complementary approaches necessary for a transition to sustainable manufacturing and specify the need for engaging in interdisciplinary research. Based on a literature review, it provides a structuring framework defining four complementary areas of research focussing on analysis, synthesis and transition solutions. The challenges of the four areas of research manufacturing technologies (“how things are produced”), product development (“what is being produced”), value creation networks (“in which organisational context”) and global manufacturing impacts (“how to make a systemic change”) are highlighted and illustrated with examples from current research initiatives
Future of business models in manufacturing

In order to achieve systematic change in pursuit of sustainable manufacturing, both a strategic long-term perspective employing methods from future studies and a concrete implementation of the knowledge gained in sustainable business models are necessary. In this chapter, the concepts and exemplary methods for sustainable business model innovation are introduced with a special focus on sustainable manufacturing. Circular Economy-based business models and Product Service Systems are explained as examples of sustainable business models, along with a deduction of sustainability factors for both examples. The fruitful combination of future studies and sustainable business model development is illustrated in the example of a so-called living factory, a modular and adaptive production environment which integrates aspects of Circular Business Models and Product Service Systems
Material reutilization cycles across industries and production lines

The concept of Industrial Symbiosis aims at organizing industrial activity like a living ecosystem where the by-product outputs of one process are used as valuable raw material input for another process. A significant method for the systematic planning of Industrial Symbiosis is found in input–output matching, which is aimed at collecting material input and output data from companies, and using the results to establish links across industries. The collection and classification of data is crucial to the development of synergies in Industrial Symbiosis. Public and private institutions involved in the planning and development of Industrial Symbiosis rely however on manual interpretation of information in the course of creating synergies. Yet, the evaluation and analysis of these data sources on Industrial Symbiosis topics is a tall order. Within this chapter a method is presented which describes value creation activities according to the Value Creation Module (VCM). They are assessed before they are integrated in Value Creation Networks (VCNs), where alternative uses for by-products are proposed by means of iterative input-output matching of selected value creation factors
Life cycle sustainability assessment approaches for manufacturing

Sustainability assessments considering the three dimensions environment, economy, and society are needed to evaluate manufacturing processes and products with regard to their sustainability performance. This chapter focuses on Life Cycle Sustainability Assessment (LCSA), which considers all three sustainability dimensions by combining the three methods life cycle assessmentLCA, life cycle costingLCC, and Social Life Cycle Assessment (SLCA). Existing LCSA approaches as well as selected ongoing work are introduced, both regarding the individual approaches as well as the combined LCSA approach. This includes, for instance, the Tiered Approach. This approach facilitates the implementation of LCSA, for instance, within the manufacturing sector, by providing a category hierarchy and guiding practitioners through the various impact and cost categories proposed for the three methods. Furthermore, ongoing developments in LCC and SLCA are presented, such as the definition of first economic and social impact pathways (linking fair wage and level of education to social damage levels) for addressing the current challenges of missing impact pathways for economic and social aspects. In addition, the Sustainability Safeguard Star suggests a new scheme for addressing the inter-linkages between the three sustainability dimensions. These approaches foster the application and implementation of LCSA and thus contribute to developing sustainable processes and products