Big Data in the Field of Civil Security Research

2016 ◽  
Vol 7 (1) ◽  
pp. 54-64 ◽  
Author(s):  
Julia Gonschorek ◽  
Anja Langer ◽  
Benjamin Bernhardt ◽  
Caroline Räbiger
Keyword(s):  
Big Data ◽  
Temporal Distribution ◽  
Tactical Planning ◽  
Fire Departments ◽  
Prevention Measures ◽  
Scientific Contribution ◽  
Security Research ◽  
Geovisual Analytics ◽  
The University ◽  
Selection Of

This article gives insight in a running dissertation at the University in Potsdam. Point of discussion is the spatial and temporal distribution of emergencies of German fire brigades that have not sufficiently been scientifically examined. The challenge is seen in Big Data: enormous amounts of data that exist now (or can be collected in the future) and whose variables are linked to one another. These analyses and visualizations can form a basis for strategic, operational and tactical planning, as well as prevention measures. The user-centered (geo-) visualization of fire brigade data accessible to the general public is a scientific contribution to the research topic 'geovisual analytics and geographical profiling'. It may supplement antiquated methods such as the so-called pinmaps as well as the areas of engagement that are freehand constructions in GIS. Considering police work, there are already numerous scientific projects, publications, and software solutions designed to meet the specific requirements of Crime Analysis and Crime Mapping. By adapting and extending these methods and techniques, civil security research can be tailored to the needs of fire departments. In this paper, a selection of appropriate visualization methods will be presented and discussed.

scholarly journals Beyond the Islamicate Chancery: Archives, Paperwork, and Textual Encounters across Eurasia, a Preface

Itinerario ◽  
2020 ◽  
Vol 44 (3) ◽  
pp. 471-473
Author(s):  
Paolo Sartori
Keyword(s):  
Cultural Encounters ◽  
University Of Pittsburgh ◽  
The Third ◽  
Austrian Academy ◽  
Iranian Studies ◽  
Technical Discipline ◽  
The University ◽  
Academy Of Sciences ◽  
The Relationship ◽  
Selection Of

AbstractThis thematic issue of Itinerario brings together a selection of papers presented at the international conference Beyond the Islamicate Chancery: Archives, Paperwork, and Textual Encounters across Eurasia, which was held at the Austrian Academy of Sciences in Vienna in early October 2018. The conference was the third instalment in a series of collaborations between the Institute of Iranian Studies at the Austrian Academy of Sciences and the University of Pittsburgh examining Islamicate cultures of documentation from different angles. Surviving precolonial and colonial chancery archives across Eurasia provide an unparalleled glimpse into the inner workings of connectivity across writing cultures and, especially, documentary practices. This particular meeting has attempted to situate what has traditionally been a highly technical discipline in a broader historical dialogue on the relationship between state power, the archive, and cultural encounters.

First person – Fanny Jaudon and Martina Albini

2021 ◽  
Vol 134 (16) ◽  
Keyword(s):  
Neurotrophic Factor ◽  
Neurological Disorders ◽  
Molecular Mechanisms ◽  
Neurological Diseases ◽  
Early Career ◽  
First Person ◽  
Early Career Researchers ◽  
And Function ◽  
The University ◽  
Selection Of

ABSTRACT First Person is a series of interviews with the first authors of a selection of papers published in Journal of Cell Science, helping early-career researchers promote themselves alongside their papers. Fanny Jaudon and Martina Albini are co-first authors on ‘ A developmental stage- and Kidins220-dependent switch in astrocyte responsiveness to brain-derived neurotrophic factor’, published in JCS. Fanny is a postdoc at the University of Trieste in the lab of Lorenzo A. Cingolani at Center for Synaptic Neuroscience and Technology, Istituto Italiano di Tecnologia, Genova, Italy, investigating the molecular mechanisms controlling development and function of neuronal circuits and implementing genome-editing approaches for the treatment of neurological disorders. Martina is a PhD student at the Istituto Italiano di Tecnologia in the lab of Fabio Benfenati and Fabrizia Cesca investigating neurotrophin biology and its involvement in neurological diseases.

Big Data in Cultural Tourism – Building Sustainability and Enhancing Competitiveness

2021 ◽  
Keyword(s):  
Big Data ◽  
Case Studies ◽  
Value Chain ◽  
New Technologies ◽  
Cultural Tourism ◽  
End Users ◽  
Ethical Implications ◽  
Tourism Sector ◽  
Cultural Experiences ◽  
Selection Of

The use of big data is becoming increasingly important across the tourism sector and the value chain. With this publication, UNWTO intends to provide a baseline research on using big data by tourism and culture stakeholders, in order to improve the competitiveness of cultural tourism and reinforce its sustainability. The study sets the basis to connect tourism, culture and new technologies for mutual benefits, while calling for a reflection on the ethical implications for policymakers, businesses and end-users. The selection of case studies illustrates the most frequent case-scenarios of the use of big data in cultural tourism within destinations, compiled during the research. As the new technologies are facing ever-evolving scenarios, their use will be harnessed by the tourism sector in its endeavour to innovate and provide new cultural experiences.

Model of predicting customer behavior based on big data analysis technologies

2021 ◽  
Vol 1 (2 (6)) ◽  
Author(s):  
Anastasiia Ivanitska ◽  
Dmytro Ivanov ◽  
Ludmila Zubik
Keyword(s):  
Machine Learning ◽  
Big Data ◽  
Customer Behavior ◽  
Learning Technologies ◽  
User Preferences ◽  
Data Sets ◽  
Learning Technology ◽  
Behavior Prediction ◽  
Network Information ◽  
Selection Of

The analysis of the available methods and models of formation of recommendations for the potential buyer in network information systems for the purpose of development of effective modules of selection of advertising is executed. The effectiveness of the use of machine learning technologies for the analysis of user preferences based on the processing of data on purchases made by users with a similar profile is substantiated. A model of recommendation formation based on machine learning technology is proposed, its work on test data sets is tested and the adequacy of the RMSE model is assessed. Keywords: behavior prediction; advertising based on similarity; collaborative filtering; matrix factorization; big data; machine learning

scholarly journals From the theory to practice: Five years of urban regeneration workshops

2018 ◽  
Vol 8 (3) ◽  
pp. 179
Author(s):  
Raimundo Bambó-Naya ◽  
Pablo De la Cal-Nicolás ◽  
Carmen Díez-Medina ◽  
Sergio García-Pérez ◽  
Javier Monclús-Fraga
Keyword(s):  
Urban Regeneration ◽  
Joint Work ◽  
Teaching Innovation ◽  
Academic Field ◽  
Future Challenges ◽  
Academic Courses ◽  
The Subject ◽  
The University ◽  
Previous Phase ◽  
Selection Of

The aim of this communication is to present the experience of four academic courses in the subject of Integrated Urban and Landscape Design, taught in the framework of the Master in Architecture of the School of Engineering and Architecture of the University of Zaragoza. It addresses urban regeneration interventions in vulnerable areas of the consolidated city with approaches to teaching innovation in the academic field and in the topic of user participation.The workshop methodology is explained in detail, paying more attention to the process followed than to the specific results of the workshop. The different stages of the process are presented: previous phase and selection of the study area, phase of analysis and diagnosis, phase of proposals, where a joint work is carried out with vision of action in the whole of the neighbourhood, and phase of presentation of the results to the Neighbours. Finally, some future challenges of this workshop are outlined.

scholarly journals BEAR-FP: A ROBUST FRAMEWORK FOR FLOORPLANNING

1992 ◽  
Vol 03 (01) ◽  
pp. 137-170 ◽  
Author(s):  
MASSOUD PEDRAM ◽  
ERNEST S. KUH
Keyword(s):  
Shape Function ◽  
Optimization Procedure ◽  
University Of California ◽  
Global Routing ◽  
Top Down ◽  
Function Computation ◽  
Wide Range ◽  
The University ◽  
Linear Assignment ◽  
Selection Of

This paper presents a hierarchical floorplanning approach for macrocell layouts which is based on the bottom-up clustering, shape function computation, and top-down floorplan optimization with integrated global routing and pin assignment. This approach provides means for specifying and techniques for satisfying a wide range of constraints (physical, topological, timing) and is, therefore, able to generate floorplans for a number of different layout styles. A systematic and efficient optimization procedure during the selection of suitable floorplan patterns that integrates floorplanning, global routing and pin assignment, a new pin assignment technique based on linear assignment and driven by the global routing solution and floorplan topology, and an effective timing-driven floorplanning scheme are among the other novel features of the floorplanner. These techniques have been incorporated in BEAR-FP, a macrocell layout system developed at the University of California, Berkeley. Results on various placement and floorplanning benchmarks are quite good.

scholarly journals Research and development projects fuzzy definition in the university context

2019 ◽  
Author(s):  
Dorota Kuchta
Keyword(s):  
Research Funding ◽  
Fuzzy Theory ◽  
Value Added ◽  
Project Managers ◽  
Structured Interviews ◽  
Innovative Potential ◽  
Definition Of ◽  
The University ◽  
Practical Implications ◽  
Selection Of

Purpose – research on R&D projects implemented at universities shows that many researchers feel that the requirements set on R&D project definition in the process of calls for projects brake the innovativeness and the freedom of research. Thus, the objective of the paper is to propose a soft, fuzzy set based method of R&D project definition, which would allow to evaluate projects in the stage of project calls, but at the same time would not act contrary to the research ideas of the most ingenious and innovative researchers. Research methodology – the proposal is based on the results of over 70 structured interviews with R&D project managers from Polish and French universities. The respondents expressed their critical opinion about the required definition of R&D projects in the application stage of most calls, suggested which elements should be improved and in which way. Most of them criticised the required detail level of projects description and emphasized the uncertainty present in their research. Then we propose to model this uncertainty by means of fuzzy sets. Findings – the result of the research presented in the paper is a new way of R&D project definition, based on the fuzzy theory, adjustable to each R&D project type. The new method of project definition will express the actual uncertainty and innovative potential of each R&D project and thus allow a selection of R&D projects which would maximise their contribution to the university and science development. Research limitations – the proposed approach needs to be validated and verified on the basis of a big sample of a real world R&D project, with the participation of a representative sample of researchers. Another limitation is a highly probable resistance against such an approach among the researchers and research funding institutions, as it requires a deep analysis of the planned research and its context. Practical implications – it is proposed that the method will be used by research funding institutions in project calls. This will increase the efficiency of financial resources spent on research, in terms of value-added per one dollar invested in the research. Originality/Value – the proposed method is the first approach to project definition based on fuzzy numbers and one of very few existing approaches to project definition taking uncertainty into account

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