DataPro

2021 ◽  
pp. 98-108
Author(s):  
Vala Ali Rohani ◽  
Sedigheh Moghavvemi ◽  
Tiago Pinho ◽  
Paulo Caldas
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Unemployment Rate ◽  
Recommender System ◽  
Social Problems ◽  
National Level ◽  
Point Of View ◽  
Web Based ◽  
Four Dimensions ◽  
Online Portal

Due to the COVID‐19 pandemic, most countries are exposed to unprecedented social problems in the current global situation. According to the official reports, it caused a dramatic increase of 44% in graduates' unemployment rate in Portugal. Moreover, from the human resource point of view, the whole of Europe is expected to face a shortage of 925,000 data professionals by 2025. Given the existing situations, the DataPro aims to propose a national-level reskilling solution in big data to mitigate both social problems of unemployability and the shortage of data professionals in Portugal. DataPro project consists of four dimensions, including an online portal for the hiring companies and unemployed graduates, along with a web-based analytics talent upskilling (ATU) platform empowered by an artificial intelligence recommender system to match the reskilled data professionals and the hiring companies.

scholarly journals Public Health and Epidemiology Informatics

2016 ◽  
Vol 25 (01) ◽  
pp. 240-246 ◽  
Author(s):  
A. Bar-Hen ◽  
N. Paragios ◽  
A. Flahault
Keyword(s):  
Public Health ◽  
Big Data ◽  
Health Sector ◽  
Point Of View ◽  
General Point ◽  
Full Potential ◽  
Web Based ◽  
Challenging Tasks ◽  
Epidemiology Data ◽  
Using Data

Summary Objectives: The aim of this manuscript is to provide a brief overview of the scientific challenges that should be addressed in order to unlock the full potential of using data from a general point of view, as well as to present some ideas that could help answer specific needs for data understanding in the field of health sciences and epidemiology. Methods: A survey of uses and challenges of big data analyses for medicine and public health was conducted. The first part of the paper focuses on big data techniques, algorithms, and statistical approaches to identify patterns in data. The second part describes some cutting-edge applications of analyses and predictive modeling in public health. Results: In recent years, we witnessed a revolution regarding the nature, collection, and availability of data in general. This was especially striking in the health sector and particularly in the field of epidemiology. Data derives from a large variety of sources, e.g. clinical settings, billing claims, care scheduling, drug usage, web based search queries, and Tweets. Conclusion: The exploitation of the information (data mining, artificial intelligence) relevant to these data has become one of the most promising as well challenging tasks from societal and scientific viewpoints in order to leverage the information available and making public health more efficient.

scholarly journals Smart Cities, Big Data, Artificial Intelligence and Respect for the European Union Data Protection Rules

2020 ◽  
Vol 3 (2) ◽  
pp. 101
Author(s):  
Francisco Javier Durán Ruiz
Keyword(s):  
Artificial Intelligence ◽  
European Union ◽  
Big Data ◽  
Data Protection ◽  
Smart City ◽  
Smart Cities ◽  
Open Data ◽  
Personal Data ◽  
Point Of View ◽  
The European Union

The importance of cities and their populations grow more and more, as well as the need to apply ICT in their management to reduce their environmental impact and improve the services they offer to their citizens. Hence the concept of smart city arises, a transformation of urban spaces that the European Union is strongly promoting which is largely based on the use of data and its treatment using Big data and Artificial Intelligence techniques based in algorithms. For the development of smart cities it is basic, from a legal point of view, EU rules about open data and the reuse of data and the reconciliation of the massive processing of citizens' data with the right to privacy, non-discrimination and protection of personal data. The use of Big data and AI needed for the development of smart city projects requires a particular respect to data protection regulations. In this sense, the research explores in depth the specific hazards of vulnerating this fundamental right in the framework of smart cities due to the use of Big Data and AI.

scholarly journals Data Economy 2.0: From Big Data Value to AI Value and a European Data Space

2021 ◽  
pp. 379-399
Author(s):  
Sonja Zillner ◽  
Jon Ander Gomez ◽  
Ana García Robles ◽  
Thomas Hahn ◽  
Laure Le Bars ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Big Data ◽  
Point Of View ◽  
Driven Systems ◽  
Significant Growth ◽  
Data Space ◽  
European Data ◽  
Data Value ◽  
Data Volume

AbstractArtificial intelligence (AI) has a tremendous potential to benefit European citizens, economy, environment and society and already demonstrated its potential to generate value in various applications and domains. From a data economy point of view, AI means algorithm-based and data-driven systems that enable machines with digital capabilities such as perception, reasoning, learning and even autonomous decision making to support people in real scenarios. Data ecosystems are an important driver for AI opportunities as they benefit from the significant growth of data volume and the rates at which it is generated. This chapter explores the opportunities and challenges of big data and AI in exploiting data ecosystems and creating AI value. The chapter describes the European AI framework as a foundation for deploying AI successfully and the critical need for a common European data space to power this vision.

scholarly journals Tracking the New Demand for Justice in the Big Data Ecosystem

2018 ◽  
Vol 10 (1) ◽  
pp. 90
Author(s):  
Carmen Vargas Pérez ◽  
Juan Luis Peñaloza Figueroa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Welfare ◽  
Law And Economics ◽  
Point Of View ◽  
Unstructured Data ◽  
New Paradigm ◽  
Huge Amount ◽  
Equity And Efficiency ◽  
Data Ecosystem

Many studies have focused on the possibilities that organizations have to mine and analyze, through computational analytics, the huge amount of structured and unstructured data that is now available, to determine correlations and thus reveal patterns, trends, and associations to predict human behaviour; and to transform this information into knowledge for companies and governments. That is, just from the point of view of the suppliers of good and services. In this paper we contribute to the Law and Economics literature by showing that the logic of Big Data, the access to the cloud, and the use of Artificial Intelligence are drastically changing the ordinary citizen's way of making decisions in the field of justice; and that this new paradigm in the Demand for Justice will mean improvements in terms of both equity and efficiency, and ultimately an improvement in social welfare.

scholarly journals Tracking the New Demand for Justice in the Big Data Ecosystem

2018 ◽  
Vol 4 (1) ◽  
pp. 89-97
Author(s):  
Carmen Vargas Pérez ◽  
Juan Luis Peñaloza Figueroa
Keyword(s):  
Artificial Intelligence ◽  
Big Data ◽  
Social Welfare ◽  
Law And Economics ◽  
Point Of View ◽  
Unstructured Data ◽  
New Paradigm ◽  
Huge Amount ◽  
Equity And Efficiency ◽  
Data Ecosystem

Abstract Many studies have focused on the possibilities that organizations have to mine and analyze, through computational analytics, the huge amount of structured and unstructured data that is now available, to determine correlations and thus reveal patterns, trends, and associations to predict human behaviour; and to transform this information into knowledge for companies and governments. That is, just from the point of view of the suppliers of good and services. In this paper we contribute to the Law and Economics literature by showing that the logic of Big Data, the access to the cloud, and the use of Artificial Intelligence are drastically changing the ordinary citizen's way of making decisions in the field of justice; and that this new paradigm in the Demand for Justice will mean improvements in terms of both equity and efficiency, and ultimately an improvement in social welfare.

scholarly journals On Mathematical Proving

2015 ◽  
Vol 6 (1) ◽  
pp. 130-149 ◽  
Author(s):  
Petros Stefaneas ◽  
Ioannis M. Vandoulakis
Keyword(s):  
Artificial Intelligence ◽  
Mathematical Proof ◽  
Point Of View ◽  
Web Based ◽  
Traditional Concept ◽  
Starting Point ◽  
Temporal Aspects ◽  
Spatio Temporal ◽  
Logical Representation ◽  
Mathematical Proving

Abstract This paper outlines a logical representation of certain aspects of the process of mathematical proving that are important from the point of view of Artificial Intelligence. Our starting-point is the concept of proof-event or proving, introduced by Goguen, instead of the traditional concept of mathematical proof. The reason behind this choice is that in contrast to the traditional static concept of mathematical proof, proof-events are understood as processes, which enables their use in Artificial Intelligence in such contexts, in which problem-solving procedures and strategies are studied. We represent proof-events as problem-centered spatio-temporal processes by means of the language of the calculus of events, which captures adequately certain temporal aspects of proof-events (i.e. that they have history and form sequences of proof-events evolving in time). Further, we suggest a “loose” semantics for the proof-events, by means of Kolmogorov’s calculus of problems. Finally, we expose the intented interpretations for our logical model from the fields of automated theorem-proving and Web-based collective proving.

scholarly journals Til tross for økt satsning via Opptrappingsplanen, er produksjonen per fagårsverk marginalt endret innen norsk psykiatri

2014 ◽  
Vol 10 (1) ◽  
pp. 2
Author(s):  
Clas Waagø-Hansen
Keyword(s):  
National Level ◽  
Working Hours ◽  
Point Of View ◽  
Web Based ◽  
Cost Rate ◽  
Face To Face ◽  
Increase In Productivity ◽  
Working Day ◽  
The Cost ◽  
Available Resources

<p class="Toverskrift3">Abstract</p><p><strong><em>Despite an increase in resources through the national psychiatric Escalation plan, Norwegian psychiatry has only seen a marginally change in productivity per clinician</em></strong><em>.</em></p><p><em> </em></p><p><strong><em>Background</em></strong><em>: When an evaluation of the national Norwegian psychiatric Escalation plan was carried out, the conclusion was that the Norwegian Parliaments demand of a 50% increase in productivity had been achieved. The number of treated patients went from 476 000 to 1,1 million a year over a 10 year period. What wasn’t highlighted was the fact that the actual number of clinicians also almost doubled. The purpose of this study was to investigate how the accessible resources within Norwegian psychiatry was utilized, and from a society’s point of view, is it possible to achieve a true increase in productivity through better management of available resources. </em></p><p><strong><em>Method</em></strong><em>: For the analysis of resources used, the cost analytical tool TDABC was chosen. Data used was obtained from The Norwegian Directorate of Health, Statistics Norway and a hospital trust. Clinicians at several sites were interviewed in person, and 235 clinicians completed a web-based survey in order to gain insight in an ordinary clinical working day.</em></p><p><strong><em>Results</em></strong><em>: The findings consistently indicate low productivity on a national level within hospitals. This study investigated 95 062 outpatient consultations in the mentioned Trust, and on average 75% of the working hours were not used on face-to-face patient consultations. Further, available resources were not optimally utilized, patient related outcomes were not used as a tool to adapt/tailor service offered and low productivity has on a national level gained acceptance. The national hospital productivity was on average 38% compared to the productivity by out of hospital practitioners financed by the state. These state financed practitioners have a cost rate of approximately 14%-21% compared to practitioners in hospitals.</em></p><p><strong><em>Implications</em></strong><em>: If the issues highlighted in this study are addressed, the productivity within Norwegian psychiatry should be able to meet and excel the demands set forth by the Norwegian Parliament. Such an outcome would require appropriate management on all levels within the service.</em></p>

A Study on the Development of Appointment Algorithm of CT With Big Data using AI (Artificial Intelligence)

2018 ◽  
Vol 20 (2) ◽  
pp. 1-5
Author(s):  
Sang-ho Jeon ◽  
Sung-yeul Yang ◽  
In-beom Shin ◽  
Dae-mok Son ◽  
Tae-han Kwon ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Big Data

Innovative Marketing Strategies for Select E-Commerce Companies in India - A Review.

2018 ◽  
Vol 5 (1) ◽  
Author(s):  
Amit Kumar Bhanja ◽  
P.C Tripathy
Keyword(s):  
Artificial Intelligence ◽  
Internet Of Things ◽  
Business Environment ◽  
Marketing Strategies ◽  
Point Of View ◽  
Digital Marketing ◽  
Customer Base ◽  
Innovative Methods ◽  
Online Shoppers ◽  
Drastic Increase

Innovation is the key to opportunities and growth in today’s competitive and dynamic business environment. It not only nurtures but also provides companies with unique dimensions for constant reinvention of the existing way of performance which enables and facilitates them to reach out to their prospective customers more effectively. It has been estimated by Morgan Stanley that India would have 480 million shoppers buying products online by the year 2026, a drastic increase from 60 million online shoppers in the year 2016. E-commerce companies are aggressively implementing innovative methods of marketing their product offerings using tools like digital marketing, internet of things (IoT)and artificial intelligence to name a few. This paper focuses on outlining the innovative ways of marketing that the E-Commerce sector implements in orders to increase their customer base and aims at determining the future scope of this area. A conceptual comparative study of Amazon and Flipkart helps to determine which marketing strategies are more appealing and beneficial for both the customers and companies point of view.

Sign in / Sign up

Export Citation Format

Share Document