The document discusses using machine learning algorithms to analyze the relationship between economic freedom and quality of life. It examines the Economic Freedom of the World index and the Human Development Index with modern machine learning methods. The analysis finds that these advanced algorithms achieve a stronger correlation between the indices than statistical means alone. However, there is still some room for non-liberal interpretations of how to design economic policies to improve people's lives. The goal is to objectively evaluate the impact of economic freedom through a data-driven approach.

1. International Journal on Soft Computing, Artificial
Intelligence and Applications (IJSCAI)
ISSN : 2319 - 1015 [Online]; 2319 - 4081 [Print].
http://airccse.org/journal/ijscai/index.html
Current Issue :
November 2018, Volume 7, Number 4
-- Table of Contents
http://airccse.org/journal/ijscai/current2018.html

2. Paper 01
INTELLIGENT ELECTRICAL MULTI OUTLETS CONTROLLED
AND ACTIVATED BY A DATA MINING ENGINE ORIENTED TO
BUILDING ELECTRICAL MANAGEMENT
Alessandro massaro, giacomo meuli and angelo galiano,
dyrecta lab, italy
ABSTRACT
In the proposed paper are discussed results of an industry project concerning energy
management in building. Specifically the work analyses the improvement of electrical
outlets controlled and activated by a logic unit and a data mining engine. The engine executes
a Long Short-Terms Memory (LSTM) neural network algorithm able to control, to activate
and to disable electrical loads connected to multiple outlets placed into a building and having
defined priorities. The priority rules are grouped into two level: the first level is related to
the outlet, the second one concerns the loads connected to a single outlet. This algorithm,
together with the prediction processing of the logic unit connected to all the outlets, is
suitable for alerting management for cases of threshold overcoming. In this direction is
proposed a flow chart applied on three for three outlets and able to control load matching
with defined thresholds. The goal of the paper is to provide the reading keys of the data
mining outputs useful for the energy management and diagnostic of the electrical network
in a building. Finally in the paper are analyzed the correlation between global active power,
global reactive power and energy absorption of loads of the three intelligent outlet. The
prediction and the correlation analyses provide information about load balancing, possible
electrical faults and energy cost optimization.
KEYWORDS
Intelligent Electrical Outlets, Energy Management, Load Monitoring and Piloting, Smart
Grids, Energy Routing, Data Mining, KNIME, Long Short-Term Memory (LSTM), Neural
Network, Correlation Matrix.
For more details : http://aircconline.com/ijscai/V7N4/7418ijscai01.pdf
Volume link: http://airccse.org/journal/ijscai/current2018.html

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CorrespondingAuthor
Alessandro Massaro: Research & Development Chief of Dyrecta Lab s.r.l.

7. Paper 02
FORECASTING MACROECONOMICAL INDICES WITH
MACHINE LEARNING : IMPARTIAL ANALYSIS OF THE
RELATION BETWEEN ECONOMIC FREEDOM AND
QUALITY OF LIFE
Jonathan Staufer and Patricia Brockmann, Technische Hochschule
Nurnberg, Germany
ABSTRACT
The importance of economic freedom has often been stressed by supporters of liberalism, but
can its actual effect be observed in a data driven, objective way? To analyze this relation the
Economic Freedom of the World (EFW) index and the Human Development Index (HDI) were
examined with modern machine learning algorithms and a wide-ranging approach. Considering
the EFW index’s preference of a liberalistic oriented economic policy, an objective
recommendation for creating an economic policy that improves people’s everyday lives might
be derived by the analysis results. It was found that these more advanced algorithms achieve a
considerably stronger correlation between both indices than pure statistical means yet leave a
small room for interpretation towards a counter-liberalistic implementation of demand-driven
economic policy.
KEYWORDS
Data Mining, Machine Learning, Neural Networks, Economic Freedom of the World Index,
Human Development Index
For more details:http://aircconline.com/ijscai/V7N4/7418ijscai02.pdf
Volume link: http://airccse.org/journal/ijscai/current2018.html

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Authors
Jonathan Staufer completed his Bachelor of Science and Master of Science Degrees in Information
Systems at the Technische Hochschule Nuernberg
Patricia Brockmann is a professor for Information Systems at the Technische Hochschule Nuernberg,
Germany

12. Paper 03
DESIGN AND IMPLEMENTATION OF SMART COOKING BASED
ON AMAZON ECHO
Lin Xiaoguang1,2,3, Yang Yong3 and Zhang Ju1,3, 1University of
Chinese Academy of Sciences, China, 2Chinese Academy
of Sciences - Chengdu, China and 3Chinese Academy of Sciences -
Chongqing, China
ABSTRACT
Smart cooking based on Amazon Echo uses the internet of things and cloud computing to assist
in cooking food. People may speak to Amazon Echo during the cooking in order to get the
information and situation of the cooking. Amazon Echo recognizes what people say, then
transfers the information to the cloud services, and speaks to people the results that cloud
services make by querying the embedded cooking knowledge and achieving the information of
intelligent kitchen devices online. An intelligent food thermometer and its mobile application
are well-designed and implemented to monitor the temperature of cooking food.
KEYWORDS
Smart Cooking, Things of Internet, Cloud Services, Smart Home.
For More details ; http://aircconline.com/ijscai/V7N4/7418ijscai03.pdf
Volume Link: http://airccse.org/journal/ijscai/current2018.html

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Authors
Lin Xiaoguang
Lin Xiaoguang is a Ph.D. candidate in University of Chinese Academy of Sciences.