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SWUFE 2019 Summer School

Written on March 14, 2019.

SWUFE 2019 Summer School

Agora University is partner of Southwestern University of Finance and Economics, Chengdu, China (SWUFE).

On May 19, 2013, Agora University of Oradea, Romania and The Southwestern University of Finance and Economics (SWUFE) in Chengdu, China has signed an Agreement of Cooperation including visits and training periods for the students.

SWUFE offer two fee-waived places to each partner university of SWUFE (with signed agreements or prospective partners). The applicants  from Agora University for SWUFE2019 must contact before their deans.

In 2019 a targeted program of focused academic content will be complementing the rich cultural exchange experiences. Students will be evaluated and certificated based on their contributions and performance within the academic, helping recognize the importance of the academic exchange within their personal academic development.

The Discover SWUFE International Summer School is one of the signature events in the university calendar, bringing together 80 of the top student ambassadors from throughout the SWUFE global network for an extraordinary 14 day program from July 14th to July 27th, 2019. During this unique experience we offer you an authentic ‘taste’ of modern day life in China, a chance to learn more about Chengdu, to foster a better understanding of business innovation and entrepreneurship, and giving you a short but wonderful experience at SWUFE.

As one of China’s leading universities in the fields of finance, economics and management, SWUFE is centrally located within China. The university is based in Chengdu, the capital city of Sichuan province, known internationally for its rich and culturally significant history, rapid internationalization, unique Sichuan foods, and being the home of the giant panda. Through this event we will get the special chance to communicate and learn from each other and also make a few new friends along the way.

The 2019 Discover SWUFE international summer school will offer a unique opportunity to experience SWUFE and China, and more than this it will provide a platform to explore approaches to innovation and entrepreneurship by young international professionals.

Why to join the Discover SWUFE International Summer School?

·        An opportunity to visit Chengdu, one of China’s most rapidly expanding cities and host for the Summer School;

·        A comprehensive 2-week program immersing students in business education in China context with corporate experience;

·        A variety of curricular and cultural activities featuring lectures, workshop, company visits, sightseeing, cultural night and social events.

·        A diverse student body of the brightest young talents from the leading universities across continents;

·        A Certificate from SWUFE and 2 credits to serve as a permanent record for your academic achievements and active engagement during this memorable experience.

Who should apply?

Open to FULL-TIME undergraduate and post-graduate university students currently enrolled

Participants are required to be adults aged at or above 18.

How to apply?

Students interested in applying to the program should follow the steps outlined below:

l  Complete the online registration at

http://admission.swufe.edu.cn/member/login.do by 30th April, 2019.

l  Shortlisted candidates will be notified by the Discover SWUFE selection committee within two weeks of the application deadline.

For your reference, the following documents  can be  downloaded via the website http://e.swufe.edu.cn/ADMISSIONS/Discover_SWUFE_International_Summer_School.htm :

1. 2019 Discover SWUFE International Summer School Brochure
2. 2019 Discover SWUFE International Summer School Syllabus
3. Discover SWUFE Online Application Guideline

For any enquiries, please

contact us at discover@swufe.edu.cn

U-Multirank 2018

Written on June 11, 2018.

U-Multirank 2018

Agora University of Oradea

Agora University of Oradea is one of 44 universities included in U-Multirank for Romania. Agora University of Oradea is a small private university located in Oradea. It was founded in 2012. With regard to the scope of its subjects and degree programmes offered, the Agora University of Oradea is a specialised institution. It is characterised by a none percentage of international students. As made clear by its sunburst chart – a snapshot illustration of the university’s performance profile across the five U-Multirank dimensions. It’s overall profile shows top performance across various indicators, with 2 ‘A’ (very good) scores. For a comprehensive overview of this university’s performance, see its complete performance scores in the tables below.

https://www.umultirank.org/study-at/agora-university-of-oradea

ITQM2018

Written on May 28, 2018.

ITQM2018

Accepted Special Session at ITQM2018

The Sixth International Conference on Information Technology and Quantitative Management

Special Session 01: Soft computing methods in quantitative management and decision making processes

October, 21-22, Omaha, Nebraska, USA

Organizers:

Ioan Dzitac, Aurel Vlaicu University of Arad & Agora University of Oradea, Romania, professor.ioan.dzitac@ieee.org

Florin Gheorghe Filip,Romanian Academy, Romania, ffilip@acad.ro

Misu-Jan Manolescu, Agora University of Oradea, Romania, mmj@univagora.ro

Simona Dzitac,University of Oradea, Romania, simona@dzitac.ro

Session scope

In 1965 Lotfi A. Zadeh published "Fuzzy Sets", his pioneering and controversial paper, that now reaches over 101,000 citations. All Zadeh’s papers were cited over 195,000 times. Starting from the ideas presented in that paper, Zadeh founded later the Fuzzy Logic theory, that proved to have useful applications, from consumer to industrial intelligent products. We are presenting general aspects of Zadeh’s contributions to the development of Soft Computing(SC) and Artificial Intelligence(AI).
In accordance with Zadeh’s definition, Soft Computing (SC) consist of computational techniques in computer science, machine learning and some engineering disciplines, which study, model, and analyze very complex reality: those for which more traditional methods have unusable or inefficiently.
SC uses soft techniques, contrasting it with classical artificial intelligence, Hard Computing (HC) techniques), and includes: Fuzzy Logic, Neural Computing, Evolutionary Computation, Machine Learning, and Probabilistic Reasoning.
HC is bound by a Computer Science (CS) concept called NP-Complete, which means that there is a direct connection between the size of a problem and the amount of resources needed to solve that called "grand challenge problem". SC aids to surmount NP-complete problems by using inexact methods to give useful but inexact answers to intractable problems.
SC became a formal CS area of study in the early 1990’s. Earlier computational approaches could model and precisely analyze only relatively simple systems. More complex systems arising in biology, medicine, the humanities, management sciences, and similar fields often remained intractable to HC. It should be pointed out that simplicity and complexity of systems are relative, and many conventional mathematical models have been both challenging and very productive.
SC techniques resemble biological processes more closely than traditional techniques, which are largely based on formal logical systems, such as Boolean logic, or rely heavily on computer-aided numerical analysis (as in finite element analysis).
SC techniques are intended to complement HC techniques. Unlike HC schemes, which strive for exactness and full truth, soft computing techniques exploit the given tolerance of imprecision, partial truth, and uncertainty for a particular problem. The inductive reasoning plays a larger role in SC than in HC. SC and HC can be used together in certain fusion techniques.
Soft Computing can deal with ambiguous or noisy data and is tolerant of imprecision, uncertainty, partial truth, and approximation. In effect, the role model for SC is the human mind.
Artificial Intelligence and Computational Intelligence based on SC provide the background for the development of smart management systems and decisions in case of ill-posed problems.
The goal of this special session is to bring together researchers interested in applications of soft computing algorithms and procedures in quantitative management and decision making, in order to exchange ideas on problems, solutions, and to work together in a friendly environment.
Decision making in fuzzy environments In many real-world situations, the problems of decision making are subjected to some constraints, objectives and consequences that are not accurately known. After Bellman and Zadeh introduced for the first time (1970) fuzzy sets within multiple-criteria decision-making (MCDM), many researchers have been preoccupied by decision making in fuzzy environments.
The fusion between MCDM and fuzzy set theory has led to a new decision theory, known today as fuzzy multi-criteria decision making (FMCDM), where we have decision-maker models that can deal with incomplete and uncertain knowledge and information. The most important thing is that, when we want to assess, judge or decide we usually use a natural language in which the words do not have a clear, definite meaning. As a result, we need fuzzy numbers to express linguistic variables, to describe the subjective judgement of a decision maker in a quantitative manner. Fuzzy numbers (FN) most often used are triangular FN, trapezoidal FN and Gaussian FN.
We highlight that the concept of linguistic variable introduced by Lotfi A. Zadeh in 1975 allows computation with words instead of numbers and thus linguistic terms defined by fuzzy sets are intensely used in problems of decision theory for modelling uncertain information.
Topics of interest include, but are not limited to, the following:
  • Ant colony optimization algorithms;
  • Artificial intelligence methods for web mining;
  • Bayesian networks and decision graphs; Computational intelligence methods for data mining;
  • Decision support systems for quantitative management;
  • Decision making with missing and/or uncertain data;
  • Fuzzy multi-criteria decision making;
  • Fuzzy and neuro-fuzzy modelling and simulation;
  • Fuzzy numbers applications to decision making;
  • Fuzzy-sets-based models in operation research;
  • Knowledge Discovery in Databases;
  • Machine learning for intelligent support of quantitative management;
  • Neural networks in decision making tools;
  • Smarter decisions;
  • Support Vector Machine in SC applications.
Bibliography Ioan Dzitac, Florin Gheorghe Filip, Misu-Jan Manolescu, Fuzzy Logic Is Not Fuzzy: World-renowned Computer Scientist Lotfi A. Zadeh, International Journal of Computers Communications & Control, ISSN 1841-9836, 12(6), 748-789, December 2017. DOI: https://doi.org/10.15837/ijccc.2017.6.3111

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