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Bogdan
Patrut
Abstract:First pages
BRAIN: Broad Research in Artificial Intelligence and Neuroscience, Volume 8 (2017), Issue 1 (April 2017)
BRAIN vol. 8, issue 1 - April 2017
Table of Contents
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Articles
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Authors:
Nabil
M. Hewahi
, Saira
Rashid
Abstract:
Nowadays taking photos via mobile phone has become a very important part of everyone's life. Almost each and every person who has a smart phone also has thousands of photos in their mobile device. At times it becomes very difficult to find a particular photo from thousands of photos, and it takes time. This research was done to come up with an innovative solution that could solve this problem. The solution will allow the user to find the required photo by simply drawing a sketch on the objects in the required picture, for example a tree or car, etc. Two types of supervised Artificial Neural Networks are used for this purpose; one is trained to identify the handmade sketches and other is trained to identify the images. The proposed approach introduces a mechanism to relate the sketches with the images by matching them after training. The experimentation results for testing the trained neural networks reached 100% for the sketches, and 84% for the images of two objects as a case study.
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Authors:
Razvan
Bogdan
Abstract:
Massive Open Online Courses (MOOCs) have been producing an electrified feeling in the academic circles since 2012. This was amplified once profit initiatives like Coursera and Udacity joined their forces with renowned universities like Stanford, Harvard and the Massachusetts Institute of Technology. This paper presents a modality of integrating Embedded Systems MOOCs into blended courses, but at the same time it provides an evaluation of this approach: the sentiment analysis technique. Such an evaluation not only reveals the polarity, but also valuable insights into improving the course content and integration of MOOCs into the intricacies of teaching embedded systems.
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Authors:
Ciprian
Bogdan Chirila
Abstract:
Nowadays, regional IT industry lacks human resources because of the pressure created on the labor market by the high-value economic projects. Tutors tend to be more and more loaded with teaching, research, and administrative tasks. Students tend to use more and more electronically devices like laptops, tablets, and mobile phones in their learning sessions. In this context, universities should rely more on technologies like: LMSs (Learning Management Systems), MOOCs (Massive Open Online Courses), and why not GLOs (Generative Learning Objects) or evenAGLOs (Auto-generative Learning Objects). Auto-generative learning objects are reusable pedagogical patterns to be instantiated with generated content based on random numbers to fulfill the learning objectives. Many online e-learning resources are available containing interactive presentations, gamifications of several learning objectives. Such e-learning resources are hard to reuse and even harder to modify and adapt to; each discipline needs this because it needs access to the source code, programming knowledge to change, test and deploy etc. In this paper, we will focus on computer science disciplines needed in the regional IT industry, namely data structures and algorithms. We will show how a tutor can build several auto-generative learning objects in order to assess the knowledge of a class of students. We will start with the design of the generic models, then we will assess the generated content created with the help of a tool based on meta-programming, afterwards, we will deploy the content to a webserver to be consumed by the students. Finally, we will evaluate the assessed results and discuss the approach both from the student's and the tutor's perspective.
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Authors:
Daina
Vasilevska
, Baiba
Rivza
, Razvan
Bogdan
Abstract:
Distance learning environment with its different approaches has become one of the most researched paradigms in the late years. Different technologies have been developed and introduced into these systems, but at the same time, a spectrum of use-cases has been offered for this model. This paper aims at addressing the most important problem facing with the distance learning eco-system, namely its evaluation. The evaluation process has been undertaken in different European countries, such as Latvia, Lithuania, Serbia, Poland, Belarus, and Romania. The obtained results show that not all of the students are at the same level of readiness when it comes to distance education, there are no criteria developed for the evaluation of the students' readiness to this education model. For the purpose of this study, authors suggest that readiness to distance education includes knowledge, skills, and abilities that are necessary for students to successfully possess while using the technologies of distance education. After the analysis of the results of this research, the authors developed a structure and described elements that define the level of students' readiness to distance education.
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Authors:
Daniela
Danciulescu
, Mihaela
Colhon
, Gheorghe
Grigoras
Abstract:
In Tudor (Preda) (2010) a method for formal languages generation based on labeled stratified graph representations is sketched. The author proves that the considered method can generate regular languages and context-sensitive languages by considering an exemplification of the proposed method for a particular regular language and another one for a particular contextsensitive language. At the end of the study, the author highlights some open problems for future research among which we remind: (1) The study of the language families that can be generated by means of these structures; (2) The study of the infiniteness of the languages that can be represented in stratified graphs. In this paper, we extend the method presented in Tudor (Preda)(2010), by considering the stratified graph formalism in a system of knowledge representation and reasoning. More precisely, we propose a method that can be applied for generating any Right Linear Language construction. Our method is proved and exemplified in several cases.
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Authors:
Sebastian
Fuicu
, Mircea
Popa
, Dalibor
Dobrilovic
, Marius
Marcu
, Razvan
Bogdan
Abstract:
By using a plethora of technologies and formats, the distance learning paradigm offers access to education through a large spectrum of subjects which are situated in different geographic areas. This paper presents the successful collaboration between Politehnica University of Timisoara, Romania, and the Technical Faculty "Mihajlo Pupin" of Zrenjanin, Serbia, which offer a low maintenance cooperation model based on a web cast system that allows subjects from both countries to have access to each other's educational material. The aim of this project is to raise the interest of pupils, students and graduates to the latest information regarding technical content used in the IT industry. The access takes place in real time and from the distance without the necessity of being present in order to receive the information. The obtained results are very encouraging regarding the usage of such a distance learning environment and the further development of such tools and cooperation.
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Authors:
Laurențiu
Mihai Treapăt
, Anda
Gheorghiu
Abstract:Mainly, this paper focuses on the roles of artificial intelligence based systems and especially on risk-covering operations. In this context, the paper comes with theoretical explanations on real-life based examples and applications. From a general perspective, the paper enriches its value with a wide discussion on the related subject. The paper aims to revise the volatilities' estimation models and the correlations between the various time series and also by presenting the Risk Metrics methodology, as explained is a case study. The advantages that the VaR estimation offers, consist of its ability to quantitatively and numerically express the risk level of a portfolio, at a certain moment in time and also the risk of on open position (in titles, in FX, commodities or granted loans), belonging to an economic agent or even individual; hence, its role in a more efficient capital allocation, in the assumed risk delimitation, and also as a performance measurement instrument. In this paper and the study case that completes our work, we aim to prove how we can prevent considerable losses and even bankruptcies if VaR is known and applied accordingly. For this reason, the universities inRomaniashould include or increase their curricula with the study of the VaR model as an artificial intelligence tool. The simplicity of the presented case study, most probably, is the strongest argument of the current work because it can be understood also by the readers that are not necessarily very experienced in the risk management field.