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BRAIN: A speech to text transcription approach based on Romanian corpus

Speech recognition applications enable the recognition and translation of spoken languages into text by computers. Due to the fact that the traditional approaches are costly and time consuming, the worldwide industry adopted speech recognition systems.

Andrei Scutelnicu, Anca Diana Bibiri, Mihaela Onofrei, and Mircea Hulea will present in their paper “A speech to text transcription approach based on Romanian corpus” a simple and efficient method for speech to text recognition, based on a machine learning approach, using a Romanian speech corpus.

Main components of a speech recognition system
Main components of a speech recognition system

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BRAIN: Integrating MOOCs in Embedded Systems Blended Courses

The Massive Open Online Course (MOOC) phenomenon has been growing in popularity and importance in the last decade, receiving valuable recognition from renowned universities from all over the world. MOOC can be simply defined as an online course aimed at unlimited participation and open access via the web. In the latest issue of the BRAIN Journal, Răzvan Bogdan’s paper approaches a modality of integrating MOOCs into embedded systems higher education.

The academic field of Embedded Systems aims to enhance student’s understanding through various methods, however students find the concepts as being very monotonous and tend to avoid building practical solutions. In this paper, the author presents the introduction of MOOCs with no synchronization into the Embedded Systems courses at “Politehnica” University of Timișoara, Romania.

Embedded Systems course space for distance learning
Embedded Systems course space for distance learning

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BRAIN: Pseudo-holographic Displays as Teaching Tools in Mathematics

A pseudo-holographic display is a display that creates a virtual three-dimensional image of an object, producing viewing experiences that are virtually indistinguishable from viewing a true hologram.

In the upcoming issue of BRAIN Journal the researchers Monica Ciobanu, Antoanela Naaji, Ioan Dascal, and Ioan Virag will present in their paper “Pseudo-holographic Displays as Teaching Tools in Mathematics” an innovative approach for the education system. This team of researchers came up with the idea of creating and implementing a set of interactive teaching tool packages (ITTPs) to help students grasp abstract mathematical notions by linking them to a specific physical representation.

holographic-display

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BRAIN: Social Media as Medical Validator

The electronic word of mouth (eWOM) is a communication form adapted to the digitalized world of today where persons that never met communicate in an impersonal manner. The paper Social Media as Medical Validator written by Laura Broasca, Versavia-Maria Ancusa and Horia Ciocarlie aims to explore the receptiveness towards a negative bias in health-related electronic Word of Mouth.

The researchers point out that when evaluating the credibility of the eWOM we should take into account that social factors play an unexpected role, as most people use personal details and peripheral cues, not a clear, logical, fact-based judgement to reach a conclusion. And yet, the credibility of the traditional information sources is surpassed by that of eWOM.

Google trends comparison between vaccine-related search words
Google trends comparison between vaccine-related search words

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BRAIN: Artificial Intelligence as a Decision-making Tool in Planning the Research

Because of their ability to reproduce the biological neural networks, ANNs (Artificial neural networks) have found uncountable applications to a wide range of disciplines. Simina Maris, Titus Slavici, Petre Nenu and Liliana Baciu will present in the latest volume of BRAIN journal an article about the usage of artificial intelligence, especially artificial neural networks (ANNs), in the development of an efficient research plan for studying the quality of finite products, in particular wood briquettes obtained from various biomass mixtures.

Their work is a response to the needs expressed by a private company (SC Andrei Slavici SRL) searching for innovation in the production of wood pellets and briquettes on the market of nonconventional bio-fuels.

Example of multilayer neural network (source: Samarasinghe, 2016)
Example of multilayer neural network (source: Samarasinghe, 2016)

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BRAIN: The Analysis of E-Commerce Sites with Eye-Tracking Technologies

In this era of technology, it cannot come as a surprise that E-Commerce sites have become a significant part of the user’s online activity. In order for these websites to remain relevant to the visitors over long periods of time, attention should be brought to their efficiency and effectiveness when it comes to their interactivity dimensions. The study The Analysis of E-Commerce Sites with Eye-Tracking Technologies – written by O. Dospinescu and A. E. Percă-Robu – is examining the effects of the interactivity dimensions on users’ content comprehension and their attitudes towards e-commerce websites by using eye-tracking technologies.

Various fields use the eye tracking technology to assess the visual attention, but when considering the decision-making process, the specialized literature acknowledge that the eye movements are directly linked to peoples’ cognitive goals. By investigating the website’s interactivity dimensions, the authors explore the visual process and drawing the time spent on the site or on various regions of it. Dospinescu and Percă-Robu assume that a high level of interactivity leads to a favourable attitude towards the website, therefore it is important for the content creators to pay attention to the ease of use and the visual elements of their E-Commerce bussiness.

Eye Tribe Tracker
Eye Tribe Tracker

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BRAIN: A Robust Approach of Facial Orientation Recognition from Facial Features

In the field of computer vision and pattern recognition, face orientation recognition stands as a significant topic. In the paper A Robust Approach of Facial Orientation Recognition from Facial Features, the authors Stefan Andrei, Kishor Datta Gupta, Md Manjurul Ahsan and Kazi Md. Rokibul Alam introduce us to an image mapping technique for face analysis.

The methodology of the study consists of two main phases: Face Feature Extraction and creating the graph image, and Matching Graph image with stored images. The Face Feature Extraction presents four steps that include Face Detection, Feature Extraction, Obtaining Feature Data and Creating image with these data.

The first step in facial feature detection is detecting the face. This requires analyzing the entire image. The second step is using the isolated face(s) to detect each feature. The technique of this study relies on the four main features of the face: left eye, right eye, nose, and mouth. It is mandatory to obtain the positions, size, height, width, and angle of these features respective to each face. By acquiring the data from the features, a new picture including the model and shape of the face is created.

Experiment Results: Sample image data 1
Experiment Results: Sample image data 1

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BRAIN: Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics

In order to ensure optimal teaching conditions for university students, attention should be brought to their personality traits and academic performance. In the paper Personality Questionnaires as a Basis for Improvement of University Courses in Applied Computer Science and Informatics, the authors Vladimir Ivančević, Marko Knežević, and Ivan Luković present the foundation for such an adaptation of the teaching process, supported by an analytical software solution (in its initial version).

The software solution presents two main components: a data warehouse for storing collected data and an analytical software tool (built using the Shiny framework). The data warehouse contains collected data about student academic performance and personality traits, while the analytical tool is a web application that retrieves data from the data warehouse or external CSV files matching the required structure and allows analysts to perform exploration and analysis of data concerning student performance and personality.

 A data warehouse schema segment for scores of university students on scales of personality questionnaires
A data warehouse schema segment for scores of university students on scales of personality questionnaires

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BRAIN: Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed

In neurology and neuroscience research, Steady-State Visually Evoked Potential (SSVEP) are brain signals which occur in response to visual stimulation. The paper Novel Detection Features for SSVEP Based BCI: Coefficient of Variation and Variation Speed – written by Abdullah Talha Sözer and Can Bülent Fidan – aims to introduce novel detection features for the SSVEP based brain computer interfaces. Brain-computer interface (BCI) is a collaboration between a brain and a device that enables signals from the brain to direct some external activity, such as control of a cursor or a prosthetic limb. The interface enables direct communication between the brain and the object to be controlled.

Time vs frequency analysis of 10 Hz SSVEP response
Time vs frequency analysis of 10 Hz SSVEP response

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BRAIN: Novel Ontologies-Based OCR – Error Correction Cooperating with Graph Component Extraction

The article written by Sarunya Kanjanawattana and Masaomi Kimura is a study about Optical Character Recognition (OCR), which represents a a typical tool used to transform image-based characters to computer editable characters. The two illustrate a novel method which is a combination of a graph componenet extraction and an OCR-error correction.

In the last years, graphs became very important to researches, as they contain significant information which can be extracted and used. Graphs offer data summarization which presents essential information that is interpreted by acquiring small descriptive details. In order to succeed in obtaining a primary interpretation, OCR was created, which is an approving solution used for acquiring graph components as a digital format o character letters.  This study uses a collection of bar graphs which contains at least axis descriptions and a legend in order to illustrate OCR.

Steps of candidate selection

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