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6,059 results for “Journale”
BRAIN Journal-Computational Intelligence in a Human Brain Model-Figure 2. Processes and Interfaces of the SAH Human Brain Model
<p>The proposed SAH Human Brain Model starts assigning the main attributes to the “heavy pieces” (king, queen, rooks, bishops, knights) and assigning to pawns the interfaces as an advanced guard. The interface represents senses and processed human actions (equilibrium, movements, and speech) and it results from the brain activity (see Figure 2). </p>
BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 4. Table structure and relationships
<p>The structure of the tables, primary keys and foreign keys are shown in figure 4.The names of the fields in the database tables are relevant for their content. Only the SPRAS field in the translation-tables TABT and ARET must be explained: SPRAS is a system-field which stands for the language and is used in order to maintain the languages in which the tab/area is translated into.</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)
<p> In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.</p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 1. Selected Romanian counties in order to strengthen the target group of tourism organizations with informative role
<p>In this regard, we analysed the current state of presence and communication on Facebook for<br> 109 informative tourism entities located in 25 Romanian counties, selected on the basis of tourist<br> traffic indicators for the period between 2007 and 2013. The structure of the 109 organizations<br> analysed is: 43 tourist information centers (39.45%), 44 entities with the name of the association for<br> tourism promotion, ecotourism promotion, mountaineering promotion etc. (40.36%), 18 tourism<br> clubs (16.51%) and 4 tourist information points/offices (3.67%)</p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 4. Facebook adoption rate by age group in Romania
<p>Also, according to Facebrands statistics of 15 October 2015, the Facebook penetration rate in the population is 39.76% and in the total number of Romanian Internet users is 82.97%. The statistics infirm the preconceived ideas of skeptics that the websites of socialization have no relevance for tourism organizations because the contained information in these websites is unstructured, inconsistent in terms of content and irrelevant for tourism, or newer, the ideas of those who believe that the majority of Facebook users are young and very young (under 18). From Figure 4 we can see that the segment of major users (over 18 years) totals 88.3% of the total number of Facebook users and these users may have at any time the quality of tourists.</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 4. The EMD decomposition results for subject 2 when he imagines left hand movement
<p>Fig. 4 shows the EMD decomposition result of one-trial (left hand movement imagination) for subject 2 in the channels C3 and C4 respectively (the pre-filtered EEG signal used for this illustration is not corrupted by blinking artifact.). Each channel is decomposed into ten IMFs and one residue</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 5b. PSD (dB/Hz) vs freaquency (Hz) of each IMF showen in fig 4 in channel C4 (a) and in C3 (b)
<p>Therefore, the new signal is reconstructed by keeping only the two first IMFs. EMD also allows eliminating the artifacts in the EEG during the recording sessions like eye blinks and eyeball movements. In Fig 5, we noted that ocular artifact frequency is generally low around 5Hz with high amplitude. This artifact appears mainly in IMF3 and IMF4. Finally, band power was applied for the new signal. As a last step, the logarithm of the BP is calculated in order to transform the distribution of this feature to a more Gaussian like shape, because the classifiers we used, such as HMMs and SVM assume normally distributed features.</p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 3. Integration of Social Media elements on tourism organization's websites
<p>Currently, in Romania there are about 8 million Facebook users (Facebrands.ro). In the recent years there has been a spectacular increase of this phenomenon, which shows how important is the use of social networks for an economic and even for a non-profit entity in order to make the brand known or to promote an activity (DailyBusiness.ro). </p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 3. Hybrid EMD-BP approach for one trail feature extraction
<p>In this work, we propose a direct nonlinear approach to extract the more relevant IMFs corresponding to the different frequency components in the and bands and then obtain the BP in order to use them as features for mental task classification (see Fig. 3). The feature vector p used for the demonstration in this paper is composed, for each sample I, 1 < i < 2048, in a given trial (among a total of 160 trials) of four bandpower, calculated of the rhythms and in positions C3 and C4 Trad et al., 2011).</p>
BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 1. Popup layout for the Material Master Data Application
<p>The Material Master Data Application provides an update popup layout, including tabs, areas and fields (also customer-specific fields). Each tab consists of one or more areas and each area of one or more fields, similar to the example below (figure 1). The application is called flexible because the user must have the possibility to add, delete, reorder or rename tabs, areas and fields.</p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 2. Online presence through a website of Romanian tourism entities with informative role Source: authors
<p>According to research results (Figure 2), almost 68% of the entities with tourist information and promotion role own a proper site for the presentation of the work, while 18.35%, most probably do not realize in pragmatic terms the usefulness of such promotional tools. The situation can be cataloged as quite worrying, especially if we consider that today, due to the fulminant development of smartphones, more and more tourists choose to seek information on the Internet, even during their trip to a new destination (Wang el. al. 2012).</p>
BRAIN Journal-Computational Intelligence in a Human Brain Model-Figure 4. Name and role of the Chess Pieces
<p>In assigning the brain function to the computational processing units the strategy of the chess game will be pursued: 1 king – consciousness, mind, resolving undefined situations, undetermined risk analysis, feedback: 1 queen – implementation strategy, thinking, learning; 2 rooks – initial knowledge memory and learning memory; 2 bishops – good or updated, time or emergency decision; 2 knights – rules, open schemes, fixed processes, templates; 8 pawns – interfaces with own senses and actions. Double chess pieces will be assigned in the model with initial knowledge (‘ marked) that can be updated as a learning experience to a second set (“ marked).</p>
BRAIN Journal-Computational Intelligence in a Human Brain Model-Figure 3. Assigning ` the "SAH" Human Brain Model the role of the Chess Pieces
<p>The components are not topically subordinated to each other but in a strong interoperability and used for outputs reflected as result of thinking, actions to receiving information from the sensor of the interfaces, movement or speaking. </p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 4b. The EMD decomposition results for subject 2 when he imagines left hand movement
<p>d et al., 2011). Fig. 4 shows the EMD decomposition result of one-trial (left hand movement imagination) for subject 2 in the channels C3 and C4 respectively (the pre-filtered EEG signal used for this illustration is not corrupted by blinking artifact.). Each channel is decomposed into ten IMFs and one residue.</p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 6. The general conception of our asynchronous system BCI (offline - online) for reinforcement of a joystick movement
<p>Once the motor imagery is identified, a command may be associated to this mental task in order to control a machine (Prataksita et al., (2014)) (Guger et al., 1999). In this work, we constructed a new Simuhnk/MathWork model to translate on-line the EEG signals into low-level commands. Fig. 6 shows our experimental EEG-based BCI System </p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 1. General architecture of an online (BCI)
<p>One major challenge of our BCI system is to describe the signals EEG by a few relevant values called features i.e. step 3 in Fig (1). The success of the mental imagery classification depends on the choice of features used to characterize the raw EEG signals. These features can then be used in step 4 in order to classify the user’s mental state. Several approaches for feature extraction have been proposed in literature. </p>
BRAIN Journal-Motor Imagery signal Classification for BCI System Using Empirical Mode Décomposition and Bandpower Feature Extraction-Figure 3. Hybrid EMD-BP approach for one trail feature extraction
<p>In this work, we propose a direct nonlinear approach to extract the more relevant IMFs corresponding to the different frequency components in the and bands and then obtain the BP in order to use them as features for mental task classification (see Fig. 3). The feature vector pi used for the demonstration in this paper is composed, for each sample I, 1 < i < 2048, in a given trial (among a total of 160 trials) of four bandpower, calculated of the rhythms and in positions C3 and C4 (Trad et al., 2011).</p>
BRAIN Journal-The Presence and Activity on Facebook of the Informative Travel Organizations in Romania-Figure 5. The attendance rate and active communication on Facebook of the Romanian tourism organizations with informative role
<p>As we can see in Figure 5, the presence on Facebook of the organizations involved in information and promotion of tourism activities (54.12%) is lower than the rate of online presence through a website (67.89%), which broadly confirms that Social Media visibility is the second step in the strategy of online business promotion of entities that were subject of this research. The fact that 99% of the tourist organizations present on Facebook already have a website that promotes their own work confirms the previous statement</p>
BRAIN Journal-Computational Intelligence in a Human Brain Model-Figure 5. Block Diagram of the SAH Human Brain Model
<p>Three vertical areas are defined in the field of activities: Processes units, Computational Intelligence Block, and Smart Interfaces Block (Details are presented in Figure 5). The Processes units fully communicate with the Computational Intelligence Block, Central Processing Unit and Smart Interfaces. Some specific links and functions are not specified here. Smart interfaces defined for “sight, sound, taste, touch and hearing senses” are bidirectional and completed by input-output interfaces that ensure the communication for output actions like “speech, sound, movements” and other commands resulting in the thinking process. An important issue is the ‘equilibrium’ that must be treated in either “decision or movement” framework.</p>
BRAIN Journal-Redesigning a Flexible Material Master Data Application with Language Dependency-Figure 3. The logical data model of tables and views
<p>The five tables, named TAB, TABT, AREA, ARET and FLD, are combined within three views (TABV, AREV and FLDV) which build a cluster view, TAFC (figure 3). </p>
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.