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1,423 results for “separation”
BRAIN Journal-Isomorphism Between Estes' Stimulus Fluctuation Model and a Physical- Chemical System-Figure 1. Two compartments containing solution separated by a membrane.
<p>In fact, this equation will be found first if one consults physical or chemical textbooks for<br> diffusion. Also one may be able to find already-existing diffusion simulators to see vivid images of<br> the process.</p>
Figure 1. DiagAgentExpertDM architecture (adapted from Ioniță, 2014) -Intelligent System for Diagnosis of a Three-Phase Separator
<p>For the current hybrid system</p> <p>(DiagAgentExpertDM)</p> <p>, data from different sources and in</p> <p>various forms are preprocessed, in order to represe</p> <p>nt them in a unified way to be able to upload</p> <p>them in a learning module. Simultaneously, inconsis</p> <p>tency tests are made to eliminate the</p> <p>measurement errors caused by improper calibration o</p> <p>f transducers etc.</p> <p>In condition of using a diagnosis method based on p</p> <p>rocess history, the next step in fault</p> <p>identification referring to the gas-oil separation</p> <p>process is to scan the historical data. Retrieved d</p> <p>ata</p> <p>will possess a label with a certain priority which</p> <p>will be used in the next retrieval process. The</p> <p>learning module is supplied with multiple preproces</p> <p>sed data samples, in order to extract knowledge</p> <p>from them. For each data samples, a data mining alg</p> <p>orithm will be applied (figure 1).</p> <p> </p>
Figure 2. Correct Classified Instances for different data sets-Intelligent System for Diagnosis of a Three-Phase Separator
<p>The data mining models may be considered a superior</p> <p>technique that may be successful</p> <p>applied in diagnosis and may be develop in the futu</p> <p>re on the base of more training data to increase</p> <p>the accuracy of results.</p> <p>Industrial processes are dynamic processes with ran</p> <p>dom behavior and whose evolution over</p> <p>time cannot be predicted unless it is well known th</p> <p>e process model and use advanced predictive</p> <p>techniques. Consequently, design and implement an a</p> <p>utomated online monitoring and diagnosis</p> <p>three-phase separator remains a future direction of</p> <p>research conducted so far.</p> <p>Conceptually, this system should have permanent acc</p> <p>ess to data collected from field</p> <p>transducers, to be able to identify the type of fau</p> <p>lt occurred, to locate the fault and provide</p> <p>recommendations to remedy abnormal operating condit</p> <p>ion. Also, updating the database defects with</p> <p>new types of defects occurred and the adequate solu</p> <p>tions adopted for eliminating errors in the</p> <p>operating mode is an important feature to be consid</p> <p>ered during the design of the online diagnosis</p> <p>system. This is possible if the system would have s</p> <p>elf-learning capabilities. To acquire this "skill",</p> <p>the automatic online diagnosis system may contain a</p> <p>diagnosis module based on artificial neural</p> <p>networks.</p>
BRAIN Journal-An Energy-Saving Concept of the Smart Building Power Grid with Separated Lines for Standby Devices-Figure 1. The whole-building switch concept for the power lines of standby devices
<p>68 million houses in North America and Europe will be smart by 2019 (Kurkinen, 2016) with a compound annual growth rate of 37 % and 61 %, respectively. The smart equipment is usually installed together with an upgrade (e.g. aluminum wires are replaced by copper ones) of the power grid. In this case, additional power lines for standby devices are cabled, and the WBS concept is applied using one power switch only (see figure 1). For instance, the Songle high-power relay T90 can control the whole building electricity with load up to 30 A using NodeMcu Lua ESP8266 WiFi and/or Arduino Uno / Mega boards.</p>
BRAIN Journal-An Energy-Saving Concept of the Smart Building Power Grid with Separated Lines for Standby Devices-Figure 3. The unified hardware unit based on NodeMcu Lua ESP8266 WiFi development board, ACS712T ELC-30A current sensor, and relay SRD-05VDC-SL-C
<p>The software consists of two parts, low-level Arduino sketches and high-level C# Windows form appplication. They are connected using the open-source message MQTT broker Mosquitto.11 Every hardware unit has the unique identifier and commands to control the relay. The MQTT topic “/VPP/Relays” is used by subscribers and publishers. The number “50” sent from C# Windows form (it equals number “2” sent from the standard Mosquitto publisher) is a command to switch on the second relay, “51” (“3”) – to switch off, respectively. The prototype was developed with one root controller and two descendant relays. The commands are as follows: “52” (“4”) / “53” (“5”) – to switch on / off the first relay, “54” (“6”) / “55” (“7”) – to switch on / off the third relay, respectively. This solution is similar to the one presented in [22], but ACS712T ELC-30A current sensor and ESP8266WiFi.h library are applied here. In addition, other commands, e.g. “56” (“8”) to get the value of the current in the 3rd segment, are in use as well.</p>
BRAIN Journal-An Energy-Saving Concept of the Smart Building Power Grid with Separated Lines for Standby Devices-Figure 5. An example of smart lighting using NodeMcu Lua ESP8266 ESP-12 WiFi board
<p> for different purposes together with switching on/off relays, e.g. to control the motors, to acquire the data from sensors. It allows developing multifunctional smart systems. For instance, the smart lighting unit is created using NodeMcu Lua ESP8266 ESP-12 WiFi board, Arduino light sensor, and relay SRD-05VDC-SL-C, which controls the power supply of the lamp. Figure 5 shows a simplified example of smart lighting, where the lamp is represented by eight 5 mm light-emitting diodes (LEDs).</p>
BRAIN Journal-An Energy-Saving Concept of the Smart Building Power Grid with Separated Lines for Standby Devices-Figure 4. Screen shot of the C# Windows form app
<p>The screen shot of the C# Windows form app is shown in figure 4. The text field on the left side includes numbers from 2 to 7, which are commands to control the states of relays. </p>
BRAIN Journal-An Energy-Saving Concept of the Smart Building Power Grid with Separated Lines for Standby Devices-Figure 2. An example of smart power grid with hierarchical structure
<p> Figure 2 shows an example of smart power grid with hierarchical structure, where every segment equals a room or office. This approach is similar to the idea presented in Alboteanu et al. (2015), where the connecting / disconnecting of renewable energy sources and consumers are made via the appropriate contactors, automatically (or manually) controlled according to the energy consumption/generation. However, the management of micro smart grid is discussed in Alboteanu et al. (2015) only</p>
BRAIN Journal-ANNSVM: A Novel Method for Graph-Type Classification by Utilization of Fourier Transformation, Wavelet Transformation, and Hough Transformation-Figure 10. Detailed accuracy separated by classes and a confusion matrix which belongs to the dataset of Coiflet 1 applied by our main method (ANNSVM)
<p>With regard to accuracy values of each class as presented in Figure 10, we observed that the accuracy of the two-dimensional chart class was the lowest (i.e., 0.875), while others were over 0.9. Results here suggested that both the bar and pie classes have their own unique characteristics, as opposed to the 2Dchart class. For example, the graph images that contained some rectangles were individually categorized in the bar graph class. A similar phenomenon occurred for circles in the pie chart class. In contrast, the 2Dchart class contained mixed types of graphs; hence, the graph characteristics belonging to the 2Dchart class varied. </p>
A new and highly robust light-responsive Azo-UiO-66 for highly selective and low energy post-combustion CO2 capture and its application in a mixed matrix membrane for CO2/N2 separation
<p>Supporting information for publication in Journal of Materials Chemistry A, <a href="https://dx.doi.org/10.1039/C8TA03553A">https://dx.doi.org/10.1039/C8TA03553A </a></p>
Investigation of Azo-COP-2 as a photo-responsive low-energy CO2 adsorbent and porous filler in mixed matrix membranes for CO2/N2 separation
<p>Dataset supporting publication. All raw data for figures is included in the Excel file, and the full high-resolution SEM images are included in this repository.</p> <p>A preprint of the manuscript is available from <a href="https://doi.org/10.26434/chemrxiv.7593902">https://doi.org/10.26434/chemrxiv.7593902</a> </p> <p>The published paper is: Siyao Li, Nicholaus Prasetya, and Bradley P Ladewig, <em>Ind. Eng. Chem. Res.</em>, Just Accepted Manuscript<br> DOI: <a href="https://doi.org/10.1021/acs.iecr.9b00762">https://doi.org/10.1021/acs.iecr.9b00762</a></p>
An Insight on the Effect of Azobenzene Functionalities Studied in UiO-66 Framework for Low Energy CO2 Capture and CO2/N2 Membrane Separation
<p>Data supporting journal manuscript. Includes an Excel spreadsheet with all the raw data for the figures in the manuscript, calibrations and calculations. Also includes 3D chemical structures of MOF units, and SEM images of MOF/polymer composite materials.</p> <p><strong>Abstract</strong></p> <p>In this paper, we report a simple approach to study the fundamental aspect of light-responsive metal organic framework (MOF) in UiO-66 topology through a mixed-ligand approach. Apart from change in the structural property, the loading of azobenzene linker inside the framework also affects the CO<sub>2 </sub>light-responsive property and CO<sub>2</sub>/N<sub>2 </sub>selectivity which could help to design future low-energy CO<sub>2 </sub>adsorbents. Further study to incorporate the MOFs into mixed matrix membranes also indicates the benefit of higher azobenzene loading in the MOF to enhance the CO<sub>2</sub>/N<sub>2 </sub>separation performance since it can improve the separation performance which could not be obtained in non-functionalized fillers. </p> <p><strong>Preprint manuscript</strong></p> <p>A Preprint version of the manuscript is available at: <a href="https://doi.org/10.26434/chemrxiv.7568696.v1">https://doi.org/10.26434/chemrxiv.7568696.v1</a> </p> <p><strong>Published article</strong></p> <p>Journal of Materials Chemistry A, 2019, DOI: <a href="https://doi.org/10.1039/C9TA02096A">https://doi.org/10.1039/C9TA02096A</a></p>
Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties
<p><strong>Publication:</strong> M. Xie. N. Prasetya and B. P. Ladewig, Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties, Inorganic Chemistry Communications (2019).</p> <p><strong>Preprint:</strong> M. Xie. N. Prasetya and B. P. Ladewig, Systematic screening of DMOF-1 with NH2, NO2, Br and azobenzene functionalities for elucidation of carbon dioxide and nitrogen separation properties, Inorganic Chemistry Communications (2019), <a href="https://doi.org/10.26434/chemrxiv.8862239.v1">https://doi.org/10.26434/chemrxiv.8862239.v1</a></p> <p>Dataset supporting publication, including SEM images, optical microscope images, NMR spectra, data used in Figures, and full resolution figures as included in the manuscript.</p> <p><strong>Abstract:</strong> In this study, dabco MOF-1 (DMOF-1) with four different functional groups (NH<sub>2</sub>, NO<sub>2</sub>, Br and azobenzene) has been successfully synthesized through systematic control of the synthesis condition of their parent framework. The functionalised DMOF-1 is characterized using various analytical techniques including PXRD, TGA and N<sub>2</sub> sorption. The effect of the various functional groups on the performance of the MOFs for post-combustion CO<sub>2</sub> capture is evaluated. DMOF-1s with polar functional groups are found to have better affinity with CO<sub>2</sub> compared with the parent framework as indicated by higher CO<sub>2</sub> heat of adsorption. However, imparting steric hindrance to the framework as in Azo-DMOF-1 enhances CO<sub>2</sub>/N<sub>2</sub> selectivity, potentially as a result of lower N2 affinity for the framework. </p>
Audio Source Separation Dataset
<p>AUDIO SOURCE SEPARATION DATASET.</p> <p>This dataset has been constructed from audio excerpts taken from the Bach10 dataset by Duan et al. [1]. This database can be used in performance evaluation and results can be compared with the ones presented in my PhD thesis [2], Section 5.8.5, on pages 153-158, in Chapter 5. A percussive sequence from the Open Air Library [3], has also been used in these experiments.</p> <p>[1] Z. Duan, B. Pardo, and C. Zhang, "Multiple fundamental frequency estimation by modeling spectral peaks and non-peak regions," IEEE Transactions on Audio, Speech and Language Processing, vol. 18, no. 8, pp. 2121-2133, 2010.</p> <p>[2] Delgado Castro, A. "Iterative separation of note events from single-channel polyphonic recordings," Ph.D. University of York. 2019.</p> <p>[3] https://www.york.ac.uk/electronic-engineering/research/communication-technologies/projects/open-acoustic-impulse-response-library/</p>
Blind Source Separation of Musical Notes
<p>BLIND SOURCE SEPARATION OF MUSICAL NOTES.</p> <p>This dataset contains 12 groups of three musical notes whose pitches are not in harmonic relation. They were extracted from the RWC Musical Instrument Sound Database [1] and were used for performance evaluation of an audio source separation system, proposed in my PhD thesis [2], in Chapter 5, Section 5.8.2, on page 150.</p> <p>[1] M. Goto, H. Hashiguchi, T. Nishimura, and R. Oka, "RWC music database: music genre database and musical instrument sound database," in Proceedings of the 4th International Conference on Music Information Retrieval, pp. 229-230, 2003.</p> <p>[2] Delgado Castro, A. "Iterative separation of note events from single-channel polyphonic recordings". Ph.D. University of York. 2019.</p>
Data for: "Considering unique, shared, and dominant brain activation in the VWFA and LOC: A comparison of separate and combined word and picture naming"
<p>FMRI data underlying analyses for Experiments 1 and 2 in "Considering unique, shared, and dominant brain activation in the VWFA and LOC: A comparison of separate and combined word and picture naming".</p>
Figure 4 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 4. Abundance-based accumulation curves for ground-dwelling macro-invertebrates from montane meadows and mixed forests in South Tyrol, Italy. The data come from pitfall traps along a linear transect from extensively managed hay meadows ('MM' and 'M', squares) across an abrupt ecotone ('E', diamonds) towards mixed forest stands ('F' and 'FF', circles). The curves show from left to right: the sampling coverage, taxa and species richness (Hill number q = 0), Shannon (q = 1) and Simpson diversity (q = 2). Plot [A] shows the total faunal community data at the highest taxonomic resolution, plot [B] the Araneae data at species level.
Figure 3 in Abrupt boundaries between mountain meadows and forests separate ground-dwelling invertebrate communities: a case study from South Tyrol, Italy
Figure 3. Boxplots with jitter of ground-dwelling macro-invertebrate activity densities from montane meadows and mixed forests in South Tyrol, Italy. Each data point represents a pitfall trap along a linear transect starting from extensively managed hay meadows ('MM' and 'M') across an abrupt ecotone ('E') towards mixed forest stands ('F' and 'FF'). Significant differences between the habitat plots (i.e. on the X-axes) according to GLM and Tukey's HSD post-hoc tests are indicated with different letters at top of each plot.
Figure 3 in Human activity mediates reciprocal distribution and niche separation of two sympatric mongoose species on the Pothwar Plateau, Pakistan
Figure 3. Photomicrographs of whole mounts of hair structure of three rodent species (recovered from fecal samples and reference hairs) consumed by the small Indian mongoose on the Pothwar Plateau. A) Whole mount of recovered hair of Rattus rattus, B) Whole mount of reference hair of Rattus rattus, C) Whole mount of recovered hair of Nesokia indica, D) Whole mount of reference hair of Nesokia indica, E) Whole mount of recovered hair of Mus musculus, F) Whole mount of reference hair of Mus musculus.
Figure 2 in Human activity mediates reciprocal distribution and niche separation of two sympatric mongoose species on the Pothwar Plateau, Pakistan
Figure 2. Average length (cm), mass (g), and diameter (cm) of SIM and GM fecal samples collected from study sites on the Pothwar Plateau.
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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.