4,924 research outputs found
Performance improvement of GSM traffic using adaptive multi rate (AMR) / Ahmed Fawwaz Hadi Ahmed Mahir
No full textThis paper describes the implementation of the Adaptive Multi Rate (AMR) speech codec for improving the performance of GSM traffic and the speech service. In other words, the AMR is used to reallocate the existing speech codec configuration to offer higher percentage of call success among mobile user with AMR capability. In this paper, the trial of AMR implementation process in Cyberjaya area have been explained and discussed. An application software is developed using Visual Basic 6 to analyze the data obtained from the project and to assist traffic personnel to monitor traffic utilization in implementing AMR at any given area and date
msberends/AMR: v0.6.0
No full text<p><strong>AMR 0.6.0</strong></p>
<p><strong>New website!</strong></p>
<p>We’ve got a new website: <a href="https://msberends.gitlab.io/AMR/">https://msberends.gitlab.io/AMR</a> (built with the great <a href="https://pkgdown.r-lib.org/"><code>pkgdown</code></a>)</p>
<ul>
<li>Contains the complete manual of this package and all of its functions with an explanation of their parameters</li>
<li>Contains a comprehensive tutorial about how to conduct antimicrobial resistance analysis, import data from WHONET or SPSS and many more.</li>
</ul>
<p>New</p>
<ul>
<li><strong>BREAKING</strong>: removed deprecated functions, parameters and references to ‘bactid’. Use <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> to identify an MO code.</li>
<li>Catalogue of Life as a new taxonomic source for data about microorganisms, which also contains all ITIS data we used previously. The <code>microorganisms</code> data set now contains:
<ul>
<li>All ~55,000 (sub)species from the kingdoms of Archaea, Bacteria and Protozoa</li>
<li>All ~3,000 (sub)species from these orders of the kingdom of Fungi: Eurotiales, Onygenales, Pneumocystales, Saccharomycetales and Schizosaccharomycetales (covering at least like all species of <em>Aspergillus</em>, <em>Candida</em>, <em>Pneumocystis</em>, <em>Saccharomyces</em> and <em>Trichophyton</em>)</li>
<li>All ~2,000 (sub)species from ~100 other relevant genera, from the kingdoms of Animalia and Plantae (like <em>Strongyloides</em> and <em>Taenia</em>)</li>
<li>All ~15,000 previously accepted names of included (sub)species that have been taxonomically renamed</li>
<li>
<p>The responsible author(s) and year of scientific publication</p>
This data is updated annually - check the included version with the new function <code><a href="https://msberends.gitlab.io/AMR/reference/catalogue_of_life_version.html">catalogue_of_life_version()</a></code>.</li>
<li>Due to this change, some <code>mo</code> codes changed (e.g. <em>Streptococcus</em> changed from <code>B_STRPTC</code> to <code>B_STRPT</code>). A translation table is used internally to support older microorganism IDs, so users will not notice this difference.</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/mo_property.html">mo_rank()</a></code> for the taxonomic rank (genus, species, infraspecies, etc.)</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/mo_property.html">mo_url()</a></code> to get the direct URL of a species from the Catalogue of Life</li>
</ul>
</li>
<li>Support for data from <a href="https://whonet.org/">WHONET</a> and <a href="https://ecdc.europa.eu/en/about-us/partnerships-and-networks/disease-and-laboratory-networks/ears-net">EARS-Net</a> (European Antimicrobial Resistance Surveillance Network):
<ul>
<li>Exported files from WHONET can be read and used in this package. For functions like <code><a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">first_isolate()</a></code> and <code><a href="https://msberends.gitlab.io/AMR/reference/eucast_rules.html">eucast_rules()</a></code>, all parameters will be filled in automatically.</li>
<li>This package now knows all antibiotic abbrevations by EARS-Net (which are also being used by WHONET) - the <code>antibiotics</code> data set now contains a column <code>ears_net</code>.</li>
<li>The function <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> now knows all WHONET species abbreviations too, because almost 2,000 microbial abbreviations were added to the <code>microorganisms.codes</code> data set.</li>
</ul>
</li>
<li>
<p>New filters for antimicrobial classes. Use these functions to filter isolates on results in one of more antibiotics from a specific class:</p>
<pre><code><a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_aminoglycosides</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_carbapenems</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_cephalosporins</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_1st_cephalosporins</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_2nd_cephalosporins</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_3rd_cephalosporins</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_4th_cephalosporins</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_fluoroquinolones</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_glycopeptides</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_macrolides</a>()
<a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_tetracyclines</a>()</code></pre>
<p>The <code>antibiotics</code> data set will be searched, after which the input data will be checked for column names with a value in any abbreviations, codes or official names found in the <code>antibiotics</code> data set. For example:</p>
<pre><code>septic_patients %>% <a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_glycopeptides</a>(result = "R")
# Filtering on glycopeptide antibacterials: any of `vanc` or `teic` is R
septic_patients %>% <a href="https://msberends.gitlab.io/AMR/reference/filter_ab_class.html">filter_glycopeptides</a>(result = "R", scope = "all")
# Filtering on glycopeptide antibacterials: all of `vanc` and `teic` is R</code></pre>
</li>
<li>
<p>All <code>ab_*</code> functions are deprecated and replaced by <code>atc_*</code> functions:</p>
<pre><code>ab_property -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_property</a>()
ab_name -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_name</a>()
ab_official -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_official</a>()
ab_trivial_nl -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_trivial_nl</a>()
ab_certe -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_certe</a>()
ab_umcg -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_umcg</a>()
ab_tradenames -> <a href="https://msberends.gitlab.io/AMR/reference/atc_property.html">atc_tradenames</a>()</code></pre>
These functions use <code><a href="https://msberends.gitlab.io/AMR/reference/as.atc.html">as.atc()</a></code> internally. The old <code>atc_property</code> has been renamed <code><a href="https://msberends.gitlab.io/AMR/reference/atc_online.html">atc_online_property()</a></code>. This is done for two reasons: firstly, not all ATC codes are of antibiotics (ab) but can also be of antivirals or antifungals. Secondly, the input must have class <code>atc</code> or must be coerable to this class. Properties of these classes should start with the same class name, analogous to <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> and e.g. <code>mo_genus</code>.</li>
<li>New functions <code><a href="https://msberends.gitlab.io/AMR/reference/mo_source.html">set_mo_source()</a></code> and <code><a href="https://msberends.gitlab.io/AMR/reference/mo_source.html">get_mo_source()</a></code> to use your own predefined MO codes as input for <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> and consequently all <code>mo_*</code> functions</li>
<li>Support for the upcoming <a href="https://dplyr.tidyverse.org"><code>dplyr</code></a> version 0.8.0</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/guess_ab_col.html">guess_ab_col()</a></code> to find an antibiotic column in a table</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">mo_failures()</a></code> to review values that could not be coerced to a valid MO code, using <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code>. This latter function will now only show a maximum of 10 uncoerced values and will refer to <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">mo_failures()</a></code>.</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">mo_uncertainties()</a></code> to review values that could be coerced to a valid MO code using <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code>, but with uncertainty.</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">mo_renamed()</a></code> to get a list of all returned values from <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> that have had taxonomic renaming</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/age.html">age()</a></code> to calculate the (patients) age in years</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/age_groups.html">age_groups()</a></code> to split ages into custom or predefined groups (like children or elderly). This allows for easier demographic antimicrobial resistance analysis per age group.</li>
<li>
<p>New function <code><a href="https://msberends.gitlab.io/AMR/reference/resistance_predict.html">ggplot_rsi_predict()</a></code> as well as the base R <code><a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot()</a></code> function can now be used for resistance prediction calculated with <code><a href="https://msberends.gitlab.io/AMR/reference/resistance_predict.html">resistance_predict()</a></code>:</p>
<pre><code>x <- <a href="https://msberends.gitlab.io/AMR/reference/resistance_predict.html">resistance_predict</a>(septic_patients, col_ab = "amox")
<a href="https://www.rdocumentation.org/packages/graphics/topics/plot">plot</a>(x)
<a href="https://msberends.gitlab.io/AMR/reference/resistance_predict.html">ggplot_rsi_predict</a>(x)</code></pre>
</li>
<li>
<p>Functions <code><a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">filter_first_isolate()</a></code> and <code><a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">filter_first_weighted_isolate()</a></code> to shorten and fasten filtering on data sets with antimicrobial results, e.g.:</p>
<pre><code>septic_patients %>% <a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">filter_first_isolate</a>(...)
# or
<a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">filter_first_isolate</a>(septic_patients, ...)</code></pre>
<p>is equal to:</p>
<pre><code>septic_patients %>%
mutate(only_firsts = <a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">first_isolate</a>(septic_patients, ...)) %>%
<a href="https://www.rdocumentation.org/packages/stats/topics/filter">filter</a>(only_firsts == TRUE) %>%
select(-only_firsts)</code></pre>
</li>
<li>New function <code><a href="https://msberends.gitlab.io/AMR/reference/availability.html">availability()</a></code> to check the number of available (non-empty) results in a <code>data.frame</code></li>
<li>
<p>New vignettes about how to conduct AMR analysis, predict antimicrobial resistance, use the <em>G</em>-test and more. These are also available (and even easier readable) on our website: <a href="https://msberends.gitlab.io/AMR">https://msberends.gitlab.io/AMR</a>.</p>
</li>
</ul>
<p>Changed</p>
<ul>
<li>Function <code><a href="https://msberends.gitlab.io/AMR/reference/eucast_rules.html">eucast_rules()</a></code>:
<ul>
<li>Updated EUCAST Clinical breakpoints to <a href="http://www.eucast.org/clinical_breakpoints/">version 9.0 of 1 January 2019</a>, the data set <code>septic_patients</code> now reflects these changes</li>
<li>Fixed a critical bug where some rules that depend on previous applied rules would not be applied adequately</li>
<li>Emphasised in manual that penicillin is meant as benzylpenicillin (ATC <a href="https://www.whocc.no/atc_ddd_index/?code=J01CE01">J01CE01</a>)</li>
<li>New info is returned when running this function, stating exactly what has been changed or added. Use <code><a href="https://msberends.gitlab.io/AMR/reference/eucast_rules.html">eucast_rules(..., verbose = TRUE)</a></code> to get a data set with all changed per bug and drug combination.</li>
</ul>
</li>
<li>Removed data sets <code>microorganisms.oldDT</code>, <code>microorganisms.prevDT</code>, <code>microorganisms.unprevDT</code> and <code>microorganismsDT</code> since they were no longer needed and only contained info already available in the <code>microorganisms</code> data set</li>
<li>Added 65 antibiotics to the <code>antibiotics</code> data set, from the <a href="http://ec.europa.eu/health/documents/community-register/html/atc.htm">Pharmaceuticals Community Register</a> of the European Commission</li>
<li>Removed columns <code>atc_group1_nl</code> and <code>atc_group2_nl</code> from the <code>antibiotics</code> data set</li>
<li>Functions <code><a href="https://msberends.gitlab.io/AMR/reference/AMR-deprecated.html">atc_ddd()</a></code> and <code><a href="https://msberends.gitlab.io/AMR/reference/AMR-deprecated.html">atc_groups()</a></code> have been renamed <code><a href="https://msberends.gitlab.io/AMR/reference/atc_online.html">atc_online_ddd()</a></code> and <code><a href="https://msberends.gitlab.io/AMR/reference/atc_online.html">atc_online_groups()</a></code>. The old functions are deprecated and will be removed in a future version.</li>
<li>Function <code><a href="https://msberends.gitlab.io/AMR/reference/AMR-deprecated.html">guess_mo()</a></code> is now deprecated in favour of <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code> and will be removed in future versions</li>
<li>Function <code><a href="https://msberends.gitlab.io/AMR/reference/AMR-deprecated.html">guess_atc()</a></code> is now deprecated in favour of <code><a href="https://msberends.gitlab.io/AMR/reference/as.atc.html">as.atc()</a></code> and will be removed in future versions</li>
<li>Improvements for <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo()</a></code>:
<ul>
<li>
<p>Now handles incorrect spelling, like <code>i</code> instead of <code>y</code> and <code>f</code> instead of <code>ph</code>:</p>
<pre><code># mo_fullname() uses as.mo() internally
<a href="https://msberends.gitlab.io/AMR/reference/mo_property.html">mo_fullname</a>("Sthafilokockus aaureuz")
#> [1] "Staphylococcus aureus"
<a href="https://msberends.gitlab.io/AMR/reference/mo_property.html">mo_fullname</a>("S. klossi")
#> [1] "Staphylococcus kloosii"</code></pre>
</li>
<li>
<p>Uncertainty of the algorithm is now divided into four levels, 0 to 3, where the default <code>allow_uncertain = TRUE</code> is equal to uncertainty level 2. Run <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">?as.mo</a></code> for more info about these levels.</p>
<pre><code># equal:
<a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo</a>(..., allow_uncertain = TRUE)
<a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo</a>(..., allow_uncertain = 2)
# also equal:
<a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo</a>(..., allow_uncertain = FALSE)
<a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo</a>(..., allow_uncertain = 0)</code></pre>
Using <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">as.mo(..., allow_uncertain = 3)</a></code> could lead to very unreliable results.</li>
<li>Implemented the latest publication of Becker <em>et al.</em> (2019), for categorising coagulase-negative <em>Staphylococci</em></li>
<li>All microbial IDs that found are now saved to a local file <code>~/.Rhistory_mo</code>. Use the new function <code><a href="https://msberends.gitlab.io/AMR/reference/as.mo.html">clean_mo_history()</a></code> to delete this file, which resets the algorithms.</li>
<li>
<p>Incoercible results will now be considered ‘unknown’, MO code <code>UNKNOWN</code>. On foreign systems, properties of these will be translated to all languages already previously supported: German, Dutch, French, Italian, Spanish and Portuguese:</p>
<pre><code><a href="https://msberends.gitlab.io/AMR/reference/mo_property.html">mo_genus</a>("qwerty", language = "es")
# Warning:
# one unique value (^= 100.0%) could not be coerced and is considered 'unknown': "qwerty". Use mo_failures() to review it.
#> [1] "(género desconocido)"</code></pre>
</li>
<li>Fix for vector containing only empty values</li>
<li>Finds better results when input is in other languages</li>
<li>Better handling for subspecies</li>
<li>Better handling for <em>Salmonellae</em>, especially the ‘city like’ serovars like <em>Salmonella London</em></li>
<li>Understanding of highly virulent <em>E. coli</em> strains like EIEC, EPEC and STEC</li>
<li>There will be looked for uncertain results at default - these results will be returned with an informative warning</li>
<li>Manual (help page) now contains more info about the algorithms</li>
<li>Progress bar will be shown when it takes more than 3 seconds to get results</li>
<li>Support for formatted console text</li>
<li>Console will return the percentage of uncoercable input</li>
</ul>
</li>
<li>Function <code><a href="https://msberends.gitlab.io/AMR/reference/first_isolate.html">first_isolate()</a></code>:
<ul>
<li>Fixed a bug where distances between dates would not be calculated right - in the <code>septic_patients</code> data set this yielded a difference of 0.15% more isolates</li>
<li>Will now use a column named like “patid” for the patient ID (parameter <code>col_patientid</code>), when this parameter was left blank</li>
<li>Will now use a column named like “key(…)ab” or “key(…)antibiotics
Unsupervised tracking of time-evolving data streams and an application to short-term urban traffic flow forecasting
No full textI am indebted to many people for their help and support I receive during my Ph.D. study and research at DIBRIS-University of Genoa. First and foremost, I would like to express my sincere thanks to my supervisors Prof.Dr. Masulli, and Prof.Dr. Rovetta for the invaluable guidance, frequent meetings, and discussions, and the encouragement and support on my way of research. I thanks all the members of the DIBRIS for their support and kindness during my 4 years Ph.D. I would like also to acknowledge the contribution of the projects Piattaforma per la mobilià Urbana con Gestione delle INformazioni da sorgenti eterogenee (PLUG-IN) and COST Action IC1406 High Performance Modelling and Simulation for Big Data Applications (cHiPSet). Last and most importantly, I wish to thanks my family: my wife Shaimaa who stays with me through the joys and pains; my daughter and son whom gives me happiness every-day; and my parents for their constant love and encouragement
Microgrid Operation and Control
No full textA Master of Science thesis in Electrical Engineering by Mohammad Saad Suleiman entitled, “Microgrid Operation and Control”, submitted in April 2021. Thesis advisor is Dr. Ahmed Osman-Ahmed and thesis co-advisor is Dr. Amr Mohamed El Nady. Soft copy is available (Thesis, Completion Certificate, Approval Signatures, and AUS Archives Consent Form).The world is moving toward renewable energy resources as a result of rising energy demand and the decline of fossil fuels. This move led to the shift of interest from the centralized conventional electric grids to decentralized smart grids. Microgrid is the basic structural unit of smart grid, it can utilize both renewable and non-renewable types of distributed generator (DG) technology. As many renewable DG technologies and storage elements are based on DC power, while many loads and devices depend on AC power, the importance of inverter-based DG technology increased. The output of these inverters in an islanded microgrid must achieve a good current sharing between DG unites in microgrid, maintaining stability and synchronization between DGs, and keeping voltages and frequencies within specific range. These criteria can be achieved with various control strategies including centralized control, master slave control, current distribution control and droop control methods. Consequently, the control and operation of microgrid is a challenging task that requires overcoming the obstacles relates to the nonlinearities and disturbances in the power system. In this thesis work, two feed-back control strategies were developed and implemented in droop control to operate multiple DG units in a microgrid. The two control strategies are state feedback control and hyperbolic tangent exponential Sliding Mode Control (SMC). The developed state feedback control provided a powerful performance with respect power sharing accuracy in steady state conditions and regulating the voltage and current disturbance caused by other DG units within the same microgrid. The proposed hyperbolic tangent exponential SMC utilizes the exponential SMC method and hyperbolic tangent reaching mode to provide robust, accurate, reliable behavior against unmodeled dynamics, hard nonlinearities, and parametric uncertainties. Furthermore, an experimental set is built to imitate a microgrid operation in real life application.College of EngineeringDepartment of Electrical EngineeringMaster of Science in Electrical Engineering (MSEE
Sequence analysis and identification of new isoform of EP4 receptors in different atlantic salmon tissues (Salmo salar L.) and its role in PGE2 induced immunomodulation in vitro.
Get PDFPGE2 plays an important role in a broad spectrum of physiological and pathological processes mediated through a membrane-bound G protein-coupled receptor (GPCR) called EP receptor. In mammals, four subtypes of EP receptor (EP 1-4) are identified and each of them functions through different signal transduction pathways. Orthologous EP receptors have also been identified in other non-mammalian species, such as chicken and zebrafish. EP4 is the only identified PGE2 receptor to date in Atlantic salmon but its tissue distribution and function have not been studied in any detail. In this study, we first sequenced EP4 receptor in different tissues and found that the presence of the 3nt deletion in the 5' untranslated region was accompanied by silent mutation at nt 668. While attempting to amplify the same sequence in TO cells (an Atlantic salmon macrophage-like cell line), we failed to obtain the full-length product. Further investigation revealed different isoform of EP4 receptor in TO cells and we subsequently documented its presence in different Atlantic salmon tissues. These two isoforms of EP4 receptor share high homology in their first half of sequence but differ in the second half part with several deletion segments though the final length of coding sequence is the same for two isoforms. We further studied the immunomodulation effect of PGE2 in TO cells and found that PGE2 inhibited the induction of CXCL-10, CCL-4, IL-8 and IL-1β genes expression in a time dependent manner and without cAMP upregulation
Comparison of Methods for Community Detection in Networks
No full textCommunity detection refers to extracting dense interacting nodes or subgraphs that form relevant aggregation (aka, communities) within networks. We present nine community detection methods based on different approaches, and we compare them on the Girvan-Newman community detection benchmark network. Two methods proposed by our group using spectral graph theory and fuzzy clustering obtain the best experimental results evaluated using the Omega Index
Layered ensemble model for short-term traffic flow forecasting with outlier detection
Get PDFYesReal time traffic flow forecasting is a necessary requirement for traffic management in order to be able to evaluate the effects of different available strategies or policies. This paper focuses on short-term traffic flow forecasting by taking into consideration both spatial (road links) and temporal (lag or past traffic flow values) information. We propose a Layered Ensemble Model (LEM) which combines Artificial Neural Networks and Graded Possibilistic Clustering obtaining an accurate forecast of the traffic flow rates with outlier detection. Experimentation has been carried out on two different data sets. The former was obtained from real UK motorway and the later was obtained from simulated traffic flow on a street network in Genoa (Italy). The proposed LEM model for short-term traffic forecasting provides promising results and given the ability for outlier detection, accuracy, robustness of the proposed approach, it can be fruitful integrated in traffic flow management systems
A scientometric analysis of <i>Knowledge Management Research and Practice</i> literature: 2003–2015
Get PDFThe purpose of this paper is to explore the current research trends in Knowledge Management (KM) through a scientometric analysis of all literature published in KMRP between 2003 and 2015 (506 articles). The review framework explores three sets of review questions addressing Research Productivity, Research Themes and Methods, and Citation Analysis. The study elucidates wide global interest in KM and an increasing trend towards multi-author collaboration. Although more than 55 different industries have featured in the journal, certain knowledge-intensive sectors remain underrepresented. Country productivity shows few nations taking the lead with an interesting correlation between research activity and economic prosperity. Moreover, a growing tendency towards empirical methods is observed in contrast to a decrease in literature review papers, coupled with a recent rise in articles that integrate KM and Information Technology (IT). In terms of citation and influences, few published articles have stood out in the journal’s history. This is the first comprehensive scientometric research of KMRP describes the state-of-the-art value and provides an outlook of the future
CAMRA: Copilot for AMR Annotation
Get PDFIn this paper, we introduce CAMRA (Copilot for AMR Annotatations), a
cutting-edge web-based tool designed for constructing Abstract Meaning
Representation (AMR) from natural language text. CAMRA offers a novel approach
to deep lexical semantics annotation such as AMR, treating AMR annotation akin
to coding in programming languages. Leveraging the familiarity of programming
paradigms, CAMRA encompasses all essential features of existing AMR editors,
including example lookup, while going a step further by integrating Propbank
roleset lookup as an autocomplete feature within the tool. Notably, CAMRA
incorporates AMR parser models as coding co-pilots, greatly enhancing the
efficiency and accuracy of AMR annotators. To demonstrate the tool's
capabilities, we provide a live demo accessible at: https://camra.colorado.eduComment: EMNLP 2023 System Demonstratio
A Simple Angle of Arrival Estimation System
Get PDFWe propose a practical, simple and hardware friendly, yet novel and very efficient, angle of arrival (AoA) estimation system. Our intuitive, two-phases cross-correlation based system requires a switched beam antenna array with a single radio frequency chain. Our system cross correlates a reference omni-directional signal with a set of received directed signals to determine the AoA. Practicality and high efficiency of our system are demonstrated through performance and complexity comparisons with multiple signal classification algorithm.Scopu
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