It is essential to analyze scientific literature when conducting review studies (systematic, narrative, etc.). Review articles can improve in quality by choosing or incorporating papers with high research impact. The ...
It is essential to analyze scientific literature when conducting review studies (systematic, narrative, etc.). Review articles can improve in quality by choosing or incorporating papers with high research impact. The quality of research has been measured using a variety of indicators. These metrics primarily address certain characteristics like the citation index. It is impossible to study the caliber of research in any field on an individual basis. It has to do with connections. Therefore, it would be advantageous to create a network of research items. In this study, we introduce a novel tool for the analysis of metadata in scientific literature. We tested our technique on the literature of breast cancer. The tool extracted 49,604 papers resulting in 575,894 nodes and 1,532,328edges. We looked at the topological and structural characteristics of the constructed network, briefly. However, this tool can be utilized in any other domain of interest.
Health insurance eligibility services (HIES) are being used in modern health care systems widely. The most important advantage of HIESs is their capability to provide fast, reliable, and real-time information about th...
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作者:
Ekstein, JanFleischner, HerbertDepartment of Mathematics
European Centre of Excellence Ntis - New Technologies for the Information Society Faculty of Applied Sciences University of West Bohemia Pilsen Technická 8 Plzeň306 14 Czech Republic Institute of Logic and Computation
Algorithms and Complexity Group Technical University of Vienna Favoritenstrasse 9 - 11 Wien1040 Austria
On the basis of recent results on hamiltonicity, [4], and hamiltonian connectedness, [8], in the square of a 2-block, we determine the most general block-cutvertex structure a graph G may have in order to guarantee th...
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We investigate whether it is possible to teleport the coherence of an unknown quantum state from Alice to Bob by communicating a smaller number of classical bits in comparison to what is required for teleporting an un...
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We investigate whether it is possible to teleport the coherence of an unknown quantum state from Alice to Bob by communicating a smaller number of classical bits in comparison to what is required for teleporting an unknown quantum state. We find that we cannot achieve perfect teleportation of coherence with one bit of classical communication for an arbitrary qubit. However, we find that if the qubit is partially known, i.e., chosen from the equatorial and polar circles of the Bloch sphere, then teleportation of coherence is possible with the transfer of one cbit of information when we have maximally entangled states as a shared resource. In the case of the resource being a nonmaximally entangled state, we can teleport the coherence with a certain probability of success. In a general teleportation protocol for coherence, we derive a compact formula for the final state at Bob's laboratory in terms of the composition of the completely positive maps corresponding to the shared resource state and a joint positive operator-valued measure (POVM) performed by Alice on her qubit and the unknown state. Using this formula, we show that teleportation of the coherence of a partially known state with real matrix elements is perfectly possible with the help of a maximally entangled state as a resource. Furthermore, we explore the teleportation of coherence with Werner states and show that even when Werner states become separable, the amount of teleported coherence is nonzero, implying the possibility of teleportation of coherence without entanglement.
Association rule mining, one of the most important branches of data mining, which focused on detecting frequent patterns of itemsets. Apriori is the first algorithm proposed for association rule mining. This algorithm...
Association rule mining, one of the most important branches of data mining, which focused on detecting frequent patterns of itemsets. Apriori is the first algorithm proposed for association rule mining. This algorithm has the best response and can detect all frequent itemsets from transaction databases. Apriori is of time complexity order two to the power n at worst case, n is the number of items in the database. At each step, the database is scanned to detect frequent itemsets. As a result, this algorithm has a very large response time for large databases. There are two ways to reduce the response time of this algorithm. First, prune the itemsets which candidate for checking. Second, reduce the dimension of the database. We used the second solution and reduce the dimension of the database considering that if a set is frequent, all of its subsets are frequent with more frequencies in the database. In the proposed algorithm, database scanned one time, and then frequent itemsets are detected by the reduced database. Our algorithm improved an apriori response time. To evaluate the algorithm, precision and recall measures have been used. According to the experimental in most cases, the algorithm can provide precision and recall above ninety percent.
The increase of receiving attention to music recommendation and playlist generation in today's music industry is undeniable. One of the main goals is to generate personalized playlists automatically for each user....
The increase of receiving attention to music recommendation and playlist generation in today's music industry is undeniable. One of the main goals is to generate personalized playlists automatically for each user. Beyond that, an appropriate switching among these playlists to play the tracks based on the current mood of the user would certainly lead to the development of more advanced and personalized music player apps. In this paper, a data scientific approach is provided to model the music moods which are created by clustering the tracks extracted from users' listening. Each Cluster consists of music tracks with similar audio features existing in the user's listening history. Knowing which music track is currently being listened by users, their mood would be specified by determining the cluster of that music. It is presumed that playing the other music tracks contained in the same cluster as the next tracks will enhance their satisfaction. A suggestion for making the results visually interpretable which could help the corresponding music players with GUI design is provided as well. Experimental results of a case study from real datasets collected from Users' listening history on *** benefiting from Spotify API clarifies the framework along with supporting the mentioned presumption.
In July 2023,the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 *** report summarizes the rich discussions that occ...
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In July 2023,the Center of Excellence in Respiratory Pathogens organized a two-day workshop on infectious diseases modelling and the lessons learnt from the Covid-19 *** report summarizes the rich discussions that occurred during the *** workshop participants discussed multisource data integration and highlighted the benefits of combining traditional surveillance with more novel data sources like mobility data,social media,and wastewater *** advancements were noted in the development of predictive models,with examples from various countries showcasing the use of machine learning and artificial intelligence in detecting and monitoring disease *** role of open collaboration between various stakeholders in modelling was stressed,advocating for the continuation of such partnerships beyond the pandemic.A major gap identified was the absence of a common international framework for data sharing,which is crucial for global pandemic ***,the workshop underscored the need for robust,adaptable modelling frameworks and the integration of different data sources and collaboration across sectors,as key elements in enhancing future pandemic response and preparedness.
It is shown that for any choice of four different vertices x1,...,x4 in a 2-block G of order p > 3, there is a hamiltonian cycle in G2 containing four different edges xiyi of E(G) for certain vertices yi, i = 1,2,3...
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Adaptivity is a dynamical feature that is omnipresent in nature, socio-economics, and technology. For example, adaptive couplings appear in various real-world systems like the power grid, social, and neural networks, ...
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Quantum computers offer an intriguing path for a paradigmatic change of computing in the natural sciences and beyond, with the potential for achieving a so-called quantum advantage, namely a significant (in some cases...
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