ORCID Profile
0000-0002-9059-330X
Current Organisation
Deakin University
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Research Topics
In Research Link Australia (RLA), "Research Topics" refer to ANZSRC FOR and SEO codes. These topics are either sourced from ANZSRC FOR and SEO codes listed in researchers' related grants or generated by a large language model (LLM) based on their publications.
Top 5 Research Topics
ANZSRC Field of Research (FoR)
Information Systems | Database Management | Data and information privacy | Computer vision and multimedia computation | Pattern Recognition and Data Mining | Pattern recognition | Graph social and multimedia data |
ANZSRC Socio-Economic Objective (SEO)
Electronic Information Storage and Retrieval Services | Learner and Learning not elsewhere classified | Information Processing Services (incl. Data Entry and Capture) |
Related Links
Publications
Machine learning-aided design and prediction of cementitious composites containing graphite and slag powder
Publisher: Elsevier BV
Date: 11-2021
One-step approach for synthesis of nanosized Cu-doped zeolite A crystals using the Cu-EDTA-complex
Publisher: Elsevier BV
Date: 11-2014
Interface phenomena in synroc, a titanate-based nuclear waste ceramic
Publisher: Elsevier
Date: 1995
Coupled online sequential extreme learning machine model with ant colony optimization algorithm for wheat yield prediction
Publisher: Springer Science and Business Media LLC
Date: 31-03-2022
DOI: 10.1038/S41598-022-09482-5
Abstract: Inadequate agricultural planning compounded by inaccurate predictions results in an inflated local market rate and prompts higher importation of wheat. To tackle this problem, this research has designed two-phase universal machine learning (ML) model to predict wheat yield (W pred ), utilizing 27 agricultural counties’ data within the Agro-ecological zone. The universal model, online sequential extreme learning machines coupled with ant colony optimization (ACO-OSELM) is developed, by incorporating the significant annual yield data lagged at ( t − 1) as the model’s predictor to generate future yield at 6 test stations. In the first phase, ACO is adopted to search for suitable, statistically relevant data stations for model training, and the corresponding test station by virtue of a feature selection strategy. An annual wheat yield time-series input dataset is constructed utilizing data from each selected training station (1981–2013) and applied against 6 test stations (with each case modelled with 26 station data as the input) to evaluate the hybrid ACO-OSELM model. The partial autocorrelation function is implemented to deduce statistically significant lagged data, and OSELM is applied to generate W pred . The two-phase hybrid ACO-OSELM model is tested within the 6 agricultural districts (represented as stations) of Punjab province, Pakistan and the results are benchmarked with extreme learning machine (ELM) and random forest (RF) integrated with ACO (i.e., hybrid ACO-ELM and hybrid ACO-RF models, respectively). The performance of the ACO-OSELM model was proven to be good in comparison to ACO-ELM and ACO-RF models. The hybrid ACO-OSELM model revealed its potential to be implemented as a decision-making system for crop yield prediction in areas where a significant association with the historical agricultural crop is well-established.
High-temperature study of CaZrTi2 O7
Publisher: Elsevier BV
Date: 08-1992
Deep attributed network representation learning of complex coupling and interaction
Publisher: Elsevier BV
Date: 2021
A Vehicular Task Offloading Method With Eliminating Redundant Tasks in 5G HetNets
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2023
Efficient Maximal Biclique Enumeration for Large Sparse Bipartite Graphs
Publisher: Association for Computing Machinery (ACM)
Date: 04-2022
Abstract: Maximal bicliques are effective to reveal meaningful information hidden in bipartite graphs. Maximal biclique enumeration (MBE) is challenging since the number of the maximal bicliques grows exponentially w.r.t. the number of vertices in a bipartite graph in the worst case. However, a large bipartite graph is usually very sparse, which is against the worst case and may lead to fast MBE algorithms. The uncharted opportunity is taking advantage of the sparsity to substantially improve the MBE efficiency for large sparse bipartite graphs. We observe that for a large sparse bipartite graph, a vertex u may converge to a few vertices in the same vertex set as u via its neighbours, which reveals that the enumeration scope for a vertex could be very small. Based on this observation, we propose novel concepts: unilateral coreness for in idual vertices, unilateral order for each vertex set and unilateral convergence (ζ) for a large sparse bipartite graph, ζ could be a few thousand for a large sparse bipartite graph with hundreds of million edges. Using the unilateral order, every vertex with τ unilateral coreness only needs to check at most 2 τ combinations so that all maximal bicliques can be enumerated and τ is bounded by ζ, which leads to a novel MBE algorithm running in O * (2 ζ ). We then propose a batch-pivots technique to eliminate all enumerations resulting in non-maximal bicliques, which guarantees that every maximal biclique is reported in O (ζ e )-delay, where e is the number of edges. We devise novel data structures that allow storing subgraphs at omissible space for further speeding up MBE. Extensive experiments are conducted on synthetic and real large datasets to justify that our proposed algorithm is faster and more scalable than the existing algorithms.
Antiferromagnetism in a technetium oxide. Structure of catco3
Publisher: American Chemical Society (ACS)
Date: 26-01-2011
DOI: 10.1021/JA109431T
Abstract: The technetium perovskite CaTcO(3) has been synthesized. Combining synchrotron X-ray and neutron diffraction, we found that CaTcO(3) is an antiferromagnetic with a surprisingly high Neel temperature of ∼800 K. The transition to the magnetic state does not involve a structural change, but there is obvious magnetostriction. Electronic structure calculations confirm the experimental results.
Incremental Graph Computation: Anchored Vertex Tracking in Dynamic Social Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
RLCC: Practical Learning-based Congestion Control for the Internet
Publisher: IEEE
Date: 18-07-2021
High Temperature Magnetic Ordering in the4 d
Publisher:
American Physical Society (APS)
Date:
07-02-2011
Publisher: American Physical Society (APS)
Date: 07-02-2011
Novel rattling of K atoms in aluminium-doped defect pyrochlore tungstate.
Publisher: IOP Publishing
Date: 04-07-2014
DOI: 10.1088/0953-8984/26/30/305401
Abstract: Rattling dynamics have been identified as fundamental to superconductivity in defect pyrochlore osmates and aluminium vanadium intermetallics, as well as low thermal conductivity in clathrates and filled skutterudites. Combining inelastic neutron scattering (INS) measurements and ab initio molecular dynamics (MD) simulations, we use a new approach to investigate rattling in the Al-doped defect pyrochlore tungstates: AAl0.33W1.67O6 (A = K, Rb, Cs). We find that although all the alkali metals rattle, the rattling of the K atoms is unique, not only among the tungstates but also among the analogous defect osmates, KOs2O6 and RbOs2O6. Detailed analysis of the MD trajectories reveals that two unique features set the K dynamics apart from the rest, namely, (1) quasi one-dimensional local diffusion within a cage, and (2) vibration at a range of frequencies. The local diffusion is driven by strongly anharmonic local potentials around the K atoms exhibiting a double-well structure in the direction of maximum displacement, which is also the direction of local diffusion. On the other hand, vibration at a range of frequencies is a consequence of the strong anisotropy in the local potentials around the K atoms as revealed by directional magnitude spectra. We present evidence to show that it is the smaller size rather than the smaller mass of the K rattler which leads to the unusual dynamics. Finally, we suggest that the occurrence of local diffusion and vibration at a range of frequencies in the dynamics of a single rattler, as found here for the K atoms, may open new possibilities for phonon engineering in thermoelectric materials.
Asymmetric Commutative Encryption Scheme Based Efficient Solution to the Millionaires' Problem
Publisher: IEEE
Date: 08-2018
Database Systems for Advanced Applications - DASFAA 2018 International Workshops: BDMS, BDQM, GDMA, and SeCoP, Gold Coast, QLD, Australia, May 21-24, 2018, Proceedings
Publisher: Springer International Publishing
Date: 2018
On the origin of strengthening mechanisms in Ni-Mo alloys prepared via powder metallurgy
Publisher: Elsevier BV
Date: 2017
CBML: A Cluster-based Meta-learning Model for Session-based Recommendation
Publisher: ACM
Date: 26-10-2021
Summary: 2021 International Consultation on Incontinence Evidence-Based Surgical Pathway for Pelvic Organ Prolapse
Publisher: MDPI AG
Date: 17-10-2022
DOI: 10.3390/JCM11206106
Abstract: (1) Background: There is wide variation in the reported prevalence rates for pelvic organ prolapse (POP). There is also wide variation in the rate at which surgical interventions for pelvic organ prolapse are performed, as well as the type of interventions undertaken. As part of the International Consultation on Incontinence (ICI), our committee was tasked to produce evidence-based pathways for the surgical management of POP, any associated stress urinary incontinence (SUI), and bowel dysfunction. (2) Methods: To enable us to generate such evidence, we undertook a thorough search for the POP surgery-related, English-language scientific literature published up to April 2021. (3) Results: The committee evaluated the literature and made recommendations based on the Oxford grading system. (4) Conclusions: This review serves to provide a summary of the 2021 ICI surgical management of an evidence-based prolapse pathway and outline the evidence used to inform this guidance.
Microstructure of Cr (N,O) thin films studied by high resolution transmission electron microscopy
Publisher: Elsevier BV
Date: 03-2017
The flexible socio spatial group queries
Publisher: Association for Computing Machinery (ACM)
Date: 10-2018
Abstract: A socio spatial group query finds a group of users who possess strong social connections with each other and have the minimum aggregate spatial distance to a meeting point. Existing studies limit to either finding the best group of a fixed size for a single meeting location, or a single group of a fixed size w.r.t. multiple locations. However, it is highly desirable to consider multiple locations in a real-life scenario in order to organize impromptu activities of groups of various sizes. In this paper, we propose Top k Flexible Socio Spatial Group Query (Top k-FSSGQ) to find the top k groups w.r.t. multiple POIs where each group follows the minimum social connectivity constraints. We devise a ranking function to measure the group score by combining social closeness, spatial distance, and group size, which provides the flexibility of choosing groups of different sizes under different constraints. To effectively process the Top k-FSSGQ, we first develop an Exact approach that ensures early termination of the search based on the derived upper bounds. We prove that the problem is NP-hard, hence we first present a heuristic based approximation algorithm to effectively select members in intermediate solution groups based on the social connectivity of the users. Later we design a Fast Approximate approach based on the relaxed social and spatial bounds, and connectivity constraint heuristic. Experimental studies have verified the effectiveness and efficiency of our proposed approaches on real datasets.
Immobilization of iodine via copper iodide
Publisher: Elsevier BV
Date: 07-2018
Discovering Transit-Oriented Development Regions of Megacities Using Heterogeneous Urban Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Reliable community search in dynamic networks
Publisher: Association for Computing Machinery (ACM)
Date: 07-2022
Abstract: Searching for local communities is an important research problem that supports advanced data analysis in various complex networks, such as social networks, collaboration networks, cellular networks, etc. The evolution of such networks over time has motivated several recent studies to identify local communities in dynamic networks. However, these studies only utilize the aggregation of disjoint structural information to measure the quality and ignore the reliability of the communities in a continuous time interval. To fill this research gap, we propose a novel (θ, k )- core reliable community (CRC) model in the weighted dynamic networks, and define the problem of most reliable community search that couples the desirable properties of connection strength, cohesive structure continuity, and the maximal member engagement. To solve this problem, we first develop a novel edge filtering based online CRC search algorithm that can effectively filter out the trivial edge information from the networks while searching for a reliable community. Further, we propose an index structure, Weighted Core Forest-Index (WCF-index), and devise an index-based dynamic programming CRC search algorithm, that can prune a large number of insignificant intermediate results and support efficient query processing. Finally, we conduct extensive experiments systematically to demonstrate the efficiency and effectiveness of our proposed algorithms on eight real datasets under various experimental settings.
Towards both Local and Global Query Result Diversification
Publisher: Springer International Publishing
Date: 2019
High temperature transformations of the Au7 Cu5 Al 4 shape-memory alloy
Publisher: Elsevier BV
Date: 02-2011
Temporal Interaction Biased Community Detection in Social Networks
Publisher: Springer International Publishing
Date: 2016
Geo-Social Influence Spanning Maximization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2017
Secure Range Query over Encrypted Data in Outsourced Environments
Publisher: Springer International Publishing
Date: 2018
Finding maximal k-edge-connected subgraphs from a large graph
Publisher: ACM
Date: 27-03-2012
Analysis and Modeling for Big Data in Cancer Research
Publisher: Hindawi Limited
Date: 2017
DOI: 10.1155/2017/1972097
Message from the ISPA-2020 general chairs ISPA-BDCloud-SocialCom-SustainCom 2020
Publisher: IEEE
Date: 12-2020
DOI: 10.1109/ISPA-BDCLOUD-SOCIALCOM-SUSTAINCOM51426.2020.00005
Context-Based Diversification for Keyword Queries Over XML Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2015
C-SIW Rumor Propagation Model with Variable Propagation Rate and Perception Mechanism in Social Networks
Publisher: Hindawi Limited
Date: 05-08-2020
DOI: 10.1155/2020/5712968
Abstract: The propagation of rumor has become a common phenomenon in social networks. Studying the dynamic propagation of rumor can help locate the key points to control rumor propagation. To further research the internal motivation of state transition, a corrector-ignorant-spreader-weakener (C-SIW) model is proposed in this paper. When the in idual changes state to transmit rumor, the neighbor may have a significant impact on rumor propagation. Considering the point, this paper constructs a function to describe the propagation rate, which relates to the state of neighbors and the reputation of the spreader. In addition, perception from life also can cause in idual state changes. Based on the above fact, the links from the spreader and the weakener to the corrector are added to describe the perception mechanism. Then, combining the derived average field equations, the steady state of the model is analyzed and verified in experimental simulation. Moreover, the experimental results on different networks show that the perception mechanism reduces the rumor influence. Besides, the variable propagation rate can position the fast-growing stage of rumor propagation more accurately and facilitate the control of rumor propagation.
The stability of Na-doped Bi2 (NbCr)O7-x pyrochlores: The non-existence of (BiNa)(NbCr)O6
Publisher: Elsevier BV
Date: 04-2008
EBSS: A secure blockchain-based sharing scheme for real estate financial credentials
Publisher: Springer Science and Business Media LLC
Date: 04-10-2022
Semi-Supervised Community Detection via Constraint Matrix Construction and Active Node Selection
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Secure Boolean Spatial Keyword Query With Lightweight Access Control in Cloud Environments
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-01-2222
CrashSim: An Efficient Algorithm for Computing SimRank over Static and Temporal Graphs
Publisher: IEEE
Date: 04-2020
When geo-text meets security: Privacy-preserving boolean spatial keyword queries
Publisher: IEEE
Date: 04-2019
Structure, crystal chemistry and magnetism of rare earth calcium-doped cobaltates: Ln2−xCaxCoO4+δ (Ln = Pr, Nd, Sm, Eu and Gd)
Publisher: Elsevier BV
Date: 12-2011
A Sentiment Analysis Method of Capsule Network Based on BiLSTM
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Pdke: an efficient distributed embedding framework for large knowledge graphs
Publisher: Springer International Publishing
Date: 2020
Cardiovascular Diseases Risk Assessment among South and South-East Asian Migrants Living in Greater Sydney, Australia: A Cross-Sectional Study
Publisher: ClinMed International Library
Date: 31-12-2022
Top-k Socio-Spatial Co-engaged Location Selection for Social Users
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
A Shared Bus Profiling Scheme for Smart Cities Based on Heterogeneous Mobile Crowdsourced Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2020
Finding smallest k-Compact tree set for keyword queries on graphs using mapreduce
Publisher: Springer Science and Business Media LLC
Date: 24-03-2015
Optimal Subgraph Matching Queries over Distributed Knowledge Graphs Based on Partial Evaluation
Publisher: Springer International Publishing
Date: 2021
ELCA evaluation for keyword search on probabilistic XML data
Publisher: Springer Science and Business Media LLC
Date: 16-05-2012
dLow Temperature of formation of Nickel Germanide by reaction of Nickel and Crystalline Germanium
Publisher: Springer Science and Business Media LLC
Date: 2014
DOI: 10.1557/OPL.2014.408
Abstract: The formation of nickel germanide has been examined over a range of low temperatures (200-400 °C) in an attempt to minimize the thermal budget for the process. Cross-sectional Transmission Electron Microscopy (TEM) was used to determine the texture of the germanide layer and the morphology and constituent composition of the Ge/NiGe interface. The onset and completion of reaction between Ni and Ge were identified by means of a heated stage in combination with in-situ x-ray diffraction (XRD) measurements. The stages of reaction were also monitored using measurements of sheet resistance of the germanides by the Van der Pauw technique. The results have shown that the minimum temperature for the initiation of reaction of Ni and Ge to form NiGe was 225 °C. However, an annealing temperature 275 °C was necessary for the extensive (and practical) formation of NiGe. Between 200 and 300 °C, the duration of annealing required for the formation of NiGe was significantly longer than at higher temperatures. The stoichiometry of the germanide was very close to NiGe (1:1) as determined using energy dispersive spectroscopy (EDS).
Structural and spectroscopic studies of Ba2 Y1−δ UO6+x
Publisher: Elsevier BV
Date: 11-2016
Unbalanced Multi-view Deep Learning
Publisher: ACM
Date: 26-10-2023
Efficient Answering of Why-Not Questions in Similar Graph Matching
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2015
Technetium and ruthenium incorporation into rutile TiO2
Publisher: Elsevier BV
Date: 10-2013
GoMIC: Multi-view image clustering via self-supervised contrastive heterogeneous graph co-learning
Publisher: Springer Science and Business Media LLC
Date: 12-10-2022
DOI: 10.1007/S11280-022-01110-6
Abstract: Graph learning is being increasingly applied to image clustering to reveal intra-class and inter-class relationships in data. However, existing graph learning-based image clustering focuses on grouping images under a single view, which under-utilises the information provided by the data. To address that, we propose a self-supervised multi-view image clustering technique under contrastive heterogeneous graph learning. Our method computes a heterogeneous affinity graph for multi-view image data. It conducts Local Feature Propagation (LFP) for reasoning over the local neighbourhood of each node and executes an Influence-aware Feature Propagation (IFP) from each node to its influential node for learning the clustering intention. The proposed framework pioneeringly employs two contrastive objectives. The first targets to contrast and fuse multiple views for the overall LFP embedding, and the second maximises the mutual information between LFP and IFP representations. We conduct extensive experiments on the benchmark datasets for the problem, i.e. COIL-20, Caltech7 and CASIA-WebFace. Our evaluation shows that our method outperforms the state-of-the-art methods, including the popular techniques MVGL, MCGC and HeCo.
Empowering A* Algorithm With Neuralized Variational Heuristics for Fastest Route Recommendation
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2023
The role of π-bonding on the high temperature structure of the double perovskites Ba2 CaUO6 and BaSrCaUO6
Publisher: Royal Society of Chemistry (RSC)
Date: 2015
DOI: 10.1039/C5DT02663F
Abstract: High temperature synchrotron X-ray and neutron diffraction powder diffraction studies of the uranium perovskites Ba 2 CaUO 6 and BaSrCaUO 6 reveal unusual phase transition behavior associated with the progressive loss of cooperative octahedral tilting.
Proprioceptive Opsin Functions in Drosophila Larval Locomotion
Publisher: Elsevier BV
Date: 04-2018
DOI: 10.1016/J.NEURON.2018.02.028
Abstract: Animals rely on mechanosensory feedback from proprioceptors to control locomotory body movements. Unexpectedly, we found that this movement control requires visual opsins. Disrupting the Drosophila opsins NINAE or Rh6 impaired larval locomotion and body contractions, independently of light and vision. Opsins were detected in chordotonal proprioceptors along the larval body, localizing to their ciliated dendrites. Loss of opsins impaired mechanically evoked proprioceptor spiking and cilium ultrastructure. Without NINAE or Rh6, NOMPC mechanotransduction channels leaked from proprioceptor cilia and ciliary Inactive (Iav) channels partly disappeared. Locomotion is shown to require opsins in proprioceptors, and the receptors are found to express the opsin gene Rh7, in addition to ninaE and Rh6. Besides implicating opsins in movement control, this documents roles of non-ciliary, rhabdomeric opsins in cilium organization, providing a model for a key transition in opsin evolution and suggesting that structural roles of rhabdomeric opsins preceded their use for light detection.
Structural studies of the rhombohedral and orthorhombic monouranates: CaUO4 , α-SrUO4 , β-SrUO4 and BaUO4
Publisher: Elsevier BV
Date: 05-2016
Correction to: Database Systems for Advanced Applications
Publisher: Springer International Publishing
Date: 2019
Efficient Batch Processing for Multiple Keyword Queries on Graph Data
Publisher: ACM
Date: 24-10-2016
Charge trapping and defect segregation in quartz
Publisher: AIP Publishing
Date: 07-1999
DOI: 10.1063/1.370718
Abstract: Irradiation induced charging of wide band gap materials may significantly influence the development of radiation damage and associated defect migration. Charge trapped at irradiation induced and/or pre-existing defects induces a localized electric field within the irradiated volume of specimen. The powerful combination of cathodoluminescence microanalysis and electric force microscopy allows direct monitoring of the development of the irradiation induced charge distribution and its effect on the microscopic spatial segregation of defects. These techniques have been used to demonstrate the important influence of the induced local field on the microscopic defect structure of quartz.
Structural studies of the aeschynite-euxenite transformation in the series Ln(TiTa)O6 Ln = Lanthanide
Publisher: Elsevier BV
Date: 07-2010
Efficient Sample Location Selection for Query Zone in Geo-Social Networks
Publisher: Hindawi Limited
Date: 17-12-2021
DOI: 10.1155/2021/2581288
Abstract: While promoting a business or activity in geo-social networks, the geographical distance between its location and users is critical. Therefore, the problem of Distance-Aware Influence Maximization (DAIM) has been investigated recently. The efficiency of DAIM heavily relies on the s le location selection. Specifically, the online seeding performance is sensitive to the distance between the promoted location and its nearest s le location, and the offline precomputation performance is sensitive to the number of s le locations. However, there is no work to fully study the problem of s le location selection for DAIM in geo-social networks. To do this, we first formalize the problem under a reasonable assumption that a promoted location always adheres to the distribution of users (query zone). Then, we propose two efficient location s ling approaches based on facility location analysis, which is one of the most well-studied areas of operations research, and these two approaches are denoted by Facility Location based S ling (FLS) and Conditional Facility Location Based S ling (CFLS), respectively. FLS conducts one-time s le location selection, and CFLS extends the one-time s le location selection to a continuous process, so that an online advertising service can be started immediately without s ling a lot of locations. Our experimental results on two real datasets demonstrate the effectiveness and efficiency of the proposed methods. Specifically, both FLS and CFLS can achieve better performance than the existing s ling methods for the DAIM problem, and CFLS can initialize the online advertising service in a matter of seconds and achieve better objective distance than FLS after s ling a large number of s le locations.
Cation antisite disorder in uranium-doped gadolinium zirconate pyrochlores
Publisher: Elsevier BV
Date: 09-2014
XBridge-Mobile: efficient XML keyword search on mobile web data
Publisher: Springer Science and Business Media LLC
Date: 06-03-2014
Intricate disorder in defect fluorite/pyrochlore: a concord of chemistry and crystallography
Publisher: Springer Science and Business Media LLC
Date: 16-06-2017
DOI: 10.1038/S41598-017-02787-W
Abstract: Intuitively scientists accept that order can emerge from disorder and a significant amount of effort has been devoted over many years to demonstrate this. In metallic alloys and oxides, disorder at the atomic scale is the result of occupation at equivalent atomic positions by different atoms which leads to the material exhibiting a fully random or modulated scattering pattern. This arrangement has a substantial influence on the material’s properties, for ex le ionic conductivity. However it is generally accepted that oxides, such as defect fluorite as used for nuclear waste immobilization matrices and fuel cells, are the result of disorder at the atomic scale. To investigate how order at the atomic scale induces disorder at a larger scale length, we have applied different techniques to study the atomic composition of a homogeneous La 2 Zr 2 O 7 pyrochlore, a textbook ex le of such a structure. Here we demonstrate that a pyrochlore, which is considered to be defect fluorite, is the result of intricate disorder due to a random distribution of fully ordered nano-domains. Our investigation provides new insight into the order disorder transformations in complex materials with regards to domain formation, resulting in a concord of chemistry with crystallography illustrating that order can induce disorder.
Web of Students: Class-Level Friendship Network Discovery from Educational Big Data
Publisher: Springer International Publishing
Date: 2021
A cooperative mobility model for multiple autonomous vehicles
Publisher: Elsevier BV
Date: 11-2022
Overview of Influence Maximization in Social Media Data Analytics
Publisher: ACM Press
Date: 2017
MODEL: Motif-Based Deep Feature Learning for Link Prediction
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2020
The Optimal Distribution of Electric-Vehicle Chargers across a City
Publisher: IEEE
Date: 12-2016
Finding Effective Geo-social Group for Impromptu Activities with Diverse Demands
Publisher: ACM
Date: 20-08-2020
Comparing results of X-ray diffraction, µ-Raman spectroscopy and neutron diffraction when identifying chemical phases in seized nuclear material, during a comparative nuclear forensics exercise
Publisher: Springer Science and Business Media LLC
Date: 24-01-2018
Guest Editorial: Advanced Complex Data Analytics for Smart City Industrial Environment
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2021
Analyzing the Implementation of Policies and Guidelines for the Prevention and Management of Type 2 Diabetes at Primary Health Care Level in Nepal
Publisher: Frontiers Media SA
Date: 09-02-2022
DOI: 10.3389/FPUBH.2022.763784
Abstract: Nepal, in recent years, is witnessing an increasing problem of type 2 diabetes that has resulted significant premature deaths and disability. Prevention and management of non-communicable diseases (NCDs) including diabetes have been prioritized in the national policies and guidelines of the Nepal Government. However, research looking at the overview of the implementation of the existing policies and guidelines for diabetes prevention and control is scarce. Hence, this study reviewed diabetes related existing policies and its implementation process at the primary health care level in Nepal. This study involved two phases: Phase I: situation analyses through review of documents and Phase II: qualitative exploratory study. In phase I, four databases (Medline, Web of Science, Embase and PubMed) were systematically searched using key search terms related to diabetes care and policies between January 2000 and June 2021. Also, relevant gray literature was reviewed to understand the trajectory of policy development and its translation with regards to diabetes prevention and management at primary health care level in Nepal. Following the phase I, we conducted in-depth interviews (IDI) and key informant interviews (KII) with health care providers, policy makers, and managers (IDI = 13, and KII = 7) at peripheral and central levels in Kavrepalanchowk and Nuwakot districts of Nepal. The in-depth interviews were audio recorded, transcribed, and coded. The triangulation of data from document review and interviews was done and presented in themes. Four key themes were identified through triangulating findings from the document review and interviews including (i) limited implementation of policies into practices (ii) lack of coordination among the different levels of service providers (iii) lack of trained human resources for health and inadequate quality services at the primary health care level, and (iv) inadequate access and utilization of diabetes care services at primary health care level. Specifically, this study identified some key pertinent challenges to the implementation of policies and programs including inadequate resources, limited engagement of stakeholders in service design and delivery, lack of trained health care providers, lack of financial resources to strengthen peripheral health services, fragmented health governance, and weak reporting and monitoring systems. This study revealed that the policies, plans, and strategies for prevention and management of NCDs in Nepal recognized the importance of diabetes prevention and control. However, a major gap remains with adequate and lack of clarity in terms of implementation of available policies, plans, strategies, and programs to address the problem of diabetes. We suggest the need for multisectoral approach (engaging both health and non-health sectors) at central as well as peripheral levels to strengthen the policies implementation process, building capacity of health care providers, ensuring adequate financial and non-financial resources, and improving quality of services at primary health care levels.
Progressive Average-Based Smart Meter Privacy Enhancement Using Rechargeable Batteries
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 12-2019
Anchored vertex exploration for community engagement in social networks
Publisher: IEEE
Date: 04-2020
LSFL: A Lightweight and Secure Federated Learning Scheme for Edge Computing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Capturing Local and Global Spatial-Temporal Correlations of Spatial-Temporal Graph Data for Traffic Flow Prediction
Publisher: IEEE
Date: 18-07-2022
Exploring Human Mobility Patterns in Urban Scenarios: A Trajectory Data Perspective
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 03-2018
A Novel Chinese Entity Relationship Extraction Method Based on the Bidirectional Maximum Entropy Markov Model
Publisher: Hindawi Limited
Date: 19-01-2021
DOI: 10.1155/2021/6610965
Abstract: To identify relationships among entities in natural language texts, extraction of entity relationships technically provides a fundamental support for knowledge graph, intelligent information retrieval, and semantic analysis, promotes the construction of knowledge bases, and improves efficiency of searching and semantic analysis. Traditional methods of relationship extraction, either those proposed at the earlier times or those based on traditional machine learning and deep learning, have focused on keeping relationships and entities in their own silos: extracting relationships and entities are conducted in steps before obtaining the mappings. To address this problem, a novel Chinese relationship extraction method is proposed in this paper. Firstly, the triple is treated as an entity relation chain and can identify the entity before the relationship and predict its corresponding relationship and the entity after the relationship. Secondly, the Joint Extraction of Entity Mentions and Relations model is based on the Bidirectional Long Short-Term Memory and Maximum Entropy Markov Model (Bi-MEMM). Experimental results indicate that the proposed model can achieve a precision of 79.2% which is much higher than that of traditional models.
Novel K rattling: A new route to thermoelectric materials?
Publisher: AIP Publishing
Date: 15-01-2014
DOI: 10.1063/1.4861641
Abstract: We have performed ab initio molecular dynamics simulations to study the alkali-metal dynamics in the Al-doped (KAl0.33W1.67O6 and RbAl0.33W1.67O6) and undoped (KW2O6 and RbW2O6) defect pyrochlore tungstates. The K atoms exhibit novel rattling dynamics in both the doped and undoped tungstates while the Rb atoms do not. The KAl0.33W1.67O6 experimental thermal conductivity curve shows an unusual depression between ∼50 K and ∼250 K, coinciding with two crossovers in the K dynamics: the first at ∼50 K, from oscillatory to diffusive, and the second at ∼250 K, from diffusive back to oscillatory. We found that the low-temperature crossover is a result of the system transitioning below the activation energy of the diffusive dynamics, whereas the high-temperature crossover is driven by a complex reconstruction of the local potential around the K atoms due to the cage dynamics. This leads to a hardening of the K potential with increasing temperature. This unusual reconstruction of the potential may have important implications for the interpretation of finite-temperature dynamics based on zero-temperature potentials in similar materials. The key result is that the novel K rattling, involving local diffusion, leads to a significant reduction in the thermal conductivity. We suggest that this may open a new route in the phonon engineering of cage compounds for thermoelectric materials, where the rattlers are specifically selected to reduce the lattice thermal conductivity by the mechanism of local diffusion.
Sentiment Correlation Discovery From Social Media to Share Market
Publisher: ACM
Date: 29-01-2019
Matching top-k answers of twig patterns in probabilistic XML
Publisher: Springer Berlin Heidelberg
Date: 2010
Traffic Signal Control With Reinforcement Learning Based on Region-Aware Cooperative Strategy
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Distributed Pregel-based provenance-aware regular path query processing on RDF knowledge graphs
Publisher: Springer Science and Business Media LLC
Date: 14-11-2019
Exploring Human Mobility for Multi-Pattern Passenger Prediction: A Graph Learning Framework
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2022
Dynamic network embedding survey
Publisher: Elsevier BV
Date: 02-2022
Thermal expansion coefficients of zirconolite (CaZrTi2 O7 ) and perovskite (CaTiO3 ) from X-ray powder diffraction analysis
Publisher: Elsevier BV
Date: 08-1992
Enabling Efficient, Verifiable, and Secure Conjunctive Keyword Search in Hybrid-Storage Blockchains
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Thin films of AuCuAl shape memory alloy for use in plasmonic nano-actuators
Publisher: Springer Science and Business Media LLC
Date: 2011
DOI: 10.1557/OPL.2011.180
Abstract: We describe the fabrication and structure of nanoscale thin films of β phase shape memory alloys with the nominal atomic stoichiometry Au 7 Cu 5 Al 4 (corresponding to 5.8 wt% Al). These alloys possess properties that suggest they could be used in nanoscale actuators. The films described here are between 20 and 50 nm thick which is below the thickness at which some other shape memory alloys cease to transform. However, microstructural and X-ray studies confirm that the coatings still exhibit the displacive transformations that are a prerequisite for the shape memory effect.
Multiview Learning for Impervious Surface Mapping Using High-Resolution Multispectral Imagery and LiDAR Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
SNPR: A Serendipity-Oriented Next POI Recommendation Model
Publisher: ACM
Date: 26-10-2021
Transmission Line Ice Coating Prediction Model Based on EEMD Feature Extraction
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Containment between Unions of XPath Queries
Publisher: Springer Berlin Heidelberg
Date: 2009
Distributed Optimization of Graph Convolutional Network Using Subgraph Variance
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Prevalence and associated factors of elder mistreatment: a cross sectional study from urban Nepal.
Publisher: Oxford University Press (OUP)
Date: 27-06-2016
Abstract: mistreatment of elderly people is internationally recognised as a serious public health issue. This study aimed at estimating the prevalence and risk factors associated with mistreatment in urban Nepal. this was a descriptive cross-sectional study of 212 elderly people residing in Butwal sub-metropolitan city, an urban area in Nepal the study was conducted between March and October 2015. Two-stage cluster design with simple random s ling was adopted for the study. Information was collected using an interviewer administered semi-structured questionnaire of older people. Logistic regression analysis was used to identify factors associated with elder mistreatment. this study found a prevalence of 49.1% for mistreatment of the elderly population. Prevalence rates of caregiver neglect, financial, psychological or physical mistreatment and other types (including sexual assault) were 47.2%, 11.8%, 10.8%, 1.42% and 3.3%, respectively. Being a dalit (untouchable backward class in the traditional Hindu caste system), unemployed, widowed, orced or separated, problems concentrating and smoking were independent factors associated with mistreatment. Smoking was found to be consistently associated with the three most common mistreatment types. mistreatment of older people is common in urban Nepal, with neglect, financial and psychological abuse most common. Along with standard risk factors, specific ethnic issues (membership of dalit community) are associated with increased risk.
Correlate Influential News Article Events to Stock Quote Movement
Publisher: Springer International Publishing
Date: 2019
Special Issue on Decision Making in Heterogeneous Network Data Scenarios and Applications
Publisher: Springer Science and Business Media LLC
Date: 22-03-2022
D2D-LSTM: LSTM-Based Path Prediction of Content Diffusion Tree in Device-to-Device Social Networks
Publisher: Association for the Advancement of Artificial Intelligence (AAAI)
Date: 03-04-2020
Abstract: With the proliferation of mobile device users, the Device-to-Device (D2D) communication has ascended to the spotlight in social network for users to share and exchange enormous data. Different from classic online social network (OSN) like Twitter and Facebook, each single data file to be shared in the D2D social network is often very large in data size, e.g., video, image or document. Sometimes, a small number of interesting data files may dominate the network traffic, and lead to heavy network congestion. To reduce the traffic congestion and design effective caching strategy, it is highly desirable to investigate how the data files are propagated in offline D2D social network and derive the diffusion model that fits to the new form of social network. However, existing works mainly concern about link prediction, which cannot predict the overall diffusion path when network topology is unknown. In this article, we propose D2D-LSTM based on Long Short-Term Memory (LSTM), which aims to predict complete content propagation paths in D2D social network. Taking the current user's time, geography and category preference into account, historical features of the previous path can be captured as well. It utilizes prototype users for prediction so as to achieve a better generalization ability. To the best of our knowledge, it is the first attempt to use real world large-scale dataset of mobile social network (MSN) to predict propagation path trees in a top-down order. Experimental results corroborate that the proposed algorithm can achieve superior prediction performance than state-of-the-art approaches. Furthermore, D2D-LSTM can achieve 95% average precision for terminal class and 17% accuracy for tree path hit.
Transmutation of ABO4 compounds incorporating technetium-99 and caesium-137
Publisher: IOP Publishing
Date: 13-01-2017
Detecting Topic and Sentiment Dynamics Due to COVID-19 Pandemic Using Social Media
Publisher: Springer International Publishing
Date: 2020
Anomalous lattice parameter increase in alkali earth aluminium substituted tungsten defect pyrochlores
Publisher: Elsevier BV
Date: 03-2009
SVkNN: Efficient secure and verifiable k-nearest neighbor query on the cloud platform
Publisher: IEEE
Date: 04-2020
Efficient distance-based representative skyline computation in 2D space
Publisher: Springer Science and Business Media LLC
Date: 24-08-2017
DP-GAN: Differentially private consecutive data publishing using generative adversarial nets
Publisher: Elsevier BV
Date: 07-2021
Stock market analysis using social networks
Publisher: ACM
Date: 29-01-2018
Structural Role Enhanced Attributed Network Embedding
Publisher: Springer International Publishing
Date: 2019
Community Aware Personalized Hashtag Recommendation in Social Networks
Publisher: Springer Singapore
Date: 2019
Development of LEU-based targets for radiopharmaceutical manufacturing: A review
Publisher: Elsevier BV
Date: 06-2019
Structure and phase transformations in the titanosilicate, sitinakite. the importance of water
Publisher: American Chemical Society (ACS)
Date: 06-07-2010
DOI: 10.1021/CM100727H
GNN-based long and short term preference modeling for next-location prediction
Publisher: Elsevier BV
Date: 06-2023
Target-aware holistic influence maximization in spatial social networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Efficient Computation of Multiple XML Keyword Queries
Publisher: Springer Berlin Heidelberg
Date: 2013
Thermal expansion of ammonium pertechnetate and ammonium perrhenate
Publisher: Elsevier BV
Date: 06-2019
Location prediction in large-scale social networks: an in-depth benchmarking study
Publisher: Springer Science and Business Media LLC
Date: 09-07-2019
Business Location Selection Based on Geo-Social Networks
Publisher: Springer International Publishing
Date: 2020
Explainable Link Prediction in Knowledge Hypergraphs
Publisher: ACM
Date: 17-10-2022
Structure and cation ordering in spinel-type TcCo2 O4 . An example of a trivalent technetium oxide
Publisher: Royal Society of Chemistry (RSC)
Date: 2011
DOI: 10.1039/C1DT10954E
Abstract: The structure of TcCo(2)O(4) has been determined using a combination of synchrotron X-ray and neutron powder diffraction methods. It has an inverse spinel structure where the Tc occupies the octahedral sites. Both the refined Tc-O distance and X-ray absorption spectra suggest the Tc is predominantly trivalent.
The evolution of young gambling studies: digital convergence of gaming, gambling and cryptocurrency technologies
Publisher: Informa UK Limited
Date: 31-01-2023
Database Systems for Advanced Applications
Publisher: Springer International Publishing
Date: 2018
Formation of (Cr, Al)UO4 from doped UO2 and its influence on partition of soluble fission products
Publisher: Elsevier BV
Date: 11-2013
The effect of alternate heating rates during cure on the structure-property relationships of epoxy/MMT clay nanocomposites
Publisher: Elsevier BV
Date: 10-2011
Secure range query over encrypted data in outsourced environments
Publisher: Springer Science and Business Media LLC
Date: 27-11-2020
Sequential engagement-based online learning analytics and prediction
Publisher: Elsevier
Date: 2021
Functional status and its associated factors among community-dwelling older adults in rural Nepal: findings from a cross-sectional study
Publisher: Springer Science and Business Media LLC
Date: 25-05-2021
DOI: 10.1186/S12877-021-02286-8
Abstract: The high burden of chronic conditions, coupled with various physical, mental, and psychosocial changes that accompany the phenomenon of aging, may limit the functional ability of older adults. This study aims to assess the prevalence of poor functional status and investigate factors associated with poor functional status among community-dwelling older adults in rural communities of eastern Nepal. Data on 794 older adults aged ≥ 60 years from a previous community-based cross-sectional study was used. Participants were recruited from rural municipalities of Morang and Sunsari districts of eastern Nepal using multi-stage cluster s ling. Functional status was assessed in terms of participants’ ability to perform activities of daily living using the Barthel Index. Covariates included sociodemographic characteristics, lifestyle factors, and self-reported chronic conditions. A binary logistic regression model was used to investigate factors associated with poor functional status. The overall prevalence of poor functional status was 8.3 % (male: 7.0 % and female: 9.6 %), with most dependence noted for using stairs (17.3 %), followed by dressing (21.9 %) on Barthel Index. In the adjusted model, oldest age group (odds ratio [OR] = 2.83, 95 %CI: 1.46, 5.50), those unemployed (OR = 2.41, 95 %CI: 1.26, 4.65), having memory/concentration problems (OR = 2.32, 95 %CI: 1.30, 4.13), depressive symptoms (OR = 2.52, 95 %CI: 1.28, 4.95), and hypertension (OR = 1.78, 95 %CI: 1.03, 3.06) had almost or more than two times poor functioning. One in 12 older adults had poor functional status as indicated by their dependency on the items of the Barthel Index those in the oldest age bracket were more likely to exhibit poor functional status. We suggest future studies from other geographies of the country to supplement our study from the rural setting for comprehensive identification of the problem, which could guide the development of prevention strategies and comprehensive interventions for addressing the unmet needs of the older adults for improving functional status.
Optimizing subgraph matching over distributed knowledge graphs using partial evaluation
Publisher: Springer Science and Business Media LLC
Date: 08-07-2022
DOI: 10.1007/S11280-022-01075-6
Abstract: The partial evaluation and assembly framework has recently been applied for processing subgraph matching queries over large-scale knowledge graphs in the distributed environment. The framework is implemented on the master-slave architecture, endowed with outstanding scalability. However, there are two drawbacks of partial evaluation: if the volume of intermediate results is large, a large number of repeated partial matches will be generated and the assembly computation handled by the master would be a bottleneck. In this paper, we propose an optimal partial evaluation algorithm and a filter method to reduce partial matches by exploring the computing characteristics of partial evaluation and assembly framework. (1) An index structure named inner boundary node index (IBN-Index) is constructed to prune for graph exploration to improve the searching efficiency of the partial evaluation phase. (2) The boundary characteristics of local partial matches are utilized to construct a boundary node index (BN-Index) to reduce the number of local partial matches. (3) The experimental results over benchmark datasets show that our approach outperforms the state-of-the-art methods.
The Effect of Grain Size and Dislocation Density on the Tensile Properties of Ni-SiCNP Composites During Annealing
Publisher: Springer Science and Business Media LLC
Date: 12-02-2016
Emerging Scientific Topic Discovery by Finding Infrequent Synonymous Biterms
Publisher: Springer International Publishing
Date: 2022
Structural characterization of the perovskite series La1-x Srx Cr1-x Tix O3
Publisher: Elsevier BV
Date: 12-2000
The quantification of radiation damage in orthophosphates using confocal μ-luminescence spectroscopy of Nd3+
Publisher: Frontiers Media SA
Date: 05-02-2019
Nutritional assessment and factors associated with malnutrition among the elderly population of Nepal: a cross-sectional study.
Publisher: Springer Science and Business Media LLC
Date: 30-04-2019
Compression techniques for 2-hop labeling for shortest distance queries
Publisher: Springer Science and Business Media LLC
Date: 27-11-2022
Root Cause Analysis of Traffic Anomalies Using Uneven Diffusion Model
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Towards multi-dimensional knowledge-aware approach for effective community detection in LBSN
Publisher: Springer Science and Business Media LLC
Date: 14-09-2022
Effective Deep Attributed Network Representation Learning With Topology Adapted Smoothing
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2022
Community-diversified influence maximization in social networks
Publisher: Elsevier BV
Date: 09-2020
Co-Engaged Location Group Search in Location-Based Social Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Immobilization of Sodium in Perovskite
Publisher: Wiley
Date: 04-1991
Prediction model for recurrence of hepatocellular carcinoma after resection by using neighbor2vec based algorithms
Publisher: Wiley
Date: 12-11-2021
DOI: 10.1002/WIDM.1390
Machine-learning-assisted shear strength prediction of reinforced concrete beams with and without stirrups
Publisher: Springer Science and Business Media LLC
Date: 14-07-2020
Efficient Exact Algorithms for Maximum Balanced Biclique Search in Bipartite Graphs
Publisher: ACM
Date: 09-06-2021
A survey on deep learning based knowledge tracing
Publisher: Elsevier BV
Date: 12-2022
Interpretable and Efficient Heterogeneous Graph Convolutional Network
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Predicting the spread of a new tweet in twitter
Publisher: Springer International Publishing
Date: 2015
Self-supervised Cross-Iterative Clustering for Unlabeled Plant Disease Images
Publisher: Elsevier BV
Date: 10-2021
Personalized Influential Topic Search via Social Network Summarization
Publisher: IEEE
Date: 04-2017
DOI: 10.1109/ICDE.2017.15
Sample Location Selection for Efficient Distance-Aware Influence Maximization in Geo-Social Networks
Publisher: Springer International Publishing
Date: 2018
Editorial: Real-time Dynamic Network Learning for Location Inference Modelling and Computing
Publisher: Elsevier BV
Date: 02-2021
Urban Traffic Signal Control with Reinforcement Learning from Demonstration Data
Publisher: IEEE
Date: 18-07-2022
Towards Multi-User, Secure, and Verifiable $k$NN Query in Cloud Database
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 09-2023
Determination of martensite structures of the Au7 Cu 5 Al4 and Au7 Cu5.7 Al3.3 shape-memory alloys
Publisher: Elsevier BV
Date: 10-2014
Generative Adversarial Nets Enhanced Continual Data Release Using Differential Privacy
Publisher: Springer International Publishing
Date: 2020
The Item Response Theory Model for an AI-based Adaptive Learning System
Publisher: IEEE
Date: 09-2019
Suggestion of promising result types for XML keyword search
Publisher: ACM
Date: 22-03-2010
Fast ELCA computation for keyword queries on XML data
Publisher: ACM
Date: 22-03-2010
Supervised Contrastive Learning for Product Classification
Publisher: Springer International Publishing
Date: 2022
Robust cross-network node classification via constrained graph mutual information
Publisher: Elsevier BV
Date: 12-2022
Top-k keyword search over probabilistic XML data
Publisher: IEEE
Date: 04-2011
Pilot randomised controlled trial of a brief coping-focused intervention for hearing voices blended with smartphone-based ecological momentary assessment and intervention (SAVVy): Feasibility, accepta
Publisher: Elsevier BV
Date: 02-2020
DOI: 10.1016/J.SCHRES.2019.10.026
Abstract: Voice-hearing experiences can be distressing and impairing, and existing psychological treatments show modest effectiveness. Ecological momentary assessment and intervention (EMA/I) are two promising approaches which may be used as digital tools to support and enhance existing psychological therapies. The aim of this study was to investigate the potential clinical utility of smartphone-based EMA/I in a blended, coping focused therapy for voice-hearing experiences. This pilot RCT focused on feasibility, acceptability and preliminary estimations of efficacy. Thirty-four participants with persisting and distressing voices were randomised to receive the four-session intervention along-side treatment-as-usual (TAU) or TAU-only. Findings supported the feasibility and acceptability of the approach, with good engagement and satisfaction rates, and clinical outcomes showed the intervention holds promise for improving coping, overall severity of voices and to some degree their negative impact. This is the first examination of the use of EMA/I in a blended therapy for psychotic experiences, with findings suggesting these technologies show promise as clinical tools.
KGVis: An Interactive Visual Query Language for Knowledge Graphs
Publisher: Springer International Publishing
Date: 2019
Social media mining under the COVID-19 context: Progress, challenges, and opportunities
Publisher: Elsevier BV
Date: 09-2022
Discovering and tracking query oriented active online social groups in dynamic information network
Publisher: Springer Science and Business Media LLC
Date: 10-08-2019
Deep fusion of multimodal features for social media retweet time prediction
Publisher: Springer Science and Business Media LLC
Date: 24-10-2021
Self-care behaviours among people with type 2 diabetes mellitus in South Asia: A systematic review and meta-analysis.
Publisher: International Society of Global Health
Date: 03-08-2022
Pu, U, and Hf incorporation in Gd silicate apatite
Publisher: Wiley
Date: 07-2003
Knowledge Graph Recommendation Model Based on Adversarial Training
Publisher: MDPI AG
Date: 24-07-2022
DOI: 10.3390/APP12157434
Abstract: The recommendation model based on the knowledge graph (KG) alleviates the problem of data sparsity in the recommendation to a certain extent and further improves the accuracy, ersity, and interpretability of recommendations. Therefore, the knowledge graph recommendation model has become a major research topic, and the question of how to utilize the entity and relation information fully and effectively in KG has become the focus of research. This paper proposes a knowledge graph recommendation model based on adversarial training (ATKGRM), which can dynamically and adaptively adjust the knowledge graph aggregation weight based on adversarial training to learn the features of users and items more reasonably. First, the generator adopts a novel long- and short-term interest model to obtain user features and item features and generates a high-quality set of candidate items. Then, the discriminator discriminates candidate items by comparing the user’s scores of positive items, negative items, and candidate items. Finally, experimental studies on five real-world datasets with multiple knowledge graph recommendation models and multiple adversarial training recommendation models prove the effectiveness of our model.
HIT-COVID, a global database tracking public health interventions to COVID-19
Publisher: Springer Science and Business Media LLC
Date: 27-08-2020
DOI: 10.1038/S41597-020-00610-2
Abstract: The COVID-19 pandemic has sparked unprecedented public health and social measures (PHSM) by national and local governments, including border restrictions, school closures, mandatory facemask use and stay at home orders. Quantifying the effectiveness of these interventions in reducing disease transmission is key to rational policy making in response to the current and future pandemics. In order to estimate the effectiveness of these interventions, detailed descriptions of their timelines, scale and scope are needed. The Health Intervention Tracking for COVID-19 (HIT-COVID) is a curated and standardized global database that catalogues the implementation and relaxation of COVID-19 related PHSM. With a team of over 200 volunteer contributors, we assembled policy timelines for a range of key PHSM aimed at reducing COVID-19 risk for the national and first administrative levels (e.g. provinces and states) globally, including details such as the degree of implementation and targeted populations. We continue to maintain and adapt this database to the changing COVID-19 landscape so it can serve as a resource for researchers and policymakers alike.
Ceramic conversion and densification of zirconium phosphonate sorbent materials
Publisher: Elsevier BV
Date: 04-2019
The Effect of a Rapid Heating Rate, Mechanical Vibration and Surfactant Chemistry on the Structure-Property Relationships of Epoxy/Clay Nanocomposites
Publisher: MDPI AG
Date: 20-08-2013
DOI: 10.3390/MA6083624
XClean: Providing valid spelling suggestions for XML keyword queries
Publisher: IEEE
Date: 04-2011
Efficient targeted influence minimization in big social networks
Publisher: Springer Science and Business Media LLC
Date: 19-03-2020
Empirical Analysis of Factors Influencing Twitter Hashtag Recommendation on Detected Communities
Publisher: Springer International Publishing
Date: 2017
HET-KG: Communication-Efficient Knowledge Graph Embedding Training via Hotness-Aware Cache
Publisher: IEEE
Date: 05-2022
METoNR: A meta explanation triplet oriented news recommendation model
Publisher: Elsevier BV
Date: 02-2022
Database Systems for Advanced Applications - 23rd International Conference, DASFAA 2018, Gold Coast, QLD, Australia, May 21-24, 2018, Proceedings, Part II
Publisher: Springer International Publishing
Date: 2018
Keyword-based correlated network computation over large social media
Publisher: IEEE
Date: 03-2014
Formation and stability of Pb-, Zn-& Cu-PO 4 phases at low temperatures: Implications for heavy metal fixation in polar environments
Publisher: Elsevier BV
Date: 02-2012
DOI: 10.1016/J.ENVPOL.2011.09.035
Abstract: Low temperatures and frequent soil freeze-thaw in polar environments present challenges for the immobilisation of metals. To address these challenges we investigated the chemical forms of Pb, Zn and Cu in an Antarctic landfill, examined in vitro reaction kinetics of these metals and orthophosphate at 2 and 22 °C for up to 185 days, and subjected the products to freeze-thaw. Reaction products at both temperatures were similar, but the rate of production varied, with Cu-PO(4) phases forming faster, and the Zn- and Pb-PO(4) phases slower at 2 °C. All metal-orthophosphate phases produced were stable during a 2.5 h freeze-thaw cycle to -30 °C. Metal immobilisation using orthophosphate can be successful in polar regions, but treatments will need to consider differing mineral stabilities and reaction rates at low temperatures.
Holistic Constraint-Preserving Transformation from Relational Schema into XML Schema
Publisher: Springer Berlin Heidelberg
Date: 2008
Contextual Community Search Over Large Social Networks
Publisher: IEEE
Date: 04-2019
In situ micro-Raman analysis and X-ray diffraction of nickel silicide thin films on silicon
Publisher: Elsevier BV
Date: 2009
DOI: 10.1016/J.MICRON.2008.03.007
Abstract: This article reports on the in situ analysis of nickel silicide (NiSi) thin films formed by thermal processing of nickel thin films deposited on silicon substrates. The in situ techniques employed for this study include micro-Raman spectroscopy (microRS) and X-ray diffraction (XRD) in both cases the variations for temperatures up to 350 degrees C has been studied. Nickel silicide thin films formed by vacuum annealing of nickel on silicon were used as a reference for these measurements. In situ analysis was carried out on nickel thin films on silicon, while the s les were heated from room temperature to 350 degrees C. Data was gathered at regular temperature intervals and other specific points of interest (such as 250 degrees C, where the reaction between nickel and silicon to form Ni(2)Si is expected). The transformations from the metallic state, through the intermediate reaction states, until the desired metal-silicon reaction product is attained, are discussed. The evolution of nickel silicide from the nickel film can be observed from both the microRS and XRD in situ studies. Variations in the evolution of silicide from metal for different silicon substrates are discussed, and these include (100) n-type, (100) p-type, and (110) p-type silicon substrates.
Reliability-Driven Local Community Search in Dynamic Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Uncovering attribute-driven active intimate communities
Publisher: Springer International Publishing
Date: 2018
Dynamical Modeling, Analysis, and Control of Information Diffusion over Social Networks
Publisher: Hindawi Limited
Date: 21-10-2021
DOI: 10.1155/2021/9815653
Cation disorder in NaW2 O6δ ·nH 2-z O post-ion exchange with K, Rb, Sr, and Cs
Publisher: Elsevier BV
Date: 06-2011
Structure and magnetism in S r1-xAxTc O3 perovskites: Importance of the A -site cation
Publisher: American Physical Society (APS)
Date: 27-02-2017
A Spatial-Temporal Graph Attention Network for Multi-intersection Traffic Light Control
Publisher: IEEE
Date: 18-07-2021
Economic Evaluation of Health Behavior Interventions to Prevent and Manage Type 2 Diabetes Mellitus in Asia: A Systematic Review of Randomized Controlled Trials
Publisher: MDPI AG
Date: 30-08-2022
Abstract: Health behavior interventions implemented in Asian countries often lack economic evaluations that effectively address the problems of type 2 diabetes mellitus. This review systematically assessed the existing literature on economic evaluation of health behavior interventions to prevent and manage type 2 diabetes mellitus for people living in Asian countries. Eligible studies were identified through a search of six bibliographic databases, namely, PubMed, Scopus, Public Health Database by ProQuest, Cumulative Index to Nursing and Allied Health Literature Complete, Web of Science, and Google Scholar. Randomized controlled trials of health behavior interventions and studies published in the English language from January 2000 to May 2022 were included in the review. The search yielded 3867 records, of which 11 studies were included in the review. All included studies concluded that health behavior interventions were cost-effective. Eight of these studies undertook an evaluation from a health system perspective, two studies used both societal and health system perspectives, and one study utilized a societal and multi-payer perspective. This review identified the time horizon, direct and indirect medical costs, and discount rates as the most important considerations in determining cost effectiveness. These findings have implications in extending health behavior interventions to prevent and manage type 2 diabetes mellitus in low-resource settings, and are likely to yield the most promising outcomes for people with type 2 diabetes mellitus.
CHIEF: Clustering With Higher-Order Motifs in Big Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 05-2022
Sentiment analysis and topic modeling for COVID-19 vaccine discussions
Publisher: Springer Science and Business Media LLC
Date: 25-02-2022
DOI: 10.1007/S11280-022-01029-Y
Abstract: The outbreak of the novel coronavirus disease (COVID-19) has been ongoing for almost two years and has had an unprecedented impact on the daily lives of people around the world. More recently, the emergence of the Delta variant of COVID-19 has once again put the world at risk. Fortunately, many countries and companies have developed vaccines for the coronavirus. As of 23 August 2021, more than 20 vaccines have been approved by the World Health Organization (WHO), bringing light to people besieged by the pandemic. The global rollout of the COVID-19 vaccine has sparked much discussion on social media platforms, such as the effectiveness and safety of the vaccine. However, there has not been much systematic analysis of public opinion on the COVID-19 vaccine. In this study, we conduct an in-depth analysis of the discussions related to the COVID-19 vaccine on Twitter. We analyze the hot topics discussed by people and the corresponding emotional polarity from the perspective of countries and vaccine brands. The results show that most people trust the effectiveness of vaccines and are willing to get vaccinated. In contrast, negative tweets tended to be associated with news reports of post-vaccination deaths, vaccine shortages, and post-injection side effects. Overall, this study uses popular Natural Language Processing (NLP) technologies to mine people’s opinions on the COVID-19 vaccine on social media and objectively analyze and visualize them. Our findings can improve the readability of the confusing information on social media platforms and provide effective data support for the government and policy makers.
Robust image clustering via context-aware contrastive graph learning
Publisher: Elsevier BV
Date: 06-2023
Structural phase transitions and magnetic order in SrTcO3
Publisher: Royal Society of Chemistry (RSC)
Date: 2011
DOI: 10.1039/C1DT10445D
Abstract: The structure of the perovskite SrTcO(3) has been investigated using both synchrotron X-ray and neutron powder diffraction. At room temperature SrTcO(3) is orthorhombic as a consequence of cooperative tilting of the corner sharing TcO(6) octahedra. The tilts are sequentially removed as the s le is heated with the oxide displaying the sequence of structres Pnma→Imma→I4/mcm→Pm ̅3m. Neutron powder diffraction data collected in the temperature range 4-1023 K indicate that SrTcO(3) has G-type antiferromagnetic structure, in which each Tc moment is antiparallel to its six nearest neighbours, below ∼1000 K. The magnetic structure is collinear antiferromagnetic with the technetium moments parallel to c-axis and can be described by the propagation vector k = [0,0,0] and the basis vector (0,0,A(z)). The same magnetic structure is observed in each of the four crystal structures.
Erratum: Novel K rattling: A new route to thermoelectric materials? (Journal of Applied Physics (2014) 115 (033703))
Publisher: AIP Publishing
Date: 11-04-2014
DOI: 10.1063/1.4871185
Crystal chemistry of the orthorhombic Ln2 TiO5 compounds with Ln=La, Pr, Nd, Sm, Gd, Tb and Dy
Publisher: Elsevier BV
Date: 07-2015
Diffuse scattering in the cesium pyrochlore CsTi0.5W1.5O6
Publisher: Elsevier BV
Date: 04-2008
Reservoir Production Prediction Based on Variational Mode Decomposition and Gated Recurrent Unit Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2021
Everyone in SDN Contributes: Fault localization via well-designed rules
Publisher: IEEE
Date: 07-2021
Spatiooral-Social Multi-Feature-based Fine-Grained Hot Spots Prediction for Content Delivery Services in 5G Era
Publisher: ACM
Date: 26-10-2021
Uncertainty-Aware Multiview Deep Learning for Internet of Things Applications
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 02-2023
Query-Driven Frequent Co-Occurring Term Computation over Relational Data Using MapReduce
Publisher: Oxford University Press (OUP)
Date: 24-09-2014
Graph Intelligence Enhanced Bi-Channel Insider Threat Detection
Publisher: Springer Nature Switzerland
Date: 2022
Community-based lifestyle intervention for diabetes (Co-LID study) management rural Nepal: study protocol for a clustered randomized controlled trial
Publisher: Springer Science and Business Media LLC
Date: 05-07-2023
DOI: 10.1186/S13063-023-07451-5
Abstract: Type 2 diabetes mellitus (T2DM) has increased globally with a disproportionate burden in South and Southeast Asian countries, including Nepal. There is an urgent need for clinically and cost-effective culturally adapted T2DM management programs. In this study, we aim to assess the effectiveness of community based culturally appropriate lifestyle intervention in improving the management and care of people with T2DM. We will conduct a cluster randomized control trial to evaluate the effectiveness of community based culturally appropriate lifestyle intervention in improving T2DM outcomes. The trial will be conducted in 30 randomly selected healthcare facilities from two purposively selected districts (Kavrepalanchowk and Nuwakot districts) of Bagmati province, Nepal. The selected healthcare facilities are being randomized into 15 interventions ( n = 15) and usual care ( n = 15) groups. Those in the intervention will receive group-based 12 an hour-long fortnightly session delivered over 6 months period. The intervention package includes 12 planned modules related to diabetes care, ongoing support, supervision and monitoring, follow-up from the trained community health workers, and educational materials on diabetes self-management. The participants in the usual care groups will receive pictorial brochure on diabetes management and they will continue receiving the usual care available from the local health facilities. The primary outcome is HbA1c level, and the secondary outcomes include quality of life, health care utilization, and practice of self-care behaviour, depression, oral health quality of life, and economic assessment of the intervention. Two points measurements will be collected by the trained research assistants at baseline and at the end of the intervention. This study will provide tested approaches for culturally adapting T2DM interventions in the Nepalese context. The findings will also have practice and policy implications for T2DM prevention and management in Nepal. Australia and New Zealand Clinical Trial Registry (ACTRN12621000531819). Registered on May 6, 2021.
Maximum co-located community search in large scale social networks
Publisher: Association for Computing Machinery (ACM)
Date: 06-2018
Abstract: The problem of k-truss search has been well defined and investigated to find the highly correlated user groups in social networks. But there is no previous study to consider the constraint of users' spatial information in k-truss search, denoted as co-located community search in this paper. The co-located community can serve many real applications. To search the maximum co-located communities efficiently, we first develop an efficient exact algorithm with several pruning techniques. After that, we further develop an approximation algorithm with adjustable accuracy guarantees and explore more effective pruning rules, which can reduce the computational cost significantly. To accelerate the real-time efficiency, we also devise a novel quadtree based index to support the efficient retrieval of users in a region and optimise the search regions with regards to the given query region. Finally, we verify the performance of our proposed algorithms and index using five real datasets.
Analysis and Applications of Location-Aware Big Complex Network Data
Publisher: Hindawi Limited
Date: 14-07-2019
DOI: 10.1155/2019/3410262
Quasi-SLCA Based Keyword Query Processing over Probabilistic XML Data
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 04-2014
DOI: 10.1109/TKDE.2013.67
Structure of the hydrated pyrochlore NaW2 O6 ·nH2 O
Publisher: Elsevier BV
Date: 11-2006
The emergence of the brain non-CpG methylation system in vertebrates
Publisher: Springer Science and Business Media LLC
Date: 18-01-2021
MPTO-MT: A multi-period vehicular task offloading method in 5G HetNets
Publisher: Elsevier BV
Date: 10-2022
The influence of composition and temperature on the phases in Sr1-x Bax Zro3 perovskites: A high-resolution powder diffraction study
Publisher: Elsevier BV
Date: 10-2001
Awareness of occupational hazards and associated factors among automobile repair artisans in Kathmandu Metropolitan City, Nepal
Publisher: Medknow
Date: 2018
StarMR: An Efficient Star-Decomposition Based Query Processor for SPARQL Basic Graph Patterns Using MapReduce
Publisher: Springer International Publishing
Date: 2018
Access Time Oracle for Planar Graphs
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 08-2016
Efficiently answering top-k frequent term queries in temporal-categorical range
Publisher: Elsevier BV
Date: 10-2021
A Measurement-Driven Analysis and Prediction of Content Propagation in the Device-to-Device Social Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Evidence-driven dubious decision making in online shopping
Publisher: Springer Science and Business Media LLC
Date: 07-07-2019
Seeds Selection for Influence Maximization Based on Device-to-Device Social Knowledge by Reinforcement Learning
Publisher: Springer International Publishing
Date: 2020
Influence Propagation Model for Clique-Based Community Detection in Social Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 06-2018
Filtering Techniques for Rewriting XPath Queries Using Views
Publisher: Springer Berlin Heidelberg
Date: 2008
Diffraction and fluorescence studies of bushranger armour
Publisher: Elsevier BV
Date: 10-2004
Efficient Subgraph Matching on Large RDF Graphs Using MapReduce
Publisher: Springer Science and Business Media LLC
Date: 03-2019
Targeted Influence Minimization in Social Networks
Publisher: Springer International Publishing
Date: 2018
Zn-doped TiO 2 electrodes in dye-sensitized solar cells for enhanced photocurrent
Publisher: Royal Society of Chemistry (RSC)
Date: 2012
DOI: 10.1039/C2JM32409A
Personalized Influential Topic Search via Social Network Summarization
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 07-2016
CoPFun: an urban co-occurrence pattern mining scheme based on regional function discovery
Publisher: Springer Science and Business Media LLC
Date: 28-05-2018
An unconventional method for measuring the Tc L3-edge of technetium compounds
Publisher: International Union of Crystallography (IUCr)
Date: 10-2014
DOI: 10.1107/S1600577514014891
Abstract: Tc L 3 -edge XANES spectra have been collected on powder s les of SrTcO 3 (octahedral Tc 4+ ) and NH 4 TcO 4 (tetrahedral Tc 7+ ) immobilized in an epoxy resin. Features in the Tc L 3 -edge XANES spectra are compared with the pre-edge feature of the Tc K -edge as well as other 4 d transition metal L 3 -edges. Evidence of crystal field splitting is obvious in the Tc L 3 -edge, which is sensitive to the coordination number and oxidation state of the Tc cation. The Tc L 3 absorption edge energy difference between SrTcO 3 (Tc 4+ ) and NH 4 TcO 4 (Tc 7+ ) shows that the energy shift at the Tc L 3 -edge is an effective tool for studying changes in the oxidation states of technetium compounds. The Tc L 3 -edge spectra are compared with those obtained from Mo and Ru oxide standards with various oxidation states and coordination environments. Most importantly, fitting the Tc L 3 -edge to component peaks can provide direct evidence of crystal field splitting that cannot be obtained from the Tc K -edge.
Discovering and tracking active online social groups
Publisher: Springer International Publishing
Date: 2017
Masking and purifying inputs for blocking textual adversarial attacks
Publisher: Elsevier BV
Date: 11-2023
Fine-Grained Spatio-Temporal Distribution Prediction of Mobile Content Delivery in 5G Ultra-Dense Networks
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2022
Adaptive relaxation for querying heterogeneous XML data sources
Publisher: Elsevier BV
Date: 09-2010
JKT: A joint graph convolutional network based Deep Knowledge Tracing
Publisher: Elsevier BV
Date: 11-2021
Index for supporting XML structural join efficiently and effectively-CATI
Publisher: China Science Publishing & Media Ltd.
Date: 2007
DOI: 10.1360/CRAD20070116
Thermal Expansion Behavior in TcO2 . Toward Breaking the Tc-Tc Bond
Publisher: American Chemical Society (ACS)
Date: 24-07-2017
DOI: 10.1021/ACS.INORGCHEM.7B01235
Abstract: The structure of TcO
A Comprehensive Survey on Multi-view Clustering
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2023
Efficient Structural Clustering on Probabilistic Graphs
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Multi-Community Influence Maximization in Device-to-Device social networks
Publisher: Elsevier BV
Date: 06-2021
Deglacial mesophotic reef demise on the Great Barrier Reef
Publisher: Elsevier BV
Date: 12-2013
Most Influential Community Search over Large Social Networks
Publisher: IEEE
Date: 04-2017
SEPN: A Sequential Engagement Based Academic Performance Prediction Model
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2020
Structure and dehydration of the pyrochlore system NaW2-y Moy O6+δ ·nH2-z O between 10 and 675 K
Publisher: Elsevier BV
Date: 07-2008
Structures in the System CaTiO3 /SrTiO3
Publisher: Elsevier BV
Date: 09-1998
DataType-Aware Knowledge Graph Representation Learning in Hyperbolic Space
Publisher: ACM
Date: 26-10-2021
Guest Editorial: Big Traffic Data Analysis and Mining
Publisher: Institution of Engineering and Technology (IET)
Date: 09-2018
Structures and Phase Transitions in Pertechnetates
Publisher: American Chemical Society (ACS)
Date: 09-07-2019
DOI: 10.1021/ACS.INORGCHEM.9B01257
Abstract: The temperature dependence of the structures of four pertechnetates (
XML keyword search with promising result type recommendations
Publisher: Springer Science and Business Media LLC
Date: 17-01-2013
Holistic influence maximization for targeted advertisements in spatial social networks
Publisher: IEEE
Date: 04-2018
The effect of B4 C addition to MnO2 in a cathode material for battery applications
Publisher: Elsevier BV
Date: 2010
Health Service Utilization by Elderly Population in Urban Nepal: A Cross-Sectional Study
Publisher: Nepal Journals Online (JOL)
Date: 26-09-2016
DOI: 10.3126/JMMIHS.V2I0.15794
Abstract: Background The elderly population is in increasing trend all over the world. Elderly people experience many physiological, biological and psychological changes. The general objective of the study is to assess the utilization of health care services among the elderly population of Butwal sub-metropolitan city.Methods A quantitative descriptive-cross sectional study, with a total number of 212 elderly people residing in Butwal sub-metropolitan city, was selected for the study purpose. The study period was from March to October 2015. The s les were randomly selected from the s ling frame of 3 different wards of Butwal sub-metropolitan city. Information was collected using an interviewer administered semi-structured questionnaire. Chi-square test was used to identify the factors associated with the utilization of health care services among elderly population.Results Our findings reveal that 84.4% of elderly people visited to the health facility during past 1 year. There were more females (50.9%) than males (49.1%). Majority of elderly people were diagnosed with one of the chronic ailment were under regular medication. More than 4/5th (84.9%) of older adults rated “satisfactory” to their health condition. Monthly family income, chronic disease, elderly on medication and self-rated health status are statistically significant with utilization of health care services at 95% level of confidence.Conclusions The finding suggests that monthly family income, chronic disease, elderly on medication and self rated health are strongly associated with utilization of health care services by elderly people. Thus the study suggests further interventions to improve the health care service utilization by elderly people.Journal of Manmohan Memorial Institute of Health Sciences Vol. 2 2016 p.27-36
Representation Learning with Depth and Breadth for Recommendation Using Multi-view Data
Publisher: Springer International Publishing
Date: 2018
Activity location inference of users based on social relationship
Publisher: Springer Science and Business Media LLC
Date: 28-05-2021
Evaluating Irredundant Maximal Contained Rewritings for XPath Queries on Views
Publisher: Oxford University Press (OUP)
Date: 22-08-2013
Microcrystalline hexagonal tungsten bronze. 1. Basis of ion exchange selectivity for cesium and strontium
Publisher: American Chemical Society (ACS)
Date: 11-06-2009
DOI: 10.1021/IC801294X
Abstract: The structural basis of selectivity for cesium and strontium of microcrystalline hexagonal tungsten bronze (HTB) phase Na(x)WO(3+x/2).zH(2)O has been studied using X-ray and neutron diffraction techniques, 1D and 2D (23)Na magic angle spinning (MAS) nuclear magnetic resonance (NMR) spectroscopy, and radiochemical ion exchange investigations. For the HTB system, this study has shown that scattering techniques alone provide an incomplete description of the disorder and rapid exchange of water (with tunnel cations) occurring in this system. However, 1D and 2D (23)Na MAS NMR has identified three sodium species within the HTB tunnels-species A, which is located at the center of the hexagonal window and is devoid of coordinated water, and species B and C, which are the di- and monohydrated variants, respectively, of species A. Although species B accords with the traditional crystallographic model of the HTB phase, this work is the first to propose and identify the anhydrous species A and monohydrate species C. The population (total) of species B and C decreases in comparison to that of species A with increasing exchange of either cesium or strontium that is, species B and C appear more exchangeable than species A. Moreover, a significant proportion of tunnel water is redistributed by these cations. Multiple ion exchange investigations with radiotracers (137)Cs and (85)Sr have shown that for strontium there is a definite advantage in ensuring that any easily exchanged sodium is removed from the HTB tunnels prior to exchange. The decrease in selectivity (wrt cesium) is most probably due to the slightly smaller effective size of Sr(2+) namely, it is less of a good fit for the hexagonal window, ion exchange site. The selectivity of the HTB framework for cesium has been shown unequivocally to be defined by the structure of the hexagonal window, ion exchange site. Compromising the geometry of this window even in the slightest way by either (1) varying the cell volume through changes to hydration or sodium content or (2) introducing disorder in the a-b plane through isomorphous substitution of molybdenum is sufficient to reduce the selectivity. Indeed, it is our hypothesis that this applies for all cations which are strongly bound by the HTB framework.
Distributed Subgraph Matching on Big Knowledge Graphs Using Pregel
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 2019
Knowledge Graph Recommendation Model Based on Feature Space Fusion
Publisher: MDPI AG
Date: 31-08-2022
DOI: 10.3390/APP12178764
Abstract: The existing recommendation model based on a knowledge graph simply integrates the behavior features in a user–item bipartite graph and the content features in a knowledge graph. However, the difference between the two feature spaces is ignored. To solve this problem, this paper presents a new recommendation model named the knowledge graph recommendation model based on feature space fusion (KGRFSF). Specifically, in the behavioral feature space, the behavioral features of users and items are constructed by extracting the behavioral feature from the user–item bipartite graph. In the content feature space, the content features related to users and items are extracted through the attention mechanism on the knowledge graph, and then the content feature vectors of users and items are constructed. Finally, through the feature space fusion model, the behavior features and content features are projected into the same preference feature space, and then the fusion of the two feature spaces is completed to construct the complete vector representations of users and items and calculate the vector similarity to predict the score of the user to the item. This paper applies the presented model to public datasets in the fields of music and film. It can be found through the experimental results that KGRFSF can effectively improve the recommendation accuracy compared with the existing models.
Special Issue of DASFAA 2018
Publisher: Springer Science and Business Media LLC
Date: 17-11-2018
Crystal structure and phase transitions in the uranium perovskite, Ba 2 SrUO6
Publisher: Elsevier BV
Date: 02-2013
Pyrochlore based glass-ceramics for the immobilization of actinide-rich nuclear wastes: From concept to reality
Publisher: Elsevier BV
Date: 2013
The time has come to eliminate the gaps in the under-recognized burden of elder mistreatment: A community-based, cross-sectional study from rural eastern Nepal.
Publisher: Public Library of Science (PLoS)
Date: 20-06-2018
Message from the CIT 2021 General Chairs IUCC/CIT/DSCI/SmartCNS 2021
Publisher: IEEE
Date: 12-2021
Mixed method approach for determining use, effectiveness, and technical soundness of the sanitary pad incinerators in the schools of Nepalgunj submetropolitan city
Publisher: ScopeMed
Date: 2017
Evaluating Contained Rewritings for XPath Queries on Materialized Views
Publisher: Springer Berlin Heidelberg
Date: 2011
Efficient Top-k Search Across Heterogeneous XML Data Sources
Publisher: Springer Berlin Heidelberg
Date: 2008
Representation Learning for Short Text Clustering
Publisher: Springer International Publishing
Date: 2021
Benchmark Data and Method for Real-Time People Counting in Cluttered Scenes Using Depth Sensors
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 10-2019
Efficient answering of why-not questions in similar graph matching
Publisher: IEEE
Date: 05-2016
An Effective Data Fusion Model for Detecting the Risk of Transmission Line in Smart Grid
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Date: 15-11-2022
HyConvE: A Novel Embedding Model for Knowledge Hypergraph Link Prediction with Convolutional Neural Networks
Publisher: ACM
Date: 30-04-2023
Geo-social Influence Spanning Maximization
Publisher: IEEE
Date: 04-2018
Predictive Representation Learning in Motif-Based Graph Networks
Publisher: Springer International Publishing
Date: 2019
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Dr.Davidraja And Dr.Chandraleka Educational Institute
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