Multiple Imputation Ensembles (MIE) for dealing with missing data

Missing data is a significant issue in many real-world datasets, yet there are no robust methods for dealing with it appropriately. In this paper, we propose a robust approach to dealing with missing data in classification problems: Multiple Imputation Ensembles (MIE). Our method integrates two approaches: multiple imputation and ensemble methods and compares two types of ensembles: bagging and stacking. We also propose a robust experimental set-up using 20 benchmark datasets from the UCI machine learning repository. For each dataset, we introduce increasing amounts of data Missing Completely at Random. Firstly, we use a number of single/multiple imputation methods to recover the missing values and then ensemble a number of different classifiers built on the imputed data. We assess the quality of the imputation by using dissimilarity measures. We also evaluate the MIE performance by comparing classification accuracy on the complete and imputed data. Furthermore, we use the accuracy of simple imputation as a benchmark for comparison. We find that our proposed approach combining multiple imputation with ensemble techniques outperform others, particularly as missing data increases

The roles of endolithic fungi in bioerosion and disease in marine ecosystems. II. Potential facultatively parasitic anamorphic ascomycetes can cause disease in corals and molluscs

Anamorphic ascomycetes have been implicated as causative agents of diseases in tissues and skeletons of hard corals, in tissues of soft corals (sea fans) and in tissues and shells of molluscs. Opportunist marine fungal pathogens, such as Aspergillus sydowii, are important components of marine mycoplankton and are ubiquitous in the open oceans, intertidal zones and marine sediments. These fungi can cause infection in or at least can be associated with animals which live in these ecosystems. A. sydowii can produce toxins which inhibit photosynthesis in and the growth of coral zooxanthellae. The prevalence of many documented infections has increased in frequency and severity in recent decades with the changing impacts of physical and chemical factors, such as temperature, acidity and eutrophication. Changes in these factors are thought to cause significant loss of biodiversity in marine ecosystems on a global scale in general, and especially in coral reefs and shallow bays

Chalcogenide Glass-on-Graphene Photonics

Two-dimensional (2-D) materials are of tremendous interest to integrated photonics given their singular optical characteristics spanning light emission, modulation, saturable absorption, and nonlinear optics. To harness their optical properties, these atomically thin materials are usually attached onto prefabricated devices via a transfer process. In this paper, we present a new route for 2-D material integration with planar photonics. Central to this approach is the use of chalcogenide glass, a multifunctional material which can be directly deposited and patterned on a wide variety of 2-D materials and can simultaneously function as the light guiding medium, a gate dielectric, and a passivation layer for 2-D materials. Besides claiming improved fabrication yield and throughput compared to the traditional transfer process, our technique also enables unconventional multilayer device geometries optimally designed for enhancing light-matter interactions in the 2-D layers. Capitalizing on this facile integration method, we demonstrate a series of high-performance glass-on-graphene devices including ultra-broadband on-chip polarizers, energy-efficient thermo-optic switches, as well as graphene-based mid-infrared (mid-IR) waveguide-integrated photodetectors and modulators

The Mediating Role of Social Media Usage as a Learning Tool on Students’ Academic Performance: A Structural Equation Modelling (SEM-AMOS) Approach

Social media is used in many aspects of modern life. Lately, higher education has also expanded its focus to include globalized online learning using social media. Educational establishments have acknowledged that social media gives students a chance to interact with teachers, other students, and higher authorities. However, there is little information available on it in educational settings, especially in the classroom. Only a small number of studies in Malaysia have specifically examined social media, even though many studies have looked at how social media influences the academic performance of university students. Therefore, we conducted this quantitative study to determine whether social media usage mediates the relationship between educational variables and academic performance among students enrolled in Malaysian public higher education institutions. We conducted a cross-sectional study at UiTM Segamat, involving 388 respondents. The findings demonstrate that social media usage mediates the relationship between students' performance and perceived usefulness, perceived enhanced communication, and resource sharing. Social media use does not mediate perceived ease of use, collaborative learning, or perceived enjoyment of students' performance. To use social media as a teaching tool, particularly in higher education institutions, the research findings bring new knowledge to the field. The higher education community may share knowledge anytime and anywhere. This platform allows educators and students to interact with one another after learning sessions, which will help the student succeed academically

Improvement of bone properties and enhancement of mineralization by ethanol extract of Fructus Ligustri Lucidi

2007-2008 > Academic research: refereed > Publication in refereed journalVersion of RecordPublishe

Analyzing Consumers Online Shopping Behavior Using Different Online Shopping Platforms: A Case Study in Malaysia

Nowadays, online shopping is gaining increasing popularity in Malaysia. The development of online shopping has led some to argue that there are additional elements influencing consumer behavior. As a result, a growing number of researchers are currently studying online consumer behavior to better understand the specific characteristics of online shopping. Therefore, this study is conducted to determine the factors that influence online shopping behavior between different online shopping platforms among Malaysian consumers. This is a quantitative study, and 371 students and staff from Universiti Teknologi MARA (UiTM) were randomly picked to participate. The data was gathered via an online questionnaire using Google Forms. The findings show a positive relationship between the variables, namely web characteristics, external stimulus, affection, and cognition. It indicates that all variables influence online shopping behavior among Malaysian consumers. Furthermore, the findings reveal that consumer behavior patterns for online shopping are not different even when using different online shopping platforms. Therefore, it is very critical to understand consumer online purchasing behavior and its influencing factors to improve online shopping in Malaysia. Malaysian businesses must have an in-depth knowledge of the market for their goods and the demographics of the customers they are targeting before engaging in online commerce

Charged-particle distributions at low transverse momentum in √s=13 13 TeV pp interactions measured with the ATLAS detector at the LHC

Measurements of distributions of charged particles produced in proton–proton collisions with a centre-of-mass energy of 13 TeV are presented. The data were recorded by the ATLAS detector at the LHC and correspond to an integrated luminosity of 151 μb −1 μb−1 . The particles are required to have a transverse momentum greater than 100 MeV and an absolute pseudorapidity less than 2.5. The charged-particle multiplicity, its dependence on transverse momentum and pseudorapidity and the dependence of the mean transverse momentum on multiplicity are measured in events containing at least two charged particles satisfying the above kinematic criteria. The results are corrected for detector effects and compared to the predictions from several Monte Carlo event generators

Search for supersymmetry at √s = 13 TeV in final states with jets and two same-sign leptons or three leptons with the ATLAS detector

A search for strongly produced supersymmetric particles is conducted using signatures involving multiple energetic jets and either two isolated leptons (e or μμ ) with the same electric charge or at least three isolated leptons. The search also utilises b-tagged jets, missing transverse momentum and other observables to extend its sensitivity. The analysis uses a data sample of proton–proton collisions at s√=13s=13 TeV recorded with the ATLAS detector at the Large Hadron Collider in 2015 corresponding to a total integrated luminosity of 3.2 fb −1−1. No significant excess over the Standard Model expectation is observed. The results are interpreted in several simplified supersymmetric models and extend the exclusion limits from previous searches. In the context of exclusive production and simplified decay modes, gluino masses are excluded at 95%95% confidence level up to 1.1–1.3 TeV for light neutralinos (depending on the decay channel), and bottom squark masses are also excluded up to 540 GeV. In the former scenarios, neutralino masses are also excluded up to 550–850 GeV for gluino masses around 1 TeV

Measurement of the inelastic proton-proton cross section at √s=13 TeV with the ATLAS detector at the LHC

This Letter presents a measurement of the inelastic proton-proton cross section using 60  μb −1 of pp collisions at a center-of-mass energy √s of 13 TeV with the ATLAS detector at the LHC. Inelastic interactions are selected using rings of plastic scintillators in the forward region (2.0710 −6 , where M X is the larger invariant mass of the two hadronic systems separated by the largest rapidity gap in the event. In this ξ range the scintillators are highly efficient. For diffractive events this corresponds to cases where at least one proton dissociates to a system with M X >13  GeV . The measured cross section is compared with a range of theoretical predictions. When extrapolated to the full phase space, a cross section of 78.1±2.9  mb is measured, consistent with the inelastic cross section increasing with center-of-mass energy

Measurement of the photon identification efficiencies with the ATLAS detector using LHC Run-1 data

© 2016, CERN for the benefit of the ATLAS collaboration.The algorithms used by the ATLAS Collaboration to reconstruct and identify prompt photons are described. Measurements of the photon identification efficiencies are reported, using 4.9 fb- 1 of pp collision data collected at the LHC at s=7 TeV and 20.3 fb- 1 at s=8 TeV. The efficiencies are measured separately for converted and unconverted photons, in four different pseudorapidity regions, for transverse momenta between 10 GeV and 1.5 TeV. The results from the combination of three data-driven techniques are compared to the predictions from a simulation of the detector response, after correcting the electromagnetic shower momenta in the simulation for the average differences observed with respect to data. Data-to-simulation efficiency ratios used as correction factors in physics measurements are determined to account for the small residual efficiency differences. These factors are measured with uncertainties between 0.5% and 10% in 7 TeV data and between 0.5% and 5.6% in 8 TeV data, depending on the photon transverse momentum and pseudorapidity