Multi-sensor fusion based on multiple classifier systems for human activity identification

Multimodal sensors in healthcare applications have been increasingly researched because it facilitates automatic and comprehensive monitoring of human behaviors, high-intensity sports management, energy expenditure estimation, and postural detection. Recent studies have shown the importance of multi-sensor fusion to achieve robustness, high-performance generalization, provide diversity and tackle challenging issue that maybe difficult with single sensor values. The aim of this study is to propose an innovative multi-sensor fusion framework to improve human activity detection performances and reduce misrecognition rate. The study proposes a multi-view ensemble algorithm to integrate predicted values of different motion sensors. To this end, computationally efficient classification algorithms such as decision tree, logistic regression and k-Nearest Neighbors were used to implement diverse, flexible and dynamic human activity detection systems. To provide compact feature vector representation, we studied hybrid bio-inspired evolutionary search algorithm and correlation-based feature selection method and evaluate their impact on extracted feature vectors from individual sensor modality. Furthermore, we utilized Synthetic Over-sampling minority Techniques (SMOTE) algorithm to reduce the impact of class imbalance and improve performance results. With the above methods, this paper provides unified framework to resolve major challenges in human activity identification. The performance results obtained using two publicly available datasets showed significant improvement over baseline methods in the detection of specific activity details and reduced error rate. The performance results of our evaluation showed 3% to 24% improvement in accuracy, recall, precision, F-measure and detection ability (AUC) compared to single sensors and feature-level fusion. The benefit of the proposed multi-sensor fusion is the ability to utilize distinct feature characteristics of individual sensor and multiple classifier systems to improve recognition accuracy. In addition, the study suggests a promising potential of hybrid feature selection approach, diversity-based multiple classifier systems to improve mobile and wearable sensor-based human activity detection and health monitoring system. - 2019, The Author(s).This research is supported by University of Malaya BKP Special Grant no vote BKS006-2018.Scopu

MSI-CIEC: MSI Cyberinfrastructure Empowerment Coalition and the TeraGrid

Paper written as a collaboration of the following institutions and presented at the 2006 TeraGrid Conference, Indianapolis, IN June 12-16: 1. University of Houston Downtown 2. NAFEO: National Association for Equal Opportunity in Higher Education 3. SDSC: San Diego Supercomputer Center 4. Indiana University, Computer Science Department 5. AIHEC: The American Indiana Highter Education Consortium 6. HACU: Hispanic Association of Colleges and Universitie

Sustainable entrepreneurship development in Oman: A multi-stakeholder qualitative study

Purpose: Even though sustainable entrepreneurship has increasingly received researchers’ attention in recent years, the topic remains rather under-researched in natural resources’ rich Arabian gulf countries such as Oman. Hence, the current paper fills this gap in the literature and is one of the first attempts to assess the state of sustainable entrepreneurship development in Oman from a multi-stakeholder perspective. Design/Methodology/Approach: The current paper uses a qualitative research approach where in-depth semi-structured interviews were undertaken with twelve (12) respondents representing relevant stakeholders of sustainable entrepreneurship development in Oman. Our interviewees included four (4) sustainable entrepreneurs, four (4) policy makers, and four (4) educationists representing entrepreneurial skills development institutes in Oman. Findings: Our findings highlight that despite some positive improvements, several critical challenges remain, which hinder sustainable entrepreneurship development. We further found the role of FinTech to be critical in this concern by all stakeholders, though its usage and acceptance remain low. Also, the costs associated with the post-carbon (sustainable) economy and different profitability evolution have resulted in a slow change in the policy development in this concern. From educational (skills development) perspective, a lack of context specific training programmes and culture-based hesitations appeared to be hindering achieving sustainable entrepreneurship possibilities in Oman. The premature entrepreneurial ecosystem, bureaucracy, and lack of human capital (attaining as well as retention) appeared to be significant challenges for entrepreneurs. Finally, our findings highlighted the need for cross-sector collaboration with clear benchmarks for effective policy development concerning sustainable entrepreneurship in Oman. Originality: The current paper is the first academic study explicitly highlighting the state of sustainable entrepreneurship in Oman by incorporating the development initiatives as well as the major challenges in the analysis. Secondly, our study is also a pioneering work specifying the interlinkage between financing (FinTech), policy initiatives and skills development, and the development of a sustainable entrepreneurship ecosystem in an under-researched context of Oman. Finally, the transition to a sustainable economy is challenging in natural resources’ dependent economies like Oman, as it needs to be supported by the mindset change in the larger society (legitimacy). In this concern, our paper is one of the first academic endeavours to also specify the role of legitimacy from the perspective of different stakeholders (and larger society) for sustainable entrepreneurship development in such contexts

An analyses of the status of landfill classification systems in developing countries: Sub Saharan Africa landfill experiences

Municipal solid waste (MSW) management remains a challenge in developing countries due to increasing waste generation, high costs associated with waste management and the structure of the containment systems implemented. This study analyses the classification of landfilling systems by using documented cases reported mainly in publications in waste management in relation to non-engineered landfilling systems/approved dumpsites in Sub Saharan African (SSA) countries from 2000 to 2018. The work identifies an existing system for the classification of landfill sites and utilises this system to determine the situation of landfill sites in SSA countries. Each article was categorised according to the main landfilling management practice reported: Uncontrolled dumping, semi controlled facility, medium controlled facility, medium/high-engineered facility or high state-of the-art facility. Findings suggested that 80% of the documented cases of landfill sites assessed in SSA countries were classified as level 0 or 1. The structure of the containment and controlled regime were identified by the focus group discussion participants as important predictors of possible strengths, weaknesses, opportunities and threats for the landfill sites considered. The study represents the first identifiable and comprehensive academic evaluation of landfill site classification based on site operations reported in the available peer reviewed literature. The information provides insight on the status of landfill sites in SSA countries with respect to the landfilling management practice and a baseline for alternative corrective measures

Neurobiology of rodent self-grooming and its value for translational neuroscience

Self-grooming is a complex innate behaviour with an evolutionarily conserved sequencing pattern and is one of the most frequently performed behavioural activities in rodents. In this Review, we discuss the neurobiology of rodent self-grooming, and we highlight studies of rodent models of neuropsychiatric disorders-including models of autism spectrum disorder and obsessive compulsive disorder-that have assessed self-grooming phenotypes. We suggest that rodent self-grooming may be a useful measure of repetitive behaviour in such models, and therefore of value to translational psychiatry. Assessment of rodent self-grooming may also be useful for understanding the neural circuits that are involved in complex sequential patterns of action.National Institutes of Health (U.S.) (Grant NS025529)National Institutes of Health (U.S.) (Grant HD028341)National Institutes of Health (U.S.) (Grant MH060379

Measurement of the nuclear modification factor for muons from charm and bottom hadrons in Pb+Pb collisions at 5.02 TeV with the ATLAS detector

Heavy-flavour hadron production provides information about the transport properties and microscopic structure of the quark-gluon plasma created in ultra-relativistic heavy-ion collisions. A measurement of the muons from semileptonic decays of charm and bottom hadrons produced in Pb+Pb and pp collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV with the ATLAS detector at the Large Hadron Collider is presented. The Pb+Pb data were collected in 2015 and 2018 with sampled integrated luminosities of 208 mu b(-1) and 38 mu b(-1), respectively, and pp data with a sampled integrated luminosity of 1.17 pb(-1) were collected in 2017. Muons from heavy-flavour semileptonic decays are separated from the light-flavour hadronic background using the momentum imbalance between the inner detector and muon spectrometer measurements, and muons originating from charm and bottom decays are further separated via the muon track's transverse impact parameter. Differential yields in Pb+Pb collisions and differential cross sections in pp collisions for such muons are measured as a function of muon transverse momentum from 4 GeV to 30 GeV in the absolute pseudorapidity interval vertical bar eta vertical bar < 2. Nuclear modification factors for charm and bottom muons are presented as a function of muon transverse momentum in intervals of Pb+Pb collision centrality. The bottom muon results are the most precise measurement of b quark nuclear modification at low transverse momentum where reconstruction of B hadrons is challenging. The measured nuclear modification factors quantify a significant suppression of the yields of muons from decays of charm and bottom hadrons, with stronger effects for muons from charm hadron decays

A search for an unexpected asymmetry in the production of e+μ− and e−μ+ pairs in proton-proton collisions recorded by the ATLAS detector at root s = 13 TeV

This search, a type not previously performed at ATLAS, uses a comparison of the production cross sections for e(+)mu(-) and e(-)mu(+) pairs to constrain physics processes beyond the Standard Model. It uses 139 fb(-1) of proton-proton collision data recorded at root s = 13 TeV at the LHC. Targeting sources of new physics which prefer final states containing e(+)mu(-) and e(-)mu(+), the search contains two broad signal regions which are used to provide model-independent constraints on the ratio of cross sections at the 2% level. The search also has two special selections targeting supersymmetric models and leptoquark signatures. Observations using one of these selections are able to exclude, at 95% confidence level, singly produced smuons with masses up to 640 GeV in a model in which the only other light sparticle is a neutralino when the R-parity-violating coupling lambda(23)(1)' is close to unity. Observations using the other selection exclude scalar leptoquarks with masses below 1880 GeV when g(1R)(eu) = g(1R)(mu c) = 1, at 95% confidence level. The limit on the coupling reduces to g(1R)(eu) = g(1R)(mu c) = 0.46 for a mass of 1420 GeV

Differential cross-section measurements of the production of four charged leptons in association with two jets using the ATLAS detector

Differential cross-sections are measured for the production of four charged leptons in association with two jets. These measurements are sensitive to final states in which the jets are produced via the strong interaction as well as to the purely-electroweak vector boson scattering process. The analysis is performed using proton-proton collision data collected by ATLAS at √s = 13 TeV and with an integrated luminosity of 140 fb−1. The data are corrected for the effects of detector inefficiency and resolution and are compared to state-of-the-art Monte Carlo event generator predictions. The differential cross-sections are used to search for anomalous weak-boson self-interactions that are induced by dimension-six and dimension-eight operators in Standard Model effective field theory

Retrospective survey of hydatid cyst infection in sheep and cattle based on abattoir data in Al-Najaf province, Iraq

Cystic echinococcosis (CE) is a parasitic zoonotic disease which is highly endemic in Iraq and has an extensive effect on livestock productivity and human health. The current study focused on slaughtered sheep and cattle in Al-Najaf city abattoir, which infected with hydatid cysts from the period between January 2016 till December 2018. The total sheep examined were 244806, in which 3339 were found to be positive for hydatidosis, while in cattle, the total examined number was 59001, in which 887 were found to be positive for hydatidosis. In current study, the prevalence rate was estimated to be 1.49 % for hydatidosis in sheep, whereas in cattle it was 1.60 %. There were no differences between sheep and cattle rate infections. The highest rate of infection in sheep and cattle was observed in April 2.03% and July 1.89 respectively, while the lowest rate was observed in September 1.27% and November 1.04, respectively. Seasonally, the highest infection rate of hydatid cysts was 1.60 % in spring for sheep and 1.77 % in summer for cattle. The findings of this study demonstrated that the prevalence of hydatid cysts infections is generally lower than those reported from other regions of Iraq, and at the same time, it clearly remains prevalent. Hydatid cysts are common and widely distributed in sheep and cattle and they might play an important role in the life cycle and transmission of this zoonosis in Al-Najaf province