Adaptive scaling of cluster boundaries for large-scale social media data clustering

The large scale and complex nature of social media data raises the need to scale clustering techniques to big data and make them capable of automatically identifying data clusters with few empirical settings. In this paper, we present our investigation and three algorithms based on the fuzzy adaptive resonance theory (Fuzzy ART) that have linear computational complexity, use a single parameter, i.e., the vigilance parameter to identify data clusters, and are robust to modest parameter settings. The contribution of this paper lies in two aspects. First, we theoretically demonstrate how complement coding, commonly known as a normalization method, changes the clustering mechanism of Fuzzy ART, and discover the vigilance region (VR) that essentially determines how a cluster in the Fuzzy ART system recognizes similar patterns in the feature space. The VR gives an intrinsic interpretation of the clustering mechanism and limitations of Fuzzy ART. Second, we introduce the idea of allowing different clusters in the Fuzzy ART system to have different vigilance levels in order to meet the diverse nature of the pattern distribution of social media data. To this end, we propose three vigilance adaptation methods, namely, the activation maximization (AM) rule, the confliction minimization (CM) rule, and the hybrid integration (HI) rule. With an initial vigilance value, the resulting clustering algorithms, namely, the AM-ART, CM-ART, and HI-ART, can automatically adapt the vigilance values of all clusters during the learning epochs in order to produce better cluster boundaries. Experiments on four social media data sets show that AM-ART, CM-ART, and HI-ART are more robust than Fuzzy ART to the initial vigilance value, and they usually achieve better or comparable performance and much faster speed than the state-of-the-art clustering algorithms that also do not require a predefined number of clusters

Adaptive Resonance Theory (ART) for social media analytics

This chapter presents the ART-based clustering algorithms for social media analytics in detail. Sections 3.1 and 3.2 introduce Fuzzy ART and its clustering mechanisms, respectively, which provides a deep understanding of the base model that is used and extended for handling the social media clustering challenges. Important concepts such as vigilance region (VR) and its properties are explained and proven. Subsequently, Sects. 3.3-3.7 illustrate five types of ART adaptive resonance theory variants, each of which addresses the challenges in one social media analytical scenario, including automated parameter adaptation, user preference incorporation, short text clustering, heterogeneous data co-clustering and online streaming data indexing. The content of this chapter is several prior studies, including Probabilistic ART [15

The role of perceived organizational support and emotional intelligence towards workplace deviance among teachers

Workplace deviant behaviour has been a challenging issue for the organization today. It is widely recognized as it leads to major loss in organization’s productivity. Thus, this research aims to investigate the relationship between perceived organizational support and emotional intelligence towards workplace deviant behaviour among secondary school teachers. The study was carried out at nine secondary schools in Pasir Gudang district by using cross-sectional survey design. A total of 359 respondents were participated in this study. The data were analyzed using correlation and simple regression. The findings indicated that both perceived organizational support (r=-0.38, p<0.01) and emotional intelligence (r=-0.23, p<0.01) have a weak negative but significant relationship with the workplace deviant behaviour. In addition, the regression result indicated both perceived organizational support and emotional intelligence have significant impact on workplace deviance. The findings may help the school organization to understand the impact of organizational support and emotional intelligence of individual teacher to develop suitable course in handling workplace deviance

Effect of exogenous emulsifier on growth performance, fat digestibility, apparent metabolisable energy in broiler chickens

This research was done to evaluate the effect of a commercial exogenous emulsifier (polyethylene glycol ricinoleate (PEGR)) with high hydrophilic-to-lipophilic balance (HLB) supplementation to broiler chicken diets on growth performance, digestibility of fat and apparent metabolisable energy (AME) content in week 1, 3 and 5. A total of 360 one-day-old male Cobb broiler chicks were assigned in groups of 30 to 12 battery cages. The chicks were randomly assigned to two dietary treatments, with 6 replicate cages per treatment. The diets were either standard broiler starter and finisher, with rice bran oil (RBO) as supplemented fat source or similar diets + 0.05% emulsifier (RBOV). Feed intakes of RBOV groups significantly increased compared to those of RBO groups from week 2 till 4 while body weights of RBOV diets significantly increased in week 4 and 5. Both RBOV and RBO groups had similar FCR except for week 5. Addition of this strongly hydrophilic emulsifier showed no significant difference in fat digestibility of both RC and RV groups but higher AME was noted for the treatment than for the control groups at week 5. Therefore, supplementing the exogenous emulsifier into a broiler diet enriched with rice bran oil improved body weight and AME content at week 5 with minimal effect on fat digestibility

Seroepidemiology of coxsackievirus A6, coxsackievirus A16, and Enterovirus 71 infections among children and adolescents in Singapore, 2008-2010

10.1371/journal.pone.0127999PLoS ONE105e012799

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO

Performance of CMS muon reconstruction in pp collision events at sqrt(s) = 7 TeV

The performance of muon reconstruction, identification, and triggering in CMS has been studied using 40 inverse picobarns of data collected in pp collisions at sqrt(s) = 7 TeV at the LHC in 2010. A few benchmark sets of selection criteria covering a wide range of physics analysis needs have been examined. For all considered selections, the efficiency to reconstruct and identify a muon with a transverse momentum pT larger than a few GeV is above 95% over the whole region of pseudorapidity covered by the CMS muon system, abs(eta) < 2.4, while the probability to misidentify a hadron as a muon is well below 1%. The efficiency to trigger on single muons with pT above a few GeV is higher than 90% over the full eta range, and typically substantially better. The overall momentum scale is measured to a precision of 0.2% with muons from Z decays. The transverse momentum resolution varies from 1% to 6% depending on pseudorapidity for muons with pT below 100 GeV and, using cosmic rays, it is shown to be better than 10% in the central region up to pT = 1 TeV. Observed distributions of all quantities are well reproduced by the Monte Carlo simulation.Comment: Replaced with published version. Added journal reference and DO