EEG Based Emotion Prediction with Neural Network Models

The term "emotion" refers to an individual\u27s response to an event, person, or condition. In recent years, there has been an increase in the number of papers that have studied emotion estimation. In this study, a dataset based on three different emotions, utilized to classify feelings using EEG brainwaves, has been analysed. In the dataset, six film clips have been used to elicit positive and negative emotions from a male and a female. However, there has not been a trigger to elicit a neutral mood. Various classification approaches have been used to classify the dataset, including MLP, SVM, PNN, KNN, and decision tree methods. The Bagged Tree technique which is utilized for the first time has been achieved a 98.60 percent success rate in this study, according to the researchers. In addition, the dataset has been classified using the PNN approach, and achieved a success rate of 94.32 percent

Hybrid Classification Model for Emotion Prediction from EEG Signals: A Comparative Study

This paper introduces a novel hybrid algorithm for emotion classification based on electroencephalogram (EEG) signals. The proposed hybrid model consists of two layers: the first layer includes three parallel adaptive neuro-fuzzy inference systems (ANFIS), and the second layer called the adaptive network comprises various models such as radial basis function neural network (RBFNN), probabilistic neural network (PNN), and ANFIS. It is examined that the feature distribution graphs of the dataset, which includes three emotion classes: positive, negative, and neutral, and selected the most appropriate features for classification. The three parallel ANFIS structures were trained using the selected features as input vectors, and the outputs of these models were combined to obtain a new feature vector. This feature vector was then used as the input to the adaptive network, which produced the output of emotion prediction. In addition, it is evaluated the accuracy of the network trained using only the first features of the dataset. The hybrid structure was designed to enhance the system's performance, and the best accuracy result of 96.51% was achieved using the ANFIS-ANFIS model. Overall, this study provides a promising approach for emotion classification based on EEG signals.&nbsp

New perturbation theory of low-dimensional quantum liquids II: operator description of Virasoro algebras in integrable systems

We show that the recently developed {\it pseudoparticle operator algebra} which generates the low-energy Hamiltonian eigenstates of multicomponent integrable systems also provides a natural operator representation for the the Virasoro algebras associated with the conformal-invariant character of the low-energy spectrum of the these models. Studying explicitly the Hubbard chain in a non-zero chemical potential and external magnetic field, we establish that the pseudoparticle perturbation theory provides a correct starting point for the construction of a suitable critical-point Hamiltonian. We derive explicit expressions in terms of pseudoparticle operators for the generators of the Virasoro algebras and the energy-momentum tensor, describe the conformal-invariant character of the critical point from the point of view of the response to curvature of the two-dimensional space-time, and discuss the relation to Kac-Moody algebras and dynamical separation.Comment: 35 pages, RevteX, preprint UA

Distributive politics and regional development: assessing the territorial distribution of Turkey’s public investment

Turkey is often perceived as a country with low bureaucratic capacity and prone to political manipulation and ‘pork-barrel’. This article tests whether this is the case, by analysing the extent to which politics, rather than equity and efficiency criteria, have determined the geographical allocation of public investment across the 81 provinces of Turkey between 2005 and 2012. The results show that although the Turkish government has indeed channelled public expenditures to reward its core constituencies, socioeconomic factors remained the most relevant predictors of investment. Moreover, in contrast to official regional development policy principles, we uncover the concentration of public investment in areas with comparatively higher levels of development. We interpret this as the state bureaucracy’s intentional strategy of focussing on efficiency by concentrating resources on ‘the better off among the most in need’

Search for the standard model Higgs boson in the H to ZZ to 2l 2nu channel in pp collisions at sqrt(s) = 7 TeV

A search for the standard model Higgs boson in the H to ZZ to 2l 2nu decay channel, where l = e or mu, in pp collisions at a center-of-mass energy of 7 TeV is presented. The data were collected at the LHC, with the CMS detector, and correspond to an integrated luminosity of 4.6 inverse femtobarns. No significant excess is observed above the background expectation, and upper limits are set on the Higgs boson production cross section. The presence of the standard model Higgs boson with a mass in the 270-440 GeV range is excluded at 95% confidence level.Comment: Submitted to JHE

Search for New Physics with Jets and Missing Transverse Momentum in pp collisions at sqrt(s) = 7 TeV

A search for new physics is presented based on an event signature of at least three jets accompanied by large missing transverse momentum, using a data sample corresponding to an integrated luminosity of 36 inverse picobarns collected in proton--proton collisions at sqrt(s)=7 TeV with the CMS detector at the LHC. No excess of events is observed above the expected standard model backgrounds, which are all estimated from the data. Exclusion limits are presented for the constrained minimal supersymmetric extension of the standard model. Cross section limits are also presented using simplified models with new particles decaying to an undetected particle and one or two jets

Measurement of the Z/gamma* + b-jet cross section in pp collisions at 7 TeV

The production of b jets in association with a Z/gamma* boson is studied using proton-proton collisions delivered by the LHC at a centre-of-mass energy of 7 TeV and recorded by the CMS detector. The inclusive cross section for Z/gamma* + b-jet production is measured in a sample corresponding to an integrated luminosity of 2.2 inverse femtobarns. The Z/gamma* + b-jet cross section with Z/gamma* to ll (where ll = ee or mu mu) for events with the invariant mass 60 < M(ll) < 120 GeV, at least one b jet at the hadron level with pT > 25 GeV and abs(eta) < 2.1, and a separation between the leptons and the jets of Delta R > 0.5 is found to be 5.84 +/- 0.08 (stat.) +/- 0.72 (syst.) +(0.25)/-(0.55) (theory) pb. The kinematic properties of the events are also studied and found to be in agreement with the predictions made by the MadGraph event generator with the parton shower and the hadronisation performed by PYTHIA.Comment: Submitted to the Journal of High Energy Physic

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