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( Manoj Kushwaha ),( M. S. Abirami ) 한국감성과학회 2021 한국감성과학회 국제학술대회(ICES) Vol.2021 No.-
Accidents occurred usually on roads, which bring enormous losses to society. Road accidents are a universal problem which causes the loss of precious human lives and property. The purpose of this paper is to extract important influence features of road accidents and reduce the dimensionality of datasets for getting better results from machine learning algorithms. Collected datasets from Kaggle and constructed new datasets from existing datasets based on the influence feature of road accidents and perform preprocessing, feature selection and feature extraction. Feature selection is done using heat map and correlation matrix. Feature extraction is done using dimensionality reduction methods such as the Principal Component Analysis (PCA), Linear discriminate analysis (LDA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). The different feature extraction techniques are applied and the results are compared based on the accuracy parameter. It was found that LDA performs better than PCA with accuracy of 85% which uses Random Forest classifier.
( Manoj Kushwaha ),( M. S. Abirami ),( Corresponding Author M. S. Abirami ) 한국감성과학회 2021 추계학술대회 Vol.2021 No.0
Accidents occurred usually on roads, which bring enormous losses to society. Road accidents are a universal problem which causes the loss of precious human lives and property. The purpose of this paper is to extract important influence features of road accidents and reduce the dimensionality of datasets for getting better results from machine learning algorithms. Collected datasets from Kaggle and constructed new datasets from existing datasets based on the influence feature of road accidents and perform preprocessing, feature selection and feature extraction. Feature selection is done using heat map and correlation matrix. Feature extraction is done using dimensionality reduction methods such as the Principal Component Analysis (PCA), Linear discriminate analysis (LDA) and t-Distributed Stochastic Neighbor Embedding (t-SNE). The different feature extraction techniques are applied and the results are compared based on the accuracy parameter. It was found that LDA performs better than PCA with accuracy of 85% which uses Random Forest classifier.
Analysis of 1/f Noise in Fully Depleted n-channel Double Gate SOI MOSFET
Kushwaha Alok,Pandey Manoj Kumar,Pandey Sujata,Gupta A.K. The Institute of Electronics and Information Engin 2005 Journal of semiconductor technology and science Vol.5 No.3
An analysis of the 1/f or flicker noise in FD n-channel Double Gate SOI MOSFET is proposed. In this paper, the variation of power spectral density (PSD) of the equivalent noise voltage and noise current with respect to frequency, channel length and gate-to-source voltage at various temperatures and exponent $C(i.e\;1/f^c$ is reported. The temperature is varied 125 K from to room temperature. The variation of PSD with respect to channel length down to $0.1{\mu}m$ technology is considered. It is analyzed that l/f noise in FD n-channel Double Gate SOI MOSFET is due to both carrierdensity fluctuations and mobility-fluctuations. But controversy still exits to its origin.
Kushwaha, Alok,Pandey, Manoj K.,Pandey, Sujata,Gupta, Anil K. The Institute of Electronics and Information Engin 2007 Journal of semiconductor technology and science Vol.7 No.2
A new two-dimensional analytical model for dual-material double-gate fully-depleted SOI MOSFET with Pearson-IV type Doping Distribution is presented. An investigation of electrical MOSFET parameters i.e. drain current, transconductance, channel resistance and device capacitance in DM DG FD SOI MOSFET is carried out with Pearson-IV type doping distribution as it is essential to establish proper profiles to get the optimum performance of the device. These parameters are categorically derived keeping view of potential at the center (${\phi}_c$) of the double gate SOI MOSFET as it is more sensitive than the potential at the surface (${\phi}_s$). The proposed structure is such that the work function of the gate material (both sides) near the source is higher than the one near the drain. This work demonstrates the benefits of high performance proposed structure over their single material gate counterparts. The results predicted by the model are compared with those obtained by 2D device simulator ATLAS to verify the accuracy of the proposed model.
Analysis of 1/f Noise in Fully Depleted n-channel Double Gate SOI MOSFET
Alok Kushwaha,Manoj Kumar Pandey,Sujata Pandey,A. K. Gupta 대한전자공학회 2005 Journal of semiconductor technology and science Vol.5 No.3
An analysis of the 1/f or flicker noise in FD n-channel Double Gate SOI MOSFET is proposed. In this paper, the variation of power spectral density (PSD) of the equivalent noise voltage and noise current with respect to frequency, channel length and gate-tosource voltage at various temperatures and exponent C(i.e 1/f^c) is reported. The temperature is varied 125 K from to room temperature. The variation of PSD with respect to channel length down to 0.1 μm technology is considered. It is analyzed that 1/f noise in FD n-channel Double Gate SOI MOSFET is due to both carrierdensity fluctuations and mobility-fluctuations. But controversy still exits to its origin.