Analysis of Motor Action and Motor Imagery Signals for BCI Applications |
Author : B.Vivekananthan , R.Nithya , B.Divya |
Abstract | Full Text |
Abstract :Brain Computer Interface ( BCI) is a computerized system that acquires brain signals, extracts and
classifies features during different mental activities, and converts them into correct control signals, and
transfers them to external devices. BCI helps people with motor disabilities. Real-time application of a BCI
system needs an efficient classification of motor tasks. Motor Imagery task identification based on EEG
signals is still challenging for researchers. Extraction of robust, mutual information and discriminative
features which can be converted into device commands is the biggest challenge in Motor Imagery BCI
system. This study aims to analyse the effectiveness of motor and motor imagery classification for left hand
and right-hand movements. The motor and motor imagery of left and right-hand movements is defined using
statistical features of a higher order that are fed to classifier SVM and Random Forest Classifier. Using SVM
classifier, for motor action the classification accuracy of 62.5% was reached and for motor imagery
classification accuracy of 45.83% was reached. Using random forest classifier, for motor action the
classification accuracy of 80.2% was reached and for motor imagery classification accuracy of 64.58% was
reached. |
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Location Identification Using Stanford NLP |
Author : S. Vishnu Manoj |
Abstract | Full Text |
Abstract :Even since the 40s the scope of natural language processing has been primal dismay in
computer science and Artificial Intelligence. It aspires to include the next strive forward in Artificial
Knowledge which can perform both computers and Individual work with better malleability and
apprehension. It incorporates various methods like machine translation, speech recognition, online
learning, auto tutor etc. Researchers recalled it as a potential bridge that can amalgamate human
spoken language and computer which uses programming language and binary codes. Since it is an
impossible task to prepare a computer to recognize human natural language, further techniques and
enhancements will foster the demanding yet rewarding and innovative computational trends. This
paper confers a restrained domain metaphysical model for agriculture cultivation question answering
system. The question answering system has been noted as a significant tactic for knowledge
engineering research. Ontologies facilitate the computers in deciphering the restrain domain concept
of semantics. Thus forming a significant technique for the question-answering system. This paper
inculcates introduction ontology and the definition of a domain ontology for agriculture cultivation.
The paper also focused on presenting the restricted domain ontology models and concept level vector
space model of information retrieval. |
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Experimental Study on Strength and Durability Properties of High Strength Concrete Using Mineral Admixtures and Copper Slag |
Author : Vignesh Kumar.B , Dr.K.Arumugam , M.Vijayakumar , Akila.R |
Abstract | Full Text |
Abstract :Concrete is the most widely used building material. In worldwide the high rise
buildings are constructed by using high strength concrete mode only. Growing demand for
construction materials necessitated the usage of alternative materials in the production of
conventional concrete. Now a days fine aggregate source is reduced due to high
consumption, so some material is needed to replacing of sand. The objective of this work is
to study the strength and durability properties of concrete. Here M 70 grade concrete used
and concrete containing copper slag as partial replacement of fine aggregate and mineral
admixture as partial replacement of cement in the concrete mix design. Copper slag content
has been 40% as a replacement of fine aggregate and silica fume 5%,10%,15% & 20% and
GGBS 5%,10%,15% & 20% as a replacement of cement respectively .This research paper
study on strength test& Durability test. The test results show 40% replacement of fine
aggregate as copper slag gives them more strength. And Silica fume & GGBS as partial
replacement of cement (up to 15%). From the results, it was observed that the use of copper
slag and mineral admixture in concrete has shown a considerable increase in strength and
reduction of the cost when compared with normal concrete. |
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15 Level Single Phase Multilevel Inverter Topology with Equal Area Criteria PWM Technique |
Author : B. T. Venu Gopal , N.Yashwanth Kumar , E. G. Shivakumar |
Abstract | Full Text |
Abstract :90 percent of the motors used in industries are induction motors due to its simple
design and high robustness. Total Harmonic Distortion of output voltage waveform keeps
decreasing as the number of voltage levels increases. The main consideration while selecting a
multilevel inverter is its quality of the output voltage waveform which is assessed in terms of the
amount of harmonics content present in it. So, Total Harmonic Distortion (THD) value in the
output voltage waveform is one of the important criteria in the multilevel inverter (MLI). The 15
level hybrid multilevel inverter circuit was simulated in Matlab/Simulink environment and the
results were experimentally analysed for a resistive load. C code was developed to generate PWM
pulses. Arduino microcontroller is used to feed the PWM pulses to the switches in the inverter
circuit. From the overall analysis, it is proved that the Equal Area Criteria (EAC) method is
superior to the other PWM methods. |
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Used Car Price Prediction using K-Nearest Neighbor Based Model |
Author : K.Samruddhi , Dr R.Ashok Kumar |
Abstract | Full Text |
Abstract :Predicting the price of used cars is one of the significant and interesting areas of
analysis. As an increased demand in the second-hand car market, the business for both buyers and
sellers has increased. For reliable and accurate prediction it requires expert knowledge about the field
because of the price of the cars dependent on many important factors. This paper proposed a
supervised machine learning model using KNN (K Nearest Neighbor) regression algorithm to analyze
the price of used cars. We trained our model with data of used cars which is collected from the
Kaggle website. Through this experiment, the data was examined with different trained and test
ratios. As a result, the accuracy of the proposed model is around 85% and is fitted as the optimized
model. |
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