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Sentiment analysis of malayalam tweets using machine learning techniques
Soumya S.,Pramod K.V. 한국통신학회 2020 ICT Express Vol.6 No.4
Sentiment Analysis of Malayalam Tweets using Machine Learning techniques is done in this paper. The tweets are classified into positive and negative using different machine learning techniques such as Naive Bayes (NB), Support Vector Machine (SVM) and Random Forest (RF). The different features like Bag of Words (BOW), Term Frequency vs. Inverse Document Frequency (TF IDF), Unigram with Sentiwordnet, and Unigram with Sentiwordnet including negation words are considered for feature vector formation of input dataset. The Random Forest classifier shows higher accuracy while considering Unigram with Sentiwordnet including negation words as a feature.
Model-based, Distributed, and Cooperative Control of Planar Serial-link Manipulators
S. Soumya,K. R. Guruprasad 제어·로봇·시스템학회 2021 International Journal of Control, Automation, and Vol.19 No.2
In this paper, we propose a novel distributed control scheme for a planar serial-link manipulator with revolute joints. The control scheme is based on the conventional model-based nonlinear control scheme that achieves linearization by feedback. A dedicated controller controls each joint of the manipulator, as in the case of the decentralized manipulator control scheme. However, in the proposed control scheme, the joint-level controllers communicate and cooperate to account for the nonlinear dynamic coupling between the links. The proposed control scheme can achieve the performance level of that of the model-based nonlinear control scheme, and at the same time, reduce the computational lead-time by distributing the computational load associated with the control law among the joint-level controllers. We design a distributed cooperative control law for a three-link planar manipulator and demonstrate its trajectory tracking performance using simulation experiments.
Dielectrically Modulated Hetero Channel Double Gate MOSFET as a Label Free Biosensor
Soumya S. Mohanty,Sikha Mishra,Meryleen Mohapatra,Guru Prasad Mishra 한국전기전자재료학회 2022 Transactions on Electrical and Electronic Material Vol.23 No.2
A dielectric modulation (DM) highly sensitive InP/InGaAs/InP hetero channel dual material double gate MOSFET (H-DMDG MOSFET) is designed and simulated for accurate identifi cation of the bio-targets such as protein, streptavidin, uricase, biotin, APTES, and Keratin. Group III–V based materials are considered for biosensor design for its chemical inertness, high temperature/power ability, and high carrier velocity. Nanogap cavity is incorporated near the source and drain ends within the gate dielectric for sensing the neutral and charged analytes. The simulated parameters of the proposed structure are analyzed by varying dielectric constant and the charge density of the biomolecules. The infl uence of both the biomolecules on the electrical features like surface potential, drain current, electric fi eld, and sensitivity have been examined. The highest sensitivity of 0.513 and a lower electric fi eld of 1.98 × 10 6 V/cm is attained at the drain end for K = 8 as compared to other biomolecules.
Biomechanical Assessment of Stabilization of Simulated Type II Odontoid Fracture with Case Study
Roy T. Daniel,Mir M. Hussain,Noelle Klocke,Soumya S. Yandamuri,Lukas Bobinski,John M. Duff,Brandon S. Bucklen 대한척추외과학회 2017 Asian Spine Journal Vol.11 No.1
Study Design: Researchers created a proper type II dens fracture (DF) and quantified a novel current posterior fixation technique with spacers at C1–C2. A clinical case study supplements this biomechanical analysis. Purpose: Researchers explored their hypothesis that spacers combined with posterior instrumentation (PI) reduce range of motion significantly, possibly leading to better fusion outcomes. Overview of Literature: Literature shows that the atlantoaxial joint is unique in allowing segmental rotary motion, enabling head turning. With no intervertebral discs at these joints, multiple ligaments bind the axis to the skull base and to the atlas; an intact odontoid (dens) enhances stability. The most common traumatic injury at these strong ligaments is a type II odontoid fracture. Methods: Each of seven specimens (C0–C3) was tested on a custom-built six-degrees-of-freedom spine simulator with constructs of intact state, type II DF, C1–C2 PI, PI with joint capsulotomy (PIJC), PI with spacers (PIS) at C1–C2, and spacers alone (SA). A bending moment of 2.0 Nm (1.5°/sec) was applied in flexion-extension (FE), lateral bending (LB), and axial rotation (AR). One-way analysis of variance with repeated measures was performed. Results: DF increased motion to 320%, 429%, and 120% versus intact (FE, LB, and AR, respectively). PI significantly reduced motion to 41%, 21%, and 8%. PIJC showed negligible changes from PI. PIS reduced motion to 16%, 14%, and 3%. SA decreased motion to 64%, 24%, and 54%. Reduced motion facilitated solid fusion in an 89-year-old female patient within 1 year. Conclusions: Type II odontoid fractures can lead to acute or chronic instability. Current fixation techniques use C1–C2 PI or an anterior dens screw. Addition of spacers alongside PI led to increased biomechanical rigidity over intact motion and may offer an alternative to established surgical fixation techniques.
Singh, Ajay,Singh, Avtar,Singh, Manvendra,Prakash, Ved,Ambhore, G.S.,Sahoo, S.K.,Dash, Soumya Asian Australasian Association of Animal Productio 2016 Animal Bioscience Vol.29 No.6
A single trait linear mixed random regression test-day model was applied for the first time for analyzing the first lactation monthly test-day milk yield records in Karan Fries cattle. The test-day milk yield data was modeled using a random regression model (RRM) considering different order of Legendre polynomial for the additive genetic effect (4th order) and the permanent environmental effect (5th order). Data pertaining to 1,583 lactation records spread over a period of 30 years were recorded and analyzed in the study. The variance component, heritability and genetic correlations among test-day milk yields were estimated using RRM. RRM heritability estimates of test-day milk yield varied from 0.11 to 0.22 in different test-day records. The estimates of genetic correlations between different test-day milk yields ranged 0.01 (test-day 1 [TD-1] and TD-11) to 0.99 (TD-4 and TD-5). The magnitudes of genetic correlations between test-day milk yields decreased as the interval between test-days increased and adjacent test-day had higher correlations. Additive genetic and permanent environment variances were higher for test-day milk yields at both ends of lactation. The residual variance was observed to be lower than the permanent environment variance for all the test-day milk yields.