Anita Agrawal

Birla Institute of Technology and Science, Pilani - Goa Campus

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A. Amalin Prince

Birla Institute of Technology and Science, Pilani - Goa Campus

Shibu Clement

Birla Institute of Technology and Science, Pilani

F. Robert

SRM Institute of Science and Technology

S. Sankhar Reddy

Birla Institute of Technology and Science, Pilani - Goa Campus

G. Praveen

Manipal Hospital

K. R. Anupama

Birla Institute of Technology and Science, Pilani

Saif Nalband

Thapar Institute of Engineering & Technology

Anupama Karuppiah

Birla Institute of Technology and Science, Pilani - Goa Campus

Mohammad Atique

Sant Gadge Baba Amravati University

Praveen Gurunath Bharathi

Stanford Medicine

Cooperative Institutions

Birla Institute of Technology and Science, Pilani - Goa Campus

Birla Institute of Technology and Science, Pilani

Banaras Hindu University

Indian Institute of Technology BHU

Indian Institute of Technology Kanpur

Imperial College London

Sant Gadge Baba Amravati University

All India Institute of Medical Sciences

All India Institute of Medical Sciences Raipur

All India Institute of Medical Sciences Bhopal

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Hybrid approach for brain tumor detection and classification in magnetic resonance images

Praveen Gurunath Bharathi Anita Agrawal

Computerized methods are used in medical imaging to image the inner portions of the human body for medical diagnosis. Image segmentation plays an important role in diagnosis, surgical planning, navigation and various medical evaluations. Manual, semi-automatic and automatic methods are existing for segmentation of the region of interest. In this paper, a hybrid approach for brain tumor detection and classification through magnetic resonance images has been proposed. First phase of the proposed approach deals with image preprocessing which includes noise filtering, skull detection, etc. The second phase deals with feature extraction of MR brain images using gray level co-occurrence matrix. Third phase deals with classification of inputs into normal or abnormal using Least Squares Support Vector Machine classifier with Multilayer perceptron kernel. Final phase is the segmentation of the tumor part from the brain using fast bounding box. The experiments were carried out on 100 images consisting of 25 normal and 75 abnormal from a real human brain and synthetic MRI dataset. The classification accuracy on both training and test images was found to be 96.63%.

10.1109/ccintels.2015.7437900

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Citations (53)

Towards EMG Based Gesture Recognition for Indian Sign Language Interpretation Using Artificial Neural Networks

Communications in computer and information science (2015)

Abhiroop Kaginalkar Anita Agrawal

Software portability

Interfacing

10.1007/978-3-319-21380-4_121

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Citations (1)

SQ-BOT - a modular robot prototype for self-reconfiguring structures

S. Sankhar Reddy Sharath patlolla Anita Agrawal K. R. Anupama

The modular robotics offers various advantages in relative to traditional robotic solutions for real world scenarios due to application specific nature and limited flexibilities of later. The low cost robust capabilities of the modular systems inspired researchers of swarm robotics, automation etc. to research modular robotics for developing affordable and capable systems to various applications in surveillance, disaster management etc. The research work in modular robotics so far is limited to laboratory prototyping and the development is yet to take complete form for real world applications. In this paper, a design of modular unit named "SQ-BOT" suitable for practical applications is proposed along with model simulations and hardware experiments.

Self-reconfiguring modular robot

10.1109/rctfc.2016.7893408

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Citations (1)

Effect of Anode Temperature and Contact Voltage on the Design of Arc- Less Micro Electrical Contact

Micro and Nanosystems (2018)

F. Robert Anita Agrawal Shibu Clement

Objective: This paper presents the effect of anode temperature and contact voltage on the breakdown arc of micro electrical contact pair under DC excitation. Methods: A rectangular micro electrical contact pair is considered. The resistance and capacitance of the contact pair are obtained for the materials Al, Cu, Au and Pt. The anode temperature is calculated based on the 3D heat equation. Pre-breakdown arc due to anode temperature is analyzed. Result: The breakdown voltage and breakdown electric field characteristics for the gap between 0.5µm and 30µm are reported. The electric field of micro electrical contact pair is analyzed mathematically. The calculated values of resistance, anode temperature and electric field are compared with the simulation results obtained using COMSOL multiphysics FEA software tool. The arc-less operating region of micro contact is identified. Four cases with the ratings 50V/5A, 50V/0.5A, 400 V/ 5A and 400V/0.5A have been considered for the analysis of arcless micro electrical contact. Conclusion: These results can be considered while designing arc-less micro electrical switches, micro relays and micro circuit breakers which can be applicable for the future DC electric power distribution, protection system and automobiles. Also these results can be considered when designing micro actuators, sensors and electrostatic devices.

Multiphysics

Contact resistance

Electrical contacts

Electrical breakdown

Electric arc

10.2174/1876402911666181214143451

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Citations (2)

Modular Self-Reconfigurable Robotic Systems: A Survey on Hardware Architectures

Journal of Robotics (2017)

S. Sankhar Reddy Anita Agrawal Anupama Karuppiah

Modular self-reconfigurable robots present wide and unique solutions for growing demands in the domains of space exploration, automation, consumer products, and so forth. The higher utilization factor and self-healing capabilities are most demanded traits in robotics for real world applications and modular robotics offer better solutions in these perspectives in relation to traditional robotics. The researchers in robotics domain identified various applications and prototyped numerous robotic models while addressing constraints such as homogeneity, reconfigurability, form factor, and power consumption. The diversified nature of various modular robotic solutions proposed for real world applications and utilization of different sensor and actuator interfacing techniques along with physical model optimizations presents implicit challenges to researchers while identifying and visualizing the merits/demerits of various approaches to a solution. This paper attempts to simplify the comparison of various hardware prototypes by providing a brief study on hardware architectures of modular robots capable of self-healing and reconfiguration along with design techniques adopted in modeling robots, interfacing technologies, and so forth over the past 25 years.

Interfacing

Reconfigurability

Control reconfiguration

Self-reconfiguring modular robot

10.1155/2017/5013532

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Citations (75)

Investigation of Microelectromechanical Switches for Next Generation DC Power Distribution System

International Journal of Emerging Electric Power Systems (2014)

F. Robert Shibu Clement Anita Agrawal A. Amalin Prince

Abstract This paper investigates the application of microelectromechanical system (MEMS) switches for DC power distribution system. Traditional electromechanical switches, solid state switches and solid state switch array are studied and simulated to understand their characteristics. Performance and characteristics of MEMS switches are reviewed and identified that electrostatically actuated MEMS switches are suitable for DC power applications. Scalable total cross tied (TCT) array configuration using MEMS switches has been proposed. The proposed configuration is suitable for variable voltage/current rating. Arc-less behavior of the switch configuration is analyzed using modified Paschen’s curve. 400 V/6 A system is considered for the simulation and comparative study. The simulated result of the proposed MEMS switch array configuration is compared with the traditional switches. The comparative study shows that the proposed switch array configuration gives better performance in terms of voltage drop, leakage current, power loss, arc and size. This can be used in DC power system protection, circuit breaking, battery protection and smart grid load switching applications.

Solid-state relay

Voltage drop

10.1515/ijeeps-2014-0042

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Citations (8)

Entropy‐based feature extraction and classification of vibroarthographic signal using complete ensemble empirical mode decomposition with adaptive noise

IET Science Measurement & Technology (2017)

Saif Nalband A. Amalin Prince Anita Agrawal

Non‐invasive methods accomplished by a computer aided diagnosis of knee‐joint disorders provide an effective tool. The objective of this study is to analyse vibroarthographic (VAG) signals using non‐linear signal processing technique. This study includes different entropy‐based feature extraction techniques to attain highly distinguishable features. The authors proposed to use a non‐linear method known as complete ensemble empirical mode decomposition with adaptive white noise to decompose the VAG signals into intrinsic mode functions (IMFs). Entropy‐based features involving approximate entropy, sample entropy, Shannon entropy, Rényi entropy, Tsallis entropy and permutation entropy (PeEn) are computed from dominant IMFs and reconstructed VAG signals. These extracted features are given as input to the least squares support vector machine as a classifier. The results illustrated that PeEn performed better with respect to other entropies. PeEn gives a classification accuracy of 86.61% and Matthews correlation coefficient of 0.7082. The computational complexity of entropies was also analysed. Results inferred that PeEn has a computational complexity of O ( N ) provided a simple, robust and low computational feature extraction technique. Analysis of VAG signals using non‐linear preprocessing and entropy‐based features can provide highly distinguishable features for accurate detection of knee‐joint disorders.

Ensemble Learning

Approximate entropy

10.1049/iet-smt.2017.0284

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Citations (44)

Design of a Floating-Point ALU for Calculating Shortest Distance Between Two Floating Point Numbers

Anita Agrawal Arijit Biswas Shruti Singh S. Neogy

10.1109/icses63445.2024.10763154

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Ultrasonic Guided Waves for Structural Health Monitoring Applications

2020 IEEE International Students' Conference on Electrical,Electronics and Computer Science (SCEECS) (2020)

Anirudh Dwarakanath Anita Agrawal

Ultrasonic guided waves present several properties that make them optimal for use in structural health monitoring applications. This paper aims to simulate the behaviour exhibited by these waves in solids, and to experimentally verify their efficacy in detection of various defects in aluminium sheets, with an aim to monitor the structural health of airframes using piezoelectric wafer active sensors as actuators and sensors - primarily to detect fractures, or surface corrosion for advance warning against airframe failures.

Airframe

Structural Health Monitoring

Lamb waves

10.1109/sceecs48394.2020.138

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Corrigendum to “Modular Self-Reconfigurable Robotic Systems: A Survey on Hardware Architectures”

Journal of Robotics (2017)

S. Sankhar Reddy Anita Agrawal Anupama Karuppiah

10.1155/2017/7139382

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Citations (4)