Papers by suvarna chorage
Global journal of computer science and technology, 2017
Network-On-Chip (NoC) is used as a main part of a system. NoC overcomes traditional System-On-Chi... more Network-On-Chip (NoC) is used as a main part of a system. NoC overcomes traditional System-On-Chip (SoC) problems. Because, SoC has problems like cost, design risk, more complexity and more power consumption. In software part, Xilinx ISE Design suite 14.5 with VHDL programming is used. It is simple programming language. In hardware part, FPGA of Spartan 3E family is used. It is advanced 90nm technology. It is world’s the cheapest FPGA family. It has 500K gates and 40 LUTs. It has lowest cost per logic. Its better advantage is that it is designed for more volume-to-market. Power consumption of given system is compared with previous system. From output power analysis chart, it is concluded that given system has lower power consumption than previous system. Power consumption of gray to binary conversion block of previous system is nearly equal to power consumption of present (given) whole system. This proves that there is a great reduction in power consumption in the system.
Proceedings of Engineering and Technology Innovation
Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are... more Nanometer-sized carbon particulates generated by incomplete combustion in heavy-duty vehicles are harmful to human health. A high-resolution technique is needed to detect and measure these pollutants. This study aims to optimize a capacitive sensor design for detecting and measuring particulates. Firstly, the effect of design parameters on particulate detection and sensor compliance sensitivity is investigated by using the finite element method. By comparing the simulation results with literature findings for performance validation, the sensor structure is optimized to detect lower particulate concentrations. The simulation result shows that particulate detection sensitivity has linear variations with changes in particulate mass. With optimum electrode spacing and top insulation layer thickness of 5 µm, the sensor can detect a particulate deposition of 0.033 mg/min and generate a maximum capacitance of 581 pF. Since the optimized design can measure particulate deposition at a lower ...
Optimized Neural Network with Refined Features for Categorization of Motor Imaginary Signals
International Journal of Image and Graphics
Motor imaginary (MI) is an attractive research field in the brain–computer interfaces (BCIs) func... more Motor imaginary (MI) is an attractive research field in the brain–computer interfaces (BCIs) function, in which the system is directed by the imaginary arm movement of the subject. This attention is due to the monstrous potential for its pertinence in neurorestoration, neuroprosthetics, and gaming, where the client’s considerations of envisioned developments should be decoded. An electroencephalography (EEG) device is regularly utilized for monitoring frontal cortex movements in BCI frameworks. The EEG signals are perceived through the two fundamental processes such as feature extraction and characterization process. This research concentrates on developing a predominant MI categorization model utilizing deep learning techniques. The prominence of this research relies on the combined features + proposed PROA-based RideNN process known as holo-entropy-based WPD, which extracts the most dominant feature from the EEG signals. The extracted features enhance the performance of the RideNN...
An empirical survey of electroencephalography-based brain-computer interfaces
Bio-Algorithms and Med-Systems
Objectives The Electroencephalogram (EEG) signal is modified using the Motor Imagery (MI) and it ... more Objectives The Electroencephalogram (EEG) signal is modified using the Motor Imagery (MI) and it is utilized for patients with high motor impairments. Hence, the direct relationship between the computer and brain is termed as an EEG-based brain-computer interface (BCI). The objective of this survey is to presents an analysis of the existing distinct BCIs based on EEG. Methods This survey provides a detailed review of more than 60 research papers presenting the BCI-based EEG, like motor imagery-based techniques, spatial filtering-based techniques, Steady-State Visual Evoked Potential (SSVEP)-based techniques, machine learning-based techniques, Event-Related Potential (ERP)-based techniques, and online EEG-based techniques. Subsequently, the research gaps and issues of several EEG-based BCI systems are adopted to help the researchers for better future scope. Results An elaborative analyses as well as discussion have been provided by concerning the parameters, like evaluation metrics, ...
Review: Soot (Particulate Matter) Sensor with an application to control pollution in diesel exhaust
2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA)
Environmental awareness and stringent emission norms [BS-VI] made it necessary to achieve cleaner... more Environmental awareness and stringent emission norms [BS-VI] made it necessary to achieve cleaner exhaust gases from diesel engines. Additional systems are required to reduce harmful components. The performance of these systems depends on sensors and controls. Reducing emission like Hydrocarbon (HC), Oxides of carbon (Cox), Oxides of Nitrogen (Nox) & particulate matter (PM) in diesel engines will be one of the greatest development challenge in future. Exhaust after treatments systems (EATS) sensors are introduced in the exhaust systems to measure and control these emissions. Particulate matter (PM) is a major pollutant from the exhaust gas, which are ultra-fine particles of size less than 100nm. PM can penetrate to cell membranes, enter into the blood, and reach the brain causing serious health problems. Hence exact measurement and control of PM emission are imperative. Diesel particulate filter is an important component of EATS. Because of stringent emission norms for diesel engines especially for PM emission, diesel particulate filters are contributing vital role for exhaust gas after treatment systems. It requires very low [0.0125g/KM] PM emission monitoring for onboard diagnostic (OBD) of DPF malfunction detection. PM sensor detects soot mass and helps to control DPF clogging through an electronic control unit. This paper aims at a study of various PM sensing methods. The study emphasizes on its significance and improving the sensing parameters for PM detection as per BS-VI norms. Review of available methods for soot sensing helps to propose an optimized and accurate way of soot sensing.
Particle Rider Optimization-Driven Classification for Brain-Computer Interface
International Journal of Swarm Intelligence Research
The emerging technology for translating the intention of human into control signals is the Brain–... more The emerging technology for translating the intention of human into control signals is the Brain–computer interface (BCI). The BCI helps the patients with complete motor dysfunction to interact with the people. In this research, a method for abnormality assessment in humans from the perspective of the BCI was proposed by developing a hybrid optimization algorithm based on Electroencephalography (EEG). The hybrid optimization algorithm, called Particle Rider Optimization Algorithm (PROA) is designed through the incorporation of Particle Swarm Optimization (PSO) and Rider Optimization algorithm (ROA). The pre-processing is done for filtering the noise and removal of artefact. In pre-processing, the noise is removed through the Common Average Referencing (CAR) and Laplacian filters, whereas the artifacts are eliminated by Principle component analysis (PCA).
MEMS Interdigital Electrode Sensor Design for Gas sensing Mechanism
2021 International Conference on Emerging Smart Computing and Informatics (ESCI), 2021
Numerous technologies uses Interdigital electrode [IDE] capacitors as a key component for sensing... more Numerous technologies uses Interdigital electrode [IDE] capacitors as a key component for sensing mechanism. The present paper aims at studying significance of design parameters of IDE and variation in sensitivity with the variation of these parameters. Sensitivity of the capacitive sensor is evaluated using COMSOL, Q3D Multiphysics simulations. Reliable and simple IDE structure and fabrication process is proposed. Simulations show that width of sensing film is higher than $1/2$ of the wavelength of interdigital electrode structure. Sensitivity increases with width of film and its depth is enough which fills the gap between electrodes. IDE capacitive sensors are also known as planar capacitive sensors.
Fault resistant encryption system using high speed AES algorithm on FPGA
2017 International conference of Electronics, Communication and Aerospace Technology (ICECA), 2017
In confidential data transmission data security is an important factor. Advance Encryption Standa... more In confidential data transmission data security is an important factor. Advance Encryption Standard is symmetric cryptography standard used for confidential data transmission. However, some faults are injected during implementation of AES to reduce its reliability and may cause information leakage. Fault detection scheme includes the details of each transformation in AES algorithm. Simulation results shows outputs of encryption and decryption process and flag error shows the state of faults that is detected or not detected. After fault detection one operation is performed that is redundancy check. Detected error or fault is corrected using redundancy check. The scheme is implemented using FPGA platform
Microstrip Antennas used for Noninvasive Determination of Blood Glucose Level
2020 4th International Conference on Intelligent Computing and Control Systems (ICICCS), 2020
Noninvasive determination of biological parameters is a research challenge now a day. A suitable ... more Noninvasive determination of biological parameters is a research challenge now a day. A suitable noninvasive technique that measures blood glucose level (BGL) accurately without any side effect is not available till date. This paper presents possibility of measurement of BGL of human being noninvasively using Microwave Sensor. Various microstrip antenna structures like a spiral antenna, ultra-wideband antenna, and narrowband antenna are proposed as microwave sensors, and performance is measured in terms of return loss. Experimentation on each antenna is carried out to check the frequency response of antenna for various BGLs measured using the available invasive technique. BGL and microwave frequency relation is determined using these proposed antennas to a model noninvasive blood glucose meter. A comparative study of antennas is done.
Feature Extraction of Surface EMG Using Wavelet Transform for Identification of Motor Neuron Disorder
In the process of identification of motor neuron disorder, feature extraction is the most importa... more In the process of identification of motor neuron disorder, feature extraction is the most important and powerful method. Analysis of surface electromyography signal for the motor neuron muscle disorder identification using wavelet transform is most simple and powerful tool being used all over the world. Surface EMG signal of normal and MND patients for both male and female are considered. Various features are considered for analysis. KNN classifier has been used to classify the MND patients and normal person. Database of sEMG of various MND patients and normal person has been used from publically open source database. ALS is an amyotrophic lateral sclerosis which is a very fatal and rare disease related to Motor Neuron Disorder. It is a progressive degenerative motor neuron disorder.
Journal of emerging technologies and innovative research, 2018
Airway obstructive diseases like asthma, chronic obstructive pulmonary disease (COPD) and bronchi... more Airway obstructive diseases like asthma, chronic obstructive pulmonary disease (COPD) and bronchitis produces wheeze pattern in lung sounds. Due to changing lifestyles, pulmonary diseases are increasing day by day. The current methods of detecting diseases for example asthma involves usage of spirometers and stethoscope. The results with these techniques are not efficient or depend upon doctors’ experience. Accuracy of existing methods is depend on patient’s health. It is troublesome for heart patients and children. In such cases, need for automatic tools that can detect presence of wheeze present in lung sound is emerged. This paper gives long-term solution to existing problems. This paper also explains details about wheeze pattern in lung sounds. This paper involves the system for lung sound acquisition and real time pre-processing and detection of wheeze in lung sounds using DSP processor. The aim of the paper is to design and develop portable device for acquisition and detection...
Global journal of computer science and technology, 2017
Information security is an essential issue in communication system. Advance Encryption Standard (... more Information security is an essential issue in communication system. Advance Encryption Standard (AES) is utilized as a part of many embedded applications to give data security. Different counter measures are present in AES against fault injection attacks. Plain text and key of 128-bit is given as an input to the system and encryption and decryption operations are performed. Flag error shows the status of fault. Fault is produced randomly during encryption and decryption. For this reason, round transformation is broken into two sections and a pipeline stage is inserted in between. After fault detection one operation is performed that is redundancy check. Detected error or fault is corrected using redundancy check. The scheme is implemented using FPGA.
The Journal of medical research, 2017
In the process of identification of Amyotrophic Lateral Sclerosis (ALS) which is a motor neuron d... more In the process of identification of Amyotrophic Lateral Sclerosis (ALS) which is a motor neuron disorder, extraction of feature is the most important step. In this work normal and ALS class for identification and monitoring have been included. Analysis of surface electromyography (sEMG) signal for ALS identification using discrete wavelet transform is most simple and powerful method being used all over the world. Time domain parameters, like Zero Crossing Rate (ZCR) and Root Mean Square (RMS) and frequency domain parameters like Mean Frequency (MF) and Waveform Length (WL) are considered. Threshold values for the above mentioned parameters are calculated for both the normal and ALS classes. Discrete Wavelet Transform (DWT) parameters are considered and their threshold values are also calculated for both normal and ALS classes. Surface EMG (sEMG) signal database of normal and ALS patients for both male and female is considered.
International Journal of Advanced engineering, Management and Science, 2016
Due to new developed technology man is leading a comfortable life. People want each work should b... more Due to new developed technology man is leading a comfortable life. People want each work should be done automatically. So in this paper introduces a system called UNMANNED GROUND VEHICLE. UGV as name indicate it operates in contact with ground and without any human resource. The vehicle will have a set of sensors to observe the environment. In this paper for the working of UGV, FPGA is embedded with image processing. FPGA as main processing platform used to control UGV. The performance evaluation of proposed system takes place by capturing the image of UGV with help of camera. This system demonstrate accurate localization of UGV. This UGV vehicle used in military, mall, automobile industry. To work system properly provide proper interfacing and synchronization between hardware/software module.
Eye-Blink artifact Detection and Removal Approaches for BCI using EEG
2021 International Conference on Recent Trends on Electronics, Information, Communication & Technology (RTEICT), 2021
Electroencephalography (EEG) has been widely used in the development of a BCI system that can tra... more Electroencephalography (EEG) has been widely used in the development of a BCI system that can translate and decode user goals without clinical procedures. Unfortunately, because of volume conduction, the spatial resolution of the multichannel electroencephalogram (EEG) is poor. The signals from various areas of the head are recorded by each EEG electrode. There are various artifacts like ECG, EMG, and eye movement artifacts present in the EEG. MI-based Brain-Computer Interface (BCI) helps motor impaired persons to connect to the outside world by carrying out a set of motor functions. The BCI system commonly includes pre-processing of raw brain signals, extraction of significant features and classification. Pre-processing plays an important role in the performance of the BCI system. In this paper, three preprocessing methods namely Band pass filtering, Common average referencing and Surface Laplacian are effectively implemented to reduce the various artifacts present in EEG signal thereby improving the performance of the BCI system.
Non-invasive determination of blood glucose level using narrowband microwave sensor
Journal of Ambient Intelligence and Humanized Computing, 2021
Automatic Wheeze Detection in Lung Sounds
International Journal of Computer Sciences and Engineering, 2018
Intelligent car parking system
2016 International Conference on Inventive Computation Technologies (ICICT), 2016
Localization is a key issue of the navigation system to guide unmanned ground vehicle in an intel... more Localization is a key issue of the navigation system to guide unmanned ground vehicle in an intelligent Space. Intelligent Space is an environmental system. This intelligent Space able to support informative and physical ways. The proposed system includes sensors information fusion, position estimation, path planning and tracking. Camera is used to get image information of the robot. Image processing and FPGA embedded together to identify position and orientation of UGV very correctly and accurately. The proposed architecture works on distributed image processing pixels which causes the amount of data to be transmitted through communication network will be minimum. This causes a reasonable, very efficient solution, simple, adaptable. The hardware/software localization setup described in this paper is cheap and easy to use and may provide support in several industrial and domestic sceneries.
International Journal of Emerging Technology and Advanced Engineering
Noninvasive estimation of blood glucose using microwave based sensor is one of the most challengi... more Noninvasive estimation of blood glucose using microwave based sensor is one of the most challenging research fields in recent days. These methods are more adaptable to avoid soreness and skin estrangement that occur in traditional invasive blood glucose measurement techniques. This paper suggests the investigational outcomes of a microwave based noninvasive blood glucose meter to check performance of the microwave antenna sensor. Narrowband micro strip antenna with resonating microwave frequency of 1.3 GHz is utilized to measure Blood Glucose Level (BGL) noninvasively. Validity of sensor is assessed by performing medical tests on non diabetic and diabetic human volunteers. Mean Absolute Relative Difference (MARD) and Surveillance Error Grid (SEG) analyses were performed during experimentation to find deviation of estimated BGL from reference BGL which is measured using available invasive technique. Direct assessment of estimated data with reference data provides excellent reliability and repeatability of proposed microwave technique.
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Papers by suvarna chorage