shital Raut | Vishwakarma Institute of Technology, Pune (original) (raw)

Papers by shital Raut

Indian Scientific Journal Of Research In Engineering And Management, Apr 4, 2024

The objective of this research is to develop a Deep Learning model to forecast the stock price, b... more The objective of this research is to develop a Deep Learning model to forecast the stock price, by using the variant of Long Short-Term Memory. This model predicts the close price of the stock for the future selected date, choosing as inputs the following data: open, high, low, adj close and close prices. This model shows a comparative analysis between three different LSTM networks: Long Short-Term Memory (LSTM), Stacked Long Short-Term Memory (Stacked LSTM), and Stacked Bi-directional Long Short-Term Memory (Stacked Bidirectional LSTM) concluding which one is the best and implementing the model using that variant. We have used the historical stock prices data from yahoo's financial website over 5 years, by choosing multiple datasets: Apple, Amazon, Google, Meta, Microsoft and Tesla (daily values). In order to get effective in the forecasting model, we have tested the network with different iterations and epochs. The model represents Multiple Graphs for data visualization in different comparisons. We have estimated the effectiveness of our proposed model by using the following performance indicators: the Mean Square Error (MSE), the Root Mean Square Error (RMSE), and the R-Squared of the model. The experimental results clearly show that our Stacked Bi-LSTM model has the highest accuracy values when comparing with the LSTM and Stacked LSTM Models. Hence, we can conclude that our Stacked Bi-LSTM Model is suitable for accurate prediction of the stock market time series.

International Journal for Research in Applied Science and Engineering Technology, Dec 31, 2022

This paper presents a real-time driver drowsiness detection system for driving safety. Supported ... more This paper presents a real-time driver drowsiness detection system for driving safety. Supported computer vision techniques, the driver's face is found from color video captured in an exceedingly car. Then, face detection is used to locate the regions of the driver's eyes, which are used because the templates for eye tracking in subsequently frames. Finally, the tracked eye's images are used for drowsiness detection so as to come up with waring alarms. The proposed approach has three phases: Face, Eye detection and drowsiness detection The role of image processing is to acknowledge the face of the driving force then extracts the image of the eyes of the driving force for detection of drowsiness. The HAAR face detection algorithm takes captured frames of image as input and so the detected face as output. Next, CHT is employed to tracking eyes from the detected face. If the eyes are closed for a predefined period of your time the eyes of the motive force are considered closed and hence an alarm are beginning to alert the driving force.

International Journal for Research in Applied Science and Engineering Technology

For ages humans have travelled to different places in the world and have required luggage for sup... more For ages humans have travelled to different places in the world and have required luggage for supplies of goods and other things. To make the travel experience of people better day by day new technologies are coming up. Going back to luggage being made of leather and stuff to now luggage's being smart luggage, technology is growing adversely. In this paper we would be talking about the smart luggage system in which we would be aiming to solve difficulties faced by people while carrying luggage.

International Journal for Research in Applied Science and Engineering Technology

The use of mobile devices can easily divert a driver's attention away from the road. Dangerous dr... more The use of mobile devices can easily divert a driver's attention away from the road. Dangerous driving, such as texting and driving, can cause havoc in traffic and jeopardize safety. The goal of this project is to develop an accident-avoidance system that can detect the presence of a mobile phone in the driver's hand by installing an in-car camera facing the driver and running a YOLOv3-Tiny algorithm for mobile phone detection. In addition, the model will issue an audio alert to the driver and use face detection algorithms to determine the driver's identity. Twilio APIs are being used to send live messages to car owners about the actions taken using the car's location information.

Wireless Personal Communications, 2021

Recent mobile telecommunication systems are using multiple-input multiple-output system (MIMO) co... more Recent mobile telecommunication systems are using multiple-input multiple-output system (MIMO) collective with the orthogonal frequency division multiplexing (OFDM), which is well-known as MIMO-OFDM, to offer robustness and higher spectrum efficiency. The most important challenge in this scenario is to achieve an accurate channel estimation to identify the information symbols once the receiver must have the channel state information to balance and process the received signal. Hence, an effective technique is introduced by proposing the Taylor-least square error algorithm (TLSE) to improve the performance of the MIMO-OFDM system in multimedia applications. In addition, the user admission control is done in multi user-MIMO (MU-MIMO) system using the priority-based scheduling based on Dolphin-rider optimization (DRO) algorithm that is integrated within the space–time block code (STBC) STBC-MIMO-OFDM system for efficient power allocation to ensure the energy efficiency. The DRO is the integration of rider optimization algorithm (ROA) and Dolphin Echolocation (DE). Here, channel estimation is done using the novel optimization algorithm, termed TLSE, which is designed by modifying LSE with the Taylor series. Moreover, the fitness parameters, such as power, priority, throughput, and Proportionally Fair, are computed. The experimentation is conducted in different fading environments with three modulation schemes, binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), and quadrature amplitude modulation (QAM) with the performance metrics, namely bit error rate (BER) and throughput. The developed TLSE + DRO (QAM) outperformed other methods with minimal BER of 0.0001 based on channel-2 and maximal throughput of 0.9965 with respect to channel-1.

International Journal of Advanced Research in Science, Communication and Technology, 2021

This paper aims to develop an innovative neural network approach to achieve better stock market p... more This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysis. To study the influence of market characteristics on stock prices, traditional neural network algorithms may incorrectly predict the stock market, since the initial weight of the random selection problem can be easily prone to incorrect predictions. Based on the development of word vector in deep learning, we demonstrate the concept of “stock vector.” The input is no longer a single index or single stock index, but multi-stock high-dimensional historical data. We propose the deep long short-term memory neural network (LSTM) with embedded layer and the long short-term memory neural network with automatic encoder to predict the stock market. In these two models, we use the embedded layer ...

IET Communications, 2019

Resource allocation in wireless communication systems is of great concern in order to guarantee t... more Resource allocation in wireless communication systems is of great concern in order to guarantee the efficient utilisation of scary resources. In space-time block codes-based multiple-input multiple-output with orthogonal frequency division multiplexing (STBC-MIMO-OFDM) system, scheduling the appropriate user to the available antenna is the major challenge. To overcome the challenge, this study proposes a priority-based scheduling mechanism using the hybrid optimisation, Dolphin-Rider Optimisation (DRO), which is a combination of Dolphin Echolocation Algorithm and Rider Optimisation Algorithm. The prioritisation follows the power and quality of service constraints of the users in such a way that the energy efficiency is enabled in the system. The performance of the system is analysed using the Rayleigh and Rician channels with the transmission media as, text, audio, and image. Moreover, the comparative analysis of the proposed DRO is enabled using three modulation schemes, Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying, and quadrature amplitude modulation. The proposed user scheduling mechanism with the BPSK modulation is found to be effective with a minimal bit error rate and maximal throughput of 3.78×10 −7 and 0.875.

International Journal of Innovative Technology and Exploring Engineering, 2020

The proposed system includes smart helmet where in the IR sensor is enabled only when the helmet ... more The proposed system includes smart helmet where in the IR sensor is enabled only when the helmet is put on. This system also incorporates other features like GPS and Accelerometer. Such features serve as the rider aids. The IOT techniques has added in this systems to monitor a vehicle of the respective people and has used to send the message if any changes occurred in the above parameters

International Journal of Electrical and Computer Engineering (IJECE), 2017

The consistent demand for higher data rates and need to send giant volumes of data while not comp... more The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environmen...

International Journal of Electrical and Computer Engineering (IJECE), 2017

The consistent demand for higher data rates and need to send giant volumes of data while not comp... more The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environment e.g. Rayleigh fading, Rician fading, Nakagami fading, composite fading.

Indian Scientific Journal Of Research In Engineering And Management, Apr 4, 2024

The objective of this research is to develop a Deep Learning model to forecast the stock price, b... more The objective of this research is to develop a Deep Learning model to forecast the stock price, by using the variant of Long Short-Term Memory. This model predicts the close price of the stock for the future selected date, choosing as inputs the following data: open, high, low, adj close and close prices. This model shows a comparative analysis between three different LSTM networks: Long Short-Term Memory (LSTM), Stacked Long Short-Term Memory (Stacked LSTM), and Stacked Bi-directional Long Short-Term Memory (Stacked Bidirectional LSTM) concluding which one is the best and implementing the model using that variant. We have used the historical stock prices data from yahoo's financial website over 5 years, by choosing multiple datasets: Apple, Amazon, Google, Meta, Microsoft and Tesla (daily values). In order to get effective in the forecasting model, we have tested the network with different iterations and epochs. The model represents Multiple Graphs for data visualization in different comparisons. We have estimated the effectiveness of our proposed model by using the following performance indicators: the Mean Square Error (MSE), the Root Mean Square Error (RMSE), and the R-Squared of the model. The experimental results clearly show that our Stacked Bi-LSTM model has the highest accuracy values when comparing with the LSTM and Stacked LSTM Models. Hence, we can conclude that our Stacked Bi-LSTM Model is suitable for accurate prediction of the stock market time series.

International Journal for Research in Applied Science and Engineering Technology, Dec 31, 2022

This paper presents a real-time driver drowsiness detection system for driving safety. Supported ... more This paper presents a real-time driver drowsiness detection system for driving safety. Supported computer vision techniques, the driver's face is found from color video captured in an exceedingly car. Then, face detection is used to locate the regions of the driver's eyes, which are used because the templates for eye tracking in subsequently frames. Finally, the tracked eye's images are used for drowsiness detection so as to come up with waring alarms. The proposed approach has three phases: Face, Eye detection and drowsiness detection The role of image processing is to acknowledge the face of the driving force then extracts the image of the eyes of the driving force for detection of drowsiness. The HAAR face detection algorithm takes captured frames of image as input and so the detected face as output. Next, CHT is employed to tracking eyes from the detected face. If the eyes are closed for a predefined period of your time the eyes of the motive force are considered closed and hence an alarm are beginning to alert the driving force.

International Journal for Research in Applied Science and Engineering Technology

For ages humans have travelled to different places in the world and have required luggage for sup... more For ages humans have travelled to different places in the world and have required luggage for supplies of goods and other things. To make the travel experience of people better day by day new technologies are coming up. Going back to luggage being made of leather and stuff to now luggage's being smart luggage, technology is growing adversely. In this paper we would be talking about the smart luggage system in which we would be aiming to solve difficulties faced by people while carrying luggage.

International Journal for Research in Applied Science and Engineering Technology

The use of mobile devices can easily divert a driver's attention away from the road. Dangerous dr... more The use of mobile devices can easily divert a driver's attention away from the road. Dangerous driving, such as texting and driving, can cause havoc in traffic and jeopardize safety. The goal of this project is to develop an accident-avoidance system that can detect the presence of a mobile phone in the driver's hand by installing an in-car camera facing the driver and running a YOLOv3-Tiny algorithm for mobile phone detection. In addition, the model will issue an audio alert to the driver and use face detection algorithms to determine the driver's identity. Twilio APIs are being used to send live messages to car owners about the actions taken using the car's location information.

Wireless Personal Communications, 2021

Recent mobile telecommunication systems are using multiple-input multiple-output system (MIMO) co... more Recent mobile telecommunication systems are using multiple-input multiple-output system (MIMO) collective with the orthogonal frequency division multiplexing (OFDM), which is well-known as MIMO-OFDM, to offer robustness and higher spectrum efficiency. The most important challenge in this scenario is to achieve an accurate channel estimation to identify the information symbols once the receiver must have the channel state information to balance and process the received signal. Hence, an effective technique is introduced by proposing the Taylor-least square error algorithm (TLSE) to improve the performance of the MIMO-OFDM system in multimedia applications. In addition, the user admission control is done in multi user-MIMO (MU-MIMO) system using the priority-based scheduling based on Dolphin-rider optimization (DRO) algorithm that is integrated within the space–time block code (STBC) STBC-MIMO-OFDM system for efficient power allocation to ensure the energy efficiency. The DRO is the integration of rider optimization algorithm (ROA) and Dolphin Echolocation (DE). Here, channel estimation is done using the novel optimization algorithm, termed TLSE, which is designed by modifying LSE with the Taylor series. Moreover, the fitness parameters, such as power, priority, throughput, and Proportionally Fair, are computed. The experimentation is conducted in different fading environments with three modulation schemes, binary phase shift keying (BPSK), quadrature phase shift keying (QPSK), and quadrature amplitude modulation (QAM) with the performance metrics, namely bit error rate (BER) and throughput. The developed TLSE + DRO (QAM) outperformed other methods with minimal BER of 0.0001 based on channel-2 and maximal throughput of 0.9965 with respect to channel-1.

International Journal of Advanced Research in Science, Communication and Technology, 2021

This paper aims to develop an innovative neural network approach to achieve better stock market p... more This paper aims to develop an innovative neural network approach to achieve better stock market predictions. Data were obtained from the live stock market for real-time and off-line analysis and results of visualizations and analytics to demonstrate Internet of Multimedia of Things for stock analysis. To study the influence of market characteristics on stock prices, traditional neural network algorithms may incorrectly predict the stock market, since the initial weight of the random selection problem can be easily prone to incorrect predictions. Based on the development of word vector in deep learning, we demonstrate the concept of “stock vector.” The input is no longer a single index or single stock index, but multi-stock high-dimensional historical data. We propose the deep long short-term memory neural network (LSTM) with embedded layer and the long short-term memory neural network with automatic encoder to predict the stock market. In these two models, we use the embedded layer ...

IET Communications, 2019

Resource allocation in wireless communication systems is of great concern in order to guarantee t... more Resource allocation in wireless communication systems is of great concern in order to guarantee the efficient utilisation of scary resources. In space-time block codes-based multiple-input multiple-output with orthogonal frequency division multiplexing (STBC-MIMO-OFDM) system, scheduling the appropriate user to the available antenna is the major challenge. To overcome the challenge, this study proposes a priority-based scheduling mechanism using the hybrid optimisation, Dolphin-Rider Optimisation (DRO), which is a combination of Dolphin Echolocation Algorithm and Rider Optimisation Algorithm. The prioritisation follows the power and quality of service constraints of the users in such a way that the energy efficiency is enabled in the system. The performance of the system is analysed using the Rayleigh and Rician channels with the transmission media as, text, audio, and image. Moreover, the comparative analysis of the proposed DRO is enabled using three modulation schemes, Binary Phase Shift Keying (BPSK), Quadrature Phase Shift Keying, and quadrature amplitude modulation. The proposed user scheduling mechanism with the BPSK modulation is found to be effective with a minimal bit error rate and maximal throughput of 3.78×10 −7 and 0.875.

International Journal of Innovative Technology and Exploring Engineering, 2020

The proposed system includes smart helmet where in the IR sensor is enabled only when the helmet ... more The proposed system includes smart helmet where in the IR sensor is enabled only when the helmet is put on. This system also incorporates other features like GPS and Accelerometer. Such features serve as the rider aids. The IOT techniques has added in this systems to monitor a vehicle of the respective people and has used to send the message if any changes occurred in the above parameters

International Journal of Electrical and Computer Engineering (IJECE), 2017

The consistent demand for higher data rates and need to send giant volumes of data while not comp... more The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environmen...

International Journal of Electrical and Computer Engineering (IJECE), 2017

The consistent demand for higher data rates and need to send giant volumes of data while not comp... more The consistent demand for higher data rates and need to send giant volumes of data while not compromising the quality of communication has led the development of a new generations of wireless systems. But range and data rate limitations are there in wireless devices. In an attempt to beat these limitations, Multi Input Multi Output (MIMO) systems will be used which also increase diversity and improve the bit error rate (BER) performance of wireless systems. They additionally increase the channel capacity, increase the transmitted data rate through spatial multiplexing, and/or reduce interference from other users. MIMO systems therefore create a promising communication system because of their high transmission rates without additional bandwidth or transmit power and robustness against multipath fading. This paper provides the overview of Multiuser MIMO system. A detailed review on how to increase performance of system and reduce the bit error rate (BER) in different fading environment e.g. Rayleigh fading, Rician fading, Nakagami fading, composite fading.