Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151351
Mayank Dutta, Fakhra Najm, Dhruv Tomar, S. Mehfuz
The Smart Queuing Management System (SQMS) proposed in this paper aims to improve the efficiency of the patient appointment process in healthcare facilities by optimizing the organization of patients based on their age, appointment time, and severity of their disease. This system uses a scoring mechanism that considers the importance of these factors and assigns a score to each patient. The scoring mechanism ensures that patients with higher priority are given a higher score, and therefore are placed at the top of the queue. To ensure fairness in the queue, the system also incorporates a Tribonacci series for incrementing the score of late patients. This mechanism ensures that patients who have been waiting for longer periods of time are given priority over those who have just arrived, while also preventing the queue from becoming too unbalanced. The proposed system has several benefits for healthcare facilities, including better organization of patients, reduced wait times, and improved healthcare outcomes. By prioritizing patients based on their age, appointment time, and severity of their disease, the system ensures that patients with more urgent medical needs receive prompt attention. This can lead to better healthcare outcomes, as patients receive the care they need in a timely manner.
{"title":"Smart Queueing Management System for Digital Healthcare","authors":"Mayank Dutta, Fakhra Najm, Dhruv Tomar, S. Mehfuz","doi":"10.1109/REEDCON57544.2023.10151351","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151351","url":null,"abstract":"The Smart Queuing Management System (SQMS) proposed in this paper aims to improve the efficiency of the patient appointment process in healthcare facilities by optimizing the organization of patients based on their age, appointment time, and severity of their disease. This system uses a scoring mechanism that considers the importance of these factors and assigns a score to each patient. The scoring mechanism ensures that patients with higher priority are given a higher score, and therefore are placed at the top of the queue. To ensure fairness in the queue, the system also incorporates a Tribonacci series for incrementing the score of late patients. This mechanism ensures that patients who have been waiting for longer periods of time are given priority over those who have just arrived, while also preventing the queue from becoming too unbalanced. The proposed system has several benefits for healthcare facilities, including better organization of patients, reduced wait times, and improved healthcare outcomes. By prioritizing patients based on their age, appointment time, and severity of their disease, the system ensures that patients with more urgent medical needs receive prompt attention. This can lead to better healthcare outcomes, as patients receive the care they need in a timely manner.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117295651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151319
Rohit Gupta, Amit Bhongade, T. Gandhi
The state of art Brain-computer interface (BCI) utilized discrete or model-based control strategies for external device control. However, for efficient and seamless control a continuous control strategy is required. In order to achieve this continuous estimation of control parameters is required with minimum delay. It will improve the performance as well as acceptability of the mind-controlled prosthesis, exoskeleton and robotic arm among the uses. In this research paper, an attempt had been made to estimate the human hand trajectory in 3D space using multichannel electroencephalogram (EEG) signals. The proposed model utilized a time-delayed multi-input multi-out neural network to estimate the trajectories in a continuous manner. The developed model is well suited for control applications as it generates a high-density of estimated trajectory stream. The developed model has been tested over the dataset of 12 subjects for different frequency ranges/bands of EEG signal. The developed model shows the best estimation accuracy as 0.638±0.030 and consistency of estimation as 0.654±0.030, if the entire frequency range of the EEG signal has been utilized. The developed model depicted better performance if utilized for trajectory estimation in 2D space rather than 3D space. The developed model can be directly utilized for planer robot control or any upper limb assistive and rehabilitative device with 2DoF.
{"title":"Hand 3D Trajectory Estimation for BCI Application","authors":"Rohit Gupta, Amit Bhongade, T. Gandhi","doi":"10.1109/REEDCON57544.2023.10151319","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151319","url":null,"abstract":"The state of art Brain-computer interface (BCI) utilized discrete or model-based control strategies for external device control. However, for efficient and seamless control a continuous control strategy is required. In order to achieve this continuous estimation of control parameters is required with minimum delay. It will improve the performance as well as acceptability of the mind-controlled prosthesis, exoskeleton and robotic arm among the uses. In this research paper, an attempt had been made to estimate the human hand trajectory in 3D space using multichannel electroencephalogram (EEG) signals. The proposed model utilized a time-delayed multi-input multi-out neural network to estimate the trajectories in a continuous manner. The developed model is well suited for control applications as it generates a high-density of estimated trajectory stream. The developed model has been tested over the dataset of 12 subjects for different frequency ranges/bands of EEG signal. The developed model shows the best estimation accuracy as 0.638±0.030 and consistency of estimation as 0.654±0.030, if the entire frequency range of the EEG signal has been utilized. The developed model depicted better performance if utilized for trajectory estimation in 2D space rather than 3D space. The developed model can be directly utilized for planer robot control or any upper limb assistive and rehabilitative device with 2DoF.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116166608","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151213
Shagufta Khan, Md. Tausif Ahmad, Shashi Ranjan, Nadeem Sarwar
This paper deals with the interconnection of three AC systems via High voltage DC links. Both synchronous and asynchronous connections of the AC systems are considered. Neutral point diode clamped (NPC) based VSC HVDC system is considered for analysis. NPC based VSC HVDC provides three level DC voltages as VDC / 2, - VDC / 2 and 0. It reduce total switches connected in series. Due to this, harmonics are also reduced comparatively to two level converters. DC voltage and reactive power control mode is selected for both inverters. Real and imaginary power flows are controlled at rectifier end. The interconnected system is analyzed under three phase fault. The AC faults occurs at the end of inverter-1 (connected to AC system-2). The behavior of AC currents, AC voltages, active and reactive powers and DC voltages are studied in case of AC faults. All results are performed in MATLAB Simulink environment.
{"title":"AC Fault Analysis on NPC based Multi-terminal Hybrid AC-DC system","authors":"Shagufta Khan, Md. Tausif Ahmad, Shashi Ranjan, Nadeem Sarwar","doi":"10.1109/REEDCON57544.2023.10151213","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151213","url":null,"abstract":"This paper deals with the interconnection of three AC systems via High voltage DC links. Both synchronous and asynchronous connections of the AC systems are considered. Neutral point diode clamped (NPC) based VSC HVDC system is considered for analysis. NPC based VSC HVDC provides three level DC voltages as VDC / 2, - VDC / 2 and 0. It reduce total switches connected in series. Due to this, harmonics are also reduced comparatively to two level converters. DC voltage and reactive power control mode is selected for both inverters. Real and imaginary power flows are controlled at rectifier end. The interconnected system is analyzed under three phase fault. The AC faults occurs at the end of inverter-1 (connected to AC system-2). The behavior of AC currents, AC voltages, active and reactive powers and DC voltages are studied in case of AC faults. All results are performed in MATLAB Simulink environment.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114697170","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10150603
S. Sarkar, P. Swati Patro, P. Kundu, Lakshay Singh, Gunja Gupta, Yangchen Lhamu Bhutia
Grid connected solarised homes are becoming very popular in the recent times and Government of India (GoI) is giving emphasis to increase the photo-voltaic (PV) generation in order to reduce the dependency on the conventional energy sources. But due to the unpredictable nature of the solar PV generation connected to the distribution system, forecasting of load becoming difficult for the local utilities. Energy management systems (EMS) can be very useful for such grid-connected solarised homes so as to utilize green energy consumption locally when the utility power balance is already maintained. Such a system can also be useful to reduce the energy requirements throughout the day and thereby having monetary benefits as well. In order to realize such an EMS, development of a suitable DAS is a must. An attempt is made in this paper to realize a cloud based DAS for acquiring data from different sensors and store the information in the cloud based on which switching of different relays can be performed. The work will be extended further to develop the utility assisting EMS suitable for grid-connected solarised homes. Furthermore, there are several future scopes of this work in different applications.
{"title":"Realisation of a cloud based Data Acquisition System (DAS) for grid connected solarised homes","authors":"S. Sarkar, P. Swati Patro, P. Kundu, Lakshay Singh, Gunja Gupta, Yangchen Lhamu Bhutia","doi":"10.1109/REEDCON57544.2023.10150603","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10150603","url":null,"abstract":"Grid connected solarised homes are becoming very popular in the recent times and Government of India (GoI) is giving emphasis to increase the photo-voltaic (PV) generation in order to reduce the dependency on the conventional energy sources. But due to the unpredictable nature of the solar PV generation connected to the distribution system, forecasting of load becoming difficult for the local utilities. Energy management systems (EMS) can be very useful for such grid-connected solarised homes so as to utilize green energy consumption locally when the utility power balance is already maintained. Such a system can also be useful to reduce the energy requirements throughout the day and thereby having monetary benefits as well. In order to realize such an EMS, development of a suitable DAS is a must. An attempt is made in this paper to realize a cloud based DAS for acquiring data from different sensors and store the information in the cloud based on which switching of different relays can be performed. The work will be extended further to develop the utility assisting EMS suitable for grid-connected solarised homes. Furthermore, there are several future scopes of this work in different applications.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124886368","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10150439
Faiyaz Ahmad, Mohd Tarik, Musheer Ahmad, M. Z. Ansari
Weather forecasting aims to predict atmospheric conditions at a particular time and place. Timely alert of weather events is made possible through weather forecasting. For instance, accurate weather predictions enable us to offer early warning of natural disasters that significantly destroy both lives and property, such as cyclones, tsunamis, cloud bursts, etc. The aim of weather scientists has always been to provide accurate weather forecasts in a timely manner. Formerly, pattern recognition was frequently used for weather forecasting and all of such predictions have been lacking performance as far as accurate and precise forecasting is concern. As the conventional weather prediction techniques face a number of difficulties, such as: incomplete knowledge of physical processes, huge volumes of observational data are difficult to analyze, a need for strong computer resources, etc. To tackle these difficulties, this paper proposes to present an automatic weather forecasting model for short-range forecasting based on numerical and time series data using deep learning algorithms. This paper compares and assesses the performance of models created with various transfer functions in order to investigate the applicability of time series algorithms such as LSTM, GRU, and Bi-LSTM to develop an efficient and trustworthy nonlinear forecasting model for automatic weather analysis.
{"title":"Weather Forecasting Using Deep Learning Algorithms","authors":"Faiyaz Ahmad, Mohd Tarik, Musheer Ahmad, M. Z. Ansari","doi":"10.1109/REEDCON57544.2023.10150439","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10150439","url":null,"abstract":"Weather forecasting aims to predict atmospheric conditions at a particular time and place. Timely alert of weather events is made possible through weather forecasting. For instance, accurate weather predictions enable us to offer early warning of natural disasters that significantly destroy both lives and property, such as cyclones, tsunamis, cloud bursts, etc. The aim of weather scientists has always been to provide accurate weather forecasts in a timely manner. Formerly, pattern recognition was frequently used for weather forecasting and all of such predictions have been lacking performance as far as accurate and precise forecasting is concern. As the conventional weather prediction techniques face a number of difficulties, such as: incomplete knowledge of physical processes, huge volumes of observational data are difficult to analyze, a need for strong computer resources, etc. To tackle these difficulties, this paper proposes to present an automatic weather forecasting model for short-range forecasting based on numerical and time series data using deep learning algorithms. This paper compares and assesses the performance of models created with various transfer functions in order to investigate the applicability of time series algorithms such as LSTM, GRU, and Bi-LSTM to develop an efficient and trustworthy nonlinear forecasting model for automatic weather analysis.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"114 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124149770","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10150687
Anam Suri, S. Jabin, Munna Khan, Kashif I. K. Sherwani, M. Sardar, Mohammad Monis Khan
Brain-computer interface (BCI) is a well-established technology that facilitates the communication between a user and an external device solely based on brain activity, bridging users' intentions from a variety of human brain signals, including EEG (Electroencephalogram), fNIRS (functional near-infrared spectroscopy), and DTI (diffusion tensor imaging). Out of these, EEG, a technique to record electrical brain activities using a noninvasive electrophysiological method that measures voltage fluctuations induced by the ionic current within brain neurons, is the most commonly applied method. With no clinical risk, EEG data can be recorded using affordable acquisition equipment and is highly portable. Among the various paradigms of EEG, Motor Imagery (MI) has garnered a lot of recognition in the last ten years. Owing to its potential, several ground-breaking research transforming human life have been conducted resulting in world-class BCI products. In this paper, we provide a comprehensive overview of the various EEG-based MI-BCI classification trends and challenges with a particular emphasis on deep learning approaches.
{"title":"Recent trends and Indications in the field of Motor Imagery: a Brain-computer interface paradigm","authors":"Anam Suri, S. Jabin, Munna Khan, Kashif I. K. Sherwani, M. Sardar, Mohammad Monis Khan","doi":"10.1109/REEDCON57544.2023.10150687","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10150687","url":null,"abstract":"Brain-computer interface (BCI) is a well-established technology that facilitates the communication between a user and an external device solely based on brain activity, bridging users' intentions from a variety of human brain signals, including EEG (Electroencephalogram), fNIRS (functional near-infrared spectroscopy), and DTI (diffusion tensor imaging). Out of these, EEG, a technique to record electrical brain activities using a noninvasive electrophysiological method that measures voltage fluctuations induced by the ionic current within brain neurons, is the most commonly applied method. With no clinical risk, EEG data can be recorded using affordable acquisition equipment and is highly portable. Among the various paradigms of EEG, Motor Imagery (MI) has garnered a lot of recognition in the last ten years. Owing to its potential, several ground-breaking research transforming human life have been conducted resulting in world-class BCI products. In this paper, we provide a comprehensive overview of the various EEG-based MI-BCI classification trends and challenges with a particular emphasis on deep learning approaches.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123229499","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151152
Krishna D Jadhav
The World-Wide-Web has become one of the major aspects of everyone’s existence around the globe practically. In this day and age where internet is incorporated in everyone’s lives, it is undoubtedly challenging to carry out today’s tasks without its utilization. In addition to this, the arrival of the global pandemic has significantly improved the priorities of the Internet in the times of unexpected unprecedented times of disaster.
{"title":"Impact of Web 3.0 on Blockchain Technology","authors":"Krishna D Jadhav","doi":"10.1109/REEDCON57544.2023.10151152","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151152","url":null,"abstract":"The World-Wide-Web has become one of the major aspects of everyone’s existence around the globe practically. In this day and age where internet is incorporated in everyone’s lives, it is undoubtedly challenging to carry out today’s tasks without its utilization. In addition to this, the arrival of the global pandemic has significantly improved the priorities of the Internet in the times of unexpected unprecedented times of disaster.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131422797","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151436
Arbab Ahmed Khan, A. Siddiqui, Shahid Geelani, M. Sarwar, Syed Mashood Shafi
Energy conservation is an important matter as resources are decreasing at an alarming rate and this would create a lot of problems for the next generations. To overcome from this issue, a proper energy saving method and automatic lighting control needs to be implemented. This work proposes a model for modifying Street lights illumination using sensors at minimum electrical consumption as well as elimination of manual operation. In this work the LED lights are used as streetlights, LDR sensor is used for detecting light intensity for differentiating between daytime and night-time and IR sensors are used to sense vehicle movements. If presence is not detected, all nearby streetlights remain in the dim mode, which is 30% intensity for pedestrians, and only illuminate at 100% intensity when presence is detected. LED bulbs shall be used as they are better than conventional incandescent bulbs in every way. The intensity of LED can be controlled using PWM techniques. Through this proposed System the overall energy being utilized now-a-days for lighting is minimized. The automatic control of lighting is required to control the complex lighting system due to growth of cities and the standard of living.
{"title":"Smart Street Lighting System Based on Detecting Vehicle Movement","authors":"Arbab Ahmed Khan, A. Siddiqui, Shahid Geelani, M. Sarwar, Syed Mashood Shafi","doi":"10.1109/REEDCON57544.2023.10151436","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151436","url":null,"abstract":"Energy conservation is an important matter as resources are decreasing at an alarming rate and this would create a lot of problems for the next generations. To overcome from this issue, a proper energy saving method and automatic lighting control needs to be implemented. This work proposes a model for modifying Street lights illumination using sensors at minimum electrical consumption as well as elimination of manual operation. In this work the LED lights are used as streetlights, LDR sensor is used for detecting light intensity for differentiating between daytime and night-time and IR sensors are used to sense vehicle movements. If presence is not detected, all nearby streetlights remain in the dim mode, which is 30% intensity for pedestrians, and only illuminate at 100% intensity when presence is detected. LED bulbs shall be used as they are better than conventional incandescent bulbs in every way. The intensity of LED can be controlled using PWM techniques. Through this proposed System the overall energy being utilized now-a-days for lighting is minimized. The automatic control of lighting is required to control the complex lighting system due to growth of cities and the standard of living.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"43 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126407082","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151372
Ehtesham Sana, N. Akhtar
Multi-document summarization has been a challenging task due to the difficulties in capturing essential information from multiple sources and generating coherent and non-redundant summaries. In this proposed model, we address these challenges by leveraging the power of two popular natural language processing techniques, Bidirectional Encoder Representations from Transformers (BERT) and Gated Recurrent Unit (GRU). The Document Understanding Conference (DUC) dataset, a widely recognized benchmark dataset for multi-document summarization, was used to train and evaluate the model. By using BERT to generate contextual embeddings and GRU to capture sequence information, the proposed method outperforms previous methods in terms of summarization quality metrics such as ROUGE (RecallOriented Understudy for Gisting Evaluation). The proposed model has significant potential for use in various applications, such as news summarization, document summarization, and automated content creation. This study demonstrates that combining BERT and GRU models can effectively capture the contextual and sequential information in multi-document summarization, leading to high-quality summaries that overcome the limitations of previous methods.
{"title":"Improving Multi-Document Summarization with GRU-BERT Network","authors":"Ehtesham Sana, N. Akhtar","doi":"10.1109/REEDCON57544.2023.10151372","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151372","url":null,"abstract":"Multi-document summarization has been a challenging task due to the difficulties in capturing essential information from multiple sources and generating coherent and non-redundant summaries. In this proposed model, we address these challenges by leveraging the power of two popular natural language processing techniques, Bidirectional Encoder Representations from Transformers (BERT) and Gated Recurrent Unit (GRU). The Document Understanding Conference (DUC) dataset, a widely recognized benchmark dataset for multi-document summarization, was used to train and evaluate the model. By using BERT to generate contextual embeddings and GRU to capture sequence information, the proposed method outperforms previous methods in terms of summarization quality metrics such as ROUGE (RecallOriented Understudy for Gisting Evaluation). The proposed model has significant potential for use in various applications, such as news summarization, document summarization, and automated content creation. This study demonstrates that combining BERT and GRU models can effectively capture the contextual and sequential information in multi-document summarization, leading to high-quality summaries that overcome the limitations of previous methods.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125704495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-01DOI: 10.1109/REEDCON57544.2023.10151322
A. Malik, Ahteshamul Haque, K. Bharath
With the increase in the energy demand, the grid-tied PV systems have become extensively popular. Though they are assumed to be highly reliable. However, in practical scenarios, like any complex system, they are prone to failures. Investigations have revealed that inverters are weakest components in terms of reliability in a grid-tied PV system. The key factor behind inverter to be the weakest link is that it has majority of power switching devices. These switching devices are susceptible to faults owing to various aspects. Furthermore, the next vulnerable component is a capacitor. These two components working and functionality highly affects the system reliability. The PV mission profile is another important factor in influencing the system reliability. Consequently, it is utmost important to study the reliability guidelines in such systems. This work provides a guidance towards estimating the overall lifetime and based on that, ultimately, predicting the reliability of a grid-tied PV system.
{"title":"Grid-Tied PV Inverter Reliability Estimation Based on Mission Profile","authors":"A. Malik, Ahteshamul Haque, K. Bharath","doi":"10.1109/REEDCON57544.2023.10151322","DOIUrl":"https://doi.org/10.1109/REEDCON57544.2023.10151322","url":null,"abstract":"With the increase in the energy demand, the grid-tied PV systems have become extensively popular. Though they are assumed to be highly reliable. However, in practical scenarios, like any complex system, they are prone to failures. Investigations have revealed that inverters are weakest components in terms of reliability in a grid-tied PV system. The key factor behind inverter to be the weakest link is that it has majority of power switching devices. These switching devices are susceptible to faults owing to various aspects. Furthermore, the next vulnerable component is a capacitor. These two components working and functionality highly affects the system reliability. The PV mission profile is another important factor in influencing the system reliability. Consequently, it is utmost important to study the reliability guidelines in such systems. This work provides a guidance towards estimating the overall lifetime and based on that, ultimately, predicting the reliability of a grid-tied PV system.","PeriodicalId":429116,"journal":{"name":"2023 International Conference on Recent Advances in Electrical, Electronics & Digital Healthcare Technologies (REEDCON)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131625863","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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