Pub Date : 2021-11-26DOI: 10.1109/iccica52458.2021.9697256
Priya Maidamwar, P. Saraf, N. Chavhan
Ongoing advancements in Block chain Innovation's development have made an imaginative gathering for the two industrialists and analysts. Block chain has various points of interest, for example, disseminated systems, security y, and trustless structures. There are different block chain applications extending from riches the board, cross border protection cryptographic money moves, budgetary administrations, chance management, government, and social government assistance Internet of Things (loT); There are a few articles dependent on the use of block chain innovation in various fields and features of utilization, there is no orderly investigation of block chain innovation in both specialized and business viewpoint. To address this void, an itemized review of the block chain innovation was done. This paper would, specifically, give various specialists the usage of block chain, its executions and talk about innovative difficulties just as ongoing improvements in conquering the difficulties. Likewise, this paper additionally investigates possibilities for concentrate soon.
{"title":"Blockchain Applications, Challenges, and Opportunities: A Survey of a Decade of Research and Future Outlook","authors":"Priya Maidamwar, P. Saraf, N. Chavhan","doi":"10.1109/iccica52458.2021.9697256","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697256","url":null,"abstract":"Ongoing advancements in Block chain Innovation's development have made an imaginative gathering for the two industrialists and analysts. Block chain has various points of interest, for example, disseminated systems, security y, and trustless structures. There are different block chain applications extending from riches the board, cross border protection cryptographic money moves, budgetary administrations, chance management, government, and social government assistance Internet of Things (loT); There are a few articles dependent on the use of block chain innovation in various fields and features of utilization, there is no orderly investigation of block chain innovation in both specialized and business viewpoint. To address this void, an itemized review of the block chain innovation was done. This paper would, specifically, give various specialists the usage of block chain, its executions and talk about innovative difficulties just as ongoing improvements in conquering the difficulties. Likewise, this paper additionally investigates possibilities for concentrate soon.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125079470","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697209
A. Wankhade, K. Wagh
With the expansion of IoT and its network connected devices, security is a major concerns. In IoT networks, the participating nodes are usually resource constrained, due to which they are vulnerable to cyber attacks. Security is the major concerns in the domain of IoT network. As there is a development of IoT network, the security of network layer has a big challenge. So to secure a dynamic IoT network different approaches like deployment of Intrusion Detection and Prevention model can be used to defend against various types of attacks on IoT network. With this Machine Learning can be used to improve the performance of detection and mitigation of attacks.ML which can embed intelligence in the IoT devices and networks, can be used for solving different security problems. The aim is to apply the ML techniques for defending against attacks that cloud enhance the security as well as privacy for IoT systems.
{"title":"Machine Learning Techniques for defending Cloud enabled IoT network","authors":"A. Wankhade, K. Wagh","doi":"10.1109/iccica52458.2021.9697209","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697209","url":null,"abstract":"With the expansion of IoT and its network connected devices, security is a major concerns. In IoT networks, the participating nodes are usually resource constrained, due to which they are vulnerable to cyber attacks. Security is the major concerns in the domain of IoT network. As there is a development of IoT network, the security of network layer has a big challenge. So to secure a dynamic IoT network different approaches like deployment of Intrusion Detection and Prevention model can be used to defend against various types of attacks on IoT network. With this Machine Learning can be used to improve the performance of detection and mitigation of attacks.ML which can embed intelligence in the IoT devices and networks, can be used for solving different security problems. The aim is to apply the ML techniques for defending against attacks that cloud enhance the security as well as privacy for IoT systems.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124705357","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697316
Bh. Srinivas Sasikanth, Lingamsetty Naga Yoshita, G. N. Reddy, Manitha P.V.
Waste Management is the most challenging issue of modern society. Fast growth in population, increased factory presence and modern lifestyle have contributed towards the large amount of waste. An efficient waste management system mainly revolves around waste segregation and processing. Segregation makes it effective to recycle and reuse the waste conventionally. This paper proposes a novel and efficient automated waste segregator and management system at household level. The prototype of the proposed system is developed using an Arduino microcontroller and Raspberry Pi, website to govern the entire process with comfort and simplicity. The most important part of the proposed system is the sensory unit which helps in segregating different types of waste. The module contains sensors for detecting moisture, metal so as to categorize different categories of waste. The major units of the segregating module consist of four noticeable components such as metal sensor, a moisture sensor, segregation bins and the camera, while the waste management is performed at the software system. Identification of waste is done by respective sensors. The microcontroller controls all the activity of the DC motor accordingly. The dry waste collected will be segregated through image analysis by the images captured using the camera. This quantity and other metadata of the collected waste is monitored via a website.
{"title":"An Efficient & Smart Waste Management System","authors":"Bh. Srinivas Sasikanth, Lingamsetty Naga Yoshita, G. N. Reddy, Manitha P.V.","doi":"10.1109/iccica52458.2021.9697316","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697316","url":null,"abstract":"Waste Management is the most challenging issue of modern society. Fast growth in population, increased factory presence and modern lifestyle have contributed towards the large amount of waste. An efficient waste management system mainly revolves around waste segregation and processing. Segregation makes it effective to recycle and reuse the waste conventionally. This paper proposes a novel and efficient automated waste segregator and management system at household level. The prototype of the proposed system is developed using an Arduino microcontroller and Raspberry Pi, website to govern the entire process with comfort and simplicity. The most important part of the proposed system is the sensory unit which helps in segregating different types of waste. The module contains sensors for detecting moisture, metal so as to categorize different categories of waste. The major units of the segregating module consist of four noticeable components such as metal sensor, a moisture sensor, segregation bins and the camera, while the waste management is performed at the software system. Identification of waste is done by respective sensors. The microcontroller controls all the activity of the DC motor accordingly. The dry waste collected will be segregated through image analysis by the images captured using the camera. This quantity and other metadata of the collected waste is monitored via a website.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123156625","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}
We all are facing an immense health calamity due to the speedy transmission of Covid-19. People are dying due to this deadly virus. Physical contact with an affected individual can transmit this disease. World Health Organization (WHO) issued many ways to avoid infection of Covid-19. In communal locations, wearing a face mask is one of the most effective strategies to protect oneself. For long periods of time, several countries have been in lockdown. As the world returns to normalcy, wearing a mask in public places might be crucial. Manually monitoring the mob would be challenging. So, we devised a way for determining whether or not a person in the crowd is wearing a mask. The proposed framework can detect masks and face shields with an accuracy of 95.7%.
{"title":"Deep Learning based Face-Mask and Shield Detection","authors":"Vaibhav Mukund Shinde, Nakshatra Jagtap, Hrushikesh Shukla","doi":"10.1109/iccica52458.2021.9697237","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697237","url":null,"abstract":"We all are facing an immense health calamity due to the speedy transmission of Covid-19. People are dying due to this deadly virus. Physical contact with an affected individual can transmit this disease. World Health Organization (WHO) issued many ways to avoid infection of Covid-19. In communal locations, wearing a face mask is one of the most effective strategies to protect oneself. For long periods of time, several countries have been in lockdown. As the world returns to normalcy, wearing a mask in public places might be crucial. Manually monitoring the mob would be challenging. So, we devised a way for determining whether or not a person in the crowd is wearing a mask. The proposed framework can detect masks and face shields with an accuracy of 95.7%.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121151682","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697193
Nageshwar Nath Pandey, Naresh Babu Muppalaneni
According to the preceding year’s road statistical report emphasize that the prime reasons of mortal road accidents are because of drowsy or distracted state of driver. Recognition of such critical states of driver at its initial phase with higher accuracy can rescue several precious lives. To satisfy this demand, we have analyzed the five different classifier’s i.e. Fuzzy min-max, Decision tree, K- Nearest Neighbor’s, Linear Support Vector Machine and VGG-16 neural network. Among these classifier’s, VGG-16 has given outstanding result with accuracy of 96.4 % on validation data but lagged in the terms training time.
{"title":"Driver Distraction Identification using Multiple Machine Learning Approaches","authors":"Nageshwar Nath Pandey, Naresh Babu Muppalaneni","doi":"10.1109/iccica52458.2021.9697193","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697193","url":null,"abstract":"According to the preceding year’s road statistical report emphasize that the prime reasons of mortal road accidents are because of drowsy or distracted state of driver. Recognition of such critical states of driver at its initial phase with higher accuracy can rescue several precious lives. To satisfy this demand, we have analyzed the five different classifier’s i.e. Fuzzy min-max, Decision tree, K- Nearest Neighbor’s, Linear Support Vector Machine and VGG-16 neural network. Among these classifier’s, VGG-16 has given outstanding result with accuracy of 96.4 % on validation data but lagged in the terms training time.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"36 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124343215","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}
Over the years, Accidents due to animals crossing the road at unexpected moments have still been a significant cause of road death. Roads near the forest are dark and dense; hence drivers cannot spot the animals clear. Truck drivers face issues due to blindspot regions. This paper proposes a model that can efficiently detect the animals and alarm the driver. Using Machine learning - A deep learning algorithm, we are segregating the animals with the help of a vast open-source dataset. Using convolution neural networks, the model will predict the object for every image frame received from the Live Camera. If the machine marks an object as an animal, the system gives an alert of 3 seconds to make the driver conscious about the approaching animal. This model doesn't stop with few animals as the dataset is open-sourced the variety of animals detection keep increasing. The model gives 91% accuracy.
{"title":"Animal Detection for Road safety using Deep Learning","authors":"Sanjay Santhanam, Sudhir Sidhaarthan B, Sai Sudha Panigrahi, Suryakanta Kashyap, Bhargav Krishna Duriseti","doi":"10.1109/iccica52458.2021.9697287","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697287","url":null,"abstract":"Over the years, Accidents due to animals crossing the road at unexpected moments have still been a significant cause of road death. Roads near the forest are dark and dense; hence drivers cannot spot the animals clear. Truck drivers face issues due to blindspot regions. This paper proposes a model that can efficiently detect the animals and alarm the driver. Using Machine learning - A deep learning algorithm, we are segregating the animals with the help of a vast open-source dataset. Using convolution neural networks, the model will predict the object for every image frame received from the Live Camera. If the machine marks an object as an animal, the system gives an alert of 3 seconds to make the driver conscious about the approaching animal. This model doesn't stop with few animals as the dataset is open-sourced the variety of animals detection keep increasing. The model gives 91% accuracy.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130236918","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697213
Pratik Dhoke, Prasad P. Lokulwar, Basant K. Verma, H. Deshmukh
The healthcare industry faces a broad spectrum of challenges. These challenges might range from unavailability of resources, Affordability to slight human errors or even accessibility. All of them resulting in the loss of money or lives for the ordinary person. While some can’t afford the expensive treatments or pay the enormous medical bills, others face a lack of availability of doctors. This project aims to minimize and overcome these challenges in the health care system, thereby making the services affordable and available at the same time. The goal is to provide a design to the existing healthcare system to make it more flexible, affordable, and accessible. This new design is discussed in this paper with one developed system to test the end-to-end life cycle of the healthcare services/systems.
{"title":"Design and Development of Healthcare System using Block chain and Artificial Intelligence","authors":"Pratik Dhoke, Prasad P. Lokulwar, Basant K. Verma, H. Deshmukh","doi":"10.1109/iccica52458.2021.9697213","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697213","url":null,"abstract":"The healthcare industry faces a broad spectrum of challenges. These challenges might range from unavailability of resources, Affordability to slight human errors or even accessibility. All of them resulting in the loss of money or lives for the ordinary person. While some can’t afford the expensive treatments or pay the enormous medical bills, others face a lack of availability of doctors. This project aims to minimize and overcome these challenges in the health care system, thereby making the services affordable and available at the same time. The goal is to provide a design to the existing healthcare system to make it more flexible, affordable, and accessible. This new design is discussed in this paper with one developed system to test the end-to-end life cycle of the healthcare services/systems.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"175 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133444581","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697181
A. Garg, N. Garg, Kamali Gupta, D. Prasad
Digitization and computers is impacting different research areas. The numerical results are very difficult to analyse and compare with the traditional manual approach. Whereas, mathematics is the main backbone of computers which can do huge calculations in few seconds. On the other hand to read the results of different objects related to various material science areas were also a tedious job. But, with the help of computer applications/software equipped machines this task became too easy and could provide better results with least time. In this study, different computer applications which are useful to study the mechanical properties of High-Strength Low-Alloy (HSLA) steels are discussed.
{"title":"Impact of Computer Applications to Study Mechanical Properties of HSLA Steels","authors":"A. Garg, N. Garg, Kamali Gupta, D. Prasad","doi":"10.1109/iccica52458.2021.9697181","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697181","url":null,"abstract":"Digitization and computers is impacting different research areas. The numerical results are very difficult to analyse and compare with the traditional manual approach. Whereas, mathematics is the main backbone of computers which can do huge calculations in few seconds. On the other hand to read the results of different objects related to various material science areas were also a tedious job. But, with the help of computer applications/software equipped machines this task became too easy and could provide better results with least time. In this study, different computer applications which are useful to study the mechanical properties of High-Strength Low-Alloy (HSLA) steels are discussed.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124759758","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697151
A. Raghuwanshi, Virendra Singh Chaudhary
With the widespread use of WSNs, it has become very important for routing to use energy efficiently. The efficient use of energy by routing directly affects the life span of WSN. Most of the studies in the literature have focused on increasing energy efficiency. In this study, energy sensitive Routing protocols are focused. The goal is which protocol will save energy more efficiently. All Routing protocols analysed are all about collision prevention, eliminating latency and solving existing energy sensitive problems. Despite all these developments, there are no standard MAC protocols for WSNs yet, but a lot of work is being done on this subject. The main purpose of the envisaged MAC protocols is to find a solution to the energy problem that determines the life span of the WSN. It is to seek new ways and methods to minimize energy waste. In addition, efforts are also made to reduce the transmission delays that occur in applications that are effective against delays. This paper introduce a comparative analysis of routing protocols over different network scenarios and yield interesting facts regarding capabilities and deficiency of these protocol over different network density.
{"title":"Comparative analysis of Energy Efficient Routing Protocol over WSN","authors":"A. Raghuwanshi, Virendra Singh Chaudhary","doi":"10.1109/iccica52458.2021.9697151","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697151","url":null,"abstract":"With the widespread use of WSNs, it has become very important for routing to use energy efficiently. The efficient use of energy by routing directly affects the life span of WSN. Most of the studies in the literature have focused on increasing energy efficiency. In this study, energy sensitive Routing protocols are focused. The goal is which protocol will save energy more efficiently. All Routing protocols analysed are all about collision prevention, eliminating latency and solving existing energy sensitive problems. Despite all these developments, there are no standard MAC protocols for WSNs yet, but a lot of work is being done on this subject. The main purpose of the envisaged MAC protocols is to find a solution to the energy problem that determines the life span of the WSN. It is to seek new ways and methods to minimize energy waste. In addition, efforts are also made to reduce the transmission delays that occur in applications that are effective against delays. This paper introduce a comparative analysis of routing protocols over different network scenarios and yield interesting facts regarding capabilities and deficiency of these protocol over different network density.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128518522","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 : 2021-11-26DOI: 10.1109/iccica52458.2021.9697315
Priyanka Deotale, Prasad P. Lokulwar
Crops in the farms are many times devastated by the wild as well as domestic animals and low productivity of crops is one of the reasons for this. It is not possible to stay 24 hours in the farm to sentinel the crops. So to surmount this issue an automated perspicacious crop aegis system is proposed utilizing Internet of Things (IOT). The system consists of esp8266 (nodeMCU), soil moisture sensor, dihydrogen monoxide sensor, GPRS and GSM module, servo motor, dihydrogen monoxide pump, etc. to obtain the required output. As soon as any kineticism is detected the system will engender an alarm to be taken and the lights will glow up implemented at every corner of the farm. This will not harm any animal and the crops will stay forfended.
{"title":"Smart Crop Protection System from Wild Animals Using IoT","authors":"Priyanka Deotale, Prasad P. Lokulwar","doi":"10.1109/iccica52458.2021.9697315","DOIUrl":"https://doi.org/10.1109/iccica52458.2021.9697315","url":null,"abstract":"Crops in the farms are many times devastated by the wild as well as domestic animals and low productivity of crops is one of the reasons for this. It is not possible to stay 24 hours in the farm to sentinel the crops. So to surmount this issue an automated perspicacious crop aegis system is proposed utilizing Internet of Things (IOT). The system consists of esp8266 (nodeMCU), soil moisture sensor, dihydrogen monoxide sensor, GPRS and GSM module, servo motor, dihydrogen monoxide pump, etc. to obtain the required output. As soon as any kineticism is detected the system will engender an alarm to be taken and the lights will glow up implemented at every corner of the farm. This will not harm any animal and the crops will stay forfended.","PeriodicalId":327193,"journal":{"name":"2021 International Conference on Computational Intelligence and Computing Applications (ICCICA)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127501957","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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