Pub Date : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974524
Sakshi Sharma, Nidhi
Vehicular Ad-hoc Networks (VANETs) helps in making smart vehicles by establishing communication network between vehicles or vehicle and Road Side Units (RSUs) enhancing road safety by improving traffic flow resulting in significant reduction of car accidents. In this paper, we are focusing on providing researchers and developers with a brief description of VANET, its architecture, characteristics, applications and security problems related to it.
{"title":"Vehicular Ad-Hoc Network: An Overview","authors":"Sakshi Sharma, Nidhi","doi":"10.1109/ICCCIS48478.2019.8974524","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974524","url":null,"abstract":"Vehicular Ad-hoc Networks (VANETs) helps in making smart vehicles by establishing communication network between vehicles or vehicle and Road Side Units (RSUs) enhancing road safety by improving traffic flow resulting in significant reduction of car accidents. In this paper, we are focusing on providing researchers and developers with a brief description of VANET, its architecture, characteristics, applications and security problems related to it.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115290093","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974480
Monika Gupta, P. Tiwari, R. Viral, A. Shrivastava
In a renewable energy system (RES), maintaining the balance of power between supply and demand with minimum cost in homes connected to these systems present one of the most important challenges to consider. Generally, a large capacity of batteries is usually used to store the energy and reused in absence or insufficient power supply in order to maintain the required energy balance. Thus, a hybrid proposed controller is proposed to analyze the stability of Micro Grid system (MG) using Particle Swarm optimisation (PSO) technique. Two modes of controllers are utilised to attain the stability of the MG system. The first PV / WT method works by using the voltage modulated direct power control (VMDPC) to achieve maximum grid power and also used to enhance the maximum power and the steady-state performances. The second mode of battery storage is operating to maintain the voltage and frequency in the MG through the utilization of the conventional controller. The key objective function is to achieve the maximum power and stability of the system with the implementation of the proposed controller. Simulink/MATLAB environment is used to examine the performance of the proposed system.
{"title":"Performance Enhancement of a Grid-Connected Micro Grid System using PSO Optimisation Technique","authors":"Monika Gupta, P. Tiwari, R. Viral, A. Shrivastava","doi":"10.1109/ICCCIS48478.2019.8974480","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974480","url":null,"abstract":"In a renewable energy system (RES), maintaining the balance of power between supply and demand with minimum cost in homes connected to these systems present one of the most important challenges to consider. Generally, a large capacity of batteries is usually used to store the energy and reused in absence or insufficient power supply in order to maintain the required energy balance. Thus, a hybrid proposed controller is proposed to analyze the stability of Micro Grid system (MG) using Particle Swarm optimisation (PSO) technique. Two modes of controllers are utilised to attain the stability of the MG system. The first PV / WT method works by using the voltage modulated direct power control (VMDPC) to achieve maximum grid power and also used to enhance the maximum power and the steady-state performances. The second mode of battery storage is operating to maintain the voltage and frequency in the MG through the utilization of the conventional controller. The key objective function is to achieve the maximum power and stability of the system with the implementation of the proposed controller. Simulink/MATLAB environment is used to examine the performance of the proposed system.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122412494","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974540
Moksh Grover, Bharti Verma, Nikhil Sharma, I. Kaushik
Nowadays with the increase in advancement of traffic network methodology we have potentials to control traffic congestion and hindrance using huge range of traffic management strategies. Feasibly there are two most promising techniques proffered are chaos theory and reinforcement leaning techniques, the goal of this research technique is to make up a model that self-sufficiently learns by itself the optimal policy. In this paper, we use V-2-V based fuzzy node mechanism and chaos theory that notifies where the traffic could get clustered. On other hand, our reinforcement learning agent makes up discretions (signal status) for the proffered environment.
{"title":"Traffic control using V-2-V Based Method using Reinforcement Learning","authors":"Moksh Grover, Bharti Verma, Nikhil Sharma, I. Kaushik","doi":"10.1109/ICCCIS48478.2019.8974540","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974540","url":null,"abstract":"Nowadays with the increase in advancement of traffic network methodology we have potentials to control traffic congestion and hindrance using huge range of traffic management strategies. Feasibly there are two most promising techniques proffered are chaos theory and reinforcement leaning techniques, the goal of this research technique is to make up a model that self-sufficiently learns by itself the optimal policy. In this paper, we use V-2-V based fuzzy node mechanism and chaos theory that notifies where the traffic could get clustered. On other hand, our reinforcement learning agent makes up discretions (signal status) for the proffered environment.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122590895","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974507
Sahil Lamba, Rishab Lamba
Deep learning has revolutionised the field of machine learning in near years, particularly for computer vision. Two methods are used to view supervised learning, SNN networks with the handwritten Digit Recognition Problem (NOD) and Normalized Normalized Approximate Descent (NORMAD). Experiments show that the identification accuracy of the prototype SNN does not deteriorate by more than 1% relative to the floating-point baseline, even with synaptic weights of 3-bit. In addition, the proposed SNN, which is trained on the basis of accurate spike timing data, outperforms the equivalent non-spiking artificial neural network (ANN) trained with back propagation, especially at low bit precision, and is in line with the convolutionary neural network that is normally used to train these system. Recent work shows the potential to use Spike-Based Data Encoding and learning for applications of the real world for positive neuromorphism.
{"title":"Spiking Neural Networks Vs Convolutional Neural Networks for Supervised Learning","authors":"Sahil Lamba, Rishab Lamba","doi":"10.1109/ICCCIS48478.2019.8974507","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974507","url":null,"abstract":"Deep learning has revolutionised the field of machine learning in near years, particularly for computer vision. Two methods are used to view supervised learning, SNN networks with the handwritten Digit Recognition Problem (NOD) and Normalized Normalized Approximate Descent (NORMAD). Experiments show that the identification accuracy of the prototype SNN does not deteriorate by more than 1% relative to the floating-point baseline, even with synaptic weights of 3-bit. In addition, the proposed SNN, which is trained on the basis of accurate spike timing data, outperforms the equivalent non-spiking artificial neural network (ANN) trained with back propagation, especially at low bit precision, and is in line with the convolutionary neural network that is normally used to train these system. Recent work shows the potential to use Spike-Based Data Encoding and learning for applications of the real world for positive neuromorphism.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129699716","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974519
Mahima Harjani, Moksh Grover, Nikhil Sharma, I. Kaushik
By applying machine learning algorithms, patterns are identified or recognized in the process of Pattern Recognition. On the grounds of prior knowledge, the data is collected and sorted. In this method, the raw data is transformed into a susceptible form which can be used by the machine. Electrocardiogram (ECG) Pattern Recognition is the main focus of this paper. ECG keeps a track of heart’s electrical activity. In the field of biometric it is used as a robust biometric. On the person, off the person and in the person, are the three categories for tracking and capturing signals. Only Off-the-person category in which there is no or minimal skin contact, is included in this paper. To analyze and implement data, six baseline methods are utilized. These baseline methods are applied two publicly available databases-CYBHi and UofT. Raw signals and spectrogram of heartbeat are used for studying about representing features. Various machine learning algorithms are also discussed. Implementation for predicting heartbeat as normal or abnormal and heart diseases, is performed.
{"title":"Analysis of Various Machine Learning Algorithm for Cardiac Pulse Prediction","authors":"Mahima Harjani, Moksh Grover, Nikhil Sharma, I. Kaushik","doi":"10.1109/ICCCIS48478.2019.8974519","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974519","url":null,"abstract":"By applying machine learning algorithms, patterns are identified or recognized in the process of Pattern Recognition. On the grounds of prior knowledge, the data is collected and sorted. In this method, the raw data is transformed into a susceptible form which can be used by the machine. Electrocardiogram (ECG) Pattern Recognition is the main focus of this paper. ECG keeps a track of heart’s electrical activity. In the field of biometric it is used as a robust biometric. On the person, off the person and in the person, are the three categories for tracking and capturing signals. Only Off-the-person category in which there is no or minimal skin contact, is included in this paper. To analyze and implement data, six baseline methods are utilized. These baseline methods are applied two publicly available databases-CYBHi and UofT. Raw signals and spectrogram of heartbeat are used for studying about representing features. Various machine learning algorithms are also discussed. Implementation for predicting heartbeat as normal or abnormal and heart diseases, is performed.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115954927","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974461
A. Das, M. Nabi
Nature inspires engineers to build robots with soft and flexible materials. Advancements in technology have opened doors for designing compliant and soft robots. Such robots find applications in designing soft surgical tools, soft wearable, implantable devices, etc. which can be used in collaboration with humans to execute a variety of non-conventional tasks. These robots have the ability to achieve any kinematic configurations through deformations. Unlike conventional robots, soft robots interact with an unknown environment with improved dexterity. However, this comes at the cost of increased complexity within existing modeling frameworks which motivated researchers to come up with specialized modeling techniques for soft robots. When a reasonable model is available, the next challenge for soft robots is to design a suitable control law to achieve some desired performance. This article gives some insights into soft robots with a focus on existing control methodologies. It also discusses the state of the art: biological inspirations, modeling, simulation, actuation methods, control and applications in human-robot interaction.
{"title":"A review on Soft Robotics: Modeling, Control and Applications in Human-Robot interaction","authors":"A. Das, M. Nabi","doi":"10.1109/ICCCIS48478.2019.8974461","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974461","url":null,"abstract":"Nature inspires engineers to build robots with soft and flexible materials. Advancements in technology have opened doors for designing compliant and soft robots. Such robots find applications in designing soft surgical tools, soft wearable, implantable devices, etc. which can be used in collaboration with humans to execute a variety of non-conventional tasks. These robots have the ability to achieve any kinematic configurations through deformations. Unlike conventional robots, soft robots interact with an unknown environment with improved dexterity. However, this comes at the cost of increased complexity within existing modeling frameworks which motivated researchers to come up with specialized modeling techniques for soft robots. When a reasonable model is available, the next challenge for soft robots is to design a suitable control law to achieve some desired performance. This article gives some insights into soft robots with a focus on existing control methodologies. It also discusses the state of the art: biological inspirations, modeling, simulation, actuation methods, control and applications in human-robot interaction.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"84 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124128446","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974557
Ramandeep Singh Kathuria, S. Gautam, Arjan Singh, Smarth Khatri, N. Yadav
Social media sites have emerged as one of the platforms to talk about issues and raise voice regarding almost anything going on in the world, with millions of people using social media sites every day, these sites enjoy tremendous popularity, and play a vital role in forming the opinion of the public. Due to this reason it becomes vital for any brand, political party, etc. to get a grasp of the prevailing sentiment among people, analyse it and create strategies to shape the opinion if needed. This is where sentiment analysis comes into play. It requires handling of huge amounts of data which is unstructured data which can be handled using deep learning, classifying algorithms
{"title":"Real Time Sentiment Analysis On Twitter Data Using Deep Learning(Keras)","authors":"Ramandeep Singh Kathuria, S. Gautam, Arjan Singh, Smarth Khatri, N. Yadav","doi":"10.1109/ICCCIS48478.2019.8974557","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974557","url":null,"abstract":"Social media sites have emerged as one of the platforms to talk about issues and raise voice regarding almost anything going on in the world, with millions of people using social media sites every day, these sites enjoy tremendous popularity, and play a vital role in forming the opinion of the public. Due to this reason it becomes vital for any brand, political party, etc. to get a grasp of the prevailing sentiment among people, analyse it and create strategies to shape the opinion if needed. This is where sentiment analysis comes into play. It requires handling of huge amounts of data which is unstructured data which can be handled using deep learning, classifying algorithms","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130888533","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974469
J. Singh, B. Bhushan
Among the ranking of the largest road network in the world, India stood at third position. According to a survey held in 2016 the total number of vehicles in India were 260 million. Therefore, there is a necessity to develop Expert Automatic Number Plate Recognition (ANPR) systems in India because of the tremendous rise in the number of automobiles flying on the roads. It would help in proper tracking of the vehicles,expert traffic examining, tracing stolen vehicles, supervising parking toll and imposing strict actions against red light breaching. Implementing an ANPR expert system in real life seems to be a challenging task because of the variety of number plate (NP) formats,designs, shapes, color, scales, angles and non-uniform lightning situations during image accession. So, we implemented an ANPR system which acts more robustly in different challenging scenarios then the previous proposed ANPR systems.The goal of this paper,is to design a robust technique forLicense Plate Detection(LPD) in the images using deep neural networks, Pre-process the detected license platesand performLicense Plate Recognition (LPR) usingLSTMTesseract OCR Engine. According to our experimentalresults, we have successfully achieved robust results withLPD accuracy of 99% and LPR accuracy of 95%just like commercial ANPR systemsi.e., Open-ALPRand Plate Recognizer.
{"title":"Real Time Indian License Plate Detection using Deep Neural Networks and Optical Character Recognition using LSTM Tesseract","authors":"J. Singh, B. Bhushan","doi":"10.1109/ICCCIS48478.2019.8974469","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974469","url":null,"abstract":"Among the ranking of the largest road network in the world, India stood at third position. According to a survey held in 2016 the total number of vehicles in India were 260 million. Therefore, there is a necessity to develop Expert Automatic Number Plate Recognition (ANPR) systems in India because of the tremendous rise in the number of automobiles flying on the roads. It would help in proper tracking of the vehicles,expert traffic examining, tracing stolen vehicles, supervising parking toll and imposing strict actions against red light breaching. Implementing an ANPR expert system in real life seems to be a challenging task because of the variety of number plate (NP) formats,designs, shapes, color, scales, angles and non-uniform lightning situations during image accession. So, we implemented an ANPR system which acts more robustly in different challenging scenarios then the previous proposed ANPR systems.The goal of this paper,is to design a robust technique forLicense Plate Detection(LPD) in the images using deep neural networks, Pre-process the detected license platesand performLicense Plate Recognition (LPR) usingLSTMTesseract OCR Engine. According to our experimentalresults, we have successfully achieved robust results withLPD accuracy of 99% and LPR accuracy of 95%just like commercial ANPR systemsi.e., Open-ALPRand Plate Recognizer.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131775884","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 : 2019-10-01DOI: 10.1109/icccis48478.2019.8974482
{"title":"ICCCIS 2019 Author Index","authors":"","doi":"10.1109/icccis48478.2019.8974482","DOIUrl":"https://doi.org/10.1109/icccis48478.2019.8974482","url":null,"abstract":"","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131626251","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 : 2019-10-01DOI: 10.1109/ICCCIS48478.2019.8974478
Rani Kumari, P. Nand, Rani Astya
In today modern digital world, there is huge need of security in medical field also. Among all modern data transfer techniques, Blockchain is a fast growing technology which provide a cryptodata through which we can transfer data between peer-to –peer node. Blockchain provide security which depends on highly cryptographic schemes. We can integrate blockchain with wireless body area network. Because WBAN is also a very emerging field of medical department. All the data of patient is maintained in a electronic health record (EHR). So Maintaining a EHR is very challenging face of medical field. In WBAN we transfer the patients data among different entities like healthcare server, medical staff, health insurer over the network. So we can provide security in this field through blockchain. In this paper we propose an architectural model of block chain with WBAN. We also mention some challenges which are faced in the field of medical health care applications.
{"title":"Integration of Blockchain in WBAN","authors":"Rani Kumari, P. Nand, Rani Astya","doi":"10.1109/ICCCIS48478.2019.8974478","DOIUrl":"https://doi.org/10.1109/ICCCIS48478.2019.8974478","url":null,"abstract":"In today modern digital world, there is huge need of security in medical field also. Among all modern data transfer techniques, Blockchain is a fast growing technology which provide a cryptodata through which we can transfer data between peer-to –peer node. Blockchain provide security which depends on highly cryptographic schemes. We can integrate blockchain with wireless body area network. Because WBAN is also a very emerging field of medical department. All the data of patient is maintained in a electronic health record (EHR). So Maintaining a EHR is very challenging face of medical field. In WBAN we transfer the patients data among different entities like healthcare server, medical staff, health insurer over the network. So we can provide security in this field through blockchain. In this paper we propose an architectural model of block chain with WBAN. We also mention some challenges which are faced in the field of medical health care applications.","PeriodicalId":436154,"journal":{"name":"2019 International Conference on Computing, Communication, and Intelligent Systems (ICCCIS)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133866698","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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