Pub Date : 2021-07-27DOI: 10.1109/NCC52529.2021.9530036
M. Ahmed, Kunwar Pritiraj Rajput, A. Jagannatham
This work develops a robust linear joint transceiver design framework toward tracking a time varying parameter in a multi-sensor network considering channel state information (CSI) uncertainty. To begin with, an optimal parameter tracking framework is developed for a scenario with perfect CSI. This is followed by formulation of the per slot average mean square error (MSE) optimization problem subject to individual sensor power constraints considering stochastic CSI uncertainty. Next, a fast block coordinate descent (BCD) based robust transceiver design is developed that minimizes the average MSE in each slot. Simulation results demonstrate the performance of the proposed scheme and also show the improvement against the existing schemes in the literature that ignore the CSI uncertainty.
{"title":"Robust Linear Transceiver Design for Parameter Tracking in IoT Networks","authors":"M. Ahmed, Kunwar Pritiraj Rajput, A. Jagannatham","doi":"10.1109/NCC52529.2021.9530036","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530036","url":null,"abstract":"This work develops a robust linear joint transceiver design framework toward tracking a time varying parameter in a multi-sensor network considering channel state information (CSI) uncertainty. To begin with, an optimal parameter tracking framework is developed for a scenario with perfect CSI. This is followed by formulation of the per slot average mean square error (MSE) optimization problem subject to individual sensor power constraints considering stochastic CSI uncertainty. Next, a fast block coordinate descent (BCD) based robust transceiver design is developed that minimizes the average MSE in each slot. Simulation results demonstrate the performance of the proposed scheme and also show the improvement against the existing schemes in the literature that ignore the CSI uncertainty.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123157600","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530186
Abirami B, Prerna Saxena, P. K
We propose a compact bandpass filter over 0.52-2.07 GHz at the receiver front-end of an intentional electromagnetic interference detection system. We design the filter using five microstrip stubs arranged in interdigital configuration along with a dumbbell shaped defected ground structure. We design the proposed filter on FR4 substrate with a relative permittivity of 4.4 and a thickness of 1.6 mm. We obtain a 3dB fractional bandwidth of 119.96%. The proposed filter exhibits a return loss >12 dB, an insertion loss ≈0.922 dB and a flat group delay over the entire bandwidth. Also, the proposed filter is compact and occupies an area of 3.55 × 1.557 cm2. As compared to the state-of-the-art designs, the proposed bandpass filter is highly miniaturized, easy to fabricate and exhibits good performance.
{"title":"A Miniaturized Interdigital Bandpass Filter for Intentional Electromagnetic Interference Applications","authors":"Abirami B, Prerna Saxena, P. K","doi":"10.1109/NCC52529.2021.9530186","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530186","url":null,"abstract":"We propose a compact bandpass filter over 0.52-2.07 GHz at the receiver front-end of an intentional electromagnetic interference detection system. We design the filter using five microstrip stubs arranged in interdigital configuration along with a dumbbell shaped defected ground structure. We design the proposed filter on FR4 substrate with a relative permittivity of 4.4 and a thickness of 1.6 mm. We obtain a 3dB fractional bandwidth of 119.96%. The proposed filter exhibits a return loss >12 dB, an insertion loss ≈0.922 dB and a flat group delay over the entire bandwidth. Also, the proposed filter is compact and occupies an area of 3.55 × 1.557 cm2. As compared to the state-of-the-art designs, the proposed bandpass filter is highly miniaturized, easy to fabricate and exhibits good performance.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128339369","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 consider a system with a sensor tracking a time-varying quantity and sending updates to a monitoring station using one of $K$ different data-rates for each update. The probability of an attempted update is an unknown function of the data-rate of the update. The metric of interest is the Age-of-Information (AoI), defined as the time elapsed since the sensor made the measurement sent in the latest update received by the monitoring station. The algorithmic challenge is to determine which data-rate to use to minimize cumulative AoI over a finite time-horizon. We propose two policies and characterize their performance via analysis and simulations. One of the key takeaways is that taking the current AoI into account while determining which data-rate to use is key for good performance. In addition, we study the trade-off between AoI and throughput for the system considered.
{"title":"Age-of-Information Bandits with Heterogeneous Data Rates","authors":"Harsh Deshpande, Sucheta Ravikanti, Sharayu Moharir","doi":"10.1109/NCC52529.2021.9530103","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530103","url":null,"abstract":"We consider a system with a sensor tracking a time-varying quantity and sending updates to a monitoring station using one of $K$ different data-rates for each update. The probability of an attempted update is an unknown function of the data-rate of the update. The metric of interest is the Age-of-Information (AoI), defined as the time elapsed since the sensor made the measurement sent in the latest update received by the monitoring station. The algorithmic challenge is to determine which data-rate to use to minimize cumulative AoI over a finite time-horizon. We propose two policies and characterize their performance via analysis and simulations. One of the key takeaways is that taking the current AoI into account while determining which data-rate to use is key for good performance. In addition, we study the trade-off between AoI and throughput for the system considered.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127549853","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530167
Anil Kumar Nayak, Vinit Singh Yadav, A. Patnaik
In this paper, a new H-plane multi-horn antenna is designed for small nonmetallic unmanned aerial vehicle (UAV) application. Four H-plane horn antennas are integrated into a single square substrate using the substrate integrated waveguide (SIW) concept. In fact, they are placed concentrically and directed at the four edges of the substrate. In order to control the resonant frequency at 5.8 GHz and to obtain proper matching, the co-axial connector is placed the center of the structure. The antenna provides the quasi-omnidirectional radiation instead of the directional radiation pattern at the H-plane. The laboratory prototype of the structure is measured to validate the theoretical results. This antenna is suitable for UAV applications.
{"title":"An H-Plane multi-Horn Antenna Using Substrate Integrated Waveguide Technique","authors":"Anil Kumar Nayak, Vinit Singh Yadav, A. Patnaik","doi":"10.1109/NCC52529.2021.9530167","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530167","url":null,"abstract":"In this paper, a new H-plane multi-horn antenna is designed for small nonmetallic unmanned aerial vehicle (UAV) application. Four H-plane horn antennas are integrated into a single square substrate using the substrate integrated waveguide (SIW) concept. In fact, they are placed concentrically and directed at the four edges of the substrate. In order to control the resonant frequency at 5.8 GHz and to obtain proper matching, the co-axial connector is placed the center of the structure. The antenna provides the quasi-omnidirectional radiation instead of the directional radiation pattern at the H-plane. The laboratory prototype of the structure is measured to validate the theoretical results. This antenna is suitable for UAV applications.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127250752","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530047
Prasad Gaikwad, Saidhiraj Amuru, K. Kuchi
Long Term Evolution (LTE) focused on providing high data rates at low latency when compared to previous-generation technologies. The recent research and development in machine learning for wireless communication networks focus on making these networks more efficient, intelligent, and optimal. We propose a machine learning algorithm to improve the performance of LTE in a real-time deployments. Specifically, we focus on the case of single-user multiple-input multiple-output transmission mode (TM4 as known in LTE). The channel quality feedback from user to the base stations plays a crucial role to ensure successful communication with low error rate in this transmission mode. The feedback from the user includes precoding matrix indicator (PMI), rank indicator apart from the channel quality feedback. However, in practical systems, as the base station must support several users, there is a delay expected from the time a user sends feedback until the time it is scheduled. This time lag can cause significant performance degradation depending on the channel conditions and also in cases when the user is mobile. Hence, to eliminate this adverse impact, we present a machine learning model that predict future channels and the feedback from the user is calculated based on these predictions. Via several numerical simulations, we show the effectiveness of the proposed algorithms under a variety of scenarios. Without loss of generality, the same work can be applied in the context of 5G NR. LTE is used only as a case study due to its vast prevalence and deployments even as of today.
{"title":"Improving the Throughput of a Cellular Network using Machine Learning - A Case Study of LTE","authors":"Prasad Gaikwad, Saidhiraj Amuru, K. Kuchi","doi":"10.1109/NCC52529.2021.9530047","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530047","url":null,"abstract":"Long Term Evolution (LTE) focused on providing high data rates at low latency when compared to previous-generation technologies. The recent research and development in machine learning for wireless communication networks focus on making these networks more efficient, intelligent, and optimal. We propose a machine learning algorithm to improve the performance of LTE in a real-time deployments. Specifically, we focus on the case of single-user multiple-input multiple-output transmission mode (TM4 as known in LTE). The channel quality feedback from user to the base stations plays a crucial role to ensure successful communication with low error rate in this transmission mode. The feedback from the user includes precoding matrix indicator (PMI), rank indicator apart from the channel quality feedback. However, in practical systems, as the base station must support several users, there is a delay expected from the time a user sends feedback until the time it is scheduled. This time lag can cause significant performance degradation depending on the channel conditions and also in cases when the user is mobile. Hence, to eliminate this adverse impact, we present a machine learning model that predict future channels and the feedback from the user is calculated based on these predictions. Via several numerical simulations, we show the effectiveness of the proposed algorithms under a variety of scenarios. Without loss of generality, the same work can be applied in the context of 5G NR. LTE is used only as a case study due to its vast prevalence and deployments even as of today.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116825870","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530041
Durgesh Kalwar, V. Sukumaran
We consider the problem of designing a sequential decision making agent to maximize an unknown time-varying function which switches with time. At each step, the agent receives an observation of the function's value at a point decided by the agent. The observation could be corrupted by noise. The agent is also constrained to take safe decisions with high probability, i.e., the chosen points should have a function value greater than a threshold. For this switching environment, we propose a policy called Adaptive-SafeOpt and evaluate its performance via simulations. The policy incorporates Bayesian optimization and change point detection for the safe sequential optimization problem. We observe that a major challenge in adapting to the switching change is to identify safe decisions when the change point is detected and prevent attraction to local optima.
{"title":"Safe Sequential Optimization in Switching Environments","authors":"Durgesh Kalwar, V. Sukumaran","doi":"10.1109/NCC52529.2021.9530041","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530041","url":null,"abstract":"We consider the problem of designing a sequential decision making agent to maximize an unknown time-varying function which switches with time. At each step, the agent receives an observation of the function's value at a point decided by the agent. The observation could be corrupted by noise. The agent is also constrained to take safe decisions with high probability, i.e., the chosen points should have a function value greater than a threshold. For this switching environment, we propose a policy called Adaptive-SafeOpt and evaluate its performance via simulations. The policy incorporates Bayesian optimization and change point detection for the safe sequential optimization problem. We observe that a major challenge in adapting to the switching change is to identify safe decisions when the change point is detected and prevent attraction to local optima.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124057848","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530070
Manjeer Majumder, A. Jagannatham
This paper develops a novel data dependent superimposed training technique for channel estimation in generic block transmission (BT) systems comprising of single/multi-carrier (SC/MC) and zero-padded (ZP)/ cyclic prefix (CP) systems. The training sequence comprises of the summation of a known training sequence and a data-dependent sequence that is not known to the receiver. A unique aspect of the scheme is that the channel estimation is not affected by the use of a data-dependent sequence. The pilot design framework is conceived in order to minimize the Bayesian Cramér-Rao bound (BCRB) associated with channel estimation error. Simulation results are provided to exhibit the performance of the proposed scheme for single and multi carrier zero-padded and cyclic prefixed systems.
{"title":"Optimal Pilot Design for Data Dependent Superimposed Training based Channel Estimation in Single/Multi carrier Block Transmission Systems","authors":"Manjeer Majumder, A. Jagannatham","doi":"10.1109/NCC52529.2021.9530070","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530070","url":null,"abstract":"This paper develops a novel data dependent superimposed training technique for channel estimation in generic block transmission (BT) systems comprising of single/multi-carrier (SC/MC) and zero-padded (ZP)/ cyclic prefix (CP) systems. The training sequence comprises of the summation of a known training sequence and a data-dependent sequence that is not known to the receiver. A unique aspect of the scheme is that the channel estimation is not affected by the use of a data-dependent sequence. The pilot design framework is conceived in order to minimize the Bayesian Cramér-Rao bound (BCRB) associated with channel estimation error. Simulation results are provided to exhibit the performance of the proposed scheme for single and multi carrier zero-padded and cyclic prefixed systems.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129460264","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530107
Shivam Gujral
This paper explores a relay aided bidirectional communications scenario between two users embedded with two different technologies. One of these two energy constrained users is a backscatter device and the other is an energy harvesting (EH) device. The relay node controls the communication process between the two users in such a way that it facilitates in both energy and information cooperation and therefore, acts as a global controller for the model under consideration. Under this setting, we aim to maximize the weighted sum-throughput over a joint set of constraints in the time allocation parameter and the energy and information beamforming vectors. Henceforth, we present an optimal solution for the special case of our problem such that the relay node is equipped with a single antenna. In addition, we also present a sub-optimal solution to the generalized case for the multi-antenna relay node. Finally, the numerical simulations demonstrate our system's performance when we vary the key parameters of the simulation setting.
{"title":"Relay-Aided Bidirectional Communications Between Devices in a Hybrid User Scenario for IoT","authors":"Shivam Gujral","doi":"10.1109/NCC52529.2021.9530107","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530107","url":null,"abstract":"This paper explores a relay aided bidirectional communications scenario between two users embedded with two different technologies. One of these two energy constrained users is a backscatter device and the other is an energy harvesting (EH) device. The relay node controls the communication process between the two users in such a way that it facilitates in both energy and information cooperation and therefore, acts as a global controller for the model under consideration. Under this setting, we aim to maximize the weighted sum-throughput over a joint set of constraints in the time allocation parameter and the energy and information beamforming vectors. Henceforth, we present an optimal solution for the special case of our problem such that the relay node is equipped with a single antenna. In addition, we also present a sub-optimal solution to the generalized case for the multi-antenna relay node. Finally, the numerical simulations demonstrate our system's performance when we vary the key parameters of the simulation setting.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132486751","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530154
Ravi Kumar Sanjay Sane, Pharvesh Salman Choudhary, L. Sharma, Prof. Samarendra Dandapat
Electrocardiogram(ECG) is one of the most frequently used modality by cardiologists across the globe to detect any heart function abnormalities. In hospitals, ECG results are printed on paper by the ECG machines, which then is analysed by an expert. This work proposes a one-dimensional convolutional neural network(CNN) framework for automated myocardial infarction (MI) detection from multi-lead ECG signals extracted from ECG images. The model is developed using PTB diagnostic database consisting of 148 ECGs of (MI) cases. The results verify the efficacy of the proposed method with accuracy, sensitivity and precision of 86.21%, 89.19%, and 91.30%, respectively. The work is also compared with other state-of-the-art approaches for MI detection using ECG images.
{"title":"Detection of Myocardial Infarction from 12 Lead ECG Images","authors":"Ravi Kumar Sanjay Sane, Pharvesh Salman Choudhary, L. Sharma, Prof. Samarendra Dandapat","doi":"10.1109/NCC52529.2021.9530154","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530154","url":null,"abstract":"Electrocardiogram(ECG) is one of the most frequently used modality by cardiologists across the globe to detect any heart function abnormalities. In hospitals, ECG results are printed on paper by the ECG machines, which then is analysed by an expert. This work proposes a one-dimensional convolutional neural network(CNN) framework for automated myocardial infarction (MI) detection from multi-lead ECG signals extracted from ECG images. The model is developed using PTB diagnostic database consisting of 148 ECGs of (MI) cases. The results verify the efficacy of the proposed method with accuracy, sensitivity and precision of 86.21%, 89.19%, and 91.30%, respectively. The work is also compared with other state-of-the-art approaches for MI detection using ECG images.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133447745","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 : 2021-07-27DOI: 10.1109/NCC52529.2021.9530037
Aman Kumar Sharma, Kavya Ranjan Saxena, Vipul Arora
Extraction of the predominant melodic line from polyphonic audio containing more than one source playing simultaneously is a challenging task in the field of music information retrieval. The proposed method aims at providing finer F0s, and not coarse notes while using deep classifiers. Frequency-anchored input features extracted from constant Q-transform allow the signatures of melody to be independent of F0. The proposed scheme also takes care of the data imbalance problem across classes, as it uses only two or three output classes as opposed to a large number of notes. Experimental evaluation shows the proposed method outperforms a state-of-the-art deep learning-based melody estimation method.
{"title":"FREQUENCY-ANCHORED DEEP NETWORKS FOR POLYPHONIC MELODY EXTRACTION","authors":"Aman Kumar Sharma, Kavya Ranjan Saxena, Vipul Arora","doi":"10.1109/NCC52529.2021.9530037","DOIUrl":"https://doi.org/10.1109/NCC52529.2021.9530037","url":null,"abstract":"Extraction of the predominant melodic line from polyphonic audio containing more than one source playing simultaneously is a challenging task in the field of music information retrieval. The proposed method aims at providing finer F0s, and not coarse notes while using deep classifiers. Frequency-anchored input features extracted from constant Q-transform allow the signatures of melody to be independent of F0. The proposed scheme also takes care of the data imbalance problem across classes, as it uses only two or three output classes as opposed to a large number of notes. Experimental evaluation shows the proposed method outperforms a state-of-the-art deep learning-based melody estimation method.","PeriodicalId":414087,"journal":{"name":"2021 National Conference on Communications (NCC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-07-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131539022","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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