IEEE Open Journal of the Communications Society最新文献

{"title":"GP-DGECN: Geometric Prior Dynamic Group Equivariant Convolutional Networks for Specific Emitter Identification","authors":"Yu Han;Xiang Chen;Manxi Wang;Long Shi;Zhongming Feng","doi":"10.1109/OJCOMS.2024.3486459","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3486459","url":null,"abstract":"With the rapid development of mobile Internet technology, the number of access devices is increasing exponentially. However, due to inadequate encryption measures or low encryption strength of some devices, illegal access and the easy acquisition of legitimate device user information can lead to privacy breaches and property loss. Recently, physical layer security authentication technology has been adopted to improve the accuracy of identifying illegal devices. However, during signal propagation, noise and channel effects often degrade identification performance. To address this, this paper proposes a dynamic group-equivariant convolutional network based on geometric priors, termed GP-DGECN. This framework combines group-equivariant convolutional layers and dynamic convolution kernel strategies to resolve the limitation of traditional CNN models that only possess translational equivariance. By fully extracting intrinsic signal features, it enhances resistance to high noise and channel effects. Performance tests on real WiFi datasets demonstrate that the proposed framework can achieve an accuracy of 80% under both LoS and NLoS channel scenarios. Even under strong interference from SUIA channel parameters, it can achieve a recognition accuracy of nearly 60%.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10735345","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142595129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Tractable Framework for Spectrum Coexistence Between Satellite Receivers and Terrestrial Networks","authors":"Nicholas R. Olson;Theodore S. Rappaport;Jeffrey G. Andrews","doi":"10.1109/OJCOMS.2024.3485569","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3485569","url":null,"abstract":"We study the interference resulting from transmissions from terrestrial cellular networks on passive satellite receivers. This has important implications for the future allocation and terrestrial use of spectrum on a shared basis with satellite systems, in particular above 100 GHz. We develop an extensive, general model for the interference received at a typical passive satellite. Utilizing a stochastic geometry framework, we precisely characterize the outage probability for a set of satellites – which is the distribution of the interference with respect to spatial and temporal randomness inherent in the aforementioned interference model. We obtain upper and lower bounds on the outage probability using a new analytical method based on a matrix function generalization of the Laplace transform of the interference model. This analytical method allows for the distribution of the interference to be tightly bounded while affording a similar level of tractability to that encountered in the more typical coverage probability analysis of wireless networks using stochastic geometry. Using the analytical characterizations for outage probability, we investigate design choices and constraints such as the antenna gain and positioning at the passive satellite receiver and terrestrial nodes, out-of-band rejection, terrestrial network density, and the scan pattern of the passive receiver. Our analysis indicates that spectrum coexistence is feasible with minimal spectral separation, and that in-band coexistence may even be possible with low, but non-negligible, outage probability. A key insight from our analysis is that outage events are largely driven by spatial events corresponding to the presence of large clusters of transmitters as opposed to temporal fluctuations in interference power. The impact of these spatial events on EESS sensors may be mitigated by varying the boresight direction of the receive beam over the measurement duration.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10729879","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555118","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Survey of LoRaWAN-Integrated Wearable Sensor Networks for Human Activity Recognition: Applications, Challenges and Possible Solutions","authors":"Nahshon Mokua Obiri;Kristof Van Laerhoven","doi":"10.1109/OJCOMS.2024.3484002","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3484002","url":null,"abstract":"Long-Range Wide Area Networks (LoRaWAN), a prominent technology within Low-Power Wide Area Networks (LPWANs), have gained traction in remote monitoring due to their long-range communication, scalability, and low energy consumption. Compared to other LPWANs like Sigfox, Ingenu Random Phase Multiple Access (Ingenu-RPMA), Long-Term Evolution for Machines (LTE-M), and Narrowband Internet of Things (NB-IoT), LoRaWAN offers superior adaptability in diverse environments. This adaptability makes it particularly effective for Human Activity Recognition (HAR) systems. These systems utilize wearable sensors to collect data for applications in healthcare, elderly care, sports, and environmental monitoring. Integrating LoRaWAN with edge computing and Internet of Things (IoT) frameworks enhances data processing and transmission efficiency. However, challenges such as sensor wearability, data payload constraints, energy efficiency, and security must be addressed to deploy LoRaWAN-based HAR systems in real-world applications effectively. This survey explores the integration of LoRaWAN technology with wearable sensors for HAR, highlighting its suitability for remote monitoring applications such as Activities of Daily Living (ADL), tracking and localization, healthcare, and safety. We categorize state-of-the-art LoRaWAN-integrated wearable systems into body-worn, hybrid, objectmounted, and ambient sensors. We then discuss their applications and challenges, including energy efficiency, sensor scalability, data constraints, and security. Potential solutions such as advanced edge processing algorithms and secure communication protocols are proposed to enhance system performance and user comfort. The survey also outlines specific future research directions to advance this evolving field.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10726628","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142550545","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Few-Shot Class-Incremental Learning for Network Intrusion Detection Systems","authors":"Davide Di Monda;Antonio Montieri;Valerio Persico;Pasquale Voria;Matteo De Ieso;Antonio Pescapè","doi":"10.1109/OJCOMS.2024.3481895","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3481895","url":null,"abstract":"In today’s digital landscape, critical services are increasingly dependent on network connectivity, thus cybersecurity has become paramount. Indeed, the constant escalation of cyberattacks, including zero-day exploits, poses a significant threat. While Network Intrusion Detection Systems (NIDSs) leveraging machine-learning and deep-learning models have proven effective in recent studies, they encounter limitations such as the need for abundant samples of malicious traffic and full retraining upon encountering new attacks. These limitations hinder their adaptability in real-world scenarios. To address these challenges, we design a novel NIDS capable of promptly adapting to classify new attacks and provide timely predictions. Our proposal for attack-traffic classification adopts Few-Shot Class-Incremental Learning (\u0000<monospace>FSCIL</monospace>\u0000) and is based on the Rethinking Few-Shot (\u0000<monospace>RFS</monospace>\u0000) approach, which we experimentally prove to overcome other \u0000<monospace>FSCIL</monospace>\u0000 state-of-the-art alternatives based on either meta-learning or transfer learning. We evaluate the proposed NIDS across a wide array of cyberattacks whose traffic is collected in recent publicly available datasets to demonstrate its robustness across diverse network-attack scenarios, including malicious activities in an Internet-of-Things context and cyberattacks targeting servers. We validate various design choices as well, involving the number of traffic samples per attack available, the impact of the features used to represent the traffic objects, and the time to deliver the classification verdict. Experimental results witness that our proposed NIDS effectively retains previously acquired knowledge (with over 94% F1-score) while adapting to new attacks with only few samples available (with over 98% F1-score). Thus, it outperforms non-\u0000<monospace>FSCIL</monospace>\u0000 state of the art in terms of classification effectiveness and adaptation time. Moreover, our NIDS exhibits high performance even with traffic collected within short time frames, achieving 95% F1-score while reducing the time-to-insight. Finally, we identify possible limitations likely arising in specific application contexts and envision promising research avenues to mitigate them.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720176","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142551997","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Detection of Zero-Day Attacks in a Software-Defined LEO Constellation Network Using Enhanced Network Metric Predictions","authors":"Dennis Agnew;Ashlee Rice-Bladykas;Janise Mcnair","doi":"10.1109/OJCOMS.2024.3481965","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3481965","url":null,"abstract":"SATCOM is crucial for tactical networks, particularly submarines with sporadic communication requirements. Emerging SATCOM technologies, such as low-earth-orbit (LEO) satellite networks, provide lower latency, greater data reliability, and higher throughput than long-distance geostationary (GEO) satellites. Software-defined networking (SDN) has been introduced to SATCOM networks due to its ability to enhance management while strengthening network control and security. In our previous work, we proposed a SD-LEO constellation for naval submarine communication networks, as well as an extreme gradient boosting (XGBoost) machine-learning (ML) approach for classifying denial-of-service attacks against the constellation. Nevertheless, zero-day attacks have the potential to cause major damage to the SATCOM network, particularly the controller architecture, due to the scarcity of data for training and testing ML models due to their novelty. This study tackles this challenge by employing a predictive queuing analysis of the SD-SATCOM controller design to rapidly generate ML training data for zero-day attack detection. In addition, we redesign our singular controller architecture to a decentralized controller architecture to eliminate singular points of failure. To our knowledge, no prior research has investigated using queuing analysis to predict SD-SATCOM controller architecture network performance for ML training to prevent zero-day attacks. Our queuing analysis accelerates the training of ML models and enhances data adaptability, enabling network operators to defend against zero-day attacks without precollected data. We utilized the CatBoost algorithm to train a multi-output regression model to predict network performance statistics. Our method successfully identified and classified normal, non-attack samples and zero-day cyberattacks with over 94% accuracy, precision, recall, and f1-scores.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10720072","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142516850","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Joint Power Allocation for Transmitter and Relay in a Full-Duplex Relay Covert Communication System","authors":"Gui Fang;Jin Chen;Guoxin Li;Rongrong He;Haichao Wang;Yang Yang","doi":"10.1109/OJCOMS.2024.3481264","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3481264","url":null,"abstract":"This paper considers a full-duplex relay-assisted system for covert communication, in which both the transmitter and the relay are the sender of covert messages. Different from current works that only consider the transmitter power optimization or relay power optimization individually, we propose a joint optimization approach for the transmitter and relay power, which is expected to enhance the system’s covert performance. We establish the minimum error detection probability using the Kullback-Leibler (KL) divergence, which serves as the foundation for formulating our joint optimization problem. The objective is to achieve the highest covert transmission rate within the constraints of covertness requirement and total power limitation. Employing a graphical method, we effectively transform inequality constraints into equality constraints, leading to the derivation of an optimal closed-form solution. The simulation results confirm the accuracy of the theoretical derivation and demonstrate that the proposed power allocation method is effective in determining the optimal power for both the transmitter and the full-duplex relay within a two-hop covert communication system.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716740","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555115","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Improving Recognition of Sub-GHz LPWANs: A Deep Learning Approach With the UPC-LPWAN-1 Dataset","authors":"Edgar Maya-Olalla;Mario García-Lozano;David Pérez-Díaz-de-Cerio;Silvia Ruiz-Boqué","doi":"10.1109/OJCOMS.2024.3480856","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3480856","url":null,"abstract":"Deep neural networks (DNNs) have emerged as an effective technique for modulation/system recognition but rely heavily on representative datasets. This paper introduces the “UPC-LPWAN-1” dataset, a comprehensive collection of 40 Sub-GHz LPWAN transmission modes acquired using real hardware. Publicly available to the scientific community, this dataset includes raw and pre-processed samples across different Signal-to-Noise Ratios (SNRs) and features multi-carrier modulations, which are typically underrepresented in existing datasets. The variability in studies using different neural network architectures and small, unrepresentative datasets complicates research comparisons. To address this, this paper compares seven proposed architectures using UPC-LPWAN-1, providing a standardized evaluation. To further enhance accuracy, we propose four new convolutional neural network (CNN) architectures adapted to four forms of signal representation. Our results demonstrate that while some existing models perform well under high SNR conditions, their performance degrades significantly in low SNR environments. The proposed spectrogram-based CNN consistently outperforms other models, achieving a classification accuracy of 99.71% at SNR = 0 dB, above 90% at SNR =−10 dB, and above 70% at SNR =−15 dB, while still being able to differentiate between systems.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716536","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142518031","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Model-Driven Channel Estimation for MIMO Monostatic Backscatter System With Deep Unfolding","authors":"Yulin Zhou;Xiaoting Li;Xianmin Zhang;Xiaonan Hui;Yunfei Chen","doi":"10.1109/OJCOMS.2024.3479234","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3479234","url":null,"abstract":"Monostatic backscatter has garnered significant interest due to its distinct benefits in low-cost passive sensing. Observing and sensing with backscatter necessitates determining the phase and amplitude of the backscatter channel to identify the state of the target of interest. In the detection of multiple targets, colliding signals can distort the backscatter channel, complicating channel state recovery. It becomes even more challenging when multiple backscattering devices (BDs) are used. This paper proposes a novel channel estimation scheme to tackle the challenge, which is applied to a monostatic backscatter communication system with multiple reader antennas (RAs) and backscatter devices. Specifically, we propose a backscatter communication model and subsequently develop a de-interfering channel estimation framework that considers the ambient interference in the channel, named model-driven unfolded channel estimation (MUCE). To validate the effectiveness and advantages of the MUCE method, it is compared with the least square (LS) algorithm and convolutional neural network (CNN). The results prove that MUCE requires lower computational costs for the same channel estimation performance and achieves an optimal balance between estimation performance and computational expense.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10715725","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555114","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Multi-OLT Multi-Lane PON for 5G Fronthaul and Differential Services Through Access Class Priority-Based 2D Scheduling","authors":"Fahmida Rawshan;Monir Hossen;Md. Rafiqul Islam","doi":"10.1109/OJCOMS.2024.3479241","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3479241","url":null,"abstract":"Optical and wireless convergence is a quest of time. The rising bandwidth demand focuses on optical technology while increasing mobile bandwidth access requires wireless connectivity. Network convergence is a must to go through the solution. Multi-optical line terminal (multi-OLT) passive optical network (PON) has gained consideration for this solution for its widespread integration aptitudes. This paper proposes a multi-OLT multi-lane PON-based access network that provides service to the fifth-generation (5G) centralized radio access network (C-RAN) fronthaul on top of the existing access services. The design follows 100 Gb/s next-generation Ethernet passive optical network (NG-EPON) standards along with an optical network unit (ONU) structure to provoke dynamic channel bonding. A novel wavelength and bandwidth allocation scheme named access class priority-based 2D scheduling (ACP-2D) for upstream traffic is also designed. Computer simulations are performed to justify the performance of the ACP-2D scheme in a mini-slot-based 5G new radio (5G NR). Four different service providers (SPs) occupy four different OLTs. The services provided by the SPs are the Internet of Things (IoT), fiber-to-the-home (FTTH), wireless sensor network (WSN), and 5G. Simulation results show that 5G fronthaul traffic is successfully transmitted (owing to the full desired throughput of 0.798) within the 3GPP delay requirement of \u0000<inline-formula> <tex-math>$250~mu $ </tex-math></inline-formula>\u0000sec while maintaining other services. For example, the maximum FTTH service jitter is achieved to be \u0000<inline-formula> <tex-math>$0.26~mu $ </tex-math></inline-formula>\u0000sec for a maximum delay of \u0000<inline-formula> <tex-math>$546.94~mu $ </tex-math></inline-formula>\u0000sec at a mini-slot of \u0000<inline-formula> <tex-math>$250~mu $ </tex-math></inline-formula>\u0000sec. Network upstream bandwidth utilization is achieved by about 99.9%, which indicates a very small amount of network overhead. This innovative work signifies that multi-OLT PON can promote acceleration on the journey from C-RAN to open RAN.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10715724","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142517867","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Enhanced Hybrid TIM-TDMA to Maximize the Total Throughput With Fairness Constraints","authors":"David Jia;Xavier Leturc;Christophe J. Le Martret;Mohamad Assaad","doi":"10.1109/OJCOMS.2024.3480325","DOIUrl":"https://doi.org/10.1109/OJCOMS.2024.3480325","url":null,"abstract":"This paper addresses the problem of topological interference management (TIM) in ad hoc networks operating under a frequency-flat Rayleigh fading channel in single-input single-output (SISO). Assuming that the nodes have access to the statistical channel state information of the direct and interfering links, we introduce an extension of TIM referred to as enhanced TIM (eTIM) that maximizes an approximation of the expected average sum rate (EASR) when all the nodes communicate on the same channel. The drawback of eTIM is that it leads to poor fairness. By fairness, we mean in this paper ensuring a minimum average data rate for each user. To address this issue, we provide a second extension of the TIM, called eTIM-hybrid, by combining eTIM with time-division multiple access (TDMA) to improve both the EASR and the user fairness. The main idea of eTIM-hybrid involves partitioning the links into two groups: the “good links” on which we apply eTIM and “bad links” on which TDMA is used. Subsequently, a scheduling optimization phase optimizes the time allocation for each link within a given frame. We provide the closed-form expression of the optimal solution of the scheduling optimization to maximize eTIM-hybrid’s EASR while ensuring an expected average minimum user rate (EAMUR) for each link in the network. Additionally, we extend eTIM-hybrid to scenarios with two available channels by combining a novel channel allocation strategy with eTIM-hybrid, and called this method joint channel allocation eTIM-hybrid (JCA-eTIM-hy). Numerical results show that both eTIM-hybrid and JCA-eTIM-hy outperform the simulated state-of-the-art approaches in various scenarios in terms of EASR while satisfying an EAMUR constraint.","PeriodicalId":33803,"journal":{"name":"IEEE Open Journal of the Communications Society","volume":null,"pages":null},"PeriodicalIF":6.3,"publicationDate":"2024-10-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10716534","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142587628","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}