In recent years, many efforts have been devoted to reducing vehicles' energy consumption through optimizing their velocities. However, all previous methods neglect avoiding vehicle collision when calculating vehicles' optimal velocity profiles. In this paper, we formulate a new problem, called the Collision-Aware vehicle Energy consumption Minimization (CAEM) problem that calculates the optimal velocity profiles which avoid vehicle collision. CAEM is more difficult to solve than the traditional velocity optimization problem that is for a single vehicle, since CAEM needs to take into account the mobility of all the vehicles together to avoid collision. This problem is a convex problem that cannot be directly solved by existing methods. Further, it is impractical to get the mobility information of all vehicles at the beginning. Even if it is feasible, the computation efficiency is very low. We propose a novel method that can tackle these challenges. In order to keep each vehicle velocity as stable as possible to reduce the energy consumption, it builds a light schematic map to help identify the green light time interval of each traffic light in the source-destination route of a vehicle, during which the vehicle must drive through the traffic light. Rather than considering the mobility of all vehicles at a time, it calculates each vehicle's velocity profile in sequence based on the starting time to prevent the vehicle from colliding with all the previously scheduled vehicles. Finally, CAEM is transformed to non-convex problem and can be solved by existing optimization methods. Simulation and real-world testbed experimental results demonstrate the superior performance of our method over the previous methods.
{"title":"Cloud-Based Collision-Aware Energy-Minimization Vehicle Velocity Optimization","authors":"Chenxi Qiu, Haiying Shen","doi":"10.1109/MASS.2018.00026","DOIUrl":"https://doi.org/10.1109/MASS.2018.00026","url":null,"abstract":"In recent years, many efforts have been devoted to reducing vehicles' energy consumption through optimizing their velocities. However, all previous methods neglect avoiding vehicle collision when calculating vehicles' optimal velocity profiles. In this paper, we formulate a new problem, called the Collision-Aware vehicle Energy consumption Minimization (CAEM) problem that calculates the optimal velocity profiles which avoid vehicle collision. CAEM is more difficult to solve than the traditional velocity optimization problem that is for a single vehicle, since CAEM needs to take into account the mobility of all the vehicles together to avoid collision. This problem is a convex problem that cannot be directly solved by existing methods. Further, it is impractical to get the mobility information of all vehicles at the beginning. Even if it is feasible, the computation efficiency is very low. We propose a novel method that can tackle these challenges. In order to keep each vehicle velocity as stable as possible to reduce the energy consumption, it builds a light schematic map to help identify the green light time interval of each traffic light in the source-destination route of a vehicle, during which the vehicle must drive through the traffic light. Rather than considering the mobility of all vehicles at a time, it calculates each vehicle's velocity profile in sequence based on the starting time to prevent the vehicle from colliding with all the previously scheduled vehicles. Finally, CAEM is transformed to non-convex problem and can be solved by existing optimization methods. Simulation and real-world testbed experimental results demonstrate the superior performance of our method over the previous methods.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"122 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133944785","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}
Yinyin Gong, Lei Xie, Chuyu Wang, Yanling Bu, Sanglu Lu
Nowadays, novel approaches of 3D human-computer interaction have enabled the capability of manipulating in the 3D space rather than 2D space. For example, Microsoft Surface Pen leverages the embedded sensors to sense the 3D manipulations, such as inclining the pen to get bolder handwriting. In this paper, we propose RF-Brush, a battery-free and light-weight solution for 3D human-computer interaction based on RFID, by simply attaching a linear RFID tag array onto the linear shaped object like a brush. RF-Brush senses the 3D orientation and 2D movement of the linear shaped object, when the human subject is drawing with this object in the 3D space. Here, the 3D orientation refers to the relative orientation of the linear shaped object to the operating plane, whereas the 2D movement refers to the moving trace in the 2D operating plane. In this way, we are able to transform an ordinary linear shaped object like a brush or pen to an intelligent HCI device. Particularly, we build two geometric models to depict the relationship between the RF-signal and the 3D orientation as well as 2D movement, respectively. Based on the geometric model, we propose the linear tag array-based HCI solution, implemented a prototype system, and evaluated the performance in real environment. The experiments show that RF-Brush achieves an average error of 5.7° and 8.6° of elevation and azimuthal angle, respectively, and an average error of 3.8cm and 4.2cm in movement tracking along X-axis and Y-axis, respectively. Moreover, RF-Brush achieves 89% in letter recognition accuracy.
{"title":"RF-Brush: 3D Human-Computer Interaction via Linear Tag Array","authors":"Yinyin Gong, Lei Xie, Chuyu Wang, Yanling Bu, Sanglu Lu","doi":"10.1109/MASS.2018.00051","DOIUrl":"https://doi.org/10.1109/MASS.2018.00051","url":null,"abstract":"Nowadays, novel approaches of 3D human-computer interaction have enabled the capability of manipulating in the 3D space rather than 2D space. For example, Microsoft Surface Pen leverages the embedded sensors to sense the 3D manipulations, such as inclining the pen to get bolder handwriting. In this paper, we propose RF-Brush, a battery-free and light-weight solution for 3D human-computer interaction based on RFID, by simply attaching a linear RFID tag array onto the linear shaped object like a brush. RF-Brush senses the 3D orientation and 2D movement of the linear shaped object, when the human subject is drawing with this object in the 3D space. Here, the 3D orientation refers to the relative orientation of the linear shaped object to the operating plane, whereas the 2D movement refers to the moving trace in the 2D operating plane. In this way, we are able to transform an ordinary linear shaped object like a brush or pen to an intelligent HCI device. Particularly, we build two geometric models to depict the relationship between the RF-signal and the 3D orientation as well as 2D movement, respectively. Based on the geometric model, we propose the linear tag array-based HCI solution, implemented a prototype system, and evaluated the performance in real environment. The experiments show that RF-Brush achieves an average error of 5.7° and 8.6° of elevation and azimuthal angle, respectively, and an average error of 3.8cm and 4.2cm in movement tracking along X-axis and Y-axis, respectively. Moreover, RF-Brush achieves 89% in letter recognition accuracy.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"30 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134541006","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}
Xiangyun Meng, Daniel Lin-Kit Wong, B. Leong, Zixiao Wang, Yabo Dong, Dongming Lu
Duty-cycling is generally adopted in existing sensor networks to reduce power consumption and these networks depend on neighbor discovery protocols to ensure that nodes wake up and discover each other. For different neighbor discovery protocols, the discovery latency is determined by two factors: the wake-sleep pattern and slot size. To the best of our knowledge, previous works on neighbor discovery have thus far been focused on improving the wake-sleep pattern. In this paper, we investigate the extent to which we can improve discovery latency by reducing the slot size. We found that by reducing the slot size, i.e., reducing the listening time in active slots, the collisions between beacons and synchronization between nodes become more severe, which can lead to discovery failures that are not predicted by existing theoretical models. We show that we can mitigate these effects by reducing the number of beacons and introducing randomization. We propose a new continuous-listening-based neighbor discovery algorithm called Spotlight. Our evaluations with a practical sensor testbed suggest that Spotlight can achieve a 50% reduction in discovery latency over existing state-of-the-art neighbor discovery protocols without increasing power consumption in existing sensor networks.
{"title":"Improving Neighbor Discovery by Operating at the Quantum Scale","authors":"Xiangyun Meng, Daniel Lin-Kit Wong, B. Leong, Zixiao Wang, Yabo Dong, Dongming Lu","doi":"10.1109/MASS.2018.00041","DOIUrl":"https://doi.org/10.1109/MASS.2018.00041","url":null,"abstract":"Duty-cycling is generally adopted in existing sensor networks to reduce power consumption and these networks depend on neighbor discovery protocols to ensure that nodes wake up and discover each other. For different neighbor discovery protocols, the discovery latency is determined by two factors: the wake-sleep pattern and slot size. To the best of our knowledge, previous works on neighbor discovery have thus far been focused on improving the wake-sleep pattern. In this paper, we investigate the extent to which we can improve discovery latency by reducing the slot size. We found that by reducing the slot size, i.e., reducing the listening time in active slots, the collisions between beacons and synchronization between nodes become more severe, which can lead to discovery failures that are not predicted by existing theoretical models. We show that we can mitigate these effects by reducing the number of beacons and introducing randomization. We propose a new continuous-listening-based neighbor discovery algorithm called Spotlight. Our evaluations with a practical sensor testbed suggest that Spotlight can achieve a 50% reduction in discovery latency over existing state-of-the-art neighbor discovery protocols without increasing power consumption in existing sensor networks.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"104 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115659738","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}
Protocol format reverse engineering aims to extract the protocol fields automatically without access to the protocol specification. Existing works focus on the methodology of deriving the protocol format efficiently, but neglect the relationship between the statistical characteristics of protocol data and the intrinsic properties of the protocol format. In this paper, we study two problems to see how the protocol specification affects the statistical properties, and how the latter affect the difficulty of format reverse analysis. Through empirical analysis of known protocols, we first verify the stationarity of protocol features, which is the stand for developing trace-based reverse methods. We study the position arrangement and value distribution of protocol fields, and investigate their influence on the statistical properties of the protocol format. Then we propose an HMP-based model of protocol data. Using this model, we define two quantitative indicators by protocol fields' structure and content to reflect the reversibility of protocol format: the field non-interlacing ratio and the field information variation. We apply the analysis of format reversibility to a number of typical realistic protocols. The results suggest that the fields of most protocols can be partially revealed, but there are also certain fields difficult for reverse analysis. The quantitative results can provide hints for improving protocol reverse engineering approaches.
{"title":"Quantifying the Reversibility of Protocol Format","authors":"Zhengguo Xu, Ling You, Hui Zheng","doi":"10.1109/MASS.2018.00079","DOIUrl":"https://doi.org/10.1109/MASS.2018.00079","url":null,"abstract":"Protocol format reverse engineering aims to extract the protocol fields automatically without access to the protocol specification. Existing works focus on the methodology of deriving the protocol format efficiently, but neglect the relationship between the statistical characteristics of protocol data and the intrinsic properties of the protocol format. In this paper, we study two problems to see how the protocol specification affects the statistical properties, and how the latter affect the difficulty of format reverse analysis. Through empirical analysis of known protocols, we first verify the stationarity of protocol features, which is the stand for developing trace-based reverse methods. We study the position arrangement and value distribution of protocol fields, and investigate their influence on the statistical properties of the protocol format. Then we propose an HMP-based model of protocol data. Using this model, we define two quantitative indicators by protocol fields' structure and content to reflect the reversibility of protocol format: the field non-interlacing ratio and the field information variation. We apply the analysis of format reversibility to a number of typical realistic protocols. The results suggest that the fields of most protocols can be partially revealed, but there are also certain fields difficult for reverse analysis. The quantitative results can provide hints for improving protocol reverse engineering approaches.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124049313","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}
One of the major challenges in indoor localization is the matching difficulty and prediction accuracy of anchor points. In this work, we innovate in proposing a camera-based, sensorand WiFi-assisted, and easy-to-deploy system for localization. The proposed method is based on muliti-modal sensing to enhancing localization measurement. We implement a prototype with smartphones and commercial WiFi devices and evaluate it in distinct indoor environments. Experimental results show that the 85-percentile error is within 0.21m for indoor POIs that sheds light on sub-meter level localization.
{"title":"Enhancing Smartphone-Based Multi-modal Indoor Localization with Camera and WiFi Signal","authors":"Jing Xu, Yanchao Zhao, Jie Wu, Hongyan Qian","doi":"10.1109/MASS.2018.00031","DOIUrl":"https://doi.org/10.1109/MASS.2018.00031","url":null,"abstract":"One of the major challenges in indoor localization is the matching difficulty and prediction accuracy of anchor points. In this work, we innovate in proposing a camera-based, sensorand WiFi-assisted, and easy-to-deploy system for localization. The proposed method is based on muliti-modal sensing to enhancing localization measurement. We implement a prototype with smartphones and commercial WiFi devices and evaluate it in distinct indoor environments. Experimental results show that the 85-percentile error is within 0.21m for indoor POIs that sheds light on sub-meter level localization.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123643166","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}
VANET is emerging as a new landscape of mobile ad-hoc networks to make the connected vehicles' projects a reality. The continuous connectivity in VANET is a huge challenge caused by the extremely dynamic network topology and the highly variable number of mobile nodes. Moreover, this specific network faces many challenges to define reliable protocols and mechanisms like rate adaptation schemes. The performance of different VANET applications like traffic management and multimedia delivery depends on the network throughput and the success ratio these networks can provide. Rate adaptation is the key method to maximize the throughput and to avoid performance network degradation by estimating the current channel qualities and deciding the best bitrate for the next frames. Although numerous data rate adaptation mechanisms are available for 802.11 WLANs standards, there is little work dedicated to the IEEE 802.11p rate adaptation in vehicular networks. In this paper, we evaluate and compare the available 802.11 wireless networks rate adaptation mechanisms in various vehicular scenarios to analyze their performance and understand their behavior under different conditions. Five mechanisms were selected to be compared using NS-3 simulations: Minstrel, AARF-CD, CARA, Onoe, and Ideal algorithm. The performance results show that Minstrel is the most stable algorithm since it performs better in dynamic and dense environments when compared with the other algorithms.
{"title":"Performance Evaluation of Rate Adaptation Algorithms in IEEE802.11p Heterogeneous Vehicular Networks","authors":"A. Zekri, W. Jia","doi":"10.1109/MASS.2018.00025","DOIUrl":"https://doi.org/10.1109/MASS.2018.00025","url":null,"abstract":"VANET is emerging as a new landscape of mobile ad-hoc networks to make the connected vehicles' projects a reality. The continuous connectivity in VANET is a huge challenge caused by the extremely dynamic network topology and the highly variable number of mobile nodes. Moreover, this specific network faces many challenges to define reliable protocols and mechanisms like rate adaptation schemes. The performance of different VANET applications like traffic management and multimedia delivery depends on the network throughput and the success ratio these networks can provide. Rate adaptation is the key method to maximize the throughput and to avoid performance network degradation by estimating the current channel qualities and deciding the best bitrate for the next frames. Although numerous data rate adaptation mechanisms are available for 802.11 WLANs standards, there is little work dedicated to the IEEE 802.11p rate adaptation in vehicular networks. In this paper, we evaluate and compare the available 802.11 wireless networks rate adaptation mechanisms in various vehicular scenarios to analyze their performance and understand their behavior under different conditions. Five mechanisms were selected to be compared using NS-3 simulations: Minstrel, AARF-CD, CARA, Onoe, and Ideal algorithm. The performance results show that Minstrel is the most stable algorithm since it performs better in dynamic and dense environments when compared with the other algorithms.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"102 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116665848","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}
This paper proposed an advanced round modification fault analysis (RMFA) at the theoretical level on AEGIS-128, which is one of seven finalists in CAESAR competition. First, we clarify our assumptions and simplifications on the attack model, focusing on the encryption security. Then, we emphasize the difficulty of applying vanilla RMFA to AEGIS-128 in the practical case. Finally we demonstrate our advanced fault analysis on AEGIS-128 using machine-solver based algebraic techniques. Our enhancement can be used to conquer the practical scenario which is difficult for vanilla RMFA. Simulation results show that when the fault is injected to the initialization phase and the number of rounds is reduced to one, two samples of injections can extract the whole 128 key bits within less than two hours. This work can also be extended to other versions such as AEGIS-256.
{"title":"Theoretical Round Modification Fault Analysis on AEGIS-128 with Algebraic Techniques","authors":"Fan Zhang, Xiaofei Dong, Xin-jie Zhao, Yidi Wang, Samiya Qureshi, Yiran Zhang, Xiaoxuan Lou, Yongkang Tang","doi":"10.1109/MASS.2018.00056","DOIUrl":"https://doi.org/10.1109/MASS.2018.00056","url":null,"abstract":"This paper proposed an advanced round modification fault analysis (RMFA) at the theoretical level on AEGIS-128, which is one of seven finalists in CAESAR competition. First, we clarify our assumptions and simplifications on the attack model, focusing on the encryption security. Then, we emphasize the difficulty of applying vanilla RMFA to AEGIS-128 in the practical case. Finally we demonstrate our advanced fault analysis on AEGIS-128 using machine-solver based algebraic techniques. Our enhancement can be used to conquer the practical scenario which is difficult for vanilla RMFA. Simulation results show that when the fault is injected to the initialization phase and the number of rounds is reduced to one, two samples of injections can extract the whole 128 key bits within less than two hours. This work can also be extended to other versions such as AEGIS-256.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115449959","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}
Dimitris Chatzopoulos, Sujit Gujar, B. Faltings, P. Hui
The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the mobile users who contribute their resources and preserve their privacy. Blockchain technologies enable semi-anonymous multi-party interactions and can be utilized in crowdsensing applications to maintain the privacy of the mobile users while ensuring first-rate crowdsensed data. In this work, we propose to use blockchain technologies and smart contracts to orchestrate the interactions between mobile crowdsensing providers and mobile users for the case of spatial crowdsensing, where mobile users need to be at specific locations to perform the tasks. Smart contracts, by operating as processes that are executed on the blockchain, are used to preserve users' privacy and make payments. Furthermore, for the assignment of the crowdsensing tasks to the mobile users, we design a truthful, cost-optimal auction that minimizes the payments from the crowdsensing providers to the mobile users. Extensive experimental results show that the proposed privacy preserving auction outperforms state-of-the-art proposals regarding cost by ten times for high numbers of mobile users and tasks.
{"title":"Privacy Preserving and Cost Optimal Mobile Crowdsensing Using Smart Contracts on Blockchain","authors":"Dimitris Chatzopoulos, Sujit Gujar, B. Faltings, P. Hui","doi":"10.1109/MASS.2018.00068","DOIUrl":"https://doi.org/10.1109/MASS.2018.00068","url":null,"abstract":"The popularity and applicability of mobile crowdsensing applications are continuously increasing due to the widespread of mobile devices and their sensing and processing capabilities. However, we need to offer appropriate incentives to the mobile users who contribute their resources and preserve their privacy. Blockchain technologies enable semi-anonymous multi-party interactions and can be utilized in crowdsensing applications to maintain the privacy of the mobile users while ensuring first-rate crowdsensed data. In this work, we propose to use blockchain technologies and smart contracts to orchestrate the interactions between mobile crowdsensing providers and mobile users for the case of spatial crowdsensing, where mobile users need to be at specific locations to perform the tasks. Smart contracts, by operating as processes that are executed on the blockchain, are used to preserve users' privacy and make payments. Furthermore, for the assignment of the crowdsensing tasks to the mobile users, we design a truthful, cost-optimal auction that minimizes the payments from the crowdsensing providers to the mobile users. Extensive experimental results show that the proposed privacy preserving auction outperforms state-of-the-art proposals regarding cost by ten times for high numbers of mobile users and tasks.","PeriodicalId":146214,"journal":{"name":"2018 IEEE 15th International Conference on Mobile Ad Hoc and Sensor Systems (MASS)","volume":"91 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-08-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124669891","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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