Co-Attention Hierarchical Network: Generating Coherent Long Distractors for Reading Comprehension

In reading comprehension, generating sentence-level distractors is a significant task, which requires a deep understanding of the article and question. The traditional entity-centered methods can only generate word-level or phrase-level distractors. Although recently proposed neural-based methods like sequence-to-sequence (Seq2Seq) model show great potential in generating creative text, the previous neural methods for distractor generation ignore two important aspects. First, they didn't model the interactions between the article and question, making the generated distractors tend to be too general or not relevant to question context. Second, they didn't emphasize the relationship between the distractor and article, making the generated distractors not semantically relevant to the article and thus fail to form a set of meaningful options. To solve the first problem, we propose a co-attention enhanced hierarchical architecture to better capture the interactions between the article and question, thus guide the decoder to generate more coherent distractors. To alleviate the second problem, we add an additional semantic similarity loss to push the generated distractors more relevant to the article. Experimental results show that our model outperforms several strong baselines on automatic metrics, achieving state-of-the-art performance. Further human evaluation indicates that our generated distractors are more coherent and more educative compared with those distractors generated by baselines.Comment: 8 pages, 3 figures. Accepted by AAAI202

A QoS-aware cache replacement policy for Vehicular Named Data Networks

International audienceVehicular Named Data Network (VNDN) uses Named Data Network (NDN) as a communication enabler. The communication is achieved using the content name instead of the host address. NDN integrates content caching at the network level rather than the application level. Hence, the network becomes aware of content caching and delivering. The content caching is a fundamental element in VNDN communication. However, due to the limitations of the cache store, only the most used content should be cached while the less used should be evicted. Traditional caching replacement policies may not work efficiently in VNDN due to the large and diverse exchanged content. To solve this issue, we propose an efficient cache replacement policy that takes the quality of service into consideration. The idea consists of classifying the traffic into different classes, and split the cache store into a set of sub-cache stores according to the defined traffic classes with different storage capacities according to the network requirements. Each content is assigned a popularity-density value that balances the content popularity with its size. Content with the highest popularity-density value is cached while the lowest is evicted. Simulation results prove the efficiency of the proposed solution to enhance the overall network quality of service

Named Data Networking in Vehicular Ad hoc Networks: State-of-the-Art and Challenges

International audienceInformation-Centric Networking (ICN) has been proposed as one of the future Internet architectures. It is poised to address the challenges faced by today's Internet that include, but not limited to, scalability, addressing, security, and privacy. Furthermore, it also aims at meeting the requirements for new emerging Internet applications. To realize ICN, Named Data Networking (NDN) is one of the recent implementations of ICN that provides a suitable communication approach due to its clean slate design and simple communication model. There are a plethora of applications realized through ICN in different domains where data is the focal point of communication. One such domain is Intelligent Transportation System (ITS) realized through Vehicular Ad hoc NETwork (VANET) where vehicles exchange information and content with each other and with the infrastructure. To date, excellent research results have been yielded in the VANET domain aiming at safe, reliable, and infotainment-rich driving experience. However, due to the dynamic topologies, host-centric model, and ephemeral nature of vehicular communication, various challenges are faced by VANET that hinder the realization of successful vehicular networks and adversely affect the data dissemination, content delivery, and user experiences. To fill these gaps, NDN has been extensively used as underlying communication paradigm for VANET. Inspired by the extensive research results in NDN-based VANET, in this paper, we provide a detailed and systematic review of NDN-driven VANET. More precisely, we investigate the role of NDN in VANET and discuss the feasibility of NDN architecture in VANET environment. Subsequently, we cover in detail, NDN-based naming, routing and forwarding, caching, mobility, and security mechanism for VANET. Furthermore, we discuss the existing standards, solutions, and simulation tools used in NDN-based VANET. Finally, we also identify open challenges and issues faced by NDN-driven VANET and highlight future research directions that should be addressed by the research community

Efficient Opinion Summarization on Comments with Online-LDA

Customer reviews and comments on web pages are important information n our daily life. For example, we prefer to choose a hotel with positive comments rom previous customers. As the huge amounts of such information demonstrate the haracteristics of big data, it places heavy burdens on the assimilation of the customercontributed pinions. To overcoming this problem, we study an efficient opinion ummarization approach for a set of massive user reviews and comments associated ith an online resource, to summarize the opinions into two categories, i.e., positive nd negative. In this paper, we proposed a framework including: (1) overcoming the ig data problem of online comments using the efficient online-LDA approach; (2) electing meaningful topics from the imbalanced data; (3) summarizing the opinion f comments with high precision and recall. This framework is different from much f the previous work in that the topics are pre-defined and selected the topics for etter opinion summarization. To evaluate the proposed framework, we perform the xperiments on a dataset of hotel reviews for the variety of topics contained. The esults show that our framework can gain a significant performance improvement on pinion summarization

The characteristics of impaired fasting glucose associated with obesity and dyslipidaemia in a Chinese population

<p>Abstract</p> <p>Background</p> <p>Different populations have diverse patterns of relationships between Impaired Fasting Glucose (IFG) and obesity and lipid markers, it is important to investigate the characteristics of associations between IFG and other related risk factors including body mass index (BMI), waist circumstance (WC), serum lipids and blood pressure (BP) in a Chinese population.</p> <p>Methods</p> <p>This was a case-control study of 648 IFG subjects and 1,296 controls derived from a large-scale, community-based, cross-sectional survey of 10,867 participants. Each subject received a face-to-face interview, physical examination, and blood tests, including fasting blood glucose and lipids. Student's <it>t</it>-test, Chi-square test, Spearman correlation and multiple logistic regressions were used for the statistical analyses.</p> <p>Results</p> <p>Fasting plasma glucose (FPG) was positively correlated with BMI, WC, systolic blood pressure (SBP), diastolic blood pressure (DBP), triglyceride (TG), and total cholesterol (TC), and was negatively correlated with high density lipoprotein-cholesterol (HDL-C) (all p < 0.05). BMI was more strongly correlated with IFG than with WC. The correlation coefficient of FPG was remarkably higher with TG (0.244) than with TC (0.134) and HDL-C (-0.192). TG was an important predictor of IFG, with odds ratios of 1.76 (95%CI: 1.31-2.36) for subjects with borderline high TG level (1.70 mmol/l ≤ TG < 2.26 mmol/l) and 3.13 (95% CI: 2.50-3.91) for those with higher TG level (TG ≥ 2.26 mmol/l), when comparing to subjects with TG < 1.70 mmol/l. There was a significant dose-response relationship between the number of abnormal variables and increased risk of IFG.</p> <p>Conclusions</p> <p>In this Chinese population, both BMI and WC were important predictors of IFG. Abnormal TG as a lipid marker was more strongly associated with IFG than were TC and HDL-C. These factors should be taken into consideration simultaneously for prevention of IFG.</p

A QoS-aware cache replacement policy for Vehicular Named Data Networks

International audienceVehicular Named Data Network (VNDN) uses Named Data Network (NDN) as a communication enabler. The communication is achieved using the content name instead of the host address. NDN integrates content caching at the network level rather than the application level. Hence, the network becomes aware of content caching and delivering. The content caching is a fundamental element in VNDN communication. However, due to the limitations of the cache store, only the most used content should be cached while the less used should be evicted. Traditional caching replacement policies may not work efficiently in VNDN due to the large and diverse exchanged content. To solve this issue, we propose an efficient cache replacement policy that takes the quality of service into consideration. The idea consists of classifying the traffic into different classes, and split the cache store into a set of sub-cache stores according to the defined traffic classes with different storage capacities according to the network requirements. Each content is assigned a popularity-density value that balances the content popularity with its size. Content with the highest popularity-density value is cached while the lowest is evicted. Simulation results prove the efficiency of the proposed solution to enhance the overall network quality of service

Impact-Based Electromagnetic Energy Harvester with High Output Voltage under Low-Level Excitations

To expand the applications of vibrational energy harvesters (VEHs) as power sources of wireless sensor nodes, it is of significance to improve the scavenging efficiency for the broadband, low-frequency, and low-level vibrational energy. The output voltages of electromagnetic vibrational energy harvesters (EMVEHs) are usually low, which complicates the power management circuit by an indispensable voltage boosting element. To this end, an impact-based non-resonant EMVEH mainly composed of an outer frame and an inner frame on rollers is proposed. Numerical simulations based on a mathematical model of the harvester are conducted to analyze the effects of structural parameters on the output performance. Under base excitation of 0.1 and 0.3 (where g is the gravitational acceleration, 1 g = 9.8 m · s − 2 ), the experimental maximum root mean square voltages of a harvester prototype across a resistor of 11 kΩ are as high as 7.6 and 16.5 V at 6.0 and 8.5 Hz, respectively, with the maximum output powers of 5.3 and 24.8 mW, or the power densities of 54.6 and 256 μW cm−3. By using a management circuit without a voltage boosting element, a wireless sensor node driven by the prototype can measure and transmit the temperature and humidity every 20 s under base excitation of 0.1 g at 5.4 Hz

LQCC: a Link Quality-based Congestion Control scheme in named data networks

International audienceInformation-Centric Networking (ICN) is a new communication paradigm that replaces the host addresses by the name of content; Named Data Networking (NDN) is a promising ICN architecture that has attracted research attention in recent years. NDN is a receiver-driven architecture implements pull-based communication in the form of one-interest-one-data. This model poses different challenges, especially from the transport layer perspective. In contact to IP-based networks where the congestion is handled in an end-to-end manner, NDN cannot apply the same concept, while most of the existing solutions are based on hop-by-hop connection. In this paper, we present a new congestion control mechanism for NDN based on link quality estimation. We focus our efforts to provide fast data transmission, decrease packet dropping rate, and maximize the link utilization. The simulation results show that our solution outperforms the NDN schemes in terms of throughput and drop packets

A Name-to-Hash Encoding scheme for vehicular named data networks

International Wireless Communications & Mobile Computing Conference (IWCMC), June 2019, Tangier, MoroccoInternational audienceIn contrast to the host-centric model where the communication is directed using the destination address, Information-Centric Networking (ICN) adopts the content name as the pillar network element to provide data discovery and delivery process, as well as in other network functionalities. Named Data Networking (NDN) is an active ICN project that uses hierarchical unbounded names. These names are used in both interest and data packets and other data structures that may consume more memory with long lookup time. This paper targets the naming aspect in vehicular named data networks and proposes a Name-to-Hash Encoding scheme. The idea consists of hashing each name components separately to a fixed length, then perform a heuristic Wu-Manber-like algorithm lookup process. The former process enhances the NDN to consume less memory compared to hierarchical names, the latter process provides a fast lookup time. We have evaluated the proposed scheme against different related solutions using real domain datasets. Both theoretical analysis and experiments prove that the proposed scheme is efficient in terms of complexity, memory consumption, and lookup time

Security and Privacy Issues in Vehicular Named Data Networks: An Overview

A tremendous amount of content and information are exchanging in a vehicular environment between vehicles, roadside units, and the Internet. This information aims to improve the driving experience and human safety. Due to the VANET’s properties and application characteristics, the security becomes an essential aspect and a more challenging task. On the contrary, named data networking has been proposed as a future Internet architecture that may improve the network performance, enhance content access and dissemination, and decrease the communication delay. NDN uses a clean design based on content names and Interest-Data exchange model. In this paper, we focus on the vehicular named data networking environment, targeting the security attacks and privacy issues. We present a state of the art of existing VANET attacks and how NDN can deal with them. We classified these attacks based on the NDN perspective. Furthermore, we define various challenges and issues faced by NDN-based VANET and highlight future research directions that should be addressed by the research community