3,542 research outputs found

    A Complete Equivalent Circuit for Linear Induction Motors With Laterally Asymmetric Secondary for Urban Railway Transit

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    Since the linear induction motor commonly work with a laterally asymmetric secondary as it is applied to pull rail vehicles, this paper presents a complete equivalent circuit model considering the asymmetry to predict thrust, vertical and transversal forces. First, six correction factors are presented to quantify the variations in the air-gap magnetic flux and secondary induced current as the linear induction motor operating with a laterally asymmetric secondary. Second, it develops a circuit model based on the existing T-model for the rotary induction motor and two correction factors for the magnetizing branch, which is used to indicate the electromagnetic variations in the air-gap flux and secondary plate due to the asymmetry. Third, the mathematical expressions for the thrust, vertical and transversal forces are derived by applying the equivalent circuit model. Then, the six correction factors are calculated with a prototype motor, and the results of them are comprehensively analyzed. Finally, the characteristics in the prototype motor are calculated with the mathematical expressions in a range of rated speed,and validated by the experimental measurements carried out on a test rig and line for linear motors

    A survey of spatial crowdsourcing

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    Efficient and Private Federated Trajectory Matching

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    Federated Trajectory Matching (FTM) is gaining increasing importance in big trajectory data analytics, supporting diverse applications such as public health, law enforcement, and emergency response. FTM retrieves trajectories that match with a query trajectory from a large-scale trajectory database, while safeguarding the privacy of trajectories in both the query and the database. A naive solution to FTM is to process the query through Secure Multi-Party Computation (SMC) across the entire database, which is inherently secure yet inevitably slow due to the massive secure operations. A promising acceleration strategy is to filter irrelevant trajectories from the database based on the query, thus reducing the SMC operations. However, a key challenge is how to publish the query in a way that both preserves privacy and enables efficient trajectory filtering. In this paper, we design GIST, a novel framework for efficient Federated Trajectory Matching. GIST is grounded in Geo-Indistinguishability, a privacy criterion dedicated to locations. It employs a new privacy mechanism for the query that facilitates efficient trajectory filtering. We theoretically prove the privacy guarantee of the mechanism and the accuracy of the filtering strategy of GIST. Extensive evaluations on five real datasets show that GIST is significantly faster and incurs up to 3 orders of magnitude lower communication cost than the state-of-the-arts.Comment: 14 page

    Preference-aware task assignment in on-demand taxi dispatching: An online stable matching approach

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    A central issue in on-demand taxi dispatching platforms is task assignment, which designs matching policies among dynamically arrived drivers (workers) and passengers (tasks). Previous matching policies maximize the profit of the platform without considering the preferences of workers and tasks (e.g., workers may prefer high-rewarding tasks while tasks may prefer nearby workers). Such ignorance of preferences impairs user experience and will decrease the profit of the platform in the long run. To address this problem, we propose preference-aware task assignment using online stable matching. Specifically, we define a new model, Online Stable Matching under Known Identical Independent Distributions (OSM-KIID). It not only maximizes the expected total profits (OBJ-1), but also tries to satisfy the preferences among workers and tasks by minimizing the expected total number of blocking pairs (OBJ-2). The model also features a practical arrival assumption validated on real-world dataset. Furthermore, we present a linear program based online algorithm LP-ALG, which achieves an online ratio of at least 1−1/e on OBJ-1 and has at most 0.6·|E| blocking pairs expectedly, where |E| is the total number of edges in the compatible graph. We also show that a natural Greedy can have an arbitrarily bad performance on OBJ-1 while maintaining around 0.5·|E| blocking pairs. Evaluations on both synthetic and real datasets confirm our theoretical analysis and demonstrate that LP-ALG strictly dominates all the baselines on both objectives when tasks notably outnumber workers

    De Novo Transcriptome of the Hemimetabolous German Cockroach (\u3ci\u3eBlattella germanica\u3c/i\u3e)

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    Background: The German cockroach, Blattella germanica, is an important insect pest that transmits various pathogens mechanically and causes severe allergic diseases. This insect has long served as a model system for studies of insect biology, physiology and ecology. However, the lack of genome or transcriptome information heavily hinder our further understanding about the German cockroach in every aspect at a molecular level and on a genome-wide scale. To explore the transcriptome and identify unique sequences of interest, we subjected the B. germanica transcriptome to massively parallel pyrosequencing and generated the first reference transcriptome for B. germanica. Methodology/Principal Findings: A total of 1,365,609 raw reads with an average length of 529 bp were generated via pyrosequencing the mixed cDNA library from different life stages of German cockroach including maturing oothecae, nymphs, adult females and males. The raw reads were de novo assembled to 48,800 contigs and 3,961 singletons with highquality unique sequences. These sequences were annotated and classified functionally in terms of BLAST, GO and KEGG, and the genes putatively coding detoxification enzyme systems, insecticide targets, key components in systematic RNA interference, immunity and chemoreception pathways were identified. A total of 3,601 SSRs (Simple Sequence Repeats) loci were also predicted. Conclusions/Significance: The whole transcriptome pyrosequencing data from this study provides a usable genetic resource for future identification of potential functional genes involved in various biological processes

    De Novo Transcriptome of the Hemimetabolous German Cockroach (\u3ci\u3eBlattella germanica\u3c/i\u3e)

    Get PDF
    Background: The German cockroach, Blattella germanica, is an important insect pest that transmits various pathogens mechanically and causes severe allergic diseases. This insect has long served as a model system for studies of insect biology, physiology and ecology. However, the lack of genome or transcriptome information heavily hinder our further understanding about the German cockroach in every aspect at a molecular level and on a genome-wide scale. To explore the transcriptome and identify unique sequences of interest, we subjected the B. germanica transcriptome to massively parallel pyrosequencing and generated the first reference transcriptome for B. germanica. Methodology/Principal Findings: A total of 1,365,609 raw reads with an average length of 529 bp were generated via pyrosequencing the mixed cDNA library from different life stages of German cockroach including maturing oothecae, nymphs, adult females and males. The raw reads were de novo assembled to 48,800 contigs and 3,961 singletons with highquality unique sequences. These sequences were annotated and classified functionally in terms of BLAST, GO and KEGG, and the genes putatively coding detoxification enzyme systems, insecticide targets, key components in systematic RNA interference, immunity and chemoreception pathways were identified. A total of 3,601 SSRs (Simple Sequence Repeats) loci were also predicted. Conclusions/Significance: The whole transcriptome pyrosequencing data from this study provides a usable genetic resource for future identification of potential functional genes involved in various biological processes
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