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Qing Wang

Publications and source records attributed to Qing Wang.

At least 379 records · Page 21Linked to original sources
arXiv2018

Developing a Temporal Bibliographic Data Set for Entity Resolution

Entity resolution is the process of identifying groups of records within or across data sets where each group represents a real-world entity. Novel techniques that consider temporal features to improve the quality of entity resolution have recently attracted significant attention. However, there are currently no large data sets available that contain both temporal information as well as ground truth information to evaluate the quality of temporal entity resolution approaches. In this paper, we describe the preparation of a temporal data set based on author profiles extracted from the Digital Bibliography and Library Project (DBLP). We completed missing links between publications and author profiles in the DBLP data set using the DBLP public API. We then used the Microsoft Academic Graph (MAG) to link temporal affiliation information for DBLP authors. We selected around 80K (1%) of author profiles that cover 2 million (50%) publications using information in DBLP such as alternative author names and personal web profile to improve the reliability of the resulting ground truth, while at the same time keeping the data set challenging for temporal entity resolution research.

cs.DB↗
arXiv2018

End-to-end driving simulation via angle branched network

Imitation learning for end-to-end autonomous driving has drawn attention from academic communities. Current methods either only use images as the input which is ambiguous when a car approaches an intersection, or use additional command information to navigate the vehicle but not automated enough. Focusing on making the vehicle drive along the given path, we propose a new navigation command that does not require human's participation and a novel model architecture called angle branched network. Both the new navigation command and the angle branched network are easy to understand and effective. Besides, we find that not only segmentation information but also depth information can boost the performance of the driving model. We conduct experiments in a 3D urban simulator and both qualitative and quantitative evaluation results show the effectiveness of our model.

cs.CV↗
arXiv2018

Crowdtesting : When is The Party Over?

Trade-offs such as "how much testing is enough" are critical yet challenging project decisions in software engineering. Most existing approaches adopt risk-driven or value-based analysis to prioritize test cases and minimize test runs. However, none of these is applicable to the emerging crowd testing paradigm where task requesters typically have no control over online crowdworkers's dynamic behavior and uncertain performance. In current practice, deciding when to close a crowdtesting task is largely done by guesswork due to lack of decision support. This paper intends to fill this gap by introducing automated decision support for monitoring and determining appropriate time to close the crowdtesting tasks. First, this paper investigates the necessity and feasibility of close prediction of crowdtesting tasks based on industrial dataset. Then,it designs 8 methods for close prediction, based on various models including the bug trend, bug arrival model, capture-recapture model.Finally, the evaluation is conducted on 218 crowdtesting tasks from one of the largest crowdtesting platforms in China, and the results show that a median of 91% bugs can be detected with 49% saved cost.

cs.SE↗
arXiv2018

Effective Automated Decision Support for Managing Crowdtesting

Crowdtesting has grown to be an effective alter-native to traditional testing, especially in mobile apps. However,crowdtesting is hard to manage in nature. Given the complexity of mobile applications and unpredictability of distributed, parallel crowdtesting process, it is difficult to estimate (a) the remaining number of bugs as yet undetected or (b) the required cost to find those bugs. Experience-based decisions may result in ineffective crowdtesting process. This paper aims at exploring automated decision support to effectively manage crowdtesting process. The proposed ISENSE applies incremental sampling technique to process crowdtesting reports arriving in chronological order, organizes them into fixed-size groups as dynamic inputs, and predicts two test completion indicators in an incrementally manner. The two indicators are: 1)total number of bugs predicted with Capture-ReCapture (CRC)model, and 2) required test cost for achieving certain test objectives predicted with AutoRegressive Integrated Moving Average(ARIMA) model. We assess ISENSE using 46,434 reports of 218 crowdtesting tasks from one of the largest crowdtesting platforms in China. Its effectiveness is demonstrated through two applications for automating crowdtesting management, i.e. automation oftask closing decision, and semi-automation of task closing trade-off analysis. The results show that decision automation using ISENSE will provide managers with greater opportunities to achieve cost-effectiveness gains of crowdtesting. Specifically, a median of 100% bugs can be detected with 30% saved cost basedon the automated close prediction

cs.SE↗
arXiv2018

NeuroStorm: Accelerating Brain Science Discovery in the Cloud

Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales. However, our ability to capitalize on existing datasets, tools, and intellectual capacities is hampered by technical challenges. The key barriers to accelerating scientific discovery correspond to the FAIR data principles: findability, global access to data, software interoperability, and reproducibility/re-usability. We conducted a hackathon dedicated to making strides in those steps. This manuscript is a technical report summarizing these achievements, and we hope serves as an example of the effectiveness of focused, deliberate hackathons towards the advancement of our quickly-evolving field.

q-bio.OT↗
arXiv2018

On Harish-Chandra modules of the Lie algebra arising from the $2$-Dimensional Torus

Let $A=\mathbb{C}[t_1^{\pm1},t_2^{\pm1}]$ be the algebra of Laurent polynomials in two variables and $B$ be the set of skew derivations of $A$. Let $L$ be the universal central extension of the derived Lie subalgebra of the Lie algebra $A\rtimes B$. Set $\widetilde{L}=L\oplus\mathbb{C} d_1\oplus\mathbb{C} d_2$, where $d_1$, $d_2$ are two degree derivations. A Harish-Chandra module is defined as an irreducible weight module with finite dimensional weight spaces. In this paper, we prove that a Harish-Chandra module of the Lie algebra $\widetilde{L}$ is a uniformly bounded module or a generalized highest weight (GHW for short) module. Furthermore, we prove that the nonzero level Harish-Chandra modules of $\widetilde{L}$ are GHW modules. Finally, we classify all the GHW Harish-Chandra modules of $\widetilde{L}$.

math.RT↗
arXiv2017

Light Field Segmentation From Super-pixel Graph Representation

Efficient and accurate segmentation of light field is an important task in computer vision and graphics. The large volume of input data and the redundancy of light field make it an open challenge. In the paper, we propose a novel graph representation for interactive light field segmentation based on light field super-pixel (LFSP). The LFSP not only maintains light field redundancy, but also greatly reduces the graph size. These advantages make LFSP useful to improve segmentation efficiency. Based on LFSP graph structure, we present an efficient light field segmentation algorithm using graph-cuts. Experimental results on both synthetic and real dataset demonstrate that our method is superior to previous light field segmentation algorithms with respect to accuracy and efficiency.

cs.CV↗
arXiv2017

Derivation of the gap and Bethe-Salpeter equations at large $N_c$ limit and symmetry preserving truncations

We develop a framework for deriving Dyson-Schwinger Equations (DSEs) and Bethe-Salpeter Equation (BSE) in QCD at large $N_c$ limit. The starting point is a modified form (with auxiliary fields) of QCD generating functional. This framework provides a natural order-by-order truncation scheme for DSEs and BSE, and the kernels of the equations up to any order are explicitly given. Chiral symmetry (at chiral limit) is preserved in any order truncation, so it exemplifies the symmetry preserving truncation scheme. It provides a method to study DSEs and BSE beyond the Rainbow-Ladder truncation, and is especially useful to study contributions from non-Abelian dynamics (those arise from gluon self-interactions). We also derive the equation for the quark-ghost scattering kernel, and discuss the Slavnov-Taylor identity connecting the quark-gluon vertex, the quark propagator and the quark-ghost scattering kernel.

hep-th↗
arXiv2017

TARN: A SDN-based Traffic Analysis Resistant Network Architecture

Destination IP prefix-based routing protocols are core to Internet routing today. Internet autonomous systems (AS) possess fixed IP prefixes, while packets carry the intended destination AS's prefix in their headers, in clear text. As a result, network communications can be easily identified using IP addresses and become targets of a wide variety of attacks, such as DNS/IP filtering, distributed Denial-of-Service (DDoS) attacks, man-in-the-middle (MITM) attacks, etc. In this work, we explore an alternative network architecture that fundamentally removes such vulnerabilities by disassociating the relationship between IP prefixes and destination networks, and by allowing any end-to-end communication session to have dynamic, short-lived, and pseudo-random IP addresses drawn from a range of IP prefixes rather than one. The concept is seemingly impossible to realize in todays Internet. We demonstrate how this is doable today with three different strategies using software defined networking (SDN), and how this can be done at scale to transform the Internet addressing and routing paradigms with the novel concept of a distributed software defined Internet exchange (SDX). The solution works with both IPv4 and IPv6, whereas the latter provides higher degrees of IP addressing freedom. Prototypes based on OpenvSwitches (OVS) have been implemented for experimentation across the PEERING BGP testbed. The SDX solution not only provides a technically sustainable pathway towards large-scale traffic analysis resistant network (TARN) support, it also unveils a new business model for customer driven, customizable and trustable end-to-end network services.

cs.NI↗
arXiv2017

q-Virasoro algebra and affine Kac-Moody Lie algebras

We establish a natural connection of the $q$-Virasoro algebra $D_{q}$ introduced by Belov and Chaltikian with affine Kac-Moody Lie algebras. More specifically, for each abelian group $S$ together with a one-to-one linear character $χ$, we define an infinite-dimensional Lie algebra $D_{S}$ which reduces to $D_{q}$ when $S=\mathbb{Z}$. Guided by the theory of equivariant quasi modules for vertex algebras, we introduce another Lie algebra ${\mathfrak{g}}_{S}$ with $S$ as an automorphism group and we prove that $D_{S}$ is isomorphic to the $S$-covariant algebra of the affine Lie algebra $\widehat{\mathfrak{g}_{S}}$. We then relate restricted $D_{S}$-modules of level $\ell\in \mathbb{C}$ to equivariant quasi modules for the vertex algebra $V_{\widehat{\mathfrak{g}_{S}}}(\ell,0)$ associated to $\widehat{\mathfrak{g}_{S}}$ with level $\ell$. Furthermore, we show that if $S$ is a finite abelian group of order $2l+1$, $D_{S}$ is isomorphic to the affine Kac-Moody algebra of type $B^{(1)}_{l}$.

math.QA↗
arXiv2017

Online Interactive Collaborative Filtering Using Multi-Armed Bandit with Dependent Arms

Online interactive recommender systems strive to promptly suggest to consumers appropriate items (e.g., movies, news articles) according to the current context including both the consumer and item content information. However, such context information is often unavailable in practice for the recommendation, where only the users' interaction data on items can be utilized. Moreover, the lack of interaction records, especially for new users and items, worsens the performance of recommendation further. To address these issues, collaborative filtering (CF), one of the recommendation techniques relying on the interaction data only, as well as the online multi-armed bandit mechanisms, capable of achieving the balance between exploitation and exploration, are adopted in the online interactive recommendation settings, by assuming independent items (i.e., arms). Nonetheless, the assumption rarely holds in reality, since the real-world items tend to be correlated with each other (e.g., two articles with similar topics). In this paper, we study online interactive collaborative filtering problems by considering the dependencies among items. We explicitly formulate the item dependencies as the clusters on arms, where the arms within a single cluster share the similar latent topics. In light of the topic modeling techniques, we come up with a generative model to generate the items from their underlying topics. Furthermore, an efficient online algorithm based on particle learning is developed for inferring both latent parameters and states of our model. Additionally, our inferred model can be naturally integrated with existing multi-armed selection strategies in the online interactive collaborating setting. Empirical studies on two real-world applications, online recommendations of movies and news, demonstrate both the effectiveness and efficiency of the proposed approach.

cs.IR↗
arXiv2017

Orderness Predicts Academic Performance: Behavioral Analysis on Campus Lifestyle

Quantitative understanding of relationships between students' behavioral patterns and academic performances is a significant step towards personalized education. In contrast to previous studies that mainly based on questionnaire surveys, in this paper, we collect behavioral records from 18,960 undergraduate students' smart cards and propose a novel metric, called orderness, which measures the regularity of campus daily life (e.g., meals and showers) of each student. Empirical analysis demonstrates that academic performance (GPA) is strongly correlated with orderness. Furthermore, we show that orderness is an important feature to predict academic performance, which remarkably improves the prediction accuracy even at the presence of students' diligence. Based on these analyses, education administrators could better guide students' campus lives and implement effective interventions in an early stage when necessary.

physics.soc-ph↗
arXiv2017

Serialisable Multi-Level Transaction Control: A Specification and Verification

We define a programming language independent controller TaCtl for multi-level transactions and an operator $TA$, which when applied to concurrent programs with multi-level shared locations containing hierarchically structured complex values, turns their behavior with respect to some abstract termination criterion into a transactional behavior. We prove the correctness property that concurrent runs under the transaction controller are serialisable, assuming an Inverse Operation Postulate to guarantee recoverability. For its applicability to a wide range of programs we specify the transaction controller TaCtl and the operator $TA$ in terms of Abstract State Machines (ASMs). This allows us to model concurrent updates at different levels of nested locations in a precise yet simple manner, namely in terms of partial ASM updates. It also provides the possibility to use the controller TaCtl and the operator $TA$ as a plug-in when specifying concurrent system components in terms of sequential ASMs.

cs.DB↗
arXiv2017

Ding-Iohara algebras and quantum vertex algebras

In this paper, we associate quantum vertex algebras to a certain family of associative algebras $\widetilde{\A}(g)$ which are essentially Ding-Iohara algebras. To do this, we introduce another closely related family of associative algebras $\A(h)$. The associated quantum vertex algebras are based on the vacuum modules for $\A(h)$, whereas $ϕ$-coordinated modules for these quantum vertex algebras are associated to $\widetilde{A}(g)$-modules. Furthermore, we classify their irreducible $ϕ$-coordinated modules.

math.QA↗
arXiv2017

A Complete Logic for Database Abstract State Machines

In database theory, the term $\textit{database transformation}$ was used to refer to a unifying treatment for computable queries and updates. Recently, it was shown that non-deterministic database transformations can be captured exactly by a variant of ASMs, the so-called Database Abstract State Machines (DB-ASMs). In this article we present a logic for DB-ASMs, extending the logic of Nanchen and Stärk for ASMs. In particular, we develop a rigorous proof system for the logic for DB-ASMs, which is proven to be sound and complete. The most difficult challenge to be handled by the extension is a proper formalisation capturing non-determinism of database transformations and all its related features such as consistency, update sets or multisets associated with DB-ASM rules. As the database part of a state of database transformations is a finite structure and DB-ASMs are restricted by allowing quantifiers only over the database part of a state, we resolve this problem by taking update sets explicitly into the logic, i.e. by using an additional modal operator $[X]$, where $X$ is interpreted as an update set $Δ$ generated by a DB-ASM rule. The DB-ASM logic provides a powerful verification tool to study properties of database transformations.

cs.LO↗
arXiv2017

A Logic for Non-Deterministic Parallel Abstract State Machines

We develop a logic which enables reasoning about single steps of non-deterministic parallel Abstract State Machines (ASMs). Our logic builds upon the unifying logic introduced by Nanchen and Stärk for reasoning about hierarchical (parallel) ASMs. Our main contribution to this regard is the handling of non-determinism (both bounded and unbounded) within the logical formalism. Moreover, we do this without sacrificing the completeness of the logic for statements about single steps of non-deterministic parallel ASMs, such as invariants of rules, consistency conditions for rules, or step-by-step equivalence of rules.

cs.LO↗
arXiv2017

Passive Sensing and Communication Using Visible Light: Taxonomy, Challenges and Opportunities

For more than a century, artificial lighting has served mainly for illumination. Only recently, we start to transform our lighting infrastructure to provide new services such as indoor localization and network connectivity. These innovative advancements rely on two key requirements: the ability to modulate light sources (for data transmission) and the presence of photodetectors on objects (for data reception). But not all lights can be modulated and most objects do not have photodetectors. To overcome these limitations, researchers are developing novel sensing and communication methods that exploit passive light sources, such as the sun, and that leverage the external surfaces of objects, such as fingers and car roofs, to create a new generation of cyber-physical systems based on visible light. In this article we propose a taxonomy to analyze these novel contributions. Our taxonomy allows us to identify the overarching principles, challenges and opportunities of this new rising area.

cs.NI↗