OpenRaiser/Intern-Atlas huggingface dataset:
Autonomous Thermalling as a Partially Observable Markov Decision Process (Extended Version)
Venue: arXiv cs.RO 2018
Year: 2018

Small uninhabited aerial vehicles (sUAVs) commonly rely on active propulsion to stay airborne, which limits flight time and range. To address this, autonomous soaring seeks to utilize free atmospheric energy in the form of updrafts (thermals). However, their irregular nature at low altitudes makes them hard to exploit for existing methods. We model autonomous thermalling as a POMDP and present a receding-horizon controller based on it. We implement it as part of ArduPlane, a popular open-source autopilot, and compare it to an existing alternative in a series of live flight tests involving two sUAVs thermalling simultaneously, with our POMDP-based controller showing a significant advantage.
Greedy Graph Searching for Vascular Tracking in Angiographic Image Sequences
Venue: arXiv cs.CV 2018
Year: 2018

Vascular tracking of angiographic image sequences is one of the most clinically important tasks in the diagnostic assessment and interventional guidance of cardiac disease. However, this task can be challenging to accomplish because of unsatisfactory angiography image quality and complex vascular structures. Thus, this study proposed a new greedy graph search-based method for vascular tracking. Each vascular branch is separated from the vasculature and is tracked independently. Then, all branches are combined using topology optimization, thereby resulting in complete vasculature tracking. A gray-based image registration method was applied to determine the tracking range, and the deformation field between two consecutive frames was calculated. The vascular branch was described using a vascular centerline extraction method with multi-probability fusion-based topology optimization. We introduce an undirected acyclic graph establishment technique. A greedy search method was proposed to acquire all possible paths in the graph that might match the tracked vascular branch. The final tracking result was selected by branch matching using dynamic time warping with a DAISY descriptor. The solution to the problem reflected both the spatial and textural information between successive frames. Experimental results demonstrated that the proposed method was effective and robust for vascular tracking, attaining a F1 score of 0.89 on a single branch dataset and 0.88 on a vessel tree dataset. This approach provided a universal solution to address the problem of filamentary structure tracking.
Reachability Analysis and Safety Verification for Neural Network Control Systems
Venue: arXiv cs.SY 2018
Year: 2018

Autonomous cyber-physical systems (CPS) rely on the correct operation of numerous components, with state-of-the-art methods relying on machine learning (ML) and artificial intelligence (AI) components in various stages of sensing and control. This paper develops methods for estimating the reachable set and verifying safety properties of dynamical systems under control of neural network-based controllers that may be implemented in embedded software. The neural network controllers we consider are feedforward neural networks called multilayer perceptrons (MLP) with general activation functions. As such feedforward networks are memoryless, they may be abstractly represented as mathematical functions, and the reachability analysis of the network amounts to range (image) estimation of this function provided a set of inputs. By discretizing the input set of the MLP into a finite number of hyper-rectangular cells, our approach develops a linear programming (LP) based algorithm for over-approximating the output set of the MLP with its input set as a union of hyper-rectangular cells. Combining the over-approximation for the output set of an MLP based controller and reachable set computation routines for ordinary difference/differential equation (ODE) models, an algorithm is developed to estimate the reachable set of the closed-loop system. Finally, safety verification for neural network control systems can be performed by checking the existence of intersections between the estimated reachable set and unsafe regions. The approach is implemented in a computational software prototype and evaluated on numerical examples.
Prestige drives epistemic inequality in the diffusion of scientific ideas
Venue: arXiv cs.SI 2018
Year: 2018

The spread of ideas in the scientific community is often viewed as a competition, in which good ideas spread further because of greater intrinsic fitness, and publication venue and citation counts correlate with importance and impact. However, relatively little is known about how structural factors influence the spread of ideas, and specifically how where an idea originates might influence how it spreads. Here, we investigate the role of faculty hiring networks, which embody the set of researcher transitions from doctoral to faculty institutions, in shaping the spread of ideas in computer science, and the importance of where in the network an idea originates. We consider comprehensive data on the hiring events of 5032 faculty at all 205 Ph.D.-granting departments of computer science in the U.S. and Canada, and on the timing and titles of 200,476 associated publications. Analyzing five popular research topics, we show empirically that faculty hiring can and does facilitate the spread of ideas in science. Having established such a mechanism, we then analyze its potential consequences using epidemic models to simulate the generic spread of research ideas and quantify the impact of where an idea originates on its longterm diffusion across the network. We find that research from prestigious institutions spreads more quickly and completely than work of similar quality originating from less prestigious institutions. Our analyses establish the theoretical trade-offs between university prestige and the quality of ideas necessary for efficient circulation. Our results establish faculty hiring as an underlying mechanism that drives the persistent epistemic advantage observed for elite institutions, and provide a theoretical lower bound for the impact of structural inequality in shaping the spread of ideas in science.
McEliece-type Cryptosystems over Quasi-cyclic Codes
Venue: arXiv cs.IT 2018
Year: 2018

In this thesis, we study algebraic coding theory based McEliece-type cryptosystems over quasi-cyclic codes. The main goal of this thesis is to construct a cryptosystem that resists quantum Fourier sampling making it quantum secure. We propose a new variant of Niederreiter cryptosystem over rate $\frac{m-1}{m}$ quasi-cyclic codes which is secure against quantum Fourier sampling due to indistinguishability of the hidden subgroup. The proof of indistinguishability is achieved due to two constraints over automorphism group; small size and large minimal degree. Apart from this cryptosystem, we also present a class of $\frac{1}{m}$ quasi-cyclic codes, with small size and large minimal degree of the automorphism group.
SOSA: A Lightweight Ontology for Sensors, Observations, Samples, and Actuators
Venue: arXiv cs.AI 2018
Year: 2018

The Sensor, Observation, Sample, and Actuator (SOSA) ontology provides a formal but lightweight general-purpose specification for modeling the interaction between the entities involved in the acts of observation, actuation, and sampling. SOSA is the result of rethinking the W3C-XG Semantic Sensor Network (SSN) ontology based on changes in scope and target audience, technical developments, and lessons learned over the past years. SOSA also acts as a replacement of SSN's Stimulus Sensor Observation (SSO) core. It has been developed by the first joint working group of the Open Geospatial Consortium (OGC) and the World Wide Web Consortium (W3C) on \emph{Spatial Data on the Web}. In this work, we motivate the need for SOSA, provide an overview of the main classes and properties, and briefly discuss its integration with the new release of the SSN ontology as well as various other alignments to specifications such as OGC's Observations and Measurements (O\&M), Dolce-Ultralite (DUL), and other prominent ontologies. We will also touch upon common modeling problems and application areas related to publishing and searching observation, sampling, and actuation data on the Web. The SOSA ontology and standard can be accessed at \url{https://www.w3.org/TR/vocab-ssn/}.
Key Person Aided Re-identification in Partially Ordered Pedestrian Set
Venue: arXiv cs.CV 2018
Year: 2018

Ideally person re-identification seeks for perfect feature representation and metric model that re-identify all various pedestrians well in non-overlapping views at different locations with different camera configurations, which is very challenging. However, in most pedestrian sets, there always are some outstanding persons who are relatively easy to re-identify. Inspired by the existence of such data division, we propose a novel key person aided person re-identification framework based on the re-defined partially ordered pedestrian sets. The outstanding persons, namely "key persons", are selected by the K-nearest neighbor based saliency measurement. The partial order defined by pedestrian entering time in surveillance associates the key persons with the query person temporally and helps to locate the possible candidates. Experiments conducted on two video datasets show that the proposed key person aided framework outperforms the state-of-the-art methods and improves the matching accuracy greatly at all ranks.
Strong link between BWT and XBW via Aho-Corasick automaton and applications to Run-Length Encoding
Venue: arXiv cs.DS 2018
Year: 2018

The boom of genomic sequencing makes compression of set of sequences inescapable. This underlies the need for multi-string indexing data structures that helps compressing the data. The most prominent example of such data structures is the Burrows-Wheeler Transform (BWT), a reversible permutation of a text that improves its compressibility. A similar data structure, the eXtended Burrows-Wheeler Transform (XBW), is able to index a tree labelled with alphabet symbols. A link between a multi-string BWT and the Aho-Corasick automaton has already been found and led to a way to build a XBW from a multi-string BWT. We exhibit a stronger link between a multi-string BWT and a XBW by using the order of the concatenation in the multi-string. This bijective link has several applications: first, it allows to build one data structure from the other; second, it enables one to compute an ordering of the input strings that optimises a Run-Length measure (i.e., the compressibility) of the BWT or of the XBW.
Effects of Social Bots in the Iran-Debate on Twitter
Venue: arXiv cs.SI 2018
Year: 2018

2018 started with massive protests in Iran, bringing back the impressions of the so called "Arab Spring" and it's revolutionary impact for the Maghreb states, Syria and Egypt. Many reports and scientific examinations considered online social networks (OSN's) such as Twitter or Facebook to play a critical role in the opinion making of people behind those protests. Beside that, there is also evidence for directed manipulation of opinion with the help of social bots and fake accounts. So, it is obvious to ask, if there is an attempt to manipulate the opinion-making process related to the Iranian protest in OSN by employing social bots, and how such manipulations will affect the discourse as a whole. Based on a sample of ca. 900,000 Tweets relating to the topic "Iran" we show, that there are Twitter profiles, that have to be considered as social bot accounts. By using text mining methods, we show that these social bots are responsible for negative sentiment in the debate. Thereby, we would like to illustrate a detectable effect of social bots on political discussions on Twitter.
Towards Incremental Cylindrical Algebraic Decomposition in Maple
Venue: arXiv cs.SC 2018
Year: 2018

Cylindrical Algebraic Decomposition (CAD) is an important tool within computational real algebraic geometry, capable of solving many problems for polynomial systems over the reals. It has long been studied by the Symbolic Computation community and has found recent interest in the Satisfiability Checking community. The present report describes a proof of concept implementation of an Incremental CAD algorithm in Maple, where CADs are built and then refined as additional polynomial constraints are added. The aim is to make CAD suitable for use as a theory solver for SMT tools who search for solutions by continually reformulating logical formula and querying whether a logical solution is admissible. We describe experiments for the proof of concept, which clearly display the computational advantages compared to iterated re-computation. In addition, the project implemented this work under the recently verified Lazard projection scheme (with corresponding Lazard valuation).
UMDSub at SemEval-2018 Task 2: Multilingual Emoji Prediction Multi-channel Convolutional Neural Network on Subword Embedding
Venue: arXiv cs.CL 2018
Year: 2018

This paper describes the UMDSub system that participated in Task 2 of SemEval-2018. We developed a system that predicts an emoji given the raw text in a English tweet. The system is a Multi-channel Convolutional Neural Network based on subword embeddings for the representation of tweets. This model improves on character or word based methods by about 2\%. Our system placed 21st of 48 participating systems in the official evaluation.
Forecasting the successful execution of horizontal strategy in a diversified corporation via a DEMATEL-supported artificial neural network - A case study
Venue: arXiv cs.NE 2018
Year: 2018

Nowadays, competition is getting tougher as market shrinks because of financial crisis of the late 2000s. Organizations are tensely forced to leverage their core competencies to survive through attracting more customers and gaining more efficacious operations. In such a situation, diversified corporations which run multiple businesses have opportunities to get competitive advantage and differentiate themselves by executing horizontal strategy. Since this strategy completely engages a number of business units of a diversified corporation through resource sharing among them, any effort to implement it will fail if being not supported by enough information. However, for successful execution of horizontal strategy, managers should have reliable information concerning its success probability in advance. To provide such a precious information, a three-step framework has been developed. In the first step, major influencers on successful execution of horizontal strategy have been captured through literature study and interviewing subject matter experts. In the second step through the decision making trial and evaluation laboratory (DEMATEL) methodology, critical success factors (CSFs) have been extracted from major influencers and a success probability assessment index system (SPAIS) has been formed. In the third step, due to the statistical nature (multivariate and distribution free) of SPAIS, an artificial neural network has been designed for enabling organizational managers to forecast the success probability of horizontal strategy execution in a multi-business corporation far better than other classical models.
Learning in the Large - An Exploratory Study of Retrospectives in Large-Scale Agile Development
Venue: arXiv cs.SE 2018
Year: 2018

Many see retrospectives as the most important practice of agile software development. Previous studies of retrospectives have focused on pro- cess and outcome at team level. In this article, we study how a large-scale agile development project uses retrospectives through an analysis of retrospective reports identifying a total of 109 issues and 36 action items as a part of a longitudinal case study. We find that most of the issues identified relate to team-level learning and improvement, and discuss these findings in relation to current advice to improve learning outcome in large-scale agile development.
Toward Extractive Summarization of Online Forum Discussions via Hierarchical Attention Networks
Venue: arXiv cs.CL 2018
Year: 2018

Forum threads are lengthy and rich in content. Concise thread summaries will benefit both newcomers seeking information and those who participate in the discussion. Few studies, however, have examined the task of forum thread summarization. In this work we make the first attempt to adapt the hierarchical attention networks for thread summarization. The model draws on the recent development of neural attention mechanisms to build sentence and thread representations and use them for summarization. Our results indicate that the proposed approach can outperform a range of competitive baselines. Further, a redundancy removal step is crucial for achieving outstanding results.
An Improved Phrase-based Approach to Annotating and Summarizing Student Course Responses
Venue: arXiv cs.CL 2018
Year: 2018

Teaching large classes remains a great challenge, primarily because it is difficult to attend to all the student needs in a timely manner. Automatic text summarization systems can be leveraged to summarize the student feedback, submitted immediately after each lecture, but it is left to be discovered what makes a good summary for student responses. In this work we explore a new methodology that effectively extracts summary phrases from the student responses. Each phrase is tagged with the number of students who raise the issue. The phrases are evaluated along two dimensions: with respect to text content, they should be informative and well-formed, measured by the ROUGE metric; additionally, they shall attend to the most pressing student needs, measured by a newly proposed metric. This work is enabled by a phrase-based annotation and highlighting scheme, which is new to the summarization task. The phrase-based framework allows us to summarize the student responses into a set of bullet points and present to the instructor promptly.
On the non-existence of linear perfect Lee codes: The Zhang-Ge condition and a new polynomial criterion
Venue: arXiv cs.IT 2018
Year: 2018

The Golomb-Welch conjecture (1968) states that there are no $e$-perfect Lee codes in $\mathbb{Z}^n$ for $n\geq 3$ and $e\geq 2$. This conjecture remains open even for linear codes. A recent result of Zhang and Ge establishes the non-existence of linear $e$-perfect Lee codes in $\mathbb{Z}^n$ for infinitely many dimensions $n$, for $e=3$ and $4$. In this paper we extend this result in two ways. First, using the non-existence criterion of Zhang and Ge together with a generalized version of Lucas' theorem we extend the above result for almost all $e$ (i.e. a subset of positive integers with density $1$). Namely, if $e$ contains a digit $1$ in its base-$3$ representation which is not in the unit place (e.g. $e=3,4$) there are no linear $e$-perfect Lee codes in $\mathbb{Z}^n$ for infinitely many dimensions $n$. Next, based on a family of polynomials (the $Q$-polynomials), we present a new criterion for the non-existence of certain lattice tilings. This criterion depends on a prime $p$ and a tile $B$. For $p=3$ and $B$ being a Lee ball we recover the criterion of Zhang and Ge.
Time-Shared Execution of Realtime Computer Vision Pipelines by Dynamic Partial Reconfiguration
Venue: arXiv cs.AR 2018
Year: 2018

This paper presents an FPGA runtime framework that demonstrates the feasibility of using dynamic partial reconfiguration (DPR) for time-sharing an FPGA by multiple realtime computer vision pipelines. The presented time-sharing runtime framework manages an FPGA fabric that can be round-robin time-shared by different pipelines at the time scale of individual frames. In this new use-case, the challenge is to achieve useful performance despite high reconfiguration time. The paper describes the basic runtime support as well as four optimizations necessary to achieve realtime performance given the limitations of DPR on today's FPGAs. The paper provides a characterization of a working runtime framework prototype on a Xilinx ZC706 development board. The paper also reports the performance of realtime computer vision pipelines when time-shared.
Nonlinear Inductive Matrix Completion based on One-layer Neural Networks
Venue: arXiv cs.LG 2018
Year: 2018

The goal of a recommendation system is to predict the interest of a user in a given item by exploiting the existing set of ratings as well as certain user/item features. A standard approach to modeling this problem is Inductive Matrix Completion where the predicted rating is modeled as an inner product of the user and the item features projected onto a latent space. In order to learn the parameters effectively from a small number of observed ratings, the latent space is constrained to be low-dimensional which implies that the parameter matrix is constrained to be low-rank. However, such bilinear modeling of the ratings can be limiting in practice and non-linear prediction functions can lead to significant improvements. A natural approach to introducing non-linearity in the prediction function is to apply a non-linear activation function on top of the projected user/item features. Imposition of non-linearities further complicates an already challenging problem that has two sources of non-convexity: a) low-rank structure of the parameter matrix, and b) non-linear activation function. We show that one can still solve the non-linear Inductive Matrix Completion problem using gradient descent type methods as long as the solution is initialized well. That is, close to the optima, the optimization function is strongly convex and hence admits standard optimization techniques, at least for certain activation functions, such as Sigmoid and tanh. We also highlight the importance of the activation function and show how ReLU can behave significantly differently than say a sigmoid function. Finally, we apply our proposed technique to recommendation systems and semi-supervised clustering, and show that our method can lead to much better performance than standard linear Inductive Matrix Completion methods.
Slow Beam Steering for Indoor Multi-User Visible Light Communications
Venue: arXiv cs.NI 2018
Year: 2018

Visible light communications (VLC) is an emerging technology that enables broadband data rates using the visible spectrum. VLC beam steering has been studied in the literature to track mobile users and to improve coverage. However, in some scenarios, it may be needed to track and serve multiple users using a single beam, which has not been rigorously studied in the existing works to our best knowledge. In this paper, considering slow beam steering where beam directions are assumed to be fixed within a transmission frame, we find the optimum steering angles to simultaneously serve multiple users within the frame duration. This is achieved by solving a non-convex optimization problem using grid based search and majorization-minimization (MM) procedure. Additionally, we consider multiple steerable beams case with larger number of users in the network, and propose an algorithm to cluster users and serve each cluster with a separate beam. The simulation results show that clustering users can provide higher rates compared to serving each user with a separate beam, and two user clusters maximizes the sum rate in a crowded room setting.