OpenRaiser/Intern-Atlas huggingface dataset:
Context-Aware Scheduling of Joint Millimeter Wave and Microwave Resources for Dual-Mode Base Stations
Venue: arXiv cs.IT 2016
Year: 2016

One of the most promising approaches to overcome the drastic channel variations of millimeter wave (mmW) communications is to deploy dual-mode base stations that integrate both mmW and microwave (\muW) frequencies. Reaping the benefits of a dual-mode operation requires scheduling mechanisms that can allocate resources efficiently and jointly at both frequency bands. In this paper, a novel resource allocation framework is proposed that exploits users' context, in terms of user application (UA) delay requirements, to maximize the quality-of-service (QoS) of a dual-mode base station. In particular, such a context-aware approach enables the network to dynamically schedule UAs, instead of users, thus providing more precise delay guarantees and a more efficient exploitation of the mmW resources. The scheduling of UAs is formulated as a one-to-many matching problem between UAs and resources and a novel algorithm is proposed to solve it. The proposed algorithm is shown to converge to a two-sided stable matching between UAs and network resources. Simulation results show that the proposed approach outperforms classical CSI-based scheduling in terms of the per UA QoS, yielding up to 36% improvement. The results also show that exploiting mmW resources provides significant traffic offloads reaching up to 43% from \muW band.
Connectivity Scaling Laws in Wireless Networks
Venue: arXiv cs.NI 2016
Year: 2016

We present scaling laws that dictate both local and global connectivity properties of bounded wireless networks. These laws are defined with respect to the key system parameters of per-node transmit power and the number of antennas exploited for diversity coding and/or beamforming at each node. We demonstrate that the local probability of connectivity scales like $\mathcal{O}(z^\mathcal C)$ in these parameters, where $\mathcal C$ is the ratio of the dimension of the network domain to the path loss exponent, thus enabling efficient boundary effect mitigation and network topology control.
A semi-automatic computer-aided method for surgical template design
Venue: arXiv cs.GR 2016
Year: 2016

This paper presents a generalized integrated framework of semi-automatic surgical template design. Several algorithms were implemented including the mesh segmentation, offset surface generation, collision detection, ruled surface generation, etc., and a special software named TemDesigner was developed. With a simple user interface, a customized template can be semi- automatically designed according to the preoperative plan. Firstly, mesh segmentation with signed scalar of vertex is utilized to partition the inner surface from the input surface mesh based on the indicated point loop. Then, the offset surface of the inner surface is obtained through contouring the distance field of the inner surface, and segmented to generate the outer surface. Ruled surface is employed to connect inner and outer surfaces. Finally, drilling tubes are generated according to the preoperative plan through collision detection and merging. It has been applied to the template design for various kinds of surgeries, including oral implantology, cervical pedicle screw insertion, iliosacral screw insertion and osteotomy, demonstrating the efficiency, functionality and generality of our method.
Uniformity Properties of Construction C
Venue: arXiv cs.IT 2016
Year: 2016

Construction C (also known as Forney's multi-level code formula) forms a Euclidean code for the additive white Gaussian noise (AWGN) channel from $L$ binary code components. If the component codes are linear, then the minimum distance is the same for all the points, although the kissing number may vary. In fact, while in the single level ($L=1$) case it reduces to lattice Construction A, a multi-level Construction C is in general not a lattice. We show that the two-level ($L=2$) case is special: a two-level Construction C satisfies Forney's definition for a geometrically uniform constellation. Specifically, every point sees the same configuration of neighbors, up to a reflection of the coordinates in which the lower level code is equal to 1. In contrast, for three levels and up ($L\geq 3$), we construct examples where the distance spectrum varies between the points, hence the constellation is not geometrically uniform.
Leveraging Mid-Level Deep Representations For Predicting Face Attributes in the Wild
Venue: arXiv cs.CV 2016
Year: 2016

Predicting facial attributes from faces in the wild is very challenging due to pose and lighting variations in the real world. The key to this problem is to build proper feature representations to cope with these unfavourable conditions. Given the success of Convolutional Neural Network (CNN) in image classification, the high-level CNN feature, as an intuitive and reasonable choice, has been widely utilized for this problem. In this paper, however, we consider the mid-level CNN features as an alternative to the high-level ones for attribute prediction. This is based on the observation that face attributes are different: some of them are locally oriented while others are globally defined. Our investigations reveal that the mid-level deep representations outperform the prediction accuracy achieved by the (fine-tuned) high-level abstractions. We empirically demonstrate that the midlevel representations achieve state-of-the-art prediction performance on CelebA and LFWA datasets. Our investigations also show that by utilizing the mid-level representations one can employ a single deep network to achieve both face recognition and attribute prediction.
Diagnosis and Repair for Synthesis from Signal Temporal Logic Specifications
Venue: arXiv cs.SY 2016
Year: 2016

We address the problem of diagnosing and repairing specifications for hybrid systems formalized in signal temporal logic (STL). Our focus is on the setting of automatic synthesis of controllers in a model predictive control (MPC) framework. We build on recent approaches that reduce the controller synthesis problem to solving one or more mixed integer linear programs (MILPs), where infeasibility of a MILP usually indicates unrealizability of the controller synthesis problem. Given an infeasible STL synthesis problem, we present algorithms that provide feedback on the reasons for unrealizability, and suggestions for making it realizable. Our algorithms are sound and complete, i.e., they provide a correct diagnosis, and always terminate with a non-trivial specification that is feasible using the chosen synthesis method, when such a solution exists. We demonstrate the effectiveness of our approach on the synthesis of controllers for various cyber-physical systems, including an autonomous driving application and an aircraft electric power system.
Fast Multiplier Methods to Optimize Non-exhaustive, Overlapping Clustering
Venue: arXiv cs.LG 2016
Year: 2016

Clustering is one of the most fundamental and important tasks in data mining. Traditional clustering algorithms, such as K-means, assign every data point to exactly one cluster. However, in real-world datasets, the clusters may overlap with each other. Furthermore, often, there are outliers that should not belong to any cluster. We recently proposed the NEO-K-Means (Non-Exhaustive, Overlapping K-Means) objective as a way to address both issues in an integrated fashion. Optimizing this discrete objective is NP-hard, and even though there is a convex relaxation of the objective, straightforward convex optimization approaches are too expensive for large datasets. A practical alternative is to use a low-rank factorization of the solution matrix in the convex formulation. The resulting optimization problem is non-convex, and we can locally optimize the objective function using an augmented Lagrangian method. In this paper, we consider two fast multiplier methods to accelerate the convergence of an augmented Lagrangian scheme: a proximal method of multipliers and an alternating direction method of multipliers (ADMM). For the proximal augmented Lagrangian or proximal method of multipliers, we show a convergence result for the non-convex case with bound-constrained subproblems. These methods are up to 13 times faster---with no change in quality---compared with a standard augmented Lagrangian method on problems with over 10,000 variables and bring runtimes down from over an hour to around 5 minutes.
Massively Multilingual Word Embeddings
Venue: arXiv cs.CL 2016
Year: 2016

We introduce new methods for estimating and evaluating embeddings of words in more than fifty languages in a single shared embedding space. Our estimation methods, multiCluster and multiCCA, use dictionaries and monolingual data; they do not require parallel data. Our new evaluation method, multiQVEC-CCA, is shown to correlate better than previous ones with two downstream tasks (text categorization and parsing). We also describe a web portal for evaluation that will facilitate further research in this area, along with open-source releases of all our methods.
Threshold games and cooperation on multiplayer graphs
Venue: arXiv cs.GT 2016
Year: 2016

Objective: The study investigates the effect on cooperation in multiplayer games, when the population from which all individuals are drawn is structured - i.e. when a given individual is only competing with a small subset of the entire population. Method: To optimize the focus on multiplayer effects, a class of games were chosen for which the payoff depends nonlinearly on the number of cooperators - this ensures that the game cannot be represented as a sum of pair-wise interactions, and increases the likelihood of observing behaviour different from that seen in two-player games. The chosen class of games are named "threshold games", and are defined by a threshold, $M > 0$, which describes the minimal number of cooperators in a given match required for all the participants to receive a benefit. The model was studied primarily through numerical simulations of large populations of individuals, each with interaction neighbourhoods described by various classes of networks. Results: When comparing the level of cooperation in a structured population to the mean-field model, we find that most types of structure lead to a decrease in cooperation. This is both interesting and novel, simply due to the generality and breadth of relevance of the model - it is likely that any model with similar payoff structure exhibits related behaviour. More importantly, we find that the details of the behaviour depends to a large extent on the size of the immediate neighbourhoods of the individuals, as dictated by the network structure. In effect, the players behave as if they are part of a much smaller, fully mixed, population, which we suggest an expression for.
On the Capacity of the Half-Duplex MIMO Gaussian Diamond Channel
Venue: arXiv cs.IT 2016
Year: 2016

In this paper, we analyze the 2-relay multiple-input multiple-output (MIMO) Gaussian diamond channel. We show that a multihopping decode-and-forward with multiple access (MDF-MAC) protocol achieves rates within a constant gap from capacity when a channel parameter $Δ$ is greater than zero. We also identify the transmit covariance matrices to be used by each relay in the multiple-access (MAC) state of the MDF-MAC protocol. As done for the single-antenna 2-relay Gaussian diamond channel, the channel parameter $Δ$ is defined to be the difference between the product of the capacities of the links from the source to the two relays and the product of the capacities of the links from the two relays to the destination.
Code Generation for Event-B
Venue: arXiv cs.SE 2016
Year: 2016

Stepwise refinement and Design-by-Contract are two formal approaches for modelling systems. These approaches are widely used in the development of systems. Both approaches have (dis-)advantages. This thesis aims to answer, is it possible to combine both approaches in the development of systems, providing the user with the benefits of both? We answer this question by translating the stepwise refinement method with Event-B to Design-by-Contract with Java and JML, so users can take full advantage of both formal approaches without losing their benefits. This thesis presents a set of syntactic rules that translates Event-B to JML-annotated Java code. It also presents the implementation of the syntactic rules as the EventB2Java tool. We used the tool to translate several Event-B models. It generated JML-annotated Java code for all the considered models that serve as initial implementation. We also used EventB2Java for the development of two software applications. Additionally, we compared EventB2Java against two other tools for Event-B code generation. EventB2Java enables users to start the software development process in Event-B, where users can model the system and prove its consistency, to then transition to JML-annotated Java code, where users can continue the development process.
Preoperative Volume Determination for Pituitary Adenoma
Venue: arXiv cs.CV 2016
Year: 2016

The most common sellar lesion is the pituitary adenoma, and sellar tumors are approximately 10-15% of all intracranial neoplasms. Manual slice-by-slice segmentation takes quite some time that can be reduced by using the appropriate algorithms. In this contribution, we present a segmentation method for pituitary adenoma. The method is based on an algorithm that we have applied recently to segmenting glioblastoma multiforme. A modification of this scheme is used for adenoma segmentation that is much harder to perform, due to lack of contrast-enhanced boundaries. In our experimental evaluation, neurosurgeons performed manual slice-by-slice segmentation of ten magnetic resonance imaging (MRI) cases. The segmentations were compared to the segmentation results of the proposed method using the Dice Similarity Coefficient (DSC). The average DSC for all datasets was 75.92% +/- 7.24%. A manual segmentation took about four minutes and our algorithm required about one second.
Utilização de Grafos e Matriz de Similaridade na Sumarização Automática de Documentos Baseada em Extração de Frases
Venue: arXiv cs.CL 2016
Year: 2016

The internet increased the amount of information available. However, the reading and understanding of this information are costly tasks. In this scenario, the Natural Language Processing (NLP) applications enable very important solutions, highlighting the Automatic Text Summarization (ATS), which produce a summary from one or more source texts. Automatically summarizing one or more texts, however, is a complex task because of the difficulties inherent to the analysis and generation of this summary. This master's thesis describes the main techniques and methodologies (NLP and heuristics) to generate summaries. We have also addressed and proposed some heuristics based on graphs and similarity matrix to measure the relevance of judgments and to generate summaries by extracting sentences. We used the multiple languages (English, French and Spanish), CSTNews (Brazilian Portuguese), RPM (French) and DECODA (French) corpus to evaluate the developped systems. The results obtained were quite interesting.
A Note on the Complexity of Computing the Number of Reachable Vertices in a Digraph
Venue: arXiv cs.CC 2016
Year: 2016

In this work, we consider the following problem: given a digraph $G=(V,E)$, for each vertex $v$, we want to compute the number of vertices reachable from $v$. In other words, we want to compute the out-degree of each vertex in the transitive closure of $G$. We show that this problem is not solvable in time $\mathcal{O}\left(|E|^{2-ε}\right)$ for any $ε>0$, unless the Strong Exponential Time Hypothesis is false. This result still holds if $G$ is assumed to be acyclic.
Participation Incentives in Randomized Social Choice
Venue: arXiv cs.GT 2016
Year: 2016

When aggregating preferences of agents via voting, two desirable goals are to identify outcomes that are Pareto optimal and to incentivize agents to participate in the voting process. We consider participation notions as formalized by Brandl, Brandt, and Hofbauer (2015) and study how far efficiency and participation are achievable by randomized social choice functions in particular when agents' preferences are downward lexicographic (DL) or satisfy stochastic dominance (SD). Our results include the followings ones: we prove formal relations between the participation notions with respect to SD and DL and we show that the maximal recursive rule satisfies very strong participation with respect to both SD and DL.
On the Capacity of the Dirty Paper Channel with Fast Fading and Discrete Channel States
Venue: arXiv cs.IT 2016
Year: 2016

The "writing dirty paper" capacity result crucially dependents on the perfect channel knowledge at the transmitter as the presence of even a small uncertainty in the channel realization gravely hampers the ability of the transmitter to pre-code its transmission against the channel state. This is particularly disappointing as it implies that interference pre-coding in practical systems is effective only when the channel estimates at the users have very high precision, a condition which is generally unattainable in wireless environments. In this paper we show that substantial improvements are possible when the state sequence is drawn from a discrete distribution, such as a constrained input constellation, for which state decoding can be approximately optimal. We consider the "writing on dirty paper" channel in which the state sequence is multiplied by a fast fading process and derive conditions on the fading and state distributions for which state decoding closely approaches capacity. These conditions intuitively relate to the ability of the receiver to correctly identify both the input and the state realization despite of the uncertainty introduced by fading.
The Carbon Copy onto Dirty Paper Channel with Statistically Equivalent States
Venue: arXiv cs.IT 2016
Year: 2016

Costa's "writing on dirty paper" capacity result establishes that full state pre-cancellation can be attained in Gelfand-Pinsker channel with additive state and additive Gaussian noise. The "carbon copy onto dirty paper" channel is the extension of Costa's model to the compound setting: M receivers each observe the sum of the channel input, Gaussian noise and one of M Gaussian state sequences and attempt to decode the same common message. The state sequences are all non-causally known at the transmitter which attempts to simultaneously pre-code its transmission against the channel state affecting each output. In this correspondence we derive the capacity to within 2.25 bits-per-channel-use of the carbon copying onto dirty paper channel in which the state sequences are statistically equivalent, having the same variance and the same pairwise correlation. For this channel capacity is approached by letting the channel input be the superposition of two codewords: a base codeword, simultaneously decoded at each user, and a top codeword which is pre-coded against the state realization at each user for a portion 1/M of the time. The outer bound relies on a recursive bounding in which incremental side information is provided at each receiver. This result represents a significant first step toward determining the capacity of the most general "carbon copy onto dirty paper" channel in which state sequences appearing in the different channel outputs have any jointly Gaussian distribution.
Fuzzy Maximum Satisfiability
Venue: arXiv cs.LO 2016
Year: 2016

In this paper, we extend the Maximum Satisfiability (MaxSAT) problem to Łukasiewicz logic. The MaxSAT problem for a set of formulae Φ is the problem of finding an assignment to the variables in Φ that satisfies the maximum number of formulae. Three possible solutions (encodings) are proposed to the new problem: (1) Disjunctive Linear Relations (DLRs), (2) Mixed Integer Linear Programming (MILP) and (3) Weighted Constraint Satisfaction Problem (WCSP). Like its Boolean counterpart, the extended fuzzy MaxSAT will have numerous applications in optimization problems that involve vagueness.
Adaptive Mean Queue Size and Its Rate of Change: Queue Management with Random Dropping
Venue: arXiv cs.NI 2016
Year: 2016

The Random early detection (RED) active queue management (AQM) scheme uses the average queue size to calculate the dropping probability in terms of minimum and maximum thresholds. The effect of heavy load enhances the frequency of crossing the maximum threshold value resulting in frequent dropping of the packets. An adaptive queue management with random dropping (AQMRD) algorithm is proposed which incorporates information not just about the average queue size but also the rate of change of the same. Introducing an adaptively changing threshold level that falls in between lower and upper thresholds, our algorithm demonstrates that these additional features significantly improve the system performance in terms of throughput, average queue size, utilization and queuing delay in relation to the existing AQM algorithms.
Monitoring Temporal Properties using Interval Analysis
Venue: arXiv cs.LO 2016
Year: 2016

Verification of temporal logic properties plays a crucial role in proving the desired behaviors of continuous systems. In this paper, we propose an interval method that verifies the properties described by a bounded signal temporal logic. We relax the problem so that if the verification process cannot succeed at the prescribed precision, it outputs an inconclusive result. The problem is solved by an efficient and rigorous monitoring algorithm. This algorithm performs a forward simulation of a continuous-time dynamical system, detects a set of time intervals in which the atomic propositions hold, and validates the property by propagating the time intervals. In each step, the continuous state at a certain time is enclosed by an interval vector that is proven to contain a unique solution. We experimentally demonstrate the utility of the proposed method in formal analysis of nonlinear and complex continuous systems.
The problem of popular primes: Logjam
Venue: arXiv cs.CR 2016
Year: 2016

This paper will discuss the Logjam attack on TLS. The Logjam attack allows, under certain conditions, to defeat the security provided by TLS. This is done by manipulating server and client into using weak and deprecated export grade crypto, and subsequently breaking the Diffie-Hellman key exchange. We explore how the attack works conceptually and how exactly TLS is vulnerable to this attack. Also, the conditions under which the attack can be mounted are discussed, and an estimate of the impact of the attack is presented. Lastly, several mitigations are presented.
Exploring the Limits of Language Modeling
Venue: arXiv cs.CL 2016
Year: 2016

In this work we explore recent advances in Recurrent Neural Networks for large scale Language Modeling, a task central to language understanding. We extend current models to deal with two key challenges present in this task: corpora and vocabulary sizes, and complex, long term structure of language. We perform an exhaustive study on techniques such as character Convolutional Neural Networks or Long-Short Term Memory, on the One Billion Word Benchmark. Our best single model significantly improves state-of-the-art perplexity from 51.3 down to 30.0 (whilst reducing the number of parameters by a factor of 20), while an ensemble of models sets a new record by improving perplexity from 41.0 down to 23.7. We also release these models for the NLP and ML community to study and improve upon.