OpenRaiser/Intern-Atlas huggingface dataset:
Metamorphosis of Fuzzy Regular Expressions to Fuzzy Automata using the Follow Automata
Venue: arXiv cs.FL 2014
Year: 2014

To deal with system uncertainty, finite automata have been generalized into fuzzy automata. Stamenkovic and Ciric proposed an approach using the position automata for the construction of fuzzy automata from fuzzy regular expressions. There exist multifarious methodologies for the construction of finite automata from regular expressions known as Thompson construction, Antimirov partial derivatives, Glushkov automata and follow automata etc. In this paper, we propose an approach for the conversion of fuzzy regular expressions into fuzzy automata using the concept of follow automata. The number of states of the obtained Fuzzy automata using the proposed approach is lesser than the extant approaches in the literature.
Improving Robustness of Next-Hop Routing
Venue: arXiv cs.DS 2014
Year: 2014

A weakness of next-hop routing is that following a link or router failure there may be no routes between some source-destination pairs, or packets may get stuck in a routing loop as the protocol operates to establish new routes. In this article, we address these weaknesses by describing mechanisms to choose alternate next hops. Our first contribution is to model the scenario as the following {\sc tree augmentation} problem. Consider a mixed graph where some edges are directed and some undirected. The directed edges form a spanning tree pointing towards the common destination node. Each directed edge represents the unique next hop in the routing protocol. Our goal is to direct the undirected edges so that the resulting graph remains acyclic and the number of nodes with outdegree two or more is maximized. These nodes represent those with alternative next hops in their routing paths. We show that {\sc tree augmentation} is NP-hard in general and present a simple $\frac{1}{2}$-approximation algorithm. We also study 3 special cases. We give exact polynomial-time algorithms for when the input spanning tree consists of exactly 2 directed paths or when the input graph has bounded treewidth. For planar graphs, we present a polynomial-time approximation scheme when the input tree is a breadth-first search tree. To the best of our knowledge, {\sc tree augmentation} has not been previously studied.
Asymptotics of Continuous Bayes for Non-i.i.d. Sources
Venue: arXiv cs.IT 2014
Year: 2014

Clarke and Barron analysed the relative entropy between an i.i.d. source and a Bayesian mixture over a continuous class containing that source. In this paper a comparable result is obtained when the source is permitted to be both non-stationary and dependent. The main theorem shows that Bayesian methods perform well for both compression and sequence prediction even in this most general setting with only mild technical assumptions.
A Probabilistic Delay Model for Bidirectional VANETs in City Environments
Venue: arXiv cs.NI 2014
Year: 2014

Routing in VANETs (Vehicular Ad hoc NETworks) is a challenging task due to large network sizes, rapidly changing topology and frequent network disconnections. State-of-the-art routing protocols tried to address these specific problems especially in city environments (vehicles constrained by road geometry, signal transmissions blocked by obstacles, degree of congestion in roads etc). It was noticed that in city scenarios codirectional roads consist of a collection of disconnected clusters because of traffic control strategies (e.g., RSU (Road Side Units), stop signs and traffic lights). In this paper, we propose an intervehicle ad-hoc routing metric called EFD (Expected Forwarding Delay) based on the vehicular traffic statistics (e.g., densities and velocities) collected on-the-fly. We derive an analytical expression for the expected size of a cluster in co-directional traffic. In case of disconnection between two co-directional clusters the opposite directional clusters are used as a bridge to propagate a message in the actual forwarding direction to reduce the delay due to carry and forward. Through theoretical analysis and extensive simulation, it is shown that our link delay model provides the accurate link delay estimation in bidirectional city environments.
Full-Duplex Wireless-Powered Relay with Self-Energy Recycling
Venue: arXiv cs.IT 2014
Year: 2014

This letter studies a wireless-powered amplify-and-forward relaying system, where an energy-constrained relay node assists the information transmission from the source to the destination using the energy harvested from the source. We propose a novel two-phase protocol for efficient energy transfer and information relaying, in which the relay operates in full-duplex mode with simultaneous energy harvesting and information transmission. Compared with the existing protocols, the proposed design possesses two main advantages: i) it ensures uninterrupted information transmission since no time switching or power splitting is needed at the relay for energy harvesting; ii) it enables the so-called self-energy recycling, i.e., part of the energy (loop energy) that is used for information transmission by the relay can be harvested and reused in addition to the dedicated energy sent by the source. Under the multiple-input single-output (MISO) channel setup, the optimal power allocation and beamforming design at the relay are derived. Numerical results show a significant throughput gain achieved by our proposed design over the existing time switching-based relay protocol.
EMEEDP: Enhanced Multi-hop Energy Efficient Distributed Protocol for Heterogeneous Wireless Sensor Network
Venue: arXiv cs.NI 2014
Year: 2014

In WSN (Wireless Sensor Network) every sensor node sensed the data and transmit it to the CH (Cluster head) or BS (Base Station). Sensors are randomly deployed in unreachable areas, where battery replacement or battery charge is not possible. For this reason, Energy conservation is the important design goal while developing a routing and distributed protocol to increase the lifetime of WSN. In this paper, an enhanced energy efficient distributed protocol for heterogeneous WSN have been reported. EMEEDP is proposed for heterogeneous WSN to increase the lifetime of the network. An efficient algorithm is proposed in the form of flowchart and based on various clustering equation proved that the proposed work accomplishes longer lifetime with improved QOS parameters parallel to MEEP. A WSN implemented and tested using Raspberry Pi devices as a base station, temperature sensors as a node and xively.com as a cloud. Users use data for decision purpose or business purposes from xively.com using internet.
Novel Power and Completion Time Models for Virtualized Environments
Venue: arXiv cs.DC 2014
Year: 2014

Power consumption costs takes upto half of operational expenses of datacenters making power management a critical concern. Advances in processor technology provide fine-grained control over operating frequency and voltage of processors and this control can be used to tradeoff power for performance. Although many power and performance models exist, they have a significant error margin while predicting the performance of memory or file-intensive tasks and HPC applications. Our investigations reveal that the prediction error is due in part to the fact that they do not take frequency AND CPU variations account, rather they just depend on the CPU by itself. In this paper, we empirically derive power and completion time models using linear regression with CPU utilization and operating frequency as parameters. We validate our power model on several Intel and AMD processors by predicting within 2-7% of measured power. We validate our completion time model using five kernels of NASA Parallel Benchmark suite and five CPU, memory and file-intensive benchmarks on four heterogeneous systems and predicting within 1-6% of observed performance. We then show how these models can be employed to realize as much as 15% savings in power while delivering 44% better performance for applications deployed in a virtualized environment.
Investigating Rumor Propagation with TwitterTrails
Venue: arXiv cs.SI 2014
Year: 2014

Social media have become part of modern news reporting, used by journalists to spread information and find sources, or as a news source by individuals. The quest for prominence and recognition on social media sites like Twitter can sometimes eclipse accuracy and lead to the spread of false information. As a way to study and react to this trend, we introduce {\sc TwitterTrails}, an interactive, web-based tool ({\tt twittertrails.com}) that allows users to investigate the origin and propagation characteristics of a rumor and its refutation, if any, on Twitter. Visualizations of burst activity, propagation timeline, retweet and co-retweeted networks help its users trace the spread of a story. Within minutes {\sc TwitterTrails} will collect relevant tweets and automatically answer several important questions regarding a rumor: its originator, burst characteristics, propagators and main actors according to the audience. In addition, it will compute and report the rumor's level of visibility and, as an example of the power of crowdsourcing, the audience's skepticism towards it which correlates with the rumor's credibility. We envision {\sc TwitterTrails} as valuable tool for individual use, but we especially for amateur and professional journalists investigating recent and breaking stories. Further, its expanding collection of investigated rumors can be used to answer questions regarding the amount and success of misinformation on Twitter.
Handling owl:sameAs via Rewriting
Venue: arXiv cs.DB 2014
Year: 2014

Rewriting is widely used to optimise owl:sameAs reasoning in materialisation based OWL 2 RL systems. We investigate issues related to both the correctness and efficiency of rewriting, and present an algorithm that guarantees correctness, improves efficiency, and can be effectively parallelised. Our evaluation shows that our approach can reduce reasoning times on practical data sets by orders of magnitude.
A note on diagonal and Hermitian surfaces
Venue: arXiv cs.IT 2014
Year: 2014

Aspects of the properties, enumeration and construction of points on diagonal and Hermitian surfaces have been considered extensively in the literature and are further considered here. The zeta function of diagonal surfaces is given as a direct result of the work of Wolfmann. Recursive construction techniques for the set of rational points of Hermitian surfaces are of interest. The relationship of these techniques here to the construction of codes on surfaces is briefly noted.
A Hybrid Approach to Finding Relevant Social Media Content for Complex Domain Specific Information Needs
Venue: arXiv cs.IR 2014
Year: 2014

While contemporary semantic search systems offer to improve classical keyword-based search, they are not always adequate for complex domain specific information needs. The domain of prescription drug abuse, for example, requires knowledge of both ontological concepts and 'intelligible constructs' not typically modeled in ontologies. These intelligible constructs convey essential information that include notions of intensity, frequency, interval, dosage and sentiments, which could be important to the holistic needs of the information seeker. We present a hybrid approach to domain specific information retrieval (or knowledge-aware search) that integrates ontology-driven query interpretation with synonym-based query expansion and domain specific rules, to facilitate search in social media. Our framework is based on a context-free grammar (CFG) that defines the query language of constructs interpretable by the search system. The grammar provides two levels of semantic interpretation: 1) a top-level CFG that facilitates retrieval of diverse textual patterns, which belong to broad templates and 2) a low-level CFG that enables interpretation of certain specific expressions that belong to such patterns. These low-level expressions occur as concepts from four different categories of data: 1) ontological concepts, 2) concepts in lexicons (such as emotions and sentiments), 3) concepts in lexicons with only partial ontology representation, called lexico-ontology concepts (such as side effects and routes of administration (ROA)), and 4) domain specific expressions (such as date, time, interval, frequency and dosage) derived solely through rules. Our approach is embodied in a novel Semantic Web platform called PREDOSE developed for prescription drug abuse epidemiology. Keywords: Knowledge-Aware Search, Ontology, Semantic Search, Background Knowledge, Context-Free Grammar
Query complexity of sampling and small geometric partitions
Venue: arXiv cs.CC 2014
Year: 2014

In this paper we study the following problem: Discrete partitioning problem (DPP): Let $\mathbb{F}_q P^n$ denote the $n$-dimensional finite projective space over $\mathbb{F}_q$. For positive integer $k \leq n$, let $\{ A^i\}_{i=1}^N$ be a partition of $(\mathbb{F}_q P^n)^k$ such that (1) for all $i \leq N$, $A^i = \prod_{j=1}^k A^i_j$ (partition into product sets), (2) for all $i \leq N$, there is a $(k-1)$-dimensional subspace $L^i \subseteq \mathbb{F}_q P^n$ such that $A^i \subseteq (L^i)^k$. What is the minimum value of $N$ as a function of $q,n,k$? We will be mainly interested in the case $k=n$.
Quantum emulation of query extension in information retrieval
Venue: arXiv cs.IR 2014
Year: 2014

An operationalistic scheme, called Melucci metaphor, is suggested representing Information Retrieval as physical measurements with beam of particles playing the role of the flow of retrieved documents. The possibilities of query expansion by extra term are studied from this perspective, when the particles-`docuscles' are assumed to be of classical or quantum nature. It is shown that in both cases the choice of an extra term based on Bayesian belief revision is still valid on the qualitative level for boosting the relevance of the retrieved documents.
Learning Fuzzy Controllers in Mobile Robotics with Embedded Preprocessing
Venue: arXiv cs.RO 2014
Year: 2014

The automatic design of controllers for mobile robots usually requires two stages. In the first stage,sensorial data are preprocessed or transformed into high level and meaningful values of variables whichare usually defined from expert knowledge. In the second stage, a machine learning technique is applied toobtain a controller that maps these high level variables to the control commands that are actually sent tothe robot. This paper describes an algorithm that is able to embed the preprocessing stage into the learningstage in order to get controllers directly starting from sensorial raw data with no expert knowledgeinvolved. Due to the high dimensionality of the sensorial data, this approach uses Quantified Fuzzy Rules(QFRs), that are able to transform low-level input variables into high-level input variables, reducingthe dimensionality through summarization. The proposed learning algorithm, called Iterative QuantifiedFuzzy Rule Learning (IQFRL), is based on genetic programming. IQFRL is able to learn rules with differentstructures, and can manage linguistic variables with multiple granularities. The algorithm has been testedwith the implementation of the wall-following behavior both in several realistic simulated environmentswith different complexity and on a Pioneer 3-AT robot in two real environments. Results have beencompared with several well-known learning algorithms combined with different data preprocessingtechniques, showing that IQFRL exhibits a better and statistically significant performance. Moreover,three real world applications for which IQFRL plays a central role are also presented: path and objecttracking with static and moving obstacles avoidance.
Sample-targeted clinical trial adaptation
Venue: arXiv cs.LG 2014
Year: 2014

Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. The main goal is to make the process of introducing new medical interventions to patients more efficient by reducing the cost and the time associated with evaluating their safety and efficacy. The principal question is how should adaptation be performed so as to minimize the chance of distorting the outcome of the trial. We propose a novel method for achieving this. Unlike previous work our approach focuses on trial adaptation by sample size adjustment. We adopt a recently proposed stratification framework based on collected auxiliary data and show that this information together with the primary measured variables can be used to make a probabilistically informed choice of the particular sub-group a sample should be removed from. Experiments on simulated data are used to illustrate the effectiveness of our method and its application in practice.
Robust topology optimisation of microstructural details without length scale separation - using a spectral coarse basis preconditioner
Venue: arXiv cs.CE 2014
Year: 2014

This paper applies topology optimisation to the design of structures with periodic microstructural details without length scale separation, i.e. considering the complete macroscopic structure and its response, while resolving all microstructural details, as compared to the often used homogenisation approach. The approach takes boundary conditions into account and ensures connected and macroscopically optimised microstructures regardless of the difference in micro- and macroscopic length scales. This results in microstructures tailored for specific applications rather than specific properties. Dealing with the complete macroscopic structure and its response is computationally challenging as very fine discretisations are needed in order to resolve all microstructural details. Therefore, this article shows the benefits of applying a contrast-independent spectral preconditioner based on the multiscale finite element method (MsFEM) to large structures with fully-resolved microstructural details. The density-based topology optimisation approach combined with a Heaviside projection filter and a stochastic robust formulation is used on various problems, with both periodic and layered microstructures. The presented approach is shown to allow for the topology optimisation of very large problems in \textsc{Matlab}, specifically a problem with 26 million displacement degrees of freedom in 26 hours using a single computational thread.
Designing for the Don't Cares: A story about a sociotechnical system
Venue: arXiv cs.CY 2014
Year: 2014

This article discusses the difficulties that arose when attempting to specify and design a large scale digital learning environment for Scottish schools. This had a potential user base of about 1 million users and was intended to replace an existing, under-used system. We found that the potential system users were not interested in engaging with the project and that there were immense problems with system governance. The only technique that we found to be useful were user stories, presenting scenarios of how the system might be used by students and their teachers. The designed architecture was based around a layered set of replaceable services.
Formal Semantic Annotations for Models Interoperability in a PLM environment
Venue: arXiv cs.SE 2014
Year: 2014

Nowadays, the need for system interoperability in or across enterprises has become more and more ubiquitous. Lots of research works have been carried out in the information exchange, transformation, discovery and reuse. One of the main challenges in these researches is to overcome the semantic heterogeneity between enterprise applications along the lifecycle of a product. As a possible solution to assist the semantic interoperability, semantic annotation has gained more and more attentions and is widely used in different domains. In this paper, based on the investigation of the context and the related works, we identify some existing drawbacks and propose a formal semantic annotation approach to support the semantics enrichment of models in a PLM environment.
A Discriminative CNN Video Representation for Event Detection
Venue: arXiv cs.CV 2014
Year: 2014

In this paper, we propose a discriminative video representation for event detection over a large scale video dataset when only limited hardware resources are available. The focus of this paper is to effectively leverage deep Convolutional Neural Networks (CNNs) to advance event detection, where only frame level static descriptors can be extracted by the existing CNN toolkit. This paper makes two contributions to the inference of CNN video representation. First, while average pooling and max pooling have long been the standard approaches to aggregating frame level static features, we show that performance can be significantly improved by taking advantage of an appropriate encoding method. Second, we propose using a set of latent concept descriptors as the frame descriptor, which enriches visual information while keeping it computationally affordable. The integration of the two contributions results in a new state-of-the-art performance in event detection over the largest video datasets. Compared to improved Dense Trajectories, which has been recognized as the best video representation for event detection, our new representation improves the Mean Average Precision (mAP) from 27.6% to 36.8% for the TRECVID MEDTest 14 dataset and from 34.0% to 44.6% for the TRECVID MEDTest 13 dataset. This work is the core part of the winning solution of our CMU-Informedia team in TRECVID MED 2014 competition.
Learning Multi-Relational Semantics Using Neural-Embedding Models
Venue: arXiv cs.CL 2014
Year: 2014

In this paper we present a unified framework for modeling multi-relational representations, scoring, and learning, and conduct an empirical study of several recent multi-relational embedding models under the framework. We investigate the different choices of relation operators based on linear and bilinear transformations, and also the effects of entity representations by incorporating unsupervised vectors pre-trained on extra textual resources. Our results show several interesting findings, enabling the design of a simple embedding model that achieves the new state-of-the-art performance on a popular knowledge base completion task evaluated on Freebase.
Dynamic aerodynamic-structural coupling numerical simulation on the flexible wing of a cicada based on ansys
Venue: arXiv cs.CE 2014
Year: 2014

Most biological flyers undergo orderly deformation in flight, and the deformations of wings lead to complex fluid-structure interactions. In this paper, an aerodynamic-structural coupling method of flapping wing is developed based on ANSYS to simulate the flapping of flexible wing. Fluent module and Transient Structural module are connected through the System Coupling module to make a two-way fluid-structure Coupling computational framework. Comparing with the rigid wing of a cicada, the coupling results of the flexible wing shows that the flexible deformation can increase the aerodynamic performances of flapping flight.