Miracle-dz/UniFAR-FTUs huggingface dataset:
Enhancing extraction based summarization with outside word space

We present results from improving vector space based extraction summarizers. The summarizer uses Random Indexing and Page Rank to extract those sentences whose importance are ranked highest for a document, based on vector similarity. Originally the summarizer used only word vectors based on the words in the document to be summarized. By using a larger word space model the performance of the summarizer was improved. Along with the performance, robustness was improved as random seeds did not affect the summarizer as much as before, making for more predictable results from the summarizer.
Engineering self-organizing referral networks for trustworthy service selection

Developing, maintaining, and disseminating trust in open, dynamic environments is crucial. We propose self-organizing referral networks as a means for establishing trust in such environments. A referral network consists of autonomous agents that model others in terms of their trustworthiness and disseminate information on others' trustworthiness. An agent may request a service from another; a requested agent may provide the requested service or give a referral to someone else. Possibly with its user's help, each agent can judge the quality of service obtained. Importantly, the agents autonomously and adaptively decide with whom to interact and choose what referrals to issue, if any. The choices of the agents lead to the evolution of the referral network, whereby the agents move closer to those that they trust. This paper studies the guidelines for engineering self-organizing referral networks. To do so, it investigates properties of referral networks via simulation. By controlling the actions of the agents appropriately, different referral networks can be generated. This paper first shows how the exchange of referrals affects service selection. It identifies interesting network topologies and shows under which conditions these topologies emerge. Based on the link structure of the network, some agents can be identified as authorities. Finally, the paper shows how and when such authorities emerge. The observations of these simulations are then formulated into design recommendations that can be used to develop robust, self-organizing referral networks.
Spiders and pseudoscorpions (Arachnida: Araneae, Pseudoscorpiones) in old oaks of a Central European floodplain

Abstract. Spiders and pseudoscorpions on old pedunculate oaks (Quercus robur) with tree cavities were studied in a Central European floodplain (South Moravia, Czech Republic). Altogether 322 specimens from 47 spider taxa and 71 specimens of six pseudoscorpion species were collected during 2010 and 2011 from tree cavities using two methods. More specimens and species of spiders were obtained from flight interception traps and more specimens and species of pseudoscorpions were obtained from pitfall traps. Remarkable records represent typical cavity dwellers, i.e. the spider Midia midas (Simon, 1884), the pseudoscorpions Larca lata (Hansen, 1884) and Apocheiridium ferum (Simon, 1879), the latter occurs mostly under tree bark. Five arachnid species are listed in the Czech red list: Midia midas, Leptorchestes berolinensis (C. L. Koch, 1846), Dipoena erythropus (Simon, 1881), Larca lata and Dendrochernes cyrneus (L. Koch, 1873).
Theory for Coordinating Concurrent Hierarchical Planning Agents Using Summary Information

Interacting agents that interleave planning, plan coordination, and plan execution for hierarchical plans (e.g. HTNs or procedures for PRS) should reason about abstract plans and their concurrent execution before they are fully refined. Poor decisions made at abstract levels can lead to costly backtracking or even failure. We claim that better decisions require information at abstract levels that summarizes the preconditions and effects that must or may apply when a plan is refined. Here we formally characterize concurrent hierarchical plans and a method for deriving summary information for them, and we illustrate how summary conditions can be used to coordinate the concurrent interactions of plans at different levels of abstraction. The properties of summary conditions and rules determining what interactions can or might hold among asynchronously executing plans are proven to support the construction of sound and complete coordination mechanisms for concurrent hierarchical planning agents.
Control over WirelessHART network

It has been observed that the history of industrial process control development is also a history of reducing the number of wires necessary for effecting the control. Control over wireless is the end of this evolution. Wireless control faces a lot of challenges such as security, reliability, feedback latency, battery longevity, etc. In this paper we report some experience with implementing control over wireless. The platform we use is the WirelessHART mesh network, the first international industrial wireless control standard. We describe a full implementation of the standard and study the issues and solutions in its application. Our data suggest that WirelessHART technology is up to the challenge of wireless control.
2 DCBS : A Model for Developing Dependable Component-Based Software

The software industry has adopted component-based software development (CBSD) to rapidly build and deploy large and complex software systems with significant savings at minimal engineering effort, cost, and time. However, CBSD encounters issues on security trust, mainly with respect to dependability attributes. A system is considered dependable when it can produce the outputs for which it was designed with no adverse effect on its intended environment. Dependability consists of several attributes that imply availability, confidentiality, integrity, reliability, safety, and maintainability. Dependability attributes must be embedded in a CBSD model to develop dependable component software. Motivated by the importance of these attributes, this paper pursues two objectives: to design a model for developing a dependable system that mitigates the vulnerabilities of software components, and to evaluate the proposed model. The model proposed in this study is labelled as developing dependable component-based software (2DCBS). To develop this model, the CBSD architectural phases and processes must be framed and the six dependability attributes embedded according to the best practice method. The expert opinion approach was applied to evaluate 2DCBS framing. In addition, the 2DCBS model was applied to the development of an information communication technology (ICT) portal through an empirical study method. Vulnerability assessment tools (VATs) were employed to verify the dependability attributes of the developed ICT portal. Results show that the 2DCBS model can be adopted to develop web application systems and to mitigate the vulnerabilities of the developed systems. This study contributes to CBSD and facilitates the specification and evaluation of dependability attributes throughout model development. Furthermore, the reliability of the dependable model can increase confidence in the use of CBSD for industries.
Colour by Correlation : A Simple , Unifying Framework for Colour Constancy

This paper considers the problem of illuminant estimation: how, given an image of a scene, recorded under an unknown light, we can recover an estimate of that light. Obtaining such an estimate is a central part of solving the colour constancy problem that is of recovering an illuminant independent representation of the re ectances in a scene. Thus the work presented here will have applications in elds such as colour based object recognition and digital photography, where solving the colour constancy problem is important. The work in this paper di ers from much previous work in that, rather than attempting to recover a single estimate of the illuminant as many previous authors have done, we instead set out to recover a measure of the likelihood that each of a set of possible illuminants was the scene illuminant. We begin by determining which image colours can occur (and how these colours are distributed) under each of a set of possible lights. We discuss in the paper, how for a given camera, we can obtain this knowledge. We then correlate this information with the colours in a particular image to obtain a measure of the likelihood that each of the possible lights was the scene illuminant. Finally we use this likelihood information to choose a single light as an estimate of the scene illuminant. Computation is expressed and performed in a generic correlation framework which we develop in this paper. We propose a new probabilistic instantiation of this correlation framework and we show that it delivers very good colour constancy on both synthetic and real images. We show further that the proposed framework is rich enough to allow many existing algorithms to be expressed within it: the grey-world and gamut mapping algorithms are presented in this framework and we explore too the relationship of these algorithms to other probabilistic and neural network approaches to colour constancy.
Modified Powder-in-Tube Technique Based on the Consolidation Processing of Powder Materials for Fabricating Specialty Optical Fibers

The objective of this paper is to demonstrate the interest of a consolidation process associated with the powder-in-tube technique in order to fabricate a long length of specialty optical fibers. This so-called Modified Powder-in-Tube (MPIT) process is very flexible and paves the way to multimaterial optical fiber fabrications with different core and cladding glassy materials. Another feature of this technique lies in the sintering of the preform under reducing or oxidizing atmosphere. The fabrication of such optical fibers implies different constraints that we have to deal with, namely chemical species diffusion or mechanical stress due to the mismatches between thermal expansion coefficients and working temperatures of the fiber materials. This paper focuses on preliminary results obtained with a lanthano-aluminosilicate glass used as the core material for the fabrication of all-glass fibers or specialty Photonic Crystal Fibers (PCFs). To complete the panel of original microstructures now available by the MPIT technique, we also present several optical fibers in which metallic particles or microwires are included into a silica-based matrix.
The Genome and Methylome of a Beetle with Complex Social Behavior, Nicrophorus vespilloides (Coleoptera: Silphidae)

Testing for conserved and novel mechanisms underlying phenotypic evolution requires a diversity of genomes available for comparison spanning multiple independent lineages. For example, complex social behavior in insects has been investigated primarily with eusocial lineages, nearly all of which are Hymenoptera. If conserved genomic influences on sociality do exist, we need data from a wider range of taxa that also vary in their levels of sociality. Here, we present the assembled and annotated genome of the subsocial beetle Nicrophorus vespilloides, a species long used to investigate evolutionary questions of complex social behavior. We used this genome to address two questions. First, do aspects of life history, such as using a carcass to breed, predict overlap in gene models more strongly than phylogeny? We found that the overlap in gene models was similar between N. vespilloides and all other insect groups regardless of life history. Second, like other insects with highly developed social behavior but unlike other beetles, does N. vespilloides have DNA methylation? We found strong evidence for an active DNA methylation system. The distribution of methylation was similar to other insects with exons having the most methylated CpGs. Methylation status appears highly conserved; 85% of the methylated genes in N. vespilloides are also methylated in the hymentopteran Nasonia vitripennis. The addition of this genome adds a coleopteran resource to answer questions about the evolution and mechanistic basis of sociality and to address questions about the potential role of methylation in social behavior.
CUSTOM FPGA CRYPTOGRAPHIC BLOCKS FOR RECONFIGURABLE EMBEDDED NIOS PROCESSOR

This paper introduces two custom blocks for Nios reconfigurable embedded processor implemented on Altera Field Programmable Gate Arrays (FPGAs). When operations like modular multiplication and modular exponentiation of long integers or other complex algebraic functions are performed on a general-purpose processor they usually consume a lot of processor resources and execution times are not satisfactory. A solution of this problem lies in development of custom coprocessors. The algebraic coprocessor for Montgomery Multiplication (MM) makes possible a fast execution of modular multiplication with large numbers that can be used in several public key cryptographic algorithms. A True Random Number Generator (TRNG) enhances an application of the Nios processor in cryptographic protocols. Until now only few implementations of TRNG on FPGA have been presented in literature. We describe a custom TRNG implementation based on a recently proposed method that reliably extracts intrinsic randomness from low-jitter clock signals synthesized by on-chip FPGA analog PLLs. Both peripheral blocks are connected to the Nios processor through Altera Avalon bus that directly supports scalable connection and different sources of the clock signal. In this way we can optimally use the resources of Altera FPGAs and implement designs customisable with regard to available area resources and desired level of security or timing constraints. Proposed solutions significantly improve security and computational power of System on a Chip (SoC) embedded cryptographic applications based on the Nios processor.
Fast learning discriminative dictionaries for large-scale visual recognition

In this paper, we aim at improving the discriminative jointly dictionaries for large-scale image classification. Sparse representation is a popular tool for image classification. Visual dictionary is very critical to the classification performance. A visual tree is constructed according to the visual similarity, in which the higher layer represents the coarser membership and the lower layer represents the finer membership. Jointly dictionary is learned according to the visual tree. Bregman iterative algorithm is implemented to solve the optimal problem of joint dictionary learning, which makes the solution accurate and the running speed fast. Furthermore, we try to implement the pre-trained features learned from the convolution neural network (CNN) to represent an image, and the residual error of the sparse representation is utilized for image classification. The experimental results demonstrate that the CNN feature is more distinct than SIFT, and the hierarchical classification framework with the Bregman iteration algorithm can greatly improve the performance of classification.
Assessing the impact of pavement surface condition and geometric characteristics on the performance of signalised intersections

Signalised intersections are considered to be the most dangerous parts of an urban highway network and carry a very high crash risk. This study aims at investigating the effects of pavement surface condition and geometric characteristics on the performance of such sites in terms of safety and capacity. Using a large sample size of signalised intersections from a metropolitan region, the effects of these parameters have been assessed through the application of advanced statistical techniques that are suitable for the data relevant to the different performance criteria. The outcomes of this thesis would help road agencies in prioritising their maintenance programs related to surface treatments and upgrades of geometric elements at such locations.
Improving Word Sense Disambiguation in Lexical Chaining

Previous algorithms to compute lexical chains suffer either from a lack of accuracy in word sense disambiguation (WSD) or from computational inefficiency. In this paper, we present a new linear-time algorithm for lexical chaining that adopts the assumption of one sense per discourse. Our results show an improvement over previous algorithms when evaluated on a WSD task.
Effect of Amlodipine on the Progression of Atherosclerosis and the Occurrence of Clinical Events

BackgroundThe results of angiographic studies have suggested that calcium channel–blocking agents may prevent new coronary lesion formation, the progression of minimal lesions, or both. Methods and ResultsThe Prospective Randomized Evaluation of the Vascular Effects of Norvasc Trial (PREVENT) was a multicenter, randomized, placebo-controlled, double-masked clinical trial designed to test whether amlodipine would slow the progression of early coronary atherosclerosis in 825 patients with angiographically documented coronary artery disease. The primary outcome was the average 36-month angiographic change in mean minimal diameters of segments with a baseline diameter stenosis of 30%. A secondary hypothesis was whether amlodipine would reduce the rate of atherosclerosis in the carotid arteries as assessed with B-mode ultrasonography, which measured intimal-medial thicknesses (IMT). The rates of clinical events were also monitored. The placebo and amlodipine groups had nearly identical average 36-month reductions in the minimal diameter: 0.084 versus 0.095 mm, respectively (P =0.38). In contrast, amlodipine had a significant effect in slowing the 36-month progression of carotid artery atherosclerosis: the placebo group experienced a 0.033-mm increase in IMT, whereas there was a 0.0126-mm decrease in the amlodipine group (P =0.007). There was no treatment difference in the rates of all-cause mortality or major cardiovascular events, although amlodipine use was associated with fewer cases of unstable angina and coronary revascularization. ConclusionsAmlodipine has no demonstrable effect on angiographic progression of coronary atherosclerosis or the risk of major cardiovascular events but is associated with fewer hospitalizations for unstable angina and revascularization.
Dynamic Response and Optimal Design of Curved Metallic Sandwich Panels under Blast Loading

It is important to understand the effect of curvature on the blast response of curved structures so as to seek the optimal configurations of such structures with improved blast resistance. In this study, the dynamic response and protective performance of a type of curved metallic sandwich panel subjected to air blast loading were examined using LS-DYNA. The numerical methods were validated using experimental data in the literature. The curved panel consisted of an aluminum alloy outer face and a rolled homogeneous armour (RHA) steel inner face in addition to a closed-cell aluminum foam core. The results showed that the configuration of a “soft” outer face and a “hard” inner face worked well for the curved sandwich panel against air blast loading in terms of maximum deflection (MaxD) and energy absorption. The panel curvature was found to have a monotonic effect on the specific energy absorption (SEA) and a nonmonotonic effect on the MaxD of the panel. Based on artificial neural network (ANN) metamodels, multiobjective optimization designs of the panel were carried out. The optimization results revealed the trade-off relationships between the blast-resistant and the lightweight objectives and showed the great use of Pareto front in such design circumstances.
Remifentanil used as adjuvant in general anesthesia for spinal fusion does not exhibit acute opioid tolerance

Background Although acute tolerance to opioids, especially to remifentanil, has been demonstrated consistently in animal studies, the results of clinical trials in humans are controversial. The aim of this study was to determine whether intraoperative infusions of remifentanil used as an adjuvant in general anesthesia result in acute tolerance, an event manifested by increased postoperative pain and a higher opioid requirement than usual. Methods Sixty patients who underwent surgery under general anesthesia for spinal fusion were randomly assigned to receive sevoflurane-nitrous oxide-oxygen (group SO, n = 20), sevoflurane-remifentanil-nitrous oxide-oxygen (group SR, n = 20), or propofol-remifentanil-oxygen (group PR, n = 20) in a double-blinded manner. All patients within 1 hour after induction received PCA (fentanyl 0.4 µg/kg/ml and ondansetron 16 mg) administered intravenously at a basal infusion rate of 1 ml/h, after being intravenously injected with a loading dose of fentanyl (1 µg/kg). Data for fentanyl requirement, verbal Numerical Rating Scale (NRS) pain score at rest, and presence of nausea or vomiting were collected at 1, 24, and 48 hours after surgery. Results We did not find any significant difference in postoperative PCA fentanyl requirements, NRS or side effects among the groups. Conclusions Remifentanil as an adjuvant to sevoflurane or propofol in general anesthesia for adults having surgery for spinal fusion does not appear to cause acute opioid tolerance or hyperalgesia in patients. However, further studies are needed to elucidate whether sevoflurane and propofol exert a clinically significant effect on opioid-induced tolerance or hyperalgesia and whether this effect is related to the age of the patient, the dose and duration of remifentanil given and the intensity of pain experienced postoperatively.
Generation of macro-operators via investigation of action dependencies in plans

Abstract There are many approaches for solving planning problems. Many of these approaches are based on ‘brute force’ search methods and they usually do not care about structures of plans previously computed in particular planning domains. By analyzing these structures, we can obtain useful knowledge that can help us find solutions to more complex planning problems. The method described in this paper is designed for gathering macro-operators by analyzing training plans. This sort of analysis is based on the investigation of action dependencies in training plans. Knowledge gained by our method can be passed directly to planning algorithms to improve their efficiency.
New efficient fillers for unlimited word recognition and keyword spotting

Describes our complete results for improved lexical fillers as well as two new kinds of fillers, gives their results in unlimited speech recognition as well as for keyword spotting and compares them to the acoustic-phonetic filler in the case of keyword spotting. Tests have been conducted on different vocabularies derived from ATIS (Air Travel Information System) and the Wall Street Journal database. Results for keyword spotting show the superiority of the independent lexical phonemic filler that combines accuracy (92% for a false alarm rate of 1.2 FA/h/kw) as well as task-independent training. As for new-word detection, the syllabic and the independent lexical fillers perform quite well, and allow relevant detection of the phonetic transcription.