pinecone/core-2020-05-10-deduplication huggingface dataset:
Automatic speed graph generation for predefined camera paths

Predefined camera paths are a valuable tool for the exploration of complex virtual environments. The speed at which the virtual\ud
camera travels along different path segments is key for allowing users to perceive and understand the scene while maintaining their attention. Current tools for speed adjustment of camera motion along predefined\ud
paths, such as keyframing, interpolation types and speed curve editors provide the animators with a great deal of flexibility but offer little support for the animator to decide which speed is better for each point along the path. In this paper we address the problem of computing a suitable speed curve for a predefined camera path through an arbitrary scene. We strive at adapting speed along the path to provide non-fatiguing,\ud
informative, interestingness and concise animations. Key elements of our approach include a new metric based on optical flow for quantifying the amount of change between two consecutive frames, the use of perceptual\ud
metrics to disregard optical flow in areas with low image saliency, and the incorporation of habituation metrics to keep the user attention. We also present the results of a preliminary user-study comparing user response with alternative approaches for computing speed curves.Peer ReviewedPostprint (published version
A method for reconstructing sketched polyhedral shapes with rounds and fillets

In this paper we present a method for detecting rounds and fillets in 
engineering sketches and drawings, and automatically generating a 3D model of 
the corresponding object, with rounds and fillets applied. This method is useful 
both as a component of computer-aided sketching tools and in determining de-
sign intent—although rounds and fillets are common in engineering parts, they 
often conceal design intent, which is more easily determined from the object’s 
underlying polyhedral skeleton
An Interactive Interface for Lighting-by-Example

International audienceLighting design in computer graphics is essentially not a random process but one driven by both a technical and aesthetic appreciation of lighting. In some applications, the result of the lighting design process is a 2D image derived by rendering a 3D scene. Users with limited understandings of manipulation of lighting parameters may have difficulties in properly modifying the lighting parameters in order to achieve desired lighting effects. We present and demonstrate an approach to lighting design in applications where the expected result of the lighting design process is a 2D image. In this approach, the lighting-by-example method using perception-based objective function is used in combination with an interactive interface in order to optimize lighting parameters for an object or a group of objects individually, and the visual results of these separate processes are combined (utilizing 3D depth information) in the seamless generation of a final 2D image
Accurately Measuring the Satisfaction of Visual Properties in Virtual Camera Control

International audienceAbstract. Declarative approaches to camera control model inputs as properties on the camera and then rely on constraint-based and/or optimization techniques to compute the camera parameters or paths that best satisfy those properties. To reach acceptable performances, such approaches often (if not always) compute properties satisfaction in an approximate way. Therefore, it is diﬃcult to measure results in terms of accuracy, and also compare approaches that use diﬀerent approxima- tions. In this paper, we propose a simple language which can be used to express most of the properties proposed in the literature and whose semantics provide a way to accurately measure their satisfaction. The language can be used for several purposes, for example to measure how accurate a speciﬁc approach is and to compare two distinct approaches in terms of accuracy
Program verification in SPARK and ACSL : a comparative case study

We present a case-study of developing a simple software module using contracts, and rigorously verifying it for safety and functional correctness using two very diﬀerent programming languages, that share the fact that both are extensively used in safety-critical development: SPARK and C/ACSL. This case-study, together with other investigations not detailed here, allows us to establish a comparison in terms of speciﬁcation eﬀort and degree of automation obtained with each toolset.Fundação para a Ciência e a Tecnologia (FCT
Complexity invariance of real interpretations

The original publication is available at www.springerlink.comInternational audienceIn the field of implicit computational complexity, we are con- sidering in this paper the fruitful branch of interpretation methods. In this area, the synthesis problem is solved by Tarski's decision procedure, and consequently interpretations are usually chosen over the reals rather than over the integers. Doing so, one cannot use anymore the (good) properties of the natural (well-) ordering of N employed to bound the complexity of programs. We show that, actually, polynomials over the reals benefit from some properties that allow their safe use for complex- ity. We illustrate this by two characterizations, one of PTIME and one of PSPACE
A batch-service queueing model with a discrete batch Markovian arrival process

Queueing systems with batch service have been investigated extensively during the past decades. However, nearly all the studied models share the common feature that an uncorrelated arrival process is considered, which is unrealistic in several real-life situations. In this paper, we study a discrete-time queueing model, with a server that only initiates service when the amount of customers in system (system content) reaches or exceeds a threshold. Correlation is taken into account by assuming a discrete batch Markovian arrival process (D-BMAP), i.e. the distribution of the number of customer arrivals per slot depends on a background state which is determined by a first-order Markov chain. We deduce the probability generating function of the system content at random slot marks and we examine the influence of correlation in the arrival process on the behavior of the system. We show that correlation merely has a small impact on the threshold that minimizes the mean system content. In addition, we demonstrate that correlation might have a significant influence on the system content and therefore has to be included in the model
The preemptive repeat hybrid server interruption model

We analyze a discrete-time queueing system with server interruptions and a hybrid preemptive repeat interruption discipline. Such a discipline encapsulates both the preemptive repeat identical and the preemptive repeat different disciplines. By the introduction and analysis of so-called service completion times, we significantly reduce the complexity of the analysis. Our results include a.o. the probability generating functions and moments of queue content and delay. Finally, by means of some numerical examples, we assess how performance measures are affected by the specifics of the interruption discipline
Secure Anonymous Routing for MANETs Using Distributed Dynamic Random Path Selection

Most of the MANET security research has so far focused on providing routing security and confidentiality to the data packets, but less has been done to ensure privacy and anonymity of the communicating entities. In this paper, we propose a routing protocol which ensures anonymity, privacy of the user. This is achieved by randomly selecting next hop at each intermediate. This protocol also provides data security using public key ciphers. The protocol is simulated using in-house simulator written in C with OpenSSL crypto APIs. The robustness of our protocol is evaluated against known security attacks
End-to-end QoS Measurement over a DVB-RCS Satellite Network

Satellites play an important role in the future network due to their wide area coverage and for providing connectivity in remote regions of the world. This paper presents the end-to-end quality of service (QoS) measurements taken employing a European Space Agency (ESA) testbed over DVB-RCS infrastructure, in collaboration with University of Surrey, UK. The applications chosen for these experiments are file transfer (FTP), web browsing (HTTP) and video streaming. File transfer and web browsing require reliable transport mechanism as a corrupted bit will hinder the intact data delivery. Therefore, these applications use transmission control protocol (TCP) as the transport protocol. TCP involves a three way handshake, which introduces extra delay during data transfer. Video streaming is a real time application. It is time-sensitive and requires lesser reliability compared to FTP and Web services. Hence, it employs user datagram protocol (UDP) at the transport layer, which do not offer any guarantee of reliable data delivery but timely. The parameters that have been used to evaluate quality of service (QoS) are packet delivery time, file download time, round trip delay, packet sizes and packet loss. The paper presented measurement results and comparative analysis of the QoS of the applications over the DVB-RCS testbed
End-to-End QoS Evaluation of IP-Diffserv Network over LEO Satellite Constellation

In this paper, we present an end-to-end QoS simulation studies on\ud
internetworking of remote LAN and long range communications over LEOIridium\ud
satellites constellation taking SuperJARING network in Malaysia as an\ud
example. A macro level network simulation scenario based on actual network\ud
topology in Malaysia is implemented as Diffserv network model using the\ud
Network Simulator-2 (NS-2). Web traffic (HTTP) is used as the internet traffic\ud
models in the simulation analysis. All simulations are carried out in error-free\ud
and link-loss environment. In error-free simulations, the accumulative network\ud
traffic loads are varied from 20%, 50% and 80% while in link-loss environment\ud
simulations only 20% traffic load is used with bit error rate (BER) varied from\ud
1x10-5, 1x10-4 and 2x10-4. The results show clearly that QoS can be achieved\ud
with IP Diffserv over satellites constellation like Iridium
Dynamic composition of cross-organizational features in distributed software systems

Companies offering software services to external customer organizations must ensure that the non-functional requirements of all these customer organizations are satisfied. However, in such a cross-organizational context where services are provided and consumed by different organizations, the implementation of features, for example security, is scattered across the services of the different organizations and cannot be condensed into a single module that is applicable to multiple services.
 
In this paper we present an aspect-based coordination architecture for dynamic composition of cross-organizational features in distributed software systems such as systems of systems or service supply chains. The underlying approach of this architecture is to specify the features at a higher level that abstracts the internal mechanism of the organizations involved. A coordination middleware dynamically integrates the appropriate features into the service composition, driven by metadata-based user preferences.
 
In this paper we present an aspect-based coordination architecture for dynamic composition of cross-organizational features in distributed software systems such as systems of systems or service supply chains. The underlying approach of this architecture is to improve existing aspect-based composition technology by leveraging some of the principles of cross-org coordination architectures. Features, supporting for example security, can be automatically and dynamically integrated driven by metadata-based user preferences.status: publishe
Experiments in Model Driven Composition of User Interfaces

International audienceReusing and composing pieces of software is a common practice in software engineering. However, reusing the user interfaces that come with software systems is still an ongoing work. The Alias framework helps developers to reuse and compose user interfaces according to the way they are composing new systems from smaller units as a mean of speeding up the design process. In this paper we describe how we rely on Model Driven Engineering to operationalize our composition process
Satisfying privacy requirements: one step before anonymization

In this paper, we study a problem of privacy protection in\ud
large survey rating data. The rating data usually contains both ratings of sensitive and non-sensitive issues, and the ratings of sensitive issues include personal information. Even when survey participants do not reveal any of their ratings, their survey records are potentially identifiable by using information from other public sources. We propose a new (k, , l)- anonymity model, in which each record is required to be similar with at least k−l others based on the non-sensitive ratings, where the similarity is controlled by , and the standard deviation of sensitive ratings is at least l. We study an interesting yet nontrivial satisfaction problem of the (k, , l)-anonymity, which is to decide whether a survey rating data set satisfies the privacy requirements given by users. We develop a slice technique for the satisfaction problem and the experimental results show that the slicing technique is fast, scalable and much more efficient in terms of execution time than the heuristic pairwise method
Using Association Rules to Solve the Cold-Start Problem in Recommender Systems

Recommender systems are widely used online to help users\ud
find other products, items etc that they may be interested in based on what is known about that user in their profile. Often however user profiles may be short on information and thus it is difficult for a recommender system to make quality recommendations. This problem is known as the cold-start problem. Here we investigate using association rules as a source of information to expand a user profile and thus avoid this problem. Our experiments show that it is possible to use association rules to noticeably improve the performance of a recommender system under the cold-start situation. Furthermore, we also show that the improvement in\ud
performance obtained can be achieved while using non-redundant rule sets. This shows that non-redundant rules do not cause a loss of information and are just as informative as a set of association rules that contain redundancy
Classifier ensemble for uncertain data stream classification

Currently available algorithms for data stream classification are all designed to handle precise data, while data with uncertainty or imperfection is quite natural and widely seen in real-life applications. Uncertainty can arise in attribute values as well as in class values. In this paper, we focus on the classification of streaming data that has different degrees of uncertainty within class values. We propose two types of ensemble based algorithms, Static Classifier Ensemble (SCE) and Dynamic Classifier Ensemble (DCE) for mining uncertain data streams. Experiments on both synthetic and real-life data set are made to compare and contrast our proposed algorithms. The experimental results reveal that DCE algorithm outperforms SCE algorithm
Combined Reconstruction and Registration of Digital Breast Tomosynthesis

Digital breast tomosynthesis (DBT) has the potential to en-\ud
hance breast cancer detection by reducing the confounding e ect of su-\ud
perimposed tissue associated with conventional mammography. In addi-\ud
tion the increased volumetric information should enable temporal datasets\ud
to be more accurately compared, a task that radiologists routinely apply\ud
to conventional mammograms to detect the changes associated with ma-\ud
lignancy. In this paper we address the problem of comparing DBT data\ud
by combining reconstruction of a pair of temporal volumes with their reg-\ud
istration. Using a simple test object, and DBT simulations from in vivo\ud
breast compressions imaged using MRI, we demonstrate that this com-\ud
bined reconstruction and registration approach produces improvements\ud
in both the reconstructed volumes and the estimated transformation pa-\ud
rameters when compared to performing the tasks sequentially
Fast perceptron decision tree learning from evolving data streams

Mining of data streams must balance three evaluation dimensions: accuracy, time and memory. Excellent accuracy on data streams has been obtained with Naive Bayes Hoeffding Trees—Hoeffding Trees with naive Bayes models at the leaf nodes—albeit with increased runtime compared to standard Hoeffding Trees. In this paper, we show that runtime can be reduced by replacing naive Bayes with perceptron classifiers, while maintaining highly competitive accuracy. We also show that accuracy can be increased even further by combining majority vote, naive Bayes, and perceptrons. We evaluate four perceptron-based learning strategies and compare them against appropriate baselines: simple perceptrons, Perceptron Hoeffding Trees, hybrid Naive Bayes Perceptron Trees, and bagged versions thereof. We implement a perceptron that uses the sigmoid activation function instead of the threshold activation function and optimizes the squared error, with one perceptron per class value. We test our methods by performing an evaluation study on synthetic and real-world datasets comprising up to ten million examples
Multi-sensor fire detection by fusing visual and non-visual flame features

This paper proposes a feature-based multi-sensor fire detector operating on ordinary video and long wave infrared (LWIR) thermal images. The detector automatically extracts hot objects from the thermal images by dynamic background subtraction and histogram-based segmentation. Analogously, moving objects are extracted from the ordinary video by intensity-based dynamic background subtraction. These hot and moving objects are then further analyzed using a set of flame features which focus on the distinctive geometric, temporal and spatial disorder characteristics of flame regions. By combining the probabilities of these fast retrievable visual and thermal features, we are able to detect the fire at an early stage. Experiments with video and LWIR sequences of lire and non-fire real case scenarios show good results in id indicate that multi-sensor fire analysis is very promising
Synthesis of OCL Pre-conditions for Graph Transformation Rules

Proceedings of: Third International Conference on Model Transformation (ICMT 2010): Theory and Practice of Model Transformation. Málaga, Spain, 28 June-02 July, 2010Graph transformation (GT) is being increasingly used in Model Driven Engineering (MDE) to describe in-place transformations like animations and refactorings. For its practical use, rules are often complemented with OCL application conditions. The advancement of rule post-conditions into pre-conditions is a well-known problem in GT, but current techniques do not consider OCL. In this paper we provide an approach to advance post-conditions with arbitrary OCL expressions into pre-conditions. This presents benefits for the practical use of GT in MDE, as it allows: (i) to automatically derive pre-conditions from the meta-model integrity constraints, ensuring rule correctness, (ii) to derive pre-conditions from graph constraints with OCL expressions and (iii) to check applicability of rule sequences with OCL conditions.Work funded by the Spanish Ministry of Science and Innovation through projects “Design and construction of a Conceptual Modeling Assistant” (TIN2008-00444/TIN - Grupo Consolidado), “METEORIC” (TIN2008-02081),mobility grants JC2009-00015 and PR2009-0019, and the R&D program of the Community of Madrid (S2009/TIC-1650, project “e-Madrid”).Publicad
A new human identification protocol and Coppersmith's baby-step giant-step algorithm

We propose a new protocol providing cryptographically secure authentication to unaided humans against passive adversaries. We also propose a new generic passive attack on human identification protocols. The attack is an application of Coppersmith’s baby-step giant-step algorithm on human identification protcols. Under this attack, the achievable security of some of the best candidates for human identification protocols in the literature is further reduced. We show that our protocol preserves similar usability while achieves better security than these protocols. A comprehensive security analysis is provided which suggests parameters guaranteeing desired levels of security
Shrinking the keys of discrete-log-type lossy trapdoor functions

To this day, realizations in the standard-model of (lossy) trapdoor functions from discrete-log-type assumptions require large public key sizes, e.g., about Θ(λ 2) group elements for a reduction from the decisional Diffie-Hellman assumption (where λ is a security parameter). We propose two realizations of lossy trapdoor functions that achieve public key size of only Θ(λ) group elements in bilinear groups, with a reduction from the decisional Bilinear Diffie-Hellman assumption.\ud
\ud
Our first construction achieves this result at the expense of a long common reference string of Θ(λ 2) elements, albeit reusable in multiple LTDF instantiations. Our second scheme also achieves public keys of size Θ(λ), entirely in the standard model and in particular without any reference string, at the cost of a slightly more involved construction.\ud
\ud
The main technical novelty, developed for the second scheme, is a compact encoding technique for generating compressed representations of certain sequences of group elements for the public parameters
Automatic phases recognition in pituitary surgeries by microscope images classification

International audienceThe segmentation of the surgical workflow might be helpful for providing context-sensitive user interfaces, or generating automatic report. Our approach focused on the automatic recognition of surgical phases by microscope image classification. Our workflow, including images features extraction, image database labelisation, Principal Component Analysis (PCA) transformation and 10-fold cross-validation studies was performed on a specific type of neurosurgical intervention, the pituitary surgery. Six phases were defined by an expert for this type of intervention. We thus assessed machine learning algorithms along with the data dimension reduction. We finally kept 40 features from the PCA and found a best correct classification rate of the surgical phases of 82% with the multiclass Support Vector Machine
Human perception in segmentation of sketches

In this paper, we study the segmentation of sketched engineering 
drawings into a set of straight and curved segments. Our immediate objective is 
to produce a benchmarking method for segmentation algorithms. The criterion 
is to minimise the differences between what the algorithm detects and what 
human beings perceive. We have created a set of sketched drawings and have 
asked people to segment them. By analysis of the produced segmentations, we 
have obtained the number and locations of the segmentation points which  
people perceive. Evidence collected during our experiments supports useful  
hypotheses, for example that not all kinds of segmentation points are equally 
difficult to perceive. The resulting methodology can be repeated with other 
drawings to obtain a set of sketches and segmentation data which could be used 
as a benchmark for segmentation algorithms, to evaluate their capability to 
emulate human perception of sketches