pinecone/core-2020-05-10-deduplication huggingface dataset:
Cost Minimization of Virtual Machine Allocation in Public Clouds Considering Multiple Applications

International Conference, GECON 2017 (14. 2017. Biarritz)This paper presents a virtual machine (VM) allocation strategy to optimize the cost of VM deployments in public clouds. It can simultaneously deal with multiple applications and it is formulated as an optimization problem that takes the level of performance to be reached by a set of applications as inputs. It considers real characteristics of infrastructure providers such as VM types, limits on the number VMs that can be deployed, and pricing schemes. As output, it generates a VM allocation to support the performance requirements of all the applications. The strategy combines short-term and long-term allocation phases in order to take advantage of VMs belonging to two different pricing categories: on-demand and reserved. A quantization technique is introduced to reduce the size of the allocation problem and, thus, significantly decrease the computational complexity. The experiments show that the strategy can optimize costs for problems that could not be solved with previous approache
Anveshak - A Groundtruth Generation Tool for Foreground Regions of
  Document Images

We propose a graphical user interface based groundtruth generation tool in
this paper. Here, annotation of an input document image is done based on the
foreground pixels. Foreground pixels are grouped together with user interaction
to form labeling units. These units are then labeled by the user with the user
defined labels. The output produced by the tool is an image with an XML file
containing its metadata information. This annotated data can be further used in
different applications of document image analysis.Comment: Accepted in DAR 201
Virtual PET Images from CT Data Using Deep Convolutional Networks:
  Initial Results

In this work we present a novel system for PET estimation using CT scans. We
explore the use of fully convolutional networks (FCN) and conditional
generative adversarial networks (GAN) to export PET data from CT data. Our
dataset includes 25 pairs of PET and CT scans where 17 were used for training
and 8 for testing. The system was tested for detection of malignant tumors in
the liver region. Initial results look promising showing high detection
performance with a TPR of 92.3% and FPR of 0.25 per case. Future work entails
expansion of the current system to the entire body using a much larger dataset.
Such a system can be used for tumor detection and drug treatment evaluation in
a CT-only environment instead of the expansive and radioactive PET-CT scan.Comment: To be presented at SASHIMI2017: Simulation and Synthesis in Medical
  Imaging, MICCAI 201
An Annotation Tool for a Digital Library System of Epidermal Data

Melanoma is one of the deadliest form of skin cancers so it becomes crucial the developing of automated systems that analyze and investigate epidermal images to early identify them also reducing unnecessary medical exams. A key element is the availability of user-friendly annotation tools that can be used by non-IT experts to produce well-annotated and high-quality medical data. In this work, we present an annotation tool to manually crate and annotate digital epidermal images, with the aim to extract meta-data (annotations, contour patterns and intersections, color information) stored and organized in an integrated digital library. This tool is obtained following rigid usability principles also based on doctors interviews and opinions. A preliminary but functional evaluation phase has been conducted with non-medical subjects by using questionnaires, in order to check the general usability and the efficacy of the proposed tool
Indexing of Historical Document Images: Ad Hoc Dewarping Technique for Handwritten Text

This work presents a research project, named XDOCS, aimed at extending to a much wider audience the possibility to access a variety of historical documents published on the web. The paper presents an overview of the indexing process that will be used to achieve the goal, focusing on the adopted dewarping technique. The proposed dewarping approach performs its task with the help of a transformation model which maps the projection of a curved surface to a 2D rectangular area. The novelty introduced with this work regards the possibility of applying dewarping to document images which contain both handwritten and typewritten text
A Video Library System Using Scene Detection and Automatic Tagging

We present a novel video browsing and retrieval system for edited videos, in which videos are automatically decomposed into meaningful and storytelling parts (i.e. scenes) and tagged according to their transcript. The system relies on a Triplet Deep Neural Network which exploits multimodal features, and has been implemented as a set of extensions to the eXo Platform Enterprise Content Management System (ECMS). This set of extensions enable the interactive visualization of a video, its automatic and semi-automatic annotation, as well as a keyword-based search inside the video collection. The platform also allows a natural integration with third-party add-ons, so that automatic annotations can be exploited outside the proposed platform
A Generic Framework for Quality-based Autonomic Adaptation within Sensor-based Systems

With the growth of the Internet of Things (IoT), sensor-based systems deal with heterogeneous sources, which produce heterogeneous observations of disparate quality. Since network QoS is rarely sufficient to expertise Quality of Observation (QoO), managing such diversity at the application level is a very complex task and requires high levels of experience from application developers. Given this statement, this paper proposes a generic framework for QoO-based autonomic adaptation within sensor-based systems. An abstract architecture is first introduced, intended to bridge the gap between sensors capabilities and application needs thanks to the Autonomic Computing paradigm. Then, the framework is instantiated and practical considerations when implementing an autonomous sensor-based system are given. We illustrate this instantiation with concrete examples of sensor middlewares and IoT platforms
Provenance-Based Rumor Detection

With the advance of social media networks, people are sharing contents in an unprecedented scale. This makes social networks such as microblogs an ideal place for spreading rumors. Although different types of information are available in a post on social media, traditional approaches in rumor detection leverage only the text of the post, which limits their accuracy in detection. In this paper, we propose a provenance-aware approach based on recurrent neural network to combine the provenance information and the text of the post itself to improve the accuracy of rumor detection. Experimental results on a real-world dataset show that our technique is able to outperform state-of-the-art approaches in rumor detection.Full Tex
Exploiting partial knowledge for efficient model analysis

The advancement of constraint solvers and model checkers has enabled the effective analysis of high-level formal specification languages. However, these typically handle a specification in an opaque manner, amalgamating all its constraints in a single monolithic verification task, which often proves to be a performance bottleneck. This paper addresses this issue by proposing a solving strategy that exploits user-provided partial knowledge, namely by assigning symbolic bounds to the problem’s variables, to automatically decompose a verification task into smaller ones, which are prone to being independently analyzed in parallel and with tighter search spaces. An effective implementation of the technique is provided as an extension to the Kodkod relational constraint solver. Evaluation shows that, in average, the proposed technique outperforms the regular amalgamated verification procedure.ERDF - European Regional Development Fund(POCI-01-0145-FEDER-016826)This work is financed by the ERDF – European Regional Development Fund through the Operational Programme for Competitiveness and Internationalisation - COMPETE 2020 Programme and by National Funds through the Portuguese funding agency, FCT - Fundação para a Ciência e a Tecnologia within project POCI-01-0145-FEDER-016826.info:eu-repo/semantics/publishedVersio
A comparative study of image processing methods for the assessment of the red blood cells deformability in a microfluidic device

Red blood cells (RBCs) deformability is a high relevant mechanical property, whose variations are associated with some diseases, such as diabetes and malaria. Therefore, the present study aims to compare different image processing methods for assessing the RBCs deformability in a continuous flow, measured in a polydimethylsiloxane (PDMS) microchannel composed by 15 μm spacing inner pillars. The images were acquired with a high speed camera and analyzed with ImageJ software for tracking and measuring the RBCs deformation index (DI). Additionally, to understand the performance of the software, it was performed a comparison between different image processing tools provided by ImageJ and the best methods for the deformation measurements were selected, considering the measured RBCs number and their DIs. The results show that those image methods significantly affect the number of measured RBCs and their DIs and, therefore, the studies focused on the deformability measurements need to take into account the effect of the image processing methods for avoiding loss of relevant information in the images.This work was supported by FCT with the reference project UID/EEA/
04436/2013, by FEDER funds through the COMPETE 2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01- 0145-FEDER- 006941.
V. Faustino, S.O. Catarino and D. Pinho thank, respectively, the FCT for the grants SFRH/BD/
99696/2014, SFRH/BPD/108889/2015 and SFRH/BD/89077/2012, supported by national funds
from Ministérios da Ciência, Tecnologia e Ensino Superior and by FSE through the POCH -
Programa Operacional Capital Humano. The authors also acknowledge the financial support
provided by the project Nos. UID/EMS/00532/2013 and UID/EMS/04077/2013.info:eu-repo/semantics/publishedVersio
Visualization and measurement of the cell-free layer (CFL) in a microchannel network

In the past years, in vitro blood studies have revealed several significant hemodynamic phenomena that have played a key role in recent developments of biomedical microdevices for cells separation, sorting and analysis. However, the blood flow phenomena happening in complex geometries, such as microchannel networks, have not been fully understood. Thus, it is important to investigate in detail the blood flow behavior occurring at microchannel networks. In the present study, by using a high-speed video microscopy system, we have used two working fluids with different haematocrit (1% Hct and 15% Hct) and we have investigated the cell-free layer (CFL) in a microchannel network composed by asymmetric bifurcations. By using the Z Project method from the image analysis software ImageJ, it was possible to conclude that the successive bifurcations and confluences influence the formation of the CFL not only along the upper and lower wall of the microchannel but also at the region immediately downstream of the confluence apex.The authors acknowledge the financial support provided by the project POCI-01-0145 FEDER-016861 (with associated reference PTDC/QEQ-FTT/4287/2014), UID/EMS/00532/2013 and UID/CEC/00319/2013 funded by FCT (Foundation for Science and Technology), through national funds (PIDDAC), and FEDER through COMPETE2020 - Programa Operacional Competitividade e Internacionalização (POCI). D. Bento acknowledges the PhD scholarship SFRH/BD/91192/2012 granted by FCT.
The authors also acknowledge the financial support provided by the project Nos. UID/EMS/00532/2013 and UID/EMS/04077/2013 and the project Nos. UID/EMS/00532/2013,
UID/EMS/04077/2013, POCI-01-0145-FEDER-007043, UID/CEC/00319/2013info:eu-repo/semantics/publishedVersio
Numerical simulation of hyperelastic behaviour in aneurysm models

The aneurysm is a fragile region on the wall of a blood vessel that causes it to form a bulge. In limiting situations, this weakening can lead to vessel disruption.The authors acknowledge the financial support provided by Fundação para
a Ciência e a Tecnologia (FCT), COMPETE, and FEDER through the project POCI-01–
0145-FEDER-016861 (with associated reference PTDC/QEQ-FTT/4287/2014) funded by
COMPETE2020—Programa Operacional Competitividade e Internacionalizacao (POCI) with
the financial support of FCT/MTES through national funds (PIDDAC) and by the project Nos.
UID/EMS/00532/2013, and UID/EMS/04077/2013.info:eu-repo/semantics/publishedVersio
Red blood cells (RBCs) visualisation in bifurcations and bends

Bifurcating networks are commonly found in nature. One example is the microvascular system, composed of blood vessels consecutively branching into daughter vessels, driving the blood into the capillaries, where the red blood cells (RBCs) are responsible for delivering O 2 and up taking cell waste and CO 2 . In this preliminary study, we explore a microfluidic bifurcating geometry inspired by such biological models, for investigating RBC partitioning as well as RBC-plasma separation favored by the consecutive bifurcating channels. A biomimetic design rule [1] based on Murray’s law [2] was used to set the channels’ dimensions along the network, which consists of consecutive bifurcating channels of reducing diameter. The ability to apply differential flow resistances by controlling the flow rates at the end of the network allowed us to monitor the formation of a cell-free layer (CFL) for different flow conditions at haematocrits of 1% and 5%. We have also compared the values of CFL thickness determined directly by the measurement on the projection image created from a stack of images or indirectly by analyzing the intensity profile in the same projection. The results obtained from this study confirm the potential to study RBC partitioning along bifurcating networks, which could be of particular interest for the separation of RBCs from plasma in point-of-care devices.JF would like to thank Professor Graça Minas and her coworkers for
providing the laboratory facilities and technical help during the experiments.info:eu-repo/semantics/publishedVersio
A dual-modal CT/US kidney phantom model for image-guided percutaneous renal access

Percutaneous renal access (PRA) is a crucial step in some minimally invasive kidney interventions. During this step, the surgeon inserts a needle through the skin until the kidney target site using fluoroscopy and ultrasound imaging. Recently, new concepts of enhanced image-guided interventions have been introduced in these interventions. However, their validation remains a challenging task. Phantom models have been presented to solve such challenge, using realistic anatomies in a controlled environment. In this work, we evaluate the accuracy of a porcine kidney phantom for validation of novel dual-modal computed tomography (CT)/ultrasound (US) image-guided strategies for PRA. A porcine kidney was combined with a tissue mimicking material (TMM) and implanted fiducial markers (FM). While the TMM mimics the surrounding tissues, the FM are used to accurately assess the registration errors between the US and CT images, providing a valid ground-truth. US and CT image acquisitions of the phantom model were performed and the FM were manually selected on both images. A rigid alignment was performed between the selected FM, presenting a root-mean-square error of 1.1 mm. Moreover, the kidney was manually segmented, presenting volumes of 203 ml and 238 ml for CT and US, respectively. The initial results are promising on achieving a realistic kidney phantom model to develop new strategies for PRA, but further work to improve the manufacturing process and to introduce motion and anatomical artifacts in the phantom is still required.This work has been funded by FEDER funds, through the Competitiveness Factors
Operational Programme (COMPETE), and by National funds, through the Foundation for Science
and Technology (FCT), under the scope of the project NORTE-01-0145-FEDER-000013, supported
by the NORTE 2020, under the Portugal 2020 Partnership Agreement, through the
European Regional Development Fund (FEDER). J. Gomes-Fonseca, A. Miranda, P. Morais, and
S. Queirós were funded by FCT under the Ph.D. grants PD/BDE/113597/2015, SFRH/BD/52059/
2012, SFRH/BD/95438/2013, and SFRH/BD/93443/2013, respectively.info:eu-repo/semantics/publishedVersio
Monitoring of bioelectrical and biomechanical signals in Taekwondo training: first insights

Taekwondo is an Olympic combat sport that has gained much popularity in the last years. Portugal is not an exception to the substantial growth of this martial art. Currently there are about 4500 practitioners of this art affiliated in the national federation. Several have already produced excellent results not only in national but also in international competitions, recognized by the International Olympic Com-mittee of Portugal, Taekwondo European Union and the World Taekwondo Feder-ation (WTF). This work is a joint project between the University of Minho, Sporting Club de Braga Taekwondo section and the National Technical Team of the Portu-guese Federation of Taekwondo. It is aimed at developing a system to analyse, mon-itor and quantify the athlete performance in real time. The developed system should be able to help the athlete improve his/her technique and performance by monitoring his/her heart rate, analyzing and identifying the technical movements in the training by comparing the various movements performed, as well as quantifying variables related to the athlete’s performance. Visual cues for the heart rate and performance are indicated by LEDs. With this system, we propose a contribution to innovation and development in Taekwondo training.This work is financed by FEDER funds through the Competitivity Factors Op-erational Program - COMPETE and by national funds through FCT – Foundation for Science and Technology within the scope of the project POCI-01-0145-FEDER-007136. Pedro Cunha thanks FCT for PhD scholarship SFRH/BD/121994/2016. Special thanks to Coach Joaquim Peixoto, as well as Sport Club de Braga Taekwondo section and to the national team, for allowing us to use their training site, as well as seeing/participating in training to test the developed system, and in general, for all the cooperation provided.info:eu-repo/semantics/acceptedVersio
Recording of occurrences through image processing in Taekwondo training: first insights

Nowadays, the most used evaluation method of athlete’s performance in the martial art Taekwondo is still performed manually, where the coach analyses the collected videos of the athlete training. This method besides being time consuming, it is prone to errors. Aiming the development of methods for improvement the training, this project intends to present a new method for recording occurrences and recognizing the movements of athletes in real time during the Taekwondo training. To achieve the purpose, it was used the Microsoft Kinect sensor fused with image processing technics. This project arises as a collaboration between the University of Minho, the School of Technology from the Polytechnic Institute of Cávado and Ave and the Sporting Club de Braga Taekwondo section, Portugal. It is the authors believe that the proposed system may improve the athlete’s performance and the development of the Taekwondo training technics.The authors would like also to express their acknowledgments to COMPETE: POCI-01-0145-FEDER-007043 and FCT – Fundação para a Ciência e Tecnologia within the Project Scope: UID/CEC/00319/2013. Pedro Cunha thanks FCT for PhD scholarship SFRH/BD/121994/2016. Special thanks to Coach Joaquim Peixoto, as well as Sport Club de Braga Taekwondo section and to the national team, for allowing us to use their training 10 site, as well as seeing/participating in training to test the developed system, as in general for all the cooperation. Additional thanks to Ricardo Guimarães from Vitória Sport Clube Taekwondo team for testing the first versions of the system and help with the calibration of the system.info:eu-repo/semantics/acceptedVersio
iBoccia: a framework to monitor the Boccia gameplay in elderly

The increase of the elderly population has an enormous effect on the health
care system of a country, as the rise of this population sets the mood to an exponential
growth in assistance and care. Indeed, the inherent costs of this populational
class are higher when comparing to the younger classes. Today paradigm focuses
on the reduction of these costs by promoting a healthier lifestyle on all classes of
the populations. Thus, the concern of a more active lifestyle is present in the elderly
population, which has proven to reduce, for example, the risk of coronary problems.
The stimulus on physical activity is now higher and it is possible to get several
monitoring devices to keep track on the activity that was performed. Following this
trend, the present paper presents a hybrid approach that employs the use of wearable
devices, the Mio Fuse band and the pandlet, and a non-wearable device, the Kinect
camera, to monitor elderly people during a Boccia game scenario. Preliminary tests
were performed in laboratory. The results include data collected concerning a main
movement that is used during a Boccia gameplay.This article is a result of the project Deus ex machina: NORTE-01-0145-
FEDER-000026, supported by Norte Portugal Regional Operational Programme (NORTE 2020),
under the PORTUGAL 2020 Partnership Agreement, through the European Regional Development
Fund (ERDF).info:eu-repo/semantics/publishedVersio
Practical update management in ontology-based data access

Ontology-based Data Access (OBDA) is gaining importance both scientifically and practically. However, little attention has been paid so far to the problem of updating OBDA systems. This is an essential issue if we want to be able to cope with modifications of data both at the ontology and at the source level, while maintaining the independence of the data sources. In this paper, we propose mechanisms to properly handle updates in this context. We show that updating data both at the ontology and source level is first-order rewritable. We also provide a practical implementation of such updating mechanisms based on non-recursive Datalog.Peer ReviewedPostprint (author's final draft
The Efficacy of OWL and DL on User Understanding of Axioms and Their Entailments

OWL is recognized as the de facto standard notation for on- tology engineering. The Manchester OWL Syntax (MOS) was developed as an alternative to symbolic description  logic (DL) and it is believed to be more eective for users. This paper sets out to test that belief from two perspectives by evaluating how accurately and quickly people understand the informational content of axioms and derive inferences from them. By conducting a between-group empirical study, involving 60 novice participants, we found that DL is just as eective as MOS for people's understanding of axioms. Moreover, for two types of inference problems, DL supported signi cantly better task performance than MOS, yet MOS never signi cantly outperformed DL. These surprising results suggest that the belief that MOS is more eective than DL, at least for these types of task, is unfounded. An outcome of this research is the suggestion that ontology axioms, when presented to non experts, may be better presented in DL rather than MOS. Further empirical studies are needed to explain these unexpected results and to see whether they hold for other types of task