pinecone/core-2020-05-10-deduplication huggingface dataset:
Electronic health record in dermatology service

In this paper we describe the implementation of an Electronic Health Record in the Dermatology service of a Portuguese hospital. This system must follow the principle of simplicity, enabling recording quality and analytical processing. Standards and norms were also followed and it is shown that interoperability has a key role in the whole process. This project is a good example of cooperation between academic and healthcare institutions and shows the impact of new technology on healthcare organizations.Fundação para a Ciência e a Tecnologia (FCT
Data acquisition process for an intelligent decision support in gynecology and obstetrics emergency triage

Manchester Triage System is a reliable system of triage in the emergency department of a hospital. This system when applied to a specific patients’ condition such the pregnancy has several limitations. To overcome those limitations an alternative triage IDSS was developed in the MJD. In this approach the knowledge was obtained directly from the doctors’ empirical and scientific experience to make the first version of decision models. Due to the particular gynecological and/or obstetrics requests other characteristics had been developed, namely a system that can increase patient safety for women in need of immediate care and help low-risk women avoid high-risk care, maximizing the use of resources. This paper presents the arrival flowchart, the associated decisions and the knowledge acquisition cycle. Results showed that this new approach enhances the efficiency and the safety through the appropriate use of resources and by assisting the right patient in the right place.The work of Filipe Portela was supported by the grant SFRH/BD/70156/2010 from FC
Grid data mining for outcome prediction in intensive care medicine

This paper introduces a distributed data mining approach suited to grid computing environments based on a supervised learning classifier system. Specific Classifier and Majority Voting methods for Distributed Data Mining (DDM) are explored and compared with the Centralized Data Mining (CDM) approach. Experimental tests were conducted considering a real world data set from the intensive care medicine in order to predict the outcome of the patients. The results demonstrate that the performance of the DDM methods are better than the CDM method.Fundação para a Ciência e a Tecnologia (FCT
Electrocardiogram events detection

This work aims to create a system of medical diagnosis of the Electrocardiogram (ECG). The events of the ECG are related with the functioning of the heart and different disorders of the heart functioning have their own ECG pattern allowing the connection between ECG patterns and cardiac disorders. For this purpose, we present here an algorithm that detects the P, QRS and T events of the ECG under MATLAB environment. The algorithm is based in two techniques. The search for picks and valleys and the search of event using a known patter and the correlation with ECG signal inside of a previously detected period. Finally the results are presented and discussed
An iTV audio description service: suggesting requirements and features for visually impaired users

The ongoing Digital Terrestrial Television (DTT) switchover leads to an interesting opportunity for the implementation of advanced television services. Actually, these services can even be interactive, since it is foreseen that the required Set-Top Boxes (STB) could be equipped with an Internet connection. However, among the future clients of DTT there are a large number of elderly and visually impaired people who can not entirely benefit of these services due to their physical limitations. Nevertheless, considering that Interactive Television (iTV) services can contribute to improve life quality of this type of users, it is essential to apply accessibility, usability and design-oriented guidelines for their development. In this context, this paper introduces a research related to universal design applied to iTV, being its aim to propose an advanced and accessible audio description service. In order to perceive the visually impaired users’ problems and needs, a group of individuals was asked to participate in an interview
Back-propagation artificial neural network for ERP adoption cost estimation

Published version of a chapter in the book: Enterprise information systems, vol 220, part 2, 180-187. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-24355-4_19Small and medium size enterprises (SMEs) are greatly affected by cost escalations and overruns Reliable cost factors estimation and management is a key for the success of Enterprise Resource Planning (ERP) systems adoptions in enterprises generally and SMEs specifically. This research area is still immature and needs a considerable amount of research to seek solid and realistic cost factors estimation. Majority of research in this area targets the enhancement of estimates calculated by COCOMO family models. This research is the beginning of a series of models that would try to replace COCOMO with other models that could be more adequate and focused on ERP adoptions. This paper introduces a feed-forward back propagation artificial neural network model for cost factors estimation. We comment on results, merits and limitations of the model proposed. Although the model addresses SMEs, however, it could be extended and applied in various environments and contexts
Developing an instrument to assess information technology staff motivation

Motivation is a key factor that influences individual effort, which, in turn, affects individual and organizational performance. Nevertheless, motivation at work depends on the organizational rewards and incentives, according to individual goals. This paper reports on the development of an instrument designed to measure the motivation of Information Technology people at their workplace. Psychology theories and work addressing intrinsic and extrinsic motivation have been studied. Some motivation instruments were reviewed and analyzed. Specificities and special characteristics regarding IT workers were evidenced and combined with other more general motivation factors. The instrument has been developed according to the five dimensions of the Worldatwork framework, resulting in a set of 30 scale items addressing 23 variables. Besides measuring the IT motivation levels, the tool may also help any organization to understand the weaknesses and strengths regarding incentive policies, and therefore, assist on the definition of new ones
ERP lifecycle: When to retire your ERP system?

Published version of a chapter in the book: Enterprise information systems, vol 219, part 3, 168-177. Also available from the publisher at: http://dx.doi.org/10.1007/978-3-642-24358-5_17A lot of research has been undertaken focusing on ERP systems lifecycles, but very little paid attention to retirement. ERP retirement means the replacement of an ERP with another. The aim of this research paper is to investigate why and when should organizations retire their ERP systems. A convenience case study of an SME has been selected from Egypt. The case study under investigation has retired their local ERP system and replaced it with SAP ERP. Results of our analysis indicated that reasons of retirement were: wrong selection, users were not involved in the selection process, and lack of an official implementation methodology. This is considered a new finding since main stream literature was mainly focused on retirement after maturity
Tailoring temporal description logics for reasoning over temporal conceptual models

Temporal data models have been used to describe how data can evolve in the context of temporal databases. Both the Extended Entity-Relationship (EER) model and the Unified Modelling Language (UML) have been temporally extended to design temporal databases. To automatically check quality properties of conceptual schemas various encoding to Description Logics (DLs) have been proposed in the literature. On the other hand, reasoning on temporally extended DLs turn out to be too complex for effective reasoning ranging from 2ExpTime up to undecidable languages. We propose here to temporalize the ‘light-weight’ DL-Lite logics obtaining nice computational results while still being able to represent various constraints of temporal conceptual models. In particular, we consider temporal extensions of DL-Lite^N_bool, which was shown to be adequate for capturing non-temporal conceptual models without relationship inclusion, and its fragment DL-Lite^N_core with most primitive concept inclusions, which are nevertheless enough to represent almost all types of atemporal constraints (apart from\ud
covering)
Universal prediction of selected bits

Many learning tasks can be viewed as sequence prediction problems. For example, online classification can be converted to sequence prediction with the sequence being pairs of input/target data and where the goal is to correctly predict the target data given input data and previous input/target pairs. Solomonoff induction is known to solve the general sequence prediction problem, but only if the entire sequence is sampled from a computable distribution. In the case of classification and discriminative learning though, only the targets need be structured (given the inputs). We show that the normalised version of Solomonoff induction can still be used in this case, and more generally that it can detect any recursive sub-pattern (regularity) within an otherwise completely unstructured sequence. It is also shown that the unnormalised version can fail to predict very simple recursive sub-patterns
Axioms for rational reinforcement learning

We provide a formal, simple and intuitive theory of rational decision making including sequential decisions that affect the environment. The theory has a geometric flavor, which makes the arguments easy to visualize and understand. Our theory is for complete decision makers, which means that they have a complete set of preferences. Our main result shows that a complete rational decision maker implicitly has a probabilistic model of the environment. We have a countable version of this result that brings light on the issue of countable vs finite additivity by showing how it depends on the geometry of the space which we have preferences over. This is achieved through fruitfully connecting rationality with the Hahn-Banach Theorem. The theory presented here can be viewed as a formalization and extension of the betting odds approach to probability of Ramsey and De Finetti [Ram31, deF37]
Time consistent discounting

A possibly immortal agent tries to maximise its summed discounted rewards over time, where discounting is used to avoid infinite utilities and encourage the agent to value current rewards more than future ones. Some commonly used discount functions lead to time-inconsistent behavior where the agent changes its plan over time. These inconsistencies can lead to very poor behavior. We generalise the usual discounted utility model to one where the discount function changes with the age of the agent. We then give a simple characterisation of time-(in)consistent discount functions and show the existence of a rational policy for an agent that knows its discount function is time-inconsistent
Successful reuse of software components: A report from the open source perspective

Copyright @ 2011 Springer Berlin HeidelbergA promising way of software reuse is Component-Based Software Development (CBSD). There is an increasing number of OSS products available that can be freely used in product development. However, OSS communities themselves have not yet taken full advantage of the “reuse mechanism”. Many OSS projects duplicate effort and code, even when sharing the same application domain and topic. One successful counter-example is the FFMpeg multimedia project, since several of its components are widely and consistently reused into other OSS projects. This paper documents the history of the libavcodec library of components from the FFMpeg project, which at present is reused in more than 140 OSS projects. Most of the recipients use it as a black-box component, although a number of OSS projects keep a copy of it in their repositories, and modify it as such. In both cases, we argue that libavcodec is a successful example of reusable OSS library of components.The work of Klaas-Jan Stol is partially funded by IRCSET under grant no. RS/2008/134 and by Science Foundation Ireland grant 03/CE2/I303 1 to Lero (www.lero.ie)
Joint T1 and Brain Fiber Diffeomorphic Registration Using the Demons

International audienceNon-linear image registration is one of the most challenging task in medical image analysis. In this work, we propose an extension of the well-established diffeomorphic Demons registration algorithm to take into account geometric constraints. Combining the deformation field induced by the image and the geometry, we define a mathematically sound framework to jointly register images and geometric descriptors such as fibers or sulcal lines. We demonstrate this framework by registering simultaneously T 1 images and 50 fiber bundles consistently extracted in 12 subjects. Results show the improvement of fibers alignment while maintaining, and sometimes improving image registration. Further comparisons with non-linear T 1 and tensor registration demonstrate the superiority of the Geometric Demons over their purely iconic counterparts
Identifying Neuroimaging and Proteomic Biomarkers for MCI and AD via the Elastic Net

Multi-modal neuroimaging and biomarker data provide exciting opportunities to enhance our understanding of phenotypic characteristics associated with complex disorders. This study focuses on integrative analysis of structural MRI data and proteomic data from an RBM panel to examine their predictive power and identify relevant biomarkers in a large MCI/AD cohort. MRI data included volume and thickness measures of 98 regions estimated by FreeSurfer. RBM data included 146 proteomic analytes extracted from plasma and serum. A sparse learning model, elastic net logistic regression, was proposed to classify AD and MCI, and select disease-relevant biomarkers. A linear support vector machine coupled with feature selection was employed for comparison. Combining RBM and MRI data yielded improved prediction rates: HC vs AD (91.9%), HC vs MCI (90.5%) and MCI vs AD (86.5%). Elastic net identified a small set of meaningful imaging and proteomic biomarkers. The elastic net has great power to optimize the sparsity of feature selection while maintaining high predictive power. Its application to multi-modal imaging and biomarker data has considerable potential for discovering biomarkers and enhancing mechanistic understanding of AD and MCI
Implementation architecture and multithreaded runtime system of S-Net.

S-NET is a declarative coordination language and component technology aimed at modern multi-core/many-core architectures and systems-on-chip. It builds on the concept of a stream processing to structure networks of communicating asynchronous components, which can be implemented using a conventional (sequential) language. In this paper we present the architecture of our S-NET implementation. After sketching out the interplay between compiler and runtime system, we characterise the deployment and operational behaviour of our multi-threaded runtime system for contemporary multi-core processors. Preliminary runtime figures demonstrate the effectiveness of our approach
Impact of the initialization in tree-based fast similarity search techniques

Many fast similarity search techniques relies on the use of pivots (specially selected points in the data set). Using these points, specific structures (indexes) are built speeding up the search when queering. Usually, pivot selection techniques are incremental, being the first one randomly chosen. This article explores several techniques to choose the first pivot in a tree-based fast similarity search technique. We provide experimental results showing that an adequate choice of this pivot leads to significant reductions in distance computations and time complexity. Moreover, most pivot tree-based indexes emphasizes in building balanced trees. We provide experimentally and theoretical support that very unbalanced trees can be a better choice than balanced ones.The authors thank the Spanish CICyT for partial support of this work through projects TIN2009-14205-C04-C1, the Ist Programme of the European Community, under the Pascal Network of Excellence, (Ist–
2006-216886), and the program Consolider Ingenio 2010 (Csd2007-00018)
Vision Paper: Make a Difference! (Semantically)

International audienceSyntactic difference between models is a wide research area with applications in tools for model evolution, model synchronization and version control. On the other hand, semantic difference between models is rarely discussed. We point out to main use cases of semantic difference between models, and then propose a framework for defining well-formed difference operators on model semantics as adjoints of model combinators such as conjunction, disjunction and structural composition. The framework is defined by properties rather than constructively. We instantiate the framework for two rather different modeling languages: feature models and automata specifications. We believe that the algebraic theory of semantic difference will allow to define practical model differencing tools in the future
Modeling Model Slicers

International audienceAmong model comprehension tools, model slicers are tools that extract a subset from a model, for a specific purpose. Model slicers are tools that let modelers rapidly gather relevant knowledge from large models. However, existing slicers are dedicated to one modeling language. This is an issue when we observe that new domain specific modeling languages (DSMLs), for which we want slicing abilities, are created almost on a daily basis. This paper proposes the Kompren language to model and generate model slicers for any DSL (e.g. software development and building architecture) and for different purposes (e.g. monitoring and model comprehension). Kompren's abilities for model slicers construction is based on case studies from various domains
Quality of Service and Quality of Experience Correlations in a Location-Based Mobile Multiplayer Role-Playing Game

The well-established Quality of Service and the relatively recently emerged Quality of Experience research topics are unquestionably linked, yet to date little effort has been invested in the study of their precise correlation and mutual reciprocity. This paper examines the impact of three representative QoS-related parameters on user QoE in the particular context of location-based multiplayer games played on mobile devices. The choice for this research context is motivated by the rapidly expanding popularity of this application domain. Analysis of the quantitative and qualitative results from an empirical study involving 32 participants confirms that modifications in the performance of the investigated technical parameters does indeed hold implications for the quality of the users’ experiences; at the same time, the results clarify the magnitude of these implications. Our findings are valuable as they provide practical insight in the QoS/QoE relationship and can hence aid software developers in delivering high-quality usage experiences to their customers.status: publishe
Self-organizing urban transportation systems

Urban transportation is a complex phenomenon. Since many agents are
constantly interacting in parallel, it is difficult to predict the future state
of a transportation system. Because of this, optimization techniques tend to
give obsolete solutions, as the problem changes before it can be optimized. An
alternative lies in seeking adaptive solutions. This adaptation can be achieved
with self-organization. In a self-organizing transportation system, the
elements of the system follow local rules to achieve a global solution. Like
this, when the problem changes the system can adapt by itself to the new
configuration.
  In this chapter, I will review recent, current, and future work on
self-organizing transportation systems. Self-organizing traffic lights have
proven to improve traffic flow considerably over traditional methods. In public
transportation systems, simple rules are being explored to prevent the "equal
headway instability" phenomenon. The methods we have used can be also applied
to other urban transportation systems and their generality is discussed.Comment: Final version to be published in "Complexity theories of cities have
  come of age", edited by Juval Portugali and Han Meyer, Springer, 201
Formal Verification of Consensus Algorithms Tolerating Malicious Faults

International audienceConsensus is the paradigmatic problem in fault-tolerant distributed computing: it requires network nodes that communicate by message passing to agree on a common value even in the presence of (benign or malicious) faults. Several algorithms for solving Consensus exist, but few of them have been rigorously verified, much less so formally. The Heard-Of model proposes a simple, unifying framework for defining distributed algorithms in the presence of communication faults. Algorithms proceed in communication-closed rounds, and assumptions on the faults tolerated by the algorithm are stated abstractly in the form of communication predicates. Extending previous work on the case of benign faults, our approach relies on the fact that properties such as Consensus can be verified over a coarse-grained, round-based representation of executions. We have encoded the Heard-Of model in the interactive proof assistant Isabelle/HOL and have used this encoding to formally verify three Consensus algorithms based on synchronous and asynchronous assumptions. Our proofs give some new insights into the correctness of the algorithms, in particular with respect to transient faults
Towards a model checker for NesC and wireless sensor networks

Wireless sensor networks (WSNs) are expected to run unattendedly for critical tasks. To guarantee the correctness of WSNs is important, but highly nontrivial due to the distributed nature. In this work, we present an automatic approach to directly verify WSNs built with TinyOS applications implemented in the NesC language. To achieve this target, we firstly define a set of formal operational semantics for most of the NesC language structures for the first time. This allows us to capture the behaviors of sensors by labelled transition systems (LTSs), which are the underlying semantic models of NesC programs. Secondly, WSNs are modeled as the composition of sensors with a network topology. Verifications of individual sensors and the whole WSN become possible by exploring the corresponding LTSs using model checking. With substantial engineering efforts, we implemented this approach in the tool NesC@PAT to support verifications of deadlock-freeness, state reachability and temporal properties for WSNs. NesC@PAT has been applied to analyze and verify WSNs, with unknown bugs being detected. To the best of our knowledge, NesC@PAT is the first model checker which takes NesC language as the modeling language and completely preserves the interrupt-driven feature of the TinyOS execution model.Full Tex