Miracle-dz/UniFAR-FTUs huggingface dataset:
A typology of educationally focused medical simulation tools

Background: The concept of simulation as an educational tool in healthcare is not a new idea but its use has really blossomed over the last few years. This enthusiasm is partly driven by an attempt to increase patient safety and also because the technology is becoming more affordable and advanced. Aims: Simulation is becoming more commonly used for initial training purposes as well as for continuing professional development, but people often have very different perceptions of the definition of the term simulation, especially in an educational context. This highlights the need for a clear classification of the technology available but also about the method and teaching approach employed. The aims of this paper are to discuss the current range of simulation approaches and propose a clear typology of simulation teaching aids. Method: Commonly used simulation techniques have been identified and discussed in order to create a classification that reports simulation techniques, their usual mode of delivery, the skills they can address, the facilities required, their typical use, and their pros and cons. Results: This paper presents a clear classification scheme of educational simulation tools and techniques with six different technological levels. They are respectively: written simulations, three-dimensional models, screen-based simulators, standardized patients, intermediate fidelity patient simulators, and interactive patient simulators. This typology allows the accurate description of the simulation technology and the teaching methods applied. Thus valid comparison of educational tools can be made as to their potential effectiveness and verisimilitude at different training stages. Conclusions: The proposed typology of simulation methodologies available for educational purposes provides a helpful guide for educators and participants which should help them to realise the potential learning outcomes at different technological simulation levels in relation to the training approach employed. It should also be a useful resource for simulation users who are trying to improve their educational practice.
Face recognition using LBP for personal image management system and its analysis

In this paper, LBP and its variant were tested on Family Face Database which was constructed in the earlier work by the author [1] in the framework of personal image management system. The combination of LBP and other features were also tested for comparison. In addition, several illumination normalizing methods, dissimilarity measures and sub-block divisions were also tested in our framework.
Information technology and competitors: a case for collaborative advantage

Competitors who view information technology exclusively as a strategic weapon for competitive advantage risk missing a valuable opportnnit y: the use of information technology in conjunction with competitors for collaborative advantage. Collaborative advantage is defined as the benefit gained by a group of participants as the result of their cooperation rather than their competition. Experiences in the development of a community health information net work provide significant les~sonsabout such a use of information technology. A description of the creation of a multi-organizational information system among seven competing hospitals in Dayton, Ohio, contributes to the development of a needed body of literature regwding information technology f or collaborative adv:int age. an important phenomenon that is notably scarce in the current literature.
DALI! - Drawing Animated Lines!

We present an animation system for the creation of non-photorealistic 3D animations. Our system daLi! is able to render images using a common 3D model as input. This model may be enriched with additional information concerning for instance hierarchy, structure and presentation style. The rendering is done analytically, which means the output is resolution independent. It results in a series of images that depict the animation using line-drawings. The implementation of daLi! was completely done in Smalltalk.
Is No Child Left Behind an Un (or Under) funded Federal Mandate? Evidence from Texas

The No Child Left Behind Act of 2001 requires states to establish goals for all students and for groups of students characterized by race, ethnicity, poverty, disability, and limited English proficiency, and requires schools to make annual progress in meeting these goals. In a number of states, officials have argued that increased federal education funding is not sufficient to cover the costs imposed by the new legislation. In this paper, we use data from Texas to estimate the additional costs of meeting the new student performance standards. We find that these costs substantially exceed the additional federal funding.
Visual activity recognition based on depth contour image

In this paper, a novel visual activity recognition algorithm based on the depth contour image and nearest neighbor (NN) classifier is presented, where the depth contour image is acquired by solving algebraic matrix equations in terms of the newly-defined Spatial Motion Accumulative Image (SMAI) and Temporal Motion Accumulative Image (TMAI). More precisely, firstly, SMAI and TMAI are defined based on the binary image sequences of action video segments; secondly, the pixel values in SMAI are re-evaluated by the average traveling time for (virtual) free particles from the corresponding pixel positions to the contour border with the so-called TMAI-determined speed, which leads to the proposed depth contour image; thirdly, the principal component analysis (PCA) is applied to extract the feature vectors from the depth contour image to characterize human actions; finally, the NN classifier is used to recognize the human actions. Experimental results on the open Weizmann activity database confirm the expected recognition performance of the proposed algorithm.
Performance comparison of GPU and FPGA architectures for the SVM training problem

The Support Vector Machine (SVM) is a popular supervised learning method, providing high accuracy in many classification and regression tasks. However, its training phase is a computationally expensive task. In this work, we focus on the acceleration of this phase and a geometric approach to SVM training based on Gilbert's Algorithm is targeted, due to the high parallelization potential of its heavy computational tasks. The algorithm is mapped on two of the most popular parallel processing devices, a Graphics Processor and an FPGA device. The evaluation analysis points out the best choice under different configurations. The final speed up depends on the problem size, when no chunking techniques are applied to the training set, achieving the largest speed up for small problem sizes.
RADIOMETRIC CALIBRATION METHODS FOR CHANGE DETECTION ANALYSIS OF SATELLITE DATA AIMED AT ENVIRONMENTAL RISK MONITORING

The research proposes the investigation of automatic methods, in order to prepare next Change detection techniques for environmental risk monitoring, executable on satellite data that are heterogeneous for spatial and spectral resolution. Homogenization and registration in an unique digital information environment, with the identification and quantification of variation occurred in a chosen test area, will permit the rapid evaluation of risk level and the consequent planning of prevention and intervention works. To that end, the most suitable radiometric correction techniques and the development of innovative algorithms and automatic methodology were executed, in order to improve the accuracy level of results. With this aim, the relative radiometric normalization scene-to-scene with ELC (Empirical Line Calibration) and MAD (Multivariate Alteration Detection) techniques on Landsat ETM+ and ASTER data were investigated. In the ELC technique Pseudo-Invariant Features (PIFs) were manually selected, whereas the Features to derive the normalization coefficients were automatically identified with the aid of an algorithm based on MAD transformation. The exactness of both the procedures was evaluated by executing a quantitative and qualitative comparison of gains and offset values resulted in the analysis.
YML / LAKe Web Portal : Web based research portal for linear algebra application

In the passed decades the development of the numerical libraries was a response to the needs in the field of high performance computing. With the advent of the GRID computing, it becomes necessary to adapt these libraries and or their subroutines as components and to integrate them in a global computing system. To allow the end-user to be concerned by its science activity and not by the implementation details of the tools used, the infrastructures complexity of the GRID must be hidden to him. Indeed, a GRID computing environment, proposing services such as numerical libraries, must offer a convivial web portal to the user. GRID portals can interact with underlying middleware using integrated workflow engines and with the components constituting a library relying integrated implementation catalogs. This paper presents a web based solution for scientific computation portals. The proposed portal example is based on the integration of LAKe, a component-oriented library in the YML workflow engine. YML is composed of several tools allowing workflow graph description adaptable to several middleware and LAKe is an object-oriented linear algebra class library. By using a representative numerical hybrid method we show the interest of our high-level application portal.
On the cosmological evolution of the FR II radio source population

We present an analytical model for the cosmological evolution of the FR II source population. Based on an earlier model for the intrinsic radio luminosity -- linear size evolution of these objects, we construct theoretical source samples. The source distributions in the radio power -- linear size plane of these samples are then compared with that of an observed flux-limited sample. We find that the source parameters determining the radio luminosity of FR II objects cannot be independent of each other. The best-fitting models predict the jet power to be correlated either with the lifetime of the source or with the shape of the density distribution of the source environment. The latter case is consistent with the observed tendency of the most luminous radio sources at high redshift to be located in richer and more extended environments than their low redshift counterparts. We also find evidence for a class of FR II sources distinctly different from the main population. These sources are extremely old and/or are located in very underdense environments. The luminosity function of FR II sources resulting from the model is in good agreement with previous results for high-luminosity sources. The apparent luminosity evolution of the radio luminosity function is not reproduced because of the high flux limit of the comparison sample used. The cosmological evolution of the median linear size of FR II sources is found to be mild.
E-wobble: An electronic wobble board for ankle and toe rehabilitation

Foot-drop is a common symptom among post stroke patients. It is characterized by the inability of a person to raise his/her foot at the ankle and to drag the toes during swing. To overcome such disability, long-term rehabilitation is crucial. However, such treatment might not be accessible to many people, especially those living far from the cities where most of the rehabilitation centers are located. In this paper, we present our interactive rehabilitation system called “E-Wobble” that consists of a modified version of a wobble board mounted with sensors and actuators. The proposed system aims to help patients with foot-drop symptoms so they can train their ankles and toes from home. The E-Wobble tangible interface is associated with a 2D golf game that motivates the patients to spend more time exercising while having fun.
Anti-Reconnaissance Tools: Detecting Targeted Socialbots

Advanced attackers use online social networks to extract useful information about the target organization, including its members and their connections, affiliations, and positions. Socialbots are artificial, machine-operated, social network profiles that connect to real members of an organization, greatly increasing the amount of information an attacker can collect. To connect socialbots, attackers can employ several strategies. The authors' approach hunts socialbots using a carefully chosen monitoring strategy by intelligently selecting organization member profiles and monitoring their activity. Their results demonstrate their method's efficacy-specifically, when attackers know the defense strategy being deployed, the attack they will most likely use is randomly sprayed friend requests, which eventually lead to a low number of connections.
Environmental Model Adaptation Based on Histogram Equalization

In this letter, a new environmental model adaptation method is proposed for robust speech recognition under noisy environments. The proposed method adapts initial acoustic models of a speech recognizer into environmentally matched models by utilizing the histogram equalization technique. Experiments performed on the Aurora noisy environment showed that the proposed technique provides substantial improvement over the baseline speech recognizer trained on the clean speech data.
Global analysis of new gravitational singularities in string and particle theories.

We present a global analysis of the geometries that arise in noncompact current algebra (or gauged Wess-Zumino-Witten (WZW)) coset models of strings and particles propagating in curved space-time. The simplest case is the two-dimensional (2D) black hole. In higher dimensions these geometries describe new and much more complex singularities. For string and particle theories (defined in the text) we introduce general methods for identifying global coordinates and give the general exact solution for the geodesics for any gauged WZW model for any number of dimensions. We then specialize to the 3D geometries associated with SO(2,2)/SO(2,1) (and also SO(3,1)/SO(2,1)) and discuss in detail the global space, geodesics, curvature singularities, and duality properties of this space. The large-small (or mirror-) type duality property is reformulated as an inversion in group parameter space. The 3D global space has two topologically distinct sectors, with patches of different sectors related by duality. The first sector has a singularity surface with the topology of pinched double trousers. '' It can be pictured as the world sheet of two closed strings that join into a single closed string and then split into two closed strings, but with a pinch in each leg of the trousers. The second sectormore » has a singularity surface with the topology of double saddle,'' pictured as the world sheets of two infinite open strings that come close but do not touch. We discuss the geodesically complete spaces on each side of these surfaces and interpret the motion of particles in physical terms. A cosmological interpretation is suggested and comments are made on possible physical applications. « less
Small eigenvalues of the Neumann realization of the semiclassical Witten Laplacian

This article follows the previous works \cite{HKN} by Helffer-Klein-Nier and \cite{HelNi1} by Helffer-Nier about the metastability in reversible diffusion processes via a Witten complex approach. Again, exponentially small eigenvalues of some self-adjoint realization of $\Delta_{f,h}^{(0)}=-h^{2}\Delta +\left|\nabla f(x)\right|^{2}-h\Delta f(x)\;,$ are considered as the small parameter $h>0$ goes to $0$. The function $f$ is assumed to be a Morse function on some bounded domain $\Omega$ with boundary $\partial\Omega$. Neumann type boundary conditions are considered. With these boundary conditions, some simplifications possible in the Dirichlet problem studied in \cite{HelNi1} are no more possible. A finer treatment of the three geometries involved in the boundary problem (boundary, metric, Morse function) is carried out.
A Common Explosion Mechanism for Type Ia Supernovae

Type Ia supernovae, the thermonuclear explosions of white dwarf stars composed of carbon and oxygen, were instrumental as distance indicators in establishing the acceleration of the universe's expansion. However, the physics of the explosion are debated. Here we report a systematic spectral analysis of a large sample of well-observed type Ia supernovae. Mapping the velocity distribution of the main products of nuclear burning, we constrain theoretical scenarios. We find that all supernovae have low-velocity cores of stable iron-group elements. Outside this core, nickel-56 dominates the supernova ejecta. The outer extent of the iron-group material depends on the amount of nickel-56 and coincides with the inner extent of silicon, the principal product of incomplete burning. The outer extent of the bulk of silicon is similar in all supernovae, having an expansion velocity of ∼11,000 kilometers per second and corresponding to a mass of slightly over one solar mass. This indicates that all the supernovae considered here burned similar masses and suggests that their progenitors had the same mass. Synthetic light-curve parameters and three-dimensional explosion simulations support this interpretation. A single explosion scenario, possibly a delayed detonation, may thus explain most type Ia supernovae.
Studying Data Mining and Data Warehousing with Different E-Learning System

Data Mining and Data Warehousing are two most significant techniques for pattern detection and concentrated data management in present technology. ELearning is one of the most important applications of data mining. The foremost idea is to provide a proposal for a practical model and architecture. The standards and system structural design are analyzed here. This paper provides importance to the combination of Web Services on the e-Learning application domain, because Web Service is the most complex choice for distance education during these days. The process of e-Learning can be promising more efficiently by utilizing of Web usage mining. Mor07/e sophisticated tools are developed for internet customer’s behaviour to boost sales and profit, but no such tools are developed to recognize learner’s performance in e-Learning. In this paper, some data mining techniques are examined that could be used to improve web-based learning environments.
Automated Surveillance System and Data Communication

Automated video surveillance systems plays vital role in the business areas , military system and etc . Many research areas in video surveillance system is mainly focuses on algorithms to evaluate background subtraction system and alert to the system, to repeatedly detect major actions For example, our proposed technique stores, for each pixel, a set of values taken in the past at the same location or in the neighborhood. It then compares this set to the current pixel value in order to determine whether that pixel belongs to the background, and adapts the model by choosing randomly which values to substitute from the background model. This approach differs from those based upon the classical belief that the oldest values should be replaced first. In background comparison if the difference in the values reaches the threshold value then user can get alert message. So whenever user getting SMS from server system and the background image is updated whenever the system is detecting a motion.
Selecting Strategies for Infinite-Horizon Dynamic LIMIDS

In previous work we have introduced dynamic limited-memory influence diagrams (DLIMIDs) as an extension of LIMIDs aimed at representing infinite-horizon decision processes. If a DLIMID respects the first-order Markov assumption then it can be represented by 2TLIMIDS. Given that the treatment selection algorithm for LIMIDs, called single policy updating (SPU), can be infeasible even for small finite-horizon models, we propose two alternative algorithms for treatment selection with 2TLIMIDS. First, single rule updating (SRU) is a hill-climbing method inspired upon SPU which needs not iterate exhaustively over all possible policies at each decision node. Second, a simulated annealing algorithm can be used to avoid the local-maximum policies found by SPU and SRU.
Typed Concurrent Programming with Logic Variables

We present a concurrent higher-order programming language called Plain and a concomitant static type system. Plain is based on logic variables and computes with possibly partial data structures. The data structures of Plain are procedures, cells, and records. Plain’s type system features record-based subtyping, bounded existential polymorphism, and access modalities distinguishing between reading and writing.
Higher Inductive Types in Programming

: We propose general rules for higher inductive types with non-dependent and dependent elimination rules. These can be used to give a formal treatment of data types with laws as has been discussed by David Turner in his earliest papers on Miranda [Turner(1985)]. The non-dependent elimination scheme is particularly useful for deﬁning functions by recursion and pattern matching, while the dependent elimination scheme gives an induction proof principle. We have rules for non-recursive higher inductive types, like the integers, but also for recursive higher inductive types like the truncation. In the present paper we only allow path constructors (so there are no higher path constructors), which is suﬃcient for treating various interesting examples from functional programming, as we will brieﬂy show in the paper: arithmetic modulo, integers and ﬁnite sets.
A Study on Components and Assembly Primitives in B

This paper is the result of a reeexion coming from the usage and learning of the language B. It tries to better explain and understand the assembly primitives includes and uses of the language. It presents a high-level notion of components and develops a \component algebra". This algebra is specialized to deal with the B-components. The B assembly primitives are re-expressed in this basic formalism. Some problems about independence of concepts in the B methodology are pointed out and are discussed.
Combining Selective Pressures to Enhance the Durability of Disease Resistance Genes

The efficacy of disease resistance genes in plants decreases over time because of the selection of virulent pathogen genotypes. A key goal of crop protection programs is to increase the durability of the resistance conferred by these genes. The spatial and temporal deployment of plant disease resistance genes is considered to be a major factor determining their durability. In the literature, four principal strategies combining resistance genes over time and space have been considered to delay the evolution of virulent pathogen genotypes. We reviewed this literature with the aim of determining which deployment strategy results in the greatest durability of resistance genes. Although theoretical and empirical studies comparing deployment strategies of more than one resistance gene are very scarce, they suggest that the overall durability of disease resistance genes can be increased by combining their presence in the same plant (pyramiding). Retrospective analyses of field monitoring data also suggest that the pyramiding of disease resistance genes within a plant is the most durable strategy. By extension, we suggest that the combination of disease resistance genes with other practices for pathogen control (pesticides, farming practices) may be a relevant management strategy to slow down the evolution of virulent pathogen genotypes.
From Numerical Probabilities to Linguistic Probabilities: A Theoretical Justification of Empirical Granules Used in Risk Management

In many risk management situations, instead of the exact probability values, specialists use a granule to which this probability belongs. Specically, they use ve granules, corresponding to thresholds 10%, 40%, 60%, and 90%. In this paper, we provide an explanation for such non-uniform granulation. Mathematics Subject Classication: 91B30, 62F25, 60A86, 62A86