Miracle-dz/UniFAR-FTUs huggingface dataset:
Wavelet entropy method for EEG analysis: application to global brain injury

A novel method, "wavelet entropy," is presented for the analysis of EEG signals recorded during injury and recovery following global cerebral ischemia. The EEG is recorded from rodent brains in a controlled experimental brain injury model by hypoxic-ischemic cardiac arrest. Wavelet analysis is used to decompose the EEG into standard clinical subbands. Entropy is then computed using these wavelet coefficients. The wavelet entropy helps segment periods of bursting in EEG signals. The residual entropy of the wavelet coefficients is also computed. It reflects the degree of synchronization of the brain rhythm generators.
Norwich Castle: Excavations and Historical Survey 1987-98. Part III A Zooarchaeological Study

This is Part III of the Norwich Castle report (EAA 132). Although Parts I and II both contain summary accounts of the faunal remains, setting them into their wider context and including additional information on craft activities, the scale of the data required the production of a separate and more specialised report on the faunal remains which permits presentation of metrical and other data that could not be published in detail within the monograph, where the faunal assemblage is considered largely in chronological terms. Instead, this occasional paper details the evidence more specifically by species. Excavations at Castle Mall yielded the largest faunal assemblage ever recovered from Norwich with the greatest, most continuous chronological spread. The assemblages recovered demonstrate the breadth of information available from faunal remains, from the common farm animals providing milk, meat and eggs, to the trade in horns, antlers, hides and bones for crafts and industries. Evidence ranging from the occasional exotic species to the use of non-traditional food animals such as horse and dog has revealed a picture of the human-animal interaction within a medieval town. The analyses reveal details of how animals were procured and butchered, which foods people ate and how they disposed of their waste. It has also been possible to link archaeological and zooarchaeological evidence to trace the changing use of space within and around the castle throughout its long history.
Player falling detection in soccer matches video

In recent years, most sports such as Soccer are recorded during the actual game and analysed later on by the coaches for training their teams to perform better in the future. The training can be in several aspects such as avoiding fouls, injuries, improving passes and tactics. Automatic detection/retrieval of such specific events from the video database will be of great assistance to the coaches. In this paper, we analyse Soccer match videos with the objective to detect two events – players playing or falling. Player falling, often leading to injury can be costly for the players’ health and also the team performance as a whole.
Reconstruction of the Decimal Number Line Concept Through Teacher＇s Scaffolding Practices

This research investigated the reconstruction of the decimal line concept by Alice, the research subject, after she had received the four stages of scaffolding assistance: “multiple representations scenario”, “explanation and demonstration”, “concept reconstruction”, and “concept extension”. The research discovered that there were two reasons for Alice’s incorrect understanding of the decimal line concept. First, Alice did not understand the concept of the counting system for decimals; and Second, she could not distinguish between the different decimal units on the various line segments after the decimal line was segmented. The research further discovered that under a scenario with multiple representations, Alice was able to effectively reconstruct the decimal counting system. With the help of explanation and demonstration of the equivalent decimal concept, she was also able to effectively use the counting system and equivalent decimal concept to reconstruct the decimal number line system and develop conceptual thinking to solve non-routine problems.
Alcohol y embarazo: Análisis de estrategias para disminuir el consumo de alcohol en mujeres en edad reproductiva en Uruguay

In Uruguay one out of three fetuses are exposed to alcohol during gestation. Due to the fact that this is the main cause of non-inheritable mental retardation and that it is easily preventable, it is importantto detect in early stages of pregnancy all those cases of exposure to this substance. The main purpose of this study was to analyse effectiveness and applicability of different methods to detect prenatal exposureto alcoholic drinks and of existent interventions to decrease the prevalence of alcohol exposed pregnancies, in order to generate some recommendations which could be used by every health professional in Uruguay. After an exhaustive analysis of bibliography, the strategy that is recommended in order to identify fetal alcohol exposure is the standardized questionnaire AUDIT-C, which has a sensibility of 95 % and a specificity of 85 %, and which should be applied during the first pregnancy control.Afterwards, the application of a brief intervention strategy with a motivational and collaborative approach, has demonstrated to be cost-effective to decrease the rates of alcohol exposed pregnancies. Theapproach used in these interventions aims to educate patients in order to allow themselves to identify and understand the importance of changing their habits.
An Illumination Invariant Face Recognition Method Based on Gradientfaces and 2DLDA

Extracting illumination invariant features is an effective method to improve recognition rate of algorithm with varying illumination. In this paper, a novel illumination invariant method which combines Gradientface and 2DPDA is proposed. First, this approach transforms a face image into Gradientface, then the 2DPCA is used to reduce the dimension of Gradientface. The experimental results verify the effectiveness of our approach on CAS-PEAR-R1 and CMU PIE face databases. Keywords—Gradientfaces, 2DLDA, face recognition
Digital surface representation and the constructibility of Gehry's architecture

This thesis presents work in the development of computational descriptions of Gehry’s architectural forms. In Gehry’s process for realizing buildings, computation serves as an intermediary agent for the integration of design intent with the geometric logics of fabrication and construction. This agenda for digital representation of both formal and operational intentions, in the context of an ongoing exploration of challenging geometries, has provided new roles for computation in architectural practice. The work described in this thesis focuses on the digital representation of surface geometry and its capacity for describing the constructibility of building enclosure systems. A particular class of paper surface forms – curved surfaces with minimal in plane deformation of the surface material – provide the specific object of inquiry for exploring the relationships between form, geometry and constructibility. An analysis and framework for the description of Gehry’s geometry is developed through existing theory of differential geometry and topology. Geometric rules of constructibility associated with several enclosure system strategies are presented in this framework. With this theoretical framework in place, the discussion turns to efforts to develop generative strategies for the rationalization of surface forms into constructible configurations. Thesis Supervisor: William J. Mitchell Title: Dean of the School of Architecture and Planning, Professor of Architecture and Media Arts and Sciences, MIT
CB3-01: Comparison of Ethnicity and Race Categorization in Electronic Medical Records and by Self-report

Background/Aims Members of minority groups are more likely than non-minorities to have worse health outcomes. Electronic medical records (EMR) data are often used for research on health disparities, and can help identify patient risk factors, but accuracy of ethnicity and race data in the EMR is often questioned. Aims To compare HealthPartners Medical Group (HPMG) EMR data on ethnicity/race to self-reported classification. Methods We compared percent agreement of self-reported and EMR data on ethnicity/race among 1719 patients who expressed interest in a hypertension clinical trial, completed an eligibility phone screen, and consented to EMR review. Patients classified their ethnicity/race in two questions: Are you of Latino or Hispanic descent? (Yes, No, Don’t know, Refused); How would you describe your race (Check all that apply) (American Indian/Alaskan Native, Asian, Black or African American, Native Hawaiian or Pacific Islander, White or Caucasian, Other, Don’t know, Refused). EMR race categories allowed multiple selections among: White, Black, Asian, Hispanic, American Indian, Other, and No Answer. Results Race data was missing in 0.7% of phone screens and 1.2% of EMRs. Self-reported race was 79% white, 14% African American, 3% mixed, 2% other, 1% Asian, <1% Native American. In the EMR, race was recorded as 79% white, 14% African American, 3% mixed race, 1% Asian, <1% each for American Indian, and other. Overall agreement for race was 91.1%. EMR data agreed with self-report for 97% of those reporting white, 94% of those reporting African American, 83% Asian, 50% Native American, 9% mixed race and 6% other. Hispanic ethnicity was self-reported by 1.3% and coded for 2.4% in the EMR. EMR confirmed Hispanic ethnicity for 51% self-reporting Hispanic ethnicity. Discussion EMR race/ethnicity data was quite complete, and agreement of data sources was high overall and among whites, African Americans and Asians. Lower agreement was observed among Hispanic, Native American, and mixed race patients, subgroups that may be disproportionately affected by disparities. Some caution is needed in interpreting EMR-based results for those subgroups, and their proper classification in the EMR is warranted. Similar comparisons should be conducted in other settings and patient populations.
Bodies Politic: Disease, Death and Doctors in Britain, 1650-1900

Roy Porter Reaktion Books, £25, pp 328 ISBN 1 86189 094 X Rating: ! [Graphic][1] ! [Graphic][2] This book comes well announced: “… splendid book … a tonic to those dismayed by the current writing-down of English history” ( Sunday Telegraph ); “… exhilarating” ( Sunday Times ); “simply superb” ( New Statesman ). This should be enough not only to whet the reviewer's appetite but also to bias opinion. And yet my reaction at the end of an enjoyable read is one of disappointment, disappointment that a magnificent opportunity to do justice to an immense and unique labour of historiography has been squandered. Let me explain. [][3] Roy … [1]: /embed/inline-graphic-1.gif [2]: /embed/inline-graphic-2.gif [3]: /embed/graphic-1.gif
Measuring 3D face geometry for integration with apperance models

OF THE THESIS Measuring 3D Face Geometry for Integration with Appearance Models by Siddharth K. Madan Thesis Director: Dr. Kristin J. Dana Capturing the appearance of skin is a nontrivial problem. The appearance of skin depends significantly on the illumination and viewing direction. The global and fine scale local geometry influence the appearance of skin. In this thesis, we work towards capturing the appearance of skin by acquiring the global geometry and modeling the skin texture. We explore the use of structured light techniques to acquire global geometry. Two novel structured light techniques have been developed. The techniques use image ratios to obtain reliable reconstruction of low albedo regions. The use of laser scanner for geometry acquisition and it’s advantages and disadvantages have also been discussed. We model the interaction of light with the skin surface as a combination of surface and subsurface scattering. The reflectance due to subsurface scattering and the reflectance due to surface scattering have different properties and are modeled separately. The subsurface components lie on a lower dimensional linear subspace and the surface components lie on nonlinear manifolds. We look into the use of linear dimensionality reduction techniques to model the subsurface reflectance and nonlinear dimensionality reduction techniques to model the surface reflectance. In the initial results, separate modeling of the surface and the subsurface components preserved the specularities.
Error Resilient Transmission of Video over Mobile Networks

The deployment of third generation mobile networks enabled new real-time multimedia services like video call, conferencing and streaming. The real-time nature of these services excludes the possibility of end-to-end retransmissions. Therefore, errors affecting the quality of the received service are inevitable. The aim of error resilience methods is to minimize the impact of errors on the end-user quality. In this talk, the effect of errors at different positions in the video stream and the possibility of their detection will be discussed. Typically, within an IP video stream, the presence of errors in one IP packet can be detected by means of a simple checksum. Thus, the IP packet size determines the resolution of the error detection. In order to reduce the rate increase due to packet headers, the IP packets are rather large and their loss results in a loss of a considerable part of a picture. Currently, the erroneous IP packets are discarded at the receiver and the corresponding missing parts of the video sequence are concealed. However, the discarded IP packets may still contain correctly received information. If this information is used additionally, an essential improvement in the end-user quality can be obtained. If the access network technology is known, an appropriate cross-layer design enables easier error detection and allows for further improvements of error resilience. In this talk, the UMTS access network is focused. Error resilience methods can be further improved by an appropriate scheduling of the video stream. Here, link-error aware and distortion-aware concepts and their combinations will be discussed and their performance demonstrated.
Software docente para el reconocimiento de objetos sumergidos fabricados por el hombre mediante el procesado de imagen de un sonar de barrido lateral de simple haz

The knowledge about digital images provided by onboard sidescan sonar in unmanned undersea vehicle s (UUVs), usually, is far away of educational purposes. Our r esearch team demonstrates in previous papers [1] that this targe t is possible at affordable cost. This communication shows how th e educational software developed by our team, have be en enhanced in terms of implementation the state of th e art in underwater recognition techniques, including manmade submerged objects, to improve the skills of our stu dents. This work shows an economical solution for this problem by using digital image processing techniques under MATLAB environment. Results are comparable in quality with the commercial expensive hardware solutions. The applic ation presented here is easy to use and has been develope d under “user friendly” philosophy and could be operated for users at any level.
Dictionary of Health Economics

Comprehensive, concise and easily accessible, this is the first health economics dictionary of its kind and is an essential reference tool for everyone involved, or interested in, healthcare. The modern terminology of health economics and relevant terms used by economists working in the fields of epidemiology, public health, decision management and policy studies are all clearly explained. Combined with hundreds of key terms, the skillful use of examples, figures, tables and a simple cross-referencing system between definitions, allows the often complex language of health economics to be demystified.
Challenges and supports for struggling learners in a student-centered mathematics classroom

ABSTRACT This qualitative study examines the challenges and supports inherent in a student-centered mathematics curriculum developed for a constructivist environment. Mathematics education faculty and special education faculty from a university college of education collaborated on this study to determine how students responded to specific components of curriculum and instruction. Classroom observation data from a first-grade class and a sixth-grade class identified areas where the respective curriculum and pedagogy promoting student-centered learning posed specific challenges for struggling learners and suggested potential supports that could help students access critical content and processes. The article identifies three areas for consideration and discusses implications for practice.
Early Detection Prediction of Learning Outcomes in Online Short-Courses via Learning Behaviors

We study learning outcome prediction for online courses. Whereas prior work has focused on semester-long courses with frequent student assessments, we focus on short-courses that have single outcomes assigned by instructors at the end. The lack of performance data and generally small enrollments makes the behavior of learners, captured as they interact with course content and with one another in Social Learning Networks (SLN), essential for prediction. Our method defines several (machine) learning features based on the processing of behaviors collected on the modes of (human) learning in a course, and uses them in appropriate classifiers. Through evaluation on data captured from three two-week courses hosted through our delivery platforms, we make three key observations: (i) behavioral data contains signals predictive of learning outcomes in short-courses (with classifiers achieving AUCs <inline-formula><tex-math notation="LaTeX">$\geq 0.8$</tex-math></inline-formula> after the two weeks), (ii) early detection is possible within the first week (AUCs <inline-formula><tex-math notation="LaTeX">$\geq 0.7$</tex-math></inline-formula> with the first week of data), and (iii) the content features have an “earliest” detection capability (with higher AUC in the first few days), while the SLN features become the more predictive set over time as the network matures. We also discuss how our method can generate behavioral analytics for instructors.
A rule based identifier for unknown systems

The paper deals with the problem of rule based identification for unknown systems. Several rules have been established which give a desirable estimate for the time delay, minimum structure order and unknown parameters, by using only one open-loop step response test. These rules actually adjust the poles and zeros of the proposed linear model to make its response as close as possible to that of the original open-loop system. It has also been shown that this method can be directly used to identify the unknown parameters of MIMO systems. Finally, this rule based identifier is applied to three real experimental systems: a jet engine speed control system (SISO), a temperature process control system (SISO) and a coupled electric drive control system, (MIMO). For all the systems, desirable identification results have been obtained.
Relationship Between Deep Vein Thrombosis and Lower Limb Swelling in Patients with Brain Lesions

• There is no significant relationship between unilateral lower limb swelling and the presence of deep vein thrombosis (DVT) in stroke patients. • In stroke patients with diagnosed DVT, there is no correlation between lower limb swelling and functional outcome that are frequently used in a rehabilitation unit. Brain Neurorehabil. 2017 Sep;10(2):e17 https://doi.org/10.12786/bn.2017. 10.e17 pISSN 1976-8753·eISSN 2383-9910
Space-time coding schemes for wireless communications over flat fading channels

The increasing demand for higher data rates and higher quality in wireless communications has motivated the use of multiple antenna elements at both the transmitter and the receiver sides in a wireless link. The problem discussed in our research is the development of fundamental space-time (ST) coding and modulation methods to achieve the gains provided by multiple antennas, in terms of both improved robustness of the link and a higher spectral efficiency. We focus on a point-to-point wireless environment, in which the channel is modeled as flat fading, and channel knowledge is not available at the transmitter. Several new and improved schemes tailored for different applications are proposed. We first consider the design of ST trellis codes that reduce the probability of error without loss of spectral efficiency. It is found that the typical assumption of high signalto-noise ratio (SNR) and, consequently, traditional design criteria are invalid in certain situations. Analyzing pair-wise error probability, we derive two sets of tighter design criteria for low and moderate SNR regions, respectively. New ST trellis codes optimized for moderate SNR are provided via a computer search. To avoid the prohibitively high complexity of searching for good codes with a larger number of transmit antennas and higher-level modulation, we introduce a novel systematic code construction method, diagonal block ST coding. This two-step approach demonstrates promising results at the commonly assumed high SNR.
Left-corner Parsing for Dependency Grammar

In this article, we present an incremental dependency parsing algorithm with an arc-eager variant of the left-corner parsing strategy. Our algorithm’s stack depth captures the center-embeddedness of the recognized dependency structure. A higher stack depth occurs only when processing deeper center-embedded sentences in which people find difficulty in comprehension. We examine whether our algorithm can capture the syntactic regularity that universally exists in languages through two kinds of experiments across treebanks of 19 languages. We first show through oracle parsing experiments that our parsing algorithm consistently requires less stack depth to recognize annotated trees relative to other algorithms across languages. This result also suggests the existence of a syntactic universal by which deeper center-embedding is a rare construction across languages, a result that has yet to be quantitatively cross-linguistically examined. We further investigate the above claim through supervised parsing experiments and show that our proposed parser is consistently less sensitive to constraints on stack depth bounds when decoding across languages, while the performance of other parsers such as the arc-eager parser is largely affected by such constraints. We thus conclude that the stack depth of our parser represents a more meaningful measure for capturing syntactic regularity in languages than those of existing parsers.
Synthesizing Race: Towards an Analysis of the Performativity of Vocal Timbre

Vocaloid is a vocal synthesis software package that "sings back" any pitch and word combination entered by a user, impersonating a singer with a designated sex, age and race. Lola and Leon, the first pair of "singers" designed, were introduced as "generic soul-singing voices. " Investigating vocal timbre as a cultural artifact, I look at the processes by which audience connect specific vocal sounds with particular ideas such as race and gender. Such reification of notions of race through vocal timbre is circular: audiences join sounds with concepts; (live or digital) performers respond to these sound/concept compounds, and in turn confirm the listeners' linkages. Thus an analysis of timbre as an inner choreography is necessary to begin to map and denaturalize the connection between vocal timbre and race