Miracle-dz/UniFAR-FTUs huggingface dataset:
Abbreviated models for predicting fall risk in adults with intellectual disabilities

The purpose of this study is threefold: first, to describe anthropometric measures in individuals with Down syndrome (DS) and those with other intellectual disabilities (ID); second, to generate abbreviated methods for predicting fall risk in each population; and third, to assess the validity of these abbreviated models. Body mass index (BMI), Timed Up and Go (TUG), and Berg Balance Scale (BBS) scores from participants (n=49 (12 DS, 37 ID); ages 18-44) recruited at the 2015 Special Olympics Fall Classic in Bryan, Texas were used in stepwise linear regression analyses to produce three equations predicting fall risk: one for those specifically with DS, one for those with any other ID, and one combining the two subgroups. BBS item “standing on one foot” explained a majority of the variance in total BBS scores for both ID (R=0.677) and DS (R=.816) subgroups, as well as in the overall participant group (R=.709). BMI (R = 0.14) and TUG (R = 0.27), however, only accounted for a small fraction of the variance. Validity was assessed on a separate group of participants (n=41 (9 DS, 32 ID); ages 18-45) recruited from the 2016 Special Olympics Winter Games in Austin, Texas. Using predictive equations based on “standing on one foot”, minimal difference was found between actual and predicted BBS in the ID (mean diff = -0.74%), DS (mean diff = 4.51%), and combined (mean diff = -1.38%) models. Results suggest these models are valid alternatives to more extensive fall risk assessments typically used in clinical
Some Thoughts on a Framework for Crowdsourcing A Position Paper for the CHI 2011 Workshop on Crowdsourcing and Human Computation

First, some crowdsourcing systems add value because they can perform a task more quickly than an individual. Examples include von Ahn’s ESP Game [14] in which people generate textual labels for images, or Galaxy Zoo [7] in which people classify images of galaxies as spiral or elliptical. This is usually managed by recruiting large numbers of people to perform one or two very simple tasks, and capturing and integrating the results. The ‘magic’ of this kind of crowdsourcing system lies in its ability to create a situation in which many people will perform the task even though it may be trivially simple.
Towards Better Attack Path Visualizations Based on Deep Normalization of Host/Network IDS Alerts

Mitigation techniques employed by attackers has meant that traditional Network Intrusion Detection Systems (NIDS) are no longer able to reliably protect a network in the face of ever more sophisticated attacks. Security Information and Event Management (SIEM) systems monitor network systems by analyzing the logs they produce. In this paper, we propose a method of visualizing attacks by aggregating, normalizing and analyzing alerts raised by SIEM-based IDS (SIDS) systems as well as NIDS systems in real-time. We present the results of our proposed visualization technique when applied to different attack scenarios. In many cases, our approach allows for the path an attacker takes during their attack to be visualized.
Change Classification in Graphics-Intensive Digital Documents

This paper proposes an approach for the automatic detection and classification of changes occurring in images of documents with identical content, but generated with different software versions, or under different operating platforms. Our work is performed on a database of digitally-born business documents created using financial reporting tools. The proposed method involves a multi-stage process, where the end goal is to present to a human user the reports which have changed and the changes which were detected. Our main contribution is related to matching and comparing of graphical document elements. This paper focuses on detection of local, translation-based changes. Future work will explore other local changes involving size, color, and rotation.
3: FACULTY ENGAGEMENT IN PROGRAM-LEVEL OUTCOMES ASSESSMENT: A LEARNING PROCESS

Faculty areoften not seen as engaged in the work ofprogram-level student learning outcomes assessment. This study investigates the experiences of faculty who self-identified as engaged, a term used to describe attitudes of excitement as well as participatory behaviors. To encourage faculty engagement and recognize the learning process that engagement embodies, institutions can providefaculty development or rolecatalysts, an environ ment that values assessment work, support for learning, and opportunities for faculty membersto make contributions usingwhat they have learned.
Design and implementation of IR based line follower robot for cooperative task sharing

ABSTACTIn this paper we introduce a task sharing demonstrate by relay race of robots. This race is analogous to relay race of human being. Each robot is designed using microcontroller P89V51RD2 which have distinguished addresses. These robots are line follower also and capable to interact with each other using IR sensor. Present mechanism is important in various industrial applications where a task is divided into various modules or subtasks which is performed by separate robots.
Algebraic Framework for Synchronous Language Semantics

In this article, we study several relevant algebraic frameworks to define synchronous language semantics. Synchronous languages are quite dedicated to design critical embedded applications. Thus, verification and compilation is challenging and should rely on mathematical semantics. We study multi-valued algebras as foundation for semantics definition and we show that a 4-valued algebra with a bilattice structure is well suited to our concern. With this approach we can define semantics offering both the generation of models where verification techniques apply, and separated compilation means.
Uma abordagem deep learning para reconhecimento de expressões faciais.

Facial expressions are the result of changes in facial muscles in response to the internal emotional state of a person. Based on Darwin studies, Paul Ekman developed a study suggesting the existence of seven basic universal facial expressions: joy, sadness, fear, disgust, contempt, surprise and anger, plus the neutral expression. Also, Paul Ekman developed a tool, the Facial Action Coding System or simply FACS, to taxomize all facial muscle movements and their intensity and study more deeply the facial behavior. From this tool, hence more and more applications, which automatically detect facial expressions, start to be pervasive in various fields, such as education, entertainment, psychology, human-computer interaction, behavior monitoring, just to cite a few. Unlike the available methods in the literature, this work suggests a new approach to the development of a system for recognizing the seven basic facial expressions proposed by Ekman: joy, sadness, fear, disgust, contempt, surprise and anger. The proposed method builds a conspicuous map of the main region faces, training it via a convolutional neural network. For that was developed two neural network architectures that have the legitimacy of the training done through cross-validation and the test results were evaluated by ROC curve analysis and matrix of confusion. The evaluation of the proposed approach indicated a promising result. Experimental results achieved an average accuracy of 90% over the extended Cohn-Kanade data set for the seven basic expressions, demonstrating the best performance against all state-of-the-art methods and, in absolute terms, the proposed approach had a best result in three of seven facial expressions which shows a promising result.
NoSQL Data Modeling Techniques

NoSQL databases are often compared by various non-functional criteria, such as scalability, performance, and consistency. This aspect of NoSQL is well-studied both in practice and theory because specific non-functional properties are often the main justification for NoSQL usage and fundamental results on distributed systems like the CAP theorem apply well to NoSQL systems. At the same time, NoSQL data modeling is not so well studied and lacks the systematic theory found in relational databases. In this article I provide a short comparison of NoSQL system families from the data modeling point of view and digest several common modeling techniques.
Research on Fatigue Driving Assessment Based on Multi-Source Information Fusion

Fatigue driving has become one of the main causes of traffic accidents. At present, many driving fatigue detection methods are based on the image processing technology, while these methods are easy to be affected by the driving environment, which limits the accuracy and reliability and accuracy of the detection. For this limitation, this paper introduces the multi-source information detection and fusion technology, using sensors to get kinds of information, including PERCLOS value, attitude feature, facial expressions and body temperature, then uses the neural network learning method to identify the driver's state based on the fused information, which could improve the improve the accuracy and reliability of driving fatigue detection. Experiments have been carried out to prove that the proposed method is considerably effective.
Public scene recognition using mobile phone sensors

Smartphones evolve rapidly and become more powerful in computing capabilities. More importantly, they are becoming smarter as more sensors such as the accelerometer, gyroscope, compass and the camera have been embedded on the digital board. In this paper, we propose a novel framework to recognize public scenes based on the sensors embedded in mobile phones. We build individual models for audio, light, wifi and bluetooth first, then integrate these sub-models using dynamically-weighted majority voting. We consider two factors when deciding the voting weight. One factor is the recognition rate of each sub-model and the other factor is recognition precision of the sub-model in specific scenes. We build the data-collecting app on the Android phone and implement the recognition algorithm on a Linux server. Evaluation of the data collected in the bar, cafe, elevator, library, subway station and the office shows that the ensemble recognition model is more accurate and robust than each individual sub-models. We achieved 83.33% (13.33% higher than audio sub-model) recognition accuracy when we evaluated the ensemble model with test dataset.
Unraveling decentralized authorization for multi-domain collaborations

Current authorization solutions take highly case-by-case approaches. First of all, the solutions address particular types of multi-domain collaborations such as virtual organization or resource-sharing collaborations. Secondly, they tend to be based on specific technology their subject interactions adopt. We consider this phenomena of having a number of different authorization solutions as a result of taking a mainly bottom-up approach to cater the authorization need of diverse types of mult-domain collaborations currently existing. In this paper, we present an extended analysis of different types of multi-domain collaborations based on various e-Government case studies as well as that of existing authorization solutions. With the converged requirements resulting from those analyses, we take a top-down approach of explicitly highlighting generic and interoperable components for a decentralized authorization scheme. This approach appears to be more suitable to produce a more efficient and elegant authorization solution for the majority of multi-domain collaborations.
The Interplay between Cognition and Worry

An increasing amount of research findings is showing that higher engagement in cognitive tasks alleviates the interference of anxiety and worry on task performance as compared to lower task engagement. Yet, it is still not clear which cognitive functions are mostly contributing to this relieving effect. To add to the current knowledge, the present experimental work investigated the relations between task performance, patterns in pupil dilation and increased difficulty in tasks requiring, among others, cognitive maintenance and updating functions in induced ‘worry’ and ‘no worry’ conditions. In addition, the present experiment explored if visual complexity level of stimuli is modulating these relations. Data analyses of the response speed, proportion of correct answers and pupillary baseline measures revealed statistically significant three-way interactions between the condition (‘worry’, ‘no worry’), visual complexity (low, high), and task (n-back, reference-back). The results showed lower performance measures in the ‘worry’ condition than in the ‘no worry’ condition in an easier n-back task, but this disadvantage was eliminated with increased task difficulty. Results of the reference-back task revealed that increased period of mental object maintenance may be sufficient to shield from disadvantages in the performance efficiency in the ‘worry’ condition. The results also showed that increased visual complexity of stimuli interfered with the task performance more in the ‘worry’ condition than in the ‘no worry’ condition. Pupil dilation data showed higher baseline pupil sizes in the ‘no worry’ condition linked with, among others, higher working memory capacity, as compared to smaller pupil sizes in the ‘worry’ condition.
Flexible architecture to automate farm machinery operation: Preliminary results

A versatile framework for automation of sophisticated farm machinery has been proposed in this paper. The paper details the functional design and development of the hardware and software architecture of the framework for electronic monitoring and control of a complex system. The framework aims to provide a user friendly bridge between the digital world and the physical world and covers the core software functionalities for monitoring and control. The user interface is hosted on a local web server running off a single board computer. This interface is accessed by a web browser on a mobile device (such as a smart phone or a tablet) through a Wi-Fi connection. The computer monitors and controls the mounted sensors and actuators through an I/O extension cape. It stores all monitored data and control updates in a database. The user interface is updated regularly to ensure that what the operator sees is the latest information. The paper summarizes the outcome of implementing the framework using a few sensors and actuators in a lab environment.
Niche convergence suggests functionality of the nocturnal fovea

The fovea is a declivity of the retinal surface associated with maximum visual acuity. Foveae are widespread across vertebrates, but among mammals they are restricted to haplorhine primates (tarsiers, monkeys, apes, and humans), which are primarily diurnal. Thus primates have long contributed to the view that foveae are functional adaptations to diurnality. The foveae of tarsiers, which are nocturnal, are widely interpreted as vestigial traits and therefore evidence of a diurnal ancestry. This enduring premise is central to adaptive hypotheses on the origins of anthropoid primates; however, the question of whether tarsier foveae are functionless anachronisms or nocturnal adaptations remains open. To explore this question, we compared the diets of tarsiers (Tarsius) and scops owls (Otus), taxa united by numerous anatomical homoplasies, including foveate vision. A functional interpretation of these homoplasies predicts dietary convergence. We tested this prediction by analyzing stable isotope ratios that integrate dietary information. In Borneo and the Philippines, the stable carbon isotope compositions of Tarsius and Otus were indistinguishable, whereas the stable nitrogen isotope composition of Otus was marginally higher than that of Tarsius. Our results indicate that species in both genera consumed mainly ground-dwelling prey. Taken together, our findings support a functional interpretation of the many homoplasies shared by tarsiers and scops owls, including a retinal fovea. We suggest that the fovea might function similarly in tarsiers and scops owls by calibrating the auditory localization pathway. The integration of auditory localization and visual fixation during prey detection and acquisition might be critical at low light levels.
Ledoux's convection criterion in evolution and asteroseismology of massive stars

Saio et al. (2006) have shown that the presence of an intermediate convective zone (ICZ) in post-main sequence models could prevent the propagation of g-modes in the radiative interior and hence avoid the corresponding radiative damping. The development of such a convective region highly depends on the structure of the star in the mu-gradient region surrounding the convective core during the main sequence phase. In particular,the development of this ICZ depends on physical processes such as mass loss, overshooting (Chiosi & Maeder 1986, Chiosi et al. 1992, see also Godart et al., these proceedings) and convective instability criterion (Schwarzschild's or Ledoux's criteria). In this paper we study the consequences of adopting the Ledoux's criterion on the evolution of the convective regions in massive stars (15 and 20 Msun), and on the pulsation spectrum of these new B-type variables (also called SPBsg).
Adopting Malay Syllable Structure for Syllable Based Speech Synthesizer for Iban and Bidayuh Languages

Sarawak, Malaysia, has many under-resourced languages, which stands to become extinct if measures are not taken to preserve and maintain them. These languages are mostly spoken by the indigenous groups and not all of the languages are documented or studied. As an initiative to preserve, a Text to Speech (TTS) system has been built for Iban and Bidayuh languages, two out of 44 living languages in Sarawak. To expedite the development, we employed knowledge of closely-related language, i.e. Malay, which is the first language in Malaysia. In this paper, we employed a syllabification algorithm based on Malay syllable structure to build the Iban and Bidayuh syllable list and speech corpus. An accuracy test for the algorithm was conducted to determine the quality of the output from the TTS system using Categorical Estimation (CE). Test showed high percentage in accuracy and quality has a mean score of 3.07 out of 5, suggesting the approach works.
A Role for Identification in the Gradual Decline in the Pleasantness of Flavors With Age

Objectives: This study investigated a possible role for identification in the decline in flavor pleasantness with age. Methods: Two hundred sixty-four individuals aged from 16 to 85 years tasted 6 flavored drinks of varying identity and ease of identification, and rated each on pleasantness, a range of other characteristics and identified all flavors. Results: Using regression, firstly, pleasantness was inversely associated with age (β = −0.22, p < .01). Secondly, the decline in pleasantness with age was associated with poorer identification (β = 0.30, p < .01), lower perceptions of sweetness (β = 0.01, p < .01), lower strength of flavor (β = 0.00, p = .02), lower familiarity (β = 0.01, p < .01), and a lower frequency of usual drink consumption (β = 0.04, p < .01). Thirdly, improved identification with age was associated with increased drink familiarity (β =< 0.01, p < .01), coloration compared with no color (β = <0.06, p < .01), and correct compared with incorrect coloration (β = <0.27, p < .01). Discussion: These findings demonstrate a clear role for identification in the decline in flavor pleasantness with age. These findings thus provide clear evidence for a cognitive and perceptual element to these hedonic processes. Our findings suggest that likings for flavors in older individuals may be increased/maintained through the use of improved visual cues, easily recognizable foods, and/or identity labels.
FUNDAMENTAL PROPERTIES OF STARS USING ASTEROSEISMOLOGY FROM KEPLER AND CoRoT AND INTERFEROMETRY FROM THE CHARA ARRAY

We present results of a long-baseline interferometry campaign using the PAVO beam combiner at the CHARA Array to measure the angular sizes of five main-sequence stars, one subgiant and four red giant stars for which solar-like oscillations have been detected by either Kepler or CoRoT. By combining interferometric angular diameters, Hipparcos parallaxes, asteroseismic densities, bolometric fluxes, and high-resolution spectroscopy, we derive a full set of near-model-independent fundamental properties for the sample. We first use these properties to test asteroseismic scaling relations for the frequency of maximum power (νmax) and the large frequency separation (Δν). We find excellent agreement within the observational uncertainties, and empirically show that simple estimates of asteroseismic radii for main-sequence stars are accurate to ≲ 4%. We furthermore find good agreement of our measured effective temperatures with spectroscopic and photometric estimates with mean deviations for stars between Teff = 4600–6200 K of −22 ± 32 K (with a scatter of 97 K) and −58 ± 31 K (with a scatter of 93 K), respectively. Finally, we present a first comparison with evolutionary models, and find differences between observed and theoretical properties for the metal-rich main-sequence star HD 173701. We conclude that the constraints presented in this study will have strong potential for testing stellar model physics, in particular when combined with detailed modeling of individual oscillation frequencies.
Into the Role of Enhanced Adrenergic Receptor-Effector Coupling in the Print

Heart New Insight Into the Role of Enhanced Adrenergic Receptor-Effector Coupling in the Print ISSN: 0009-7322. Online ISSN: 1524-4539 Copyright © 1999 American Heart Association, Inc. All rights reserved. is published by the American Heart Association, 7272 Greenville Avenue, Dallas, TX 75231 Circulation doi: 10.1161/01.CIR. 100.6. 579 1999;100:579-582 Circulation. http://circ.ahajournals. org/content/100/6/579 World Wide Web at: The online version of this article, along with updated information and services, is located on the
Research on MPPT for Solar Cells Based on Flyback Converter

A voltage source and rheostat are successfully used to simulate the solar cell's character in this paper. Its feasibility is analyzed theoretically. The basic principle of the maximum power point tracking (MPPT) is described. An improved disturbance method with variable-voltage step is introduced. It inherits the advantages of traditional disturbance voltage method, overcomes the shortcomings of slow response of traditional method, reduces the power loss caused by maximum power point due to continuous disturbance, and realizes the maximum power point tracking for solar cells. The proposed method improves the system's speed and efficiency. The experimental results show that the system can track the maximum power point accurately and quickly.