nils-herrmann/clean_scirepeval huggingface dataset:
An Observational Study to Compare Prevalence and Demography of Sensorineural Hearing Loss Among Military Personnel and Civilian Population
Venue: Indian Journal of Otolaryngology and Head Neck Surgery
Year: 2020

To evaluate the pattern of sensorineural hearing loss (SNHL) in patients attending ENT OPD in a military setup as well as to compare the incidence of hearing loss in Military Personnel with civilian population. This observational cross sectional comparative study was conducted over a period of April 2018 to July 2019. A total of 300 patients with hearing loss (HL) were included. Demographic characteristics along with laterality of sensorineural hearing impairment were compared between military personnel and civilians. Data was statistically compared between civilians and military personnel. A P value of 0.05 was considered statistically significant. We report an overall prevalence of 3.78% SNHL in the ENT OPD. Specifically the prevalence of SNHL among military personnel was 2.17% and in civilian population was 4.83% (P 0.0001) The mean age of the military personnel was significantly less than civilians (62.53 10.03 vs 65.98 12.46, P 0.003) There were 68% Males and 32% females. Significantly higher number of males were present in military group as all participants were males (100% vs 58.62% P 0.0001) There was no significant difference in the laterality of SNHL between Military personnel and the civilian population with bilateral involvement being common in both populations. It can be concluded that bilateral SNHL type is the most common type of hearing impairment among military personnel as well as civilians complaining of HL. Males of 51 70 years are most affected with SNHL.
User experience sharing: Understanding customer initiation of value co creation in online communities
Year: 2018

This paper aims to propose user experience sharing (UES) as a customer based initiation of value co creation pertaining to service provision, which represents customers' level of effort made for the direct benefit of others in their service network. The authors propose and empirically examine a user experience sharing model (UESM) that explicates customer to customer (C2C) UES and its impacts on firm desired customer based outcomes in online communities.  Based on an extensive review, the authors conceptualize UES and UESM. By using online survey data collected from mobile app users in organic online communities, the authors performed structural equation modeling analyses by using AMOS 24.  The results support the proposed UESM, showing that C2C UES acts as a key driver of both firm desired customer efforts and customer insights. The results also confirmed that service dominant (S D) logic informed motivational drivers exert a significant impact on C2C UES. Importantly, C2C UES mediates the relationship between S D logic informed motivational drivers and firm desired customer based outcomes.  This study offers a pioneering attempt to develop an overarching concept, UES, which reflects customers' initiation of value co creation, and to empirically examine C2C UES. The empirical evidence supports the key contention that firms should proactively facilitate C2C UES.
Evaluating Two Stream CNN for Video Classification
Venue: ICMR
Year: 2015

Videos contain very rich semantic information. Traditional hand crafted features are known to be inadequate in analyzing complex video semantics. Inspired by the huge success of the deep learning methods in analyzing image, audio and text data, significant efforts are recently being devoted to the design of deep nets for video analytics. Among the many practical needs, classifying videos (or video clips) based on their major semantic categories (e.g."skiing" is useful in many applications. In this paper, we conduct an in depth study to investigate important implementation options that may affect the performance of deep nets on video classification. Our evaluations are conducted on top of a recent two stream convolutional neural network (CNN) pipeline, which uses both static frames and motion optical flows, and has demonstrated competitive performance against the state of the art methods. In order to gain insights and to arrive at a practical guideline, many important options are studied, including network architectures, model fusion, learning parameters and the final prediction methods. Based on the evaluations, very competitive results are attained on two popular video classification benchmarks. We hope that the discussions and conclusions from this work can help researchers in related fields to quickly set up a good basis for further investigations along this very promising direction.
Posibilidad o no de grabar las clases de los profesores en las aulas de los colegios publicos con el fin de garantizar que no exista adoctrinamiento
Year: 2019

espanolSe analiza si la posibilidad de grabar las clases de los profesores sin su consentimiento en las aulas de los colegios publicos con el fin de garantizar que no exista adoctrinamiento podria atentar contra el derecho fundamental a la intimidad personal, consagrado en el articulo 18 de la Constitucion, y contra la libertad de catedra recogida en el articulo 20.1.c) de la Constitucion, como expresion de la libertad ideologica y religiosa de los individuos, y tambien si existen otras medidas o actuaciones que puedan ser adoptadas a fin de evitar el adoctrinamiento. EnglishThe article discusses if the possibility of recording the classes of theachers without their consent in the classrooms of the public schools to ensure that do not exist indoctrination, could attempt against the fundamental right of personal privacy, devoted in article 18 of the Constitution, and against freedom of chair collected in article 20.1.c) of the Constitution, as expression of the ideological and religious freedom of the individuals, and also if there are other measures or actions that can be taken in order to avoid the indoctrination.
Ain't Nobody Checkin' For Us' Race, Fugitivity and the Urban Geographies of Black Girlhood
Year: 2019

My dissertation examines the intimate relationship between racialized state violence, gender based violence, and Black girlhood. By studying a national nonprofit based in Chicago that runs an art and activism leadership program for African American girls, my research examines how working class black girls use their voices, bodies, and stories to navigate and contest the socio economic and political structures that lead to their and their families' disposability and displacement. In turn, building on the work of Saidiya Hartman, Fred Moten, and Stefano Harney, I identify those contested sites as "fugitive spaces" in which black girls put forth nuanced self narratives that unpack the multi layered operations that render them invisible to themselves, their communities, and the various apparati of the state. Additionally, it provides a framework for a pedagogy of care as we engage with Black girls from a place of solidarity.
Web Educativo como Recurso para la Ensenanza de Fronteras Nacionales de la Universidad del Zulia
Year: 2017

El proposito de esta investigacion de caracter tecnologico, fue desarrollar un Web educativo como recurso para la ensenanza de la asignatura fronteras nacionales de la Universidad del Zulia. La metodologia fue un hibrido entre el espiral de Pressman y el diseno de sitios educativos de Rojas, el tipo de investigacion es descriptiva y proyecto factible, de igual forma tuvo un diseno mixto con fases de diagnostico y aplicacion de metodologia, con una poblacion censal de 104 individuos, utilizando un guion de entrevista y cuestionarios para la recoleccion de datos y para procesar los datos la estadistica descriptiva. Se concluye que este sitio web sera recomendado por los profesores de las asignaturas como herramientas para el fortalecimiento de los conocimientos adquiridos, asi mismo para aclarar dudas al estudiante o complementar la informacion asignada por el docente, y ademas cumplio todas las expectativas en su fase de simulacion y visualizacion, cumpliendo su factibilidad e importancia.
Robust Tracking Approach for Dealing with Classification Uncertainty
Year: 2018

Every year about 1.25 million people die as a result of road traffic accidents. Besides the traffic on the road increases every day, including the environmental impact due to the corresponding traffic emissions. Autonomous driving could be a unique opportunity to increase these traffic safety, traffic flow efficiency and to reduce emissions in future. In order to operate reliably and accurately, autonomous driving vehicles and autonomous features require an accurate perception of the infrastructure and other road users in the surrounding. Multi object tracking is the process concerned with the estimation of the states of the objects in the environment, given the noisy measurements from the sensors. Besides the estimation of the states, it is also necessary to estimate the classification of the objects e.g. for a correct situation analysis and path planning. Classifiers are used to detect and classify objects from image frames, however the classification is sometimes incorrect or uncertain. This results in a decrease of tracking accuracy and an incorrect classification in these classification uncertain conditions. The contribution in this work is, by keeping the classification uncertainty in the tracking approach and using it in all steps, to jointly improve the tracking accuracy as well as the classification.
The Sloan Digital Sky Survey Reverberation Mapping Project: Initial C iv Lag Results from Four Years of Data
Year: 2019

We present reverberation mapping (RM) lags and black hole mass measurements using the C iv l1549 broad emission line from a sample of 348 quasars monitored as a part of the Sloan Digital Sky Survey RM Project. Our data span four years of spectroscopic and photometric monitoring for a total baseline of 1300 days, allowing us to measure lags up to ~750 days in the observed frame (this corresponds to a rest frame lag of ~300 days in a quasar at z 1.5 and ~190 days at z 3) We report significant time delays between the continuum and the C iv l1549 emission line in 48 quasars, with an estimated false positive detection rate of 10% Our analysis of marginal lag measurements indicates that there are on the order of ~100 additional lags that should be recoverable by adding more years of data from the program. We use our measurements to calculate black hole masses and fit an updated C iv radius luminosity relationship. Our results significantly increase the sample of quasars with C iv RM results, with the quasars spanning two orders of magnitude in luminosity toward the high luminosity end of the C iv radius luminosity relation. In addition, these quasars are located at some of the highest redshifts (z 1.4 2.8) of quasars with black hole masses measured with RM. This work constitutes the first large sample of C iv RM measurements in more than a dozen quasars, demonstrating the utility of multiobject RM campaigns.
Development and Application of Precise Debris flow Risk Assessment Index in Urban Area
Year: 2015

In recent years, social demands for debris flow disaster prevention measures are increasing because the more landslides make, the more loss of lives and property damages in urban area. However, in domestic, there are no precise indexes for the assessment of debris flow risk in urban area. For this reason, precise debris flow risk assessment indexes should be identified as a basic research. In this study, index of precise debris flow risk assessment considering Korean situations was derived through the analysis of inventory system using HAZAUS MH of FEMA. Twenty one indexes have been selected and categorized as three groups such as population, buildings and infrastructures. Assessment indexes were validated by AHP expert survey as 73.5% for population, 14.8% for infrastructure and 11.7% for Buildings. The indexes were applied to assess debris flow risk in Seocho gu, debris flow damaged area as a case study. As the result of comparison between the results of Uran Vulnerability Assessment considering Climate change in 2011 and the results of this study, the precise debris flow risk assessment of building units could be conducted.
Centipede venoms as a source of drug leads
Venue: Expert opinion on drug discovery
Year: 2016

Centipedes are one of the oldest and most successful lineages of venomous terrestrial predators. Despite their use for centuries in traditional medicine, centipede venoms remain poorly studied. However, recent work indicates that centipede venoms are highly complex chemical arsenals that are rich in disulfide constrained peptides that have novel pharmacology and three dimensional structure.  This review summarizes what is currently known about centipede venom proteins, with a focus on disulfide rich peptides that have novel or unexpected pharmacology that might be useful from a therapeutic perspective. The authors also highlight the remarkable diversity of constrained three dimensional peptide scaffolds present in these venoms that might be useful for bioengineering of drug leads.  Like most arthropod predators, centipede venoms are rich in peptides that target neuronal ion channels and receptors, but it is also becoming increasingly apparent that many of these peptides have novel or unexpected pharmacological properties with potential applications in drug discovery and development.
Good Counterfactuals and Where to Find Them: A Case Based Technique for Generating Counterfactuals for Explainable AI (XAI)
Venue: ICCBR
Year: 2020

Recently, a groundswell of research has identified the use of counterfactual explanations as a potentially significant solution to the Explainable AI (XAI) problem. It is argued that (a) technically, these counterfactual cases can be generated by permuting problem features until a class change is found, (b) psychologically, they are much more causally informative than factual explanations, (c) legally, they are GDPR compliant. However, there are issues around the finding of good counterfactuals using current techniques (e.g. sparsity and plausibility) We show that many commonly used datasets appear to have few good counterfactuals for explanation purposes. So, we propose a new case based approach for generating counterfactuals using novel ideas about the counterfactual potential and explanatory coverage of a case base. The new technique reuses patterns of good counterfactuals, present in a case base, to generate analogous counterfactuals that can explain new problems and their solutions. Several experiments show how this technique can improve the counterfactual potential and explanatory coverage of case bases that were previously found wanting.
Conversational Bot for Newcomers Onboarding to Open Source Projects
Venue: ICSE
Year: 2020

This paper targets the problems newcomers face when onboarding to open source projects and the low retention rate of newcomers. Open source software projects are becoming increasingly more popular. Many major companies have started building open source software. Unfortunately, many newcomers only commit once to an open source project before moving on to another project. Even worse, many novices struggle with joining open source communities and end up leaving quickly, sometimes before their first successful contribution. In this paper, we propose a conversational bot that would recommend projects to newcomers and assist in the onboarding to the open source community. The bot would be able to provide helpful resources, such as Stack Overflow related content. It would also be able to recommend human mentors. We believe that this bot would improve newcomers' experience by providing support not only during their first contribution, but by acting as an agent to engage them to the project.
Effectiveness of online presence in a blended higher learning environment in the Pacific
Venue: Studies in Higher Education
Year: 2019

The widespread use of technology has facilitated many changes in the education sector including higher education. Academic institutes are concentrating their efforts on measuring the level of student engagement and participation in online learning environments for student success. This paper analyses student log data to quantify the effectiveness of online presence on student performance in a blended course using frequency and duration as indicators. The analysis shows both frequency and duration having a statistically significant impact on the students' final marks. The study proposes a multiple linear regression model using these measurements to predict the final mark of students in a blended learning environment. The predictive regression model, explained through the use of two new models; Online Measurable Presence Model (OMPM) and Slingshot model, can be used to determine the effectiveness of student online presence for success in a blended higher learning environment in the Pacific.
SUCAG: Stochastic Unbiased Curvature aided Gradient Method for Distributed Optimization
Venue: 2018 IEEE Conference on Decision and Control (CDC)
Year: 2018

We propose and analyze a new stochastic gradient method, which we call Stochastic Unbiased Curvature aided Gradient (SUCAG) for finite sum optimization problems. SUCAG constitutes an unbiased total gradient tracking technique that uses Hessian information to accelerate convergence. We analyze our method under the general asynchronous model of computation, in which each function is selected infinitely often with possibly unbounded (but sublinear) delay. For strongly convex problems, we establish linear convergence for the SUCAG method. When the initialization point is sufficiently close to the optimal solution, the established convergence rate is only dependent on the condition number of the problem, making it strictly faster than the known rate for the SAGA method. Furthermore, we describe a Markov driven approach of implementing the SUCAG method in a distributed asynchronous multi agent setting, via gossiping along a random walk on an undirected communication graph. We show that our analysis applies as long as the graph is connected and, notably, establishes an asymptotic linear convergence rate that is robust to the graph topology. Numerical results demonstrate the merits of our algorithm over existing methods.
Hand Gesture Recognition System for Parking Applications based on Machine Vision
Venue: 2020 IEEE 3rd International Conference on Electronic Information and Communication Technology (ICEICT)
Year: 2020

In this paper, we aim to combine the best features of image recognition along with embedded control system. The system completes the image preprocessing and recognizes the gesture information, and then feeds the recognition results back to the Raspberry Pi through the Bluetooth device. Raspberry Pi sends the corresponding gesture number to STC89C52 according to the recognition result, and STC89C52 converts the gesture number into a motion instruction and sends it to the machine to control the movement of car. For the choice of gestures, we use five different gestures to control the car's forward, backward, turn left.turn right, and stop. The geometric moment feature and histogram feature of the preprocessed gesture image are extracted, and the first two components of the seven feature components and the compactness of the preprocessed gesture image are selected as feature values. Anaconda distribution of Python is used to build a BP neural network, and takes feature value as input. After the BP neural network outputs the recognition results, the embedded system converts the recognition results into control instructions to control the the car movement.
Effects of dietary supplementation with epidermal growth factor on nutrient digestibility, intestinal development and expression of nutrient transporters in early weaned piglets
Venue: Journal of animal physiology and animal nutrition
Year: 2019

The abnormalities in intestinal morphology and digestive function during weaning are associated with the loss of milk borne growth factors. Epidermal growth factor (EGF) has been shown to stimulate the growth of animals. This study was to determine the effect of dietary EGF on nutrient digestibility, intestinal development and the expression of genes encoding nutrient transporters in weaned piglets. Forty two piglets were weaned at 21 days and assigned to one of three treatment groups: (1) basal diet (control) (2) basal diet 200 ug/kg EGF or (3) basal diet 400 ug/kg EGF. Each treatment consisted of 14 replicates, and seven piglets from each treatment were sampled on day 7 and 14. The EGF supplementation significantly elevated (p 0.05) the coefficients of total tract apparent digestibility of crude protein, calcium and phosphorus, but tended to decrease sucrase activity (p 0.10) than the control group. At day 7 post weaning, animals receiving EGF diets showed a tendency (p 0.10) towards greater ileal villus height (VH) jejunal crypt depth (CD) and duodenal VH:CD when compared with the control group. Moreover, the mRNA levels of glucose transporter 2 (Slc2a2) neutral amino acid transporter (Slc6a19) and calbindin D9k (S100G) tended to be higher (p 0.10) for EGF groups than the control group. By day 14, EGF supplementation markedly enhanced (p 0.05) the VH, CD and VH:CD in the jejunum compared to the control group. This addition also up regulated (p 0.05) the mRNA level and the protein abundance of peptide transporter 1 than the control group. These findings demonstrated that dietary EGF beneficially enhanced nutrient digestibility, improved intestinal development and increased the mRNA expression of nutrient transporters in weaned piglets.
Piezoelectric Thin Films of ZnO Nanorods/Nanowalls Grown by Chemical Bath Deposition
Venue: IEEE Transactions on Nanotechnology
Year: 2018

This study presents a comparison of the piezoelectric properties of nanostructured thin films made of arrays of vertically oriented ZnO nanorods (ZnO NRs) over ITO glass substrate and of ZnO nanowalls (ZnO NWs) over aluminium substrate. Both nanostructures were synthesized on a large area through chemical bath deposition. The morphological, structural, and chemical characteristics of the produced nanostructures were investigated in order to assess the crystal quality and purity. To this purpose, we used different techniques, such as field emission scanning electron microscopy, atomic force microscopy, energy dispersive x ray analysis, powder x ray diffraction, x ray photoelectron spectroscopy, and photoluminescence spectroscopy. Moreover, the piezoelectric response of the nanostructured films was assessed through piezoresponse force microscopy. This technique was employed to obtain a quantitative evaluation of the piezoelectric coefficient <inline formula><tex math notation="LaTeX"{d_{33}/tex math>/inline formula> of the film. We obtained <inline formula><tex math notation="LaTeX"{d_{33}/tex math>/inline formula> values as high as (7.01 0.33) pm/V for ZnO NRs and (2.63 0.49) pm/V for ZnO NWs films.