nils-herrmann/clean_scirepeval huggingface dataset:
Origami Wheel Transformer: A Variable Diameter Wheel Drive Robot Using an Origami Structure.
Year: 2017

A wheel drive mechanism is simple, stable, and efficient, but its mobility in unstructured terrain is seriously limited. Using a deformable wheel is one of the ways to increase the mobility of a wheel drive robot. By changing the radius of its wheels, the robot becomes able to pass over not only high steps but also narrow gaps. In this article, we propose a novel design for a variable diameter wheel using an origami based soft robotics design approach. By simply folding a patterned sheet into a wheel shape, a variable diameter wheel was built without requiring lots of mechanical parts and a complex assembly process. The wheel's diameter can change from 30 to 68 mm, and it is light in weight at about 9.7 g. Although composed of soft materials (fabrics and films) the wheel can bear more than 400 times its weight. The robot was able to change the wheel's radius in response to terrain conditions, allowing it to pass over a 50 mm gap when the wheel is shrunk and a 50 mm step when the wheel is enlarged.
Visual Rationalizations in Deep Reinforcement Learning for Atari Games
Venue: BNCAI
Year: 2018

Due to the capability of deep learning to perform well in high dimensional problems, deep reinforcement learning agents perform well in challenging tasks such as Atari 2600 games. However, clearly explaining why a certain action is taken by the agent can be as important as the decision itself. Deep reinforcement learning models, as other deep learning models, tend to be opaque in their decision making process. In this work, we propose to make deep reinforcement learning more transparent by visualizing the evidence on which the agent bases its decision. In this work, we emphasize the importance of producing a justification for an observed action, which could be applied to a black box decision agent.
Thinking About the Learning Design: Theories, Models, Frameworks, and Heuristics
Year: 2019

People have been studying how humans learn and theorizing about ways to support their learning for many years. This chapter addresses the importance of using relevant concepts and empirical based knowledge of human learning to inform the design and development of the open shared learning objects and sequences. This chapter may be one of the more challenging ones given the number of potential concepts and data that may inform design practice, and also given that there are many different preferences that open shared learning designers and developers may have in their selections. The core idea is that designing for learning centeredness benefits from knowledge of human learning and thought through and informed processes in learning design.
Risk Factors for 30 Day Hospital Readmission in Patients =65 Years of Age
Venue: Proceedings
Year: 2008

The objective of the study was to develop and validate predictors of 30 day hospital readmission using readily available administrative data and to compare prediction models that use alternate comorbidity classifications. A retrospective cohort study was designed; the models were developed in a two thirds random sample and validated in the remaining one third sample. The study cohort consisted of 29,292 adults aged 65 or older who were admitted from July 2002 to June 2004 to any of seven acute care hospitals in the Dallas Fort Worth metropolitan area affiliated with the Baylor Health Care System. Demographic variables (age, sex, race) health system variables (insurance, discharge location, medical vs surgical service) comorbidity (classified by the Elixhauser classification or the High Risk Diagnoses in the Elderly Scale) and geographic variables (distance from patient's residence to hospital and median income) were assessed by estimating relative risk and risk difference for 30 day readmission. Population attributable risk was calculated. Results showed that age 75 or older, male sex, African American race, medical vs surgical service, Medicare with no other insurance, discharge to a skilled nursing facility, and specific comorbidities predicted 30 day readmission. Models with demographic, health system, and either comorbidity classification covariates performed similarly, with modest discrimination (C statistic, 0.65) and acceptable calibration (Hosmer Lemeshow k2 6.08; P 0.24) Models with demographic variables, health system variables, and number of comorbid conditions also performed adequately. Discharge to long term care (relative risk, 1.94; 95% confidence interval, 1.80 2.09) had the highest population attributable risk of 30 day readmission (12.86% A 25% threshold of predicted probability of 30 day readmission identified 4.1% of patients =65 years old as priority patients for improved discharge planning. We conclude that elders with a high risk of 30 day hospital readmission can be identified early in their hospital course.
De Globalisation? Global Value Chains in the Post COVID 19 Age
Year: 2020

This paper evaluates the extent to which the world economy has entered a phase of de globalisation, and it offers some speculative thoughts on the future of global value chains in the post COVID 19 age. Although the growth of international trade flows relative to that of GDP has slowed down since the Great Recession, this paper finds little systematic evidence indicating that the world economy has already entered an era of de globalisation. Instead, the observed slowdown in globalisation is a natural sequel to the unsustainable increase in globalisation experienced in the late 1980s, 1990s and early 2000s. I offer a description of the mechanisms leading to that earlier expansionary phase, together with a discussion of why these forces might have run out of steam, and of the extent to which they may be reversible. I conclude that the main challenge for the future of globalisation is institutional and political in nature rather than technological, although new technologies might aggravate the trends in inequality that have created the current political backlash against globalisation. Zooming in on the COVID 19 global pandemic, I similarly conclude that the current health crisis may further darken the future of globalisation if it aggravates policy tensions across countries.
Prevalence of primary dysmenorrhea, its intensity, impact and associated factors among female students' at Gondar town preparatory school, Northwest Ethiopia
Venue: BMC Women's Health
Year: 2020

BackgroundPrimary dysmenorrhea is defined as a crampy pain in the lower abdomen before or during the menstrual period in the absence of any pelvic pathology. It is the leading motherhood problem worldwide but there is limited evidence on the prevalence of primary dysmenorrhea in the study area as well in Ethiopia. Researching primary dysmenorrhea helps to focus on the treatment plan. The study aimed to assess the prevalence, intensity, impact, and associated factors of primary dysmenorrhea among female students at Gondar town preparatory school.MethodsA cross sectional study design conducted among female students at Gondar town Preparatory School from May 1 10/2017. A total of 459 study participants were used. A simple random sampling technique was used to select study participants. A self administered structured questionnaire was employed.  20 were used for data entry and analysis respectively. A binary logistic regression model was computed. Variables having a p value 0.05 in the multivariate logistic regression model were considered as statistically significant. total of 459 female students participated in the study with a response rate of 96.29% The prevalence of primary dysmenorrhea among female students was found to be 64.7% (95% CI; 60.2 69.2% Around 61% reported moderate intensity of menstrual pain and 50.7% complain about lower abdominal pain. Sixty five percent of study participants reported that absenteeism from school was the impact of menstrual pain. Having irregular monthly menstrual cycle (AOR 1.70, 95% CI; 1.02, 2.84) and positive family history of dysmenorrhea (AOR 5.19, 95% CI: 3.21, 8.37) were significantly associated with primary dysmenorrhea.ConclusionsThe prevalence of primary dysmenorrhea was found to be high. Having an irregular monthly menstrual cycle and a positive family history of dysmenorrhea were determinants of primary dysmenorrhea.
Sobrepoblacion canina relacionada con salud publica y su incidencia en La transmision de enfermedades en los habitantes de la ciudad de Tulcan
Year: 2014

Durante muchos anos la poca generacion de politicas de saneamiento ambiental locales ligadas a la salud publica y la falta de educacion y responsabilidad en las personas, ha desencadenado que la poblacion canina de la ciudad de Tulcan haya crecido de una manera desproporcionada en donde se evidencia que la gran mayoria de los animales que estan en la calle tienen duenos y los dejan deambular sin importar lo que les pase. La presente investigacion se la realiza porque en la actualidad existe y se ve a simple vista una sobrepoblacion canina, catalogada como problema de salud publica a nivel mundial; asi como la falta de cumplimiento de los derechos de los animales. Las mascotas estan expuestas a parasitos externos, como las pulgas y garrapatas, que pueden actuar como vectores de varias patologias debido al contacto del animal con el ser humano. Estudios realizados por la Facultad de veterinaria de la UBA reportaron que en Buenos Aires: Existen alrededor de 400 mil perros los que vierten 68 toneladas de excrementos solidos y 120 mil litros de orina, en las veredas y plazas de la ciudad. Este estudio revela la contaminacion del ambiente y el riesgo para la salud publica con la presencia de agentes zoonoticos. La sobrepoblacion canina segun Downes (2009) indica que "El crecimiento descontrolado de perros causa un impacto negativo sobre la Salud Publica de los paises en desarrollo" Tomando en cuenta estos antecedentes, hemos visto con mucha preocupacion que los perros en la ciudad de Tulcan estan aumentando, por lo tanto se ha incrementado la irresponsabilidad de los duenos de los perros que no se responsabilizan por sus mascotas.
Tugas Pramuwisata dalam Meeting Service
Venue: PARIWISATA BUDAYA: JURNAL ILMIAH AGAMA DAN BUDAYA
Year: 2019

Tourists guide, for common people, is mainly known as a person who escort tourists to tourist objects. Only a few people, specially those who works for travel industries, know that a tourist guide has several jobs to do, from picking up clients at the airport, transfering to different hotels, escorting back to the departure terminal, and also conducting meeting service that include solving problems and selling optional tours. Meeting service plays important role in increasing economic benefit both for the travel agent and also for the tourists guide as a representative. It also helps the customers in achieving customers' satisfaction through problem solving, hotel and resort presentation and tour organizaton. This article gives technical knowledge to improve skill as a representative of the company and suficient understanding of the job description as a tourists guide during the meeting service after the clients' arrival.
How could I reduce my student anxiety about evaluating mathematics by mixed method research?
Year: 2020

This research has been applied in terms of purpose and descriptive in terms of method of action research.  The method of collecting information was using a new approach of combined research method. The research site was one of the elementary schools in Birjand in the academic year 2014 2015. The research sample was selected by purposeful sampling method. In this research, after proving the existence of anxiety and anxiety of the sixth grade student in the evaluation of math lesson, using scientifically and creatively collected evidence and information, scientific and creative methods were used to reduce anxiety and anxiety. Research tools included qualitative methods such as peer evaluation, observation and interview with parents, as well as quantitative methods such as Test Anxiety Inventory (TAI) for data collection.  Recommended solutions to the present study include: examining the student's nutritional status and improving it as one of the most important prerequisites for learning, examining the history of fear in math through conversation with the student and his parents focusing on the principle of succession fear, helping students to volunteer in situations The course was anxious, offering a few simple exercises to the student before the main assessment in the math bell and so on.  After implementation of these solutions, the student's anxiety was assessed again with the help of combined research method. The results showed that students' anxiety was reduced in math lessons.
DiracNets: Training Very Deep Neural Networks Without Skip Connections
Venue: ArXiv
Year: 2017

Deep neural networks with skip connections, such as ResNet, show excellent performance in various image classification benchmarks. It is though observed that the initial motivation behind them training deeper networks does not actually hold true, and the benefits come from increased capacity, rather than from depth. Motivated by this, and inspired from ResNet, we propose a simple Dirac weight parameterization, which allows us to train very deep plain networks without explicit skip connections, and achieve nearly the same performance. This parameterization has a minor computational cost at training time and no cost at all at inference, as both Dirac parameterization and batch normalization can be folded into convolutional filters, so that network becomes a simple chain of convolution ReLU pairs. We are able to match ResNet 1001 accuracy on CIFAR 10 with 28 layer wider plain DiracNet, and closely match ResNets on ImageNet. Our parameterization also mostly eliminates the need of careful initialization in residual and non residual networks. The code and models for our experiments are available at this https URL
A tutorial for analyzing human reaction times: How to filter data, manage missing values, and choose a statistical model
Venue: Applied Psycholinguistics
Year: 2011

This tutorial for the statistical processing of reaction times collected through a repeated measure design is addressed to researchers in psychology. It aims at making explicit some important methodological issues, at orienting researchers to the existing solutions, and at providing them some evaluation tools for choosing the most robust and precise way to analyze their data. The methodological issues we tackle concern data filtering, missing values management, and statistical modeling (F1, F2, F1 F2, quasi F, mixed effects models with hierarchical, or with crossed factors) For each issue, references and remedy suggestions are given. In addition, modeling techniques are compared on real data and a benchmark is given for estimating the precision and robustness of each technique.
Security Enhancements over AODV Using Multi hop Acknowledgment
Year: 2020

In most applications of Mobile Ad hoc Networking and Wireless Sensor networks (WSNs) security and power consumption is a recurring problem which is very difficult to solve due to unpredictable behaviour, environmental changes and mobility of nodes. TERP is a Trust based Energy Routing Protocol that considers the energy conservation and security aspects of WSNs. It is an improved version of AODV and ensures low power consumption while adding a trust based system to the reactive nature of AODV. It also provides the solutions for the most basic attacks like node selfishness, spoofing, misbehaviour and packet sniffing. But black hole attack, gray hole attack, Sybil and wormhole attacks are yet to be addressed in the TERP. This paper provides a solution to detect and prevent the node misbehaviour and gray hole attack. TERP identifies the node misbehaviour using direct and indirect trust recommendations received from neighbour nodes. The detection rate of misbehaving nodes is less during the initial life of the network. Therefore we propose a method that detects the node misbehaviour during the initial life by using a multi hop acknowledgement system. The simulation results show that the proposed method performs well in detecting the gray hole and node misbehaviour.
Certificateless Searchable Public Key Encryption Scheme for Industrial Internet of Things
Venue: IEEE Transactions on Industrial Informatics
Year: 2018

With the widespread adoption of Internet of Things and cloud computing in different industry sectors, an increasing number of individuals or organizations are outsourcing their Industrial Internet of Things (IIoT) data in the cloud server to achieve cost saving and collaboration (e.g. data sharing) However, in this environment, preserving the privacy of data remains a key challenge and inhibiting factor to an even wider adoption of IIoT in the cloud environment. To mitigate these issues, in this paper, we design a new secure channel free certificateless searchable public key encryption with multiple keywords scheme for IIoT deployment. We then demonstrate the security of the scheme in the random oracle model against two types of adversaries, where one adversary is given the power to choose a random public key instead of any user's public key and another adversary is allowed to learn the system master key. In the presence of these types of adversaries, we evaluate the performance of the proposed scheme and demonstrate that it achieves (computational) efficiency with low communication cost.
A note on the Duffin Schaeffer conjecture
Year: 2013

Given a sequence of real numbers \psi(n)}_{n\in\mathbb{N} with $0\leq \psi(n) 0$ such that \sum_{n\in\mathbb{N}\psi(n){1+\epsilon}\cdot\frac{\varphi(n){n}\infty, then the Lebesgue measure of $W(\psi) equals 1.
A report on the piloting of a novel computer based medical case simulation for teaching and formative assessment of diagnostic laboratory testing
Venue: Medical education online
Year: 2011

Insufficient attention has been given to how information from computer based clinical case simulations is presented, collected, and scored. Research is needed on how best to design such simulations to acquire valid performance assessment data that can act as useful feedback for educational applications. This report describes a study of a new simulation format with design features aimed at improving both its formative assessment feedback and educational function.  Case simulation software (LabCAPS) was developed to target a highly focused and well defined measurement goal with a response format that allowed objective scoring. Data from an eight case computer based performance assessment administered in a pilot study to 13 second year medical students was analyzed using classical test theory and generalizability analysis. In addition, a similar analysis was conducted on an administration in a less controlled setting, but to a much large sample (n=143) within a clinical course that utilized two random case subsets from a library of 18 cases.  Classical test theory case level item analysis of the pilot assessment yielded an average case discrimination of 0.37, and all eight cases were positively discriminating (range=0.11 0.56) Classical test theory coefficient alpha and the decision study showed the eight case performance assessment to have an observed reliability of s=G=0.70. The decision study further demonstrated that a G=0.80 could be attained with approximately 3 h and 15 min of testing. The less controlled educational application within a large medical class produced a somewhat lower reliability for eight cases (G=0.53) Students gave high ratings to the logic of the simulation interface, its educational value, and to the fidelity of the tasks.  LabCAPS software shows the potential to provide formative assessment of medical students' skill at diagnostic test ordering and to provide valid feedback to learners. The perceived fidelity of the performance tasks and the statistical reliability findings support the validity of using the automated scores for formative assessment and learning. LabCAPS cases appear well designed for use as a scored assignment, for stimulating discussions in small group educational settings, for self assessment, and for independent learning. Extension of the more highly controlled pilot assessment study with a larger sample will be needed to confirm its reliability in other assessment applications.
The relationship of teacher child play interactions to mathematics learning in preschool
Year: 2016

Teacher child interactions in preschool children's play may enhance mathematics learning in several ways. As teachers interact with children, they may promote more complex, independent, and symbolic play. Resulting increases in play abilities, in turn, can enhance intellectual growth, including mathematical thinking. Teachers may also facilitate math learning directly by engaging children in mathematical thinking as they play. The purpose of this study was to examine the effects on math learning of interactions that enhance play, itself, and those that directly engage children in mathematical thinking. The classroom play interactions of 47 preschoolers and their teachers were video recorded and analysed. The relationship between specific teacher child interactions both enhancing play strategies and promoting math approaches was examined. Pre test and post test scores on the Test of Early Mathematics Ability, Third Edition (TEMA 3) showed that three play interactions predicted growth in math learning: 'good fit' interactions to support play, itself, and number and math communication interactions. Findings confirm that teacher interactions in children's play can have an impact on academic performance. Interactions that are a good fit with what children are currently playing and those that prompt children's thinking about number or engage them in communicating about math enhance early math performance.
Pengaruh Employee Engagement terhadap Kepuasan Kerja dan Turnover Intention Perawat (Studi pada Rumah Sakit Wava Husada Kepanjen Malang)
Year: 2016

Human resources is essential to prevent turnover intention of hospital nurses. Nurses engagement is expected to produce nurses satisfaction and finally lower turnover intention. This study aims to examine the effect of employee engagement on job satisfaction and turnover intention of nurses at Wava Husada Hospital Kepanjen Malang. The research was a cross sectional research. Sample of the study were 102 nurses who work at inpatient and outpatient unit of Wava Husada Hospital. Questionnaire with 5 point Likert scale was used to measure employee engagement, job satisfaction, turnover intention. Path analysis was used to test the direct and indirect direct effect of the variables. The results showed that employee engagement has direct effect on job satisfaction and turnover intention. On the other hand, job satisfaction has direct effect on turnover intention of nurses in hospitals Wava Husada Kepanjen. The results also indicate that there was an indirect effect of employee engagement on turnover intention through job satisfaction