nils-herrmann/clean_scirepeval huggingface dataset:
A Systematic Review on Exploring the Potential of Educational Robotics in Mathematics Education
Year: 2020

By providing students with a highly interactive and hands on learning experience, robotics promises to inspire a new generation of mathematical learning. This paper aims to review the empirical evidence on the application of robotics in mathematics education and to define future research perspectives of robot assisted mathematics education. After a systematic search in online database via keyword search and snowballing approach, we analyzed 20 empirical studies on how to teach and learn mathematical knowledge through robotics. The results indicate that (1) most studies were conducted with a small sample size, the largest research groups were elementary school students and secondary school students, most studies used LEGO robots, robots were primarily applied to teach and/or learn graphics, geometry, and algebra, and almost half of the studies taught mathematics by engaging students in game like interactions with robots; (2) half of the studies adopted a non experimental research design, and most studies evaluated student performance through observation, test/examination, questionnaires, or verbal interviews; and (3) instructional implications proposed in the 20 papers can be clustered into four themes: human robot interaction, connections between mathematics and real life, pedagogical suggestions, and facility conditions. The 20 papers suggest that robotics generally plays an active role in mathematics education; however, there are indeed situations in which no significant improvement was found in students' mathematical learning. In view of this, we prospect the future research perspectives of robot assisted mathematics education and propose that more rigorous intervention studies could be conducted to further explore the integration of robotics and mathematics education.
E Procurement Service Quality in Malaysia
Year: 2017

The government in Malaysia has fully adopted and developed the applications and practices of information communication technologies (ICTs) to provide better online services to enhance the government's credibility. To understand service quality issues within this new delivery channel, this paper investigates e procurement portal/websites through the use of E Service Quality (E S QUAL) and E Recovery Service Quality (E RecS QUAL) scales by employing a questionnaire survey distributed to 400 respondents. The collected data were analyzed using Smart PLS 3.0 to test the relationships among efficiency, system availability and privacy, responsiveness, and contact. The results show that both E S QUAL and E RecS QUAL strongly influence perceived service quality and behavioral intentions. In addition, the evidence of perceived service quality in its role as a mediator was significant. The findings constitute an empirical contribution to the literature on the application of electronic service quality.
State of the Art Review of Biocementation by Microbially Induced Calcite Precipitation (MICP) for Soil Stabilization
Year: 2017

Biocementation is a recently developed new branch in geotechnical engineering that deals with the application of microbiological activity to improve the engineering properties of soils. One of the most commonly adopted processes to achieve soil biocementation is through microbially induced calcite precipitation (MICP) This technique utilizes the metabolic pathways of bacteria to form calcite (CaCO3) that binds the soil particles together, leading to increased soil strength and stiffness. This paper presents a review of the use of MICP for soil improvement and discusses the treatment process including the primary components involved and major affecting factors. Envisioned applications, potential advantages and limitations of MICP for soil improvement are also presented and discussed. Finally, the primary challenges that lay ahead for the future research (i.e. treatment optimization, upscaling for in situ implementation and self healing of biotreated soils) are briefly discussed.
Collision Free Distributed Multi Target Tracking Using Teams of Mobile Robots with Localization Uncertainty
Venue: 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Year: 2020

Accurately tracking dynamic targets relies on robots accounting for uncertainties in their own states to share information and maintain safety. The problem becomes even more challenging when there is an unknown and time varying number of targets in the environment. In this paper we address this problem by introducing four new distributed algorithms that allow large teams of robots to: i) run the prediction and ii) update steps of a distributed recursive Bayesian multi target tracker, iii) determine the set of local neighbors that must exchange data, and iv) exchange data in a consistent manner. All of these algorithms account for a bounded level of localization uncertainty in the robots by leveraging our recent introduction of the convex uncertainty Voronoi (CUV) diagram, which extends the traditional Voronoi diagram to account for localization uncertainty. The CUV diagram introduces a tessellation over the environment, which we use in this work both to distribute the multi target tracker and to make control decisions about where to search next. We examine the efficacy of our method via a series of simulations and compare them to our previous work which assumed perfect localization.
Why a London museum should return the stolen bones of an Irish giant
Year: 2018

Why a London museum should return the stolen bones of an Irish giant June 6, 2018 3.31pm BST *Updated June 7, 2018 12.27pm BST It has all the hallmarks of a Mary Shelley style Gothic melodrama. A young man, born in 18th century Ireland with a condition that makes him a "giant" turns himself into a freakshow curiosity and becomes a celebrated figure in Georgian London. Then he comes to the notice of an eminent Scots surgeon who becomes obsessed with his potential value as a medical exhibit. The young man is left devastated when he is pickpocketed of his life savings, contracts TB and succumbs to an untimely death at just 22. Enter the evil bodysnatchers who remove his body before it can be buried at sea.
Botulinum toxin management of spasmodic dysphonia (laryngeal dystonia) A 12 year experience in more than 900 patients
Venue: The Laryngoscope
Year: 2015

This paper reviews a 12 year experience in more than 900 patients with spasmodic dysphonia who have been treated with botulinum toxin.  This is a retrospective analysis of patients with adductor spasmodic dysphonia (strainstrangled voice) abductor spasmodic dysphonia (whispering voice) and adductor breathing dystonia (paradoxical vocal fold motion) all of whom have been treated with botulinum toxin injections for relief of symptom.  All of the patients were studied with a complete head and neck and neurologic examination; fiberoptic laryngostroboscopy; acoustic and aerodynamic measures; and a speech evaluation including the Universal spasmodic dysphonia rating scale. Some were given electromyography. All patients received botulinum toxin injections into the affected muscles under electromyographic guidance.  The adductor patients had an average benefit of 90% of normal function lasting an average of 15.1 weeks. The abductor patients had an average benefit of 66.7% of normal function lasting an average of 10.5 weeks. Adverse effects included mild breathiness and coughing on fluids in the adductor patients, and mild stridor in a few of the abductor patients.  Botulinum toxin A injection of the laryngeal hyperfunctional muscles has been found over the past 12 years to be the treatment of choice to control the dystonic symptoms in most patients with spasmodic dysphonia. Laryngoscope, 108:1435 1441, 1998
SAT LB98 Early Atherosclerosis in Polycystic Ovary Syndrome. a Systematic Review, Meta Analysis and Meta Regression
Venue: Journal of the Endocrine Society
Year: 2020

Polycystic ovary syndrome (PCOS) is a common disorder affecting reproductive age women and is a cluster of endocrine and metabolic alterations ranging from impaired ovulation and androgen excess to abdominal obesity and metabolic syndrome leading to increased cardiovascular risk profile.  To perform a meta analysis on the effect of PCOS on surrogate markers of atherosclerosis, namely intima media thickness (IMT) flow mediated dilation (FMD) and pulse wave velocity (PWV) and to run a meta regression on the potential determinants of preclinical atherosclerosis.  A search through Pubmed/Medline and ISI web of knowledge retrieved 90 studies that were used for meta analysis. Selected outcomes were IMT (n=6199) FMD (n=3090) and PWV (n=2477) while age, BMI, waist circumference, total testosterone, free androgen index (FAI) total HDL and LDL cholesterol, HOMA index, systolic and diastolic blood pressure were used for meta regression analysis.  Random effect meta analysis showed that IMT was significantly increased (ES 0.47, 95% C.I. 0.64 to 0.30, p<0.0001) FMD was significantly impaired (ES 0.92, 95% C.I. 0.69 to 1.15, p<0.0001) and PWV was significantly increased (ES 0.28, 95% C.I. 0.48 to 0.08, p=0.006) in PCOS compared to controls. Meta regression analysis showed that FMD was positively correlated with FAI (p=0.018) while negative correlations were found between Effect Size (IMT) and BMI (p=0.02) waist circumference (p=0.05) and total cholesterol (p=0.02)  This meta analysis shows a clear effect of PCOS on all markers of preclinical atherosclerosis (IMT, FMD and PWV) Heterogeneity of results is explained in part by the androgen status that was positively linked to impairment of FMD while increasing of anthropometric and metabolic variables (waist, BMI and total cholesterol) seem to overcome PCOS on preclinical atherosclerosis.
Evaluation de la satisfaction des patients de la prise en charge de la douleur au service des urgences de l'Hopital Militaire d'Instruction Mohamed V, Rabat, Maroc
Year: 2015

La douleur reste le premier motif de consultation aux services des urgences. Sa prise en charge differe en fonction des structures de soins, du personnel soignant, du contexte et en fonction du malade lui meme. L'evaluation de cette prise en charge peut porter sur plusieurs aspects. La satisfaction reste l'un des ces aspects qui reflete la relation complexe entre les besoins des patients, leurs esperances, leurs experiences en matiere de soins et ce qui leur etait offert comme prestation. L'objectif de notre etude est d'evalue cette satisfaction.  Il s'agit d'une etude descriptive transversale qui a concerne 105 patients ayant eu recours au service des urgences de l'Hopital Militaire d'Instruction Mohamed V, Rabat, Maroc. La collecte des donnees s'est faite entre le 8 septembre 2014 et le 5 decembre 2014 en utilisant un questionnaire elabore a partir d'autres etudes faites dans le meme domaine. Resultats Notre population avait une moyenne d'age de 40 20,72 ans avec un sex ratio M/F 3/2. Les militaires representaient 61 de l'effectif 85,5 etaient satisfaits des conditions d'accueil au niveau du bureau d'enregistrement alors que 75 etaient peu satisfaits voire insatisfaits au niveau de la salle d'attente. Ce sentiment d'insatisfaction etait plus marque au niveau du temps d'attente avant de voir le medecin. Concernant la prise en charge medicale 89 de nos patients etaient satisfaits et leur sentiment de douleur evalue par une echelle verbale numerique a chute de 8,5 2 a 3,5 1,5 de facon statistiquement significative (p 0,02) L'age et le niveau d'etude etaient des facteurs associes de facon statistiquement significative au degre de satisfaction globale. Les patients ages et d'un niveau educatif eleve etaient moins satisfaits.  L'evaluation de la satisfaction de la prise en charge de la douleur au niveau d'un service des urgences permet de connaitre l'angle de vue des patients et deceler des anomalies qui paraient normales par l'etablissement.
Comprehensive Investigation on IoT based Smart HealthCare System
Venue: 2020 First International Conference on Power, Control and Computing Technologies (ICPC2T)
Year: 2020

Internet of Thing (IoT) is seen as a promising technology in the healthcare system for continuously monitoring of patient health. The IoT based Smart healthcare System (SHCS) is a collaborative interconnection of healthcare devices, embedded system and internet through the smart devices. This connected device provides various application and services for vital signs monitoring, along with detection and diagnosis ofvarious diseases. A comparative study on different IoT based healthcare system, services and their key component have been presented in this paper. The exhaustive investigations on the classification of the IoT based SHCS have been carried out. In addition, recent trends and advancement of the SHCS system have been discussed along with issues and challenges in the context of futuristic IoT based healthcare system.
Navigation modes, operation methods, observation scales and background options in UI design for high learning performance in VR based architectural applications
Venue: J. Comput. Des. Eng.
Year: 2019

Reality (VR) technologies have been widely applied to the field of architecture education because of its unique immersion. There have been many researches on hardware and platform development in the world. However, there are relatively few on User Interface (UI) design. This is a study of UI design in VR applications applied in architectural education, which aims to improve users' learning performance. Through a previous study and other scholars' researches, four key factors have been extracted from the challenges of UI design in VR applications: navigation modes, operation methods, observation scales and background options. A set of experiments were conducted based on correlation analysis with 120 students of these four factors and learning performance. It is concluded that fishing mode with instantaneous movement is preferred rather than flying mode in HTC Vive navigation; the way of direct grasp in virtual operation performs better than the way of using an operational proxy in virtual construction process; a virtual observation scale close to body and mockup in real world performs best; contribution of a background environment in VR is not as significant as expected. In brief, the learning performances in a VR platform vary greatly with different UI designs.
IMPLEMENTASI DATA MINING UNTUK MENGETAHUI MANFAAT RPTRA MENGGUNAKAN METODE K MEANS CLUSTERING
Venue: Jurnal Pilar Nusa Mandiri
Year: 2019

The vacant land in DKI Jakarta is increasingly reducing due to the construction of houses, queues, factories, which are increasingly rapid. Making less green open space and water catchment areas. That way, the park of the children to play even decreases, as well as the DKI Jakarta Provincial Government, decides to make a Child Friendly Integrated Public Room or what we know as RPTRA with facilities that can help the community around it. With this RPTRA, the public especially children can play and interact with each other. Using the K Means Clustering method can help the government or officers in each RPTRA more easily see how useful this RPTRA and the government also facilitates some of the rooms contained in this RPTRA namely the hall, library, and playroom. The results of this research are the hall that has the highest value for visitors who come where the value obtained is 1319 visitors.
A novel method for reducing motion sickness susceptibility through training visuospatial ability A two part study.
Venue: Applied ergonomics
Year: 2020

Everyone can be susceptible to motion sickness (except those with complete loss of labyrinth function) and around one in three are known to be servery susceptible. Motion sickness can be experienced in many domains, including car travel, on a boat, using virtual reality headsets and simulator use amongst others. It is expected that due to potential designs and use cases, self driving cars will increase motion sickness onset likelihood and severity for many car travellers. Besides medication, there are limited methods through which one can actively reduce their motion sickness susceptibility. This research develops a novel visuospatial training tool and explores the effect of visuospatial training on motion sickness. With a combined sample of 42 participants split between driving simulator trials (n 20) and on road trials (n 22) baseline visuospatial skills and motion sickness were first measured. After a 14 day training period where participates completed 15 min of pen and paper tasks per day, it was found that visuospatial skills improved by 40% This increase in visuospatial ability was shown to be directly responsible for a reduction in motion sickness by 51% in the simulator (with a 60% reduction in participant dropouts) and a 58% reduction in the on road trial. This research has successfully identified a new method to reduce motion sickness susceptibility and the impact of these findings have wide reaching implications for motion sickness research, especially in the field of self driving vehicles.
9. Writing a Research Proposal
Venue: How to do your Social Research Project or Dissertation
Year: 2019

Before starting a dissertation, it is common practice to have to write a research proposal. Not only does a research proposal help make sense of the student's own project and what it will look like, it also allows he or she to connect research idea to a wider audience so that other people can give advice about whether, and how, it makes 'research sense' Often submitted alongside an ethics application, the research proposal is sometimes a requirement of the dissertation process, needing 'approval' before undertaking the research project. This chapter details what research proposals look like and why they are important, before outlining the requirements of a typical research proposal.
Optimization of 3o Method for Phase Change Materials Thermal Conductivity Measurement at High Temperature
Venue: 2019 IEEE 32nd International Conference on Microelectronic Test Structures (ICMTS)
Year: 2019

Thermal conductivity (kth) of Ge rich Ge Sb Te phase change material (GGST) is here investigated at temperatures up to $400\ \circ}\mathrm{C} through "3o method" We present the engineering of the test vehicle, with the optimization of the metal based heater to achieve a reliable measurement even at high temperature. Finally, we compare the results from four different approaches, showing which method is more accurate for the kth evaluation in phase change materials.
Modeling Brain Networks with Artificial Neural Networks
Venue: GRAIL/Beyond MIC@MICCAI
Year: 2018

In this study, we propose a neural network approach to capture the functional connectivities among anatomic brain regions. The suggested approach estimates a set of brain networks, each of which represents the connectivity patterns of a cognitive process. We employ two different architectures of neural networks to extract directed and undirected brain networks from functional Magnetic Resonance Imaging (fMRI) data. Then, we use the edge weights of the estimated brain networks to train a classifier, namely, Support Vector Machines (SVM) to label the underlying cognitive process. We compare our brain network models with popular models, which generate similar functional brain networks. We observe that both undirected and directed brain networks surpass the performances of the network models used in the fMRI literature. We also observe that directed brain networks offer more discriminative features compared to the undirected ones for recognizing the cognitive processes. The representation power of the suggested brain networks are tested in a task fMRI dataset of Human Connectome Project and a Complex Problem Solving dataset.
One step robust deep learning phase unwrapping.
Venue: Optics express
Year: 2019

Phase unwrapping is an important but challenging issue in phase measurement. Even with the research efforts of a few decades, unfortunately, the problem remains not well solved, especially when heavy noise and aliasing (undersampling) are present. We propose a database generation method for phase type objects and a one step deep learning phase unwrapping method. With a trained deep neural network, the unseen phase fields of living mouse osteoblasts and dynamic candle flame are successfully unwrapped, demonstrating that the complicated nonlinear phase unwrapping task can be directly fulfilled in one step by a single deep neural network. Excellent anti noise and anti aliasing performances outperforming classical methods are highlighted in this paper.
Cooperative manipulation with least number of robots via robust caging
Venue: 2012 IEEE/ASME International Conference on Advanced Intelligent Mechatronics (AIM)
Year: 2012

One problem in multi robot cooperative manipulation is redundancy. Too many robots are waste of hardware and increase control complexity. This paper solves the problem of redundancy by robust caging. Robust caging calculates caging positions from translational immobilization with respect to translational constraints and rotational constraints. On the one hand, robust caging helps to reduce the necessary number of robots in cooperation. On the other hand, the initial positions of necessary robots in robust caging are optimized to offer large robustness to control errors. Our proposal with robust caging is implemented to transport target objects over slopes. The algorithm can choose least number of robots with respect to shape of target objects and requirements of robustness. At the same time, each robot may endure as much as 256 ms time step and 1 cm control error, showing the superiority of robust caging.
Atmospheric coherence time measurement by four aperture DIMM defocus velocity technique.
Venue: Applied optics
Year: 2019

In this work, we estimate the atmospheric Fried parameter {r_0} $r0, average wind speed \bar v $v and subsequently, atmospheric coherence time \tau _0} $t0 by experimental measurement via a four aperture differential image motion monitor (DIMM) instrument at the Iranian National Observatory (INO) site. The experimental approach is based on the four aperture DIMM defocus velocity theory, which uses the angle of arrival fluctuation measurement of starlight propagation through atmospheric turbulence in the form of a four spot configuration provided by the four aperture DIMM telescope. Here, we measure the defocus variance \sigma _{{C_4}^2 $sC42 and its velocity variance \sigma _{\partial {C_4}\partial t}^2 $sC4/t2 and use the preceding theory to estimate the atmospheric turbulence parameters. We have implemented the data sampling at the INO site at an altitude of 3600 m above sea level with a 12 inch Meade Cassegrain telescope consisting of a four aperture mask at its entrance pupil and a fast CCD camera recording short exposure images with frame rates in the range of 480 fps to 620 fps from the Capella star. The experimental recorded data sets are analyzed and the results compared to those of our simulation and other methods and demonstrate good agreement.
Determination of Chokanan mango sweetness (Mangifera indica) using non destructive image processing technique
Year: 2014

The Chokanan mango (Mangifera indica) has a high commercial potential. Its sugar content increases as the colour changes during the maturation process. In this research, the relationship between the sweetness of the Chokanan mango and its mean pixel values in RGB and HSB colour space is analyzed. This information could be utilized in determining the level of sweetness of the Chokanan mango without destroying the fruit. A Keyence machine vision system was employed to capture the images of the mango in RGB and HSB colour spaces. Based on the findings, it could be concluded that hue not only has the highest correlation value 0.916) but also has the lowest value of the standard deviation at all levels of sweetness compared to other colour components. It is possible to determine sweetness at Level 1 and Level 2 with a 100% success rate and a 87% success rate at Level 3.