nils-herrmann/clean_scirepeval huggingface dataset:
Buckling analysis of reinforced composite plates with a multiwall carbon nanotube (MWCNT)
Venue: Periodicals of Engineering and Natural Sciences (PEN)
Year: 2019

Buckling analysis of mechanical structures is essential to insure stability under loading .Critical load of buckling refer to the maximum load can be withstood without losing of stability and avoid a catastrophic damage due to the collapse of columns .Improving of mechanical properties spatially those related with elastic behaviors of materials can lead to improving buckling since it can be raised the value of critical load Nanotechnology is one of the modern methods which makes significant effects on the mechanical properties of materials. In the field of composite materials this technology leads to valuable improvements for the favorite properties. In this regard Nano composite materials are paid a spatial attention in research for the last decade. The main aim of the present work is to investigate the effect of Nano carbon weight fraction on buckling of the composite plate. Five samples of Nano composite plates were prepared and fabricated for experimental investigations .The plate samples are combined of woven reinforcement fiber and polyester matrix with Carbon .The weight fraction of Nano additives are 0 0.5% 1% ,1.5 and 2% of resin materials weight. To provide homogenous composite an ultrasonic homogenizer is utilized. The experimental work include buckling test for different Nano plates samples with simply supported at two ends and free at the other .Finite Element analysis was achieved via ANSYS R15.0 with proper elements ,meshing ,boundary condition and static analysis .It is found that increasing of Nano carbon weight ratio tends to increase critical load of buckling ,the maximum buckling load is at 2% wt ratio and the experimental results shows fair validation for the numerical analysis where the maximum error dos not exceeded 15%
Hive a petabyte scale data warehouse using Hadoop
Venue: 2010 IEEE 26th International Conference on Data Engineering (ICDE 2010)
Year: 2010

The size of data sets being collected and analyzed in the industry for business intelligence is growing rapidly, making traditional warehousing solutions prohibitively expensive.  is a popular open source map reduce implementation which is being used in companies like Yahoo, Facebook etc. to store and process extremely large data sets on commodity hardware. However, the map reduce programming model is very low level and requires developers to write custom programs which are hard to maintain and reuse. In this paper, we present Hive, an open source data warehousing solution built on top of Hadoop. Hive supports queries expressed in a SQL like declarative language HiveQL, which are compiled into map reduce jobs that are executed using Hadoop. In addition, HiveQL enables users to plug in custom map reduce scripts into queries. The language includes a type system with support for tables containing primitive types, collections like arrays and maps, and nested compositions of the same. The underlying IO libraries can be extended to query data in custom formats. Hive also includes a system catalog Metastore that contains schemas and statistics, which are useful in data exploration, query optimization and query compilation. In Facebook, the Hive warehouse contains tens of thousands of tables and stores over 700TB of data and is being used extensively for both reporting and ad hoc analyses by more than 200 users per month.
A Stylometric Inquiry into Hyperpartisan and Fake News
Venue: ACL
Year: 2018

We report on a comparative style analysis of hyperpartisan (extremely one sided) news and fake news. A corpus of 1,627 articles from 9 political publishers, three each from the mainstream, the hyperpartisan left, and the hyperpartisan right, have been fact checked by professional journalists at BuzzFeed: 97% of the 299 fake news articles identified are also hyperpartisan. We show how a style analysis can distinguish hyperpartisan news from the mainstream (F1 0.78) and satire from both (F1 0.81) But stylometry is no silver bullet as style based fake news detection does not work (F1 0.46) We further reveal that left wing and right wing news share significantly more stylistic similarities than either does with the mainstream. This result is robust: it has been confirmed by three different modeling approaches, one of which employs Unmasking in a novel way. Applications of our results include partisanship detection and pre screening for semi automatic fake news detection.
Identity Theory and College Hookup Culture
Year: 2019

General Audience) Hooking up can mean many different things to different people, but is still somehow an almost unavoidable part of college life. This paper looks at this relatively new culture of sex and dating on campus, also known as hookup culture, in order to better understand who is more likely to hook up. By using survey data from a "College Identity Study" collected between 2015 2016 at a large, southeastern public university, from students aged 18 24 the study analyzes what kinds of college identities are most likely to engage in hooking up behaviors. Ultimately, the hypothesis that college students who claim the partier identity are more likely to hook up was supported, meaning there is a positive relationship between partying and hooking up.
Water vapor mapping by fusing InSAR and GNSS remote sensing data and atmospheric simulations
Year: 2015

Data fusion aims at integrating multiple data sources that can be redundant or complementary to produce complete, accurate information of the parameter of interest. In this work, data fusion of precipitable water vapor (PWV) estimated from remote sensing observations and data from the Weather Research and Forecasting (WRF) modeling system are applied to provide complete grids of PWV with high quality. Our goal is to correctly infer PWV at spatially continuous, highly resolved grids from heterogeneous data sets. This is done by a geostatistical data fusion approach based on the method of fixed rank kriging. The first data set contains absolute maps of atmospheric PWV produced by combining observations from the Global Navigation Satellite Systems (GNSS) and Interferometric Synthetic Aperture Radar (InSAR) These PWV maps have a high spatial density and a millimeter accuracy; however, the data are missing in regions of low coherence (e.g. forests and vegetated areas) The PWV maps simulated by the WRF model represent the second data set. The model maps are available for wide areas, but they have a coarse spatial resolution and a still limited accuracy. The PWV maps inferred by the data fusion at any spatial resolution show better qualities than those inferred from single data sets. In addition, by using the fixed rank kriging method, the computational burden is significantly lower than that for ordinary kriging.
Factors associated with the physical and mental health of drug users participating in community based drug rehabilitation programmes in China.
Venue: Health social care in the community
Year: 2019

Since the promulgation and implementation of a new anti drug law in 2008, the Chinese central government has encouraged local governments to carry out community based drug rehabilitation programmes. This study explores the association between community based drug rehabilitation programmes and drug users' physical and mental health. This study collected data between October 2018 and February 2019 from a community based rehabilitation programme in a community in Foshan Municipality in Guangdong Province of China. A total of 162 drug users participating in a community based drug rehabilitation program were selected to complete a self administered and anonymous questionnaire. A cover letter interpreting the purpose of the study and a self administered questionnaire was provided to the drug users. Ethics approval for this study was obtained from the Academic Committee of School of Public Administration, JiNan University, Guangzhou, China. All participants gave verbal informed consent. Four multiple linear regression models were used to explain social services that influence drug users' physical and mental health. The findings show that the number of service items provided by the social service organization was significantly associated with physical and mental health among drug users. Particularly, the employment assistance service influenced the drug user's physical and mental health status significantly.
Research on Three dimension Visual Simulation of Concrete Face Rockfill Dam Construction Process
Year: 2012

Concrete face rock fill dam (CFRD) is widely used in hydropower construction. There are many certainty and uncertainty factors involved in its construction process. Hence, computer simulation technology was applied to study it. Based on the analysis of CFRD construction system, firstly the system was divided into three sub systems: material allocating, transporting and dam filling to establish the simulation system. Secondly the earth rocks were allocated according to dam construction schedule. Then the allocation results were applied in transporting system and dam filling system to simulate the construction process, from which the duration, road intensity, machine configuration and utilization were obtained, which can be demonstrated by tables and graphics. Finally, simulation results were illustrated by three dimensional (3D) visual technology.
Temporal weighting of azimuthal cues in the free field and in headphone listening
Year: 2017

Dynamic aspects of binaural cue processing can be captured via several types of psychophysical measurements in human listeners. These include sensitivity measures with spatially dynamic stimuli, temporal integration measurements, and perceptual weighting measurement with stochastic spatial cue variation. The latter approach has been adopted in a series of papers and ongoing studies. These assessed the time course of binaural lateralization and azimuthal localization as a function of stimulus frequency, bandwidth, modulation rate, temporal regularity, duration, envelope shape, and reverberation. The detailed temporal profile of perceptual weights, or "temporal weighting function," can be captured psychophysically and through Monte Carlo simulations based on computational binaural model outputs. Among the results that will be reviewed in this talk are (1) demonstration of sparse temporal sampling of binaural cues at moments of positive envelope slope, (2) impacts of cochlear interference on low frequency bi.
Rezension: Herbert Bassarak (Hrsg. 2018) Lexikon der Schulsozialarbeit. Aktuell und praxisnah: Umfassendes Nachschlagewerk fur Soziale Arbeit an Schulen
Year: 2019

Herbert Bassarak (Hrsg. 2018) Lexikon der Schulsozialarbeit 1. Auflage, Nomos Verlag, Baden Baden, 634 Seiten, EUR 98,
DERADIKALISASI AGAMA BERBASIS PENDIDIKAN MULTIKULTURAL INKLUSIF DI PONDOK PESANTREN KOTA BANDAR LAMPUNG
Year: 2020

Penelitian ini bertujuan untuk memetakan kurikulum pendidikan multikultural inklusivisme yang dikembangkan di Pondok Pesantren di kota Bandar Lampung, menganalisis proses internalisasi nilai nilai multikultural inklusivisme yang dilaksanakan di Pondok Pesantren di Kota Bandar Lampung, serta menganalisis efektivitas penerapan pendidikan multikultural inklusivisme yang dikembangkan di Pondok Pesantren di Kota Bandar Lampung. Penelitian ini berjenis penelitian lapangan berbasis penelitian kualitatif. Pendekatan yang digunakan dalam penelitian ini adalah pendekatan psikologi agama. Subjek pada penelitian ini adalah santri Pondok Pesantrenn Al Hikmah, Way Halim, Pondok Pesantren Madarijul Ulum Telukbetung, dan Pondok Pesantren Al Khairiyah Telukbetung. Data yang akan dicari dalam penelitian ini berupa data tertulis dan data tidak tertulis. Sumber data penelitian ini adalah Kiayi pimpinan pondok pesantren sebagai informan kunci. Teknik pengumpulan data direncanakan dengan tiga cara, yaitu wawancara, pengamatan, dan dokumentasi. Sebelum dianalisis, data yang telah diperoleh divalidasi dengan menggunakan teknik triangulasi. Semua data yang telah dikumpulkan dan divalidasi kemudian dianalisis dengan menggunakan metode berpikir induktif. Penelitian ini menghasilkan bahwa penerapan model pendidikan multikultural inklusif cukup efektif sebagai upaya deradikalisasi di lingkungan tiga pondok pesantren tersebut
High power fiber lasers: current status and future perspectives [Invited]
Year: 2010

The rise in output power from rare earth doped fiber sources over the past decade, via the use of cladding pumped fiber architectures, has been dramatic, leading to a range of fiber based devices with outstanding performance in terms of output power, beam quality, overall efficiency, and flexibility with regard to operating wavelength and radiation format. This success in the high power arena is largely due to the fiber's geometry, which provides considerable resilience to the effects of heat generation in the core, and facilitates efficient conversion from relatively low brightness diode pump radiation to high brightness laser output. In this paper we review the current state of the art in terms of continuous wave and pulsed performance of ytterbium doped fiber lasers, the current fiber gain medium of choice, and by far the most developed in terms of high power performance. We then review the current status and challenges of extending the technology to other rare earth dopants and associated wavelengths of operation. Throughout we identify the key factors currently limiting fiber laser performance in different operating regimes in particular thermal management, optical nonlinearity, and damage. Finally, we speculate as to the likely developments in pump laser technology, fiber design and fabrication, architectural approaches, and functionality that lie ahead in the coming decade and the implications they have on fiber laser performance and industrial/scientific adoption.
Project Omnivore: A Variable Compression Ratio ATAC 2 Stroke Engine for Ultra Wide Range HCCI Operation on a Variety of Fuels
Year: 2010

The paper describes the principal features of Omnivore, a spark ignition based research engine designed to investigate the possibility of true wide range HCCI operation on a variety of fossil and renewable liquid fuels. The engine project is part funded jointly by the United Kingdom's Department for the Environment, Food and Rural Affairs (DEFRA) and the Department of the Environment of Northern Ireland (DoENI) The engineering team includes Lotus Engineering, Jaguar Cars, Orbital Corporation and Queen's University Belfast. The research engine so far constructed is of a typical automotive cylinder capacity and operates on an externally scavenged version of the two port Day 2 stroke cycle, utilising both a variable charge trapping mechanism to control both trapped charge and residual concentration and a wide range variable compression ratio (VCR) mechanism in the cylinder head. This approach permits individual control of retained and compression heat as separate inputs to the ATAC combustion process (now commonly referred to as HCCI) an ideal situation which is not possible when attempting to operate a traditional fixed compression ratio, variable valve timing 4 stroke engine in HCCI combustion. The ease of application of the VCR system due to the elimination of poppet valves for gas exchange is fundamental to the concept and this feature is discussed in detail, together with the very wide range of compression ratios that the chosen solution permits (from 10:1 to 40:1 in this initial configuration) In addition to describing the engine and its technologies, test results from its initial operation on 98 RON gasoline are presented, including stable operation at idle load and 450 rpm in true HCCI (i.e. without spark assistance)
Neural Bayesian Information Processing
Venue: CIKM
Year: 2020

Deep learning is developed as a learning process from source inputs to target outputs where the inference or optimization is performed over an assumed deterministic model with deep structure. A wide range of temporal and spatial data in language and vision are treated as the inputs or outputs to build such a complicated mapping in different information systems. A systematic and elaborate transfer is required to meet the mapping between source and target domains. Also, the semantic structure in natural language and computer vision may not be well represented or trained in mathematical logic or computer programs. The distribution function in discrete or continuous latent variable model for words, sentences, images or videos may not be properly decomposed or estimated. The system robustness to heterogeneous environments may not be assured. This tutorial addresses the fundamentals and advances in statistical models and neural networks, and presents a series of deep Bayesian solutions including variational Bayes, sampling method, Bayesian neural network, variational auto encoder (VAE) stochastic recurrent neural network, sequence to sequence model, attention mechanism, end to end network, stochastic temporal convolutional network, temporal difference VAE, normalizing flow and neural ordinary differential equation. Enhancing the prior/posterior representation is addressed in different latent variable models. We illustrate how these models are connected and why they work for a variety of applications on complex patterns in language and vision. The word, sentence and image embeddings are merged with semantic constraint or structural information. Bayesian learning is formulated in the optimization procedure where the posterior collapse is tackled. An informative latent space is trained to incorporate deep Bayesian learning in various information systems.
Subject Identification Across Large Expression Variations Using 3D Facial Landmarks
Venue: ICPR Workshops
Year: 2020

Landmark localization is an important first step towards geometric based vision research including subject identification. Considering this, we propose to use 3D facial landmarks for the task of subject identification, over a range of expressed emotion. Landmarks are detected, using a Temporal Deformable Shape Model and used to train a Support Vector Machine (SVM) Random Forest (RF) and Long Short term Memory (LSTM) neural network for subject identification. As we are interested in subject identification with large variations in expression, we conducted experiments on 3 emotion based databases, namely the BU 4DFE, BP4D, and BP4D+ 3D/4D face databases. We show that our proposed method outperforms current state of the art methods for subject identification on BU 4DFE and BP4D. To the best of our knowledge, this is the first work to investigate subject identification on the BP4D+ resulting in a baseline for the community.
The Application of Multi Agent Reinforcement Learning in UAV Networks
Venue: 2019 IEEE International Conference on Communications Workshops (ICC Workshops)
Year: 2019

This article investigates autonomous resource allocation of multiple UAVs enabled communication networks with the goal of maximizing long term rewards. To model the uncertainty of environments, we formulate the long term resource allocation problem as a stochastic game, where each UAV becomes a learning agent and each resource allocation solution corresponds to an action taken by the UAVs. Furthermore, we propose a multi agent reinforcement learning (MARL) framework that each agent discovers its best strategy according to its local observations using learning. More specifically, we propose an agent independent method, for which all agents conduct a decision algorithm independently but share a common structure based on Q learning. Finally, simulation results reveal that the proposed MARL algorithm provides acceptable performance compared to the case with complete information exchanges among UAVs.
Verb argument structure overgeneralisations for the English intransitive and transitive constructions: grammaticality judgments and production priming
Year: 2021

We used a multi method approach to investigate how children avoid (or retreat from) argument structure overgeneralisation errors (e.g. You giggled me Experiment 1 investigated how semantic and statistical constraints (preemption and entrenchment) influence children's and adults' judgments of the grammatical acceptability of 120 verbs in transitive and intransitive sentences. Experiment 2 used syntactic priming to elicit overgeneralisation errors from children (aged 5 6) to investigate whether the same constraints operate in production. For judgments, the data showed effects of preemption, entrenchment, and semantics for all ages. For production, only an effect of preemption was observed, and only for transitivisation errors with intransitive only verbs (e.g. *The man laughed the girl We conclude that preemption, entrenchment, and semantic effects are real, but are obscured by particular features of the present production task.
Metformin for the Treatment of Hyperandrogenism in Adolescents with Type 1 Diabetes Mellitus
Venue: Hormone Research in Paediatrics
Year: 2013

A high prevalence of hyperandrogenism has been reported in women with type 1 diabetes (T1D) Metformin has been used as a therapeutic agent in patients with polycystic ovarian syndrome and in T1D patients without hyperandrogenism. This study sought to determine the effect of metformin on hyperandrogenism and ovarian function in adolescents with T1D.  We recruited 24 girls with T1D. The participants had hyperandrogenism and displayed suboptimal metabolic control. The patients were enrolled in a randomized, double blind, placebo controlled trial. One group received metformin (850 mg bid) and the other group received a placebo. Treatment was administered for 9 months. Ovulation, steroids and gonadotropin levels were evaluated.  Metformin treatment was associated with decreases in testosterone, free androgen index, androstenedione, 17 OH progesterone and estradiol levels. The girls who were treated with placebo showed stable steroid, gonadotropin and sex hormone binding globulin levels during the analysis. No differences were observed in the Ferriman Gallwey scores, ovulation rates, HbA1c levels or daily insulin doses of the girls treated with metformin compared with the placebo group.  Treating hyperandrogenic T1D adolescents with metformin significantly decreased the serum androgens compared to the placebo, but metformin therapy did not significantly affect clinical parameters, such as hirsutism, ovulation and metabolic control.
New group interaction parameters of the UNIFAC model for the solubility of water in fatty acid methyl esters and biodiesel
Year: 2018

Water content is one of the most important quality indexes of biodiesel. In this study, the group interaction parameters of UNIFAC model are optimized to improve this model in predicting the solubility of water in fatty acid methyl esters and biodiesel. To determine the binary interaction parameters between water and the main functional groups attached to the molecules of the biodiesel compounds, 55 experimental data points related to the solubility of water in nine pure fatty acid methyl esters in the temperature range of 282.2 K 323.2 K are employed. Then, the model is used to predict the water solubility in 10 different biodiesels (60 data points) to evaluate the calculated interaction parameters in predicting the solubility of water in the mixture of fatty acid methyl esters. The average absolute relative deviations of the model in predicting the water content of pure fatty acid methyl esters and biodiesel are 4.31% and 4.69% respectively. To show the superior performance of the model, the results of the model are compared with the results of previous models.