nils-herrmann/clean_scirepeval huggingface dataset:
Effective graph based point matching algorithms
Venue: 2016 2nd International Conference on Industrial Engineering, Applications and Manufacturing (ICIEAM)

Several new fast graph based point matching algorithms that give approximate solution are proposed for usage with epipolar geometry constraints based systems. These algorithms may also be used for finding a complete point correspondence provided that certain techniques will be utilized in a photogrammetric system. New algorithms are much faster than existing algorithms or superclique approach, which is proposed in this paper too.
Assessing the utility of FIB SEM images for shale digital rock physics

Shales and other unconventional or low permeability (tight) reservoirs house vast quantities of hydrocarbons, often demonstrate considerable water uptake, and are potential repositories for fluid sequestration. The pore scale topology and fluid transport mechanisms within these nanoporous sedimentary rocks remain to be fully understood. Image informed pore scale models are useful tools for studying porous media: a debated question in shale pore scale petrophysics is whether there is a representative elementary volume (REV) for shale models? Furthermore, if an REV exists, how does it differ among petrophysical properties? We obtain three dimensional (3D) models of the topology of microscale shale volumes from image analysis of focused ion beam scanning electron microscope (FIB SEM) image stacks and investigate the utility of these models as a potential REV for shale. The scope of data used in this work includes multiple local groups of neighboring FIB SEM images of different microscale sizes, corresponding core scale (milli and centimeters) laboratory data, and, for comparison, series of two dimensional (2D) cross sections from broad ion beam SEM images (BIB SEM) which capture a larger microscale field of view than the FIB SEM images; this array of data is larger than the majority of investigations with FIB SEM derived microscale models of shale. Properties such as porosity, organic matter content, and pore connectivity are extracted from each model. Assessments of permeability with single phase, pressure driven flow simulations are performed in the connected pore space of the models using the lattice Boltzmann method. Calculated petrophysical properties are compared to those of neighboring FIB SEM images and to core scale measurements of the sample associated with the FIB SEM sites. Results indicate that FIB SEM images below ~5000 um3 volume (the largest volume analyzed) are not a suitable REV for shale permeability and pore scale networks; i.e. field of view is compromised at the expense of detailed, but often unconnected, nanopore morphology. Further, we find that it is necessary to acquire several local FIB SEM or BIB SEM images and correlate their extracted geometric properties to improve the likelihood of achieving representative values of porosity and organic matter volume. Our work indicates that FIB SEM images of microscale volumes of shale are a qualitative tool for petrophysical and transport analysis. Finally, we offer alternatives for quantitative pore scale assessments of shale.
Ecology, Biogeography, and Conservation of Checkered Beetles (Insecta: Cole?ptera: Cleridae) in Southeastern Arizona: A Geographic Information System (GIS) Study

Aspects of the ecology, biogeography, and conservation biology of 57 check ered beetle species (Insecta: Cole?ptera: Cleridae, subfamilies Tillinae and Clerinae) in southeastern Arizona were studied using commercial Geographic Information Systems (GIS) software. Clerid beetles previously investigated in this region are known to be restricted to certain well defined vegetation types. For the 57 species in this study, published distribution records and label data from specimens in four major institutional collections were combined in a single database. Fifty two of the collecting sites in this database could be identified on standard topographic maps at an appropriate level of precision for use in the GIS portion of this study. The ArcView GIS software program was used to compare points representing these 52 sites with the Arizona Gap Analysis Project's digital vegetation map of Arizona. The vegetation type(s) present at each clerid collecting site was determined, and a simple habitat model was used to predict the distribution of each clerid species in southeast ern Arizona. From these predicted distributions, clerid species richness values were assigned to vegetation polygons in four mountain ranges in southeastern Arizona. A digital map of federally designated wilderness areas in Arizona was used to evaluate the conservation status of vegetation patches with high predicted clerid species richness. The conservation status of eight species of Cleridae (Cymatodera cazierorum Barr, Cymatodera horni Wolcott, Cymatodera knausi Wolcott, Cymatodera schwarzi Wolcott, Cymatodera tricolor Skinner, Priocera catalinae Cazier, Priocera chiricahuae Knull, and Enoclerus bimaculatus (Skinner) that are endemic to the "Sky Island" mountains of Arizona, New Mexico, Sonora, and Chihuahua was also assessed. In southeastern Arizona, mid elevation evergreen oak pine forests and woodlands in the Chiricahua, Huachuca, and Santa Rita Mountains were found to have highest clerid species richness, and to also provide habitat for multiple endemic clerid species. Expansion of existing wilderness areas in these mountain ranges is recom mended to conserve important areas for clerid biodiversity.
The Edinburgh/LMU Hierarchical Machine Translation System for WMT 2016
Venue: WMT

This paper describes the hierarchical phrase based machine translation system built jointly by the University of Edinburgh and the University of Munich (LMU) for the shared translation task at the ACL 2016 First Conference on Machine Translation (WMT16) The WMT16 Edinburgh/LMU system was trained for translation of news domain texts from English into Romanian. We participated in the shared task for machine translation of news under "constrained" conditions, i.e. using the provided training data only.
Role of pressure retarded osmosis (PRO) in the mega ton water project

AbstractReverse osmosis (RO) membranes have been widely applied to seawater desalination and wastewater reclamation, and many large RO plants >100,000 m3/d) have been constructed since 2000. Energy efficiency is indispensable for large plants, especially for future mega ton scale seawater reverse osmosis (SWRO) plant (1,000,000 m3/d) In order to reduce energy demand in RO operation, high efficient low pressure RO membrane, energy recovery device (ERD) and pressure retarded osmosis (PRO) which would recover power from salinity gradient between freshwater and concentrated brine were studied in the "Mega ton Water System" project. A PRO hollow fiber membrane module was newly developed, and a practical continuous operation has been examined at a prototype plant for one year. The maximum 13.5 W/m2 of membrane power density using 10 inch module was established at our prototype PRO plant. As the results of the plant cost estimation and the financial impacts on the energy saving operation at the mega ton scale.
The Water Project

This resource was created to embark on a STEM project in grade 8 science class. Students are exposed to four different units during the year in Ontario, including: Cells, Fluids, Systems in Action, and Water Systems. The learning objective was to create a project that linked each of these units together under a "systems" theme and incorporate engineering, math, and technology. Students were able to showcase their learning in a final presentation that highlighted the different components of the STEM project. This includes the pulley schematics, design, and calculations of their water filter and technology implementation. This project uses Google Apps for Education so students can collaborate on the project synchronously and asynchronously, as well as incorporates hard skills like using a microscope, and provides students with the opportunity to design and build techniques. Cette ressource a ete creee pour s'embarquer en un projet de STIM en utilisant comme guide le curriculum de science ontarien de la 8e annee. Les etudiants apprennent a propos quatre sujets differents pendant l'annee scolaire, incluant Les Cellules, Les Fluides, Les Systemes en Action, et les Systemes Hydrographiques. L'objectif d'apprentissage etait de creer un projet qui liait tous ces sujets ensemble sous un theme commun, les systemes, et integrerait aussi l'ingenie, les mathematiques, et la technologie. Les etudiants ont eu la chance de montrer les connaissances qu'ils ont apprises dans une presentation finale qui a souligne les elements differents du projet. Cela inclut les moufles, la conception, les calculs de leur filtre a eau et l'implementation de la technologie. Ce projet utilise 'Google Apps for Education' pour que les etudiants puissent collaborer sur le projet en synchronie et seule. Il incorpore aussi les competences du niveau plus eleve, comme l'utilisation d'un microscope et donne les etudiants la chance de developper les strategies et techniques de la conception et construction.
A New Time varying Concept of Risk in a Changing Climate
Venue: Scientific reports

In a changing climate arising from anthropogenic global warming, the nature of extreme climatic events is changing over time. Existing analytical stationary based risk methods, however, assume multi dimensional extreme climate phenomena will not significantly vary over time. To strengthen the reliability of infrastructure designs and the management of water systems in the changing environment, multidimensional stationary risk studies should be replaced with a new adaptive perspective. The results of a comparison indicate that current multi dimensional stationary risk frameworks are no longer applicable to projecting the changing behaviour of multi dimensional extreme climate processes. Using static stationary based multivariate risk methods may lead to undesirable consequences in designing water system infrastructures. The static stationary concept should be replaced with a flexible multi dimensional time varying risk framework. The present study introduces a new multi dimensional time varying risk concept to be incorporated in updating infrastructure design strategies under changing environments arising from human induced climate change. The proposed generalized time varying risk concept can be applied for all stochastic multi dimensional systems that are under the influence of changing environments.
The U.S. Election Hacks, Cybersecurity, and International Law
Venue: AJIL Unbound

In October 2016, the United States accused Russia of hacking political organizations involved in the U.S. elections and leaking pilfered information to influence the outcome. In December, President Obama imposed sanctions for the hacking. This incident damaged President Obama's cybersecurity legacy. The "hack and leak" campaign targeted American self government a challenge to his administration's promotion of democracy in cyberspace. It created problems for the president's emphasis on international law and norms as "rules of the road" for cybersecurity. The episode exposed failures in his attempts to make deterrence an important instrument of U.S. cybersecurity.
An Analysis of the Campaign Context in the U.S. How did Political Parties Use Social Media in the 2014 Midterm Election Campaign?

Contextual factors influence the ways in which social media are used in elections. By observing the 2014 U.S. midterm election campaign, this paper will consider the impact of social media on political parties, the new professionalization of campaigns, and campaign finance reform. It will first address political parties' use of social media in the election campaign. Second, it will discuss which new trends in the professionalization of campaigns have been instigated by new media. Third, it will examine the role of super PACs and 501 (c)(4) organizations in the current campaign finance regulatory regime. These questions will be tackled in this paper based on interviews with those who played a firsthand role in the campaigns, newspapers, professional journals, and official documents, including political parties' websites. In conclusion, it will reveal three significant contextual factors to consider in the polarized social media environment of American election campaigns. One is that political parties use social media to advertise their campaigns to voters, while they still prefer to use e mails as a fundraising source. Another is how the changing media environments affect media consultants and other types of political consultants. The more digital technology advances, the more the circumstance of political consultants changes. The other factor is that super PACs play an important role in providing plentiful campaign finance for candidates, although there are regulations banning coordination with individual candidates' campaigns under the current regulatory system. Thus, in the American election system and fundraising mechanism, will American political parties really have more presence in the election campaigns by using digital media? To further research on this topic, this question needs to be considered in depth. CW6_A8350_03_D01.indd 16 2016/09/29 13:27:06 Journal of Socio Informatics Vol. 9 No. 1 Sep. 2016
An analysis of sentiments on facebook during the 2016 U.S. presidential election
Venue: 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)

Social networking sites (SNS) such as Facebook and Twitter, are important spaces for political engagement. SNS have become common elements in political participation, campaigns, and elections. However, little is known about the dynamics between candidate posts and commentator sentiment in response to those posts on SNS. This study enriches computational political science by studying the 2016 U.S. elections and how candidates and commentators engage on Facebook. This paper also examines how online activity might be connected to offline activity and vice versa. We extracted 9,700 Facebook posts by five presidential candidates (Hillary Clinton, Donald Trump, Bernie Sanders, Ted Cruz, and John Kasich) from their official Facebook pages and 12,050,595 comments on those posts. We employed topic modeling, sentiment analysis, and trends detection using wavelet transforms to discover topics, trends, and reactions. Our findings suggest that Republican candidates are more likely to share information on controversial events that have taken place during the election cycle, while Democratic candidates focus on social policy issues. As expected, commentators on Republican candidate pages express negative sentiments toward current public policies as they seldom support decisions made by the Obama administration, while commentators on democratic candidate pages are more likely to express support for continuation or advancement of existing policies. However, the significance (strong/weak) and nature (positive/negative) of sentiments varied between candidates within political parties based on perceived credibility of the candidate's degree of credibility on a given issue. Additionally, we explored correlation between online trends of comments/sentiment and offline events. When analyzing the trend patterns, we found that changes in online trends are driven by three factors: 1) popular post, 2) offline debates, and 3) candidates dropping out of the race.
And the winner is Bayesian Twitter based prediction on 2016 U.S. presidential election
Venue: 2016 International Conference on Computer, Control, Informatics and its Applications (IC3INA)

This paper describes a Naive Bayesian predictive model for 2016 U.S. Presidential Election based on Twitter data. We use 33,708 tweets gathered since December 16, 2015 until February 29, 2016. We propose a simple way for data preprocessing which can still achieve 95.8% accuracy on predicting sentiments. The predicted sentiments are used to forecast the U.S. Republican and Democratic parties candidacies. The forecast is compared to the poll collected from RealClearPolitics.com with 26.7% accuracy. However, the true forecasting capacity of the method still have to be observed after the election process come to conclusion.
Predicting 2016 US Presidential Election Polls with Online and Media Variables

Traditional media has always played a large role in elections by informing voters and shaping opinions, and recently, social media and various Internet information sources have also become considerable influencers on the voters. There is data publicly available on how these information sources and media channels are being used, which could potentially be analyzed for their effects on the election process. This chapter aims to determine if social media, Internet traffic, and traditional media data can be used to predict elections by searching for patterns between the data and poll numbers for 2016 US Republican and Democratic primaries. The results suggest that machine learning models with linear regression can produce quite accurate predictions; also statistically significant correlations were found between polls and betting odds and polls and Facebook page likes. More sophisticated methods could allow for better forecasting using this publicly available data.
Dynamic Allocation of Crowd Contributions for Sentiment Analysis during the 2016 U.S. Presidential Election
Venue: ArXiv

Opinions about the 2016 U.S. Presidential Candidates have been expressed in millions of tweets that are challenging to analyze automatically. Crowdsourcing the analysis of political tweets effectively is also difficult, due to large inter rater disagreements when sarcasm is involved. Each tweet is typically analyzed by a fixed number of workers and majority voting. We here propose a crowdsourcing framework that instead uses a dynamic allocation of the number of workers. We explore two dynamic allocation methods: (1) The number of workers queried to label a tweet is computed offline based on the predicted difficulty of discerning the sentiment of a particular tweet. (2) The number of crowd workers is determined online, during an iterative crowd sourcing process, based on inter rater agreements between labels.We applied our approach to 1,000 twitter messages about the four U.S. presidential candidates Clinton, Cruz, Sanders, and Trump, collected during February 2016. We implemented the two proposed methods using decision trees that allocate more crowd efforts to tweets predicted to be sarcastic. We show that our framework outperforms the traditional static allocation scheme. It collects opinion labels from the crowd at a much lower cost while maintaining labeling accuracy.
From Foe to Friend and Back Again: The Temporal Dynamics of Intra Party bias in the 2016 U.S. Presidential Election

Political identification is strong, stable, and the basis of enduring conflict, suggesting that attitudes towards candidates and their supporters will be difficult to change. Here, however, we show that the shift from party primaries (characterized by intra party conflict) to the general election (characterized by inter party conflict) can cause identities to be reconfigured animosities between supporters of rival primary candidates can attenuate as superordinate goals (defeat rival party) and superordinate identities (Democrat/Republican) come to the fore. We provide a fine grained account of these temporal dynamics by collecting data weekly from mid June to early September 2016 (total N 2,183) examining prosocial giving between supporters of competing primary candidates recruited from the online labor market Amazon Mechanical Turk. At the outset of our study, both Democrats and Republicans showed intra party bias: that is, they shared more money with people from their own party who supported the same primary candidate compared to members of their own party who supported a different primary candidate. This in group bias among Democrats remained high until the Democratic National Convention, and then disappeared entirely shortly thereafter. Bias among Republicans, conversely, existed at a high level both before and after, but not during, the conventions. These findings emphasize both the discontinuity and contingency of changing identities. The abrupt elimination of bias among Democrats, but resurgence of bias among Republicans, suggests that a superordinate goal of defeating the other party (which was salient for both sides during the shift to the general election and was particularly emphasized during party conventions) was not sufficient to bring supporters of different primary candidates together for a sustained period. Rather, sustained change may require successful efforts to emphasize shared (superordinate) party based identity a task which our data suggest the Democratic National Convention succeeded in achieving.
The PollyVote Forecast for the 2016 American Presidential Election
Venue: PS: Political Science &amp; Politics

The PollyVote applies a century old principle of combining different evidence based methods for forecasting the outcome of American presidential elections. In this article, we discuss the principles followed in constructing the PollyVote formula, summarize its components, review the accuracy of its previous forecasts, and make a prediction for this year's presidential election.  Forthcoming (subject to changes) in PS: Political Science Politics Andreas Graefe Randall J. Jones, Jr. J. Scott Armstrong Alfred G. Cuzan
Customer Satisfaction Level in Islamic Banking and conventional Banking (A Case of Pakistan)

The main purpose of this research study was to identify the level of customer's satisfaction by using the products and services of both Islamic and conventional banks in Pakistan. Furthermore, this research study determined the customer's satisfaction level in banking in terms of; internet banking, management interaction and the banking environment, service quality in term of SERVQUAL model, ATM facilities, privacy and security The main objective of the study was to investigate the following main points.(1) Customer`s satisfaction level in Islamic and conventional banks. (2) Why customers prefer to choose Islamic banking system in Pakistan? (3) Why customers prefer to choose conventional banking system in Pakistan? It is therefore, a critical literature has been carried out which investigated the real factors through which customer satisfaction take place in banking sector. The closed ended questionnaire has been used in this research study in order to collect research data. To analyze the collected data, cross tabulations and charts have also been used which showed the satisfaction level of the customers of Islamic and conventional banks and also to differentiate between the participant`s responses of Islamic and conventional banks. A large number of factors have been observed from the research study analysis which illustrated that, in Pakistan, customers are more satisfied from the products and services of conventional banks rather than that of Islamic banks. However, in Pakistan, the customer satisfaction in all financial institutions is not as good as according to the standard. In addition, the banking sector is trying to improve all of their products and services and want to make them according to the international standard. But due to various factors such as; the political instability and religious norms, the banking sector is still far behind.