Miracle-dz/UniFAR-FTUs huggingface dataset:
Storm Crowds: Evidence from Zooniverse on Crowd Contribution Design

Crowdsourcing - a collaborative form of content production based on the contributions of large groups of individuals - has proliferated in the past decade. Due to this growth, recent research has focused on understanding the factors that affect its sustainability. Prior studies have highlighted the importance of volunteers’ prosocial motivations, the sense of belonging to a community, and symbolic rewards within crowdsourcing websites. One factor that has received limited attention in the existing literature is how the design of crowdsourcing platforms affects their sustainability. We study whether the design element - particularly, the divisibility of contributions (i.e. whether contributing tasks are bundled together or can be carried out separately) - is a factor that affects the level and quality of crowdsourcing contributions. We investigate this in the context of Zooniverse, the world’s largest crowd-sourced science site, in which volunteers contribute to scientific research by performing data processing tasks. Our choice of empirical setting is motivated by the fact that one of the Zooniverse projects, Cyclone Center, underwent a format change that decreased the divisibility of contributions, by bundling together two tasks that were previously separate. We refer to contributions for which both tasks were done as complete, and contributions for which only one task was done as incomplete. In this context, we develop a theoretical model that predicts (i) a positive relationship between contribution divisibility and the total number of contributions (i.e. complete and incomplete) per volunteer, (ii) an ambiguous relationship between contribution divisibility and the number of complete contributions per volunteer, and (iii) an ambiguous relationship between contribution divisibility and the value of complete contributions. We test these predictions empirically by exploiting the format change in Cyclone Center. We find that after the format change, which decreased contribution divisibility, (i) the total number of contributions per volunteer decreased, (ii) the number of complete contributions made by anonymous volunteers increased, while that made by registered volunteers remained unchanged, and (iii) the value of complete contributions increased because anonymous volunteers, who increased their number of complete contributions, contributed high quality contributions. Our results have strategic implications for crowdsourcing platforms because they suggest that the design of crowdsourcing platforms, specifically the divisibility of contributions, is a factor that matters for their sustainability.
Layers Adaptive Generating Test Base Based on Content Balancing

Layers adaptive generating test base based on content balancing, its algorithms of generating test including information close to its largest algorithm, using parameters (a) stratified algorithm, (a) stratified and parameters (a) blocking algorithms. At the same time, the reliability, bias, mean squared error, exposure rate, statistics and test-overlap rate etc. were used to test the performance of generating test. After the "Constructing adaptive item bank and intelligent generating test" applications show the methods were better than the traditional generating test algorithms clearly.
A Personalized Information Recommendation Method Based on Network Bookmark

For the present Internet information detonation type grew,this paper proposed a kind personalized information recommendation method based on the Web mining.It introduced the personalized recommendation's flow and realizes model,and profits from the complex network the mass organization structure division method.It proposed personalized information recommendation method based on the network bookmark,analyzed in the mass organization based on the cooperation filtration and the mass organization based on "the information bridge" personalized information recommendation.Through the experiment this method is proved to be effective in the individualized information recommendation.
CRITERIA OF OPEN WEB-OPERATED TECHNOLOGIES OF TEACHING THE FUNDAMENTALS OF PROGRAMS OF FUTURE TEACHERS OF INFORMATICS

У статті наведено критерії добору відкритих web-орієнтованих технологій навчання основ програмування майбутніх учителів інформатики. Аналіз наявних відкритих web-орієнтованих технологій навчання основ програмування майбутніх учителів інформатики дозволив поділити їх на: компілятори, автоматизовані системи перевірки завдань з програмування та інтелектуальні карти. До кожної з них визначено критерії та відповідні показники: для web-орієнтованих компіляторів та інтелектуальних карт виділено проектувальний та функціональний критерії, для web-орієнтованих автоматизованих систем перевірки завдань з програмування виділено проектувальний, інформаційнодидактичний та комунікаційний критерії. Наведено порівняльні таблиці для окремих web-орієнтованих технологій навчання основ програмування майбутніх учителів інформатики за визначеними критеріями та показниками.
An Examination of Cyberloafing Behaviors in Classrooms from Students’ Perspectives

Bu calismanin amaci yuksekogrenimde ogrencilerin siberaylaklik yapma sebeplerini “ogrenci” ve “ogretmen (ders hocasi)” kapsaminda incelemektir. Nitel arastirma yontemlerinden faydalanilan bu arastirmanin calisma grubunu, 2015-2016 egitim-ogretim yili guz doneminde bir devlet universitesinde okumakta olan 228 sinif ogretmeni adayi olusturmaktadir. Katilimcilara yoneltilen acik uclu sorular sonucunda elde edilen veriler icerik analizi yontemi ile degerlendirilmistir. Bulgular dort ana baslik altinda irdelenmistir: ogretenden kaynakli siberaylaklik davranislari, ogretenden kaynakli siberaylaklik davranislarini minimize etmek icin oneriler, ogrenenden kaynakli siberaylaklik davranislari ve ogrenenden kaynakli siberaylaklik davranislarini minimize etmek icin oneriler. Elde edilen veriler dogrultusunda katilimcilar ogretim elemaninin iletisim becerilerinden ve sectikleri ogretim yontem ve tekniklerinin kendilerini siberaylaklik davranisina yonlendirdigini ifade etmistir. Ayrica kendi kisisel sorunlarinin ve motivasyon dusukluklerinin de benzer sonuc dogurdugunu soylemistir. Bu sonuclar, gelecekte yapilacak arastirmalarin uygulamaya yogunlasmasi gerektigini gostermektedir.
A real-time KLT implementation for radio-SETI applications

SETI, the Search for ExtraTerrestrial Intelligence, is the search for radio signals emitted by alien civilizations living in the Galaxy. Narrow-band FFT-based approaches have been preferred in SETI, since their computation time only grows like N*lnN, where N is the number of time samples. On the contrary, a wide-band approach based on the Kahrunen-Lo`eve Transform (KLT) algorithm would be preferable, but it would scale like N*N. In this paper, we describe a hardware-software infrastructure based on FPGA boards and GPU-based PCs that circumvents this computation-time problem allowing for a real-time KLT.
Vision based Vehicle Counting for Traffic Congestion Analysis during Night Time

Background/Objectives: To create an automated system that controls the traffic signals effectively based on the instantaneous calculation of traffic congestion during the given time using image processing techniques. Methods/ Statistical Analysis: Vision based Congestion analysis is done based on the vehicles counted from the camera fixed on the signal post. In this paper, the vehicles are detected based on head lights and counted as two wheelers or four wheelers. The congestion is categorized into light, medium and heavy based on this count. Findings: The headlights are separated from the illuminated bright spots by considering its circular and elliptical nature. The accuracy of identifying four wheelers depend on the pairing of the head lights. The existing pairing algorithm fails when one head light is hidden by other vehicles. In this paper, a simple pairing algorithm based on the spatial adjacency is experimented. This had less accuracy due to pairing of two wheeler head lights with that of four wheelers. The problem is alleviated by considering a varying scale factor proportional to the perspective projection of the vehicles in the line of sight. The accuracy of counting increased to 98%, where the drop is due to non-elliptical blobs of head lights that were not detected. Improvements: To guarantee the robust performance of the system, particularly the accuracy and the real-time processing speed. Limitation: The presence of fog lights in modern 4 wheelers are detected as separate cars which reduces the accuracy. The area of improvement will be to consider them as fog lights of the same car and not to mark them as a separate 4 wheelers.
Reliability Study of Hip Range of Motion Measurement by Smartphone Inclinometer

Purpose : The purpose of this study was to evaluate inter-tester reliability and Intra-tester reliability about range of motion(ROM) measurement of hip joint with smartphone inclinometer. Method : Six observers performed goniometric and smartphone inclinometer measurements of various hip movements, including both active ROM for flexion, extension, external rotation, internal rotation. Measurements were performed in the right hip of fifty normal subjects. All measures were performed three times for evaluating reliability of observer. Interand intra-observer reliabilities were evaluated using the intraclass correlation coefficient(ICC). Result : The results were as follows, inter-observer reliability ICC value showed . 948-. 974 in smartphone inclinometer. And showed . 781-. 827 in goniometer. Intra-observer reliability ICC value showed . 653-. 992 in smartphone inclinometer. And showed . 613-. 854 in goniometer. Conclusion : Smartphone inclinometer are portable and widely available tools that are mostly reliable and valid for assessing active hip range of motion, with potential use when a goniometer is not available.
Hybrid Consensus Pruning of Ensemble Classifiers for Big Data Malware Detection

One of the major challenges for safeguarding the security of big data in the cloud is how to detect and prevent malicious software (malware). Despite of the fact that security and privacy are critical issues in big data, more research needs to be done in this area. As malware can affect the reliability of the data and subsequently the reputation of the system, it is critical to detect and remove malware from a system as early as possible. Recently, ensembles that combine a set of classifiers have been proposed as an efficient approach for malware detection. Unfortunately, the size, memory and processing requirements as well as the high cost of data transfer during training and operation make large ensemble classifiers unsuitable for big data in the cloud. To address this problem, we propose a new advanced ensemble pruning method, Hybrid Consensus Pruning (HCP), which is the first pruning algorithm that employs a fast consensus function to combine several classifier classes into one scheme. To test the effectiveness of the HCP method, we conducted experiments comparing its performance with Ensemble Pruning via Individual Contribution ordering (EPIC), Directed Hill Climbing Ensemble Pruning (DHCEP) and K-Means Pruning approaches for pruning very large ensemble classifiers for malware detection. The results of the experiments show that HCP achieved better results by producing better ensemble classifiers as compared to those created by EPIC, DHCEP and K-Means Pruning.
Economic Well-being and Non-economic Well-being: A Review of the Meaning and Measurement of Poverty

This paper discusses the measurement of poverty and well-being. A historical overview is given of the last fifty years. This is followed by discussion of three groupings of indicators: those measures based primarily on economic well-being; those based on non-economic well-being and composite indicators. It is argued that the choice of indicator should reflect its purpose and that economic measures are best when quick, rough-and-ready, short run, aggregate inferences are required. In contrast, non-economic measures are better when greater depth on medium- or longer-term trends and/or dis-aggregation are required. [Research Paper No. 2004/30]
Forecast Analysis of Food Price Inflation in Pakistan: Applying Rationality Criterion for VAR Forecast

Forecast performance is considered to be a tart test of an econometric model. An accurate forecasting system is necessary for every industry to be able to take appropriate actions for future planning and planning creates a substantial need for forecasts. The purpose of this study is to evaluate forecast efficiency by using Rationality criterion of forecasts. It is therefore designed to analyze forecasting efficiency of food price inflation and consumer price index by using thirty three years quarterly data of Pakistan covering the period 1975 to 2008. Forecasts are obtained from VAR model specification. Four forecasting accuracy techniques, such as, Root Mean Square Error (RMSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE) and Theil‘s Inequality Coefficient (TIC) are used to be able to select the most accurate forecast from VAR. Later on these forecasts are evaluated on the basis of Rationality criterion defined. We found food price forecast are consistent, efficient and fulfilling the criteria of weak and strong rationality given. We propose that assessment of forecasts obtained by applying different criterion used will make them more reliable and correct to be used in policymaking and management decision. Keywords: Food Price Forecasts, Weak Rationality, Strong rationality, Strict rationality
Rarely Enjoyed? – A Count Data Analysis of Ridership in Germany’s Public Transport

Focusing on adult members of German households, this paper investigates the determinants of public transit ridership with the aim of quantifying the effects of fuel prices, fares, person-level attributes, and characteristics of the transit system on transport counts over a five-day week. The reliance on individual data raises several conceptual and empirical issues, the most fundamental of which is the large proportion of zero values in transit counts. To accommodate this feature of the data, we employ modeling procedures referred to as zero-inflated models (ZIMs), which order observations into two latent regimes defined by whether the individual never uses public transport. Our estimates reveal fuel prices to have a positive and substantial influence on transit ridership, though there is no evidence for a statistically signifi cant impact of the fare.
Unconditional Quantile Treatment Effects in the Presence of Covariates

Many economic applications have found quantile models useful when the explanatory variables may have varying impacts throughout the distribution of the outcome variable. Traditional quantile estimators provide conditional quantile treatment effects. Typically, we are interested in unconditional quantiles, characterizing the distribution of the outcome variable for different values of the treatment variables. Conditioning on additional covariates, however, may be necessary for identification of these treatment effects. With conditional quantile models, the inclusion of additional covariates changes the interpretation of the estimates. This paper discusses identification of unconditional quantile treatment effects when it is necessary or simply desirable to condition on covariates. It discusses identification for both exogenous and endogenous treatment variables, which can be discrete or continuous, without functional form assumptions.
The impact of European Union austerity policy on women's work in Southern Europe

Contrary to consolidated economic theory principles, in Europe (but also in other world regions), austerity policy has been implemented instead of stimulus measures which have proven to be successful in crisis associated with credit crunch and insufficient demand. These policies cannot be only considered as an "austericide" due to ideological blindness. They also need to be considered as a strategy for imposing an economic and social reform which proved too difficult to be implemented in the years previous to the great recession. The ongoing fiscal contraction policies include the typical adjustment measures which are now driving the European economy towards a new type of insertion within the international economy. And as a consequence, they imply deep changes on the gender division of work deepening gender inequality. This article analyses the different effects of European Union austerity policy on women and mens participation in the labour markets in two Southern European countries beaten by the Debt crisis: Spain and Italy. During the first part of this economics crisis, unemployment grew higher for men than for women, but in the second phase with the all sectors hit by the recession and the implementation of harsh austerity policies affecting public-sector jobs, women are also losing their jobs at the same rate than men. We have estimated labour supply models for individuals aged 25 to 54 living in couples with or without children by gender by using the EU-SILC 2011 micro data for Spain and Italy. The analysis carried out shows a strong countercyclical added-worker effect for women in response to transitory shocks in partners earnings, in contrast with a procyclical discouraged-worker effect for men. However though the added-worker effect prevails for women in Spain, in Italy still the discouraged worker effect dominates. The results show also a positive effect of the provision of childcare services on womens labour supply. A cut in social and care services due to austerity promotion may turn the tendency to a decline in womens participation and employment rates in the labour force with the subsequent loss of total well-being, due to gender differences in education performance, and especially of womens well-being.
Türkçe Metinlerin Sınıflandırılmasında Metin Temsil Yöntemlerinin Performans Karşılaştırılması / A Comparison of Text Representation Methods for Turkish Text Classification

Bir metnin sinifina metnin hangi ozelliklerine bakilarak karar verilebilir? Siniflandirma probleminin turunun (metnin yazarini, yazarin cinsiyetini, yazarin ruh halini, metnin konusunu, metnin olumlu ya da olumsuz ifadeler icerdigini tanima) bu soruya verilecek cevaba etkisi nedir? Bu sorulara cesitli cevaplar vererek, metin dosyalarinin otomatik siniflandirilmasi icin uzun zamandir calismalar surmektedir. Bu calismada cesitli turdeki 6 adet Turkce siniflandirma veri kumesi uzerinde 17 adet ozellik grubunun etkisi incelenmistir. Cikarilan ozellik gruplarina ornek olarak; cumle, kelime, ek sayilari, ngramlar, kelimeler, kelime gruplari ve sakli anlam indeksi verilebilir. Turkce icin bugune kadar yapilmis en kapsamli karsilastirma calismasi sunulmustur. Sonuclarda n-gramlarin genel olarak diger temsil yontemlerinden daha basarili sonuclar urettigi gorulmustur. Abstract Which features are the most important for text classification tasks? How does the type of text classification problem (authorship attribution, gender identification, mood identification, topic identification, sentiment analysis) affect the answer of this question? By giving various answers to these questions, the automatic text classification studies are ongoing for a long time. In this study, 17 text representation methods are compared over 6 different Turkish text classification tasks. Frequencies of the words, stem words, word phrases, n-grams, tokens, and word clusters, Latent Semantic Indexing are examples of the extracted text features. To the best of our knowledge, the most comprehensive study for Turkish text classification is presented. In general, n-grams were produced more successful results than the other text representing methods.
Essays on Democratic Institutions and Policy Outcomes

ESSAYS ON DEMOCRATIC INSITUTIONS AND POLICY OUTCOMES BY VLADIMIR FLEURIMOND August 2015 Committee Chair: Dr. Jorge L. Martinez-Vazquez Major Department: Economics This dissertation consists of three essays that examine the impact of democratic institutions on policy outcomes. The first essay investigates the impact of direct democracy on redistribution, tax progressivity and income inequality in the American states from 1984 to 2005. Currently available in 24 states, the statewide initiative allows citizens to directly influence policy outcomes. Theoretically, how this political institution impacts inequality and redistribution is ambiguous. Using a pooled OLS specification, I have found that direct democracy leads to an increase in income inequality and a decrease in state tax burden, with no effect on tax progressivity and only modest effect on expenditure redistribution. However, controlling for unobserved heterogeneity using a Correlated Random Effects model, I have found that direct democracy leads to an increase in marginal and average tax rates, with no effect on state tax burden. In their entirety, the findings of this essay underscore that the way in which direct democracy impacts redistribution and inequality is quite complex. This second essay examines the extent to which fiscal spillovers exist in county governments in California. At the county level in California, many fiscal decisions are made through the use of tax and expenditure referenda. Extant theory suggests that expenditures and revenues of neighboring jurisdictions are interdependent. That is, neighboring jurisdictions incorporate their neighbors’ fiscal choices into their own fiscal decisions. Using spatial econometric analysis and a novel dataset of county expenditures and revenues from 2003 to 2013, I have found strong evidence of fiscal spillovers in California counties. That is, counties respond to what their neighbors do. The third essay examines the impact of state-mandated alternative education programs for expelled and suspended students on juvenile crime. From 1987 to 2010, fourteen states adopted policies designed to reduce time students spend out of school as punishment by mandating that school districts establish alternative education programs to serve expelled and suspended students. Using difference-in-differences and event study methodologies, I estimate the impact of the state mandate on juvenile crime, finding that state-level juvenile homicide offending rates for black youth aged 12-17 significantly decrease after the implementation of