nils-herrmann/clean_scirepeval huggingface dataset:
Optimizing MySQL database system on information systems research, publications and community service
Venue: 2016 3rd International Conference on Information Technology, Computer, and Electrical Engineering (ICITACEE)

MySQL is the most trusted and depended on open source database platform in use today. Many of the most popular and highly trafficked websites in the world are built on MySQL because of its ubiquity across heterogeneous platforms and application stacks and for its well known performance, reliability and ease of use. Research, publications and community service is one activity that is managed by the Institute for Research and Community Service. The process of managing these activities today cannot be separated from the Internet, therefore we need a system that can manage every activity. To obtain the proper management it needs a system that is supported by the database system is also good. This paper discusses how to conduct the process of optimizing the database system so that when the data is accessed does not affect the performance of server systems. Process optimization is done on the design of the database system. Database design plays an important role in determining system performance. Process optimization is done in this study by using one of the functions that have been given in MySQL by using VIEW. This virtual table process to be performed by the system to be faster. This is because during the system requests to the server is does not need to query over and over because it has been done in the database management system.
Predicting Flight Delays by Using a Meta classifier

Airlines around the world are facing delays which incur extra costs to airlines, passengers, and society and difficulties for airport operations. Thus predicting the occurrence and magnitude of these delays is a major objective of airlines. This paper identifies the most important factors that generate delays in airline operation. It also provides a new hybrid method to predict flight delays. This technique, called meta classifier, combines two conventional machine learning approaches: the decision tree approach and the cluster classification approach. Proposed technique was implemented on an actual dataset of one of the major Iranian airlines with more than 35 airplanes that fly between 52 airports. Results show age of fleet, aircraft type, and departure time have the most influences on flight delays. Proposed hybrid approach has more accurate performance compare to regular data mining techniques. For this method, the accuracy of delay occurrence prediction is 76.4 percent and the accuracy of estimation of delay magnitude is 76 percent. It is hoped that this technique will enable airline agencies to predict delays accurately and improve flight planning process to prevent delay propagation.
Threat analysis of IoT networks using artificial neural network intrusion detection system
Venue: 2016 International Symposium on Networks, Computers and Communications (ISNCC)

The Internet of things (IoT) is still in its infancy and has attracted much interest in many industrial sectors including medical fields, logistics tracking, smart cities and automobiles. However as a paradigm, it is susceptible to a range of significant intrusion threats. This paper presents a threat analysis of the IoT and uses an Artificial Neural Network (ANN) to combat these threats. A multi level perceptron, a type of supervised ANN, is trained using internet packet traces, then is assessed on its ability to thwart Distributed Denial of Service (DDoS/DoS) attacks. This paper focuses on the classification of normal and threat patterns on an IoT Network. The ANN procedure is validated against a simulated IoT network. The experimental results demonstrate 99.4% accuracy and can successfully detect various DDoS/DoS attacks.
(212)Pb as tracer for PM deposition on urban vegetation.
Venue: The Science of the total environment

(212)Pb concentration in outdoor air is closely correlated with fine suspended particulate matter in the atmosphere. Thanks to this association, this isotope can be used to trace the sinking processes of particulate matter due to the vegetation, also providing accurate estimations of the deposition velocity on foliar surfaces. This approach is particularly effective in areas with high thoron fluxes and, consequently, high (212)Pb fluxes from soil. The contribution of vegetation to the improvement of air quality (AQImp) in the municipality area (MA) of Rome (Latium, Italy) almost entirely located on Th enriched volcanic soils, was estimated by studying (212)Pb deposition velocity on the grasses (0.9 2.5mm*s( 1) and on the most common tree classes, namely conifers (1.5 15mm*s( 1) evergreen (1 4mm*s( 1) and deciduous (0.2 1.5mm*s( 1) (212)Pb activity in outdoor air was determined by gamma spectrometry after air pumping with accumulation on cellulose filters and after collection on artificial electrostatically charged surfaces (ECS) The high (212)Pb activity values obtained from this analysis (0.90+ 0.6Bqm( 3) and 0.58+ 0.15Bqm( 3) respectively near and far from the soil) are consistent both with the average regional thoron flux from volcanic soils (2.9*10(4)Bqm( 2)*h( 1) and with the thoron flux measured in the volcanic soils of the study area. Thoron and (212)Pb fluxes were also measured both in laboratory and in the field under different soil moisture conditions. The total AQImp for the period from September 2014 to September 2015, calculated after the classification of the MA of Rome into six classes of vegetation, provided a value of 0.20 corresponding to 2.3 Tons per day of removed PM10. The role of grasslands in the PM10 removal, the contribution of the vegetation to the improvement of AQImp and the possibility of improving the sinking efficiency of green areas by increasing conifer trees coverage were also highlighted.
Assessing Families (Not Just Individuals) for Missionary Service

The assessment of missionaries tends to focus on the adult members of the family unit being approved for service. Yet, the family is the one consistent relational network that missionaries are connected to throughout the pre field, on the field, and post field phases of mission service. In addition, throughout the history of missions sending bodies have struggled to balance the needs of the missions context, the ministry gifts that the adult members of the family bring to the field, and the dynamics of their marital and family relationships. While the literature on missionary children has grown significantly, adopting a perspective that prioritizes the family unit as the unit being "sent" may result in helpful information regarding missionary attrition and longevity. Therefore, assessing missionary families, not only the individual members of the family, at the various stages of missionary service is warranted. Using concepts and techniques from systems theory, a model and logistical factors for assessing missionary families are presented, along with suggestions for whom to assess, what to assess, and how to conduct family assessment. Resources and possible assessment techniques are also provided.
Using "The Machine Stops" for Teaching Ethics in Artificial Intelligence and Computer Science
Venue: AAAI Workshop: AI, Ethics, and Society

A key front for ethical questions in artificial intelligence, and computer science more generally, is teaching students how to engage with the questions they will face in their professional careers based on the tools and technologies we teach them. In past work (and current teaching) we have advocated for the use of science fiction as an appropriate tool which enables AI researchers to engage students and the public on the current state and potential impacts of AI. We present teaching suggestions for E.M. Forster's 1909 story, "The Machine Stops," to teach topics in computer ethics. In particular, we use the story to examine ethical issues related to being constantly available for remote contact, physically isolated, and dependent on a machine all without mentioning computer games or other media to which students have strong emotional associations. We give a high level view of common ethical theories and indicate how they inform the questions raised by the story and afford a structure for thinking about how to address them.
The effects of acute stress on core executive functions: A meta analysis and comparison with cortisol
Venue: Neuroscience Biobehavioral Reviews

Core executive functions such as working memory, inhibition, and cognitive flexibility are integral to daily life. A growing body of research has suggested that acute stress may impair core executive functions. However, there are a number of inconsistencies in the literature, leading to uncertainty about how or even if acute stress influences core executive functions. We addressed this by conducting a meta analysis of acute stress effects on working memory, inhibition, and cognitive flexibility. We found that stress impaired working memory and cognitive flexibility, whereas it had nuanced effects on inhibition. Many of these effects were moderated by other variables, such as sex. In addition, we compared effects of acute stress on core executive functions to effects of cortisol administration and found some striking differences. Our findings indicate that stress works through mechanisms aside from or in addition to cortisol to produce a state characterized by more reactive processing of salient stimuli but greater control over actions. We conclude by highlighting some important future directions for stress and executive function research.
Active Surveillance versus Spontaneous Reporting for First Line Antiretroviral Medicines in Namibia: A Cost Utility Analysis
Venue: Drug Safety

IntroductionActive surveillance pharmacovigilance is a systematic approach to medicine safety assessment and health systems strengthening, but has not been widely implemented in low and middle income countries. This study aimed to assess the cost effectiveness of a national active surveillance pharmacovigilance system for highly active antiretroviral therapy (HAART) compared with the existing spontaneous reporting system in Namibia.MethodsA cost utility analysis from a governmental perspective compared active surveillance pharmacovigilance to spontaneous reporting. Data from a sentinel site active surveillance program in Namibia from August 2012 to April 2013 was projected to all HIV infected adults initiating HAART in Namibia. Costs (pharmacovigilance program, HAART, adverse event [AE] treatment) quality adjusted life years (QALYs) and incremental cost effectiveness ratios (ICERs, dollars/QALY) were evaluated. Analysis was completed for (i) cohort analysis: a single cohort beginning HAART in 1 year in Namibia followed over their remaining lifetime, and (ii) population analysis: patients continued to enter and leave care and treatment over 10 years.ResultsFor the cohort analysis, totals were US$21,267,902 (2015 US dollars) and 116,224 QALYs for care and treatment under active surveillance pharmacovigilance versus US$15,257,381 and 116,122 QALYs for care and treatment under spontaneous reporting pharmacovigilance, resulting in an ICER of US$58,867/QALY for active surveillance compared with spontaneous reporting pharmacovigilance. The population analysis ICER was US$4989/QALY. Results were sensitive to quality of life associated with AEs.ConclusionActive surveillance pharmacovigilance was projected to be highly cost effective to improve treatment for HIV in Namibia. Active surveillance pharmacovigilance may be valuable to improve lives of HIV patients and more efficiently allocate health resources in Namibia.
Finding de novo methylated DNA motifs

Increasing evidence has shown that posttranslational modifications (PTMs) such as methylation and hydroxymethylation on cytosine would greatly impact the binding of transcription factors (TFs) However, there is a lack of motif finding algorithms with the function to search for motifs with PTMs. In this study, we expend on our previous motif finding pipeline Epigram to provide systematic de novo motif discovery and performance evaluation on methylated DNA motifs. Using the tool, we were able to identified methylated motifs in Arabidopsis DAP seq data that were previously demonstrated to contain such motifs1. When applied to TF ChIP seq and DNA methylome data in H1 and GM12878, our method successfully identified novel methylated motifs that can be recognized by the TFs or their co factors. We also observed spacing constraint between the canonical motif of the TF and the newly discovered methylated motifs, which suggests operative recognition of these cis elements by collaborative proteins.
Pre Exercise Infrared Low Level Laser Therapy (810 nm) in Skeletal Muscle Performance and Postexercise Recovery in Humans, What Is the Optimal Dose? A Randomized, Double Blind, Placebo Controlled Clinical Trial.
Venue: Photomedicine and laser surgery

This study aimed to evaluate the medium term effects of low level laser therapy (LLLT or photobiomodulation) in postexercise skeletal muscle recovery and performance enhancement and to identify the optimal dose of 810 nm LLLT.  A randomized, double blind, placebo controlled trial was performed, with voluntary participation of 28 high level soccer athletes. We analyzed maximum voluntary contraction (MVC) delayed onset muscle soreness (DOMS) creatine kinase (CK) activity, and interleukin 6 (IL 6) expression. The assessments were performed before exercise protocols, after 1 min, and 1, 24, 48, 72, and 96 h after the end of eccentric exercise protocol used to induce fatigue. LLLT was applied before eccentric exercise protocol with a cluster with five diodes, and dose of 10, 30, or 50 J (200 mW and 810 nm) in six sites of quadriceps.  LLLT increased (p 0.05) MVC from immediately after exercise to 24 h with 50 J dose, and from 24 to 96 h with 10 J dose. Both 10 J then 50 J dose decreased (p 0.05) CK and IL 6 with better results in favor of 50 J dose. However, LLLT had no effect in decreasing DOMS. No differences (p 0.05) were found for 30 J dose in any of the outcomes measured.  Pre exercise LLLT, mainly with 50 J dose, significantly increases performance and improves biochemical markers related to skeletal muscle damage and inflammation.
Probabilistic forecasting of the solar irradiance with recursive ARMA and GARCH models

Forecasting of the solar irradiance is a key feature in order to increase the penetration rate of solar energy into the energy grids. Indeed, the anticipation of the fluctuations of the solar renewables allows a better management of the production means of electricity and a better operation of the grid connected storage systems. If numerous methods for forecasting the mean of the solar irradiance were recently developed, there are only few works dedicated to the evaluation of prediction intervals associated to these point forecasts. Time series of solar irradiance and more specifically of clear sky index show some similarities with that of financial time series. The aim of this paper is to assess the performances of a commonly used combination of two linear models (ARMA and GARCH) in econometrics in order to provide probabilistic forecasts of solar irradiance. In addition, a recursive estimation of the parameters of the models has been set up in order to provide a framework that can be applied easily in an operational context. A comprehensive testing procedure has been used to assess both point forecasts and probabilistic forecasts. Using only the past records of the solar irradiance, the proposed model is able to perform point forecasts as accurately as other methods based on machine learning techniques. Moreover, the recursive ARMA GARCH model is easier to set up and it gives additional information about the uncertainty of the forecasts. Even if some strong assumption has been made regarding the statistical distribution of the error, the reliability of the probabilistic forecasts stands in the same order of magnitude as other works done in the field of solar forecasting.
Ensemble forecasting of solar irradiance by applying a mesoscale meteorological model

The solar irradiance and its prediction interval are forecasted with the aid of a meteorological model for the prediction of the photovoltaic systems generation. The solar irradiances of the same target day are computed utilizing a model with different initial conditions, and the accuracy of the forecasting is discussed in this paper. Forecasting reliability is also estimated from the variance of the forecasted irradiances. The relationship between the forecasted reliability and the forecasting error is derived, and the prediction interval of the solar irradiance forecasting is evaluated from both its reliability and relationship. The performance of the probabilistic forecasting of the solar irradiance which consists of the prediction interval is discussed in the observation. The size of the prediction interval changes as the forecasting reliability varies. The observed data in the interval is almost the same rate as the coverage rate determined in advance.
Exploring Limits to Prediction in Complex Social Systems
Venue: WWW

How predictable is success in complex social systems? In spite of a recent profusion of prediction studies that exploit online social and information network data, this question remains unanswered, in part because it has not been adequately specified. In this paper we attempt to clarify the question by presenting a simple stylized model of success that attributes prediction error to one of two generic sources: insufficiency of available data and/or models on the one hand; and inherent unpredictability of complex social systems on the other. We then use this model to motivate an illustrative empirical study of information cascade size prediction on Twitter. Despite an unprecedented volume of information about users, content, and past performance, our best performing models can explain less than half of the variance in cascade sizes. In turn, this result suggests that even with unlimited data predictive performance would be bounded well below deterministic accuracy. Finally, we explore this potential bound theoretically using simulations of a diffusion process on a random scale free network similar to Twitter. We show that although higher predictive power is possible in theory, such performance requires a homogeneous system and perfect ex ante knowledge of it: even a small degree of uncertainty in estimating product quality or slight variation in quality across products leads to substantially more restrictive bounds on predictability. We conclude that realistic bounds on predictive accuracy are not dissimilar from those we have obtained empirically, and that such bounds for other complex social systems for which data is more difficult to obtain are likely even lower.
Environmental responses of the Northeast Antarctic Peninsula to the Holocene climate variability

In this study, we present a unique high resolution Holocene record of oceanographic and climatic change based on analyses of diatom assemblages combined with biomarker data from a sediment core collected from the Vega Drift, eastern Antarctic Peninsula (EAP) These data add to the climate framework already established by high resolution marine sedimentary records from the Palmer Deep, western Antarctic Peninsula (WAP) Heavy sea ice conditions and reduced primary productivity were observed prior to 7.4 ka B.P. in relation with the proximity of the glacial ice melt and calving. Subsequent Holocene oceanographic conditions were controlled by the interactions between the Westerlies Antarctic Circumpolar Current (ACC) Weddell Gyre dynamics. A warm period characterized by short seasonal sea ice duration associated with a southern shift of both ACC and Westerlies field persisted until 5 ka B.P. This warm episode was then followed by climate deterioration during the middle to late Holocene (5 to 1.9 ka B.P. with a gradual increase in annual sea ice duration triggered by the expansion of the Weddell Gyre and a strong oceanic connection from the EAP to the WAP. Increase of benthic diatom species during this period was indicative of more summer/autumn storms, which was consistent with changes in synoptic atmospheric circulation and the establishment of low to high latitude teleconnections. Finally, the multicentennial scale variability of the Weddell Gyre intensity and storm frequency during the late Holocene appeared to be associated with the increased El Nino Southern Oscillation frequency.
Last Glacial Holocene climate variability in the Atlantic sector of the Southern Ocean

The Southern Ocean plays a major role in the glacial/interglacial global carbon cycle. However, there is a substantial lack of information from its Antarctic Zone south of the Polar Front (PF) to understand key climate processes (e.g. sea ice variability, productivity changes, CO2 source region, shifts of the Southern Westerly Wind) active in this region during the glacial/interglacial transition, due to the limited high resolution sediment records from this area. To close this gap, we investigated high resolution diatom records from a series of sediment cores from the Atlantic and Western Indian sectors of the Southern Ocean between the modern PF and the Winter Sea Ice (WSI) edge. Summer Sea Surface Temperature (SSST) and sea ice information spanning the past 30 thousand years were derived from diatom transfer functions and indicators, which augment comprehensive information on past surface ocean conditions and related ocean and atmospheric circulation, as well as opal deposition. These complementary lines of evidences also provide important environmental boundary conditions for climate simulations understanding the past climate development in the high latitudes Southern Ocean. Our reconstructions show that the Last Glacial (LG) SSSTs south of the modern PF are 1 3 degC colder than modern conditions, WSI expanded to the modern PF. Our data suggests effective carbon export in the Antarctic Zone during the LG. Deglacial two steps of warming support the bipolar seesaw mechanism. Antarctic Zone is an important source region for the CO2 deglacial increase. The warming was more suppressed towards south, due to continuous ice discharge from Antarctica. The SSSTs exceeded modern values during the early Holocene optimum, when WSI extent probably retreated south of its modern position. The southern boundary of maximum opal deposition zone may have shifted to south of 55degS in the Bouvet Island area at this time. The mid late Holocene cooling with WSI re expanding to the Bouvet Island area, probably related to enhanced cold water export by the Weddell Gyre from the developing cavity under the West Antarctic Ice Shelf. The cooling also suggests a northward shift of the Southern Westerly Wind, at least its southern boundary.
A comparison of ASR and human errors for transcription of non native spontaneous speech
Venue: 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

In this paper, we compare ASR and human transcriptions of non native speech to investigate to what extent the accuracy and the patterns of errors of a modern ASR system match those of human listeners in the context of automated assessment of L2 English language proficiency. We obtained multiple naive transcriptions of short fragments of non native spontaneous speech with different proficiency levels using crowdsourcing and matched these against the output of an ASR system. We compare WER and recall at the fragment level and consider human ASR agreement at the word level. We find that we are able to attain a commensurate level of transcription quality using ASR, but the patterns of errors between the two groups differ at the word level.