nils-herrmann/clean_scirepeval huggingface dataset:
Lambada: Interactive Data Analytics on Cold Data Using Serverless Cloud Infrastructure
Venue: SIGMOD Conference
Year: 2020

Serverless computing has recently attracted a lot of attention from research and industry due to its promise of ultimate elasticity and operational simplicity. However, there is no consensus yet on whether or not the approach is suitable for data processing. In this paper, we present Lambada, a serverless distributed data processing framework designed to explore how to perform data analytics on serverless computing. In our analysis, supported with extensive experiments, we show in which scenarios serverless makes sense from an economic and performance perspective. We address several important technical questions that need to be solved to support data analytics and present examples from several domains where serverless offers a cost and performance advantage over existing solutions.
Measuring Perceived Usability: The CSUQ, SUS, and UMUX
Venue: Int. J. Hum. Comput. Interact.
Year: 2018

The primary purpose of this research was to investigate the relationship between two widely used questionnaires designed to measure perceived usability: the Computer System Usability Questionnaire (CSUQ) and the System Usability Scale (SUS) The correlation between concurrently collected CSUQ and SUS scores was 0.76 (over 50% shared variance) After converting CSUQ scores to a 0 100 point scale (to match the range of the SUS scores) there was a small but statistically significant difference between CSUQ and SUS means. Although this difference (just under 2 scale points out of a possible 100) was statistically significant, it did not appear to be practically significant. Although usability practitioners should be cautious pending additional independent replication, it appears that CSUQ scores, after conversion to a 0 100 point scale, can be interpreted with the Sauro Lewis curved grading scale. As a secondary research goal, investigation of variations of the Usability Metric for User Experience (UMUX) replicated previous findings that the regression adjusted version of the UMUX LITE (UMUX LITEr) had the closest correspondence with concurrently collected SUS scores. Thus, even though these three standardized questionnaires were independently developed and have different item content and formats, they largely appear to be measuring the same thing, presumably, perceived usability.
3D Convolutional Neural Networks for Tumor Segmentation using Long range 2D Context
Venue: Comput. Medical Imaging Graph.
Year: 2019

We present an efficient deep learning approach for the challenging task of tumor segmentation in multisequence MR images. In recent years, Convolutional Neural Networks (CNN) have achieved state of the art performances in a large variety of recognition tasks in medical imaging. Because of the considerable computational cost of CNNs, large volumes such as MRI are typically processed by subvolumes, for instance slices (axial, coronal, sagittal) or small 3D patches. In this paper we introduce a CNN based model which efficiently combines the advantages of the short range 3D context and the long range 2D context. Furthermore, we propose a network architecture with modality specific subnetworks in order to be more robust to the problem of missing MR sequences during the training phase. To overcome the limitations of specific choices of neural network architectures, we describe a hierarchical decision process to combine outputs of several segmentation models. Finally, a simple and efficient algorithm for training large CNN models is introduced. We evaluate our method on the public benchmark of the BRATS 2017 challenge on the task of multiclass segmentation of malignant brain tumors. Our method achieves good performances and produces accurate segmentations with median Dice scores of 0.918 (whole tumor) 0.883 (tumor core) and 0.854 (enhancing core)
Donne e carriera tra stereotipi di genere e conciliazione lavoro famiglia. Un'analisi psico sociale
Year: 2017

Nel mondo occidentale le disparita dei percorsi di carriera tra donne e uomini persistono ancora: le posizioni di status piu elevato rimangono una prerogativa maschile, le donne sono invece bloccate in posizioni intermedie, presentando percorsi di carriera accidentati e caratterizzati da difficolta, legate in gran parte all'equilibrio lavoro resto della vita. Nel quadro teorico della Role Congruity Theory di Eagly e Karau (2002) e della conciliazione, la presente ricerca intende approfondire, attraverso interviste in profondita, la narrazione di 15 donne in posizioni lavorative di responsabilita. Nello specifico, lo studio intende indagare: il ruolo degli stereotipi di genere che hanno influenzato i percorsi di carriera e i vissuti di conciliazione lavoro resto della vita e come questi hanno condizionato le scelte personali e professionali. Le interviste sono state sottoposte ad analisi del contenuto con l'ausilio di Atlas ti 6.0.
Adding Prior Knowledge in Hierarchical Attention Neural Network for Cross Domain Sentiment Classification
Venue: IEEE Access
Year: 2019

Domain adaptation tasks have raised much attention in recent years, especially, the task of cross domain sentiment classification (CDSC) Due to the domain discrepancy, a sentiment classifier trained in a source domain often performs less well, when directly applied to a target domain. Adversarial neural networks have been used in mainstream approaches for learning domain independent features, such as pivots, which are words with the same sentiment polarity in different domains. However, domain specific features can often determine sentiment in its context. In this paper, we propose a hierarchical attention network with prior knowledge information (HANP) for the CDSC task. Unlike other existing methods, the HANP can obtain both domain independent and domain specific features at the same time by adding prior knowledge. In addition, the HANP also includes a hierarchical representation layer with attention mechanism, so that the HANP can capture important words and sentences in relation to sentiment. Moreover, the proposed model can offer a direct visualization of the sentimental prior knowledge. The experiments on the Amazon review datasets demonstrate that the proposed HANP can significantly outperform the state of the art methods.
Psychiatric associations of adult onset focal dystonia phenotypes
Venue: Journal of Neurology, Neurosurgery, and Psychiatry
Year: 2017

Depression and anxiety frequently accompany the motor manifestations of isolated adult onset focal dystonias. Whether the body region affected when this type of dystonia first presents is associated with the severity of these neuropsychiatric symptoms is unknown.  The aim of this study was to determine whether depression, anxiety and social anxiety vary by dystonia onset site and evaluate whether pain and dystonia severity account for any differences.  Patients with isolated focal dystonia evaluated within 5 years from symptom onset, enrolled in the Natural History Project of the Dystonia Coalition, were included in the analysis. Individual onset sites were grouped into five body regions: cervical, laryngeal, limb, lower cranial and upper cranial. Neuropsychiatric symptoms were rated using the Beck Depression Inventory, Hospital Anxiety and Depression Scale and Liebowitz Social Anxiety Scale. Pain was estimated using the 36 Item Short Form Survey.  Four hundred and seventy eight subjects met our inclusion criteria. High levels of depression, anxiety and social anxiety occurred in all groups; however, the severity of anxiety and social anxiety symptoms varied by onset site group. The most pronounced differences were higher anxiety in cervical and laryngeal, lower anxiety in upper cranial and higher social anxiety in laryngeal. Increases in pain were associated with worse neuropsychiatric symptom scores within all groups. Higher anxiety and social anxiety in laryngeal and lower anxiety in upper cranial persisted after correcting for pain and dystonia severity.  Anxiety and social anxiety severity vary by onset site of focal dystonia, and this variation is not explained by differences in pain and dystonia severity.
The Use of Letterland Strategies in Teaching English Vocabulary to Young Learners
Year: 2020

This research discussed about the use of Letterland strategies in teaching English vocabulary to young learners. Descriptive qualitative design was applied in this research and the data gathered from the sentences of four teachers in Nursery class at a Singapore Pre School, Medan. Observation and interview were the techniques of collecting data. Then, the techniques in analyzing the data were condensation, data display, and conclusion drawing/verification. Based on the data analysis, it was found that the sounds trick strategy (64.49% the character names trick (33.68% the action trick (1.57% and the capital letter trick (0.26% were four of the Letterland strategies used by the teachers. From the findings, it was concluded that Letterland strategies were good for young learners in learning English vocabulary because it provided some fun activities that contained of multi sensory based learning which they were able to see, hear, do, and touch it.
The contracts, structures and pricing mechanisms of sukuk: A critical assessment
Venue: Borsa Istanbul Review
Year: 2019

The existing literature focuses only on the contacts and structures of sukuk, but the pricing of sukuk is largely ignored. This paper examines the contracts, structures and pricing mechanism of sukuk. More specifically, this study examines several sukuk instruments, reviews the existing structures, demonstrates sukuk pricing mechanisms and discusses critical issues of each type of sukuk. The paper also considers possible solutions for those issues discussed in this study. By doing so, the readers are able to understand the important technical elements of sukuk and can differentiate sukuk from the conventional bonds and appreciate the spirit of Islamic finance.
A nonparametric welfare analysis on water quality improvement of the floating people on Inlay Lake via a randomized conjoint field experiment
Year: 2016

The present work was in part conducted for methodological advancements in social science of and supported by the Hiroshima University TAOYAKA Program for creating a flexible, enduring, peaceful society, funded by the Program 19 for Leading Graduate Schools, Ministry of Education, Culture, Sports, Science and Technology. In addition, the field experiment was in part financially supported by Japanese Grant Aid for Human Resource Development Scholarship (JDS) Project.
LDEF Satellite Radiation Analyses
Year: 2013

This report covers work performed by Science Applications International Corporation (SAIC) under contract NAS8 39386 from the NASA Marshall Space Flight Center entitled LDEF Satellite Radiation Analyses. The basic objective of the study was to evaluate the accuracy of present models and computational methods for defining the ionizing radiation environment for spacecraft in Low Earth Orbit (LEO) by making comparisons with radiation measurements made on the Long Duration Exposure Facility (LDEF) satellite, which was recovered after almost six years in space. The emphasis of the work here is on predictions and comparisons with LDEF measurements of induced radioactivity and Linear Energy Transfer (LET) measurements. These model/data comparisons have been used to evaluate the accuracy of current models for predicting the flux and directionality of trapped protons for LEO missions.
Statut nutritionnel des enfants ages de 0 a 36 mois admis au CHU de Sidi Bel Abbes (Ouest algerien)
Year: 2006

Resume L'objectif de ce travail est d'evaluer le statut nutritionnel d'une population d'enfants ages de 0 a 36 mois admis au CHU de Sidi Bel Abbes pour diverses pathologies. L'analyse des dossiers et l'examen complet des patients demontrent des signes de malnutrition proteino energetique (MPE) et d'affections liees a cette pathologie. Les donnees socioeconomiques revelent de tres bas niveaux de vie pour la majorite de nos patients. Les parametres anthropometriques indiquent un arret de croissance pour les patients ages de 12 a 36 mois et l'indice de Kanawati et McLaren objective une denutrition moyenne chez les filles, et presque severe chez les garcons. Les dosages biologiques demontrent une hypoprotidemie, et des taux bas de calcium, de phosphore et de fer.
A revisao de textos traduzidos do ingles para o portugues questoes pertinentes a reflexao e a pratica do revisor textual
Year: 2018

A poorly written text does not build credibility and is viewed in a negative way by the reader. Proofreading is the process in which the proofreader identifies errors and inadequacies and intervenes to improve the quality of a text. More specifically, when it comes to proofreading translated texts (TT) one may encounter recurrent problems, such as inadequate punctuation and lack of fluency in the target language, ambiguities of all sorts, awkward literal translations that sound funny, unwanted repetitions, among other inadequacies that compromise the translation and, consequently, the reader's understanding of the original message. In this sense, this paper aims at identifying some problems encountered by the proofreader of TT from English into Portuguese and proposing alternatives to solve them. Technical scientific texts will be the focus of this paper, since the literary genre would require a differentiated analysis. The discussion here is based on authors such as Hurtado Albir (2001) Reuillard (2014) Carvalhal (1993) Mossop (2006) Coelho Neto (2013) Parra Galiano (2007) among other recognized researchers in the areas of translation and proofreading, respectively, and whose reflections contributed to the approach mobilized in this paper. The methodology consisted of selection and manual extraction of TT sections that showcase the problems listed; identification and categorization of the problems; and proposals for improvement of the excerpts, along with explanations of why such inadequacies may be a problem to the reader and how the suggestions made can provide more quality to the text. In the analysis section, the problems identified are analyzed in depth. In the final considerations, the indispensability of the proofreader is emphasized as the qualified professional to intervene in the writing of texts in order to preserve the clarity, the adequacy to the Portuguese language rules, and to ensure that the translation reflects the meaning of the original.
Spiking Neural Networks: Background, Recent Development and the NeuCube Architecture
Venue: Neural Processing Letters
Year: 2020

This paper reviews recent developments in the still off the mainstream information and data processing area of spiking neural networks (SNN) the third generation of artificial neural networks. We provide background information about the functioning of biological neurons, discussing the most important and commonly used mathematical neural models. Most relevant information processing techniques, learning algorithms, and applications of spiking neurons are described and discussed, focusing on feasibility and biological plausibility of the methods. Specifically, we describe in detail the functioning and organization of the latest version of a 3D spatio temporal SNN based data machine framework called NeuCube, as well as it's SNN related submodules. All described submodules are accompanied with formal algorithmic formulations. The architecture is highly relevant for the analysis and interpretation of various types of spatio temporal brain data (STBD) like EEG, NIRS, fMRI, but we highlight some of the recent both STBD and non STBD based applications. Finally, we summarise and discuss some open research problems that can be addressed in the future. These include, but are not limited to: application in the area of EEG based BCI through transfer learning; application in the area of affective computing through the extension of the NeuCube framework which would allow for a biologically plausible SNN based integration of central and peripheral nervous system measures. Matlab implementation of the NeuCube's SNN related module is available for research and teaching purposes.
Instructional video in e learning: Assessing the impact of interactive video on learning effectiveness
Venue: Inf. Manag.
Year: 2006

Interactive video in an e learning system allows proactive and random access to video content. Our empirical study examined the influence of interactive video on learning outcome and learner satisfaction in e learning environments. Four different settings were studied: three were e learning environments with interactive video, with non interactive video, and without video. The fourth was the traditional classroom environment. Results of the experiment showed that the value of video for learning effectiveness was contingent upon the provision of interactivity. Students in the e learning environment that provided interactive video achieved significantly better learning performance and a higher level of learner satisfaction than those in other settings. However, students who used the e learning environment that provided non interactive video did not improve either. The findings suggest that it may be important to integrate interactive instructional video into e learning systems.
Why Do Latino Survey Respondents Acquiesce? Respondent and Interviewer Characteristics as Determinants of Cultural Patterns of Acquiescence Among Latino Survey Respondents
Venue: Cross cultural research official journal of the Society for Cross Cultural Research
Year: 2019

Research indicates that Latino survey respondents are more likely to acquiesce than non Latino European Americans (EAs) thereby decreasing the potential for measurement invariance across cultural groups. To better understand what drives this culturally patterned response style, we examined the influence of respondent and interviewer characteristics on acquiescence. Data were obtained from a telephone survey of 400 Mexican American, Puerto Rican, Cuban American, and non Latino EA respondents, and a self administered survey of 21 interviewers. Higher acquiescence was associated with several respondent characteristics: older age, lower education, stronger Latino cultural orientation, Spanish use, Latino ethnicity, and, among Latinos, Cuban American ethnicity. In contrast, acquiescence was not influenced by respondent interviewer social distance, social deference, or interviewer characteristics (e.g. education, gender, acculturation, interviewer experience) These findings indicate that acquiescence differs across Latino ethnic subgroups and that respondent and language factors are more influential determinants of acquiescence than survey interviewers.
Evaluation of the Effects of Digitization in the Process of Accounting Operations in a Selected Manufacturing Company
Year: 2020

The principles of industry 4.0 progressively penetrate into accounting. The process of accounting activities from entering accounting documents to posting accounting documents is now fully automated. Through digitization and artificial intelligence, the invoice is automatically read and recorded in the accounts. On the other hand, activities in the process of control of realized accounting operations, including financial management of the company, remain to the accountants. Digitization of invoices is based on converting from paper form by using document scanners to digital form. This is followed by automatic reading from invoices through AI which uses neural networks. Accounting Act is intended to define methods of using electronic documents, understanding accounting records. It will give the sufficient knowledge of the technology used and knowledge of employees to automate accounting operations. Despite this, digitization brings benefits in terms of time savings, lower costs, and an overview of the volume of liabilities on invoices. The aim of the paper is to evaluate the effects of digitization of accounting operations through corporate economic data. At the same time identify the main problems that arise during digitization. Case study will document the findings. The business data of a particular company and data from the Czech Statistical Office will be used for processing.
Bidirectional Representation Learning From Transformers Using Multimodal Electronic Health Record Data to Predict Depression
Venue: IEEE Journal of Biomedical and Health Informatics
Year: 2021

Advancements in machine learning algorithms have had a beneficial impact on representation learning, classification, and prediction models built using electronic health record (EHR) data. Effort has been put both on increasing models' overall performance as well as improving their interpretability, particularly regarding the decision making process. In this study, we present a temporal deep learning model to perform bidirectional representation learning on EHR sequences with a transformer architecture to predict future diagnosis of depression. This model is able to aggregate five heterogenous and high dimensional data sources from the EHR and process them in a temporal manner for chronic disease prediction at various prediction windows. We applied the current trend of pretraining and fine tuning on EHR data to outperform the current state of the art in chronic disease prediction, and to demonstrate the underlying relation between EHR codes in the sequence. The model generated the highest increases of precision recall area under the curve (PRAUC) from 0.70 to 0.76 in depression prediction compared to the best baseline model. Furthermore, the self attention weights in each sequence quantitatively demonstrated the inner relationship between various codes, which improved the model's interpretability. These results demonstrate the model's ability to utilize heterogeneous EHR data to predict depression while achieving high accuracy and interpretability, which may facilitate constructing clinical decision support systems in the future for chronic disease screening and early detection.
Reconstructing the giant: On the importance of rigour in documenting the literature search process
Venue: ECIS
Year: 2009

Science is a cumulative endeavour as new knowledge is often created in the process of interpreting and combining existing knowledge. This is why literature reviews have long played a decisive role in scholarship. The quality of literature reviews is particularly determined by the literature search process. As Sir Isaac Newton eminently put it: If I can see further, it is because I am standing on the shoulders of giants. Drawing on this metaphor, the goal of writing a literature review is to reconstruct the giant of accumulated knowledge in a specific domain. And in doing so, a literature search represents the fundamental first step that makes up the giant's skeleton and largely determines its reconstruction in the subsequent literature analysis. In this paper, we argue that the process of searching the literature must be comprehensibly described. Only then can readers assess the exhaustiveness of the review and other scholars in the field can more confidently (re)use the results in their own research. We set out to explore the methodological rigour of literature review articles published in ten major information systems (IS) journals and show that many of these reviews do not thoroughly document the process of literature search. The results drawn from our analysis lead us to call for more rigour in documenting the literature search process and to present guidelines for crafting a literature review and search in the IS domain.