nils-herrmann/clean_scirepeval huggingface dataset:
Grand Challenge Producing Meaningful Texts
Year: 2015

We will develop an automatic system capable of understanding scientific and humanistic texts, identifying novel ideas and key concepts, and then producing specialized summaries understandable for different audiences. The system will collect information from research publications, identify major topics, and produce readable summaries that can be targeted towards, for instance, other researchers, the general public, school children, or people with reading impairments. This task requires contributions from diverse fields, e.g. Computational Linguistics, Artificial Intelligence, Cognitive Science, and Science of Science. Subtasks include the automatic linguistic analysis of texts/recordings, production of text from abstract representations of meaning, identification of key topics in documents and of texts with a high potential for being cited, etc. While major progress has been made in some subtasks, major limitations remain: automatic generation systems often produce incoherent/unreadable text, while readable text can be reliably produced only in very limited areas such as fantasy football reporting. As such, the approaches we develop will catapult computational language understanding into a new era. We will produce a system that generates press releases summarizing university research that are judged (1) understandable and (2) indistinguishable from human authored press releases by at least 50% of adult readers. The system can be adapted to rephrase medical texts, patents, intelligence information from a wide range of sources, etc. IU is ideally suited to address this challenge because we have a critical mass of researchers from different fields working on those subareas, e.g. Computer Science, Computational Linguistics, Cognitive Science, and Information and Library  We will develop an automatic system capable of understanding scientific and humanistic texts, identifying novel ideas and key concepts, and then producing specialized summaries understandable for different audiences. The system will collect information from research publications, identify major topics, and produce readable summarizes that can be targeted towards, for instance, other researchers, the general public, primary and secondary school children, or people with reading impairments. This task requires contributions from diverse fields, e.g. Computational Linguistics, Artificial Intelligence, Cognitive Science, and Science of Science, as well as from domain experts from the sciences and the humanities. Subtasks include the automatic linguistic analysis of texts and recordings, production of text from abstract representations of meaning, identification of key topics in documents and of texts with a high potential for being cited, etc. While major progress has been made in some subtasks, major limitation remain: automatic generation systems often produce incoherent/unreadable text, while readable text can be reliably produced only in very limited areas such as fantasy football reporting. As such, the approaches we develop will catapult computational text understanding into a new era.
Sollen das schweizerische IPR Gesetz von 1987 und insbesondere sein Erstes Kapitel <Gemeinsame Bestimmungen> Art. 1 32 IPRG) revidiert werden?
Year: 2015

Since more than 25 years, the Swiss Code on Private International Law (CPIL) is in force. Meanwhile, the legislation of all states has undergone rapid developments. These significant changes, and in particular the harmonization of the private international law as well as the international law on civil procedure in the European Union give rise to consider a revision of the CPIL (see part A) The author puts forward a specific proposal of an modification of the Common Provisions of the CPIL (i.e. Articles 1 32 CPIL) In particular, this proposal relates to methodical problems as well as new suggestions for improving the international coordination of different jurisdictions (see part B)
Atlas based automatic planning and 3D 2D fluoroscopic guidance in pelvic trauma surgery.
Venue: Physics in medicine and biology
Year: 2019

Percutaneous screw fixation in pelvic trauma surgery is a challenging procedure that often requires long fluoroscopic exposure times and trial and error insertion attempts along narrow bone corridors of the pelvis. We report a method to automatically plan surgical trajectories using preoperative CT and assist device placement by augmenting the fluoroscopic scene with planned trajectories. A pelvic shape atlas was formed from 40 CT images and used to construct a statistical shape model (SSM) Each member of the atlas included expert definition of volumetric regions representing safe trajectory within bone corridors for fixating 10 common fracture patterns. Patient specific planning is obtained by mapping the SSM to the (un segmented) patient CT via active shape model (ASM) registration and free form deformation (FFD) and the resulting transformation is used to transfer the atlas trajectory volumes to the patient CT. Fluoroscopic images acquired during K wire placement are in turn augmented with projection of the planned trajectories via 3D 2D registration. Registration performance was evaluated via leave one out cross validation over the 40 member atlas, computing the root mean square error (RMSE) in pelvic surface alignment (volumetric registration error) the positive predicted value (PPV) of volumetric trajectories within bone corridors (safety of the automatically planned trajectories) and the distance between trajectories within the planned volume and the bone cortex (absence of breach) A cadaver study was conducted in which K wires were placed under fluoroscopic guidance to validate 3D 2D registration accuracy and evaluate the potential utility of augmented fluoroscopy with planned trajectories. The leave one out cross validation achieved surface RMSE of 2.2 0.3 mm after ASM registration and 1.8 0.2 mm after FFD refinement. Automatically determined surgical plans conformed within bone corridors with PPV 90% and centerline trajectory within 3 5 mm of the bone cortex. 3D 2D registration in the cadaver study achieved 0.3 0.8 mm accuracy (in plane translation) and <4deg accuracy (in plane rotation) Fluoroscopic images augmented with planning data exhibited >90% conformance of volumetric planning data overlay within bone, and all centerline trajectories were within safe corridors. The approach yields a method for both automatic planning of pelvic fracture fixation and augmentation of fluoroscopy for improved surgical precision and safety. The method does not require segmentation of the patient CT, operates without additional hardware (e.g. tracking systems) and is consistent with common workflow in fluoroscopically guided procedures. The approach has the potential to reduce operating time and radiation dose by minimizing trial and error attempts in percutaneous screw placement.
Design and analysis of roller conveyor and fixture
Year: 2016

ARTICLE INFO Roller conveyor for diesel engine assembly line is a effective technique for numbering engine blocks using laser machine. Main objective of roller conveyor for diesel engine assembly line is to modernize the manual technique. By using this technique, the roller conveyor for diesel engine assembly line we can number the engine parts automatically and computerized by using laser with it. This technique is time saving over the conventional technique. Manually printing numbers and verification on engine blocks is time consuming process. This process includes manual printing and inspection which leads to increase the lean time of operation as well as manual efforts. This project presents design of automatic conveyor system which contains design of roller, fixture. It proposes a new approach for fixture configuration design for a family of diesel engine block with technique are using laser as a printing elements which print engine serial number by using roller conveyor assembled in a single reconfigurable line. The problem formulated as a constrained design by considering frame of roller conveyor, roller, fixture with pins, The result using this technique is time saving over the conventional technique. Main conclusion of roller conveyor for diesel engine assembly line is to modernize the manual technique. The aim of this research is to help these numbering of engine block with using laser machine by totally computerized process. The problem formulated as a constrained design by considering frame of roller conveyor, roller, and fixture with pins used to solve the design of machine problem and established the total layout of the diesel engine assembly line. Keywords roller, fixture, engine block, automatic conveyor system, laser printing machine. Article History Received :18 th November 2015 Received in revised form
Chapter 3 High Efficiency Video Coding (HEVC) for Next Generation Video Applications
Year: 2014

The recent emergence of high resolution video content, such as high definition and ultra high definition, together with an increasingly broad range of content types has demanded highly efficient solutions for video coding. This chapter provides an overview of the new coding tools adopted in the emerging video coding standard, High Efficiency Video Coding (HEVC) In particular, the coding units, prediction units, and transform units are discussed and their effect on the encoding of the new content types is evaluated. All experiments are based on the HEVC test model. The results show that HEVC has halved the bit rate over the predecessor video coding standard, H.264/AVC, while maintaining the same video quality. The results also confirm the efficiency of the newly proposed tools in compressing the emerging next generation video content.
Guided Reinforcement Learning via Sequence Learning
Venue: ICANN
Year: 2020

Applications of Reinforcement Learning (RL) suffer from high sample complexity due to sparse reward signals and inadequate exploration. Novelty Search (NS) guides as an auxiliary task, in this regard to encourage exploration towards unseen behaviors. However, NS suffers from critical drawbacks concerning scalability and generalizability since they are based off instance learning. Addressing these challenges, we previously proposed a generic approach using unsupervised learning to learn representations of agent behaviors and use reconstruction losses as novelty scores. However, it considered only fixed length sequences and did not utilize sequential information of behaviors. Therefore, we here extend this approach by using sequential auto encoders to incorporate sequential dependencies. Experimental results on benchmark tasks show that this sequence learning aids exploration outperforming previous novelty search methods.
Examining the effects of study abroad on L 2 Chinese development among
Year: 2017

This study tracked ten third year English students learning Mandarin Chinese as a second language (L2) at a UK university, to examine changes in L2 Mandarin during an eight month period spent studying abroad (SA) We used three writing tasks and four speaking tasks as measures of writing and speaking proficiency, to assess total output, grammatical accuracy, lexical development, pronunciation and fluency, repeated before and after SA in China. Overall mean oral proficiency scores improved significantly (p .05) especially speech rate (p .01) supporting the claim that SA favours fluency development (Freed et al. 2004) although the measures highlighted difficulties in clarifying precisely how to assess oral proficiency. Written proficiency showed fewer marked improvements: only one writing test (an untimed short essay) significantly improved in length (p .05) and increased complex grammar (use of de relative clause morphemes, p .001) A sub group (n=7) provided quantitative data on L2 Mandarin use at different times during SA, showing clear individual differences, highlighting the value of capturing details of students' experiences during SA (Regan et al. 2009) We also note the lack of standardised linguistically informed measures for tracking development in L2 Mandarin (Freed et al. 2004; Pallotti 2009; De Jong et al. 2012) Further research is therefore much needed to identify systematic linguistic development in L2 Mandarin, and also to bridge theory and practice in L2 Mandarin language teaching to clarify the interconnecting factors that affect L2 Mandarin language development. We gratefully acknowledge the support of Newcastle University (HASS Faculty Board) for funding this research, also Linda Cheng of the School of Modern Languages for collecting the data, and Dr Alex Ho Cheong Leung of Northumbria University and Dr Chi Wai Lee of Newcastle University for assistance with data analysis. We are also most grateful to colleagues from Newcastle University and to this journal's reviewers, for their support, advice and comments.
Early life exposure to EDCs: role in childhood obesity and neurodevelopment
Venue: Nature Reviews Endocrinology
Year: 2017

Endocrine disrupting chemicals (EDCs) might increase the risk of childhood diseases by disrupting hormone mediated processes that are critical for growth and development during gestation, infancy and childhood. The fetus, infant and child might have enhanced sensitivity to environmental stressors such as EDCs due to their rapid development and increased exposure to some EDCs as a consequence of development specific behaviour, anatomy and physiology. In this Review, I discuss epidemiological studies examining the relationship between early life exposure to bisphenol A (BPA) phthalates, triclosan and perfluoroalkyl substances (PFAS) with childhood neurobehavioural disorders and obesity. The available epidemiological evidence suggest that prenatal exposure to several of these ubiquitous EDCs is associated with adverse neurobehaviour (BPA and phthalates) and excess adiposity or increased risk of obesity and/or overweight (PFAS) Quantifying the effects of EDC mixtures, improving EDC exposure assessment, reducing bias from confounding, identifying periods of heightened vulnerability and elucidating the presence and nature of sexually dimorphic EDC effects would enable stronger inferences to be made from epidemiological studies than currently possible. Ultimately, improved estimates of the causal effects of EDC exposures on child health could help identify susceptible subpopulations and lead to public health interventions to reduce these exposures.
SESF Fuse: An Unsupervised Deep Model for Multi Focus Image Fusion
Venue: Neural Comput. Appl.
Year: 2021

In this work, we propose a novel unsupervised deep learning model to address multi focus image fusion problem. First, we train an encoder decoder network in unsupervised manner to acquire deep feature of input images. And then we utilize these features and spatial frequency to measure activity level and decision map. Finally, we apply some consistency verification methods to adjust the decision map and draw out fused result. The key point behind of proposed method is that only the objects within the depth of field (DOF) have sharp appearance in the photograph while other objects are likely to be blurred. In contrast to previous works, our method analyzes sharp appearance in deep feature instead of original image. Experimental results demonstrate that the proposed method achieves the state of art fusion performance compared to existing 16 fusion methods in objective and subjective assessment.
Demystifying Time Series Momentum Strategies: Volatility Estimators, Trading Rules and Pairwise Correlations
Year: 2017

Motivated by studies of the impact of frictions on asset prices, we examine the effect of key components of time series momentum strategies on their turnover and performance from 1984 until 2013. We show that more efficient volatility estimation and price trend detection can significantly reduce portfolio turnover by more than one third, without causing a statistically significant performance penalty. We shed light on the post 2008 underperformance of the strategy by linking it to the increased level of asset co movement. We propose a novel implementation of the strategy that incorporates the pairwise signed correlations by means of a dynamic leverage mechanism. The correlation adjusted variant outperforms the naive implementation of the strategy and the outperformance is more pronounced in the post 2008 period. Finally, using a transaction costs model for futures based strategies that separates costs into roll over and rebalancing costs, we show that our findings remain robust to the inclusion of transaction costs.
Between Investigator and Suspect: The Role of the Working Alliance in Investigative Interviewing
Year: 2014

The importance of building rapport when interviewing witnesses and suspects is emphasized in many interview models developed in Europe as well as in the United States. The construct of rapport shows a number of similarities with the construct of the working alliance, which is already extensively examined in therapeutic settings. Despite the important predictive role found in therapy, the role of the working alliance in investigative interviewing was not addressed in police research. The present study aims at looking into possible benefits of using the theoretical framework and the operationalisation of the working alliance in order to gain insights into the dynamics of investigative interviewing. It is examined to what extent the working alliance contributes to satisfaction with the interview from both investigators and interviewees in actual interviews. It also considers which factors are important to the working alliance. Besides therapeutic factors the study also explores significant factors from investigative interviewing literature on building rapport. Self report questionnaires completed by investigators and interviewees show the mediating role of the working alliance between empathy, interview style, clarity of the interview and interview satisfaction. The research findings will also be discussed in the light of interview training and follow up. More in particular, experiences with building rapport from interview training will be presented as well as experiences from a supervision project on suspect interviewing. Finally, in light of the recent Salduz case law and the subsequent introduction of legal advice in Europe, police officers' views on building rapport with suspects and lawyers are touched upon.
Modeling humidity and stress dependent subgrade soils in flexible pavements
Year: 2020

This study aimed to develop a finite element model to simulate the flexible pavement structure by considering the nonlinear characteristics of subgrade soils which are related to humidity and stress. First, an analytical model was proposed and proven to quantify the effect of the humidity and stress on the resilient modulus of subgrade soils. Second, a UMAT was programmed to characterize nonlinear moisture and stress sensitive relationship of subgrade soils. Then, the humidity field values of subgrade were calculated by GEOSTUDIO and verified by field measurement. Meanwhile, the humidity field values were imported into ABAQUS through MATLAB. Finally, the UMAT was implemented in the finite element model of flexible pavement structures. The finite element simulation indicated that the distribution of moisture content of subgrade significantly affects the resilient modulus distribution of subgrade and critical response of pavement structures. Resilient modulus of subgrade soils in the vicinity of load area are significantly larger than those far away the load area. The surface deflection, the tensile stress at the bottom of inorganic binder base, and the compressive strains on the top of subgrade increase greatly with the initial humidity field condition to the equilibrium humidity field condition.
Point clouds registration based on the point to plane approach for orthogonal transformations
Year: 2018

The most popular algorithm for aligning of 3D point data is the Iterative Closest Point (ICP) This paper proposes a new algorithm for orthogonal registration of point clouds based on the point to plane ICP algorithm for affine transformation. At each iterative step of the algorithm, an approximation of the closed form solution for the orthogonal transformation is derived.
Higher education institutions and the use of online instruction and online tools and resources during the COVID 19 outbreak An online review of selected U.S. and SA's universities
Year: 2020

This online quasi scoping review set out to review how 64 U.S. and 21 South African universities pivoted to online course delivery and used online tools and resources as one of their collective responses to continue their teaching and learning activities during the COVID 19 pandemic. The review was conducted on five online search engines, six online databases and two online social networking sites. Generally, all of the U.S and South African universities investigated transitioned to online classes and temporarily relinquished their in person, campus based classes. Additionally, all of these universities transiently opted for a strong form of social distancing and embraced emergency remote online pedagogy. Moreover, four online delivery typologies, with their attendant multiple permutations, emerged from these two sets of universities. Furthermore, when both U.S. and South African universities temporarily pivoted their classes to online delivery during the COVID 19 pandemic outbreak, they embraced and adopted certain online tools and resources more than the others. For instance, pertaining to 64 U.S. universities, Zoom was the most preferred tool, with video conferencing and LMS platforms emerging as the two dominant platforms. As regards the 21 South African universities, Blackboard (Collaborate) emerged as the most preferred tool, with both LMS and video conferencing platforms emerging as the two dominant platforms. Overall, Zoom, Blackboard (Collaborate) and institutional LMSes were the three common tools to which both sets of universities pivoted during the pandemic. Finally, the two sets of universities only embraced low tech versions of the 4IR technologies such as video conferencing, social media technologies, and cloud computing.
Agro cadenas Vigilancia tecnologica de los tres principales productos agricolas base de alimentacion y cultivados en cada uno de los paises, objeto de estudio
Year: 2017

El presente trabajo hace un estudio de las diferentes cadenas agroindustriales que hay en los cinco paises de la alianza del pacifico los cuales son, Argentina, chile, Colombia, Peru y Mexico e identifica los productos de mayor importancia y productividad en cada una de estos. Por otro lado mediante la investigacion se identifica que los principales problemas sociales son la hambruna, la desnutricion, poblaciones con problemas cardiovasculares, el desplazamiento de zonas rurales, la desercion y la sobrepoblacion en las grandes ciudades. Por lo anterior se hace una propuesta logistica que abarque los problemas detectados en cada una de las cadenas para poder integral todos los eslabones y poder dar solucion a los problemas sociales detectados.