nils-herrmann/clean_scirepeval huggingface dataset:
Is Faster R CNN Doing Well for Pedestrian Detection?
Venue: ECCV

Detecting pedestrian has been arguably addressed as a special topic beyond general object detection. Although recent deep learning object detectors such as Fast/Faster R CNN have shown excellent performance for general object detection, they have limited success for detecting pedestrian, and previous leading pedestrian detectors were in general hybrid methods combining hand crafted and deep convolutional features. In this paper, we investigate issues involving Faster R CNN for pedestrian detection. We discover that the Region Proposal Network (RPN) in Faster R CNN indeed performs well as a stand alone pedestrian detector, but surprisingly, the downstream classifier degrades the results. We argue that two reasons account for the unsatisfactory accuracy: (i) insufficient resolution of feature maps for handling small instances, and (ii) lack of any bootstrapping strategy for mining hard negative examples. Driven by these observations, we propose a very simple but effective baseline for pedestrian detection, using an RPN followed by boosted forests on shared, high resolution convolutional feature maps. We comprehensively evaluate this method on several benchmarks (Caltech, INRIA, ETH, and KITTI) presenting competitive accuracy and good speed. Code will be made publicly available.
Supply chain collaboration: A Game theoretic approach to profit allocation

This paper aims to develop a theoretical framework for profit allocation, as a mechanism for aligning incentives, in collaborative supply chains.  The issue of profit distribution is approached from a game theoretic perspective. We use the nucleolus concept. The framework is illustrated through a numerical example based on the Beer Game scenario.  The nucleolus offers a powerful perspective to tackle this problem, as it takes into consideration the bargaining power of the different echelons. We show that this framework outperforms classical alternatives.  The allocation of the overall supply chain profit is analyzed from a static perspective. Considering the dynamic nature of the problem would be an interesting next step.  We provide evidence of drawbacks derived from classical solutions to the profit allocation problem. Real world collaborative supply chains need of robust mechanisms like the one tackled in this work to align incentives from the various actors.  Adopting an efficient collaborative solution is a major challenge for supply chains, since it is a wide and complex process that requires an appropriate scheme. Within this framework, profit allocation is essential.
New comb shaped ionomers based on hydrophobic poly(aryl ether ketone) backbone bearing hydrophilic high concentration sulfonated micro cluster

A new difluoride monomer containing an aliphatic bridge between 2,6 difluoropheyl and hexaphenylbenzene is designed and synthesized. Then, a series of novel hexa sulfonated poly(aryl ether ketone)s (HS PAEK x) containing an aliphatic spacer between hydrophobic poly(aryl ether ketone)s main chain and hydrophilic sulfonated hexaphenylbenzene are prepared from the new difluoride monomer with 4,4' (hexafluoroisopropylidene) diphenol and 4,4' difluorobenzophenone by nucleophilic polycondensation, and subsequent postsulfonation using chlorosulfonic acid. All the polymers give tough, flexible, and transparent membranes by solvent casting. The membranes with comparatively low ion exchange capacity (IEC) values ranging from 0.87 to 1.42 meq g 1, achieve good mechanical properties, suitable proton conductivity (111 mS cm 1) compared with Nafion 117 at 80 degC, and excellent dimensional stability (the highest swelling ratio of length is 9.2% at 80 degC) Furthermore, compared with the previous reported polymers with similar main chain, such as the polymer with pendant sulfoalkyl groups and hollow aromatic hexa sulfonated polymer, the HS PAEK x exhibit higher proton conductivities at similar IEC level, which attributes to the specific molecular structure and improving morphology. Overall, all of the above mentioned results indicate that the HS PAEK x membranes are good candidate materials for proton exchange membranes (PEMs)
Preparation and evaluation of crosslinked sulfonated polyphosphazene with poly(aryloxy cyclotriphosphazene) for proton exchange membrane

Several crosslinked proton exchange membranes with high proton conductivities and low methanol permeability coefficients were prepared, based on the sulfonated poly[(4 fluorophenoxy)(phenoxy) phosphazene (SPFPP) and newly synthesized water soluble sulfonated poly(cyclophosphazene) (SPCP) containing clustered flexible pendant sulfonic acids. The structure of SPCP was characterized by fourier transform infrared spectroscopy (FTIR) and 1 H NMR spectra. The membranes showed moderate proton conductivities and much lower methanol permeability coefficients when compared to Nafion 117. Transmission electron microscopy (TEM) results indicated the well defined phase separation between the locally and densely sulfonated units and hydrophobic units, which induced efficient proton conduction. In comparison with SPFPP membrane, the proton conductivities, oxidative stabilities and mechanical properties of crosslinked membranes remarkably were improved. The selectivity values of all the crosslinked membranes were also much higher than that of Nafion 117 (0.74x10 5 S* s/cm 3 These results suggested that the cSPFPP/SPCP membranes were promising candidate materials for proton exchange membrane in direct methanol fuel cells.
Physical and chemical effects of acoustic cavitation in selected ultrasonic cleaning applications.
Venue: Ultrasonics sonochemistry

Acoustic cavitation in a liquid medium generates several physical and chemical effects. The oscillation and collapse of cavitation bubbles, driven at low ultrasonic frequencies (e.g. 20 kHz) can generate strong shear forces, microjets, microstreaming and shockwaves. Such strong physical forces have been used in cleaning and flux improvement of ultrafiltration processes. These physical effects have also been shown to deactivate pathogens. The efficiency of deactivation of pathogens is not only dependent on ultrasonic experimental parameters, but also on the properties of the pathogens themselves. Bacteria with thick shell wall are found to be resistant to ultrasonic deactivation process. Some evidence does suggest that the chemical effects (radicals) of acoustic cavitation are also effective in deactivating pathogens. Another aspect of cleaning, namely, purification of water contaminated with organic and inorganic pollutants, has also been discussed in detail. Strong oxidising agents produced within acoustic cavitation bubbles could be used to degrade organic pollutants and convert toxic inorganic pollutants to less harmful substances. The effect of ultrasonic frequency and surface activity of solutes on the sonochemical degradation efficiency has also been discussed in this overview.
Reasoning in Expressive Godel Description Logics
Venue: Description Logics

Fuzzy description logics (FDLs) are knowledge representation formalisms capable of dealing with imprecise knowledge by allowing intermediate membership degrees in the interpretation of concepts and roles. One option for dealing with these intermediate degrees is to use the so called Godel semantics, under which conjunction is interpreted by the minimum of the degrees. Despite its apparent simplicity, developing reasoning techniques for expressive FDLs under this semantics is a hard task. In this paper, we illustrate two algorithms for deciding consistency in (sublogics of) SROIQ under Godel semantics.
Deep ADMM Net for Compressive Sensing MRI
Venue: NIPS

Compressive Sensing (CS) is an effective approach for fast Magnetic Resonance Imaging (MRI) It aims at reconstructing MR image from a small number of under sampled data in k space, and accelerating the data acquisition in MRI. To improve the current MRI system in reconstruction accuracy and computational speed, in this paper, we propose a novel deep architecture, dubbed ADMM Net. ADMM Net is defined over a data flow graph, which is derived from the iterative procedures in Alternating Direction Method of Multipliers (ADMM) algorithm for optimizing a CS based MRI model. In the training phase, all parameters of the net, e.g. image transforms, shrinkage functions, etc. are discriminatively trained end to end using L BFGS algorithm. In the testing phase, it has computational overhead similar to ADMM but uses optimized parameters learned from the training data for CS based reconstruction task. Experiments on MRI image reconstruction under different sampling ratios in k space demonstrate that it significantly improves the baseline ADMM algorithm and achieves high reconstruction accuracies with fast computational speed.
Financial Openness and Total Factor Productivity Growth

[enter Abstract Body]Using a panel data set of 89 countries from 1995 through 2014, the effects of financial openness, both in general and by direction of foreign capital flows, on changes in total factor productivity growth in the economy are estimated. An overall positive relationship is found between financial openness and total factor productivity growth. The positive effect of financial openness is driven by relaxation of capital controls on foreign inflows. and on the level of domestic capital market development, with the majority of the benefits falling to countries whose credit markets are less developed. For countries with developed capital markets, we document that at a certain level of development that financial controls on capital inflows and outflows can have positive effects on total factor productivity growth at differing stages of development.
Chrono nutrition: a review of current evidence from observational studies on global trends in time of day of energy intake and its association with obesity
Venue: Proceedings of the Nutrition Society

The importance of the circadian rhythm in regulating human food intake behaviour and metabolism has long been recognised. However, little is known as to how energy intake is distributed over the day in existing populations, and its potential association with obesity. The present review describes global trends in time of day of energy intake in the general population based on data from cross sectional surveys and longitudinal cohorts. Evidence of the association between time of day of energy intake and obesity is also summarised. Overall, there were a limited number of cross sectional surveys and longitudinal cohorts that provided data on time of day of energy intake. In the identified studies, a wide variation in time of day of energy intake was observed, with patterns of energy distribution varying greatly by country and geographical area. In relation to obesity, eight cross sectional surveys and two longitudinal cohorts were identified. The association between time of day of energy intake and obesity varied widely, with several studies reporting a positive link between evening energy intake and obesity. In conclusion, the current review summarises global trends in time of day of energy intake. The large variations across countries and global regions could have important implications to health, emphasising the need to understand the socio environmental factors guiding such differences in eating patterns. Evidence of the association between time of day of energy intake and BMI also varied. Further larger scale collaborations between various countries and regions are needed to sum data from existing surveys and cohorts, and guide our understanding of the role of chrono nutrition in health.
Building Discretionary Authority in a Teacher Education Program

This article reports on a teacher education program's use of teaching rounds and action research to build teacher candidates' discretionary authority, the confidence to make their own teaching decisions rather than model their classroom choices solely on a mentor teacher's classroom pedagogy. Discretionary authority is promoted by many contemporary business and government organizations as a central feature of the transformational leadership that Burns long ago contrasted with transactional leadership. The impact of candidates' discretionary authority is validated by the top marks awarded by their principals and mentors on the NC Department of Public Instructions IHE Performance Report. Their independence of mind is further corroborated by the important accomplishments they achieved in their first 5 years of teaching.
A Robust Method to Generate a Consistent Time Series From DMSP/OLS Nighttime Light Data
Venue: IEEE Transactions on Geoscience and Remote Sensing

The long time series of nighttime light (NTL) data collected by DMSP/OLS sensors provides a unique and valuable resource to study changes in human activities. However, its full time series potential has not been fully explored, mainly due to inconsistencies in the temporal signal. Previous studies have tried to resolve this issue in order to generate a consistent NTL time series. However, due to geographic limitations with the algorithms, these approaches cannot generate a coherent NTL time series globally. The purpose of this study is to develop a methodology to create a consistent NTL time series that can be applied globally. Our method is based on a novel sampling strategy to identify pseudoinvariant features. We select data points along a ridgeline the densest part of a density plot generated between the reference image and the target image and then use those data points to derive calibration models to minimize inconsistencies in the NTL time series. Results show that the algorithm successfully calibrates DMSP/OLS annual composites and generates a consistent NTL time series. Evaluation of the results shows that the calibrated NTL time series significantly reduces the differences between two images within the same year and increases the correlations between the NTL time series and gross domestic product as well as with energy consumption, and outperforms the Elvidge et al. (2014) method. The methodology is simple, robust, and easy to implement. The quality enhanced NTL time series can be used in a myriad of applications that require a consistent data set over time.
Curve separation for line graphs in scholarly documents
Venue: 2016 IEEE/ACM Joint Conference on Digital Libraries (JCDL)

Line graphs are abundant in scholarly papers. They are usually generated from a data table and that data can not be accessed. One important step in an automated data extraction pipeline is the curve separation problem: segmenting the pixels into separate curves. Previous work in this domain has focused on raster graphics extracted from scholarly PDFs, whereas most scholarly plots are embedded as vector graphics. We report a system to extract these plots as SVG images and show how that can improve both the accuracy (90% and the scalability (5 8 seconds) of the curve separation problem.
A study of transparency behaviour of domes in Islamic mosque with emphasis on the notion of the spiritual lighting

This research studies the concept of transparency behaviour of domes in Islamic mosque, with emphasis on the notion of the spiritual lighting.The topic of this study is important not only because it allows for a better understanding of the different types and purposes of these domes, but also because through calculating the veiling and revealing factor of each type, one can regenerate the use of dome in the architecture.In the analysis of quantitative factors, the quality of light in space and how to show the influence of Iranian architecture, structural elements play a prominent role.In the other words:Phrases related architectural lighting control within architecture elements that define spatial quality, are to identify and understand the value and meaning of the concept of light, began to attention to the importance of light in architecture. The research method was used for which it is the consecutive combination explanation. Here, in the first stage, the quantitative data collected and analyzed, then in the second stage qualitative data collected and analyzed. Finally, both qualitative and quantitative analyzes are interpreted together. The present study uses field measurements that the instrument used to collect the data, cameras and imaging and to take accurate of brightness quantitative information, and the digital photometer and simple devices were used, and its information has been gathered from documents and fieldwork. In this way the fieldwork for photometry to factors of physical and quantitative impact on the quality of light were studied and after identifying the physical factors affecting the quality of lighting the domes, the defining quality components transparency in relation to the characteristics of quality discussed and with quality components explaining to evaluate the degree of transparency of the domes of mosques reviewed, were studied. After examining different examples, seven residential mosque (Taj al Mulk dome Isfahan Jame Mosque, Sheikh Lotfollah Mosque of Isfahan, Blue Mosque of Tabriz, Barsian mosque, Imam 113 Received: 22/2/2016  18/10/2016 D ow nl oa de d fr om w w w .iu st .a c. ir at 1 6: 31 IR D T o n W ed ne sd ay A pr il 28 th 2 02 1
Procrastination is linked with insomnia symptoms: The moderating role of morningness eveningness

Procrastination may negatively impact professional advancement and general well being, yet to our knowledge, the relationship with sleep quality has not been investigated. Poor sleep impacts physical and emotional health, underscoring the importance of addressing this potential outcome. It was hypothesized that procrastination will be associated with subjective sleep difficulties, an association mediated by ruminative cognitions. 598 respondents (154 men: Mage 25.6 3.8; 444 women Mage 24.8 3.3) completed online questionnaires regarding procrastination, sleep disturbances, rumination, emotional state, and chronotype. A structural equation model approach was used for model testing. Results demonstrated that procrastination positively correlated with sleep disturbance, a link moderated by chronotype, such that self identified Morning Types reported lower procrastination, fewer sleep disturbances, and the two measures did not correlate. Among Intermediate and Evening Types the relationship between procrastination and sleep was mediated by rumination and negative mood. These findings suggest that addressing the impact on sleep should be one of the targets of interventions for treating procrastination.
Rethinking the sustainability of Israel's irrigation practices in the Drylands.
Venue: Water research

Broad utilization of drip irrigation technologies in Israel has contributed to the 1600 percent increase in the value of produce grown by local farmers over the past sixty five years. The recycling of 86% of Israeli sewage now provides 50% of the country's irrigation water and is the second, idiosyncratic component in Israel's strategy to overcome water scarcity and maintain agriculture in a dryland region. The sustainability of these two practices is evaluated in light of decades of experience and ongoing research by the local scientific community. The review confirms the dramatic advantages of drip irrigation over time, relative to flood, furrow and sprinkler irrigation and its significance as a central component in agricultural production, especially under arid conditions. In contrast, empirical findings increasingly report damage to soil and to crops from salinization caused by irrigation with effluents. To be environmentally and agriculturally sustainable over time, wastewater reuse programs must ensure extremely high quality treated effluents and ultimately seek the desalinization of recycled sewage.
Unsupervised local deep feature for image recognition
Venue: Inf. Sci.

ULDF is proposed to make better use of autoencoder for image recognition. It is performed on local patches rather than whole images, which helps to scale the algorithm to realistic sized images.Owning to the combination with BoW, it is more robust to local translation.The short codes transformed from vectorized patches using autoencoder have good low dimensional property. This property makes it consume less time and less memory while clustering. Moreover, short codes make it possible to use finer level spatial pyramid, such as 2 x 2 and 4 x 4.It only requires an efficient linear SVM classifier and obtains state of the art classify performance on MNIST. Unsupervised feature learning is an important problem in computer vision and machine learning. Various unsupervised learning methods, e.g. PCA, KMeans, autoencoder, have been applied for visual recognition tasks. Especially, autoencoder has superior image recognition performance, which is usually used as a global feature extractor. To make better use of autoencoder for image recognition, we propose unsupervised local deep feature (ULDF) We collect patches from training images and use autoencoder to transform vectorized patches into short codes. Then these codes are encoded using Fisher Vector with spatial pyramid. Image recognition with ULDF only requires an efficient linear SVM classifier. Finally, we perform multi scale voting to achieve more accurate classification performance. In the experiments, we evaluate ULDF on the handwritten digit recognition task and the shape classification task, and show that it achieves highly competitive performance comparing to the state of the art image recognition methods. The results suggest that the proposed local deep feature is superior than traditional global autoencoder.
Critical factors towards analysing teachers' presence in on line learning communities
Venue: Internet High. Educ.

On line teacher communities constitute a very popular and dynamic field while they foster a new philosophy for professional development which is characterised as associative, constructivist, reflective, situated, collaborative, and connectivist. This paper reports on the design and the implementation of a learning community consisting of computer science teachers teaching in primary and secondary public schools (K 9) in Greece. The conceptual and the operational dimensions of the on line community design framework are presented in detail. The architecture of an integrated platform, developed to support the teacher community, as well as the tools and the features it incorporates are also outlined. Finally, we present the findings of a pilot study concerning teachers' presence within the community as well as their views and perceptions of community learning. The results provided supportive evidence of the effectiveness of the design framework and revealed important information with regard to critical indicators of teachers' learning presence within the community, i.e. members' participation, engagement, interaction and cohesion.