nils-herrmann/clean_scirepeval huggingface dataset:
Multi scale salient object detection using graph ranking and global local saliency refinement
Venue: Signal Process. Image Commun.

We propose an algorithm for salient object detection (SOD) based on multi scale graph ranking and iterative local global object refinement. Starting from a set of multi scale image decompositions using superpixels, we propose an objective function which is optimized on a multi layer graph structure to diffuse saliency from image borders to salient objects. This step aims at roughly estimating the location and extent of salient objects in the image. We then enhance the object saliency through an iterative process employing random forests and local boundary refinement using color, texture and edge information. We also use a feature weighting scheme to ensure optimal object/background discrimination. Our algorithm yields very accurate saliency maps for SOD while maintaining a reasonable computational time. Experiments on several standard datasets have shown that our approach outperforms several recent methods dealing with SOD. HighlightsSalient object detection using multi layered graph ranking.Local global saliency refinement using objectness measure and random forests.Region and boundary information for salient object detection.Feature relevance for object/background discrimination.
Organic Dye Graphene Hybrid Structures with Spectral Color Selectivity

This study characterizes a hybrid structure formed between graphene and organic dye molecules for use in photodetectors with spectral color selectivity. Rhodamine based organic dye molecules with red, green, or blue light absorption profiles are deposited onto a graphene surface by dip coating. UV vis absorption spectroscopy, charge transport measurements, and density functional theory based calculations reveal that the photoresponses of the dye graphene hybrid films are governed by the light absorption of the dye molecules and also by the photo excited charge transfer induced photocurrent gain. The hybrid films respond only to photons with an energy exceeding the band gap of the immobilized dye. Dye Graphene charge transfer is affected by the distance and direction of the dipole moment between the two layers. The resulting hybrid films exhibit spectral color selectivities with responsivities of 103 A W 1 and specific detectivities of 1010 Jones. This study demonstrates the successful operation of photodetectors with a full color optical bandwidth using hybrid graphene structures coated with a mixture of dyes. The strategy of building a simple hybrid photodetector can further offer many opportunities to be also tuned for other optical functionalities using a variety of commercially available dye molecules.
High detectivity printed organic photodiodes for large area flexible imagers
Venue: 2016 IEEE International Electron Devices Meeting (IEDM)

The recent increase in utilization of image sensors and significant development in the field of wearable and disposable sensors not only demands a decrease in photodiode fabrication costs, but also requires new functional abilities such as operating at extremely low light intensities, narrowband and broadband spectral selectivity, lightweight and mechanical flexibility. Today, most of these demands cannot be fulfilled by conventional workhorse silicon photodetectors without a significant amount of processing steps to achieve heterogeneous integration. The chemical tunability, mechanical properties and printable processing of organic materials make them promising candidates for fabrication of low cost, highly scalable and flexible organic photodiodes (OPDs) In addition, the large area scalability of printing techniques is beneficial for photodiodes since the signal tonoise ratio (SNR) at a given light intensity, increases with detector size. Since the SNR depends on multiple parameters, such as the external quantum efficiency (EQE) the dark current density, sampling bandwidth and photoactive area, it significantly complicates the comparison of photodetectors. For this reason a useful figure of merit to consider is specific detectivity. This paper shows that state of the art all printed, flexible OPDs with average specific detectivities as high as 3.45x1013 cm Hz 0.5*W 1 can be printed using industrially scalable techniques (i.e. blade coating and screen printing) by controlling charge selectivity of organic electrodes. In addition to the high specific detectivity needed to resolve low light intensity, these OPDs are able to sustain high reverse biases. High reverse biases are used to maximize the capacity of the photodiode to capacitatively store photogenerated charge, which is essential for increasing the dynamic range of image sensors. Through optimization and characterization of the properties of each printed layer, device yield is maximized with minimal variability over large areas. The performance of all printed photodiodes achieved here becomes comparable to silicon photodiodes used in image sensors, which have a specific detectivity of approximately 6 7 x 1013 cm Hz 0.5*W 1. These results show that along with advantages such as inexpensive fabrication and mechanical flexibility, all printed OPDs can have performance competitive with their Si counterparts.
Access to primary health care services for Indigenous peoples: A framework synthesis
Venue: International Journal for Equity in Health

BackgroundIndigenous peoples often find it difficult to access appropriate mainstream primary health care services. Securing access to primary health care services requires more than just services that are situated within easy reach. Ensuring the accessibility of health care for Indigenous peoples who are often faced with a vast array of additional barriers including experiences of discrimination and racism, can be complex. This framework synthesis aimed to identify issues that hindered Indigenous peoples from accessing primary health care and then explore how, if at all, these were addressed by Indigenous health care services.MethodsTo be included in this framework synthesis papers must have presented findings focused on access to (factors relating to Indigenous peoples, their families and their communities) or accessibility of Indigenous primary health care services. Findings were imported into NVivo and a framework analysis undertaken whereby findings were coded to and then thematically analysed using Levesque and colleague's accessibility framework.ResultsIssues relating to the cultural and social determinants of health such as unemployment and low levels of education influenced whether Indigenous patients, their families and communities were able to access health care. Indigenous health care services addressed these issues in a number of ways including the provision of transport to and from appointments, a reduction in health care costs for people on low incomes and close consultation with, if not the direct involvement of, community members in identifying and then addressing health care needs.ConclusionsIndigenous health care services appear to be best placed to overcome both the social and cultural determinants of health which hamper Indigenous peoples from accessing health care. Findings of this synthesis also suggest that Levesque and colleague's accessibility framework should be broadened to include factors related to the health care system such as funding.
A survey on human activity recognition from videos
Venue: 2016 International Conference on Information Communication and Embedded Systems (ICICES)

Understanding the activities of human from videos is demanding task in Computer Vision. Identifying the actions being accomplished by the human in the video sequence automatically and tagging their actions is the prime functionality of intelligent video systems. The goal of activity recognition is to identify the actions and objectives of one or more objects from a series of examination on the action of object and their environmental condition. The major applications of Human Activity Recognition varies from Content based Video Analytics, Robotics, Human Computer Interaction, Human fall detection, Ambient Intelligence, Visual Surveillance, Video Indexing etc. This paper collectively summarizes and deciphers the various methodologies, challenges and issues of Human Activity Recognition systems. Variants of Human Activity Recognition systems such as Human Object Interactions and Human Human Interactions are also explored. Various benchmarking datasets and their properties are being explored. The Experimental Evaluation of various papers are analyzed efficiently with the various performance metrics like Precision, Recall, and Accuracy.
Anisotropic diffusion map based spectral embedding for 3D CAD model retrieval
Venue: 2016 IEEE 14th International Conference on Industrial Informatics (INDIN)

In the product life cycle, design reuse can save cost and improve existing products conveniently in most new product development. To retrieve similar models from big database, most search algorithms convert CAD model into a shape descriptor and compute the similarity two models according to a descriptor metric. This paper proposes a new 3D shape matching approach by matching the coordinates directly. It is based on diffusion maps which integrate the rand walk and graph spectral analysis to extract shape features embedded in low dimensional spaces and then they are used to form coordinations for non linear alignment of different models. These coordinates could capture multi scale properties of the 3D geometric features and has shown good robustness to noise. The results also have shown better performance compared to the celebrated Eigenmap approach in the 3D model retrieval.
A practical guide to hydrogels for cell culture
Venue: Nature Methods

There is growing appreciation of the role that the extracellular environment plays in regulating cell behavior. Mechanical, structural, and compositional cues, either alone or in concert, can drastically alter cell function. Biomaterials, and particularly hydrogels, have been developed and implemented to present defined subsets of these cues for investigating countless cellular processes as a means of understanding morphogenesis, aging, and disease. Although most scientists concede that standard cell culture materials (tissue culture plastic and glass) do a poor job of recapitulating native cellular milieus, there is currently a knowledge barrier for many researchers in regard to the application of hydrogels for cell culture. Here, we introduce hydrogels to those who may be unfamiliar with procedures to culture and study cells with these systems, with a particular focus on commercially available hydrogels.
In vitro models of the blood brain barrier: An overview of commonly used brain endothelial cell culture models and guidelines for their use
Venue: Journal of cerebral blood flow and metabolism official journal of the International Society of Cerebral Blood Flow and Metabolism

The endothelial cells lining the brain capillaries separate the blood from the brain parenchyma. The endothelial monolayer of the brain capillaries serves both as a crucial interface for exchange of nutrients, gases, and metabolites between blood and brain, and as a barrier for neurotoxic components of plasma and xenobiotics. This "blood brain barrier" function is a major hindrance for drug uptake into the brain parenchyma. Cell culture models, based on either primary cells or immortalized brain endothelial cell lines, have been developed, in order to facilitate in vitro studies of drug transport to the brain and studies of endothelial cell biology and pathophysiology. In this review, we aim to give an overview of established in vitro blood brain barrier models with a focus on their validation regarding a set of well established blood brain barrier characteristics. As an ideal cell culture model of the blood brain barrier is yet to be developed, we also aim to give an overview of the advantages and drawbacks of the different models described.
Let there be color!
Venue: ACM Trans. Graph.

We present a novel technique to automatically colorize grayscale images that combines both global priors and local image features. Based on Convolutional Neural Networks, our deep network features a fusion layer that allows us to elegantly merge local information dependent on small image patches with global priors computed using the entire image. The entire framework, including the global and local priors as well as the colorization model, is trained in an end to end fashion. Furthermore, our architecture can process images of any resolution, unlike most existing approaches based on CNN. We leverage an existing large scale scene classification database to train our model, exploiting the class labels of the dataset to more efficiently and discriminatively learn the global priors. We validate our approach with a user study and compare against the state of the art, where we show significant improvements. Furthermore, we demonstrate our method extensively on many different types of images, including black and white photography from over a hundred years ago, and show realistic colorizations.
FACTORS AFFECTING THE TEACHING AND LEARNING OF MUSIC AS A CURRICULUM SUBJECT IN RURAL SECONDARY SCHOOLS: A STUDY OF SECONDARY SCHOOLS IN MOUNT DARWIN DISTRICT OF ZIMBABWE

There have been policy reforms in education that are aimed at improving the quality of education. Such reforms include the expansion of the curriculum in order to incorporate practical subjects in the school curriculum. These practical subjects include Home Economics, Computers, Music, Carpentry, Building, Technical Graphics, Fashion and Fabrics, Woodwork, Art, and Aviation among others. The philosophy behind the advocacy for practical subjects is guided by the need to prepare students for real life situations. The school is seen as a platform to equip students with skills that are transferable to real life situations. The Presidential Commission of Inquiry into Education and Training (1999:445) made recommendations on the need for a "new education structure that vocationalises education to familiarize pupils with vocational and technical skills at Basic Education level and lay the foundation for specialization at post basic level" To support this idea there was need for the re orientation of people to appreciate practical subjects and labour. It has been more that fifteen years since the adoption of the recommendations of the commission. There are concerns as to the factors that have hindered the successful implementation of a vocationalised school curriculum in Zimbabwe. The study focuses on the factors that affect the teaching and learning of Music as a curriculum subject at ten secondary schools in Mt. Darwin district of Zimbabwe. The purposively selected sample comprised of five school heads from schools offering Music, five school heads from schools not offering Music, five Music teachers and one Music inspector in the district, thus providing a total of sixteen respondents. The study used the qualitative methodology and the case study design. The study came up with the conclusions that lack of trained teachers, lack of resources, lack of innovation, negative attitudes by school heads and education inspectors were some of the factors that negatively impacted on the teaching and learning of Music as a curriculum subject in the selected schools. The study also concluded that Music was one of the non examinable subjects at O"level and as such was not given the importance that was given to examinable subjects. The study recommends that Music as a subject be examined at O"level for teachers, school heads and pupils to take it seriously. Schools and communities have to be innovative enough to produce their own Music equipment and other related resources. Workshops by the Ministry of Primary and Secondary Education have to be held to change people"s attitudes as a curriculum subject. Vol 3, Issue 1 PP. 55 66
An Improved Arabic Handwritten Recognition System using Deep Support Vector Machines
Venue: Int. J. Multim. Data Eng. Manag.

Deep learning algorithms, as a machine learning algorithms developed in recent years, have been successfully applied in various domains of computer vision, such as face recognition, object detection and image classification. These Deep algorithms aim at extracting a high representation of the data via multi layers in a deep hierarchical structure. However, to the authors' knowledge, these deep learning approaches have not been extensively studied to recognize Arabic Handwritten Script AHS. In this paper, they present a deep learning model based on Support Vector Machine SVM named Deep SVM. This model has an inherent ability to select data points crucial to classify good generalization capabilities. The deep SVM is constructed by a stack of SVMs allowing to extracting/learning automatically features from the raw images and to perform classification as well. The Multi class SVM with an RBF kernel, as non linear discriminative features for classification, was chosen and tested on Handwritten Arabic Characters Database HACDB. Simulation results show the effectiveness of the proposed model.
Optimizing Resource Utilization of a Data Center
Venue: IEEE Communications Surveys Tutorials

To provision IT solutions with reduced operating expenses, many businesses are moving their IT infrastructures into public data centers or are starting to build their own private data centers. Data centers can provide flexible resource provisioning in order to accommodate the workload demand. In this paper, we present a comprehensive survey of most relevant research activities on resource management of data centers that aim to optimize the resource utilization. We first describe the resource overprovisioning problem in current data centers. Then, we summarize two important components in the resource management platform and present the benefit of accurately predicting the workload in resource management. Afterwards, we classify existing resource management in a data center into three categories: 1) virtual machine based, 2) physical machine based, and 3) application based resource management mechanisms. We discuss the performance degradation for implementing these three kinds of resource management in a heterogeneous data center. Finally, we present three important issues arose in the data center resource management and some potential approaches to address the issues. This paper presents a timely survey on resource management in a data center, and provides a comprehensive reference for further research in this field.
Reinforcement learning for resource provisioning in the vehicular cloud
Venue: IEEE Wireless Communications

This article presents a concise view of vehicular clouds that incorporates various vehicular cloud models that have been proposed to date. Essentially, they all extend the traditional cloud and its utility computing functionalities across the entities in the vehicular ad hoc network. These entities include fixed roadside units, onboard units embedded in the vehicle, and personal smart devices of drivers and passengers. Cumulatively, these entities yield abundant processing, storage, sensing, and communication resources. However, vehicular clouds require novel resource provisioning techniques that can address the intrinsic challenges of dynamic demands for the resources and stringent QoS requirements. In this article, we show the benefits of reinforcement learning based techniques for resource provisioning in the vehicular cloud. The learning techniques can perceive long term benefits and are ideal for minimizing the overhead of resource provisioning for vehicular clouds.
A New Structure Activity Relationship (SAR) Model for Predicting Drug Induced Liver Injury, Based on Statistical and Expert Based Structural Alerts
Venue: Front. Pharmacol.

The prompt identification of chemical molecules with potential effects on liver may help in drug discovery and in raising the levels of protection for human health. Besides in vitro approaches, computational methods in toxicology are drawing attention. We built a structure activity relationship (SAR) model for evaluating hepatotoxicity. After compiling a data set of 950 compounds using data from the literature, we randomly split it into training (80% and test sets (20% We also compiled an external validation set (101 compounds) for evaluating the performance of the model. To extract structural alerts (SAs) related to hepatotoxicity and non hepatotoxicity we used SARpy, a statistical application that automatically identifies and extracts chemical fragments related to a specific activity. We also applied the chemical grouping approach for manually identifying other SAs. We calculated accuracy, specificity, sensitivity and Matthews correlation coefficient (MCC) on the training, test and external validation sets. Considering the complexity of the endpoint, the model performed well. In the training, test and external validation sets the accuracy was respectively 81, 63, and 68% specificity 89, 33, and 33% sensitivity 93, 88, and 80% and MCC 0.63, 0.27, and 0.13. Since it is preferable to overestimate hepatotoxicity rather than not to recognize unsafe compounds, the model's architecture followed a conservative approach. As it was built using human data, it might be applied without any need for extrapolation from other species. This model will be freely available in the VEGA platform.
El cuerpo en Internet. La fotografia en las paginas web de citas utilizadas por chilenos. The body on the Internet. The photography on dating web sites used by Chileans. pp.62 84

El presente articulo analiza el rol de la fotografia en las paginas web de encuentros. En la primera parte de este estudio se contrasta el imaginario de la des corporizacion de Internet con las actuales investigaciones sobre las interacciones digitales. Luego, en la segunda parte, se explicita la metodologia utilizada en esta investigacion. En el tercer apartado, resultados, se senala que en las paginas de citas la fotografia es el cuerpo del otro en la Red; esta vendra a cumplir el rol del cuerpo en las interacciones de tipo sexual emocionales, explicitando el atractivo de las personas y propiciando (o no) la atraccion. Finalmente, en las conclusiones, se afirma que se debe profundizar en la relacion entre el propio cuerpo y el cuerpo digital, ademas se revela la importancia del imaginario del cuerpo en la investigacion actual en ciencias sociales.
An Evaluation of Effective Communication Skills Coursebook

In Communicative Language Teaching situation, role of material is not only important but also inevitable. In the traditional context of English teaching textbooks are considered the main source of materials. This paper will provide an evaluation of Effective Communication Skills (ECS) coursebook that has been introduced as a pilot project implemented in 2011 by the Ministry of Higher Education, Malaysia. For the current study, data has been collected on the basis of materials study, and questionnaires. The qualitative analysis has been conducted with a total sample of around 214 students, and 3 instructors. The results show that in spite of some shortcomings, there is a general satisfaction about this textbook as it is exclusively produced by the local experts for the tertiary level. The study concludes with suggestions and recommendations for the improvement of the Effective Communication Skills  Coursebook evaluation, communicative English, Pilot Project,