nils-herrmann/clean_scirepeval huggingface dataset:
Data Curation at Scale: The Data Tamer System

Data curation is the act of discovering a data source(s) of interest, cleaning and transforming the new data, semantically integrating it with other local data sources, and deduplicating the resulting composite. There has been much research on the various components of curation (especially data integration and deduplication). However, there has been little work on collecting all of the curation components into an integrated end-to-end system. In addition, most of the previous work will not scale to the sizes of problems that we are finding in the field. For example, one web aggregator requires the curation of 80,000 URLs and a second biotech company has the problem of curating 8000 spreadsheets. At this scale, data curation cannot be a manual (human) effort, but must entail machine learning approaches with a human assist only when necessary.  It expects as input a sequence of data sources to add to a composite being constructed over time. A new source is subjected to machine learning algorithms to perform attribute identification, grouping of attributes into tables, transformation of incoming data and deduplication. When necessary, a human can be asked for guidance. Also, Data Tamer includes a data visualization component so a human can examine a data source at will and specify manual transformations. We have run Data Tamer on three real world enterprise curation problems, and it has been shown to lower curation cost by about 90%, relative to the currently deployed production software. This article is published under a Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/), which permits distribution and reproduction in any medium as well allowing derivative works, provided that you attribute the original work to the author(s) and CIDR 2013. 6th Biennial Conference on Innovative Data Systems Research (CIDR ’13) January 6-9, 2013, Asilomar, California, USA.
AckSeer: a repository and search engine for automatically extracted acknowledgments from digital libraries

Acknowledgments are widely used in scientific articles to express gratitude and credit collaborators. Despite suggestions that indexing acknowledgments automatically will give interesting insights, there is currently, to the best of our knowledge, no such system to track acknowledgments and index them. In this paper we introduce AckSeer, a search engine and a repository for automatically extracted acknowledgments in digital libraries. AckSeer is a fully automated system that scans items in digital libraries including conference papers, journals, and books extracting acknowledgment sections and identifying acknowledged entities mentioned within. We describe the architecture of AckSeer and discuss the extraction algorithms that achieve a F1 measure above 83%. We use multiple Named Entity Recognition (NER) tools and propose a method for merging the outcome from different recognizers. The resulting entities are stored in a database then made searchable by adding them to the AckSeer index along with the metadata of the containing paper/book.
 We build AckSeer on top of the documents in CiteSeerx digital library yielding more than 500,000 acknowledgments and more than 4 million mentioned entities.
A study on Half bridge LLC resonant converter for battery charger on board

In recent years, having the advantages of being small, low in cost and high in efficiency, Half bridge (HB) LLC resonant converter for power density and high efficiency is increasingly required in the battery charge application. The HB LLC resonant converters have been used for reducing the current and voltage stress and switching losses of the components. However, it is not suited for wide range of the voltage and output voltage due to the uneven voltage and current component's stresses. The HB LLC resonant for battery charge of on board is presented in this paper. The theoretical results are verified through an experimental prototype for battery charger on board.
Understanding adolescence as a period of social–affective engagement and goal flexibility

Research has demonstrated that extensive structural and functional brain development continues throughout adolescence. A popular notion emerging from this work states that a relative immaturity in frontal cortical neural systems could explain adolescents' high rates of risk-taking, substance use and other dangerous behaviours. However, developmental neuroimaging studies do not support a simple model of frontal cortical immaturity. Rather, growing evidence points to the importance of changes in social and affective processing, which begin around the onset of puberty, as crucial to understanding these adolescent vulnerabilities. These changes in social–affective processing also may confer some adaptive advantages, such as greater flexibility in adjusting one's intrinsic motivations and goal priorities amidst changing social contexts in adolescence.
Aggregating Continuous Word Embeddings for Information Retrieval

While words in documents are generally treated as discrete entities, they can be embedded in a Euclidean space which reflects an a priori notion of similarity between them. In such a case, a text document can be viewed as a bag-ofembedded-words (BoEW): a set of realvalued vectors. We propose a novel document representation based on such continuous word embeddings. It consists in non-linearly mapping the wordembeddings in a higher-dimensional space and in aggregating them into a documentlevel representation. We report retrieval and clustering experiments in the case where the word-embeddings are computed from standard topic models showing significant improvements with respect to the original topic models.
Self-oscillating half bridge series resonant converter controlled by a small saturable core

A self-oscillating half bridge series resonant converter control is proposed. The turn-on and turn-off of the switch are zero-voltage-switching with resonant transition. A saturable core is used to achieve the self-excitation and the zero-voltage-switched resonant transition. Although the system of the self-oscillating command presents a simple working safety, it presents the necessity of determination of the magnetic parameters of the saturable core. To consider the regulation of the output current in an ulterior stage, we propose to inject a continuous current through the saturable core and to determine the influence thereafter on the command. Theoretical analysis and experimental result on the proposed converter are provided.
Estimation of respiratory waveform using an accelerometer

The cardiorespiratory signal is a fundamental vital sign to assess a person's health. Additionally, the cardio-respiratory signal gives a great deal of information to healthcare providers wishing to monitor healthy individuals. This paper proposes a method to detect the respiratory waveform from an accelerometer strapped onto the chest. A system was designed and several experiments were conducted on volunteers. The acquisition is performed in different status: normal, apnea, deep breathing and also in different postures: vertical (sitting, standing) or horizontal (lying down). This method could therefore be suitable for automatic identification of some respiratory malfunction, for example during the obstructive apnea.
WYSIWYM - Integrated visualization, exploration and authoring of semantically enriched un-structured content

The Semantic Web and Linked Data gained traction in the last years. However, the majority of information still is contained in unstructured documents. This can also not be expected to change, since text, images and videos are the natural way how humans interact with information. Semantic structuring on the other hand enables the (semi-)automatic integration, repurposing, rearrangement of information. NLP technologies and formalisms for the integrated representation of unstructured and semantic content (such as RDFa and Microdata) aim at bridging this semantic gap. However, in order for humans to truly benefit from this integration, we need ways to author, visualize and explore unstructured and semantically enriched content in an integrated manner. In this paper, we present the WYSIWYM (What  Mean) concept, which addresses this issue and formalizes the binding between semantic representation models and UI elements for authoring, visualizing and exploration. With RDFaCE and Pharmer we present and evaluate two complementary showcases implementing the WYSIWYM concept for different application domains.
Digital Twin : Mitigating Unpredictable , Undesirable Emergent Behavior in Complex Systems ( Excerpt )

While the terminology has changed over time, the basic concept of the Digital Twin model has remained fairly stable from its inception in 2001. It is based on the idea that a digital informational construct about a physical system could be created as an entity on its own. This digital information would be a “twin” of the information that was embedded within the physical system itself and be linked with that physical system through the entire lifecycle of the system.
A new mechanism of nervous system plasticity: activity-dependent myelination

The synapse is the focus of experimental research and theory on the cellular mechanisms of nervous system plasticity and learning, but recent research is expanding the consideration of plasticity into new mechanisms beyond the synapse, notably including the possibility that conduction velocity could be modifiable through changes in myelin to optimize the timing of information transmission through neural circuits. This concept emerges from a confluence of brain imaging that reveals changes in white matter in the human brain during learning, together with cellular studies showing that the process of myelination can be influenced by action potential firing in axons. This Opinion article summarizes the new research on activity-dependent myelination, explores the possible implications of these studies and outlines the potential for new research.
Metal contacts on physical vapor deposited monolayer MoS2.

The understanding of the metal and transition metal dichalcogenide (TMD) interface is critical for future electronic device technologies based on this new class of two-dimensional semiconductors. Here, we investigate the initial growth of nanometer-thick Pd, Au, and Ag films on monolayer MoS2. Distinct growth morphologies are identified by atomic force microscopy: Pd forms a uniform contact, Au clusters into nanostructures, and Ag forms randomly distributed islands on MoS2. The formation of these different interfaces is elucidated by large-scale spin-polarized density functional theory calculations. Using Raman spectroscopy, we find that the interface homogeneity shows characteristic Raman shifts in E2g(1) and A1g modes. Interestingly, we show that insertion of graphene between metal and MoS2 can effectively decouple MoS2 from the perturbations imparted by metal contacts (e.g., strain), while maintaining an effective electronic coupling between metal contact and MoS2, suggesting that graphene can act as a conductive buffer layer in TMD electronics.
Integrating product data from websites offering microdata markup

Large numbers of websites have started to markup their content using standards such as Microdata, Microformats, and RDFa. The marked-up content elements comprise descriptions of people, organizations, places, events, products, ratings, and reviews. This development has accelerated in last years as major search engines such as Google, Bing and Yahoo! use the markup to improve their search results. Embedding semantic markup facilitates identifying content elements on webpages. However, the markup is mostly not as fine-grained as desirable for applications that aim to integrate data from large numbers of websites. This paper discusses the challenges that arise in the task of integrating descriptions of electronic products from several thousand e-shops that offer Microdata markup. We present a solution for each step of the data integration process including Microdata extraction, product classification, product feature extraction, identity resolution, and data fusion. We evaluate our processing pipeline using 1.9 million product offers from 9240 e-shops which we extracted from the Common Crawl 2012, a large public Web corpus.
Direction-of-arrival estimation using radiation power pattern with an ESPAR antenna

An approach for estimating direction-of-arrival (DoA) based on power output cross-correlation and antenna pattern diversity is proposed for a reactively steerable antenna. An "estimator condition" is proposed, from which the most appropriate pattern shape is derived. Computer simulations with directive beam patterns obtained from an electronically steerable parasitic array radiator antenna model are conducted to illustrate the theory and to inspect the method performance with respect to the "estimator condition". The simulation results confirm that a good estimation can be expected when suitable directive patterns are chosen. In addition, to verify performance, experiments on estimating DoA are conducted in an anechoic chamber for several angles of arrival and different scenarios of antenna adjustable reactance values. The results show that the proposed method can provide high-precision DoA estimation.
3DNN: 3D Nearest Neighbor

In this paper, we describe a data-driven approach to leverage repositories of 3D models for scene understanding. Our ability to relate what we see in an image to a large collection of 3D models allows us to transfer information from these models, creating a rich understanding of the scene. We develop a framework for auto-calibrating a camera, rendering 3D models from the viewpoint an image was taken, and computing a similarity measure between each 3D model and an input image. We demonstrate this data-driven approach in the context of geometry estimation and show the ability to find the identities, poses and styles of objects in a scene. The true benefit of 3DNN compared to a traditional 2D nearest-neighbor approach is that by generalizing across viewpoints, we free ourselves from the need to have training examples captured from all possible viewpoints. Thus, we are able to achieve comparable results using orders of magnitude less data, and recognize objects from never-before-seen viewpoints. In this work, we describe the 3DNN algorithm and rigorously evaluate its performance for the tasks of geometry estimation and object detection/segmentation, as well as two novel applications: affordance estimation and photorealistic object insertion.
Organizational Culture and Marketing : Defining the Research Agenda

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Automated leukemia detection using hausdorff dimension in blood microscopic images

A cute lymphocytic leukemia (ALL) is a malignant disease characterized by the accumulation of lymphoblast in the bone marrow. An improved scheme for ALL detection in blood microscopic images is presented here. In this study features i.e. hausdorff dimension and contour signature are employed to classify a lymphocytic cell in the blood image into normal lymphocyte or lymphoblast (blasts). In addition shape and texture features are also extracted for better classification. Initial segmentation is done using K-means clustering which segregates leukocytes or white blood cells (WBC) from other blood components i.e. erythrocytes and platelets. The results of K-means are used for evaluating individual cell shape, texture and other features for final detection of leukemia. Fractal features i.e. hausdorff dimension is implemented for measuring perimeter roughness and hence classifying a lymphocytic cell nucleus. A total of 108 blood smear images were considered for feature extraction and final performance evaluation is validated with the results of a hematologist.
Report on the Development of the Advanced Encryption Standard (AES)

In 1997, the National Institute of Standards and Technology (NIST) initiated a process to select a symmetric-key encryption algorithm to be used to protect sensitive (unclassified) Federal information in furtherance of NIST's statutory responsibilities. In 1998, NIST announced the acceptance of 15 candidate algorithms and requested the assistance of the cryptographic research community in analyzing the candidates. This analysis included an initial examination of the security and efficiency characteristics for each algorithm. NIST reviewed the results of this preliminary research and selected MARS, RC™, Rijndael, Serpent and Twofish as finalists. Having reviewed further public analysis of the finalists, NIST has decided to propose Rijndael as the Advanced Encryption Standard (AES). The research results and rationale for this selection are documented in this report.
Effects of user similarity in social media

There are many settings in which users of a social media application provide evaluations of one another. In a variety of domains, mechanisms for evaluation allow one user to say whether he or she trusts another user, or likes the content they produced, or wants to confer special levels of authority or responsibility on them. Earlier work has studied how the relative status between two users - that is, their comparative levels of status in the group - affects the types of evaluations that one user gives to another.
 Here we study how similarity in the characteristics of two users can affect the evaluation one user provides of another. We analyze this issue under a range of natural similarity measures, showing how the interaction of similarity and status can produce strong effects. Among other consequences, we find that evaluations are less status-driven when users are more similar to each other; and we use effects based on similarity to provide a plausible mechanism for a complex phenomenon observed in studies of user evaluation, that evaluations are particularly low among users of roughly equal status.
 Our work has natural applications to the prediction of evaluation outcomes based on user characteristics, and the use of similarity information makes possible a novel application that we introduce here - to estimate the chance of a favorable overall evaluation from a group knowing only the attributes of the group's members, but not their expressed opinions.
Analog/RF Solutions Enabling Compact Full-Duplex Radios

In-band full-duplex sets challenging requirements for wireless communication radios, in particular their capability to prevent receiver sensitivity degradation due to self-interference (transmit signals leaking into its own receiver). Previously published self-interference rejection designs require bulky components and/or antenna structures. This paper addresses this form-factor issue. First, compact radio transceiver feasibility bottlenecks are identified analytically, and tradeoff equations in function of link budget parameters are presented. These derivations indicate that the main bottlenecks can be resolved by increasing the isolation in analog/RF. Therefore, two design ideas are proposed, which provide attractive analog/RF-isolation and allow integration in compact radios. The first design proposal targets compact radio devices, such as small-cell base stations and tablet computers, and combines a dual-port polarized antenna with a self-tunable cancellation circuit. The second design proposal targets even more compact radio devices such as smartphones and sensor network nodes. This design builds on a tunable electrical balance isolator/duplexer in combination with a single-port miniature antenna. The electrical balance circuit can be implemented for scaled CMOS technology, facilitating low cost and dense integration.
Connecting Generative Adversarial Networks and Actor-Critic Methods

Both generative adversarial networks (GAN) in unsupervised learning and actorcritic methods in reinforcement learning (RL) have gained a reputation for being difficult to optimize. Practitioners in both fields have amassed a large number of strategies to mitigate these instabilities and improve training. Here we show that GANs can be viewed as actor-critic methods in an environment where the actor cannot affect the reward. We review the strategies for stabilizing training for each class of models, both those that generalize between the two and those that are particular to that model. We also review a number of extensions to GANs and RL algorithms with even more complicated information flow. We hope that by highlighting this formal connection we will encourage both GAN and RL communities to develop general, scalable, and stable algorithms for multilevel optimization with deep networks, and to draw inspiration across communities.
The clinician's guide to autism.

On the basis of the most recent epidemiologic research, Autism Spectrum Disorder (ASD) affects approximately 1% to 2% of all children. (1)(2) On the basis of some research evidence and consensus, the Modified Checklist for Autism in Toddlers isa helpful tool to screen for autism in children between ages 16 and 30 months. (11) The Diagnostic Statistical Manual of Mental Disorders, Fourth Edition, changes to a 2-symptom category from a 3-symptom category in the Diagnostic Statistical Manual of Mental Disorders, Fifth Edition(DSM-5): deficits in social communication and social interaction are combined with repetitive and restrictive behaviors, and more criteria are required per category. The DSM-5 subsumes all the previous diagnoses of autism (classic autism, Asperger syndrome, and pervasive developmental disorder not otherwise specified) into just ASDs. On the basis of moderate to strong evidence, the use of applied behavioral analysis and intensive behavioral programs has a beneficial effect on language and the core deficits of children with autism. (16) Currently, minimal or no evidence is available to endorse most complementary and alternative medicine therapies used by parents, such as dietary changes (gluten free), vitamins, chelation, and hyperbaric oxygen. (16) On the basis of consensus and some studies, pediatric clinicians should improve their capacity to provide children with ASD a medical home that is accessible and provides family-centered, continuous, comprehensive and coordinated, compassionate, and culturally sensitive care.
Transformer-isolated gate drive design for SiC JFET phase-leg module

In order to take full advantage of the SiC devices' high-temperature and high-frequency capabilities, a transformer isolated gate driver is designed for the SiC JFET phase leg module to achieve a fast switching speed of 26V/ns and a small cross-talking voltage of 4.2V in a 650V and 5A inductive load test. Transformer isolated gate drive circuits suitable for high-temperature applications are compared with respect to different criteria. Based on the comparison, an improved edge triggered gate drive topology is proposed. Then, using the proposed gate drive topology, special issues in the phase-leg gate drive design are discussed. Several strategies are implemented to improve the phase-leg gate drive performance and alleviate the cross-talking issue. Simulation and experimental results are given for verification purposes.