bluuebunny/crossref_metadata_2025 huggingface dataset:
Summary graphs for relational database schemas
Authors: Yang Xiaoyan , Procopiuc Cecilia M. , Srivastava Divesh
Published: June 2020

Increasingly complex databases need ever more sophisticated tools to help users understand their schemas and interact with the data. Existing tools fall short of either providing the "big picture," or of presenting useful connectivity information.

In this paper we define summary graphs, a novel approach for summarizing schemas. Given a set of user-specified query tables, the summary graph automatically computes the most relevant tables and joins
for that query set.
The output preserves the most informative join paths between the query tables, while meeting size constraints. In the process, we define a novel information-theoretic measure over join edges. Unlike most subgraph extraction work, we allow metaedges (i.e., edges in the transitive closure) to help reduce output complexity. We prove that the problem is NP-Hard, and solve it as an integer program. Our extensive experimental study shows that our method returns high-quality summaries under independent quality measures.
Linking temporal records
Authors: Li Pei , Dong Xin Luna , Maurino Andrea , Srivastava Divesh
Published: June 2020

Many data sets contain
temporal records
over a long period of time; each record is associated with a time stamp and describes some aspects of a real-world entity at that particular time (
e.g.
, author information in DBLP). In such cases, we often wish to identify records that describe the same entity over time and so be able to enable interesting longitudinal data analysis. However, existing record linkage techniques ignore the temporal information and can fall short for temporal data.

This paper studies linking temporal records. First, we apply
time decay
to capture the effect of elapsed time on entity value evolution. Second, instead of comparing each pair of records locally, we propose clustering methods that consider time order of the records and make global decisions. Experimental results show that our algorithms significantly outperform traditional linkage methods on various temporal data sets.
Optimizing and parallelizing ranked enumeration
Authors: Golenberg Konstantin , Kimelfeld Benny , Sagiv Yehoshua
Published: June 2020

Lawler-Murty's procedure is a general tool for designing algorithms for enumeration problems (i.e., problems that involve the production of a large set of answers in ranked order), which naturally arise in database management. Lawler-Murty's procedure is used in a variety of modern database applications; particularly in those related to keyword search over structured data. Essentially, this procedure enumerates by invoking a series of instances of an optimization problem (i.e., finding the best solution); solving the optimization problem is the only part that depends on the specific task at hand. The topic of optimizing and parallelizing Lawler-Murty's procedure is investigated. Naive parallelism can be carried out by concurrently solving independent instances of the optimization problem. This can be improved by printing the next answer, in the enumeration order, as soon as none of the concurrent instances can produce a better answer. However, this approach alone suffers from poor utilization of available threads. That leads to the idea of freezing an instance of the optimization problem. Interestingly, not only is freezing beneficial to the parallel execution of Lawler-Murty's, it also substantially reduces the running time of the serial execution. Additional improvements of the freezing technique are then developed to further enhance the utilization of threads, and they result in a significant overall speedup. The effectiveness of the proposed approach is demonstrated on keyword search over data graphs, wherein an extensive experimental study is described.
Where in the world is my data?
Authors: Kadambi Sudarshan , Chen Jianjun , Cooper Brian F. , Lomax David , Ramakrishnan Raghu , Silberstein Adam , Tam Erwin , Garcia-Molina Hector
Published: June 2020

Users of websites such as Facebook, Ebay and Yahoo! demand fast response times, and these sites replicate data across globally distributed datacenters to achieve this. However, it is not necessary to replicate all data to all locations: if a European user's record is never accessed in Asia, it does not make sense to pay the bandwidth and disk costs to maintain an Asian replica.

In this paper, we describe mechanisms for selectively replicating large-scale web databases on a record-by-record basis. We introduce a flexible constraint language to specify replication policy constraints. We then present an adaptive scheme for replicating data to where it is most frequently accessed, while respecting policy constraints and using minimal bookkeeping. Experiments using a modified version of our PNUTS system demonstrate our techniques work well.
Publishing set-valued data via differential privacy
Authors: Chen Rui , Mohammed Noman , Fung Benjamin C. M. , Desai Bipin C. , Xiong Li
Published: June 2020

Set-valued data provides enormous opportunities for various data mining tasks. In this paper, we study the problem of publishing set-valued data for data mining tasks under the rigorous differential privacy model. All existing data publishing methods for set-valued data are based on partition-based privacy models, for example
k
-anonymity, which are vulnerable to privacy attacks based on background knowledge. In contrast, differential privacy provides strong privacy guarantees independent of an adversary's background knowledge and computational power. Existing data publishing approaches for differential privacy, however, are not adequate in terms of both utility and scalability in the context of set-valued data due to its high dimensionality.

We demonstrate that set-valued data could be efficiently released under differential privacy with guaranteed utility with the help of context-free taxonomy trees. We propose a probabilistic top-down partitioning algorithm to generate a differentially private release, which scales linearly with the input data size. We also discuss the applicability of our idea to the context of relational data. We prove that our result is (∈, δ)-useful for the class of counting queries, the foundation of many data mining tasks. We show that our approach maintains high utility for counting queries and frequent itemset mining and scales to large datasets through extensive experiments on real-life set-valued datasets.
Scalable SPARQL querying of large RDF graphs
Authors: Huang Jiewen , Abadi Daniel J. , Ren Kun
Published: June 2020

The generation of RDF data has accelerated to the point where many data sets need to be partitioned across multiple machines in order to achieve reasonable performance when querying the data. Although tremendous progress has been made in the Semantic Web community for achieving high performance data management on a single node, current solutions that allow the data to be partitioned across multiple machines are highly inefficient. In this paper, we introduce a scalable RDF data management system that is up to three orders of magnitude more efficient than popular multi-node RDF data management systems. In so doing, we introduce techniques for (1) leveraging state-of-the-art single node RDF-store technology (2) partitioning the data across nodes in a manner that helps accelerate query processing through locality optimizations and (3) decomposing SPARQL queries into high performance fragments that take advantage of how data is partitioned in a cluster.
Tenzing a SQL implementation on the MapReduce framework
Authors: Chattopadhyay Biswapesh , Lin Liang , Liu Weiran , Mittal Sagar , Aragonda Prathyusha , Lychagina Vera , Kwon Younghee , Wong Michael
Published: June 2020

Tenzing is a query engine built on top of MapReduce [9] for ad hoc analysis of Google data. Tenzing supports a mostly complete SQL implementation (with several extensions) combined with several key characteristics such as heterogeneity, high performance, scalability, reliability, metadata awareness, low latency, support for columnar storage and structured data, and easy extensibility. Tenzing is currently used internally at Google by 1000+ employees and serves 10000+ queries per day over 1.5 petabytes of compressed data. In this paper, we describe the architecture and implementation of Tenzing, and present benchmarks of typical analytical queries.
GrouPeer
Authors: Kantere Verena , Bousounis Dimos , Sellis Timos
Published: June 2020

Sharing structured data in a PDMS is hard due to schema heterogeneity and peer autonomy. To overcome heterogeneity, peer databases employ mappings that partially match local information to that of their direct neighbors. Traditionally, a query is successively rewritten along the propagation path on each peer. This results in gradual query degradation and the inability to retrieve data pertinent to the original version, even from peers that store such data. This demonstration presents
GrouPeer
, a system that overcomes the query degradation problem and enables the dynamic clustering of the overlay according to the semantics of the peer data, utilizing normal query traffic. Peers are provided with a methodology that allows them to choose which rewritten version of a query to answer and discover remote information-rich sources. The demonstration illustrates the functionalities in the clustering mechanism of
GrouPeer
: approximate query rewriting, query similarity methodology, construction of new mappings, iterative learning process, employment of automatic schema matching, and proves the capability of the system to perform gradual semantic clustering and enable high quality answers to peer queries.
CerFix
Authors: Fan Wenfei , Li Jianzhong , Ma Shuai , Tang Nan , Yu Wenyuan
Published: June 2020

We present CerFix, a data cleaning system that finds
certain fixes
for tuples at the point of data entry,
i.e.
, fixes that are guaranteed correct. It is based on master data, editing rules and certain regions. Given some attributes of an input tuple that are validated (assured correct), editing rules tell us what other attributes to fix and how to correct them with master data. A certain region is a set of attributes that, if validated, warrant a certain fix for the entire tuple. We demonstrate the following facilities provided by CerFix: (1) a region finder to identify certain regions; (2) a data monitor to find certain fixes for input tuples, by guiding users to validate a minimal number of attributes; and (3) an auditing module to show what attributes are fixed and where the correct values come from.
HOMES
Authors: Vu Huy , Benedikt Michael
Published: June 2020

We describe a system that integrates querying and query transformation in a single higher-order query language. The system allows users to write queries that integrate and combine query transformations. The power of higher-order functions also allows one to succinctly write complex relational queries. Our demonstration shows the utility of the system, explains the implementation architecture on top of a relational DBMS, and explains optimizations that combine subquery caching techniques from relational databases with sharing detection schemes from functional programming.
Proactive detection and repair of data corruption
Authors: Borisov Nedyalko , Babu Shivnath
Published: June 2020

Occasional corruption of stored data is an unfortunate byproduct of the complexity of modern systems. Hardware errors, software bugs, and mistakes by human administrators can corrupt important sources of data. The dominant practice to deal with data corruption today involves administrators writing ad hoc scripts that run data-integrity tests at the application, database, file-system, and storage levels. This manual approach, apart from being tedious and error-prone, provides no understanding of the potential system unavailability and data loss if a corruption were to occur. We have developed the
Amulet
system that can verify the correctness of stored data proactively and continuously. This demonstration focuses on the uses of Amulet and its technical innovations: (i) a declarative language for administrators to specify their objectives regarding the detection and repair of data corruption; (ii) optimization and execution algorithms to meet the administrator's objectives robustly and with least cost using pay-as-you-go cloud resources; and (iii) timely notification when corruption is detected, allowing proactive repair of corruption before it impacts users and applications.
++Spicy
Authors: Marnette Bruno , Mecca Giansalvatore , Papotti Paolo , Raunich Salvatore , Santoro Donatello
Published: June 2020

Recent results in schema-mapping and data-exchange research may be considered the starting point for a new generation of systems, capable of dealing with a significantly larger class of applications. In this paper we demonstrate the first of these second-generation systems, called ++Spicy. We introduce a number of scenarios from a variety of data management tasks, such as data fusion, data cleaning, and ETL, and show how, based on the system, schema mappings and data exchange techniques can be very effectively applied to these contexts. We compare ++Spicy to the previous generations of tools, to show that this is much-needed advancement in the field.
Jordan centralizer maps on trivial extension algebras
Authors: Bahmani Mohammad Ali , Ghomanjani Fateme , Shateyi Stanford
Published: June 2020

The structure of Jordan centralizer maps is investigated on trivial extension algebras. One may obtain some conditions under which a Jordan centralizer map on a trivial extension algebra is a centralizer map. As an application, we characterize the Jordan centralizer map on a triangular algebra.
Freiheit unter Bedingungen der Zeit? Schellings neuer Zeitbegriff im Nachgang zurFreiheitsschrift
Authors: Buchheim Thomas
Published: June 2020

The concept of human freedom developed by Schelling in the Freiheitsschrift (1809) prompted him to explore a new concept of time in his Weltalter project. Schelling proposes the ‘generic subjectivity of time’: Time must be understood not as a precondition of dynamism, but rather as an effect of dynamic agency. The articulation of time into its moments, ‘presence’, ‘past’, and ‘future’, is realized through the dynamic contributions (motion, causality, and action) of every single causally involved being. Schelling’s concept thus fundamentally differs from Kant’s concept of time. For Kant, change and dynamism are located in the sensible world, whereas time (as well as space) is the subjective form of our sensible intuition. As such, time must be seen as a precondition of change and dynamism for Kant.
microRNA-491-5p protects against atherosclerosis by targeting matrix metallopeptidase-9
Authors: He Zhonghan , Wang Yayun , He Qin , Chen Manhua
Published: June 2020

Abnormal proliferation and migration of vascular smooth muscle cells (VSMCs) are critical processes that are involved in atherosclerosis. The aim of this study was to explore the role of microRNA-491-5p (miR-491-5p) in the progression of atherosclerosis by regulating the growth and migration of VSMCs. In this study, we showed that the expression of miR-491-5p was downregulated in the atherosclerotic plaque tissues and plasma samples of the patients with atherosclerosis. The bioinformatic analysis and dual-luciferase reporter assay identified that matrix metallopeptidase-9 (MMP-9) was a target gene of miR-491-5p. The results showed a significant upregulation of MMP-9 in the atherosclerotic plaque tissues and plasma samples. Subsequently, the results also showed that downregulation of miR-491-5p significantly promoted the proliferation and migration of VSMCs and inhibited the apoptosis in VSMCs. Furthermore, we detected the effects of miR-491-5p mimic on the growth and migration of VSMCs, and the results illustrated that miR-491-5p mimic could inhibit the proliferation and migration of VSMCs and promote the apoptosis of VSMCs. Notably, MMP-9 plasmid could reverse all the effects of miR-491-5p mimic on VSMCs. Collectively, our study provides the first evidence that miR-491-5p inhibited the growth and migration of VSMCs by targeting MMP-9, which might provide new biomarkers and potential therapeutic targets for atherosclerosis treatment.
Nordkoreas Cyber-Krieg Strategie: Kontinuität und Wandel
Authors: Raska Michael
Published: June 2020

Nach Auffassung Pjöngjangs ist die koreanische Halbinsel Schauplatz eines eingefrorenen geopolitischen Konflikts zwischen Großmächten. Die Vereinigten Staaten betreiben dabei eine aus Sicht des nordkoreanischen Regimes „feindselige Politik“, die dessen Überleben gefährde und den politischen Gestaltungsraum sowie das wirtschaftliche Entwicklungspotenzial des Landes untergrabe. Während Südkorea und den Vereinigten Staaten vor allem das wachsende Kernwaffenarsenal und die zunehmenden ballistischen Raketenfähigkeiten Nordkoreas Sorgen bereiten, sollte das Bündnis auch der stetigen Weiterentwicklung der nordkoreanischen – offensiven und defensiven – Cyberfähigkeiten mehr Aufmerksamkeit schenken. Nordkorea strebt nach strategischer Überlegenheit, indem es kostengünstige, asymmetrische militärische Fähigkeiten einschließlich Cyberstrategien entwickelt, um Informationen zu sammeln, seine Rivalen unter Druck zu setzen, andere finanziell zu erpressen und auf anderem Wege Einfluss in einer Weise auszuüben, gegen die herkömmliche Abschreckungs- und militärische Gegenmaßnahmen wirkungslos sind. Seoul und Washington benötigen eine umfassende militärische Einsatzstrategie gegen das gesamte Spektrum potenzieller nordkoreanischer Provokationen, während europäische Staaten ihre Cybersicherheitsstrategien verstärken müssen, um die zunehmenden globalen Cyberoperationen Nordkoreas verlässlich aufzuspüren und abzuwehren.
Androstenedione changes steroidogenic activity of SGBS cells
Authors: Ernst Jana , Gert Katharina , Kraus Frank Bernhard , Rolle-Kampczyk Ulrike Elisabeth , Wabitsch Martin , Dehghani Faramarz , Schaedlich Kristina
Published: June 2020

The rapid increase of obesity during the last decades and its future prospects are alarming. Besides the general discussed causes of obesity, the ‘Developmental Origins of Health and Disease’ (DOHaD) hypothesis received more attention in recent years. This hypothesis postulates an adverse influence during early development that programs the unborn child for metabolic dysfunctions later in life. Childhood obesity – an as much increasing problem – can be predisposed by maternal overweight and diabetes. Both, obesity and hyperinsulinemia are major causes of female hyperandrogenemia. As predicted by the DOHaD hypothesis and shown in animal models, developmental androgen excess can lead to metabolic abnormalities in offspring. In this study, we investigated, if androgen exposure adversely affects the adipogenic differentiation of preadipocytes and the endocrine function of adult adipocytes. The human SGBS preadipocyte model was used to affirm the de novo biosynthesis of steroid hormones under normal adipogenesis conditions. Normal adipogenesis was paralleled by an increase of corticosteroids and androgens, whereas estrogen remained at a steady level. Treatment with androstenedione had no effect on SGBS proliferation and differentiation, but adult adipocytes exhibited a significant higher accumulation of triglycerides. Progesterone (up to 2-fold), testosterone (up to 38-fold) and cortisone (up to 1.4-fold) – but not cortisol – were elevated by androstenedione administration in adult adipocytes. Estrogen was not altered. Data suggest that androgen does not negatively influence adipogenic differentiation, but steroidogenic function of SGBS adipocytes.
Dialectología y toponimia en la obra de Flor Garita Hernández
Authors: Barahona Novoa Alberto
Published: June 2020

Este artículo reseña los estudios sobre la toponimia costarricense publicados por Flor Garita Hernández. Se presentan las tendencias en los procedimientos de nominación de los accidentes geográficos, pueblos, montes, ríos, costas y calles en Costa Rica. Se destaca la importancia del sistema clasificatorio ideado por Hernández para sistematizar los estudios toponímicos. Por otra parte, se resaltan los aportes de sus investigaciones para el conocimiento de la variedad dialectal hispánica de Costa Rica.
La autobiografía: modelo narrativo de la novela picaresca en La colina del buey (1972), de José León Sánchez
Authors: Chavarría Castro Baruc
Published: June 2020

La novela Picahueso (1971), la segunda escrita por José León Sánchez, después titulada La colina del buey (1972), ha sido asociada al modelo narrativo de la picaresca española, pero no se había estudiado en detalle. Las características estructurales determinadas por la teoría acerca del género picaresco son reconocibles en la narración de J. L. Sánchez, entre ellas la más importante: la autobiografía. A partir de esta característica fundamental, se plantea estudiar de qué manera es escrito el material vital del protagonista, Manuel Miranda Miranda, alias Picahueso. Aunque se reconoce la utilidad de conceptos estructurales presentes en el relato, el acercamiento a la novela es metodológicamente comparativo. Se considera que lo autobiográfico es manejado de modo distinto, convirtiendo la escritura del yo, en una escritura del otro, en una otobiografía.
Let Me Tell You: Experiences with Silent Books in a Framework of Early Literacy
Authors: Guichot-Muñoz Elena , De Sarlo Giulia , Ledesma Gobea Elena
Published: June 2020

This paper focuses on an experiment with Silent Books with 27 Spanish kindergarten children. Through a qualitative ethnographic methodology based on a multimodal analysis, we study the response to the self-managed reading of Silent Books given by a class group and, specifically, by five students, both in the classroom and at home. The analysis of the results highlights a drastic increase in the motivation towards books and the activation of a series of cognitive precursors.
Learning with Unsure Responses
Authors: Takeoka Kunihiro , Dong Yuyang , Oyamada Masafumi
Published: June 2020

Many annotation systems provide to add an unsure option in the labels, because the annotators have different expertise, and they may not have enough confidence to choose a label for some assigned instances. However, all the existing approaches only learn the labels with a clear class name and ignore the unsure responses. Due to the unsure response also account for a proportion of the dataset (e.g., about 10-30% in real datasets), existing approaches lead to high costs such as paying more money or taking more time to collect enough size of labeled data. Therefore, it is a significant issue to make use of these unsure.In this paper, we make the unsure responses contribute to training classifiers. We found a property that the instances corresponding to the unsure responses always appear close to the decision boundary of classification. We design a loss function called unsure loss based on this property. We extend the conventional methods for classification and learning from crowds with this unsure loss. Experimental results on realworld and synthetic data demonstrate the performance of our method and its superiority over baseline methods.
Mining Unfollow Behavior in Large-Scale Online Social Networks via Spatial-Temporal Interaction
Authors: Wu Haozhe , Hu Zhiyuan , Jia Jia , Bu Yaohua , He Xiangnan , Chua Tat-Seng
Published: June 2020

Online Social Networks (OSNs) evolve through two pervasive behaviors: follow and unfollow, which respectively signify relationship creation and relationship dissolution. Researches on social network evolution mainly focus on the follow behavior, while the unfollow behavior has largely been ignored. Mining unfollow behavior is challenging because user's decision on unfollow is not only affected by the simple combination of user's attributes like informativeness and reciprocity, but also affected by the complex interaction among them. Meanwhile, prior datasets seldom contain sufficient records for inferring such complex interaction. To address these issues, we first construct a large-scale real-world Weibo1 dataset, which records detailed post content and relationship dynamics of 1.8 million Chinese users. Next, we define user's attributes as two categories: spatial attributes (e.g., social role of user) and temporal attributes (e.g., post content of user). Leveraging the constructed dataset, we systematically study how the interaction effects between user's spatial and temporal attributes contribute to the unfollow behavior. Afterwards, we propose a novel unified model with heterogeneous information (UMHI) for unfollow prediction. Specifically, our UMHI model: 1) captures user's spatial attributes through social network structure; 2) infers user's temporal attributes through user-posted content and unfollow history; and 3) models the interaction between spatial and temporal attributes by the nonlinear MLP layers. Comprehensive evaluations on the constructed dataset demonstrate that the proposed UMHI model outperforms baseline methods by 16.44 on average in terms of precision. In addition, factor analyses verify that both spatial attributes and temporal attributes are essential for mining unfollow behavior.
An End-to-End Visual-Audio Attention Network for Emotion Recognition in User-Generated Videos
Authors: Zhao Sicheng , Ma Yunsheng , Gu Yang , Yang Jufeng , Xing Tengfei , Xu Pengfei , Hu Runbo , Chai Hua , Keutzer Kurt
Published: June 2020

Emotion recognition in user-generated videos plays an important role in human-centered computing. Existing methods mainly employ traditional two-stage shallow pipeline, i.e. extracting visual and/or audio features and training classifiers. In this paper, we propose to recognize video emotions in an end-to-end manner based on convolutional neural networks (CNNs). Specifically, we develop a deep Visual-Audio Attention Network (VAANet), a novel architecture that integrates spatial, channel-wise, and temporal attentions into a visual 3D CNN and temporal attentions into an audio 2D CNN. Further, we design a special classification loss, i.e. polarity-consistent cross-entropy loss, based on the polarity-emotion hierarchy constraint to guide the attention generation. Extensive experiments conducted on the challenging VideoEmotion-8 and Ekman-6 datasets demonstrate that the proposed VAANet outperforms the state-of-the-art approaches for video emotion recognition. Our source code is released at: https://github.com/maysonma/VAANet.
FairyTED: A Fair Rating Predictor for TED Talk Data
Authors: Acharyya Rupam , Das Shouman , Chattoraj Ankani , Tanveer Md. Iftekhar
Published: June 2020

With the recent trend of applying machine learning in every aspect of human life, it is important to incorporate fairness into the core of the predictive algorithms. We address the problem of predicting the quality of public speeches while being fair with respect to sensitive attributes of the speakers, e.g. gender and race. We use the TED talks as an input repository of public speeches because it consists of speakers from a diverse community and has a wide outreach. Utilizing the theories of Causal Models, Counterfactual Fairness and state-of-the-art neural language models, we propose a mathematical framework for fair prediction of the public speaking quality. We employ grounded assumptions to construct a causal model capturing how different attributes affect public speaking quality. This causal model contributes in generating counterfactual data to train a fair predictive model. Our framework is general enough to utilize any assumption within the causal model. Experimental results show that while prediction accuracy is comparable to recent work on this dataset, our predictions are counterfactually fair with respect to a novel metric when compared to true data labels. The FairyTED setup not only allows organizers to make informed and diverse selection of speakers from the unobserved counterfactual possibilities but it also ensures that viewers and new users are not influenced by unfair and unbalanced ratings from arbitrary visitors to the ted.com website when deciding to view a talk.
Tracking Disaster Footprints with Social Streaming Data
Authors: Cheng Lu , Li Jundong , Candan K. Selcuk , Liu Huan
Published: June 2020

Social media has become an indispensable tool in the face of natural disasters due to its broad appeal and ability to quickly disseminate information. For instance, Twitter is an important source for disaster responders to search for (1) topics that have been identified as being of particular interest over time, i.e., common topics such as “disaster rescue”; (2) new emerging themes of disaster-related discussions that are fast gathering in social media streams (Saha and Sindhwani 2012), i.e., distinct topics such as “the latest tsunami destruction”. To understand the status quo and allocate limited resources to most urgent areas, emergency managers need to quickly sift through relevant topics generated over time and investigate their commonness and distinctiveness. A major obstacle to the effective usage of social media, however, is its massive amount of noisy and undesired data. Hence, a naive method, such as set intersection/difference to find common/distinct topics, is often not practical. To address this challenge, this paper studies a new topic tracking problem that seeks to effectively identify the common and distinct topics with social streaming data. The problem is important as it presents a promising new way to efficiently search for accurate information during emergency response. This is achieved by an online Nonnegative Matrix Factorization (NMF) scheme that conducts a faster update of latent factors, and a joint NMF technique that seeks the balance between the reconstruction error of topic identification and the losses induced by discovering common and distinct topics. Extensive experimental results on real-world datasets collected during Hurricane Harvey and Florence reveal the effectiveness of our framework.
Lightweight and Robust Representation of Economic Scales from Satellite Imagery
Authors: Han Sungwon , Ahn Donghyun , Cha Hyunji , Yang Jeasurk , Park Sungwon , Cha Meeyoung
Published: June 2020

Satellite imagery has long been an attractive data source providing a wealth of information regarding human-inhabited areas. While high-resolution satellite images are rapidly becoming available, limited studies have focused on how to extract meaningful information regarding human habitation patterns and economic scales from such data. We present READ, a new approach for obtaining essential spatial representation for any given district from high-resolution satellite imagery based on deep neural networks. Our method combines transfer learning and embedded statistics to efficiently learn the critical spatial characteristics of arbitrary size areas and represent such characteristics in a fixed-length vector with minimal information loss. Even with a small set of labels, READ can distinguish subtle differences between rural and urban areas and infer the degree of urbanization. An extensive evaluation demonstrates that the model outperforms state-of-the-art models in predicting economic scales, such as the population density in South Korea (R2=0.9617), and shows a high use potential in developing countries where district-level economic scales are unknown.
Capturing the Style of Fake News
Authors: Przybyla Piotr
Published: June 2020

In this study we aim to explore automatic methods that can detect online documents of low credibility, especially fake news, based on the style they are written in. We show that general-purpose text classifiers, despite seemingly good performance when evaluated simplistically, in fact overfit to sources of documents in training data. In order to achieve a truly style-based prediction, we gather a corpus of 103,219 documents from 223 online sources labelled by media experts, devise realistic evaluation scenarios and design two new classifiers: a neural network and a model based on stylometric features. The evaluation shows that the proposed classifiers maintain high accuracy in case of documents on previously unseen topics (e.g. new events) and from previously unseen sources (e.g. emerging news websites). An analysis of the stylometric model indicates it indeed focuses on sensational and affective vocabulary, known to be typical for fake news.
Interactive Learning with Proactive Cognition Enhancement for Crowd Workers
Authors: Zhang Jing , Wang Huihui , Meng Shunmei , Sheng Victor S.
Published: June 2020

Learning from crowds often performs in an active learning paradigm, aiming to improve learning performance quickly as well as to reduce labeling cost by selecting proper workers to (re)label critical instances. Previous active learning methods for learning from crowds do not have any proactive mechanism to effectively improve the reliability of workers, which prevents to obtain steadily rising learning curves. To help workers improve their reliability while performing tasks, this paper proposes a novel Interactive Learning framework with Proactive Cognitive Enhancement (ILPCE) for crowd workers. The ILPCE framework includes an interactive learning mechanism: When crowd workers perform labeling tasks in active learning, their cognitive ability to the specific domain can be enhanced through learning the exemplars selected by a psychological model-based machine teaching method. A novel probabilistic truth inference model and an interactive labeling scheme are proposed to ensure the effectiveness of the interactive learning mechanism and the performance of learning models can be simultaneously improved through a fast and low-cost way. Experimental results on three real-world learning tasks demonstrate that our ILPCE significantly outperforms five representative state-of-the-art methods.
ÜNİVERSİTE ÖĞRENCİLERİNİN MANEVİ YÖNELİMLERİ VE SAĞLIK ALGILARI
Authors: KÖKTÜRK DALCALI Berna
Published: June 2020

Giriş: Gençlik döneminin bir parçası olan üniversite yaşamı öğrenciler için kendi rutinleri ve yaşam alışkanlıklarında ki birçok değişikliği beraberinde getirmektedir. Maneviyat öğrencilerin karşılaştıkları ve kontrol altına alamadıkları bu zorlukların aşılmasında önemli bir başa çıkma mekanizmasıdır. Manevi yönelim bireyi sevgi, anlam, huzur, umut, esenlik ve bütünlük gibi sağlıkla ilişkili birçok kavramada yönlendirmektedir. Yöntem: Araştırma tanımlayıcı-ilişki arayıcı bir çalışmadır. Araştırmanın evrenini bir meslek yüksekokulunda I. ve II. Öğretimde öğrenimlerine devam eden 2160 öğrenci oluşturmuştur ve araştırma 250 öğrenci ile tamamlanmıştır. Verilerin toplanmasında araştırmacı tarafından literatür doğrultusunda geliştirilen ‘Yapılandırılmış Kişisel Bilgi Formu’, ‘Manevi Yönelim Ölçeği’ ve ‘Sağlık Algısı Ölçeği’ kullanılmıştır. Verilerin istatistiksel analizi için SPSS 21.0 Paket programı kullanılmıştır. Bulgular: Öğrencilerin manevi yönelim puanlarının 92,62±23,31 olduğu görüldü ve manevi yönelimlerinin yüksek olduğu görüldü.  Kontrol merkezi alt boyutundan 14,59±2,84; Kesinlik alt boyutundan 11,36±2,16; sağlığın önemi alt boyutundan 6,97±2,66; öz farkındalık alt boyutundan 6,85±2,35 ve sağlık algısı ölçeği toplamından 39,78±5,46 puan aldıkları görüldü. Manevi yönelim yükseldikçe kontrol merkezi (p:0,033); kesinlik (p:0,003); öz farkındalık (p:0,015) alt boyutlarının puanlarının yükseldiği; sağlığın önemi alt boyutunun puanının ise düştüğü görüldü(p:0,000). Sonuç: Öğrencilerin manevi yönelimleri ve sağlık algısı ölçeğinin alt boyutları arasında anlamlı bir ilişki mevcutken sağlık algısı toplam puanının manevi yönelimle ilişkili olmadığı görüldü. Manevi yönelimin kontrol merkezi, kesinlik ve öz farkındalık alt boyutlarını olumlu etkilediği düşünüldüğünde öğrencilerin sağlık algılarının yükseltilmesinde manevi kaynakları kullanılabilir.
(Re) Pensar la Pedagogía en Colombia: entre formación de maestros e investigación educativa
Authors: León Palencia Ana Cristina
Published: June 2020

Este artículo de investigación señala la necesidad de (re)pensar la pedagogía en Colombia en relación con dos escenarios que permitieron su configuración histórica: la formación de maestros y la investigación educativa. A partir de la revisión de fuentes como legislación, documentos institucionales y artículos de revista, el texto se desarrolla en tres partes: en primer lugar, se revisan algunoselementos sobre la institucionalización de la pedagogía en los entornos francófono y germánico, que operan como referentes para pensar esta propuesta. En segundo lugar, se realiza un balance de la manera en que se configuró la formación de maestros en el país, así como de las formas en que se instituyó la investigación educativa. En tercer y último lugar, se señalan algunas conclusionesy proyecciones en torno a lo que significa la pedagogía en la actualidad.
2D and 3D Electron Microscopy (EM) Imaging of Tissue Biopsies and Resections v1
Authors: Riesterer Jessica , S Stempinski Erin , S Lopez Claudia
Published: June 2020

Recent developments in large format electron microscopy have enabled generation of images that provide detailed ultrastructural information on normal and diseased cells and tissues. Analyses of these images increase our understanding of cellular organization and interactions and disease-related changes therein. Here, we describe a workflow and generalized conditions for two-dimensional (2D) and three-dimensional (3D) imaging, including optical using Toluidine-Blue stained sections, large-format high-resolution scanning electron microscopy (SEM) montages, and 3D focused ion beam-scanning electron microscopy (FIB-SEM) image stacks, that allow pathologists and cancer biology researchers to identify areas of interest from human cancer biopsies. Note: Imaging conditions described here may differ somewhat depending on microscope manufacturer. Efforts have been made to generalize for any model, but small changes may be necessary. OHSU's primary microscope for this work is a FEI Helios NanoLab G3 DualBeam FIB-SEM.
Selecting the correct transfer membrane for Western blot enhances detection of alpha-synuclein and tau proteins v1
Authors: Kaminski Schierle Gabriele
Published: June 2020

The ability to detect proteins by Western blot, particularly from tissue samples, can be hampered by the choice of membrane and whether a fixation step is used. Here we compare three transfer membranes, polyvinylidene difluoride (PVDF) 0.2 μm, PVDF 0.45 μm and nitrocellulose 0.45 μm for the detection of rat α-synuclein from tissue and recombinant human tau. For α-synuclein fixation of the membrane directly after transfer was imperative for detection of the protein and use of the PVDF 0.45 μm membrane gave the highest detection signal. For tau, the signal was highest on nitrocellulose 0.45 μm and fixation did not enhance the signal.
¿Qué quiere un adolescente? los límites del psicoanálisis y los múltiples modos de interpretar a ese sujeto
Authors: Pereira Marcelo Ricardo
Published: June 2020

Con el objetivo de dilatar teóricamente algunas de las perspectivas de análisis y descripciones que sobre la condición adolescente se encuentran, en este escrito, luego de discutir críticamente dos perspectivas amplias para interpretar psicoanalíticamente la adolescencia (culturalista y estructuralista), se destacan tipos de ser y de describir adolescentes que van desde aquellos que se ven al modo de Telémaco (esperando que algo del padre retorne del mar) y los ligados maternalmente hasta adolescentes que se renombran y usan tales acciones para vincularse entre sí confrontando el mundo adulto. Con los últimos se trata el tema de la nominación.
La presencia-ausencia del objeto en la anorexia y en la bipolaridad
Authors: Santiago Idamari
Published: June 2020

En este artículo reflexivo se pretende pensar e interrogar la anorexia y la bipolaridad, no como categorías nosológicas, sino respecto a la economía afectiva del sujeto a partir de la relación de objeto. Se propone pensar la anorexia por el lado de la hiperausencia del objeto; el sujeto come nada; mientras que a la bipolaridad se procura pensarla como un circuito en donde el sujeto pasa de la hiperpresencia a la hiperausencia del objeto; el sujeto se encuentra atrapado en el circuitomanía-melancolía.
Neuro-Fuzzy Harmful Substances Control of Aircraft Gas Turbine Engine
Authors: Andrievskaya N. V. , Andrievskiy O. A. , Kuznetsov M. D. , Legotkina T. S. , Nikulin V. S. , Storozhev S. A. , Khizhnyakov Y. N. , Yuzhakov A. A.
Published: June 2020

One of the directions of aviation development is solving environmental problems, which excludes the emission of harmful substances into the atmosphere (nitric oxide, carbon monoxide) during the operation of an aircraft gas turbine engine (GTE) [1]. At low temperatures, oxygen and nitrogen are inert gases. At temperatures of 1100... 1600 K, oxides are formed, where nitrogen takes a valence of one to five. At temperatures above 1600 K, their atomic decomposition occurs. At temperatures in the range of 1100—1600 K, a reduction in NOx is possible with good mixing and a sufficient length of the combustion chamber, which determines the burning time of gases. If the combustion process is interrupted due to the poor operation of the automation, either vibro-combustion (atomic decomposition of NOx oxide) occurs at a temperature of 1600 K or flame failure occurs at 1100 K. Improving the process of converting the chemical energy of fuel and converting it into mechanical energy under conditions of uncertainty (variable caloric content of kerosene, changes in environmental parameters, wear of control equipment) is possible using neuro-fuzzy control of aviation gas turbine engine emissions into the environment. The control signal will be the fuel consumption in the diffusion manifold. In this case, fuel consumption in homogeneous reservoirs will vary evenly, provided that the total amount of fuel remains constant for the engine under consideration (the thrust should not change in the mode). A dynamic model of a neuro-fuzzy fuel consumption regulator by a diffusion collector has been developed. The method of obtaining training samples " % GT" = f (MNOx) for constructing the neural part of the regulator is presented. The desired " triangular" region of MNOx location (the integral of emission of nitrogen oxide emissions) is determined, on the basis of which control algorithms " with economy" and " without economy" of the MNOx integral are proposed.
The Path Planning Method for AUV Group Moving in Environment with Obstacles
Authors: Filaretov V. F. , Yukhimets D. A.
Published: June 2020

The new path planning method for AUV group moved in the " leader-followers" mode in a desired formation in an unknown environment with obstacles is proposed in paper. In this case one AUV plays role of AUV-leader, which has information about the mission and plans a safe trajectory of its movement, depending on its purpose and detected obstacles. AUV-followers must move behind the leader, in accordance with their assigned place in formation, using information about the current position of the leader, received via acoustic communication channels, and information about their distances to obstacles, detected by their onboard rangefinders. Due to the low bandwidth of acoustic communication channels, there is a problem of matching the position of the AUV-followers during obstacles avoidance. It is necessary to avoid collisions between AUV of group. This problem is solved by means of the preliminary forming for each follower of the only possible trajectory of movement inside formation which will provide it safe movement relatively other followers when this AUVfollower moves around detected obstacle. This approach allows do not coordinate the current position of the AUV-followers relative to other AUV of group if a high-precision control system is used, and as a result it does not require additional data exchange between the AUV group. In this paper, an approach to the forming of AUV-follower trajectories inside AUV formation and the method of forming the desired position of the AUV-followers on these trajectories are proposed. The effectiveness of the proposed method is confirmed by the results of mathematical modeling.
A View of the Disaster and Victory from below: Serbian Roma Soldiers, 1912–1918
Authors: Šarenac Danilo
Published: June 2020

The Kingdom of Serbia fought in three consecutive conflicts between 1912 and 1918. These events merged into a devastating experience of an all-out war, completely reshaping all aspects of contemporary life. As the first centenary of these events has recently shown, the memories of wartime still play a very prominent role in the Serbian national narrative. By 1915 around 20% of Serbian combatants belonged to some of the country’s minorities. Second class citizens on the social margins of society, the Serbian Roma constitute those whose wartime history is the least known to research and the public. However, the wartime diaries kept by Serbian soldiers are full of causal references to their Roma fellow combatants. This article provides an overview of the duties Roma soldiers played in the war, based on the perspective of Serbs who were fighting alongside them. The article tackles the general image and the position of the Roma population in the Kingdom of Serbia. In addition, the horrific challenges the war created for Serbian society are tackled from the perspective of those who were, already in peace time, in the most disadvantageous situation socially and economically. Overall, despite the unifying experience which the wartime suffering imposed on all citizens of the Kingdom, the old prejudices towards the Roma survived after 1918.
Sosyalleşme ve Sosyalleşmenin Sosyal Medya Mecralarındaki Anlamsal ve İşlevsel Dönüşümü
Authors: VATANDAŞ Saniye
Published: June 2020

Sosyalleşmenin birey ve toplum açısından yerine getirdiği farklı işlevler vardır. Birey sosyalleşme sayesinde insani nitelikler kazanmakta, toplumunun normal bir üyesi haline gelmekte, yaşam tarzını şekillendirmekte, geçmişin deneyimlerinden yararlanarak zaman kaybı yaşamamakta, farklı düzlemlerde söz konusu olabilecek risklerden uzak durmaktadır. İletişimin en temel aracı olan dili bile sosyalleşme sürecinde edinmekte ve geliştirmektedir. Ayrıca iletişime kapsam ve derinlik katan jest, mimik, beden dili gibi unsurları sosyalleşme sürecinde öğrenip uygulamaya aktarmaktadır. Sosyallik ve sosyalleşme açısından sosyal medya dikkate alındığında, sosyal medyanın sosyalliği, rutin dışı bir sosyalliktir. Sosyal medyanın sosyalliği ciddi tereddütleri gerektirecek, büyük sorular sormaya vesile olacak bir ‘sosyalliktir’. Çünkü ilişki ve iletişim sınırlı, sığ ve çok daha önemlisi zaman ve mekândan büyük oranda kopmuş durumdadır. Sosyal medyada sınırlı bir iletişimden bahsetmek mümkünse de ilişkiden bahsetmek çok zordur. Bu çalışma, sosyalleşmenin sosyal medya mecralarındaki serüvenini konu edinmektedir. Ne gibi özelliklere sahip olduğu ve gidişatın seyrinin ne olduğu incelenmiştir. Konu bağlamında detaylı bir şekilde mevcut literatür incelenmiştir. Araştırma ile ‘sosyalleşme’ olgusunun hem işleyiş hem de niteliksel açıdan önemli düzeyde değişime uğradığı, ‘sosyalleşmenin’ yeni bir anlam ve amaca evrildiği tespit edilmiştir.